Childhood undernutrition inequalities in Empowered Action Group states of India: evidence from NFHS, 2006-2016

INTRODUCTION

Child undernutrition is a major public health problem in many low- and middle-income countries. In these countries, malnutrition alone has an account of 45% deaths among under- five children, which is estimated at 3 million deaths yearly. Malnutrition is the concealed cause of one out of every two such deaths.^1,2 It is not equally distributed throughout the world. Disparities in health outcomes between poor and rich are increasingly attracting attention from researchers and policy makers.^3,4 Socioeconomic inequality in malnutrition refers to the degree to which childhood malnutrition rate differs between more or less socially and economically advantaged groups. At a more global level, Wagstaff and Watanabe provided evidence on socioeconomic inequality in malnutrition across 20 developing countries.⁵ Other relevant across country studies include those of who describe total inequality, and who describe inequalities between urban and rural populations.⁶ The latter two studies, nevertheless, provide no evidence on socioeconomic inequality within developing countries.

Moreover, a number of study have found consistent divergence in the prevalence of malnutrition along the lines of age, sex and birth size of children.^7-10 As well, on that point are consistent findings in child malnutrition studies that households’ wealth, usually measured in increments in household material standards which was connected with childhood nutritional status.^11,12 It is argued that children from the poorest households are stunted or underweight compared to children from the richest households.¹³ Higher rates of stunting and underweight have been associated with children who reside in rural areas than those in urban areas.^6,14 Further, the level of mother’s educational attainment is persistently associated with child malnutrition.^15,16 Regarding access to health care services, it has been proven that children from households having difficulty in accessing health care services suffer from considerably higher levels of childhood malnutrition.^17,18

In Indian society, the inequality has been characterized by its deep roots into the diversity of cultures, languages, caste and religion. This diversity has created divergence in the population in the matter of economic and familial characteristics. If inequalities are arising due to alteration in the level of efforts made by individuals of different background then morally admissible, but if inequalities are due to circumstances which are beyond the control of an individual, such as region, caste, religion, sex, ethnicity and so on, then it will be unethical and unacceptable. This study updates and enlarges the evidence of percentage changes in undernutrition and socioeconomic inequality in undernutrition during the last decade by using the secondary data of National Family Health Survey-3 (NFHS-3) (2005-6) and National Family Health Survey-4 (NFHS-4) (2015-16) of India’s 8 demographically backward empowered action group (EAG) states, viz., Bihar, Chattisgarh, Madhya Pradesh, Rajasthan, Orissa, Jharkhand, Uttar Pradesh and Uttarakhand.^19,20

METHODS

The present study presents analysis and results based on the secondary data of the two successive rounds of the National Family Health Survey data which are conducted during 2006 (NHFS-3) and 2016 (NFHS-4).^19,20 The NFHSs is a large-scale, cross-sectional, multiround survey which is nationally representative sample of households throughout India. It has been conducted under the stewardship of the Ministry of Health and Family Welfare, Government of India. The survey provides information on demographic and health parameters as well as data on various socioeconomic and program dimension, which are critical for implementing the desired changes in demographic and health parameters The sampling design was based on a two-stage sample design. In the first stage enumeration areas (EAs) were drawn from census files. In the second stage, for each selected EA a household sample was drawn from the listing of households. This study was based on Empowered Action Group (EAG) states. The number of eligible women in EAG states (in the age group 15-49 years) interviewed were 20,668 and 147,049 in NFHS-3 and NFHS-4 respectively. The analysis of this study was based on 16,802 and 128,400 children aged 0-59 months from NFHS-3 and NFHS-4 respectively with valid anthropometric component in which weight and measurement recorded in the two consecutive survey. Children whose length/height information was missing or invalid were excluded.

Outcome variables

The present study measures three outcome variables, namely, stunting, wasting and underweight.

Stunting: Stunting is an indicator of linear growth retardation relatively uncommon in the first few months of life. However, it becomes more common as children get older. Children with height-for-age scores below minus two standard deviations (z-score <˗2SD) from the median of the reference population are considered short for their age or stunted.

Wasting: Wasting indicates body mass in relation to body length. Children whose weight-for height z-scores are below minus two standard deviations (z-score <˗2SD) from the median of the reference population are considered wasted (i.e. too thin for their height) which implies that they are acutely undernourished otherwise they are not wasted.

Underweight: Underweight is a composite index of stunting and wasting. This means children may be underweight if they are either stunted or wasted, or both. In a similar manner child may be underweight, when their z-score is lower than two standard deviations.

Defining predictor variables

Important explanatory variables in the present study were based on the previous studies and data available in the data set. Further these variables were categorized into four categories namely child characteristics, maternal characteristics, household characteristics and community characteristics. Child characteristics included in the analysis were sex of the child, age of child, breastfeeding duration, baby size at birth, place of birth delivery, immunization status of child, birth order, birth interval and child was wanted or unwanted. Maternal characteristics included in the analysis were mother’s age at birth, mother’s education, Mother’s body mass index (BMI). Community characteristics included in the analysis were the place of residence and EAG states.

