Prevalence of Under Nutrition in 0-5 Year Children of...

Prevalence of Under Nutrition in 0-5 Year Children of Junagadh District, Gujarat

Dr. Apurvadan N Ratnu

Dissertation submitted in partial fulfillment of the requirement for the

award of the degree of Master of Public Health

Achutha Menon Centre for Health Science Studies

Sree Chitra Tirunal Institute for Medical Sciences and Technology

Thiruvananthapuram, Kerala, India

October, 2012

CERTIFICATE

I hereby certify that the work embodied in this dissertation titled

“Prevalence of under nutrition in 0-5 year children of Junagadh district, Gujarat” is a

bonafide record of original research work undertaken by Dr. Apurvadan N Ratnu, in

partial fulfillment of the requirements for the award of the degree of Master of

Public Health, under my guidance and supervision.

Guide

Dr. Ravi Prasad Varma

Assistant Professor




October, 2012

CERTIFICATE

I hereby certify that the work embodied in this dissertation titled

“Prevalence of under nutrition in 0-5 year children of Junagadh district, Gujarat” is a

bonafide record of original research work undertaken by Dr. Apurvadan N Ratnu, in

partial fulfillment of the requirements for the award of the degree of Master of

Public Health, under my guidance and supervision.

Co-Guide

Ms. Jissa VT,

Scientist B,




October, 2012

DECLARATION

I hereby declare that this dissertation work titled “Prevalence of under nutrition

in 0-5 year children of Junagadh district, Gujarat” is an original work of mine and it has

not been submitted to any institution or university.

Dr. Apurvadan N Ratnu




October, 2012

Acknowledgement

First of all I would like to thank the almighty for giving me courage to seek the path

of knowledge. I am grateful to him for the strength he provided to undertake this

journey.

I would like to express my sincere gratitude to my guides Dr. Ravi Prasad Varma and

Ms. Jissa VT for their supervision, guidance and encouragement to improve my

dissertation. I am indebted to both of them for their support.

I would like to take this opportunity to convey my thanks to all the faculties at AMCHSS

Dr. K R Thankappan, Dr. V Raman Kutty, Dr. TK Sundari Ravindran, Dr. Mala

Ramanathan, Dr. Biju Soman, Dr. Manju Nair and Dr. K Srinivasan for their valuable

inputs during the process.

I would like to say thanks to all my colleagues, especially my dear friends Dr. Saumya

Ranjan Mishra and Mr. Sanjeev Kr Singh for their support and encouragement. I would

like to convey my sincere thanks to Dr. Komal Raycha for her valuable input during the

process.

I am grateful to all the participants who participated or declined to participate in the

study. They made my study what it is. I am especially thankful to all small children who

selflessly participated in the study.

And finally, I would like to express my gratitude to my wife Gopi. She has been my

greatest strength during this entire journey. I would like to say thanks to her for the

untiring support and love.

I dedicate this work to my son

“DHYAN”

Who inspired me to take this research

Table of contents

List of tables

List of figures

Abbreviations

Abstract

CHAPTER 1: INTRODUCTION AND LITERATURE REVIEW

1.1 Introduction 1

1.2 Literature review 3

1.2.1 Definition 3

1.2.1.1 Oxford dictionary 3

1.2.1.2 UNICEF 3

1.2.1.3 A dictionary of Epidemiology (Last JM) 3

1.2.2 Diagnosis 4

1.2.2.1 ‘physical growth record’ 4

1.2.2.2 ‘Harvard growth curves’ 4

1.2.2.2.1 Garrow’s Classification 5

1.2.2.2.2 Gomez classification 6

1.2.2.3 NCHS (National Center for Health Statistic) classification 6

1.2.2.3.1 IAP (Indian Association of Pediatrics) classification 6

1.2.2.4 WHO Classification 7

1.2.2.4.1 multicentre growth reference study 7

1.2.2.4.2 WHO growth standards 7

1.2.2.4.3 Critique of WHO classification 8

1.2.2.4.4 Growth Reference vs Growth Standards 8

1.2.3 Causes of Malnutrition 11

1.2.3.1 Maternal Factors 12

1.2.3.1.1 Antenatal Coverage 13

1.2.3.1.2 Pre pregnancy weight 13

1.2.3.1.3 Weight gain during pregnancy 13

1.2.3.2 Child Factors 14

1.2.3.2.1 low birth weigh 14

1.2.3.2.2 exclusive breast feeding 14

1.2.3.3 Immunization 14

1.2.3.4 Diarrhoeal diseases 15

1.2.3.5 Acute respiratory infections 17

1.2.3.6 Social determinants of under nutrition 17

1.2.3.7 Growth Physiology 20

1.2.4 Disease Burden 20

1.2.4.1 Global burden 20

1.2.4.2 Burden in India 21

1.2.4.3 Burden in Gujarat 22

1.2.5 Interventions by State 23

1.2.6 Rationale 24

1.2.7 Objectives 25

CHAPTER 2: METHODOLOGY

2.1 Study type 26

2.2 Study settings and Target population 26

2.3 Sample size estimation 26

2.4 sample selection procedure 26

2.4.1 cluster selection 26

2.4.2 subject selection 27

2.4.2.1 inclusion criteria 27

2.4.2.2 exclusion criteria 28

2.5 Data collection technique 28

2.5.1 interview schedule 28

2.5.2 anthropometric measurements 29

2.5.2.1 Weight measurement protocol 29

2.5.2.2 height/length measurement protocol 30

2.5.2.2.1 height measurement 30

2.5.2.2.2 length measurement 31

2.6 ethical considerations 31

2.6.1 Non malfeasance 32

2.6.2 Beneficence 32

2.6.3 Autonomy 32

2.6.4 Justice 33

2.7 Data collection 33

2.7.1 inter rater reliability 33

2.7.2 data collection 33

2.7.3 data quality management 33

2.8 Data analysis 34

2.9 variables used in study 34

2.9.1 Outcome variables 34

2.9.2 Predictor variables 35

2.9.3 operationalization of variables 36

2.9.4 Outcome variable classification for multinomial logistic

regression

38

CHAPTER 3: RESULTS

3.1 Sample characteristics 39

3.2 Description of Predictor variables 40

3.3 Prevalence of under nutrition 41

3.4 Association of socio economic status with under nutrition 42

3.5 Association of Immunization with under nutrition 43

3.6 Association of morbidities with under nutrition 43

3.7 Association of age with under nutrition 45

3.8 Association of sex with under nutrition 46

3.9 Other signification variables for under nutrition 47

3.10 Multiple logistic regression modeling for under nutrition 47

3.11 Multinomial logistic regression modeling 50

3.12 Association between predictor variables and any under nutrition 52

CHAPTER 4: DISCUSSION

4.1 Prevalence of under nutrition 54

4.2 Underweight 55

4.3 Stunting 56

4.4 Wasting 58

4.5 Effect of age on under nutrition 58

4.6 determinants of moderate vs sever underweight 58

4.7 Recommendations 59

4.8 Strengths 60

4.9 Limitations 61

4.10 Conclusions 61

Annexure I: BMI for age chart from WHO and CDC

Annexure II: List of taluks in Junagadh district

Annexure III: Consent form for participation

Annexure IV: Questionnaire

LIST OF TABLES

CHAPTER 1 INTRODUCTION AND LITERATURE REVIEW Page no

Table 1.1: prevalence of underweight and stunting based on WHO and IAP classifications 10

Table 1.2: Immunization status and prevalence of nutritional status and morbidities 15

Table 1.3: Under nutritional status and poor rich ratio based on wealth quintiles 18

Table 1.4: Under nutrition (severe) status and poor rich ratio based on wealth quintiles 18

Table 1.5: differential vulnerabilities, exposure, outcome and consequence based on SES 19

CHAPTER 2 METHODOLOGY

Table 2.1: definition of under nutrition based on WHO classification 35

Table 2.2: Immunized for age children classification 37

Table 2.3: SES classification 38

CHAPTER 3 RESULTS

Table 3.1 age/sex distribution of sample 39

Table 3.2 maternal characteristics 40

Table 3.3 Prevalence of Under Nutrition 41

Table 3.4 Socio Economic status and under nutrition (bivariate analysis) 42

Table 3.5: Immunization and under nutrition (bivariate analysis) 43

Table 3.6: morbidity and underweight (bivariate analysis) 44

Table 3.7: morbidity and stunting (bivariate analysis) 44

Table 3.8: morbidity and wasting (bivariate analysis) 45

Table 3.9: age group and under nutrition (bivariate analysis) 46

Table 3.10: Association between sex and under nutrition (bivariate analysis) 46

Table 3.11: predictor variables having significant association (bivariate analysis) 47

Table 3.12:Binary logistic regression model –Under weight 48

Table 3.13:Binary logistic regression model –Stunting 48

Table 3.14:Binary logistic regression model –Wasting 49

Table 3.15: Association of predictor variables with various categories of underweight 50

Table 3.16: Multinomial Logistic Regression model for Underweight 51

Table 3.17 Socio Economic status and under nutrition (bivariate analysis) 52

Table 3.18:Binary logistic regression model – Moderate & Severe Under nutrition 53

LIST OF FIGURES

Figures Page No.

Figure 1.1: ‘Physical growth records’ by H V Meredith, 1949 5

Figure 1.2: weight for age distribution. WHO standards and NFHS III

data

9

Figure 1.3: height for age distribution. WHO standards and NFHS III data 10

Figure 1.4: Under nutrition framework (UNICEF) 12

Figure 1.5: Malnutrition – infection: the vicious cycle

16

Figure 4.1 Comparison of under nutrition between NFHS II, NFHS III

and present study

54

Figure 4.2 comparison of underweight prevalence between DLHS II and

present study

55

Figure 4.3 causal pathways for moderate and severe under nutrition 59

LIST OF ABBREVIATIONS

ANC Antenatal Care

ARI Acute Respiratory Illness

BCG Bacilli Calmette Guerin (Vaccine)

BMI Body Mass Index

CDC Centre For Diseases Control

CDNCs Child Development And Nutrition Centre

DALYs Disability Adjusted Life Years

DLHS District Level Household Survey

DPT Diptheria, Pertusis And Tetanus Vaccine

HAZ Height For Age Z Score

HFA Height For Age

HIB Hemophilus Influenza B

HUNGaMA Hunger And Malnutrition Report 2012

IAP Indian Association Of Pediatrics

ICDS Integrated Child Development Services

LBW Low Birth Weight

MDGS Millennium Development Goals

MGRS Multicenter Growth Reference Study

MUAC Mid Upper Arm Circumference

NCD Non Communicable Diseases

NCHS National Centre For Health Statistics

NFHS Natinal Family Health Survey

OR Odds Ratio

ORS Oral Rehydration Salt

SAM Sever Acute Malnutrition

SD Standard Deviation

SES Socio Economic Status

UNICEF United Nation Children's Emergency Fund

URTI Upper Respiratory Tract Infection

USA United States Of America

WAZ Weight For Age Z Score

WFA Weight For Age

WFH Weight For Height

WHO World Health Organization

WHZ Weight For Height Z Score

ABSTRACT

Introduction: Under nutrition among 0–5 year children remains major public health

problem in India. Prevalence of under nutrition has not declined in past decade.

Junagadh district of Gujarat state had high prevalence of underweight children

(44%) as per DLHS II, 2004. However there are no attempts thereafter to assess the

nutritional status of children in the district. Present study tries to estimate

prevalence of under nutrition in Junagadh district.

Methodology: Cross sectional household survey was conducted using multi stage

cluster design. Total 459 children were randomly selected from 48 clusters of 3

taluks. Interview schedule was administered to mother or other respondent and

anthropometric measurements were taken. Analysis was performed using SPSS

software. Logistic Regression analysis was carried out to measure association

between predictor variables and under nutrition.

Results: The prevalence of underweight, stunting and wasting was 26.4%, 49% and

10.7% respectively. More than half of the children (58.2%) suffered from any kind

of under nutrition while 27.9% children were suffering from at least one severe

under nutrition. Higher age, Low birth weight (LBW) and lower Socio economic

status (SES) were significantly associated with underweight. Diarrhoea, higher age,

complete Antenatal Checkup (ANC), mother’s age > 30 years and LBW were

significantly associated with stunting, while cough in last 2 weeks and lower SES

were significantly associated with wasting.

Conclusion: The prevalence of underweight has precipitously reduced in district

over period of 8 years. However, high level of stunting, a sign of chronic hunger,

points towards food insecurity among children in the state. SES still remains major

determinant of child nutritional status. Interaction with health system in form of

ANC, institutional delivery, immunization and treatment for morbidity has shown

preventive effect. These services should be strengthened further to improve overall

nutritional status of the children.

