child and mother nutrition survey of bangladesh 2005 · child and mother nutrition survey of...

Child and Mother Nutrition Surveyof

Bangladesh 2005

February 2007

BANGLADESH BUREAU OF STATISTICSPlanning Division, Ministry of PlanningGovernment of the People's Republic of Bangladesh

Child and Mother Nutrition Survey of Bangladesh, 2005

Published by:Bangladesh Bureau of StatisticsStatistics Division, Ministry of PlanningGovernment of the People's Republic of Bangladesh

Financial and technical support from:UNICEF Bangladesh

Suggested citation:BBS/UNICEF (2007). Child and Mother Nutrition Survey 2005. Bangladesh Bureau ofStatistics and UNICEF, Dhaka.

Design, Layout & Computer Graphics:Dhrupadi

II


T A B L E O F C O N T E N T S

LIST OF TABLES VI

LIST OF FIGURES VIII

ABBREVIATIONS X

FOREWORD XII

PREFACE XIII

MAP OF BANGLADESH XIV

EXECUTIVE SUMMARY XV

Chapter 1. INTRODUCTION 1

1.1 Nutrition and development 1

1.2 WHO Child Growth Standards 2

1.3 Nutrition interventions in Bangladesh 3

1.4 Objectives of the CMNS 2005 4

Chapter 2. METHODS 5

2.1 Survey area and population 52.2 Sampling design and sample size 5

2.3 Data collection methods 6

2.4 Survey teams 6

2.5 Training of survey teams 7

2.6 Monitoring and quality control 7

2.7 Data processing and analysis 7

2.7.1 Economic status and wealth index analysis 7

2.7.2 Household food consumption 8

2.7.3 Anthropometry 8

III


2.8 Technical oversight 10

2.9 Coverage of the sample 12

2.10 Comparison with methods of previous CNS surveys 12

Chapter 3. HOUSEHOLD CHARACTERISTICS 15

3.1 Socio-demography and socioeconomic status 15

3.2 Household food security 17

3.3 Household health environment and access to health services 17

3.4 Monsoon floods in 2004 18

Chapter 4. CHARACTERISTICS OF MOTHERS 21

Chapter 5. KNOWLEDGE AND PRACTICES ON CHILD ANDMATERNAL CARE 25

5.1 Child care 25

5.1.1 Infant and young child feeding 25

5.1.2 Care of child during illness 29

5.1.3 Vitamin A supplementation and deworming 29

5.2 Maternal care 30

Chapter 6. CHILD NUTRITION STATUS 33

6.1 National prevalence 33

6.2 Nutritional status by sex 36

6.3 Nutritional status by age 39

6.4 Nutritional status by area of residence 41

6.5 Nutritional status by season 43

6.6 Nutritional status by recent health status 43

6.7 Nutritional status by maternal characteristics 44

6.8 Other associations with nutritional status 45

6.9 Comparison of WHO 2005 GRS and NCHS 1977 GRS 48

6.10 South Asian comparison 49

6.11 National trends in the nutritional status 49

IV


Chapter 7. MATERNAL NUTRITION STATUS 51

7.1 National prevalence 51

7.2 Nutritional status by age 54

7.3 Nutritional Status by area of residence 54

7.4 Nutritional status by season 56

7.5 Nutritional status by maternal characteristics 56

7.6 Other associations with nutritional status 57

7.7 National trends in nutritional status 59

Chapter 8. CONCLUSIONS 61

ANNEXES

Annex 1: Data collection schedule 66

Annex 2: List of the primary sampling units 66

Annex 3: Questionnaire 80

Annex 4: Enumerators and supervisors 91

Annex 5: Validation of survey results 83

Annex 6: Estimation of weights 94

Annex 7: List of household assets used for wealth index 96

Annex 8: Members of the technical committee and technicalworking group 97

Annex 9: Additional analysis of anthropometric data 99

Annex 10: Comparison of child anthropometry determinedusing the NCHS 1977 GRS and WHO 2005 GRS 108

REFERENCES 110

V


L I S T O F T A B L E S

Table 1: Distribution of PSUs for the CMNS 2005 and HIES 2005 bydivision and area 6

Table 2: BMI cut-off values for chronic energy deficiency and overweight/obesity for international comparisons and Asian populations 9

Table 3: Exclusion criteria for child anthropometric indicesfor the CMNS 2005 10

Table 4: Number of PSUs, households and children enumerated by round 11

Table 5: Number of children surveyed by sex, age and area of residence 11

Table 6: Number of mothers surveyed by age and area of residence 12

Table 7: Household socio-demography and socio-economic status 16

Table 8: Household food security 17

Table 9: Household health environment and access to health services 18

Table 10: Impact of the 2004 Monsoon floods on households 19

Table 11: Mother's background characteristics 21

Table 12: Reproductive health of mothers 22

Table 13: Mother's participation in decisions on use of household resources 23

Table 14: Mother's knowledge on breastfeeding and complementaryfeeding practices 26

Table 15: Mother's reported breastfeeding and complementaryfeeding practices 27

Table 16: Reported caring practices of child with diarrhoea 29

Table 17: Coverage of vitamin A supplementation and dewormingin children 30

Table 18: Maternal caring practices during pregnancy, deliveryand postpartum 31

Table 19: Mean weight, height, MUAC and anthropometric indices inchildren aged <5 years by sex and area of residence 34

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Table 20: Prevalence of malnutrition in children aged <5 years by sex, age,area of residence and season 35

Table 21: Prevalence of moderate and severe malnutrition in children aged<5 years by sex and area of residence 36

Table 22: Prevalence of malnutrition in children aged <5 years by divisionand area of residence. 42

Table 23: Prevalence of malnutrition in children aged <5 years byrecent health status 44

Table 24: Prevalence of malnutrition in children aged <5 years bymaternal characteristics 45

Table 25: Other associations of malnutrition in children aged <5 years 46

Table 26: Prevalence of underweight, stunting and wasting in childrenaged <5 years in South Asian countries (NCHS 1977 GRS) 49

Table 27: Prevalence of malnutrition in children aged 6-59 months,1985 to 2005 (NCHS 1977 GRS) 50

Table 28: Mean age, weight, height MUAC and BMI of non-pregnantmothers by area of residence 51

Table 29: Nutritional status of non-pregnant adolescent mothers byarea of residence 52

Table 30: Nutritional status of non-pregnant adult mothers by area ofresidence (international BMI criteria) 53

Table 31: Nutritional status of non-pregnant adult mothers by area ofresidence (Asian population BMI criteria) 53

Table 32: Prevalence of malnutrition in non-pregnant adult mothersby age, area of residence and season 54

Table 33: Prevalence of malnutrition in non-pregnant adult mothers bydivision and area of residence 56

Table 34: Prevalence of malnutrition in non-pregnant adult mothers bymaternal characteristics 57

Table 35: Other associations of nutritional status in non-pregnantadult mothers 58

Table 36: Nutritional status of non-pregnant adult mothers, 1996-7 to 2005 60

VII


L I S T O F F I G U R E S

Figure 1: Infant and young child feeding indicators tracking child survival(MDG 4) by area of residence 28

Figure 2: Prevalence of underweight, stunting, wasting and overweight/obesity in children aged <5 years (WHO 2005 GRS) 33

Figure 3: Prevalence of underweight (WAZWHO) in children aged <5 years by sex 37

Figure 4: Prevalence of stunting (HAZWHO) in children aged <5 years by sex 37

Figure 5: Prevalence of wasting (WHZWHO) in children aged <5 years by sex 38

Figure 6: Prevalence of overweight/obesity (BAZWHO) in childrenaged <5 years by sex 38

Figure 7: Prevalence of underweight (WAZWHO) in children aged<5 years by age group 39

Figure 8: Prevalence of stunting (HAZWHO) in children aged <5 years by age group 40

Figure 9: Prevalence of wasting (WHZWHO) in children aged <5 yearsby age group 40

Figure 10: Prevalence of overweight/obesity (BAZWHO) in children aged<5 years by age group 41

Figure 11: Prevalence of underweight, stunting, wasting and obesity inchildren aged <5 years by area of residence (WHO 2005 GRS) 42

Figure 12: Prevalence of underweight, stunting, wasting and obesity inchildren aged <5 years by season (WHO 2005 GRS) 43

Figure 13: Comparison of the prevalence of underweight, stunting andwasting in children aged <5 years estimated using the WHO2005 GRS and NCHS 1977 GRS 48

Figure 14: Trends in undernutrition in children aged 6-59 months,1985 to 2005 (NCHS 1977 GRS) 50

Figure 15: Nutritional status of adolescent non-pregnant mothers 52

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Figure 16: Nutritional status of non-pregnant adult women by areaof residence 55

Figure 17: Nutritional status of non-pregnant adult mothers,1996-7 to 2005 60

Figure A1: Comparison of the WHO 2005 and NCHS 1977 GRSestimates of severe and moderate underweight 108

Figure A2: Comparison of the WHO 2005 and NCHS 1977 GRSestimates of severe and moderate stunting 108

Figure A3: Comparison of the WHO 2005 and NCHS 1977 GRSestimates of severe and moderate wasting 109

IX


A B B R E V I A T I O N S

BAZ BMI-for-age z-score

BBS Bangladesh Bureau of Statistics

BDHS Bangladesh Demographic and Health Survey

BMI Body mass index

CDC Center for Disease Control

CED Chronic energy deficiency

CMNS Child and Mother Nutrition Survey

CNS Child Nutrition Survey

EBR Exclusive breastfeeding rate

FWA Family Welfare Assistant

FWV Family Welfare Visitor

GRS Growth reference standard

HA Health Assistant

HAZWHO Height-for-age z-score determined using WHO 2005 GRS

HAZNCHS Height-for-age z-score determined using NCHS 1977 GRS

HIES Household Income and Expenditure Survey

HKI Helen Keller International

HNPSP Health, Nutrition and Population Sector Programme

IMPS Integrated multipurpose sampling frame

INFS Institute of Nutrition and Food Science

IYCF Infant and young child feeding

LBW Low birth weight

MA Medical Assistant

MDGs Millennium Development Goals

MUAC Mid-upper arm circumference

MUACZ MUAC-for-age z-score

X


MSCW Monitoring the Situation of Children and Women

NCHS National Center for Health Statistics

NNP National Nutrition Programme

NVAC National Vitamin A+ Campaign

ORS Oral rehydration solution

PCA Principal components analysis

PSU Primary sampling unit

SBA Skilled Birth Attendant

SVRS Sample Vital Registration System

TBA Traditional Birth Attendant

WAZWHO Weight-for-age z-score determined using WHO 2005 GRS

WAZNCHS Weight-for-age z-score determined using NCHS 1977 GRS

WHO World Health Organization

WHZWHO Weight-for-height z-score determined using WHO 2005 GRS

WHZNCHS Weight-for-height z-score determined using NCHS 1977GRS

XI


Foreword

Malnutrition is one of the most serious health problems affecting children and their mothersin Bangladesh. Undernourished mothers face greater risks during pregnancy and childbirth,and their children set off on a weaker developmental path, both physically and mentally.Undernourished children have lower resistance to infection and are more likely to die fromcommon childhood ailments as diarrhoeal diseases and respiratory infections. Those whosurvive may be locked into a vicious cycle of recurring sickness and faltering growth, oftenwith irreversible damage to their cognitive and social development.

Malnutrition prevents individuals and even the whole country from achieving full potential,and is closely related with survival, poverty and development. In fact, underweight is beingused to track the progress of Bangladesh towards the Millennium Development Goal (MDG1) for poverty reduction, and nutrition is closely linked with the MDGs for child survival(MDG 4) and maternal health (MDG 5).

The Bangladesh Bureau of Statistics (BBS) conducted a Child and Mother Nutrition Survey(CMNS) in 2005 to assess the current nutritional status of children and mothers inBangladesh. According to new growth reference standards of the World Health Organization,40% of under five children in Bangladesh were underweight in 2005, 46% were stunted and15% were wasted. These new findings indicate that the nutritional status of children isimproving, nevertheless, the levels of undernutrition remain unacceptably high. Chronicenergy deficiency of mothers is also declining; currently 32% have a low body mass index.However, there are signs that the problem of overweight among mothers is increasingrapidly.

The Government of Bangladesh is committed to reducing malnutrition among children andwomen. Nutrition is included in the Health, Nutrition and Population Sector Programme(HNPSP) of the Ministry of Health and Family Welfare, and is also being addressed bycomplementary actions of the Ministry of Agriculture and Ministry of Fisheries andLivestock, amongs others. A multi-sectoral approach is crucial, because the multiple causesof malnutrition require a coordinated response from multiple sectors.

I would like to express my sincere thanks to Director General, BBS and the Project Director,Monitoring the Situation of Children and Women (MSCW) Project for bringing out thisreport. We acknowledge the financial and technical support of UNICEF for conducting thesurvey, data analysis and publication of the report with gratitude.

I hope that the report will be useful for policy makers, planners, project managers,researchers and development partners from all relevant sectors for tracking progress and forstimulating action towards the alleviation of malnutrition in Bangladesh.

February, 2007 (Jafar Ahmed Chowdhury)Secretary

Planning Division.

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Preface

The Bangladesh Bureau of Statistics has a long history of conducting Child Nutrition Surveys(CNS) to track progress towards the alleviation of malnutrition in Bangladesh. Five suchsurveys were conducted every 3-5 years between 1985-86 and 2000. This Child and MotherNutrition Survey (CMNS) is the sixth in the series of surveys, which for the first timeincluded mothers as well as children.

Like previous surveys, the CMNS has been conducted in the same sample areas andhouseholds as the 2005 Household Income and Expenditure Survey (HIES). This enabled thenutritional data to be analysed with socio-economic data from the HIES. The CMNS covered3069 households having at least one under five children, and included 3797 children and 3050mothers. It has adopted the new growth reference standards of the World HealthOrganization for anthropometric indices of underweight, stunting and wasting. The reportpresents the nutritional status of children and mothers by age, sex, area of residence,seasonality, socio-economic status. It also provides information on underlying determinantsof malnutrition, including household food security, caring practices, health environment andhealth services.

I take this opportunity to express my sincere thanks to the concerned officials of BBS,particularly Mr. Md. Shamsul Alam, Project Director, Mr. Alamgir Hossain, Statistical Officerand Mr. Mizanur Rahman Khandaker, Statistical Officer, of the Monitoring the Situation ofChildren and Women (MSCW) Project for conducting the Survey and bringing out thisreport. The contribution of Dr. Harriet Torlesse, Project officer, United Nations Children'sFund (UNICEF) and Dr. Khurshid Talukder Consultant, UNICEF and Dr. Mohsin Ali, Projectofficer, UNICEF, is greatly acknowledged. Data processing was performed by Mr. S. M.Anwar Husain, Statistical Assistant, MSCW, BBS.

I would also like to extend my gratitude and appreciation to all members of the TechnicalCommittee and Technical Working Group for their invaluable contributions to the surveydesign and finalization of the report.

I hope that the report will be very useful for all stakeholders in nutrition and related fields.Suggestions and comments on the report for improvement of future surveys are mostwelcome.

February, 2007 (AY M Ekramul Hoque)

Director General

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Map of Bangladesh

Map of Bangladesh showing the location and number of the survey PSUs

XIV

THAKURGAON

5

PANCHAGARH

5

NILPHAMARI

5

DINAJPUR

8 RANGPUR

7

KURIGRAM

6

GAIBANDHA

6JAIPURHAT

6NAOGAON

6

C. NAWABGANJ

5RAJSHAHI

10 NATORE

6

PABNA

7

SIRAJGANJ

7

BOGRA

8

SHERPUR

4

JAMALPUR

7

TANGAIL

10

MYMENSINGH

14

KUSHTIA

5MEHERPUR

5CHUADANGA

5 JHENAIDAH

6

RAJBARI

5

MAGURA

4

FARIDPUR

6

NARAIL

6 GOPALGANJ

6JESSORE

8

BAGERHAT

5KHULNA

9

SATKHIRA

5

PATUAKHALI

5

BARGUNA

4

BHOLA

6

JHALAKATHI

5

BARISAL

8

MANIKGANJ

6

NARSHINGDI

7

BRAHMANBARIA

5

NARAYANGANJ

7

SHARIATPUR

4

MADARI PUR

5

LAKSHMIPUR

5

KHAGRACHHARI

5

RANGAMATI

5

BANDARBAN

5

PIROJPUR

3

KISHOREGANJ

6

NETRAKONA

5

SUNAMGANJ

5SYLHET

7

MOULAVIBAZAR

5HABIGANJ

4

COMILLA

11

MUNSHIGANJ

4

CHANDPUR

6

NOAKHALI

7

FENI

4

CHITTAGONG

14

COX'S BAZAR

5

GAZIPUR

7DHAKA

15

INDIA

B A Y O F B E N G A L

INDIA

INDIA

MAYANMAR

LALMONIRHAT

4


Executive Summary

Introduction

This Child and Mother Nutrition Survey (CMNS) of Bangladesh was carried outin 2005 at a time when important changes were underway in public healthnutrition in Bangladesh. The country was a signatory to achieving theMillennium Development Goals (MDGs) of which three, MDG 1 for povertyreduction, MDG 4 for child mortality and MDG 5 for maternal health, are directlyrelated to nutrition. A "double burden of malnutrition", meaning the coexistenceof undernutrition and overweight in the same population, is emerging in thecountry, partly due to economic development coupled with economic disparities.Then, as the analysis of the CMNS 2005 was about to begin, the World HealthOrganization (WHO) released new improved Growth Reference Standards (GRS)children based on a dataset of children from six countries who were raised inenvironments that promote healthy growth. Against this background, nutrition isfor the first time included in a sector wide approach (SWAp), the Health, Nutritionand Population Sector Programme (HNPSP) of the Government of Bangladesh.

The main objective of this survey was to asses the nutritional status of childrenaged less than 5 years and their mothers in Bangladesh. Additional objectiveswere to examine underlying causes of malnutrition (socio-economic status,household food security, health environment and health services), and tocompare the survey's findings with those of previous Child Nutrition Surveys(CNS) conducted by BBS.

Methods

The survey covered 3797 children aged 0-59 months and 3050 mothers living in3069 households in rural and urban Bangladesh. This sample was taken from 80%(403) of the 504 Primary Sampling Units (PSUs) of the BBS Household Incomeand Expenditure Survey (HIES) 2005. Data were collected on indicators ofhousehold socio-demographic and socio-economic status, access to healthservices and health environment, household food security, caring practices andanthropometry of children and their mothers in nine rounds between January andDecember in 2005. The weight of children and mothers was measured to thenearest 100 g using the UNISCALE and the height or length was measured to theneared 1 mm using a stadiometer.

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The new WHO GRS was used to estimate the prevalence of child underweight,stunting, wasting and overweight in 2005. The National Centre for HealthStatistics (NCHS) 1977 GRS was used for trend analysis and for comparisons withdata from other countries.

Results and conclusion

Household characteristics

The mean household size of this population was 5.8 persons, higher than valuesfrom other national surveys because the survey selected households with at leastone child aged less than 5 years. Over 95% of household heads were male, 57%were illiterate or had never attended school and the most common occupationgroup was agriculture (40%). About 60% of households relied on kerosene as theirmajor source of light and the remainder had access to electricity. Only 18% ofhouseholds had a sanitary toilet (defined as having either a flushing mechanismor a water seal) and 94% of household had access to tube well drinking water.

The per capita food energy consumption was 2077 kcal/day, and was 65 kcal/dayhigher in rural areas than urban areas. About 47% of households had homesteadgardens and more than 25% of households had taken loans to buy food in theprevious three months. One third of households suffered crop losses due to theMonsoon floods in 2004, and 29% of households were damaged or destroyed due tothe floods. When household salt was tested for iodine, 83% was found to be iodised.

Maternal and child caring practices

Both knowledge and practice of appropriate infant and young child feedingpractices (IYCF) was poor among mothers. Only 33% correctly knew that childrenshould be exclusively breastfed for six months and only 40% knew thatcomplementary feeding should begin at 6 months of age. Breastfeeding wasinitiated within one hour for 48% of infants, exclusive breastfeeding rate (EBR)under six months of age was 58%, timely complementary feeding at 6-9 monthsof age was 71%, and the continued breastfeeding rate at 20-23 months was 89%.These four parameters of IYCF practices are powerful determinants of childsurvival and all four should be universal. The findings call for morecomprehensive mainstreaming of IYCF protection, promotion and support at thecommunity level. Given that the vast majority of children are delivered at home,these interventions must target women during pregnancy, and and enlist thesupport of birth attendants in the communities, so that every infant begins lifewith immediate breastfeeding.

XVI


Over a fifth of mothers did not receive any antenatal care (ANC). Over half (52%)of mothers did not have their weight measured during pregnancy and 57% didnot take any iron supplements. Forty one percent (41%) of mothers ate less duringpregnancy, and 22% took less rest than when they were not pregnant. Manyopportunities appear to be missed in providing essential nutrition interventionsand counselling to mothers in Bangladesh.

The coverage of vitamin A supplementation was 93% among infants with themeasles vaccination at 9-11 months of age, 93% among children aged 12-59months, and only 18% among mothers within 6 weeks of delivery.

Child Nutritional Status

Using the new WHO 2005 GRS, 40% of children aged <5 years were underweight,46% were stunted, 15% were wasted and 1.4% were overweight/obese.According to criteria of the World Health Organizationi, the prevalence ofunderweight and stunting was "very high", and the prevalence of wastingindicated a "critical problem". Severe underweight, severe stunting, severewasting and obesity were found in 11%, 19%, 3% and 0.3% of the population. Thisis the first time that data on child overweight/obesity have been determined forBangladesh, and the data can provide a baseline against which to measure trendsin the future.

The prevalence of underweight increased dramatically between 6-11 months ofage and stabilized from 12 months onwards. The prevalence of stunting increasedup to the end of the second year, and stabilized thereafter, decreasing slightly inthe fourth year of life. The prevalence of wasting was highest in the first sixmonths, and decreased gradually thereafter up to the fifth year of life. Thesepatterns are likely to reflect poor breastfeeding and complementary feedingpractices in the first year of life. There were no differences in nutritional statusbetween girls or boys. In comparison with the urban population, the ruralpopulation was significantly more underweight (42% vs. 30%) and more stunted(49% vs. 36%); there was no significant difference in wasting andoverweight/obesity.

The nutritional status of children was closely linked with several maternalcharacteristics. The prevalence of underweight, stunting and wasting wassignificantly higher among mothers with low education status, and with motherswho had chronic energy deficiency (CED, defined as a body mass index less than18.5 kg/m2). Children of older mothers were significantly more underweight thanchildren of younger mothers, and children of mothers who worked outside thehome were less likely to be wasted than children whose mothers werehousewives. Children belonging to a household with a female household head

XVII


were significantly less likely to be underweight that those belonging to ahousehold with a male household head.

Child underweight, stunting, and wasting showed a predictable association withwealth quintile: all three indices significantly decreased with increase in wealthquintile, and there was almost a two-fold difference in prevalence ofundernutrition between the poorest and richest wealth quintiles. Similarly, theprevalence of all three indicators decreased with an increase in household landownership, income and expenditure.

Indicators of lower household food security, including low per capita kilocalorieconsumption and loan for food, were associated with a higher prevalence ofunderweight, stunting and wasting. Children belonging to households affectedby the 2004 Monsoon floods were more likely to be underweight and stunted andless likely to be overweight than children in other households.

Compared with the NCHS 1977 GRS, the WHO 2005 GRS estimate of childunderweight is lower (45% vs. 40%) and the estimate of child stunting (40% vs.46%) and child wasting (13% vs.15%) are higher. These differences are consistentwith the predicted differences between the two GRS.

Using the NCHS 1977 CRS to examine trends in nutritional status over time, theprevalence of child underweight decreased from 66% in 1989-90, the base year forthe MDGs, to 48% in 2005; the 18 percentage point decline amounts to 27% of the1989/90 prevalence, and indicates that considerable progress is needed to meetthe target of MDG 1 for a 50% decline in child underweight. The prevalence ofchild stunting decreased from 65% to 42% between 1989-90 and 2005, and therewas marginal change in child wasting.

Mother's nutritional status

The mean age of mothers of under-5 children was 28 years. Almost three-quarters(69%) of mothers married before 18 years of age and 72% had their first pregnancybefore 20 years of age. Almost one half (47%) of mothers were illiterate or hadnever attended school. Less than 10% of mothers were able to make their owndecisions on how much money the household spends on food, what food is boughtfor the household, and whether the mother or her child attends a health facility.

According to the new Asian adult BMI cut-offs, 32% of non-pregnant adultmothers had chronic energy deficiency (BMI <18.5 kg/m2) and 17% wereoverweight or obese (BMI >_ 23 kg/m2). The prevalence of CED in rural motherswas almost double that in urban mothers, while the prevalence of overweight/obesity was considerably higher in urban areas (32%) than rural areas (13%).

