Food Insecurity Atlas of Orissa

VAM Unit, World Food Programme, 53 Jorbagh, New Delhi 110091. Tel - 91-11-4694381 Fax - 4627109May 2000

United Nations World Food ProgrammeIndia / ROBINS

Foreword

This first edition of the Vulnerability Analysis and Mapping of food insecurity related indicators of Orissa is intended to provide guidance on the targeting of future food security development projects in Orissa. It is the result of a considerable process of consultation, review and improvement. We are grateful for the valuable comments given by those who have already read the document. We believe improvement is a continuous process and would incorporate these changes in our forthcoming initiatives. This process does not stop with this edition and the World Food Programme in New Delhi would be grateful to receive your comments and inputs (ref: VAM unit, WFP, 53 Jor Bagh, N. Delhi, fax: 91-11-462.3422).

We wish to emphasise that the collection and mapping of secondary sources of information provides only part of the story of food insecurity. We are in the process of collecting primary data from villagers and communities and key officials in the state of Orissa. We believe this combination of primary and secondary data will more wisely inform both our analysis of the situation food insecure people live and perhaps most importantly assist in identifying development programmes which will have maximum positive impact on their lives. We are looking for partners in all these activities and should your organisation be interested in partnering with WFP, please contact us.

Finally we would like to thank the following persons and organization for collaborating in the production of this document: Government of Orissa, Dr. Dipendranath Das, and Professor Amitabh Kundu, CSRD, Jawaharlal Nehru University, New Delhi.

VAM Unit,Regional Office for Bhutan, India, Nepal and Sri Lanka53 Jor baghNew DelhiMay 2000

ContentsExecutive SummaryList of tablesList of Maps

CHAPTER – I INTRODUCTION1.1 Objectives of VAM1.2 The proposed assignment1.3 Study Plan1.4 Vulnerability Index for regional analysis 1.5 Composite Index.1.6 Cartographic Methodology1.7 Thematic mapping1.8 Limitation of the Study

CHAPTER – II INTRODUCTION TO THE STATE2.1 Physiography2.2 Climate 2.3 Area, People & Culture 2.4 Population & Demography2.5 Economy

CHAPTER – III INDICATORS

3.1 Sustenance Insecurity3.1.a Population supported by cereal production

3.1.b Seasonality3.1.c Food as percentage of household expenditure3.1.d Inadequacy of safety net system3.1.e Composite Sustenance Insecurity Index

3.2 Disaster3.2.a Cattle & Crop loss due to natural disaster3.2.b Disaster proneness3.2.c Composite Disaster

3.3 Deprivation3.3.a Percentage of Population below Poverty Line

3.3.b Scheduled Caste population.3.3.c Scheduled Tribe population.3.3.d Out Migration.3.3.e Illiteracy3.3.f Agricultural labourer3.3.g Working children3.3.h Composite Deprivation index

3.4 Gender Inequality3.4.a Disparity in literacy3.4.b Disparity in IMR3.4.c Disparity in CMR3.4.d Sex ratio3.4.e Composite gender inequality index

3.5 Malnutrition & Mortality 3.5.a Infant Mortality Rate3.5.b Child Mortality Rate3.4.c Prevalence of Malnutrition under 53.5.d Population supported by AWC3.5.e Composite Malnutrition & Mortality Index

CHAPTER – IVCOMPOSITE INDEX4.1 Composite Vulnerability Index with all Broad categories4.2 Interrelationship of Indicators4.3 Rationale behind the selection of Indicators4.4 Composite index with selected indicators4.5 Safety net coverage

CHAPTER – V COPING STRATEGY

AnnexAnnex I Reference Annex II Data SourceAnnex III TablesAnnex IV Additional Indicators

List Of Maps

1. Location Map of Orissa/Index Map2. Block map of Orissa3. Agro-ecological Zones of Orissa4. Population Supported by Cereal Production5. Seasonality in Cereal Production6. Inadequacy of Safety Net System7. Composite Sustenance Insecurity Index8. Cattle and Crop loss due to disaster9. Disaster Proneness 10. Composite Disaster Index11. Households below Poverty Line.12. Distribution of Scheduled Caste Population 13. Distribution of Scheduled Tribe Population 14. Net Out Migration 15. Illiteracy Rate16. Percentage of Agricultural Labourer 17. Working Children 18. Composite Deprivation Index19. Gender Disparity in Literacy20. Gender Disparity in IMR21. Gender Disparity in CMR22. Sex Ratio23. Composite Gender Inequality Index24. Infant Mortality Rate25. Child Mortality Rate26. Prevalence of malnutrition among under 5 Years27. Population supported by Anganwadi centre28. Composite Mortality and Malnutrition Index29. Composite Vulnerability Index with Broad Categories

List of Tables

1. Basic Demographic Indicators2. Population Supported by Cereal Production3. Seasonality in Cereal Production4. Inadequacy of Safety Net System5. Sustenance Insecurity Index6. Cattle and Crop loss index7. Disaster Proneness 8. Disaster Index9. Household below Poverty Line.10. Distribution of Scheduled Caste Population 11. Block Level Data (Table 9A, 10A, 11A, 13A, 14A & 17A)12. Distribution of Scheduled Tribe Population 13. Net Out Migration 14. Illiteracy Rate15. Percentage of Agricultural Labourer 16. Working Children 17. Deprivation Index18. Gender Disparity in Literacy19. Gender Disparity in IMR20. Gender Disparity in CMR21. Sex Ratio22. Gender Inequality Index23. Infant Mortality Rate24. Child Mortality Rate25. Prevalence of malnutrition among under 5 Years26. Population supported by Anganwadi centre27. Mortality and Malnutrition Index28. Composite Vulnerability Index with all Broad Categories29. Interrelationship of the indicators30. Composite Vulnerability Index with Selected Indicators.

31. Pattern of Safety net coverage

EXECUTIVE SUMMARY

The state of Orissa inspite of being endowed with vast natural resources has remained the second

poorest state in the country (next to Bihar), the reason for its backwardness can be attributed to natural,

social and economic factors. Extensive land degradation due to erosion, salinity, damage due to natural

disaster like drought, floods and a super cyclones can be classified under the natural causes. The high

percentage of Schedule Tribe population, low level of literacy, wide spread unemployment in rural

Orissa with almost 44 percent of people living below poverty line has worsened the situation.

It is quite revealing that while all the neighbouring states of Orissa have improved their performance in

planning and have been able to reduce percentage of population living below the poverty line, in case of

Orissa the figure has increased. Poverty gets manifested thorough high mortality and low nutrition level.

This is absolutely true for a state like Orissa, which has highest infant mortality rate and second highest

child mortality rate in the major states of India. Acute under nutrition is also a common phenomenon in

Orissa.

The objective behind the WFP project on Vulnerability Analysis and Mapping is to improve the

effectiveness of its programme by reliably identifying food insecure areas and hungry population and

targeting them for food assistance. The project has two distinctive phases:

1. Vulnerability analysis and mapping of food insecurity from secondary data.

2. Preparation of vulnerability profiles through community level assessment.

The present study involves the identification of the food insecure areas and locating them spatially. The

indicators chosen for identification of vulnerability are either reasons for food insecurity or the

manifestation of the same. The indicators are conventional and during measurement all of them have

been made unidirectional so that higher value reflects higher vulnerability. The very conventional sex

ratio has been measured here as number of males per female so that high value represents vulnerability.

Along with the measurement of individual indicators the broad input variables and output variables have

been grouped together to recognise the composite vulnerability. However the safety net variables were

kept out of the composite vulnerability as they control vulnerability. The qualitative information that

was collected from various reports on Orissa has supplemented the findings from the secondary data

analysis.

In the five broad categories of vulnerability sustenance insecurity and the disaster are the one that deals

with the component of availability. Here disaster loss, population supported for cereal production and

seasonality of cereal production was taken up. It has been found that the interior districts of Orissa are

vulnerable to sustenance, and disaster. The coastal districts although are exposed to cyclones and floods

are comparatively less vulnerable to disaster and sustenance insecurity.

The third broad category deals with the accessibility component of vulnerability where below poverty

line population, scheduled caste and tribe population, illiterates and agricultural labourers etc. have been

considered. The broad composite index indicates that the tribal and interior districts are the deprived

district inspite of being endowed with rich mineral resources.

The fifth category reflects the utilisation aspect of food and nutrition and deals with malnourished

children, IMR and CMR. It has been observed that malnutrition and mortality is more prevalent in the

coastal districts and is less in the northern region.

The analysis is comprehensive and gives an overview of the situation. The variations and deviations

from the expected results cannot be justified based on the secondary data. An in depth field study is

required to understand the regional variations and the causes of such variations. But certainly this

overview invokes the interest of further probing to realise the ground reality.

CHAPTER IINTRODUCTION

Background

Families facing chronic food insecurity are caught in a hunger trap. The inadequacy and uncertainty of

their food supply make it difficult for them to take advantage of development opportunities. The special

niche of the World Food Programme is to enable poor people to access the benefits of development by

making food available to the most vulnerable and food insecure groups.

Presently, the focus of assistance of WFP is directed towards poor children and women to meet their

special nutritional and health needs and towards the Scheduled caste and tribe who depend upon

degraded natural resources for their food security.

1.1 Objectives of Vulnerability Analysis and Mapping (VAM)

The principal objective of VAM is to increase the effectiveness of WFP aid programming by improving

the understanding of the structure of food security and vulnerability to food insecurity. Such an

understanding permits WFP to (1) accurately identify food insecure areas and populations, (2) design

food aid interventions that effectively address the needs of these people, and (3) improve the assistance

of food to them.

WFP in India has set up a VAM Unit with a view to support the country office for effective monitoring

and decision making. Indicators were selected to measure the aspects of poverty and deprivation. These

indicators were aggregated and weighted into five broad sectors, viz., (i) Sustenance Insecurity (ii)

Disasters, (iii) Deprivation & Gender Inequality (iv) Malnutrition & Mortality. Vulnerability in food and

nutrition is identified as a complex manifestation of the behaviour of these indicators where a certain

section of the population are more susceptible to adopt a worse coping mechanism if these indicators

behave in a negative manner. With the above mentioned objectives, VAM effectively explores the

population of intervention where poor food and market situation, worse poverty and gender dimension,

health and nutrition situation and ill developed disaster management operates.

1.2 The Proposed Assignment

The objective of the proposed assignment is to spatially assess the current vulnerability of the

blocks/districts on the basis of 20 individual indicators as well as on the basis of the four broad

categories. The map generated through the proposed study would depict the relative level of

development among the different districts/blocks. These maps will be used by WFP for programme

formulation, decision making and monitoring

1.3 Study Plan

The study clearly involves the following tasks:

1. Data collection,

2. Data compilation,

3. Preparing the Vulnerability Index

4. Mapping the data

5. Presentation of an analysis

6. Identify and locate the vulnerable areas spatially.

In a closed system, where there is no intervention from the market or government the agricultural

production is the most important determinant of food supply. The seasonality of cereal production also

affects the supply over different season of the year. However, in the age of democracy the scenario of

food supply is influenced by the market mechanism and government intervention.

Another important component that ensures the food availability is the household income, which helps to

procure food from the market. In a welfare state however at the time of food insecurity or at period of

crisis, to keep steady food supply, the government intervenes through different ways. Nowadays the

non-governmental developmental organisations also join hands with the government in these

intervention works. Natural disaster affects food production and influences availability of food.

Therefore agricultural productivity, its seasonality, income of the households, government/non-

government intervention (safety net) and natural disaster can be considered as the direct / proximate

determinants of food and nutrition status.

There are some variables that have very complex relationship and exert their influences in a

multidimensional way, which are very difficult to explain. E.g. a literate person would have a better

understanding of agricultural practice and disaster management, which would result in less vulnerability

to disaster and better agricultural production. This would ensure easy availability of food, presuming the

absence of any market mechanism or government intervention. A literate person would also ensure a

better job and earn a better livelihood and will be capable of ensuring steady food supply from the

market. The level of literacy also determines productivity and quality of the labourers.

The core indicators were pre selected for the study and here the scope is limited to discuss all the

relationships of the variables in details. The indicators selected for the study are as follows:

Broad Categories Individual IndicatorsSustenance Insecurity 1. Population supported by cereal production.

2. Seasonality in Cereal Production.3. Inadequacy of Safety Net System.

Broad Categories Individual IndicatorsDisasters 4. Cattle loss and Crop loss index

5. Disaster PronenessDeprivation 6. Population below Poverty Line

7. Scheduled Caste Population Index 8. Scheduled Tribe Population Index

9. Net Out Migration Index10. Illiteracy Index11. Agricultural Labourer Index12. Working Children Index

Gender 13. Gender Disparity in LiteracyInequality 14. Gender Disparity in Infant Mortality Rate

15. Gender Disparity in Child Mortality Rate16. Sex Ratio

Mortality 17. Infant Mortality Rate (IMR)& Malnutrition 18. Child Mortality Rate (CMR)

19. Prevalence of Malnutrition20. Population Supported by Anganwadi Center

1.4 Vulnerability Index For Regional Analysis:

There are three steps in the methodology of developing the vulnerability index.

i. Measurement of the individual indicators selected for the study.

ii. Developing composite index separately for the five broad categories and

iii. Finally a total composite vulnerability index.

The data for computation for all the indicators has been collected from secondary sources available

primarily from Census Report 1991, District Statistical Handbook, Government of Orissa and also from

Nodal Departments.

Measurement of the individual indicators has been done in the following way:

Individual Indicators Measurements

Population supported by 100 quintals of cereal production

Total Population (1991)/ Total cereal Production(in quintals)* 100

Seasonality in Cereal Production 1- (Second crop /first crop). {depending upon the production}

Inadequacy of Safety Net System 1. Percentage EAS beneficiaries to total agricultural worker of the districts.

2. District with CARE intervention = 13. District without CARE intervention = 04. District with WFP intervention = 15. District without WFP intervention = 0

Crop loss index Crop loss (in Rs.)per hectare of net sown area of the district.Disaster Proneness Percentage of area covered under DPAP of the total area of the

district.Households below Poverty Line Percent of households below poverty line to total rural

households of the district.SC Population Index Percent of SC population to total population.

ST Population Index Percent of ST population to total population.Net Migration (Total inter district out-migration - total inter district in -

migration) / total population of the districts. Illiteracy Index Percent Illiterate to total population (above 6 years)of the

districts.Agricultural Labourer Index Percentage of Agricultural labourers to total primary workers of

the districts.Working Children Index Percent of working children to total child population in the age

group 5-14.Gender Disparity in Literacy Ratio of male female illiteracy rates. Gender disparity in IMR Number of female infant death per 1000 male infant death.Gender disparity in CMR Number of female child death per 1000 male child death.Sex Ratio Males per 1000 females in age group 0 – 16.Infant Mortality Rate (IMR) Number of infant death per 1000 live birth.Child Mortality Rate (CMR) Number of child die by age 5 per 1000 live birth. Prevalence of Malnutrition Percent of Severely malnourished + Percent of Moderately

malnourished Children of 0-3 and 3-6 age groups to total children weighed in the district.

Population Supported by Anganwadi Centre

Total rural population of the Blocks having Anganwadi / Total number of rural Anganwadi centre in the district.

** In the next edition of this report we would incorporate the following changes - 1. Projected population figures for the ref. year of the specific indicators.2. Production data would be adjusted by deducting 'Seed-Feed and Wastage' from the total figure.