1

CHAPTER 1

1.1 INTRODUCTION

Public health attempts to identify problems affecting people’s health and tries to

solve them. There are many shining examples of public health intervention leading to

improved public health. It ranges from small pox eradication, immunization programme,

reducing maternal mortality, life style modifications for non communicable diseases,

tobacco control efforts etc.

However under nutrition among children remains a challenge till date, despite

identification of the problem for more than a century. Efforts to prevent or control under

nutrition have not been very successful. Not much technical expertise is required to

prevent most of the cases of under nutrition as they are due to lack of hygiene or lack of

sufficient and appropriate food. Despite having enough food to feed everyone on the face

of earth, many are left to die due to hunger.1 Proper nutrition is essential for the physical

and mental growth of the child. Healthy children of today will become health citizens of

tomorrow.

Children are the most affected age group by under nutrition. 21.37% under five

children are under nourished in the world. South East Asia (42.48%) and Sub Saharan

Africa (24.57%) has the highest burden of under nutrition.2 Under nutrition is responsible

for 2.2 million deaths and 21% disability adjusted life years (DALYs) for under five

children annually.3 In fact most of these deaths are preventable. India is the 2

nd most

populated country in the world with population of more than 1210 million. Children less

than six constitute sizable proportion of this population (158 million).4 Unfortunately,

2

this population is worst affected by under nutrition as 43% of under five children are

under weight. The distribution of under nutrition in India is not uniform and there are

considerable INTERSTATE and INTRASTATE variations in the country.5

The government is putting sincere effort to address this problem. Improving ICDS

(Integrated Child Development Services) services, mid day meal schemes etc are

attempts to provide adequate nutritious food to the children. One major limitation of the

above intervention is institutionalization of the effort. This institutionalization excludes

all the children not attending these institutions. To address this problem National Food

Security Bill was envisaged to provide nutritious cooked food to the children irrespective

of their enrollment status with the institutions.6 However as Virchow noted ‘policy is

politics’, this bill has not become law yet and there is very little hope that it will be

implemented in its original form.

Periodic estimates provide a yardstick for measuring efficacy of the interventions.

National level estimates for under nutrition were first measured during 1992-93 in NFHS-

I (National Family health Survey).7 This was followed by NFHS-II

8 in 98-99 and NFHS-

III in 2005-06. However NFHS measured state level prevalence of under nutrition and

did not provide estimate for the districts in the state. District level prevalence was

measured in DLHS I & II (District level household suvey). However prevalence of under

nutrition was dropped from DLHS-III (07-08). At the beginning of this year,

‘HUNGAMA’ report specifically addressed this problem of under nutrition and measured

its prevalence in 100 worst performing districts across 10 states.9 However for rest of the

states, estimates from NFHS-III are now 7 years old.

3

1.2 LITERATURE REVIEW

1.2.1 DEFINITION OF MALNUTRITION

Nutrition is defined as ‘the process of providing or obtaining the food necessary

for health and growth’ (Oxford dictionary). ‘Malnutrition’ is the term widely used to

define under nutrition. The term ‘under nutrition’ came in prominence after rise of Non

Communicable Diseases (NCDs) which also represent the other end of nutrition.

Ambiguity on term malnutrition is increasing as more and more NCD literature uses this

term. Various definitions exist for the term malnutrition.

1.2.1.1 Oxford dictionary10

Malnutrition is defined as “Lack of proper nutrition, caused by not having enough

to eat, not eating enough of the right things, or being unable to use the food that one does

eat”.

1.2.1.2 UNICEF (United Nations International Children's Emergency Fund)11

“Malnutrition is a broad term commonly used as an alternative to under nutrition

but technically it also refers to over nutrition. People are malnourished if their diet does

not provide adequate calories and protein for growth and maintenance or they are unable

to fully utilize the food they eat due to illness (under nutrition). They are also

malnourished if they consume too many calories (over nutrition)”.

1.2.1.3 A Dictionary of Epidemiology (Last JM, 5th

Edition)12

Last dictionary of epidemiology defines ‘child nutrition’ as below,

4

Underweight: A composite measure of protein-energy malnutrition, indicated by low

weight for age.

Stunting: A measure of protein-energy malnutrition, indicated by low height for age or

failure to achieve expected stature.

Wasting: A measure of protein-energy malnutrition that occurs when a child’s weight for

height falls significantly below what is expected in the reference population; an indicator

of current malnutrition.

1.2.2 DIAGNOSIS

Diagnosis of under nutrition has changed significantly over the time with

sophistication of anthropometric measurements. First attempt was done by Howard V

Meredith in children from Iowa state, USA in 1949.13

1.2.2.1 “Physical growth record” for use in elementary and high schools.

This classification was developed for the school children of Iowa State, USA based on a

small sample of children from higher socio economic status. It included 3 parameters to

assess physical growth namely height, weight and age of the child. (Figure 1.1)

1.2.2.2 “Harvard growth curves”14

In early 1960’s Harvard growth curves became standard for nutritional

assessments. They were superior compared to previous charts and received great support.

In 1966 this chart was used by WHO for measuring growth in children. Harvard growth

curves has significant contribution towards clinical nutritional assessment as 2 most

famous clinical criteria Garrow classification and Gomez classification uses Harvard 50th

percentile as reference value.

5

Figure 1.1: ‘Physical growth records’ by H V Meredith, 1949.13

1.2.2.2.1 Garrow’s classification15

There were 4 major criteria used in Garrow’s classification.

a. No child is considered to be severely malnourished unless his weight is below

70% of the expected weight for age, using Harvard standards.

b. Kwashiorkor: child at minimum weight not less than 60% of expected weight for

age; oedema present, plus either hepatomegaly or dermatosis.

c. Marasmus: child with less than 60% of expected weight for age; no oedema or

other specific signs.

d. Marasmic Kwashiorkor: child with less than 60% of expected weight for age with

oedema or other signs.

6

1.2.2.2.2 Gomez classification15

This is most famous criteria for the diagnosis of under nutrition. Majority of the

medical schools across the world use these criteria in clinical practice of paediatrics.

Three categories of under nutrition in Gomez classification were based on

standard weight for age (Harvard fiftieth percentile).

a. First degree: 90-75% of standard weight for age

b. Second degree: 75-60% of standard weight for age

c. Third degree: less than 60% of standard weight for age

1.2.2.3 NCHS (National Center for Health Statistics) standards16

Considering limitations with Harvard growth curves, Center for Disease Control

(CDC) and NCHS came up with new anthropometric classifications in 1974, widely

known as NCHS curves. They were revised in year 2000. They served as international

growth standards till WHO growth standards-2004 were accepted as international

reference. Indian Association of Pediatrics also accepted this chart as reference.17

1.2.2.3.1 IAP Classification (Indian Association of Pediatrics)17

IAP classification uses NCHS standards for defining under nutrition. It is more

similar to Gomez classification, except for the cut off points used for severity

determination.

a. Grade I : 71 – 80 % of standard weight for age

b. Grade II: 61 – 70 % of standard weight for age

c. Grade III: 51 – 60% of standard weight for age

d. Grade IV: < 50% of standard weight for age

7

1.2.2.4 WHO Classification

1.2.2.4.1 Multicentre growth Reference Study (MGRS)18

WHO classification is the current accepted diagnostic criteria for under nutrition.

This criterion was developed following the multicentre growth reference study (MGRS).

Children from six countries Brazil, Ghana, India, Norway, Oman and United States of

America (USA) were recruited for this prospective study. At the end of this study, WHO

came up with standard cut off points for all three parameters of under nutrition namely

stunting, wasting and under weight.

1.2.2.4.2 WHO Growth Standards19

a. Stunting: child with height-for-age (HFA) z-score that is at least 2 standard

deviations (SD) below the median for the WHO child growth standards.

b. Wasting: child with weight-for-height (WFH) z-score that is at least 2 SD below

the median for the WHO child growth standards.

c. Under weight: child with weight-for-age (WFA) z-score that is at least 2 SD

below the median for the WHO child growth standards.

WHO classification is universally accepted for diagnosis of under nutrition. Apart

from these criteria WHO also defines Sever under nutrition. Any nutritional parameter

(WFA, HFA or WFH) less than -3SD is considered as severely under nourished.

WHO provides range of other parameters for measuring nutritional status apart

from growth standards. These parameters are developed based on multi centric growth

reference study. These parameters include MUAC (Mid Upper Arm Circumference) for

8

age, Body Mass Index for age, Head circumference for age, sub scapular skin fold for

age, triceps skin fold for age, motor development milestones, weight velocity, length

velocity and head circumference velocity.

1.2.2.4.3 Critique of WHO classification

MGRS conducted from 1997 to 2003 was the base of current WHO growth

standards. MGRS had certain inclusion and exclusion criteria (table) for participation in

the study. There has been major criticism on selection criteria for MGRS study.

Optimal nutrition

Exclusive or predominant breastfeeding for at least 4 months

Introduction of complementary foods by age of 6 months

Partial breastfeeding to be continued for at least 12 months

Optimal Environment

No microbiological contamination

No smoking

Optimal healthcare

Immunization

Pediatric routine

1.2.2.4.4 Growth Reference vs Growth standard:20

CDC defines WHO criteria as growth standard than a reference - “The WHO

charts are growth standards that describe how healthy children should grow under

optimal environmental and health conditions”. They represent growth pattern of children

during given time and place, in case of CDC children of USA during (63-94).

9

It has been argued that all children may not be able to have optimal health and

environmental conditions. In all such situations child may be thriving well without any

disease and yet be classified as under nourished as per the standard. This phenomenon is

true more for the developing countries where health and environmental conditions may

be suboptimal yet all children are not under nourished. Population distribution of child

growth is shifted towards left compared to WHO growth standards.

Evidence for these comes from analysis of NFHS-III data by Prema Ramchandran

against WHO growth standards.21

It is evident from figure 2 that entire distribution has

shifted left. +2SD values for Indian population corresponds to median value in WHO

growth standards and median value for Indian population is almost equivalent to -2SD

value. This analysis implies that nearly 50% children in India are under weight. Similar

phenomenon is observed in height for age also. (figure 1.2, 1.3)

Figure 1.2: weight for age distribution. WHO standards and NFHS III data

Black line denotes WHO standards and red line denotes Indian population21

10

Similar results were found in a cross sectional study from Karnataka where WHO

growth standards were compared with IAP standards.22

Table 1.1 explains that nearly

20% of children diagnosed ass stunted and 10% children diagnosed as underweight are

normal according to IAP standards.

Parameter Sex WHO IAP P value

Underweight Male (n=1137) 791 (69.6%) 676 (59.4%) <0.0001

Female (n=968) 606 (62.6%) 601 (62.1%) 0.935

Stunting Male (n=1137) 897 (78.8%) 709 (62.3%) 0.001

Female (n=968) 789 (81.5%) 613 (63.3%) 0.001

Table 1.1: prevalence of underweight and stunting based on WHO and IAP

classifications.22

Figure 1.3: height for age distribution. WHO standards and NFHS III data Black line denotes WHO standards and red line denotes Indian population21

11

Similar results were obtained in various international studies as well. One study in

Niger demonstrated 8 fold increase in diagnosis of Severe Acute Malnutrition (SAM)

using WHO classification compared to previous NCHS (national center for health

statistics) reference. This increased SAM cases has serious implications on under

nutrition programmes especially in developing countries.23

USA uses CDC (Center for Disease Control) growth standards for estimating

under nutrition. In the revised guidelines by CDC and American Academy of Pediatrics,

WHO standards are used up to age <24 months. CDC growth standards are to be used for

growth measurement in person from age 2 to 19 years.

1.2.3 CAUSES OF MALNUTRITION

Malnutrition is caused by a multitude of the factors. Causes of malnutrition can be

divided broadly in to medical, social, economical and political. This is one of the most

studied subjects in public health. UNICEF classified these causes into the hierarchy and

provided frame work for better understanding. (Figure 1.4)

This classification is very useful in creating hierarchical model for under

nutrition. Irrespective of basic and underlying causes there are only 2 immediate causes

of malnutrition such as diseases and inadequate dietary intake.24

important determinants

of nutritional status of child are described briefly in coming sections.

12

Figure 1.4: Under nutrition framework (UNICEF)24

1.2.3.1 Maternal factors

Intrauterine period is most important developmental period in child’s life where it

grows from single cell embryo to fully developed child. First 3 months are the most

important period in child development. Lack of proper nutrition during this period may

lead to lifelong disability. Classic example is of neural tube deficit attributable to folate

deficiency.

