BMJ Open · For peer review only Abstract Objective: To identify factors associated with anemia among lactating mothers in Ethiopia. Design: A cross-sectional secondary data analysis

For peer review only

Factors associated to develop anemia among lactating mothers in Ethiopia: A pooled data analysis from two rounds

of demographic and health surveys

Journal: BMJ Open

Manuscript ID: bmjopen-2014-006001

Article Type: Research

Date Submitted by the Author: 29-Jun-2014

Complete List of Authors: Tarekegn, Yihunie; Ethiopian Public Helth Association, Project management Biadgilign, Sibhatu Haile, Demewoz; Madawalabu University,

<b>Primary Subject Heading</b>:

Public health

Secondary Subject Heading: Nutrition and metabolism, Public health, Health policy

Keywords: NUTRITION & DIETETICS, Nutritional support < ONCOLOGY, Anaemia < HAEMATOLOGY

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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Factors associated to develop anemia among lactating mothers in Ethiopia: A pooled data

analysis from two rounds of demographic and health surveys

Yihunie Lakew1, Sibhatu Biadgilign

2, Demewoz Haile

3*

1 Ethiopian public health association, Addis Ababa, Ethiopia

2 Independent public health consultants, Addis Ababa, Ethiopia

3 Department of Public Health, College of Medicine and Health sciences, Madawalabu

University, Ethiopia

Email address

Yihunie Lakew – [email protected]

Sibhatu Biadgilign- [email protected]

Demewoz Haile–[email protected]

*Corresponding author

Address of corresponding author

Department of Public Health

College of Medicine and Health sciences

Madawalabu University, Ethiopia

Bale Goba , p, box 302

Running title: Factors associated with anemia among lactating mothers in Ethiopia

Key words: Lactating mothers, anemia, Ethiopia,

Word count: 2143

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Abstract

Objective: To identify factors associated with anemia among lactating mothers in Ethiopia.

Design: A cross-sectional secondary data analysis pooled from two rounds of the 2005 and 2011

Ethiopian demographic and health survey (EDHS) was used. Multivariable logistic regression

model was applied to determine the factors associated with anemia.

Population: A total of 7,332 lactating mothers (2,285 from EDHS 2005 and 5,047 from EDHS

2011) were included from 11 administrative states of Ethiopia.

Main outcome measures: Lactating mothers considered as anemic if hemoglobin level <12 g/dl

Results: The overall prevalence of anemia among lactating mothers was found to be 22.1%

[95% CI: (21.13-23.03)]. The prevalence in urban settings was 13.7% [95% CI: (11.35-16.05)]

and in rural areas was 23% [95% CI: (22.68-23.32)]. The multivariable statistical model showed

that lactating mothers whose husbands had attended primary and secondary education were,

respectively, 26% [adjusted odds ratio (AOR) = 0.74; 95% CI: (0.60-0.92)] and 34% [AOR=

0.66; 95% CI: (0.44-0.99)] less likely to have anemia as compared to lactating mothers whose

husbands had no education. Family planning use [AOR= 0.71; 95% CI: (0.55-0.92)], antenatal

care attendance [AOR= 0.77; 95% CI: (0.62-0.95)], engaging in work [AOR=0.78; 95% CI:

(0.63-95)] and having normal body mass index between 18.5 to 24.9 kg/m2 [AOR=0.79 (0.63-

0.98)] were found to be protective factors against developing anemia among lactating mothers.

Variables including wealth index, maternal age, maternal education, parity and religion were not

associated with anemia in lactating mothers.

Conclusion: Anemia is highly prevalent among lactating mothers, particularly in rural and

pastoralist Ethiopia. Factors including paternal education, family planning use, body mass index

(BMI), occupational status, and antenatal care attendance were strong predictors of anemia

among lactating mothers. Promoting partner education, improving BMI, scaling up family

planning and antenatal care services are recommended interventions.

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ARTICLE SUMMARY

Strength and Limitations

• The study attempted to identify factors associated with laboratory confirmed anemia at

the national level in lactating mothers which will potentially influence policy actions.

• The study is a secondary data analysis that missed key potential variables such as dietary

factors. Furthermore, the data has small sample size for some regions, which questions

the accuracy of prevalence estimates per region.

Key messages

• Anemia prevalence is a public health problem among lactating mothers in Ethiopia.

• There are regional disparities regarding the prevalence of anemia among lactating

mothers, with the highest rates found in pastoralist regions.

• Husband education, family planning and ANC attendance were protective factors for

developing anemia.

• Overweight and obese lactating mothers were at high risk for developing anemia.

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Introduction

Anemia is one of the nutrition problems affecting millions in developing countries, and remains

a major challenge for human health, social and economic development1. Lactating mothers are

one of the vulnerable groups of anemia. During the period of lactation, mothers are susceptible

to anemia due to maternal iron depletion and blood loss during child birth2. Studies have shown

that the concentration of iron in breast milk is independent of maternal iron status and that the

quality of breast milk is maintained at the expense of maternal stores2 3. Postpartum anemia has

been found highest in mothers who were anemic during pregnancy4. Furthermore, lactating

mothers are highly susceptible to iron depletion if they have not had enough energy and nutrient

intake in their diets. Yet the problem of anemia in postnatal women has been relatively neglected

which is far away from previously thoughts5. Lactating mothers enter into the postnatal period

after having iron depleted through the continuum from pregnancy to childbearing 6. A study from

South Africa evidenced that there was a strong relation between iron status and depression,

stress, and cognitive functioning in poor African mothers during the postpartum period7.

In a meta-analysis of observational and intervention trials, Ross and Thomas8, found that

approximately 20% of the maternal mortality seen in sub-Saharan Africa and South Asia was

attributable to anemia that is primarily the result of iron deficiency. Ethiopia is one of the sub-

Saharan Africa countries heavily affected by anemia9.

Anemia testing was included in the two rounds of the Ethiopian demographic and health surveys

(EDHS) 10. The prevalence of anemia among lactating mothers was 29.9% in 2005 and 18.5% in

2011 9, which is considerably higher as compared with other women (23.9% in 2005 and 15% in

2011), and low as compared with pregnant mothers (30.6% in 2005 and 22% in 2011). This

prevalence of anemia in lactating mothers is one of the highest among developing countries.

However, there is a scarcity of evidence for the factors associated with anemia among lactating

mothers in Ethiopia. Therefore, this study aims to identify the factors associated with anemia

among Ethiopian lactating mothers using the pooled data of EDHS 2005 and 2011.

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Methods

Data type and study design

This study is an in-depth analysis to identify risk factors for anemia among lactating mothers

based on secondary data of the EDHS 2005 and 2011 datasets. The EDHS was designed to

provide population and health indicators at national (urban and rural) and regional levels and

were conducted within five year intervals. Both the 2005 and 2011 EDHS samples were selected

using a stratified, two-stage cluster design. The detailed methodology is found elsewhere 9 10

.

Data Extraction

Both EDHS 2005 and 2011 data were downloaded from the Measure EDHS website in SPSS

format with permission. After understanding the detailed data coding, further data cleaning and

recoding was completed. A total of 7,332 lactating mothers (2,285 from EDHS 2005 and 5,047

from EDHS 2011) were included in the analysis. Based on published literature, information on a

wide-range of socio-demographic and economic variables, health service related factors and

anemia level indicators were extracted from the datasets that can potentially influence the

existence of anemia.

Measurement

In both rounds of the EDHS, haemoglobin analysis was carried out onsite using a battery-

operated portable HemoCue analyzer for all anemia samples. The raw measured values of

haemoglobin were obtained using the HemoCue instrument and adjusted for altitude and

smoking status9. All the necessary quality control measures were considered.

Data processing and statistical analysis

Both surveys were administered by the Ethiopian Central Statistics Authority (CSA). Data entry

and editing was performed using CSPro software. For this study’s analysis, the 2005 and 2011

EDHS data were pooled to achieve high power for detecting the associated factors and analyzed

using STATA 11 software. Descriptive statistics was used to show the prevalence of anemia

among lactating mothers across the regional states and city administrations of Ethiopia.

Multivariable binary logistic regression statistical analysis was carried out to determine the

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factors associated with anemia among lactating mothers. Both crude and adjusted odds ratios

(OR) were determined with 95% confidence interval (CI). All tests were two-sided, weighted

and a p-value <0.05 was considered statistically significant. Variables found statistically

significant at p-value <0.3 during bivariate analysis were considered for adjustment in the

multivariable logistic regression model.

Ethical statements

The data were downloaded and used after communicating the purpose of the analysis and

receiving permission from Measure DHS Organization. The original EDHS data were collected

in accordance with international and national ethical guidelines.

Results

The overall prevalence of anemia among lactating mothers during 2005 and 2011 was found to

be 22.1% (95% CI: 21.13-23.03). The prevalence was 13.8% [95% CI: (11.44-16.41)] in urban

areas and 23% [95% CI: (21.99-24.03)] in rural areas. The highest prevalence of anemia among

lactating mothers was found in Somali region (48.7%), while the lowest prevalence was reported

in Addis Ababa (9.0%) (Table 1).

Table 1. Prevalence of anemia among lactating mothers in Ethiopia using pooled data from

the EDHS 2005 and 2011

Location Variables

2005-2011

Weighted total number of

lactating mothers

Weighted prevalence of

anemia (95% CI)

Region

Tigray 422 20.8(17.18-24.93)

Afar 59 43.8(31.83-56.87)

Amhara 1943 22.9(21.12-24.86)

Oromiya 2867 22.5(21.00-24.05)

Somali 152 48.7(40.80-56.62)

Benshangul 83 22.9(14.81-32.83)

SNNP 1637 18.0(16.16-19.88)

Gambella 25 28.0(13.15-47.7)

Harar 15 20.0(5.35-45.35)

Adiss Ababa 111 9.0(4.067-15.47)

Diredawa 18 33.3(14.77-56.9)

Residence

Urban 740 13.8(11.44-16.41)

Rural 6592 23.0(21.99-24.03)

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Total 7332 22.1(21.13-23.03)

In total, 12 variables for anemia were both available from the EDHS and identified as risk factors

based on literature review. Of the twelve, the factors identified as significantly associated with

anemia in the bivariate step were wealth index, place of residence, maternal education, paternal

education, maternal occupation, family planning use, maternal BMI and antenatal care

attendance. However, in the multivariable model, paternal education, maternal occupation,

family planning use, maternal BMI and antenatal care attendance remained the independent

predictors of anemia for Ethiopian lactating mothers.

Paternal educational status was found to be a predictor of anemia among lactating mothers.

Those lactating mothers who had husbands who attended primary education were at 26% lower

risk for having anemia as compared to those mothers who had husbands with no education

[AOR=0.74; 95% CI: (0.60-0.92)]. Those lactating mothers with husbands who had secondary

education had a 34% lower risk of having anemia as compared to those lactating mothers with

husbands who had no education [AOR=0.66; 95% CI: (0.44-0.99)]. Working lactating mothers

had a 22% lower risk for anemia as compared to their counter parts [AOR=0.78; 95% CI: (0.63-

95)]. Having a normal maternal BMI was found protective of anemia [AOR=0.79; 95% CI:

(0.63-0.98)]. However, lactating mothers who had BMI 25kg/m2 had a 80% higher risk of

developing anemia as compared to undernourished (defined as BMI<18.5kg/m2) lactating

mothers[AOR=1.8; 95% CI: (1.02-3.12)](Table 2).

Among maternal health service factors, family planning use and antenatal care (ANC) were the

significant predictors of anemia in lactating mothers. Lactating mothers who ever used family

planning were 29% less likely to have anemia as compared to lactating mothers who never used

family planning [AOR=0.71; 95% CI: (0.55-0.92)]. Lactating mothers who reported ANC

attendance were 23% less likely to develop anemia as compared to their counterparts

[AOR=0.77; 95% CI: (0.62-0.95)] (Table 2).

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Table 2. Factors associated with anemia among lactating mothers in Ethiopia using pooled

data from the EDHS 2005 and 2011

Variable COR (95% CI) AOR (95% CI)

Wealth index

Poor 1 1

Medium 0.82(0.71-0.95) 1.0(0.79-1.28)

Rich 0.73(0.64-0.83) 1.1(0.88-1.42)

Place of residence

Urban 1

Rural 1.9(1.51-2.33) 1.2(0.72-1.98)

Maternal education

No education 1 1

Primary 0.79(0.70-0.91) 0.80(0.61-1.05)

Secondary 0.44(0.28-0.67) 76(0.36-1.59)

Higher 0.31(0.13-0.73) 0.5(0.001-44.44)

Paternal education

No education 1 1

Primary 0.73(0.65-0.82) 0.74(0.60-0.92)**

Secondary 0.63(0.48-0.81) 0.66(0.44-0.99)*

Higher 0.48(0.31-0.75) 0.70(0.19-2.60)

Maternal occupation

Not working 1 1

Working 0.66(0.59-0.74) 0.78(0.63-95)*

Family planning use

Never used 1 1

Used 0.60(0.48-0.76) 0.71(0.55-0.92)**

BMI(kg/m2)

< 18.5 1 1

18.5-24.99 0.88(0.77-0.99) 0.79(0.63-0.98)*

25+ 1.2(0.85-1.57) 1.8(1.024-3.117)*

ANC attendance

Not attend 1 1

Attend 0.68(0.55-0.83) 0.77(0.62-0.95)*

*P<0.05 **P<0.001

Discussion

Over one fifth of lactating mothers were anemic in Ethiopia, which is relatively lower as

compared to an Indian study where more than 90% of lactating mothers were reported as

anemic11. A study from Zimbabwe showed that about 29.6% of lactating women developed

anemia12 which is also higher than found in Ethiopia. Another study from Myanmar reported an

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anemia prevalence rate of 60.3% in lactating women, with 20.3% of lactating mothers having

severe anemia13. Although the prevalence of anemia among lactating mothers in Ethiopia was

relatively low as compared to the above studies, still it is a moderate public health problem

according to WHO classification14. Anemia during lactation has received less attention in the

Health Extension Program which is practiced in Ethiopia. Even though the health extension

package of Ethiopia has nutrition component, it has no much emphasis on prevention of anemia

among lactating mothers. The EDHS also shows that iron supplementation coverage for pregnant

mothers remained low over time, despite its known contribution for reducing the risk of

postpartum hemorrhage 9. However, the culture of care provided for lactating mothers during the

postpartum period in Ethiopia may contribute to the prevention of anemia.

Although there are common assumptions that pastoralist populations are at a lower risk for

anemia due to their dietary habits and dependence on animal food sources, this study showed that

anemia is a widespread problem in the pastoralist community. The prevalence of anemia in

lactating mothers was highest in pastoralist regions and the decrease in prevalence between 2005

and 2011 EDHS was very small. This might be associated with anemia specifically resulting

from infection, such as malaria which is prevalent in those pastoralist areas.

One of the factors determined to be associated with anemia was paternal education. Having a

husband with a higher level of education was found to be protective for anemia among lactating

mothers. Those mothers having husbands with education of primary and secondary levels were

less likely to develop anemia as compared to those with husbands who had no education.

However, maternal educational status was not statistically associated with anemia, which is

contradictory to many studies from Ethiopia as well as from abroad 13 15-17

. The absence of

association between maternal educational status and anemia versus the associate with husbands’

educational status and anemia among lactating mothers might imply that partner education is

more influential in preventing anemia. This might indicate the importance of involving husbands

in anemia prevention efforts.

Lactating mothers who are working were at lower risk of having anemia as compared to their

counter parts. This might be because working mothers are more empowered as compared to non-

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employed mothers. Therefore, women’s empowerment through economic interventions could

have a positive contribution toward preventing anemia.

As one strategy for preventing anemia, family planning has been used. This study also supports

the importance of family planning for reducing the risk of anemia. Those lactating mothers who

have ever used family planning (modern or traditional) had a lower risk of developing anemia as

compared to those who had never used family planning. This finding is consistent with an

Ethiopian study on the correlates of anemia among reproductive age women by Samson and his

colleague 15.

Maternal nutritional status (measured by body mass index) was found to be significantly

associated with anemia. As compared with undernourished lactating mothers (BMI<18.5kg/m2),

being in the normal BMI category (18.5-24.9kg/m2) was negatively associated with developing

anemia as expected. This finding is similar with others studies18 19

. When a mother is at risk of

deficiency for macronutrients, most likely she is also at risk also other micronutrient deficiencies

such as iron. This study found that overweight and obese lactating mothers were at an 80%

higher risk for having anemia. A study from Mexico found that being overweight did not

necessarily diminish the risk of anemia; rather diet quality was the determiner 19. A study by

Cepeda-Lopez and his colleagues explains lower iron status among obese individuals explained

by lower absorption of iron due to obesity related inflammation which affect regulation of

Hepcidin. Hepcidin levels are higher in obese individuals and are linked to subclinical

inflammation which affect iron absorption negatively 19.

ANC attendance was found to be a protective factor for anemia among lactating mothers. This is

most likely due to the fact that during ANC attendance mothers have been advised to take iron

supplements according to the Ethiopian micronutrient guideline and instructed to consume

different sources of iron rich food items20. Therefore, improving iron status during pregnancy

also helps to prevent anemia during the lactation period.

In many studies of anemia among reproductive age women, the wealth index was found to be a

statistically significant factor 13 15

. However, in this study the wealth index was not found to be a

statistically significant factor.

Conclusion

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Anemia is a public health problem among lactating mothers in Ethiopia. There are regional

disparities regarding the prevalence of anemia, with the highest rates found in pastoralist regions.

Factors such as husband’s educational status, family planning use, BMI, maternal occupational

status and ANC attendance were identified as associated factors for anemia among lactating

mothers. Improving BMI, promotion of family planning and ANC are recommended

interventions to prevent anemia. Involvement of males in prevention of anemia should be

considered. Attention should also be given to preventing anemia among lactating mothers

through the Health Extension Package and at any health service delivery contact for lactating

mothers.

Competing interests

The authors declare that they have no competing interests.

Funding statement

This research received no specific grant from any funding agency in the public, commercial or

not-for-profit sectors'

Authors’ contributions

YL and DH conceived the idea. YL analyzed and interpreted the data and critically reviewed the

manuscript. SB assisted in critically reviewing the manuscript. DH drafted the manuscript,

assisted in the data analysis and interpretation and critically reviewed the manuscript. All authors

reviewed and approved the manuscript.

Acknowledgements

The authors acknowledge DHS Measure for granting the data freely. We are also grateful to

thank Lianna Tabar, country representative of KHI-E, for her professional language editing and

reviewing the manuscript.

Data Sharing Statement: No additional data available

References

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14. WHO. Worldwide prevalence of anaemia 1993-2005 : WHO global database on anaemia / Edited by

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, 2008.