1.5 Composite Index :The most important issue of the composite index is – how to combine the different indicators into a single index reflecting the order of the regional units (districts) in terms of their level/status in a particular aspect of development. This task has been done very cautiously. In all the cases, individual indicators are measured in such a way that they can easily be ordered in a descending manner according to their values reflecting higher the value greater is the vulnerability of the district.

Then all the individual indicators have been made scale free by dividing the values of the indicators with

their statistical mean. This procedure also helps to minimise the variation of the values of the indicators

over the districts. These scale free indicators have been added up to calculate different composite

indices.

1.6 Cartographic Methodology:

The indicators measured by applying above methodology have been presented thematically. For

presentation of a data series, grouping of the data in different range is essential. Rational grouping helps

to bring out regional variation in the behaviour of a particular indicator. There are several methods

available for grouping the data. Among the well-applied methods equal range method, equal count

method, grouping by using mean and standard deviations, grouping by percentile method are some. The

present task has limited its analysis by adopting equal count and equal range method. These methods are

easy to understand and follow when wide ranges of variables are taken into account for analysis.

1.7 Thematic mapping

The indicators after measurement have been presented thematically. All the maps have four ranges - Red

representing the worst scenario, and Orange, Yellow and Green showing progressively improved status.

1.8 Limitations

For the entire set of indicators district level maps have been prepared to show the regional variation

within the state. Most of the data have been collected from the secondary sources mainly from the 1991

census, which has data for only 13 districts. Present day Orissa has 30 districts. The newly formed

districts are Bhadrak from Baleshwar, Jagatsinghpur, Kendrapara and Jajpur from Cuttack, Khurdah and

Nayagarh from Puri, Angul from Dhenkanal, Baragarh, Sonepur, Jharasuguda and Deogarh from

Sambalpur, Gajapati from Ganjam, Malkangir, Nawarangpur and Rayagada from Koraput, Nawapara

from Kalahandi and Boudh and Kandhamal have replaced Phulbani. The data for all the indicators are

not available for the newly formed districts. For those indicators the data of the parent district has been

repeated for the newly formed district.

The block level data for all the pre-selected indicators are not available at the State level Head Quarters

and it is cost in effective and time consuming for one to go and collect data from block and district level.

Block level map of few indicators whose data was readily available has been done. The Block level data

reflect the rural situation only.

CHAPTER IIINTRODUCTION TO THE STATE

2.1 Physiography

Orissa extends from 170 49’N to 220 34’N latitude and from 810 29’E to 870 29’E longitude on the

eastern coast of India. West Bengal in the northeast, Bihar in the north, Orissa in the West, Andhra

Pradesh in the south and Bay of Bengal in the east bound it. (Map no.1 and 2 - Location map of

Orissa)

Physiographically, Orissa can be divided into three broad regions. These are i) Coastal plain, ii).

Middle mountainous country and the plateau and iii) The Rolling uplands. The coastal plain, the

fertile green tract, is better known as the ‘rice bowl of Orissa’ and stretch westwards from the Eastern

coast of India, and run from the river Subernarekha in the North East to the River Rushikulya in the

South east.

The mountainous portions of Orissa covers about three-fourths of the entire state and hence determine

the economic standard of the state. The high plateau is within the mountainous areas with an average

elevation of 300-600 meters.

The rolling uplands are lower in elevation and they vary between 150 and 300 metres. These uplands are

the products of river action and are flat in nature. They are rich in soil nutrients and provide good

opportunities for cultivation of paddy in wet areas.

The rivers of Orissa are non-perennial in character, as none of them are snow fed. Most of these rivers

originate from the adjoining Chotanagpur and Amarkantak Plateau and drains into the Bay of Bengal.

The rivers originating from the Eastern Ghats are small. Mahanadi, the largest river of the State

facilitates irrigation and HydroElectric Power Generation.

2.2 Climate

The entire state lies in the Tropical Zone and is subject to high temperature. Being in the belt of medium

pressure it has medium rainfall with moderate variation in the different parts of the state. Orissa, on the

eastern seaboards of India, enjoys a tropical monsoon type of climate most of the other parts of the

country.

Orissa has a mean annual temperature of 260C. The summer temperature ranges between 33 0C to 380C

and increase from the coastal plains to the inland districts. The monsoon rainfall is of direct importance

as it controls the crop conditions in Orissa. Normal rainfall for the state is 1482mm, July and August

being the rainiest months. The winter rainfall helps the growth of a second Crop in the state.

The state can be divided into Ten Agro- Climatic zones with varied characteristics . (Map no. 3 – Agro

Climatic Zones of Orissa.)

Characteristics of Agro-Climatic zones in OrissaAgro climatic zones Climate Mean annual

rainfall (in mm )Soil group

North-western Plateau Hot and moist 1648 Red and YellowNorth central Plateau Hot and moist 1535 Red loamyNorth eastern coastal Plateau Hot and moist sub

humid1568 Alluvial

East and south eastern Plateau

Hot and humid 1449 Coastal Alluvial Saline

North eastern ghat Hot and moist sub humid

1597 Laterite and Brown Forest

Eastern ghat highland Warm and humid. 1522 RedSouth eastern ghat Warm and humid. 1522 Red, mixed red and

YellowWestern undulating Warm and moist. 1527 Black, mixed red and

BlackWest central Table land. Hot and moist 1527 Red, heavy textured

coloursMid central table land Hot and dry sub

humid.1421 Red loamy, laterite

mixed red and black.

2.3 Area people and culture

According to the 1991 census, the total land area of Orissa is 155,700 sq. km. which is about 4.7% of the

total land area of the country. As of 1991 the state was divided into 13 districts. By 1993, the state was

further subdivided and now has 30 districts.

Orissa has a rich cultural heritage. Situated at the confluence of North and south, the state has

assimilated the culture of both, forming a unique identity of its own. Orissa is the land of lord Jagannath,

whose heritage is intimately connected, with the social, cultural and religious life of the people of

Orissa. Jainism, Islam and Christianity have all had a considerable impact on the people of Orissa in

different periods. The cultural identities of the states tribal people who constitute about a quarter of the

states population have contributed different hues to the cultural landscape of the state. Orissa is also

distinguished by its arts and crafts. The temple architecture of Konark and other areas attracts world-

wide attention, and tourism is growing industry in the state.

2.4 Population and Demography

According to the 1991 census the state’s population is 31.7 million accounting for about 4 percent of the

countries population. The marginal decline in the growth rate from 20.17 percent to 20.06 percent may

be attributed to the rise in literacy rate and a subsequent acceptance of the governments family planning

programs. The density of population is 203 persons per sq. km. Within the state the population density is

higher in the coastal area than the inland districts. Thus, the problem is not of high pressure of

population but its uneven distribution.

Orissa is more rural than India. As a whole 86.6 percent of its population live in rural areas as compared

with 74 percent for the whole of India.

The crude birth rate has steadily declined from 34.6 per 1000 population in 1971 to 27.8 in 1992 for the

state and is slightly lower than the all India rate. However the TFR of 3.3 children per women is lower

than the all India rate (3.6).

The infant mortality rate of Orissa is very high, highest among the states in India. It is interesting to

observe that the life expectancy is slightly higher for males than for females in the state. The case for

India is the reverse.

The Schedule Castes constitute 16 percent (17 percent for the whole country). The state has one of the

highest concentrations of tribal in the country (22 percent as compared to 8 percent for the whole

country). The scheduled areas cover nearly 45 percent of the total geographical area. The literacy rate of

scheduled caste and scheduled tribe was 36.78 percent and 22.31 percent respectively according to the

1991 census.

Sex ratio

The sex ratio in the state reflects a better situation but recorded a decline from 981 in 1981 to 971 in

1991 (All India decline from 933 in 1981 to 927 in 1991).

Literacy

On the literacy front, the achievement has been noticeable, as the literacy rate has increased from 34

percent in 1981 to 49 percent in 1991. Although this improvement in literacy is more pronounced in the

case of females than males, female literacy levels continue to be substantially lower than male literacy

levels. The literacy rates are 63 percent for males and 35 percent for females in Orissa as compared with

64 percent and 39 percent for males and females, respectively for all India.

2.5 Economy

Agriculture continues to be the mainstay of the state’s economy absorbing about 80 percent of the total

work force and contributing 50 percent of the state’s domestic product. Paddy is the principle crop of the

state, and its cultivation is the main occupation of 75 percent of the people. Other important crops are

pulses, oilseeds, jute, mustard, sugarcane and turmeric.

In the absence of adequate irrigation facilities, agriculture has to depend on monsoons as a result of

which agricultural production fluctuates widely due to its erratic behaviour. The irrigation potential has

been created through major, medium, minor lift irrigation and water harvesting projects up to 24.04 lakh

hectares by 1997-98. The government has adopted some strategies for modernisation of present

irrigation system.

Orissa has declining forest area coverage of only 17.56 percent of the state as against the optimum

requirement of 33 percent. This drastic reduction of forests is primarily due to unauthorised felling,

forest fires, fast growing cattle population, unauthorised overgrazing, and encroachment on forestland

for cultivation, shifting cultivation and above all population explosion. This has resulted in a reduction

in rainfall, heavy increase in the frequency of floods and droughts. The increasing salinity in the soil

near the coastal areas are also contributing to the environmental degradation of the state.

The state is endowed with vast mineral deposits like coal, iron ore, manganese, dolomite, chromite, etc.

Other important minerals are limestone, bauxite, graphite, china clay, nickel, fine clay, nickel quartz

and mineral salts.

With vast mineral resources and abundance of raw materials, the state has immense potentiality for

industrialisation. Large industries like Rourkela Steel plant, national Aluminum Company (NALCO),

Indian Charge Chrome Ltd., Paradeep Phosphate, and coal based power plants at Talcher, Kaniha and

Banharpali has been set up during different plan period.

At present the Industrial Promotion and Investment Corporation limited (NPICOL), Industrial

Development Corporation Limited (IDCOL) and Orissa State Electronics Development Corporation

(OSEDC) are three nodal agencies promoting large and medium industries in the state. By the end of

1997-98 it had 313 large and medium industries. The state is providing institutional and financial

support with various incentives and concessions for promotion of small scale, and village and cottage

industries.

The physical, social, economical and demographic background of the state dictates the developmental

status of the same.

CHAPTER IIINDICATORS

3.1 SUSTENANCE INSECURITY

3.1.a Population Supported by Cereal Production:

Taking into account the high contribution of agriculture to the states income, the state government has

formulated the agricultural policy with the main objectives of doubling the production of food grains, to

generate employment opportunities and to make agriculture the main root to eradication of poverty.

However due to increase in population, the states per capita food grain production has declined. The

graph below shows the general trend of cereal production in the state over years.

In 1996-97 due to severe drought in the state there was a sharp fall in its production. Otherwise, the

production is stable.

The variable has been measured as number of people supported by 100 quintal of cereals produced in

the district assuming that the total cereal production is distributed equally amongst the population. Here

the market mechanism and governmental intervention are not considered. In an open economy with a

significant role of trading and with the presence of welfare interventions like Public Distribution System

and ICDS the pressure of population on each unit of crop produced gets reduced. All this has not been

captured in this measurement. According to the norm 100 quintal of cereals should support 49 persons

for a year (In ideal situation 206 kg of cereal should support one person for one year). The variable

indicates the population pressure on each unit of crop.

The data of cereal production used here is of 5-year average (1993-98). Thus, the effect of yearly

variation of production is minimized.

In the state, 4 districts, namely, Rayagada, Khandamal, Khurda and Jajpur have more number of persons

than this prescribed norm. Agricultural production of these districts is lower in comparison to the their

population size. The situation is satisfactory in the districts of Sambalpur, and its adjoining districts

Deogarh, Baragarh and Sonepur, Nawarangapur and Cuttack. The better irrigation facilities in

Sambalpur and adjoining districts due to presence of Hirakund Dam on Mahanadi River is likely to be

the reason for good agricultural production. Cuttack, which is situated along the lower track and upper

delta region of Mahanadi River, is also good in rice production. Lower density of population may be the

reason for low population pressure per 100 quintals of cereal in Nawarangapur.

The south and southwestern districts have shown better situation in terms of cereal availability. But, it is

to be mentioned that the south and southwestern districts dominated by tribal population have less

control over the production due more inequitable distribution of land. The distribution of land is in

favour of some higher caste population. Moreover, there is inter-border sale of food grains particularly

form Orissa to Orissa and Andhra Pradesh. (Annex: Table - 1, Map no. 4 )

3.1.b Seasonality in Cereal Production :

Agriculture in Orissa has lagged behind several developed states. The major factors contributing to low

productivity are continuance of traditional agricultural practices, inadequate capital formation,

inadequate irrigation facilities, and uneconomic size of holdings. About 70% of the total cropped area

are rainfed and exposed to the vagaries of monsoon. Technological inputs, systems of land holdings

posses equal importance as the factors like agro-climatic conditions have for the development of

agriculture.

The uncertainty of monsoons, their mal-distribution, and great variation in the amount of annual

precipitation have forced the government and the people to make provisions for artificial irrigation to

prevent frequent crop failures. Even during a good rainy season, which itself is short, the rainfall is so

erratic that the standing crop do not get water at the time when they require it most. The harvest, thus

fall far short of expectations, to the great disappointment of the rural community.

Indian agriculture is the ‘gamble of monsoon’ and this true in the scenario of agriculture of Orissa also.

That is why influence of seasonality in agriculture is very high. Most of the districts of Orissa are

overwhelmingly dependent on the production of Kharif crops to support their population. Contribution

of Rabi crops to total cereal production very less in all the districts, except Puri, Baragarh and Sonepur

yielding rather lower seasonality in these districts. (Annex: Table -2 , Map no. 5 )

Studies have shown that food availability in the rural households is closely tied to the agricultural

calendar. For the months of Oct. – Feb the food is available in the households. During the harvesting

season food availability goes up as the marginal farmers harvest their own crops. The lands less

labourers also earn some wages during this season and ensure the supply of food in the households.

Among the poor households the food supply during March – May is made from money earned through

daily wage labour (mainly in government funded construction activity). During the summer, stock of

rice gets exhausted in the household and rice becomes expensive in the market. People consume ‘saag’-

green leafy vegetables, as the rice intake goes down. The situation improves a bit in the rainy season as a

short duration paddy is harvested from their own field. In the rainy season poor households mostly

depend on forest to collect various kinds of leaves and tubers and wild fruits that are available. During

these months, government works such as roads and bridge construction also comes to temporary halt and

this result in the loss of daily wage employment. The real stressful period is Bhado- Aswin as work

availability is low and households cannot afford to purchase food items from market.

