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eCommons@AKU eCommons@AKU
Department of Paediatrics and Child Health Division of Woman and Child Health
2011
Pakistan National Nutrition Survey, 2011 Pakistan National Nutrition Survey, 2011
Zulfiqar A Bhutta Aga Khan University
Sajid Bashir Soofi Aga Khan University
S. Shujaat H Zaidi Aga Khan University
Atif Habib Aga Khan University, [email protected]
Imtiaz Hussain Aga Khan University
Follow this and additional works at: https://ecommons.aku.edu/
pakistan_fhs_mc_women_childhealth_paediatr
Recommended Citation Recommended Citation Bhutta, Z., Soofi, S., Zaidi, S., Habib, A., Hussain, I. (2011). Pakistan National Nutrition Survey, 2011. Available at:Available at: https://ecommons.aku.edu/pakistan_fhs_mc_women_childhealth_paediatr/262
Forward
National economic planning has a key role in socio economic development of any country, which requires accurate and current data and statistics. The Planning Commission maintains updated national socio economic statistics - an important element of sustained planning process. The nutrition status which is both the cause and consequence of poverty is a key challenge for any country. Malnutrition, particularly in mothers and children leads to many adverse consequences for development. It impacts learning abilities in children and put them at disadvantage in life. Nutrition remains a difficult area to gauge and monitor by virtue of its multiple dimensions and vulnerability to the changes in allied sectors. The present National Nutrition Survey (NNS) Report, based on information collected and managed through cross sectional population survey, is fourth in the series since 1980. The Report provides an important input for policy planning with priorities aligned in line with the present time challenges. The Survey not only analyses data and information about existing nutritional status of the population but also co-relates these to the course of action to be developed. It also identifies underlying causes like food security, dietary behaviours, breastfeeding and complementary feeding practices, literacy level, etc. contributing towards present level of malnutrition.
The work on the fourth National Nutrition Survey was initiated during 2010-11 with the objective of assessing the nutritional status of the population particularly women and children. The task was assigned to Aga Khan University (AKU) Karachi with the technical & financial support of development partners. The exercise was overseen and ratified by the Federal Steering Committee while detailed micro planning was carried out by a Technical Committee comprising relevant stakeholders; from Federal and Provincial Governments, International NGOs, the UN Agencies, Pakistan Bureau of Statistics (PBS) and Pakistan Medical and Research Council (PMRC). The agreed survey manual covering sampling procedure, questionnaire and consent form was reviewed and approved by the National Bioethics Committee (NBC) of the Government of Pakistan and the AKU’s Research Ethics Review Committee. The field work was conducted during the first half of 2011.
The survey implementation was closely monitored by the AKU University, UNICEF and external monitors.The results were disseminated at federal level in September 2011, with subsequent information sharing and dissemination workshops organized for the provincial governments and regions. Following their inputs and endorsement, the report has been finalized. This is the first nutrition survey that provides key nutrition data for the provinces and the regions.
The NNS 2011 presents the current nutrition situation, analysis of the trends in indicators and gauges progress towards the targets set for the Millennium Development Goals (MDGs) and beyond. The survey also assesses the severity and geographical scope of nutrition related issues. Furthermore, it sets the platform for policy and strategy development to prioritize the programs for short, medium and long term interventions at the national and provincial level.
The survey reports that in past decade there has been marginal improvement in the core maternal and childhood indicators, universal salt iodization, while other key indicators like stunting, wasting, anaemia, and vitamin A deficiency have shown declining trends which is more prominent in the rural areas.
Government of Pakistan wishes to thank all concerned for undertaking this survey, which is the one of largest survey of this kind in Pakistan. We are committed to a vigorous policy response to the findings of this survey in order to make malnutrition history in Pakistan.
(AHSAN IQBAL) Federal Minister/Deputy Chairman
Ministry of Planning & Development
Acknowledgement
The completion of the NNS 2011 is an important achievement supporting the Government of
Pakistan in its quest to set priorities for the development of the country in the post devolution
scenario. This is the first national nutrition survey conducted after a decade of the last survey
and provides essential information on the actual scale and magnitude of under-nutrition in
Pakistan. It gives critical information on determinants, differentials and provides information for
policy guidance to the federal and provincial Governments. The completion of the survey is the
outcome of concerted efforts of a well guided and technically robust survey team supervised by
Ministry of Health, whose members worked tirelessly and continuously under exceptionally
difficult circumstances. We wish to express our deep gratitude for all those that contributed to
the completion of this enormous task.
Firstly, we deeply acknowledge the participating families, mothers, and the children for their
willingness and cooperation with the survey team, provision of the required information,
samples and valuable insights during the survey. Without their support, this survey would not
have been possible.
We wish to express our sincere gratitude to government institutions, including representatives
of the former Ministry of Health and its pre-devolution Nutrition Wing, represented by Dr. Abdul
Baseer Khan Achakzai, Director Nutrition (Former Deputy Director General/National Nutrition
Focal Person for the Survey, Mr Mohammed Ayub and Mr Muhammad Aslam Shaheen of the
Planning Commission, Dr. Ali Nasir Bugti, Dr. Mehmood Ahmad, Dr. Dure Shehwar, Dr. Qaisar
Ali, Dr. Shabir Dar, Dr. Fawad Khan, Mr. M.Abbas, Mr. Khair ul Bashar of the Provincial
Nutrition Cells, and Mr. Muhammad Ramzan Khan of the PBS, for supporting this ambitious
survey in Pakistan. We would like to express our sincere appreciation to the National Steering
Committee for its directives and guidance. We are most appreciative of the invaluable technical
inputs provided by the National Technical Committee members which included representatives
from Federal and Provincial Departments of Health, the Nutrition Wing of the Ministry of Health,
Pakistan Bureau of Statistics, Planning Commission, Agricultural University Peshawar, National
Institute of Health, WHO, UNICEF, WFP, AusAID, DFID, USAID, World Bank, and the
Micronutrient Initiative.
Special thanks to UNICEF for taking overall responsibility for supporting and coordination of the
survey through the Aga Khan University and Pakistan Medical Research Council. We wish to
acknowledge Prof. Zulfiqar A Bhutta, Dr. Sajid Soofi and their team from the Aga Khan
University, Dr. Assad Hafeez of HSA and Dr. Huma Qureshi from the Pakistan Medical
Research Council, for conducting the survey in a highly professional manner, including in-
depth survey preparation, data collection, analysis, and dissemination and completion of the
report.
We are grateful to DFID and AusAID for the core financial support without which this valuable
survey would not have been possible.
At the end I urge all the nutrition partners to come forward for their technical and resources
support in the planning of nutrition interventions for the provinces and regions in Pakistan to
address the issues of malnutrition, specifically of mothers and children.
(Imtiaz Inayat Elahi)
SECRETARY
| National Nutrition Survey 2011 May 2013 ii
CREDITS
Principal Survey Lead Institution: Aga Khan University, Pakistan
Principal Investigator: Professor Zulfiqar A Bhutta, FCPS, FRCPCH, PhD Founding Chair Division of Women and Child Health & Director Center of Excellence in Women and Child Health, Aga Khan University, Pakistan National Survey Coordinator: Dr. Sajid Bashir Soofi, MBBS, FCPS Assistant Professor, Department of Paediatrics & Child Health, Aga Khan University, Pakistan Survey Coordinators Dr. Muhammad Atif Habib, Senior Instructor, Research Mr. Imtiaz Hussain Hilbi, Senior Social Scientist, Research Mr. S. Shujaat H. Zaidi, Senior Social Scientist, Research Dr. Noushad Ali, Research Supervisor Regional Coordinators Mr. Maswar Hussain, Dr. Abdul Razzaq Lasi, Mr. Gul Nawaz, Dr. Azam Baber, Dr. Tariq Samejo, Dr. Mushtaq Dero, Mr. Mushtaq Mirani, Dr. Aftab Bhatti and Mr. Asmatullah Khan Data Management Analyst Mr. Imran Ahmed, Data Manager, Mr. Zaid Shakoor Bhatti, Data Analyst & Mr. Najeebur Rehman, Data Coordinator Management and Administration Mir Asghar Ali Khan, Senior Manager, Research and Grants Mr. Ishrat Abbas, Manager, Budget and Finance Mr. M. Siddique, Shukurullah Baig, Fida H. Choghtai, Logistic Management Mr. Rashid Khan and Mr. Khuram Noorani, Financial Management Mr. Didar Alam, Laboratory Coordinator Collaborators: Pakistan Medical Research Council (PMRC) Dr. Huma Qureshi, Deputy Director Dr. Arif Munir, Mr. Mehmood and Mr. Rizwanullah Federal Bureau of Statistics Mr. Muhammad Ramzan Khan, Ex-Director, Sample Design Planning Commission, Government of Pakistan Federal & Provincial Nutrition Wing, Ministry of Health, Government of Pakistan UNICEF, Pakistan
INDEX
A. Acronyms------ ------------------------------------------------------------ ----------------------------------------- vi
B. General definitions ------------------------------------------------------ ----------------------------------------- viii
C. Reference ranges for biochemical assessments---------------------- ------------------------------------- ix
D. Executive summary ----------------------------------------------------- -------------------------------------- xi
CHAPTER 1: Introduction --------------------------------------------------- ------------------------------------------ 1 1.1 Introduction ---------------------------------------------------------- ------------------------------------------ 1
1.2 Context of malnutrition -------------------------------------------- ------------------------------------------ 1
1.3 Need for a National Nutrition Survey -------------------------- ------------------------------------------ 5
1.4 Survey duration ------------------------------------------------------ ------------------------------------------ 6
CHAPTER 2: Survey Design and Methods------------------------------- ------------------------------------------ 7 2.1 Survey Objectives --------------------------------------------------- ------------------------------------------ 7
2.2 Methodology ---------------------------------------------------------- -------------------------------------------- 7
2.3 Sample size and its allocation ------------------------------------------------------------------------------- 7
2.3.1 Sample size estimation for household survey and biochemical assessment -------------------- 7
2.3.2 Sampling frame and design --------------------------------------- ------------------------------------------ 9
2.3.3 Sample selection procedure -------------------------------------- ------------------------------------------ 10
2.3.4 Target population --------------------------------------------------- ------------------------------------------ 10
2.3.5 Description of questionnaire ------------------------------------- ------------------------------------------ 10
2.3.6 Description of qualitative research ----------------------------- ------------------------------------------ 11
2.3.7 Biochemical analysis ------------------------------------------------ ------------------------------------------ 11
2.3.8 FATA specific data --------------------------------------------------- ------------------------------------------ 11
2.3.9 Project pre implementation steps ------------------------------ ------------------------------------------- 12
2.3.10 Plan of operation, training and monitoring ------------------- ------------------------------------------ 14
2.3.11 Data management, transfer and analysis --------------------- ------------------------------------------ 14
2.3.12 Ethical approval and confidentiality ---------------------------- ----------------------------------------- 15
RESULTS OF THE NATIONAL NUTRITION SURVEY -------------------- ------------------------------------------ 16
CHAPTER 3: Background and Household Characteristics---------------------- ------------------------------- 17 3.1 Completion of data collection ------------------------------------ ------------------------------------------ 17 3.1.1 Blood and urine specimen ----------------------------------------- ------------------------------------------ 18
3.2 Background and household characteristics ------------------- ------------------------------------------ 18
3.3 Formal education – head of household and mothers ------- -------------------------------------------- 18
3.4 Occupation – head of household ----------------------------------------------------------------------- ------ 18
3.5 Nature of dwelling by type of floor, roof and walls ----------------------------------------------- ------- 19 3.6 Type of cooking fuel ----------------------------------------------- ------------------------------------------- 20
CHAPTER 4: Food Insecurity in Pakistan -------------------------------- ------------------------------------------ 21 4.1 Food secure ----------------------------------------------------------- ------------------------------------------ 21
4.2 Food insecure without hunger ----------------------------------- ------------------------------------------ 21 4.3 Food insecure with hunger (moderate) ------------------------ ------------------------------------------ 22
4.4 Food insecure with hunger (severe) ---------------------------- ------------------------------------------ 22
CHAPTER 5: Maternal Health and Nutrition --------------------------- ------------------------------------------ 23 5.1: Basic data – age, education and marital status of mothers-------------- ------------------------------ 23 5.1.1 Age distribution ------------------------------------------------------ ------------------------------------------ 23
5.1.2 Marital status and current pregnancy status ----------------- ------------------------------------------ 23
5.2: Reproductive history and antenatal care --------------------- ------------------------------------------ 23
iii | National Nutrition Survey 2011
5.2.1 Reproductive history ------------------------------------------------ ------------------------------------------ 23
5.2.2 Antenatal care -------------------------------------------------------- ------------------------------------------ 23
5.3: Knowledge of micronutrients and micronutrient rich foods ----------------------------------------- 25
5.3.1 Knowledge of micronutrients ------------------------------------- ------------------------------------------ 25
5.3.2 Knowledge of vitamin rich foods --------------------------------- ------------------------------------------ 26
5.3.3 Knowledge about iodized salt and its usage------------------- ------------------------------------------ 26
5.4: Clinical examination ----------------------------------------------- -------------------------------------------- 27
5.5: Anthropometry ------------------------------------------------------ ------------------------------------------- 28
5.6: Micronutrient deficiency ------------------------------------------ ------------------------------------------- 29
5.6.1 Urinary iodine excretion of mother ----------------------------- ------------------------------------------ 29
5.6.2 Night blindness ------------------------------------------------------ ------------------------------------------- 29
5.7: Biochemical analysis ------------------------------------------------ ------------------------------------------ 30
5.7.1 Anaemia (haemoglobin levels)------------------------------------ ------------------------------------------ 30
5.7.2 Ferritin concentration ---------------------------------------------- ------------------------------------------ 31
5.7.3 Vitamin A deficiency ------------------------------------------------ ------------------------------------------ 31
5.7.4 Zinc deficiency -------------------------------------------------------- ------------------------------------------ 32
5.7.5 Vitamin D deficiency ------------------------------------------------ ------------------------------------------ 33 5.7.6 Calcium Status -------------------------------------------------------- ------------------------------------------ 34
CHAPTER 6: Child Health and Nutrition -------------------------------- ------------------------------------------ 35 6.1: Nutrition status of children --------------------------------------- ------------------------------------------ 35 6.1.1 Children 0–59 months ---------------------------------------------- ------------------------------------------ 35
6.1.2 Anthropometry (children under 5 years of age) -------------- ------------------------------------------ 35
6.1.3 Stunting (children under 5 years of age) ----------------------- ------------------------------------------ 36
6.1.4 Wasting (children under 5 years of age) ----------------------- ------------------------------------------ 36
6.1.5 Underweight (children under 5 years of age) ----------------- ------------------------------------------ 36
6.1.6 Education of mothers and its effect on nutritional status of children ---------------------------- 37
6.1.7 Malnutrition trends in children under 5 years of age – comparison of SAARC countries ----- 37
6.2: Biochemical assessment ------------------------------------------ ------------------------------------------- 39
6.2.1 Anaemia ---------------------------------------------------------------- ------------------------------------------ 39
6.2.2 Iron deficiency (low ferritin levels) ------------------------------ ------------------------------------------ 40
6.2.3 Vitamin A deficiency in children (under 5 years) ------------- ------------------------------------------ 40
6.2.4 Zinc deficiency -------------------------------------------------------- ------------------------------------------ 41
6.2.5 Vitamin D deficiency ------------------------------------------------ ------------------------------------------ 42
6.2.6 Urinary iodine excretion in children 6–12 years ------------- ------------------------------------------ 42 6.2.7 Clinical examination of children under 5 years of age ------ ------------------------------------------ 43
6.3: Child morbidity ------------------------------------------------------- -------------------------------------------- 43 6.3.1 Prevalence of acute respiratory infections -------------------- ------------------------------------------ 44
6.3.2 Prevalence of diarrhoea -------------------------------------------- ------------------------------------------ 44
CHAPTER 7: Infant and Young Child Feeding Practices ------------- ------------------------------------------ 45 CHAPTER 8: Food Intake and Practices ---------------------------------- ------------------------------------------ 50
CHAPTER 9: Elderly Persons Health and Nutritional Status ------- ------------------------------------------ 54
Chapter 10: National Nutrition Survey – Qualitative Findings---- ------------------------------------------ 56
Chapter 11: What Next? ---------------------------------------------------- ------------------------------------------ 63
Bibliography ------------------------------------------------------------------- ------------------------------------------ 67
Annex: NNS Detailed Tables , Sample Design and Sample Weight ----------------------------------------- 69
iv | National Nutrition Survey 2011
CONTENT OF FIGURES AND TABLES
Table 2.1: Sample size and allocation plan 8
Table 2.2: Region wise sample size and its distribution 8
Table 2.3: Description of biochemical analysis/tests 11
Table 2.4: Pre-implementation steps 12
Table 2.5: Details of the training agenda 13
Fig 3.1: Population density 17
Fig 3.2: National Nutrition Survey coverage 17
Table 3.1: Details of sample size coverage (Number of PSUs and SSUs by Province / Region 17
Fig 3.3: Formal education of mothers of children under five years of age. 18
Fig 3.4 (a-c): Nature of dwelling – materials used 19
Fig 3.5: Nature of dwelling – urban/rural comparison of materials used for construction 20
Fig 3.6: Source of fuel for cooking 20
Fig 4.1: Food insecurity situation 22
Fig 5.1: Antenatal care during last pregnancy 24
Fig 5.2: Seeking ANC from skilled care provider 24
Fig 5.3: Micro-nutrient supplementation during last pregnancy 25
Fig 5.4: Knowledge about micronutrients 25
Fig 5.5: Level of Iodine content in salt 27
Fig 5.6: Clinical examination of mothers (comparison NNS 2001-02 and NNS 2011) 28
Fig 5.7: Body Mass Index 28
Fig 5.8: Median urinary iodine excretion in mothers 29
Fig 5.9: Comparison of night blindness in women 30
Fig 5.10: Maternal anemia 30
Fig 5.11: Comparison of anemia in mothers 31
Fig 5.12: Ferritin concentration 31
Fig 5.13: Vitamin A deficiency (pregnant women) 32
Fig 5.14: Comparison of vitamin A deficiencies among non-pregnant women (urban/rural) 32
Fig 5.15: Zinc deficiency (pregnant women) 33
Fig 5.16: Comparison of Zinc deficiency among non-pregnant women (urban/rural) 33
Fig 5.17: Vitamin-D deficiency (pregnant women) 34
Fig 5.18: Calcium deficiency (pregnant women) 34
Fig 6.1: Households with children under 5 years of age 35
Fig 6.2: Prevalence of malnutrition in Pakistan (children under 5 years of age) 35
Fig 6.3: National stunting rates for children under 5 years of age 36
Fig 6.4: National wasting rates (children under 5 years of age) 36
Fig 6.5: Underweight (children under 5 years of age) national 37
Fig 6.6: Education of mothers and its association with nutritional status of children 37
Fig 6.7: SAARC countries national stunting trends 38
Fig 6.8: SAARC countries national wasting trends 38
v | National Nutrition Survey 2011
Fig 6.9: SAARC Countries national underweight trends 38
Fig 6.10: Anaemia in children under 5 years of age 39
Fig 6.11: Trends of prevalence of anemia in children under 5 years of age 39
Fig 6.12: Iron deficiency among children 40
Fig 6.13: Vitamin A deficiency 40
Fig 6.14: Trend of vitamin A deficiency in children under 5 years 41
Fig 6.15: Zinc deficiency in children (0–5 years) 41
Fig 6.16: Comparison of zinc deficiency in children under 5 years of age 42
Fig 6.17: Vitamin D Deficiency 42
Fig 6.18: Median urinary iodine excretion in children 6-12 years 43
Fig 6.19: Current ARI status 43
Fig 6.20: Reported Prevalence of diarrhoea 44
Fig 7.1: Exclusive breastfeeding of children 0-23 months (reported by mothers) 45
Fig 7.2: Predominant breastfeeding of children 0-6 months (24 Hours dietary recall) 45
Fig 7.3: Initiation of breastfeeding within one hour 46
Fig 7.4: Continued breastfeeding practices 46
Fig 7.5: Introduction of Semi-Solid (6-8 months) 47
Fig 7.6: Minimum dietary diversity (6-23 months) 47
Fig 7.7: Minimum meal frequency (6-23 months) 48
Fig 7.8: Minimum acceptable diet (6-23 months) 48
Fig 7.9: Age appropriate breastfeeding (0-23 months) 49
Table 8.1: Food groups consumed by 0-23 months children (based on 24 Hours food recall) 51
Table 8.2: Frequency of Daily Intake of Food Groups (Children 0 – 23 months) 51
Table 8.3: Frequency of Daily Intake of Food Groups among Children by their Age Group 52
Table 8.4: Food groups consumed by mothers of children 0 – 23 months (based on 24 Hours 52
food recall)
Table 8.5: Average Frequency of daily intake of food groups (mothers of children) 53
Fig 9.1 Age distribution of elderly persons 54
Table 9.2: Detail data according to the WHO classifications 55
vi | National Nutrition Survey 2011
ACRONYMS
AGP Alpha-1-Acid Glycoprotein
AJK Azad Jammu and Kashmir
AKU Aga Khan University
ANC Antenatal care
ARI Acute respiratory infection
BMI Body Mass Index
CF Complementary feeding
CHW Community health worker
CRP C-Reactive Protein
DHS Demographic health survey
DMU Data management unit
EB Enumeration block
ERC Ethical Review Committee
FATA Federally Administered Tribal Areas
FBS Federal Bureau of Statistics
FGD Focus group discussion
FHI Family Health International
GB Gilgit Baltistan
GAIN Global Alliance for Improved Nutrition
Gm. Gram
HH Household
IDA Iron deficiency anaemia
IDI In-depth Interview
IYCF Infant and young child feeding
K. Cal Kilocalories
KAP Knowledge, attitude and practice
KP Khyber Pakhtunkhwa
LBW Low birth weight
LHV Lady Health visitor LHW Lady Health worker
MDG Millennium Development Goal Mg Milligram
Ml Millilitre
MOH Ministry of Health
MUAC Mid-upper arm circumference
MWRA Married women of reproductive age
NGO Non-governmental organization
NID National Immunization Day
NNS National Nutrition Survey
vii | National Nutrition Survey 2011
ORS Oral rehydration salt PCO Population Census Organization PDHS Pakistan Demographic Health Survey PMRC Pakistan Medical Research Council PPS Proportion to population size PRSP Punjab Rural Support Program PSU Primary sampling unit RDA Recommended dietary allowance SAARC South Asia Association of Regional Cooperation SSU Secondary sampling unit TBA Traditional birth attendant UIE Urinary iodine excretion UNICEF United Nations Children’s Fund USAID United States Agency for International Development VAD Vitamin A deficiency WHO World Health Organization WRA Women of reproductive age viii | National Nutrition Survey 2011
General Definitions
Body mass index (BMI): Statistical measure of weight scaled according to height, determined by dividing a person’s weight by the square of their height in metric units. For adults, a BMI of less than 18.5 typically indicates under nutrition, while a BMI of more than 40 indicates morbid obesity.
Complementary feeding: This is the period starting when breast milk alone is no longer sufficient to meet the nutritional requirements of infants. Other foods and liquids are needed to complement breast milk at this stage. This transition from exclusive breastfeeding to family foods typically covers the period from 6 months to 18-24 months of age.
Exclusive breastfeeding: The practice of only feeding breast milk to an infant with no supplementation of any kind (e.g. no water, juice, food, or non-human milk). Exclusive breastfeeding has been shown to provide improved protection against many diseases. According to the World Health Organization, on a population basis, exclusive breastfeeding for six months is the optimal way of feeding infants. Thereafter infants should receive complementary foods with continued breastfeeding up to two years of age or beyond.
Malnutrition: Various forms of poor nutrition leading to both underweight and overweight conditions caused by a complex array of issues, including dietary inadequacy, infections, and socio-cultural factors. Malnutrition can lead to wasting and stunting, micronutrient deficiencies, as well as diabetes and other diseases.
Micronutrients: Nutrients needed for life in miniscule amounts. These substances enable the body to produce enzymes, hormones and other substances essential for proper growth and development. Micronutrients are used to improve nutrition through processes such as bio fortification and supplementation.
Stunting: Failure to reach linear growth potential because of inadequate nutrition or poor health, also defined as a chronic restriction of growth in height indicated by low height-for-age. Stunting is usually a reliable indicator of long-term under nutrition among young children.
Supplementation: Process of supplying nutrients – in forms such as bars, capsules, and powders – those missing or not consumed in a person’s diet. Typical supplements include vitamin A, iron, and zinc.
Under-nutrition: According to the 2008 Lancet series on maternal and child under nutrition, under nutrition includes a wide array of effects including intrauterine growth restriction resulting in low birth weight, underweight, stunting, wasting and less visible micronutrient deficiencies. Under nutrition is caused by poor dietary intake that may not provide sufficient nutrients, and/or by common infectious diseases such as diarrhoea. These conditions are most significant during the first two years of life.
ix | National Nutrition Survey 2011
Underweight: This indicates a person has a low weight for their age and implies stunting or wasting. The rate of underweight children is the percentage of children who have low weight for their age.
Wasting: Acute weight loss indicated by a low weight for height ratio. Wasting is usually a result of acute starvation or severe disease. Often more chronic during the first two years of life, wasting is part of a pattern of under nutrition.
Reference ranges for biochemical assessments
Women of Reproductive Age
Women of Reproductive Age
Pregnant
Biochemical Test Children under 5 years Non-pregnant
Severe (<0.35 µmol/L) Severe (<0.35 µmol/L) Severe (<0.35 µmol/L)
Vitamin A Mild (0.35 - 0.70 µmol/L) Mild (0.35 - 0.70 µmol/L) Mild (0.35 - 0.70 µmol/L)
Non-deficient (>0.70µmol/L) Non-deficient (>0.70µmol/L) Non-deficient (>0.70µmol/L)
Severe deficiency (<8.0 ng/mL) Severe deficiency (<8.0 ng/mL) Severe deficiency (<8.0 ng/mL)
Vitamin D Deficiency (8.0 - 20.0 ng/mL) Deficiency (8.0 - 20.0 ng/mL) Deficiency (8.0 - 20.0 ng/mL)
Desirable (>20.0 - 30.0 ng/mL) Desirable (>20.0 - 30.0 ng/mL) Desirable (>20.0 - 30.0 ng/mL)
Sufficient (>30.0 ng/mL) Sufficient (>30.0 ng/mL) Sufficient (>30.0 ng/mL)
Zinc Deficient (<60 µg/dL) Deficient (<60 µg/dL) Deficient (<60 µg/dL)
Non-deficient (>=60 µg/dL) Non-deficient (60 - 150 µg/dL) Non-deficient (60 - 150 µg/dL)
Severe deficiency (<7 gm./dL) Severe deficiency (<7 gm./dL) Severe deficiency (<7 gm./dL)
Haemoglobin Moderate deficiency (7 - 10.99 Moderate deficiency (7 - 11.99 Moderate deficiency (7 - 10.99
gm./dL) gm./dL) gm./dL)
Normal (>= 11 gm./dL) Normal (>= 12 gm./dL) Normal (>= 11 gm./dL)
Ferritin Low Ferritin (<12 ng/mL) Low Ferritin (<12 ng/mL) Low Ferritin (<12 ng/mL)
Normal (>=12 ng/mL) Normal (>=12 ng/mL) Normal (>=12 ng/mL)
Hypocalcaemia (<8.4 mg/dL) Hypocalcaemia (<8.4 mg/dL)
Calcium Not conducted with children Normocalcaemia (8.4 - 10.2 mg/dL) Normocalcaemia (8.4 - 10.2 mg/dL)
Hypercalcaemia (>10.2 mg/dL) Hypercalcaemia (>10.2 mg/dL)
x | National Nutrition Survey 2011
Executive Summary
The Pakistan’s National Nutrition Survey 2011 was conducted by Aga Khan University’s
Division of Women and Child Health, Pakistan’s Ministry of Health and UNICEF. The major
objective of NNS 2011 was to assess the population nutritional status (especially of women
and children and/or other target groups), and key micronutrient indicators in comparison
with the last survey in 2001. The findings of NNS 2011 provide relevant information for planning, implementation and
monitoring appropriate population based interventions in Pakistan. Population groups
surveyed included: pre-school children (0–59 months old), school aged children (6–12 years
old), women of childbearing age (15–49 years old), and elderly persons (50 years and
above). This was the first time a National Nutrition Survey provided provincial specificity
with representative population based samples. However, it does not offer district level
estimates. A two stage stratified sampling design was adopted and an overall sample size of
30,000 households was selected and calculated on the basis of major nutrition indicators
used in the 2001 NNS. These included: 1. stunting in children and 2. Anaemia among women
of reproductive age (WRA) and in children. In all, 27,963 households interviewed; 24,421
blood samples were taken (women 12,282; children 12,139); and 2,917 urine samples were
collected from women (1,460) and children 6-12 years (1,457) for urinary iodine
assessments.
The NNS 2011 covered all provinces: Gilgit Baltistan (GB), Balochistan, Khyber Pakhtunkhwa
(KP), Sindh, Punjab, Azad Jammu and Kashmir (AJK) and the Federally Administered Tribal
Areas (FATA). This included 1,500 enumeration blocks (EBs)/villages and 30,000 households,
with a 49% urban and 51% rural distribution. Renewed listing of all households in each
enumeration block was conducted and twenty households were selected randomly using a
computer automated selection process. Twenty-two survey teams conducted field activities
included data collection, biochemical samples and physical examination across Pakistan. Results from the 2011 National Nutrition Survey (NNS) indicated little change over the last
decade in terms of core maternal and childhood nutrition indicators. With regard to
micronutrient deficiencies, while iodine status had improved nationally, vitamin A status had
deteriorated and there had been little or no improvement in other areas linked to
micronutrient deficiencies. The ratio of males to females was approximately 50.4% to 49.6%
across Pakistan. A total of 45.7% of household heads were illiterate and 38.7% were workers
or laborers. 15.5% of the population was unemployed – with higher rates in the urban
population (18.9% urban unemployment, 14.0% rural unemployment). Using a standard
questionnaire, the NNS 2011 indicated that 58.1% of households were food insecure
nationally. xi | National Nutrition Survey 2011
Overall, In Pakistan, 51.9% mothers were having normal weight, 14.1% thin and 33.9%
overweight while thin mothers were highest (16.4%) in rural areas compare to urban (9.0%)
and overweight mothers were higher (48.4%) in urban areas compare to rural (27.4%).
Among the regions and provinces the ratio of overweight mothers was highest (38.2%) in
KP and thin mothers were highest (20.6%) in Sindh.
Night blindness prevalence reported by women who were pregnant at the time of this
survey was 12.7% while night blindness prevalence reported by women during their last
pregnancy was 15.6%. Approximately 42.8% of the population reported awareness of the
importance of iodine whereas 64.2% reported awareness about the benefits of iodized salt.
Only 39.8% reported using iodized salt whereas kit-testing results confirmed use at 69.1%.
This is a significant improvement over the 2001 NNS result of 17%. Overall knowledge of the
importance of vitamin A in Pakistan was 24.0%. Knowledge about other micronutrient
deficiencies was very low with significant rural and urban differences. Widespread micronutrient deficiencies were found in women. For example, the survey
discovered the following micronutrient deficiency levels in pregnant women: Anaemia
51.0%, iron deficiency anaemia 37.0%, vitamin A deficiency 46.0%, zinc deficiency 47.6%,
vitamin D deficiency 68.9%. The prevalence of micronutrient deficiencies in non-pregnant
women were as follows: Anaemia 50.4%, iron deficiency anaemia 26.8%, vitamin A
deficiency 42.1%, zinc deficiency 41.3%, and vitamin D deficiency 66.8%. Adequate iodine
status was documented at national level and in most of the provinces. Balochistan, AJK and GB were the only provinces that documented inadequate levels (<100 μg/l median iodine excretion) of iodine status. The proportion of women who were breastfeeding was estimated on the basis of feeding
practices in the past 24 hours dietary recall. Data indicated 63.5% of mothers predominantly
breastfed children from 0–6 months of age and 77.3% of mothers continued breastfeeding
up to 12–15 months. Anthropometry status has not changed much over the past decade. Among children under
5, 43.7% were stunted in 2011 as compared to 41.6% in the 2001 National Nutrition Survey.