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Anemia prevalence and associated factors among lactating mothers in Ethiopia: Evidence from the 2005 and 2011

demographic and health surveys

Journal: BMJ Open

Manuscript ID: bmjopen-2014-006001.R1


Date Submitted by the Author: 29-Nov-2014

Complete List of Authors: Tarekegn, Yihunie; Ethiopian Public Helth Association, Project management Biadgilign, Sibhatu; 2 Independent public health consultants, Addis Ababa, Ethiopia,

Haile, Demewoz; Madawalabu University,


Public health


Keywords: Anaemia < HAEMATOLOGY, NUTRITION & DIETETICS, Nutritional support < ONCOLOGY


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Anemia prevalence and associated factors among lactating mothers in Ethiopia: Evidence from the

2005 and 2011 demographic and health surveys


2, Demewoz Haile

3*





Email address












Word count: 2388

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Abstract







Main outcome measures: Lactating mothers considered as anemic if hemoglobin level <12

gram per deciliter.


[95% CI: (21.13-23.03)]. The highest prevalence was 48.7% [95% CI: (40.80-56.62)] found in

Ethiopian Somali region, followed by 43.8% [95% CI: (31.83-56.87)] in Afar region. The

multivariable statistical model showed that lactating mothers who had husbands who had

attended primary education [AOR=0.79; 95% CI: (0.68-0.91)], who were currently working

[AOR=0.71; 95% CI: (0.63-0.80)], had normal maternal body mass index (BMI) from 18.5kg/m2

to 24.99kg/m2 [AOR=0.78; 95% CI: (0.68-0.89)], were in the middle wealth quintile

[AOR=0.83; 95% CI: (0.71-0.98)] and rich wealth quintile [AOR=0.83; 95% CI: (0.70-0.98)],

reported ever use of family planning [AOR=0.68; 95% CI: (0.57-0.80)], were attending antenatal

care (ANC) for indexed pregnancy four times or more [AOR=0.73; 95% CI: (0.59-0.91)],

experienced time variation between two surveys [AOR=0.73; 95%CI: (0.64-0.85)] and who

breastfed for two years [AOR=0.76; 95% CI: (0.66-0.87)] were found to be associated with

anemia

Conclusion: Anemia is highly prevalent among lactating mothers, particularly among pastoralist

communities of Ethiopian Somali and Afar. Promoting partner education, improving maternal

nutritional status, creating behaviour change among lactating mothers to use family planning and

attend ANC services at health facilities are recommended interventions to reduce the prevalence

of anemia among lactating mothers in Ethiopia..

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ARTICLE SUMMARY


• The study attempted to identify factors associated with laboratory confirmed anemia in

lactating mothers at the national level. The study findings can be used to inform policy

and program actions. Some regions from which data was collected had small sample

size. So that it should be interpreted in caution. .

Key messages

• Anemia prevalence is a public health problem among lactating mothers in Ethiopia, with

the highest prevalence found in pastoralist regions of Ethiopian Somali and Afar

• A statistically significant reduction of anemia prevalence in lactating mothers was

observed from 2005 to 2011.

• Being in middle and rich wealth quintiles, two years of breastfeeding, currently working,

normal body mass index, husbands’ primary education, ever use of family planning and

antenatal care attendance for four or more visits were factors found to be associated with

anemia.

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Introduction

Anemia is a serious nutrition problem affecting millions in developing countries, and remains a

major challenge for human health, social and economic development1. Lactating mothers are one

of the vulnerable groups of anemia. During the period of lactation, mothers are susceptible to

anemia due to maternal iron depletion and blood loss during child birth2. Studies have shown that

though breast milk is not a good source of iron, the concentration of iron in breast milk is

independent of maternal iron status. This showed that the quality of breast milk is maintained at

the expense of maternal stores2 3

.

Postpartum anemia has been found highest in mothers who were anemic during pregnancy4.

Furthermore, lactating mothers are highly susceptible to iron depletion if they have not had

enough energy and nutrient intake in their diets.. Lactating mothers begin the postnatal period


South Africa showed that iron status was associated with depression, stress, and cognitive

functioning in poor African mothers during the postpartum period6. In a meta-analysis of

observational and intervention trials, Ross and Thomas, found that approximately 20% of the

maternal mortality seen in sub-Saharan Africa and South Asia was attributable to anemia that

was primarily the result of iron deficiency 7.

Ethiopia is one of the countries in sub-Saharan Africa affected by anemia and it contributes to

high rates of maternal, infant and child mortality globally8 9

. In Ethiopia, the maternal mortality

ratio was 676 maternal deaths per 100,000 live births for the seven-year period preceding the

2011 EDHS survey. This rate is one of the highest in the world. The infant mortality rate was 59

per 1,000 live births and the under-five mortality rate was 88 per 1,000 live births10

.

. Anemia testing was included in the two rounds of the Ethiopian Demographic and Health

Surveys (EDHS)10 11

. The prevalence of anemia in lactating mothers was 29.9% in 2005 and

18.5% in 201110

. It was 30.6% in 2005 and 22% in 2011 among pregnant women and it was

23.9% in 2005 and 15% in 2011 among women neither non-pregnant nor lactating. This shows

that a relatively higher prevalence of anemia was found among Ethiopian pregnant and lactating

mothers.

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(EDHS)10

,11

. The prevalence of anemia in lactating mothers was 29.9% in 2005 and 18.5% in

2011 12

. It was 30.6% in 2005 and 22% in 2011 among pregnant women and it was 23.9% in

2005 and 15% in 2011 among women neither non-pregnant nor lactating. This shows that a

relatively higher prevalence of anemia was found among Ethiopian pregnant and lactating

mothers. However, little information is available regarding socio-economic factors associated

with anemia among lactating mothers. This study aimed to identify factors associated with

anemia among lactating mothers in Ethiopia using the pooled data of EDHS 2005 and 2011.This

study aimed to identify factors associated with anemia among lactating mothers in Ethiopia using

the pooled data of EDHS 2005 and 2011.

Methods


This study is an in-depth analysis to identify factors associated with anemia among lactating

mothers based on secondary data of the EDHS 2005 and 2011 datasets. The EDHS was designed

to provide population and health indicators at national and regional levels. It is conducted every

five year. Both the 2005 and 2011 EDHS samples were selected using a stratified, two-stage

cluster design. The detailed methodology is found elsewhere 11 12

.

Data Extraction

Both EDHS 2005 and 2011 data were downloaded with permission from the Measure DHS

website in SPSS format. After reviewing the detailed data coding, further data cleaning and




anemia level indicators were extracted.

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Measurement




smoking status12

. All the necessary quality control measures were considered9.





using STATA 11 software. Anemia was re-categorized as anemic and non-anemic from prior

classifications in levels (no, mild, moderate, severe). The background variables were selected

based on literature review and data availability from the two rounds of EDHS. The chosen

variables were region, residence, wealth index, occupation, BMI, duration of breastfeeding,

respondent’s education, husband’s education, family planning use, ANC use, iron

supplementation during pregnancy, time variation between two surveys, marital status, age and

parity.

Descriptive statistics were used to show the prevalence of anemia among lactating mothers

varying by background characteristics. Binary and multivariable logistic regression statistical

analysis were carried out to determine the factors associated with anemia among lactating

mothers. Variables found statistically significant at p-value <0.25 during bivariate analysis were

analyzed in the multivariable logistic regression model13

. This p-value cut off point prevented

removing variables that would potentially have an effect during multivariable analysis. Both

crude and adjusted odds ratios (OR) were reported with 95% confidence interval (CI). Variables

at p-value <0.05 were considered statistically significant in the multivariable logistic regression

model.

Ethical statements

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Results

Prevalence of anemia in lactating mothers by background characteristics:

.

The overall prevalence of anemia among lactating mothers during 2005 to 2011 was found to be

22.1% (95% CI: 21.13-23.03). The prevalence of anemia for the years 2005 and 2011 was 29.9%

[95% CI: (28.04-31.79)] and 18.5% [95% CI: 17.45-19.60)], respectively. The prevalence was

13.8% [95% CI: (11.44-16.41)] in urban areas and 23% [95% CI: (21.99-24.03)] in rural areas.

In the period 2005 to 2011, the highest prevalence of anemia among lactating mothers was

48.7% [95%CI: (40.80-56.62)] found in Ethiopian Somali region, while the lowest prevalence

was 9.0% [95%CI: (4.07-15.47)] reported in Addis Ababa. In the period 2005 to 2011, the

prevalence of anemia in lactating mothers was consistently higher among those in the poor

wealth index group, not currently working, with BMI greater or equal to 25 kg/m2, one year

duration of breastfeeding, never educated, never used ANC, never used family planning services,

no iron supplement during pregnancy, and with higher parity. A significant reduction in the

prevalence of anemia among lactating mothers was observed in all background variables from

2005 to 2011(Table 1). Figure 1 shows the classification of anemia in terms of its detailed

parameter.

In the bivariate step of our analysis, age and marital status were not statistically significant in the

data from both individual surveys and pooled data with the cutoff point of p<0.25. The variable

associated with anemia for the 2005 data was BMI, whereas for the 2011 data the variables were

working status, wealth index, ever use of family planning, ANC attendance four times and above

for indexed pregnancy, husband’s education, maternal BMI and duration of breastfeeding.

In the final multivariable model using pooled data, the independent predictors of anemia for

Ethiopian lactating mothers were currently working, wealth index, ever use of family planning,

ANC attendance four times and above for indexed pregnancy, husband’s education, maternal

BMI, time variation in the two surveys, and durations of breastfeeding remained..

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Those lactating mothers who had husbands who attended primary education were at 21% less

likely to have anemia as compared to those mothers who had husbands with no education

[AOR=0.79; 95% CI: (0.68-0.91)].The odd of being anemic in working lactating mothers was

29% less as compared to their counter parts [AOR=0.71; 95% CI: (0.63-0.80)].Those lactating

mothers having a normal maternal BMI (18.5kg/m2-24.99kg/m

2) were 22% less likely to be

anemic as compared to lactating mother with low BMI (<18.5kg/m2) [AOR=0.78; 95% CI:

(0.68-0.89)].Similarly, lactating women who are categorized in middle [AOR=0.83; 95% CI:

(0.71-0.98)] and rich wealth quintiles [AOR=0.83; 95% CI: (0.70-0.98)] were each 17% less

likely to have anemia as compared to lactating women in poorer quintiles.

Among reproductive characteristics, family planning use and antenatal care (ANC) were the

significant factors associated with anemia in lactating mothers. Lactating mothers who ever used

family planning were 32% less likely to have anemia as compared to lactating mothers who

never used family planning [AOR=0.68; 95% CI: (0.57- 0.80)]. Lactating mothers who reported

ANC attendance four times or more for indexed pregnancy were 27% less likely to have anemia

as compared to mothers who never attended ANC [AOR=0.73; 95% CI: (0.59-0.91)]. Those

lactating mothers who breastfed for two years were 24% less likely to have anemia as compared

to lactating women who breastfed for one year [AOR=0.76; 95% CI: (0.66-0.87)] (Table 2).

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Discussion

Over one fifth of lactating mothers were anemic in Ethiopia, which is lower as compared to other

developing countries. For example, more than 90% of lactating mothers have been reported as

having anemia in India 14

and 29.6% of lactating mothers in Zimbabwe developed anemia15

.

Another study from Myanmar reported an anemia prevalence rate of 60.3% in lactating women,

with 20.3% of lactating mothers having severe anemia16

. Although the prevalence of anemia

among lactating mothers in Ethiopia was relatively low as compared to these studies, it remains a

public health problem according to WHO classification17

. The relatively better prevalence of

anemia in Ethiopia among lactating mothers may be due to the cultural norms of providing

nutritional care to lactating mothers during the postpartum period. During the post-partum

period, lactating mothers are encouraged to rest for 3 to 6 months and to eat a variety of foods

including from animal sources, even during religious fasting periods. Iron supplementation

coverage in Ethiopia remained low among pregnant mothers10

, despite its known contribution for

reducing the risk of postpartum hemorrhage 12

. Post-partum hemorrhage was also found to be

one of the risk factors for anemia during the period of lactation18

. This study showed that anemia

is a widespread problem in the pastoralist communities of Ethiopian Somali and Afar. The

prevalence of anemia in lactating mothers was higher in the pastoralist regions and showed slow

decline in these regions from 2005 to 2011. This could be due to the fact that pastoralist

communities are heavily dependent on animal milk as a source of daily food, with poor iron

bioavailability19 20

. The other reason could be due to low utilization of family planning and

antenatal care services in pastoralist areas10

.


husband with a higher level of education was found to be associated with less odd of having

anemia among lactating mothers. Those mothers having husbands with primary level education

were less likely to have anemia as compared to those with husbands who had no education.


contradictory to many studies from Ethiopia as well as from abroad 16 21-23

. This might be one

important motivator to involve husbands in anemia prevention efforts.

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Working lactating mothers had lower odd of having anemia as compared to their counter parts.

This might be because working mothers were earning money as compared to non-working

mothers and the extra income enabled access to purchase more food items, including animal

sources (meat, poultry, fish etc), and increase dietary diversity. Studies have shown that income

growth improves diet diversity which in turn improves micronutrient intake, including iron 24 25

.

Similarly, the lactating mothers in the lower wealth groups had greater odds of anemia as

compared to lactating mothers in the higher wealth quintiles. In many other studies of anemia

among reproductive age women, the wealth index was found to be a statistically significant

factor 16 21

. Other studies have also shown that women of low socio-economic status are at risk

for iron deficiency anemia (IDA) in late pregnancy and in the postpartum period26 27

. Therefore,

women’s empowerment through economic interventions and working status could have a

positive contribution towards preventing anemia.

This study also supports the importance of family planning for reducing the risk of anemia.

Those lactating mothers who have ever used family planning (modern or traditional) had a lower

odd of having anemia as compared to those who had never used family planning. This finding is

consistent with studies from Ethiopia and Timor-Leste which showed that use of family planning

was associated with lower odd of having anemia.21 28

.21

.



being in the normal BMI category (18.5-24.9kg/m2) was associated with a lower odd of having

anemia. This finding is similar with others studies29 30

. When a mother is at risk of deficiency for

macronutrients, most likely she is also at risk also other micronutrient deficiencies such as

iron31

..

ANC attendance was found to be associated with anemia among lactating mothers. This is most

likely due to the fact that during ANC attendance mothers have been advised to take iron

supplements according to the Ethiopian micronutrient guideline and instructed to consume

different sources of iron rich food items32

. Therefore, improving iron status during pregnancy

also helps to prevent anemia during the lactation period.

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disparities regarding the prevalence of anemia, with the highest prevalence found in pastoralist

regions of Ethiopian Somali and Afar. Promoting partner education, improving maternal

nutritional status, creating behavior change among lactating mothers to use family planning and

attend antenatal care services at health facilities are recommended interventions to reduce the

prevalence of anemia among lactating women in Ethiopia.

Conclusion


disparities regarding the prevalence of anemia, with the highest found in pastoralist regions of

Ethiopian Somali and Afar. Promoting partner education, improving maternal nutritional status,

creating behavior change among lactating mothers to use family planning and attend antenatal

care services at health facilities are recommended interventions to reduce the prevalence of

anemia among lactating women in Ethiopia.

Competing interests


Funding statement








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Acknowledgements




References







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2001;185:4348-53.

5. Sserunjogi L, Scheut F, Whyte SR. Postnatal anaemia: neglected problems and missed opportunities in

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8. Brabin BJ, Hakimin M, Pelletier D. An Analysis of Anemia and Pregnancy-Related Maternal Mortality.

The Journal of Nutrition 2001;131:604S-15S.

9. Kassebaum NJ, Jasrasaria R, Naghavi M, Wulf SK, Johns N, Lozano R, et al. A systematic analysis of

global anemia burden from 1990 to 2010. Blood 2014;123(5).

10. Central Statistical Agency (CSA) Ethiopia. Demographic and Health Survey 2011. Addis Ababa,

Ethiopia and Calverton, Maryland, USA: CSA and ORC Macro. 2011.





13. Peter C, Jack V. Automated variable selection methods for logistic regression produced unstable

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18. World Health Organization (WHO). Recommendations for the Prevention of Postpartum

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25. Doan D. Does income growth improve diet diversity in China?Selected Paper prepared for

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February 2014 2014.

26. Bodnar L, Cogswell M, Scanlon K. Low income postpartum women are at risk of iron deficiency.

Journal of Nutrition 2002;132:2298–302.

27. Sadeghian M, Fatourechi A, Lesanpezeshki M, Ahmadnezhad E. Prevalence of Anemia and Correlated

Factorsin the Reproductive Age Women in Rural Areas of Tabas. Journal of Family and

Reproductive Health 2013;7(3):143.