Seasonality Timeline

Jan Feb Mar Apr May Jun July Aug Sept Oct Nov Dec

Rabi

Crops Wheat, Maize, Ragi, Summer paddy, Pulses, Till and Ground nut

Kharif

Crops Winter & Autumn paddy, Potato, Sugar cane

Hungry season

3.1.c Inadequacy of Safety Net System :

The policy of the state government is to ensure availability of essential commodities to the consumers by

ensuring price stability, ensuring availability of food grains, sugar and kerosene oil and adopting a

special programme for drought prone and tribal areas. The Revamped Public Distribution System (PDS)

was implemented in ITDP & DPAP blocks and were supplied with 10 kg rice per family per month at

the specially subsidised price of Rs.2.00 per kg and all families above poverty line got the same quantity

at Rs. 4.00 per kg. The allotment of essential commodities to Orissa for distribution through PDS during

1995 to 1998 is as follows

Allotment of Essential Commodities received from Government of India

Sl. No. Commodities Unit Receipt during1995-96 1996-97 1997-98

1. Sugar Lakh MT 1.58 1.79 1.682. Wheat Lakh MT 3.50 4.51 2.193. Rice Lakh MT 7.90 10.02 5.954. Imported Edible Oil MT 10,000 7,000 8,3005. Kerosene Oil Kilo litres 2,71,728 3,00,008 3,11,419

Source: Food, Supplies and Consumer Welfare Dept. Govt. of Orissa

The percentage of households using the PDS Orissa is 5.2 as against India 33.2. The per capita

consumption of food grains met from PDS per Orissa s only 16.4 percent and percentage of requirement

of cereals met by PDS is 16.7 percent. Data on units of Ration card and Fair Price shops were not

available. However after the disastrous cyclone the position of PDS in cyclone affected districts are as

follows:

Ration Card/Position in cyclone affected districtsSl.No. Districts No of Retail No. of Families

Outlets BPL APL Total1. Cuttack 1739 174713 329506 5042192. Jagatsinghpur 916 75217 227859 3030763. Jajpur 1120 103087 226440 3295274. Kendrapara 828 84310 233884 3181945. Khurdah 879 130246 245597 3758436. Puri 811 118063 144658 2627217. Baleshwar 1462 266384 207396 4737808. Bhadrak 1089 109102 116144 2252469. Dhenkanal 844 112642 100024 21266610. Keonjhar 405 224603 135859 36046211 Nayagarh 564 104400 98786 203186

Sl.No. Districts No of Retail No. of Families

Outlets BPL APL Total12. Mayurbhanj 1915 279306 208247 48755313. Ganjam 1644 312039 306197 61823614. Gajapati 375 74871 40567 115438

Total 2019 386910 346764 733674Grand Total 14591 2168983 2621164 4790147

Other than the normal PDS there are several governmental and non-governmental interventions in the

vulnerable districts to ensure food supply. The population in these districts are supported with food

through different operational projects like wage employment programmes, integrated child development

scheme, mid day meal, food for work etc.

The index of inadequate safety net is calculated combining the three indicators - presence of CARE,

presence of WFP and percentage of EAS beneficiaries to the total agricultural workers. There are two

major wage employment programmes namely, EAS and Jawahar Rojgar Yojana (JRY) in operation in

the state. These programmes seek to provide employment for short duration in the form of casual

manual work during the lean agricultural season and also create economic infrastructure and community

assets in the rural areas. While JRY is being implemented for taking up small works according to the felt

needs to the people, EAS is implemented as a demand driven scheme under which public works are

being taken up for generation of assured employment. JRY has the objective of providing the gainful

employment to the unemployed and underemployed persons who live below the poverty line with

special preference being given to Scheduled Caste, Scheduled Tribe and women. Since, the data of

employment generated through JRY are not available at district level, only EAS is considered in the

indexing of safety net.

The map shows that coastal district (except Kendrapara and Jagatsinghpur) and districts adjacent to them

higher inadequacy of safety net index. On the other hand, northern, southern and western border districts

(except Koraput and Jharsaguda) have better safety net coverage. (Annex: Table -3, Map no. 6 )

3.1.d Percentage of Income Spent on Food:

The variable is collected and processed by National Sample Survey Organisation (NSSO) at the state

level in their various rounds over last 25 years. However, the samples drawn are such where any district

level estimates are not possible.

The NSSO Report shows that in rural Orissa a substantial proportion of expenditure of the people goes

on food items only. In general, there is a decline in the trend of expenditure on food items but according

to the 50th round (1993-94) it remains as high as above 68 percent of the total expenditure.

National Council for Applied Economic Research has done a survey during 1994 to prepare Human

Development Index. The published report contains state level data. According to the report at the state

level Orissa spends 42.7 percent of total per capita expenditure on food grains. This figure is higher than

the all India average of 30.5 per cent. In total people of Orissa spends 68.9 percent of their total income

on food whereas the national average is 63.9 percent.

3.1.e Composite Sustenance Insecurity Index.

While composing the composite sustenance insecurity composite index the intervention variable of safety net was excluded as the data reveals only the existence but not their efficiency. The scale free value of population supported by cereal production and seasonality has been added and divided by 2.

The composite scores thus obtained shows that the most vulnerable district is Khurdah, Kandhamal,

Angul, Sundergarh, and Rayagada. The districts of Baragarh, Sonepur, Sambalpur and Puri show least

venerability in terms of sustenance. . (Annex: Table - 4, Map no. -7 )

3.2 DISASTERS

3.2.a Crop Loss Index:

Orissa has been experiencing a lot of disaster due to flood havoc and famine over decades. Flood causes

damage to standing crops and to human habitation and take heavy toll in terms of human and cattle

population. Far more terrible than the floods themselves, are the post flood effects. Millions face

shortage of food. Famine and diseases sweep over the area. The countryside in Orissa gets dislocated

and cultivable lands fall barren.

The rivers that cause floods in Orissa are the Mahanadi, the Brahmani, the Baitarini, the Salandi, the

Kopali and the Subarnarekha. The eastern coastal districts are more prone to flood and cyclone damages

than the interior districts. The government has estimated the damage caused due to the recent super

cyclone in the coastal districts of Orissa. Besides the damaged caused to the population and habitat the

loss of agricultural lands is severe in the districts of Mayurbhanj, Cuttack, Bhadrak and Jajpur out of the

twelve affected districts.

The other forms of disaster, which also add to the crop loss in Orissa, are drought and cyclones. The

districts of Kalahandi, Bolangir and Baragarh faces severe drought situation.

The data on cattle loss was not available and the data of crop loss due to disaster is of 1996-97 only. The

time series data on crop loss could not be collected. Therefore, the average crop loss of the districts due

to disaster was not possible to present. The extent of crop loss has been calculated in Rs. Per hectare of

net sown area.

Stretch of districts extending in east to west direction from the coast to the western margin has higher

crop loss. Crop loss was high in the districts of Bolangir, Baragarh, Sonepur and Boudh during the

drought of 1996-97. These districts are already under the drought prone area programme (DPAP) of the

state. The other districts, which are under the DPAP, have not been affected much in that drought. The

less crop loss in the southern and northern districts of Orissa may be explained as – these districts are

already affected by the problems of soil erosion and chronic drought resulting low agricultural

productivity over the years and thus show lower loss during the drought of 1996-97. The coastal districts

also reflect moderate loss of crops due to flood. (Annex: Table - 5, Map no. - 8)

3.2.b Disaster Proneness:

Drought prone areas are characterised by degraded environment, acute soil erosion, and insufficiency of

water and moisture stress. Disaster proneness has an adverse effect on productivity. In Orissa there are 8

districts and 47 blocks of these districts are under the drought prone area programmes (DPAP) of the

state. These districts are mainly clustered in the west central part of the state except Dhenkanal, which is

in the central Orissa. These districts are away from the coast and receive less annual rainfall leading to

chronic drought in those areas. (Annex: Table - 6 , 6a, Map no. -9)

3.2.c Composite Disaster Index

The composite score of disaster was calculated dividing the aggregate value of Disaster proneness and

cattle and crop loss by 2. The districts which are most vulnerable to disaster and disaster damage –

Kandhamal, Nawapara, Baragarh Angul. Comparatively bellow districts are Cuttack Jagatsinghpur,

Ganjam, Keonjhar & Jharsaguda, Koraput, Malkangir, Sundergarh and Nawarangpur shows best

situation. (Annex: Table -7 , Map no. -10)

3.3 DEPRIVATION

3.3a Population Below Poverty line (BPL)

Orissa is the worst state in terms of poverty. Districts of Phulbani Boudh Koraput, Kalahandi,

Dhenkanal, Bolangir, Keonjhar, Mayurbhanj and Sundergarh are the worst hit by poverty. More than

65% of rural household live blow poverty line.

There are different estimates of population below ‘poverty line’ for last three decades or more. NSSO

provides Head Count Ratio (HCR) or percentage below poverty line at the national and state level. The

HCR estimates released by Planning Commission (computed using the revised expert group

methodology) for Orissa are 66.18, 70.07, 65.29 and 55.58 for 1973-74, 1977-78, 1983-84 and 1993-94

respectively. These HCR figures for all India for the said periods are 54.88, 51.32, 44.48 and 38.86

respectively. Among the states, Orissa has the highest incidence of poverty that is 31 percent higher than

the all India average. There has been an accelerated decline of HCR for all-India and Orissa, during

1980’s and early 1990’s compared to the 1970’s.

Department of Panchyati Raj provides the data on the percentage of family below poverty line (BPL) at

district level. The definition adopted here for identifying BPL is the households with income of Rs.250

per capita per month. In general, Orissa has very high incidence of poverty.

The distribution shows that the districts, which have more than 60 percent below poverty line

households, are also dominated by Scheduled Tribe population of more than 30 percent except for

Dhenkanal, Puri and Nayagarh. In Puri and Dhenkanal there are higher proportion of Scheduled Caste

population also. (Annex: Table -8 , Map no. -11)

3.3.b Scheduled Caste Population Index:

Under the Indian Constitution Scheduled Castes mean such castes or parts or groups within castes as are

declared by the President of India to be Scheduled Castes under Article-341 of the Constitution. The

persons belonging to a Scheduled Caste in a particular State or union Territory will be enumerated as

belonging to Scheduled Castes only if such a caste is listed in the Scheduled Caste list of that particular

state/union territory.

There are 93 Scheduled Castes classified in Orissa as per the Indian constitution. Indian society is

stratified on the basis of caste. People in the lower rung of the caste system are also in the bottom of the

ladder of socio-economic development. The state average of SC population is 16.20 percent. The areas

having better agricultural activities are also having higher proportion of SC population. In Orissa, the SC

population is mainly concentrated along the Mahanadi River system and its delta. Mahanadi delta region

is popularly known as the rice bowl of Orissa.

Malkangir is the only district, which has higher concentration of both Scheduled Caste and Scheduled

Tribe. The Scheduled Castes are mostly engaged in agriculture as agricultural labourers and marginal

farmers. In rural areas they also perform different caste specific occupations like carpentry, black smith

etc. (Annex: Table -9 , Map no. - 12, 12A)

3.3.c Scheduled Tribe Population Index:

Under the Indian Constitution Scheduled Tribes mean such races or tribes or parts or groups within races

or tribes as are declared by the president of India to be Scheduled Tribes under Article 342 of the

Constitution.

Orissa is one of the few states with a heavy concentration of tribal population (7.0 million) in 1991.

There are about 62 Scheduled Tribes in the State. In other words about one in every four citizens in

Orissa is a tribal and they form a major minority. They are exerting a dragging effect on the economy of

the state.

The tribes are concentrated in areas of high relief and high slopes, which sociologically suit their

environment. Their distribution pattern shows two distinct tracts of tribal concentration, the south-west

tract and the north east tract. The former consists of districts Kandhamal, Gajapati, Rayagada, Koraput,

Malkangir, Nawarangapur, Nawapara, while the latter constitute the districts of Mayurbhanj, Keonjhar,

Sundergarh, Sambalpur. (Annex: Table –9, Map no. - 13, 13A)

The Scheduled Tribes are engaged mainly in the occupation of agriculture both as cultivators and

agricultural labourers. In some parts, still now, they perform shifting cultivation following the slash and

burn method. Apart from this, they depend on the collection from the forest (mainly non-timber forest

products). Since the fifth plan period, a Tribal sub-plan has been formulated with the objectives of

improving the socio-economic conditions of the tribal population, strengthening of infrastructure in the

tribal areas, protecting the tribals against exploitation, and promoting tribal interests through legal and

administrative support.

About 58.82% of tribals work as against the state average of 43.64% and non-tribals figure of 40.44%.

Inspite of this higher participation in the workforce their low level of economy drive them to depend

more on muscle power for their livelihood. Despite some progress in the tribal regions, the tribals

seldom enjoy the fruits of planning. The higher the percentage of tribal population, the lower is the

urbanisation and hence a low development.

3.3.d. Net Migration Index:

In the scenario of migration of the state it is seen that the short distance migrants (intra-district) have

dominance over medium (inter–district) and long distance (inter-state) migrants. Short distance migrants

constitute nearly 75 percent of the total migrants of the state and these percentages for inter districts and

inter states are nearly 15 and 10 respectively.

Net migration has been measured as :

Out migration to other districts – In migration from other districts of Orissa

Total Population of the District.

The map shows that a few central, coastal and northern districts are more out-migrating. Southern,

northern and western bordering districts show more immigration This may be primarily because these

areas have better operated safety net (employment assurance scheme, Jowahar Rojgar Yojana, CARE

intervention etc.) as they are drought prone with higher concentration of ST population. (Annex: Table -10 , Map no. - 14)

3.3.e. Illiteracy:

The level of its literacy in a region or state determines the quality of population. The higher the level of

literacy greater the efficiency of the labour force. In this regard it is very unfortunate that Orissa lags far

behind the national average.

The illiteracy rate in Orissa during 1991 was 50.9 per cent against the all India average of 47.9 per cent.

While the male illiteracy rate of 36.9 per cent in the state in 1991 was nearer to the national average of

35.9 per cent, the female illiteracy stood at 65.3 per cent in 1991 which was significantly higher than the

national average of 60.7 per cent.

The map shows that all the southern districts have higher illiteracy. Proportions of tribal population are

also high in these districts. Coastal, central and northern districts (except Mayurbhanj) have lower

illiteracy index. (Annex: Table -11, Map no. -15)

To improve the literacy rates and educational levels the government has undertaken several programmes

namely, Universalisation of Elementary Education (UEE), District Primary Education Programme

(DPEP), Non-Formal Education, Mass Education (Total Literacy Campaign and Post Literacy

Campaign) etc. The improvement of literacy of the Scheduled Caste, Scheduled Tribe and women is in

special focus in the several programmes (DPEP, Non-Formal Education).

3.3.f. Agricultural Labourer Index:

The role of the agricultural sector in the states economy is crucial, as its contribution to the state income

is the highest. It provides direct and indirect employment to around 64% of the total work force.

Cultivators and agricultural labourers together constitute 63.75% of the total workers.

The data of agricultural labourers has been collected from 1991Census. These include both the marginal

cultivators and landless labourers. The block level data has been collected, compiled and has been

calculated as percent to total primary workers of the district.

The distribution shows that the districts in the central Orissa have higher proportion of agricultural

labourers. Most of the coastal districts, on the other hand, have less proportion of agricultural labourers.

All the northern districts, except Mayurbhanj and districts in the southern tip of Orissa have low

percentage of agricultural labourers. (Annex: Table - 12, Map no. -16)

3.3.g. Working Children Index:

Child Labour is not peculiar to India alone it is a global phenomenon. Although India has the largest

child labour population in the world in terms of absolute number, the proportion of working children to

the total labour force is lower in India than many other developing countries.

The distribution of child labour in various states indicates certain correlation. States having a large

population living below the poverty line have a higher incidence of child labour. Similarly, higher

incidence of child labour is accompanied by high dropout rates in schools.

Families stricken with poverty can not afford to bear educational expenses and send their children to

school. Instead, they prefer to engage them in gainful employment at an early age to enhance family

income. It is seen in the peak agricultural season families withdraw their children from school to

compensate the shortage of labour and earn higher income to cope up the low income during lean

agricultural seasons. In many a cases the long absence of the children from school ultimately leads to

drop-out.