15.1% were wasted compared to 14.3% in 2001, which has not changed since 2001 (NNS
2001). The anthropometric indices were relatively better in urban areas. Micronutrient deficiencies were also widespread in children. Biochemical analysis revealed
the prevalence of various micronutrient deficiencies in children <5 years of age: Anaemia
61.9%, iron deficiency 43.8%, vitamin A deficiency 54.0%, zinc deficiency 39.2% and vitamin
D deficiency 40.0%. xii | National Nutrition Survey 2011
An illustrative sample of 7,612 elderly persons was examined at their residence during the
survey. The data revealed that more than half (53.9%) of the Pakistan’s elderly population
did not have normal weight; they were either underweight or overweight. Among them
15.8% were thin, 24.2% overweight and 13.9% obese. The National Nutrition Survey 2011 indicates that stunting, wasting and micronutrient
malnutrition are endemic in Pakistan. These are caused by a combination of dietary
deficiencies; poor maternal and child health and nutrition; a high burden of morbidity; and
low micronutrient content in the soil, especially iodine and zinc. Most of these
micronutrients have profound effects on immunity, growth, and mental development. They
may underlie the high burden of morbidity and mortality among women and children in
Pakistan. Increasing rates of chronic and acute malnutrition in the country is primarily due to
poverty, high illiteracy rates among mothers and food insecurity. Such rates can also be
attributed to inherent problems in infant feeding practices and lack of access to the age-
appropriate foods. xiii | National Nutrition Survey 2011
Chapter 1: Introduction
1.2 Introduction
Pakistan is a federal parliamentary republic consisting of four provinces – Balochistan, Khyber
Pakhtunkhwa, Punjab and Sindh – and four federal territories – the capital Islamabad, the
Federally Administered Tribal Areas (FATA), Azad-Jammu and Kashmir (AJK) and Gilgit Baltistan
(GB). Bordering India, China, Iran and Afghanistan, the country can be divided into the Indus
plain in the East, the mountainous area in the North and Northwest and the Balochistan plateau
in the West. [1]
Pakistan is the sixth biggest country in the world, with an estimated population of more than 180
million people. It has the second largest Muslim population of any single country after Indonesia.
Ranking 141 out of 182 countries in the Human Development Index (HDI), Pakistan is an
impoverished and underdeveloped country. Life expectancy at birth stands at 65 years and the
adult literacy rate is 49% (male 63%, female 36%).
Pakistan is a disaster-prone country and is exposed to a multitude of natural disasters including
earthquakes, floods, storms and droughts [2-6]. The country was under military dictatorship for
33 of its 64-year existence.
The security situation in Pakistan is complex. There are a number of overlapping threats,
including the presence of non-state actors targeting government installations and security
forces, especially in the areas bordering Afghanistan. [4, 6]
1.2 Context of malnutrition
Estimates suggest that more than 150 million malnourished children around the world are under
5 years of age. It is also well recognized that half of the 12 million deaths among children under
5, or almost 54% of young child mortality in developing countries, can be linked to malnutrition.
[8] Studies suggest that malnutrition has a multiplicative effect on the risk of mortality from
infectious diseases. [9]
Like other major health issues, malnutrition is a prevalent problem in the South Asian region.
Half of the world’s malnourished women and children are found in just three countries:
Bangladesh, India and Pakistan. South Asia is the worst affected region and presents what has
been termed an “Asian Enigma” due to high rates of low birth weight (LBW), unhygienic
conditions, unsatisfactory breastfeeding and weaning practices and the poor status of women.
[10]
Malnutrition is a recognized health problem in Pakistan and plays a substantial role in the
country’s elevated child morbidity and mortality rates. Due to its correlation with infections,
malnutrition in Pakistan currently threatens maternal and child survival, especially in poor and
1 | National Nutrition Survey 2011
underdeveloped areas. However, there are concrete solutions, which depend on political will, economic advancement and viable targeted research. [7] The number of underweight children and women is very high in the South Asian region. About
one third of babies are underweight and more than half of women of reproductive age weigh
less than 45 kg. [11] It is believed that malnourished adult women have a much higher risk of
giving birth to low birth weight infants. Infants born with a low birth weight are at a higher risk
of morbidity and mortality in the neonatal period or later infancy, especially in developing
countries. [12] The infants who survive are often poorly breastfed and weaned, resulting in
stunted and malnourished children. These conditions result in children growing into adults who
are less prepared to contribute to society and productivity, thus adding to poverty and
unemployment in the country. Low birth weight women also develop into malnourished
mothers who give birth to LBW babies and perpetuate this cycle.
Stunting is used as a reliable indicator of growth retardation in developing countries. The
stunting rates in Pakistan fell from 47% in 1980 to about 33% in 2000. [13] It is estimated that
the most important factors associated with lower prevalence of stunting are the availability of
high-energy nutrients, female literacy and gross national product. [16] Challenges linked to these
factors are still serious in Pakistan and particularly affect children, young girls and women. [16]
Like other developing countries in South Asia, with the exception of Sri Lanka, the situation in
Pakistan linked to maternal and child under nutrition is serious. [18] Pakistan’s prevalence of
stunting declined from 67% in 1977 to an estimated 40-50% and remained at such levels until
the end of the 1990s. However, these rates are still very high when compared to the global
average. [19] According to the national survey (1990-94), among the urban middle to lower
economic group, the prevalence of stunting was approximately 30-36% and as high as 35-45% in
the same economic group in rural areas. [20] The national survey categorized economic status
on the basis of material possessions and facilities owned by the household. However, it used
different criteria for urban and rural households. Thus, Pakistan’s urban-rural difference may be
partially explained by the relatively higher level of education among the urban population as
well as their access to basic health services. [21]
Malnourished children begin to fall behind on their regular growth at around six months of age.
This is the time when an infant starts receiving complementary foods in addition to breast milk.
[22] The divergence from normal growth is linked to a combination of poor nutrition and intra-
uterine growth. [23] This problem is aggravated by the burden of morbidity. [24] Poor quality
and quantity of complementary foods and inadequate caring practices are the key determinants
for this early phase of childhood growth retardation, [25] which can lead to late onset of the
childhood growth spurt and subsequent retardation. [26] Growth faltering is linked to a series of
occurrences a child suffers, including repeated illnesses, inadequate appetite, insufficient food
intake and poor standard care. Many of these children die before their first birthday and those
who survive suffer long-term consequences such as weak stature and challenged mental
capacity. [27] 2 | National Nutrition Survey 2011
Pakistan’s economy is largely dependent on agricultural output. The country’s farmers cultivate
sufficient amounts of diverse crops to feed most of the population, which makes the degree of
malnutrition even more distressing. However, the issue of malnutrition has been a constant
challenge in Pakistan for decades. The micronutrient survey in 1976-1977 revealed that 60% of
children under 5 were malnourished. Widespread malnutrition in younger infants was further
highlighted by a survey of children under 2 years of age. [28] The results of these surveys were
confirmed by high rates of early childhood malnutrition from studies conducted in Lahore.
[29,30] The National Nutrition Survey that was conducted in 1985-87 further revealed that 48%
of children were malnourished and 10% were severely malnourished. The 2001-2002 National
Nutrition Survey also showed a dire malnutrition situation in Pakistan. This was the first time a
NNS highlighted the true extent and burden of macronutrient and micronutrient malnutrition in
the country. [31]
Widespread macronutrient malnutrition coupled with subclinical micronutrient deficiencies
prevail in South Asia and have been largely ignored in the region and in Pakistan. “Subclinical
deficiency” is micronutrient malnutrition without visible signs of deficiency, also termed as the “hidden hunger”. It is estimated that more than seven million people suffer from clinical forms of these micronutrient deficiencies and another 2 billion from subclinical forms. [32] Various studies and surveys from Pakistan indicate that subclinical micronutrient deficiencies
such as iron-deficiency, zinc deficiency and vitamin A deficiency are widespread among pre-
school children and women of reproductive age, particularly pregnant women. [31] A survey
conducted with pre-school children in the North West Frontier Province (now Khyber
Pakhtunkhwa) revealed that about 50% of the children showed evidence of significant anaemia
and zinc deficiency. [33] Data on micronutrient malnutrition are scarce and limited. Only a few
studies have been conducted on a local scale and these cannot be relied upon to measure larger
scale issues. [34] To implement successful strategies and sustainable interventions, the direct and indirect causes
of Pakistan’s huge malnutrition burden must be identified. The analysis below identifies some of
the determinants of malnutrition in Pakistan and the impact these factors have on the status of
malnutrition in the country. More than 30% of Pakistan’s population lives below the poverty line. [35] The Gini coefficient,
used to measure economic inequality in a society (using the range of 0 to 1, “0” indicating
complete equality and “1” indicating complete inequality), is 0.410 in Pakistan. This shows a very
high rate of inequality. The poorest 20% of the population earn 6.2% of the country’s total
income and most households in Pakistan spend almost half of their income on food. Poor food
availability, poor quality of diet, and limited knowledge about nutritious foods all contribute to a
vicious cycle of malnutrition. Political issues, security issues linked to non-state actors and
unemployment in the country have amplified this problem. Another important risk factor
contributing to malnutrition is a high and repeated burden of infections. 3 | National Nutrition Survey 2011
Repeated acute respiratory infections (ARI), diarrhoea and other infections lead to a decrease in dietary intake and nutrient use due to loss of appetite and reduced absorption. [36] Poor breastfeeding and weaning practices are also common in Pakistan. As a result, infants do
not consume adequate calories, proteins and micronutrients. While almost 90% of women
breastfeed their children, very few start breastfeeding within one hour of birth and most of
them discard colostrum considering it as waste or impure milk that is not suitable for their
babies. The rate of exclusive breastfeeding in the first four months is only 16%. The current
number of mothers introducing complementary foods at the right time is low and poor food
choices commonly result in increased risk of diarrhoea and malnutrition. It is well known that
lack of awareness about proper nutrition and feeding practices, coupled with poor food choices,
trigger the widespread use of weaning diets with poor micronutrient content and bioavailability.
[37]
The fertility rate in Pakistan is very high. On average, Pakistani women give birth 6.8 times in
their lives. Approximately only 28% of women between 15 and 49 years of age use
contraception. A high fertility rate and lack of birth spacing result in a continuous cycle of
pregnancy and lactation. Such a cycle can deplete the body reserves of an already malnourished
mother. The adult literacy rate in 2011 in Pakistan was low, 67% for males and 42% for females. It is
believed such low levels of education among women in Pakistan influence their reproductive
behaviour. It also makes reproduction related decisions in families and in society at large
principally dependent on men’s knowledge and practices. In general, women in Pakistan have
very little control over areas of life such as food distribution within household and family
planning. [38, 39] Antenatal care plays a vital role in the wellbeing of mothers and growing children. The care a
mother receives during pregnancy and after delivery determines how well she will be able to
feed and care for her child. This includes breastfeeding, food preparation, general care, hygiene
and home health care. In Pakistan most pregnant mothers are unaware of the importance of
antenatal care and have limited access to health facilities. The use of antenatal health care
facilities is very low in the country and access has remained static over the years. To make
matters worse, in 2011 trained health personnel attended only 39% of births. [40]
The rates of malnutrition in children under 5 determined by the 2001 National Nutrition Survey
(NCHS standard) were as follows: wasting 13%, underweight 38% and stunting 37%. In the same
survey about 13% of non-pregnant and 16% of pregnant women were reported to be
malnourished (BMI<18.5). Similarly high estimates for micronutrient deficiencies shocked both
the Pakistani population and the world. In terms of Iodine deficiency about 7% of school going
children (6 -12 years) had either palpable or visible goitres on clinical examination. Vitamin A
deficiency, as measured by serum retinol levels, quoted 6% of mothers and 12.5% of pre-school
children to be deficient. 4 | National Nutrition Survey 2011
Evaluation for iron deficiency showed 45% prevalence in mothers and 66.5% in children. Caring
practices were also recognized as poor in the same survey. Many of these indicators are well
above the World Health Organization (WHO) cut off points and warrant putting in place
immediate public health measures and programs. The direct and indirect factors that lead to malnutrition contribute to nearly 35% of all under 5
deaths in Pakistan and affect the future health, socioeconomic development and productive
potential of the society. Despite an increase in food availability over the past 20 years there has
been little change in the prevalence of malnutrition in the population. This may be related to the
cross-sectoral and complex nature of malnutrition, which includes issues related to poverty,
intra-household food security and contemporary socio-cultural factors determining dietary
patterns in pregnancy and early childhood.
1.3 Need for a National Nutrition Survey
National Nutrition Surveys provide an estimate of the severity and geographical scope of
nutrition related challenges in a country. They also expose problems closely linked to nutrition
issues and identify the most-at-risk groups. Nutrition surveys assess the likely evolution and
impact of nutrition levels on the health and nutritional status of the population at large while
taking into account secondary information such as food security and food distribution. They also
help identify what types of nutrition interventions would be most effective to prevent or
minimize the problem in the future. Governments use national surveys when deciding whether
or not to establish or expand existing nutrition surveillance and to ensure effectiveness and
monitor progress over time. To assess the magnitude of the problem, governments and partners
also look at the population size, demographic characteristics of the population and distribution
of malnutrition cases therein. To understand the underlying causes of under nutrition and to plan and implement appropriate
interventions and programs to improve the situation, the government and partners must
identify the current nutritional status of both the population at large and vulnerable groups,
recognize changes in nutritional status over time, and acknowledge the context in which
challenges have surfaced. Sources of information that promote a deeper understanding of this
context and help identify potential responses include formal nutrition surveys, food security
surveys and records of malnutrition cases. Formal nutrition surveys are still the best way to
accurately estimate prevalence of malnutrition because they reveal trends in the number of
malnutrition cases and identify opportunities for action. The last National Nutrition Survey was conducted in 2001/2002, almost 15 years after the
1985/1987 National Nutrition Survey. Almost a decade later, the current survey was undertaken
with the following goals:
Establish the current nutrition benchmark and related indicators for gauging progress
toward the targets set for the Millennium Development Goals (MDGs); 5 | National Nutrition Survey 2011
Establish a benchmark for missing data/indicators, especially since the recent Demography and Health Survey (DHS) did not include anthropometric indicators.
Prioritize the programs and initiatives at the national and provincial level and refine the planning and implementation of initiatives on the basis of identified priorities.
1.4 Survey duration
Data collection began in January 2011 and was completed on 30th June 2011. The survey teams
underwent five days of extensive training led by senior and experienced staff from The Aga Khan
University who had experience conducting similar surveys in Pakistan and also abroad (Sri Lanka
and Maldives). Training sessions and refreshers were conducted in Karachi, Faisalabad, Lahore,
Rawalpindi, Peshawar, Abbottabad, Quetta and Gawadar. 6 | National Nutrition Survey 2011
Chapter 2: Survey Design and Methods
2.1 Survey Objectives The specific objectives of the National Nutrition Survey 2011 were: Assess the population’s nutritional status, especially children under 5, women of
reproductive age, adults and elderly on a national and provincially representative sample.
Collect specific representative data on height, weight and age of children under 5 years of age, women of reproductive age, adults and elderly.
Collect blood specimens for micronutrient status assessments of children and women of reproductive age – mainly vitamin A, zinc, calcium and vitamin D, and iron.
Collect urine samples to assess the iodine status of women of reproductive age and children between 6–12 years of age.
Assess infant and young child feeding and care practices, including breastfeeding, complementary feeding and morbidity of children.
2.2 Methodology The survey was conducted at national scale through a representative cross-sectional survey at household level. Cross-sectional surveys are useful in providing an overall estimate of prevalence and coverage in a geographic area. The survey used both quantitative and qualitative methods to achieve the objectives. The survey consisted of interviews, measurement of anthropometric indices, collection and testing of biologic specimens. A multi stage cluster methodology was de-signed so as to provide national and provincial representative data. This survey was conducted in all the four provinces (Sindh, Punjab, Balochistan and KP) plus Azad Jammu and Kashmir (AJK), Gilgit Baltistan and Federally Administered Tribal Areas (FATA) as defined by the 1998 population census. 2.3 Sample Size and its Allocation 2.3.1 Sample size estimates for household survey After considering a variety of characteristics including population distribution and field resources available, a sample size of 30,000 households was calculated as a sufficient number of households to provide representative results. An exercise to compute the sample size based on the prevalence rate of three key variables – wasting in children under 5 years of age, stunting in children under 5 and maternal iron deficiency – was undertaken. The sample is estimated to have a 95% confidence interval and a 5% margin of error. A 5% non-response rate was also considered. The design effect of 1.6 was used to finalize and fix the overall sample size. The entire sample of 30,000 households (SSUs) was fixed comprising of 1,500 (PSUs) out of which 618 were urban and 882 were rural. As the urban population was more heterogeneous, a larger proportion of the sample size was allocated to urban domain. As KP and Balochistan are smaller provinces, a higher proportion of the sample size was allocated to these two provinces in order to obtain reliable estimates. After fixing the sample size at provincial level, further distribution of sample PSUs into different strata in rural and urban 7 | National Nutrition Survey 2011
domains in each province was made proportionately. The distribution of PSUs and SSUs enumerated in the urban and rural domain of the provinces and regions is indicated below:
Table 2.1: Sample size and allocation plan Number of sample PSUs Number of sample SSUs Province/Region Total Urban Rural Total Urban Rural
Punjab* 682 307 375 13,640 6,140 7,500
Sindh 323 157 166 6,460 3,140 3,320
KP 218 67 151 4,360 1,340 3,020
Balochistan 110 44 66 2,200 880 1,320
FATA 67 0 67 1,340 0 1,340
AJK 66 28 38 1,320 560 760
GB 34 15 19 680 300 380
Total 1,500 618 882 30,000 12,360 17,640
* Including Islamabad
A-Biochemical Assessment: For biochemical analysis prevalence of Anemia in women and chil-
dren was taken as an indicator for sample size estimation. For 51% Prevalence of anemia in
women and 29% in children (NNS 2001), with a precision of 2%, design effect of 1.6 and power
of 90% the sample size achieved was 8534 for WRA and 7032 for children under five years of
age. 15% attrition rate was added to the sample size achieved and the final sample size came to
9836 for WRA and 8100 for children under five years.
For biochemical assessment we selected households where having a pair of mother and under
five children, the youngest child (under five) was selected for blood sampling from selected
households. The below table describes the sample size and its distribution among the WRA and
Children under five years of age in various regions.
Table 2.2 Region wise sample size and its distribution
Population
Rural Urban
children
Sample
WRA
Sample
Proportion
Distribution
Distribution
proportion N=8004 N=9836
Urban
Rural
Urban
Rural
Urban
Rural
AJK 2.1 12.88 87.12 168 22 146 207 27 180
Balochistan 4.8 23.9 76.1 384 92 292 472 113 359
FATA 2.3 2.7 97.3 194 15 179 226 6 220
GB 0.7 32.34 67.66 52 18 34 69 22 47
KP 13 16.9 83.1 1061 186 875 1279 216 1063
Punjab 54.7 97 103 4398 1387 3011 5380 1704 3676
Sindh 22.4 48.8 51.2 1843 885 958 2203 1075 1128
100 32.5 67.5 8100 2605 5495 9836 3197 6639
B. Sampling Frame and Design
A-Universe of the survey: The universe for this survey was comprised of all urban and rural areas of all four provinces of Pakistan, the Federally Administered Tribal Areas (FATA), Azad
8 | National Nutrition Survey 2011
Jammu Kashmir (AJK) and Gilgit Baltistan (GB) defined as such by the 1998 Population Census,
and the subsequent changes made by the provincial governments periodically. The population of
the military restricted areas was excluded from the scope of this survey. B-Sampling frame: For National Nutrition Survey in Pakistan the sampling frame of Federal
Bureau of Statistics (FBS) was used. The Federal Bureau of Statistics (FBS) has its own sampling
frame for all urban and rural areas of Pakistan in the form of enumeration block. Each
enumeration block consists of about 200 to 250 households with well-defined boundaries, which
are recorded on forms and maps that also include physical features of the area and important
landmarks. B.1: Urban areas: In urban areas each enumeration block has been classified into low, middle or
high income groups depending on what income group the majority of the households located in
that particular enumeration block belonged to. This information was then used to formulate
sub-stratification. This sampling frame covers all urban areas of Pakistan Due to rapid growth in
these areas; the frame is regularly updated every 5 to 7 years. It was entirely updated in 2004.
There are 26,753 enumeration blocks in all urban areas of the country.
B.2: Rural areas: The Enumeration blocks in In rural areas consists of mouzas, dehs and villages. A mouza, deh or village can be defined as the smallest “revenue estate” and FBS has used these
as rural Enumeration blocks. The rural sampling frame is comprised of 50,572
mouzas/dehs/villages and has been used to draw the sample for this survey. C-Role of Federal Bureau of Statistics in Sample design and Frame: FBS was one of the main
collaborators in the implementation of National Nutrition Survey; FBS provided the sample size
estimation, sample design and the sampling frame providing the provincial representativeness.
The Sampling frame for NNS was comprised of 1500 PSU (618 Urban and 882 Rural) randomly
selected from their main sampling frame. FBS also provided support for the listing of households
in each PSU. D-Listing of Households (SSU) in each enumeration Block (PSU): Fresh listing of households was
undertaken in all enumeration blocks (PSU) after a comprehensive training of the quantitative
survey team. The sketch map of enumeration blocks drafted by the Federal Bureau of Statistics
(FBS) in urban areas was used to perform listings. In rural areas, villages were taken as the PSUs,
in line with the 1998 Population Census. Large sample villages that have a population of more
than 2,000 (according to the 1998 Population Census) were split into hamlets/blocks of equal
size. One of these blocks was selected randomly for data collection. Small villages were
completely listed. The listing of households was used to select a specified number of households
from urban and rural sample areas.
2.3.3 Sample selection procedure a) Selection of primary sampling units (PSUs) Enumeration blocks in urban domain and mouzas/dehs/villages in rural domain were taken as PSUs. In the urban domain, sample PSUs from each ultimate stratum/sub-stratum were selected 9 | National Nutrition Survey 2011
using the PPS method of the sampling scheme. In the rural domain, the number of households in
the enumeration block from the 2004 Economic Census and the population from the 1998
census for each village/mouza/deh were considered as the measure of size.
b) Selection of secondary sampling units (SSUs) Households within the sample PSUs were taken as SSUs. Twenty Households from each urban
and rural sample PSU were selected with equal probability using a systematic sampling
technique with a random start. Complete household lists freshly prepared during the listing
activities was used to draw the required SSUs from the list of households.
2.3.4 Target population The target population included women of reproductive age (15–49 years), children 0–59 months and elderly persons (>50 years).
2.3.5 Description of questionnaire (quantitative) A structured questionnaire was used to obtain the data. The questionnaire was developed using
standard components from previous and recent surveys undertaken nationally and
internationally. All the data collection tools were thoroughly assessed by the technical
committee established to oversee the NNS 2011. Three iterations of the survey instrument were
reviewed and the final version was approved in December 2010. In Section 1 of module “A”, all members of each household were listed by their gender, age,
education, occupation and marital status. Besides such information, anthropometry (height,
weight and clinical examination for anaemia, jaundice, cyanosis, edema and goitre) was
conducted for anyone who was present at the time of the survey. Data corresponding to the
name of each member was recorded. Section 2 of module “A” was exclusively designed for
obtaining socioeconomic data along with health and hygiene characteristics. Knowledge,
attitudes and practices about micronutrients (iron, iodine, and vitamins A, B, C and D) were
recorded in the module “B” while module “C” focused on reproductive history, intra-birth
interval, antenatal care, night blindness, worm infestation, iron supplementation and
morbidities. Additionally, module “C” assessed dietary intake and food practices using a 24-hour
dietary recall to determine patterns of eating habits and variety of foods consumed over a
longer period of time by WRA.
The infant and young child feeding (IYCF) Module “D” was used to capture several indicators
including data on birth, newborn weight, resuscitation, breastfeeding initiation, complementary
feeding, micronutrients, and 24-hour dietary recall and food practices for the youngest child. A
separate Module “E” was developed to determine the health status, immunization, physical
examination and lab investigation of children under-5 years of age. The appetite, movement,
mobility and morbidities of elderly persons were also investigated in Module “F”. The poverty
assessment and food security Module “G” was also completed. 10 | National Nutrition Survey 2011
2.3.6 Description of qualitative research
The overall aim was to identify food consumption patterns, nutrition and food behaviour as well
as to gain insight into the factors affecting decision-making. These factors include, the
connection between diet, disease and health, beliefs about certain foods, dietary practices, food
intake patterns, consumption of local versus imported foods, and other factors relating to food
choices.
A-Qualitative research sample and target population
In qualitative research, purposive sampling is the dominant strategy and purposive sample size is
often determined on the basis of theoretical saturation (FHI, 2005). A total of 40 focus group
discussions and 16 in-depth interviews were conducted. Participants were identified and
selected through the community recruiters at their living sites.
2.3.7 Biochemical analysis
Biochemical assessment for micronutrient deficiencies was performed on children under 5 years
of age and women of reproductive age. Children between 6–12 years of age and WRA were also
assessed for urinary iodine. Details of the biochemical test that were done for NNS are shown in
table below.
Table 2.3: Description of biochemical analysis/tests
Biochemical Test
Children 0 to 59 months
Children 6 – 12 years
WRA
Vitamin A Yes - Yes
Vitamin D Yes - Yes
Zinc Yes - Yes
Haemoglobin Yes - Yes
Ferritin Yes - Yes
Calcium - - Yes
Urinary Iodine Yes Yes Yes
AGP and CRP Yes Yes
AGP and CRP were done to adjust the concentrations of micronutrients.
2.3.8 FATA Specific Data
The sample size for the National Nutrition Survey was calculated to be representative at regional
level. However, in FATA higher refusal rate (about 32%) was recorded. Therefore data from FATA
lost its regional specificity considering this fact we have presented the data of FATA in the report
at National level but not at regional level. We presented FATA specific data in the annexes along
with other regions but have recommend caution in its use and interpretations. Furthermore, the
refusal rate for collection of blood samples was even higher. Considering this fact the
biochemical assessments of FATA have not been presented.
11 | National Nutrition Survey 2011
2.3.9 Project pre-implementation steps Before launching the field activities the following steps were undertaken:
Table 2.4 Pre-implementation steps
Activities /Steps
Description of steps
Formation of Technical Technical committees – with representatives from the relevant stakeholders to
Committee oversee technical aspects of the NNS 2011 – were notified.
Liaison with partners:
Liaison with the local • Federal Bureau of Statistics (FBS)
partners • Ministry of Health (MoH) and provincial health departments
• Pakistan Medical and Research Council (PMRC) – data collection in KP and FATA
A detailed manual of operations for survey procedures was developed. This
Development of survey encompasses qualitative and quantitative data collection strategies,
manual anthropometry guidelines, sample collection and transportation guidelines, and
data management strategies.
Development Instruments The relevant consent forms and instruments were developed. The instruments
and consent forms have different modules relevant to study participants.
Ethical Review Committee Ethical review applications were submitted to National Bioethics and to AKU ethics
application submission committees for approval of the methodology and consent forms.
Acquisition of sample frame Worked closely with the FBS to develop the research design and sampling frame. A
sample size of 30,000 households and 1,500 enumeration blocks was proposed
and design from FBS
and agreed to.
Establishment of survey Survey hubs were established for the operational movement of field teams in the
following locations:
hubs: Punjab=8 (average 85
Sindh: Karachi, Hyderabad, Mirpurkhas and Sukkur
enumeration blocks per one
Punjab: RY Khan, Multan, DG Khan, Bahawalpur, Faisalabad, Lahore & Rawalpindi
Hub), Sindh=5 (65), KP and
KP and FATA: Abbottabad, Peshawar, Swat, D I Khan and Kohat
FATA=5 (57), Balochistan=5
AJK: Muzaffarabad, Bagh and Mirpur
(22), AJK=3 (22) and Gilgit
Gilgit Baltistan: Gilgit and Skardu
Baltistan=2 (17)
Balochistan: Gawadar, Khuzdar, Bella, Quetta, Dalbandin and Jaffarabad
A-Identification and recruitment of field staff: Advertisements (in-house and in the national
daily newspapers) were placed and candidates were shortlisted and interviewed in Karachi,
Faisalabad, Rawalpindi, Peshawar and Quetta.
B-Survey teams Initially 15 survey teams were established and more teams inducted as the
survey progressed to keep the momentum and to meet the time target. At one point, 22 teams
were simultaneously operating in different parts of the country. Each team consisted of 1 field
supervisor, 1 team leader, 4–5 data collectors, 3 registered nurses (with 1 phlebotomist), 2
logistic assistants and 2 community facilitators. Separate teams consisting of moderators and
facilitators, observers, note-takers and community recruiters were also established. C-Staff profile: The staff team included a national survey coordinator, a senior survey
coordinator and survey coordinators. All the team supervisors were senior medical doctors and
lead social scientists with over ten years of experience in nutrition related surveys nationally and
internationally. The team included experienced female team leaders who were trained in social 12 | National Nutrition Survey 2011
sciences. They helped gain access to households to ensure the quality and validity of data. All
data collectors were at least university graduates supported by logistics assistants and local
community facilitators.
D-Separate teams for mapping and listing: Each team consisted of a FBS representative and a
logistic assistant and were supported by local community facilitators as they visited each
EB/village prior to data collection for demarcation of the EB/village as per FBS maps. During this
exercise, all structures and households were listed and allotted a unique ID (NNS 1, 2, 3 for
structures and HH 1, 2, 3 for households). Additionally, basic data including that of children
under 5 years of age, the household head, women of reproductive age and elderly persons
above 50 years of age were obtained. From each of the listed HHs in the EB, 20 HHs were
randomly selected through a computerized process using Microsoft Excel.
E. Training: Training sessions and refreshers were conducted in Karachi, Faisalabad, Lahore,
Peshawar, Abbottabad, Quetta and Gawadar. These sessions took place over a period of five
days and were carried out by staff from the department of paediatrics and child health of Aga
Khan University who had prior experience in similar surveys. Some of the details of the training
agenda are shown in Table 2.5.
Table 2.5: Details of the training agenda
Staff
Training Components
All Staff Introduction to NNS Research design survey methodology
Community rapport building, counselling techniques, research basics, interviewing
techniques, dress code, consent procedures, interpersonal skills, ensuring high
Team Leaders response, sampling methodology, question by question explanation, mock interviews,
operational procedures, field procedures, daily documentation, log sheet completion,
dealing with refusals, spot checking, random checking and desk editing
Community rapport building, research basics, interviewing techniques, dress code,
Data Collectors consent procedures, interpersonal skills, ensuring high response sampling
methodology, question by question explanation, mock interviews, operational
procedures, field procedures, daily documentation, log sheet completion
Nurses Physical examination, anthropometry, field practice and urine sampling
Phlebotomists Blood sampling, safe injection practices, labelling and storage, transportation of
samples and field practice
F-Piloting/pre-testing: A pre-test was undertaken to pilot the questionnaire and to identify and
solve unforeseen problems before actual data collection. The objectives of the pre-test were to
improve the language of the questionnaire; establish the order of questions; check accuracy
and adequacy of the questionnaire instructions such as “skip” and “go to”; clarify the
instructions to the interviewers; eliminate unnecessary questions and add necessary ones;
endeavour to lessen discomfort, harm, or embarrassment to the respondent; improve
translation of technical terms; and estimate the time needed to conduct an interview.
