The burden of anthropometric failure and child mortality in India

Developing and demonstrating an atomistic and holistic model of anthropometric failure among children under five years of age using the National Family Health Survey (NFHS)-5 data from India

Introduction

Composite Index of Anthropometric Failure (CIAF) and its further modifications have not incorporated all the combinations of malnutrition. We propose a new model incorporating all the forms of malnutrition among children under five years of age. However, the current models might misclassify a growing child as malnourished. Our objective is to develop a comprehensive scoring system using the three anthropometric Z-scores [height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) Z-scores] and demonstrate the proposed CIAF model using the National Family Health Survey-5 (NFHS-5) data from India.

Methods

A new scoring system was developed using the WAZ, HAZ, and WHZ scores to determine the child's nutritional status. We also proposed a new CIAF model by including all possible categories of malnutrition and practically demonstrated it using the NFHS-5 dataset after applying the new scoring system. Under-five children with heights, weights, and ages available were included in the analysis. The groups of malnutrition are presented as weighted proportions before and after applying the new score to the proposed model.

Results

Our final analysis included individual-level data of 198,802 children under five years of age (weighted N = 195,197). After applying the new scoring system to the proposed model, the prevalence of stunting has reduced to 11.8% (95% CI 11.66-11.94) from 13.2% (95% CI 13.09-13.39) and wasting prevalence has reduced to 4.9% (95% CI 4.85-5.04) from 6.4% (95% CI 6.29-6.51). The most common forms of anthropometric failures among Indian children by using the newly developed CIAF model are: "Stunting and underweight" (30,127; 15.4%), Stunting only (23,035; 11.8%), and "wasting and underweight" (14,698; 7.5%). We found a new category called "Stunting, underweight, and overweight" (stunting = HAZ < -2SD, underweight = WAZ < -2SD, overweight = WHZ > +2SD). It constituted 0.1% (220 children) of the total sample.

Conclusion

When the new scoring system is applied to the proposed CIAF model, it captures all forms and combinations of malnutrition among under-five children without overlap and prevents misclassifying a growing child as malnourished. The newly identified category shows that stunting (HAZ < -2SD), overweight (WHZ > +2SD) and underweight (WAZ < -2SD) can co-exist in the same child.

Contribution of low birth weight to childhood undernutrition in India: evidence from the national family health survey 2019-2021

BACKGROUND

Infants born with low birth weight (LBW), i.e. less than 2500g, is considered an important factor of malnutrition in Asia. In India, research related to this issue is still neglected and limited. Evidence exists that a large number of child deaths occur in India due to maternal and child malnutrition-related complications. Moreover, it has been found that the cost of malnutrition in India results in a significant reduction of the country's Gross Domestic Product (GDP). Thus, in this current context, this study aims to explore the contribution of low birth weight to childhood undernutrition in India.

METHODS

The study used data from the 5^th round of the National Family Health Survey (NFHS-5), a large-scale survey conducted in India. The survey collected information from 176,843 mothers and 232,920 children. The study used the last birth information (last children born 5 years preceding the survey) due to the detailed availability of maternal care information. Univariate and bivariate analyses were conducted to determine the percentage distribution of outcome variables. Multivariate logistic regression was employed to examine the association between LBW and undernutrition (stunting, wasting, and underweight). The study also used the Fairlie decomposition analysis to estimate the contribution of LBW to undernutrition among Indian children.

RESULTS

The results show that childhood undernutrition was higher in states like Uttar Pradesh, Bihar, Jharkhand, Gujarat, and Maharashtra. The results of the logistic regression analysis show that infants born with low birth weight were more likely to be stunted (OR = 1.46; 95% CI: 1.41-1.50), wasted (OR = 1.33; 95% CI: 1.27-1.37), and underweight (OR = 1.76; 95% CI: 1.70-1.82) in their childhood compared to infants born without low birth weight. The findings from the decomposition analysis explained that approximately 14.8% of the difference in stunting, 10.4% in wasting, and 9.6% in underweight among children born with low birth weight after controlling for the individuals' selected characteristics.

CONCLUSION

The findings suggest that LBW has a significant contribution to malnutrition. The study suggests that policymakers should prioritize strengthening maternal and child healthcare schemes, particularly focusing on antenatal and postnatal care, as well as kangaroo mother care at the grassroots level to reduce the burden of LBW and undernourished children.