13

Lack of proper nutrition during pregnancy is one of the important causes for low

birth weight. Multitude of factors affects this pathway of maternal nutrition to birth

weight.

1.2.3.1.1 Antenatal Coverage

Various studies found association between antenatal care and low birth weight.

Compared to 5 or more Antenatal care visits, under visitors (1-5 times) and non visitors

(no ANC) had Odds Ratio (OR) of 9.18 (6.65-12.68) and 5.46 (3.90 – 7.65) respectively

of having low birth weight baby.25

However, quality of ANC is also important than just number of visits. Study used

2 proxy measures for quality of ANC, tetanus toxoid injections and guidance on where to

go for pregnancy related complications. Study found lower OR of having small sized

babies in quality services group.26

1.2.3.1.2 Pre pregnancy weight

Pre pregnancy weight represents overall nutritional status of mother. It is

associated with higher level of low birth weight. Study in Maharashtra found that pre

pregnancy weight < 45 kg was associated with high chance of Low Birth Weight (LBW)

(OR= 4.41, 2.30-8.46) compared to pre pregnancy weight > 45 kg.27

Another prospective

cohort study from Pune found relative risk for LBW 1.3 in pre pregnancy weight < 40 kg

compared to reference group (40-45 kg).28

1.2.3.1.3 Weight gain during pregnancy

14

This is most important factor determining birth weight of child. Importance of

weight gain can be ascertained by study conducted by Luke. Her study found that

Chinese mothers having equal pregnancy weight gain had equal weights of infants,

despite their lower pre pregnancy weights compared to control group of western

mothers.29

1.2.3.2 Child factors

1.2.3.2.1 Low birth weight

Low birth weight is under nutrition (under weight) at age 0. In her paper (South

Asian Enigma) Monica Das Gupta has identified three major factors responsible for

higher level of under nutrition in Indian population compared to African subcontinent

namely, low birth weight, women empowerment and hygiene & sanitation. Higher

incidence of Low birth weight in India (28%) compared to 16% in African setup makes

nearly one third children begin their lives with disadvantage as such.30

1.2.3.2.2 Exclusive breast feeding

Exclusive breast feeding has protective effect, if provided for appropriate

duration. Beyond certain point continuing breast feeding may be risk for under nutrition

itself. Weaning should be started at appropriate age. Cut off point for this consideration is

an issue of debate. Wafie found significant less weight gain in breastfed children of 6 to

12 months compared to completely weaned children of same age group.31

1.2.3.3 Immunization

15

A recent study conducted in Indonesia which collected immunization and

nutritional information on 286, 500 children provided very strong evidence to support

protective effect of immunization on under nutrition.32

Table 1.2 provides details of the

same.

Children missed by the childhood immunization program, Indonesia (n-286,500)

Immunization status

Severe

under

weight (%)

Severe

stunting

(%)

Diarrhoea

(%)

IMR

(%)

U5MR

(%)

Complete

immunization

(7 doses)

5.4 10.2 3.8 6.4 7.3

Partial immunization

(1 to 6 doses) 9.9 16.2 7.3 11.4 13.4

No immunization 12.6 21.5 8.6 16.5 16.5

Note: Complete immunization means (3 DPT, 3 OPV and measles) All values are significant at p<

0.0001

Table 1.2: Immunization status and prevalence of nutritional status and

morbidities.

1.2.3.4 Diarrhoeal diseases

Diarrhoea and malnutrition are two most common ailments in developing world.

Both of them are partly dependent on each other. Diarrhoea leads to under nutrition and

under nutrition further increases risk of getting infections. This phenomenon sets vicious

cycle between diarrhoeal disease and under nutrition. This relationship is further

influenced by socio economic status (poverty).

16

Moore studied effects of diarrhoea on under nutrition.33

Even after controlling for

all other maternal and child factors significant association between diarrhoea and under

nutrition was found. On an average of 9.1 occurrences of diarrhoea in 0 -2 years, lead to

3.6 cm reduction in height growth at age 7 years of age. Similar findings were reported

by moore in another study where prolonged diarrhoea was associated with lower mean

HAZ and WAZ scores compared to acute diarrhoea.34

In Indian scenario Bhaskaran explored relationship of infections with under

nutrition.35

He postulated that infectious diseases and under nutrition are inter dependent.

Figure 1.5 provides graphical representation of the same.

Figure 1.5: Malnutrition – infection: the vicious cycle35

17

Figure 1.5 shows inter relation between diarrhoeal diseases and under nutrition. Under

nutrition leads to altered immunity which is responsible for higher rates of infection in

under nourished children. Infections lead to physiological and metabolic alterations

which further aggravates under nutrition. This relationship is affected by poverty as a

social determinant of nutrition.

1.2.3.5 Acute Respiratory infections (ARI)

Respiratory infections share the same relationship as diarrohea with under

nutrition. However the mechanisms are different for both diseases. Respiratory infections

lead to cachexia leading to decreased energy input. Same time introduction of pathogen

stimulates immune system which requires metabolically derived anabolic energy, further

depleting energy stores and creative negative energy balance in child manifested as under

nutrition.

1.2.3.6 Social determinants of under nutrition

Social determinants are called ‘cause of causes’.36

They are found to be most

important underlying factor in majority of human disorders. These inequalities are

defined as “systematic, socially produced and unfair”.37

It is directly as well as indirectly

associated with child nutritional status.

Poor socio economic status is manifested as hunger, which is directly associated

with under nutrition. Worst of such association can be traced back to ‘The Bengal

Famine’ in 1943. It affected poor most and accounted for nearly 3 million deaths. This

famine was perpetrated by British government, which prioritized world war troops over

citizens of West Bengal to provide ration.38

18

Even in present world, health inequalities continue to persist. Majority of under

nourished children belong to the developing world. Majority of under 5 deaths are

reported in developing countries. Inequalities exist within these countries at the state

level. Concentration index and poor rich ratios are used to measure these inequalities.

Strongest evidence in Indian scenario comes from latest NFHS III survey where

nutritional status is segregated by wealth quintiles. Table 1.3 represents difference in

prevalence of underweight, stunting and wasting based on wealth quintiles.

Wealth quintile Underweight Stunting Wasting

Lowest 56.6 59.9 25

Second 49.2 54.3 22

Middle 41.4 48.9 18.8

Fourth 33.6 40.8 16.6

Highest 19.7 25.3 12.7

Poor rich ratio

(lowest/highest) 2.87 2.37 1.97

Table 1.3: Under nutritional status and poor rich ratio based on wealth quintiles.5

Poor rich ratio is nearly 3 for underweight category meaning lowest quintile group

has 3 times more prevalence of underweight compared to highest wealth quintile group.

These differences are further expanded if data is looked for severe under nutrition. (table

1.4)

Wealth quintile Severe Underweight Severe Stunting Severe Wasting

Lowest 24.9 34.2 8.7

Second 19.4 27.9 6.7

Middle 14.1 23.1 6.2

Fourth 9.5 16.5 5

Highest 4.9 8.2 4.2

Poor rich ratio

(lowest/highest) 5.08 4.17 2.07

Table 1.4: Under nutrition (severe) status and poor rich ratio based on wealth

quintiles5

19

As severity of disease increases, burden of disease also increases in on the poorest group,

who has more than 5 times higher prevalence of underweight compared to highest wealth

quintile group. Same is true for stunting as well as wasting.

in the paper ‘the social basis of disparities in health’ Diderichsen has defined

social inequalities into 4 different groups namely differential exposure, differential

vulnerability, differential outcomes and differential consequences39

Commission of social

determinants of health tried to fit nutritional inequalities in to this model which is

summarized in table 1.5.40

Differential exposure Poor water and sanitation (diarrhoea)

Crowding (associated with pneumonia, measles

and other water or air borne diseases)

Indoor pollution (respiratory diseases)

High vector density (malaria)

Differential vulnerability Low immunization coverage

Reduced period of exclusive breastfeeding

Increased severity of disease as child’s

nutritional status may not be as immune as

possible.

Differential outcome High prevalence of respiratory and

gastrointestinal morbidities

High proportion of Low Birth Weight

Stunting and wasting is very high in lowest

group.

Differential consequence High under 5 mortality and infant mortality

Table 1.5: differential vulnerabilities, exposure, outcome and consequence based on SES

20

1.2.3.7 Growth Physiology

Growth is a normal physiological phenomenon. It starts from embryonic cell to

full term foetus in 9 months. Within first 4-5 days after birth child loses weight in

response to maternal hormone withdrawal. After initial phase child doubles birth weight

in first 4 months of life and triples by end of 1st year. Same time height also increases at

stable rate.

BMI for age charts allows comparing rate of weight and height gain in children.

BMI at birth is 14.8, which goes to as high as 18 in first 6 months of infant life. After 6 to

8 months clear decline in BMI ratio is observed. It steadily declines till BMI become 15

by age 6. After that again BMI increases. This reduction in BMI from 6 month to 6 years

may be attributable to faster growth of height compared to weight.(Annexure-I)

1.2.4 DISEASE BURDEN

1.2.4.1 Global Burden

Improved nutrition, sanitation and public health are three great reforms which has

improved health status of western world in last century. Diseases like Rickets, pellagra,

Goiter and nutritional blindness, highly prevalent at dawn of twentieth century, are

almost obsolete in industrialized countries. 41

However, developing countries have a long

way to go for improving nutrition status of people in their countries. At the beginning of

this century 818 million people (16% of total population) in developing countries were

undernourished. This vulnerability further extends in children as 23% of children under 5

years are still underweight in 2009.42

21

Echoing this problem, United Nations declared 8 Millennium Development Goals

(MDGs) in 2000. Not surprisingly ‘eradicate extreme poverty and hunger’ was 1st

MDG. A target was set to halve the level of malnutrition by 2015 from the 1990 level of

malnutrition.43

Current prevalence of underweight is 15.7% in under 5 children for the world in

2011.44

There are regional differences in prevalence of under nutrition. Lowest prevalence

is noted in Latin America (3.4 %) followed by East Asia & Pacific (5.4%), Middle

East & North Africa (6.3%), Sub Saharan Africa (21.4%). Highest burden of

under nutrition is in South Asia (33.2 %).44

In South Asia prevalence of under nutrition is India (43.5%), Bangladesh (41.3%),

Afghanistan (32.9%), Pakistan (30.9 %) and Sri Lanka (21.6%). 44

1.2.4.2 Burden in India

India is the second most populated country in the world. Under nutrition is highly

prevalent in the country with 52% of children under 3 years being under nourished in 91-

92. As late as 2006, prevalence of under nutrition was 40% in children under 5 years.

India has set goal to reduce malnutrition to 26% by 2015. At the present rate of decline,

India will be able to achieve reduction of under nutrition to 33%, which is much higher

than MDG for India.45

As per the report of NFHS III there are better performing states on one hand like

Kerala (22.9%), Punjab (24.9) and Goa (25%) while on the other hand there are states

22

like Gujarat (44.6%), Bihar (55.9%), Jharkhand (56.5%) and Madhya Pradesh (60%),

with higher prevalence of under nutrition.5

Other 2 indicators are also not impressive for under nutrition as 48% children are

stunted while 20% are wasted. Apart from the estimation NFHS III attempted to identify

causes associated with nutrition status of children. According to their report major

contributors were ARIs, Diarrhoea, vaccination coverage and IYCF practices (Infant and

Yong Child Feeding). Many states with higher rate of under nutrition perform worst on

these indicators.

Recently at the beginning of year 2012, report on the current malnutrition status,

Hunger and Malnutrition ‘HUNGaMA’ was released. This report has explored

prevalence of under nutrition in 100 worst performing districts of India. As per the report

prevalence of underweight and stunting is 42% and 59% respectively. However the

prevalence of underweight has been reduced from 53% of DLHS, 2004. 46

1.2.4.3 Burden in Gujarat

Gujarat is the 10th

biggest state of India with more than 603 million people.

Sizable proportion of this population, 75 million, is consisted of children between 0 to 6

years of age. Gujarat is an economically prosperous state in India. State domestic product

per capita is 5th

in India after Maharashtra, Delhi, Haryana and Goa.47

However prevalence of malnutrition has not decreased as expected in Gujarat.