13 | National Nutrition Survey 2011
Both the “participating” and “undeclared” pre-tests were undertaken. Participating pre-tests
were done in the classroom among the interviewers themselves while undeclared pre-tests were
done in the field without informing respondents that it was a pre-test. About 100–150 respondents with reasonably similar characteristics from the survey population
were interviewed in different parts of Karachi. The questionnaire was then revised and finalized
on the basis of the pre-test results and direct observations by survey supervisors. The survey
coordinators also closely monitored the pre-testing.
G-Coding scheme for assigning processing: A seven-digit coding scheme was developed in order
to provide processing codes to primary sampling units [i.e. enumeration blocks/villages (PSUs)]
and secondary sampling units [i.e. households (SSUs)]. 2.3.10. Plan of operation, training and monitoring In order to ensure timely completion of the survey, effective tools were developed for periodic
field activity checks. A one step forward strategy was developed instead of the conventional
approaches of monitoring. Additionally, internal monitoring survey stakeholders including
Federal and Provincial Nutrition Wings, the Ministry of Health, the Government of Pakistan and
UNICEF were proactively engaged in the training sessions as well as in monitoring and evaluating
the progress of the survey activities. Besides this, independent and experienced monitors were
also engaged.
A-Data Collection: On the day of survey the team identified each selected household using the
listing being recently done by the listing team and proper informed consent was taken before
the data collection. A total of twenty households from each enumeration areas were selected
and data collection on the structured instrument was done. The team leader ensured the
completion of data collection and quality of data in each cluster. For Biochemical assessment
every third household was selected for Biochemical assessment. A Mother and her youngest
child under five years were selected for blood draw. Blood samples were collected by trained
phlebotomists ensuring safe injection practice. The blood samples were sent to Nutrition
Research Lab of Aga Khan University through the national network of Clinical labs of Aga Khan
University. Cold chain was ensured during the transportation of the samples 2.3.11 Data management, transfer and analysis The filled-in questionnaires were first desk-edited at the field sites for completeness and
checked for major errors by the team leaders. Once this was complete, the questionnaires were
sent through a courier service to Aga Khan University’s Data Management Unit (DMU) in Karachi,
where a full time desk was established to receive the survey questionnaires, maintain log
registers and check for completeness. Where there was inconsistency or missing responses, the
editors flagged the errors/omissions and consulted the team leaders for clarification. Before
data entry, all questionnaires were coded for open-ended responses.
A-Software for data entry and analysis: Visual Fox Pro was used for designing the databases,
data entry software and procedures for data quality assurance. Range and consistency checks as
well as skip patterns were built in the data entry program to minimize entry of erroneous data.
14 | National Nutrition Survey 2011
Special arrangements were made to enforce referential integrity of the database so that all data tables were related to each other. Analysis of data was undertaken using SPSS version 18. B-Data entry and quality checks: Two pass verification or double data entry was carried out for
each filled-in questionnaire to minimize keypunch errors. An error check program was also
incorporated into the data entry system to ensure quality of data. Data entry started after one
week of data collection following clearance by the survey coordinator and requisite data quality
assurance.
C-Data Analysis: Data analysis SPSS version 18 was used and data was analysed. Statistical
Analysis was performed after the availability of clean and quality data. Each file was converted
from Fox Pro into SPSS files so that they could be read into SPSS for further analysis. Descriptive
statistics for the subjects was obtained and frequency tables were generated to ascertain the
information on various variables. Data was analysed using univariate method. Analysis was done
to ascertain and establish an association with the malnutrition of children. WHO Anthro (version 3.2.2, January 2011) was used for anthropometric analysis. However, ENA-
SMART software was used to check the day-to-day consistency of anthropometric data, which helped
to address measurement errors at the initial stages of data collection. We used height for age Z
scores, weight for height Z scores and weight for age Z score to assess the level of malnutrition.
Ranges of -6 to +6, -5 to +5 and -6 to +5 Z scores were used to assess HAZ, WHZ and WAZ re-
spectively while we flagged the values of <-6 and >+6, <-5 and >+5 and <-6 and >+5 in HAZ, WHZ
and WAZ respectively. The flagged values were excluded from the data analysis to avoid meas-
urement bias. We also done weighted analysis to limit the variability among enumeration blocks
and region, pre assigned weights from FBS were used to conduct this analysis
2.3.11. Ethical approval and confidentiality The survey design, sampling strategy and analytical plan were reviewed and approved by the Aga Khan University’s Ethics Review Committee as well as by the National Bioethics Committee (NBC) of the Government of Pakistan. Confidentiality of all collected data was assigned high priority during each stage of data handling. All the names and personal information regarding any individual were kept confidential and data sets were kept anonymous for analysis. Only senior staff had access to the data. All data files have been protected by passwords and serum and blood samples were duly secured, as per standard procedures of the institution. 15 | National Nutrition Survey 2011
Results of the
National Nutrition Survey 2011
16 | National Nutrition Survey 2011
Chapter 3: Background and Household Characteristics
3.1 Completion of data collection
The required sample size for data collection was 30,000 households. The survey teams were able
to approach the required number of households, however, 6.8% of the sampled households
refused to participate in the survey. A total of 27,963 households consented to participate in the
survey and interviews were conducted successfully. The refusal rate varied widely between
regions – the lowest being in AJK at 1.3% and the highest being FATA1 at 32.8%. This was
possibly related to the prevalent insurgency, security issues and accessibility in the FATA region.
A verbal consent was obtained from participating households prior to the interview for
permission to collect information and anthropometric measurements through a pre-printed
questionnaire. For blood draws, urine samples collection and clinical examination a written
consent was obtained. The NNS 2011 coverage and population density maps for comparison of
sample distribution and population conglomeration are featured below:
Fig 3.1 Population density Fig 3.2 National Nutrition Survey coverage
Sample size coverage by provinces and regions is listed in the next table.
Table 3.1: Details of sample size coverage (Number of PSUs and SSUs by Province / Region – Household Interviews Completed)
PSUs Household (HH) Interviews
Province / Region
Target Completed HH Visited Consent HH Refusal Rate (%)
Refused Completed
Punjab 682 682 13,640 452 13,188 3.3
Sindh 323 323 6,460 178 6,282 2.8
Khyber Pakhtunkhwa 218 218 4,360 734 3,626 16.2
Balochistan 110 110 2,200 204 1,996 9.3
FATA 67 67 1,340 440 900 32.8
AJK 66 66 1,320 17 1,303 1.3
Gilgit Baltistan 34 34 680 12 668 1.8
All Pakistan 1,500 1,500 30,000 2,037 27,963 6.8
1
Data from FATA are not representative due to high non-response rate.
17 | National Nutrition Survey 2011
3.1.1 Blood and urine specimen Overall 24,421 blood samples (12,282 women and 12,139 children) were collected across Pakistan. The
survey teams also collected 2,900 urine samples from women (1,460) and children 6-12 years (1,457) for
biochemical assessments.
3.2 Background and household characteristics The total population counted in the surveyed households was 187,095. Males slightly outnumbered
females (approximately 50.4% of the population were males and 49.6% females). The gender breakdown
was 101.6 males to 100 females, which differed from the last census conducted in 1998 that found 108.5
males for every 100 females. This is, however, similar to the 2006 Pakistan Demographic and Health
Survey statistics, which found 102 males for every 100 females. However, in AJK it was 95.7 males per
100 females. The average household size was 6.6, which is similar to what was found in the 1998 census.
3.3 Formal education – head of household and mothers In the NNS 2011, 45.7% of the household heads were illiterate. The proportion of illiterate heads of
household was lowest in AJK at 27.3%, whereas the proportion was highest in Balochistan at 58.2%.
Female literacy in Pakistan has been a challenge for many decades.
The results of the NNS 2011 showed that the proportion of illiterate mothers was 59.3% and the
proportion was almost double in rural areas than it urban areas (36.6% urban and 69.4% rural). Only
10.5% of mothers completed their 10 years of schooling and 9.0% managed to complete their studies
beyond grade 10. Data from the survey further revealed that about 10.9% of mothers from rural areas
received education 9th grade and above while in urban areas 38.8% achieved the same.
Fig 3.3: Formal education of mothers of children under five years of age.
100%
9.0%
4.0% 9.7% 11.2%
5.9% 3.4% 1.0% 12.9% 10.9%
90%
20.3% 14.5% 8.3% 12.1%
19.2%
16.3% 16.0% 6.3% 4.6%
80%
12.1% 21.7%
5.9%
20.2%
70%
12.5% 29.7%
10.3%
39.0% 6.5%
60%
16.0%
50%
13.4%
82.0% 82.3%
40%
17.7%
69.4%
72.2% 62.4%
30%
59.3%
62.2%
52.6%
20%
36.6%
30.4%
10%
0%
Pakistan
Urban
Rural
Punjab
Sindh
KP Balochistan FATA*
AJK
GB
Illiterate
1-5 Years
6-10 Years
Above Matric.
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
18 | National Nutrition Survey 2011
3.4 Occupation – head of household The NNS 2011 data showed that 53.6% of household heads were labourers, workers or farmers. Of these,
35.9% belonged to the urban population and 61.6% to the rural population. In comparison to the
previous findings in the NNS 2001, 16.6% of household heads belonged to the labour/worker/farmer
groups. Government and private service employees were the second largest group of those in
employment (16.4%). The figures showed that the proportion of unemployed heads of households had
doubled since 2001 (7.7% in 2001 compared to 15.5% in 2011).
3.5 Nature of dwelling by type of floor, roof and walls The survey found that a large proportion of people living in urban and rural areas lacked basic civic
necessities. The NNS 2011 data show that 64.2% of families were residing in houses that were
constructed using bricks and concrete, which was an increase from the NNS 2001 findings (50%). The
facilities available differed significantly between urban and rural areas, with less houses constructed with
bricks and concrete in the rural areas (53.7%) than in the urban areas (86.9%). In 2011, across Pakistan
20.7% of household walls were made only with bricks and 55.9% houses had cement or tiled floors. 40.8%
of houses had mud/sand floors – 10.2 % in urban areas and 54.9% in rural areas. Rural households were
more likely than urban households to have sand or mud floors, while urban households were more likely
than rural households to have floors made with cement.
Fig 3.4 (a-c) Nature of dwelling – materials used
70% 64.2%
60% 50.0% 49.0%
50%
40%
30% 20.7%
20% 15.2%
10% 2.0%
0%
Cement/lime bricks Brick (not Others
cemented)
Type of wall 2001 Type of wall 2011
60% 55.9%
50% 43.0%
45.0%
40.8%
40%
30%
20% 12.0%
10% 3.4%
0%
Cement/Tiles Mud/sand Others
Type of Floor 2001
Type of Floor 2011
80%
69.1%
70%
60%
50% 43.0%
40% 36.0%
30% 21.0% 19.9%
20% 11.0%
10%
0%
RRC/Tiles Wood Others
Type of Roof 2001 Type of Roof 2011
19 | National Nutrition Survey 2011
Fig 3.5 Nature of dwelling – urban/rural comparison of materials used for construction
100%
Bricks, cement and lime
Bricks (Not cement)
Other materials
86.9%
84.7%
90%
80%
70%
64.2% 62.3%
60% 49.7%
53.7%
50% 48.7%
35.4%
40%
25.6%
30% 20.7%
20.8%
20% 15.2%
10.1%
14.5%
10%
1.7%
1.4% 3.0% 0.8%
0%
NNS 2001 NNS 2011
NNS 2001 NNS 2011
NNS 2001 NNS 2011
National Urban Rural
3.6 Type of fuel used for cooking Over the last decade the use of firewood has decreased. At the time the NNS 2011 was being carried out,
around 57.9% of the households in Pakistan were still using firewood as the prime source of cooking fuel
while the use of firewood was reported to be 66.7% in the NNS 2001. At 35.8%, natural gas was found to
be the second main source of cooking fuel. This was available in 83.3% of households in urban areas. Use
of animal dung as fuel was observed to have reduced significantly in all parts of Pakistan. Only 6.1% were
using animal dung during the NNS 2011 as compared to 14.6% in the NNS 2001. The use of kerosene oil
also reduced substantially from 3.3% to 0.2%.
Fig 3.6: Source of fuel for cooking
100%
Wood
Gas
Kerosene oil
Animal dung
87.8%
90%
83.3%
77.4%
80%
66.7%
69.3%
70%
57.9%
60%
50%
35.8%
40% 15.4%
29.2%
30%
15.5%
20.3%
20% 14.6%
13.9%
4.4% 10.2% 8.3%
6.1%
1.2%
10% 3.3%
3.9%
2.9%
0.3%
0.2% 0.0%
0%
NNS 2001 NNS 2011
NNS 2001
NNS 2011
NNS 2001
NNS 2011
Pakistan Urban Rural
20 | National Nutrition Survey 2011
Chapter 4: Food Insecurity in Pakistan
According to the FAO Publication, The State of Food Insecurity 2001, “Food security [is] a
situation that exists when all people, at all times, have physical, social and economic access to
sufficient, safe and nutritious food that meets their dietary needs and food preferences for an
active and healthy life”2 No single indicator can capture the full range of food insecurity and
hunger and the most reliable methods require periods of observation and household food
inventories. Instead, most commonly household levels of food insecurity or hunger are
determined by obtaining standardized information on a variety of specific conditions,
experiences and behaviours that serve as indicators of the varying degrees of severity. While
developing the module and data collection data were collected using standard internationally
validated food security question; these included: Anxiety that household food budget or food supply may be insufficient to meet basic needs.
The experience of running out of food, without money to obtain more.
Perceptions by the respondent that the food eaten by household members was inadequate in quality or quantity.
Adjustments to normal food use, substituting fewer and cheaper foods than usual.
Instances of reduced food intake by adults in the household, or consequences of reduced intake such as the physical sensation of hunger or loss of weight.
Instances of reduced food intake or consequences of reduced intake for children in the household.
The following steps were followed to analyse the food security data considering the guide to measuring household food security as a standard:
Converting the survey responses collected using the core-module questionnaire into the data set needed for applying the measurement model;
Applying the model to the data to determine the food security status level of each household;
Determining the severity level of the condition experienced in those households that show evidence of food-insecurity/hunger.
In the NNS 2011 the household food security was determined on the basis of four categories:
food secure, food insecure without hunger, food insecure with hunger (moderate) and food
secure with hunger (insecure). Given that the sample was not powered for provincial estimates,
we report national averages.
4.1. Food secure This category include households that show no or minimal evidence of food insecurity.
4.2. Food insecure without hunger Food insecurity is evident in household members’ concerns about adequacy of the household food supply and in adjustments to household food management, including reduced quality of food and increased unusual coping patterns. Little or no reduction in members’ food intake is reported.
2 FAO. 2002. The State of Food Insecurity in the World 2001. Rome
21 | National Nutrition Survey 2011
4.3. Food insecure with hunger (moderate) Food intake for adults in the household has been reduced to an extent that implies that adults
have repeatedly experienced the physical sensation of hunger. In most (but not all) food-
insecure households with children, such reductions are not observed at this stage for children.
4.4. Food insecure with hunger (severe) At this level, all households with children have reduced the children’s food intake to an extent
indicating that the children have experienced hunger. For some other households with children,
this already has occurred at an earlier stage of severity. Adults in households with and without
children have repeatedly experienced more extensive reductions in food intake. The results revealed that 41.9% of households were food secure at the national level. 28.4%
were food insecure without hunger, 19.8% were food insecure with moderate hunger and 9.8%
were food insecure with severe hunger. Rural households were more food insecure (60.6%) as
compared to urban households (52.4%).
Fig 4.1: Food insecurity situation
70% Food Insecure Without Hunger
Food Insecure With Hunger (Moderate)
Food Insecure With Hunger (Severe)
60%
9.8%
10.5%
50%
8.2%
40%
19.8% 17.7%
20.7%
30%
20%
28.4% 26.5% 29.3%
10%
0%
Pakistan Urban Rural
The food security situation showed no signs of improvement since the last food insecurity
assessment conducted by the United Nations in Pakistan3, which revealed that 51% of the
population was food insecure. The situation has, in fact, deteriorated further. This will have serious implications on the nutrition, growth and health of the Pakistani population.
3 WFP (2009). Food insecurity in Pakistan.
22 | National Nutrition Survey 2011
Chapter 5: Maternal Health and Nutrition
During the National Nutrition Survey 2011, detailed data were collected on basic nutritional
indicators including dietary intake, reproductive history, anthropometry, clinical and biochemical
micronutrient deficiencies and on knowledge and practices linked to micronutrients.
5.1: Basic data – age and marital status of mothers
5.1.1 Age distribution
The survey revealed that about 63.7% of mothers were between 20–34 years of age, 28.2% were
between 25–29 years and 23.9% were between 30–34 years. The data revealed no major
differences between urban and rural age group distribution.
5.1.2 Marital status and current pregnancy status
Only 1.3% of mothers were either separated or widowed (2.0% urban; 1.0% rural), the rest of
them were currently living with their husbands. Among all married women (24694), 10.0%
women were pregnant. Provincial results showed variations; number of currently pregnant
women was the highest in Sindh (11.9%) followed by Punjab 11.2%, AJK 9.1%, GB 7.3%, KP 6.0%
and Balochistan 5.1%.
5.2: Reproductive history and antenatal care
5.2.1 Reproductive history
29.7% of women surveyed had been pregnant 1 to 2 times, 46.6% had been pregnant 3 to 5
times and 23.7% had been pregnant 6 or more times. The data did not find any major difference
in the number of pregnancies between urban and rural areas but provincial variation was
observed. Further data regarding outcome of the last pregnancy showed that 93.4% of
pregnancies resulted in live births, whereas 5.7% ended as miscarriages and 0.8% in stillbirths.
5.2.2 Antenatal care
A-Antenatal care during last pregnancy: Seeking antenatal care during pregnancy is of great
importance as it identifies risk factors. Unfortunately, there has been no improvement in the
percentage of women seeking ANC since 2006-07. The PDHS 2006-07 data showed that 65.3% of
pregnant women sought care during their last pregnancy while the NNS 2011 results found
62.0% sought ANC. The data revealed a clear difference of ANC seeking behaviour patterns when
comparing women living in urban areas, where 81.4% sought ANC, and rural areas, where 53.7%
sought ANC. Provincial data revealed that women who sought care during their last pregnancy in
Punjab was 66.5%, Sindh 61.6%, KP 55.7%, Balochistan 47.1%, AJK 80.8% and GB 80.0%.
23 | National Nutrition Survey 2011
Fig 5.1: Antenatal care during last pregnancy
90% 81.4%
80.8% 80.0%
80%
66.5%
70% 62.0%
61.6%
60% 53.7% 55.7%
47.1%
50%
40%
27.1%
30%
20%
10%
0%
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution. B-Choice of care provider: The selection of a qualified and skilled health care provider ensures
quality care during pregnancy. In Pakistan, the percentage of women seeking care from skilled
care providers has not significantly improved. The survey showed that in 2011 58.9% of mothers
received ANC from a skilled provider. Of those who sought care from a skilled provider, 49.5%
received care from a qualified doctor, 7.1% from a nurse and 2.3% from a Lady Health Visitors.
The percentage of women who sought care from skilled care provider varied by province: Punjab
63.5%, Sindh 59.9%, KP 50.9%, Balochistan 42.5%, AJK 79.7% and GB 77.0%.
Fig 5.2: Seeking ANC from skilled care provider
90%
80%
70%
60%
50%
40%
78.4%
30%
58.9%
50.5%
20%
10%
0%
Pakistan Urban Rural
C-Micronutrient Supplementation during pregnancy: Data on women’s micronutrient
supplementation during their last pregnancy were also collected. 24.4% of pregnant women
consumed iron (33.2% in urban areas and 20.4% in rural areas); 25.3% consumed folic acid
(35.7% in urban areas and 20.7% in rural areas); 3.9% consumed micronutrients; and 35.6%
consumed calcium. The details of the nutrition supplements consumed during last pregnancy are
illustrated below in figure 5.3. 24 | National Nutrition Survey 2011
Fig 5.3: Micro-nutrient supplementation during last pregnancy
60% Pakistan
Urban
Rural
48.6%
50%
40%
33.2%
35.7%
35.6%
29.9%
30%
24.4% 25.3%
20.4% 20.7%
20%
10%
3.9% 3.5% 4.0%
0%
Iron Folic Acid Micronutrient Calcium
5.3: Knowledge of micronutrients and micronutrient rich foods Micronutrient deficiencies are an important public health problem in Pakistan. In the NNS 2011,
questions were asked to determine respondents’ level of knowledge about micronutrients,
micronutrient rich foods and the impact of deficiencies (the education level of the respondents
was taken into account).
5.3.1 Knowledge of micronutrients
To obtain information on micronutrient knowledge, survey respondents were asked simple
questions such as, “Have you ever heard about (name of micronutrient)?” to determine if they
knew what “foods contain (name of micronutrient)” and the “impact on health if deficient.”
Fig 5.4: Knowledge about micronutrients
70%
Iron
Iodine
Vitamin A
Zinc
Vitamin D
Vitamin B
61.6%
60%
50%
42.8%
42.0% 41.6%
40% 38.0%
34.4%
34.2%
30%
24.8% 24.0% 20.8%
12.5%
20% 19.3% 17.0% 16.0%
12.8% 13.0%
10% 6.1%
3.1%
0%
Pakistan Urban Rural
25 | National Nutrition Survey 2011
The survey found that knowledge about micronutrients was generally low and varied greatly
between urban and rural areas. Only 24.8% of mothers had knowledge about iron across
Pakistan – 42.0% in urban and 17.0% in rural areas. Only 6.1% of mothers had knowledge about
zinc – 12.8% in urban areas and 3.1% in rural areas. 24.0% mothers had knowledge about
vitamin A – 41.6% in urban areas and 16.0% in rural areas. 20.8% of mothers had knowledge
about vitamin D – 38.0% urban areas and 13.0% in rural areas. 19.3% of mothers had knowledge
about vitamin B complex – 34.4% in urban areas and 12.5% in rural areas. Finally, 42.8% of
mothers in Pakistan had knowledge about iodine – 61.6% in urban areas and 34.2% in rural
areas.
5.3.2 Knowledge of vitamin rich foods Pregnant women are considered to be a nutritionally vulnerable segment of the population due
to their greater need for nutritious foods during pregnancy. Marginal nutrient intake increases
the risk of nutritional deficiencies during pregnancy. For this reason, it is concerning that across
Pakistan only 24.8% of mothers had heard about iron and half of them did not know which foods
contain iron. However, among those who knew, 36.5% mentioned that green leafy vegetables
contained iron while 20.1% mentioned meat. Mothers also had poor knowledge about health
problems caused by zinc deficiency. Overall, 73.3% of mothers did not know about foods that
contain zinc. Only 7.4% mentioned meat and meat products while 2.3% mentioned watermelon
seeds as a source of zinc. The majority of mothers (58.4%) in Pakistan did not know which foods
contain vitamin A and just a small proportion had knowledge about vitamin A rich foods. The
majority of mothers (64.4%) also did not know about Vitamin D rich foods in Pakistan. Only 4.8%
mentioned eggs, 9.3% mentioned meat and liver, and 3.7% mentioned sunlight as a source.
Approximately 69.6% of mothers were not aware about the vitamin B complex rich foods in
Pakistan. 13.4% of women mentioned that they thought fruits contained it and 11.9%
mentioned green leafy vegetables were vitamin B complex rich foods.
The national iodine deficiency disorder control program was launched in 1994 to promote use of
iodized salt. Nevertheless, across Pakistan mothers had relatively poor knowledge about health
problems caused by iodine deficiency. The NNS 2011 survey findings revealed 66.9% of the
respondents mentioned iodized salt as the major source of iodine, while just 2.4% were aware of
other iodine rich foods like fish and seafood.
5.3.3 Knowledge about iodized salt and its usage Overall, 64.2% of mothers said they were aware of iodized salt. Knowledge of iodized salt was
higher (83.0%) in urban areas than in rural areas (55.6%). The respondents from AJK (82.0%),
Gilgit Baltistan (79.5%) and Punjab (71.4%) had excellent awareness as compared to other
provinces. The reported use of iodized salt for cooking was 39.8% across Pakistan. A considerable
provincial/regional variation was found between Gilgit Baltistan (94.8%), AJK (71.6%) and Punjab
(36.1%). The reported use of iodized salt was higher (46.5%) in urban areas than in rural areas
(35.2%). 26 | National Nutrition Survey 2011
Rapid iodized salt test kits were used in the survey to assess iodine content in salt used in
households. The kit can test salt with drops of stabilized starch based solution, which causes a
chemical reaction leading to colour change. The salt sample was taken on a teaspoon, and, after
shaking the reagent (test solution) bottle well, a drop of the test solution was poured on the salt.
The salt turned light blue to dark violet depending on the iodine content of the salt. To assess
the iodine content, the colour of the salt is compared to that on a chart (0, 15, 25, 50 parts per
million, ppm). The cut-off proportion of 15 PPM and above was considered as adequately iodized
salt using the WHO/UNICEF reference indicators for the monitoring of iodized salt.
Fig 5.5: Level of Iodine content in salt
100%
80%
51.8% 40.8%
55.1%
69.1%
67.6%
63.6%
72.4% 78.8%
60%
84.9%
87.9%
40%
48.2% 59.2% 44.9%
20% 30.9% 27.6% 32.4% 21.2%
36.4%
15.1%
12.1%
0%
Pakistan Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
0 PPM
15 PPM and Above
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
According to the test, the proportion of households using iodized salt in Pakistan was 69.1%. This
was higher in urban areas (72.4%) than in rural areas (67.6%). The provinces with the greatest
proportion of households using iodized salt were AJK (87.9%) and Gilgit Baltistan (84.9%). The
provinces with the lowest rates of usage were Balochistan (40.8%) and Sindh (51.8%).
5 4: Clinical examination During the NNS 2011, clinical examination of mothers was also performed. Trained nurses
conducted this examination. This was a direct assessment of micronutrient deficiencies on the
basis of clinical signs and symptoms. The mothers were examined for anaemia, edema, jaundice,
goitre and bitot’s spots. Each of these conditions represents a micronutrient deficiency. The survey revealed that overall, 26.1% mothers had pallor – 20.5% in urban areas and 28.6% in
rural areas. The prevalence of clinical anaemia (pallor) amongst the provinces were as follows:
28.0% in Punjab, 33.7% in Sindh, 11.0% in KP, 20.2% in Balochistan, 35.9% in AJK and 16.0% in
Gilgit Baltistan. The prevalence of edema was 1.6% with no significant variance among provinces
except for Gilgit Baltistan where it was 4.1%. Bitot’s spot was found in 0.4% of mothers, with no
urban/rural variance. When assessed by province, Balochistan had the highest prevalence of Bitot’s spot (2.8%).
27 | National Nutrition Survey 2011
The prevalence of clinical anaemia found in the NNS 2001 was 48.7%. The NNS 2011 revealed a
reduction to 26.1%. Similar trends were found for edema, jaundice, visible goitre and bitot’s
spot.
Fig 5.6: Clinical examination of mothers (comparison between NNS 2001-02 and NNS 2011)
60%
48.7%
50.0%
50%
46.4%
40%
28.6%
30%
26.1%
20.5%
20%
10.4%
11.8%
10% 0.0%
1.6%
2.9% 5.8% 2.1%
1.8%
1.4% 3.4%
1.4% 1.0% 1.6%
0.0%
0%
NNS 2001
NNS 2011 NNS 2001
NNS 2011
NNS 2001
NNS 2011
Pakistan Urban Rural
Edema
Jaundice
Anemia/pallor
Goiter
Bitot’s spot
5.5: Anthropometry Data were collected from non-pregnant women of reproductive age (15-49 years old), both
married and unmarried, to calculate Body Mass Indices. The BMI were divided into four
categories: underweight had a BMI of <18.5, normal had a BMI of 18.5–24.99, overweight had a
BMI of 25–29.9 and obese had a BMI of >=30. The data showed that 18.0% of women had low BMI and were underweight (14.4% from urban
areas and 19.7% from rural areas) and about 53.1% had normal BMI (46.0% from urban areas
and 56.6% from rural areas). 19.4% of women of reproductive age were overweight and 9.5% of
WRAs were obese (15.7% from urban areas compared to 6.5% from rural areas).
Figure 5.7: Body Mass Index
60% 56.6%
53.1%
50% 46.0%
40%
30% 23.9%
19.7%
20% 18.0% 19.4%
17.2% 15.7%
14.4%
9.5%
10% 6.5%
0%
Underweight (<18.5) Normal (18.5-24.9) Overweight (25-29.9) Obese (>29.9)
Pakistan Urban Rural
28 | National Nutrition Survey 2011
5. 6: Micronutrient deficiency
5.6.1. Urinary iodine excretion of mother
In the NNS 2011, urine samples from mothers were collected to assess their urinary iodine
excretion. Urinary Iodine excretion is the most appropriate indicator of iodine deficiency in large
populations. Adequate iodine nutrition is considered to pertain when the median urinary iodine
concentration is 100–199 μg/l. The median urinary excretion of mothers indicates adequate levels of iodine status at national
level, in both urban and rural area, and in most of the provinces (as indicated in the figure
below). Balochistan, AJK and Gilgit Baltistan showed <100 μg/l urinary excretion, which indicates
that the iodine intake in the population is insufficient.
Fig 5.8: Median urinary iodine excretion in mothers
180
Median UIE 149
160
140
113
120 105
103
96 102
100 90
80 63 64
60
40
20
0
5.6.2: Night blindness among mothers 12.7% of women surveyed had experienced night blindness during their previous pregnancy and
15.6% had experienced night blindness during their current pregnancy. Among provinces of
Pakistan, women in Sindh had the highest reported rates of night blindness during their last
pregnancy (21.3%) followed by AJK, Balochistan, Punjab, KP and Gilgit Baltistan. Among those
women who reported night blindness during their current pregnancy, women in Sindh (22.7%)
had the highest rates followed by AJK, Balochistan, Punjab, KP and Gilgit Baltistan. When comparing this survey with the NNS 2001, night blindness rates during previous
pregnancies had gone up (12.7% in the NNS 2011 compared to 7.8% in the NNS 2001). Similar
trends were seen in urban and rural areas. The night blindness rates during current pregnancies
had also increased (in the NNS 2011 they were 15.6%, while in the NNS 2001 they were 9.9%).
29 | National Nutrition Survey 2011
Fig 5.9: Comparison of night blindness in women 18%
15.6%
16.1%
16%
14.3%
14% 12.7% 13.2%
11.7%
12%
10.0%
9.9%
9.4%
10%
7.8% 7.5%
8.0%
8%
6% 4% 2% 0%
NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011
Pakistan Urban Rural
Last pregnancy
Current pregnancy
5.7: Biochemical analysis Blood specimens were collected to assess the biochemical status of micronutrients. These
specimens were assessed for hemoglobin, ferritin, vitamin A, zinc, calcium and vitamin D levels.
The results are as follows:
5.7.1 Anaemia (haemoglobin levels)
Haemoglobin levels of both pregnant and non-pregnant women were checked during the NNS
2011. 50.4% of non-pregnant women were found to be suffering from anaemia (49.3% in urban
areas and 50.9% in rural areas). Provincial data revealed that 62.0% in Sindh were suffering from
anaemia, followed by Balochistan (48.9%), Punjab (48.6%), AJK (41.0%), KP (35.6%) and Gilgit
Baltistan (23.3%). Similar trends were observed for pregnant women.
Fig 5.10: Maternal anaemia
70%
62.0% 59.7%
60% 51.0% 50.3% 50.5% 49.3%
50.9%
50.4% 49.3%
48.9%49.7%
48.6%
50% 43.0%
41.0%
40% 35.6% 33.6%
30.2%
30% 23.3%
20%
10%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
Non-Pregnant Women
Pregnant Women
When the NNS 2011 data for anaemia in pregnant and non-pregnant mothers was compared
with that of the NNS 2001, it was found that the prevalence of anaemia in non-pregnant women
had worsened in 2011 (28.4% in NNS 2001 compared to 50.4% in the NNS 2011). Similar trends
were observed for pregnant women.