XVIII


Mothers with lower education status were more likely to have CED and less likelyto be overweight/obese than mothers who had higher education status. Workingmothers were more likely to be overweight/obese and less likely to have CEDthan housewives. Mothers belonging to a household with a female householdhead were more likely to be overweight/obese than mothers belonging to ahousehold with a male household head.

The prevalence of CED significantly decreased with increase in wealth quintile,and there was a three-fold difference in prevalence between the poorest (15%) andrichest quintile (44%); the prevalence of overweight/obesity significantlyincreased with the increase in wealth quintile, and there was an eight-folddifference in prevalence between the poorest (5%) and richest quintile (40%).Similar patterns were observed for other indicators of socio-economic status,including household landownership, income and expenditure. Both children andmothers from the poorest households are clearly most disadvantaged. Allinterventions to address undernutrition should actively seek ways to reach andimprove access by the poorest households to essential interventions.

Indicators of lower household food security, including low per capita kilocalorieconsumption and loan for food, were associated with a higher prevalence of CEDand a lower prevalence of overweight/obesity. However, ownership of ahomestead garden was not associated with maternal nutritional status. Mothersbelonging to households affected by the 2004 Monsoon floods were more likely tohave CED and less likely to be overweight/obese than mothers in otherhouseholds.

As the previous CNSs did not include the anthropometry of mothers, the CMNS2005 data were compared with the findings of the three previous BangladeshDemographic and Health Survey (BDHS) findings. Between 1996-7 and 2005, theprevalence of CED decreased from 53% to 32% and the prevalence ofoverweight/obesity increased from 7% to 17%. These findings provide conclusiveproof that maternal overweight/obesity is a rapidly emerging public healthproblem in Bangladesh, particularly in urban areas. This calls for public healthaction to reverse the trend before it reaches the epidemic proportions thatcurrently affect other countries of the world. Adult men should be included in thenext national nutritional survey so that overweight/obesity can also be trackedamong the adult male population, who account for the majority of income earnersin Bangladesh.

The findings from the CMNS clearly demonstrate that the double burden ofmalnutrition is now present in Bangladesh, and that problems of bothundernutrition and overnutrition need to be addressed simultaneously.

XIX


Chapter I: Introduction

1.1 Nutrition and development

Improving nutrition, particularly in the early years, is crucial towards meeting theMillennium Development Goals (MDGs). Good nutrition is the cornerstone forsurvival, health and development. Well-nourished children perform better inschool, grow into healthier adults and are able to give their own children a betterstart in life.

Despite much recent progress, Bangladesh continues to struggle with malnutrition.Undernourished mothers face greater risks during pregnancy and childbirth, andtheir children set off on a weaker developmental path, both physically andmentally. Undernourished children have lower resistance to infection and aremore likely to die from common childhood ailments as diarrhoeal diseases andrespiratory infections. When survival is possible, it is an existence tainted by avicious cycle of recurring sickness and faltering growth, often with irreversibledamage to their cognitive and social development. Malnutrition preventsindividuals from achieving their full potential, and has ever-wideningsignificance at the family, community and national levels, with ill-health and poorproductivity leading to economic loss and delayed national development.

Good nutrition is not only a determinant of development, it is also an outcome.The two-way relationship between nutrition and development applies equally tomalnutrition and poverty. For this reason, the prevalence of underweight is beingused to track the progress of Bangladesh towards MDG 1 for poverty reduction.The baseline prevalence of underweight in children in 1990 was 66% (CNS1989/90 for children aged 6-71 months), and to meet the target for a 50%reduction in underweight, this prevalence must fall to 33% by 2015. Some analysisindicates that Bangladesh is on target for a 50% reduction in underweightii,however, the recent slow-down in the reduction of underweight between the twomost recent Bangladesh Demographic and Health Surveys (BDHS) in 1999-2000and 2004 is of concern.

The significance of nutrition for the MDGs does not end with poverty reduction:good nutrition is essential for reducing child mortality (MDG 4) and improvingmaternal health (MDG 5). Malnutrition contributes to over one-half of childdeaths. If taken to scale, breastfeeding and complementary feeding can prevent19% of these deaths; vitamin A and zinc supplementation can prevent a further7% of deathsiii. A study conducted in Ghana showed that initiation ofbreastfeeding within one hour reduces neonatal mortality by more than 20% and

1


under-5 mortality by 9%iv. It is not surprising, therefore, that key indicators ofbreastfeeding, complementary feeding and vitamin A supplementation coverageare being used to track progress towards the child mortality reduction (MDG 4)v.

Malnutrition, particularly chronic energy deficiency (CED) and anaemia,contribute to poor maternal health and pregnancy outcomes for both the motherand her infant. Severe anaemia increases the risk of maternal mortality frompostpartum haemorrhage and obstructed labour, which together account for overone-third of maternal deaths. The most recent data indicate that 40% of adolescentgirls, 46% of non-pregnant and 39% of pregnant women are anaemicvi. Poormaternal nutritional status often leads to poor nutrition for the child, beginningwith low birth weight, which affects 36% of infants in Bangladeshvii.

While the focus in Bangladesh is justly on the magnitude and scale ofundernutrition, overweight and obesity are emerging as new public healthproblems that also demand attention. There is extensive evidence that overweightand obesity in adults elevates the risk of adult health problems, such as diabetesand cardiovascular disease. Recent trend analysis of the body mass index ofmothers of children aged less than 5 years has shown a doubling of the prevalenceof overweight/obesity from 7.1% to 15.5% in the 7 year period between 1996-97and 2004viii. This "double burden of malnutrition", meaning the coexistence ofoverweight and undernutrition in the same population, may be a consequence ofeconomic development and of the growing inequities amongst the rich and poor.Between 2000 and 2005, the proportion the population that was poor fell from49% to 40% and the proportion that was very poor fell from 34% to 25%ix, butthese national level markers of progress mask inequities in progress, particularlyamong the poorest population groups. Any analysis of progress towards MDGsmust therefore disaggregate indicators by poverty or wealth, otherwise healthynational averages will hide a litany of inequities in societyx.

1.2 WHO Child Growth Standards

The World Health Organization developed new growth reference standards(GRS) for children in 2005. These GRS have been based on a globallyrepresentative cohort of 8440 children from six diverse countries who were raisedin environments that promote healthy growth such as breastfeeding, good dietsand prevention and control of infections. They show how every child in the world"should grow", and are a major improvement on the previous GRS of the NationalChild for Health Statistics (NCHS), which showed how children "do grow" at thetime they were developed in 1977.

The new WHO GRS are considered to be a technically robust tool to measure,monitor and evaluate the growth of all children worldwide, regardless of

2


ethnicity, socioeconomic status and type of feeding. For this reason, they havebeen adopted for the first time in Bangladesh for the CMNS 2005, with theexception of trend analyses and international comparisons with surveys that usedthe 1977 NCHS GRS for computation of anthropometic indices.

1.3 Nutrition interventions in Bangladesh

Malnutrition is difficult to address because it has numerous causes includingimmediate (inadequate dietary intake, disease), underlying (household foodinsecurity; lack of maternal and child caring practices; and unhealthyenvironment and poor health services) and basic, including poverty at its verybase. A multi-sectoral approach is crucial, because the multiple causes ofmalnutrition require a coordinated response from multiple sectors.

There have been many attempts to address malnutrition in this country. TheGovernment of Bangladesh is committed to reducing malnutrition amongchildren and women. Nutrition is included in the Health, Nutrition andPopulation Sector Programme (HNPSP) of Ministry of Health and FamilyWelfare, and is also being addressed by complementary actions of the Ministry ofAgriculture, Ministry of Fisheries and Livestock, amongst others. In addition,national and international non-government organizations (NGOs), community-based organizations, UN agencies, research organizations, donors and manyothers are also working together to improve nutrition in Bangladesh.

The key interventions that are currently being implemented under the HNPSPinclude the following:

Growth monitoring and promotion (GMP): The National Nutrition Programme(NNP) provides GMP in its operational areas. Children and pregnant women areweighed monthly, and those who are not gaining sufficient weight are targetedfor counselling. Severely malnourished or growth faltering children and severelymalnourished pregnant women are also targeted for supplementary feeding.

Infant and young child feeding (IYCF): A National Strategy for IYCF has beendeveloped by the Institute of Public Health Nutrition (IPHN). It identifiescomprehensive actions that will be taken to improve legislation, policies andstandards to protect optimum infant and young child feeding practices, and tostrengthen the capacity of health services and communities to promote andsupport the nutritional needs of infants and young children.

Prevention and control of anaemia: The National Strategy for the Prevention andControl of Anaemia in Bangladesh recognizes the key strategies needed to

3


address all major causes of anaemia, including both targeted strategies for high-risk groups (micronutrient supplementation, dietary improvement, parasiticdisease control, and family planning and safe motherhood) and population-basedstrategies (food fortification and production of micronutrient rich foods).

Prevention and control of vitamin A deficiency: Vitamin A supplements are givento infants aged 9 months with their measles vaccination through the ExpandedProgramme on Immunization; to children aged 12-59 months every six monthsthrough the National Vitamin A+ Campaigns; and to mothers within 6 weeks ofeach delivery. For longer term sustainable solutions to vitamin A deficiency, theavailability and affordability of vitamin A rich foods needs to be improvedthrough food-based approaches such as homestead gardening and food fortification.

Prevention and control of iodine deficiency: The soil in Bangladesh naturallylacks iodine and so it is added to edible salt during processing to prevent iodinedeficiency disorders. All edible salt should be iodized by law.

In addition to the above interventions, numerous actors are working to improvethe health environment, health services and household food security, which areall necessary for good nutrition.

1.4 Objectives of the CMNS 2005

The Bangladesh Bureau of Statistics has a long history of conducting ChildNutrition Surveys (CNS) to obtain up-to-date data on the scale, magnitude andcauses of malnutrition in Bangladesh and to track progress towards thealleviation of malnutrition. Five such surveys were conducted every 3-5 yearsbetween 1985-86 and 2000. This Child and Mother Nutrition Survey (CMNS) isthe sixth in the series of surveys, which for the first time included mothers as wellas children. The objectives of the CMNS were as follows:

a) To determine the nutritional status of children aged 0-59 months, includingunderweight, stunting, wasting and overweight.

b) To determine the nutritional status of mothers of children aged 0-59 months.

c) To obtain information on knowledge, attitudes and practices concerning keycaring practices that affect child and maternal nutritional status, includinginfant and young child feeding practices and care practices during illness.

d) To examine the associations of nutritional status with socio-economic,demographic and individual characteristics.

e) To compare the findings of CMNS 2005 with previous nutrition surveys.

4


Chapter 2: Methods

2.1 Survey area and population

The CMNS was carried out among a nationally representative sample of rural andurban children aged 0-59 months and their mothers. The data was collected overnine 'rounds' of data collection between January 2005 and December 2005, coveringall seasons of the year. Annex 1 provides the schedule for the data collection.

2.2 Sampling design and sample size

The CMNS was conducted among a subsample of households surveyed by the2004-5 Household Income and Expenditure Survey (HIES). The sample sizeneeded to provide data representative at the national and divisional level for theCMNS was calculated using the following formula:

n = z2 [P(1-P)/d2]*Deff

where n = sample sizez = two-sided normal variate at 95% confidence level (1.96)P = indicator percentaged = precision Deff = design effect

Assuming the most conservative estimate of indicator percentage (50%), a precisionof 5%, a 95% confidence level and design effect of 2, a total of 769 households wereneeded in each division, thus a total of 4,614 households overall (769*6).

The HIES surveyed 20 households in 504 primary sampling units (PSUs). Data forthe CMNS was collected from a sub-sample of 80% of these HIES PSUs (403PSUs). In each PSU there were at least 12 households with a child aged <5 yearsand his/her mother, thus the expected minimum sample size from 403 PSUs was4,836 households (403*12). Table 1 shows the distribution of CMNS 2005 andHIES 2005 PSUs by division and area, and details on the location of each PSUgiven in Annex 2.

5


Table 1: Distribution of PSUs for the CMNS 2005 and HIES 2005 by divisionand area

2.3 Data collection methods

A questionnaire was designed to record data on indicators of household socio-economic and socio-demographic status, access to health services and healthenvironment, household food security, caring practices and anthropometry ofchildren and their mothers. The questionnaire was prepared in English, reviewedand approved by a Technical Committee, translated to Bangla and pre-testedbefore finalisation. The English version of the questionnaire is given in Annex 3.

The UNISCALE (Seca, Hamburg, Germany) was used to measure the weight ofchildren and mothers to the nearest 100 g. A stadiometer was used to measure thelength of children aged less than 2 years and the height of mothers and childrenaged at least 2 years to the nearest 1 mm. Mid-upper arm circumference (MUAC)was measured using MUAC tapes to the nearest 1 mm. Iodine testing solutionwas used to determine the presence or absence of iodine in household salt.

2.4 Survey teams

Data was collected by three-member survey teams from BBS head office,comprising two female and one male worker. All enumerators were collegegraduates with 10 to 22 years of survey experience, and two enumerators in eachteam had worked on a previous BBS CNS. Each team was assisted in the field bya local female facilitator, who was a regular recruit for the BBS Sample VitalRegistration Survey (SVRS). These facilitators introduced the survey teammembers to the surveyed households. The survey teams were supervised and

6

DivisionCMNS 2005 HIES 2005

Rural Urban Total Rural Urban Total

Barisal 23 10 33 28 13 41

Chittagong 46 26 72 58 32 90

Dhaka 69 49 118 86 61 147

Khulna 35 23 58 44 29 73

Rajshahi 68 33 101 85 41 126

Sylhet 15 6 21 19 8 27

Total 256 147 403 320 184 504


coordinated by six field supervisors and one co-ordinator. Annex 4 lists the datacollectors for the CMNS.

2.5 Training of survey teams

All survey teams were trained for five days on data collection before the start ofdata collection. They also attended refresher training between each round of datacollection at the BBS headquarters. The training included sessions on how toadminister the questionnaires, take anthropometric measurements, and addressproblems in the field. It included role play and practical sessions on filling up thequestionnaires and taking anthropometric measurements. All training wasprovided by master trainers from BBS.

2.6 Monitoring and quality control

Seven Officers from the BBS Project Office were assigned as supervisors (seeAnnex 4). A supervisor was assigned to each data collection team to ensure dataquality by guiding interviewers during data collection, checking data collectionin randomly chosen households, checking all the filled-in data collection formsand holding discussion meetings at the end of each day with the team members.Any problems in data collection were discussed with the team members, andremedial measures taken accordingly. BBS also engaged 23 Regional StatisticalOfficers to supervise field visits and spot check data collection.

To check the quality of the anthropometry data, a post-evaluation check (PEC)was conducting by comparing the data collected by the enumerators and qualitycontrol officers in a selected number of households (see Annex 5).

2.7 Data processing and analysis

The data were double-entered using Integrated Multipurpose Sampling Frame(IMPS) software, and validated and cleaned using Epi-Info Version 6.04. Datawere analysed with SPSS Version 11.5. All data were weighted to providedivisional, national, rural and urban estimates, as described in Annex 6.

2.7.1 Economic status and wealth index analysis

Previous CNS used household income and expenditure data as indicators ofeconomic status. In this report, principal components analysis (PCA)xi was alsoused to derive an index of household economic status ('wealth index') from dataon household ownership of assets and use of selected services. The wealth indexhas recently been used in many countries to explore inequities in household

7


income, use of health services and health outcomesxii and correlates withmeasures of expenditure and incomexiii. The data for the wealth index wasobtained from the HIES 2005 dataset (see Annex 7 for full list of indicators). Fromthe PCA, each household was assigned a wealth index score and households wereranked accordingly by quintiles.

2.7.2 Household food consumption

Data on household food consumption was collected by HIES 2005 using seven 48hour dietary recalls over a two week period. Daily per capita household foodconsumption was estimated by averaging the data from 14 days of consumptiondata and dividing by the number of household members. Food compositiontables developed by the Institute of Nutrition and food Science, University ofDhaka, were used to determine the nutritional value of foods consumed.

2.7.3 Anthropometry

For children, the values of height-for-age z-score (HAZ), weight-for-age z-score(WAZ) and weight-for-height z-score (WHZ) were computed using both theNCHS 1977 growth reference standards (GRS) and WHO 2005 GRS. Todistinguish between these two GRS, anthropometric indices computed with theNCHS data are post-fixed with "NCHS" (HAZNCHS, WAZNCHS, and WHZNCHS) andanthropometric indices computed with the WHO Growth Standards are post-fixed with 'WHO" (HAZWHO, WAZWHO, and WHZWHO).

The WHO 2005 GRS was selected as the primary GRS for the 2005 CMNS, andalmost all data are presented using this GRS. The NCHS 1977 GRS was used forcomparisons of the 2005 CMNS data with data from previous surveys inBangladesh and other countries that used the NCHS 1977 GRS. For all estimatesof HAZ, WAZ and WHZ, the following categories were applied: serious <-3.00SD; moderate -3.00 to -2.01 SD; total <-2.00 SD.

The nutritional status of adolescents was determined using BMI-for-age,according to WHO recommendationsxiv. Adolescents were considered thin if BMI-for-age was <5th percentile and at risk of overweight if the BMI-for-age was >85th

percentile. Height-for-age Z-scores (HAZ) for adolescents were derived fromCDC 2000 cut-offs using Epi Info Version 3.2.2.

For adults, body mass index (BMI) categories for international comparisons andAsian populations were applied, as indicated in Table 2.

8


Table 2: BMI cut-off values for chronic energy deficiency and overweight/obesity for international comparisons and Asian populations

During data processing exclusion criteria were applied to the childanthropometric data, based on WHO recommendationsxv, to remove data that aremost likely to be erroneous. Table 3 shows the exclusion criteria that wereapplied.

9

Population Category BMI (kg/m2)

Internationalcomparisons

Chronic energy deficiency

Grade III <16.0

Grade II 16.0 to 16.9

Grade I 17.0 to 18.4

Total <18.5

Normal 18.5 to 24.9

Overweight/obesity



Grade III >40.0

Total >25.0

Asian

Chronic energy deficiency

Grade III <16.0



Total <18.5

Normal 18.5 to 22.9

Overweight/obesity

Increased risk 23.0 to 27.4

High risk >27.5

Total >23.0


Table 3: Exclusion criteria for child anthropometric indices for the CMNS2005

All maternal BMI data were within the recommended limits of 12 and 40, andtherefore no maternal anthropometry data were excluded.

2.8 Technical oversight

A Technical Committee was formed to officially approve the survey design, toreview the findings of the draft report and provide comments for finalization ofthe report. The Technical Committee was assisted by a Technical Working Group,which guided the data analysis and report preparation. A list of members of theTechnical Committee and Technical Working Group is provided in Annex 8.

10

Indices Mean Exclusion range

HAZ -1.75 < -5.75 and > +2.25

WAZ -1.66 < -5.66 and > +2.34

WHZ - 0.94 < -4.00 and > +5.00


11

Rou

nd

Num

ber

of P

SUs

Num

ber

of h

ouse

hold

sC

over

-ag

e(%

)

Non

-re

spo-

nse

(%)

Num

ber

of h

ouse

hold

s no

t int

ervi

ewed

and

reas

ons

why

Num

ber

of

mot

hers

mea

sure

d

Num

ber

of c

hild

ren

mea

sure

d

Rur

alU

rban

Tota

lTo

tal

No

surv

eych

ild

Surv

eych

ildpr

esen

t

Inte

rvi

ewed

Chi

ldno

t at

hom

eTr

ans-

Ill-n

ess

Oth

ers

Tota

lG

irls

Boy

sTo

tal

128

1846

920

511

409

343

83.9

16.1

533

37

6635

421

921

443

3

228

1442

840

463

377

331

87.8

12.2

441

-1

4634

618

522

841

3

323

2245

900

521

379

343

90.5

9.5

321

12

3635

721

420

742

1

430

1040

800

441

359

314

87.5

12.5

371

16

4532

317

920

538

4

531

1647

940

554

386

343

88.9

11.1

384

-1

4335

319

621

741

3

627

1340

800

475

325

291

89.5

10.5

312

-1

3430

016

818

935

7

732

1648

960

557

403

367

91.1

8.9

314

1-

3637

521

424

545

9

832

1547

940

510

430

376

87.4

12.6

493

11

5439

023

124

147

2

925

2348

960

571

389

361

92.8

7.2

242

-2

2837

822

721

844

5

Tota

l25

614

740

380

6046

0334

5730

6988

.811

.233

921

721

388

3176

1833

1964

3797

Tabl

e 4:

Num

ber

of P

SUs,

hou

seho

lds

and

child

ren

enum

erat

ed b

y ro

und

Tabl

e 5:

Num

ber

of c

hild

ren

surv

eyed

by

sex,

age

and

are

a of

res

iden

ce

Age

(mon

ths)

Rur

alU

rban

Nat

iona

lG

irls

Boy

sTo

tal

Girl

sB

oys

Tota

lG

irls

Boy

sTo

tal

No.

%N

o.%

No.

%N

o.%

No.

%N

o.%

No.

%N

o.%

No.

%

0-11

220

18.0

226

17.4

446

17.7

123

20.2

113

17.0

236

18.5

343

18.7

339

17.3

682

18.0

12-2

324

119

.726

820

.650

920

.210

517

.213

420

.223

918

.834

618

.940

220

.574

819

.7

24-3

526

521

.724

919

.251

420

.414

123

.212

318

.526

420

.740

622

.137

218

.977

820

.5

36-4

726

021

.227

821

.453

821

.311

819

.414

421

.726

220

.637

820

.642

221

.580

021

.1

48-5

923

819

.427

921

.551

720

.512

220

.015

022

.627

221

.436

019

.642

921

.878

920

.8

Tota

l12

2410

0.0

1300

100.

025

2410

0.0

609

100.

066

410

0.0

1273

100.

018

3310

0.0

1964

100.

037

9710

0.0


2.9 Coverage of the sample

Table 4 shows the actual number of PSUs, households and children enumeratedby round. A total of 3069 households participated in the survey, of which 35%were urban and 65% were urban. Data and anthropometric measurements weretaken from 3050 mothers and 3797 children.

Table 5 shows the distribution of children by age and sex. The percentage ofchildren aged <12 months was smaller than the other age groups, which mayreflect oversampling of older children or a tendency to round children aged 10-11months up to 12 months. Boys outnumber girls with a sex ratio of 107:100, whichis similar to the sex ratio of the 2001 National Census (106.6:100).

Table 6 shows that 3.8% of mothers were adolescents (<20 years) and 5.5% wereat least 40 years of age.

Table 6: Number of mothers surveyed by age and area of residence

2.10 Comparison with methods of previous CNSsurveys

There were a few changes made to methods for the CMNS 2005 compared withprevious CNS surveys. Previously, the CNS survey population included childrenaged 6-71 months. However almost all other national and international surveys ofchild nutritional status include children aged <6 months and have an upper agelimit of 59 months. This is consistent with nutritional research which has shown

12

Age (years)Rural Urban Total

No. % No. % No. %

<20 77 3.8 38 3.6 115 3.8

20-24 527 26.3 310 29.6 837 27.4

25-29 610 30.5 320 30.5 930 30.5

30-34 421 21.0 198 18.9 619 20.3

35-39 247 12.3 134 12.8 381 12.5

40+ 119 5.9 49 4.7 168 5.5

Total 2001 100.0 1049 100.0 3050 100.0


that infants and young children aged <24 months are at greatest risk ofundernutrition and its consequences in later life. Therefore the target age groupfor children was changed to 0-59 months for the CMNS. A change of the targetgroup from 6-71 months to 0-59 months does not rule out an examination oftrends in CNS data since 1992, as statistics on children aged 6-59 months from allsurveys can be compared.

In addition, the nutritional status of mothers of children aged 0-59 months wasincluded in the CMNS for the first time. A mother's nutritional status is animportant indicator of her own health, well-being and status in society.Undernourished mothers are physically weak, and are at greater risk of dying,especially during childbirth. Mother's nutritional status is also a crucialdeterminant of child nutritional status. Mothers who are malnourished before orduring pregnancy are more likely to deliver low birth weight infants, who growpoorly during childhood, do less well at school and have less productive workinglives than well-nourished infants.

13


14


Chapter 3: Household characteristics

3.1 Socio-demography and socioeconomic status

The mean household size of the study population was 5.8 persons (Table 7),which is higher than the figures quoted in SVRS 2003 (4.9 persons)xvi, BDHS 2004(5.0 persons)xvii and HIES 2005 (4.8 persons)xviii.The reason for the higherhousehold size in the CMNS is likely to be the fact that it surveyed householdsonly with children aged <5 years, and hence excluded households with nochildren and those with older children who had siblings that had left home. Thehigher mean household size is consistent with the three previous Child NutritionSurveys (6.2 persons in 1992, 6.0 persons in 1996 and 5.9 persons in 2000).