Mapping Concurrent Wasting and Stunting Among Children Under Five in India: A Multilevel Analysis

Objectives: The study aims to examine the coexisting forms, patterns, and predictors of concurrent wasting and stunting (WaSt) among children under five in India. Methods: We used data from the National Family Health Survey to understand the trend and association of WaSt among children under five-year-old in India. Univariate analysis and cross-tabulations were performed for WaSt cases. The association was determined using multilevel binary logistic regression and multilevel regression, and the results were provided as adjusted odds ratios (aOR) with 95% confidence intervals at the significance level of p < 0.05. Results: The prevalence of WaSt has decreased from 8.7% in 2005-06 to 5.2 percent in 2019-2020. The proportion of WaSt children grew rapidly from 6 to 18 months, peaked at 19 months (8%), then dropped after 24 months. The prevalence of concurrent wasting and stunting is higher among boys compared to girls. Compared to children of different birth orders, those in the higher birth order are 1.2 times more likely to be WaSt cases (aOR = 1.20, 95% CI = 1.09, 1.33). The education of the mother is strongly correlated with WaSt instances, and children of more educated mothers have a 47% lower chance of being WaSt cases (aOR = 0.63, 95% CI = 0.57, 0.71). Children from wealthy families are 52% less likely to be WaSt cases (aOR = 0.48, 95% CI = 0.43, 0.55). Conclusion: This study emphasizes the importance of concurrent wasting and stunting and its relationship with socioeconomic factors among children under five in India.

Effects of Dietary Diversity on Growth Outcomes of Children Aged 6 to 23 Months in India: Evidence from National Family and Health Survey

Low dietary diversity significantly interplays with children’s growth failure. However, evidence of its crucial role in children’s health remains inconclusive in developing countries such as India. This study attempts to find the association between dietary diversity and growth outcomes among children aged between 6 and 23 months in India using the fourth round of the National Family Health Survey (NFHS), 2015−2016. A total of 67,278 mother-child pairs of children between the ages of 6−23 months and mothers aged 15−49 years were included in this study. Pearson’s chi-square significance test and multivariable logistic regression were used to determine the association between dietary diversity and child growth outcomes (stunted, wasted, and underweight). The study found that the prevalence of stunting and severe stunting among children aged between 6 and 23 months were 35.9% and 16.2%; 23.8% and 8.5% represented wasting, and severe wasting; and more than 32%, 10% were underweight and severely underweight respectively. This present study found that having an inadequate minimum dietary diversity (<4 food groups) significantly increases the risk of being stunted (adjusted odds ratio (AOR) = 1.29; 95% confidence interval (CI); 1.21−1.38), wasted (AOR = 1.29; 95% CI; 1.21−1.38), and underweight (AOR = 1.47; 95% CI; 1.39−1.56). Further, it was noted that children who did not intake dairy products, eggs, and other fruits and vegetables were more likely to be stunted, wasted, and underweight and more likely to be severely stunted, wasted, and underweight. Therefore, additional nutrition-specific interventions are urgently needed to strengthen and enhance existing feeding interventions aimed at improving infant and young child feeding (IYCF) practices, including complementary feeding practices among children aged between 6 and 23 months in India. The Government should focus such interventions more on states or regions where the prevalence of adequate minimum dietary diversity (MDD) and malnutrition is high.

Quality of anthropometric data in India's National Family Health Survey: Disentangling interviewer and area effect using a cross-classified multilevel model

India has adopted a target-based approach to reduce the scourge of child malnourishment. Because the monitoring and evaluation required by this approach relies primarily on large-scale data, a data quality assessment is essential. As field teams are the primary mode of data collection in large-scale surveys, this study attempts to understand their contribution to variations in child anthropometric measures. This research can help disentangle the confounding effects of regions/districts and field teams on the quality of child anthropometric data. The anthropometric z-scores of 2,25,002 children below five years were obtained from the fourth round of India's National Family and Health Survey (NFHS-4), 2015–16. Unadjusted and adjusted standard deviations (SD) of the anthropometric measures were estimated to assess the variations in measurements. In addition, a cross-classified multilevel model (CCMM) approach was adopted to estimate the contribution of geographical regions/districts and teams to variations in anthropometric measures. The unadjusted SDs of the measures of stunting, wasting, and underweight were 1.7, 1.4, and 1.2, respectively. The SD of stunting was above the World Health Organisation threshold (0.8–1.2), as well as the Demographic and Health Survey mark. After adjusting for team-level characteristics, the SDs of all three measures reduced marginally, indicating that team-level workload had a marginal but significant role in explaining the variations in anthropometric z-scores. The CCMM showed that the maximum contribution to variations in anthropometric z-scores came from community-level (Primary Sampling Unit (PSU)) characteristics. Team-level characteristics had a higher contribution to variations in anthropometric z-scores than district-level attributes. Variations in measurement were higher for child height than weight. The present study decomposes the effects of district- and team-level factors and highlights the nuances of introducing teams as a level of analysis in multilevel modelling. Population size, density, and terrain variations between PSUs should be considered when allocating field teams in large-scale surveys.