30 | National Nutrition Survey 2011
Fig 5.11: Comparison of anaemia in mothers
60%
Severe deficiency (<7 gm/dL)
Moderate deficiency (7 - 11.9 gm/dL)
48.9%
48.5%
49.1%
50%
40%
28.3%
25.9%
29.6%
30%
20%
10%
1.1% 1.5% 0.7%
0.8%
1.3% 1.8%
0%
NNS 2001 NNS 2011 NNS 2001
NNS 2011 NNS 2001
NNS 2011
Pakistan Urban Rural
5.7.2 Ferritin concentration 26.8% of non-pregnant women had low ferritin levels (26.8% in urban areas and 26.6% in rural
areas). When the data was disaggregated by province, Sindh had the highest proportion of
women with low ferritin levels (31.5%), followed by Punjab, AJK, Balochistan, Gilgit Baltistan and
KP. Among pregnant women, 37.0% had low ferritin levels at national level whereas it was
highest in GB (45.7%) followed by Punjab, Balochistan, Sindh, AJK and KP.
Fig 5.12: Ferritin concentration
Low
Fer
riti
n L
evel
(<1
2 n
g/d
L)
50%
37.0%
38.1% 39.2%
37.1%
45.7%
40%
34.5%
34.1%
31.6%
31.5%
30% 26.8% 26.8% 26.8% 27.3% 27.0%
21.8% 25.2%
20%
15.6%
14.9%
10%
0%
Pakistan
Urban
Rural
Punjab
Sindh
KP
Balochistan
AJK
GB
Non-pregnant
Pregnant
5.7.3. Vitamin A deficiency Retinol levels were tested in women (pregnant and non-pregnant) to determine vitamin A
deficiency. Vitamin A deficiency among all married women was prevalent at 42.5% (35.7% in
urban areas and 45.4% in rural areas). Provincial variance showed vitamin A deficiency at the
following levels in all married women: highest in KP 66.4% followed by Balochistan 54.9%,
Punjab 41.8%, GB 39.1%, and Sindh 37.1%. Among the non-pregnant women, vitamin A
deficiency was prevalent at 42.1% (34.9% in urban areas and 45.1 in rural areas). Provincial
variance showed that VAD remained highest in KP 65.7% followed by 54.5% in Balochistan,
41.5% in Punjab, 38.7% in GB, 35.4% in Sindh and 13.7% in AJK . Among the pregnant women,
vitamin A deficiency was prevalent at 46.0% (41.5% in urban areas and 47.8 in rural areas). 31 | National Nutrition Survey 2011
Provincial variance showed that VAD remained highest in KP 76.2% followed by 60.7 in Balochistan, 46.7% in Sindh, 44.1% in GB, 43.7% in Punjab and 32.2% in AJK.
Fig 5.13: Vitamin A deficiency (pregnant women) 100%
Severe (<0.35 µmol/L)
Moderate (0.35 - 0.70 µmol/L)
80%
60%
40.7%
40% 34.6%
27.3% 25.4% 28.1% 24.1%
31.6%
24.1%
20%
35.5% 26.1%
28.9%
18.7% 16.1% 19.7% 19.6% 15.1%
20.0%
0%
3.3%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
Comparison of Vitamin A Deficiency among all women NNS 2011 vs. NNS 2001: Vitamin A
deficiency levels found in the NNS 2011 had significantly increased over the NNS 2001 levels
(5.9% in 2001 to 42.5% in 2011). Similar trends were seen in urban and rural areas.
Fig 5.14: Comparison of vitamin A deficiencies among non-pregnant women (urban/rural) 30%
25.1%
24.0%
25.5%
25%
17.0%
19.6%
20%
15%
10.9%
10%
5.4%
3.4%
6.7%
5%
0.8%
0.5%
0%
NNS 2001
NNS 2011 NNS 2001
NNS 2011 NNS 2001
NNS 2011
Pakistan Urban Rural
Severe (<0.35 µmol/L)
Moderate (0.35 - 0.70 µmol/L)
5.7.4 Zinc deficiency Serum zinc levels were determined in women. The serum analysis of non-pregnant women
revealed that 41.3% of women were zinc deficient (38.2% in urban areas and 42.7% in rural
areas). Women’s serum zinc levels by province were as follows in 2011: Punjab 40.2%, Sindh
38.5%, KP 48.3%, Balochistan 43.7%, AJK 64.8% and Gilgit Baltistan 63.7%. The data also showed
that 47.6% of pregnant women were zinc deficient across the country. The provincial variance
for pregnant women was as follows: Punjab 47.3%, Sindh 44.5%, KP 52.6%, Balochistan 43.6%,
AJK 95.8% and Gilgit Baltistan 54.4%. It was also noted that there has not been any change in the prevalence of zinc deficiency in the last ten years. The prevalence was 41.9% in the NNS 2001 and 41.3% in the NNS 2011.
32 | National Nutrition Survey 2011
Fig 5.15: Zinc deficiency (pregnant women) 120%
Zinc Deficiency (<60 µg/dL)
100%
80%
60%
95.8%
40%
47.6% 47.4% 47.7% 47.3% 44.5% 52.6%
43.6%
54.8%
20%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
Fig 5.16: Comparison of Zinc deficiency among non-pregnant women (urban/rural) 50%
Zinc Deficiency (<60…
45%
44.9%
40%
41.4%
41.3%
42.7%
35% 36.2%
38.2%
30%
25%
20%
15%
10%
5%
0%
NNS 2001
NNS 2011 NNS 2001
NNS 2011 NNS 2001
NNS 2011
Pakistan Urban Rural
5.7.5 Vitamin D deficiency The NNS 2011 is the first survey in Pakistan assessing Vitamin D deficiency through bio-chemical
data at a large a large scale. Widespread deficiency was found among non-pregnant women –
66.8% were vitamin D deficient (72.5% in urban areas and 64.3% in rural areas). On a provincial
level, the prevalence of vitamin D deficiency among non-pregnant women in Punjab was 66.4%,
in Sindh 71.2%, in KP 61.0%, in Balochistan 54.6%, in AJK 73.3% and in Gilgit Baltistan 80.9%. The prevalence of vitamin D deficiency was also tested in pregnant women. 68.9% were
determined vitamin D deficient (73.5% in urban areas and 67.2%in rural areas). Provincial data
revealed vitamin D deficiency among pregnant women in Punjab was 71.1%, in Sindh 66.9%, in
KP 63.8%, in Balochistan 43.6%, in AJK 73.4% and in Gilgit Baltistan 76.1%. 33 | National Nutrition Survey 2011
Fig 5.17: Vitamin-D deficiency (pregnant women) 120%
100%
Severe deficiency (<8.0 ng/mL)
Deficiency (8.0 - 20.0 ng/mL)
Desirable (>20.0 - 30.0 ng/mL)
21.1% 80%
60%
40%
20%
17.6% 15.3%
18.4%
43.6% 39.7%
45.1%
33.8%
17.6% 42.9%
16.1% 23.3%
46.1% 45.9%
11.2%
26.7% 31.7%
51.9%
23.1%
44.4%
0%
25.3% 22.1% 28.2%
20.8% 17.9% 20.5% 21.5%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
5.7.5 Calcium Status: The NNS 2011 calculated calcium levels for the first time on such a large population of women
(non-pregnant and pregnant). The calculated calcium levels were not adjusted for serum
albumin. The data revealed that 52.1% of non-pregnant women had hypocalcaemia. Provincial
data also showed that 51.7% of non-pregnant women had hypocalcaemia in Punjab, 44.6% in
Sindh, 74.0% in KP, 63.1% in Balochistan, 8.2% in AJK and 44.5% in GB. Data on pregnant women showed that 58.9% had hypocalcaemia. The levels of calcium in
pregnant women at the provincial level showed that 63.2% of pregnant women in Punjab, 50.3%
in Sindh, 67.6% in KP, 67.4% in Balochistan, 13.3% in AJK and 71.3% in GB had hypocalcaemia.
Fig 5.18: Calcium deficiency (pregnant women)
100%
7.6% 7.7%
7.6%
8.3% 8.1% 2.9% 2.2% 0.5%
80% 29.4% 30.4% 28.7%
33.5% 30.8%
34.6% 28.5% 41.6%
60%
86.2%
40%
58.9% 61.5%
63.2%
67.6% 67.4%
71.3%
57.9%
50.3%
20%
13.3%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
Hypo Calcaemia (<8.4 mg/dL)
Normo Calcaemia (8.4 - 10.2 mg/dL)
Hyper Calcaemia (>10.2 mg/dL)
34 | National Nutrition Survey 2011
Chapter 6: Child Health and Nutrition
6.1: Nutrition status of children
6.1.1 Children 0 – 59 months The percentage of households with children aged 0–59 months was measured in the NNS 2011.
25.6% of households in Pakistan did not have a child in the home that was under 5 while 40.1%
had only one child less than 5 years of age. The average number of children living in each
household is listed by province and region in the following figure.
Fig 6.1: Households with children under 5 years of age
100%
No children
1 child
2 children
3 children
4 or more children
23.4
18.1
80%
23.1
26.2 27.6 26.9
25.7
27.9
36.7
34.5
60%
40.1 37.1
36.0
38.0 46.4
40% 41.5
78.2
46.3
54.6 47.7
20%
25.6 32.5
22.4 27.5
28.0 27.5
14.7
3.8
0% 0.8 0.2
Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
6.1.2 Anthropometry (children under 5 years of age)
Anthropometric measurement of all children <5 who were present at household at the time of
visit was undertaken. Results showed that in Pakistan 43.7% of children were stunted. In rural
areas stunting in children was higher (46.3 %) than in urban areas (36.9%). The wasting rate was
15.1% and the proportion of wasted children was lower in urban areas (12.7%) than in rural
areas (16.1%). About 31.5% of the children were underweight, with higher rates in rural areas
(33.3%). The indicators of malnutrition appeared to be worse in rural areas than in urban areas
across country.
Fig 6.2: Prevalence of malnutrition in Pakistan (children under 5 years of age)
50% 43.7%
Stunted
Wasted
Underweight 46.3%
40%
31.5% 36.9%
33.3%
30% 26.6%
20%
15.1%
12.7% 16.1%
10%
0%
Pakistan Urban Rural
35 | National Nutrition Survey 2011
6.1.3 Stunting (children under 5 years of age) Severe stunting in children showed an alarming situation (21.9%) across Pakistan. It was higher
in rural areas (24.0 %) than in urban areas (16.4%).
Fig 6.3: National stunting rates for children under 5 years of age
50%
Severe Stunting
Moderate Stunting
45%
40%
35% 21.8%
22.3%
30%
20.5%
25%
20%
15%
21.9%
24.0%
10%
16.4%
5%
0%
Pakistan Urban Rural
6.1.4 Wasting (children under 5 years of age) Overall wasting rates were 5.8% for severe wasting and 9.3% for moderate wasting. The
proportion of wasted children was higher in rural areas than in urban areas. In urban areas 4.7%
of children under 5 years of age suffered from severe wasting while 8.0% were affected by
moderate wasting. In rural areas severe wasting reached 6.3% and moderate wasting was 9.8%.
Fig 6.4: National wasting rates (children under 5 years of age)
18% Severe wasting
Moderate Wasting
16%
14%
12%
9.3%
9.8%
10%
8.0%
8%
6%
4%
5.8%
4.7%
6.3%
2%
0%
Pakistan Urban Rural
6.1.5 Underweight (children under 5 years of age) Across Pakistan, 11.6% of children were severely underweight while 19.9% were moderately underweight. No significant difference was found between rural and urban areas. 36 | National Nutrition Survey 2011
Fig 6.5: Underweight (children under 5 years of age) national 35%
Severely underweight
Moderately underweight
30%
25%
19.9%
20.5%
20%
18.2%
15%
10%
11.6%
12.8%
5%
8.4%
0%
Pakistan Urban Rural
6.1.6: Education of mothers and its association with nutritional status of children It is evident that the employment status and education level of a mother is directly associated
with the nutritional status of her children. The findings of the NNS 2011 revealed that a mother’s
education level is closely associated with children’s stunting, wasting and underweight status.
Malnutrition in children was lower for those whose mothers had a higher education status.
Fig 6.6: Education of mothers and its association with nutritional status of children
30% 27%
25%
20% 19%
17%
15%
15%
12%
10% 8%
10% 8% 9%
6%
6%
5% 5% 7% 5%
4%
0%
Illiterate 1-5 years 6-8 years 9-10 years Above Matric.
% Stunted % Wasted % Underweight
6.1.7 Malnutrition trends in children under 5 years of age – comparison of SAARC countries
Of the South Asia Association of Regional Cooperation (SAARC) countries, Pakistan has the
second highest stunting rate (43.7%). It follows Afghanistan, a country that faces extreme social,
political and economic complexities. Nepal and India have similar stunting rates (43%). Bhutan
has considerably better nutrition indicators than Pakistan. 37 | National Nutrition Survey 2011
Fig 6.7: SAARC countries national stunting trends* 60%
54%
50%
37% 36% 43%
43%
44%
40%
25%
30%
20%
14%
10%
0%
Afg
hani
sta
n-N
S 20
04
Bh
uta
n-
NS
2009
Ban
glad
esh
- D
HS
2007
Indi
a-N
FHS
2005
-200
6
Mal
div
es-M
ICS
2001
Nep
al-
DH
S200
6
Sri L
anka
-DH
S 20
00
Paki
stan
-NN
S 20
11
* These data are based on different standards and references i.e. NCHS reference for earlier assessments & WHO standards for more recent.
Pakistan and Sri Lanka have the third highest wasting rates in the region and Afghanistan has better rates than both. Fig 6.8 SAARC countries national wasting trends*
25%
20%
20%
17%
15% 15%
15%
9%
13% 13%
10%
5%
5%
0%
Afgh
anis
tan-
NS20
04
Bhut
an-
NS20
09
Ban
glad
esh-
DHS
2007
In
dia-
NFHS
200
5-20
06
Mal
div
es-
MIC
S20
01
Ne pal
- DH S20
06
Sri
La nk a- DH S2 00 0 Pa kist
an-
NN S2 01 1
* These data are based on different standards and references i.e. NCHS reference for earlier assessments and WHO standards for more recent. Pakistan had lower rates of underweight children than half of the other SAARC countries. Fig 6.9: SAARC Countries national underweight trends*
60%
46% 48%
45%
50%
39%
40%
32%
30%
29%
30%
20%
11%
10%
0%
Afg
ha
nis
tan
-NS
20
04
Bh
uta
n-
NS
2009
Bang
lade
sh-
DHS2
007
Indi
a-NF
HS
2005
-200
6
Ma
ldiv
es-M
ICS
200
1
Nep
al-
DH
S200
6
Sri L
an
ka-D
HS
200
0
Pa
kist
an
-NN
S 2
01
1
* These data are based on different standards and references i.e. NCHS reference for earlier assessments and WHO standards for more recent. 38 | National Nutrition Survey 2011
6.2: Biochemical assessment
Biochemical assessments are one of the established methods used to study the micronutrient
status of a given population. Biochemical assessments are much more accurate and precise than
most other forms of testing because many micronutrient deficiencies do not produce signs or
symptoms until they are quite severe. For this reason, mild micronutrient deficiencies can only
be diagnosed using biochemical indicators. Commonly used biochemical assessments include the
haemoglobin estimation for anaemia, serum retinol levels for vitamin A deficiency, serum zinc
levels for zinc deficiency, and urinary iodine levels for urinary iodine excretion.
6.2.1 Anaemia At the national level, 61.9% of children were found to be anaemic (Hb level <11.00gm/dL)
(severe deficiency 5.0% and moderate deficiency 56.9%). Regional differences in the prevalence
of anaemia were substantial, ranging from 41.0% in Gilgit Baltistan to 72.5% in Sindh. Prevalence
of severe anaemia was comparatively higher in rural areas (5.5%) than in urban (3.6%). Fig 6.10: Anaemia in children under 5 years of age
80% 72.5%
70% 61.9% 62.9% 61.4% 60.3% 56.8%
60%
50% 47.3% 46.0%
41.0%
40%
30%
20%
10%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
Children under 5 years of age with anaemia
Fig 6.11: Trends of prevalence of anaemia in children under 5 years of age 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0%
0.0%
56.9%
59.3% 55.9%
49.1% 53.2%
49.2%
47.3%
44.4% 46.5%
38.1% 37.0% 38.6%
3.6% 5.0% 2.4% 3.6% 4.3% 5.5%
NNS 2001 NNS 2011 NNS 2001 NNS 2011 NNS 2001 NNS 2011
Pakistan Urban Rural
Severe deficiency (<7 gm/mL) Moderate deficiency (7 - 11.99 gm/mL)
Normal (>= 12 gm/mL)
39 | National Nutrition Survey 2011
6.2.2 Iron deficiency (low ferritin concentration) High levels of iron deficiency (low ferritin concentration) were observed in 43.8% of children
across Pakistan. Provincial differences in prevalence of low ferritin levels varied ranging from
26.4% in KP to 48.6% in Punjab. Comparatively high prevalence was noted in urban areas (46.1%)
as compared to rural areas (42.9%).
Figure 6.12: Iron deficiency among children
60% Iron deficiency among children
50% 46.1%
48.6%
43.8%
43.5%
42.9%
40.6%
40% 32.5%
36.2%
30%
26.4%
20%
10%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
6.2.3 Vitamin A deficiency in children (under 5 years) During the NNS 2011, vitamin A deficiency was assessed among children. The data showed that
overall 54.0% of children in Pakistan were vitamin A deficient. 20.9% were severely deficient and
33.1% were moderately deficient.
Fig 6.13: Vitamin A deficiency
80%
Severe (<0.35 µmol/L)
Moderate (0.35 - 0.70 µmol/L)
70%
60%
34.6% 35.5%
50%
44.6%
40%
33.1%
33.4% 31.9% 34.5%
32.3%
30%
36.7%
20%
33.9% 38.0%
27.2%
10%
20.9% 23.5%
19.1% 18.8%
14.6%
7.1%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
40 | National Nutrition Survey 2011
Fig 6.14: Trend of vitamin A deficiency in children under 5 years 40%
Severe (<0.35 µmol/L)
33.1%
33.4%
35%
32.3%
30%
Moderate(0.35 - 0.70 µmol/L)
23.5%
25%
20.9%
20%
14.6%
15%
12.6%
11.7% 10.3%
10%
5%
0.8% 0.6%
0.9%
0%
Pakistan Urban
Rural Pakistan Urban Rural
NNS 2001 NNS 2011
6.2.4 Zinc deficiency The survey revealed that overall prevalence of zinc deficiency among children in Pakistan was
39.2% (39.3% urban and 39.1% rural). Provincial data showed zinc deficiency at 38.4% in Punjab,
38.6% in Sindh, 45.4% in KP, 39.5% in Balochistan, 47.2% in AJK and 32.6% in Gilgit Baltistan.
Fig 6.15: Zinc deficiency in children (0–5 years)
50% Zinc Deficiency (<60 µg/dL)
45%
40%
35%
30%
25%
45.4%
47.2%
20%
39.2% 39.3% 39.1% 38.4% 38.6%
39.5%
32.6%
15%
10%
5%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
When zinc deficiency data from the NNS 2011 was compared with that of NNS 2001, there was a
slight change in the proportion of zinc deficient children as measured by serum zinc
concentrations.
41 | National Nutrition Survey 2011
Fig 6.16: Comparison of zinc deficiency in children under 5 years of age
80%
Deficient (<60 µg/dL)
Non-Deficient (>=60 µg/dL)
67.8%
70%
62.9%
59.8% 60.8% 60.7% 60.9%
60%
50%
37.1%
40.2% 39.2% 39.3% 39.1%
40%
32.2%
30%
20%
10%
0%
Pakistan
Urban Rural
Pakistan Urban Rural
NNS 2001 NNS 2011
6.2.5 Vitamin D deficiency The prevalence of vitamin D deficiency among children at national level was 40.0%. A high
prevalence of vitamin D deficiency (45.9%) was noted in urban areas. Substantial variations were
noted at the provincial level, ranging from 28.9% in KP to 43.4% in Balochistan.
Fig 6.17: Vitamin D Deficiency
80%
Severe Deficiency (<8.0 ng/mL)
Deficiency (8.0 - 20.0 ng/mL)
Desirable (>20.0 - 30.0 ng/mL)
70%
60%
27.3% 22.2% 29.4% 27.2% 25.4%
23.6% 35.3% 36.0%
50%
31.4%
40%
30%
30.8% 31.9%
30.4% 31.0% 32.6%
34.3%
20%
32.9%
30.5%
23.0%
10%
9.2% 14.0% 7.2%
9.3% 10.7% 5.9%
9.1%
0%
4.1% 4.1%
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
6.2.6 Urinary iodine excretion in children 6-12 years The main indicator of iodine status in the population is measured by median urinary iodine
concentration in a population of children aged 6–12 years. Adequate iodine nutrition is
considered to pertain when the median urinary iodine concentration is 100–199 μg/l. Generally,
the median urinary excretion of children aged between 6-12 years found in the 2011 survey
indicated adequate levels of iodine status at national level, both urban and rural, and in all of the
provinces except AJK and GB.
42 | National Nutrition Survey 2011
Fig 6.18: Median urinary iodine excretion in children 6-12 years 180
Median UIE
160
160
136 146
140 126 134
119
117
120
100
80
64 62
60
40
20
0
Pakistan Urban Rural Punjab Sindh KP Balochistan AJK GB
6.2.7 Clinical examination of children under 5 years of age During the NNS 2011, trained nurses performed clinical examinations of children. The children
were examined for anaemia, edema, jaundice, goitre and bitot’s spot. The survey revealed that
overall 22.8% of the children had pallor. Provincial variations were found in the prevalence of
clinical anaemia ranging from 31.7% in AJK to 3.4% in KP. The prevalence of edema was 0.4%
with no significant variance between provinces except for Gilgit Baltistan, where not a single
case was found. Bitot’s spot was present in 0.2% of the children.
6. 3: Child morbidity Apart from neonatal disorders, diarrhoea and pneumonia are the other major causes of death in
children under 5 years of age worldwide. In the NNS 2011, mothers of children under 5 were
asked if the children had symptoms associated with acute respiratory illness (cough/flu,
pneumonia, severe pneumonia and diarrhoea) on the day of the interview or two weeks
preceding the survey.
Fig 6.19: Current ARI status
30%
Severe Pneumonia
Pneumonia
Cough/Flu
25%
20%
18.0%
15% 16.0%
15.0%
15.0%
12.0%
11.0%
10%
5%
5.0% 6.0%
5.0%
5.0% 5.0% 5.0%
0% 1.0% 2.0% 1.0% 1.0% 1.0% 1.0%
Pakistan
Urban Rural
Pakistan
Urban
Rural
By Information By Observation
43 | National Nutrition Survey 2011
6.3.1 Prevalence of acute respiratory infections ARI is a common cause of morbidity and death among children under 5 years of age. Pneumonia
is characterized by difficult or rapid breathing. Severe pneumonia is defined as difficult or rapid
breathing and chest in-drawing. According to mothers of children, 4.9% of children had pneumonia on the day of the interview.
However upon observation by the community nurse, 5.4% children had signs consistent with
pneumonia. The survey findings revealed that either by observation or reported by mother, the
ARI (cough/flu, pneumonia and severe pneumonia) were more prevalent in urban areas than in
rural areas across Pakistan. Severe pneumonia symptoms were reported in 1.4% of children and
the observed proportion was 1.0%.
6.3.2 Prevalence of diarrhoea Diarrhoea is also a major cause of mortality among children. Childhood diarrhoea has been a
serious health problem in Pakistan. Both its prevention, through improved water and sanitation,
and management through oral rehydration salts (ORS) and zinc are on the top of the
government’s priority list. The prevalence of diarrhoea was determined using the WHO
definition. The mother was asked to report whether her child had diarrhoea on the day of the
interview or two weeks preceding the survey.
Fig 6.20: Reported Prevalence of diarrhoea
Diarrhoea (last 2 weeks)
Current diarrhoea
30% 28.5%
26.2% 28.5%
25% 22.3% 23.2% 22.0%
23.4%
20% 19.2%
15.6%
15% 12.0% 11.6% 12.1%
11.7% 12.9%
11.2%
10% 8.0%
6.4%
5% 4.3%
2.6%
2.4%
0%
Pakistan
Urban
Rural
Punjab
Sindh
KP
Balochistan FATA*
AJK
GB
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution. Approximately 12.0% of children were reported to be suffering from diarrhoea at the time of the
visit and 22.3% had diarrhoea during the previous two weeks. The prevalence of diarrhoea
(current and over the previous two weeks) was similar between urban and rural areas. Current diarrhoea prevalence was highest in Gilgit Baltistan (19.2%) and Punjab (15.6%).
Similarly, prevalence of diarrhoea during previous weeks was highest in Punjab (28.5%), Gilgit
Baltistan (28.5%), AJK (26.2%) and Sindh (23.4%). 44 | National Nutrition Survey 2011
Chapter 7: Infant and Young Child Feeding Practices
Infant and young child feeding (IYCF) practices directly affect the nutritional status of children
under two years of age and impact overall child survival. Improving infant and young child
feeding practices in Pakistan for children 0–23 months of age is critical to guaranteeing them
better nutrition, health and development. In the NNS 2011, the mothers of the children <24
months of age were queried on exclusive breastfeeding (no intake other than breast milk,
including water). The reported frequencies at the national level were 20.9% at 4 months of age
and 12.9% at 6 months of age respectively. The corresponding predominant breastfeeding data
from 24 hours recall of mothers with children under 6 months of age reflected 69.8% and 63.5%
at 4 months and 6 months across Pakistan respectively.
Fig 7.1: Exclusive breastfeeding of children 0-23 months (reported by mothers)
100%
90%
80%
70%
55.5%
60%
52.0%
47.0%
50%
42.0% 42.0%
40%
23.5%
26.8%
25.7%
30%
20.9% 22.1% 20.4%
14.5%
20% 12.9% 12.7% 13.0% 12.9% 9.6%
7.5%
7.7%
10%
4.3%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Upto 4 months
Upto 6 months
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Fig 7.2: Predominant breastfeeding of children 0-6 months (24 Hours dietary recall)
100% 89.4%
90% 87.1%
79.2% 80%
72.4% 75.4% 72.2%
69.8%
63.0% 67.3%
64.3% 66.4%
63.3% 64.7%
70% 63.5% 62.1%
57.5% 56.9% 61.7%
60%
48.3%
50%
40% 35.6%
30%
20%
10%
0%
Upto 6 months upto 4 months
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution. 45 | National Nutrition Survey 2011
Predominant breastfeeding practices were assessed using the past 24 hour dietary recall of 0-6
months old children. The data showed that 69.8% of mothers were predominantly breastfeeding
their children who were under 4 months and 63.5% under 6 months. Predominant Breastfeeding
practices were higher in rural areas (66.4%) than in urban areas (57.5%).
Fig 7.3: Initiation of breastfeeding within one hour of birth
100%
90%
74.3% 79.5%
80%
63.4%
70%
61.8%
60%
50.5%
50%
40.5% 38.4% 41.4%
38.3%
40%
28.1%
30%
20%
10%
0%
Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Within 1 hour
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution. NNS 2011 data revealed that 40.5% of mothers had initiated breastfeeding within one hour of
birth. The percentage was greater in rural areas (41.4%) than in urban areas (38.4%). The early
initiation of breastfeeding was highest in KP 74.3% followed by Balochistan 63.4% and Gilgit
Baltistan 61.8%. Trends observed in Punjab (28.1%), Sindh (50.5 %) and AJK (38.3 %) differed.
Fig 7.4: Continued breastfeeding practices
100%
87.4%
91.9%
90% 84.4%
77.3%
79.6%
74.5%
80%
73.3%
72.3%
72.3%
70%
60%
50% 43.4%
40%
30%
20%
10%
0%
Continued Breast Feeding practices * Data from FATA are not representative due to high non-response rate and must be interpreted with caution. 46 | National Nutrition Survey 2011
The data showed that in Pakistan 77.3% mothers continued breastfeeding to children up to 12-
15 months. Continued breastfeeding practices were higher in rural areas (79.6%) than in urban
areas (72.3%). Provincial and regional differences in the rates of continued breastfeeding
practices were substantial, ranging from 72.3 % in the Balochistan to 91.9% in the Gilgit
Baltistan.
Fig 7.5: Introduction of Semi-Solid (6-8 months)
100%
90%
80%
68.4%
70%
62.6%
60% 51.3%
49.2%
55.0%
51.3%
48.6%
50%
44.7%
35.3%
35.7%
40%
30%
20%
10%
0%
PakistanUrban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Introduction of Semi-Solid (6-8 months)
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution. More than half (51.3%) of the mothers interviewed across Pakistan reported they had started
giving semisolid foods to their children at 6–8 months. The proportion was higher (68.4%) in
urban areas than in rural areas (44.7%). KP (35.3%) and AJK (35.7%) had lower trends than other
provinces.
Fig 7.6: Minimum dietary diversity (6-23 months)
30%
24.0%
25%
20%
15%
10%
5.6%
6.9%
3.2% 5.1%
5%
3.0% 1.9% 2.6% 2.7% 2.1%
0%
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
47 | National Nutrition Survey 2011
Minimum dietary diversity is estimated as the proportion of children 6–23.9 months of age who received foods of 4 or more food groups out of a total number of 7 food groups defined. The NNS 2011 findings revealed that only 3.0% of the children received a diet that meets the minimum standards of dietary diversity. Children in urban areas were more likely to receive a minimum dietary diversity than those in rural areas (5.6% compared to 1.9%). AJK (6.9%) ranked highest in minimum dietary diversity amongst the provinces.
Fig 7.7: Minimum meal frequency (6-23 months)
100%
90% Minimum Meal Frequency (6-23 months)
80%
65.4%
69.0%
70%
59.4%
60.7%
56.4%
54.1%
60%
53.3%
52.4%
50% 45.0%
40%
30.4%
30%
20%
10%
0%
Pakistan Urban
Rural
Punjab
Sindh
KP Balochistan FATA*
AJK
GB
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Minimal meal frequency is estimated as the minimum number of times solid, semi-solid or soft
foods (including milk for children who are not breastfed) are given to breastfed and non-
breastfed children who are 6-23.9 months of age. “Minimum is defined as 2 times for breastfed
infants 6-8.9 months, 3 times for breastfed children 9-23.9 months and 4 times for non-
breastfed children 6-23.9 months.4” Overall, 56.4% of mothers provided food to their children at
an acceptable meal frequency. The minimum meal frequency practice was higher in urban areas
(65.4%) than in rural areas (52.4%). About half of all mothers practiced minimal meal frequency
in all provinces.
Fig 7.8: Minimum acceptable diet (6-23 months)
40% 36.6%
35%
30%
25%
20%
15.1%
15%
11.2%
7.6%
10% 7.3% 5.6% 5.8% 5.6% 5.1%
3.9%
5%
0%
Pakistan Urban
Rural
Punjab
Sindh
KP Balochistan FATA*
AJK
GB
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
4 Indicators for assessing infant and young child feeding practices: conclusions of a consensus meeting held 6–
8 November 2007 in Washingtonm D.C., for acceptable diet of young child indicators 48 | National Nutrition Survey 2011
A minimum acceptable diet is a composite indicator of the adequacy of complementary feeding
practices. It is the proportion of children 6–23 months of age who received a minimum
acceptable diet (apart from breast milk). Across Pakistan only 7.3% of children received a
minimum acceptable diet. Similar trends were observed in all provinces except AJK.