India follows a proactive policy in the matter of tacking the problem of child labour. Article 39 under &

(f) the Directive Principles of the State Policy affirms; (e) ‘’that the health and strength of workers, men

and women, and the tender age of children are not abused and that citizens are not forced by economic

necessity to enter avocations unsuited to their age or strength;

(f) That children are given opportunities and facilities to develop in a healthy manner and in conditions

of freedom and dignity and that childhood and youth are protected against exploitation and against

moral and material abandonment.'’

In 1987 the National Child Labour Policy was adopted to deal with a situation where children work or

are compelled to work on a regular or continuous basis to earn a living for themselves and or their

family, and where conditions of work result in their being disadvantaged and exploited.

Out of 133 child labour endemic districts in 13 states of India Orissa’s contribution is of 16 districts (2 nd

highest after Maharashtra). The Child labour endemic districts in Orissa are Koraput, Ganjam,

Kalahandi, Sambalpur, Mayurbhanj, Bolangir, Malkangir, Nawarangpur, Rayagada, Nawapara,

Gajapati, Baragarh, Deogarh, Jharsaguda, Angul and Sundergarh.

On an average 5.9 percent of the children in Orissa are in the workforce. This figure is higher than the

national figure of 5.3 percent.

The distribution shows that the incidence of child labour is very high (even above 10 percent) in the

southern districts of Orissa. This region is characterised by higher level of poverty, more concentration

of Scheduled Tribe population and lower level of literacy along with higher gender disparity. Studies

have shown that the working children in Orissa are mostly engaged in the works of agriculture, cattle

raring and non-timber forest product collection. (Annex: Table - 12, Map no. - 17)

3.3.h Composite Deprivation Index

The composite deprivation index was calculated by aggregating all the scale free values and dividing

them by the number of indicators.

From the composite score that was arrived at it has been observed that Sambalpur, Deogarh, Jharsaguda,

Baragarh, etc. are the most deprived districts. Nayagarh, Baleshwar, Khurdah, Jagatsinghpur and

Dhenkanal are comparatively better.

Ganjam, Gajapati, Mayurbhanj, Bolangir reflect a better situation. (Annex: Table -13, Map no. -18).

3.4 GENDER INEQUALITY

3.4.a Gender Disparity in Literacy:

The low value attached to female education in much of India links with some deep-rooted features of

gender relations. The three very common links are as follows:

In rural India a large majority of girls are expected to spend most of their adult life in domestic work

and child rearing. Thus female education to most of the parents appears to be somewhat pointless.

The investments that parents make in the education of their daughter primarily benefit other, once

the daughter is married away. This strongly reduces the value of education from the parental self-

interest point of view.

Again, if an educated girl can only marry a more educated boy and if dowry payments increase with

education of the groom then the parents will obviously be reluctant to send their daughter for

education.

These three and other links between female education and gender relations result in female male

disparity in education.

There is a differential level of literacy among males and females. In this respect, Orissa also has figures

lower than the national average. In India while 63% of males and 32.42 percent of females were literate

in 1991, in Orissa the percentage was only 63.1 and 31.9%.

Disparity in literacy is usually measured as number of female literate per 1000 of male literate. But here

to reflect vulnerability the disparity has been measured as :

Percent of male literate to total male population

Percent of female literate to total female population.

There is a wide variation in the gender disparity of literacy. In Orissa there are 510 female literate per

1000 male literate. The south and southwestern part, areas of higher concentration of Scheduled Tribe

population, have very high gender disparity in literacy. Districts located in the rice bowl of Orissa have

lower disparity in literacy. The poor schooling facilities in the tribal areas might have resulted in higher

gender disparity in literacy there. (Annex: Table no.-14, Map No. -19)

3.4.b Gender Disparity in IMR:

Disparity in Infant Mortality Rate is measured as number of female infant death per 1000 of male infant

death.

While the levels of infant and child mortality in Orissa are very high, the gender differential in infant

mortality is not. The NFHS data in Orissa reveals that in both the neonatal and postnatal period males

have higher risks of dying than females do. The biological factor still prevails the social prejudice only

occurs after age one.

The districts with high disparity in IMR are Angul, Dhenkanal, Baragarh, Ganjam, and Sundergarh. The

districts, which have comparatively low disparity, are Kalahandi, Keonjhar and Nawapara. (Annex: Table no.- 15 , Map No. -20)

3.4.c Gender Disparity in CMR:

Child mortality in Orissa is 45 percent higher for females than for males. This reversal of sex

differentials in mortality after the age of weaning reflects the relative nutritional and medical neglect of

girls after breast-feeding has ceased. Angul, Baleshwar, Bhadrak, Bolangir Cuttack, Jagatsinghpur,

Jajpur, Kendrapara, Sonepur have high disparity in CMR. Puri, Khurdah, Nayagarh and Kalahandi

show low disparity in CMR.

The districts showing highest vulnerability of women are Nawarangpur, Sonepur, Bolangir, Boudh and

Kandhamal.

The moderates vulnerable districts are Jajpur, Kendrapara, Jharsaguda and Sundergarh whereas

comparatively better situation in Puri, Khurdah, Mayurbhanj and Nayagarh. (Annex: Table no.- 15 , Map No. –21)

3.4.d. Sex Ratio:

Sex composition in Orissa is gradually becoming more and more male dominated with each passing

decade. In 1901, there were 1,039 females per 1000 males. This declined to 1022 females in 1951 and in

1991 the figure was only 972 females per 1,000 males.

Sex ratio is generally measured as number of female per 1000 male. The data thus computed generally

reveals better situation with higher value. But since in this particular study all the indicators needs to be

unidirectional, this indicator here has been computed as male per 1000 female, revealing higher the

value more the vulnerability.

The sex ratio of Orissa as a whole is 1014 males per 1000 females in the age group of 0-16. In the age

group of 0-16 the social factors are more dominating in determining the sex ratio and in these ages the

effect of migration is very less.

The distribution reveals that a continuous belt in the northern coastal and the adjacent districts have

higher sex ratio (in favour of males). These districts are also having higher concentration of SC

population. Southern, central and western districts are having sex ratio in favour of females. These

districts are having more ST population. Sex ratio in favour of females in tribal areas are attributed to

the facts that women enjoy an equal or even higher status among tribal societies and female child is

desirable. (Annex: Table no.- 16, Map No. –22)

It has been observed that whenever both the sexes receive comparable attention and care, females have

better survival advantages over males in terms of age specific mortality rates.

3.4.e Composite Gender Inequality Index

The districts showing highest vulnerability of women are Nawarangpur, Sonepur, Bolangir, Boudh and

Kandhamal.

The moderately vulnerable districts are Jajpur, Kendrapara, Jharsaguda and Sundergarh whereas

comparatively better situation in Puri, Khurdah, Mayurbhanj and Nayagarh. (Annex: Table no.- 17 , Map No. -23)

3.5 MORTALITY AND MALNUTRITION

3.5.a Infant Mortality Rate:

Infant mortality rate (IMR) is defined as the number of death of the infants (below one year) per 1000

live births.

The level of infant mortality rate in Orissa is the highest (120) as against (80) all India average.

Accordingly to the NFHS study (1995) Neonatal and IMR for the Scheduled Tribe (113.4) are less than

the same for Scheduled Castes and other castes (160.8 & 115.0 respectively). The IMR rate is higher in

rural areas than in urban areas, 126 per 1000 live births compared with 85 per 1000. The NFHS data also

have revealed that IMR declines sharply with the increasing education of mothers

The Census of India has estimated the infant mortality rate using the indirect method of Brass technique.

Three districts (Puri, Khurdah and Nayagarh) which have very low disparity in IMR and CMR have

very IMR. Low IMR are observed in Angul, Deogarh, Dhenkanal, Keonjhar, Mayurbhanj and

Sundergarh, Sambalpur. High IMR is seen in Gajapati, Ganjam, Khurdah and Puri. (Annex: Table no.-18 , Map No. -24)

3.5.b Child Mortality Rate :

Child mortality rate (CMR) is defined as the number of death of the children below 5 years per 1000 live

births. The Census of India has estimated this child mortality rate using the indirect method of Brass

technique. The district wise picture of child mortality is more or less similar with the IMR.

Bhadrak, Puri, Kandhamal, Boudh, Khurdah and Nayagarh have high CRM, whereas low, CMR is

observed in Mayurbhanj, Sambalpur and Baragarh. (Annex: Table no.-18 , Map No. -25)

3.5. c Prevalence of Malnutrition:

Both chronic and acute under nutrition are very common in Orissa. Accordingly to the NFHS (1992)

report slightly more than half (53%) of all children are underweight and 48% are stunted. Malnutrition is

a physical manifestation of inability to receive adequate nutrition or the inability of the body to

assimilate normally. Under nutrition is lowest in the first six months when most babies are being fully

breastfed. There is a marked increase in the prevalence of under nutrition in the first year.

In Orissa malnutrition is consistently higher in rural than in urban areas. The socio-economic status of

the family and the mothers schooling are important for children’s nutritional status. Unfortunately, the

majority of young children in Orissa has illiterate mothers and is consequently at high risk of suffering

under nutrition.

Prevalence of malnutrition is measured for children below 5 years of age as weight for age as

standardised by Gomez classification. Both the categories of moderate and server malnourished are

combined to identify the percentage of malnourished children. The Data available was for children of

the age group of 0-3 and 3-6 years.

The distribution shows percentage of severely and moderately malnourished children are high in

Gajapati, Kalahandi, Boudh Nawapara, Nawarangpur and Khurdah. Comparatively less percentage are

seen in Baragarh, Mayurbhanj, Sundergarh, Cuttack, Jharsaguda, Deogarh Dhenkanal & Sambalpur.

(Annex: Table no.-19, Map No. –26A, 26B)

3.5.d Population per Anganwadi Centre (AWC):

Anganwadi centre is the unit through which the programmes of Integrated Child Development Scheme

(ICDS) are implemented. The universalised network of ICDS provides vital services in the

disadvantaged areas. They are – immunisation, Health, check up, referral services, Treatment of minor

illness, Supplementary Feeding, Growth monitoring and promotion, nutrition and health education and

early childhood care and pre-school education.

The sanctioned norm for Anganwadi Centres (AWC) is 750 population per AWC when the block is

tribal and 1000 population per AWAC when the blocks are dominated by non-tribal population. The

pressure on AWC is lower in the districts of higher tribal population. Districts with very high population

pressure per AWC are Ganjam, Kendrapara, Nayagarh, Puri, Khurdah, Dhenkanal, Bhadrak and

Baleshwar. Kandhamal Mayurbhanj, Rayagada, Sundergarh and Gajapati have low population pressure

on each Anganwadi Centre. (Annex: Table no. - 20, Map No. - 27)

3.5.e Composite Mortality and Malnutrition Index

The individual values of Infant Mortality Rate and Child Mortality Rate have been added and divided by

2 to arrive at Mortality Index. The indicator of Population supported by Anganwadi is an intervention

variable just like the safety net taking care of vulnerability, and does not add to it. This indicator has

been kept out of the composite Index.

Unit free value of Malnutrition and Mortality were aggregated and divided by the number of indicator.

Gajapati, Kalahandi Khurdah, Puri and Nawapara are mot vulnerable to mortality and malnutrition.

Mayurbhanj, Balagarh, Sundergarh, Jharsaguda and Deogarh show comparatively better situation.

(Annex: Table no.- 21, Map No. -28)

CHAPTER IVCOMPOSITE INDEX

4.1 Composite Vulnerability Index with all Broad Categories

To arrive at an overall image of the state in regard to vulnerability all the broad categories of

Vulnerability Indices were aggregated and divided by 5.

The distribution shows that the districts of Ganjam, Gajapati, Mayaurbhanj, Bhadrak, Jagatsinghpur,

Baleshwar, Keonjhar, Puri, Cuttack, Dhenkanal, Kendrapara and Jajpur are less vulnerable.

The Tribal districts of Kandhamal, Nawapara, and Baragarh, Angul Boudh, Kalahandi are the most

vulnerable to food insecurity.

The overall situation reflects that the poor deprived and tribal districts are more vulnerable to food

insecurity whereas the coastal districts are comparatively better off. (Annex: Table no.-22, Map No. -29)

4.2 Interrelationship of Indicators

Detailed nature of relationship of the indicators with each other is presented in the table of correlation

matrix and the statistically significant relationships are discussed.

Among the indicators of Sustenance Insecurity, population supported by 100 quintals of cereal and

seasonality of cereal production are found to have no significant relationship with any other indicators

(except significant association between seasonality and inadequacy of safety net system). But the

indicator inadequacy of safety net index has significant relationship with several indicators. In an

expected way, areas with higher seasonality of crop production, illiteracy, disparity in literacy, ST

population, child labour, malnutrition of the children have better safety net cover. With all these

indicators inadequacy of safety net index shows a significant negative relationship. However, the safety

net cover is less in the districts of higher IMR and CMR - which is quite unexpected.

Among the indicators of disasters, crop loss is found to be higher in the districts of higher disparity in

IMR and population per AWC, and lower in the districts of higher BPL population, ST population,

illiteracy and child labour. While the districts under DPAP have higher disparity in literacy and child

labour and lower sex ratio.

As it is expected, families below poverty line shows significant positive association with illiteracy,

disparity in literacy, ST population, child labour and malnutrition of the children (3-6) and negative

association with AWC. The indicator, Scheduled Castes (SC) has positive relationship with disparity in

CMR and AWC while negative relationship with ST population, illiteracy and malnutrition of the

children (0-3). The negative relationship of SC with illiteracy and malnutrition is quite unexpected.

Scheduled tribes show positive association with illiteracy, disparity in literacy, child labour and

malnutrition of the children and, negative association with AWC and CMR. Sex ratio shows a positive

relationship with AWC and negative relationship with disparity in literacy and child labour. Here, the

direction of relationship of sex ratio with disparity in literacy is contrary to our expectation because male

favoured sex ratio is expected to lead higher disparity in literacy. Higher illiteracy shows higher

disparity in literacy, child labour and higher malnutrition among children. The indicator is found to have

negative association with AWC. It is usually noticed that most of the child labourers are engaged in

agricultural sector. Thus, child labour shows positive association agricultural labourers. It also shows a

positive relationship with disparity in literacy and malnutrition and a negative association with AWC.

Disparity of IMR and CMR are positively related among themselves and negatively related with IMR

and CMR. Net out migration has only significant positive relationship with AWC.

IMR and CMR, like disparity in IMR and CMR, are also positively related among themselves and they

are also positively related with AWC. CMR is negatively related with ST and disparity in CMR is

positively related with SC reveals the fact of higher gender discrimination among SCs. Malnutrition of

the children 0-3 and 3-6 years show positive relationship among themselves and negative relationship

with AWC. (Annex: Table no.-23 )

4.3 Composite Index with Selected Indicators – ‘The Rationale’

Affluence has similar manifestation whereas there are different dimensions of manifestation of poverty.

Among the 20 indicators selected for the present exercise some can be grouped as input indicators, some

as intervention indicators and some as the output indicators. The input indicators are those, which are

causing vulnerability to food insecurity, e.g. Population supported by cereal production, General

Inequality Indicators and Disaster indicators. The output indicators being those which are manifestations

of vulnerability e.g. Mortality indicators and Below poverty line population. The indicators like the

safety net and population supported by Anganwadi centres in a intervention variable. They are designed

to take care of Vulnerability.

To get a perfect picture of the vulnerable regions of the state, selection of indicators and the number of

indicator chosen are essential. The regions constructed through the indicators would change with the

changing indicators.

The main objective of this exercise being mapping of vulnerability to food insecurity, it is necessary to

choose indicators that are the manifestations of poverty and food insecurity.