1% Reduction is observed from 42% in 98-99 to 41% in 05-06.5,8

23

This picture is further complicated by high prevalence of malnutrition among non

poor people (30% in wealthiest quintile group).48

Boys are more likely to be underweight (47%) compared to girls (42%).48

Nutritional status doesn’t improve much in adulthood as 36% adults are too thin,

while 17% women and 11% male are overweight or obese.48

Complete vaccination coverage is as low as 45%. Nearly 5% children do not

receive any vaccination at all.

Recent study on rural primary school children estimated range of underweight to

be 69%-75% with 35% children severely malnourished. 49

1.2.5 INTERVENTIONS BY GUJARAT STATE GOVERNMENT

The State Government has taken various steps to reduce level of malnutrition in

Gujarat. Various schemes have been implemented to fight against malnutrition in

children.50

CDNCs (Child Development Nutrition Centers) to provide in patient treatment

and diet to severely malnourished children. Dietary education and cooking skills

are taught to mothers attending the clinic.

THR (Take Home Ration) is provided to ANC receiving mothers, Breastfeeding

mothers and adolescent girls. It contains pre cooked nutritious food to meet

caloric as well as protein requirements.

BALBHOG is scheme to provide 3.5 kg nutritious food per month to 7-36 month

old children. This scheme caters services to all children in state without any

distinctions. Additional diet is supplemented to severely malnourished children.

24

1.2.6 RATIONALE

Junagadh is the 7th

biggest district in Gujarat the state with population of nearly 2.8

million. As per recent census, district has 301, 395 children between age 0 – 6 years.51

District has distinct geography as 6 taluks are in coastal region, 5 taluks are highly

populated urban areas and rest 3 taluks are in forest (Gir Forest National Park).

Last estimation of under nutrition was done in year 2004 (DLHS II). Prevalence of

underweight was 43.8% and 12.4% children suffered from severe under weight. Other

important indicators in the district were measured in 2007-08 (DLHS III). Complete

ANC coverage was 74.7% and rate of institutional deliveries was 56.3%. Two third of

the children (66.7%) are immunized for age. 12.9% children had diarrhoea in last 2

weeks while 3.9% suffered from ARI (acute respiratory infection).48

‘Nutrition mission’ is a government program aiming at reduction of under nutrition in

children. This program has been running for more than 2 years. However there are no

studies at district level to quantify overall benefits of this program. Prevalence estimation

is 8 year old, way before the program implemented in Gujarat.

Present study aims to fill this gap by estimating prevalence of under nutrition in 0 – 5

year children of Junagadh district. Apart from prevalence attempts will be made to

identify relationship of socio economic status, immunization coverage and morbidities on

prevalence of under nutrition.

25

OBJECTIVES

Major Objective

To estimate prevalence of under nutrition in 0 – 5 year children of Junagadh

district.

Minor Objectives

To describe relation of under nutrition with socio economic status.

To describe relation of under nutrition with vaccination coverage.

To describe relation of under nutrition with acute respiratory illnesses and

diarrhoea.

26

CHAPTER 2

METHODOLOGY

2.1 Study type

Community based cross sectional study using multi stage cluster design.

2.2 Study setting & Target population

Present study was carried out on 0 – 5 year old children of Junagadh district. All children

less than 5 years of age in the district were the target population. Sampling frame was the

administrative unit (village or city area).

2.3 Sample size estimation

Sample size was calculated for the population of 301395 children as per Census 2011

data, using estimated prevalence of 41% with precision level of 6% and design effect 1.7

(NFHS III), to be 439 using “OPEN EPI version 2.3.1”. Considering 10% dropouts,

sample size was 482, which was further rounded off to 480 children of 0-5 years.

2.4 Sample selection procedure

Junagadh district is divided into 14 administrative taluks. This taluks were categorized

into 3 major regions namely coastal, urban and forest region. For better representation,

one taluk was randomly selected from each region namely Una, Talala and Junagadh.

List of region and number of taluks in each region is described in annexure - II.

2.4.1 Cluster selection

Villages or city administrative areas were defined as cluster for present study. To select

48 clusters from 3 taluks, multi stage cluster sampling was used.

27

a. Step 1: 3 taluks (Junagadh, Una, Talala) were randomly selected from 14

taluks of district.

b. Step 2: Every Taluk was further stratified in to urban area and rural area to

accommodate rural urban difference in population (68% rural vs 32% urban).

c. Step 3: Administrative maps of the city was used to identify number of wards

in the city. From the list 4 wards were randomly selected as clusters.

d. Step 4: Taluk wise village list with population was obtained from district

panchayat (census 2001).52,53,54

From the list all villages with population less

than 200 were merged to nearest village as they may not have required

number of children from village. Villages were entered alphabetically into

Microsoft Excel. Random numbers between 0 to 1 were generated for every

village using excel software. 12 villages with highest score were selected as

cluster in rural area.

So, total 12 city areas and 36 villages were included in present study.

2.4.2 Subject selection

At the village level or city administrative area, one point was selected near the middle of

the village or ward area. Starting from that point, all the houses in one direction were

interviewed till required numbers of eligible children were enrolled. At the household

level child aged less than 5 years were selected for the study after getting consent from

the parents and the information was obtained from mother or primary care giver of child.

If there were more than one eligible child in a house, KISH method was used for

selecting the child.

2.4.2.1 Inclusion criteria

28

Children of age < 5 years.

2.4.2.2 Exclusion criteria

Child with any physical disability

Child suffering from any illness presently.

If respondent is mother and she is pregnant.

2.5 Data collection techniques

Data collection was divided in to 2 parts interview schedule and anthropometric

measurements.

2.5.1 Interview schedule

Close ended interview schedule was designed for the mother or the primary care taker of

children. This schedule intended to explore the secondary objectives of the study.

Interview schedule was administered by field investigator. Following sections were

included in to the interview schedule.

A. Basic identification detail and random selection of child (KISH method)

B. Demographic details of respondent

C. Birth details of the children and breast feeding practices including prelacteal

feeding

D. Details of vaccination

E. History of illness: Diarrhoea

F. History of illness: ARI

G. Socio Economic Status assessment: Kuppuswamy classification

H. Anthropometric measurements.

29

2.5.2 Anthropometric measurements

Anthropometry is very sensitive and useful tool to measure nutritional status.

Auxological measurements have refined over period and hence require standard protocol

for the measurements.

Present section describes measurement protocols for height and weight. Field

investigators collected anthropometric measurements. Parents were asked to assist in

measurements

2.5.2.1 Weight measurement protocol

Weight is the essential component for measuring under weight (wt/age) and wasting

(wt/ht). It is very sensitive measurement especially in children as slight increase or

decrease in weight can categorize normal children to be under weight or underweight

children to be normal. To address this issue, digital weighing scale with measurement

sensitivity up to 100 grams were used (00.0 kg) in the present study.

Standardization is another very important aspect of anthropometry. This allows

identifying any error or deviation in the machine. Machines were checked for accuracy

using standard 5 Kg weight daily during field work. Total 3 measurements of weight

were taken per machine. Average of these weights was taken as measuring sensitivity.

Permissible range for the machine was 4.8 kg to 5.2 kg. If any machine gives value

beyond this it was planned not be used in the field and be replaced by other machine.

This standard protocol was followed throughout the study period.

Young age children may not stand properly on the weighing machine. Ideal protocol

requires measuring weight of the child only whenever possible. When it is not feasible

30

first the weight of mother or care taker is noted with child and then child is handed over

to other family member or interviewer to measure weight of care taker without child.

Mother’s weight without child is subtracted from mother’s weight with child, to get

child’s weight.

In the present study all children above age 2 were allowed to stand by themselves on the

weighing machine. Due care was taken to avoid any fall during this procedure. For the

safety of young children, all children below 2 years of age were weighed with the help of

care takers. First the weight of mother with child was noted down and then baby was

handed over to other members or interviewer for measuring weight of mother without

child.

2.5.2.2 Height/length measurement protocol

Measuring height in young children is not possible as they may not stand still for required

period. All anthropometry guidelines favour use of length measurement for children less

than 2 years. In some cases it may be difficult to determine age with accuracy. In all such

cases first height is taken. If height is > 85 cm then there is no further measurement

requirement. Length measurement should be taken for all the cases were height is < 85

cm.

2.5.2.2.1 Height measurement

To measure height, child should be made stand on the height board without any footwear.

In the present study, field investigators measured height of the children with the

assistance of their parents. Before taking measurement of height, following check list was

ticked to ascertain precise measurement.

31

A. Child is standing upright with both the feet together. Heels are touching

back of the measuring board

B. Same way knees are in straight position. There was no flexion at knee or

hip.

C. Parents were requested to hold child’s knee as well as ankle to prevent any

flexion.

D. Child stands straight such that imaginary mid axillary line is perpendicular

to the base of board.

E. Child was asked to look straight to the parents horizontally.

Headpiece was lowered from the top till the top of head. Nearest 0.1 centimeter recording

was taken for the height measurement.

2.5.2.2.2 Length measurement

For measuring length, child was put in supine position with head touching the base of

length board that was placed on a flat surface. Parents were requested to assist in taking

measurement. Following things were assured before taking measurement.

Child is looking straight up perpendicular to the board.

Now hold the knees with the thumb and index finger. Press it gently so that

back of knee touches the board. Right handed person should hold the knees

with left hand and measuring board with right and vice versa.

After ascertaining above checklist, foot piece was gently but firmly pressed against the

heel of the child. Measurement was taken to the nearest 0.1 cm and noted down.

2.6 Ethical considerations

32

Beneficence, Non-malfeasance, autonomy and justice are four principles which guide

research ethics.55

Present study was conducted as per guidelines of public health ethics.

2.6.1 Non-malfeasance

Present study involved minimal risk of physical injury to children. All safety measures

were taken to assure safety of children. Special training was conducted for surveyors to

assure safety of children as the priority.

Data safety is another important aspect of non malfeasance. Principal investigator (PI)

has assured safety of these data. Data Entry was done under supervision of PI. No

photocopying or scanning was done for these data.

2.6.2 Beneficence

There were no direct benefits for children to participate in the present study. However

study provided important information on malnutrition which will be useful for effective

implementation of the programs aiming at reducing malnutrition.

Surveyors were trained on WHO guidelines for diagnosing malnutrition and were

provided with one pamphlet containing this cut off weight for age. Mothers of all under

nourished children were informed about the condition and its hazards. She was also

informed about nearest hospital where facility is available for treating malnutrition. Same

information was shared with mothers of children taking part in reliability measurements.

2.6.3 Autonomy

Written informed consent was sought from mother (or primary care giver) of children

prior to starting interview. It was clearly emphasized that study participation is

completely voluntary and the respondent has right to refuse any question at any time and

33

finish interview. Also they were reassured that their participation or denial will not affect

to receive any future services to the child or other members of the family.

2.6.4 Justice

Principle of justice requires equitable distribution of burden and benefits of research to

the society. Vulnerable communities should not be coerced to participate. Present study

was completely voluntary and no attempts were made to selectively select certain groups

or communities to participate. Selection of villages or city area was completely random

using computer software. So participation in the study was judicious without any

coercion.

2.7 Data collection

2.7.1 Inter rater reliability

Data collection was done by 2 field investigators separately. To ascertain inter rater

reliability in anthropometric measurements, separate sample of 30 children was drawn

from Junagadh municipal corporation area. After consent, height and weight

measurements and age were ascertained by both the teams.

2.7.2 Data collection

Data collection was done taluk wise considering feasibility. First of all villages from the

taluk were interviewed followed by urban area. First taluk selected was Una followed by

Talala, and finally data was collected from Junagadh taluk.

2.7.3 Data quality management

Supervision was given due emphasis in data collection. Principal investigator participated

in data collection of 50% of children with first team. To assure quality of data, 12 cases

34

(5%) were randomly selected from data collected by other team. These cases were

revisited by principal investigator to assure data quality.

2.8 Data analysis

Data entry was done in EPIDATA software. ANTHRO software (WHO) was used for

primary objective analysis. Z scores were generated for weight for age, height for age and

weight for height using ANTHRO software. Data analysis was primarily carried out in

SPSS version 17. EPI INFO software was used to create graphs for present study.

Univariate Analysis: descriptive analysis for all predictor and outcome variables.

Bivariate Analysis: Chi square test was used to find association between predictor and

outcome variables. Odds Ratio for binary outcome variables (normal/undernourished)

were estimated by logistic regression, while multinomial logistic regression was used to

estimate the Odds Ratio for the outcome variable having three categories (normal,

moderate and severe) to assess the risk separately for each category. Multiple logistic

regression models were used to estimate the adjusted Odds Ratio.