Statistical analysis

To meet the objective, bivariate and multivariate analysis are carried out to estimate the levels and trends of childhood undernutrition by different socioeconomic and demographic characteristics. Chi-square at the 0.05 level is used to check the statistical association between the outcome and predictor variables in the bivariate analysis. Non-linear Fairlie decomposition method of binary outcome variables were used to identify and quantify the separate contribution of different socioeconomic characteristics in gap of childhood malnutrion between 2006 and 2016.²¹ All statistical analysis was done using Excel, R-CRAN and STATA 13 after adjusting survey design and sampling weight.

RESULTS

Trends in childhood undernutrition in EAG state, India

Results from Figure 1 indicates that the prevalence of undernutrition has decreased in EAG, states during last one decade (2006 to 2016) while the prevalence of wasting remained almost same as 10 years back. The stunting decreased nearly 8% from 52.2% during 2006 to 44.0% during 2016. The prevalence of underweight declined from 48.3% in 2006 to 40.5% in 2016.

Socioeconomic differentials in childhood undernutrition

Table 1 represent the socioeconomic differentials in childhood undernutrition by selected socioeconomic characteristics in EAG states, India 2006 to 2016. The prevalence of stunting (15.7%), wasting (5.8%) and underweight (16.1%) in EAG states has dropped during 2006 to 2016. The prevalence of stunting, wasting and underweight were associated with wealth quintile and mother’s education.

Sources: Based on author’s computation from NFHS-3 (2005-2006) and NFHS-4 (2016). Calculated as relative change = [(2006 %-2016%)/2006%*100]

The prevalence of stunting, wasting and underweight were declined among sex of child and children whose birth size small. Prevalence of stunting (50% versus 42%) and underweight (46% versus 38%) were more in home delivery as compared to institutional delivery. Examining the prevalence of undernutrition by mother’s level of education also provides similar patterns of decline. For instance, the prevalence of stunting has declined from 59 percent in 2006 to 53 percent in 2016 and underweight has 55 percent in 2006 to 42 percent in 2016 among the uneducated mothers. In contrast, the prevalence of stunting and underweight among the most educated mothers (>secondary) has increased in 2006 to 2016. Undernourished mother has played a significant role to increased stunting and underweight. In other words, the prevalence of both, stunting and underweight, during this period have declined across wealth and educational categories. For instance, among the richest wealth quintile, the prevalence of stunting has dropped from 27 percent in 2006 to 25 percent in 2016. Among the poorest wealth quintile, the prevalence of stunting and underweight has declined by 12 percent and 16 percent respectively during a last decade. The trends remain more or less similar across other wealth quintiles. Percentage of stunting and underweight are more among children who belong to rural areas than who belong to urban areas and has almost similar patterns of declined.

Multivariate analysis

In this study Table 2, 3 and 4 depict the magnitude of change in childhood undernutrition by selected socioeconomic characteristics over a decade. Table 2, result indicate that the predicted probabilities of stunted among male and female children were almost same however the decline in the prevalence of stunted was 4 percent higher among female compared to male children during 2006-16. At the same period, the prevalence of stunted was about twice higher (21%) among children whose age 4 to 5 years than the children whose age less than 1 year (10%). Likewise, the decline in the prevalence of stunted children was almost double (21%) among mothers who had completed middle or below middle as compared to mothers who had completed high school or above (11%) and obesity mother (16%) as compared to low BMI of mother (32%). There were no much difference found in breastfeeding status, birth size, and place of delivery, immunization, birth order, birth interval, status of child, mother’s age at time of birth. Caste and religion also varied the changes. Over the same period, children who belong to the poorest quintile, the probability of stunted declined from 0.578 to 0.473, a decline of 18 percent points whereas, children who belong richer quintile, the probability of stunted declined by 25 percent. The higher percentage of declining in prevalence of stunting in Jharkhand as compared to other states. The predicted probabilities of stunted was higher among children from Madhya Pradesh (0.463). The declined of predicted probability was lower in Madhya Prdaesh (14%) than Jharkhand (26%) during 2006-16.

According to Table 3, the predicted probabilities of wasted among children below 5 years of age were increased during a decade. It varied by age of child, breastfeeding status, birth size, birth order and birth interval while sex of child, place of delivery, immunization and status of child had no much difference of predicted probabilities of wasted. Considering mother’s education, the predicted probability of wasted higher among children of mothers with no education, from 0.228 in 2006 to 0.437 in 2016, which was increased by 92 percent. Children who belong to the poorest quintile had a higher probability of wasted as compared to the richest quintile. The predicted probability of wasted was increased more among poorest children (88%) than the richest children (57%). In the case of variation in the probability of wasted children, the predicted probability of wasted increased by 92 percent in urban areas and 78 percent in rural areas over the last decade.