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Unadjusted standard deviation for child malnourishment indicators are above the recommended level of DHS data quality standards.

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Variation in stunting is directly proportional to workload measured by number of eligible children in the PSUs.

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Cross-classified multilevel models show significant team-level contribution in explaining variations in anthropometric scores.

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Team-level contribution to explaining variations in child anthropometric measures is larger than district-level factors.

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The number of days assigned to gather anthropometric measurements should be dependent on the number of eligible respondents in a PSU, which may be identified at the time of mapping & listing, rather than being a fixed number of days across all the states of India.

Factor associated with anthropometric failure among under-five Bengali children: A comparative study between Bangladesh and India

Background

Child undernutrition is a burden and the leading cause of child mortality in low-and middle-income countries like Bangladesh and India. Currently, this issue is a matter of great concern, inasmuch as achieving the Sustainable Development Goals (SDGs). The study intends to determine the factors of child undernutrition using a single composite index of anthropometric failure (CIAF) among the Bengali population.

Methods

Unit level data on 14055 under 5 children were extracted from the Bangladesh Demographic and Health Survey 2017–18 (BDHS) and the 4^th National Family Health Survey of India (NFHS-4). To understand child undernutrition and generate CIAF, data on height-for-age (stunting), weight-for-height (wasting), and weight-for-age (underweight) were used by WHO guidelines. These three undernutrition indicators were combined into a single undernutrition indicator called anthropometric failure (anth-failure) using the CIAF concept. Explanatory factors of anth-failure included data on maternal health, socio-demographic and birth-related variables. Differences of frequency were determined by Z-proportional and Chi-square tests; predictors of anth-failure were determined by binary logistic regression. Cut off point of p-value was taken as 0.05 to test the significance.

Results

Inter-country disparities were revealed, about half of Bengali children in India and two-fifths in Bangladesh being prone to anth-failure. Stunting and underweight were more prevalent in both countries than wasting. Maternal undernutrition, lack of maternal education, and poor wealth index were common factors of anth-failure for both countries. Children in Bangladesh developed anth-failure after the end of breastfeeding period, indicating a lack of nutritious food. Lack of antenatal care was another significant factor in Bangladesh. In India, the first child suffered from anth-failure due to lack of maternal education.

Conclusions

This study provides a better understanding of multifactorial impact on child undernutrition. It is proposed that the emphasis should be on initiatives that improve maternal education and nutrition, child food security, boost household wealth index, and enhance mothers’ access to health care. The study strongly recommends that the governments of Bangladesh and India invest financially in preventing child malnutrition, which will contribute to achieving the first four SDGs.

Is maternal autonomy associated with child nutritional status? Evidence from a cross-sectional study in India