28. Lovermail AA, Hartman M, Chia KS, Heymann DL. Demographic and Spatial Predictors of Anemia in

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Table 1. Prevalence of anemia among lactating mothers by background characteristics in Ethiopia

using pooled data from the EDHS 2005 and 2011

Background

characteristics

2005 2011 2005-2011

Total

lactating

women

Prevalence of

anemia (95% CI)

Total

lactating

women

Prevalence of

anemia (95% CI)

Total

lactating

women

Prevalence of

anemia (95% CI)

Region

Tigray 142 35.4(27.69-43.33) 281 13.4(9.89-17.90) 422 20.8(17.18-24.93)

Afar 22 46.2(25.88-66.16) 38 42.4(27.27-58.10) 59 43.8(31.83-56.87)

Amhara 591 32.2(28.47-36.00) 1352 18.9(16.91-21.09) 1,943 22.9(21.12-24.86)

Oromia 826 28.5(25.45-31.60) 2041 20.1(18.39-21.87) 2,867 22.5(21.00-24.05)

Somali 60 49.2(37.50-62.50) 92 48.3(37.76-58.02) 152 48.7(40.80-56.62)

Benshangul-gumz 24 26.8(10.81-44.92) 59 20.5(11.51-32.02) 83 22.9(14.81-32.83)

SNNPR 578 26.2(22.66-29.82) 1059 13.5(11.54-15.66) 1,637 18.0(16.16-19.88)

Gambella 6 46.5(14.66-85.34) 18 23.2(7.49-45.31) 25 28.0(13.15-47.7)

Harari 3 27.1(1.67-86.80) 10 23.4(3.50-51.95) 15 20.0(5.35-45.35)

Addis Ababa 27 14.4(4.89-31.97) 83 7.3(2.98-14.43) 111 9.0(4.067-15.47)

Dire Dawa 5 33.0(7.35-81.76) 13 35.8(15.68-65.91) 18 33.3(14.77-56.9)

Residence

Urban 145 19.4(13.49-26.34) 595 12.4(9.96-15.27) 740 13.8(11.44-16.41)

Rural 2140 30.6(28.68-32.59) 4452 19.4(18.27-20.59) 6592 23.0(21.99-24.03)

Wealth index

Poor 986 32.2(29.29-35.12) 2306 21.4(19.74-23.09) 3293 24.6(23.15-26.09)

Middle 517 29.9(26.15-34.04) 1102 17.0(14.84-19.27) 1619 21.1(19.19-23.16)

Rich 782 27.0(23.96-30.18) 1639 15.6(13.86-17.37) 2420 19.3(17.76-20.91)

Current occupation

status

Not working* 1568 31.8(29.55-34.16) 2325 21.0(19.37-22.68) 3893 25.4(24.06-26.29)

Working ≠ 712 25.5(22.46-28.86) 2722 16.4(15.03-17.81) 3434 18.3(17.02-19.61)

BMI

<18.5 481 33.9(29.76-38.21) 1138 19.3(17.12-21.70) 1619 23.6(21.57-25.71)

18.5-24.99 1729 28.3(26.20-30.44) 3723 18.1(16.89-19.37) 5453 21.3(20.22-22.39)

25+ 65 42.1(30.05-53.76) 175 20.4(15.07-27.04) 240 26.3(20.98-32.09)

Duration of

breastfeeding

1 year 1072 30.7(27.98-33.50) 2461 20.6(19.04-22.23) 3533 23.7(22.31-25.11)

2 years 728 26.6(23.53-29.95) 1490 15.4(13.61-17.27) 2218 19.1(17.52-20.79)

3+ years 478 32.5(28.34-36-72) 1096 18.2(15.96-20.52) 1575 22.6(20.59-24.72)

Respondents

education

none 1804 31.8(29.70-34.00) 3486 19.2(17.91-20.52) 5291 23.5(22.36-24.65)

Primary 394 24.3(20.32-28.79) 1377 18.3(16.32-20.41) 1770 19.6(17.80-21.50)

secondary 79 17.3(10.46-27.31) 126 8.3(4.10-13.69) 205 11.8(7.83-16.67)

Higher 8 1.1(0.63-48.03) 58 9.7(4.30-20.28) 66 8.7(3.77-17.95)

Husband education

None 1333 33.9(31.40-36.48) 2531 20.3(18.77-21.91) 3864 25.0(23.65-26.38)

Primary 701 26.2(23.09-29.60) 2048 17.2(15.60-18.87) 2749 19.5(18.05-21.01)

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Secondary 199 20.7(15.41-26.64) 238 14.3(10.26-19.17) 437 17.2(13.84-20.92)

Higher 23 14.8(3.43-31.53) 147 13.7(8.75-19.88) 170 13.8(8.99-19.30)

Family planning

Never use 1775 32.1(29.97-34.31) 2889 21.2(19.72-22.70) 4663 25.4(24.16-26.66)

Ever use 15 16.4(2.30-37.52) 2158 14.9(13.46-16.47) 2173 14.9(13.46.16.45)

ANC use

Never 1636 32.0(29.80-34.32) 2977 20.4(18.97-21-87) 4613 24.5(23.27-25.75)

1-3 386 27.7(23.43-32.35) 1208 18.4(16.27-20.64) 1594 20.6(18.65-22.62)

4+ 260 18.9(14.44-23.95) 845 12.6(10.44-14.91) 1105 14.1(12.16-16.27)

Iron supplement

during pregnancy

No 2046 30.1(28.15-32.12) 4196 18.8(17.64-20.01) 6242 22.5(21.47-23.54)

Yes 236 27.1(21.74-33.06) 840 16.9(14.48-19.55) 1076 19.2(16.97-21.68)

Parity

1-4 1293 28.9(26.50-31.44) 3111 18.1(16.77-19.48) 4404 21.3(20.11-22.53)

5-9 903 30.5(27.52-33.52) 1739 19.6(17.79-21.53) 2642 23.3(21.73-24.96)

10+ 89 37.1(27.53-47.46) 197 17.0(12.02-12.46) 287 23.2(18.72-28.50)

Total 2285 29.9(28.04-31.79) 5047 18.5(17.45-19.60) 7332 22.1(21.13-23.03) ANC-Antenatal Care, BMI-Body Mass Index, *those mothers who currently work to earn money, ≠ those mothers

who do not currently engage in any type of formal work to earn money.


data from the EDHS 2005 and 2011 Variables 2005 2011 2005-2011

COR 95%CI AOR 95%CI COR 95%CI AOR 95%CI COR 95%CI AOR 95%CI

Occupation

Not working* 1.00 1.00 1.00 1.00 1.00 1.00

Working≠ 0.82(0.66-1.00) 0.83(0.64-1.06) 0.62(0.54- 0.71) 0.68(0.58-0.78) 0.64(0.57-0.72) 0.71(0.63-0.80)

Wealth index

Poor 1.00 1.00 1.00 1.00 1.00 1.00

Middle 0.71(0.54-0.92) 0.82(0.61-1.10) 0.74(0.61- 0.89) 0.85(0.69-1.04) 0.74(0.64-0.87) 0.83(0.71-0.98)

Rich 0.66(0.53-0.82) 0.91(0.68-1.22) 0.62(0.52-0.72) 0.80(0.65-0.97) 0.65(0.57-0.73) 0.83(0.70-0.98)

FP use

Never used 1.00 1.00 1.00 1.00 1.00 1.00

Ever used 0.37(0.11-1.28) 0.51(0.14-1.91) 0.54(0.46-0.63) 0.69(0.58-0.82) 0.48(0.41-0.55) 0.68(0.57-0.80)

ANC attended

Never 1.00 1.00 1.00 1.00 1.00 1.00

1-3 0.78(0.59-1.03) 0.94(0.66-1.33) 0.78(0.59-1.00) 1.00(0.83-1.2) 0.81(0.71-0.94) 0.99(0.84-1.16)

4+ 0.55(0.41-0.74) 0.82(0.53-1.28) 0.55(0.41-0.74) 0.71(0.55-0.92) 0.52(0.44-0.61) 0.73(0.59-0.91)

Husband

education

None 1.00 1.00 1.00 1.00 1.00 1.00

Primary 0.77(0.61-0.96) 0.77(0.58-1.01) 0.69(0.59-0.80) 0.80(0.67-0.94) 0.69(0.61-0.78) 0.79(0.68-0.91)

Secondary 0.55(0.39-0.77) 0.83(0.50-1.38) 0.64(0.48-0.87) 0.81(0.58-1.14) 0.62(0.49-0.77) 0.83(0.62-1.09)

Higher 0.58(0.26-1.30) 0.50(0.73-3.40) 0.72(0.49-1.0) 0.96(0.61-1.52) 0.64(0.46-0.90) 0.94(0.61-1.45)

BMI*

<18.5 1.00 1.00 1.00 1.00 1.00 1.00

18.5-24.99 0.74(0.59-0.92) 0.76(0.59-0.99) 0.74(0.64-0.86) 0.79(0.68-0.93) 0.76(0.67-0.86) 0.78(0.68-0.89)

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25+ 1.1(0.62-1.90) 1.66(0.79-3.48) 0.82(0.58-1.2) 1.12(0.77-1.62) 0.85(0.64-1.12) 1.21(0.87-1.68)

Breastfeeding

1 year 1.00 1.00 1.00 1.00 1.00 1.00

2 years 0.79(0.64-0.99) 0.79(0.62-1.03) 0.71(0.60-0.83) 0.75(0.63-0.88) 0.75(0.66-0.85) 0.76(0.66-0.87)

3+ years 0.99(0.77-1.27) 1.10(0.82-1.49) 0.71(0.59-0.86) 0.82(0.67-0.99) 0.81(0.70-0.94) 0.89(0.76-1.05)

Time laps

2005 1.00 1.00

2011 0.65(0.58-0.73) 0.73(0.64-0.85) COR: Crude Odds Ratio, AOR: Adjusted Odds Ratio, BMI: Body Mass Index, ANC: Antenatal Care, 1.00 is the

reference category, *those mothers who currently work to earn money, ≠ those mothers who do not currently engage

in any type of formal work to earn money.

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Factors associated to develop anemia among lactating mothers in Ethiopia: A pooled data

analysis from two rounds of demographic and health surveys

Anemia prevalence and associated factors among lactating mothers in Ethiopia: Evidence from the

2005 and 2011 demographic and health surveys

Yihunie Lakew1, Sibhatu Biadgilign2, Demewoz Haile3*





Email address











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Abstract








gram per deciliter.g/dl



Ethiopian Somali region, followed by 43.8% [95% CI: (31.83-56.87)] in Afar region. The

prevalence in urban settings was 13.7% [95% CI: (11.35-16.05)] and in rural areas was 23%

[95% CI: (22.68-23.32)]. The multivariable statistical model showed that lactating mothers who

had husbands who attended primary education mothers whose husbands had attended primary

and secondary education were, respectively, 26% [AOR=0.79; 95% CI: (0.68-0.91)], adjusted

odds ratio (AOR) = 0.74; 95% CI: (0.60-0.92)] who were currently working [AOR=0.71; 95%

CI: (0.63-0.80)], had normal maternal body mass index (BMI) from 18.5kg/m2 to 24.99kg/m

2

[AOR=0.78; 95% CI: (0.68-0.89)], were in the middle wealth quintile [AOR=0.83; 95% CI:

(0.71-0.98)] and rich wealth quintile [AOR=0.83; 95% CI: (0.70-0.98)], reported ever use of

family planning [AOR=0.68; 95% CI: (0.57-0.80)], were attending antenatal care (ANC) for

indexed pregnancy four times or more [AOR=0.73; 95% CI: (0.59-0.91)], experienced time

variation between two surveys [AOR=0.73; 95%CI: (0.64-0.85)] and who breastfed for two

years [AOR=0.76; 95% CI: (0.66-0.87)] were found to be associated with anemia


communities of Ethiopian Somali and Afar.in rural and pastoralist Ethiopia. Factors including

paternal education, family planning use, body mass index (BMI), occupational status, and







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antenatal care attendance were strong predictors of anemia among lactating mothers. Promoting

partner education, improving maternal nutritional status, creating behaviour change among

lactating mothers to use family planning and attend ANC services at health facilities are

recommended interventions to reduce the prevalence of anemia among lactating mothers in

Ethiopia.Promoting partner education, improving BMI, scaling up family planning and antenatal

care services are recommended interventions.

ARTICLE SUMMARY


• The study attempted to identify factors associated with laboratory confirmed anemia in

lactating mothers at the national level. The study findings can be used to inform policy

and program actions.

• Some regions from which data was collected had, the data has small sample size. So that

it should be interpreted in caution. for some regions, which questions the accuracy of

prevalence estimates per region.

Key messages

• Anemia prevalence is a public health problem among lactating mothers in Ethiopia, .with

the highest prevalence found in pastoralist regions of Ethiopian Somali and Afar

• There are regional disparities regarding the prevalence of anemia among lactating

mothers, with the highest rates found in pastoralist regions.

• A statistically significant reduction of anemia prevalence in lactating mothers was


• Being in middle and rich wealth quintiles, two years of breastfeeding, currently working,


antenatal care attendance for four or more visits were factors found to be associated with

anemia.

• Husband education, family planning and ANC attendance were protective factors for

developing anemia.


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• Overweight and obese lactating mothers were at high risk for developing anemia.

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Introduction

Anemia is a serious nutrition problem affecting millions in Anemia is one of the nutrition

problems affecting millions in developing countries, and remains a major challenge for human

health, social and economic development1. Lactating mothers are one of the vulnerable groups of

anemia. During the period of lactation, mothers are susceptible to anemia due to maternal iron

depletion and blood loss during child birth2. Studies have shown that though breast milk is not a

good source of iron, the concentration of iron in breast milk is independent of maternal iron

status. This showed that the quality of breast milk is maintained at the expense of maternal

stores2 3. Studies have shown that the concentration of iron in breast milk is independent of

maternal iron status and that the quality of breast milk is maintained at the expense of maternal

stores2 3

.



enough energy and nutrient intake in their diets. Yet the problem of anemia in postnatal women

has been relatively neglected which is far away from previously thoughts8. Lactating mothers

enter begin into the postnatal period after having iron depleted through the continuum from

pregnancy to childbearing 5. A study from South Africa evidenced showed that iron status was

associated with there was a strong relation between iron status and depression, stress, and

cognitive functioning in poor African mothers during the postpartum period6. In a meta-analysis

of observational and intervention trials, Ross and Thomas6, found that approximately 20% of the

maternal mortality seen in sub-Saharan Africa and South Asia was attributable to anemia that is

was primarily the result of iron deficiency 7.. Ethiopia is one of the sub-Saharan Africa countries

heavily affected by anemia8


high rates of maternal, infant and child mortality globally8 9. In Ethiopia, the maternal mortality

ratio was 676 maternal deaths per 100,000 live births for the seven-year period preceding the

2011 EDHS survey. This rate is one of the highest in the world. The infant mortality rate was 59

per 1,000 live births and the under-five mortality rate was 88 per 1,000 live births10

.





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Surveys (EDHS)1011

. The prevalence of anemia in lactating mothers was 29.9% in 2005 and

18.5% in 201110




mothers.


(EDHS)10,11. The prevalence of anemia among in lactating mothers was 29.9% in 2005 and

18.5% in 2011 12




mothers., which is considerably higher as compared with other women (23.9% in 2005 and 15%

in 2011), and low as compared with pregnant mothers (30.6% in 2005 and 22% in 2011). This

prevalence of anemia in lactating mothers is one of the highest among developing countries.

However, little information is available regarding socio-economic factors associated with anemia

among lactating mothers. This study aimed to identify factors associated with anemia among

lactating mothers in Ethiopia using the pooled data of EDHS 2005 and 2011.However, there is a

scarcity of evidence for the factors associated with anemia among lactating mothers in Ethiopia.

Therefore, tThis study aimsed to identify the factors associated with anemia among Ethiopian

lactating mothers in Ethiopia using the pooled data of EDHS 2005 and 2011.

Methods


This study is an in-depth analysis to identify risk factors associated for with anemia among

lactating mothers based on secondary data of the EDHS 2005 and 2011 datasets. The EDHS was

designed to provide population and health indicators at national (urban and rural) and regional

levels. It is and were conducted within every five year intervals. Both the 2005 and 2011 EDHS

samples were selected using a stratified, two-stage cluster design. The detailed methodology is

found elsewhere 11 12.

Data Extraction



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Both EDHS 2005 and 2011 data were downloaded with permission from the Measure EDHS

website in SPSS format with permission. After reviewing understanding the detailed data coding,

further data cleaning and recoding was completed. A total of 7,332 lactating mothers (2,285 from

EDHS 2005 and 5,047 from EDHS 2011) were included in the analysis. Based on published

literature, information on a wide-range of socio-demographic and economic variables, health

service related factors and anemia level indicators were extracted.

Measurement




smoking status12

. All the necessary quality control measures were considered9..





using STATA 11 software. Anemia was re-categorized as anemic and non-anemic from prior

classifications in levels (no, mild, moderate, severe). The background variables were selected

based on literature review and data availability from the two rounds of EDHS. The chosen

variables were region, residence, wealth index, occupation, BMI, duration of breastfeeding,

respondent’s education, husband’s education, family planning use, ANC use, iron

supplementation during pregnancy, time variation between two surveys, marital status, age and

parity.

Descriptive statistics was were used to show the prevalence of anemia among lactating mothers

varying by background characteristics.across the regional states and city administrations of

Ethiopia. Binary and multivariable Multivariable binary logistic regression statistical analysis

was were carried out to determine the factors associated with anemia among lactating mothers.

Variables found statistically significant at p-value <0.25 during bivariate analysis were analyzed

in the multivariable logistic regression model13. This p-value cut off point prevented removing

variables that would potentially have an effect during multivariable analysis. Both crude and







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adjusted odds ratios (OR) were determined reported with 95% confidence interval (CI). All tests

were two-sided, weighted and a p-value <0.05 was considered statistically significant. Variables

at p-value <0.05 were considered statistically significant found statistically significant at p-value

<0.3 during bivariate analysis were considered for adjustment in the multivariable logistic

regression model.

Ethical statements




Results

Prevalence of anemia in lactating mothers by background characteristics:

The overall prevalence of anemia among lactating mothers during 2005 and to 2011 was found

to be 22.1% (95% CI: 21.13-23.03). The prevalence of anemia for the years 2005 and 2011 was

29.9% [95% CI: (28.04-31.79)] and 18.5% [95% CI: 17.45-19.60)], respectively. The prevalence

was 13.8% [95% CI: (11.44-16.41)] in urban areas and 23% [95% CI: (21.99-24.03)] in rural

areas. In the period 2005 to 2011, the highest prevalence of anemia among lactating mothers was

48.7% [95%CI: (40.80-56.62)] found in Ethiopian Somali region, while the lowest prevalence

was 9.0% [95%CI: (4.07-15.47)] reported in Addis Ababa. . The highest prevalence of anemia

among lactating mothers was found in Somali region (48.7%), while the lowest prevalence was

reported in Addis Ababa (9.0%) In the period 2005 to 2011, the prevalence of anemia in lactating

mothers was consistently higher among those in the poor wealth index group, not currently

working, with BMI greater or equal to 25 kg/m2, one year duration of breastfeeding, never

educated, never used ANC, never used family planning services, no iron supplement during

pregnancy, and with higher parity. A significant reduction in the prevalence of anemia among

lactating mothers was observed in all background variables from 2005 to 2011 (Table 1). Figure

1 shows the classification of anemia in terms of its detailed parameter.

Table 1. Prevalence of anemia among lactating mothers in Ethiopia using pooled data from

the EDHS 2005 and 2011

Location Variables 2005-2011



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Weighted total number of

lactating mothers

Weighted prevalence of

anemia (95% CI)

Region

Tigray 422 20.8(17.18-24.93)

Afar 59 43.8(31.83-56.87)

Amhara 1943 22.9(21.12-24.86)

Oromiya 2867 22.5(21.00-24.05)

Somali 152 48.7(40.80-56.62)

Benshangul 83 22.9(14.81-32.83)

SNNP 1637 18.0(16.16-19.88)

Gambella 25 28.0(13.15-47.7)

Harar 15 20.0(5.35-45.35)

Adiss Ababa 111 9.0(4.067-15.47)

Diredawa 18 33.3(14.77-56.9)

Residence

Urban 740 13.8(11.44-16.41)

Rural 6592 23.0(21.99-24.03)

Total 7332 22.1(21.13-23.03)


data from both individual surveys and pooled data with the cutoff point of p<0.25. The variable




In total, 12 variables for anemia were both available from the EDHS and identified as risk factors

based on literature review. Of the twelve, the factors identified as significantly associated with

anemia in the bivariate step were wealth index, place of residence, maternal education, paternal

education, maternal occupation, family planning use, maternal BMI and antenatal care

attendance. In the final multivariable model using pooled data, the independent predictors of

anemia for Ethiopian lactating mothers were currently working, wealth index, ever use of family

planning, ANC attendance four times and above for indexed pregnancy, husband’s education,

maternal BMI, time variation in the two surveys, and durations of breastfeeding

remained.However, in the multivariable model, paternal education, maternal occupation, family

planning use, maternal BMI and antenatal care attendance remained the independent predictors

of anemia for Ethiopian lactating mothers.