Four very typical indicators were chosen keeping the objective in view. They are:

1) Below Poverty Line Population – Manifestation of Poverty

2) Mortality

3) Malnutrition, both being physical manifestation of vulnerability, and

4) Migration.’

The composite index constructed with the selected indicators show that Ganjam, Gajapati, Mayurbhanj

Bolangir, Sonepur, Dhenkanal are less vulnerable to as far as these indicators are concerned.

The coastal districts of Puri, Cuttack, Keonjhar, Kalahandi are moderately vulnerable whereas the most

vulnerable districts are Deogarh, Sambalpur, Baragarh, Jharasaguda, Boudh, Sundergarh, Kandhamal &

Koraput. (Annex: Table no.- 24)

4.4 Pattern of Safety net Coverage in the State

As discussed earlier that within the 20 chosen indicators two indicators are intervention variables and

they are not manifestations of vulnerability to food insecurity and rather take care or control

vulnerability. These two are Safety net and Population Supported by Anganwadi Centre. Mapping of

these indicators was done in such a way that the data revealed more the higher the vulnerability. The

indicators were named as Inadequacy of safety net and Population supported by AWC.

Given the present situation of food insecurity to see the pattern of safety net coverage in the state of

Orissa the safety net index was calculated. The indicators were changed to Existence of Safety net and

number of AWC per 1000 population. The scale free values were aggregated and then divided by 2 to

arrive at the composite score. The composite score will reveal better coverage with higher value.

The distribution of the score shows that the vulnerable districts like Rayagada, Malkangir, Sundergarh,

Sonepur, Kandhamal, Nawapara have better safety net coverage than the coastal districts which are less

vulnerable. (Annex: Table no.-25)

CHAPTER IVCOPING STRATEGY

Physiographically Orissa can be divided into 3 broad divisions and there are 10 distinctive agro-climatic

zones. All these agro-climatic zones have distinctive characteristics and are results of different weather

conditions. As a result the kind of natural disaster which is likely to take over in these regions would

also differ. The coastal areas are more likely to face flood and cyclones whereas the inner districts would

experience drought and consecutive famine.

The coping mechanism for different kinds of natural disaster would differ with different regions and

from community to community. Different communities would have different indigenous coping

mechanisms to mitigate the effects of drought.

Look for alternative employment options / Working for long hours/ low wage

Com

mitm

ent of D

omestic

Resources

Time

LowH

igh

Borrowing grain/money

Mortgaging productive asset

Sale of Girl Child

Sale of Livestock

Mortaging of Household assets

Sale of utensils

Migration

Skipping meals

Shift to non conventional food items

Starvation

COPING STRATEGY

From a study done in the district of Bolangir1 it has been found that when there is drought the first

damage gets reflected through crop loss. There will be immediate decrease in household income and the

landless labourers working in others field will loose their employment. Lack of employment arising

from crop loss is believed to result in migration opportunities, sub normal wages delayed payment of

wages and distress.

A poor farmer first seeks loan or looks for alternative options to generate funds to mitigate his loss in the

field. This often leads to depletion of household assets, which are sold off for raising money. Scarcity of

money leads to sale of lands, mortgage of lands, sale of utensils, cattle, goat, sheep and even sale of girl

child.

In earlier days using sturdier traditional varieties of seeds of paddy could reduce the impacts of drought,

which are no longer available to the farmers and also not available in the market. During drought the

consumption pattern of the poor people also shifts to non-conventional food items. People’s dependence

on rice as a staple food declines in the wake of droughts and shifts mainly to tubers, leaves, fibres, fruits

and several forms of minor millets. Daily food intake is also reduced from thrice to twice and even to

one skimpy meal. During prolonged droughts a handful of rice is used for several times. It is tied to one

end of cloth and dipped in boiling water. Pieces of Mahua flowers are added to the boiling water with

smell of rice. The syrup thus prepared is then consumed. The rice tied in the cloth is again reused the

next day. This cycle continues till the rice totally loses its character.

People living close to forest survive on flesh of wild reptiles and animals. Small farmer owning two to

three acres of land sometimes grow vegetable to minimise stress of drought. However rarely the

situation deteriorates to starvation as the state intervenes by supplying foodgrains through the PDS .

The ultimate stress-coping mechanism is to migrate from the village to nearby urban areas in search of

employment. Popular destinations are brick kilns in Andhra Pradesh , irrigation projects within the state

or construction. Migration to urban areas enables people to tide over the lean months and earn just

enough for their subsistence.

1 Participatory Poverty Profile Study, Bolangir District, Orissa, June-Aug, 1998, DFID- Praxis.

Annex I

REFERENCES

1. State Orissa’s Environment, 1994, Council of Professional Social Workers.2. DFID Study on Orissa3. Natural Hazards Map of India, Natmo, 1991, Department of Science and Technology,

Govt. of India.4. Vulnerability Atlas of India, 1997, Building Materials and Technology Promotion

Council, Ministry of Urban Development , Govt. of India.5. IFAD evaluation of Orissa Project6. Impact of WFP Orissa Project – An Evaluation, 1995.7. WFP Generated Funds Investment on Targeted Population of Orissa.8. ‘Public Health Services and Vulnerable Groups : a study related to the issues of access,

affordability, pattern of utilization and financing in government health services in Orissa’ Oxfam, June 1999.

9. ‘Micro health and education research, Koraput site report’ Oxfam10.‘Micro health and education research, Keonjhar site report’ Oxfam11.‘Micro health and education research, Puri site report’ Oxfam12.Sinha, B. N. Geography of Orissa, National Book Trust, 199913.Economic Survey, 1998-99, Govt. of Orissa14.Status of Women in Orissa, CENDERET, Xavier Institute of Management, Orissa, 1996.15.Breaking the shackles of HUNGER, Process Documentation on the Orissa Household

Food Security Project (1993-98), UNICEF and Govt. of Orissa.16.Dreeze, Jean and Sen Amartya, India-Economic Development and Social Opportunity

Oxford University Press, Delhi., 199617.Govt. of India, Census of India, Fertility Indicators, 1991.18.Govt. of India, Final population Totals: Brief Analysis of primary Census Abstract,

Census of India (1991, Paper-2 of 1992).19.Kundu, A, Measurement of Urban Process, A study in regionalisation, Popular,

Prakashan, Bombay, 1998.20.NCAER – Human Development profile of India Inter State and Inter Groups

Differentials.Vol. II Statistical Tables, New Delhi, 1996.21.Prabhu, K. Seeta and P.C. Sarkar, Identification of Levels of Development, Economic

and Political Weekly, Vol. XXVII (36), p.p 1927-37, 1992.22.Profile of District, Centre for Monitoring Indian Economy Bombay-400025, 1993

23.Reidar Dale, Evaluation Frameworks for Development Programmes and Projects, Sage Publications India Pvt. Ltd., New Delhi, 1998.

24.UNDP Human Development Report, Oxford University Press, New Delhi- 1, 1999.25. A. Shariff and A. Kundu, State of Human Development in India and the Deprived

Districts in the Selected States, Research supported by DFID, 1998.26. A. Shariff and A. Kundu, Poverty Deprivation and Levels of Living in Andhra Pradesh,

Orissa and West Bengal, Research supported by DFID, 1998.27. Dipendra Nath Das, Child Labour in India, Sane Publications, New Delhi, 199628.Ruchi Tripathi, The Urmul experience in promoting grain banks,1998.29.Manas Ranjan Mishra, Some critical issues in KENDU leaf collection & marketing in

Orissa.30.Cyclone oB5 Eastern Orissa, India, Internal Assessment Report, Nov. 1999.31.Geeta Menon, The Impact of Migration on the Work and Status of Tribal Women in

Orissa.32.Social and Institutional analysis and livelihood systems study of tribal communities in

some selected villages in Kandhamal and gajapati districts of Orissa.

Annex II

Sources of Data:The data of the above mentioned selected indicators have been collected from different sources. The indicator, its source and year are given below:

Individual Indicators Source of data YearPopulation supported by 100 quintals of cereal production.

Govt. of Orissa, Directorate of Economics & Statistics

1993-98(5-year average)

Seasonality in Cereal Production

Govt. of Orissa, Directorate of Economics & Statistics

1993-98(5-year average

Existence of Safety Net1.Employment Assurance Scheme(EAS)2. Presence of CARE

3. Presence of WFP

Govt. of Orissa, Department of Panchayati Raj

Govt. of Orissa, Department of Women & Child DevelopmentUnited Nations World Food Programme

1999 (September)

1999

1999

Scarcity index (crop loss) Govt. of Orissa, Department of Revenue and Excise

1996-97

State declared disaster prone areas

Govt. of Orissa, Department of Rural Development

1999

Percentage of Population below Poverty Line

Govt. of Orissa, Department of Panchayati Raj

1997

Concentration of SC/ ST Census of India 1991 1991Migration (net of out and in migration)

Migration Tables, Census of India 1991

1991

Total Literacy Census of India 1991 1991Gender Disparity in Literacy Calculated from available data

from census of India 19911991

Gender disparity in IMR Estimates of child mortality indicator by sex 1991

1991

Gender disparity in CMR Estimates of child mortality indicator by sex 1991

1991

Sex Ratio Census of India 1991 1991State Declared Backward Districts

Planning Commission

Percentage of Working Children

Census of India 1991 1991

Agricultural Labourers Census of India,1991 1991Infant Mortality Rate (IMR) Estimates of child mortality

indicator by sex 19911991

Child Mortality Rate (CMR) Estimates of child mortality indicator by sex 1991

1991

Prevalence of Malnutrition Govt. of Orissa, Department of Women and Child Development

1999 (March)

Population per Anganwadi Centre

Govt. of Orissa, Department of Women and Child Development

1999

Annex III

Orissa

Table 1- POPULATION SUPPORTED BY CEREAL PRODUCTION

DISTRICT Total cereal Production (in

Qtls.)

Total

Population (1995)

Population supported by 100 quintal

cereal

Index

Angul 1972855.8 1028073 52 1.37Baleshwar 5123873.4 1814926 35 0.93

Baragarh 8092558.4 1291377 16 0.42Bhadrak 4094784.8 1182970 29 0.76Bolangir 3800137.6 1316801 35 0.91Boudh 1160774.6 339777 29 0.77Cuttack 9079733.4 2110345 23 0.61Deogarh 919116 250577 27 0.72Dhenkanal 2526795.4 1013987 40 1.06Gajapati 956847.2 486426 51 1.34Ganjam 6715099 2892674 43 1.13Jagatsinghpur 2159109.8 1084989 50 1.32Jajpur 2788330 1482868 53 1.40Jharasuguda 1213547.4 477887 39 1.04Kalahandi 3822656.2 1209788 32 0.83Kandhmal 1097204 584386 53 1.40Kendrapara 3053949.4 1229683 40 1.06Keonjhar 3554718.4 1430289 40 1.06Khurda 2530415.6 1606785 63 1.67Koraput 2734546.4 1101831 40 1.06Malkangir 1580839.4 451347 29 0.75Mayurbhanj 6245612 2016036 32 0.85Nawarangpur 3268777 905717 28 0.73Nawapara 1401483.6 502230 36 0.93Nayagarh 2380161.8 837240 35 0.94Puri 3471247.4 1396419 40 1.06Rayagada 1416254 763787 54 1.42Sambalpur 3475751.8 865449 25 0.66Sonepur 2948723.2 510075 17 0.46Sundargarh 3347018.8 1683383 50 1.32Orissa 91401089.2 33868121 37

Source: Government of Orissa, Directorate of Economic & Statistics

Table 2SEASONALITY IN CEREAL PRODUCTION (in quintal) 1993-94 to 1997-98

DISTRICT Kharif cereals

Rabi cereals Total cereal % of rabi crop

Seasonality

Angul 1873192 99663.8 1972855.8 5.05 0.95Baleshwar 4354861.8 769011.6 5123873.4 15.01 0.82Baragarh 5793747.6 2298810.8 8092558.4 28.41 0.60Bhadrak 3708632.2 386152.6 4094784.8 9.43 0.90Bolangir 3744937 55200.6 3800137.6 1.45 0.99Boudh 1134703.8 26070.8 1160774.6 2.25 0.98Cuttack 8754433.8 325299.6 9079733.4 3.58 0.96Deogarh 858454.4 60661.6 919116 6.60 0.93Dhenkanal 2431237.4 95558 2526795.4 3.78 0.96Gajapati 875403.6 81443.6 956847.2 8.51 0.91Ganjam 6658451.4 56647.6 6715099 0.84 0.99Jagatsinghpur 2013855.6 145254.2 2159109.8 6.73 0.93Jajpur 2511022.6 277307.4 2788330 9.95 0.89Jharasuguda 1195201.2 18346.2 1213547.4 1.51 0.98Kalahandi 3749878.2 72778 3822656.2 1.90 0.98Kandhmal 1049749.8 47454.2 1097204 4.33 0.95Kendrapara 2701697.6 352251.8 3053949.4 11.53 0.87Keonjhar 3453185.8 101532.6 3554718.4 2.86 0.97Khurda 2287381 243034.6 2530415.6 9.60 0.89Koraput 2279891.6 454654.8 2734546.4 16.63 0.80Malkangir 1557390 23449.4 1580839.4 1.48 0.98Mayurbhanj 6094685 150927 6245612 2.42 0.98Nawarangpur 2933866 334911 3268777 10.25 0.89Nawapara 1361692 39791.6 1401483.6 0.71 0.97Nayagarh 2363361.2 16800.6 2380161.8 2.84 0.99Puri 2384326 1086921.4 3471247.4 31.31 0.54Rayagada 1263551 152703 1416254 10.78 0.88Sambalpur 2881492.4 594259.4 3475751.8 17.10 0.79Sonepur 2269275.2 679448 2948723.2 23.04 0.70Sundargarh 3283105.2 63913.6 3347018.8 1.91 0.98Orissa 82290829.8 9110259.4 91401089.2 9.97 0.89Source: Government of Orissa, Directorate of Economics & Statistics

Table 3INADEQUACY OF SAFETY NET SYSTEM

District Total agricultural workers

Average Labour

Employed

% of EAS beneficiaries

Presence of WFP

Presence of CARE

Total Safety net Index

Angul 236353 3122 1.32 1 0 2.34 0.43Balasore 375599 646 0.17 0 0 0.17 5.88Bargarh 376039 7499 1.99 1 1 4.02 0.25Bhadrak 824524 2776 0.34 0 0 0.34 2.94Bolangir 876963 9657 1.10 1 1 3.12 0.32Boudh 409535 2070 0.51 1 1 2.51 0.40Cuttack 1341977 3418 0.25 0 0 0.26 3.92Deogarh 75812 1179 1.56 1 0 2.59 0.39Dhenkanal 695507 3549 0.51 1 0 1.52 0.66Gajapati 173604 4159 2.40 0 1 3.44 0.29Ganjam 1606202 10741 0.67 0 0 0.68 1.47Jagatsinghpur 194644 8400 4.32 0 0 4.38 0.23Jajpur 286867 4101 1.43 0 0 1.45 0.69Jharsuguda 86212 228 0.26 1 0 1.27 0.79Kalahandi 925245 8109 0.88 1 1 2.89 0.35Kandhamal 190255 2409 1.27 1 1 3.29 0.30Kendrapara 227428 6780 2.98 0 0 3.03 0.33Keonjhar 675560 1567 0.23 1 1 2.23 0.45Khurda 208586 1861 0.89 0 0 0.90 1.11Koraput 1424709 8325 0.58 1 0 1.60 0.63Malkangiri 152044 6153 4.05 1 0 5.11 0.20Mayurbhanj 1214789 10153 0.84 1 1 2.85 0.35Nabarangpur 309807 9019 2.91 1 0 3.96 0.25Nayagarh 197115 1837 0.93 0 0 0.95 1.06Nuapada 159646 2792 1.75 1 1 3.78 0.26Puri 946597 1100 0.12 0 0 0.12 8.55Rayagada 253765 10482 4.13 1 1 6.19 0.16Sambalpur 946653 13457 1.42 1 0 2.45 0.41Sonepur 150483 5081 3.38 1 0 4.43 0.23Sundargarh 304352 5585 1.84 1 1 3.86 0.26ORISSA 15846872 156254 0.99