Despite India’s steady economic growth over recent the period, the burden of childhood malnutrition persists, contributing to higher neonatal and infant mortality. There is limited evidence available to contextualise mothers’ crucial role in childcare practices and health status in the Indian context. This study attempts to assess the association between maternal autonomy and the nutritional status of children under five. We used samples of 38,685 mother-child pairs from the fourth round of the National Family Health Survey (NFHS-4), conducted in 2015–16. We considered three widely used indicators of child nutrition as outcome variables: stunting, wasting, and underweight. Maternal autonomy (measured from three dimensions: household decision-making, freedom of physical movement, and access to economic resources/control over assets) was the key predictor variable, and various child demographics, maternal, and household characteristics were considered control variables. Stepwise binary logistic regression models were performed to examine the association. Of study participants, 38%, 21%, and 35% of children were stunted, wasted, and underweight, respectively. Our results (models 1 to 4) indicate that mothers with greater autonomy were significantly associated with lower odds of malnourished children. After controlling for all potential confounding variables (in model 5), maternal autonomy had a statistically insignificant association with children’s stunting (Odds ratio [OR]: 0.93; 95% confidence interval [CI]: 0.87, 1.00) and wasting (OR: 0.92; 95% CI: 0.85, 1.00). However, a significant relationship (though marginally) was retained with underweight (OR: 0.94; 95% CI: 0.88, 0.99). In addition, socio-demographic characteristics such as child age, birth order, maternal education, maternal BMI, place of residence and household wealth quintile were found to be strong predictors of child nutritional status. Future policies should not only inform women’s empowerment programmes but also emphasise effective interventions toward improving female educational attainment and nutritional status of women, as well as addressing socioeconomic inequalities in order to combat the persistent burden of childhood malnutrition in India.

Effect of nutritional education on anthropometric deficits among pre-school aged children in south West Ethiopia: quasi-experimental study

BACKGROUND

Under-nutrition is a global problem and one of the most serious public health issues. Globally, 156 million under-five children were stunted, and 50 million were wasted in 2016. Malnutrition among preschool-age children is caused by low socioeconomic status, food insecurity, poor feeding practices, and infectious diseases. This intervention aimed to evaluate the effect of nutrition education delivered through trained health professionals in improving the nutritional status of preschool -aged children.

METHODS

A quasi-experimental design among 588 preschool -aged children was used. A multistage sampling technique followed by a systematic random sampling technique was used to identify caregivers with preschool-aged children. Structured questionnaires were used to collect data. The baseline difference in demographic and socioeconomic characteristics between the two groups was examined using a chi-square test and an independent sample t-test was used to determine the mean difference in under-nutrition between the intervention and control groups. Generalized estimating equations (GEE) were used to determine the change in the difference in outcome between the intervention and control groups as well as the association of predictors with under-nutrition in children. The Adjusted odds ratio (AOR) with the corresponding 95% confidence intervals was reported to show the strength of the association. Variables with a p-value of less than 0.05 were considered statistically significant in multivariable analysis.

RESULTS

In this study, the nutritional status of preschool age children was significantly associated with nutrition education intervention [AOR = 0.566, 95% CI: (0.347, 0.923)], place of delivery [AOR = 0.724, 95% CI: (0.551, 0.951)], ARI in the last 2 weeks [AOR = 1.823, 95% CI: (1.226, 2.710)], source of drinking water [AOR = 0.624, 95% CI: (0.484, 0.805)] and household food security [AOR = 1.311, 95% CI: (1.030, 1.669)] .

CONCLUSIONS

Findings of this study showed that nutrition education can effectively reduce the magnitude of under-nutrition among preschool children. Under-nutrition was e significantly associated with nutritional education, place of delivery, ARI in the last 2 weeks, source of drinking water, and food security. Therefore, both government and non-government should consider the impacts of nutrition education to alleviate under-nutrition and improve the health status of preschool-age children.

Do children in India grow well into adolescents? Longitudinal analysis of growth transitions from Young Lives panel survey in India

OBJECTIVES

Studies that examined the growth during late childhood and early adolescence beyond 8 years of age are very limited. Further, most studies have used dichotomized classification of stunting, thereby limiting the understanding of moderate stunting in childhood growth trajectory. We aimed to examine the course of stunting from childhood to adolescence by undertaking robust analyses of the Young Lives Survey (YLS) longitudinal data from India using multilevel categorization of stunting.

STUDY DESIGN

Retrospective cohort analysis was undertaken from YLS in India among 1827 children from the younger cohort born in 2001-02 with complete follow-up data in all five rounds of YLS collected in 2002, 2006, 2009, 2013, and 2016.

METHODS

A three-state multistate Markov model (not stunted, moderate, severe) was performed to estimate annual transition probabilities, mean sojourn-time, and transition-specific risk factors.