Fig 7.9: Age appropriate breastfeeding (0-23 months)
80%
72.4%
75.3%
70%
63.6% 62.7% 64.0% 60.5%
63.5% 65.9%
60% 54.3%
50%
40.0%
40%
30%
20%
10%
0%
Pakistan
Urban
Rural
Punjab
Sindh
KP
Balochistan FATA*
AJK
GB
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Age-appropriate breastfeeding was defined as the proportion of children 0–23 months of age
who were appropriately breastfed. The proportion of age-appropriately breastfed children was
63.6% in Pakistan. Similar trends were recorded both in urban and rural areas. All provinces
showed similar trends with the highest being in Gilgit Baltistan (75.3%). 49 | National Nutrition Survey 2011
Chapter 8: Food Intake and Practices
8.1: Methodologies adopted for Food Intake and Practices
Diet is usually described in terms of its nutrient content however the use of specific foods groups can also
describe diet. Three of the most common methods used for assessing dietary intake; are food frequency
questionnaires, food records and 24-hours dietary recalls. In the NNS 2011, Food Frequency Question-
naire was used to assess the past dietary intake and 24-hour Dietary Recall for the current dietary intake.
8.1.1: Methodology for 24 Hour Recall
An open ended semi quantitative 24-hours dietary recall questionnaire was used to estimate the
consumption of various food groups intake. The respondent (mother herself and for her child 0 – 23 months) was asked to report all of the food, beverages and/or supplements that she and her child has
consumed during the past 24 hours.
The interview was structured with specific probes to help the mother remember all of the foods eaten.
Probing was done in collecting details on different foods and also for in recovering foods that are forgot-
ten (e.g., butter on toast) or in retrieving eating occasions not originally reported by the mother such as
snacks or tea breaks.
Standard utensils (Cup, plates, spoons, glass, etc.) were given to the specially trained Data Collectors to
measure the actual quantity eaten on 7 points in time during the past 24-hours (after wakeup, breakfast,
in-between breakfast and lunch, lunch, in-between lunch and dinner, dinner and after dinner before go
to bed).
8.1.2: Methodology for Food Frequency Questionnaire
The food frequency questionnaire was administered to ascertain the information on the fre-
quency of food consumption and nutrients. The purpose of this questionnaire was to know the
frequency of food items usually consumed. The respondent (mother herself and for her child 0 – 23
months) was asked to report listed food items in the table. Food frequency per day, per week and
per month was estimated.
8.2: Pattern of Food Consumption among Children 0 – 23 month
The data of food consumption were analyzed on the basis of 24-hours dietary recall. Data showed that
the pattern of food consumption in 0–23 months by different food groups in Pakistan was: breast milk
80.9%, followed by grains, roots and tubers 58.2% and dairy products (milk, yogurt, cheese, etc.) 48.2%.
Breast milk feeding was higher (82.6%) in rural and lower (77.0%) in urban areas however the consump-
tion of other food groups (grains, roots and tubers, legumes and nuts, dairy products (milk, yogurt,
cheese), flesh foods (meat, fish, poultry and liver/organ meats), eggs, vitamin -A rich fruits and vegetables
& other fruits and vegetables was higher in urban and lower in rural areas. In provincial and regional
comparison breastfeeding was highest (92.2%) in Gilgit Baltistan and lowest (73.9%) in Balochistan.
Grains, roots and tubers were consumed at the lowest in KP (41.7%) and highest (58.2) in AJK while dairy
products were also lowest (41.7%) in KP and but highest (65.1) in Sindh. Details are given in the following
table:
50 | National Nutrition Survey 2011
Table 8.1: Proportion of children below 2 years consumed food items of the listed food groups (based on 24 hour recall)
Food Groups Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit
Breast milk 80.9 77.0 82.6 77.6 86.9 90.1 73.9 46.8 79.6 92.2
Grains, roots and tubers 58.2 63.6 55.7 57.6 65.1 41.7 59.6 86.8 59.5 52.4
Legumes and nuts 5.3 7.1 4.5 4.2 7.5 5.4 6.2 6.2 6.5 5.2
Dairy Products(milk, yogurt, 48.2
51.9 46.5 57.7 38.2 22.2 32.6 62.7 58.2 42.1
cheese)
Flesh foods (meat, fish, poul-
2.7
3.4
2.4
2.3
2.3
1.7
5.1
30.1
5.6
3.1
try and liver/organ meats)
Eggs 5.8 10.0 3.9 4.8 5.1 11.8 3.4 13.8 9.6 15.1
Vitamin -A rich fruits and
1.7
1.9
1.5
1.9
0.9
1.0
1.3
11.3
2.4
7.6
Vegetables
Other fruits and Vegetables 9.4 13.3 7.6 8.5 8.3 11.2 11.4 32.3 20.0 8.4
N 9083 3665 5418 4457 2179 842 697 65 548 295
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
8.3: Frequency of Daily Intake of Food Groups (Children 0 – 23 months)
The data showed that average daily intake of breast milk by children 0 – 23 months in Pakistan was 7.37
times on an average (Urban 7.01 - Rural 7.53) while it was the highest (10) in Sindh and the lowest (5.94)
in Gilgit-Baltistan. All over Pakistan, the average daily intake of dairy products (milk, yogurt, and cheese)
was 1.49 times per day and grains, roots and tubers 1.27 while the lowest intake (0.03) was of both food
groups of legumes and nuts and vitamin -A rich fruits and vegetables.
Table 8.2: Frequency of Daily Intake of Food Groups (Children 0 – 23 months) Food Groups Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit
Breast Milk 7.37 7.01 7.53 6.26 10.00 8.25 6.59 3.45 6.19 5.94
Grains, roots and tubers 1.27 1.38 1.21 1.24 1.49 0.78 1.33 1.45 1.43 1.14
Legumes and nuts 0.03 0.03 0.03 0.02 0.05 0.04 0.04 0.04 0.05 0.02
Dairy Products (milk, yo- 1.49 1.70 1.39 1.90 1.03 0.58 0.90 0.76 1.86 0.86
gurt, cheese)
Flesh foods (meat, fish,
poultry and liver/organ 0.06 0.11 0.04 0.05 0.09 0.02 0.18 0.06 0.06 0.06
meats)
Eggs 0.11 0.19 0.08 0.10 0.10 0.16 0.13 0.27 0.12 0.20
Vitamin A rich fruits and
0.03
0.03
0.03
0.02
0.04
0.02
0.03
0.16
0.04
0.13
vegetables
Other fruits and vegetables 0.28 0.40 0.23 0.28 0.29 0.22 0.21 0.50 0.45 0.16
N 9019 3647 5372 4441 2168 841 680 55 548 286
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
8.4: Frequency of Daily Intake of Food Groups among Children by their Age Group
In Pakistan, average daily intake of different foods showed the logical trends in different age groups
among children of 0 – 23 months i.e. the higher the age group lowers the feeding of breast milk. The av-
erage intake of breast milk was 10.4 times on an average in children <6 months, 8.31 times in children 6 –
11 months and 5.11 times in children 12 – 23 months while on the other hand average of semi-solid
foods was lower in children <6 month and gradually increase in higher age i.e. 6-11 and 12-23 moths.
51 | National Nutrition Survey 2011
Table 8.3: Frequency of Daily Intake of Food Groups among Children by their Age Group Average Daily Intake by Age Group (Children) < 6 months 6-11 months 12-23 months
Breast Milk 10.39 8.31 5.10 Grains, roots and tubers 0.11 1.02 2.06 Legumes and nuts 0.01 0.05 0.03 Dairy Products (milk, yogurt, cheese) 0.95 1.41 1.84 Flesh foods (meat, fish, poultry and liver/organ meats) 0.00 0.03 0.11 Eggs 0.01 0.08 0.20 Vitamin A rich fruits and vegetables 0.00 0.01 0.06 Other fruits and vegetables 0.02 0.18 0.49 N 2150 2804 4065
8.5: Pattern of Food Consumption among Mothers of Children below 2 Years of Age
Across the country irrespective of provinces and regions all mothers eat wheat and rice (>99%) however
foods also eaten along with wheat and rice were tuber and roots (29.2%), legumes and nuts 29.8%), dairy
products (milk, yogurt, cheese) 41.6%, flesh foods (meat, fish, poultry and liver/organ meats) 30.6%, eggs
(10.4%), vitamin -A rich fruits and vegetables (13.5%) and other fruits and vegetables (51.4%).
Table 8.4: Proportion of mothers of children below 2 years who consumed food items of the listed food groups (based on 24 hour recall) Food Groups Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit
Grains
99.5
99.6
99.4
99.6
99.9
99.5
99.9
94.4
99.8
99.6
(Wheat/Rice)
Tuber & Roots 29.2 25.7 30.7 26.8 41.5 21.5 31.1 12.1 27 11.9
Legumes and nuts 29.8 34.9 27.7 32.1 27 27.5 32.4 25.8 37.5 23.2
Dairy Prod-
ucts(milk, yogurt, 41.6 39.2 42.7 50.3 40.2 24.2 28.5 48.8 32.8 37.4
cheese)
Flesh foods (meat,
fish, poultry and 30.6 39.4 26.8 28.7 28 33.2 39.6 47.8 31.4 16.5
liver/organ meats)
Eggs 10.4 16.3 7.8 9.5 7.2 17.4 8 13.1 10.6 10.4
Vitamin -A rich
fruits and Vegeta- 13.5 14.5 13.1 12.9 10.2 16.9 13.8 21.6 15.9 52.8
bles
Other fruits and 51.4
52.8 50.7 59.3 37.3 51.3
49.9 46.7
60.8 52.4
Vegetables
N 19808 7816 11992 8005 5028 3042 1608 891 823 411
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
8.5 Frequency of Daily Intake of Food Groups among Mothers of Children below 2 Years of Age
The average daily intake of grains, tuber and roots by mothers of children all over Pakistan was 3.15 times
followed by dairy products (milk, yogurt, cheese, etc.) 1.05 times. On an average, other fruits and vegeta-
bles apart from vitamin A rich were eaten by 0.85 time in a day.
52 | National Nutrition Survey 2011
Table 8.5: Average Frequency of daily intake of food groups (mothers of children) Food Groups Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK Gilgit
Grains, roots and
3.15
3.08
3.18
3.15
3.04
3.35
2.91
3.07
3.46
3.72
tubers
Legumes and nuts 0.03 0.05 0.02 0.03 0.01 0.05 0.02 0.06 0.03 0.03
Dairy Prod-
ucts(milk, yogurt, 1.05 0.98 1.08 1.04 0.79 1.47 0.84 1.81 0.43 0.51
cheese)
Flesh foods (meat,
fish, poultry and 0.31 0.4 0.27 0.28 0.33 0.29 0.5 0.40 0.31 0.36
liver/organ meats)
Eggs 0.32 0.4 0.29 0.29 0.2 0.58 0.26 0.58 0.22 0.26
Vitamin A rich
fruits and vegeta- 0.29 0.24 0.31 0.2 0.27 0.5 0.31 0.52 0.18 0.9
bles
Other fruits and
0.85
0.97 0.8
0.92 0.71
0.87 0.75
0.98 1.02
1.09
vegetables
N 19575 7805 11770 7995 5014 2940 1623 771 821 411
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
53 | National Nutrition Survey 2011
Chapter 9: Elderly Persons Health and Nutritional Status
Studies suggest that people's perceptions of their own health generally give a good indication of
their mental and physical condition and are predictors of mortality for those who are 50 years of
age and above. There are a number of factors that are known to have an impact on the general
health of the population. These factors can contribute to an increased risk of diseases such as
cardiovascular disease and cancer. Some of the contributing factors include cigarette smoking;
excessive alcohol, excessive fat consumption; high blood pressure, high cholesterol levels,
limited exercise and being overweight. In the NNS 2011, elderly persons were interviewed to
determine their health and nutritional status. In all, 7,612 elderly persons were interviewed at
their residence.
Fig 9.1: Age distribution of elderly persons 100%
7.3% 5.9% 7.9% 8.4%
5.6% 3.9% 5.8% 4.3% 10.9% 10.1%
90%
9.5% 9.3%
15.2% 13.4%
16.0% 17.4%
12.9% 10.3%
12.7%
80% 17.4%
28.8%
70% 32.7%
34.4%
38.2%
60%
35.2% 35.5%
36.4%
36.2% 37.2%
50%
86.4%
40%
30%
42.4% 46.3%
43.4%
57.9% 51.2%
40.8%
20%
40.6%
38.0%
34.5%
10%
0%
Pakistan
Urban
Rural
Punjab Sindh
KP
Balochistan
FATA*
AJK
GB
50-59 years
60-69 years
70-79 years
80+ years
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
There were 30.4% male and 69.7% female respondents in this sample because mostly women
were at their homes during the day. Approximately 42.4% of the elderly population belonged to
the age group between 50–59 years (46.3% urban and 40.6% rural).
9.1 Body Mass Index (Elderly Persons):
In all, 69.7% women and 30.4% men were assessed for BMI. The main reason behind this
variation was that the data collection conducted mostly from 10 am to 04 pm and menfolk are
usually not available at home during this time slot. The data revealed that more than half
(53.9%) of the Pakistan’s elderly population does not have normal weight; they were either
underweight or overweight. Among them 15.8% were thin, 24.2% overweight and 13.9% obese.
In provinces highest thinness was in Balochistan (19.6%) and lowest in KP (7.5%) while about half
(49.7%) of the elderly population were overweight and obese in KP. In Gilgit Baltistan 61.6%
elderly population maintained normal weight.
54 | National Nutrition Survey 2011
Table 9.2: Detail data according to the WHO classifications
100% 13.9%
9.9% 12.9% 14.3%
12.9%
7.8% 4.3%
90%
19.3%
23.0%
18.3%
33.3% 19.1%
80%
21.1%
19.4%
24.2%
23.8% 22.1%
70%
31.4%
30.4%
60%
50%
49.8%
46.2%
48.2% 47.4% 51.9% 61.6%
40%
46.3%
46.1%
30%
37.5%
42.8%
20%
21.0%
10%
15.8% 8.1%
19.3% 17.1% 17.4% 7.5%
19.6% 19.3% 15.8%
0% 0.0%
Pakistan Urban Rural Punjab Sindh
KP Balochistan FATA*
AJK Gilgit
Thinness (<=18.49)
Normal (18.5-24.99)
Over-weight(25-29.99)
obese (>=30)
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
About half (49.8%) of the rural elderly population was on normal weight whereas it was only
37.5% in urban areas while thinness was higher (19.3%) in rural and lower (8.1%) in urban. The
tendency of overweight was 31.0% in rural areas in comparison of 54.4% in urban areas.
55 | National Nutrition Survey 2011
Chapter 10: National Nutrition Survey – Qualitative Findings
INTRODUCTION
We conducted 40 focus group discussions and 16 in depth interviews at different places to cover almost all provinces/regions of Pakistan. Focus group discussions (FGDs) were conducted with mothers having child less than five years of age, male & female elders of the family and lady health workers. In-depth interviews were conducted with male & female health care professionals.
Around 400 participants attended these FGDs & IDIs. The characteristics of participants were presented below;
10.1: Gender 25%
10.2: Age
100% 84.0%
19.0% 20.0%
80% 20% 18.0%
16.0%
60% 15%
8.0%
12.0%
40% 10%
16.0%
5%
3.0%
3.0%
20%
0%
0%
< 21 21 - 24 25 - 29 30 - 34 35 - 39 40 - 45 46 - 49 50+
Male Female
Years Years Years Years Years Years Years Years
10.3: Education 30% 28.0%
25%
20% 16.0%
18.0%
15.0%
14.0%
15%
10% 9.0%
5%
0%
No Education Primary Middle Matric Inter Graduation and
above
Data were transcribed and translated directly from native language to English. The validity of the transcripts and translations was checked with back translation.
A-PERCEPTION OF HEALTH AND ILLNESS
The majority of rural mothers had opinion that f women lack the freedom to access medical care for themselves and their children unless the household decision maker allows them to do so.
Majority of the participants across the country reported fever, cough, diarrhoea and intestinal worms are ailments of children.
Majority of participants from Baluchistan, rural Sindh and southern Punjab said that we have to
collect water from wells located outside the house and store it for our use and there is no proper
system of collection and disposal of sewerage in the community/locality. The inability to access
56 | National Nutrition Survey 2011
clean water and unsatisfactory sanitary conditions are important contributors to many childhood
illnesses. Waterborne diseases and worm infestation are very common amongst those living in
rural areas or where there is improper sanitation coverage.
Regarding perceptions about women’s health, the most common criterion appeared to be the amount of physical work that they were able to do.
Majority of participants of group discussions stated that if a woman is not looking pale and per-
forming her routine household work she is considered to be healthy. Rural mother stated “ In
laws expect to do the same amount of work even during pregnancy”. One participant remarked
that “if a woman is fulfilling all her routine work and her cheeks are rosy, we assume she is
well and healthy”.
The majority of participant acknowledged that joint pains and swelling, leucorrhoea, backache,
lower body pain, high blood pressure and irregular menstruation were major illnesses of women.
However many mothers from Upper Sindh and Southern Punjab perceived that they were suffer-
ing from health problem due to low or insufficient diet. The majority of participants also stated
that they do not have enough food to eat, poor and cannot afford eating as desired, even they
cannot afford medical care except some home remedies. Access to a health facility was identi-
fied as a specific barrier to availing health services during discussions. Location of health facili-
ties, besides that dependency on male decision makers, transportation cost, long waiting times
at the facility etc. were also mentioned by participants as major barriers to access health ser-
vices. Majority of participants acknowledged that if the illness is not serious then some self-
medication is done from the leftover drugs, however a few participants said that we consult the
nearby health care provider and the also lady health workers for taking advice. Apart from lady
health workers, traditional birth attendants (TBA’s) were also consulted for minor ailments. For
instance, in Balochistan, upper Sindh, Azad Jammu Kashmir and Gilgit a mixture comprising of
cardamom, ginger and lemon is used for treatment of leucorrhea. Some mothers of Gilgit Bal-
tistan and Khyber Pakhtunkhwa said that women were only permitted to consult ‘lady’ doctors
due to the cultural barriers.
Majority of health professionals interviewed had opinion that most patients didn’t follow doc-
tors’ advice and instructions. Patients were generally didn’t complete the course of treatment
regimens and follow up with medical professionals. B-DIET DURING PREGNANCY AND LACTATION
The majority of participants of group discussion across country stated that pregnancy was not
considered as a special event and no extra dietary consideration was given to it. Although the
medical professionals unanimously said that woman should encourage women to eat healthy
and extra food during pregnancy and lactation.. Across the regions the majority of participants
said that diet was dependent on economic circumstances of family and was not a matter of
choice. The majority of participant mothers stated that their usual diet consisted of vegetables
and milk. Rice, pulses/lentils was also mentioned as staple food by most of participants. Majori-
ty of participants across the country said that they cannot afford to buy meat or chicken. Few 57 | National Nutrition Survey 2011
mothers also stated that they took vitamin or mineral tablets during their pregnancies and lacta-
tion period. The majority of health professionals interviewed were stated that malnutrition,
anemia and hypertension can cause complications during pregnancy and delivery. C - INFANT AND YOUNG CHILD FEEDING PRACTICES
1- Breast Feeding
Almost all participants across country were aware of the necessity breast milk as first feed of the child after birth. During the discussion most of mothers stated that, breast milk is healthy and prevent from illnesses. The majority of mothers were not aware the timing of initiation of breast milk and had different opinions, ranged from immediately within half an hour of birth to up to three days after birth. “Breastfeeding should be initiated within 24 hours of child birth” (Urban Mother – FGD). “It should be initiated within first 1 and half hour after child birth” (Rural Mother – FGD). Mother from urban Punjab stated “We think that immediate breastfeeding af-ter delivery is essential otherwise child will not suck properly which can result in child ill health”.
Most of the mothers interviewed believed breastfeeding should be continued up to two years of age of child. Continued breastfeeding was perceived by mothers to protect them from breast cancer and their child from infections. This was also confirmed in the KAP survey where more than 75% of the respondents from all the sectors opined that breastfeeding should be continued for up to 2 years.
During the discussions and interviews, participants were knowledgeable and had many opinions regarding the benefits of the breastfeeding. Mothers from rural areas also perceived some eco-nomic benefits of breastfeeding. The benefits of breastfeeding mentioned for the child during discussion were that it supplied all necessary nutrients, provide antibodies to illnesses, increases child’s mental development digests easily and protects against diarrhea (9%). Other benefits mentioned by the participants in the FGDs were as follows: baby will be healthy and it is good for child’s growth, vital for mental and physical growth, easy to feed and natural and breast milk is not contaminated so it protects against disease and reduces the chance of infection.
However, there were a few mothers who believed that first milk i.e. colostrum should be dis-carded to get rid of the sour taste. They thought that colostrum caused abdominal pain. Another negative practice Although there are no medical/ scientific advantages attributed to pre-lacteal food yet ‘ghutti’ is
very much a tradition first feed of child across Pakistan. This fact was confirmed by most of par-
ticipants of group discussions. Honey was identified by most of participant that was commonly
used across the country but variation existed as “Gurr” (Jaggery) in Northern Punjab, clarified
butter in Northern Punjab/KP /Gilgit-Baltistan, Fennel-flavoured sherbet (Mixture) in Khyber
Pakhtunkhwa were also used as first feed after birth of child.. Some mothers from Gilgit Bal-
tistan stated that “Donkey’s milk, which is perceived to prevent epilepsy, was also given to child
after birth.
Majority of lady health workers acknowledged during discussions that breast feeding is the common norm in rural communities but women still need to know the proper feeding tech- 58 | National Nutrition Survey 2011
niques. Majority of mothers were aware that they should be exclusively breastfeeding up-to 6
months. The vast majority of mothers stated said that they practiced exclusive breast feeding
during first six months of their child but many of them admitted that they also gave water to the
child during this time period, especially after the age of four months. The duration of the exclu-
sive breastfeeding varied from 4 months to 7 months. “Exclusive breastfeeding for five months
is sufficient for the child” (Mother – FGD).
The multiple factors were identified as barrier for exclusive breast feeding as lack of milk produc-
tion, anxiety, exhaustion, psychosocial issues, delayed initiation of breast feeding. Others factors
included promotion of infant commercial formulas leading to misconception in mothers that it is
better feed for their babies.
There were some beliefs related to breastfeeding stated by some mothers from rural Sindh that
mothers practice to protect their child from disease or the evil eye. To avoid the evil eye, a child
should be breastfed separately from everyone. Being watched by others can affect both mother
and child. Specifically, it was thought that a child can get indigestion, stomach ache and/or
phlegm, if they were observed breastfeeding. It was also believed that the evil eye could dry
breast milk. “Children are not given breast milk outside home after sun set because of devil
eyes” (Rural Sindh Mother).
Regarding duration of breast feeding, the participants opined from one to two and half years.
Most of mothers from Lower Sindh continued to feed till 1.5 to 2 years and similar responses
from other provinces. Few mothers from Khyber Pakhtunkhwa stated that duration of lactation
as 2 years for male and 2.5 years for female child.
Majority of mother also said that top milk was also introduced during this time. The range of top
milk included formula milk, packed milk as well as fresh cow’s milk largely depending on the par-
ticipant’s socio economic status. One of the participants stated that “they breastfed their in-
fants due to the poverty and unavailability of formula milk in surrounding of rural areas there-
fore women or young mothers have no choice other than to breast fed”. The most common
reason revealed for stopping breastfeeding was pregnancy, child not sucking and followed by
insufficient milk.
2- Complementary Feeding (CF) Majority of Pakistani children between 6-9 months of age had commenced complementary
foods. The age for introduction of complementary foods was varies across the Pakistan but ma-
jority had initiated complementary feeding at about 6 months of age. The most commonly mentioned complementary food that was first introduced to the child was
semolina, rice, bread, sago, rice and milk dessert (kheer), buttermilk, egg, banana, tea, porridge,
chapatti, potato curry, lentils, meat and broth, fish and vegetables. Almost all the mothers stated
that the consistency of the first foods was thin and liquidy. In the FGDs and interviews, mothers 59 | National Nutrition Survey 2011
mentioned that initial CF’s were simply milk mixed in mashed rice. Vegetables are gradually in-troduced. Rarely was meat or dairy products given as complimentary foods. From 12 months onwards many mothers start giving the child the same diet as the adults. If reg-
ular family foods were given, then mothers first washed these with water to remove the spices-a
practice that could potentially contaminate the food if untreated water was used. Spices were
gradually introduced. Formula milk was not introduced at all by mothers whereas others intro-
duced formula milk between first and 12 months of age. According to the guiding principles of complementary feeding, there are six things that could be
considered during the complementary feeding stage: amount/quantity; frequency; densi-
ty/consistency; quality/diversity; hygiene; and responsive or active feeding. There was a lack of
knowledge about these facts among majority of mothers but a larger proportion of urban moth-
ers mentioned the various components of good complementary foods than their rural counter-
parts. Very few mothers were aware that the density/consistency of complementary foods is an im-
portant component of CF. Few mothers could not mention any aspects of feeding they need to
consider when preparing complementary foods. Very few mothers stated that the characteristics
of good complementary foods should be ones that are rich in energy, protein and micronutrients
but half of mothers opined that good CF should be clean and safe. Majority of the urban and rural mothers were not aware that the ideal age to commence com-
plementary feeding was at 6 months. Some thought the ideal age to commence complementary
feeding was 9 months and few stated that the ideal time was at 4 months of age. Reasons for early initiation of complementary feeding mentioned by the few who did commence
CF before 6 months included employment of mother; perceived insufficiency of the breast milk
to meet the needs of infant; infant’s reluctance to take breast milk (urban), maternal illness and
early pregnancy; child underweight; family members influence mother to initiate CF (rural); poor
sucking by infant and perception that breastfeeding hindered in maintaining mother’s figure (ur-
ban and rural). Delayed initiation of complementary feeding was a more common occurrence in Pakistan. The
main reasons of delayed initiation of complementary feeding cited were financial (rural and ur-
ban); complementary foods cause allergy (urban); the belief that breast milk was nutritious
enough to meet infants needs even beyond 6 months (rural and urban); infant gaining well on
exclusive breast milk so why initiate CF. When asked how mothers can determine if the food they are giving to their child is appropriate,
almost half of the mothers mentioned that they would know if their child refuses to eat it. Some
mentioned that the child would vomit the food. Mothers also mentioned that signals that indi- 60 | National Nutrition Survey 2011
cated to them that their child was ready to commence CF were the infants’ interest in eating food.
When the participants were asked as to who actually fed the child, the majority of mothers re-
sponded that herself or sometimes the grandmother or an older sibling The majority of mothers
also stated that they generally fed their children in the living room or veranda.
Majority of women in discussions acknowledged that they washed their hands before prepara-
tion of food for their children. When participants were asked regarding hand washing of child
before meal very few of them were followed that practice. Majority of mothers acknowledged
that they don’t use separate utensils (plate, cup or spoon) to feed their children.
Most of mothers also stated that child left over food was eaten by some other family member.
Most of urban mothers pointed out, frequent use of refrigerator for storage of child leftover
food.
Majority of health care professional interviewed commented that there was a uniform lack of
knowledge about diet and nutrition amongst families, including those belonging to affluent
backgrounds. One comment was that “Sometimes we have to tell them to buy Rs.10 worth of
rice and lentils instead of spending more money on commercial food”. D- OTHER DETERMINANTS OF MALNUTRITION
The most of participants of group discussions from both urban and rural areas opined that there was no inequality in distribution of food in terms of proportion and quantity between boys and girls in the family. However a mother of the focus groups was stated that “boys must get more food than girls because they have more responsibilities in future”.
Some participants were said that “the family sat down together at the meal time but that food
was served in order of seniority” Mothers from southern Punjab said that. “Feeding the girl child
is not a viable deal as she has to go another house after marriage”. Another mother stated that
“The male child is an important asset because he will be productive and bring income into the
family. He will also be responsible for carrying the name of the family”.
The role of culturally deep rooted food taboos across the provinces also plays its part in affecting
health and nutrition. The concept of “Hot” and “Cold” was observed across the country during
group discussions..
Majority of participants across all provinces were able to segregate food into the hot and cold variety. The common perception in all regions was that eggplant, bitter gourd and meat have a ‘hot’ effect. Cold food includes vegetables, raw mango, rice and lentils in Lower Sindh, Zucchini, Okra and Pumpkin in Upper Sindh, spinach, carrot and cucumber in Baluchistan, pumpkin in Southern Punjab, lentils, and dairy products and Apricot extract in Gilgit. “Hot” foods also included seafood in Lower and Upper Sindh, meat in Upper Sindh, Northern and Southern Punjab and Gilgit Baltistan, okra in Southern Punjab, Azad Jammu Kashmir, green vege- 61 | National Nutrition Survey 2011
tables in Southern Punjab, clarified butter and eggs in GB, lentils in GB/Azad Jammu Kashmir and soup, spinach and spices in Azad Jammu Kashmir. Some mothers said that they avoided giving “hot” food to young girls as it would speed up puberty in them.
Some participants from rural areas also highlighted another interesting myth present within so-
ciety elders that taking medicine in the form of “pill/capsule” during pregnancy is harmful. Some
lady health workers in pointed that “we cannot convince the women to take vitamin or iron
supplements because they are suspicious that it will harm the baby”, while a women partici-
pant stated “even if I take the medicine home my mother in law will not allow me to taking it”.
The most of participants across all regions acknowledged the importance of education for their
children. Mother from rural area stated. “We know that by educating our children we can build
a better life and secure a future for our children”. The major barriers to education stated by
most of participants included cultural biases, economic and access issues. A mother from KP
stated that “We want our girls to go to school but there is discouragement from our elders and
we are unable to convince them”.
62 | National Nutrition Survey 2011
Chapter 11: What Next
A-Implications for interventions and research
The key finding from the NNS 2011 is that very little has changed over the last decade in terms of
core maternal and childhood nutrition indicators. The survey does point towards gains in iodine
status nationally following the implementation of a universal salt iodization and promotion
strategy. However, this is counterbalanced by substantial deterioration in vitamin A status and
little to no gains in other areas of micronutrient deficiencies. These are reflective of an
insufficient response to the nutrition situation in Pakistan and the lack of coordination in
developing and implementing of a coherent nutrition strategy. A draft nutrition strategy was
developed in 2003–2004 and was approved by the planning commission. However, its final
approval and implementation never took place. Additionally the efforts of the bilateral agencies
and the World Bank have not translated into a tangible response. Although the floods of 2010
and 2011 once again highlighted the seriousness of under nutrition in Pakistan, the response was
largely reactive with little movement towards a national strategy for addressing under nutrition.
Despite the fact that these aspects of the poor nutritional status of women and children of
Pakistan have been known for a long time, and have been the subject of multiple surveys, there
is little public awareness at a national level of the importance and impact of nutrition in the
social and economic development of society. Several successive governments have failed to
recognize the level of importance nutrition has in the health and development of the population.
Nutrition has thus remained unrecognized in current social safety nets and income support
programs. Given the agrarian nature of the national economy, there has been consistent denial
of household food insecurity. This is especially true in the case of girls and women in Pakistan
and few effective interventions target them.
There is a widespread perception that malnutrition is closely related to poverty. While the
relationship cannot be denied, it is complex and the poverty-nutrition interaction in Pakistan is
strongly influenced by the degree and form of female subjugation, which affects the girl child
and women alike.
It must also be recognized that nutrition is more than food and poverty is more than mere
income or assets. The few nutrition related interventions in Pakistan that have been undertaken
over the last fifty years have largely followed the pattern of vertical programs and are largely
supported through external aid and grants. These include vitamin A supplementation, wheat
flour fortification and promotion of iodized salt use. A huge amount of resources have been
invested in therapeutic feeding of malnourished children in the wake of the floods but relatively
less in preventive and promotion strategies. Although there have been breastfeeding promotion
and support programs at both community and facility level, (through the LHW program and the
Baby Friendly Hospital initiative), the comparable rolling out of complementary feeding
promotion and education strategies or the provision of fortified nutritious weaning foods has
been lacking. Not surprisingly, the net impact of all such interventions has been negligible in
63 | National Nutrition Survey 2011
terms of either nutrition awareness or improvement. In addition to planning nutritional
interventions, the creation of a demand at a population level for adequate nutrition is pivotal for
the success of any initiative. Neither widespread malnutrition nor poor dietary practices
amongst Pakistani women and children have been subjects of national awareness or public
education campaigns. In addition to well-designed interventions, Pakistan needs a mass
campaign for public awareness on the importance and impact of malnutrition on the nation's
health. There is thus an overwhelming argument for making an investment in adequate nutrition for the
families and children of Pakistan, as a means for economic revival and boosting national morale.