Source: Government of Orissa, Department of Panchayati RajGovernment of Orissa, Department of Women and Child Developmentn United Nations World Food Programme

Table 4

SUSTENANCE INSECURITY INDEX

DISTRICT Population supported by 1 qtl

Seasonality in cereal

Composite Index

Angul 1.37 1.05 1.21

Baleshwar 0.93 0.92 0.92

Baragarh 0.42 0.67 0.55

Bhadrak 0.76 1.00 0.88

Bolangir 0.91 1.10 1.00

Boudh 0.77 1.09 0.93

Cuttack 0.61 1.07 0.84

Deogarh 0.72 1.03 0.88

Dhenkanal 1.06 1.07 1.06

Gajapati 1.34 1.01 1.17

Ganjam 1.13 1.10 1.12

Jagatsinghpur 1.32 1.03 1.18

Jajpur 1.40 0.99 1.20

Jharasuguda 1.04 1.10 1.07

Kalahandi 0.83 1.09 0.96

Kandhmal 1.40 1.06 1.23

Kendrapara 1.06 0.97 1.01

Keonjhar 1.06 1.08 1.07

Khurda 1.67 1.00 1.33

Koraput 1.06 0.89 0.98

Malkangir 0.75 1.10 0.92

Mayurbhanj 0.85 1.09 0.97

Nabarangpur 0.73 0.99 0.86

Nayagarh 0.93 1.11 1.02

Nuapada 0.94 1.08 1.01

Puri 1.06 0.61 0.83

Rayagada 1.42 0.98 1.20

Sambalpur 0.66 0.88 0.77

Sonepur 0.46 0.78 0.62

Sundargarh 1.32 1.09 1.21

Source: Government of Orissa, Department of Revenue and Excise

Table 5

SCARCITY DUE TO DISASTER, 1996-97

Districtcrop loss (in Rs 10

Million)Net Sown Area

(in hect.)Croploss (Rs. Per

hect net sown area)

Angul 18.67 19046 9803Baleshwar 51.3 232099 2210Baragarh 68.4 288540 2371Bhadrak 42.18 176347 2392Bolangir 81.7 287342 2843Boudh 16.34 75924 2152Cuttack 31.92 153545 2079Deogarh 0.38 54970 69Dhenkanal 31.16 138573 2249Gajapati 1.14 61559 185Ganjam 48.64 327884 1483Jagatsinghpur 18.62 111945 1663Jajpur 42.18 147743 2855Jharasuguda 7.6 55284 1375Kalahandi 33.44 264240 1266Kandhmal 7.6 83675 908Kendrapara 52.06 145111 3588Keonjhar 20.9 219305 953Khurda 35.72 118579 3012Koraput 0 405267 0Malkangir 0 117862 0Mayurbhanj 45.22 350643 1290Nawarangpur 1.14 212126 54Nawapara 43.7 111135 3932Nayagarh 8.74 133532 655Puri 36.86 135040 2730Rayagada 5.32 120745 441Sambalpur 11.2 134379 833Sonepur 34.2 97366 3513Sundargarh 0 237693 0Orissa 796.48 5017499 1587

Source: Government of Orissa, Department of Rural Development

Table 6 (a)

STATE DECLARED DROUGHT PRONE AREAS

DISTRICTS UNDER DPAP PROGRAMMEDistrict Total geographical

area (in hect.)Area under

DPAP blocks (in hect.)

No. of DPAP Blocks

% of area under DPAP

programmeAngul 521789.26 - - 0Balasore 333517.25 - - 0Bargarh 476823.58 282790 6 59.3Bhadrak 784835.03 - - 0.0Bolangir 1393578.15 378545 8 27.2Boudh 890501.2 151997 2 17.1Cuttack 1592104.39 - - 0.0Deogarh 186353.03 - - 0.0Dhenkanal 1270205.71 72661 2 5.7Gajapati 452070.33 - - 0.0Ganjam 1708352.61 - - 0.0Jagatsinghpur 175560.22 - - 0.0Jajpur 336145.91 - - 0.0Jharsuguda 176341.39 - - 0.0Kalahandi 1427301.28 450868 10 31.6Kandhamal 462473.22 462474 12 100.0Kendrapara 228511.42 - - 0.0Keonjhar 1867400.78 - - 0.0Khurda 263010.94 - - 0.0Koraput 3233416.17 - - 0.0Malkangiri 363942.74 - - 0.0Mayurbhanj 1424197.62 - - 0.0Nabarangpur 554513.77 - - 0.0Nayagarh 249931.44 - - 0.0Nuapada 318671.68 318671 5 100.0Puri 1047192.08 - - 0.0Rayagada 808498.06 - - 0.0Sambalpur 1669232.11 - - 0.0Sonepur 191436.61 67354 2 35.2Sundargarh 730320.8 - - 0.0Orissa 25138228.78 2185360 47 8.7

Source: Government of Orissa, Department of Panchayati Raj

Table 6 (b)BLOCKS UNDER DPAP

DISTRICT NAME OF THE BLOCKS

BALANGIR BelpadaBongomundaKhaprakholMuribahalPatnagarhSaintalaTitilagarhTurekela

BARAGARH BijepurGaisilatJharbandhPadampurPaikamalSohela

BOUDH HarvangaKantamal

DHENKANAL DhenkanalOdapada

KALAHANDI BhawanipatnaDharamgarhGolmundaJunagarhKalampur

KALAHANDI KesingaLanjigarhMadanpur RampurNarlaThuamul Rampur

KANDHAMAL BaligudaChakapadDaringbodiG.UdyagiriKhajuripadeKotgarhNuagoonPhiringiaPhulbaniRoikiaTikaballiTumuribandha

NAWAPARA BodenKhariarKomnaNawaparaSinapalli

SONEPUR BirmaharajpurTarva

Source: Government of Orissa, Department of Rural Development

Table 7COMPOSITE DISASTER INDEX

DISTRICT Crop loss DPAP Area Composite Index

Angul 5.17 0.00 2.58

Baleshwar 1.17 0.00 0.58

Baragarh 1.25 4.73 2.99

Bhadrak 1.26 0.00 0.63

Bolangir 1.50 2.17 1.83

Boudh 1.13 1.36 1.25

Cuttack 1.10 0.00 0.55

Deogarh 0.04 0.00 0.02

Dhenkanal 1.19 0.46 0.82

Gajapati 0.10 0.00 0.05

Ganjam 0.78 0.00 0.39

Jagatsinghpur 0.88 0.00 0.44

Jajpur 1.50 0.00 0.75

Jharasuguda 0.72 0.00 0.36

Kalahandi 0.67 2.52 1.59

Kandhmal 0.48 7.98 4.23

Kendrapara 1.89 0.00 0.95

Keonjhar 0.50 0.00 0.25

Khurda 1.59 0.00 0.79

Koraput 0.00 0.00 0.00

Malkangir 0.00 0.00 0.00

Mayurbhanj 0.68 0.00 0.34

Nabarangpur 0.03 0.00 0.01

Nayagarh 2.07 0.00 1.04

Nuapada 0.35 7.98 4.16

Puri 1.44 0.00 0.72

Rayagada 0.23 0.00 0.12

Sambalpur 0.44 0.00 0.22

Sonepur 1.85 2.81 2.33

Sundargarh 0.00 0.00 0.00

Table 8

POPULATION BELOW POVERTY LINE

DISTRICT % of population below

poverty line

%P_BPL

Angul 58.1 0.88Balasore 73.7 1.11Bargarh 60.4 0.91Bhadrak 55.3 0.83Bolangir 59.4 0.90Boudh 80.2 1.21Cuttack 50.1 0.76Deogarh 77.9 1.17Dhenkanal 68.0 1.03Gajapati 60.8 0.92Ganjam 53.5 0.81Jagatsingpur 52.5 0.79Jajpur 60.4 0.91Jharsuguda 44.3 0.67Kalahandi 63.1 0.95Kandhamal 78.4 1.18Kendrapara 55.9 0.84Keonjhar 75.0 1.13Khurda 58.3 0.88Koraput 84.6 1.28Malkangir 81.9 1.23Mayurbhanj 77.9 1.17Nabarangpur 73.7 1.11Nayagarh 64.7 0.98Nuapada 82.4 1.24Puri 71.2 1.07Rayagada 72.0 1.09Sambalpur 61.2 0.92Sonepur 69.7 1.05Sundargar 65.2 0.98ORISSA 66.0

Source: Government of Orissa, Department of Panchayati Raj

Table 9

SCHEDULED CASTES (SC) AND SCHEDULED TRIBES (ST) INDEX

DISTRICT %_SC %_STAngul 16.82 11.68

Balasore 18.57 10.57

Bargarh 18.44 19.56

Bhadrak 21.71 1.69

Bolangir 15.39 22.06

Boudh 19.64 12.92

Cuttack 18.19 3.49

Deogarh 14.60 33.31

Dhenkanal 16.03 12.68

Gajapati 8.77 47.88

Ganjam 17.91 2.93

Jagatsingpur 21.72 0.61

Jajpur 22.87 7.40

Jharsuguda 17.15 31.88

Kalahandi 17.01 28.88

Kandhamal 18.21 51.51

Kendrapara 19.83 0.40

Keonjhar 11.49 44.52

Khurda 13.62 5.14

Koraput 13.41 50.67

Malkangir 19.96 58.36

Mayurbhanj 6.99 57.87

Nabarangpur 15.09 55.27

Nayagarh 13.78 5.96

Nuapada 13.09 35.95

Puri 18.56 0.27

Rayagada 14.28 56.04

Sambalpur 17.07 35.08

Sonepur 22.11 9.50

Sundargar 8.78 50.74

ORISSA 16.0 22.0Source: Census of India 1991

Table 10

NET OUT MIGRATION INDEX

DISTRICT Net out migration

Angul 1.00

Balasore 0.43

Bargarh -4.17

Bhadrak 0.43

Bolangir 1.84

Boudh -2.51

Cuttack -2.55

Deogarh -4.17

Dhenkanal 1.00

Gajapati 4.59

Ganjam 4.59

Jagatsingpur 0.08

Jajpur 0.08

Jharsuguda -4.17

Kalahandi 0.06

Kandhamal -2.51

Kendrapara 0.08

Keonjhar -0.30

Khurda 0.00

Koraput -2.41

Malkangir -2.41

Mayurbhanj 2.76

Nabarangpur -2.41

Nayagarh 0.00

Nuapada 0.06

Puri 0.00

Rayagada -2.41

Sambalpur -4.17

Sonepur 1.84

Sundargar -3.42

Source: Migration Tables, census of India 1991

Table11

ILLITERACY

District Male literacy Female literacy Total illiteracy Total literacyAngul 67.66 34.32 48.47 51.53Balasore 71.23 43.4 42.36 57.64Bargarh 63.78 31.21 52.35 47.65Bhadrak 74.62 46.35 39.46 60.54Bolangir 55.64 21.3 61.37 38.63Boudh 60.61 21.01 59.02 40.98Cuttack 77.3 52.47 34.56 65.44Deogarh 59.23 29.26 55.55 44.45Dhenkanal 68.8 40.33 45.09 54.91Gajapati 41.76 17.44 70.63 29.37Ganjam 63.88 29.87 53.28 46.72Jagatsinghpur 78.41 52.94 34.22 65.78Jajpur 70.5 45.29 42.00 58Jharsuguda 67.21 37.01 47.36 52.64Kalahandi 46.85 15.28 68.92 31.08Kandhamal 54.68 19.82 62.77 37.23Kendrapara 76.82 50.67 36.39 63.61Keonjhar 59.04 30.01 55.27 44.73Khurda 78.7 55.39 32.28 67.72Koraput 33.99 15.15 75.36 24.64Malkangiri 28.22 11.69 79.96 20.04Mayurbhanj 21.84 23.68 62.12 37.88Nabarangpur 28.1 9.01 81.38 18.62Nayagarh 73 40.74 42.80 57.2Nuapada 42.31 12.78 72.48 27.52Puri 76.83 49.41 36.70 63.3Rayagada 36.53 15.63 73.99 26.01Sambalpur 65.94 36.48 48.44 51.56Sonepur 61.48 23.38 57.38 42.62Sundargarh 65.41 39.6 47.03 52.97ORRISA 63.09 34.68 50.91 49.09

Source: Census of India 1991

Table 12

WORKING CHILDREN AND AGRICULTURAL LABOURER INDEX

DISTRICT % of child labour to total children(5-14)