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Those lactating mothers who had husbands who attended primary education were at 216% lower

less risk likely to for haveing anemia as compared to those mothers who had husbands with no

education [AOR=0.79; 95% CI: (0.68-0.91)].[AOR=0.74; 95% CI: (0.60-0.92)]. Those lactating

mothers with husbands who had secondary education had a 34% lower risk of having anemia as

compared to those lactating mothers with husbands who had no education [AOR=0.66; 95% CI:

(0.44-0.99)]. The odd of being anemic in Wworking lactating mothers had awas 292% lower less

risk for anemia as compared to their counter parts [AOR=0.71; 95% CI: (0.63-

0.80)].[AOR=0.78; 95% CI: (0.63-95)]. Those lactating mothers Hhaving a normal maternal

BMI (18.5kg/m2-24.99kg/m

2) were 22% less likely to be anemic as compared to lactating

mother with low BMI (<18.5kg/m2) [AOR=0.78; 95% CI: (0.68-0.89)].was found protective of

anemia [AOR=0.79; 95% CI: (0.63-0.98)]. However, lactating mothers who had BMI 25kg/m2

had a 80% higher risk of developing anemia as compared to undernourished (defined as

BMI<18.5kg/m2) lactating mothers[AOR=1.8; 95% CI: (1.02-3.12)](Table 2). Similarly,

lactating women who are categorized in middle [AOR=0.83; 95% CI: (0.71-0.98)] and rich

wealth quintiles [AOR=0.83; 95% CI: (0.70-0.98)] were each 17% less likely to have anemia as

compared to lactating women in poorer quintiles.

Among reproductive maternal characteristicshealth service factors, family planning use and

antenatal care (ANC) were the significant predictors factors associated withof anemia in lactating

mothers. Lactating mothers who ever used family planning were 2932% less likely to have

anemia as compared to lactating mothers who never used family planning [AOR=0.68; 95% CI:

(0.57- 0.80)].[AOR=0.71; 95% CI: (0.55-0.92)]. Lactating mothers who reported ANC

attendance four times or more for indexed pregnancy were 273% less likely to develop have

anemia as compared to mothers who never attended ANC [AOR=0.73; 95% CI: (0.59-0.91)].

their counterparts [AOR=0.77; 95% CI: (0.62-0.95)] Those lactating mothers who breastfed for

two years were 24% less likely to have anemia as compared to lactating women who breastfed

for one year [AOR=0.76; 95% CI: (0.66-0.87)] (Table 2).












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Variable COR (95% CI) AOR (95% CI)

Wealth index

Poor 1 1

Medium 0.82(0.71-0.95) 1.0(0.79-1.28)

Rich 0.73(0.64-0.83) 1.1(0.88-1.42)

Place of residence

Urban 1

Rural 1.9(1.51-2.33) 1.2(0.72-1.98)

Maternal education

No education 1 1

Primary 0.79(0.70-0.91) 0.80(0.61-1.05)

Secondary 0.44(0.28-0.67) 76(0.36-1.59)

Higher 0.31(0.13-0.73) 0.5(0.001-44.44)

Paternal education

No education 1 1

Primary 0.73(0.65-0.82) 0.74(0.60-0.92)**

Secondary 0.63(0.48-0.81) 0.66(0.44-0.99)*

Higher 0.48(0.31-0.75) 0.70(0.19-2.60)

Maternal occupation

Not working 1 1

Working 0.66(0.59-0.74) 0.78(0.63-95)*

Family planning use

Never used 1 1

Used 0.60(0.48-0.76) 0.71(0.55-0.92)**

BMI(kg/m2)

< 18.5 1 1

18.5-24.99 0.88(0.77-0.99) 0.79(0.63-0.98)*

25+ 1.2(0.85-1.57) 1.8(1.024-3.117)*

ANC attendance

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Not attend 1 1

Attend 0.68(0.55-0.83) 0.77(0.62-0.95)*

*P<0.05 **P<0.001

Discussion

Over one fifth of lactating mothers were anemic in Ethiopia, which is relatively lower as

compared to other developing countries. For example, an Indian study where more than 90% of

lactating mothers have been reported as having anemia in India were reported as anemic14

and .

A study from Zimbabwe showed that about 29.6% of lactating women mothers in Zimbabwe

developed anemia15 which is also higher than found in Ethiopia.


with 20.3% of lactating mothers having severe anemia16

. Although the prevalence of anemia

among lactating mothers in Ethiopia was relatively low as compared to the above studiesthese

studies, still it remains a is a moderate public health problem according to WHO classification17

.

The relatively better prevalence of anemia in Ethiopia among lactating mothers may be due to

the cultural norms of providing nutritional care to lactating mothers during the postpartum

period. During the post-partum period, lactating mothers are encouraged to rest for 3 to 6 months

and to eat a variety of foods including from animal sources, even during religious fasting

periods.Anemia during lactation has received less attention in the Health Extension Program

which is practiced in Ethiopia. Even though the health extension package of Ethiopia has

nutrition component, it has no much emphasis on prevention of anemia among lactating mothers.

Iron supplementation coverage in Ethiopia remained low among pregnant mothers10

The EDHS

also shows that iron supplementation coverage for pregnant mothers remained low over time,

despite its known contribution for reducing the risk of postpartum hemorrhage 12

. Post-partum

hemorrhage was also found to be one of the risk factors for anemia during the period of

lactation18

. However, the culture of care provided for lactating mothers during the postpartum

period in Ethiopia may contribute to the prevention of anemia.

Although there are common assumptions that pastoralist populations are at a lower risk for

anemia due to their dietary habits and dependence on animal food sources, tThis study showed

that anemia is a widespread problem in the pastoralist communities of Ethiopian Somali and

Afar. The prevalence of anemia in lactating mothers was higherst in the pastoralist regions and



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showed slow decline in these regions from 2005 to 2011. the decrease in prevalence between

2005 and 2011 EDHS was very small. This could be due to the fact that pastoralist communities

are heavily dependent on animal milk as a source of daily food, with poor iron bioavailability19

20. The other reason could be due to low utilization of family planning and antenatal care services

in pastoralist areas10

.

This might be associated with anemia specifically resulting from infection, such as malaria

which is prevalent in those pastoralist areas.


husband with a higher level of education was found to be protective associated with less odd of

having for anemia among lactating mothers. Those mothers having husbands with education of

primary and secondary levels education were less likely to develop have anemia as compared to

those with husbands who had no education. However, maternal educational status was not

statistically associated with anemia, which is contradictory to many studies from Ethiopia as well

as from abroad 16 21-23

. The absence of association between maternal educational status and

anemia versus the associate with husbands’ educational status and anemia among lactating

mothers might imply that partner education is more influential in preventing anemia. This might

indicate be the one importantce motivator to of involveing husbands in anemia prevention

efforts.

Working Llactating mothers who are working were athad lower risk odd of having anemia as

compared to their counter parts. This might be because working mothers are were earning money

as compared to non-working mothers and the extra income enabled access to purchase more food

items, including animal sources (meat, poultry, fish etc), and increase dietary diversity. Studies

have shown that income growth improves diet diversity which in turn improves micronutrient

intake, including iron 24 25. Similarly, the lactating mothers in the lower wealth groups had

greater odds of anemia as compared to lactating mothers in the higher wealth quintiles. In many

other studies of anemia among reproductive age women, the wealth index was found to be a

statistically significant factor 16 21

. Other studies have also shown that women of low socio-

economic status are at risk for iron deficiency anemia (IDA) in late pregnancy and in the

postpartum period26 27

. Therefore, women’s empowerment through economic interventions and

working status could have a positive contribution towards preventing anemia.






Formatted: Font: Times New Roman, 12 pt







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more empowered as compared to non-employed mothers. Therefore, women’s empowerment

through economic interventions could have a positive contribution toward preventing anemia.

As one strategy for preventing anemia, family planning has been used. This study also supports

the importance of family planning for reducing the risk of anemia. Those lactating mothers who

have ever used family planning (modern or traditional) had a lower risk odd of developing

having anemia as compared to those who had never used family planning. This finding is


was associated with lower odd of having anemia.21 28.an Ethiopian study on the correlates of

anemia among reproductive age women by Samson and his colleague 21

.



being in the normal BMI category (18.5-24.9kg/m2) was negatively associated with a lower odd

of developing having anemia as expected. This finding is similar with others studies29 30

. When a

mother is at risk of deficiency for macronutrients, most likely she is also at risk also other

micronutrient deficiencies such as iron31

. This study found that overweight and obese lactating

mothers were at an 80% higher risk for having anemia. A study from Mexico found that being

overweight did not necessarily diminish the risk of anemia; rather diet quality was the determiner

28. A study by Cepeda-Lopez and his colleagues explains lower iron status among obese

individuals explained by lower absorption of iron due to obesity related inflammation which

affect regulation of Hepcidin. Hepcidin levels are higher in obese individuals and are linked to

subclinical inflammation which affect iron absorption negatively 28.

ANC attendance was found to be a protective associated factor with for anemia among lactating

mothers. This is most likely due to the fact that during ANC attendance mothers have been

advised to take iron supplements according to the Ethiopian micronutrient guideline and

instructed to consume different sources of iron rich food items32. Therefore, improving iron

status during pregnancy also helps to prevent anemia during the lactation period.

In many studies of anemia among reproductive age women, the wealth index was found to be a

statistically significant factor 13 19. However, in this study the wealth index was not found to be a

statistically significant factor.






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disparities regarding the prevalence of anemia, with the highest prevalence found in pastoralist

regions of Ethiopian Somali and Afar. Promoting partner education, improving maternal

nutritional status, creating behavior change among lactating mothers to use family planning and

attend antenatal care services at health facilities are recommended interventions to reduce the

prevalence of anemia among lactating women in Ethiopia.

Conclusion


disparities regarding the prevalence of anemia, with the highest rates found in pastoralist regions

of Ethiopian Somail and Afar.. Promoting partner education, improving maternal nutritional

status, creating behavior change among lactating mothers to use family planning and attend

antenatal care services at health facilities are recommended interventions to reduce the

prevalence of anemia among lactating women in Ethiopia. Factors such as husband’s educational

status, family planning use, BMI, maternal occupational status and ANC attendance were

identified as associated factors for anemia among lactating mothers. Improving BMI, promotion

of family planning and ANC are recommended interventions to prevent anemia. Involvement of

males in prevention of anemia should be considered. Attention should also be given to

preventing anemia among lactating mothers through the Health Extension Package and at any

health service delivery contact for lactating mothers.

Competing interests


Funding statement






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Acknowledgements




References







15.


amongLow income women in the United States. J. obstet. Gynecol 2001;185:4348-53.

5. SSERUNJOGI L, SCHEUT2 F, WHYTE SR. Postnatal anaemia: neglected problems and missed

opportunities in Uganda. HEALTH POLICY AND PLANNING 2003;18(2):225-31.



2005;135:267–72.















2004;57:1138-46.



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Med 1998;44(12):297-305.





, 2008.

18. World Health Organization (WHO). Recommendations for the Prevention of Postpartum

Haemorrhage (summary of results from a WHO technical consultation, October 2006) Geneva:

WHO 2007.



58(4):731-34.

20. Belachew T. Human Nutrition lecture note series for Health sciences students: JImma Univesity

2005:pp 229.




Ethiopian Women. J HEALTH POPUL NUTR 2010;28(4):359-68.



2011;1(11):304-09.


of Amatole and Nyandeni districts, South Africa International Journal of Development and




February 2014 2014.




Factorsin the Reproductive Age Women in Rural Areas of Tabas. Journal of Family and




ONE 2013;9(3):e91252.



2006;20:A986-A87.






Nutrients 2012;4(12):1958-76.

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2004.

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Background

characteristics

2005 2011 2005-2011

Total

lactating women

Prevalence of

anemia (95% CI)

Total

lactating women

Prevalence of

anemia (95% CI)

Total

lactating women

Prevalence of

anemia (95% CI)

Region

Tigray 142 35.4(27.69-43.33) 281 13.4(9.89-17.90) 422 20.8(17.18-24.93)

Afar 22 46.2(25.88-66.16) 38 42.4(27.27-58.10) 59 43.8(31.83-56.87)

Amhara 591 32.2(28.47-36.00) 1352 18.9(16.91-21.09) 1,943 22.9(21.12-24.86)

Oromia 826 28.5(25.45-31.60) 2041 20.1(18.39-21.87) 2,867 22.5(21.00-24.05)

Somali 60 49.2(37.50-62.50) 92 48.3(37.76-58.02) 152 48.7(40.80-56.62)

Benshangul-gumz 24 26.8(10.81-44.92) 59 20.5(11.51-32.02) 83 22.9(14.81-32.83)

SNNPR 578 26.2(22.66-29.82) 1059 13.5(11.54-15.66) 1,637 18.0(16.16-19.88)

Gambella 6 46.5(14.66-85.34) 18 23.2(7.49-45.31) 25 28.0(13.15-47.7)

Harari 3 27.1(1.67-86.80) 10 23.4(3.50-51.95) 15 20.0(5.35-45.35)

Addis Ababa 27 14.4(4.89-31.97) 83 7.3(2.98-14.43) 111 9.0(4.067-15.47)

Dire Dawa 5 33.0(7.35-81.76) 13 35.8(15.68-65.91) 18 33.3(14.77-56.9)

Residence

Urban 145 19.4(13.49-26.34) 595 12.4(9.96-15.27) 740 13.8(11.44-16.41)

Rural 2140 30.6(28.68-32.59) 4452 19.4(18.27-20.59) 6592 23.0(21.99-24.03)

Wealth index

Poor 986 32.2(29.29-35.12) 2306 21.4(19.74-23.09) 3293 24.6(23.15-26.09)

Middle 517 29.9(26.15-34.04) 1102 17.0(14.84-19.27) 1619 21.1(19.19-23.16)

Rich 782 27.0(23.96-30.18) 1639 15.6(13.86-17.37) 2420 19.3(17.76-20.91)

Current occupation

status

Not working* 1568 31.8(29.55-34.16) 2325 21.0(19.37-22.68) 3893 25.4(24.06-26.29)

Working ≠ 712 25.5(22.46-28.86) 2722 16.4(15.03-17.81) 3434 18.3(17.02-19.61)

BMI

<18.5 481 33.9(29.76-38.21) 1138 19.3(17.12-21.70) 1619 23.6(21.57-25.71)

18.5-24.99 1729 28.3(26.20-30.44) 3723 18.1(16.89-19.37) 5453 21.3(20.22-22.39)

25+ 65 42.1(30.05-53.76) 175 20.4(15.07-27.04) 240 26.3(20.98-32.09)

Duration of

breastfeeding

1 year 1072 30.7(27.98-33.50) 2461 20.6(19.04-22.23) 3533 23.7(22.31-25.11)

2 years 728 26.6(23.53-29.95) 1490 15.4(13.61-17.27) 2218 19.1(17.52-20.79)

3+ years 478 32.5(28.34-36-72) 1096 18.2(15.96-20.52) 1575 22.6(20.59-24.72)

Respondents

education

none 1804 31.8(29.70-34.00) 3486 19.2(17.91-20.52) 5291 23.5(22.36-24.65)

Primary 394 24.3(20.32-28.79) 1377 18.3(16.32-20.41) 1770 19.6(17.80-21.50)

secondary 79 17.3(10.46-27.31) 126 8.3(4.10-13.69) 205 11.8(7.83-16.67)

Higher 8 1.1(0.63-48.03) 58 9.7(4.30-20.28) 66 8.7(3.77-17.95)

Husband education

None 1333 33.9(31.40-36.48) 2531 20.3(18.77-21.91) 3864 25.0(23.65-26.38)

Primary 701 26.2(23.09-29.60) 2048 17.2(15.60-18.87) 2749 19.5(18.05-21.01)


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Secondary 199 20.7(15.41-26.64) 238 14.3(10.26-19.17) 437 17.2(13.84-20.92)

Higher 23 14.8(3.43-31.53) 147 13.7(8.75-19.88) 170 13.8(8.99-19.30)

Family planning

Never use 1775 32.1(29.97-34.31) 2889 21.2(19.72-22.70) 4663 25.4(24.16-26.66)

Ever use 15 16.4(2.30-37.52) 2158 14.9(13.46-16.47) 2173 14.9(13.46.16.45)

ANC use

Never 1636 32.0(29.80-34.32) 2977 20.4(18.97-21-87) 4613 24.5(23.27-25.75)

1-3 386 27.7(23.43-32.35) 1208 18.4(16.27-20.64) 1594 20.6(18.65-22.62)

4+ 260 18.9(14.44-23.95) 845 12.6(10.44-14.91) 1105 14.1(12.16-16.27)

Iron supplement

during pregnancy

No 2046 30.1(28.15-32.12) 4196 18.8(17.64-20.01) 6242 22.5(21.47-23.54)

Yes 236 27.1(21.74-33.06) 840 16.9(14.48-19.55) 1076 19.2(16.97-21.68)

Parity

1-4 1293 28.9(26.50-31.44) 3111 18.1(16.77-19.48) 4404 21.3(20.11-22.53)

5-9 903 30.5(27.52-33.52) 1739 19.6(17.79-21.53) 2642 23.3(21.73-24.96)

10+ 89 37.1(27.53-47.46) 197 17.0(12.02-12.46) 287 23.2(18.72-28.50)


who do not currently engage in any type of formal work to earn money.