The mean monthly household income was Taka 6688. Over 95% of householdheads were male, 57% were illiterate or had never attended school and the biggestoccupation group was agriculture (40%). The majority of houses had roofs madeof corrugated iron (85%) and floors made of earth (84%). About 60% ofhouseholds relied on kerosene as their major source of light and the remainderhad access to electricity.

There remain large disparities between urban and rural households in illiteracy(61% of rural household heads were illiterate or had never attended school,compared with 41% of their urban counterparts), house flooring material (91% ofrural homes had earth floors, compared with only 55% of urban homes) andaccess to electric lighting (30% in rural areas and 78% in urban areas).

15


Table 7: Household socio-demography and socio-economic status

16

Rural Urban National

Mean household size (persons) 5.8 5.7 5.8

Household (HH)size (%)

<4 persons 8.0 9.5 8.3

4 - 5 persons 42.1 45.3 42.8

6 - 7 persons 27.9 27.0 27.8

8 + persons 22.0 18.1 21.2

Mean monthly HH income (Taka) 5,905 9,687 6,688

Sex of HH head (%)Female 4.5 4.9 4.6

Male 95.5 95.1 95.4

Educational status ofhead of HH (%)

Illiterate/never attended school 61.0 41.0 56.9

Passed class I-V 18.1 17.8 18.0

Passed class VI-IX 12.0 18.5 13.3

Passed SSC/HSC & above 10.0 22.7 11.8

Main occupation of HHhead (%)

Business 14.8 27.5 17.3

Service and professional 27.8 49.3 32.1

Agriculture, animal husbandry,forestry, fisheries 47.3 12.5 40.3

Other 10.3 10.8 10.3

Roof materials of livingroom of the HH head(%)

Concrete 1.8 14.2 4.3

Corrugated iron 85.1 81.7 84.5

Others 13.0 4.1 11.2

Wall materials of livingroom of the HH head(%)

Brick 9.2 39.7 15.4

Tin 35.3 31.3 34.5

Others 55.5 28.9 50.1

Floor materials of livingroom of the HH head(%)

Concrete 6.7 43.1 14.1

Earth 91.3 55.5 84.1

Others 2.0 1.4 1.9

Main source of light(%)

Electricity 30.1 78.1 39.8

Kerosene 69.7 21.8 60.1

Solar Power 0.1 0.1 0.1


3.2 Household food security

The per capita energy consumption in the survey population was 2,077 kcal/day,and was 65 kcal/day higher in rural areas than urban areas (Table 8). About 47%of the population had homestead vegetable gardens (52% in rural areas and 28%urban areas); 85% of these families consumed the produce from the gardenswhilst the remainder both consumed and sold the produce. Over 25% of familieshave taken a loan to buy food in the previous three months, an indicator of foodinsecurity that was higher in rural households (27%) than urban households(20%). When household salt was tested for iodine, 83% was found to be iodised,which is similar to the findings of the 2006 BBS/UNICEF Multiple IndicatorCluster Survey (84%). However, only 80% of rural households use iodised salt,compared with 94% of urban households.

Table 8: Household food security

3.3 Household health environment and access tohealth services

Only 18% of households had a sanitary toilet (defined as having either a flushingmechanism or a water seal) and 94% of household had access to tube welldrinking water (Table 9). The mean distance to the nearest health facility was 4.2km (rural 4.8 km, urban 1.8 km) and the mean cost of transport to the nearesthealth facility was Taka 23 (rural Taka 26 and urban Taka 15).

17


Daily per capita consumption (kcal) 2,090 2,025 2,077

Homestead vegetable garden (%) 52.2 28.4 47.2

What do you do with thevegetable grown in yourhomestead (%)

Consume by members ofhousehold 84.1 93.1 85.3

Consumed and sold 15.5 6.9 14.4

Taken loan to buy food during the last threemonths (%) 27.2 19.7 25.6

Household salt is iodized (%) 80.2 93.5 83.0


Table 9: Household health environment and access to health services

3.4 Monsoon floods in 2004

Serious Monsoon flooding in 2004 affected 36 million people in 39 out of the 64districts in the country. The floodwaters inundated houses, roads, farmland andgardens, schools and health clinics, and isolated communities from essentialhealth services, market centres and schools. The flood destroyed cash andsubsistence crops and household gardens, and left the hundreds of thousands ofhouseholds without homes, jobs and income for many months. They caused ascarcity of proper sanitation facilities and safe drinking water, submerging some2 million tube-wells. These impacts placed an entire generation of children,including the unborn children of pregnant women, at increased risk of poorgrowth, health and development.

Table 10 shows that a considerable proportion of households, particularly ruralhouseholds, were affected by the floods in 2004. One third of households sufferedcrop losses, and 29% of houses were damaged or destroyed. Over 2% householdmembers fell sick and 0.1% household members died. The latter number impliesa death toll of around 140,000 in the whole country and may reflect amisunderstanding about the question; people may have reported all deaths,rather than deaths due only to the flood.

18


Type of toilet facility (%)

Flush/sanitary/water seal 13.4 37.3 18.2

Pit latrine 38.0 41.5 38.7

Fixed kutcha 25.8 12.9 23.2

Hanging latrine beside water/open space/no fixed space 22.8 8.3 19.9

Main source of drinkingwater (%)

Tube well 96.8 82.0 93.9

Tap 0.4 17.0 3.8

Other 2.8 1.0 2.4

Distance to nearest healthfacility (km) (%)

<1 8.5 23.6 11.6

1-4 52.8 69.4 56.1

5-9 23.9 6.4 20.4

10+ 14.8 0.6 11.9

Mean distance to nearest health facility (km) 4.8 1.8 4.2

Mean transport cost to go to nearest health centre (Taka) 26 15 23


Table 10: Impact of the 2004 Monsoon floods on households

19

Rural (%) Urban (%) National (%)

Crops damaged destroyed 38.7 12.4 33.2

House damaged/destroyed 31.0 19.6 28.6

Latrine damaged/destroyed 16.9 13.7 16.2

Fishery pond/farm destroyed 10.2 4.6 9.0

Source of drinking water damaged/destroyed 8.1 7.3 7.9

Lost employment /lost source of income 4.9 4.6 4.8

Food stocks damaged/destroyed 3.9 1.6 3.4

Livestock died 3.5 2.0 3.2

Household members fell sick 2.6 2.0 2.4

Household members died 0.1 0.1 0.1

Other 4.7 3.3 4.4


20


Chapter 4: Characteristics of mothers

Table 11 provides the socio-demographic characteristics of the surveyrespondents, who were all mothers or caregivers of children aged <5 years. Themean age of the mothers was 28 years, 98% were currently married, 47% wereilliterate or had never attended school and 97% were housewives. About 8% ofmothers had earned money in the preceding three months, the most commonsource of income being livestock rearing and gardening (28%). About 30% ofmothers who had earned income in the preceding three months managed to savesome money.

Table 11: Mother's background characteristics

21


Mother's mean age in years 28.2 27.8 28.1

Mother's age inyears (%)

<18 1.7 2.1 1.8

19-24 28.7 30.4 29.0

25-29 30.3 30.8 30.4

30-34 21.0 19.6 20.7

35+ 18.2 17.2 18.0

Marital status (%)Currently married 98.7 96.8 98.3

Never married, widowed divorceddeserted 1.3 3.2 1.7

Mother's educationstatus (%)

Illiterate/never attended school 50.7 33.0 47.0

Passed class I-V 23.2 21.8 22.9

Passed class VI-IX 18.8 26.8 20.5

Passed SSC/HSC & above 7.2 18.4 9.6

Mother'soccupation (%)

Housewife 97.5 95.4 97.1

Blue collar 1.0 0.8 1.0

White collar 1.5 3.8 2.0

Mother earned money in the last 3 months (%) 7.2 11.4 8.1

How mother earnedmoney in last 3months (%)

Business/service 16.0 21.8 17.7

House maid 8.5 11.6 9.4

Livestock/gardening 33.3 13.8 27.5

Hand work 15.4 23.4 17.7

Others 27.0 29.4 27.7


Table 12 shows that 97% of mothers were breastfeeding at the time of the survey,4% were pregnant, 3% were pregnant and breastfeeding and 2% were neitherpregnant or breastfeeding. Almost 70% off mothers had first married before theage of 18 years and 21% between the ages of 18 and 19 years. Almost three-quarters (72%) of mothers had their first pregnancy before the age of 20 years.Over half of mothers (54%) had 1-2 live births, and 16% had at least 5 live births.

Table 12: Reproductive health of mothers

22


How mother spentthe money sheearned in last 3months (%)

Spend on children 33.1 28.9 31.8

Spend on herself 18.1 15.1 17.2

Other 48.9 56.0 50.9

Mother save some money from income during the last 3months (%) 26.7 37.7 29.9

Rural(%)

Urban(%)

National(%)

Mother's physiologicalstatus

Not pregnant or breastfeeding 1.9 2.4 2.0

Pregnant 3.9 2.9 3.7

Breastfeeding 97.1 96.7 97.1

Pregnant and breastfeeding 3.2 2.3 3.0

Age in years at firstmarriage in years

<18 71.4 62.0 69.4

18 - 19 19.5 25.2 20.7

20+ 9.2 12.8 9.9

Mother's age at firstpregnancy in years

<18 41.8 35.0 40.4

18 -19 32.6 32.0 32.5

20+ 25.6 33.1 27.1

Number of live births

1-2 51.9 61.5 53.9

3-4 31.3 28.1 30.6

5+ 16.8 10.4 15.5


Table 13 provides data on mother's participation in decisions on the use ofhousehold resources. Only 5-7% of mothers were able take decisions alone onhow much money the household spends on food, what food is bought for thehousehold, and whether the mother or her child attends a health facility; a further33-42% could take these decisions together with other household members, andthe remainder were unable to participate in these decisions at all. Most mothers(78%) were able to decide, either alone or with other household members, whatfood to cook for the household.

Table 13: Mother's participation in decisions on use of household resources

23

Who makes the decisions on: Rural(%)

Urban(%)

National(%)

How much moneythe householdspends on food

Mother only 5.2 6.4 5.4

Husband only 47.8 44.3 47.1

Mother and other householdmember(s) jointly 32.0 34.8 32.6

Other household member(s) 14.9 14.6 14.9

What food is boughtfor the household





What food is cookedfor the household

Mother only 49.5 56.7 50.9




Whether motherattends a healthfacility for her ownhealth needs





Whether motherschild goes to ahealth facility for his-her health needs






24


Chapter 5: Knowledge and practices onchild and maternal care

5.1 Child care

5.1.1 Infant and young child feeding

Infant and young child feeding practices are key to the survival, health, growthand development of children. Infants should be breastfed immediately afterdelivery (within one hour); given no prelacteal feeds; exclusively breastfed for thefirst six months of life; and given complementary foods from six months of agewith continued breastfeeding up to 2 years of life.

Table 14 shows that the mothers' knowledge on breastfeeding andcomplementary practices was poor. Only 33% of mothers knew that a childshould be exclusively breastfed for six months, 42% gave incorrect answers, and25% did not know. Only 40% of mothers knew that a child should begincomplementary feeding at 6 months of age, 40% gave incorrect answers and 20%did not know. Only 13% of mothers said that a child should be given family foodfrom six months of age, over 70% from seven months or later, and 2% below sixmonths of age.

25


Table 14: Mother's knowledge on breastfeeding and complementaryfeeding practices

Table 15 provides information on reported breastfeeding and complementaryfeeding practices. Only 14% of newborns were weighed within 3 days of delivery.Colostrum was given to almost 87% of babies, which is a remarkableachievement; however, 62% received prelacteal foods. Less than one-half (48%) ofinfants were breastfed within one hour of delivery; the percentage was higher inrural areas (49%) than urban areas (43%). About 20% of infants were breastfedafter one day, and 32% between 1-24 hours of delivery.

Only 58% of children aged <6 months were exclusively breastfed; there was nosignificant difference between rural and urban areas. The exclusive breastfeedingrate (EBR) declined from 81% in infants aged <1 month to 41% in infant aged 5months. This data should be treated with caution as the questions used todetermine EBR did not include a question on whether the child had taken waterin the last 24 hours.

26

Rural(%)

Urban(%)

National(%)

Number of months a childshould be exclusively breastfed

<4 4.5 4.4 4.5

4-5 34.0 37.4 34.7

6 30.9 38.9 32.6

7+ 3.2 2.6 3.1

Don't know 27.3 16.7 25.1

At what month of age a childshould be given complementaryfood

<4 1.5 1.8 1.6

4-5 12.2 8.8 11.5

6 38.8 46.8 40.4

7+ 25.9 30.8 26.9

Don't know 21.5 11.9 19.5

At what month of age a childshould be given family food

<4 0.2 0.0 0.2

4-5 1.7 1.2 1.6

6 12.7 14.4 13.1

7+ 69.2 75.6 70.6

Don't know 16.1 8.8 14.6


About 71% of infants were given timely complementary feeding at 6-9 months ofage. The mean age at which family food was given was 8 months. Almost all(98%) of children were breastfed at 12-15 months of age, and 89% were stillbreastfed at 20-23 months of age. There was no significant difference betweenrural and urban areas in any of these indicators.

About 28% of children aged 0-23 months had been bottle fed at some point intheir lives; the percentage was significantly higher in urban areas (39%) than ruralareas (25%). Over half (58%) of children aged 0-23 months had been give animalmilk, and again, the percentage was significantly higher in urban areas (67%) thanrural areas (56%).

Table 15: Mother's reported breastfeeding and complementary feedingpractices

27


Baby weighed within 3 days of delivery (%) 10.3 28.3 13.8

Colostrum given (%) 87.7 83.4 86.9

Prelacteal feed given (%) 63.4 56.5 62.1

Initiation of breastfeeding in hours (%)

<1 49.3 43.2 48.1

1-24 29.8 39.4 31.7

>24 20.3 16.4 19.5

Never breastfed 0.1 0.2 0.1

Do not know 0.5 0.8 0.6

Exclusively breastfed at different agesin months (%)

<1 78.2 93.1 80.8

1 83.1 61.5 79.4

2 57.5 63.0 58.5

3 56.6 37.3 53.7

4 41.6 51.9 44.8

5 40.7 42.5 41.0

<6 59.1 55.3 58.4

Timely complementary feeding (%)

6 50.7 52.6 51.1

7 64.3 68.5 65.4

8 90.4 76.7 88.3

9 82.9 80.1 82.5

6-9 71.6 66.6 70.6


Figure 1 shows the key IYCF indicators that are being used to track MDG 4 for childsurvival by area of residence. There was no significant difference in these indicatorsin rural and urban areas, except for initiation of breastfeeding within 1 hour.

Figure 1: Infant and young child feeding indicators tracking child survival(MDG 4) by area of residence

28

49

59

72

88

43

55

67

93

48

58

71

89

0

20

40

60

80

100

Breaseeding

initiated within

1 hr of birth

Exclusive

breastfeeding

<6 months

Complementary

feeding at

6-9 months

Continued

breastfeeding at

20-23 months

Pre

vale

nce (

%)



Child currently breastfed by age of childin months (%)

0 - 11 98.9 98.7 98.9

12 - 15 98.2 96.5 98.0

20 - 23 87.8 92.8 88.8

Total 96.6 97.1 96.7

Ever bottle-fed by age in months (%)

0 - 5 39.7 49.8 40.3

6 - 11 29.7 43.0 32.3

12 - 17 21.2 40.0 24.4

18 - 23 24.7 34.0 26.6

Total 25.2 38.8 27.6

Ever given cow's/goat's/powder milk byage in months (%)

0 - 5 65.0 49.8 64.2

6 - 11 52.8 60.9 54.4

12 - 17 53.8 74.9 57.4

18 - 23 61.4 64.3 62.0

Total 56.4 67.1 58.4


5.1.2 Care of child during illness

Diarrhea is one of the most common childhood illnesses in Bangladesh andcontributes to malnutrition. Almost 80% of households know how to prepare salt-molasses solution, which is used to treat diarrhea (Table 16).

About a third of children had ever had diarrhea and 2.5% had diarrhea in the last15 days. Of these children with diarrhea, 84% were given oral rehydrationsolution (ORS), 28% salt-molasses or rice saline, 56% breast milk, 66% water, 20%some other liquid and 81% medicine. Only 50% of children with diarrhea weregiven more liquids than normal during diarrhea, and 35% were given less. Only17% of children with diarrhea were given more good than normal, and 67% weregiven less.

Table 16: Reported caring practices of child with diarrhoea

5.1.3 Vitamin A supplementation and deworming

Table 17 shows that 93% of infants were given a vitamin A capsule (VAC) with themeasles vaccine at 9-11 months of age. During the most recent National VitaminA Plus Campaign, 93% of children aged 12-59 months received a VAC and 87% ofchildren aged 24-59 months received a deworming tablet (albendazole).

29

Rural(%)

Urban(%)

National(%)

Knowledge to prepare salt-molasses solution 75.7 89.5 78.5

Liquids/medicine given tochildren with diarrhea

ORS 83.0 89.0 84.3

Salt-molasses or rice saline 25.0 40.4 28.4

Breast milk 55.8 56.9 56.0

Water 65.6 67.6 66.1

Other liquid 19.8 19.3 19.7

Medicine 82.5 77.6 81.4

Amount of liquid given tochild with diarrheacompared to normal

Less 34.7 35.2 34.8

Same 15.3 13.1 14.8

More 49.2 50.6 49.5

Do not know 0.8 1.1 0.8

Amount of food given tochild with diarrheacompared to normal

Less 66.2 69.7 66.9

Same 15.5 13.6 15.1

More 17.3 16.4 17.1

Do not know 1.0 0.3 0.9


Table 17: Coverage of vitamin A supplementation and deworming in children

5.2 Maternal care

Mothers were asked about the health care they received during the pregnancy ofthe child aged less than 5 years. Approximately one-fifth (21%) of mothers did notreceive any antenatal care (ANC) during their previous pregnancy, 45% received1-2 ANC checks and the remaining (34%) received 3 or more checks (Table 18). Ofmothers who received ANC, most (70%) received ANC from health careprofessionals and about 29% from Skilled Birth Attendants (SBA) or trainedTraditional Birth Attendants (TBA).

The majority of mothers (97%) received Tetanus Toxoid vaccination during thepregnancy of their child. However, 52% did not have their weight measured and57% did not take any iron tablets. Forty one percent (41%) of mothers had eatenless than usual during the pregnancy and 22% had taken less rest than usual.Most deliveries took place at home (87%), and only 25% were attended by ahealth care professional, trained SBA or TBA. Only 18% of mothers had beengiven a vitamin A capsule within six weeks of delivery.

30

Rural(%)

Urban(%)

National(%)

Vitamin A Capsule with measles vaccine 92.8 92.2 92.7

Vitamin A Capsule during the previous Vitamin A+Campaign (12-59 months) 92.2 93.9 92.6

Deworming tablet during the previous Vitamin A+Campaign (24-59 months) 87.4 84.9 86.9


Table 18: Maternal caring practices during pregnancy, delivery andpostpartum

a Includes only mothers who received any ANCb FWV=Family Welfare Visitor, FWA=Family Welfare Assistant, MA=Medical Assistant,

HA=Health Assistant, SBA=Skilled Birth Attendant, TBA=Traditional Birth Attendant

31

Rural(%)

Urban(%)

National(%)

Number ofantenatal check-ups

0 22.8 12.1 20.6

1-2 46.4 37.7 44.6

3+ 30.5 49.9 34.5

Don't know 0.3 0.3 0.3

ANC providera,b

Doctor/Nurse/FWV/FWA/MA/HA 66.3 83.0 70.2

Trained SBA/TBA 29.1 16.4 26.2

Untrained TBA/unqualified medicalpractitioner 3.1 0.5 2.5

Others 1.4 0.1 1.1

Taken Tetanus Toxoid during pregnancy 97.7 96.7 97.4

Number of timesweight waschecked duringpregnancy

0 57.2 33.5 51.8

1-2 26.1 30.9 27.2

3 7.0 8.1 7.2

4+ 9.8 27.5 13.8

Number ofmonths took irontablets duringpregnancy

0 60.4 43.6 56.9

1-2 20.4 23.2 21.0

3 8.6 12.8 9.5

4+ 10.6 20.4 12.6

Food eaten inpregnancycompared withbefore

Less 40.4 40.6 40.5

Same 46.7 40.8 45.5

More 12.9 18.6 14.0

Rest taken inpregnancycompared withbefore

Less 22.2 19.9 21.7

Same 59.4 52.4 57.9

More 18.4 27.7 20.4

Place of delivery

Health facility 8.5 28.8 12.6

Home delivery 91.3 71.3 87.2

Other 0.2 0.0 0.2


a Includes only mothers who received any ANCb FWV=Family Welfare Visitor, FWA=Family Welfare Assistant, MA=Medical Assistant,

HA=Health Assistant, SBA=Skilled Birth Attendant, TBA=Traditional Birth Attendant

32

Rural(%)

Urban(%)

National(%)

Birth attendanta,b

Doctor/Nurse/FWV/HA 9.3 31.8 13.9

Trained SBA/TBA 9.0 18.9 11.0

Untrained TBA 19.9 15.1 18.9

Neighbour/relatives/others 61.8 34.3 56.1

Taken vitamin A capsule within 6 weeks of delivery 16.5 24.4 18.1


Chapter 6: Child nutrition status

6.1 National prevalence

The mean and standard deviation of weight, height, MUAC, and anthropometricindices by sex and area of residence is provided in Table 19. Mean weight-for-ageZ-score (WAZWHO) was -1.70; mean height-for-age Z-score (HAZWHO) was -1.79;the mean weight-for-height Z-score (WHZWHO) was -0.96; the mean BMI-for-ageZ-score (BAZWHO) was -0.77; and the mean MUAC-for-age Z-score (MUACZ) was -1.57.

Nationally, 40% of children aged <5 years were underweight, 46% were stunted,15% were wasted and 1.4% were overweight/obese (Table 20 and Figure 2).According to criteria of the World Health Organizationxix, the prevalence ofunderweight and stunting was "very high", and the prevalence of wastingindicated a "critical problem". Severe underweight, severe stunting, severe wastingand obesity were found in 11%, 19%, 3% and 0.3% of the population (Table 21).About 4% of children had a MUAC <125 mm, and 0.2% had a MUAC <110 mm.

Annex 9 provides additional analysis of the anthropometric data, including themean weight, height and MUAC by sex and age (Table A6); mean anthropometricindices by age (Table A7); distribution of malnutrition by sex and area ofresidence (Table A8); and the prevalence of severe, moderate and totalmalnutrition by sex, age and area of residence (Tables A9-A12).

Figure 2: Prevalence of underweight, stunting, wasting and overweight/obesity in children aged <5 years (WHO 2005 GRS)

33

Pre

vale

nce (

%)

Severe Moderate Total

11

19

3

2927

12

40

46

15

0.3 1.1 1.40

5

10

15

20

25

30

35

40

45

50

Underweight Stunting Wasting Overweight/obesity


34

Indi

cato

r

Rur

alU

rban

Nat

iona

l

Girl

Boy

Tota

lG

irlB

oyTo

tal

Girl

Boy

Tota

l

Mea

nSD

Mea

nSD

Mea

nSD

Mea

nSD

Mea

nSD

Mea

nSD

Mea

nSD

Mea

nSD

Mea

nSD

Age

(mo)

30.1

16.8

30.3

17.2

30.2

17.0

29.8

17.0

31.1

17.3

30.5

17.2

30.5

17.3

30.0

16.9

30.3

17.1

Wei

ght (

kg)

10.0

2.9

10.6

2.9

10.3

2.9

10.5

3.3

11.3

3.3

10.9

3.3

10.7

3.0

10.1

3.0

10.4

3.0

Hei

ght (

cm)

81.9

12.5

83.4

12.6

82.7

12.6

83.3

13.1

85.2

13.1

84.3

13.1

83.8

12.8

82.2

12.6

83.0

12.7

MU

AC

(mm

)14

111

143

1014

211

145

1314

713

146

1314

411

142

1214

31.

1

WA

ZWH

O-1

.77

1.16

-1.7

81.

08-1

.77

1.12

-1.4

11.

20-1

.39

1.22

-1.4

01.

21-1

.70

1.13

-1.7

01.

17-1

.70

1.15

HA

ZWH

O-1

.87

1.55

-1.8

81.

56-1

.87

1.55

-1.3

91.

58-1

.58

1.47

-1.4

91.

52-1

.81

1.55

-1.7

71.

56-1

.79

1.56

WH

ZWH

O-0

.96

1.26

-1.0

51.