As stated in Table 4, children whose aged above less than one year were less predicted probabilities of underweight as compared to whose age above one year and the percentage change in predicted probabilities were higher among children whose age 4 to 5 years (15%) compared to children whose age less than one year (13%). The probability of underweight was higher among the small birth size of children (0.49) as compared to the large size of children (0.38) which was declined by 18 percent and 12 percent respectively. These were also varied by place of delivery, immunization, birth order, birth interval, status of the child, mother’s age at time of birth. Considering mother’s education, the probability of underweight among children of mothers with no education, from 0.505 in 2006 to 0.437 in 2016, whereas the declined among children with more educated mothers was 15 percent. Children who belong to the poorest quintile had a higher risk of underweight as compared to the richest quintile. The percentage of underweight declined more among richer children (21%) than the poorest children (15%). In the case of variation in the proportion of underweight children, the predicted probability of underweight declined by 15 percent in rural areas and 10 percent in urban areas over the last decade.

Socio-economic inequality in childhood undernutrition

Tables 5 and 6 present results from the decomposition analysis which shows how the various socioeconomic characteristics of respondents contribute to inequality in child undernutrition. According to Table 5, institutional delivery contributed 41.8 percent and educated mothers contributed 25.5 percent in reducing the prevalence of underweight. Proportion of undernourished mothers contributed 21.0 percent in reducing the prevalence of underweight children it means percentage of undernourished mothers has decreased from 2006 to 2016. Similarly, proportion of not working mothers contributed 11.7 percent in total reduction of underweight children, it possible only if proportion of not working mothers decreased from 2006 to 2016. Proportion of rich has tried to increase the prevalence of underweight children from 2006 to 2016, this is also due to reduction in proportion of rich from 2006 to 2016. Although in Table 6, institutional delivery and educated mother contributed about 56 percent and 25 percent in reducing the prevalence of stunting respectively. Mothers whose age at first birth more than 20 years were contributed 20.2 percent whereas unwanted child contributed 10.0 percent. Proportion of under-nourished mothers contributed 7.5 percent in reducing the prevalence of stunting children. Proportion of rich has tried to increase the prevalence of under-weight children from 2006 to 2016, this is also due to reduction in proportion of rich from 2006 to 2016.

DISCUSSION

There are various programmes in India that are centered around absolute undernutrition among children under five years, but as per the findings of the study, socioeconomic inequality in undernutrition is still present in India. The study investigated the prevalence of undernutrition at the national level and then measured the socioeconomic inequality in undernutrition among under five children. According to the present study, the prevalence of stunting (38%) and underweight (36%) have declined by 21 percent and 16 percent during the decade respectively while, wasting increased by 5 percent. Sex-specific differences in child undernutrition revealed that there is a significant decline among both males and females during a last decade. Sex of child, child’s age, birth size, place of delivery, immunization, birth order, birth interval, status of child, mother’s education level, BMI of mother, wealth quintile and place of residence were significantly associated with stunting and underweight. Most of the stunting and underweight children were found among women whose were young at the time of delivery. The Akombi study also suggests the increasing trend in child undernutrition in northern Nigeria, compounded by the overall status of women in the region, where pregnancies at a young age (15-19 years) were very high and women’s education levels are very low. ²²

The decomposition analysis shows how undernutrition is distributed among various socioeconomic groups. Mother’s poor nutritional status is playing significant role in the child’s short-term as well as long-term growth failures. According to Smith and Haddad, women’s nutritional status does indeed affect children’s nutritional status in early childhood through being less successful at breastfeeding, and caring practice that is vitally important for a child’s health and proper growth.²³ The children of uneducated woman have significantly higher risk of undernutrition than the children of woman who are educated. These results suggest that educated and knowledgeable mothers might have better health seeking behaviour coupled with household hygiene practices and they are likely to take appropriate actions to improve the health status of their children, which is also an important component of child nutrition. Similarly, prevalence of underweight and stunting are more improved among children whose mother are working. Besides these covariates, place of residence, birth order, child status, religion, and sanitation facility also play a vital role in child undernutrition.

Increased access to health services and the development of healthcare facilities, as well as the promotion of public health indicators after the implementation of a health care programme across the country on the one hand, and the establishment of the Multidisciplinary Program for Improvement of Nutritional Status of Children in India on the other hand, may be the main reasons that the prevalence of undernutrition has decreased in recent years in India. The average reports of undernutrition indices at the national level can be misleading and may hide useful and vital subnational information that can be used for better and more appropriate policymaking.^24,25

Therefore, obtaining a clear picture of undernutrition in children across socioeconomic groups, especially the stunting index, which has a well-proven relationship with the socioeconomic status of children seems essential for policymakers.^7,26,27

CONCLUSION

The results of this study indicated that not only the degree of socioeconomic inequality in undernutrition but also its pattern should be of concern in setting health policies. For this there is need to adopt different strategies of health policy intervention. It is important to have policies towards improving female literacy in the EAG states because maternal education plays a vital role in child health and in EAG states, the literacy rate is very low among women.

The existence of a functional health insurance system and increasing universal coverage are recommended to mitigate child undernutrition, so that the vulnerable and deprived populations who are not able to access health care facilities, can easily access health care services for early detection and treatment of undernutrition without any financial constraint.

ACKNOWLEDGEMENTS

The authors are thankful to Shri Gurmeet Singh Rana, Smt. Prabila Toppo and Shri Ganesh Prasad Jena for providing technical support.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: The study was approved by the Institutional Ethics Committee

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