Occupation

Not working* 1.00 1.00 1.00 1.00 1.00 1.00

Working≠ 0.82(0.66-1.00) 0.83(0.64-1.06) 0.62(0.54- 0.71) 0.68(0.58-0.78) 0.64(0.57-0.72) 0.71(0.63-0.80)

Wealth index

Poor 1.00 1.00 1.00 1.00 1.00 1.00

Middle 0.71(0.54-0.92) 0.82(0.61-1.10) 0.74(0.61- 0.89) 0.85(0.69-1.04) 0.74(0.64-0.87) 0.83(0.71-0.98)

Rich 0.66(0.53-0.82) 0.91(0.68-1.22) 0.62(0.52-0.72) 0.80(0.65-0.97) 0.65(0.57-0.73) 0.83(0.70-0.98)

FP use

Never used 1.00 1.00 1.00 1.00 1.00 1.00

Ever used 0.37(0.11-1.28) 0.51(0.14-1.91) 0.54(0.46-0.63) 0.69(0.58-0.82) 0.48(0.41-0.55) 0.68(0.57-0.80)

ANC attended

Never 1.00 1.00 1.00 1.00 1.00 1.00

1-3 0.78(0.59-1.03) 0.94(0.66-1.33) 0.78(0.59-1.00) 1.00(0.83-1.2) 0.81(0.71-0.94) 0.99(0.84-1.16)

4+ 0.55(0.41-0.74) 0.82(0.53-1.28) 0.55(0.41-0.74) 0.71(0.55-0.92) 0.52(0.44-0.61) 0.73(0.59-0.91)

Husband

education

None 1.00 1.00 1.00 1.00 1.00 1.00

Primary 0.77(0.61-0.96) 0.77(0.58-1.01) 0.69(0.59-0.80) 0.80(0.67-0.94) 0.69(0.61-0.78) 0.79(0.68-0.91)

Secondary 0.55(0.39-0.77) 0.83(0.50-1.38) 0.64(0.48-0.87) 0.81(0.58-1.14) 0.62(0.49-0.77) 0.83(0.62-1.09)

Higher 0.58(0.26-1.30) 0.50(0.73-3.40) 0.72(0.49-1.0) 0.96(0.61-1.52) 0.64(0.46-0.90) 0.94(0.61-1.45)

BMI*

<18.5 1.00 1.00 1.00 1.00 1.00 1.00

18.5-24.99 0.74(0.59-0.92) 0.76(0.59-0.99) 0.74(0.64-0.86) 0.79(0.68-0.93) 0.76(0.67-0.86) 0.78(0.68-0.89)

Field Code Changed


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25+ 1.1(0.62-1.90) 1.66(0.79-3.48) 0.82(0.58-1.2) 1.12(0.77-1.62) 0.85(0.64-1.12) 1.21(0.87-1.68)

Breastfeeding

1 year 1.00 1.00 1.00 1.00 1.00 1.00

2 years 0.79(0.64-0.99) 0.79(0.62-1.03) 0.71(0.60-0.83) 0.75(0.63-0.88) 0.75(0.66-0.85) 0.76(0.66-0.87)

3+ years 0.99(0.77-1.27) 1.10(0.82-1.49) 0.71(0.59-0.86) 0.82(0.67-0.99) 0.81(0.70-0.94) 0.89(0.76-1.05)

Time laps

2005 1.00 1.00



in any type of formal work to earn money.

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215x279mm (300 x 300 DPI)

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Journal: BMJ Open



Date Submitted by the Author: 27-Dec-2014

Complete List of Authors: Tarekegn, Yihunie; Ethiopian Public Helth Association, Project management Biadgilign, Sibhatu; Independent public health consultants, Addis Ababa, Ethiopia,



Public health




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Anemia prevalence and associated factors among lactating mothers in Ethiopia: Evidence

from the 2005 and 2011 demographic and health surveys


2, Demewoz Haile

3*

1 Ethiopian Public Health Association, Addis Ababa, Ethiopia

2 Independent Public Health Consultant, Addis Ababa, Ethiopia



Email address









Bale Goba, P.O.Box 302



Word count: 2388

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Abstract








gram per deciliter.

Results: The overall prevalence of anemia among lactating mothers was 22.1% [95% CI: (21.13-

23.03)]. The highest prevalence was 48.7% [95% CI: (40.80-56.62)] found in Somali region,

followed by 43.8% [95% CI: (31.83-56.87)] in Afar region. The multivariable statistical model

showed that lactating mothers who had husbands attended primary education [AOR=0.79; 95%

CI: (0.68-0.91)], had been working in the last 12 months preceding the survey [AOR=0.71; 95%

CI: (0.63-0.80)],, had normal maternal body mass index (BMI) from 18.5kg/m2 to 24.99kg/m

2

[AOR=0.78; 95% CI: (0.68-0.89)], middle wealth index [AOR=0.83; 95% CI: (0.71-0.98)] and

rich wealth index [AOR=0.83; 95% CI: (0.70-0.98)], ever use of family planning [AOR=0.68;

95% CI: (0.57-0.80)], attending antenatal care (ANC) for indexed pregnancy four times or more

[AOR=0.73; 95% CI: (0.59-0.91)], experienced time variation between two surveys [AOR=0.73;

95%CI: (0.64-0.85)] and who breastfed for two years [AOR=0.76; 95% CI: (0.66-0.87)] were

associated with lower odd of being anemic.


communities of Somali and Afar. Promoting partner education, improving maternal nutritional

status, creating behavioral change to use family planning and ANC services at health facilities

are recommended interventions to reduce the prevalence of anemia among lactating mothers in

Ethiopia.

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ARTICLE SUMMARY

Article focus

• Anemia is a serious nutritional problem, primarily affecting women of reproductive age

and children, and remains a major challenge in developing countries. In Ethiopia, more

than 20% of women in the reproductive age are anemic.

• Lactating mothers are among vulnerable groups with little information regarding social

determinants of anemia.

Key messages

• Anemia is a public health problem among lactating mothers in Ethiopia, with the highest

prevalence found in pastoralist regions of Somali and Afar.

• A statistically significant reduction of anemia prevalence among lactating mothers was


• Being in middle and rich wealth quintiles, breastfeeding for two years, currently working,


antenatal care attendance for four or more visits were factors associated with lower odds

of having anemia.


• The study attempted to identify factors associated with laboratory confirmed anemia

among lactating mothers at the national level. The study findings can be used to inform

policy and program actions.

• Some regions from which data was collected had small sample size. So that it should be

interpreted in caution. This study also shares the limitation of cross-sectional design

which makes difficult to demonstrate cause and effect relationships.

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Introduction


major challenge for human health, social and economic development1. Lactating mothers are

among vulnerable groups of anemia. During the period of lactation, mothers are susceptible to

anemia due to maternal iron depletion and blood loss during childbirth2. Studies have shown that



the expense of maternal stores2 3.



enough energy and nutrient intake in their diets. Lactating mothers begin the postnatal period






was primarily the result of iron deficiency7.




ratio was 676 maternal deaths per 100,000 live births10which is one of the highest in the world.

The country has considerably high infant and under 5 mortality rates that account for 59 and 88

deaths per 1000 live births, respectively 10.


(EDHS). The prevalence of anemia among lactating mothers was 29.9% in 2005 and 18.5% in

201110,11. It was 30.6% in 2005 and 22% in 2011 among pregnant women and 23.9% in 2005

and 15% in 2011 among women neither non-pregnant nor lactating. This shows that a relatively

higher prevalence of anemia was found among Ethiopian pregnant and lactating mothers.


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Methods



mothers based on cross-sectional secondary data of the EDHS 2005 and 2011 datasets. Both the

2005 and 2011 EDHS samples were selected using a stratified, two-stage cluster sampling

design. All women age 15-49 who were usual residents or who slept in the selected households

the night before the survey were eligible. The EDHS data include a women’s questionnaire that

measures socio-demographic characteristics of the mothers, information on reproductive health

and service use behaviours, as well as HIV and anemia test. The tool was pretested and translated

in to three local languages - Amharic, Oromifa and Tigregna. The EDHS was designed to

provide population and health indicators at national and regional levels. The survey is conducted

in every five years. The detailed methodology is found elsewhere10 11

.

Data Extraction






anemia level indicators were extracted. The chosen variables were region, residence, wealth

index, occupation, BMI, duration of breastfeeding, respondent’s education, husband’s education,

family planning use, iron tablet supplementation during pregnancy, time variation between two

surveys, marital status, age, parity and antenatal care attendance.

Measurement of variables




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smoking status10. Lactating mothers considered as anemic if hemoglobin level <12 gram per

deciliter. Haemoglobin (Hb) level of anemia was measured in g/dl, operationalised as a

categorical variable by predefined cut-off points for mild, moderate and severe anemia

recommended by the WHO for women above age 15 years. For this analysis, anemia was re-

categorized as anemic and non-anemic from prior classifications in levels (no, mild, moderate,

severe). Antenatal care (ANC) attendance referred to when women get services during

pregnancy according to the WHO recommendation of at least four ANC visits for low-risk

pregnant women. The frequency of the ANC visit is measured by asking the respondent to recall

how many times she had attended for the indexed child. Occupational status was defined as non-

working and working which comprises of professional/technical/managerial, clerical, sales and

services, skilled manual, unskilled manual and agriculture classifications. BMI (kg/m2) was

categorized using standard WHO classification into underweight <18.5 kg/m2, normal 18.5–24.9

kg/m2, overweight 25.0+. Parity, defined as the number of children ever born, was categorised as

1-4, 5-9 and 10+. The wealth index constructed from household assets and characteristics

available in both surveys to categorise individuals into wealth quintiles (poorest, poorer, middle,

rich and richest) was used. However, to make it more sensible and understandable, wealth index

was re-categorized into three groups (poor, middle and rich) to give more meaningful

interpretations and suite for recommendations.

Statistical analysis

For this study, the 2005 and 2011 EDHS data were pooled to achieve high power for detecting

the associated factors. Weighted proportions and odds ratios are presented to compromise

sampling probabilities. Sample weights were applied in order to compensate for the unequal

probability of selection between the strata that has been geographically defined as well as for

non-responses. A detailed explanation of the weighting procedure can be found in the EDHS

methodology report10. We used “svy” in STATA version 11 to weight the survey data and do the

analyses.



analysis was carried out to determine the factors associated with anemia among lactating


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analyzed in the multivariable logistic regression model12. This p-value cut off point prevented




model.

Ethical statements




Results

Majority of respondents (86%) were from rural. Nearly 60% of lactating mothers were Christian

followers followed by 38% of Muslims. The mean age of respondents was 28.4 with SD 6.8. The

overall prevalence of anemia among lactating mothers during 2005 to 2011 was found to be





48.7% [95%CI: (40.80-56.62)] found in Somali region, while the lowest prevalence was 9.0%

[95%CI: (4.07-15.47)] reported in Addis Ababa. In the period 2005 to 2011, the prevalence of

anemia in lactating mothers was consistently higher among those in the poor wealth index group,

not currently working, with BMI greater or equal to 25 kg/m2, one year duration of

breastfeeding, never educated, never used ANC, never used family planning services, no iron

tablet supplement during pregnancy, and with higher parity. A significant reduction in the



parameter.


data from both individual surveys and pooled data with the cut-off point p<0.25. The variable

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associated with lower odd of being anemic for the 2005 data was normal BMI, whereas for the

2011 data the variables were working status, wealth index, use of family planning, ANC

attendance for indexed pregnancy, husband’s education, maternal BMI and duration of

breastfeeding.

In the final multivariable model using pooled data, variables which significantly associated with

anemia for lactating mothers were working status, wealth index, use of family planning, ANC

attendance for indexed pregnancy, husband’s education, maternal BMI, time variation in the two

surveys, and durations of breastfeeding.




[AOR=0.79; 95% CI: (0.68-0.91)]. The odd of being anemic in working lactating mothers was

29% less as compared to their counter parts [AOR=0.71; 95% CI: (0.63-0.80)]. Those lactating




(0.68-0.89)]. Similarly, lactating women who are categorized in middle [AOR=0.83; 95% CI:

(0.71-0.98)] and rich wealth index [AOR=0.83; 95% CI: (0.70-0.98)] were each 17% less likely

to have anemia as compared to lactating women in poorer wealth index.









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Discussion


developing countries. For example, 66.0% of lactating mothers have been reported as having

anemia in India13 and 43.8 % of lactating mothers in Kenya had a hemoglobin level <12 g/dl

14.


with 20.3% of lactating mothers having severe anemia15. Although the prevalence of anemia


public health problem according to WHO classification16. The relatively better prevalence of


nutritional care to lactating mothers during the postpartum period. During the postpartum period,

lactating mothers are encouraged to rest for 3 to 6 months and to eat a variety of foods including

animal sources, even during religious fasting periods. Iron supplementation coverage in Ethiopia

remained low among pregnant mothers10, despite its known contribution for reducing the risk of

postpartum hemorrhage17. Postpartum hemorrhage was also found to be one of the risk factors

for anemia during the period of lactation17.

This study showed that anemia is a widespread problem in the pastoralist communities of Somali

and Afar. The prevalence of anemia in lactating mothers was higher in the pastoralist regions and

showed slow decline in these regions from 2005 to 2011. This could be due to the fact that

pastoralist communities are heavily dependent on animal milk as a source of daily food, with

poor iron bioavailability18 19

. The other reason could be due to low utilization of family planning

and antenatal care services in pastoralist areas10.



anemia among lactating mothers. This could be due to the fact that those educated husbands

might support their wives to use modern health services20 21

like family planning, ANC, postnatal

care which in turn reduce the odd of having anemia as well advised to eat a diversified diet.


contradictory to many studies from Ethiopia and abroad15 22-24

. This might be one important

motivator to involve husbands in anemia prevention efforts.

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Lactating mothers who had been working in the last 12 months preceding the survey had lower

odd of having anemia as compared to their counter parts. This might be due to working mothers

were earning money as compared to non-working mothers and the extra income enabled them to

access and purchase more food items, including animal sources (meat, poultry, fish etc), and

increase dietary diversity. Studies have shown that income growth improves diet diversity which

in turn improves micronutrient intake, including iron25 26

. Similarly, lactating mothers in the

lower wealth groups had greater odds of anemia as compared to lactating mothers in the higher

wealth index. In many other studies, anemia among reproductive age women, the wealth index

was found to be a statistically significant factor15 22

. Other studies have also shown that women

of low socio-economic status are at risk for iron deficiency anemia (IDA) in late pregnancy and

in the postpartum period27 28

. Therefore, women’s empowerment through economic interventions

and working status could have a positive contribution towards preventing anemia.





was associated with lower odd of having anemia22 29

.

Maternal nutritional status (as measured by body mass index) was found to be significantly



anemia. This finding is consistent with a study from Ethiopia and Thailand22 30

. When a mother

is at risk of deficiency for macronutrients, most likely she is also at risk of other micronutrient

deficiencies such as iron31.

ANC attendance was found to be associated with less odd of having anemia among lactating





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Those mothers who breastfed for 2 years had lower odd of having anemia as compared to

mothers who breastfed for 1 year. This could be due to the effect of breastfeeding on maternal

depletion. Because those mothers who breastfeed younger children have high burden of

breastfeeding as compared to the older one. A study by Samson and his colleagues also found

that breastfeeding increases risk of anemia significantly.

One of the strength of this study is to use laboratory confirmed anemia data at the national level.

Therefore, the study findings can be used to inform policy and program actions. However, the

study has caveats that some regions had small sample size, which questions the accuracy of

prevalence estimates per region, so that it should be interpreted in caution. The study did not

determine the presence of soil transmitted helminthes (STH) infection as it is associated with

anemia. This study also shares the limitation of cross-sectional study design which makes

difficult to demonstrate cause and effect relationships.

Conclusion



Somali and Afar. Promoting partner education, improving maternal nutritional status, creating

behavioral change to use family planning and attend ANC services at health facilities are

recommended interventions to reduce the prevalence of anemia among lactating women in

Ethiopia.

Competing interests


Funding statement





manuscript. SB assisted in data interpretation and critically reviewed the manuscript. DH drafted

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the manuscript, assisted in the data analysis and interpretation and critically reviewed the

manuscript. All authors reviewed and approved the manuscript.

Acknowledgements




References


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15.


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13. Singh AB, Kandpal SD, Chandra R, Srivastava VK, Negi KS. Anemia amongst pregnant and lactating

women in district Dehradun. Indian Journal of Preventive and Social Medicine 2009;40(1):20-21.

14. Ettyanga GA, Oloob WDvMLA, Saris WHM. Serum Retinol, Iron Status and Body Composition of

Lactating Women in Nandi, Kenya. Annals of Nutrition and Metabolism 2003;47:276-83.

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Lactating Mothers in Myanmar. The American Journal of Tropical Medicine and Hygiene

2014;doi: 10.4269/ajtmh.13-0660.


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17. WHO. Recommendations for the Prevention of Postpartum Haemorrhage (summary of results from

a WHO technical consultation, October 2006).Geneva, World Health Organization 2007.



58(4):731-34.

19. Belachew T. Human Nutrition lecture note series for Health sciences students: Jimma Univesity

2005:pp 229.

20. Kassa M, Abajobir AA, Gedefaw M. Level of male involvement and associated factors in family

planning services utilization among married men in Debremarkos town,Northwest Ethiopia.

BMC International Health and Human Rights 2014;14:33.

21. Khanal V, Lee AH, Cruz JLNBd, Karkee4 R. Factors associated with non-utilisation of health service for

childbirth in Timor-Leste: evidence from the 2009-2010 Demographic and Health Survey. BMC

International Health and Human Rights 2014;14:14.






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ONE 2013;9(3):e91252.

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Health Population Nutrition 2011;29(3):218-28.




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32. Federal Ministry of Health-Ethiopia. National guideline for control and prevention of micronutrient

deficiencies 2004.