24-1

.01

1.25

-0.8

61.

24-0

.74

1.32

-0.8

01.

29-0

.99

1.26

-0.9

41.

25-0

.96

1.26

BA

ZWH

O-0

.80

1.32

-0.8

21.

32-0

.81

1.32

-0.7

31.

27-0

.56

1.36

-0.6

41.

32-0

.76

1.33

-0.7

81.

31-0

.77

1.32

MU

AC

Z-1

.62

0.72

-1.6

30.

71-1

.63

0.71

-1.3

40.

78-1

.33

0.82

-1.3

40.

80-1

.57

0.74

-1.5

70.

74-1

.57

0.74

Tabl

e 19

:M

ean

wei

ght,

heig

ht, M

UA

C a

nd a

nthr

opom

etric

indi

ces

in c

hild

ren

aged

<5

year

s by

sex

and

area

of r

esid

ence


Table 20: Prevalence of malnutrition in children aged <5 years by sex, age,area of residence and season

*p<0.05; ***p<0.001; NS not significant

35

Characteristic Underweight (%)(WAZWHO)

Stunted (%)(HAZWHO)

Wasted (%)(WHZWHO)

Overweight (%)(BAZWHO)

Sex of childGirlBoy

39.040.3

NS

45.347.1

NS

14.514.5

NS

1.61.2NS

Age group of child(months)

0 - 56 - 1112 - 1718 - 2324 - 3536 - 4748 - 59

26.230.742.342.041.543.640.8

***

13.621.840.457.953.357.448.7

***

24.119.022.214.513.8

9.410.9

***

1.20.92.52.31.51.20.7NS

Age group of child(months)

0 - 2324 - 59

35.942.0

***

34.553.2

***

19.811.3

***

1.11.4NS

Area of residenceRuralUrban

42.229.9

***

48.835.9

***

15.112.2

NS

1.31.9NS

DivisionBarisalChittagongDhakaKhulnaRajshahiSylhet

41.639.739.635.141.140.5

NS

52.951.542.943.645.747.0

***

14.713.415.3

8.416.615.4

*

3.41.21.70.11.41.0NS

SeasonWinterSummerRainyAutumn

36.239.042.340.2

NS

49.340.848.145.8

NS

11.817.315.113.7

NS

1.70.41.71.6NS

National prevalence 39.7 46.2 14.5 1.4


Table 21: Prevalence of moderate and severe malnutrition in children aged<5 years by sex and area of residence

aModerate -3.00 to -2.01; severe <-3.00; total <-2.00

6.2 Nutritional status by sex

Figures 3-6 show the prevalence of underweight, stunting, wasting and obesity ofchildren aged <5 years by sex. There was no significant difference between girlsand boys in any of these anthropometric indices.

36

Indicatora Rural (%) Urban (%) National (%)

Girl Boy Total Girl Boy Total Girl Boy Total

Underweight(WAZWHO)

Moderate 28.3 32.3 30.3 22.6 23.2 22.9 27.1 30.4 28.8

Severe 13.1 10.7 11.9 7.1 6.9 7.0 11.9 9.9 10.9

Total 41.3 43.0 42.2 29.7 30.1 29.9 39.0 40.3 39.7

Stunting(HAZWHO)

Moderate 28.2 28.8 28.5 20.9 23.2 22.1 26.8 27.7 27.2

Severe 20.0 20.6 20.3 12.8 14.7 13.8 18.6 19.4 19.0

Total 48.2 49.4 48.8 33.7 38.0 35.9 45.3 47.1 46.2

Wasting(WHZWHO)

Moderate 12.2 11.8 12.0 11.3 8.5 9.8 12.0 11.1 11.6

Severe 2.6 3.5 3.0 2.0 2.7 2.4 2.5 3.3 2.9

Total 14.8 15.3 15.1 13.3 11.2 12.2 14.5 14.5 14.5

Obesity(BAZWHO)

Moderate 1.3 0.7 1.0 1.1 1.5 1.3 1.2 0.9 1.1

Severe 0.4 0.3 0.3 0.2 0.4 0.3 0.3 0.3 0.3

Total 1.6 1.0 1.3 1.4 1.9 1.6 1.6 1.2 1.4

MUACZ

Moderate 25.5 27.8 26.7 16.5 17.2 16.9 23.8 25.6 24.7

Severe 2.9 2.3 2.6 1.6 1.3 1.4 2.7 2.1 2.4

Total 28.4 30.1 29.3 18.1 18.5 19.3 26.5 27.7 27.1

MUAC <125 mm 6.2 3.4 4.8 2.7 2.2 2.4 5.6 3.2 4.3

MUAC <110 mm 0.3 0.2 0.2 0.3 0.0 0.1 0.3 0.1 0.2


Figure 3: Prevalence of underweight (WAZWHO) in children aged <5 years bysex

Figure 4: Prevalence of stunting (HAZWHO) in children aged <5 years by sex

37

Pre

vale

nce (

%)

Girl Boy


28

0

10

20

30

40

50

19

27

45

19

47

Pre

vale

nce (

%)

Girl Boy

12

27

39

10

30

40

0

10

20

30

40

50



Figure 5: Prevalence of wasting (WHZWHO) in children aged <5 years by sex

Figure 6: Prevalence of overweight/obesity (BAZWHO) in children aged <5years by sex

38

Pre

vale

nce (

%)

Girl Boy


2.5

12.0

14.5

3.3

11.1

14.5

0

2

4

6

8

10

12

14

16

Pre

vale

nce (

%)

Girl Boy

Severe (obesity) Moderate (overweight) Total

0.3

1.2

1.6

0.3

0.9

1.2

0.0

0.5

1.0

1.5

2.0


6.3 Nutritional status by age

Figures 7-10 show the prevalence of underweight, stunting, wasting and obesityof children aged <5 years by age group. The prevalence of underweight increaseddramatically between 6-11 months of age and stabilized from 12 months onwards.The prevalence of stunting increased up to the end of the second year, andstabilized thereafter, decreasing slightly in the fourth year of life. The prevalenceof wasting was highest in the first six months, and decreased gradually thereafterup to the fifth year of life. These patterns differ from previous CNS findingsbecause of the use of the new WHO 2005 GRS, which more accurately reflects age-specific prevalence of undernutrition in children. The prevalence of obesity washighest in the second year of life, and fell over the subsequent years, however thedifferences between the age groups were not significant.

Figure 7: Prevalence of underweight (WAZWHO) in children aged <5 years byage group

39

Pre

vale

nce (

%)


8 79

1214

1210

18

23

3330

28

32 31

26

31

42 42 4244

41

0

10

20

30

40

50

60

0 - 5 6 -11 12-17 18 - 23 24 - 35 36 - 47 48 - 59

Age of child (months)


Figure 8: Prevalence of stunting (HAZWHO) in children aged <5 years by agegroup

Figure 9: Prevalence of wasting (WHZWHO) in children aged <5 years by agegroup

40

Pre

vale

nce (

%)

0 - 5 6 -11 12-17 18 - 23 24 - 35 36 - 47 48 - 59


6 6

15

2823 23

20

8

16

2630 30

34

29

14

22

40

5853

57

49

0

10

20

30

40

50

60

70Severe Moderate Total

Pre

vale

nce (

%)


0 - 5 6 -11 12-17 18 - 23 24 - 35 36 - 47 48 - 59


8

56

3 32

1

1614

16

12 11

8

10

24

19

22

15 14

911

0

5

10

15

20

25

30


Figure 10: Prevalence of overweight/obesity (BAZWHO) in children aged <5years by age group

6.4 Nutritional status by area of residence

In comparison with the urban population, the rural population was significantlymore underweight (42% vs. 30%) and more stunted (49% vs. 36%); there was nosignificant difference in wasting and overweight/obesity (Table 20 and Figure 11).

The nutritional status of children in Khulna Division was comparatively betterthan other divisions (Table 22). These children had the lowest prevalence ofunderweight (35%), the lowest prevalence of wasting (8%), and the second lowestprevalence of stunting (44%). Meanwhile, children in Barisal Division faredworst; these children had the highest prevalence of underweight (42%) and thehighest prevalence of stunting (53%). Table 22 provides further information onrural-urban differences in the prevalence of malnutrition in these divisions.Future CMNS should include sufficient sampling from both urban slum and non-slum areas to enable comparisons of these areas to be made.

41

Pre

vale

nce (

%)

0 - 5 6 -11 12-17 18 - 23 24 - 35 36 - 47 48 - 59


1.2

0.9

2.52.3

1.2

1.5

0.7

0.0

0.5

1.0

1.5

2.0

2.5

3.0


Figure 11: Prevalence of underweight, stunting, wasting and obesity inchildren aged <5 years by area of residence (WHO 2005 GRS)

Table 22: Prevalence of malnutrition in children aged <5 years by divisionand area of residence.

42

Barisal(%)

Chittagong(%)

Dhaka(%)

Khulna(%)

Rajshahi(%)

Sylhet(%)

National(%)

Underweight(WAZWHO<-2)

Rural 41.5 41.0 45.3 36.4 42.3 42.4 42.2

Urban 42.5 35.0 26.4 28.8 33.0 20.4 29.9

Total 41.6 39.7 39.6 35.1 41.1 40.5 39.7

Stunted(HAZWHO<-2)

Rural 52.7 54.1 47.5 45.0 46.8 49.2 48.8

Urban 54.0 41.5 32.1 36.5 38.0 24.1 35.9

Total 52.9 51.5 42.9 43.6 45.7 47.0 46.2

Wasted(WHZWHO<-2)

Rural 14.9 13.5 17.0 7.6 17.0 16.2 15.1

Urban 13.8 12.8 11.3 12.8 14.3 7.4 12.2

Total 14.7 13.4 15.3 8.4 16.6 15.4 14.5

Overweight(BAZWHO>2)

Rural 3.7 1.0 1.6 0.0 1.5 0.5 1.3

Urban 1.1 1.7 1.9 0.6 0.7 5.6 1.6

Total 3.4 1.2 1.7 0.1 1.4 1.0 1.4

Pre

vale

nce (

%) 42

49

15

30

36

12

40

46

15

1.3 1.6 1.40

10

20

30

40

50

60

70

Rural Urban Total

Underweight Stunting Wasting Overweight/

obesity


Table 20 and Figure 12 show the prevalence of malnutrition by season. During theSummer months, the prevalence of stunting was lowest and the prevalence ofwasting was highest; however, none of the differences between the seasons weresignificant.

6.5 Nutritional status by season

Table 20 and Figure 12 show the prevalence of malnutrition by season. During theSummer months, the prevalence of stunting was lowest and the prevalence ofwasting was highest; however, none of the differences between the seasons weresignificant.

Figure 12: Prevalence of underweight, stunting, wasting and obesity inchildren aged <5 years by season (WHO 2005 GRS)

6.6 Nutritional status by recent health status

Diarrhea in the previous 2 weeks was not associated with nutritional status inchildren (Table 23). However, fever and cough (acute respiratory infection) wasassociated with significantly higher underweight and wasting.

43

Pre

vale

nce (

%)

Winter

Summer

Rainy

Autumn

Underweight Stunting Wasting Overweight/

obesity

36

49

12

3941

17

42

48

15

40

46

14

1.70.41.71.6

0

10

20

30

40

50

60


Table 23: Prevalence of malnutrition in children aged <5 years by recenthealth status

6.7 Nutritional status by maternal characteristics

Table 24 shows the nutritional status of children by maternal characteristics. Theprevalence of underweight, stunting and wasting significantly decreased with anincrease in the education status of mothers. Children of older mothers weresignificantly more underweight than children of younger mothers, but there wasno relationship between maternal age and stunting, wasting or overweight.Children of mothers who worked outside the home were less likely to be wastedthan children whose mothers were housewives. There was a direct relationshipbetween the nutritional status of children and their mothers: children weresignificantly more likely to be underweight, stunted, wasted and less likely to beoverweight if their mothers had CED, than if their mothers were of normal BMIor overweight.

44

Disease in the previous2 weeks

Underweight (%)(WAZWHO)

Stunted (%)(HAZWHO)

Wasted (%)(WHZWHO)


DiarrheaYesNo

46.139.6

NS

46.346.2

NS

17.314.4

NS

1.41.4NS

Fever and coughYesNo

42.938.7

*

44.846.7

NS

20.112.7

***

0.91.5NS



Table 24: Prevalence of malnutrition in children aged <5 years by maternalcharacteristics

* p<0.05; ** p<0.01; *** p<0.001; NS not significant.a National level prevalence values are slightly different to those in Table 20 because the analysis

excludes households where data were not obtained from the biological mother of the child.

6.8 Other associations with nutritional status

Child underweight, stunting, and wasting showed a predictable association withwealth quintile (Table 25): all three indices significantly decreased with increasein wealth quintile, and there was almost a two-fold difference in prevalencebetween the poorest and richest quintile. Similarly, the prevalence of all threeindicators decreased with an increase in household land ownership, income andexpenditure. Children in households with cleaner sources of water and morehygienic latrines were less likely to be underweight, stunted and wasted.Overweight increased with wealth quintiles and with other indicators ofhousehold socio-economic status, but the trend was not significant.

45

Underweight (%)(WAZWHO)

Stunted (%)(HAZWHO)

Wasted (%)(WHZWHO)


Mother's education status Illiterate/never attended schoolPassed class I-VPassed class VI-IX

Passed SSC/HSC & above

46.8

38.833.021.4

***

52.4

45.541.524.7

***

17.3

14.110.9

9.2***

0.7

2.11.32.1

*

Mother's age in years19-2425-29 30-34 35+

37.539.140.645.1

*

44.745.745.151.2

NS

13.814.416.014.0

NS

1.71.41.20.7NS

Mother's occupationHousewifeWorking (white/blue collar)

40.331.3

NS

46.246.1

NS

14.85.4

**

1.30.6NS

Mother's nutritional statusChronic energy deficiencyNormalOverweight/obesity

46.838.833.0

***

52.445.541.5

***

17.314.110.9

***

0.72.11.3

*

National prevalencea 40.0 46.2 14.5 1.3


Indicators of household food insecurity, including low per capita kilocalorieconsumption and loan for food, were associated with a higher prevalence ofunderweight, stunting and wasting. However, there was no relationship withpossession of a homestead garden. Children belonging to households affected bythe 2004 Monsoon floods were more likely to be underweight and stunted andless likely to be overweight than children in other households.

Children belonging to a household with a female household head weresignificantly less likely to be underweight that those belonging to a householdwith a male household head. The same children were less likely to be stunted andwasted, but the difference was not significant for these anthropometric indicators.

Table 25: Other associations of malnutrition in children aged <5 years

aThis question was only asked to respondents associated with agricultural activity

46


Stunted (%)(HAZWHO)

Wasted (%)(WHZWHO)


HH wealth index quintilesPoorestSecondMiddleFourthRichest

48.744.643.737.324.9

***

54.050.451.744.529.8

***

19.316.515.611.010.4

***

0.81.21.61.22.2NS

HH cultivated land (acres)a00.000.01 - 0.991.00 - 1.992.00 - 4.995.00+

42.039.636.632.529.3

**

48.347.740.634.738.5

***

15.413.614.912.912.6

NS

1.21.31.22.82.8NS

Annual HH income (Taka)<35,00035,000 - 49,99950,000 - 64,99965,000 - 79,99980,000+

42.146.040.641.432.5

***

49.351.147.048.338.4

***

15.217.815.311.512.5

*

1.21.11.01.61.9NS

Annual HH expenditure(Taka)

<35,00035,000 - 49,99950,000 - 64,99965,000 - 79,99980,000+

45.142.540.044.231.7

***

50.650.646.252.036.5

***

16.415.515.013.312.7

NS

1.11.41.30.61.9NS


* p<0.05; ** p<0.001; NS not significant.

47


Stunted (%)(HAZWHO)

Wasted (%)(WHZWHO)


Per capita kilocalorieconsumption

<1,6001,600-1,8491,850-2,1222,122+

44.440.044.635.7

***

47.549.749.342.1

**

18.914.116.312.6

**

1.11.30.71.9NS

Homestead gardenYesNo

38.640.7

NS

46.446.0

NS

13.715.2

NS

1.61.2NS

Taken loan to buy foodYesNo

44.837.9

***

50.944.5

**

17.213.5

**

1.21.5NS

Main source of drinkingwater

Tube wellTapOther

40.421.940.0

***

46.824.157.4

***

14.512.618.9

NS

1.32.53.3NS

Type of toilet facilityFlush/sanitary/water sealPit latrine Fixed kutcha Hanging latrine besidewater/ open space/nofixed space

27.438.145.447.6

***

33.746.052.151.3

***

10.713.115.819.2

***

2.41.30.91.2

NS

Affected by 2004 Monsoonfloods

YesNo

42.237.6

**

48.144.6

*

14.214.7

NS

0.91.8

*

Sex of household headMaleFemale

40.132.6

*

46.345.4

NS

14.710.1

NS

1.41.8NS



6.9 Comparison of WHO 2005 GRS and NCHS1977 GRS

Figure 13 compares the estimates of underweight, stunting and wasting usingWHO 2005 GRS and NCHS 1977 GRS. Compared with the NCHS 1977 GRS, theWHO 2005 GRS estimate of child underweight is lower (40% vs. 45%) and theestimate of child stunting (46% vs. 40%) and child wasting (15% vs. 13%) arehigher. Contrary to the estimates provided by the NCHS 1977 GRS, theprevalence of child stunting is higher than underweight. These differences areconsistent with the predicted impactxx .

Figures A1 to A3 in Annex 10 show the prevalence of severe and moderateunderweight, stunting and wasting estimated with both the WHO and NCHSGRS.

Figure 13: Comparison of the prevalence of underweight, stunting andwasting in children aged <5 years estimated using the WHO2005 GRS and NCHS 1977 GRS

48

Pre

vale

nce (

%)

NCHS 1977 WHO 2005

Underweight Stunting Wasting

45

40

13

40

46

15

0

10

20

30

40

50


6.10 South Asian comparison

To compare the prevalence of child undernutrition in Bangladesh with otherSouth Asian countries, the prevalence estimates using the NCHS 1977 GRS wereused, as there is no published data from other countries that uses the WHO 2005GRS. Table 26 shows that Bangladesh has the 3rd highest prevalence ofunderweight, the 4th highest prevalence of stunting and the 3rd highest prevalenceof wasting.

Table 26: Prevalence of underweight, stunting and wasting in childrenaged <5 years in South Asian countries (NCHS 1977 GRS)

6.11 National trends in the nutritional status

In order to compare the results from the CMNS 2005 with the previous five CNS,only children aged 6-59 months were selected for analysis and all analysis wasdone using the NCHS 1977 GRS. Figure 17 and Table 27 show a steady decline inall indicators of nutritional status, with the exception of child wasting. Theprevalence of child underweight decreased from 66% in 1989-90, the base year forthe MDGs, to 48% in 2005; the 18 percentage point decline amounts to 27% of the1989/90 prevalence, and indicates that considerable progress is needed to meetthe target of MDG 1 for a 50% decline in child underweight. The prevalence ofchild stunting decreased from 65% to 42% between 1989-90 and 2005, and therewas marginal change in child wasting.

49

Country Underweight Stunting Wasting

Afghanistan 39 54 7

Bangladesh 45 40 13

Bhutan 19 40 3

India 47 46 16

Maldives 30 25 13

Nepal 48 51 10

Pakistan 38 37 13

Sri Lanka 29 14 14


Table 27: Prevalence of malnutrition in children aged 6-59 months, 1985 to2005 (NCHS 1977 GRS)

aChildren aged 12-59 months only

Figure 14: Trends in undernutrition in children aged 6-59 months, 1985 to2005 (NCHS 1977 GRS)

50

Pre

vale

nce (

%)

7166

68

57

5148

6865 64

5148

42

15 1417 17

12 13

1411

1310

74

0

10

20

30

40

50

60

70

80

1985-86 1989-90 1992 1995-96 2000 2005

Underweight Stunting

Wasting MUAC <125mm

IndicatorYear of the CNS/CMNS

1985 1989-90 1992 1995 2000 2005

Underweight(WAZNCHS<-2)

Rural 72.0 66.7 69.8 59.3 52.6 50.1

Urban 62.3 62.7 57.2 46.3 41.8 38.5

National 70.9 65.8 68.3 57.4 51.0 47.8

Stunting(HAZNCHS<-2)

Rural 68.9 66.7 65.8 52.8 50.2 44.9

Urban 57.1 58.3 52.8 42.9 37.5 32.5

National 67.5 64.6 64.2 51.4 48.3 42.4

Wasting(WHZNCHS<-2)

Rural 15.4 14.7 16.9 17.2 12.2 13.1

Urban 14.0 14.0 15.1 13.3 10.9 10.8

National 15.3 14.4 16.7 16.6 12.0 12.7

MUAC <125mm

Rural 14.9 11.0 13.2 11.0 7.0 4.9

Urban 9.9 8.5 8.4 6.6 3.6 2.6

National 14.4 10.7 12.6 10.4 6.5 4.1


Chapter 7: Maternal nutrition status

7.1 National prevalence

Anthropometric measurements were obtained from 3,050 mothers of childrenaged less than 5 years. Of these mothers, 168 were pregnant and were excludedfrom the analysis of nutritional status.

The mean age, weight, height, MUAC and BMI of non-pregnant mothers is givenin Table 28. The mean age of mothers surveyed was 28.1 years, the mean weight45.5 kg, the mean height was 149.6 cm, the mean MUAC was 241 mm and themean BMI was 20.2 kg/m2. All values of weight, height, MUAC and BMI wereslightly higher in urban areas than rural areas.

Table 28: Mean age, weight, height MUAC and BMI of non-pregnantmothers by area of residence

A total of 111 mothers were adolescents (<19 years). As adolescents call fordifferent anthropometric analyses, this data were analysed separately accordingto recommendations of the WHOxxi . Only 8% of adolescent mothers were thin,<1% were overweight/obese and 60% were stunted (Table 29 and Figure 18).There were no significant differences between rural and urban adolescents. Thisdata should be treated with caution as the sample included only 111 adolescents.

51

Rural Urban Total

Mean SD Mean SD Mean SD

Age (years) 28.2 6.2 27.8 6.0 28.1 6.2

Weight (kg) 44.5 7.0 48.8 9.5 45.4 7.8

Height (cm) 149.5 6.4 149.9 7.8 149.6 6.7

MUAC (cm) 23.8 2.5 25.3 3.3 24.1 2.8

BMI (kg/m2) 19.9 2.8 21.7 3.7 20.2 3.1


Table 29: Nutritional status of non-pregnant adolescent mothers by area ofresidence

Figure 15: Nutritional status of adolescent non-pregnant mothers

The remainder of the analysis of maternal nutritional status considers only non-pregnant adult women. According to WHO criteria for global adult populations,32% of adult mothers had chronic energy deficiency (CED), defined as a BMI<18.5 kg/m2 (Table 30). About 4% had Grade III CED (BMI <16.0 kg/m2), 7% hadGrade II CED (BMI 16.0 to 16.9 kg/m2) and 21% had Grade I CED (17.0 to 18.4kg/m2). The prevalence of BMI >25 kg/m2, which is used for internationalcomparisons of overweight and obesity, was 8%.

52

Nutritional status Rural (%) Urban (%) Total (%)

Thin <5th percentile BMI-for-age 7.9 6.5 7.6

Normal 5th-84th percentile BMI-for-age 92.1 89.7 91.7

Overweight/obese > 85th percentile BMI-for-age 0.0 3.8 0.7

Stunting HAZ<-2.00 59.9 61.8 60.2

8

92

0.0

60

7

90

62

8

92

60

3.80.7

0

20

40

60

80

100

120

Thin Normal Overweight or

obese

unted

Pre

vale

nce (

%)



Table 30: Nutritional status of non-pregnant adult mothers by area ofresidence (international BMI criteria)

There is extensive evidence that Asian adults face a significantly elevated risk ofadult health problems, such as diabetes and cardiovascular disease, at lower BMIthan other population groups. For this reason, different BMI cut-off points havebeen developed to indicate the level of risk among Asian populationsxxii.According to these cut-off points, 17% of mothers were overweight and obese(BMI >23 kg/m2) (Table 31 and Figure 19).