2.9 VARIABLES USED IN STUDY

2.9.1 Outcome variables:

Present study attempts to estimate prevalence of under nutrition in 0 – 5 year children. So

under nutrition is the outcome variable in present study. Under nutrition is calculated by

3 parameters namely WAZ (weight for age), HAZ (height for age) and WHZ (weight for

height). WHO growth standards were used to define under nutrition. (Table 2.1)

No. Under nutrition category Definition

1 Underweight WAZ < 2 SD for WHO standard population

35

2 Severe Underweight WAZ < 3 SD for WHO standard population

3 Stunting HAZ < 2 SD for WHO standard population

4 Severe Stunting HAZ < 3 SD for WHO standard population

5 Wasting WHZ < 2 SD for WHO standard population

6 Severe Wasting WHZ < 3 SD for WHO standard population

7 Any under nutrition WAZ or WHZ or HAZ < 2SD for WHO st. Population

8 Any Severe under nutrition WAZ or WHZ or HAZ < 3SD for WHO st. Population

Table 2.1: definition of under nutrition based on WHO classification

2.9.2 Predictor variables

Demographic variables: age (date of birth or completed age in months), sex of child,

respondent detail, religion, No. of adults in house, No. of children in house and residence

(rural-urban).

Maternal factors: antenatal care, no. of ANC, place of delivery and mother’s age at birth.

Child’s birth history: birth weight, first breast feeding, prelacteal feeding, exclusive

breastfeeding and additional supplements.

Immunization: ever vaccination, presence of vaccination card, BCG vaccination,

presence of BCG scar, polio vaccine at birth, no of polio drops, DPT vaccination, no. of

DPT vaccine received, measles vaccination, vitamin A supplement and additional

vaccination details (hepatitis B, HIB, Typhoid vaccine, Rotavirus vaccine).

History of Diarrhoea: history of diarrhoea in last 2 weeks, duration, blood in stool,

treatment seeking, place of treatment, hospitalization, duration of hospitalization and use

of ORS.

36

History of Respiratory illnesses: history of fever or cough in last 2 weeks, any additional

symptom, treatment seeking, place of treatment, hospitalization and duration of

hospitalization.

Socio Economic Status: education of father, education of mother, monthly expenditure,

monthly income and father’s occupation.

2.9.3 Operationalization of variables

Age groups: age was collected using date of birth or completed age in months. From

this variable age group was created for 1 to 5 years.

Antenatal care: reclassified in to dichotomous variable yes or no. all women who had

received at least 1 ANC during pregnancy were categorized as yes and rests were

categorized as no.

Complete ANC: women with 3 or more ANC check up were categorized as received

complete ANC and rests were classified as incomplete ANC.

Institutional delivery: women delivered at Primary Health Center, Community health

center, District hospital, medical college or private institutions were categorized as

institutional deliveries. Rests were women delivered at home with or without help of

attendant and hence classified as home delivery.

Low Birth Weight: International definition of LBW is birth weight < 2500 grams.

There is ambiguity on where to categorize 2500 grams weight. Weighing scales in

India are not sensitive enough to describe difference between 2499 grams and 2500

grams. Majority have measurement sensitivity of 100 grams 2400 grams and than

directly 2500 grams.

37

In present study nearly 14% children had exactly 2500 grams noted as birth weight.

These children with 2500 grams birth weight were included as low birth weight in

present study.

Exclusive breastfeeding: information was collected in completed months of exclusive

breastfeeding. This was re classified as no exclusive breast feeding, 1 to 3 months of

exclusive breastfeeding, 4 to 9 months of exclusive breastfeeding and >9 months of

exclusive breast feeding.

Immunized for age: age of the study population was distributed from 0 – 5 years. So

immunization status differed between children significantly. Following criteria was

used to define the variable immunized for age. (Table 2.2)

Age Vaccines given

< 1 month BCG and OPV 0

1 month completed and < 2 months BCG and OPV 0,1 and DPT 1

2 months completed and < 3

months

BCG and OPV 0,1,2 and DPT 1,2

3 months completed and < 10

months

BCG and OPV 0,1,2,3 and DPT 1,2,3

10 months completed to 5 years BCG and OPV 0,1,2,3 and DPT 1,2,3 and

Measles

Table 2.2: Immunized for age children classification

Any respiratory morbidity: was computed using fever or cough in last 2 weeks.

Any morbidity: was computed using either fever or cough or diarrhoea in last 2 weeks.

Socio Economic Status: kuppuswamy classification was used to determine socio

economic status. It comprises of 3 components education, occupation and income.

Education and occupation were categorized as per the requirement of classification.

38

However monthly income was calculated using continuous values. Later they were

changed to scores for SES calculation.

Kuppuswamy classification is very old proposed first in 1976.56

So, income

components need to be revised to present year to compensate inflation effect. Income

has been reclassified for year 2012 and hence was used in present study.57

Kuppuswamy classification categorized socio economic status in 5 groups. However

in present study very few children belonged to upper socio economic group (7

children) and none belonged to lower SES (0 children). These factors allowed

regrouping of SES into 3 categories.(Table 2.3)

Original SES category New SES Category

Upper Upper

Lower upper

Middle Middle

Upper lower Lower

Lower

Table 2.3: SES classification

Mother’s education: mother’s education was grouped as illiterate, primary education,

secondary education and graduation or more.

Mother’s age at child birth: was classified as < 20 years, 21 to 25 years, 26 to 30 years

and > 30 years.

2.9.4 Outcome variable classification for Multinomial logistic regression

WAZ, HAZ and WHZ are continuous variables which can be categorized into multiple

groups. To determine impact of predictor variables on each group of under nutrition

following classification was used.

39

CHAPTER 3

RESULTS

3.1 Sample characteristics

Sample size was estimated to be 480 at the beginning of the study. Total 48 clusters were

selected from 3 taluks to achieve required sample size. At the end of study total 469

children were interviewed from 48 clusters. Further, on data cleaning 10 children were

removed from analysis as they did not have all 3 basic information required for primary

objective assessment (Age, weight and height).

Final analysis is carried out on total 459 children. This represents 95.6% coverage of

estimated sample size. Table 3.1 represents demographic profiling of the sample.

Variable categories N (%)

Age group

0 to 1 years 111 24.2

1 to 2 years 120 26.1

2 to 3 years 96 20.9

3 to 4 years 80 17.5

4 to 5 years 52 11.3

Sex Male 265 57.7

Female 194 42.3

Table 3.1 age/sex distribution of sample

Nearly half of the children (50.3%) were less than 2 years of age in sample. Mothers were

the respondents in most of the cases (89.3%) followed by father (5.5%) and others

(5.5%). Total 119 children (25.9%) were from urban area and rest 340 children (74.1%)

were from rural area (74.1%).

40

3.2 Description of predictor variables

Table 3.2 provides brief details of maternal factors in study. Mother’s age at birth was <

20 years for 15% mothers, 55.5% in 21 to 25 years, 27.3% in 26-30 years and 5.8% in >

30 years. 25.1% mothers were illiterate, 45.3% had primary education, 21.1% had

secondary education and 9.5% had studied up to graduation or more.

Variable Yes

N (%)

No

N (%)

Antenatal checkup (at least 1) 429 (93.5) 30 (6.5)

Complete ANC (3 or more ANC) 371 (80.8) 88 (19.2)

Institutional delivery 361 (78.7) 98 (21.3)

Table 3.2 maternal characteristics

412children (90%) were weighed at birth. Out of these 117 (28.4%) were found to have

low birth weight. 204 (44.4%) children received pre lacteal feeding. First breast feeding

was given within 1st hour of life to 225 children (49%), 120 (26.2%) children received

breastfeeding between 1 to 24 hours and rest 114 children (24.8%) received first breast

feeding after 24 hours. Additional supplements are very common in small children as 274

children (59.7%) received some kind of additional supplements. These supplements

included somva chotrisi, babulin, chamcho, jivan ghutti and others.

448 (97.6%) children received BCG vaccine. Out of these 437 (95.2%) children had BCG

scar present on the left shoulder. Nearly quarter of children 118 (25.7) has received

Hepatitis B vaccine. 336 children (73.2%) were immunized for age, with 79.2% children

in age group 12 to 23 months being immunized for age.

41

69 children (15%) had episode of diarrhoea in last 2 weeks. Out of these 59 children

(85.5%) sought treatment for illness. However, only 6 children (8.7%) were provided

ORS for diarrhoea. 111 children (24.18%) suffered from fever or cough (ARI) in last 2

weeks and 99 children (88.3%) sought treatment for illness.

67 children (14.6%) belonged to upper class and 149 children (32.5%) belonged to

middle class and maximum children 243 (52.9%) belonged to lower socio economic

class.

3.3 Prevalence of Under Nutrition

Primary objective of the study was to find prevalence of under nutrition in 0 – 5 year

children in Junagadh district. Under nutrition is defined as child having any sort of under

nutrition (under weight, stunting or wasting). Same way severe under nutrition is defined

as child suffering from any form of severe category. Table 3.3 describes prevalence of

under nutrition with 95% Confidence interval limit for the prevalence.

Category (N – 459) Number Prevalence (95% CI)

Underweight

Moderate & Severe 121 26.4 (22.4 - 30.5)

Severe 31 6.8 (4.6 - 9.4)

Moderate 90 19.6 (15.9 – 23.3)

Stunting

Moderate & Severe 225 49 (44.2 - 53.8)

Severe 104 22.7 (19 - 26.4)

Moderate 121 26.3 (22.2 – 30.9)

Wasting

Moderate & Severe 49 10.7 (8.1 - 13.7)

Severe 21 4.6 (2.8 - 6.8)

Moderate 28 6.1 (4.1 – 8.5)

Under nutrition Moderate & Severe 267 58.2 (53.6 - 62.7)

Severe 128 27.9 (23.7 – 32)

Table 3.3 Prevalence of Under Nutrition

42

26.4% children suffered from moderate and severe underweight. Stunting was the

commonest form of under nutrition (49%). Wasting is found in 49 (10.7%) children only.

High proportion of children suffered from any severe under nutrition (27.9%).

3.4 Association of Socio Economic Status with under nutrition

SES was captured using Kuppuswamy classification (1976). Scale was revised for year

2012 to make it more appropriate for use in present study. Table 3.4 describes association

of SES with all outcomes. Unadjusted Odds Ratios were estimated using logistic

regression.

Socio economic status is significantly associated with underweight, stunting and wasting.

Compared to upper class risk of having underweight, stunting or wasting is higher for

middle group. Lower class has the nearly 4 times higher Odds of suffering from

underweight or wasting and 2 times higher Odds of suffering from stunting.

Outcome variable SES Category Total n (%) Unadjusted OR with

95% CI

Underweight

Upper 67 7 (10.4) 1

Middle 149 38 (25.5) 2.9 (1.2 – 7)

Lower 243 76 (31.3) 3.9 (1.7 – 8.9)

Stunting

Upper 67 27 (40.3) 1

Middle 149 67 (45) 1.2 (0.7 – 2.2)

Lower 243 131 (53.9) 1.7 (1.01 – 3)

Wasting

Upper 67 2 (3) 1

Middle 149 18 (12.1) 4.5 (1.006 – 19.8)

Lower 243 29 (11.9) 4.4 (1.02 – 19)

Table 3.4 Socio Economic status and under nutrition (bivariate analysis)

43

3.5 Association of Immunization with under nutrition

Immunization history was collected for every child. Based on age and immunization

status child was categorized as immunized for age or not immunized for age. Table 3.5

describes association of immunized for age with under nutrition.

Type of Under

nutrition

Immunized for

age

Total

N n (%) OR (95% CI)

Underweight No 123 32 (26) 1

1.02 (0.6 – 1.6) Yes 336 89 (26.5)

Stunting No 123 70 (56.9) 1

0.6 (0.4 – 0.98) Yes 336 155 (46.1)

Wasting No 123 7 (5.7) 1

2.4 (1.03 – 5.4) Yes 336 42 (12.5)

Table 3.5: Immunization and under nutrition (bivariate analysis)

Immunization is significantly associated with stunting. It has protective effect for

stunting. However children immunized for age has higher proportion of Wasting.

3.6 Association of morbidities with under nutrition

Details regarding 2 diseases diarrhoea, and ARI (Acute respiratory infection) were

collected. Total 4 variables are used in present analysis to see effect of morbidities on

nutritional status. Any morbidity in last 2 weeks is composite variable of either diarrhoea

or ARI in past 2 weeks. Same way treatment sought is composite of treatment seeking for

either morbidity. Tables 3.6 to 3.8 provide individual outcome association with

morbidities.