% of agricultural labourers to total primary workers

Angul 4.61 38.82

Balasore 2.01 33.64

Bargarh 7.75 40.55

Bhadrak 2.01 28.08

Bolangir 8.52 38.17

Boudh 9.49 39.27

Cuttack 1.24 36.19

Deogarh 7.75 36.28

Dhenkanal 4.61 42.27

Gajapati 8.09 40.33

Ganjam 8.09 43.19

Jagatsingpur 1.24 30.28

Jajpur 1.24 38.93

Jharsuguda 7.75 38.43

Kalahandi 12.54 45.74

Kandhamal 9.49 40.94

Kendrapara 1.24 25.83

Keonjhar 4.89 30.75

Khurda 2.44 36.27

Koraput 12.69 38.50

Malkangir 12.69 16.16

Mayurbhanj 7.34 38.83

Nabarangpur 12.69 40.04

Nayagarh 2.44 35.29

Nuapada 12.54 34.79

Puri 2.44 33.41

Rayagada 12.69 49.27

Sambalpur 7.75 43.02

Sonepur 8.52 40.36

Sundargar 6.06 29.42

ORISSA 5.87 36.77

Source: Census of India in 19991

Table 13COMPOSITE DEPRIVATION INDEX

District %BPL % SC % ST Net Migration Illiterate Child labour

Agri.Labour

Composite Index

Angul 0.88 1.03 0.46 -1.58 0.90 0.68 1.06 0.49

Baleshwar 1.11 1.13 0.41 -0.68 0.78 0.30 0.91 0.57

Baragarh 0.91 1.13 0.77 6.61 0.97 1.15 1.10 1.81

Bhadrak 0.83 1.33 0.07 -0.68 0.73 0.30 0.76 0.48

Bolangir 0.90 0.94 0.87 -2.92 1.14 1.26 1.04 0.46

Boudh 1.21 1.20 0.51 3.99 1.09 1.40 1.07 1.50

Cuttack 0.76 1.11 0.14 4.05 0.64 0.18 0.98 1.12

Deogarh 1.17 0.89 1.31 6.61 1.03 1.15 0.99 1.88

Dhenkanal 1.03 0.98 0.50 -1.58 0.84 0.68 1.15 0.51

Gajapati 0.92 0.54 1.88 -7.29 1.31 1.20 1.10 -0.05

Ganjam 0.81 1.09 0.11 -7.29 0.99 1.20 1.17 -0.27

Jagatsinghpur 0.79 1.33 0.02 -0.12 0.63 0.18 0.82 0.52

Jajpur 0.91 1.40 0.29 -0.12 0.78 0.18 1.06 0.64

Jharasuguda 0.67 1.05 1.25 6.61 0.88 1.15 1.05 1.81

Kalahandi 0.95 1.04 1.13 -0.09 1.28 1.86 1.24 1.06

Kandhmal 1.18 1.11 2.02 3.99 1.16 1.40 1.11 1.71

Kendrapara 0.84 1.21 0.02 -0.12 0.67 0.18 0.70 0.50

Keonjhar 1.13 0.70 1.75 0.48 1.02 0.72 0.84 0.95

Khurda 0.88 0.83 0.20 0.01 0.60 0.36 0.99 0.55

Koraput 1.28 0.82 1.99 3.82 1.40 1.88 1.05 1.75

Malkangir 1.23 1.22 2.29 3.82 1.48 1.88 0.44 1.77

Mayurbhanj 1.17 0.43 2.27 -4.38 1.15 1.09 1.06 0.40

Nabarangpur 1.11 0.92 2.17 3.82 1.51 1.88 1.09 1.79

Nayagarh 0.98 0.84 0.23 0.01 0.79 0.36 0.96 0.60

Nuapada 1.24 0.80 1.41 -0.09 1.34 1.86 0.95 1.07

Puri 1.07 1.13 0.01 0.01 0.68 0.36 0.91 0.60

Rayagada 1.09 0.87 2.20 3.82 1.37 1.88 1.34 1.80

Sambalpur 0.92 1.04 1.38 6.61 0.90 1.15 1.17 1.88

Sonepur 1.05 1.35 0.37 -2.92 1.06 1.26 1.10 0.47

Sundargarh 0.98 0.54 1.99 5.43 0.87 0.90 0.80 1.64

Table 15

GENDER DISPARITY IN IMR & CMR

DISTRICT Disparity in IMR Disparity in CMR

Angul 1177 1027

Balasore 830 1062

Bargarh 953 970

Bhadrak 830 1062

Bolangir 934 1083

Boudh 912 948

Cuttack 932 1123

Deogarh 953 970

Dhenkanal 1177 1027

Gajapati 955 1007

Ganjam 955 1007

Jagatsingpur 932 1123

Jajpur 932 1123

Jharsuguda 953 970

Kalahandi 695 882

Kandhamal 912 948

Kendrapara 932 1123

Keonjhar 709 993

Khurda 807 778

Koraput 908 993

Malkangir 908 993

Mayurbhanj 926 976

Nabarangpur 908 993

Nayagarh 807 778

Nuapada 695 882

Puri 807 778

Rayagada 908 993

Sambalpur 953 970

Sonepur 934 1083

Sundargar 990 991

ORRISA 860 831

Source: Estimate of Child mortality indicator by sex 1991

Table 16

SEX RATIODISTRICT Sex ratio

(male per 1000 female in 0-16 age group)

Angul 987Balasore 1017Bargarh 1003Bhadrak 1017Bolangir 1015Boudh 1004Cuttack 1023Deogarh 1003Dhenkanal 987Gajapati 1013Ganjam 1013Jagatsingpur 1023Jajpur 1023Jharsuguda 1003Kalahandi 995Kandhamal 1004Kendrapara 1023Keonjhar 1001Khurda 1021Koraput 1013Malkangir 1013Mayurbhanj 1037Nabarangpur 1013Nayagarh 1021Nuapada 995Puri 1021Rayagada 1013Sambalpur 1003Sonepur 1015Sundargar 1020ORRISA 1014

Source: Census of India in 1991

Table 14

GENDER DISPARITY IN LITERACY

DISTRICT Disparity in literacy

Angul 1.97

Balasore 1.64

Bargarh 2.04

Bhadrak 1.61

Bolangir 2.61

Boudh 2.88

Cuttack 1.47

Deogarh 2.02

Dhenkanal 1.71

Gajapati 2.39

Ganjam 2.14

Jagatsingpur 1.48

Jajpur 1.56

Jharsuguda 1.82

Kalahandi 3.07

Kandhamal 2.76

Kendrapara 1.52

Keonjhar 1.97

Khurda 1.42

Koraput 2.24

Malkangir 2.41

Mayurbhanj 0.92

Nabarangpur 3.12

Nayagarh 1.79

Nuapada 3.31

Puri 1.55

Rayagada 2.34

Sambalpur 1.81

Sonepur 2.63

Sundargar 1.65

ORRISA 1.82

Source: Census of India 1991

Table 17

DISTRICT DIS_LIT DIS_IMR DIS_CMR Males/1000Females(0-16)

Composite Index

Angul 0.96 1.30 1.04 0.98 1.07Baleshwar 0.80 0.91 1.07 1.01 0.95Baragarh 0.99 1.05 0.98 0.99 1.00Bhadrak 0.78 0.91 1.07 1.01 0.94Bolangir 1.27 1.03 1.10 1.00 1.10Boudh 1.40 1.00 0.96 0.99 1.09Cuttack 0.71 1.03 1.14 1.01 0.97Deogarh 0.98 1.05 0.98 0.99 1.00Dhenkanal 0.83 1.30 1.04 0.98 1.03Gajapati 1.16 1.05 1.02 1.00 1.06Ganjam 1.04 1.05 1.02 1.00 1.03Jagatsinghpur 0.72 1.03 1.14 1.01 0.97Jajpur 0.75 1.03 1.14 1.01 0.98Jharasuguda 0.88 1.05 0.98 0.99 0.98Kalahandi 1.49 0.77 0.89 0.98 1.03Kandhmal 1.34 1.00 0.96 0.99 1.07Kendrapara 0.74 1.03 1.14 1.01 0.98Keonjhar 0.95 0.78 1.00 0.99 0.93Khurda 0.69 0.89 0.79 1.01 0.84Koraput 1.09 1.00 1.00 1.00 1.02Malkangir 1.17 1.00 1.00 1.00 1.04Mayurbhanj 0.45 1.02 0.99 1.03 0.87Nabarangpur 1.51 1.00 1.00 1.00 1.13Nayagarh 0.87 0.89 0.79 1.01 0.89Nuapada 1.61 0.77 0.89 0.98 1.06Puri 0.75 0.89 0.79 1.01 0.86Rayagada 1.13 1.00 1.00 1.00 1.04Sambalpur 0.88 1.05 0.98 0.99 0.98Sonepur 1.28 1.03 1.10 1.00 1.10Sundargarh 0.80 1.09 1.00 1.01 0.98

Table 18

INFANT AND CHILD MORTALITY RATE, 1991

District IMR CMR

Angul 105 148Balasore 123 164

Bargarh 103 131

Bhadrak 123 164

Bolangir 101 139

Boudh 119 170

Cuttack 112 142

Deogarh 103 131

Dhenkanal 105 148

Gajapati 133 149

Ganjam 133 149

Jagatsinghpur 112 142

Jajpur 112 142

Jharsuguda 103 131

Kalahandi 137 158

Kandhamal 119 170

Kendrapara 112 142

Keonjhar 99 137

Khurda 151 172

Koraput 118 140

Malkangiri 118 140

Mayurbhanj 91 125

Nabarangpur 118 140

Nayagarh 151 172

Nuapada 137 158

Puri 151 172

Rayagada 118 140

Sambalpur 103 131

Sonepur 101 139

Sundargarh 101 115ORISSA 125 133

Source: Estimates of Child mortality indicator by sex 1991

Table 19

PERCENTAGE OF CILDREN SUFFERING FROM MALNUTRITION, 1998

District Malnourished children (0-3 years)

Malnourished children (3-6 years)

Angul 32.29 26.27

Balasore 25.73 24.01

Bargarh 25.79 20.67

Bhadrak 23.41 23.48

Bolangir 30.63 29.02

Boudh 35.15 29.11

Cuttack 23.48 20.93

Deogarh 28.79 25.79

Dhenkanal 24.29 24.92

Gajapati 49.40 31.17

Ganjam 26.70 24.73

Jagatsinghpur 26.57 24.78

Jajpur 29.02 28.34

Jharsuguda 30.54 22.94

Kalahandi 33.62 31.18

Kandhamal 29.49 23.65

Kendrapara 26.44 23.99

Keonjhar 32.30 29.62

Khurda 26.22 21.88

Koraput 32.38 29.04

Malkangiri 30.39 26.22

Mayurbhanj 30.04 25.79

Nabarangpur 36.52 32.77

Nayagarh 25.25 17.45

Nuapada 32.04 28.52

Puri 24.00 21.61

Rayagada 33.13 30.20

Sambalpur 29.10 27.17

Sonepur 31.99 28.40

Sundargarh 31.09 24.46

ORISSA 30.50 26.62

Source: Government of Orissa, Department of Women and Child Development

Table 20POPULATION SUPPORTED BY ANGANWADI CENTRE

District Number of rural anganwadi

centre(AWC)

Total rural population Population per rural AWC

Angul 695 973551 1401Balasore 981 1765116 1799Bargarh 1193 1076969 903Bhadrak 580 1139788 1965Bolangir 1281 1206868 942Boudh 417 345788 829Cuttack 1155 1701543 1473Deogarh 294 248287 845Dhenkanal 691 995328 1440Gajapati 631 466620 739Ganjam 1264 2609517 2064Jagatsinghpur 727 1073594 1477Jajpur 795 1525159 1918Jharsuguda 433 328891 760Kalahandi 1163 1204727 1036Kandhamal 963 584339 607Kendrapara 588 1243094 2114Keonjhar 1559 1336528 857Khurda 781 1128046 1444Koraput 1289 978156 759Malkangiri 580 443432 765Mayurbhanj 2994 2023630 676Nabarangpur 994 920696 926Nayagarh 383 865607 2260Nuapada 585 507778 868Puri 491 1306744 2661Rayagada 1001 714842 714Sambalpur 786 634074 807Sonepur 416 505796 1216Sundargarh 1726 1195010 692ORISSA 27436 31049519 1132

Source : Govt. of Orissa, Department of Women and Child Development.

Table 21

COMPOSITE MORTALITY AND MALNUTRITION INDEX

DISTRICT Mortality Malnutrition Composite Index

Angul 0.95 2.48 1.71

Baleshwar 1.08 2.52 1.80

Baragarh 0.89 2.16 1.52

Bhadrak 1.08 2.47 1.78

Bolangir 0.91 2.43 1.67

Boudh 1.09 2.78 1.93

Cuttack 0.96 2.24 1.60

Deogarh 0.89 2.31 1.60

Dhenkanal 0.95 2.32 1.63

Gajapati 1.08 3.04 2.06

Ganjam 1.08 2.54 1.81

Jagatsinghpur 0.96 2.37 1.66

Jajpur 0.96 2.48 1.72

Jharasuguda 0.89 2.28 1.58

Kalahandi 1.12 2.85 1.99

Kandhmal 1.09 2.58 1.83

Kendrapara 0.96 2.35 1.66

Keonjhar 0.89 2.45 1.67

Khurda 1.23 2.71 1.97

Koraput 0.98 2.57 1.78

Malkangir 0.98 2.49 1.73

Mayurbhanj 0.81 2.22 1.52

Nabarangpur 0.98 2.71 1.85

Nayagarh 1.23 2.61 1.92

Nuapada 1.12 2.77 1.95

Puri 1.23 2.67 1.95

Rayagada 0.98 2.61 1.79

Sambalpur 0.89 2.34 1.61

Sonepur 0.91 2.44 1.67

Sundargarh 0.82 2.23 1.53

Table-22

COMPOSITE INDEX WITH ALL BROAD INDICATORS

DISTRICT Sustenance Disaster Deprivation Gender Inequality

Malnutrition &Mortality

Composite

Angul 1.21 2.58 0.49 1.07 1.71 1.41

Baleshwar 0.92 0.58 0.57 0.95 1.80 0.97

Baragarh 0.55 2.99 1.81 1.00 1.52 1.57

Bhadrak 0.88 0.63 0.48 0.94 1.78 0.94

Bolangir 1.00 1.83 0.46 1.10 1.67 1.21

Boudh 0.93 1.25 1.50 1.09 1.93 1.34

Cuttack 0.84 0.55 1.12 0.97 1.60 1.02

Deogarh 0.88 0.02 1.88 1.00 1.60 1.07

Dhenkanal 1.06 0.82 0.51 1.03 1.63 1.01

Gajapati 1.17 0.05 -0.05 1.06 2.06 0.86

Ganjam 1.12 0.39 -0.27 1.03 1.81 0.81

Jagatsinghpur 1.18 0.44 0.52 0.97 1.66 0.96

Jajpur 1.20 0.75 0.64 0.98 1.72 1.06

Jharasuguda 1.07 0.36 1.81 0.98 1.58 1.16

Kalahandi 0.96 1.59 1.06 1.03 1.99 1.33

Kandhmal 1.23 4.23 1.71 1.07 1.83 2.02

Kendrapara 1.01 0.95 0.50 0.98 1.66 1.02

Keonjhar 1.07 0.25 0.95 0.93 1.67 0.97

Khurda 1.33 0.79 0.55 0.84 1.97 1.10

Koraput 0.98 0.00 1.75 1.02 1.78 1.10

Malkangir 0.92 0.00 1.77 1.04 1.73 1.09

Mayurbhanj 0.97 0.34 0.40 0.87 1.52 0.82

Nabarangpur 0.86 0.01 1.79 1.13 1.85 1.13

Nayagarh 1.02 1.04 0.60 0.89 1.92 1.09

Nuapada 1.01 4.16 1.07 1.06 1.95 1.85

Puri 0.83 0.72 0.60 0.86 1.95 0.99

Rayagada 1.20 0.12 1.80 1.04 1.79 1.19

Sambalpur 0.77 0.22 1.88 0.98 1.61 1.09

Sonepur 0.62 2.33 0.47 1.10 1.67 1.24

Sundargarh 1.21 0 1.64 0.98 1.53 1.07

Table: 23

Correlation Coefficients

VAR00001 VAR00002 VAR00003 VAR00004 VAR00005 VAR00006VAR00001 1.0000 .2591 -.0572 .1317 -.1269 -.2045VAR00002 .2591 1.0000 -.4750** -.0882 -.0606 .1198VAR00003 -.0572 -.4750** 1.0000 .1314 -.2070 -.3470*VAR00004 .1317 -.0882 .1314 1.0000 -.0826 -.2303VAR00005 -.1269 -.0606 -.2070 -.0826 1.0000 .5811**VAR00006 -.2045 .1198 -.3470* -.2303 .5811** 1.0000VAR00007 .1025 .0454 -.2313 .3458* -.2480 -.2435VAR00008 -.1148 .1237 -.1739 .0647 -.1796 -.1470VAR00009 .0713 -.1167 .2870 -.1494 -.3673* -.5147**VAR00010 -.1427 -.0581 -.0669 -.3668* .2949 .4079*VAR00011 -.2256 -.2889 .2333 .3026 .0713 .0339VAR00012 .0284 .2190 -.4441** -.6059** .1468 .3551*VAR00013 .2473 .1405 .1032 .2944 -.0915 -.0749VAR00014 -.1666 .1661 -.4512** -.4653** .2994 .7470**VAR00015 -.2163 .1127 -.4698** -.4779** .3823* .7813**VAR00016 .0523 -.0841 -.1725 .0231 .1857 .2691VAR00017 .0975 -.2724 .6457** .4762** -.3045 -.4328**VAR00018 .2797 -.1000 .4178* .0126 .0719 .1701VAR00019 .2085 -.0526 .4436** .2677 .2290 .1806VAR00020 .1491 .1869 -.4421** -.2512 .0519 .5431**VAR00021 .0156 .1678 -.4196* -.2987 .0352 .6063**