Although Pakistan has had several national nutrition surveys in the past, none have resulted in a
national intervention program aimed at addressing the root causes and effects of malnutrition.
To illustrate this, although a food aid initiative has been in place for several years under the
management of the World Food Program and Pakistan Bait-ul-Maal, its impact and effectiveness
in reaching the most needy has been limited. For any nutrition intervention to succeed, it is
imperative that it be part of a community-based intervention targeting some of the underlying
determinants of malnutrition such as household food security, culturally acceptable food
choices, as well as communal decision making for promotion of health and nutrition. These
interventions must be firmly grounded in the principles of equity, community participation and
ownership, while retaining scientific validity.
The alarming findings from the NNS 2011 – indicating vast inequities in indicators – suggest the
urgent need for action and the implementation of a range of interventions for women and
children. These include the review of existing programs for quality, such as the vitamin A
supplementation program, micronutrient fortification strategies and interventions to address
food insecurity. Some pilot projects are underway and additional strategies need to be identified
that may help soil zinc repletion interventions with national staples. As the NNS 2011 indicates, stunting, wasting and micronutrient malnutrition is endemic in
Pakistan, and reflects a combination of dietary deficiency; poor maternal and child health and
nutrition; a high burden of morbidity; and low micronutrient content of the soil, especially for
iodine and zinc. Most of these micronutrients have profound effects on immunity, growth and
mental development, and may underlie the high burden of morbidity and mortality among
women and children in Pakistan. So what can be done? Nutrition is an area that necessitates a multi-sectoral approach for
interventions. Some of the activities that could help address the issues are within the domain of
the health sector while others merit broad sustained support and collaboration of other sectors
and partners. For coherence, the foundation of the nutrition strategic plan has been laid down
under the overall framework of the Pakistan Poverty Reduction Strategy (PRSP). This document
defines the roles and activities that the production and social sectors must assume in order to
attain the overall objective of socio economic improvement, including a better quality of life. 64 | National Nutrition Survey 2011
The strategic territories where multi-sectoral support and coordination is imminently required
are institutionalization of nutrition; food safety and regulatory mechanisms; food fortification;
and social change communication. The interventions that fall within the umbrella of the health
sector are in the areas of maternal, infant, child, adolescent, adult and elderly persons’ nutrition.
Collaboration between all partners is essentially required for improving the nutritional status of
the target population with synergy. Given the devolution of health to the provinces, it will
become even more imperative to develop a concerted and coherent national policy. The need
for a central coordination and oversight mechanism to support provinces, especially those with
limited capacity is imperative given the wide disparities highlighted by the NNS 2011. Among the
various functions, this unit could also be required to form linkages that create social safety nets,
address agricultural and food safety, and enforce food industry regulation. Effective “social change communication” is a vital component of most successful programs and
products created to reach and change behaviours in the society at large. Innovative and effective
communication strategies can target misconceptions and educate the population about nutrition
interventions and practices while still being sensitive to cultural ideas and practices. The
integration of child nutrition with child survival becomes imperative. Similarly, given the high
rates of maternal and child morbidity and mortality in Pakistan, nutrition interventions should be
closely integrated with strategies for maternal, newborn and child health. The role of addressing
some of the basic determinants of maternal and child under nutrition in Pakistan cannot be
stressed enough. These include addressing issues of maternal education, empowerment and
basic rights. It can be argued that some of the maximum gains for maternal education can be
achieved by reducing high fertility rates, addressing inappropriate child spacing, and delaying the
age of marriage (avoiding early marriages).
We would also like to underscore emerging areas of focus that have hitherto been ignored. One
of these is the role of adolescent health and nutrition. As defined by WHO the age group ranging
from 10-19 years is considered adolescent and is estimated at about 19% of the total population.
Adolescent nutrition has so far been neglected in Pakistan and needs greater attention in the
years to come. The NNS 2011 also provides illustrative data on the increasing need to address
nutrition issues of the elderly. And, although not yet evident in the under 5 population, there are
intriguing indicators in the NNS 2011 suggesting that Pakistan may be witnessing the double
burden of under nutrition and obesity within rural and urban women of reproductive age. Adult nutrition is marred by a complex interplay factors such as industrialization, urbanization,
sedentary life styles, imbalanced diets and shifting socio-cultural norms. These give way to
diseases such as hypertension, strokes, coronary heart disease, diabetes and cancers, among
others. They tip the nutritional balance in many ways and require a multifaceted approach for
interventions ranging from surveillance, research, and social change communication to simply
healthy eating habits. The growing group of people over fifty years of age faces nutritional
depletions and associated problems that are related to the changing and slowing metabolism of
the body and inadequate replenishment of these nutrients. These changes bring along a
spectrum of health problems including hypertension; strokes; coronary artery disease; 65 | National Nutrition Survey 2011
sarcopenia (loss of muscle mass); glucose intolerance and other metabolic disorders;
osteoporosis and bone fractures; and cancers, among others. Efforts should be geared to
assimilate and disseminate information on old age health issues and nutrition. Emphasis should
also be placed on focusing on this emerging priority area for provision of rehabilitative and
consultative services for needy elderly persons. It is beyond the scope of this report to suggest remedies and discuss nutrition related
interventions and strategies in depth. It is envisaged that this NNS 2011 report will provide the
basis for further discussion at federal and provincial level for concerted action and strategy
development. Pakistan urgently needs a nutrition policy and strategy for a coordinated,
interlinked and multi-pronged approach for future endeavours to address malnutrition. 66 | National Nutrition Survey 2011
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17. Khan A. Adolescents and Reproductive Health in Pakistan: A Literature Review. In: Fund UNP, ed. Research Report No. 11. Islamabad: The Population Council, 2000:ii-73.
18. Bhutta ZA. Why has so little changed in maternal and child health in south Asia? Bmj 2000; 321:809-12.
19. Pakistan Medical and Dental Council. National Health Survey of Pakistan-1990-94: Network Publishing Service, 1998.
20. FAO. Nutrition country profiles: Pakistan. Rome: FAO, 1998. 21. WHO. Complementary feeding of young children in developing countries: a review of
current scientific knowledge. Geneva: World Health Organization, 1998. 22. Fikree FF, Rahbar MH, Berendes HW. Risk factors for stunting and wasting at age six,
twelve and twenty-four months for squatter children of Karachi, Pakistan. J Pak Med Assoc. 2000; 50:341-8.
23. Jalil F, Karlberg J, Hanson LA, Lindblad BS. Growth disturbance in an urban area of Lahore, Pakistan related to feeding patterns, infections and age, sex, socio-economic factors and seasons. ActaPaediatrScandSuppl 1989; 350:44-54.
67 | National Nutrition Survey 2011
24. Zaman S, Jalil F, Karlberg J. Early child health in Lahore, Pakistan: IV. Childcare practices. ActaPaediatrSuppl 1993; 82Suppl 390:39-46.
25. Durkin MS, Hasan ZM, Hasan KZ. Prevalence and correlates of mental retardation among children in Karachi, Pakistan. Am J Epidemiol 1998; 147:281-8.
26. Pollitt E, Gorman KS, Engle PL, Rivera JA, Martorell R. Nutrition in early life and the fulfilment of intellectual potential. J Nutrition 1995; 125:1111S-1118S.
27. World Health Organization. A critical link- Interventions for physical growth and psychological development: A review. Geneva: World Health Organization, 1999.
28. Ashfaq A. Infant feeding survey. WHO report. Islamabad. 1984 29. Jalil F, Karlberg J, Hanson LA, Lindblad BS. Growth disturbance in an urban area of
Lahore, Pakistan related to feeding patterns, infections and age, sex, socio-economic factors and seasons. ActaPaediatrScandSuppl 1989;350:44-54
30. Karlberg J, Jalil F, Lindblad BS. Longitudinal analysis of infantile growth in an urban area of Lahore, Pakistan. ActaPaediatrScand 1988; 77:392-401
31. Government of Pakistan, National Nutritional Survey of Pakistan, 2001-2, Islamabad 32. Manila forum 2000: Strategies to Fortify Essential Foods in the Asia and Pacific.
Asian Development Bank, 2000. Nutrition and Development Series No.2. 33. Paracha P, Jamil A. Assessment of Micronutrient (Iron, vitamin A and zinc) status of
preschool children of NWFP, Pakistan, 1998. In collaboration with: Pakistan Institute of Community Ophthalmology, Peshawar; Aga Khan University, Karachi; Institute of Nutrition, Thailand; University of Ulster, North Ireland, UNICEF.
34. Bhutta ZA. The enigma of maternal and childhood malnutrition in Pakistan: can we break the vicious cycle? Journal of College of Physicians and Surgeons Pakistan. 2002
35. Government of Pakistan. Pakistan economic survey 2001-2, economic advisors wing, finance division, Islamabad.
36. Government of Pakistan, Diarrhoeal disorders and feeding practices in Pakistan. Planning and development division, Islamabad 1984.
37. Government of Pakistan. Multiple Indicators Cluster Survey of Pakistan, 1995. Ministry of Health.
38. UNICEF 2002: http://www.childinfo.org/eddb/brfeed/grpcompasia.htm and http://www.pbs.gov.pk/sites/default/files/pslm/publications/pslm_prov2010-11/tables/2.14b.pdf
39. World Development indicators, 2002: http://devdata.worldbank.org/external/dgcomp.asp?rmdk=110andsmdk=473881andw=0l; and http://genderstats.worldbank.org/rhealth.pdf
40. WHO, World Health Statistics 2011, available at:
http://www.who.int/whosis/whostat/2011/en/index.html 68 | National Nutrition Survey 2011
69
Annex
Detailed NNS Tables
Sample Design & Sampling Weight
70
ANNEX: NNS Detailed Tables (Tables are numbered according to their corresponding chapters in the NNS)
Table 3.1: Details of sample size coverage (Percent)
Pakistan Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA AJK GB
Number of EBs
Sampled 1500
618 882
682 323 218 110 67 66 34
Completed 1500
618 882
682 323 218 110 67 66 34
Number of households
Sampled 30000
12360 17640
13640 6460 4360 2200 1340 1320 680
Interviewed / Visited 30000
12360 17640
13640 6460 4360 2200 1340 1320 680
Consent Yes 27963
11496 16467
13188 6282 3626 1996 900 1303 668
Refusals 2037
864 1173
452 178 734 204 440 17 12
Refusal Rate 6.8
7.0 6.6
3.3 2.8 16.8 9.3 32.8 1.3 1.8
Table 3.2: Distribution of HHs by Wealth Quintiles (Percent)
Pakistan
Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
Lowest 20.9
3.4 29.0
14.4 37.8 13.0 40.3 24.7 11.5 18.3
Second 21.1
7.0 27.6
20.2 12.1 29.9 26.1 51.7 26.2 36.4
Middle 20.2
18.1 21.2
22.7 12.4 25.0 15.5 17.6 22.3 25.9
Fourth 19.4
30.7 14.2
21.8 18.0 18.2 9.8 4.2 23.8 9.3
Highest 18.4
40.8 8.1
20.9 19.7 13.9 8.3 1.8 16.2 10.0
N 27963
11496 16467
13188 6282 3626 1996 900 1303 668
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 3.3: Age and Sex Distribution of Households’ Members (Percent)
Gender/Age Group Pakistan
Residence
Province / Region
71
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
Gender
Male 50.4
50.3 50.5
502.0 50.5 50.9 50.3 55.4 48.6 49.7
Female 49.6
49.6 49.6
49.6 49.6 49.6 49.6 49.6 49.6 49.6
Age (Years)
0-2 6.3
6.2 6.3
6.8 6.2 4.4 6.1 2.6 8.8 6.6
3-4 11.8
10.1 12.6
11.1 11.9 12.6 12.5 19.5 13.4 11.8
5-9 14.3
12.6 15.0
13.1 14.2 16.4 17.4 25.3 12.6 15.5
10-14 11.1
10.8 11.2
10.3 11.8 12.5 12.8 12.1 9.8 12.1
15-19 8.4
9.2 8.0
8.3 9.1 8.3 8.8 3.3 6.9 9.9
20-24 7.5
8.9 6.8
8.0 7.4 6.8 6.1 2.8 7.3 6.7
25-29 8.6
9.1 8.4
8.7 8.0 9.2 7.8 9.6 8.6 8.0
30-34 7.5
7.8 7.3
7.4 7.6 7.4 6.8 9.5 8.1 6.7
35-39 6.3
6.3 6.3
6.2 6.7 5.9 6.5 7.0 7.1 5.5
40-44 4.3
4.5 4.3
4.3 4.6 4.0 4.5 4.0 3.6 3.6
45-49 3.4
3.6 3.3
3.5 3.4 3.6 3.1 2.0 3.1 2.5
50+ 10.6
10.8 10.5
12.2 9.1 9.0 7.6 2.3 10.8 11.0
N 187095
77062 110033
89611 40470 21817 15117 4984 9173 5923
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 3.4: Household Size (Percent)
Household Members Pakistan Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
1-4 22.0
22.4 21.8
20.1 26.9 23.1 18.2 23.0 17.6 7.9
5-7 47.9
48.7 47.6
47.7 43.2 56.3 38.0 68.6 45.1 34.2
8+ 30.1
28.9 30.6
32.2 29.9 20.6 43.8 8.4 37.2 58.0
Average Family Size (Mean ± SE) 6.6 ± 0.03 6.6 ± 0.05 6.6 ± 0.04
6.8 ± 0.04 6.4 ± 0.06 6.0 ± 0.06 7.6 ± 0.17 5.6 ± 0.10 7.0 ± 0.11 8.9 ± 0.24
N 27963
11496 16467
13188 6282 3626 1996 900 1303 668
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
72
Table 3.5: Formal Education of Head of the Household (Percent)
Characteristics Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Illiterate 45.7
33.8 51.1
44.7 47.5 44.6 58.2 48.8 27.3 47.6
1-5 11.8
10.4 12.4
13.3 13.3 6.1 6.4 5.9 14.9 9.2
6-8 11.0
11.3 10.9
12.4 6.5 12.6 6.7 17.3 15.3 10.6
9-10 17.5
21.3 15.7
18.2 13.9 20.7 13.8 16.7 25.8 14.0
Above Matric. 14.1
23.1 9.9
11.4 18.8 16.0 14.9 11.3 16.7 18.6
N 27762 11410 16352 13099 6252 3587 1983 877 1297 667
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 3.6: Occupation of Head of the Household (Percent)
Occupation Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Business 8.6
15.1 5.7
9.5 6.8 10.5 5.0 2.1 9.7 6.6
Worker/Labor 38.7
33.2 41.2
36.7 45.2 38.7 32.0 40.7 34.0 19.9
Farmer/Land Owner 14.9
2.7 20.4
18.0 11.9 9.5 18.2 12.8 3.3 12.4
Govt./Pvt. Employee 16.4
23.2 13.3
13.5 18.5 19.6 23.1 18.2 23.9 34.3
Small Business / Shop 5.9
7.0 5.4
5.6 4.4 8.1 7.2 12.0 5.6 2.2
Not Working / Unemployed 15.5
18.9 14.0
16.8 13.2 13.6 14.5 14.2 23.4 24.6
N 27566 11305 16261 13040 6219 3544 1956 851 1288 668
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
73
Table 3.7: Occupancy Status of Dwellings and Number of Rooms per Dwelling (Percent)
Ownership status of house & No. of Rooms
Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Owned 89.0
76.5 94.8
90.1 84.7 92.1 86.1 87.1 95.9 89.8
Rented 8.6
21.2 2.7
7.2 12.7 7.1 9.3 11.7 2.6 7.1
Living without paying rent 2.3
2.1 2.4
2.6 2.5 0.8 4.2 1.2 1.5 1.8
Other (specify) 0.1
0.2 0.1
0.1 0.1 0.1 0.4 0.0 0.0 1.3
N 27563 11386 16177 13093 6239 3507 1937 835 1295 657
Rooms In HH
1 37.7
31.6 40.6
35.0 56.5 24.5 36.1 13.0 26.6 21.5
2 39.4
40.1 39.0
40.3 29.7 51.1 36.4 47.2 41.0 35.6
3 14.8
18.5 13.1
15.5 9.9 17.4 15.2 25.4 18.9 21.9
>3 8.1
9.8 7.3
9.2 3.9 7.0 12.4 14.5 13.4 21.0
N 27616 11400 16216 13091 6227 3551 1969 821 1293 664
Type of Floor
Cement/Slake lime 46.1
64.7 37.5
49.2 42.9 44.5 31.1 27.9 62.3 69.7
Tiles 9.8
22.3 4.0
11.4 11.4 5.2 1.0 3.0 10.4 0.1
Mud /sand 40.8
10.2 54.9
34.2 44.9 49.2 66.7 63.1 26.1 29.1
Other materials 3.4
2.8 3.6
5.2 0.8 1.1 1.2 6.0 1.2 1.1
N 27746 11402 16344 13086 6256 3597 1979 864 1299 665
Type of Roof
RCC 19.6
41.6 9.5
23.3 19.9 12.0 8.3 3.6 22.8 3.2
Tier- Garter / Roofing tiles 49.5
45.2 51.4
57.1 40.2 48.5 27.5 46.0 28.0 3.7
Wood planks 19.9
6.5 26.1
13.8 25.5 23.0 39.9 31.0 18.9 89.4
Other materials 11.0
6.8 13.0
5.8 14.4 16.5 24.3 19.4 30.3 3.7
N 27823 11465 16358 13160 6264 3597 1983 850 1302 667
Structure of Walls
Bricks, cement and lime 64.2
86.9 53.7
69.9 54.9 69.9 29.0 39.4 80.4 85.1
Bricks (not cemented) 20.7
10.1 25.6
21.9 19.9 18.6 12.8 41.8 5.7 4.6
Other materials 15.2
3.0 20.8
8.2 25.2 11.5 58.2 18.8 13.9 10.3
N 27869 11478 16391 13171 6270 3616 1974 871 1299 668
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
74
Table 3.8: Cooking Fuel (Percent)
Type of Fuel Used Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Firewood 57.9
15.5 77.4
54.7 48.1 71.7 68.7 84.8 85.4 89.6
Gas 35.8
83.3 13.9
36.4 49.4 24.5 26.2 4.9 14.5 10.2
Kerosene Oil 0.2
0.0 0.3
0.0 0.0 0.9 0.1 2.7 0.0 0.0
Animal Dung 6.1
1.2 8.3
8.8 2.5 2.8 4.7 7.6 0.1 0.1
Other (Specify) 0.0
0.1 0.0
0.0 0.0 0.0 0.3 0.0 0.0 0.2
N 27772
11432 16340
13134 6243 3581 1970 880 1298 666
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 4.1: Food Insecurity
Pakistan
Residence
Urban Rural
Food Secure 41.9
47.6 39.4
Food Insecure Without Hunger 28.4
26.5 29.3
Food Insecure With Hunger Moderate
19.8
17.7 20.7
Food Insecure With Hunger Severe 9.8
8.2 10.5
N 15672 6397 9275
75
Table 5.1: Age Distribution of Mothers (Percent)
Age (Years) Pakistan Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
15-19 years 1.7
1.5 1.8
1.6 1.9 2.0 1.2 2.2 0.9 1.7
20-24 years 11.6
11.5 11.7
11.9 10.6 11.9 10.5 11.6 16.1 13.9
25-29 years 28.2
27.6 28.5
26.8 25.5 34.1 29.8 41.0 27.9 31.5
30-34 years 23.9
24.1 23.8
24.1 24.5 22.0 23.3 24.3 26.8 24.5
35-39 years 18.6
17.7 19.1
19.1 19.1 16.3 20.9 16.0 18.9 17.6
40-44 years 9.6
11.3 8.8
9.8 11.8 7.9 8.2 2.9 6.9 7.7
45-49 years 6.3
6.3 6.3
6.7 6.8 5.9 6.1 2.0 2.5 3.1
N 24694
9995 14699
11412 5460 3091 1888 894 1288 661
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.2: Formal Education (Mothers) (Percent)
Characteristics Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Education
Illiterate 59.3
36.6 69.4
52.6 62.2 72.2 82.0 82.3 30.4 62.4
1-5 Years 12.5
13.4 12.1
16.0 10.3 5.9 6.3 4.6 17.7 6.5
6-8 Years 8.7
11.1 7.6
9.5 6.2 9.1 4.8 8.5 19.8 9.2
9-10 Years 10.5
18.5 6.9
12.3 10.2 6.8 3.5 3.5 19.1 10.9
Above Matric. 9.0
20.3 4.0
9.7 11.2 5.9 3.4 1.0 12.9 10.9
N 24459 9928 14531 11364 5437 3030 1875 811 1282 660
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
76
Table 5.3: Marital Status and Current Pregnancy Status (Mothers) (Percent)
Characteristics Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Marital Status
Married 98.7
98.0 99.0
98.5 98.3 99.4 99.0 100.0 99.0 99.8
Widow / Separated 1.3
2.0 1.0
1.5 1.7 0.6 1.0 0.0 1.0 0.2
N 24694 9995 14699 11412 5460 3091 1888 894 1288 661
Pregnancy Status Yes 10.0
9.1 10.5
11.2 11.9 6.0 5.1 4.6 9.1 7.3
N 24694 9995 14699 11412 5460 3091 1888 894 1288 661
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.4: Reproductive History (Mothers) (Percent)
Characteristics Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Pregnancies
1-2 29.7
30.5 29.3
28.3 26.3 42.4 26.6 22.9 33.0 25.2
3-5 46.6
47.9 46.0
47.3 42.6 48.0 40.4 68.9 45.2 43.6
6+ 23.7
21.6 24.6
24.4 31.1 9.6 33.0 8.2 21.7 31.2
N 24217 9818 14399 11189 5325 3005 1864 890 1287 657
Outcome of Last Pregnancy
Live birth 93.4
91.6 94.2
92.1 91.9 97.9 95.3 99.3 94.5 95.9
Miscarriage 5.7
7.8 4.9
7.0 7.2 1.5 4.4 0.5 4.5 3.6
Still birth 0.8
0.6 0.9
1.0 0.9 0.6 0.2 0.3 1.0 0.5
N 18904 7402 11502 8361 3978 2402 1610 831 1146 576
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
77
Table 5.5: Seeking Antenatal Care from the Skilled & unskilled Provider (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
ANC
No One 37.5
18.1 45.8
33.0 38.3 43.5 52.1 70.5 19.2 20.0
Doctor 49.5
72.1 39.8
51.1 57.7 39.2 38.8 13.0 66.3 60.5
Nurse 7.1
4.5 8.2
11.5 1.9 1.1 2.3 3.4 12.5 11.9
LHV 2.3
1.8 2.5
0.9 0.3 10.6 1.4 4.4 0.9 4.7
CHW 0.4
0.5 0.3
0.3 0.3 0.9 0.2 0.9 0.1 0.4
LHW 1.1
1.0 1.2
0.9 0.4 2.5 1.6 3.1 0.7 2.6
Traditional Birth attendant 1.5
1.5 1.5
1.5 1.1 1.4 2.7 2.3 0.2 0.0
Others Specify 0.1
0.1 0.1
0.2 0.0 0.1 0.0 0.0 0.1 0.0
Don't know 0.5
0.5 0.5
0.5 0.1 0.8 0.8 2.4 0.0 0.0
N 22791 9081 13710 10167 5152 2902 1795 869 1265 641
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.6: Supplementation during Last Pregnancy (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Supplementation
None 37.8
23.0 44.4
35.8 43.3 33.7 54.5 30.2 33.4 30.3
Iron 24.4
33.2 20.4
26.3 26.1 19.3 11.4 11.7 36.4 32.8
Folic Acid 25.3
35.7 20.7
22.5 31.3 28.0 17.4 19.2 37.1 30.4
Micronutrient 3.9
3.5 4.0
2.6 2.2 8.3 5.8 13.6 5.4 0.2
Calcium 35.6
48.6 29.9
39.3 38.0 24.7 15.6 27.5 50.9 25.6
Other Vitamins 8.9
14.4 6.4
6.8 16.4 4.8 4.4 12.2 11.4 4.2
N 24694 9995 14699 11412 5460 3091 1888 894 1288 661
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.7: Knowledge of Micronutrients – Iron (Percent)
Pakistan Residence Province / Region
78
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Iron 24.8
42.0 17.0
29.8 23.6 13.9 8.6 9.5 40.8 22.7 Iron Rich Food
Don't Know 47.6
35.1 61.6
52.6 31.2 39.2 48.7 75.3 65.4 40.4
Liver 6.2
8.5 3.7
5.0 7.6 13.0 11.8 4.0 3.4 1.7 Beef 6.3
7.0 5.6
6.7 5.8 4.9 4.5 1.2 8.2 7.1
Mutton 3.6
4.3 2.9
3.6 4.3 2.4 3.8 0.0 2.6 8.9 Chicken 4.0
4.0 4.0
3.8 3.8 6.7 1.6 1.1 3.0 5.0
Egg yolk 5.0
5.4 4.6
4.4 4.9 10.6 8.1 1.0 2.9 10.9 Green leafy vegetables 36.5
48.1 23.5
34.1 51.7 28.3 29.1 1.9 21.7 39.1
Lentils 5.1
4.7 5.5
4.4 4.6 11.6 3.2 1.1 6.9 5.3 Dairy products 9.7
10.6 8.6
8.5 11.2 14.9 8.1 6.8 10.2 15.1
Fruit 9.7
13.5 5.5
7.6 21.0 0.6 4.4 0.0 6.7 18.8 Apple 4.4
6.6 1.8
3.3 9.8 0.3 3.3 1.1 2.2 0.9
Vegetable 1.1
1.1 1.1
1.4 0.2 0.0 0.0 0.0 2.9 2.4 Fish 0.9
1.3 0.5
0.6 2.4 0.2 0.5 0.0 0.5 3.1
Potato 1.0
1.3 0.6
1.0 1.5 0.2 0.3 0.0 0.6 2.3 Others 2.9
3.0 2.8
3.8 1.5 0.3 0.0 0.0 2.6 6.1
N 7023 4382 2641 4141 1300 529 190 88 592 183 Health problems due to Iron deficiency
Don't Know 60.7
52.1 70.2
64.4 49.5 52.5 54.6 80.4 76.0 55.2
Behavioral problems 0.4
0.4 0.4
0.4 0.3 0.9 1.1 1.1 0.0 0.5 Repeated infections 1.0
1.2 0.7
0.4 2.2 2.2 2.4 1.0 0.0 5.5
Loss of appetite 1.4
1.6 1.1
1.0 1.7 3.9 2.0 1.1 0.1 1.2 Lethargy 7.1
9.5 4.4
6.0 10.7 8.2 8.1 0.9 3.3 8.0
Breathlessness 0.8
0.8 0.7
0.5 1.2 2.0 0.6 1.0 0.1 0.0 Increased sweating 0.4
0.5 0.3
0.0 1.0 1.8 0.7 2.0 0.0 0.0
Strange ‘food’ cravings (pica) 0.3
0.3 0.3
0.3 0.2 0.6 1.0 0.0 0.1 0.0 Failure to grow at expected rate 1.7
2.2 1.2
2.2 0.7 0.9 0.0 0.0 1.1 9.0
Abortions in pregnant women 0.6
0.6 0.5
0.4 0.6 2.0 1.3 1.0 0.0 0.2 Still Births 0.4
0.3 0.5
0.1 0.3 2.4 0.9 3.1 0.0 0.0
Growth retardation of fetus 0.6
0.9 0.3
0.4 0.9 1.0 0.0 1.0 0.6 0.5 Anemia 26.4
33.3 18.6
22.5 38.8 33.0 23.3 2.0 16.3 16.0
Weakness 4.4
4.3 4.5
5.8 2.0 0.1 4.1 0.0 5.0 7.2 Bones Problem/pain/disease 2.5
3.5 1.4
3.0 1.9 0.8 1.6 0.0 2.1 1.9
Others 3.9
4.6 3.0
4.5 3.4 0.7 3.9 1.1 2.3 13.3 N 7023 4382 2641 4141 1300 529 190 88 592 183