Table 31: Nutritional status of non-pregnant adult mothers by area ofresidence (Asian population BMI criteria)

53

BMI categories kg/m2 Rural (%) Urban (%) National (%)

Chronicenergydeficiency

Grade III <16.0 4.1 2.0 3.7

Grade II 16.0 to 16.9 8.1 4.6 7.4

Grade I 17.0 to 18.4 23.0 14.4 21.2

Total <18.5 35.2 21.0 32.2

Normal 18.5 to 24.9 58.9 60.2 59.2

Overweightand obese

Grade I 25.0 to 29.9 5.3 15.8 7.5

Grade II 30.0 to 39.9 0.6 3.0 1.1

Grade III >40 0.0 0.0 0.0

Total >25.0 5.9 18.8 8.6

BMI categories kg/m2 Rural (%) Urban (%) National (%)

Chronic energydeficiency

Grade III <16.0 4.1 2.0 3.7

Grade II 16.0 to 16.9 8.1 4.6 7.4

Grade I 17.0 to 18.4 23.0 14.4 21.2

Total <18.5 35.2 21.0 32.2

Normal 18.5 to 22.9 52.1 47.0 51.1

Overweightand obese

Increased risk 23.0 to 27.4 10.6 23.5 13.3

High risk >27.5 2.1 8.5 3.4

Total >23.0 12.7 32.0 16.7


Table 32: Prevalence of malnutrition in non-pregnant adult mothers byage, area of residence and season

* p<0.05; ** p<0.001; NS not significant

7.2 Nutritional status by age

The nutritional status of mothers was significantly associated with maternal age(Table 32). Younger (19-24 years) and older (>35 years) mothers were most likelyto have CED, and younger mothers were also least likely to be overweight/obese.

7.3 Nutritional status by area of residence

Figure 16 shows that the prevalence of each grade of CED in rural mothers wasalmost double that in urban mothers, while the prevalence of overweight/obesity,according to Asian cut-off points, was considerably higher in urban areas (32%)than rural areas (13%).

54

Characteristic CED (%)(<18.5 kg/m2)

Normal (%)(18.5-22.9 kg/m2)

Overweight/obese(%)(>23 kg/m2)

Age group of mother (years)19-24 25-29 30-34 35+

34.427.733.834.7

**

53.753.847.547.2

*

11.918.518.818.1

***Area of residence

RuralUrban

35.121.0

***

52.247.0

*

12.732.0

***Division

BarisalChittagongDhakaKhulnaRajshahiSylhet

31.730.829.827.737.337.0

**

55.049.552.350.151.147.6

NS

13.319.717.9

22.11.615.4

***

SeasonWinterSummerRainyAutumn

30.533.031.833.7

NS

51.451.551.849.4

NS

18.115.516.416.9

NS

National prevalence 32.2 51.1 16.7


Table 32 shows that mothers in Khulna Division, like their children, were leastaffected by undernutrition (28%), however they also appeared to be at highestrisk of overweight/obesity (22%). Mothers in Sylhet and Rajshahi Division bothhad the highest prevalence of CED (37%), and those in Rajshahi had the lowestprevalence of overweight/obesity (12%). Barisal Division had the highestpercentage of mothers whose BMI were within the normal range (55%).Differences between the divisions were significant for CED andoverweight/obesity only. Table 33 provides further information on rural-urbandifferences in the prevalence of malnutrition in these divisions.

Figure 16: Nutritional status of non-pregnant adult women by area ofresidence

55

CED

(BMI <18.5)

Normal

(BMI (18.5-22.9)

Overweight/obese

(BMI >_ 23

Pre

vale

nce (

%)


35

52

13

21

47

3232

51

17

0

10

20

30

40

50

60

70


Table 33: Prevalence of malnutrition in non-pregnant adult mothers bydivision and area of residence

7.4 Nutritional status by season

Table 32 shows that the prevalence of CED and overweight/obesity did not varysubstantially from one season to another. The prevalence of CED ranged from alow of 31% in Winter to a high of 34% in Autumn, while the prevalence ofoverweight/obesity ranged from a low of 16% in Summer to a high of 18% inWinter. These differences were not significant.

7.5 Nutritional status by maternal characteristics

The nutritional status of mothers was strongly associated with mother'seducation status (Table 34). Mothers with lower education status were more likelyto have CED and less likely to be overweight/obese than mothers who had highereducation status. A staggering 46% of mothers who had passed SSC/HSC or hada higher education level were overweight/obese, compared with only 10% ofmothers who were illiterate and/or had never attended school. Working motherswere more likely to be overweight/obese and less likely to have CED thanhousewives.

56

Barisal(%)

Chittagong(%)

Dhaka(%)

Khulna(%)

Rajshahi(%)

Sylhet(%)

National(%)

CED(<18.5 kg/m2)

Rural 32.3 34.2 34.6 28.6 38.9 39.1 35.1

Urban 27.6 19.0 18.8 23.1 26.6 19.5 21.0

Total 31.7 30.8 29.8 27.7 37.3 37.0 32.2

Normal(18.5-22.9 kg/m2)

Rural 56.7 50.2 54.7 51.0 51.2 48.7 52.2

Urban 44.7 47.1 46.9 45.5 50.5 39.0 47.0

Total 55.0 49.5 52.3 50.1 51.1 47.6 51.1

Overweight/obesity(>23 kg/m2)

Rural 11.0 15.6 10.8 20.3 9.9 12.2 12.7

Urban 27.6 33.9 34.3 31.3 23.0 41.5 32.0

Total 13.3 19.7 17.9 22.2 11.6 15.4 16.7


Table 34: Prevalence of malnutrition in non-pregnant adult mothers bymaternal characteristics

7.6 Other associations with nutritional status

Maternal nutritional status, like child nutritional status, showed a predictableassociation with wealth quintile (Table 35). The prevalence of CED significantlydecreased with increase in wealth quintile, and there was a three-fold differencein prevalence between the poorest (15%) and richest quintile (44%); theprevalence of overweight/obesity significantly increased with the increase inwealth quintile, and here there was an eight-fold difference in prevalencebetween the poorest (5%) and richest quintile (40%). Similar patterns wereobserved for other indicators of socio-economic status, including householdlandownership, income and expenditure. Mothers in households with cleanersources of water and more hygienic latrines were less likely to have CED andmore likely to be overweight/obese.


57

CED %(<18.5 kg/m2)

Normal %(18.5-22.9 kg/m2)

Overweight/obese %(>23 kg/m2)

Mother's education statusIlliterate/never attended schoolPassed class I-VPassed class VI-IXPassed SSC/HSC & above

37.632.925.417.9

***

52.953.351.436.3

***

9.513.823.245.8

***

Mother's occupationHousewifeWorking

32.522.4

*

51.149.6

NS

16.328.0

**



Mothers belonging to a household with a female household head weresignificantly more likely to be overweight/obese (29%) than mothers belongingto a household with a male household head (16%).

Table 35: Other associations of nutritional status in non-pregnant adultmothers

* p<0.05; ** p<0.01; *** p<0.001; NS not significant.

58

CED %(<18.5 kg/m2)

Normal %(18.5-22.9 kg/m2)

Overweight/obese %( >23 kg/m2)

HH wealth index quintilesPoorestSecondMiddleFourthRichest

44.041.034.430.214.7

***

51.051.955.250.845.8

*

5.07.1

10.419.139.5

***

HH cultivated land (acre)00.000.01 - 0.991.00 - 1.992.00 - 4.995.00+

33.033.430.029.427.8

NS

51.151.853.548.143.1

NS

15.914.816.622.529.1

***

Annual HH income (Taka)<3500035000 - 4999950000 - 6499965000 - 7999980000+

41.833.436.230.820.6

***

50.954.750.147.450.4

NS

7.311.913.821.829.1

***

Annual HH expenditure (Taka)<3500035000 - 4999950000 - 6499965000 - 7999980000+

39.139.033.629.421.8

***

54.052.054.450.146.0

**

6.99.0

12.020.532.1

***

Per capita kilocal consumption<1,6001,600-1,8491,850-2,1222,122+

39.832.935.628.3

***

45.155.949.751.1

***

15.111.214.720.6

***


* p<0.05; ** p<0.01; *** p<0.001; NS not significant.

7.7 National trends in nutritional status

As previous CNS did not include the anthropometry of mothers, the CMNS 2005data were compared with the findings of the three previous BangladeshDemographic and Health Survey (BDHS) findings. Table 35 and Figure 17 showthat the CMNS findings are consistent with the increasing trend in maternaloverweight/obesity and decreasing trend in maternal CED. Between 1996-7 and2005, the prevalence of CED decreased from 53% to 32% and the prevalence ofoverweight/obesity increased from 7% to 17%.

59

CED %(<18.5 kg/m2)

Normal %(18.5-22.9 kg/m2)

Overweight/obese %( >23 kg/m2)

Homestead gardenYesNo

34.230.5

NS

52.250.1

NS

13.619.4

NS

Taken loan to buy foodYesNo

38.130.2

***

51.750.9

NS

13.618.9

***

Main source of drinking waterTube wellTapOther

33.013.035.9

***

51.542.049.9

NS

15.545.114.2

***

Type of toilet facilityFlush/sanitary/water sealPit latrine Fixed kutcha Hanging latrine beside water/open space/no fixed space

20.229.439.442.4

***

45.053.452.550.8

*

34.817.2

8.16.7

**

Affected by monsoon floodYesNo

34.430.4

*

51.850.5

NS

13.819.2

***

Sex of household headMaleFemale

32.329.4

NS

51.542.0

*

16.228.5

***



Table 36: Nutritional status of non-pregnant adult mothers, 1996-7 to 2005

Figure 17: Nutritional status of non-pregnant adult mothers, 1996-7 to 2005

60

BMI categories kg/m2 BDHS1996-97

BDHS1999-00

BDHS2004

CMNS2005

Chronic energydeficiency

Grade III <16.0 10.1 6.4 5.2 3.7

Grade II 16.0 to 16.9 14.1 12.0 8.4 7.4

Grade I 17.0 to 18.4 28.4 26.2 21.9 21.2

Total <18.5 52.6 44.6 35.5 32.2

Normal 18.5 to 22.9 40.3 44.7 49.0 51.1

Overweight andobese

Increased risk 23.0 to 27.4 5.8 8.6 12.4 13.4

High risk >27.5 1.3 2.0 3.0 3.3

Total >23 7.1 10.7 15.5 16.7

Pre

vale

nce (

%)

CED (BMI <18.5) Normal (BMI 18.5-22.9)

Overweight/obese (BMI >_ 23)53

45

3632

40

45

4951

7

11

16 17

0

10

20

30

40

50

60

BDHS 1996-97 BDHS 1999-00 BDHS 2004 CMNS 2005


Chapter 8: Conclusions

Household characteristics

The mean household size of this population was 5.8 persons, higher than valuesfrom other national surveys because the survey selected households with at leastone child aged less than 5 years. Over 95% of household heads were male, 57%were illiterate or had never attended school and the most common occupationgroup was agriculture (40%). About 60% of households relied on kerosene as theirmajor source of light and the remainder had access to electricity. Only 18% ofhouseholds had a sanitary toilet (defined as having either a flushing mechanismor a water seal) and 94% of household had access to tube well drinking water.

The per capita food energy consumption was 2077 kcal/day, and was 65 kcal/dayhigher in rural areas than urban areas. About 47% of households had homesteadgardens and more than 25% of households had taken loans to buy food in theprevious three months. One third of households suffered crop losses due to theMonsoon floods in 2004, and 29% of households were damaged or destroyed dueto the floods. When household salt was tested for iodine, 83% was found to beiodised.

Maternal and child caring practices

Both knowledge and practice of appropriate infant and young child feedingpractices (IYCF) was poor among mothers. Only 33% correctly knew that childrenshould be exclusively breastfed for six months and only 40% knew thatcomplementary feeding should begin at 6 months of age. Breastfeeding wasinitiated within one hour for 48% of infants, exclusive breastfeeding rate (EBR)under six months of age was 58%, timely complementary feeding at 6-9 monthsof age was 71%, and the continued breastfeeding rate at 20-23 months was 89%.These four parameters of IYCF practices are powerful determinants of childsurvival and all four should be universal. The findings call for morecomprehensive mainstreaming of IYCF protection, promotion and support at thecommunity level. Given that the vast majority of children are delivered at home,these interventions must target women during pregnancy, and enlist the supportof birth attendants in the communities, so that every infant begins life withimmediate breastfeeding.

Over a fifth of mothers did not receive any antenatal care (ANC). Over half (52%)of mothers did not have their weight measured during pregnancy and 57% didnot take any iron supplements. Forty one percent (41%) of mothers ate less during

61


pregnancy, and 22% took less rest than when they were not pregnant. Manyopportunities appear to be missed in providing essential nutrition interventionsand counselling to mothers in Bangladesh.

The coverage of vitamin A supplementation was 93% among infants with themeasles vaccination at 9-11 months of age, 93% among children aged 12-59months, and only 18% among mothers within 6 weeks of delivery.

Child Nutritional Status

Using the new WHO 2005 GRS, 40% of children aged <5 years were underweight,46% were stunted, 15% were wasted and 1.4% were overweight/obese.According to criteria of the World Health Organizationxxiii, the prevalence ofunderweight and stunting was "very high", and the prevalence of wastingindicated a "critical problem". Severe underweight, severe stunting, severewasting and obesity were found in 11%, 19%, 3% and 0.3% of the population. Thisis the first time that data on child overweight/obesity have been determined forBangladesh, and the data can provide a baseline against which to measure trendsin the future.

The prevalence of underweight increased dramatically between 6-11 months ofage and stabilized from 12 months onwards. The prevalence of stunting increasedup to the end of the second year, and stabilized thereafter, decreasing slightly inthe fourth year of life. The prevalence of wasting was highest in the first sixmonths, and decreased gradually thereafter up to the fifth year of life. Thesepatterns are likely to reflect poor breastfeeding and complementary feedingpractices in the first year of life. There were no differences in nutritional statusbetween girls or boys. In comparison with the urban population, the ruralpopulation was significantly more underweight (42% vs. 30%) and more stunted(49% vs. 36%); there was no significant difference in wasting andoverweight/obesity.

The nutritional status of children was closely linked with several maternalcharacteristics. The prevalence of underweight, stunting and wasting wassignificantly higher among mothers with low education status, and with motherswho had CED. Children of older mothers were significantly more underweightthan children of younger mothers, and children of mothers who worked outsidethe home were less likely to be wasted than children whose mothers werehousewives. Children belonging to a household with a female household headwere significantly less likely to be underweight that those belonging to ahousehold with a male household head.

Child underweight, stunting, and wasting showed a predictable association with

62


wealth quintile: all three indices significantly decreased with increase in wealthquintile, and there was almost a two-fold difference in prevalence ofundernutrition between the poorest and richest wealth quintiles. Similarly, theprevalence of all three indicators decreased with an increase in household landownership, income and expenditure.

Indicators of lower household food security, including low per capita kilocalorieconsumption and loan for food, were associated with a higher prevalence ofunderweight, stunting and wasting. Children belonging to households affectedby the 2004 Monsoon floods were more likely to be underweight and stunted andless likely to be overweight than children in other households.

Compared with the NCHS 1977 GRS, the WHO 2005 GRS estimate of childunderweight is lower (45% vs. 40%) and the estimate of child stunting (40% vs.46%) and child wasting (13% vs. 15%) are higher. These differences are consistentwith the predicted differences between the two GRS.

Using the NCHS 1977 CRS to examine trends in nutritional status over time, theprevalence of child underweight decreased from 66% in 1989-90, the base year forthe MDGs, to 48% in 2005; the 18 percentage point decline amounts to 27% of the1989/90 prevalence, and indicates that considerable progress is needed to meetthe target of MDG 1 for a 50% decline in child underweight. The prevalence ofchild stunting decreased from 65% to 42% between 1989-90 and 2005, and therewas marginal change in child wasting.

Mother's nutritional status

The mean age of mothers of under-5 children was 28 years. Almost three-quarters(69%) of mothers married before 18 years of age and 72% had their first pregnancybefore 20 years of age. Almost one half (47%) of mothers were illiterate or hadnever attended school. Less than 10% of mothers were able to make their owndecisions on how much money the household spends on food, what food isbought for the household, and whether the mother or her child attends a healthfacility.

According to the new Asian adult BMI cut-offs, 32% of non-pregnant adultmothers had chronic energy deficiency (BMI <18.5 kg/m2) and 17% wereoverweight or obese (BMI >_ 23 kg/m2). The prevalence of CED in rural motherswas almost double that in urban mothers, while the prevalence ofoverweight/obesity was considerably higher in urban areas (32%) than ruralareas (13%).

63


Mothers with lower education status were more likely to have CED and less likelyto be overweight/obese than mothers who had higher education status. Workingmothers were more likely to be overweight/obese and less likely to have CEDthan housewives. Mothers belonging to a household with a female householdhead were more likely to be overweight/obese than mothers belonging to ahousehold with a male household head.

The prevalence of CED significantly decreased with increase in wealth quintile,and there was a three-fold difference in prevalence between the poorest (15%) andrichest quintile (44%); the prevalence of overweight/obesity significantlyincreased with the increase in wealth quintile, and there was an eight-folddifference in prevalence between the poorest (5%) and richest quintile (40%).Similar patterns were observed for other indicators of socio-economic status,including household landownership, income and expenditure. Both children andmothers from the poorest households are clearly most disadvantaged. Allinterventions to address undernutrition should actively seek ways to reach andimprove access by the poorest households to essential interventions.


As the previous CNSs did not include the anthropometry of mothers, the CMNS2005 data were compared with the findings of the three previous BangladeshDemographic and Health Survey (BDHS) findings. Between 1996-7 and 2005, theprevalence of CED decreased from 53% to 32% and the prevalence ofoverweight/obesity increased from 7% to 17%. These findings provide conclusiveproof that maternal overweight/obesity is a rapidly emerging public healthproblem in Bangladesh, particularly in urban areas. This calls for public healthaction to reverse the trend before it reaches the epidemic proportions thatcurrently affect other countries of the world. Adult men should be included in thenext national nutritional survey so that overweight/obesity can also be trackedamong the adult male population, who account for the majority of income earnersin Bangladesh.

The findings from the CMNS clearly demonstrate that the double burden ofmalnutrition is now present in Bangladesh, and that problems of bothundernutrition and overnutrition need to be addressed simultaneously.

64

ANNEXES


Annex 1: Data collection schedule

Table A1: Data collection schedule for the CMNS 2005

Annex 2: List of the Primary Sampling Units(PSUs)