44

Name of variable Cat. Total

Underweight

N (%) OR with 95% CI

Diarrhoea in last 2

weeks

No 390 106 (27.2) 1

0.7 (04 – 1.4) Yes 69 15 (21.7)

URTI in last 2 weeks No 348 99 (28.4) 1

0.6 (0.4 – 1) Yes 111 22 (19.8)

Any morbidity in last

2 weeks

No 307 87 (28.3) 1

0.7 (0.5 – 1.1) Yes 152 34 (22.4)

Sought treatment

(n – 152)

No 20 5 (25) 1

0.8 (0.4 – 2.9) Yes 132 29 (22)

Table 3.6: morbidity and underweight (bivariate analysis)

Name of variable Cat. Total Stunting


Diarrhoea in last 2

weeks

No 390 201 (51.5) 1

0.5 (0.3 – 0.8) Yes 69 24 (34.8)


0.8 (0.5 – 1.2) Yes 111 49 (44.1)


2 weeks

No 307 159 (51.8) 1

0.7 (0.5 – 1.1) Yes 152 66 (43.4)

Sought treatment

(n – 152)

No 20 12 (60) 1

0.5 (0.2 – 1.3) Yes 132 54 (40.9)

Table 3.7: morbidity and stunting (bivariate analysis)

45

Name of variable Cat. Total

Wasting


Diarrhoea in last 2

weeks

No 390 37 (9.5) 1

2 (1 – 4.08) Yes 69 12 (7.4)


0.7 (0.3 – 1.4) Yes 111 9 (8.1)

Any morbidity in last 2

weeks

No 307 30 (9.80) 1

1.3 (0.7 – 2.4) Yes 152 19 (12.5)

Sought treatment

(n – 152)

No 20 2 (10) 1

1.3 (0.3 – 9.1) Yes 132 17 (12.9)

Table 3.8: morbidity and wasting (bivariate analysis)

Diarrhoea is associated with wasting. Children with diarrhoea in last 2 weeks were 2

times more likely to have wasting. However protective effect is seen for stunting.

3.7 Association of age with under nutrition

Age plays very important role in nutritional status of children. It can act as confounder to

the predictors of interest. Table 3.9 describes relationship of age with outcomes of

interest.

Type of Under

nutrition Age group Total N (%) OR (95% CI)

Underweight

0 to 1 years 111 14 (12.6) 1

1 to 2 years 120 30 (25) 2.3 (1.1 – 4.6)

2 to 3 years 96 32 (33.3) 3.5 (1.7 – 7)

3 to 4 years 80 29 (36.3) 3.9 (1.9 – 8.1)

4 to 5 years 52 16 (30.8) 3.1 (1.4 – 6.9)

46

Type of Under

nutrition Age group Total N (%) OR (95% CI)

Stunting

0 to 1 years 111 39 (35.1) 1

1 to 2 years 120 60 (50) 1.8 (1.1 – 3.1)

2 to 3 years 96 57 (59.4) 2.7 (1.5 – 4.7)

3 to 4 years 80 49 (61.3) 2.9 (1.6 – 5.3)

4 to 5 years 52 20 (38.5) 1.1 (0.6 – 2.23)

Wasting

0 to 1 years 111 11 (9.9) 1

1 to 2 years 120 13 (10.8) 1.1 (0.5 – 2.6)

2 to 3 years 96 9 (9.4) 0.9 (0.4 – 2.4)

3 to 4 years 80 11 (13.8) 1.4 (0.6 – 3.5)

4 to 5 years 52 5 (9.6) 1 (0.3 – 2.9)

Table 3.9: age group and under nutrition (bivariate analysis)

Age group is associated with underweight and stunting. Association shows increasing

trend as age increases up to age 4.rreduction in strength of association is observed for age

group 4 to5.

3.8 Association of sex with under nutrition

Table 3.10 represents association of sex with under nutrition.

Type of Under

nutrition Sex

Total

N n (%) OR (95% CI)

Underweight Male 265 69 (26) 1

1 (0.6 – 1.6) Female 194 52 (26.8)

Stunting Male 265 124 (46.8) 1

1.1 (0.8 – 1.7) Female 194 99 (51)

Wasting Male 265 29 (10.9) 1

0.9 (0.5 – 1.7) Female 194 20 (10.3)

Table 3.10: Association between sex and under nutrition (bivariate analysis)

47

There is no significant association between sex of child and any under nutrition.

3.9 Other significant variables for under nutrition.

Analysis was carried out for 15 predictor variables with each of under nutrition category

to find associations. Table 3.11 describes all significant variables. List of variables used

initially is provided below:

Predictor variables used for finding association: age group, sex, complete ANC care,

Institutional delivery, Maternal age group, Low birth weight, Prelacteal feeding, First

breast feeding, Exclusive breast feeding, Immunized for age, Diarrhoea in last 2 weeks,

ARI in last 2 weeks, Any morbidity in last 2 weeks, Sought treatment for morbidity in

last 2 weeks, Socio economic status & Mother’s education.

All variables found to be significant were taken to binary logistic regression model to

find adjusted ORs for each of these variables. Age group and sex of child were included

in the model at beginning irrespective of significance.

Underweight Wasting Stunting

Age group

Complete ANC

Low birth weight

SES

Immunized for age

Socio economic status

Age group

Low birth weight

Immunized for age

Diarrhoea in last 2 weeks

Sought treatment

Socio economic status

Table 3.11: predictor variables having significant association (bivariate analysis)

Further 4 or more ANC had protective effect on LBW {OR 0.6 (0.4 – 0.9)}.

3.10 Multiple Logistic regression modeling for under nutrition

Tables 3.12 to 3.14 provide regression models for each outcome separately.

48

Underweight

Variable Category Odds Ratio (exp B) 95% CI

Age group

0 to 1 years 1

1 to 2 years 2.9 1.3 – 6.3

2 to 3 years 4.1 1.9 – 9.1

3 to 4 years 5.3 2.4 – 11.9

4 to 5 years 3.5 1.4 – 8.9

Low birth weight No 1

1.02 – 2.8 Yes 1.7

SES

Upper 1

Middle 3.7 1.6 – 8.7

Lower 2.9 1.2 – 7.1

* Overall predictive value of model is 76%. (p value – 0.000)

* variable used at beginning and removed due to non significance are: Complete ANC

Table 3.12:Binary logistic regression model –Under weight

Stunting

Variable Category Odds Ratio (exp B) 95% CI

Age group

0 to 1 years 1

1 to 2 years 1.78 1 – 3.1

2 to 3 years 2.5 1.3 - 4.6

3 to 4 years 2.4 1.3 - 4.5

4 to 5 years 0.8 0.4 – 1.8


1.04 – 2.6 Yes 1.6

Immunized for age No 1

0.4 – 1.1 Yes 0.6

Sought Treatment No 1

0.3 – 0.98 Yes 0.5

* Overall predictive value of model is 60.9 %. (p value – 0.000)

* Variable used at beginning and removed due to non significance are: SES, Diarrhoea in 2

weeks.

Table 3.13:Binary logistic regression model –Stunting

49

Wasting

Variable Category Odds Ratio (exp

B) 95% CI


1 – 3.6 Yes 1.9

SES

Upper 1

Middle 4.7 1.1 – 20.5

Lower 4.1 0.9 – 18.3

Immunized for age No 1

0.9 – 5 Yes 2.1

Sought treatment No 1

1.1 – 5.1 Yes 2.4

* Overall predictive value of model is 88.3 %. (p value – 0.029)

* Variable used at beginning and removed due to non significance are: age group,

diarrhoea in last 2 weeks

Table 3.14:Binary logistic regression model –Wasting

Age group, low birth weight and socio economic status are significantly associated with

underweight. Age group, low birth weight, immunized for age and treatment seeking are

significantly associated with stunting. Stunting and socio economic status are not

significantly associated. Low birth weight, socio economic status, immunization and

treatment seeking are associated with wasting.

However these relationships don’t provide accurate estimations of risk for predictors.

Moderate & Severe under nutrition group includes severe under nutrition as sub group.

This may mask some of the effect of age group and socio economic status on Moderate &

Severe underweight and vice versa.

50

3.11 Multinomial Logistic Regression modelling

Multinomial logistic regression allows assessing the risk separately for each category

when there are more than 2 mutually exclusive outcomes. Multinomial regression allows

analyzing risk in single equation. This equation provides conditional probabilities of

being in either group compared to normal. So, further analysis was carried out to find true

associations of predictors with separate categories of outcome. Present analysis is limited

to underweight category as it was primary objective for which sample size was estimated.

(table 3.15 to 3.16)

Variable Categories Total

N

Normal

n (%)

Moderate

n (%)

Severe

n (%) pvalue

Age group

0 to 1 years 111 97 (87.4) 10 (9) 4 (3.6)

0.002

1 to 2 years 120 90 (75) 22 (18.3) 8 (6.7)

2 to 3 years 96 64 (66.7) 22 (22.9) 10 (10.4)

3 to 4 years 80 51 (63.8) 26 (32.5) 3 (3.7)

4 to 5 years 52 36 (69.2) 10 (19.2) 6 (11.6)

Sex Male 265 196 (74) 54 (20.4) 15 (5.6)

0.520 Female 194 142 (73.2) 36 (18.6) 16 (8.2)

Complete

ANC

No 88 56 (63.6) 24 (27.3) 8 (9.1) 0.060

Yes 371 282 (76) 66 (17.8) 23 (6.2)

Low birth

weight

No 295 230 (78) 48 (16.3) 17 (5.7) 0.116

Yes 117 80 (68.4) 26 (22.2) 11 (9.4)

SES

Upper 67 60 (89.6) 6 (9) 1 (1.4)

0.002 Middle 149 111 (74.5) 23 (15.4) 15 (10.1)

Lower 243 167 (68.7) 61 (25.1) 15 (6.2)

Diarrhoea

in 2 weeks

No 390 284 (72.8) 82 (21) 24 (6.2)

0.118 Yes 69 54 (78.3) 8 (11.6) 7 (10.1)

Table 3.15: Association of predictor variables with various categories of underweight.

51

Variable Categories

Underweight

Moderate

Crude OR (CI)

Severe

Crude OR (CI)

Moderate

Adj. OR (CI)

Severe

Adj. OR (CI)

Age group

0 to 1 years 1 1 1 1

1 to 2 years 2.4 (1.1 – 5.3) 2.2 (0.6 – 7.4) 3.1 (1.2 – 8) 2.7 (0.8 – 9.5)

2 to 3 years 3.3 (1.5 – 7.5) 3.8 (1.1 – 12.6) 4.3 (1.7 – 11) 4.2 (1.1 – 15.4)

3 to 4 years 4.9 (2.2 – 11) 1.4 (0.3 – 6.6) 7 (2.8 – 18) 1.5 (0.2 – 8.8)

4 to 5 years 2.7 (1 -7) 4 (1.1 – 15.2) 2.5 (0.8 – 8.3) 6.8 (1.6 – 28)

Sex Male 1 1 1 1

Female 0.9 (0.6 – 1.5) 1.5 (0.7 – 3.1) 1 (0.6 – 1.8) 1.6 (0.7 – 3.6)

Complete

ANC

No 1 1 1 1

Yes 0.5 (0.3 – 0.9) 0.6 (0.2 – 1.3) 0.8 (0.4 – 1.5) 0.8 (0.3 – 2.2)

Low birth

weight

No 1 1 1 1

Yes 1.6 (0.9 – 2.7) 1.9 (0.8 – 4.1) 1.5 (0.8 – 2.7) 2 (0.9 – 4.8)

SES

Upper 1 1 1 1

Middle 2.1 (0.8 – 5.4) 8.1 (1 – 62.9) 2 (0.8 – 5.4) 8.1 (1 – 65.9)

lower 3.6 (1.5 – 8.9) 5.4 (0.7 – 41.7) 3.2 (1.3 – 8.3) 6.2 (0.7 – 50.4)

Diarrhoea

in 2 weeks

No 1 1 1 1

Yes 0.5 (0.2 – 1.1) 1.5 (0.6 – 3.7) 0.6 (0.2 – 1.5) 2.6 (1 – 7.1)

Table 3.16: Multinomial Logistic Regression model for Underweight

52

3.12 Association between predictor variables and any under nutrition

Separate analysis was carried out for any under nutrition. Table 3.17 describes

relationship between various predictor variables and under nutrition. Binary logistic

model was constructed based on the significant variables (table 3.18).