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.8: Knowledge of Micronutrients – Iodine (Percent)
79
Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Iodine 42.8
61.6 34.2
47.8 38.4 41.3 17.3 17.3 59.1 37.1 Iodine Rich Food
Don't Know 0.7
1.0 1.0
1.0 1.3 2.1 3.4 8.1 2.4 3.5
Liver 0.5
0.6 0.4
0.3 0.4 1.4 1.8 0.5 0.0 0.0 Meat products 1.5
1.8 1.4
1.4 1.5 2.2 3.9 1.2 0.9 2.4
Dairy Products 1.5
1.6 1.4
1.0 1.6 3.6 2.1 0.0 0.3 0.9 Vegetables 3.8
4.9 2.9
3.8 4.6 3.3 3.1 2.2 3.5 3.1
Fish 2.4
3.1 1.7
1.8 3.7 3.0 1.6 3.6 1.5 0.3 Iodized Salt 66.9
66.2 67.4
67.0 66.5 70.5 53.7 44.8 66.5 57.2
Fruits 0.5
0.7 0.4
0.5 0.8 0.0 0.1 0.0 0.5 0.7 Egg/Egg fry 0.2
0.3 0.2
0.3 0.2 0.0 0.0 0.0 0.6 3.2
Daal / pulses 0.1
0.2 0.1
0.2 0.1 0.0 0.0 0.0 0.1 0.0 Water 0.2
0.1 0.3
0.3 0.0 0.0 0.0 0.0 0.0 0.0
Others 0.9
1.1 0.8
1.2 0.9 0.0 0.6 0.0 0.7 1.2 N 11879 6607 5272 6508 2169 1553 385 149 840 275
Problems due to iodine deficiency
Don't Know 63.7
59.0 67.6
64.9 70.1 48.6 65.0 76.0 65.1 60.6 Goitre 26.0
28.4 24.0
25.2 16.9 42.7 26.0 14.1 27.1 26.2
Mental retardation/IQ loss 2.8
3.5 2.2
2.3 3.9 3.4 3.2 2.0 2.7 3.5 Brain damage 1.0
1.6 0.6
0.7 1.7 1.3 3.3 1.6 0.4 0.3
Impairs growth/development 3.8
5.1 2.8
3.0 4.6 6.9 3.0 1.1 2.3 4.3 Defects of speech & hearing 0.5
0.6 0.4
0.5 0.6 0.4 0.3 1.0 1.0 1.3
Abortions in pregnant women 0.3
0.4 0.2
0.3 0.2 0.5 0.7 1.1 0.0 0.0 Still births 0.2
0.3 0.2
0.1 0.3 0.8 0.5 0.0 0.0 0.0
Congenital anomalies 1.5
2.2 1.0
1.4 2.5 0.5 0.9 0.6 2.4 1.2 Growth retardation of Foetus 0.3
0.5 0.2
0.2 0.6 0.3 0.3 0.5 0.2 0.0
Low Blood Pressure 1.1
0.6 1.5
1.7 0.2 0.0 0.0 0.0 1.8 3.0 Weakness 0.9
1.1 0.8
1.2 0.7 0.0 0.4 0.0 1.0 1.7
Bones Problem/pain/disease 0.7
1.2 0.3
1.0 0.5 0.1 0.7 0.0 0.7 0.0 Anemia 0.4
0.3 0.4
0.5 0.2 0.0 0.0 0.0 0.6 0.5
Dehydration 0.2
0.1 0.2
0.2 0.1 0.0 0.0 0.0 0.4 0.0 Others 2.1
2.8 1.6
2.7 2.1 0.1 1.1 0.0 2.1 6.0
N 11879 6607 5272 6508 2169 1553 385 149 840 275
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.9: Knowledge of Micronutrients - Vitamin A (Percent)
Pakistan Residence Province / Region
80
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Vitamin A 24.0
41.6 16.0
28.6 23.5 12.5 10.6 7.5 44.5 28.8 Vitamin A rich Food
Don't Know 58.4
54.7 62.9
63.4 52.3 26.9 55.3 78.1 72.1 47.3
Liver 1.5
1.5 1.5
0.9 1.4 4.8 8.0 8.1 1.1 0.2 Meat product 7.2
7.6 6.6
6.7 6.3 13.7 4.9 2.4 8.1 8.1
Egg yolk 4.7
5.2 4.0
4.1 4.6 9.9 7.8 2.5 2.7 10.2 Green leafy Vegetables 17.0
17.2 16.7
16.2 19.4 20.2 11.3 2.5 14.3 30.4
Lentils/Beans 4.5
4.4 4.7
3.3 5.5 11.8 2.9 0.0 6.7 4.3 Dairy products 9.0
9.7 8.3
8.4 9.8 16.3 3.6 0.0 5.9 7.6
Fruits 20.5
23.3 17.3
18.2 24.3 33.8 20.3 4.8 15.7 19.3 Carrots 7.8
10.1 5.1
5.4 14.7 12.2 9.1 0.0 2.9 2.0
Vegetable 0.9
0.8 0.9
1.2 0.0 0.0 0.4 0.0 1.4 2.1 Fish 0.7
1.0 0.3
0.6 1.2 0.0 0.8 0.0 0.0 1.1
Ghee 0.6
0.4 0.7
0.7 0.1 0.4 0.8 0.0 0.8 2.5 Potato 0.4
0.3 0.4
0.5 0.3 0.0 0.4 0.0 0.0 2.4
Others 2.1
2.1 2.1
2.5 1.8 0.0 0.2 0.0 1.8 5.6 N 6988 4452 2536 4018 1324 480 233 69 648 216
Health problems due to Vitamin A deficiency
Don't Know 78.1
75.1 81.5
82.5 74.4 47.8 64.6 83.7 91.4 76.6 Abortions in pregnant women 0.5
0.4 0.7
0.2 0.7 2.9 2.2 1.3 0.0 0.9
Still Births 0.6
0.4 0.8
0.2 0.7 3.2 2.1 3.7 0.3 0.2 Growth retardation of foetus 0.3
0.4 0.3
0.1 0.4 2.0 0.4 0.0 0.0 0.2
Night Blindness 7.2
9.8 4.2
5.2 12.2 11.9 17.4 1.2 1.3 1.7 Rough and Dry Skin 2.1
3.0 1.0
1.2 3.5 6.3 2.1 3.8 0.1 0.4
Vulnerable to infections 0.8
0.7 0.8
0.6 0.7 1.8 1.2 0.0 1.1 1.1 Growth retardation 8.8
9.3 8.2
5.8 9.3 34.9 9.0 5.0 4.5 5.6
Weakness 2.0
1.9 2.0
2.5 1.0 0.4 4.5 0.0 1.2 4.4 Anemia 1.0
0.8 1.2
1.4 0.2 0.0 0.2 0.0 0.6 7.4
Eye sight Problem 0.3
0.4 0.2
0.3 0.2 0.0 0.4 0.0 0.0 0.0 Others 1.9
2.2 1.6
2.2 1.6 0.6 2.4 0.0 1.6 3.7
N 6988 4452 2536 4018 1324 480 233 69 648 216
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
81
Table 5.10: Knowledge of Micronutrients – Zinc (Percent)
Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Zinc 6.1
12.8 3.1
6.6 7.5 4.2 2.8 0.9 9.7 4.5
Zinc Rich Food
Don't Know 73.3
73.4 73.1
77.6 77.1 35.7 63.6 47.8 89.8 66.9
Liver 2.5
2.7 2.2
1.7 3.1 5.2 6.4 20.1 0.4 0.0
Meat product 4.9
4.6 5.4
4.7 2.8 13.1 5.4 0.0 1.7 1.2
Egg yolk 2.6
2.7 2.3
1.9 2.0 8.7 2.8 0.0 0.5 0.0
Vegetables 8.0
9.0 6.0
7.5 8.0 12.3 11.0 0.0 1.7 13.1
Lentils/beans 4.3
4.5 4.0
4.0 3.3 10.7 1.3 0.0 1.9 2.5
Dairy products 4.9
4.0 6.5
2.2 3.5 25.9 2.8 0.0 0.0 0.0
Fruits 9.8
9.7 9.9
6.9 10.0 27.9 10.3 0.0 4.5 2.5
Watermelon seeds 2.3
1.9 3.1
0.9 2.1 10.3 7.4 10.7 0.0 0.0
Others 2.5
2.5 2.6
2.9 2.7
3.5 0.0 1.6 9.9
N 1861 1355 506 1002 413 168 66 9 161 42
Health problems due to Zinc deficiency
Don't Know 78.9
78.7 79.2
83.9 80.5 45.6 63.5 69.2 90.7 72.0
Growth retardation 7.5
6.8 8.8
4.6 6.3 28.5 9.6 20.1 1.8 4.8
Loss of appetite 1.9
1.9 1.9
1.1 0.9 8.5 5.7 0.0 1.2 0.0
Impaired immune functions 1.2
0.8 1.9
1.0 0.3 4.6 1.5 0.0 0.4 0.0
Diarrhea 5.0
5.2 4.5
2.6 9.4 6.7 5.3 10.7 2.8 11.0
Skin problems 5.5
5.7 5.1
3.5 5.0 20.2 6.3 0.0 0.4 5.3
Others 3.3
3.6 2.6
4.2 2.6 0.8 0.6 0.0 2.7 0.0
N 1861 1355 506 1002 413 168 66 9 161 42
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
82
Table 5.11: Knowledge of Micronutrients - Vitamin D (Percent)
Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Vitamin D 20.8
38.0 13.0
24.3 22.5 9.9 6.4 3.8 41.6 16.7
Vitamin D Rich Food
Don't Know 64.4
60.0 70.3
70.8 58.1 25.2 54.7 64.6 74.1 63.1
Sea Food 1.3
1.8 0.7
0.6 2.9 2.3 4.5 0.0 0.1 0.0
Cod liver oil 4.2
5.1 3.0
3.7 4.5 9.8 5.2 0.0 1.6 1.0
Liver 2.0
2.0 1.9
1.5 1.9 6.8 3.3 2.3 1.6 0.3
Meat product 7.3
7.1 7.7
6.3 7.0 18.7 4.5 2.5 6.4 12.4
Egg yolk 4.8
5.5 3.9
3.3 5.4 15.7 7.3 17.3 2.5 6.0
Green Leafy Vegetables 11.5
11.4 11.6
10.1 12.4 20.2 11.6 5.0 11.4 28.1
Lentils/ Beans 4.5
4.5 4.5
3.4 4.8 12.9 7.2 5.2 4.1 3.9
Dairy Products 10.6
12.3 8.3
7.4 16.3 22.7 9.3 0.0 7.6 8.4
Fruits 12.9
14.1 11.4
11.1 14.1 24.5 13.0 2.9 14.1 15.2
Sunlight 3.7
5.4 1.4
3.9 4.8 1.1 1.7 0.0 0.4 0.3
Vegetable 0.5
0.2 1.0
0.7 0.1 0.0 0.7 0.0 0.7 0.6
Others 2.2
2.5 1.8
2.4 2.2 0.3 1.5 0.0 2.0 10.4
N 6059 4014 2045 3480 1257 393 143 37 609 140
Health problems due to Vitamin D deficiency
Don't Know 78.2
72.5 85.9
82.7 72.4 54.2 64.0 60.5 91.4 83.2
Abortions in pregnant women 0.6
0.5 0.7
0.3 0.5 2.9 0.6 0.0 0.6 0.7
High Blood pressure in pregnant women
0.3
0.3 0.2
0.2 0.2 0.9 1.0 2.5 0.3 0.7
Still Births 0.6
0.5 0.7
0.1 0.5 4.7 0.3 2.5 0.3 0.0
Growth retardation of foetus 0.4
0.5 0.4
0.4 0.4 0.9 3.2 0.0 0.3 0.3
Bone Disease 13.3
18.9 5.9
9.3 21.6 24.6 17.5 24.6 4.3 7.5
Diarrhea 0.9
0.7 1.1
0.3 1.0 5.4 1.0 0.0 0.6 1.1
Skin problems 3.9
4.4 3.1
3.1 3.2 14.6 4.6 2.8 1.9 1.1
Weakness 1.5
1.5 1.4
1.5 1.7 0.5 2.4 0.0 0.5 5.5
Anemia 0.7
0.6 1.0
1.0 0.3 0.5 0.0 0.0 0.3 1.5
Others 2.4
3.2 1.5
3.0 1.9 0.0 5.5 0.0 1.3 1.4
N 6059 4014 2045 3480 1257 393 143 37 609 140
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
83
Table 5.12: Knowledge of Micronutrients - Vitamin B (Percent)
Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Vitamin B 19.3
34.4 12.5
23.2 19.2 9.7 5.8 3.6 40.1 15.6
Vitamin B rich Food
Don't Know 69.6
66.5 73.4
75.3 65.8 28.9 55.3 64.6 79.9 57.8
Sea Food 1.0
1.4 0.6
0.6 1.7 2.4 3.9 0.0 0.3 0.4
Cod liver oil 1.9
1.9 1.8
1.7 2.1 3.4 2.1 2.9 0.1 1.4
Liver 1.4
1.6 1.0
0.9 1.5 2.8 5.5 0.0 3.2 0.7
Meat product 6.9
7.2 6.5
6.3 6.2 15.6 9.6 0.0 4.9 17.9
Egg yolk 3.4
3.7 3.0
2.3 3.4 12.0 8.1 8.0 1.1 10.8
Green Leafy Vegetables 11.9
13.5 9.8
10.0 15.9 18.6 10.1 2.9 7.3 24.1
Lentils/Beans 5.7
6.2 5.2
4.2 7.4 15.3 10.9 5.3 3.1 5.1
Dairy Products 8.4
8.6 8.1
6.2 9.9 24.3 7.4 2.3 6.9 12.1
Fruits 13.4
16.3 9.8
11.6 16.1 22.2 14.9 8.4 11.5 13.0
Others 1.4
1.3 1.6
1.9 0.5 0.0 2.1 0.0 0.8 10.0
N 5674 3723 1951 3296 1100 385 130 36 592 135
Health problems due to Vitamin B deficiency
Don't Know 79.1
76.0 83.0
84.3 76.5 39.8 59.5 64.8 91.4 73.4
Anemia 9.2
10.3 7.8
6.2 10.4 30.2 23.9 21.0 5.3 8.7
Mouth ulcers 0.9
1.1 0.7
0.3 2.0 3.3 1.6 0.0 0.4 0.4
Angular Stomatitis 0.4
0.5 0.4
0.3 0.4 2.0 0.4 0.0 0.0 0.0
Growth retardation 2.7
3.4 1.8
1.4 3.3 12.9 5.6 0.0 0.4 2.2
Bone Disease 4.8
5.9 3.5
3.0 7.0 15.0 10.6 5.9 1.4 4.3
Skin problems 3.1
3.8 2.2
2.0 4.1 10.9 3.2 2.8 0.4 0.4
Irritability and restlessness 1.0
1.2 0.7
0.6 1.8 2.5 1.3 0.0 0.6 0.4
Weakness 1.0
1.1 0.9
1.3 0.4 0.5 2.7 0.0 0.2 7.4
Others 1.8
2.4 1.1
2.2 1.5 0.3 1.8 0.0 0.1 5.5
N 5674 3723 1951 3296 1100 385 130 36 592 135
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
84
Table 5.13: Knowledge of Iodized Salt and Its Usage (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Knowledge about Iodized Salt
Yes 64.2
83.0 55.6
71.4 59.9 58.5 29.3 29.8 82.0 79.5
No 35.8
17.0 44.4
28.6 40.1 41.5 70.7 70.2 18.0 20.5
N 26933 11026 15907 12720 5840 3572 1960 873 1300 668
Use of Iodized salt for cooking
Yes 39.8
46.5 35.2
36.1 39.2 49.0 45.4 14.1 71.6 94.8
No 56.2
51.4 59.4
63.2 59.5 26.2 50.0 82.1 28.1 3.0
Don't know 4.1
2.0 5.4
0.6 1.3 24.8 4.6 3.8 0.3 2.2
N 17306 8818 8488 9349 3413 2098 579 219 1108 540
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.14: Salt Test Results (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Not iodized (0 PPM) 30.9
27.6 32.4
21.2 48.2 36.4 59.2 44.9 12.1 15.1
15 PPM 13.4
12.3 13.9
11.6 14.0 19.0 15.2 29.2 14.9 14.8
25 PPM 17.6
16.3 18.1
19.0 11.8 24.4 9.2 15.6 22.6 16.5
50 PPM 38.2
43.9 35.5
48.2 26.0 20.2 16.5 10.4 50.4 53.5
N 23894 9924 13970 11977 5517 2701 1710 82 1272 635
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
85
Table 5.15: Clinical Examination (Mother) (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Clinical Examination
Edema 1.6
2.1 1.4
2.1 0.8 0.9 1.7 1.6 1.5 4.1
Jaundice 1.4
1.0 1.6
1.7 1.4 0.7 1.3 0.4 1.8 0.1
Anemia / Pallor 26.1
20.5 28.6
28.0 33.7 11.0 20.2 10.3 35.9 16.0
Goiter 2.9
1.8 3.4
4.1 1.3 1.2 1.1 0.7 9.8 1.2
Bitot’s spot 0.4
0.3 0.4
0.1 0.2 0.3 2.8 3.9 0.0 0.5
Cyanosis 0.2
0.2 0.2
0.2 0.1 0.4 0.5 0.1 0.3 0.0
N 24694 9995 14699 11412 5460 3091 1888 894 1288 661
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.16: Body Mass Index – Non Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
BMI (kg/m2)
<16 2.3 1.7 2.6 2.2 3.6 0.7 4.2 0.5 2.6 0.9
16-16.99 3.0 1.8 3.5 2.8 4.8 0.9 4.0 0.1 3.7 3.0
17-18.49 8.8 5.5 10.3 8.9 12.2 4.1 10.3 2.2 12.0 10.7
18.5-24.99 51.9 42.5 56.1 50.4 51.2 56.1 56.3 49.0 56.3 65.3
25-29.99 22.4 28.5 19.7 22.3 18.3 28.1 17.7 38.4 18.8 17.3
30-34.99 8.7 14.5 6.0 9.9 7.3 8.0 5.7 9.2 5.3 2.2
35-39.99 2.1 3.9 1.3 2.6 2.1 1.5 1.5 0.5 1.1 0.6
>=40 0.7 1.5 0.4 0.9 0.6 0.6 0.3 0.1 0.0 0.0
N 21907 8909 12998 9967 4768 2866 1695 836 1165 610
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
86
Table 5.17: Body Mass Index (Women 15 – 49 Married & Unmarried) (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
BMI (kg/m2)
<16 3.5 3.1 3.7 3.2 4.9 2.0 5.4 0.5 4.1 1.9
16-16.99 4.0 3.3 4.3 4.0 5.7 1.5 4.6 0.1 4.9 3.7
17-18.49 10.5 8.0 11.7 10.5 13.5 5.5 12.1 2.5 12.5 11.5
18.5-24.99 53.1 46.0 56.5 52.4 51.9 56.9 55.0 48.6 55.1 66.2
25-29.99 19.4 23.9 17.2 19.2 15.8 24.9 16.3 38.3 17.7 14.3
30-34.99 7.1 11.4 5.1 7.8 6.1 7.2 4.9 9.2 4.9 2.1
35-39.99 1.8 3.2 1.1 2.1 1.6 1.4 1.3 0.8 0.8 0.4
>=40 0.6 1.1 0.3 0.7 0.5 0.5 0.4 0.1 0.1 0.0
N 36225 15301 20924 17262 8095 4258 2770 887 1826 1127
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 5.18: Night Blindness of Mother (Last and Current Pregnancy) (Percent)
Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Night blindness Last pregnancy
Yes 12.7 11.7 13.2 11.7 21.3 4.1 12.5 10.5 14.5 3.7
No 82.1 84.6 81.0 86.1 76.8 76.7 82.9 77.0 84.4 94.9
Don't know 5.2 3.7 5.8 2.2 1.9 19.2 4.5 12.5 1.2 1.4
N 20480 8217 12263 8997 4474 2739 1700 831 1145 594
Night blindness Current pregnancy
Yes 15.6 14.3 16.1 12.6 22.7 9.7 14.1 35.4 16.8 6.5
No 81.5 82.6 81.1 86.2 76.2 68.9 84.1 62.3 79.1 92.7
Don't know 2.9 3.1 2.8 1.2 1.1 21.4 1.8 2.3 4.1 0.8
N 2247 835 1412 1157 617 173 98 43 113 46
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
87
Biochemical assessments data from FATA has not been presented due to low number of specimens collected (Table 5.17 – 5.33).
Table 5.19: Hemoglobin Level - Non Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe deficiency (<7 gm/dL) 1.5
0.8 1.8
1.1 2.8 0.7 1.7 0.4 0.6
Moderate deficiency (7 - 11.99 gm/dL)
48.9
48.5 49.1
47.5 59.2 34.9 47.2 40.6 22.7
Normal (>= 12 gm/dL) 49.6
50.7 49.1
51.4 38.0 64.4 51.0 59.0 76.7
N 10787 4415 6372 5438 2468 792 881 720 337
Table 5.20: Hemoglobin Level - Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe deficiency (<7 gm/dL) 2.3
1.6 2.6
1.0 5.3 2.0 1.4 0.0 0.0
Moderate deficiency (7 - 10.99 gm/dL)
48.7
48.7 48.7
48.3 54.4 28.2 48.3 43.0 33.6
Normal (>= 11 gm/dL) 49.0
49.7 48.7
50.6 40.3 69.8 50.3 57.0 66.4
N 1363 497 866 731 397 67 63 77 25
Table 5.21: Ferritin Level - Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Low Ferritin (<12 ng/mL) 28.0
27.6 28.2
28.7 31.9 16.3 22.9 25.8 17.4
Normal (>=12 ng/mL) 72.0
72.4 71.8
71.3 68.1 83.7 77.1 74.2 82.6
N 9143 3533 5610 4649 2279 741 590 471 353
88
Table 5.22: Ferritin Level - Non Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Low Ferritin (<12 ng/mL) 26.8
26.8 26.8
27.3 31.5 15.6 21.8 25.2 14.9
Normal (>=12 ng/mL) 73.2
73.2 73.2
72.7 68.5 84.4 78.2 74.8 85.1
N 8092 3158 4934 4080 1955 696 547 427 327
Table 5.23: Ferritin Level - Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Low Ferritin (<12 ng/mL) 37.0
34.1 38.1
39.2 34.5 27.0 37.1 31.6 45.7
Normal (>=12 ng/mL) 63.0
65.9 61.9
60.8 65.5 73.0 62.9 68.4 54.3
N 1051 375 676 569 324 45 43 44 26
89
Table 5.24: Vitamin A Deficiency - Mothers
(Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe (<0.35 µmol/L) 17.2
11.5 19.6
18.4 10.5 32.4 21.6 1.1 8.7
Mild (0.35 - 0.70 µmol/L) 25.3
24.2 25.8
23.4 26.6 34.0 33.3 14.5 30.4
Non deficient (>0.70 µmol/L) 57.5
64.3 54.6
58.2 63.0 33.6 45.0 84.5 60.8
N 9052 3554 5498 4673 2260 633 623 471 339
Table 5.25: Vitamin A Deficiency - Non-Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe (<0.35 µmol/L) 17.0
10.9 19.6
18.2 9.7 32.2 21.3 0.8 7.8
Mild (0.35 - 0.70 µmol/L) 25.1
24.0 25.5
23.3 25.7 33.5 33.2 12.9 30.9
Non deficient (>0.70 µmol/L) 58.0
65.1 54.9
58.5 64.5 34.2 45.5 86.3 61.2
N 8001 3166 4835 4096 1943 593 577 424 315
Table 5.26: Vitamin A Deficiency - Pregnant Mothers
(Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe (<0.35 µmol/L) 18.7
16.1 19.7
19.6 15.1 35.5 26.1 3.3 20.0
Mild (0.35 - 0.70 µmol/L) 27.3
25.4 28.1
24.1 31.6 40.7 34.6 28.9 24.1
Non deficient (>0.70 µmol/L) 54.0
58.4 52.2
56.4 53.3 23.8 39.3 67.8 55.9
N 1051 388 663 577 317 40 46 47 24
90
Table 5.27: Zinc Deficiency - Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Deficient (<60 µg/dL) 42.1
39.2 43.3
41.1 39.3 48.6 43.7 67.9 62.9
Non-Deficient (60 - 150 µg/dL) 57.9
60.8 56.7
58.9 60.7 51.4 56.3 32.1 37.1
N 8453 3365 5088 4266 2222 468 614 470 353
Table 5.28: Zinc Deficiency - Non Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Deficient (<60 µg/dL) 41.3
38.2 42.7
40.2 38.5 48.3 43.7 64.8 63.7
Non-Deficient (60 - 150 µg/dL) 58.7
61.8 57.3
59.8 61.5 51.7 56.3 35.2 36.3
N 7459 3003 4456 3740 1903 437 569 423 327
Table 5.29: Zinc Deficiency - Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Deficient (<60 µg/dL) 47.6
47.4 47.7
47.3 44.5 52.6 43.6 95.8 54.4
Non-Deficient (60 - 150 µg/dL) 52.4
52.6 52.3
52.7 55.5 47.4 56.4 4.2 45.6
N 994 362 632 526 319 31 45 47 26
91
Table 5.30: Vitamin D Deficiency - Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe Deficiency (<8.0 ng/mL) 23.2
33.2 19.1
24.9 24.2 14.3 16.6 22.4 21.5
Deficiency (8.0 - 20.0 ng/mL) 43.8
39.4 45.7
42.1 46.4 46.9 37.2 50.9 59.0
Desirable (>20.0 - 30.0 ng/mL) 18.6
14.8 20.2
17.8 16.8 25.2 25.7 19.1 11.1
Sufficient (>30.0 ng/mL) 14.4
12.6 15.1
15.2 12.6 13.6 20.5 7.6 8.4
N 9711 3829 5882 5095 2326 843 609 476 304
Table 5.31: Vitamin D Deficiency - Non-Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe Deficiency (<8.0 ng/mL) 23.0
33.2 18.6
24.4 24.7 14.0 16.3 22.5 19.2
Deficiency (8.0 - 20.0 ng/mL) 43.8
39.3 45.7
42.0 46.5 47.0 38.3 50.8 61.7
Desirable (>20.0 - 30.0 ng/mL) 18.7
14.7 20.5
17.8 16.9 25.4 25.6 19.9 10.1
Sufficient (>30.0 ng/mL) 14.5
12.8 15.2
15.8 11.8 13.7 19.8 6.8 9.0
N 8578 3412 5166 4464 1995 788 563 430 280
Table 5.32: Vitamin D Deficiency - Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe Deficiency (<8.0 ng/mL) 25.3
33.8 22.1
28.2 20.8 17.9 20.5 21.5 44.4
Deficiency (8.0 - 20.0 ng/mL) 43.6
39.7 45.1
42.9 46.1 45.9 23.1 51.9 31.7
Desirable (>20.0 - 30.0 ng/mL) 17.6
15.3 18.4
17.6 16.1 23.3 26.7 11.2 21.1
Sufficient (>30.0 ng/mL) 13.5
11.2 14.4
11.3 17.0 13.0 29.7 15.5 2.8
N 1133 417 716 631 331 55 46 46 24
92
Table 5.33: Calcium Deficiency - Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Hypocalcaemia (<8.4 mg/dL) 52.9
52.9 53.0
53.1 45.4 73.6 63.4 8.7 46.7
Normocalcaemia (8.4 - 10.2 mg/dL) 38.3
38.5 38.2
35.9 48.1 20.6 35.5 84.0 52.3
Hypercalcaemia (>10.2 mg/dL) 8.8
8.7 8.8
11.0 6.5 5.8 1.1 7.3 1.1
N 9672 3793 5879 4940 2263 983 598 485 350
Table 5.34: Calcium Deficiency - Non Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Hypocalcaemia (<8.4 mg/dL) 52.1
51.8 52.3
51.7 44.6 74.0 63.1 8.2 44.5
Normocalcaemia (8.4 - 10.2 mg/dL) 39.0
39.4 38.8
36.9 49.2 20.1 35.9 83.7 54.4
Hypercalcaemia (>10.2 mg/dL) 8.9
8.8 9.0
11.4 6.2 6.0 1.0 8.1 1.1
N 8549 3377 5172 4324 1935 922 554 437 324
Table 5.35: Calcium Deficiency - Pregnant Mothers (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Hypocalcaemia (<8.4 mg/dL) 58.9
61.5 57.9
63.2 50.3 67.6 67.4 13.3 71.3
Normocalcaemia (8.4 - 10.2 mg/dL) 33.5
30.8 34.6
28.5 41.6 29.4 30.4 86.2 28.7
Hypercalcaemia (>10.2 mg/dL) 7.6
7.7 7.6
8.3 8.1 2.9 2.2 0.5 0.0
N 1123 416 707 616 328 61 44 48 26
93
Table 6.1: Households with Children Under 5 Years (Percent)
Number of Children Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
None 25.6
32.5 22.4
27.5 28.0 27.5 14.7 0.8 0.2 3.8
1 40.1
37.1 41.5
36.0 38.0 46.4 46.3 78.2 54.6 47.7
2 26.2
23.1 27.6
26.9 25.7 23.4 27.9 18.1 36.7 34.5
3 6.4
5.5 6.8
7.2 7.0 2.6 7.9 2.8 6.5 9.1
4+ 1.8
1.8 1.7
2.3 1.3 0.1 3.2 0.1 1.9 4.9
N 27963 11496 16467 13188 6282 3626 1996 900 1303 668
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 6.2: Sex and Age Distribution of Children Under 5 Years of age (Percent)
Characteristics Pakistan Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Sex
Male 51.1
50.8 51.2
51.2 50.0 51.3 50.4 57.9 50.1 51.6
Female 48.9
49.2 48.8
48.8 50.0 48.7 49.6 42.1 49.9 48.4
Age (month)
< 6 months 8.5
9.1 8.2
8.9 8.3 7.9 7.8 4.0 9.5 8.5
6-11 months 10.1
10.3 10.0
10.9 10.8 7.2 9.9 1.2 11.0 10.0
12-23 months 16.1
18.7 15.1
18.2 15.0 10.7 14.9 6.8 19.1 17.5
24-35 months 20.1
20.3 20.1
20.3 19.6 21.7 18.2 18.9 19.5 18.9
36-47 months 20.9
20.0 21.2
19.8 20.5 23.1 21.5 34.8 19.6 19.4
48-59 months 24.3
21.6 25.4
21.8 25.8 29.4 27.7 34.3 21.3 25.7
N 34073
13162 20911
15990 7396 3582 2833 1102 2068 1102
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
94
Table 6.3: Anthropometry of All Children under 5 years (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Height for Age – Stunted
Severe Stunting (-6 to -3) 21.9 16.4 24.0 17.9 27.7 24.5 31.1 33.8 11.8 26.0
Moderate Stunting (-2.99 to -2) 21.8 20.5 22.3 21.3 22.1 23.3 21.1 23.8 19.9 24.6
Mild Stunting (-1.99 to -1) 24.4 26.4 23.5 26.4 22.6 19.7 19.1 21.1 30.0 24.5
Normal (>-1 to +6) 32.0 36.7 30.2 34.3 27.6 32.5 28.7 21.3 38.3 24.9
N 28825 11090 17735 13378 6605 2962 2142 805 1946 987
Weight for Height – Wasted
Severe Wasting (-5 to -3) 5.8 4.7 6.3 4.8 6.6 8.7 7.0 5.8 6.9 2.7
Moderate Wasting (-2.99 to -2) 9.3 8.0 9.8 8.9 10.9 8.6 9.1 4.2 10.7 4.1
Mild Wasting (-1.99 to -1) 22.1 22.7 21.9 23.4 26.1 12.8 18.5 6.3 23.8 12.7
Normal (>-1 to +5) 62.8 64.7 62.0 62.9 56.4 69.9 65.5 83.7 58.5 80.5
N 28312 10919 17393 13210 6553 2826 2102 717 1920 984
Weight for Age - Under weight
Severely under-Weight (-6 to -3) 11.6 8.4 12.8 9.9 16.3 10.1 17.8 7.2 6.1 8.1
Moderate Under-Weight (-2.99 to -2)
19.9 18.2 20.5 19.9 24.2 14.0 21.8 6.5 19.7 18.1
Mild Under-Weight (-1.99 to 0) 29.7 30.8 29.4 31.9 30.7 23.6 24.8 11.7 34.1 33.0
Normal (>0 to +5) 38.8 42.5 37.3 38.3 28.8 52.4 35.6 74.7 40.1 40.9
N 29525 11257 18268 13532 6707 3113 2277 941 1956 999
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
95
Table 6.4: Factors Associated with Stunting (<-2 SD) (Percent)
Characteristics N Stunted
Normal Severe Moderate Mild
Age
< 6 months 2173 11.0 12.8 20.5 55.7
6-11 months 2886 14.8 15.5 22.6 47.1
12-23 months 4172 24.7 23.2 25.3 26.8
24-35 months 3874 30.1 24.6 22.3 23.0
36-47 months 2935 25.2 27.1 22.4 25.3
48-59 months 3042 17.8 20.6 26.6 35.0
Sex
Male 9949 23.9 20.3 23.8 31.9
Female 9133 19.4 22.4 23.1 35.1
Age Groups
0-23 months 9231 18.3 18.3 23.3 40.0
24-59 months 9851 24.9 24.1 23.6 27.4
Mother's Education
Illiterate 10726 26.6 21.6 21.7 30.1
1-5 2347 19.1 22.6 26.3 31.9
6-8 1625 17.1 26.8 24.2 31.9
9-10 2044 11.5 19.4 26.9 42.2
Above Matric. 1817 8.5 13.9 26.2 51.4
Diarrhea in last two weeks
Yes 4233 21.6 21.7 24.5 32.1
Wealth Quintiles
Quintile I 4121 31.4 22.6 19.3 26.7
Quintile II 4033 25.8 23.9 22.3 28.0
Quintile III 3866 20.5 21.9 24.9 32.7
Quintile IV 3697 15.9 20.7 25.9 37.6
Quintile V 3365 10.7 15.8 26.4 47.1
96
Table 6.5: Factors Associated with Wasting (<-2SD) (Percent)
Characteristics N Wasted
Normal Severe Moderate Mild
Age
< 6 months 2045 12.5 13.8 18.0 55.7
6-11 months 2828 9.8 13.4 22.1 54.6
12-23 months 4161 6.3 9.5 21.3 62.9
24-35 months 3824 6.1 8.4 20.8 64.6
36-47 months 2869 4.3 6.9 20.4 68.5
48-59 months 2918 4.8 9.1 23.8 62.3
Sex
Male 9667 7.2 10.5 20.9 61.4
Female 8978 6.6 9.2 21.6 62.6
Age Groups
0-23 months 9034 8.8 11.7 20.8 58.7
24-59 months 9611 5.2 8.2 21.6 65.1
Mother's Education
Illiterate 10426 8.1 11.0 21.4 59.5
1-5 2318 5.8 9.1 22.8 62.2
6-8 1601 4.9 8.6 20.2 66.3
9-10 2007 6.4 7.9 21.0 64.8
Above Matric. 1790 4.0 7.4 20.2 68.4
Diarrhea in last two weeks
Yes 4179 7.3 11.9 22.5 58.3
Wealth Quintiles
Quintile I 4013 9.5 12.3 22.5 55.7
Quintile II 3911 7.0 9.6 18.1 65.2
Quintile III 3775 6.7 9.4 22.3 61.6
Quintile IV 3633 5.8 10.1 21.8 62.3
Quintile V 3313 4.7 7.0 21.6 66.7
97
Table 6.6: Factors Associated with Under Weight (<-2 SD) (Percent)
Characteristics N Under Weight
Normal Severe Moderate Mild
Age
< 6 months 2233 12.6 16.4 25.8 45.2
6-11 months 2966 14.2 19.1 26.2 40.5
12-23 months 4308 12.7 19.4 29.5 38.4
24-35 months 3992 14.6 20.7 29.2 35.6
36-47 months 3023 10.4 18.2 27.1 44.3
48-59 months 3099 8.3 18.8 29.9 43.0
Sex
Male 10254 13.2 19.3 27.7 39.8
Female 9367 11.2 18.7 28.7 41.4
Age Groups
0-23 months 9507 13.1 18.6 27.6 40.7
24-59 months 10114 11.4 19.4 28.8 40.4
Mother's Education
Illiterate 11127 15.5 21.0 27.8 35.7
1-5 2381 9.8 21.2 31.0 38.0
6-8 1661 8.0 15.8 28.7 47.5
9-10 2068 6.5 14.4 31.4 47.7
Above Matric. 1841 5.0 11.7 25.0 58.3
Diarrhea in last two weeks
Yes 4305 15.3 21.4 30.1 33.1
Wealth Quintile
Quintile I 4263 20.5 23.5 26.3 29.8
Quintile II 4198 12.5 18.5 27.1 42.0
Quintile III 3992 11.2 19.7 29.6 39.5
Quintile IV 3754 8.0 19.1 31.4 41.5
Quintile V 3414 6.2 12.2 27.0 54.6
98
Biochemical assessments data from FATA has not been presented due to low number of specimens collected (Table 6.7 – 6.11).