Table A2: List of the PSUs for the CMNS 2005

66

Round Date Number of PSUs fordata collection

Number of PSUs forquality control

1 08/02/05-20/02/05 46 7

2 08/03/05-20/03/05 42 5

3 16/04/05-27/04/05 45 6

4 05/06/05-16/06/05 40 0

5 06/07/05-18/07/05 47 4

6 20/08/05-31/08/05 41 4

7 05/10/05-17/10/05 47 5

8 12/11/05-24/11/05 47 6

9 14/12/05-30/12/05 48 6

No. District Upazilla Union Mauza No.HH Area

1. Barisal Agailjhara Gaila Gaila 11 Rural

2. Barisal Bakerganj Dudhal Kabiraj 8 Rural

3. Barisal Banari Para Saidkati Indurhaola 9 Rural

4. Barisal Mehendiganj Bidyanandapur Bidyanandapur 9 Rural

5. Barisal Muladi Nazirpur Ramarpol 7 Rural

6. Bhola Bhola Sadar Char Samaia Purba Char Kali 9 Rural

7. Bhola Burhanuddin Bara Manika Bara Manika 7 Rural

8. Bhola Char Fasson Char Kalmi Uttar Char Mangal 7 Rural

9. Bhola Daulat Khan Char Khalifa Kalakopa 8 Rural

10. Bhola Lalmohan Lord Hardinje Char Lord Hardinge 7 Rural


67


11. Jhalokati Kanthalia Chenchri Rampur Dakshin Chenchrir 7 Rural

12. Jhalokati Nalchity Mollahat Kamdebpur 6 Rural

13. Jhalokati Rajapur Mathbari Indrapasha 7 Rural

14. Pirojpur Kawkhali Kawkhali Gosantara 7 Rural

15. Pirojpur Mathbaria Tikikata Sener Tikikata 8 Rural

16. Pirojpur Nesarabad(Swarupkathi) Sohagdal Paschim Sohagdal 7 Rural

17. Barguna Amtali Barabagi Bara Nishanbaria 5 Rural

18. Barguna Bamna Bukabunia Bara Taleshwar 9 Rural

19. Barguna Barguna Sadar Gaurichanna Khajurtala 8 Rural

20. Patuakhali Bauphal Daspara Bahir Daspara 7 Rural

21. Patuakhali Dashmina Betagi Sankipura Dabari Betagi 8 Rural

22. Patuakhali Kala para Nilganj Nilganj 8 Rural

23. Patuakhali Patuakhali Sadar Kamalapur Saula 4 Rural

24. Barisal Bakerganj Ward no-04 Bakerganj 8 Urban

25. Barisal Barisal Sadar Ward no-09 Char Upan 9 Urban

26. Barisal Barisal Sadar Ward no-26 Barisal 6 Urban

27. Bhola Daulat Khan Ward no-09 College Para 7 Urban

28. Jhalokati Jhalokati Sadar Ward no-06 Basanda 9 Urban

29. Jhalokati Nalchity Ward no-06 Parampasha 10 Urban

30. Pirojpur Pirojpur Sadar Ward no-02 Royerkati 9 Urban

31. Pirojpur Pirojpur Sadar Ward no-09 Marichal (Part) 7 Urban

32. Barguna Amtali Ward no-04 Sadarpara 6 Urban

33. Patuakhali Kala Para Ward no-07 Islampur 9 Urban

34. Bandarban Bandarban Sadar Kuhalong Chemi 3 Rural

35. Bandarban Lama Gajalia Bara Bamu 4 Rural

36. Bandarban Naikhongchhar Ghandung Tumru 9 Rural

37. Chittagong Banshkhali Chambal Paschim Chambal 11 Rural

38. Chittagong Boalkhali Kandhurkhil Kandhurkhil 5 Rural

39. Chittagong Lohagara Kalauzan Purba Kalaujan 11 Rural

40. Chittagong Mirsharai Wahedpur Wahedpur 6 Rural


68


41. Chittagong Rangunia Mariamnagar Katakhali 7 Rural

42. Cox's Bazar Cox's Bazar Sadar Patali Machhua Patali Machhuakhal 9 Rural

43. Cox's Bazar Maheshkhali Saflapur Saflapur 14 Rural

44. Cox's Bazar Ukhia Haldia Palong Paglir Bil 12 Rural

45. Brahmanbaria Banchharampur Salimabad Salimabad 10 Rural

46. Brahmanbaria Brahmanbaria Sadar Ramrail Bijeshwar 8 Rural

47. Brahmanbaria Sarail Pak Shimul Bhuisar 15 Rural

48. Chandpur Faridganj Dakshin Rupsa Char Mandari 7 Rural

49. Chandpur Hajiganj Uttar Rajargaon Rajargaon 10 Rural

50. Chandpur Matlab Uttar Nayergaon Kachiara 9 Rural

51. Chandpur Shahrasti Uttar Meher Nayanpur 7 Rural

52. Comilla Barura Uttar Shilmuri Chhota Bhatua 5 Rural

53. Comilla Burichang Rajapur Panchara 8 Rural

54. Comilla Chauddagram Chauddagram Sonakatia 8 Rural

55. Comilla Daudkandi Jiarkandi Gopalpur Joar 7 Rural

56. Comilla Debidwar Dakshin Dhamti Madhyanagar 10 Rural

57. Comilla Laksam Baghmara Jamalnagar 9 Rural

58. Comilla Laksam Perul Uttar Bhatora 11 Rural

59. Comilla Muradnagar Jatrapur Raghurampur 8 Rural

60. Comilla Nangalkot Mokara Bara Fatehpur 10 Rural

61. Khagrachhari Dighinala Merung Bara Merung 7 Rural

62. Khagrachhari Mahalchhari Mahalchhari Thali Para 7 Rural

63. Khagrachhari Matiranga Gumti Gumti 6 Rural

64. Khagrachhari Panchhari Panchhari Pujgang 6 Rural

65. Feni Daganbhuiyan Jailashkara Purba Ramchandrapu 10 Rural

66. Feni Feni sadar Fazilpur Purba Shibpur 5 Rural

67. Feni Sonagazi Bagadana Aruarkhil 4 Rural

68. Lakshmipur Lakshmipur Sadar Bhabaniganj Char Bhata 9 Rural

69. Lakshmipur Lakshmipur Sadar Uttar Hamchadi Shyamganj 5 Rural

70. Lakshmipur Ramgati Char Algi Char Niamat 8 Rural


69


71. Noakhali Begumganj Ambarnagar Wasekpur 9 Rural

72. Noakhali Begumganj Mir Warishpur Kendurbagh 4 Rural

73. Noakhali Chatkhil Ramnarayanpur Sobhanpur 7 Rural

74. Noakhali Hatiya Harni Voyar char 11 Rural

75. Noakhali Noakhali Sadar Char Matua Surjya NarayanBazar 7 Rural

76. Rangamati Baghai Chhari Kedarmara Kedarmara 6 Rural

77. Rangamati Kawkhali(Betbunia) Ghagra Kachukhali 5 Rural

78. Rangamati Kaptai Kaptai Kaptai R.F. Area 8 Rural

79. Rangamati Langadu Gulshakhali Gulshakhali 11 Rural

80. Bandarban Bandarban Sadar Ward no-05 Ujani Para 4 Urban

81. Bandarban Bandarban Sadar Ward no-09 Kashem Para 8 Urban

82. Chittagong Patiya Ward no-09 Uttar Gobindarkhil 8 Urban

83. Cox's Bazar Chakaria Ward no-07 Binamara 11 Urban

84. Cox's Bazar Cox's BazarSadar Ward no-09 Baharchhara Forest 5 Urban

85. Brahmanbaria BrahmanbariaSadar Ward no-02 Purba Medda 9 Urban

86. Brahmanbaria BrahmanbariaSadar Ward no-10 Kawtali 13 Urban

87. Chandpur Chandpur Sadar Ward no-02 Puran Bazar Dakshin 9 Urban

88. Chandpur Uttar Matlab Ward no-04 Aduruiti 6 Urban

89. Comilla Chandina Ward no-05 Chandina Mahallah 8 Urban

90. Comilla Laksam Ward-02 Bara Tupa 12 Urban

91. Khagrachhari KhagrachhariSadar Ward no-06 Shalban (Segun

Bagan) 8 Urban

92. Feni Feni Sadar Ward no-08 Barahipur (Part-1) 2 Urban

93. Lakshmipur LakshmipurSadar Ward no-02 Banchanagar (Part) 7 Urban

94. Lakshmipur Roypur Ward no-02 Uttar Denayetpur 8 Urban

95. Noakhali Begumganj Ward no-01 Uttar & Madhya Naz 8 Urban

96. Noakhali Chatkhil Ward no-09 Chhayani Tabga (Part) 10 Urban

97. Rangamati Rangamati Sadar Ward no-04 A.D.C. Colony 11 Urban

98. Chittagong Bayejid Bostami Ward no-02 Jalalabad 7 Urban

99. Chittagong Chandgaon Ward no-05 Paschim Mohara 6 Urban

100. Chittagong Double Mooring Ward no-27 C. D. A. 1 Urban


70


101. Chittagong Hathazari Forhadabad Forhadabad 4 Urban

102. Chittagong Kotwali Ward no-16 Chandanpura 6 Urban

103. Chittagong Kotwali Ward no-34 Patharghata 8 Urban

104. Chittagong Panchlaish Ward no-07 Paschim Sholosahar 6 Urban

105. Chittagong Sitakunda Kumira Uttar Sonichhari 8 Urban

106. Dhaka Dhamrai Gangutia Nalai (Bara) 6 Rural

107. Dhaka Nawabganj Bandura Puakair 6 Rural

108. Dhaka Nawabganj Sholla Aona 4 Rural

109. Gazipur Kapasia Barishaba Char Durlabh Khan 7 Rural

110. Gazipur Sreepur Sreepur Kewa 11 Rural

111. Manikganj Ghior Baratia Karjana 4 Rural

112. Manikganj Manikganj Sadar Dighi Bhat Bhaur 10 Rural

113. Manikganj Shibalaya Arua Arua 10 Rural

114. Manikganj Singair Jamirta Kalabaga (Bakchar) 14 Rural

115. Munshiganj Lohojang Kanaksar Dhitpur 10 Rural

116. Munshiganj Munshiganj Sadar Rampal Kazi Kasba 6 Rural

117. Munshiganj Tongibari Hasail Banari Banari 7 Rural

118. Narayanganj Sonargaon Kachpur Kanchpur 11 Rural

119. Narayanganj Rupganj Daudpur Beldi 3 Rural

120. Narayanganj Rupganj Tarabo Dighi Baraba 6 Rural

121. Narsingdi Manohardi Char Mandalia Char Mandalia (Part) 8 Rural

122. Narsingdi Manohardi Shukundi Shukundi 9 Rural

123. Narsingdi Narsingdi Sadar Silmandi Baghata 7 Rural

124. Narsingdi Roypura Marjal Marjal 10 Rural

125. Faridpur Bhanga Kalamridha Deora 7 Rural

126. Faridpur Char Bhadrasan Char Bhadrasan Char Bhadrasan 9 Rural

127. Faridpur Nagarkanda Dangi Bhubukdia 6 Rural

128. Faridpur Sadarpur Char Nasirpur Khataria 7 Rural

129. Gopalganj Gopalganj Sadar Raghunathpur Silna 8 Rural

130. Gopalganj Kashiani Sajail Haturia 4 Rural


71


131. Gopalganj Muksudpur Banshbaria Juthigram 8 Rural

132. Gopalganj Tungipara Dumuria Jhanjhania 4 Rural

133. Madaripur Kalkini Ramjanpur Uttar Charramjanpur 10 Rural

134. Madaripur Madaripur Sadar Panchkhola Janjira 8 Rural

135. Madaripur Rajoir Rajoir Chauaribari 11 Rural

136. Madaripur Shib Char Sannyasir Char Mahabatpur 6 Rural

137. Rajbari Baliakandi Nawabpur Kursi 11 Rural

138. Rajbari Pangsha Kalimahar Tarttipur 5 Rural

139. Rajbari Pangsha Saorail Sarisha 9 Rural

140. Shariatpur Gosairhat Nalmuri Char Bhuai 6 Rural

141. Shariatpur Palong Binodpur Bara Binodpur 4 Rural

142. Shariatpur Zanjira Naodoba Paschim Naodoba 10 Rural

143. Jamalpur Sarishabari Mahadan Karbari 9 Rural

144. Jamalpur Dewanganj Ward no-01 Miapara 8 Urban

145. Jamalpur Jamalpur Sadar Ward no-06 Majumdar Para 9 Urban

146. Jamalpur Melandaha Ward no-08 Molikadahdhngha 7 Urban

147. Sherpur Nakla Chandrakona Basur Alga 8 Rural

148. Sherpur Nalitabari Ward no-02 Uttar Garkanda 7 Urban

149. Tangail Ghatail Lakher Para Chhayani Baksia 6 Rural

150. Tangail Madhupur Ward no-09 Malauri 9 Urban

151. Kishorgonj Itna Badla Barshikura 10 Rural

152. Kishorgonj Karimganj Sutar Para Sutar Para 10 Rural

153. Kishorgonj Kishoreganj Sadar Dana Patali Gaglail 6 Rural

154. Kishorgonj Mithamain Keorjori Naopara 9 Rural

155. Mymensingh Bhaluka Mallikbari Mallikbari 7 Rural

156. Mymensingh Fulbaria Balian Teligram 12 Rural

157. Mymensingh Gaffargaon Datter Bazar Birai 12 Rural

158. Mymensingh Gauripur Achintapur Phulbaria 9 Rural

159. Mymensingh Ishwarganj Rajibpur Sreenagar 10 Rural

160. Mymensingh MymensinghSadar Dapunia Sasyamala 9 Rural


72


161. Mymensingh Muktagachha Kashimpur Mohanpur 11 Rural

162. Mymensingh Nandail Moazzempur Saidgaon 8 Rural

163. Mymensingh Phulpur Kamargaon Gobindakhila 5 Rural

164. Mymensingh Trishal Bali Para Bahadurpur 9 Rural

165. Netrakona Barhatta Sahata Dashal 11 Rural

166. Netrakona Kendua Thana Paikura Majlishpur 10 Rural

167. Netrakona Netrokona Sadar Dakshin Bishiu Sreepur Bali 9 Rural

168. Netrakona Purbadhala Hogla Hogla 9 Rural

169. Tangail Delduar Dubail Subarnatali 8 Rural

170. Jamalpur Dewanganj Char Aomkhaoa Sanandabari 7 Rural

171. Tangail Kalihati Balla Kamanna 5 Rural

172. Jamalpur Jamalpur Sadar Sharifpur Mrizapur 7 Rural

173. Tangail Nagarpur Bhadra Arra Kumed 8 Rural

174. Tangail Sakhipur Hatibandha Hatibandha 9 Rural

175. Dhaka Dohar Ward no-01 Nagarkanda 10 Urban

176. Dhaka Dohar Ward no-05 Dakshin JoyparaKhaz 6 Urban

177. Manikganj Manikganj Sadar Ward no-01 Paschim Sheota 5 Urban

178. Manikganj Manikganj Sadar Ward no-06 Paschim Dashora 4 Urban

179. Munshiganj Munshiganj Sadar Ward no-01 Goalghunni 7 Urban

180. Narsingdi Narsingdi Sadar Ward no-03 Chhota MadhabdiBazar 12 Urban

181. Narsingdi Narsingdi Sadar Ward no-04 Madhya kanda Para 7 Urban

182. Narsingdi Narsingdi Sadar Ward no-09 Salida 10 Urban

183. Faridpur Bhanga Ward no-02 Gazaria 10 Urban

184. Faridpur Faridpur Sadar Ward no-03 Paschim Khabaspur 9 Urban

185. Gopalganj Gopalganj Sadar Ward no-01 Uttar Ghosher Char 9 Urban

186. Gopalganj Gopalganj Sadar Ward no-09 Pachuria 5 Urban

187. Madaripur Kalkini Ward no-01 Pangashia 9 Urban

188. Rajbari Goalandaghat Ward no-01 Uttar Ujanchar (Part) 8 Urban

189. Rajbari Pangsha Ward no-09 Maishala (Uttar Part) 7 Urban

190. Shariatpur Palong Ward no-03 Paschim Kota Para 8 Urban


73


191. Sherpur Nalitabari Nunni Nunni 8 Rural

192. Sherpur Sherpur Sadar Char Sherpur Char Serpur 8 Rural

193. Tangail Madhupur Alokdia Kalamajhi 6 Rural

194. Tangail Madhupur Solakuri Fulbagh Chala 5 Rural

195. Kishorgonj Bhairab Ward no-03 Panchabati With Flot 8 Urban

196. Kishorgonj Kishoreganj Sadar Ward no-03 Shulakia (Part) 5 Urban

197. Mymensingh Bhaluka Ward no-04 Office Para 6 Urban

198. Mymensingh Mymensingh Sadar Ward no-01 Dholadia 9 Urban

199. Mymensingh Mymensingh Sadar Ward no-17 Baghmara 5 Urban

200. Mymensingh Muktagachha Ward no-05 Paratongi (North) 8 Urban

201. Netrakona Netrokona Sadar Ward no-01 Satpai 9 Urban

202. Tangail Kalihati Ward no-03 Silimpur 4 Urban

203. Jamalpur Jamalpur Sadar Banchchara Baithamari 9 Rural

204. Tangail Tangail Sadar Ward no-12 Adi tangail 7 Urban

205. Dhaka Cantonment Ward no-15 (Part) Manikdi 6 Urban

206. Dhaka Dhanmondi Ward no-52 Elephant Road 5 Urban

207. Dhaka Hazaribagh Ward no-58 (Part) Nabipur Lane 10 Urban

208. Dhaka Keraniganj Zinjira (Part) Char Raghunathpur 8 Urban

209. Dhaka Mirpur Ward no-09 Chhota Diabari 6 Urban

210. Dhaka Mohammadpur Ward no-44 Shahjahan Road 2 Urban

211. Dhaka Motijheel Ward no-35 Malibagh 5 Urban

212. Dhaka Ramna Ward no-56 Eng. University 3 Urban

213. Dhaka Savar Dhamsana Baipail 9 Urban

214. Dhaka Shyampur Shyampur U/C(Part) Kadamtali (Part) 9 Urban

215. Gazipur Gazipur Sadar Ward no-04 Purba Joydebpur 5 Urban

216. Gazipur Gazipur Sadar Ward no-12 Ershadnagar(Dattapara) 9 Urban

217. Gazipur Gazipur Sadar Kashimpur Bhikanpur 9 Urban

218. Gazipur Gazipur Sadar Mirzapur Barui Para 10 Urban

219. Gazipur Gazipur Sadar Pubail Kudhabo 7 Urban

220. Narayanganj Bandar Bandar Mirkundir Char(Bala) 6 Urban


74


221. Narayanganj Narayanganj Sadar Ward no-04 Masdair (Part-a) 6 Urban

222. Narayanganj Narayanganj Sadar Kashipur Kashipur 9 Urban

223. Narayanganj Narayanganj Sadar Siddirganj Azibpur 10 Urban

224. Jessore Bagher Para Dhalgram Sultannagar 7 Rural

225. Jessore Jhikargachha Gadkhali Barbakpur (Part) 5 Rural

226. Jessore Keshabpur Panjia Sagar Dattakati 9 Rural

227. Jessore Manirampur Khanpur Machna 8 Rural

228. Jessore Sharsha Lakshmanpur Muktadaha 8 Rural

229. Jhenaidah Kaliganj Bara Bazar Thikdanga 11 Rural

230. Jhenaidah Maheshpur Azampur Ramchandrapur 7 Rural

231. Jhenaidah Shailkupa Dhalhara Chandra Dhalhara Shambhu 5 Rural

232. Magura Magura Sadar Chaulia Dhalhara 11 Rural

233. Magura Mohammadpur Rajapur Rajpat 6 Rural

234. Magura Sreepur Dariapur Dariapur 8 Rural

235. Narail Kalia Joynagar Union Gachhbaria 7 Rural

236. Narail Lohagara Itna Itna 12 Rural

237. Narail Lohagara Noagram Union Kalagachhi 6 Rural

238. Narail Narail Sadar Maij Para Union Balarampur 8 Rural

239. Bagerhat Chitalmari Char Baniari Durgapur 10 Rural

240. Bagerhat Kachua Rari Para Bhandarkola 11 Rural

241. Bagerhat Rampal Ujalkur Sonatunia 6 Rural

242. Khulna Batiaghata Bhanderkote Kismat Jhinaikhali 6 Rural

243. Khulna Dumuria Dhamalia Tolna 8 Rural

244. Khulna Dacope Chalna Pankhali 6 Rural

245. Satkhira Assasuni Baradal Champakhali 6 Rural

246. Satkhira Kaliganj Mautala Pania 7 Rural

247. Satkhira Satkhira Sadar Kuskhali Satani Bhadra 8 Rural

248. Satkhira Tala Dhandia Panch Para Alipur 9 Rural

249. Chuadanga Damurhuda Juranpur Bishnupur 7 Rural

250. Chuadanga Jiban Nagar Jiban Nagar Umapur 7 Rural


75


251. Kushtia Bheramara Chandgram Nowdapara (Part) 6 Rural

252. Kushtia Daulatpur Maricha Koldiar 10 Rural

253. Kushtia Kumarkhali Bagulat Adabaria 6 Rural

254. Kushtia Kushtia Sadar Alampur Alampur 3 Rural

255. Meherpur Gangni Dhankhola Joginda 7 Rural

256. Meherpur Gangni Shaharbati Bhamradaha 6 Rural

257. Meherpur Mujib Nagar Dariapur Parandarpur 7 Rural

258. Meherpur Meherpur Sadar Buripota Radhakantapur 4 Rural

259. Jessore Abhaynagar Ward no-05 Madhya Bhuikara 5 Urban

260. Jessore Kotwali Ward no-05 Khorki Chanchra 5 Urban

261. Jessore Kotwali Ward no-09 Bonupara (Part) 5 Urban

262. Jhenaidah Jhenaidaha Sadar Ward no-05 Bepari Para 7 Urban

263. Jhenaidah Kaliganj Ward no-06 Balidapara (Dakshin) 3 Urban

264. Jhenaidah Maheshpur Ward no-09 Gorabaria 4 Urban

265. Magura Magura Sadar Ward no-01 Pathra 8 Urban

266. Narail Kalia Ward no-02 Shal Barat 6 Urban

267. Narail Narail Sadar Ward no-04 Aladatpur 3 Urban

268. Bagerhat Bagerhat Sadar Ward no-06 Dakshin Bazar(Paschim) 3 Urban

269. Bagerhat Mongla Ward no-05 Bazar Area,ph,psv 7 Urban

270. Satkhira Kalaroa Ward no-02 Kalaroa Tulsidanga 5 Urban

271. Chuadanga Alamdanga Ward no-02 Radhikaganj 8 Urban

272. Chuadanga Chuadanga Sadar Ward no-05 Taltala (Part)(Paschim) 8 Urban

273. Chuadanga Damurhuda Ward no-09 Ishwar Chandrapur 8 Urban

274. Kushtia Kushtia Sadar Ward no-08 Paschim Arua Para 7 Urban

275. Meherpur Meherpur Sadar Ward no-06 Garpara 6 Urban

276. Khulna Daulatpur Ward no-04 Deana (Part) 3 Urban

277. Khulna Khalishpur Ward no-07 Uttar Kashipur 9 Urban

278. Khulna Khulna Sadar Ward no-26 Jora Gate 7 Urban

279. Khulna Khulna Sadar Ward no-36 Dakshin Tootpara 9 Urban

280. Khulna Rupsa Sreefaltala Badhal 9 Urban


76


281. Khulna Sonadanga Ward no-24 Nazirghat 7 Urban

282. Bogra Adamdighi Chhatiangram Chhatiangram 4 Rural

283. Bogra Bogra Sadar Lahiri Para Bathuabari 4 Rural

284. Bogra Gabtali Balia Dighi Balia Dighi 7 Rural

285. Bogra Kahaloo Jamgaon Jamgaon 8 Rural

286. Bogra Sariakandi Chaluabari Hatbaria Hariajani 8 Rural

287. Bogra Sherpur Mirzapur Aira 6 Rural

288. Joypurhat Joypurhat Sadar Bambu Hichmi 5 Rural

289. Joypurhat Kalai Kalai Kalai 7 Rural

290. Joypurhat Khetlal Khetlal Ikargara 5 Rural

291. Joypurhat Panchbibi Kusumba Dhurail 7 Rural

292. Dinajpur Birampur Jotbani Chakul 10 Rural

293. Dinajpur Biral Bhandara Danga Para 5 Rural

294. Dinajpur Chirirbandar Abdulpur Rasulpur 9 Rural

295. Dinajpur Ghoraghat Bulakipur Damodarpur 6 Rural

296. Dinajpur Khansama Bhabki Chak Kanchan 9 Rural

297. Dinajpur Nawabganj Bhaduria Kalikur 7 Rural

298. Dinajpur Parbatipur Manmathapur Narayanpur 8 Rural

299. Panchagarh Debiganj Chilahati Bhaulaganj 14 Rural

300. Panchagarh Panchagarh Sadar Hafizabad Islampur 6 Rural

301. Panchagarh Tentulia Salbahan Khirkidangi 8 Rural

302. Thakurgaon Baliadangi Bara Palashbari Karua 10 Rural

303. Thakurgaon Ranisankail Nonduar Union Jaogaon 7 Rural

304. Thakurgaon Thakurgaon Sadar Jagannathpur Singia 10 Rural

305. Pabna Bera Masundia Masundia 6 Rural

306. Pabna Chatmohar Nimaichara Chinabhatkur 11 Rural

307. Pabna Pabna sadar Ataikola Ataikola 8 Rural

308. Pabna Sujanagar Manikhat Ulath Chandipur 7 Rural

309. Sirajganj Belkuchi Rajapur Madhya Khamar 10 Rural

310. Sirajganj Kazipur Chalitadanga Hatsira 11 Rural


77


311. Sirajganj Royganj Ghurka Langalmura 9 Rural

312. Sirajganj Sirajganj Sadar Saidabad Chak Boyra 11 Rural

313. Sirajganj Ullah Para Durganagar Balsabari 9 Rural

314. Naogaon Badalgachhi Badalgachhi Jidhirpur 6 Rural

315. Naogaon Manda Bhalain Chak Bhalain 3 Rural

316. Naogaon Manda Tentulia Tentulia 6 Rural

317. Naogaon Niamatpur Rasulpur Kendua 10 Rural

318. Naogaon Raninagar Bargachha Baria 5 Rural

319. Natore Bagati Para Fhaguradiar Hardoul 6 Rural

320. Natore Baraigram Nagar Atai 7 Rural

321. Natore Lalpur Duaria Durgapur 8 Rural

322. Natore Natore Sadar Dighapatia Dighapatia 5 Rural

323. Nawabganj Bholahat Gohalbari Gopinathpur (Part) 9 Rural

324. Nawabganj Nachole Kasba Kasba 10 Rural

325. Nawabganj Shibganj Kansat Namo Biswhanathpur 10 Rural

326. Rajshahi Baghmara Basu para Mahammadpur 4 Rural

327. Rajshahi Charghat Yusufpur Chak Kapasia 6 Rural

328. Rajshahi Godagari Char Ashariadaha Ashariadah Malmaha 9 Rural

329. Rajshahi Tanore Kalma Nalpukhuria 7 Rural

330. Gaibandha Gaibandha Sadar Ghagoa Dakshin Ghagoa 6 Rural

331. Gaibandha Gobindaganj Kamardaha Bagh Char 7 Rural

332. Gaibandha Palashbari Barisal Purba Mirzapur 5 Rural

333. Gaibandha Sadullapur Faridpur Nayanpur 7 Rural

334. Gaibandha Sundarganj Shantiram Shantiram 11 Rural

335. Kurigram Char Rajibpur Char Rajibpur Jauniar Char 9 Rural

336. Kurigram Raumari Bandaber Purar Char 6 Rural

337. Kurigram Ulipur Hatia Hatia Bakshi 10 Rural

338. Lalmonirhat Aditmari Sarpukur Sarpukur 8 Rural

339. Lalmonirhat Kaliganj Chalbala Khalisa Barajan 8 Rural

340. Lalmonirhat Patgram Kuchlibari Panbari 6 Rural

341. Nilphamari Domar Ketkibari Chandkhana 8 Rural


78


342. Nilphamari Jaldhaka Shimulbari Rajbari 8 Rural

343. Nilphamari Nilphamari Sadar Charaikhola Kismat Charaikhola 9 Rural

344. Nilphamari Saidpur Bothlagari Bothlagari (Part) 5 Rural

345. Rangpur Kaunia Kaunia Bala Para Harishwar 12 Rural

346. Rangpur Rangpur Sadar Satgara Damodarpur 10 Rural

347. Rangpur Mitha Pukur Emadpur Faridpur 5 Rural

348. Rangpur Pirgachha Chhaola Adam 8 Rural

349. Rangpur Taraganj Alampur Fazilpur 9 Rural

350. Bogra Adamdighi Ward no-02 Dogachhi 10 Urban

351. Bogra Bogra Sadar Ward no-06 Chalo Para 8 Urban

352. Joypurhat Akkelpur Ward no-02 Rajkhanda 4 Urban

353. Joypurhat Joypurhat Sadar Ward no-05 Purba Debipur 4 Urban

354. Dinajpur Fulbari Ward no-01 Uttar Sujapur 8 Urban

355. Panchagarh Panchagarh Sadar Ward no-03 Raushnabag Paschim 5 Urban

356. Panchagarh Panchagarh Sadar Ward no-09 Distilary Khalpara 5 Urban

357. Thakurgaon Pirganj Ward no-08 Jagtha Purba 10 Urban

358. Thakurgaon Thakurgaon Sadar Ward no-07 Munshi Para 8 Urban

359. Pabna Bhangura Ward no-09 Shaah Para 11 Urban

360. Pabna Pabna Sadar Ward no-02 Parbatiganj 6 Urban

361. Pabna Santhia Ward no-02 Khalishakhali 8 Urban

362. Sirajganj Sirajganj Sadar Ward no-04 Rahmatganj 9 Urban

363. Sirajganj Sirajganj Sadar Ward no-15 Mirpur Uttargram 5 Urban

364. Naogaon Naogaon Sadar Ward no-09 Boalia (Part) 6 Urban

365. Natore Lalpur Ward no-05 Keshobpur 6 Urban

366. Natore Natore Sadar Ward no-08 Tebaria (Part) 7 Urban

367. Nawabganj Nawabganj Sadar Ward no-03 Gabtala 7 Urban

368. Nawabganj Nawabganj Sadar Ward no-14 Azaipur 5 Urban

369. Rajshahi Baghmara Ward no-01 Taherpur Dakshin 4 Urban

370. Rajshahi Godagari Ward no-08 Sarangpur 7 Urban

371. Gaibandha Gaibandha Sadar Ward no-01 David Co. Para 9 Urban

372. Kurigram Kurigram Sadar Ward no-01 Moktar Para 9 Urban


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373. Kurigram Kurigram Sadar Ward no-07 Paik Para 8 Urban

374. Kurigram Ulipur Ward no-06 Ulipur 8 Urban

375. Lalmonirhat Lalmonirhat Sadar Ward no-04 Kuddus Tary 11 Urban

376. Nilphamari Saidpur Ward no-10 Kazi Para 10 Urban

377. Rangpur Kaunia Ward no-06 Khartari 11 Urban

378. Rangpur Rangpur Sadar Ward no-08 Hanumantala 9 Urban

379. Rajshahi Matihar Ward no-31 Kazla 3 Urban

380. Rajshahi Paba Haragram Kashiadanga (Part) 8 Urban

381. Rajshahi Paba Noahata Madhusudhanpur 8 Urban

382. Rajshahi Rajpara Ward no-06 Lakshmipur 10 Urban

383. Habiganj Ajmiriganj Kakailseo Mamudpur 9 Rural

384. Habiganj Madhabpur Bagasura Kalikapur 8 Rural

385. Habiganj Nabiganj Kalair Banga Kharia 10 Rural

386. Maulvibazar Kamalganj Adampur Uttarbhag 9 Rural

387. Maulvibazar Kulaura Hajipur Pabai 7 Rural

388. Maulvibazar Sreemangal Ashidron Sungair (part) 10 Rural

389. Sunamganj Bishwambarpur Fatehpur Shyamarkandi 9 Rural

390. Sunamganj Derai Charnar Char Satyanandapur 6 Rural

391. Sunamganj Dowarabazar Duhalia Bhabanipur 12 Rural

392. Sunamganj Jamalganj Vimkhali Noagaon 9 Rural

393. Sylhet Balaganj Dewan Bazar Barkatpur 7 Rural

394. Sylhet Bishwanath Daulatpur Singerkanch 9 Rural

395. Sylhet Golabganj Fulbari Fulbari 7 Rural

396. Sylhet Jaintiapur Nijpat Jaintiapur Nijpat 9 Rural

397. Sylhet Kotwali Lala Bazar Ardilpur 11 Rural

398. Habiganj Habiganj Sadar Ward no-06 Shaymoli Residential 6 Urban

399. Maulvibazar Kulaura Ward no-07 Dattarmuri 9 Urban

400. Maulvibazar Sreemangal Ward no-02 Kalighat Road 8 Urban

401. Sunamganj Sunamganj Sadar Ward no-04 Uttar Hasan Nagar 10 Urban

402. Sylhet Kotwali Ward no-07 Jalalabad 9 Urban

403. Sylhet Kotwali Ward no-17 Chauhatta 2 Urban


Annex 3: Questionnaire

(Confidential, to be usedonly for Research)

Government of the People's Republic of BangladeshBangladesh Bureau of Statistics

Monitoring the Situation of Children & Women ProjectParisankhyan Bhaban

Agargaon, Dhaka.