Predictor variable Category Total n (%) Unadjusted OR with

CI

Socio Economic

Status

Upper 67 31 (46.3) 1

Middle 149 80 (53.7) 1.3 (0.7 – 2.4)

Lower 243 156 (64.2) 2.1 (1.2 – 3.6)

Immunized for age No 123 77 (62.6) 1

Yes 336 190 (56.5) 0.8 (0.5 – 1.2)

Diarrhoea in last 2

weeks

No 390 234 (60) 1

Yes 69 33 (47.8) 0.6 (0.4 – 1)

URTI in last 2 weeks No 348 209 (60.1)

Yes 111 58 (52.3) 0.7 (0.5 – 1.1)


2 weeks

No 307 185 (60.3) 1

Yes 152 82 (53.9) 0.8 (0.5 – 1.1)

Sought treatment No 20 13 (65) 1

Yes 132 69 (52.3) 0.6 (0.2 – 1.7)

Age Group

0 to 1 years 111 52 (46.8) 1

1 to 2 years 120 70 (58.3) 1.6 (0.9 – 2.7)

2 to 3 years 96 63 (65.6) 2.2 (1.2 – 3.8)

3 to 4 years 80 57 (71.3) 2.8 (1.5 – 5.2)

4 to 5 years 52 25 (48.1) 1.1 (0.5 – 2)

Sex Male 265 149 (56.2) 1

Female 194 118 (60.8) 1.2 (0.8 – 1.7)

Table 3.17 Socio Economic status and under nutrition (bivariate analysis)

53

Moderate & Severe Under Nutrition

Variable Category Odds Ratio (exp

B) CI for ORs

Age group

0 to 1 years 1

1 to 2 years 1.5 0.8 – 2.7

2 to 3 years 2.1 1.1 – 3.9

3 to 4 years 2.4 1.2 – 4.6

4 to 5 years 0.7 0.3 – 1.6


1.4 – 3.5 Yes 2.2

Complete ANC No 1

0.2 – 0.7 Yes 0.4

Exclusive Breast

Feeding

< 3 months 1

3 to 9 months 0.9 0.4 – 1.9

> 9 months 2.8 0.9 – 8.7

* Overall predictive value of model is 63.3%. (p value – 0.000)

* Variables used at beginning and removed due to non significance are: SES, institutional

delivery, mother’s education

Table 3.18:Binary logistic regression model – Moderate & Severe Under nutrition

Age group, low birth weight and complete ANC are significantly associated with under

nutrition. Low birth weight child has 2 times higher Odds of having under nutrition

compared to normal birth weight child. Same time complete ANC has protective effect

against under nutrition.

54

CHAPTER 4

DISCUSSION

4.1 Prevalence of under nutrition

Present study has estimated prevalence of underweight (26.4%), stunting (49%)

and wasting (10.7%) in 0-5 year children of Junagadh district of Gujarat. Apart from

prevalence, present study tried to find associations of SES, immunization status and

morbidities with under nutrition.

Study has found lower prevalence of underweight and wasting compared to

previous estimates by NFHS II & III and DLHS II. However stunting has remained

stagnant over these many years. Figure 4.1 provides comparison of nutritional status of

children over last 15 years.

Figure 4.1 Comparison of under nutrition between NFHS II, NFHS III and present

study

42

52

20

41

49

20

26.4

49

10.7

Underweight Stunting Wasting

Trends in child nutrition over 15 years

NFHS 2 (1998) NFHS 3 (2006) Present Study (2012)

55

NFHS provides state estimates for under nutrition, while this study has estimated

prevalence at district level. District level comparison was done using 0-3 year age group

(sub group analysis) of study with DLHS II survey which estimated prevalence of

underweight in 0-3 year children at district level. Figure 4.2 provides comparison

between DLHS II estimates and present study.

Figure 4.2 comparison of underweight prevalence between DLHS II and present

study

4.2 Underweight

Present study has estimated low prevalence of underweight compared to previous

studies. These can be attributable to 4 major factors such as improved antenatal care,

reduction in low birth weight, nutritional supplement provision to children and infection

control.

43.8

12.4

23.2

6.7

moderate & Severe Severe

Prevalence of underweight (0-3 years) in Junagadh district

DLHS II (2004) Present Study (2012)

56

Low birth weight is ‘underweight at birth’. Present study has found reduction in

prevalence of LBW from 22 percent in NFHS III to 14 percent. However we included

nearly 14.7 percent children with 2500 grams birth weight as also low birth weight as it is

more near to truth considering limitation of weighing scales which can measure weight

with precision of 100 grams only. Antenatal care significantly reduces incidence of low

birth weight (Florida prenatal health screen).58

Our study also found similar observation

as women with 4 or more ANC had less chance of delivering low birth weight.

Second set of factors are nutritional supplement and infection control. Evidence

for this can be traced back to very famous ‘Narangwal Study’ from Punjab.59

Study

assessed nutritional improvement in 4 groups namely control, nutritional supplement

only, diarrhoeal disease control only and nutritional supplement plus diarrhoeal disease

control. Despite ethical issues associated with conduct of the study,60-64

study proved

effectiveness of nutritional supplement and infection control practices. Our study has

found increased treatment seeking behavior for diarrhoea from 56.8 percent to 85.5

percent. However we did not collected data on nutritional supplement so it is not possible

to quantify effect of nutritional supplement on reduction of under nutrition.

4.3 Stunting

Prevalence of stunting has remained stagnant over last 15 years. Reduction is

minimal when compared to NFHS II data. Our study findings are at par with recent

‘HUNGaMA’ survey which found prevalence of stunting to be 58 percent in 100 worst

performing districts in India. Another important consideration is startling high proportion

of children suffering from severe stunting (22.7%).

57

Present study tried to explore causes of stunting also. Lower socio economic

status is associated with high level of stunting. However strength of association is not as

strong as for underweight or stunting. Immunization has shown protective effect from

stunting. Diarrhoea in last 2 weeks has shown protective effect. In our study most of the

children suffering from diarrhoea seek treatment. This may provide an opportunity for

health worker to immunized child if diarrhoea is not severe. This could be the possible

reason for such results in our study.

Stunting is classically defined as chronic under nutrition, which is manifestation

of energy deficit diet, namely hunger. Socio economic status is strongly associated with

stunting. However an alternative hypothesis may be required to explain findings such as

in present studies, where stunting is equally prevalent even in wealthiest quintiles.

Many studies have explored such pathways and found gamut of factors

responsible for stunting apart from hunger. Dietary non diversity has been found to be

significantly associated with stunting.65

Low animal product spending is found to be

associated with stunting.66

Such phenomenon is very likely in study settings such as ours

where majority population is vegetarian. As per NFHS III report, 70% of population is

vegetarian. Women and children have further restricted access to animal product as less

than 15% women consumed fish, chicken or egg.

Childhood stunting may continue in adulthood and girls end up with lesser height

gain. One study has explored relationship between maternal height and anthropometric

failure in children. Study found reduced risk of stunting (RR: 0.97, CI: 0.968-0.973) with

every 1 cm increase in maternal height.67

These findings can explain sustained high level

58

of stunting in communities where stunted child of today become stunted mothers of

tomorrow and give birth to stunted child. This vicious cycle can explain present

phenomenon.

4.4 Wasting

Lower prevalence of wasting is observed in present study. It has reduced to half

from previous estimates. Lower Socio economic status, Immunized for age and diarrhoea

in last 2 weeks increases risk of wasting. However effect of immunization seems to be

confuounded by other predictor variables because association does not come significant

on multiple logistic regression modelling. Lower socio economic status may be

responsible for increased occurrence of diarrhoea in the group.

4.5 Effect of age on under nutrition

Our study found significant association of age with the prevalence of underweight

and stunting. Proportion of child with underweight and stunting increases as age

increases reaches maximum around age 3 to 4 years followed by decline in age group 4

to5 years.

Child’s mobility increases with increasing age. By age 3 children starts playing

with other children and starts going to playhouses or anganwadis. This is the important

time when child encounters multiple airborne or waterborne infections. This may be

further aggravated by habits of playing outdoors or pica eating etc. This transition period

can partly explain the trend.

4.6 Determinants of Moderate vs Severe underweight

59

Determinants of moderate and severe underweight can be very different. Sub

group analysis using multinomial logistic regression provided adjusted ORs for moderate

as well as severe groups. Age group and lower socio economic status were significantly

associated with moderate underweight. However they are not associated with severe

underweight. Diarrhoea in last 2 weeks is the only factor which is associated with severe

underweight.

Age group and socio economic disadvantage can push children to moderate

underweight. However they are not sufficient to push children to severe underweight

group. Different set of factors like diarrhoea operates at this level and determines severity

of underweight in children. Graphical representation of these pathways is explained in

figure 4.3.

Figure 4.3 causal pathways for moderate and severe under nutrition

4.7 Recommendations

Based on the above model we propose set of recommendations for nutritional program in

the state.

60

a. Begin before birth: complete ANC care and nutrition during pregnancy can

reduce incidence of low birth weight and hence should be important part of any

nutritional program.

b. Immunization: Immunization has shown protective effect over stunting. So all

effort should be made to improve immunization coverage further.

c. Infection control: Infection control is the only important measure to prevent

severe under nutrition. Current programs do not provide enough attention to

infection control and hence have limited success. Infection control programs are

not optional. They should be back bone of any nutritional intervention program.

d. Nutritional supplement: first 3 recommendations are preventive measures only.

They are not curative for the child already suffering from under nutrition.

Nutritional supplement should be provided to every child in the program. Same

time special dietary assistance may be required for severely under nourished

children.

4.8 Strengths

Community based representative sample for prevalence estimation.

Identified major determinants of under nutrition in district.

Provides reference for measuring success of ‘nutrition mission’ program.

Considering homogeneity of Gujarati population, except certain tribal areas,

present study estimates can be used to understand current nutritional situation in

the state.

Minimum inter observer bias due to well defined protocol for anthropometric

measurement and separate sample collection for ascertaining inter rater reliability.

61

4.9 Limitations

wide age group with different determinants of under nutrition in each age group

Insufficient sample size to estimate subgroup associations.

Survivorship bias: children belonging to lower SES or having severe episodes of

diarrhoeal diseases may not have survived due to illnesses. This may lead under

estimation of prevalence as only healthy child population has survived.

4.10 Conclusions

Prevalence of under nutrition has reduced in the state. major contributor

towards reduction of under nutrition were ANC, low birth weight, immunization, Socio

Economic Status, History of diarrhoea in last 2 weeks and treatment seeking behavior.

Lower prevalence is observed for underweight and wasting. However,

stunting still remains very high in the district. Various causes apart from socio economic

status needs to be addressed to reduce prevalence of stunting.

Nutritional program provides dietary supplementation. This intervention may

have some effect in reduction of above mentioned parameters. However infection control

component of the program is not strong enough. Other important interventions showing

improvement are antenatal care and immunization.

Any nutritional program should have 4 integral components for reducing

under nutrition. These components are Antenatal Care, Immunization, Infection control

and Nutritional supplement.

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ANNEXURE I

BMI for age charts from WHO and CDC

BMI for age (boys) birth to 5 years (WHO Standard)

BMI for age chart for boys CDC

ANNEXURE – II

List of taluks in Junagadh district

List of Taluks in Junagadh district

Sr. No. Region Taluk Selected taluk

1 Coastal Region

Mangarol

Una

Maliya

Veraval

Sutrapada

Kodinar

Una

2 Urban region

Manavadar

Junagadh

Keshod

Vanthali

Junagadh

Bhesan

3 Forest region

Talala

Talala Mendarada

Visavadar

ANNEXURE III

Consent Form

Ref. No. _ _ _ _ _ _

TITLE OF THE STUDY: Prevalence of under nutrition in 0-5 year children of

Junagadh district, Gujarat.

Namaskar, I am presently doing Master of Public Health (MPH) course at Achutha

Menon Centre for Health Science Studies, SCTIMST, Thiruvananthapuram, Kerala. As

part of my course, I am required to undertake a study on a topic of public health

importance. The topic I have selected is “Prevalence of under nutrition in 0-5 year

children of Junagadh district, Gujarat.”

I request you to spare some time and participate in the study.

UNDERNUTRITION

Under nutrition is one of the major public health problems in the state.

Nearly 41% children were under weight in 2006. Under nutrition is associated with

various adverse effects on children’s health. It ranges from growth retardation to

multiple infections to death in severe cases. Various factors are associated with

under nutrition such as Socio Economic Status, maternal factors, diseases etc. in

present study we try to estimate prevalence of under nutrition in Junagadh district

and associate under nutrition with factors such as socio economic status,

vaccination coverage, diarrhea and respiratory illness.