RESULTS

Between Round-one and Round-five, cross-sectional prevalence of severe stunting decreased from 10.4% (95% confidence interval [CI]: 7.8%, 13.7%) to 5.3% (95% CI: 3.8%, 7.3%), while moderate stunting increased from 19.9% (95% CI: 16.3%,23.9%) to 21.7% (95% CI: 18.4%, 24.9%). Mean Sojourn time estimation indicated a relatively concise state for moderate stunting. The stunting trajectory had shown gender differential where more faltering to severe stunting and lower recovery to the normal state was observed among girls between 8 and 12 years and among boys between 12 and 15 years. Compared with boys, girls had 40% excess likelihood (Hazard Ratio: 1.40; 95% CI 1.00 to 1.95) for moderate-to-severe stunting transition and also had 19% excess likelihood (Hazard Ratio: 1.19; 95% CI 1.01 to 1.40) of favorable transition (moderate-to-non-stunted).

CONCLUSIONS

The transition trajectory highlights preadolescence, especially among girls, as an additional window of opportunity to ensure better nutrition in adolescent life. With a fifth of adolescents living in India, study findings call for coordinated, multisectoral, age-appropriate, and gender-responsive approach to take India closer to meeting SDG-2.

Effects of dairy intake on anthropometric failure in children ages 6 to 23 mo consuming vegetarian diets and fulfilling minimum dietary diversity in India

OBJECTIVES

In India, although nutritional conditions have improved, a high prevalence of anthropometric failure is still reported in children. Unfortunately, there are knowledge gaps surrounding nutrient and anthropometric shortcomings as well as dietary patterns. More than half of children are consuming a vegetarian diet. This study aimed to evaluate the effects of dietary adequacy levels on anthropometric failure in 5772 vegetarian children (ages 6-23 mo) satisfying minimum dietary diversity.

METHODS

Data were collected from the National Family Health Survey 2015-16. We created three food combinations: maximum adequacy (dairy and four food groups), medium adequacy (dairy and three food groups), and minimum adequacy (four food groups excluding dairy). We calculated odds ratios (ORs) for the association between dietary adequacy levels and anthropometric failures with 95% confidence intervals (CIs) using logistic regression models. The modification effect of breastfeeding status was also explored.

RESULTS

Approximately 35% of children had stunted growth. ORs showed a significant increase in the risk of anthropometric failure, notably wasting, and underweight in children with minimum-adequacy diets (OR, 1.46; 95% CI, 1.15-1.86) compared with children with maximum-adequacy diets. Those associations were more pronounced among children who were not breastfed (OR, 2.44; 95% CI, 1.19-5.00) than among children who were (OR, 1.35; 95% CI, 1.04-1.74; P value for the interaction = 0.07). Similar associations were observed for wasting among children who were not breastfed (OR, 2.82; 95% CI, 1.34-5.95) and who were breastfed(OR, 1.12; 95% CI, 0.85-1.5; P value for the interaction = 0.03).

CONCLUSIONS

Dairy is an essential source of nutrients that are required for healthy growth and development in children younger than 2 y, even if they satisfy minimum dietary diversity conditions in India.

Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis

Background

Undernutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthropometric failures. This research also includes the Spatio-temporal distribution of childhood anthropometric failures across time.

Methods

Secondary data was obtained from the Ethiopian Demographic and Health Survey for the survey 2005, 2011, and 2016 years. Data included 23,864 samples of children between the ages of 0–59 months, which is a nationally representative sample in Ethiopia. Other than descriptive statistics, the multivariate multilevel logistic regression was used to identify associated factors, and Getis-Ord spatial statistical tools were employed to identify high and low hotspots areas of anthropometric failures.

Result

The prevalence obtained with CIAF in 2005, 2011, and 2016 was, 53.5 %, 51 %, and 46.2 % of children were suffering from under-nutrition respectively. The spatial analysis revealed areas that are at a higher risk of anthropometric failures consistently were found in northern parts of the country, largely in the Amhara, Tigray, and Afar regions. Multilevel logistic regression analysis showed that the risk of anthropometric failure was higher among older children, had low birth weight, had a mother with low BMI, was in a rural area, had mothers and fathers without formal education.

Conclusions

In addition to identifying wasted, stunted, and underweight children, CIAF also identified children with multiple conditions, which are often overlooked in nutritional surveys. As revealed by this composite index, the prevalence of anthropometric failure remains considerably high and its spatial distribution also significantly varied across the regions in the country. The established socio-demographic characteristics and districts with a higher risk of anthropometric failure can be used to develop localized intervention and prevention strategies to improve Ethiopian children’s nutritional status and healthcare.