Child and Mother Nutrition Survey Questionnaire 2005

Rural Interview Time: Hour Minute

Urban non slum Start

Urban Slum End

80

Identification Name Code number

Term

Division

District

Thana/Upazilla

Union/Ward

Mauza/Mahalla

PSU number

HIES HH number

Enumerator's name and signature

Date:

Quality Control Officer's name and signature

Date:

Enumerator's name and signature

Date:

Editor/Verifier's name and signature

Date:

Supervisor's name and signature

Date:

Data entry operator's name and signature

Date:


81

Form 1: Household Information Coding Column

1. Interview date:

2. Name of the household head_______________

3. Sex of the household head1. Male 2. Female

4. What is the main occupation of the household head?1. Professional, technical, administrative and managerial2. Clerical worker3. Sales worker4. Service worker5. Agriculture, animal husbandry, forestry, fisheries6. Production and retailer workers and transport worker7. Business8. Household worker9. Others (unemployed, beggar, disabled, retired etc)

5. What is the highest class that the household headcompleted at school?01 to 09 Highest class passed (as per manual)00 Illiterate88 Can read and write but never attended school10 SSC12 HSC14 Degree and above

6. How many members are there in this household?1. Number of mothers with children aged 0-59 months2. Number of children aged 0-59 months3. Number of other household members

7. What is your household's main source of drinking water?1. Tube well 2. Tap3. Well 4. Pond/river5. Other (Specify) ________________

8. What is the household's main source of light?1. Electricity 2. Kerosene3. Solar Power 4. Gas/Bio-Gas

9. What is the construction material of the living room of thehousehold head?1. Earth, 2. Straw/Chone, 3. Polythene,4. Brick, 5. Tin, 6. Bamboo,7. Others.

a) Roof

b) Wall

c) Floor

Day Month Year


82


10. What is the distance to the nearest Govt/NGO operatedhealth centre/hospital/outreach/satellite clinic? 00 <1 km

km

11. How much does transport cost (by road or river) to go tothe nearest Govt/NGO operated healthcentre/hospital/outreach/satellite clinic?

Tk

12. May we have a pinch of salt that you use in your meal/table? (Enumerator: test the salt with the testing solution)

1. Iodine present 2. Iodine not present 3. Salt not available

13. What type of toilet facility do members of the householduse? (Enumerator: Check physically and record).

1. Flush/sanitary/water seal2. Pit latrine (excreta disposed of under the ground)3. Fixed kacha 4. Hanging latrine beside water5. Open space/no fixed space

14. Do you have a vegetable garden within your homestead?1. Yes 2. No (Go to Q. 30) .

15. What do you do with the vegetables that you grow?1. Consumed by members of the household2. Consumed and sold 3. Sell all the vegetables4. Others (specify) _____________________

(To be transcribed data (Q. 16-29) from HIES Questionnaire by HQ.)

16. Total income during last one year of this household:

17. Annual per capita income of this household:

18. Total expenditure during last one year of this household:

19. Annual per capita expenditure of this household:

20. Total annual expenditure on food of this household:

21. Annual per capita expenditure on food of this household:

22. Expenditure on food as percentage of total expenditure ofthis household:

23. Total expenditure on medical care of this household duringlast one year:

24. Annual per capita expenditure on medical care of thishousehold:

25. Total educational expenditure to this household during lastone year:

2.6 Annual per capita expenditure on education:

27. Total operated land holdings of this household (all memberstogether): (Own + taken lease - given lease = operated)

acre decimal


83


28. Total owned cultivated land of this household:

29. Daily per capita calorie consumption of this household:

30. Did any member of this household take any loan to buyfood during the last three months?

1. Yes 2. No31. Did any member of this household take any loan, except for

food, due to any reason from any source during the lastthree months (including micro credit)?

1. Yes 2. No (Go to Q. 33)

32. What were the reasons for taking loan? (Write the code oftwo fields as per maximum amount of loan taken for)

1. For medical treatment 2. For education3. For house building/repair 4. For social function 5. Agriculture 6. Other (specify)

33. Did any member of this household get any micro-creditassistance for any incoming purpose from govt. or NGO(Aasha, BRAC, Grameen Bank etc.) during last one year?

1. Yes 2. No34. Did any member of this household get any food or cash

assistance for any purpose from Govt. during last one year?1. Yes 2. No

35. Was your household affected by the Monsoon floods in lastJuly (Ashar-Srabon) 2004?

1. Yes 2. No (Go to Q. 37)

36. How was your household affected by the Monsoon floods inJuly (Ashar-Srabon) 2004?

1. Yes 2. No

a) House damaged/destroyed

b) Latrine damaged/destroyed

c) Source of drinking water damaged/destroyed

d) Food stocks damaged/destroyed

e) Household members died

f) Household members fell sick

g) Crops damaged destroyed

h) Livestock died

i) Lost employment/lost source of income

j) Other (specify)……………………………..

acre decimal

(End of Form-1)


84

Form 2: Information on mother/caretaker of underfive children Coding Column

37. Mother/caretaker's name: _________________________and ID Number

38. What is your relationship to this child?1. Mother 2. Father3. Permanent caretaker 4. Temporary caretaker5. Other (Specify)___________________

39. What is the highest class you have completed at school?01 to 09 Highest class passed (as per manual)00 Illiterate88 Can read and write but never attended school10 SSC12 HSC14 Degree and above

40. What is your marital status?1. Currently married 2. Never married3. Widow 4. Divorced5. Deserted

41. For how many months should a child be exclusivelybreastfed?

77 Don't know

42. At what age (in months) should a child be givencomplementary food?

77 Don't know

43.. At what age (in months) should a child be given family food?77 Don't know

(Enumerator: Please go to Form 3 if the respondent is not the biological mother ofsurvey child)44.. What is your age at present (in years)?

45. At what age did you first get married (in year)?

46. At what age did you first get pregnant (in year)?

47. How many times have you been pregnant (including ifcurrently pregnant)?

48. How many children have you had that were born alive?

49. What is your major occupation? 1. Professional, technical, administrative and managerial2. Clerical worker 3. Sales worker4. Service worker5. Agriculture, animal husbandry, forestry, fisheries6. Production and retailer workers and transport worker7. Business8. Household worker9. Others (unemployed, beggar, disabled, retired etc)


85

Form 2: Information on mother/caretaker of underfive children Coding Column

50. Did you earn money during the last 3 months?1. Yes 2. No (Go to Q. 56)

51. From what type of main work did you earn money? 1. Business 2. Service3. House maid 4. Poultry rearing5. Goat/livestock 6. Gardening7. Hand work 8. Others (Specify) ____________

52. How much money (taka) did you earn during the last 3months?

53. In what type of main work do you spend most of yourearning (Taka)?

1. Spend for children need 2. Spend for myself3. Other (Specify) ___________________

54. Who decided how your earnings would be spent?1. Mother only 2. Husband only3. Other family members only4. Mother and husband jointly5. Mother and other family member jointly6. Husband and other family member jointly7. Others (specify)___________________

55. Have you saved some money from your income during thelast 3 months?

1. Yes 2. No56. Who makes the following decisions in your household?

1. Mother/self only 2. Husband only3. Mother and other household member(s) jointly4. Other household member(s)

a) How much money the household spends on food?

b) What food is bought for the household?

c) What food is cooked for the household?

d) Whether mother attends a health facility for her own health needs?

e) Whether mother's child goes to a health facility forhis/her health needs?

57. Are you currently pregnant?1. Yes 2. No 7. Don't know

58. Have you ever received any prepared food (Pusti) from anyNGO?

1. Yes 2. No

59. Measurements of mother of child:

a) Height of mother (cm)

b) Weight of mother (kg)

c) MUAC of mother (mm)


86

Form 3: Child's Information (0-59 months) Coding Column

60. Mother/caretaker (a) Name _______________Mother/caretaker ID number:

61. What is the name (nick name) of this child? ___________Child ID number

62. Sex of the child1. Male 2. Female

63. What is the birth date of [the child]?

64. What is the source of the birth date?1. Documented (birth record/clinic record/home record)2. Stated and confirmed by other family members3. Estimated (using calendar of events)

65.. Enumerator: Please write the present age of the child inmonths

66.. What is the birth order of [the child] among his/her mother'slive births?

(Enumerator: Please go to Q. 88 if the respondent is not the biological mother of surveychild. If the respondent is survey child's biological mother, then ask Q. 66 through Q. 87)67. How many times did you receive antenatal care when you

were pregnant with this child?00 None (Skip to Q. 72)77 Don't know

68. Where did you go to receive the antenatal care beforedelivery of [the child]?

1. Doctor/Nurse/FWV/FWA/MA/HA2. Trained SBA/TBA3. Un trained TBA4. Unqualified Med Practitioner 5. Others_____________6. Did not receive antenatal care

69. Did you take Tetanus Toxoid during this pregnancy? 1. Yes 2. No

70. How many times was your weight checked during yourpregnancy?

00 None77 Don't know

71. How many times was your blood checked during yourpregnancy?

0 None7 Don't know

72. For how many months did you take iron tablets during yourpregnancy with this child?

01 -09 Number of months 00 Never77 Don't know

Day Month Year


87


73. When you were pregnant with your child, did you eat asmuch food as you usually ate before the pregnancy, or didyou eat more or less food than you usually ate before?

1. Less than before 2. Same as before3. More than before

74. When you were pregnant with your child, did you rest asmuch as you usually rested before the pregnancy, or yourest more or less than you usually rested before?

1. Less than before 2. Same as before3. More than before

75. Where did you deliver [name of child]?Govt. Health Center/Hospital

1. Private/NGO health centre/hospital2. Home delivery3. Other (specify)…………………4. Don't Know

76. Who was the birth attendant at the delivery of [name ofchild]?

1. Doctor/Nurse/FWV/HA 2. Trained SBA/TBA3. Un trained TBA4. Neighbour/Relatives/Others

77. Did anyone weigh your newborn infant within 3 days ofdelivery?

1. Yes 2. No 7. Don't know

78.. Did you take vitamin A capsule/tablet within 6 weeks ofdelivery of your child?


(Enumerator: Ask Q. 79 to 87 to the mother of children aged 0-23 months only)

79. How long after birth did you first put your child to thebreast?

1. Less than one hour after birth 2. Within 24 hours of birth 3. After 24 hours of birth 4. Never breastfed (Go to Q. 83)7. Don't know

80. Did you give the baby the first liquid (colostrum) that camefrom your breasts?

1. Yes 2. No

81. Did you give your child anything to drink before you first putthe baby to the breast (e.g. water, honey water, sugarwater)?



88


82. Are you still breastfeeding your child?1. Yes 2. No

83. How long (in months) was [name of child] exclusivelybreastfed? (e.g. given no food or drink, even water exceptmedicine)

00 to 59 Age in months77 Don't know99 Still exclusively breast fed (go to Q. 89)

84. How old (in months) was [name of child] when you first gavehim/her complementary solid food (e.g. suji, rice powder,etc.)?

00 to 59 Age in months77 Don't know88 Not yet given

85. How old (in months) was [name of child] when you first gavehim/her family food (rice, fish, egg, fruits, vegetables etc.)

00 to 59 Age in months77 Don't know88 Not yet given

86. Have you ever given [name of child] cows/goats milk?(powder or liquid)

1. Yes 2. No

87. Have you ever bottle-fed [name of child]?1. Yes 2. No

88.. Has this child [name of child] ever received any preparedsupplementary food from any NGO?

1. Yes 2. No

89. For mother of children aged 12-23 months only:Did this child [name of child] take a vitamin 'A' Capsule withhis/her measles vaccination at 9-11 months of age?


90. For mother of children aged 12-59 months only:Did this child [name of child] take a vitamin 'A' Capsule duringthe last National Vitamin A+ Campaign?

1. Yes 2. No

91. For mother of children aged 24-59 months only:Did this child [name of child] take a deworming tablet duringthe last National Vitamin A+ Campaign?


(Enumerator: Ask the following questions to all the mother/caretakers)


89


92. What did you give to your child to eat/drink during last 24hours?

1. Yes 2. Noa) Cow/goat milk

b) Baby food/ formula

c) Rice/wheat/bread

d) Yellow/orange fruit or vegetables

e) Green leafy vegetables

f) Vegetables

g) Others Fruits

h) Dal

i) Eggs

j) Fish

k) Chicken/Duck/Pigeon

l) Beef/Mutton

93. Has your child ever had diarrhoea (at least three loosestools in a day)?

1. Yes 2. No (Go to Q. 98)

94. When did your child have last diarrhoea?1. Last 24 hours2. Last 15 days3. Over 15 days ago

95. What liquid did you give to your child when he/she (last)had diarrhoea?

1. Yes 2. No

a) ORS

b) Laban gur/rice saline

c) Breast milk

d) Water

e) Medicine

f) Other liquid (specify)

96. Was he/she given the same amount of liquids to drink,more than usual to drink, or less than usual to drink duringdiarrhoea?

1. Less 2. Same3. More 4. Don't know


90


97. Was he/she given the same amount of foods to eat, morethan usual to eat, or less than usual to eat duringdiarrhoea?

1. Less 2. Same3. More 4. Don't know

98. Does any member of this household know to prepare saltand gur solution? [Enumerator: Please ask them todescribe the process, Tick the correct answer]

1. Yes 2. No

99. Has [name of child] had fever and severe cough during thelast two weeks?

1. Yes 2. No

100. Has [name of child] had measles during last three months?1. Yes 2. No

(Enumerator: Ask Q. 101-102 only to mothers/caregivers of children aged 18- 59 months)

101. Have you ever heard of night blindness?1. Yes 2. No (Go to Q. 103)

102. Is [name of child] night blind (cannot see well after sunset)?1. Yes 2. No

103. When [name of child] is sick, where do you usually seektreatment?

1. MBBS doctor (private/health clinic/hospital)2. Medicine taken from a person sitting in pharmacy3. Village doctor/Homeopath/Herbal 4. Spiritual water 5. No treatment/family treatment6. Others (Specify) _____________________

Measurements of child

104. a) MUAC of child aged 12-59 months (mm)

105. b) Length of chid aged 0-23 months (cm) Height of child aged 24-59 months (cm)

106. c) Child's weight (kg)

107. Are there any more children aged 0-59 monthsin this household?1. Yes (Fill up Form-3 for the next child from Q. 60)2. No

108. Are there any more mother/caretaker with children 0-59months old present in this household?

1. Yes (Take a new set of questionnaire and fill up allthe questions of Form-2 & 3)2. No (Complete interview after giving thanks)

Any other comments or observation:


Annex 4: Enumerators and supervisors

The enumerators for the CMNS 2005 were:

Ms. Shahida Begum, Statistical Investigator

Ms. Khodeza Begum, Statistical Investigator

Mr. Abid Mia, Statistical Investigator

Ms. Ferdous Mahal, Statistical Investigator

Ms. Jahan Afroz, Statistical Investigator

Ms. Nazneen Sultana Khan, Statistical Investigator

Mr. Muniruzzaman, Statistical Investigator

Mr. Wahidul Islam, Statistical Investigator

Mr. Mojaffar Rahman, Statistical Investigator

Mr. Abdul Hakim, Thana Statistician

Ms. Zaheda Begum, Statistical Assistant

Ms. Morsheda Begum, Statistical Assistant

Ms. Khohinoor Hossain, Statistical Assistant

Ms. Rokeya Begum, Statistical Assistant

Mr. A K M Faruk Ahmed Molla, Statistical Assistant

Ms. Setara Begum, Statistical Assistant

Mr. S. M. Anwar Husain, Statistical Assistant

Mr. Abdul Hamid, Statistical Assistant

Mr. Munir Ahmed, Statistical Assistant

Ms. Jahanara Begum, Statistical Assistant

Ms. Momtaz Begum, Statistical Assistant

Ms. Meherunnesa, Statistical Assistant

Mr. Sirajul Islam, Statistical Assistant

Ms. Purabi Rani Dev, Computer operator

Mr. Zahirul Hoque Sarker, Steno Typist

Ms. Monowara Begum, Draftsman

91


Ms. Josneara Begum, Junior Statistical Assistant

Ms. Ajija Begum, LDA

Supervisors from the Project Office were:

Mr. A K M Abdus Salam, Ex-Project Director, Monitoring the Situation of

Children and Women Project

Mr. Alamgir Hossain, Statistical Officer, BBS

Mr. Golam Razzak, Statistical Officer, BBS

Mr. Mizanur Rahman Khandaker, Statistical Officer, BBS

Mr. Mostafa Ashrafujjaman, Assistant Statistical Officer

Ms. Delwara Begum, Assistant Statistical Officer

Ms. Bejoya Biswas, Assistant Statistical Officer

92


Annex 5: Validation of survey results

To check the quality of the anthropometry data, a post-evaluation check (PEC)was conducting by comparing the data collected by the enumerators and qualitycontrol officers in a selected number of households. Table shows that there wereno significant differences between the mean values of the enumerator and qualitycontrol data.

Table A3: Comparison of quality control of anthropometry, CMNS 2005

A further check on the quality of anthropometry data was done by visuallyscanning the distribution graphs of child and mother age, weight and height tocheck for heaping of values. There was no major heaping in the children's data.Mother's age showed heaping in five year intervals, however this variable is notcritical for the estimation of a mother's nutrition status. Mothers' weight andheight were not heaped around whole numbers.

Another check on data quality was done by comparing non-anthropometricfindings with previous CNS surveys. Table 45 shows a sample of non-anthropometric data from the current survey; these data were consistent with thetrends from previous surveys.

93

Actual Survey Quality Control Survey

N Mean SD N Mean SD

Child height (cm) 266 82.8 11.8 266 82.8 11.8

Child weight (kg) 266 10.4 2.8 266 10.5 2.8

Child MUAC (cm) 218 14.5 1.1 218 14.5 1.0

Mother height (cm) 230 149.1 5.0 230 149.3 4.8

Mother weight (kg) 230 45.6 8.1 230 45.3 7.8

Mother MUAC (mm) 230 24.6 3.0 230 24.6 3.0


Table A4: Comparisons of non-anthropometry data from CMNS 2005 withprevious CNS

Annex 6: Estimation of weights

In this report, the data were weighted in order to determine divisional andnational estimates of nutritional status. Table 39 shows how the weights weredetermined.

94

CharacteristicsCNS1992(%)

CNS1996(%)

CNS2000(%)

CMNS2005(%)

Annualhouseholdexpenditure(Taka)

<20,000 21.9 11.1 6.2 1.7

20,0 00 - 34,999 35.4 32.1 27.5 20.1

35,000 - 49,999 19.9 20.6 23.2 23.9

50,000 and above 22.8 36.1 43.0 54.4

Sex ofhouseholdhead

Male 96.5 94.9 95.1 95.6

Female 3.5 5.1 4.9 4.4

Householdsize(persons)

<4 8.3 7.2 9.4 10.3

4 - 6 51.2 54.9 59.5 61.3

7 - 8 20.9 21.4 19.5 17.6

9 + 19.6 16.6 11.6 10.9

Mother'seducation

Never attend school 75.0 67.8 57.1 47.0

Passed class I - V 9.9 16.0 22.5 22.9

Passed class VI - IX 10.6 11.1 13.8 20.5

Passed class SSC and above 4.5 5.2 6.6 9.5

Familymember'sknowledgeof ORSpreparation

Yes 70.7 84.4 69.4 79.2

No 29.3 15.6 30.6 20.8

Diarrhoea in the previous two weeks 29.7 19.3 8.0 2.5

Safe drinking water (tap and tube well) 93.6 96.4 98.5 97.8


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Annex 7: Lists of household assets used for wealthindex

The following list of household assets and household characteristics were used inthe wealth index.

Household durable goods:RadioTVVCRDish antennaCassetteCameraMobile phoneTelephoneFridgeFanHeaterSewing machineComputerWashing machineWatchClockBicycleMotorcycleCarDrawing room furnitureBedroom furnitureDining room furnitureCarpetCutleryCrockeryCooker

96

Household characteristics:Separate dining roomSeparate kitchenRoof materials of living room of theHH headWall materials of living room of theHH headFloor materials of living room ofthe HH headElectricity Main source of drinking waterType of toilet facility


Annex 8: Members of the Technical Committeeand Technical Working Group

Technical Committee

1. Mr. A Y M Ekramul Hoque, Director General, BBS

2. Joint Secretary, Statistical Wing, Planning Division, Shere Bangla Nagar,Dhaka

3. Joint Secretary (United Nations), ERD, Shere Bangla Nagar, Dhaka

4. Deputy Secretary (Development), Statistical Wing, Planning Division,Shere Bangla Nagar, Dhaka

5. Joint Chief, SCYSWAM Wing, Planning Commission, Shere Bangla Nagar,Dhaka

6. Director General, Education and Social Sector, IMED, Shere Bangla Nagar,Dhaka

7. Director General, Directorate of Women Affairs , Eskaton Garden, Dhaka

8. Deputy Director General,Bangladesh Bureau of Statistics, Dhaka

9. Executive Director, National Nutrition Programme, Dhanmondi, Dhaka

10. Director, Primary Health Care, DG Health, Mohakhali, Dhaka

11. Director, Institute of Public Health and Nutrition, Mohakhali, Dhaka

12. Prof. Naila Z. Khan, Shishu Hospital, Shere Bangla Nagar, Dhaka

13. Director, Institute of Statistics Research and Training, Dhaka University,Dhaka

14. Director, Institute of Nutrition and Food Science, Dhaka University, Dhaka

15. Project Director, Household Income and Expenditure Survey Project, BBS,Dhaka

16. Director, Computer Wing, BBS, Dhaka

17. Director, Demography and Health Wing, BBS, Dhaka

18. Secretary in charge, Bangladesh National Nutrition Council,Mohammadpur, Dhaka

19. Ms. Misaki A Ueda, Chief, Planning Monitoring and Evaluation Section,UNICEF

20. Dr. Harriet Torlesse, Project officer, Health & Nutrition Section, UNICEF

21. Ms. Gudrun Stalkamp, Nutrition Program officer, HKI, Bangladesh

22. Md. Shamsul Alam, Project Director, MSCW Project

97


Technical Working Group

1. Mr. A Y M Ekramul Hoque, Director General, BBS

2. Mr. Abdur Rashid Sikder, Director, BBS

3. Mr. Md. Eshaque Ali, Secretary in charge, Bangladesh National NutritionCouncil (BNNC)

4. Dr. Tahmeed Ahmed, Head of Nutrition Unit, International Center forDiarrhoea Disease Research, Bangladesh (ICDDR'B), Dhaka.