Background

characteristics

2005 2011 2005-2011

Total

lactating

women

Prevalence of

anemia (95% CI)

Total

lactating

women

Prevalence of

anemia (95% CI)

Total

lactating

women

Prevalence of

anemia (95% CI)

Region

Tigray 142 35.4(27.69-43.33) 281 13.4(9.89-17.90) 422 20.8(17.18-24.93)

Afar 22 46.2(25.88-66.16) 38 42.4(27.27-58.10) 59 43.8(31.83-56.87)

Amhara 591 32.2(28.47-36.00) 1352 18.9(16.91-21.09) 1,943 22.9(21.12-24.86)

Oromia 826 28.5(25.45-31.60) 2041 20.1(18.39-21.87) 2,867 22.5(21.00-24.05)

Somali 60 49.2(37.50-62.50) 92 48.3(37.76-58.02) 152 48.7(40.80-56.62)

Benshangul-gumz 24 26.8(10.81-44.92) 59 20.5(11.51-32.02) 83 22.9(14.81-32.83)

SNNPR 578 26.2(22.66-29.82) 1059 13.5(11.54-15.66) 1,637 18.0(16.16-19.88)

Gambella 6 46.5(14.66-85.34) 18 23.2(7.49-45.31) 25 28.0(13.15-47.7)

Harari 3 27.1(1.67-86.80) 10 23.4(3.50-51.95) 15 20.0(5.35-45.35)

Addis Ababa 27 14.4(4.89-31.97) 83 7.3(2.98-14.43) 111 9.0(4.067-15.47)

Dire Dawa 5 33.0(7.35-81.76) 13 35.8(15.68-65.91) 18 33.3(14.77-56.9)

Residence

Urban 145 19.4(13.49-26.34) 595 12.4(9.96-15.27) 740 13.8(11.44-16.41)

Rural 2140 30.6(28.68-32.59) 4452 19.4(18.27-20.59) 6592 23.0(21.99-24.03)

Wealth index

Poor 986 32.2(29.29-35.12) 2306 21.4(19.74-23.09) 3293 24.6(23.15-26.09)

Middle 517 29.9(26.15-34.04) 1102 17.0(14.84-19.27) 1619 21.1(19.19-23.16)

Rich 782 27.0(23.96-30.18) 1639 15.6(13.86-17.37) 2420 19.3(17.76-20.91)

Current occupation

status

Not working 1568 31.8(29.55-34.16) 2325 21.0(19.37-22.68) 3893 25.4(24.06-26.29)

Working * 712 25.5(22.46-28.86) 2722 16.4(15.03-17.81) 3434 18.3(17.02-19.61)

BMI

<18.5 481 33.9(29.76-38.21) 1138 19.3(17.12-21.70) 1619 23.6(21.57-25.71)

18.5-24.99 1729 28.3(26.20-30.44) 3723 18.1(16.89-19.37) 5453 21.3(20.22-22.39)

25+ 65 42.1(30.05-53.76) 175 20.4(15.07-27.04) 240 26.3(20.98-32.09)

Duration of

breastfeeding

1 year 1072 30.7(27.98-33.50) 2461 20.6(19.04-22.23) 3533 23.7(22.31-25.11)

2 years 728 26.6(23.53-29.95) 1490 15.4(13.61-17.27) 2218 19.1(17.52-20.79)

3+ years 478 32.5(28.34-36-72) 1096 18.2(15.96-20.52) 1575 22.6(20.59-24.72)

Mother education

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None 1804 31.8(29.70-34.00) 3486 19.2(17.91-20.52) 5291 23.5(22.36-24.65)

Primary 394 24.3(20.32-28.79) 1377 18.3(16.32-20.41) 1770 19.6(17.80-21.50)

Secondary 79 17.3(10.46-27.31) 126 8.3(4.10-13.69) 205 11.8(7.83-16.67)

Higher 8 1.1(0.63-48.03) 58 9.7(4.30-20.28) 66 8.7(3.77-17.95)

Husband education

None 1333 33.9(31.40-36.48) 2531 20.3(18.77-21.91) 3864 25.0(23.65-26.38)

Primary 701 26.2(23.09-29.60) 2048 17.2(15.60-18.87) 2749 19.5(18.05-21.01)

Secondary 199 20.7(15.41-26.64) 238 14.3(10.26-19.17) 437 17.2(13.84-20.92)

Higher 23 14.8(3.43-31.53) 147 13.7(8.75-19.88) 170 13.8(8.99-19.30)

Family planning

Never use 1775 32.1(29.97-34.31) 2889 21.2(19.72-22.70) 4663 25.4(24.16-26.66)

Ever use 15 16.4(2.30-37.52) 2158 14.9(13.46-16.47) 2173 14.9(13.46.16.45)

ANC use

Never 1636 32.0(29.80-34.32) 2977 20.4(18.97-21-87) 4613 24.5(23.27-25.75)

1-3 386 27.7(23.43-32.35) 1208 18.4(16.27-20.64) 1594 20.6(18.65-22.62)

4+ 260 18.9(14.44-23.95) 845 12.6(10.44-14.91) 1105 14.1(12.16-16.27)

Iron supplementation

during pregnancy

No 2046 30.1(28.15-32.12) 4196 18.8(17.64-20.01) 6242 22.5(21.47-23.54)

Yes 236 27.1(21.74-33.06) 840 16.9(14.48-19.55) 1076 19.2(16.97-21.68)

Parity

1-4 1293 28.9(26.50-31.44) 3111 18.1(16.77-19.48) 4404 21.3(20.11-22.53)

5-9 903 30.5(27.52-33.52) 1739 19.6(17.79-21.53) 2642 23.3(21.73-24.96)

10+ 89 37.1(27.53-47.46) 197 17.0(12.02-12.46) 287 23.2(18.72-28.50)

Total 2285 29.9(28.04-31.79) 5047 18.5(17.45-19.60) 7332 22.1(21.13-23.03)

Table 2: Logistic regression showing the association between independent variables and

anemia among lactating mothers in Ethiopia using pooled data from the EDHS 2005 and 2011

Variables 2005 2011 2005-2011


Occupation

Not working 1.00 1.00 1.00 1.00 1.00 1.00

Working 0.82(0.66-1.00) 0.83(0.64-1.06) 0.62(0.54- 0.71) 0.68(0.58-0.78) 0.64(0.57-0.72) 0.71(0.63-0.80)

Wealth index

Poor 1.00 1.00 1.00 1.00 1.00 1.00

Middle 0.71(0.54-0.92) 0.82(0.61-1.10) 0.74(0.61- 0.89) 0.85(0.69-1.04) 0.74(0.64-0.87) 0.83(0.71-0.98)

Rich 0.66(0.53-0.82) 0.91(0.68-1.22) 0.62(0.52-0.72) 0.80(0.65-0.97) 0.65(0.57-0.73) 0.83(0.70-0.98)

FP use

Never used 1.00 1.00 1.00 1.00 1.00 1.00

Ever used 0.37(0.11-1.28) 0.51(0.14-1.91) 0.54(0.46-0.63) 0.69(0.58-0.82) 0.48(0.41-0.55) 0.68(0.57-0.80)

ANC attended

Never 1.00 1.00 1.00 1.00 1.00 1.00

1-3 0.78(0.59-1.03) 0.94(0.66-1.33) 0.78(0.59-1.00) 1.00(0.83-1.2) 0.81(0.71-0.94) 0.99(0.84-1.16)

4+ 0.55(0.41-0.74) 0.82(0.53-1.28) 0.55(0.41-0.74) 0.71(0.55-0.92) 0.52(0.44-0.61) 0.73(0.59-0.91)

Husband

education

None 1.00 1.00 1.00 1.00 1.00 1.00

Primary 0.77(0.61-0.96) 0.77(0.58-1.01) 0.69(0.59-0.80) 0.80(0.67-0.94) 0.69(0.61-0.78) 0.79(0.68-0.91)

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Secondary 0.55(0.39-0.77) 0.83(0.50-1.38) 0.64(0.48-0.87) 0.81(0.58-1.14) 0.62(0.49-0.77) 0.83(0.62-1.09)

Higher 0.58(0.26-1.30) 0.50(0.73-3.40) 0.72(0.49-1.0) 0.96(0.61-1.52) 0.64(0.46-0.90) 0.94(0.61-1.45)

BMI

<18.5 1.00 1.00 1.00 1.00 1.00 1.00

18.5-24.99 0.74(0.59-0.92) 0.76(0.59-0.99) 0.74(0.64-0.86) 0.79(0.68-0.93) 0.76(0.67-0.86) 0.78(0.68-0.89)

25+ 1.1(0.62-1.90) 1.66(0.79-3.48) 0.82(0.58-1.2) 1.12(0.77-1.62) 0.85(0.64-1.12) 1.21(0.87-1.68)

Duration of

breastfeeding

1 year 1.00 1.00 1.00 1.00 1.00 1.00

2 years 0.79(0.64-0.99) 0.79(0.62-1.03) 0.71(0.60-0.83) 0.75(0.63-0.88) 0.75(0.66-0.85) 0.76(0.66-0.87)

3+ years 0.99(0.77-1.27) 1.10(0.82-1.49) 0.71(0.59-0.86) 0.82(0.67-0.99) 0.81(0.70-0.94) 0.89(0.76-1.05)

Time laps

2005 1.00 1.00

2011 0.65(0.58-0.73) 0.73(0.64-0.85) COR: Crude Odds Ratio, AOR: Adjusted Odds Ratio, 1.00 is the reference category

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2, Demewoz Haile

3*

1 Ethiopian Ppublic Hhealth Aassociation, Addis Ababa, Ethiopia

2 Independent Ppublic Hhealth Cconsultants, Addis Ababa, Ethiopia



Email address









Bale Goba , P.O.Box 302



Word count: 2388

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Abstract








gram per deciliter.



Somali region, followed by 43.8% [95% CI: (31.83-56.87)] in Afar region. The multivariable

statistical model showed that lactating mothers who had husbands attended primary education

[AOR=0.79; 95% CI: (0.68-0.91)], had been working in the last 12 months preceding the survey

[AOR=0.71; 95% CI: (0.63-0.80)],who were currently working [AOR=0.71; 95% CI: (0.63-

0.80)], had normal maternal body mass index (BMI) from 18.5kg/m2 to 24.99kg/m

2 [AOR=0.78;

95% CI: (0.68-0.89)], middle wealth quintile index [AOR=0.83; 95% CI: (0.71-0.98)] and rich

wealth quintile index [AOR=0.83; 95% CI: (0.70-0.98)], ever use of family planning

[AOR=0.68; 95% CI: (0.57-0.80)], attending antenatal care (ANC) for indexed pregnancy four

times or more [AOR=0.73; 95% CI: (0.59-0.91)], experienced time variation between two

surveys [AOR=0.73; 95%CI: (0.64-0.85)] and who breastfed for two years [AOR=0.76; 95% CI:

(0.66-0.87)] were associated with lower odd of being anemic.





Ethiopia.

Formatted: Font: Font color: Auto

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ARTICLE SUMMARY

Article focus






Key messages

• Anemia prevalence is a public health problem among lactating mothers in Ethiopia, with

the highest prevalence found in pastoralist regions of Somali and Afar

• A statistically significant reduction of anemia prevalence amongin lactating mothers was





of anemia.






interpreted in caution. This study also shares the limitation of cross-sectional design which

makes difficult to demonstrate cause and effect relationships.

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Introduction


major challenge for human health, social and economic development1. Lactating mothers are one

amongof the vulnerable groups of anemia. During the period of lactation, mothers are

susceptible to anemia due to maternal iron depletion and blood loss during child birth2. Studies

have shown that though breast milk is not a good source of iron, the concentration of iron in

breast milk is independent of maternal iron status. This showed that the quality of breast milk is

maintained at the expense of maternal stores2 3.













ratio was 676 maternal deaths per 100,000 live births10

. for the seven-year period preceding the

2011 EDHS survey. This rate which is one of the highest in the world. The country has

considerably high infant and under 5 mortality rates that account for 59 and 88 deaths per 1000

live births, respectively The infant mortality rate was 59 per 1,000 live births and the under-five

mortality rate was 88 per 1,000 live births10

.


Surveys (EDHS)10 11. The prevalence of anemia in lactating mothers was 29.9% in 2005 and

18.5% in 201110. It was 30.6% in 2005 and 22% in 2011 among pregnant women and it was



mothers.

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(EDHS). The prevalence of anemia amongin lactating mothers was 29.9% in 2005 and 18.5% in

201110

,11

. The prevalence of anemia in lactating mothers was 29.9% in 2005 and 18.5% in 2011

1012. It was 30.6% in 2005 and 22% in 2011 among pregnant women and 23.9% in 2005 and 15%

in 2011 among women neither non-pregnant nor lactating. This shows that a relatively higher

prevalence of anemia was found among Ethiopian pregnant and lactating mothers. However,

little information is available regarding socio-economic factors associated with anemia among

lactating mothers. This study aimed to identify factors associated with anemia among lactating

mothers in Ethiopia using the pooled data of EDHS 2005 and 2011.

Methods









in to three local languages - Amharic, Oromeifa and Tigregna. The EDHS was designed to

provide population and health indicators at national and regional levels. The survey It is

conducted in every five years. Both the 2005 and 2011 EDHS samples were selected using a

stratified, two-stage cluster sampling design. The detailed methodology is found elsewhere10 11

.

Data Extraction






anemia level indicators were extracted. The chosen variables were region, residence, wealth

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index, occupation, BMI, duration of breastfeeding, respondent’s education, husband’s education,

family planning use, iron tablet supplementation during pregnancy, time variation between two

surveys, marital status, age, parity and antenatal care attendance.





smoking status10

. All the necessary quality control measures were considered9. Height and

weight measurements were carried out for the respondents. Weight measurements were obtained

using lightweight, SECA mother-infant scales with a digital screen, designed and manufactured.

under the guidance of UNICEF. Height measurements were carried out using a measuring board.

Lactating mothers considered as anemic if hemoglobin level <12 gram per deciliter.

Haemoglobin (Hb) level of anemia was measured in g/dl, operationalised as a categorical

variable by predefined cut-off points for mild, moderate and severe anemia recommended by the

WHO for women above age 15 years. For this analysis, anemia was re-categorized as anemic

and non-anemic from prior classifications in levels (no, mild, moderate, severe). Antenatal care

(ANC) attendance referreds to when women get services during pregnancy according to the

WHO recommendation of at least four ANC visits for low-risk pregnant women. The frequency

of the ANC visit is measured by asking the respondent to recall how many times she had

attended for the indexed child. Occupational status wasis defined as non-working and working

which comprises of professional/technical/managerial, clerical, sales and services, skilled

manual, unskilled manual and agriculture classifications. BMI (kg/m2) was categorised using

standard WHO classification into underweight <18.5 kg/m2, normal 18.5–24.9 kg/m2,

overweight 25.0+. Parity, defined as the number of children ever born, was categorised as 1-4, 5-

9 and 10+. The wealth index constructed from household assets and characteristics available in

both surveys to categorize individuals into wealth quintiles (poorest, poorer, middle, rich,

richest) was used. However, to make it more sensible and understandable, wealth index was re-

categorized into three groups (poor, middle and rich) to give more meaningful interpretations and

suite for recommendations.

Formatted: Underline, Font color: Red

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Data processing and sStatistical analysis


and editing was performed using CSPro software. For this study, the 2005 and 2011 EDHS data

were pooled to achieve high power for detecting the associated factors and analyzed using

STATA 11 software. Weighted proportions and odds ratios are presented to compromise




methodology report10

. We used “svy” in STATA version 11 to weight the survey data and do the

analyses. Anemia was re-categorized as anemic and non-anemic from prior classifications in

levels (no, mild, moderate, severe). The background variables were selected based on literature

review and data availability from the two rounds of EDHS. The chosen variables were region,

residence, wealth index, occupation, BMI, duration of breastfeeding, respondent’s education,

husband’s education, family planning use, iron tablet supplementation during pregnancy, time

variation between two surveys, marital status, age, parity and antenatal care attendance.





analyzed in the multivariable logistic regression model12

. This p-value cut off point prevented




model.

Ethical statements




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Results
















parameter.


data from both individual surveys and pooled data with the cut-off point of p<0.25. The variable

associated with lower odd of being anemic for the 2005 data was normal BMI, whereas for the

2011 data the variables were working status, wealth index, use of family planning, ANC

attendance for indexed pregnancy, husband’s education, maternal BMI and duration of

breastfeeding.

The variable associated with anemia for the 2005 data was BMI, whereas for the 2011 data the

variables were working status, wealth index, ever use of family planning, ANC attendance four

times and above for indexed pregnancy, husband’s education, maternal BMI and duration of

breastfeeding.

In the final multivariable model using pooled data, variables which significantly associated with

anemia for lactating mothers were working status, wealth index, use of family planning, ANC

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attendance for indexed pregnancy, husband’s education, maternal BMI, time variation in the two

surveys, and durations of breastfeeding.




BMI, time variation in the two surveys, and durations of breastfeeding remained.




[AOR=0.79; 95% CI: (0.68-0.91)]. The odd of being anemic in working lactating mothers was


mothers having a normal maternal BMI (18.5kg/m2-24.99kg/m2) were 22% less likely to be



(0.71-0.98)] and rich wealth quintiles index [AOR=0.83; 95% CI: (0.70-0.98)] were each 17%

less likely to have anemia as compared to lactating women in poorer wealth quintilesindex.









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Discussion


developing countries. For example, more than 66.090% of lactating mothers have been reported

as having anemia in India13 14 and 43.8 29.6% of lactating mothers in Zimbabwe Kenya had a

hemoglobin level <12 g/dl14

developed anemia15

. Another study from Myanmar reported an

anemia prevalence rate of 60.3% in lactating women, with 20.3% of lactating mothers having

severe anemia15

. Although the prevalence of anemia among lactating mothers in Ethiopia was

relatively low as compared to these studies, it remains a public health problem according to

WHO classification16. The relatively better prevalence of anemia in Ethiopia among lactating

mothers may be due to the cultural norms of providing nutritional care to lactating mothers

during the postpartum period. During the postpartum period, lactating mothers are encouraged to

rest for 3 to 6 months and to eat a variety of foods including animal sources, even during

religious fasting periods. Iron supplementation coverage in Ethiopia remained low among

pregnant mothers10

, despite its known contribution for reducing the risk of postpartum

hemorrhage17

10

. Postpartum hemorrhage was also found to be one of the risk factors for anemia

during the period of lactation17

.











might support their wives to use modern health services20 21 like family planning, ANC, postnatal







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Lactating mothers who had been working in the last 12 months preceding the surveyWorking

lactating mothers had lower odd of having anemia as compared to their counter parts. This might

be due to working mothers were earning money as compared to non-working mothers and the

extra income enabled them to access and purchase more food items, including animal sources

(meat, poultry, fish etc), and increase dietary diversity. Studies have shown that income growth

improves diet diversity which in turn improves micronutrient intake, including iron25 26

.

Similarly, lactating mothers in the lower wealth groups had greater odds of anemia as compared

to lactating mothers in the higher wealth quintilesindex. In many other studies, anemia among

reproductive age women, the wealth index was found to be a statistically significant factor15 22.

Other studies have also shown that women of low socio-economic status are at risk for iron

deficiency anemia (IDA) in late pregnancy and in the postpartum period27 28

. Therefore, women’s

empowerment through economic interventions and working status could have a positive

contribution towards preventing anemia.





was associated with lower odd of having anemia22 29.




anemia. This finding is similar consistent with a study from Ethiopia and Thailand22 30

. When a

mother is at risk of deficiency for macronutrients, most likely she is also at risk of other

micronutrient deficiencies such as iron31

.




instructed to consume different sources of iron rich food items32

. Therefore, improving iron


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that breastfeeding increases risk of anemia significantly22

.