Table 6.7: Hemoglobin Level - Index Child (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe deficiency (<7 gm/dL) 5.0
3.6 5.5
4.2 4.9 6.8 8.3 1.8 0.6
Moderate deficiency (7 - 10.99 gm/dL)
56.9
59.3 55.9
56.1 67.6 40.5 48.5 44.2 40.4
Normal (>= 11 gm/dL) 38.1
37.0 38.6
39.7 27.5 52.7 43.2 54.1 59.1
N 11786 4731 7055 6116 2851 794 752 800 363
Table 6.8: Ferritin Level - Index Child (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Low Ferritin (<12 ng/mL) 43.8
46.1 42.9
48.6 40.6 26.4 32.5 43.5 36.2
Normal (>=12 ng/mL) 56.2
53.9 57.1
51.4 59.4 73.6 67.5 56.5 63.8
N 8575 3297 5278 4449 2122 661 459 484 344
Table 6.9: Vitamin A Deficiency - Index Child (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe (<0.35 µmol/L) 20.9
14.6 23.5
19.1 18.8 33.9 38.0 7.1 27.2
Mild (0.35 - 0.70 µmol/L) 33.1
32.3 33.4
31.9 34.5 34.6 35.5 36.7 44.6
Non deficient (>0.70 µmol/L) 46.0
53.1 43.1
48.9 46.8 31.5 26.5 56.2 28.2
N 8634 3303 5331 4437 2204 678 438 491 333
Table 6.10: Zinc Deficiency - Index Child (Percent)
99
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Deficient (<60 µg/dL) 39.2
39.3 39.1
38.4 38.6 45.4 39.5 47.2 32.6
Non-Deficient (>=60 µg/dL) 60.8
60.7 60.9
61.6 61.4 54.6 60.5 52.8 67.4
N 8503 3274 5229 4358 2187 690 414 452 345
Table 6.11: Vitamin D Deficiency - Index Child (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan AJK GB
Severe Deficiency (<8.0 ng/mL) 9.2
14 7.2
9.3 10.7 5.9 9.1 4.1 4.1
Deficiency (8.0 - 20.0 ng/mL) 30.8
31.9 30.4
31.0 32.6 23.0 34.3 30.5 32.9
Desirable (>20.0 - 30.0 ng/mL) 27.3
22.2 29.4
27.2 25.4 31.4 23.6 35.3 36.0
Sufficient (>30.0 ng/mL) 32.7
31.9 33.0
32.6 31.3 39.6 33.1 30.0 26.9
N 8608 3324 5284 4337 2203 709 539 467 297
Table 6.13: Clinical Examination Children
(Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Clinical Examination
Edema 0.4
0.2 0.4
0.2 0.1 1.3 1.2 0.1 0.2 0.0
Jaundice 0.4
0.4 0.4
0.4 0.4 0.4 0.9 0.7 0.1 0.0
Pallor / Anemia 22.8
17.6 24.9
27.4 28.9 3.4 13.1 4.5 31.7 15.0
Goiter 0.2
0.1 0.3
0.3 0.2 0.2 0.2 0.4 0.2 0.0
Bitot's Spot 0.2
0.1 0.3
0.0 0.1 0.1 0.8 3.8 0.1 0.0
N 20537 7929 12608 9174 4409 2458 1677 888 1292 639
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 6.16: Morbidities (Index Child)
(Percent)
100
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
ARI by Information
Pneumonia 5.4
6.4 5.0
5.1 9.6 1.7 2.8 2.7 5.2 4.1
Severe Pneumonia 1.4
1.5 1.3
1.4 2.1 0.4 1.0 0.6 0.2 2.3
Only cough 15.9
18.3 15.0
19.0 18.1 4.4 11.7 2.5 26.0 13.4
N 20435 7899 12536 9127 4401 2431 1673 875 1291 637
ARI by Observation
Pneumonia 4.9
5.3 4.8
3.5 8.9 3.5 4.4 7.9 3.2 1.5
Severe Pneumonia 1.0
1.1 1.0
1.0 2.0 0.1 0.4 0.7 0.2 0.8
Only cough 12.1
14.6 11.2
12.7 17.2 4.3 7.7 4.6 18.2 9.0
N 20278 7853 12425 9090 4392 2427 1670 773 1291 635
Diarrhea in Past 2 Weeks 22.3
23.2 22.0
28.5 23.4 4.3 12.9 6.4 26.2 28.5
N 20383 7883 12500 9118 4390 2428 1663 861 1287 636
Current Diarrhea 12.0
11.6 12.1
15.6 11.7 2.6 8.0 2.4 11.2 19.2
N 20280 7866 12414 9110 4391 2423 1660 770 1289 637
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
101
Table 7.1: Initiation of Breast Feeding and Practicing Pre-Lacteal Feed (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
How long after birth did you first put to the breast?
Immediately after birth 24.6
21.4 25.9
16.3 32.5 46.1 48.1 31.9 12.4 23.5
Within 1 hour 15.9
17.0 15.5
11.8 18.0 28.2 15.3 47.6 25.9 38.3
1-12 hours 27.6
32.5 25.4
26.3 32.2 22.8 25.5 16.6 35.1 33.2
13-24 hours 0.5
0.8 0.4
0.5 0.5 0.3 0.7 0.1 0.4
> 24 hours 31.4
28.3 32.8
45.1 16.7 2.5 10.4 4.0 26.5 4.6
N 9562 3875 5687 4738 2144 852 735 88 678 327
What was the first thing the child was fed directly after birth?
Honey 41.0
52.6 35.9
54.1 22.5 16.0 28.6 23.5 43.2 4.4
Breast milk 28.2
23.6 30.2
9.0 58.2 61.0 48.7 33.4 23.5 51.7
Water (Plain/Flavored/Sugar Added)
9.5
7.1 10.6
13.0 2.6 5.7 6.5 19.4 6.3 25.0
Fresh Animal Milk 5.5
1.6 7.3
6.6 5.6 0.0 0.2 0.0 11.7 0.6
Commercial Formula/Liquid Milk 3.9
4.5 3.6
3.8 5.5 1.1 1.6 0.8 6.3 1.6
Commercial Ghutti 3.5
3.7 3.4
5.2 1.5 0.3 0.2 3.4 1.6 0.0
Tea 2.0
2.2 1.9
0.6 1.5 10.4 7.0 0.0 0.5 0.0
Gurr (Jaggery) 1.7
0.5 2.2
2.6 0.5 0.0 0.2 0.0 0.0 0.0
Others 4.7
4.4 4.9
5.0 2.0 5.5 7.0 19.6 6.8 16.7
N 9685 3929 5756 4825 2166 819 746 98 705 326
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
102
Table 7.2: Exclusive Breast Feeding (recall of mothers) (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Upto 1 month 45.8
48.5 44.6
31.2 61.4 83.3 76.7 86.1 23.7 49.0
n 9772
3962 5810
4837 2181 857 770 99 697 331
Upto 2 months 30.9
31.4 30.6
20.0 40.9 65.7 50.2 72.5 12.8 33.3
n 9259
3783 5476
4634 2035 791 741 97 648 313
Upto 3 months 25.3
27.0 24.5
16.3 30.4 59.6 45.4 60.8 10.2 30.7
n 8662
3567 5095
4350 1903 732 689 88 614 286
Upto 4 months 20.9
22.1 20.4
12.9 23.5 55.5 42.0 52.2 7.5 25.7
n 8355
3423 4932
4200 1833 698 674 87 590 273
Upto 5 months 16.3
16.1 16.4
9.9 16.3 50.3 33.1 44.2 5.7 17.8
n 7658
3155 4503
3860 1664 638 606 82 553 255
Upto 6 months 12.9
12.7 13.0
7.7 9.6 47.0 26.8 42.0 4.3 14.5
n 7349 3017 4332 3704 1596 609 595 82 526 237
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
103
Table 7.3: IYCF Indicators
(Percent)
Residence Province / Region
Pakistan Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Predominant Breastfeeding under 6 months
63.5
57.5 66.4
56.9 67.3 87.1 62.1 35.6 61.7 64.7
N 2299
924 1375
1083 587 252 158 6 128 85 Predominant Breastfeeding under 4 months
69.8 64.3 72.4 63.0 75.4 89.4 72.2 48.3 63.3 79.2
N 1391 556 835 647 351 164 89 5 86 49 Continued Breast Feeding 12-15 months
77.3
72.3 79.6
73.3 84.4 87.4 72.3 43.4 74.5 91.9
N 1616
666 950
731 375 179 140 30 103 58 Introduction of Semi-Solid (6-8 months)
51.3
68.4 44.7
49.2 62.6 35.3 48.6 55.2 35.7 51.3
N 1591
620 971
780 402 148 130 93 38 1591 Minimum Dietary Diversity (6-23 months)
3.0
5.6 1.9
2.6 3.2 2.7 2.1 23.6 6.9 5.1
N 6909
2800 4109
3431 1621 604 543 59 429 222 Minimum Meal Frequency (6-23 months)
56.4
65.4 52.4
59.4 54.1 45.0 53.3 68.8 60.7 30.4
N 6909
2800 4109
3431 1621 604 543 59 429 222 Minimum Acceptable Diet (6-23 months)
7.3
11.2 5.6
7.6 5.8 5.6 5.1 36.6 15.1 3.9
N 6909
2800 4109
3431 1621 604 543 59 429 222 Continued Breastfeeding at 2 years 54.3
50.4 56.5
50.9 66.8 58.3 42.9 46.3 48.1 62.8
N 753
351 402
433 131 55 49 6 52 27 Age-appropriate Breastfeeding Children (0-23 months)
63.6
62.7 64.0
60.5 72.4 63.5 54.3 40.0 65.9 75.3
N 9083
3665 5418
4457 2179 842 697 65 548 295 `
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
104
Table 8.1: Proportion of children below 2 years consumed food items of the listed food groups (based on 24 hour recall)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Breast Milk 80.9
77 82.6
77.6 86.9 90.1 73.9 46.8 79.6 92.2
Grains, roots and tubers 58.2
63.6 55.7
57.6 65.1 41.7 59.6 86.8 59.5 52.4
Legumes and nuts 5.3
7.1 4.5
4.2 7.5 5.4 6.2 6.2 6.5 5.2
Dairy Products(milk, yogurt, cheese) 48.2
51.9 46.5
57.7 38.2 22.2 32.6 62.7 58.2 42.1
Flesh foods (meat, fish, poultry and liver/organ meats)
2.7
3.4 2.4
2.3 2.3 1.7 5.1 30.1 5.6 3.1
Eggs 5.8
10 3.9
4.8 5.1 11.8 3.4 13.8 9.6 15.1
Vitamin -A rich fruits and Vegetables 1.7
1.9 1.5
1.9 0.9 1 1.3 11.3 2.4 7.6
Other fruits and Vegetables 9.4
13.3 7.6
8.5 8.3 11.2 11.4 32.3 20 8.4
N 9083
3665 5418
4457 2179 842 697 65 548 295
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 8.2: Average Frequency of daily intake of food groups (0-23 months children)
Pakistan
Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
Breast Milk 7.4
7.0 7.5
6.3 10.0 8.3 6.6 3.5 6.2 5.9
Grains, roots and tubers 1.3
1.4 1.2
1.2 1.5 0.8 1.3 1.5 1.4 1.1
Legumes and nuts 0.0
0.0 0.0
0.0 0.1 0.0 0.0 0.0 0.1 0.0
Dairy Products (milk, yogurt, cheese) 1.5
1.7 1.4
1.9 1.0 0.6 0.9 0.8 1.9 0.9
Flesh foods (meat, fish, poultry and liver/organ meats)
0.1
0.1 0.0
0.1 0.1 0.0 0.2 0.1 0.1 0.1
Eggs 0.1
0.2 0.1
0.1 0.1 0.2 0.1 0.3 0.1 0.2
Vitamin A rich fruits and vegetables 0.0
0.0 0.0
0.0 0.0 0.0 0.0 0.2 0.0 0.1
Other fruits and vegetables 0.3
0.4 0.2
0.3 0.3 0.2 0.2 0.5 0.5 0.2
N 9019
3647 5372
4441 2168 841 680 55 548 286
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
105
Table 8.3 Average Frequency of daily intake of food groups (0-24 months children)
< 6 months
6-11 months
12-23 months
Breast Milk 10.39 8.31 5.10 Grains, roots and tubers 0.11 1.02 2.06 Legumes and nuts 0.01 0.05 0.03 Dairy Products (milk, yogurt, cheese)
0.95 1.41 1.84
Flesh foods (meat, fish, poultry and liver/ organ meats)
0.00 0.03 0.11
Eggs 0.01 0.08 0.20 Vitamin A rich fruits and vegetables 0.00 0.01 0.06 Other fruits and vegetables 0.02 0.18 0.49 N 2150 2804 4065
Table 8.4: Proportion of mothers of children below 2 years who consumed food items of the listed food groups (based on 24 hour recall)
Pakistan
Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
Grains (Wheat/Rice) 99.5
99.6 99.4
99.6 99.9 99.5 99.9 94.4 99.8 99.6
Tuber & Roots 29.2
25.7 30.7
26.8 41.5 21.5 31.1 12.1 27 11.9
Legumes and nuts 29.8
34.9 27.7
32.1 27 27.5 32.4 25.8 37.5 23.2
Dairy Products(milk, yogurt, cheese) 41.6
39.2 42.7
50.3 40.2 24.2 28.5 48.8 32.8 37.4
Flesh foods (meat, fish, poultry and liver/organ meats)
30.6
39.4 26.8
28.7 28 33.2 39.6 47.8 31.4 16.5
Eggs 10.4
16.3 7.8
9.5 7.2 17.4 8 13.1 10.6 10.4
Vitamin -A rich fruits and Vegetables 13.5
14.5 13.1
12.9 10.2 16.9 13.8 21.6 15.9 52.8
Other fruits and Vegetables 51.4
52.8 50.7
59.3 37.3 51.3 49.9 46.7 60.8 52.4
N 19808
7816 11992
8005 5028 3042 1608 891 823 411
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
106
Table 8.5: Average Frequency of daily intake of food groups (Mothers of children)
Pakistan
Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
Grains, roots and tubers 3.2
3.1 3.2
3.2 3 3.4 2.9 3.1 3.5 3.7
Legumes and nuts 0
0.1 0
0 0 0.1 0 0.1 0 0
Dairy Products(milk, yogurt, cheese) 1.1
1 1.1
1 0.8 1.5 0.8 1.8 0.4 0.5
Flesh foods (meat, fish, poultry and liver/organ meats)
0.3
0.4 0.3
0.3 0.3 0.3 0.5 0.4 0.3 0.4
Eggs 0.3
0.4 0.3
0.3 0.2 0.6 0.3 0.6 0.2 0.3
Vitamin A rich fruits and vegetables 0.3
0.2 0.3
0.2 0.3 0.5 0.3 0.5 0.2 0.9
Other fruits and vegetables 0.9
1 0.8
0.9 0.7 0.9 0.8 1 1 1.1
N 19575
7805 11770
7995 5014 2940 1623 771 821 411
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
107
Table 9.1: Elderly Persons by Gender (Percent)
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KP Balochistan FATA* AJK GB
Gender
Male 30.4
28.6 31.2
30.6 28.3 29.0 27.3 80.4 32.2 39.0
Female 69.6
71.4 68.8
69.4 71.7 71.0 72.7 19.6 67.8 61.0
N 7612 3135 4477 4289 1118 1053 417 83 392 260
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
Table 9.2: Age distribution of Elderly Persons (Percent)
Age Pakistan Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
50-59 years 42.4
46.3 40.6
38.0 43.4 57.9 51.2 86.4 34.5 40.8
60-69 years 35.2
34.4 35.5
36.2 38.2 28.8 32.7 9.3 37.2 36.4
70-79 years 15.2
13.4 16.0
17.4 12.9 9.5 10.3 4.3 17.4 12.7
80+ years 7.3
5.9 7.9
8.4 5.6 3.9 5.8 0.0 10.9 10.1
N 7612
3135 4477
4289 1118 1053 417 83 392 260
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
108
Table 9.3: Body Mass Index of Elderly Persons (Percent)
Age Pakistan Residence
Province / Region
Urban Rural
Punjab Sindh KP Balochistan FATA* AJK GB
<16 4.7
2.5 5.7
5.1 5.7 2.4 4.7 0.0 5.4 2.3
16-16.99 3.4 1.6 4.2 3.6 4.0 1.2 5.7 0.0 5.7 1.6
17-18.49 7.7 4.0 9.4 8.4 7.7 3.9 9.2 0.0 9.9 11.9
18.5-24.99 46.1 37.5 49.8 46.3 46.2 42.8 48.2 19.3 51.9 61.6
25-29.99 24.2 31.4 21.1 23.8 22.1 30.4 19.4 47.4 19.1 18.3
30-34.99 10.1
16.2 7.4
9.2 11.2 13.9 8.8 27.4 5.9 3.3
35-39.99 2.8
4.8 1.9
2.6 2.3 4.5 1.7 5.9 1.8 0.3
>=40 1.0
2.0 0.6
1.1 0.8 0.9 2.4 0.0 0.1 0.7
N 6700
2717 3983
3776 1048 924 294 30 378 250
* Data from FATA are not representative due to high non-response rate and must be interpreted with caution.
109
SAMPLE DESIGN &SAMPLING WEIGHT
SAMPLE ESTIMATION PROCEDURE
ESTIMATION PROCEDURE ADOPTED FOR NNS 2011
NOTATIONS:
Nh = Total number of Primary Sampling Units (PSUs) in the hth stratum ofBalochistan province.
nh = Total number of sample PSUs in the hth stratum of Balochistanprovince.
Mhi = Total number of Secondary Sampling Units (SSUs) in the ith samplePSU of hth stratum of Balochistan province.
mhi = Number of sample SSUs in the ith sample PSU of hth stratum ofBalochistan province.
Phi = Assigned probability of selection of ith PSU of the hth stratum ofBalochistan province.
yhij = Value of any characteristic y of jth SSU within ith PSU of hth stratumof Balochistan province.
xhij = Value of any characteristic x of jth SSU within ith PSU of hth stratum
110
(i): ESTIMATION FORMULAE FOR TOTALS AND THEIR VARIANCES
N = Nh=1
L
h
n = nh=1
L
h
h
h i=1
nhi
hi
Y = 1
n
Y
p
h
OR
For X, another variable of interest, we have
h
h i=1
n
hi
hi
hi j=1
m
hijY = 1
n
1
p
M
m y
h hi
Y = Y1
n
Y
ph=1
L
h
h=1
L
h i=1
nhi
hi
= h
h
h i=1
nhi
hi h i=1
n
hi
hi
hi j=1
m
hijX = 1
n
X
P =
1
n
1
P
M
m x
h h hi
X = X = 1
n
X
ph=1
L
h
h=1
L
h i=1
nhi
hi
h
111
R =
Y
X
(ii): FORMULA FOR RATIO ESTIMATES
r = Y
X
where Y^ and X^ can be estimated by equations under item (i) given above.
Rel V(r) =
1
X
1
ns +
1
x
1
n
M
p m
M - m
Ms2
h=1
L
h
hb2
2h=1
L
h i=1
nhi
2
hi
2hi
hi hi
hi
hw2
h
h
h
n
i h
n
i hi
hi
hi
hiL
h
L
h hh
ht
h n
P
y
P
Y
nns
nYv
1
1
2
2
2
1 1
2
)ˆ
(ˆ
)1(
11)ˆ(
112
ALLOCATION PLAN FOR NATIONAL NUTRITION SURVEY 2010-11(AGHA KHAN UNIVERSITY)
SL.NO.
NO. OF SAMPLE PSUS
STRATUM
LARGE SIZE CITIES Other
Urban
Total
Urban Rural
Urban
+Rural LOW MIDDLE HIGH TOTAL
1 2 3 4 5 6 7 8 9 10
PUNJAB 41 92 28 161 146 307 375 682
1 ISLAMABAD 4 10 6 20 0 20 10 30
1.RAWALPINDI DIVISION 3 8 3 14 15 29 31 60
1 Attock 4 4 7
2 Rawalpindi 3 8 3 14 5 19 11
3 Jhelum 4 4 6
4 Chakwal 2 2 7
2.SARGODHA DIVISION 3 3 0 6 13 19 32 51
1 Sargodha 3 3 0 6 4 10 13
2 Bhakkar 3 3 6
3 Khushab 3 3 6
4 Mianwali 3 3 7
3.FAISALABAD DIVISION 10 14 4 28 19 47 50 97
1 Faisalabad 10 14 4 28 5 33 22
2 Jhang 6 6 11
3 T.T.Singh 4 4 10
4 Chiniot 4 4 7
4.GUJRANWALA DIVISION 6 11 5 22 24 46 57 103
113
1 Gujranwala 4 8 3 15 5 20 12
2 Gujrat 6 6 11
3 Sialkot 2 3 2 7 4 11 13
4 Hafiza Abad 3 3 6
5 Mandibahauudn 3 3 7
6 Narowal 3 3 8
5.LAHORE DIVISION 7 34 5 46 19 65 38 103
1 Lahore 7 34 5 46 2 51 8
2 Kasur 6 6 12
3 Sheikhupura 8 8 10
4 Nankana 3 3 8
6.MULTAN DIVISION 5 7 3 15 14 29 45 74
1 Vehari 4 4 13
2 Multan 5 7 3 15 2 17 13
3 Khanewal 5 5 12
4 Lodhran 3 3 7
7.DERA GHAZI KHAN DIVISION 12 12 40 52
1 D.G.Khan 4 4 9
2 Rajanpur 4 4 7
3 Leiah 4 4 7
4 Muzaffargarh 17
8.BAHAWALPUR DIVISION 3 5 2 10 16 26 42 68
1 Bahawalpur 3 5 2 10 4 14 12
2 Bahawalnagar 5 5 12
3 R. Y. Khan 7 7 18
114
9.SAHIWAL DIVISION 14 14 30 44
1 Sahiwal 4 4 10
2 Pakpattan 4 4 8
3 Okara 6 6 12
S I N D H 33 64 15 112 45 157 166 323
1.SUKKUR DIVISION 3 5 0 8 11 19 40 59
1 Khairpur 3 3 10
2 Sukkur 3 5 0 8 2 10 5
3 Nawab Shah 2 2 8
4 NesheroFeroz 2 2 8
5 Ghotki 2 2 9
2.LARKANA DIVISION 11 11 34 45
1 Jacobabad 2 2 6
2 Kashmore 2 2 6
3 Shikarpur 2 2 7
4 Larkana 3 3 7
5 ShahdadKot 2 2 8
3.HYDERABAD DIVISION 4 8 3 15 11 26 53 79
1 Dadu 2 2 8
2 Jamshoro 1 1 5
3 Hyderabad 4 8 3 15 1 16 6
4 Matiari 1 1 5
5 TandoAllahyar 1 1 5
6 Tando Mohammad Khan 1 1 6
115
7 Badin 2 2 8
8 Thatta 2 2 10
4 MIRPUR KHAS DIVISION 12 12 33 45
1 Sanghar 5 5 10
2 MirpurKhas 4 4 8
3 Tharparkar 0 0 8
4 UmerKot 3 3 7
5.KARACHI DIVISION 26 51 12 89 0 89 6 95
1 Karachi South 0 0 0
2 Karachi West 0 0 3
3 Karachi Central 0 0 0
4 Karachi Malir 0 0 3
5 Karachi East 0 0 0
KHYBER/PK 2 13 3 18 49 67 151 218
1.MALAKAND DIVISION 7 7 39 46
1 Swat 2 2 10
2 Upper Dir 0 0 6
3 Lower Dir 2 2 7
4 Chitral 2 2 4
5 Shangla 0 0 4
6 Malakand Agency 1 1 4
7 Bonair 0 0 4
2.PESHAWAR DIVISION 2 13 3 18 9 28 26 54
1 Charsada 4 4 8
116
2 Noshehra 5 5 9
3 Peshawar 2 13 3 18 0 22 9
3.KOHAT DIVISION 8 8 12 20
1 Kohat 3 3 4
2 Karak 3 3 4
3 Hangu 2 2 4
4.D. I. KHAN DIVISION 5 5 10 15
1 Tank 2 2 4
2 D.I.Khan 3 3 6
5.HAZARA DIVISION 7 7 32 39
1 Mansehra 2 2 9
2 Abbottabad 3 3 7
3 Haripur 2 2 6
4 Batagram 0 0 4
5 Kohistan 0 0 6
6.BANNU DIVISION 5 5 11 16
1 Bannu 3 3 6
2 LakkiMarwat 2 2 5
7.MARDAN DIVISION 8 8 21 29
1 Mardan 5 5 11
2 Swabi 3 3 10
BALOCHISTAN 3 6 2 11 33 44 66 110
117
1.QUETTA DIVISION 3 6 2 11 4 15 14 29
1 Quetta 3 6 2 11 4 11 3
2 Pishin 2 1 5
3 Q.Abdullah 1 1 4
4 Chaghi 0 0 1
5 Nushki 1 1 1
2.SIBBI DIVISION 4 4 7 11
1 Sibbi 2 2 1
2 Kohlu Agency 0 0 1
3 DeraBugti 0 0 2
4 Ziarat 1 1 0
5 Harnai 1 1 1
3.KALAT DIVISION 8 8 14 22
1 Kalat 1 1 3
2 Khuzdar 4 4 4
3 Kharan 0 0 1
4 Lasbela 3 3 3
5 Mustung 1 1 2
6 Awaran 0 0 2
7 Washuk 0 1
4.MEKRAN DIVISION 6 6 8 14
1 Turbat 3 3 4
2 Gawadar 3 3 1
3 Panjgur 0 0 3
5. ZHOB DIVISION 6 6 11 17
118
1 Zhob 2 2 2
2 Loralai 2 2 3
3 Barkhan 0 0 1
4 Musakhel 1 1 2
5 QilaSaifullah 1 1 2
6 Sherani 0 1
6.NASIRABAD DIVISION 5 5 12 17
1 Kachhi\Bolan 1 1 3
2 JhalMagsi 0 0 1
3 Jafar Abad 3 3 5
4 Tamboo/Nasirabad. 1 1 3
TOTAL: 79 175 48 302 273 575 758 1333
GILGIT/BALTISTAN 15 15 19 34
1 Baltistan 4 4 4
2 Daimir 2 2 3
3 Gilgit 5 5 9
4 Ghizer 2 2 3
5 Ghanche 2 2 2
6 Astore 0 0 3
A J & K 28 28 38 66
1 Kotli 3 3 5
2 Mirpur 5 5 3
3 Muzaffarabad 5 5 6
119
HattianBala 2 2 3
4 Bhimber 2 2 4
5 Bagh 2 2 4
6 Haveli 2 2 3
6 Rawalakot/Poonch 3 3 4
7 Sudhnoti 2 2 3
8 Neelum 2 2 3
FATA 0 0 67 67
1 Bajaur Agency 0 0 10
2 Khyber Agency 0 0 8
3 Kurram Agency 0 0 7
4 Mohmand Agency 0 0 6
5 North Waziristan 0 0 6
6 Orakzai Agency 0 0 5
7 South Waziristan 0 0 7
8 TA AdjLakkiMarwat 0 0 3
9 TA AdjBannu 0 0 2
11 TA AdjD.I.Khan 0 0 4
12 TA AdjKohat 0 0 3
13 TA Adj Peshawar 0 0 3
15 TA Adj Tank 0 0 3
GRAND TOTAL: 79 175 48 302 316 618 882 1500
120
Pakistan
Residence Province / Region
Urban Rural Punjab Sindh KPK Balochistan FATA AJK GilgitBaltistan
Number of Sample Areas
Sampled 1500 618 882 682 323 218 110 67 66 34
Completed 1500 618 882 682 323 218 110 67 66 34
Number of Sample households
Sampled 30000 12360 17640 13640 6460 4360 2200 1340 1320 680
Interviewed
/ Visited 30000 12360 17640 13640 6460 4360 2200 1340 1320 680
Consent
Yes 27963 11496 16467 13188 6282 3626 1996 900 1303 668
Refusals 2037 864 1173 452 178 734 204 440 17 12
Refusal
Rate 6.8 7 6.6 3.3 2.8 16.8 9.3 32.8 1.3 1.8
121
SAMPLING WEIGHT
ESTIMATION PROCEDURE
ESTIMATION PROCEDURE ADOPTED FOR NATIONAL NUTRITION SURVEY 2011
NOTATIONS:
Nh = Total number of Primary Sampling Units (PSUs) in the h-th stratum of a province/region.
nh = Total number of sample PSUs in the h-th stratum of a province/region.
Mhi = Total number of Secondary Sampling Units (SSUs) in the i-th sample PSU of h-th stratum of a province/region.
mhi = Number of sample SSUs in the ith sample PSU of h-th stratum of a province/region.
Phi = Assigned probability of selection of ith PSU of the h-th stratum of a province/region.
yhij = Value of any characteristic y of j-th SSU within ith PSU of h-th stratum of a province/region.
xhij = Value of any characteristic x of j-th SSU within i-th PSU of h-th stratum of a province with whose respect proportion is required.
122
(i): ESTIMATION FORMULAE FOR TOTALS AND THEIR VARIANCES
N = Nh=1
L
h
n = nh=1
L
h OR
h
h i=1
nhi
hi
Y = 1
n
Y
p
h
h
h i=1
n
hi
hi
hi j=1
m
hijY = 1
n
1
p
M
m y
h hi
Y = Y1
n
Y
ph=1
L
h
h=1
L
h i=1
nhi
hi
= h
h
h i=1
nhi
hi h i=1
n
hi
hi
hi j=1
m
hijX = 1
n
X
P =
1
n
1
P
M
m x
h h hi
X = X = 1
n
X
ph=1
L
h
h=1
L
h i=1
nhi
hi
h
R =
Y
X
For X, another variable of interest, we have
123
v yn
sn n
Y
P
y
P
nh
h
ht
h h
hi
hi
hi
hii
n
hi
n
h
h
( )( )
(
)
1 1
1
22
2
2
1
1
v Yn
sn n
Y
P
y
P
nh
ht
h hh
L
h
Lhi
hi
hi
hii
n
hi
n
h
h
( )( )
(
)
1 1
1
2
11
2
2
2
1
1
(ii): FORMULA FOR RATIO ESTIMATES
r = Y
X
where Y^ and X^ can be estimated by equations under item (i) given above.
Rel V(r) =
1
X
1
ns +
1
x
1
n
M
p m
M - m
Ms2
h=1
L
h
hb2
2h=1
L
h i=1
nhi
2
hi
2hi
hi hi
hi
hw2
h
124
125
126