* - Signif. LE .05 ** - Signif. LE .01 (1-tailed)" . " is printed if a coefficient cannot be computed

VAR001 Population supported by cereal production.VAR002 Seasonality in Cereal ProductionVAR003 Inadequacy of Safety Net systemVAR004 Crop Loss IndexVAR005 Disaster PronenessVAR006 Gender Disparity in LiteracyVAR007 Gender disparity in IMRVAR008 Gender disparity in CMRVAR009 Sex RatioVAR0010 Population below Poverty LineVAR0011 SC Population IndexVAR0012 ST Population IndexVAR0013 Net Out Migration IndexVAR0014 Illiteracy IndexVAR0015 Agricultural labourer IndexVAR0016 Working Children IndexVAR0017 Population per Anganwadi Centre(AWC)VAR0018 Infant Mortality Rate (IMR)VAR0019 Child Mortality Rate (CMR)VAR0020 Prevalence Malnutrition 0-3 agesVAR0021 Prevalence Malnutrition 3-6 ages

Correlation Coefficients - -(CONTD…)

VAR00007 VAR00008 VAR00009 VAR00010 VAR00011 VAR00012VAR00001 .1025 -.1148 .0713 -.1427 -.2256 .0284VAR00002 .0454 .1237 -.1167 -.0581 -.2889 .2190VAR00003 -.2313 -.1739 .2870 -.0669 .2333 -.4441**VAR00004 .3458* .0647 -.1494 -.3668* .3026 -.6059**VAR00005 -.2480 -.1796 -.3673* .2949 .0713 .1468VAR00006 -.2435 -.1470 -.5147** .4079* .0339 .3551*VAR00007 1.0000 .4435** -.1873 -.2447 .0678 -.0527VAR00008 .4435** 1.0000 .1329 -.2801 .3578* -.1068VAR00009 -.1873 .1329 1.0000 -.1214 -.0396 -.1065VAR00010 -.2447 -.2801 -.1214 1.0000 -.2745 .5570**VAR00011 .0678 .3578* -.0396 -.2745 1.0000 -.6053**VAR00012 -.0527 -.1068 -.1065 .5570** -.6053** 1.0000VAR00013 -.0041 .1131 .1961 -.1514 -.1116 -.2882VAR00014 -.1251 -.0856 -.2622 .6178** -.3324* .7937**VAR00015 -.1069 -.1929 -.3759* .5330** -.2637 .7299**VAR00016 .1656 -.1244 -.3042 -.0647 -.1529 .0772VAR00017 -.0835 -.0450 .3120* -.3743* .4515** -.8132**VAR00018 -.5180** -.6550** .0930 .0210 .0320 -.2799VAR00019 -.3902* -.4783** -.0711 .1013 .2761 -.4378**VAR00020 .0034 .0078 -.1876 .2381 -.4353** .5781**VAR00021 -.0692 .2379 -.2614 .3636* -.1733 .5077**

* - Signif. LE .05 ** - Signif. LE .01 (1-tailed)" . " is printed if a coefficient cannot be computed

VAR001 Population supported by cereal production.VAR002 Seasonality in Cereal ProductionVAR003 Inadequacy of Safety Net systemInVAR004 Crop Loss IndexVAR005 Disaster PronenessVAR006 Gender Disparity in LiteracyVAR007 Gender disparity in IMRVAR008 Gender disparity in CMRVAR009 Sex RatioVAR0010 Population below Poverty LineVAR0011 SC Population IndexVAR0012 ST Population IndexVAR0013 Net Out Migration IndexVAR0014 Illiteracy IndexVAR0015 Agricultural labourer IndexVAR0016 Working Children IndexVAR0017 Population per Anganwadi Centre(AWC)VAR0018 Infant Mortality Rate (IMR)VAR0019 Child Mortality Rate (CMR)VAR0020 Prevalence Malnutrition 0-3 agesVAR0021 Prevalence Malnutrition 3-6 ages

Correlation Coefficients - -(CONTD…)

VAR00013 VAR00014 VAR00015 VAR00016 VAR00017 VAR00018

VAR00001 .2473 -.1666 -.2163 .0523 .0975 .2797VAR00002 .1405 .1661 .1127 -.0841 -.2724 -.1000VAR00003 .1032 -.4512** -.4698** -.1725 .6457** .4178*VAR00004 .2944 -.4653** -.4779** .0231 .4762** .0126VAR00005 -.0915 .2994 .3823* .1857 -.3045 .0719VAR00006 -.0749 .7470** .7813** .2691 -.4328** .1701VAR00007 -.0041 -.1251 -.1069 .1656 -.0835 -.5180**VAR00008 .1131 -.0856 -.1929 -.1244 -.0450 -.6550**VAR00009 .1961 -.2622 -.3759* -.3042 .3120* .0930VAR00010 -.1514 .6178** .5330** -.0647 -.3743* .0210VAR00011 -.1116 -.3324* -.2637 -.1529 .4515** .0320VAR00012 -.2882 .7937** .7299** .0772 -.8132** -.2799VAR00013 1.0000 -.0504 -.2073 .0764 .3845* .2479VAR00014 -.0504 1.0000 .9333** .2082 -.6667** -.0617VAR00015 -.2073 .9333** 1.0000 .3175* -.7097** -.0568VAR00016 .0764 .2082 .3175* 1.0000 -.2107 -.0058VAR00017 .3845* -.6667** -.7097** -.2107 1.0000 .4858**VAR00018 .2479 -.0617 -.0568 -.0058 .4858** 1.0000VAR00019 .2621 -.1828 -.1952 .0192 .4889** .7972**VAR00020 .1740 .6733** .5604** .2549 -.5760** -.0303VAR00021 .1406 .7089** .6218** .2937 -.5117** -.2061

* - Signif. LE .05 ** - Signif. LE .01 (1-tailed)" . " is printed if a coefficient cannot be computed

VAR001 Population supported by cereal production.VAR002 Seasonality in Cereal ProductionVAR003 Inadequacy of Safety Net systemInVAR004 Crop Loss IndexVAR005 Disaster PronenessVAR006 Gender Disparity in LiteracyVAR007 Gender disparity in IMRVAR008 Gender disparity in CMRVAR009 Sex RatioVAR0010 Population below Poverty LineVAR0011 SC Population IndexVAR0012 ST Population IndexVAR0013 Net Out Migration IndexVAR0014 Illiteracy IndexVAR0015 Agricultural labourer IndexVAR0016 Working Children IndexVAR0017 Population per Anganwadi Centre(AWC)VAR0018 Infant Mortality Rate (IMR)VAR0019 Child Mortality Rate (CMR)VAR0020 Prevalence Malnutrition 0-3 agesVAR0021 Prevalence Malnutrition 3-6 ages

Correlation Coefficients - -(CONTD…)

VAR00019 VAR00020 VAR00021

VAR00001 .2085 .1491 .0156VAR00002 -.0526 .1869 .1678VAR00003 .4436** -.4421** -.4196*VAR00004 .2677 -.2512 -.2987VAR00005 .2290 .0519 .0352VAR00006 .1806 .5431** .6063**VAR00007 -.3902* .0034 -.0692VAR00008 -.4783** .0078 .2379VAR00009 -.0711 -.1876 -.2614VAR00010 .1013 .2381 .3636*VAR00011 .2761 -.4353** -.1733VAR00012 -.4378** .5781** .5077**VAR00013 .2621 .1740 .1406VAR00014 -.1828 .6733** .7089**VAR00015 -.1952 .5604** .6218**VAR00016 .0192 .2549 .2937VAR00017 .4889** -.5760** -.5117**VAR00018 .7972** -.0303 -.2061VAR00019 1.0000 -.1552 -.2318VAR00020 -.1552 1.0000 .7471**VAR00021 -.2318 .7471** 1.0000

* - Signif. LE .05 ** - Signif. LE .01 (1-tailed)" . " is printed if a coefficient cannot be computed

VAR001 Population supported by cereal production.VAR002 Seasonality in Cereal ProductionVAR003 Inadequacy of Safety Net systemInVAR004 Crop Loss IndexVAR005 Disaster PronenessVAR006 Gender Disparity in LiteracyVAR007 Gender disparity in IMRVAR008 Gender disparity in CMRVAR009 Sex RatioVAR0010 Population below Poverty LineVAR0011 SC Population IndexVAR0012 ST Population IndexVAR0013 Net Out Migration IndexVAR0014 Illiteracy IndexVAR0015 Agricultural labourer IndexVAR0016 Working Children IndexVAR0017 Population per Anganwadi Centre(AWC)VAR0018 Infant Mortality Rate (IMR)VAR0019 Child Mortality Rate (CMR)VAR0020 Prevalence Malnutrition 0-3 agesVAR0021 Prevalence Malnutrition 3-6 ages

Table: 24

COMPOSITE INDEX WITH SELECTED INDICATORS

DISTRICT %P BPL Mortality Malnutrition Net Migration

Composite

Angul 0.88 0.95 2.48 -1.58 0.68Baleshwar 1.11 1.08 2.52 -0.68 1.01Baragarh 0.91 0.89 2.16 6.61 2.64Bhadrak 0.83 1.08 2.47 -0.68 0.93Bolangir 0.90 0.91 2.43 -2.92 0.33Boudh 1.21 1.09 2.78 3.99 2.27Cuttack 0.76 0.96 2.24 4.05 2.00Deogarh 1.17 0.89 2.31 6.61 2.75Dhenkanal 1.03 0.95 2.32 -1.58 0.68Gajapati 0.92 1.08 3.04 -7.29 -0.56Ganjam 0.81 1.08 2.54 -7.29 -0.72Jagatsinghpur 0.79 0.96 2.37 -0.12 1.00Jajpur 0.91 0.96 2.48 -0.12 1.06Jharasuguda 0.67 0.89 2.28 6.61 2.61Kalahandi 0.95 1.12 2.85 -0.09 1.21Kandhmal 1.18 1.09 2.58 3.99 2.21Kendrapara 0.84 0.96 2.35 -0.12 1.01Keonjhar 1.13 0.89 2.45 0.48 1.24Khurda 0.88 1.23 2.71 0.01 1.21Koraput 1.28 0.98 2.57 3.82 2.16Malkangir 1.23 0.98 2.49 3.82 2.13Mayurbhanj 1.17 0.81 2.22 -4.38 -0.04Nabarangpur 1.11 0.98 2.71 3.82 2.16Nayagarh 0.98 1.23 2.61 0.01 1.20Nuapada 1.24 1.12 2.77 -0.09 1.26Puri 1.07 1.23 2.67 0.01 1.24Rayagada 1.09 0.98 2.61 3.82 2.12Sambalpur 0.92 0.89 2.34 6.61 2.69Sonepur 1.05 0.91 2.44 -2.92 0.37Sundargarh 0.98 0.82 2.23 5.43 2.37

Table 25

PATTERN OF SAFETY NET COVERAGE

District Number of rural

Anganwadi centre(AWC)

Total rural population

AWC/1000 pop

AWC index

Safety netindex

Compositeindex

Angul 695 850729 0.82 0.74 2.34 1.54Balasore 981 1542431 0.64 0.57 0.17 0.37Bargarh 1193 941100 1.27 1.14 4.02 2.58Bhadrak 580 995993 0.58 0.52 0.34 0.43Bolangir 1281 1054611 1.21 1.09 3.12 2.11Boudh 417 302164 1.38 1.24 2.51 1.88Cuttack 1155 1486878 0.78 0.70 0.26 0.48Deogarh 294 216963 1.36 1.22 2.59 1.90Dhenkanal 691 869758 0.79 0.72 1.52 1.12Gajapati 631 407752 1.55 1.39 3.44 2.42Ganjam 1264 2280303 0.55 0.50 0.68 0.59Jagatsinghpur 727 938150 0.77 0.70 4.38 2.54Jajpur 795 1332746 0.60 0.54 1.45 0.99Jharsuguda 433 287398 1.51 1.36 1.27 1.31Kalahandi 1163 1052740 1.10 1.00 2.89 1.94Kandhamal 963 510619 1.89 1.70 3.29 2.49Kendrapara 588 1086266 0.54 0.49 3.03 1.76Keonjhar 1559 1167913 1.33 1.20 2.23 1.72Khurda 781 985733 0.79 0.71 0.90 0.81Koraput 1289 854753 1.51 1.36 1.60 1.48Malkangiri 580 387489 1.50 1.35 5.11 3.23Mayurbhanj 2994 1768331 1.69 1.53 2.85 2.19Nabarangpur 994 804542 1.24 1.11 3.96 2.54Nayagarh 383 756403 0.51 0.46 0.95 0.70Nuapada 585 443717 1.32 1.19 3.78 2.48Puri 491 1141886 0.43 0.39 0.12 0.25Rayagada 1001 624658 1.60 1.44 6.19 3.82Sambalpur 786 554080 1.42 1.28 2.45 1.86Sonepur 416 441985 0.94 0.85 4.43 2.64Sundargarh 1726 1044249 1.65 1.49 3.86 2.68

Annex IV

ADDITIONAL INDICATORS RELATED TO FOOD SECURITY [Availability with the sources]

Sl.No

Indicator Sources with contact person Level latest period of availability

Comments

1 Number of beneficiaries receiving food aid including mid-day meal

Deputy Secretary, Nutrition, Department of Women and Child Development (ICDS- IV)

Project/Block

1998 Family income Rs. <=20,000 per year

2. Prevalence of protein/energy malnutrition

Not Available

3. Population Growth Rate

Census of India, 1991, District Census Hand Book, Orissa

Village 1991

4. Population Density per sq. km.

Census of India, 1991, District Census Hand Book, Orissa

Village 1991

5. Percentage planted to cash crop of cultivated area

District Statistical Handbook, Directorate of Economics and Statistics, Govt. of Orissa

District 1995

6. School Enrolment by SC/ST

Orissa Primary Education Programme Authority(OPEPA) Got. Of Orissa

Block 1998

7. School Enrolment by Gender

Do Block 1998

8. Mean price of wheat over 10 years

Price Section, Directorate of Economics and Statistics, Govt. of Orissa

District 1998

9. Mean price of rice over 10 years

Price Section, Directorate of Economics and Statistics

District 1998 PDS/ Fair price shops beneficiaries

10 Mean price of pulses over 10 years

Price Section, Directorate of Economics and Statistics

District 1998

11 Irrigated land as District Statistical Handbook, Directorate of Block 1995

percentage to total cultivable land

Economics and Statistics, Govt. of Orissa

12 Crop yield per unit area by years

Directorate of Economics and Statistics, Govt. of Orissa

District 1997-98

13 Crop yield per unit area by crops

Directorate of Economics and Statistics, Govt. of Orissa

District 1997-98

14 Average size of households

Census of India, 1991, District Census Hand Book, Orissa

Village 1991

15 Percentage of villages with safe drinking water facility

Census of India, 1991, District Census Hand Book, Orissa

Block 1991

16 Percentage of villages with PDS shop within 10 km

Not available

17 Percentage of villages with market within 30 km

Census of India, 1991, District Census Hand Book, Orissa

Block 1991

18 Percentage of villages with health services within 10 km

Census of India, 1991, District Census Hand Book, Orissa

Block 1991

19 Percentage of villages connected by metal road

Census of India, 1991, District Census Hand Book, Orissa

Block 1991

20 Percentage of landless agricultural labour

Census of India, 1991, District Census Hand Book, Orissa

Block 1991