One of the strength of this study is that it has to use large sample size with laboratory confirmed

anemia data at the national level. Therefore, the study findings can be used to inform policy and

program actions. However, the study has caveats that some regions had small sample size, which

questions the accuracy of prevalence estimates per region, so that it should be interpreted in

caution. The study did not determine the presence of soil transmitted helminthes (STH) infection

as it is associated with anemia. This study also shares the limitation of cross-sectional study

design which makes difficult to see demonstratethe cause and effect relationships.

Conclusion






Ethiopia.

Competing interests


Funding statement





manuscript. SB assisted in data interpretation and critically reviewed the manuscript. DH drafted

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the manuscript, assisted in the data analysis and interpretation and critically reviewed the

manuscript. All authors reviewed and approved the manuscript.

Acknowledgements




References


Organization. 2002.





15.



2001;185:4348-53.





2005;135:267–72.













2004;57:1138-46.





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2014;doi: 10.4269/ajtmh.13-0660.







58(4):731-34.


2005:pp 229.

20. Khanal V, Lee AH, Cruz JLNBd, Karkee R. Factors associated with non-utilisation of health service for

childbirth in Timor-Leste: evidence from the 2009-2010 Demographic and Health Survey. BMC

International Health and Human Rights 2014;14:14.

21. Kassa M, Abajobir AA, Gedefaw M. Level of male involvement and associated factors in family

planning services utilization among married men in Debremarkos town,Northwest Ethiopia.

BMC International Health and Human Rights 2014;14:33.







2011;1(11):304-09.






February 2014








ONE 2013;9(3):e91252.








Nutrients 2012;4(12):1958-76.

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deficiencies 2004.

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Background

characteristics

2005 2011 2005-2011

Total

lactating women

Prevalence of

anemia (95% CI)

Total

lactating women

Prevalence of

anemia (95% CI)

Total

lactating women

Prevalence of

anemia (95% CI)

Region

Tigray 142 35.4(27.69-43.33) 281 13.4(9.89-17.90) 422 20.8(17.18-24.93)

Afar 22 46.2(25.88-66.16) 38 42.4(27.27-58.10) 59 43.8(31.83-56.87)

Amhara 591 32.2(28.47-36.00) 1352 18.9(16.91-21.09) 1,943 22.9(21.12-24.86)

Oromia 826 28.5(25.45-31.60) 2041 20.1(18.39-21.87) 2,867 22.5(21.00-24.05)

Somali 60 49.2(37.50-62.50) 92 48.3(37.76-58.02) 152 48.7(40.80-56.62)

Benshangul-gumz 24 26.8(10.81-44.92) 59 20.5(11.51-32.02) 83 22.9(14.81-32.83)

SNNPR 578 26.2(22.66-29.82) 1059 13.5(11.54-15.66) 1,637 18.0(16.16-19.88)

Gambella 6 46.5(14.66-85.34) 18 23.2(7.49-45.31) 25 28.0(13.15-47.7)

Harari 3 27.1(1.67-86.80) 10 23.4(3.50-51.95) 15 20.0(5.35-45.35)

Addis Ababa 27 14.4(4.89-31.97) 83 7.3(2.98-14.43) 111 9.0(4.067-15.47)

Dire Dawa 5 33.0(7.35-81.76) 13 35.8(15.68-65.91) 18 33.3(14.77-56.9)

Residence

Urban 145 19.4(13.49-26.34) 595 12.4(9.96-15.27) 740 13.8(11.44-16.41)

Rural 2140 30.6(28.68-32.59) 4452 19.4(18.27-20.59) 6592 23.0(21.99-24.03)

Wealth index

Poor 986 32.2(29.29-35.12) 2306 21.4(19.74-23.09) 3293 24.6(23.15-26.09)

Middle 517 29.9(26.15-34.04) 1102 17.0(14.84-19.27) 1619 21.1(19.19-23.16)

Rich 782 27.0(23.96-30.18) 1639 15.6(13.86-17.37) 2420 19.3(17.76-20.91)

Current occupation

status

Not working 1568 31.8(29.55-34.16) 2325 21.0(19.37-22.68) 3893 25.4(24.06-26.29)

Working * 712 25.5(22.46-28.86) 2722 16.4(15.03-17.81) 3434 18.3(17.02-19.61)

BMI

<18.5 481 33.9(29.76-38.21) 1138 19.3(17.12-21.70) 1619 23.6(21.57-25.71)

18.5-24.99 1729 28.3(26.20-30.44) 3723 18.1(16.89-19.37) 5453 21.3(20.22-22.39)

25+ 65 42.1(30.05-53.76) 175 20.4(15.07-27.04) 240 26.3(20.98-32.09)

Duration of

breastfeeding

1 year 1072 30.7(27.98-33.50) 2461 20.6(19.04-22.23) 3533 23.7(22.31-25.11)

2 years 728 26.6(23.53-29.95) 1490 15.4(13.61-17.27) 2218 19.1(17.52-20.79)

3+ years 478 32.5(28.34-36-72) 1096 18.2(15.96-20.52) 1575 22.6(20.59-24.72)

Mother education

None 1804 31.8(29.70-34.00) 3486 19.2(17.91-20.52) 5291 23.5(22.36-24.65)

Primary 394 24.3(20.32-28.79) 1377 18.3(16.32-20.41) 1770 19.6(17.80-21.50)

Secondary 79 17.3(10.46-27.31) 126 8.3(4.10-13.69) 205 11.8(7.83-16.67)

Higher 8 1.1(0.63-48.03) 58 9.7(4.30-20.28) 66 8.7(3.77-17.95)

Husband education

None 1333 33.9(31.40-36.48) 2531 20.3(18.77-21.91) 3864 25.0(23.65-26.38)

Primary 701 26.2(23.09-29.60) 2048 17.2(15.60-18.87) 2749 19.5(18.05-21.01)

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Secondary 199 20.7(15.41-26.64) 238 14.3(10.26-19.17) 437 17.2(13.84-20.92)

Higher 23 14.8(3.43-31.53) 147 13.7(8.75-19.88) 170 13.8(8.99-19.30)

Family planning

Never use 1775 32.1(29.97-34.31) 2889 21.2(19.72-22.70) 4663 25.4(24.16-26.66)

Ever use 15 16.4(2.30-37.52) 2158 14.9(13.46-16.47) 2173 14.9(13.46.16.45)

ANC use

Never 1636 32.0(29.80-34.32) 2977 20.4(18.97-21-87) 4613 24.5(23.27-25.75)

1-3 386 27.7(23.43-32.35) 1208 18.4(16.27-20.64) 1594 20.6(18.65-22.62)

4+ 260 18.9(14.44-23.95) 845 12.6(10.44-14.91) 1105 14.1(12.16-16.27)


during pregnancy

No 2046 30.1(28.15-32.12) 4196 18.8(17.64-20.01) 6242 22.5(21.47-23.54)

Yes 236 27.1(21.74-33.06) 840 16.9(14.48-19.55) 1076 19.2(16.97-21.68)

Parity

1-4 1293 28.9(26.50-31.44) 3111 18.1(16.77-19.48) 4404 21.3(20.11-22.53)

5-9 903 30.5(27.52-33.52) 1739 19.6(17.79-21.53) 2642 23.3(21.73-24.96)

10+ 89 37.1(27.53-47.46) 197 17.0(12.02-12.46) 287 23.2(18.72-28.50)


who do not currently engage in any type of formal work to earn money.*working includes

professional/technical/managerial, Clerical, Sales and Services, Skilled manual, Unskilled manual and Agriculture.


data from the EDHS 2005 and 2011 Table 2: Logistic regression showing the association

between independent variables and anemia among lactating mothers in Ethiopia using pooled


Variables 2005 2011 2005-2011


Occupation

Not working* 1.00 1.00 1.00 1.00 1.00 1.00

Working*≠

0.82(0.66-1.00) 0.83(0.64-1.06) 0.62(0.54- 0.71) 0.68(0.58-0.78) 0.64(0.57-0.72) 0.71(0.63-0.80)

Wealth index

Poor 1.00 1.00 1.00 1.00 1.00 1.00

Middle 0.71(0.54-0.92) 0.82(0.61-1.10) 0.74(0.61- 0.89) 0.85(0.69-1.04) 0.74(0.64-0.87) 0.83(0.71-0.98)

Rich 0.66(0.53-0.82) 0.91(0.68-1.22) 0.62(0.52-0.72) 0.80(0.65-0.97) 0.65(0.57-0.73) 0.83(0.70-0.98)

FP use

Never used 1.00 1.00 1.00 1.00 1.00 1.00

Ever used 0.37(0.11-1.28) 0.51(0.14-1.91) 0.54(0.46-0.63) 0.69(0.58-0.82) 0.48(0.41-0.55) 0.68(0.57-0.80)

ANC attended

Never 1.00 1.00 1.00 1.00 1.00 1.00

1-3 0.78(0.59-1.03) 0.94(0.66-1.33) 0.78(0.59-1.00) 1.00(0.83-1.2) 0.81(0.71-0.94) 0.99(0.84-1.16)

4+ 0.55(0.41-0.74) 0.82(0.53-1.28) 0.55(0.41-0.74) 0.71(0.55-0.92) 0.52(0.44-0.61) 0.73(0.59-0.91)

Husband

education

None 1.00 1.00 1.00 1.00 1.00 1.00

Primary 0.77(0.61-0.96) 0.77(0.58-1.01) 0.69(0.59-0.80) 0.80(0.67-0.94) 0.69(0.61-0.78) 0.79(0.68-0.91)

Secondary 0.55(0.39-0.77) 0.83(0.50-1.38) 0.64(0.48-0.87) 0.81(0.58-1.14) 0.62(0.49-0.77) 0.83(0.62-1.09)

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Higher 0.58(0.26-1.30) 0.50(0.73-3.40) 0.72(0.49-1.0) 0.96(0.61-1.52) 0.64(0.46-0.90) 0.94(0.61-1.45)

BMI

<18.5 1.00 1.00 1.00 1.00 1.00 1.00

18.5-24.99 0.74(0.59-0.92) 0.76(0.59-0.99) 0.74(0.64-0.86) 0.79(0.68-0.93) 0.76(0.67-0.86) 0.78(0.68-0.89)

25+ 1.1(0.62-1.90) 1.66(0.79-3.48) 0.82(0.58-1.2) 1.12(0.77-1.62) 0.85(0.64-1.12) 1.21(0.87-1.68)

Duration of

breastfeeding

1 year 1.00 1.00 1.00 1.00 1.00 1.00

2 years 0.79(0.64-0.99) 0.79(0.62-1.03) 0.71(0.60-0.83) 0.75(0.63-0.88) 0.75(0.66-0.85) 0.76(0.66-0.87)

3+ years 0.99(0.77-1.27) 1.10(0.82-1.49) 0.71(0.59-0.86) 0.82(0.67-0.99) 0.81(0.70-0.94) 0.89(0.76-1.05)

Time laps

2005 1.00 1.00



in any type of formal work to earn money.* *working includes professional/technical/managerial, Clerical, Sales

and Services, Skilled manual, Unskilled manual and Agriculture.

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215x279mm (300 x 300 DPI)

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Journal: BMJ Open



Date Submitted by the Author: 20-Jan-2015

Complete List of Authors: Tarekegn, Yihunie; Ethiopian Public Helth Association, Project management Biadgilign, Sibhatu; Independent public health consultants, Addis Ababa, Ethiopia,



Public health




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2, Demewoz Haile

3*





Email address












Word count: 2388

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Abstract








gram per deciliter.







2

[AOR=0.78; 95% CI: (0.68-0.89)], middle wealth quintile [AOR=0.83; 95% CI: (0.71-0.98)] and

rich wealth quintile [AOR=0.83; 95% CI: (0.70-0.98)], ever use of family planning [AOR=0.68;




factors associated with anemia.





Ethiopia.

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ARTICLE SUMMARY

Article focus






Key messages








of anemia.








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Introduction





















which is one of the highest in the world.









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Methods









in to three local languages - Amharic, Oromefa and Tigregna. The EDHS was designed to



.

Data Extraction


website in SPSS format. After reviewing the detailed data coding, further data recoding was

completed. A total of 7,332 lactating mothers (2,285 from EDHS 2005 and 5,047 from EDHS

2011) were included in the analysis. Based on published literature, information on a wide-range

of socio-demographic and economic variables, health service related factors and anemia level

indicators were extracted. The chosen variables were region, residence, wealth index, occupation,

BMI, duration of breastfeeding, respondent’s education, husband’s education, family planning

use, iron tablet supplementation during pregnancy, time variation between two surveys, marital

status, age, parity and antenatal care attendance.





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recommended by the WHO for women above age 15 years. For this analysis, anemia was we re-

categorized anemia level as anemic and non-anemic from prior classifications in levels (no, mild,

moderate, severe) due to very small number of cases in the categories of severe and mild anemia

in all datasets of pooled and individual surveys.

Antenatal care (ANC) attendance referred to when women get services during pregnancy

according to the WHO recommendation of at least four ANC visits for low-risk pregnant

women. The frequency of the ANC visit is measured by asking the respondent to recall how

many times she had attended for the indexed child. Occupational status was defined as non-



categorised using standard WHO classification into underweight <18.5 kg/m2, normal 18.5–24.9

kg/m2, overweight 25.0 kg/m

2 and above. Parity, defined as the number of children ever born,

was categorised as 1-4, 5-9 and 10+. The wealth index constructed from household assets and

characteristics available in both surveys to categorise individuals into wealth quintiles (poorest,

poorer, middle, rich and richest) was used. For the present analysis, the wealth index was re-

categorizedcollapsed into three groups (poor, middle and rich) to give a meaningful and practical

sub-population categories for designing program interventions in the general community.








analyses.



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model.

Ethical statements




Results
















parameter.

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BMI, time variation in the two surveys, and durations of breastfeeding.




















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Discussion



anemia in India13 and 43.8 % of lactating mothers in Kenya had a hemoglobin level <12 g/dl14.










postpartum hemorrhage17 Postpartum hemorrhage was also found to be one of the risk factors for

anemia during the period of lactation17.











might support their wives to use modern health services like family planning, ANC, postnatal






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wealth quintiles. In many other studies, anemia among reproductive age women, the wealth

index was found to be a statistically significant factor15 20. Other studies have also shown that

women of low socio-economic status are at risk for iron deficiency anemia (IDA) in late

pregnancy and in the postpartum period25 26

. Therefore, women’s empowerment through

economic interventions and working status could have a positive contribution towards preventing

anemia.










. When a mother








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that breastfeeding increases risk of anemia significantly20.








Conclusion






Ethiopia.

Competing interests


Funding statement




YL and DH conceptualized the research idea. YL analyzed and interpreted the data and critically

reviewed the manuscript. SB assisted in data interpretation and critically reviewed the

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manuscript. DH drafted the manuscript, assisted in the data analysis and interpretation and

critically reviewed the manuscript. All authors reviewed and approved the manuscript.

Acknowledgements




References


Organization. 2002.





15.



2001;185:4348-53.





2005;135:267–72.













2004;57:1138-46.





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2014;doi: 10.4269/ajtmh.13-0660.







58(4):731-34.


2005:pp 229.







2011;1(11):304-09.






February 2014








ONE 2013;9(3):e91252.








Nutrients 2012;4(12):1958-76.


deficiencies 2004.

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Background

characteristics

2005 2011 2005-2011

Total

lactating women

Prevalence of

anemia (95% CI)

Total

lactating women

Prevalence of

anemia (95% CI)

Total

lactating women

Prevalence of

anemia (95% CI)

Region

Tigray 142 35.4(27.69-43.33) 281 13.4(9.89-17.90) 422 20.8(17.18-24.93)

Afar 22 46.2(25.88-66.16) 38 42.4(27.27-58.10) 59 43.8(31.83-56.87)

Amhara 591 32.2(28.47-36.00) 1352 18.9(16.91-21.09) 1,943 22.9(21.12-24.86)

Oromia 826 28.5(25.45-31.60) 2041 20.1(18.39-21.87) 2,867 22.5(21.00-24.05)

Somali 60 49.2(37.50-62.50) 92 48.3(37.76-58.02) 152 48.7(40.80-56.62)

Benshangul-gumz 24 26.8(10.81-44.92) 59 20.5(11.51-32.02) 83 22.9(14.81-32.83)

SNNPR 578 26.2(22.66-29.82) 1059 13.5(11.54-15.66) 1,637 18.0(16.16-19.88)

Gambella 6 46.5(14.66-85.34) 18 23.2(7.49-45.31) 25 28.0(13.15-47.7)

Harari 3 27.1(1.67-86.80) 10 23.4(3.50-51.95) 15 20.0(5.35-45.35)

Addis Ababa 27 14.4(4.89-31.97) 83 7.3(2.98-14.43) 111 9.0(4.067-15.47)

Dire Dawa 5 33.0(7.35-81.76) 13 35.8(15.68-65.91) 18 33.3(14.77-56.9)

Residence

Urban 145 19.4(13.49-26.34) 595 12.4(9.96-15.27) 740 13.8(11.44-16.41)

Rural 2140 30.6(28.68-32.59) 4452 19.4(18.27-20.59) 6592 23.0(21.99-24.03)

Wealth index

Poor 986 32.2(29.29-35.12) 2306 21.4(19.74-23.09) 3293 24.6(23.15-26.09)

Middle 517 29.9(26.15-34.04) 1102 17.0(14.84-19.27) 1619 21.1(19.19-23.16)

Rich 782 27.0(23.96-30.18) 1639 15.6(13.86-17.37) 2420 19.3(17.76-20.91)

Current occupation

status

Not working 1568 31.8(29.55-34.16) 2325 21.0(19.37-22.68) 3893 25.4(24.06-26.29)

Working * 712 25.5(22.46-28.86) 2722 16.4(15.03-17.81) 3434 18.3(17.02-19.61)

BMI

<18.5 481 33.9(29.76-38.21) 1138 19.3(17.12-21.70) 1619 23.6(21.57-25.71)

18.5-24.99 1729 28.3(26.20-30.44) 3723 18.1(16.89-19.37) 5453 21.3(20.22-22.39)

25+ 65 42.1(30.05-53.76) 175 20.4(15.07-27.04) 240 26.3(20.98-32.09)

Duration of

breastfeeding

1 year 1072 30.7(27.98-33.50) 2461 20.6(19.04-22.23) 3533 23.7(22.31-25.11)

2 years 728 26.6(23.53-29.95) 1490 15.4(13.61-17.27) 2218 19.1(17.52-20.79)

3+ years 478 32.5(28.34-36-72) 1096 18.2(15.96-20.52) 1575 22.6(20.59-24.72)

Mother education

None 1804 31.8(29.70-34.00) 3486 19.2(17.91-20.52) 5291 23.5(22.36-24.65)