What participation is required from your side?

If you decide to participate in this study we will administer an interview

schedule to you. This interview will last for nearly 15 to 20 minutes. This will be

followed by weight and height measurement of the child. Entire process will not last

more 30 minutes.

What are the benefits of participating in the study?

If your child is found to have under nutrition than we will inform the same to

you. We will also help you in identifying nearest government health facility for

further investigation and treatment. Other than there are no direct benefit of

participating in this study. However results of the study will be helpful in

understanding problem and will be used for betterment of society.

What are the harms of participating in the study?

Height and weight measurements are taken by field investigators trained for

this purpose. However there is possibility of minor discomfort or fall to you or child

during the measurement.

Can you withdraw from the study after it starts?

You are voluntarily participating in the study and have all the right to

withdraw from the study at any point of time. There is no pressure on you to

complete the study. You can tell us and we will stop at that point.

Will your personal details be kept confidential?

Results of this study will be published in scientific journal. However you will

not be identified by name in any publication or presentation of results.

If you have any further queries or doubts, you are always free to ask me to clarify

the same, which I shall do to the best of my ability.

If you are willing to take part in the study kindly express your willingness for the

same

CONSENT FORM

Participants name:

Date of birth:

Age:

I __________________________________________________son/daughter/wife of

_________________________________ declare that I have read the above information

provided to me regarding the study: Prevalence of under nutrition in 0-5 year

children of Junagadh district, Gujarat and have clarified any doubts that I had.

1. I also understand that my participation in this study is entirely voluntary and

that I am free to withdraw permission to continue to participate at any time.

2. I understand that the study staff and institutional ethics committee members

will not need my permission to look at my health records even if I withdraw

from the trial. I agree to this access.

3. I understand that my identity will not be revealed in any information

released to third parties or published.

4. I voluntarily agree to take part in this study.

5. I received a copy of this signed consent form.

Signature:

Date:

Name of witness:

Relation to participant:

Date:

I attest that the requirements for informed consent for the medical research project

described in this form have been satisfied. I have discussed the research project

with the participant and explained to him or her in nontechnical terms all of the

information contained in this informed consent form, including any risks and

adverse reactions that may reasonably be expected to occur. I further certify that I

encouraged the participant to ask questions and that all questions asked were

answered.

________________________________ ___________________

Name and Signature of Person Obtaining Consent

Prevalence of Under nutrition in 0–5 year children of Junagadh District, Gujarat

1

ANNEXURE IV

Questionnaire


2

NUMBER OF 0-5 YEAR CHILDREN IN HOUSE

Sl

No

Age Sex Rank Name of Selected child CODE

1

S1-9

2

3

4

5

KISH TABLE

SL

NO QUESTION DETAILS CODE

1 SURVEY FORM NO. S1-1

2 Cluster No. S1-2

3 Interviewer code S1-3

4 Name of the village S1-4

5 Name of Head of Household S1-5

6 Contact Number S1-6

7 House Number S1-7

8 Date

(dd/mm/yy)

S1-8

Number of

Eligible Children

in Household

Last Digit of Survey Form Number

0 1 2 3 4 5 6 7 8 9

1 1 1 1 1 1 1 1 1 1 1

2 1 2 1 2 1 2 1 2 1 2

3 3 1 2 3 1 2 3 1 2 3

4 1 2 3 4 1 2 3 4 1 2

5 1 2 3 4 5 1 2 3 4 5


3

DEMOGRAPHIC INFORMATION

Q

NO

DETAILS RESPONSES CODE

1 Respondent Mother…………………………….. 1

Father …………………………….. 2

Others(specify) ……………….. 3

S2-1

2 Respondent’s name S2-2

3 Religion S2-3

4 How many members are there in

household

Adults ……………..

Children ……………..

S2-4a

S2-4b

5 ABC’s date of birth (dd/mm/yy) S2-5

6 ABC’s age in month _________ months S2-6

BIRTH DETAILS FEEDING PRACTICES

7 Did mother of ABC have antenatal

checkup during the pregnancy? (if

no, go to question 9)

Yes …………………… 1

No ……………………. 2 S3-1

8 If yes, how many times ANC

checkup?

1

2

3

4 or more

S3-2

9 Where ABC was born?

Home …

Unattended ……………………... 1

Attended by health staff …... 2

Government Institution….

Sub center ……………. 3

PHC ……………………… 4

CHC ……………………… 5

District Hospital ……. 6

S3-3


4

Medical College …...... 7

Private Institution …………. 8

10 What was mother’s age at the

birth of ABC?

___________ in complete years S3-4

11 Was ABC weighed at the time of

birth?

(if no, go to question 15)

Yes …………………… 1

No ……………………. 2 S3-5

12 What was the weight of ABC at the

birth?

______________grams

Don’t know S3-6

13 When ABC was born, what did you

thought of his/her weight?

Very Large ……………………… 1

Larger than average ………... 2

Average ………………………….. 3

Smaller than average ………. 4

Very small ………………………. 5

Don’t know ……………………... 6

S3-7

14 When was the first breastfeeding

given to ABC?

Within 1 hour …………………..1

Between 1 to 24 hours...…….2

After 24 hours ………………….3

S3-8

15 Was any prelacteal feed given to

ABC?

Yes …………………… 1

No ……………………. 2

Don’t know ……….. 3

S3-9

16 How many months ABC received

exclusive breastfeeding?

Months S3-

10

17 Did you give any of the following

to ABC?

Chamcho ………………………….1

Sogathi …………………………….2

Babulin …………………………….3

Somva chotrisi ………………….4

Jivan Ghutti ………………………5

Other (Specify)………………… 6

S3-

11

18 If yes, how many months you gave Chamcho ………. months S3-


5

them? Sogathi ……… months

Babulin ……… months

Somva chotrisi … months

Jivan Ghutti ……… months

Other (Specify)… months

Not applicable………………..99

12

VACCINATION COVERAGE

19 Have you ever given vaccination

to ABC?


Yes …………………… 1

No ……………………. 2 S4-1

20 Do you have vaccination card of

ABC with you?

Yes …………………… 1

No ……………………. 2 S4-2

Fill question 23 to 33 from the card if available, otherwise ask the following questions to

fill the same.

21 Have you given BCG vaccine for

TB as injection in left arm which

causes small scar?

Yes …………………… 1

No ……………………. 2 S4-3

22 Check for the scar on Lt upper

arm.

Present ……………...1

Absent ……………… 2 S4-4

23 Have you ever given Polio drops

to ABC?

Yes …………………… 1

No ……………………. 2 S4-5

24 Were drops of Polio vaccine given

with BCG at time of birth? (Polio

0)

Yes …………………… 1

No ……………………. 2 S4-6

25 How many times you have given

polio drops to ABC?

_________ times S4-7

26 Have you given DPT vaccine to

ABC, an injection given in

anterolateral thigh?

Yes …………………… 1

No ……………………. 2 S4-8


6

27 If yes, how many times? 1

2

3

4 or more

S4-9

28 Have you given measles

vaccination to ABC, an injection at

the age of 9 months on right

upper arm?

Yes …………………… 1

No ……………………. 2 S4-

10

29 Was drops of Vitamin A was given

with measles vaccination?

Yes …………………… 1

No ……………………. 2

S4-

11

30 Is child immunized for age?

0 to 6 weeks: BCG, OPV 0

6weeks: BCG, OPV 0 & 1, DPT 1

10 weeks: BCG, OPV 0 & 1, DPT

1, 2

14 weeks: BCG, OPV 0 & 1, DPT

1, 2 & 3

9months: BCG, OPV 0 & 1, DPT

1, 2 & 3, Measles

Yes …………………… 1

No ……………………. 2

S4-

12

31 Have you given vaccine for any of

the diseases mentioned here?

(tick all appropriates)

Hepatitis B ……………………….1

Hemophilus Influenza B…….2

Typhoid……………………………3

Rotavirus ……………………….. 4

S4-

13

HISTORY OF DIARRHOEA

32 How many times in past 6 months

ABC had diarrhea?

S5-1

33 Has ABC had diarrhea in last 2

weeks?


Yes …………………… 1

No ……………………. 2 S5-2


7

34 How many days ABC had

diarrhea?

………………………days

35 Was there any blood in stool? Yes …………………… 1

No ……………………. 2 S5-3

36 Did you seek treatment for the

diarrhea?

Yes …………………… 1

No ……………………. 2 S5-4

37 Where did you go for the

treatment?

ASHA ………………………………. 1

ANM ……………………………….. 2

PHC ………………………………… 3

CHC ………………………………… 4

District Hospital ……………… 5

Medical College………………... 6

Private hospital ……………….. 7

Others (specify) ………………. 8

S5-5

38 Was ABC hospitalized for the

diarrhea?

Yes …………………… 1

No ……………………. 2 S5-6

39 If yes, for how many days ABC

was admitted?

days S5-7

40 Did you give ORS for the diarrhea? Yes …………………… 1

No ……………………. 2 S5-8

HISTORY OF RESPIRATORY ILLNESS

42 How many times in past 6 months

ABC had fever with cough?

S6-1

43 Has ABC had fever in last 2

weeks?

Yes …………………… 1

No ……………………. 2 S6-2

44 Has ABC had cough in last 2 Yes …………………… 1 S6-3


8

weeks?

No ……………………. 2

45 When ABC had cough, did he/she

had any of the following

(tick all appropriate)

Noisy breathing

Fast breathing

Difficulty in breathing

Difficulty in feeding

S6-4

46 Did you seek treatment for the

illness?

Yes …………………… 1

No ……………………. 2 S6-5

47 Where did you go for the

treatment?

ASHA ………………………………. 1

ANM ……………………………….. 2

PHC ………………………………… 3

CHC ………………………………… 4

District Hospital ……………… 5

Medical College………………... 6

Private hospital ……………….. 7

Others (specify) ………………. 8

S6-6

48 Was ABC hospitalized for the

illness?

Yes …………………… 1

No ……………………. 2 S6-7

49 If yes, for how many days? Days S6-8

50 Was ABC given any drugs for the

illness?

Yes …………………… 1

No ……………………. 2 S6-9


9

SOCIO ECONOMIC STATUS

55 What is the education

of the family head?

Professional degree …………………… 7

Graduate or Post Graduate ………… 6

Intermediate or post highschool diploma 5

High school certificate ……………….. 4

Middle school completion ………….. 3

Primary school or literate …………. 2

Illiterate ……………………………………1

S7-1

56 What is the education

of ABc’s Mother?

Professional degree …………………… 7

Graduate or Post Graduate ………… 6

Intermediate or post …………………. 5

high school diploma

High school certificate ……………….. 4

Middle school completion ………….. 3

Primary school or literate …………. 2

Illiterate ……………………………………1

S7-2

57 What was the

household expenditure

for last one month?

Rs. ___________________________ S7-3

58 What is the monthly

income of family head Rs. ___________________________ S7-4

59 What is the occupation

of the family head?

Profession ………………………………. 10

Semi profession ………………………… 6

Clerk or shop owner or farm owner …. 5

Skilled worker …………………………... 4

Semi skilled worker …………………... 3

Unskilled worker ……………………… 2

Unemployed ……………………………... 1

S7-5


10

ANTHROPOMETRY WEIGHT MEASUREMENT

Age of child < 2 years ………………………………………… go to question 1

Age of child > 2 years ……………………………….………… go to question 2

1 A Weight of Mother with child (to the nearest 0.1 kg)

………………Kg

B Weight of mother without child (to the nearest 0.1 kg)

……………… kg

C Weight of child (A-B) ………………. Kg

2 Weight of child (to the nearest 0.1 kg) ………………. Kg

HEIGHT MEASUREMENT

Age of child > 2 years ………………………………………… go to question 3

Age of child < 2 years ……………………………….………… go to question 4

3 A Check the following before taking height

Child is standing upright without footwear

Heels touching back of board Both knees are in straight position Child is looking straight horizontally

B Measure the height of child with nearest 0.1 cm ……………………cm

LENGTH MEASUREMENT

If height of child is < 85 cm or age < 2 years

4 A Check the following before taking length

Child in lying down position Looking straight up Back of knees touching the board

B Measure the length of child to nearest 0.1 cm …………………..cm

INTERVIEWER CHECKLIST 1. Check whether all entries have been made correctly. 2. Height and weight of children is noted properly. 3. For all malnutrition cases mothers have been advised to seek treatment from

the medical facility. 4. Thanked participant for their time and co operation.

________________________________________ SIGNATURE OF THE INTEVIEWER

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