5. Ms. Chantell Witten, Country Director, Helen Keller International (HKI)

6. Director, Institute of Public Health and Nutrition (IPHN)

7. ExecutiveDirector, National Nutrition Programme (NNP)

8. Director, Institute of Nutrition and Food Science (INFS)

9. Director, Research Division, Bangladesh Rural Advancement Committee(BRAC)

10. Md. Shamsul Alam, Project Director , MSCW Project

11. Dr. Harriet Torlesse, Project officer, Health and Nutrition Section, UnitedNations Children's Fund (UNICEF)

12. Mr. Nawshad Ahmed, Program officer, Planning Section, United NationsChildren's Fund (UNICEF)

13. Mr. Tapan Kumar Bhowmick, Deputy Director, BBS

14. Mr. Zahidul Huq Sarder, Deputy Director, BBS

98


Annex 99: Additional aanalysis oof aanthropometric ddata

Table A6: Mean weight, height and MUAC by sex and age

99

Age incompleted

months

Weight (kg) Height (cm) Mid-upper armcircumference (mm)

Girls Boys Total Girls Boys Total Girls Boys Total

0 3.4 3.4 3.4 52.1 52.0 52.0

1 4.1 4.3 4.2 54.1 54.9 54.6

2 4.9 4.8 4.9 57.6 57.0 57.3

3 5.1 5.6 5.3 58.9 61.0 59.9

4 5.6 6.4 6.0 61.0 63.2 62.1

5 6.3 6.6 6.5 63.7 64.5 64.2

6 6.3 7.2 6.7 64.6 67.0 65.8

7 6.7 7.4 7.0 65.8 67.5 66.5

8 7.1 7.6 7.3 67.9 68.9 68.4

9 6.9 7.7 7.4 67.6 69.9 68.8

10 7.4 8.0 7.6 68.8 71.6 69.6

11 7.4 7.9 7.7 70.3 71.4 70.9

12 7.7 8.1 7.9 70.6 72.7 71.7 134 138 136

13 7.8 8.5 8.2 71.5 73.5 72.5 133 139 136

14 7.8 8.5 8.2 71.5 74.1 72.9 133 137 135

15 8.0 8.8 8.4 73.4 74.4 73.9 135 139 137

16 8.2 9.0 8.7 74.4 75.4 75.0 133 139 137

17 8.5 9.0 8.8 75.2 76.9 76.1 134 139 137

18 8.7 9.5 9.2 76.0 76.2 76.1 131 140 136

19 8.2 9.2 8.8 74.6 79.0 77.2 132 138 136

20 8.9 9.8 9.2 76.7 79.0 77.5 138 141 139

21 8.9 9.4 9.1 77.0 78.3 77.7 135 139 137

22 9.6 9.1 9.3 78.8 79.1 79.0 141 137 139

23 9.6 9.9 9.8 79.1 79.4 79.3 135 142 138

24 9.8 9.7 9.7 80.9 80.0 80.5 139 141 140

25 9.6 10.3 10.0 81.1 82.0 81.6 138 141 140

26 9.9 10.8 10.3 81.2 83.7 82.4 138 143 140

27 10.1 10.3 10.2 81.7 82.6 82.3 141 142 142

28 10.0 11.6 10.7 81.8 86.8 84.0 139 146 142


100

Age incompleted

months

Weight (kg) Height (cm) Mid-upper armcircumference (mm)

Girls Boys Total Girls Boys Total Girls Boys Total

29 10.0 10.8 10.4 81.9 84.1 83.1 139 145 142

30 10.3 11.0 10.6 83.0 85.8 84.2 141 142 142

31 10.5 11.0 10.7 83.3 86.3 84.4 142 145 143

32 10.4 11.2 10.8 84.7 85.5 85.0 141 142 141

33 10.7 11.0 10.8 85.7 86.2 85.9 141 141 141

34 10.9 11.6 11.3 85.9 86.8 86.4 143 144 143

35 10.9 11.4 11.2 86.4 86.7 86.6 144 146 145

36 11.2 11.8 11.6 86.5 88.9 87.8 143 145 144

37 11.7 11.8 11.7 88.2 88.3 88.3 146 143 144

38 11.8 11.6 11.7 89.9 87.3 88.4 147 146 146

39 11.3 12.1 11.6 88.6 89.4 88.9 142 147 144

40 11.8 12.0 11.9 89.8 91.1 90.4 143 145 144

41 11.6 12.2 11.9 89.8 91.4 90.6 144 144 144

42 12.0 12.5 12.3 90.8 91.1 91.0 145 146 145

43 12.3 12.2 12.3 91.3 92.4 92.0 144 143 143

44 12.2 12.2 12.2 92.4 91.9 92.2 146 141 144

45 12.5 13.1 12.9 93.4 93.2 93.3 146 146 146

46 12.1 13.5 12.8 91.5 95.4 93.6 146 149 148

47 12.4 13.6 12.9 92.3 94.7 93.3 147 150 148

48 13.2 13.5 13.3 93.8 95.5 94.7 149 148 148

49 12.8 13.4 13.1 93.3 95.5 94.6 146 147 147

50 13.4 13.2 13.3 95.3 95.5 95.4 150 146 148

51 12.8 13.6 13.3 95.6 97.2 96.6 143 148 146

52 13.2 13.7 13.4 96.7 97.6 97.1 146 147 146

53 13.6 13.9 13.7 97.7 98.0 97.8 148 147 147

54 13.3 14.1 13.8 95.8 98.7 97.6 150 149 149

55 13.3 14.4 13.8 96.9 99.0 97.9 146 149 148

56 13.3 13.6 13.5 97.9 98.0 97.9 149 147 148

57 14.1 14.3 14.2 99.6 100.2 100.0 150 145 148

58 13.8 14.4 14.1 99.8 99.6 99.7 147 150 149

59 14.3 14.7 14.5 101.0 102.5 101.8 148 150 149

Total 10.2 10.8 10.5 82.3 83.9 83.1 116 120 118


Table A7: Mean WAZWHO, HAZWHO, WHZWHO and BAZWHO by age

101

Child age (months) WAZWHO HAZWHO WHZWHO BAZWHO

0 - 5

Mean -1.33 -0.78 -1.04 -1.24

SD 1.14 1.23 1.31 1.20

N 284 284 283 284

6 - 11

Mean -1.40 -1.04 -1.05 -1.09

SD 1.17 1.27 1.16 1.17

N 353 353 353 353

12 - 17

Mean -1.60 -1.73 -1.05 -0.80

SD 1.16 1.21 1.27 1.31

N 377 377 377 377

18 - 23

Mean -1.73 -2.23 -0.84 -0.46

SD 1.14 1.23 1.17 1.20

N 348 348 348 348

24 - 35

Mean -1.78 -2.09 -0.88 -0.62

SD 1.09 1.34 1.07 1.13

N 764 764 764 764

36 - 47

Mean -1.82 -2.14 -0.83 -0.59

SD 1.00 1.25 0.98 1.00

N 785 785 785 785

48 - 59

Mean -1.79 -1.96 -0.91 -0.75

SD 0.91 1.18 0.94 0.94

N 778 778 778 778

Total

Mean -1.70 -1.85 -0.92 -0.74

SD 1.07 1.33 1.09 1.13

N 3689 3689 3688 3689


Table A8: Distribution of malnutrition among children aged <5 years by sexand area of residence

102

Rural Urban NationalGirls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

WAZWHO

<-3.00 13.1 10.7 11.9 7.1 6.9 7.0 11.9 9.9 10.9

-3.00 to -2.01 28.3 32.3 30.3 22.6 23.2 22.9 27.1 30.4 28.8

-2.00 to -1.01 35.5 34.8 35.1 39.1 35.6 37.3 36.2 34.9 35.5

-1.00 to 0.99 21.8 21.3 21.5 28.9 31.1 30.1 23.2 23.3 23.3

1.00 to 1.99 1.3 0.7 0.9 1.9 2.9 2.4 1.4 1.1 1.2

2.00+ 0.2 0.2 0.2 0.5 0.3 0.4 0.2 0.2 0.2

HAZWHO

<-3.00 20.0 20.6 20.3 12.8 14.7 13.8 18.6 19.4 19.0

-3.00 to -2.01 28.2 28.8 28.5 20.9 23.2 22.1 26.8 27.7 27.2

-2.00 to -1.01 27.7 30.1 29.0 32.6 29.5 31.0 28.7 30.0 29.4

-1.00 to 0.99 22.3 18.4 20.3 29.8 29.4 29.5 23.7 20.7 22.2

1.00 to 1.99 1.4 1.9 1.6 3.2 3.0 3.1 1.8 2.1 1.9

2.00+ 0.4 0.2 0.3 0.7 0.2 0.4 0.5 0.2 0.3

WHZWHO

<-3.00 2.6 3.5 3.0 2.0 2.7 2.4 2.5 3.3 2.9

-3.00 to -2.01 12.2 11.8 12.0 11.3 8.5 9.8 12.0 11.1 11.6

-2.00 to -1.01 33.8 34.1 33.9 30.2 29.4 29.8 33.1 33.1 33.1

-1.00 to 0.99 46.9 47.5 47.2 53.1 52.4 52.7 48.1 48.5 48.3

1.00 to 1.99 3.4 2.5 2.9 2.1 5.2 3.7 3.1 3.0 3.1

2.00+ 1.2 0.7 1.0 1.4 1.7 1.6 1.2 0.9 1.1

BAZWHO

<-3.00 2.7 2.4 2.6 2.0 1.7 1.8 2.5 2.3 2.4

-3.00 to -2.01 10.0 9.4 9.7 9.1 7.9 8.5 9.9 9.1 9.5

-2.00 to -1.01 27.8 28.6 28.2 28.4 24.1 26.2 27.9 27.7 27.8

-1.00 to 0.99 54.1 54.6 54.4 56.0 57.9 57.0 54.4 55.3 54.9

1.00 to 1.99 3.8 3.9 3.9 3.1 5.9 4.6 3.7 4.3 4.0

2.00+ 1.6 1.0 1.3 1.4 2.4 1.9 1.6 1.3 1.4


103

Rural Urban NationalGirls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

WAZNCHS

<-3.00 13.8 9.4 11.5 6.7 6.2 6.4 12.4 8.8 10.5

-3.00 to -2.01 33.4 36.9 35.2 30.1 29.3 29.7 32.8 35.3 34.1

-2.00 to -1.01 35.0 35.9 35.5 37.9 35.2 36.5 35.6 35.7 35.7

-1.00 to 0.99 16.4 17.2 16.8 23.1 26.9 25.1 17.7 19.2 18.5

1.00 to 1.99 1.2 0.6 0.9 1.5 2.0 1.8 1.2 0.9 1.1

2.00+ 0.3 0.0 0.1 0.7 0.3 0.5 0.3 0.1 0.2

HAZNCHS

<-3.00 16.9 13.4 15.1 10.9 9.8 10.3 15.8 12.7 14.2

-3.00 to -2.01 25.4 28.3 26.9 18.9 21.2 20.1 24.1 26.9 25.5

-2.00 to -1.01 29.3 32.0 30.7 31.6 31.5 31.6 29.8 31.9 30.9

-1.00 to 0.99 26.2 24.4 25.3 34.1 34.3 34.2 27.7 26.5 27.1

1.00 to 1.99 1.8 1.5 1.7 3.9 3.2 3.5 2.2 1.9 2.0

2.00+ 0.3 0.2 0.3 0.7 0.0 0.3 0.4 0.2 0.3

WHZNCHS

<-3.00 0.8 1.5 1.2 0.0 0.7 0.4 0.6 1.3 1.0

-3.00 to -2.01 12.5 9.9 11.2 12.0 8.0 9.9 12.4 9.5 10.9

-2.00 to -1.01 41.5 43.8 42.7 35.8 40.4 38.2 40.4 43.1 41.8

-1.00 to 0.99 41.9 43.1 42.5 49.5 46.3 47.8 43.4 43.7 43.6

1.00 to 1.99 2.3 1.2 1.8 1.9 3.4 2.7 2.2 1.7 2.0

2.00+ 1.0 0.5 0.7 0.7 1.1 0.9 0.9 0.6 0.8

MUACZCDC/WHO

<-3.00 3.1 2.3 2.7 1.7 1.3 1.5 2.9 2.1 2.5

-3.00 to -2.01 25.4 28.2 26.8 16.2 17.5 16.9 23.6 26.0 24.9

-2.00 to -1.01 52.3 51.2 51.8 49.9 47.6 48.6 51.9 50.5 51.1

-1.00 to 0.99 19.1 17.9 18.5 31.4 31.8 31.6 21.5 20.7 21.1

1.00 to 1.99 0.0 0.3 0.2 0.6 1.5 1.1 0.1 0.5 0.3

2.00+ 0.0 0.1 0.0 0.3 0.4 0.3 0.1 0.2 0.1


Table A9: Prevalence of severe, moderate and total underweight (WAZWHO)by sex, age, and area of residence.

a Moderate -3.00 to -2.01; severe <-3.00; total <-2.00

104

Category aAge

group(month)


Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Moderate

0 - 5 20.4 19.4 19.8 12.3 9.8 11.0 18.8 17.6 18.1

6 - 11 20.8 30.0 25.0 17.6 17.4 17.5 20.1 27.2 23.4

12 - 17 31.9 34.8 33.5 30.4 33.3 32.0 31.7 34.5 33.2

18 - 23 30.6 32.2 31.4 18.4 28.1 24.1 28.5 31.3 30.0

24 - 35 22.3 34.6 28.3 25.1 24.3 24.7 22.9 32.5 27.5

36 - 47 32.5 36.2 34.4 20.1 21.0 20.6 30.2 33.1 31.7

48 - 59 34.1 31.0 32.4 27.2 24.4 25.6 32.7 29.6 31.0

0 - 23 26.3 29.6 28.0 19.8 23.2 21.6 25.0 28.3 26.7

24 - 59 29.5 33.9 31.7 24.2 23.2 23.7 28.4 31.7 30.1

0 - 59 28.3 32.3 30.3 22.6 23.2 22.9 27.1 30.4 28.8

Severe

0 - 5 3.6 11.3 7.9 11.6 6.5 8.9 5.2 10.4 8.1

6 - 11 8.9 7.5 8.3 3.5 4.8 4.1 7.7 6.9 7.4

12 - 17 11.0 8.8 9.8 1.1 9.2 5.7 9.3 8.9 9.1

18 - 23 11.3 14.7 13.0 11.5 6.2 8.4 11.4 12.8 12.1

24 - 35 19.8 11.4 15.7 6.7 7.8 7.2 17.1 10.7 14.0

36 - 47 16.4 10.2 13.2 6.2 6.7 6.5 14.5 9.5 11.9

48 - 59 9.6 10.8 10.2 9.7 6.6 7.9 9.6 9.9 9.8

0 - 23 9.1 10.6 9.9 6.4 6.7 6.6 8.6 9.8 9.2

24 - 59 15.5 10.8 13.1 7.5 7.0 7.2 13.9 10.0 11.9

0 - 59 13.1 10.7 11.9 7.1 6.9 7.0 11.9 9.9 10.9

Total

0 - 5 24.0 30.7 27.7 24.0 16.3 19.8 24.0 28.0 26.2

6 - 11 29.7 37.5 33.3 21.1 22.1 21.6 27.8 34.2 30.7

12 - 17 43.0 43.6 43.3 31.5 42.5 37.7 40.9 43.4 42.3

18 - 23 41.9 46.9 44.4 29.9 34.3 32.5 39.9 44.1 42.0

24 - 35 42.1 46.0 44.0 31.8 32.1 31.9 39.9 43.2 41.5

36 - 47 48.9 46.4 47.6 26.3 27.7 27.1 44.7 42.6 43.6

48 - 59 43.7 41.8 42.7 36.8 30.9 33.5 42.3 39.5 40.8

0 - 23 35.4 40.1 37.8 26.2 29.9 28.1 33.6 38.0 35.9

24 - 59 44.9 44.7 44.8 31.7 30.2 30.9 42.3 41.7 42.0

0 - 59 41.3 43.0 42.2 29.7 30.1 29.9 39.0 40.3 39.7


Table A10: Prevalence of severe, moderate and total stunting (HAZWHO) bysex, age, and area of residence.


105

CategoryaAge

group(month)


Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Moderate

0 - 5 4.7 9.0 7.1 6.4 16.8 12.0 5.0 10.5 8.0

6 - 11 14.1 20.9 17.2 7.2 13.0 9.8 12.6 19.2 15.6

12 - 17 23.4 28.3 26.1 22.9 25.5 24.4 23.4 27.7 25.7

18 - 23 32.1 29.9 31.0 26.8 28.7 27.9 31.2 29.7 30.4

24 - 35 31.9 30.8 31.4 28.2 23.4 26.0 31.1 29.3 30.3

36 - 47 35.2 37.4 36.3 20.0 31.1 26.1 32.4 36.1 34.3

48 - 59 33.1 28.9 30.8 23.5 18.4 20.6 31.2 26.6 28.7

0 - 23 19.5 22.7 21.1 15.3 21.6 18.6 18.7 22.5 20.6

24 - 59 33.4 32.4 32.9 24.2 24.2 24.2 31.6 30.7 31.1

0 - 59 28.2 28.8 28.5 20.9 23.2 22.1 26.8 27.7 27.2

Severe

0 - 5 4.9 7.6 6.4 2.5 1.5 2.0 4.4 6.4 5.5

6 - 11 5.7 6.6 6.1 3.9 10.2 6.7 5.3 7.4 6.3

12 - 17 15.2 16.0 15.6 5.2 14.1 10.2 13.4 15.6 14.6

18 - 23 25.6 32.9 29.2 18.5 21.9 20.5 24.4 30.4 27.5

24 - 35 25.2 24.5 24.8 14.6 17.5 16.0 23.0 23.1 23.0

36 - 47 25.4 24.8 25.1 12.6 16.3 14.7 23.0 23.1 23.0

48 - 59 21.1 20.5 20.8 20.9 14.1 17.1 21.1 19.1 20.0

0 - 23 13.3 16.2 14.8 7.2 12.7 10.2 12.1 15.5 13.9

24 - 59 24.0 23.2 23.6 16.0 15.9 15.9 22.4 21.7 22.0

0 - 59 20.0 20.6 20.3 12.8 14.7 13.8 18.6 19.4 19.0

Total

0 - 5 9.6 16.6 13.5 8.9 18.3 14.0 9.4 16.9 13.6

6 - 11 19.8 27.5 23.3 11.1 23.1 16.6 17.9 26.6 21.8

12 - 17 38.6 44.2 41.7 28.1 39.5 34.5 36.8 43.4 40.4

18 - 23 57.7 62.8 60.2 45.3 50.6 48.4 55.6 60.1 57.9

24 - 35 57.1 55.3 56.2 42.8 40.9 41.9 54.1 52.4 53.3

36 - 47 60.6 62.2 61.4 32.6 47.4 40.7 55.4 59.2 57.4

48 - 59 54.2 49.4 51.6 44.4 32.5 37.7 52.3 45.8 48.7

0 - 23 32.8 38.9 35.9 22.5 34.3 28.8 30.8 38.0 34.5

24 - 59 57.4 55.6 56.5 40.1 40.1 40.1 54.0 52.4 53.2

0 - 59 48.2 49.4 48.8 33.7 38.0 35.9 45.3 47.1 46.2


Table A11: Prevalence of severe, moderate and total wasting (WHZWHO) bysex, age, and area of residence.


106

Category aAge

group(months)


Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Moderate

0 - 5 14.0 19.2 16.8 21.6 7.8 14.1 15.5 17.0 16.3

6 - 11 16.7 12.4 14.7 12.0 14.8 13.2 15.7 12.9 14.4

12 - 17 15.2 18.7 17.1 16.7 11.4 13.7 15.4 17.3 16.4

18 - 23 9.6 12.8 11.2 14.4 11.9 12.9 10.4 12.6 11.5

24 - 35 13.7 10.5 12.1 9.3 6.8 8.1 12.8 9.8 11.3

36 - 47 7.6 8.9 8.3 7.7 4.6 6.0 7.6 8.1 7.8

48 - 59 12.4 8.9 10.5 9.5 8.8 9.1 11.8 8.8 10.2

0 - 23 13.9 15.9 14.9 15.6 11.6 13.5 14.2 15.0 14.6

24 - 59 11.2 9.4 10.3 8.9 6.8 7.8 10.8 8.9 9.8

0 - 59 12.2 11.8 12.0 11.3 8.5 9.8 12.0 11.1 11.6

Severe

0 - 5 9.7 5.4 7.3 13.5 6.4 9.6 10.4 5.6 7.8

6 - 11 6.6 2.9 4.9 5.4 1.2 3.5 6.4 2.6 4.6

12 - 17 4.3 8.0 6.3 0.0 5.4 3.0 3.6 7.5 5.7

18 - 23 0.0 6.9 3.5 0.0 2.1 1.2 0.0 5.9 3.0

24 - 35 1.9 3.2 2.5 1.5 3.2 2.3 1.8 3.2 2.5

36 - 47 1.2 2.1 1.7 0.0 1.5 0.8 1.0 2.0 1.5

48 - 59 0.4 0.8 0.6 0.0 1.9 1.1 0.3 1.0 0.7

0 - 23 4.9 6.0 5.5 4.5 3.7 4.1 4.8 5.5 5.2

24 - 59 1.2 2.0 1.6 0.6 2.1 1.4 1.1 2.0 1.6

0 - 59 2.6 3.5 3.0 2.0 2.7 2.4 2.5 3.3 2.9

Total

0 - 5 23.7 24.6 24.2 35.1 14.1 23.7 25.9 22.6 24.1

6 - 11 23.4 15.3 19.7 17.4 16.0 16.8 22.0 15.4 19.0

12 - 17 19.5 26.7 23.4 16.7 16.8 16.8 19.0 24.8 22.2

18 - 23 9.6 19.7 14.6 14.4 14.0 14.2 10.4 18.4 14.5

24 - 35 15.5 13.7 14.7 10.8 10.0 10.4 14.6 13.0 13.8

36 - 47 8.8 11.1 10.0 7.7 6.1 6.8 8.6 10.1 9.4

48 - 59 12.9 9.6 11.1 9.5 10.6 10.1 12.2 9.8 10.9

0 - 23 18.8 21.9 20.4 20.0 15.3 17.5 19.0 20.6 19.8

24 - 59 12.4 11.4 11.9 9.4 8.9 9.1 11.8 10.9 11.3

0 - 59 14.8 15.3 15.1 13.3 11.2 12.2 14.5 14.5 14.5


Table A12: Prevalence of overweight (BAZWHO>2.00) by sex, age, and areaof residence.

107

Age group(months)


Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

Girls(%)

Boys(%)

Total(%)

0 - 5 1.0 1.2 1.1 2.8 0.0 1.5 1.3 1.0 1.2

6 - 11 0.0 1.6 0.9 2.6 0.0 1.2 0.6 1.3 0.9

12 -17 2.2 4.2 3.1 0.0 0.0 0.0 1.8 3.4 2.5

18 - 23 2.6 2.6 2.6 2.1 0.0 1.2 2.5 2.2 2.3

24 - 35 1.5 1.0 1.3 3.2 2.0 2.6 1.8 1.2 1.5

36 - 47 0.7 1.5 1.1 1.8 2.1 1.9 0.9 1.6 1.2

48 - 59 0.0 0.9 0.4 1.1 2.4 1.7 0.2 1.2 0.7

0 - 23 1.5 2.5 2.0 1.8 0.0 1.0 1.6 2.0 1.8

24 - 59 0.7 1.1 0.9 1.9 2.2 2.1 1.0 1.3 1.1

0-59 1.0 1.6 1.3 1.9 1.4 1.6 1.2 1.6 1.4


Annex 10: Comparison of child anthropometrydetermined using the NCHS 1977 GRSand WHO 2005 GRS

Figure A1: Comparison of the WHO 2005 and NCHS 1977 GRS estimatesof severe and moderate underweight

Figure A2: Comparison of the WHO 2005 and NCHS 1977 GRS estimatesof severe and moderate stunting

108

Pre

vale

nce (

%)

NCHS 1977 WHO 2005

Moderate Severe All

26

14

40

27

19

46

0

10

20

30

40

50

Pre

vale

nce (

%)

NCHS 1977 WHO 2005

Moderate Severe All

34

11

45

29

11

40

0

10

20

30

40

50


Figure A3: Comparison of the WHO 2005 and NCHS 1977 GRS estimates ofsevere and moderate wasting

109

Pre

vale

nce (

%)

NCHS 1977 WHO 2005

Moderate Severe All

10.9

1.0

11.911.6

2.9

14.5

0

2

4

6

8

10

12

14

16


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