Primary 394 24.3(20.32-28.79) 1377 18.3(16.32-20.41) 1770 19.6(17.80-21.50)

Secondary 79 17.3(10.46-27.31) 126 8.3(4.10-13.69) 205 11.8(7.83-16.67)

Higher 8 1.1(0.63-48.03) 58 9.7(4.30-20.28) 66 8.7(3.77-17.95)

Husband education

None 1333 33.9(31.40-36.48) 2531 20.3(18.77-21.91) 3864 25.0(23.65-26.38)

Primary 701 26.2(23.09-29.60) 2048 17.2(15.60-18.87) 2749 19.5(18.05-21.01)

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Secondary 199 20.7(15.41-26.64) 238 14.3(10.26-19.17) 437 17.2(13.84-20.92)

Higher 23 14.8(3.43-31.53) 147 13.7(8.75-19.88) 170 13.8(8.99-19.30)

Family planning

Never use 1775 32.1(29.97-34.31) 2889 21.2(19.72-22.70) 4663 25.4(24.16-26.66)

Ever use 15 16.4(2.30-37.52) 2158 14.9(13.46-16.47) 2173 14.9(13.46.16.45)

ANC use

Never 1636 32.0(29.80-34.32) 2977 20.4(18.97-21-87) 4613 24.5(23.27-25.75)

1-3 386 27.7(23.43-32.35) 1208 18.4(16.27-20.64) 1594 20.6(18.65-22.62)

4+ 260 18.9(14.44-23.95) 845 12.6(10.44-14.91) 1105 14.1(12.16-16.27)


during pregnancy

No 2046 30.1(28.15-32.12) 4196 18.8(17.64-20.01) 6242 22.5(21.47-23.54)

Yes 236 27.1(21.74-33.06) 840 16.9(14.48-19.55) 1076 19.2(16.97-21.68)

Parity

1-4 1293 28.9(26.50-31.44) 3111 18.1(16.77-19.48) 4404 21.3(20.11-22.53)

5-9 903 30.5(27.52-33.52) 1739 19.6(17.79-21.53) 2642 23.3(21.73-24.96)

10+ 89 37.1(27.53-47.46) 197 17.0(12.02-12.46) 287 23.2(18.72-28.50)

Total 2285 29.9(28.04-31.79) 5047 18.5(17.45-19.60) 7332 22.1(21.13-23.03)




Occupation

Not working 1.00 1.00 1.00 1.00 1.00 1.00

Working 0.82(0.66-1.00) 0.83(0.64-1.06) 0.62(0.54- 0.71) 0.68(0.58-0.78) 0.64(0.57-0.72) 0.71(0.63-0.80)

Wealth index

Poor 1.00 1.00 1.00 1.00 1.00 1.00

Middle 0.71(0.54-0.92) 0.82(0.61-1.10) 0.74(0.61- 0.89) 0.85(0.69-1.04) 0.74(0.64-0.87) 0.83(0.71-0.98)

Rich 0.66(0.53-0.82) 0.91(0.68-1.22) 0.62(0.52-0.72) 0.80(0.65-0.97) 0.65(0.57-0.73) 0.83(0.70-0.98)

FP use

Never used 1.00 1.00 1.00 1.00 1.00 1.00

Ever used 0.37(0.11-1.28) 0.51(0.14-1.91) 0.54(0.46-0.63) 0.69(0.58-0.82) 0.48(0.41-0.55) 0.68(0.57-0.80)

ANC attended

Never 1.00 1.00 1.00 1.00 1.00 1.00

1-3 0.78(0.59-1.03) 0.94(0.66-1.33) 0.78(0.59-1.00) 1.00(0.83-1.2) 0.81(0.71-0.94) 0.99(0.84-1.16)

4+ 0.55(0.41-0.74) 0.82(0.53-1.28) 0.55(0.41-0.74) 0.71(0.55-0.92) 0.52(0.44-0.61) 0.73(0.59-0.91)

Husband

education

None 1.00 1.00 1.00 1.00 1.00 1.00

Primary 0.77(0.61-0.96) 0.77(0.58-1.01) 0.69(0.59-0.80) 0.80(0.67-0.94) 0.69(0.61-0.78) 0.79(0.68-0.91)

Secondary 0.55(0.39-0.77) 0.83(0.50-1.38) 0.64(0.48-0.87) 0.81(0.58-1.14) 0.62(0.49-0.77) 0.83(0.62-1.09)

Higher 0.58(0.26-1.30) 0.50(0.73-3.40) 0.72(0.49-1.0) 0.96(0.61-1.52) 0.64(0.46-0.90) 0.94(0.61-1.45)

BMI

<18.5 1.00 1.00 1.00 1.00 1.00 1.00

18.5-24.99 0.74(0.59-0.92) 0.76(0.59-0.99) 0.74(0.64-0.86) 0.79(0.68-0.93) 0.76(0.67-0.86) 0.78(0.68-0.89)

25+ 1.1(0.62-1.90) 1.66(0.79-3.48) 0.82(0.58-1.2) 1.12(0.77-1.62) 0.85(0.64-1.12) 1.21(0.87-1.68)

Duration of

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breastfeeding 1 year 1.00 1.00 1.00 1.00 1.00 1.00

2 years 0.79(0.64-0.99) 0.79(0.62-1.03) 0.71(0.60-0.83) 0.75(0.63-0.88) 0.75(0.66-0.85) 0.76(0.66-0.87)

3+ years 0.99(0.77-1.27) 1.10(0.82-1.49) 0.71(0.59-0.86) 0.82(0.67-0.99) 0.81(0.70-0.94) 0.89(0.76-1.05)

Time laps

2005 1.00 1.00


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2, Demewoz Haile

3*





Email address












Word count: 2388

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Abstract








gram per deciliter.







2

[AOR=0.78; 95% CI: (0.68-0.89)], middle wealth quintile [AOR=0.83; 95% CI: (0.71-0.98)] and

rich wealth quintile [AOR=0.83; 95% CI: (0.70-0.98)], ever use of family planning [AOR=0.68;




factors associated with anemia.





Ethiopia.

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ARTICLE SUMMARY

Article focus






Key messages








of anemia.








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Introduction





















which is one of the highest in the world.









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Methods









in to three local languages - Amharic, Oromefa and Tigregna. The EDHS was designed to



.

Data Extraction


website in SPSS format. After reviewing the detailed data coding, further data recoding was

completed. A total of 7,332 lactating mothers (2,285 from EDHS 2005 and 5,047 from EDHS

2011) were included in the analysis. Based on published literature, information on a wide-range

of socio-demographic and economic variables, health service related factors and anemia level

indicators were extracted. The chosen variables were region, residence, wealth index, occupation,

BMI, duration of breastfeeding, respondent’s education, husband’s education, family planning

use, iron tablet supplementation during pregnancy, time variation between two surveys, marital

status, age, parity and antenatal care attendance.





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recommended by the WHO for women above age 15 years. For this analysis, we re-categorized

anemia level as anemic and non-anemic from prior classifications in levels (no, mild, moderate,

severe) due to very small number of cases in the categories of severe and mild anemia in all

datasets of pooled and individual surveys.

Antenatal care (ANC) attendance referred to when women get services during pregnancy

according to the WHO recommendation of at least four ANC visits for low-risk pregnant

women. The frequency of the ANC visit is measured by asking the respondent to recall how

many times she had attended for the indexed child. Occupational status was defined as non-



categorised using standard WHO classification into underweight <18.5 kg/m2, normal 18.5–24.9

kg/m2, overweight 25.0 kg/m

2 and above. Parity, defined as the number of children ever born,

was categorised as 1-4, 5-9 and 10+. The wealth index constructed from household assets and

characteristics available in both surveys to categorise individuals into wealth quintiles (poorest,

poorer, middle, rich and richest) was used. For the present analysis, the wealth index was

collapsed into three groups (poor, middle and rich) to give a meaningful and practical sub-

population categories for designing program interventions in the general community.








analyses.



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model.

Ethical statements




Results
















parameter.

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BMI, time variation in the two surveys, and durations of breastfeeding.




















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Discussion



anemia in India13 and 43.8 % of lactating mothers in Kenya had a hemoglobin level <12 g/dl14.










postpartum hemorrhage17 Postpartum hemorrhage was also found to be one of the risk factors for

anemia during the period of lactation17.











might support their wives to use modern health services like family planning, ANC, postnatal






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wealth quintiles. In many other studies, anemia among reproductive age women, the wealth

index was found to be a statistically significant factor15 20. Other studies have also shown that

women of low socio-economic status are at risk for iron deficiency anemia (IDA) in late

pregnancy and in the postpartum period25 26

. Therefore, women’s empowerment through

economic interventions and working status could have a positive contribution towards preventing

anemia.










. When a mother








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that breastfeeding increases risk of anemia significantly20.








Conclusion






Ethiopia.

Competing interests


Funding statement




YL and DH conceptualized the research idea. YL analyzed and interpreted the data and critically

reviewed the manuscript. SB assisted in data interpretation and critically reviewed the

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manuscript. DH drafted the manuscript, assisted in the data analysis and interpretation and

critically reviewed the manuscript. All authors reviewed and approved the manuscript.

Acknowledgements




References


Organization. 2002.





15.



2001;185:4348-53.





2005;135:267–72.













2004;57:1138-46.





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2014;doi: 10.4269/ajtmh.13-0660.







58(4):731-34.


2005:pp 229.







2011;1(11):304-09.






February 2014








ONE 2013;9(3):e91252.








Nutrients 2012;4(12):1958-76.


deficiencies 2004.

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Background

characteristics

2005 2011 2005-2011

Total

lactating women

Prevalence of

anemia (95% CI)

Total

lactating women

Prevalence of

anemia (95% CI)

Total

lactating women

Prevalence of

anemia (95% CI)

Region

Tigray 142 35.4(27.69-43.33) 281 13.4(9.89-17.90) 422 20.8(17.18-24.93)

Afar 22 46.2(25.88-66.16) 38 42.4(27.27-58.10) 59 43.8(31.83-56.87)

Amhara 591 32.2(28.47-36.00) 1352 18.9(16.91-21.09) 1,943 22.9(21.12-24.86)

Oromia 826 28.5(25.45-31.60) 2041 20.1(18.39-21.87) 2,867 22.5(21.00-24.05)

Somali 60 49.2(37.50-62.50) 92 48.3(37.76-58.02) 152 48.7(40.80-56.62)

Benshangul-gumz 24 26.8(10.81-44.92) 59 20.5(11.51-32.02) 83 22.9(14.81-32.83)

SNNPR 578 26.2(22.66-29.82) 1059 13.5(11.54-15.66) 1,637 18.0(16.16-19.88)

Gambella 6 46.5(14.66-85.34) 18 23.2(7.49-45.31) 25 28.0(13.15-47.7)

Harari 3 27.1(1.67-86.80) 10 23.4(3.50-51.95) 15 20.0(5.35-45.35)

Addis Ababa 27 14.4(4.89-31.97) 83 7.3(2.98-14.43) 111 9.0(4.067-15.47)

Dire Dawa 5 33.0(7.35-81.76) 13 35.8(15.68-65.91) 18 33.3(14.77-56.9)

Residence

Urban 145 19.4(13.49-26.34) 595 12.4(9.96-15.27) 740 13.8(11.44-16.41)

Rural 2140 30.6(28.68-32.59) 4452 19.4(18.27-20.59) 6592 23.0(21.99-24.03)

Wealth index

Poor 986 32.2(29.29-35.12) 2306 21.4(19.74-23.09) 3293 24.6(23.15-26.09)

Middle 517 29.9(26.15-34.04) 1102 17.0(14.84-19.27) 1619 21.1(19.19-23.16)

Rich 782 27.0(23.96-30.18) 1639 15.6(13.86-17.37) 2420 19.3(17.76-20.91)

Current occupation

status

Not working 1568 31.8(29.55-34.16) 2325 21.0(19.37-22.68) 3893 25.4(24.06-26.29)

Working * 712 25.5(22.46-28.86) 2722 16.4(15.03-17.81) 3434 18.3(17.02-19.61)

BMI

<18.5 481 33.9(29.76-38.21) 1138 19.3(17.12-21.70) 1619 23.6(21.57-25.71)

18.5-24.99 1729 28.3(26.20-30.44) 3723 18.1(16.89-19.37) 5453 21.3(20.22-22.39)

25+ 65 42.1(30.05-53.76) 175 20.4(15.07-27.04) 240 26.3(20.98-32.09)

Duration of

breastfeeding

1 year 1072 30.7(27.98-33.50) 2461 20.6(19.04-22.23) 3533 23.7(22.31-25.11)

2 years 728 26.6(23.53-29.95) 1490 15.4(13.61-17.27) 2218 19.1(17.52-20.79)

3+ years 478 32.5(28.34-36-72) 1096 18.2(15.96-20.52) 1575 22.6(20.59-24.72)

Mother education

None 1804 31.8(29.70-34.00) 3486 19.2(17.91-20.52) 5291 23.5(22.36-24.65)

Primary 394 24.3(20.32-28.79) 1377 18.3(16.32-20.41) 1770 19.6(17.80-21.50)

Secondary 79 17.3(10.46-27.31) 126 8.3(4.10-13.69) 205 11.8(7.83-16.67)

Higher 8 1.1(0.63-48.03) 58 9.7(4.30-20.28) 66 8.7(3.77-17.95)

Husband education

None 1333 33.9(31.40-36.48) 2531 20.3(18.77-21.91) 3864 25.0(23.65-26.38)

Primary 701 26.2(23.09-29.60) 2048 17.2(15.60-18.87) 2749 19.5(18.05-21.01)

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Secondary 199 20.7(15.41-26.64) 238 14.3(10.26-19.17) 437 17.2(13.84-20.92)

Higher 23 14.8(3.43-31.53) 147 13.7(8.75-19.88) 170 13.8(8.99-19.30)

Family planning

Never use 1775 32.1(29.97-34.31) 2889 21.2(19.72-22.70) 4663 25.4(24.16-26.66)

Ever use 15 16.4(2.30-37.52) 2158 14.9(13.46-16.47) 2173 14.9(13.46.16.45)

ANC use

Never 1636 32.0(29.80-34.32) 2977 20.4(18.97-21-87) 4613 24.5(23.27-25.75)

1-3 386 27.7(23.43-32.35) 1208 18.4(16.27-20.64) 1594 20.6(18.65-22.62)

4+ 260 18.9(14.44-23.95) 845 12.6(10.44-14.91) 1105 14.1(12.16-16.27)


during pregnancy

No 2046 30.1(28.15-32.12) 4196 18.8(17.64-20.01) 6242 22.5(21.47-23.54)

Yes 236 27.1(21.74-33.06) 840 16.9(14.48-19.55) 1076 19.2(16.97-21.68)

Parity

1-4 1293 28.9(26.50-31.44) 3111 18.1(16.77-19.48) 4404 21.3(20.11-22.53)

5-9 903 30.5(27.52-33.52) 1739 19.6(17.79-21.53) 2642 23.3(21.73-24.96)

10+ 89 37.1(27.53-47.46) 197 17.0(12.02-12.46) 287 23.2(18.72-28.50)

Total 2285 29.9(28.04-31.79) 5047 18.5(17.45-19.60) 7332 22.1(21.13-23.03)




Occupation

Not working 1.00 1.00 1.00 1.00 1.00 1.00

Working 0.82(0.66-1.00) 0.83(0.64-1.06) 0.62(0.54- 0.71) 0.68(0.58-0.78) 0.64(0.57-0.72) 0.71(0.63-0.80)

Wealth index

Poor 1.00 1.00 1.00 1.00 1.00 1.00

Middle 0.71(0.54-0.92) 0.82(0.61-1.10) 0.74(0.61- 0.89) 0.85(0.69-1.04) 0.74(0.64-0.87) 0.83(0.71-0.98)

Rich 0.66(0.53-0.82) 0.91(0.68-1.22) 0.62(0.52-0.72) 0.80(0.65-0.97) 0.65(0.57-0.73) 0.83(0.70-0.98)

FP use

Never used 1.00 1.00 1.00 1.00 1.00 1.00

Ever used 0.37(0.11-1.28) 0.51(0.14-1.91) 0.54(0.46-0.63) 0.69(0.58-0.82) 0.48(0.41-0.55) 0.68(0.57-0.80)

ANC attended

Never 1.00 1.00 1.00 1.00 1.00 1.00

1-3 0.78(0.59-1.03) 0.94(0.66-1.33) 0.78(0.59-1.00) 1.00(0.83-1.2) 0.81(0.71-0.94) 0.99(0.84-1.16)

4+ 0.55(0.41-0.74) 0.82(0.53-1.28) 0.55(0.41-0.74) 0.71(0.55-0.92) 0.52(0.44-0.61) 0.73(0.59-0.91)

Husband

education

None 1.00 1.00 1.00 1.00 1.00 1.00

Primary 0.77(0.61-0.96) 0.77(0.58-1.01) 0.69(0.59-0.80) 0.80(0.67-0.94) 0.69(0.61-0.78) 0.79(0.68-0.91)

Secondary 0.55(0.39-0.77) 0.83(0.50-1.38) 0.64(0.48-0.87) 0.81(0.58-1.14) 0.62(0.49-0.77) 0.83(0.62-1.09)

Higher 0.58(0.26-1.30) 0.50(0.73-3.40) 0.72(0.49-1.0) 0.96(0.61-1.52) 0.64(0.46-0.90) 0.94(0.61-1.45)

BMI

<18.5 1.00 1.00 1.00 1.00 1.00 1.00

18.5-24.99 0.74(0.59-0.92) 0.76(0.59-0.99) 0.74(0.64-0.86) 0.79(0.68-0.93) 0.76(0.67-0.86) 0.78(0.68-0.89)

25+ 1.1(0.62-1.90) 1.66(0.79-3.48) 0.82(0.58-1.2) 1.12(0.77-1.62) 0.85(0.64-1.12) 1.21(0.87-1.68)

Duration of

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breastfeeding 1 year 1.00 1.00 1.00 1.00 1.00 1.00

2 years 0.79(0.64-0.99) 0.79(0.62-1.03) 0.71(0.60-0.83) 0.75(0.63-0.88) 0.75(0.66-0.85) 0.76(0.66-0.87)

3+ years 0.99(0.77-1.27) 1.10(0.82-1.49) 0.71(0.59-0.86) 0.82(0.67-0.99) 0.81(0.70-0.94) 0.89(0.76-1.05)

Time laps

2005 1.00 1.00


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215x279mm (300 x 300 DPI)

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Documents

BMJ Open · For peer review only Abstract Objective: To identify factors associated with anemia among lactating mothers in Ethiopia. Design: A cross-sectional secondary data analysis