Socioeconomic inequality in child health outcomes in India: analyzing trends between 1993 and 2021.

BACKGROUND: The health of India's children has improved over the past thirty years. Rates of morbidity and anthropometric failure have decreased. What remains unknown, however, is how those patterns have changed when examined by socioeconomic status. We examine changes in 11 indicators of child health by household wealth and maternal education between 1993 and 2021 to fill this critical gap in knowledge. Doing so could lead to policies that better target the most vulnerable children. METHODS: We used data from five rounds of India's National Family Health Survey conducted in 1993, 1999, 2006, 2016, and 2021 for this repeated cross-sectional analysis. We studied mother-reported cases of acute respiratory illness and diarrhea, hemoglobin measurements for anemia, and height and weight measurements for anthropometric failure. We examined how the prevalence rates of each outcome changed between 1993 and 2021 by household wealth and maternal education. We repeated this analysis for urban and rural communities.  RESULTS: The socioeconomic gradient in 11 indicators of child health flattened between 1993 and 2021. This was in large part due to large reductions in the prevalence among children in the lowest socioeconomic groups. For most outcomes, the largest reductions occurred before 2016. Yet as of 2021, except for mild anemia, outcome prevalence remained the highest among children in the lowest socioeconomic groups. Furthermore, we show that increases in the prevalence of stunting and wasting between 2016 and 2021 are largely driven by increases in the severe forms of these outcomes among children in the highest socioeconomic groups. This finding underscores the importance of examining child health outcomes by severity. CONCLUSIONS: Despite substantial reductions in the socioeconomic gradient in 11 indicators of child health between 1993 and 2021, outcome prevalence remained the highest among children in the lowest socioeconomic groups in most cases. Thus, our findings emphasize the need for a continued focus on India's most vulnerable children.

Anthropometric failures and its predictors among under five children in Ethiopia: multilevel logistic regression model using 2019 Ethiopian demographic and health survey data.

BACKGROUND: Composite Index of Anthropometric Failure (CIAF) combines all three forms of anthropometric failures to assess undernutrition status of children. There is no study on CIAF to identify the real and severe form of under nutrition among Ethiopian children that addressed community level factors. So, this study determined CIAF and identified important factors which helps to design appropriate intervention strategies by using multi-level advanced statistical model. METHODS: The study included 5,530 under five children and utilized a secondary data (EMDHS 2019) which was collected through community-based and cross-sectionally from March 21 to June 28, 2019. Composite index of anthropometric failure among under five children was assessed and a two-stage sampling technique was used to select the study participants. Descriptive summary statistics was computed. A multi-level binary logistic regression model was employed to identify important predictors of CIAF in under five children. Adjusted odds ratio with its 95% CI was estimated and level of significance 0.05 was used to determine significant predictors of CIAF. RESULTS: The prevalence of composite index of anthropometric failure (CIAF) was 40.69% (95% CI: 39.41, 42.00) in Ethiopia. Both individual and community level predictors were identified for CIAF in under five children. Among individual level predictors being male sex, older age, short birth interval, from mothers who have not formal education, and from poor household wealth quintile were associated with higher odds of CIAF among under five children. Low community women literacy and being from agriculturally based regions were the community level predictors that were associated with higher odds of CIAF in under five children in Ethiopia. CONCLUSIONS: The burden of composite index of anthropometric failure in under five children was high in Ethiopia. Age of child, sex of child, preceding birth interval, mother's education, household wealth index, community women literacy and administrative regions of Ethiopia were identified as significant predictors of CIAF. Therefore, emphasis should be given for those factors to decrease the prevalence of CIAF in under five children in Ethiopia.

Intersectional Inequalities in Anthropometric Failure among Indian Children: Evidence from the National Family Health Survey (2015-2016).

Increasing body of health planning and policy research focused upon unravelling the fundamental drivers of population health and nutrition inequities, such as wealth status, educational status, caste/ethnicity, gender, place of residence, and geographical context, that often interact to produce health inequalities. However, very few studies have employed intersectional framework to explicitly demonstrate how intersecting dimensions of privilege, power, and resources form the burden of anthropometric failures of children among low-and-middle income countries including India. Data on 2,15,554 sampled children below 5 years of age from the National Family Health Survey 2015-2016 were analysed. This study employed intersectional approach to examine caste group inequalities in the anthropometric failure (i.e. moderate stunting, severe stunting, moderate underweight, severe underweight, moderate wasting, severe wasting) among children in India. Descriptive statistics and multinomial logistic regression models were fitted to investigate the heterogeneities in the burden of anthropometric failure across demographic, socioeconomic and contextual factors. Interaction effects were estimated to model the joint effects of socioeconomic position (household wealth, maternal education, urban/rural residence and geographical region) and caste groups with the likelihood of anthropometric failure among children.More than half of under-5 children suffered from anthropometric failure in India. Net of the demographic and socioeconomic characteristics, children from the disadvantageous caste groups whose mother were illiterate, belonged to economically poor households, resided in the rural areas, and coming from the central and eastern regions experienced disproportionately higher risk of anthropometric failure than their counterparts in India. Concerted policy processes must recognize the existing heterogeneities between and within population groups to improve the precision targeting of the beneficiary and enhance the efficiency of the nutritional program among under-5 children, particularly for the historically marginalized caste groups in India.

Household food insecurity and nutritional status of schoolchildren in rural regions of Bajo Lampa, El Salvador (2018-2019).

In 2018, a cross-sectional study was conducted in six communities of Tecoluca, Bajo Lempa (El Salvador). Weight, height, sitting-height, skinfolds thickness and head, arm, and waist circumferences were measured in a sample of 334 schoolchildren. Nutritional status, body composition, and Extended Composite Index for Anthropometric Failure (ECIAF) were estimated. The Food Security Perception Survey (Spanish acronym: EPSA) was applied to 143 households. Anthropometric failure was observed in 37.5% of the schoolchildren. Association between stunting and underweight in boys and stunting and weight excess in girls was observed. About 58.7% of the households suffered from food insecurity.

Spatial data analysis of malnutrition among children under-five years in Ethiopia.

BACKGROUND: Childhood malnutrition is a major cause of child mortality under the age of 5 in the sub-Saharan Africa region. This study sought to identify the risk factors and spatial distribution of the composite index of anthropometric failure (CIAF). METHODS: Secondary data from 2000, 2005, 2011, and 2016 Ethiopian Health and Demographic Survey (EDHS) were used. The generalized geo-additive mixed model was adopted via the Integrated Nested Laplace Approximation (INLA) with a binomial family and logit link function. RESULTS: The CIAF status of children was found to be positively associated with the male gender, the potency of contracting a disease, and multiple births. However, it was negatively associated with family wealth quartiles, parental level of education, place of residence, unemployment status of mothers, improved sanitation, media exposure, and survey years. Moreover, the study revealed significant spatial variations on the level of CIAF among administrative zones. CONCLUSIONS: The generalized geo-additive mixed-effects model results identified gender of the child, presence of comorbidity, size of child at birth, dietary diversity, birth type, place of residence, age of the child, parental level of education, wealth index, sanitation facilities, and media exposure as main drivers of CIAF. The results would help decision-makers to develop and carry out target-oriented programs.

Bivariate binary analysis on composite index of anthropometric failure of under-five children and household wealth-index.

BACKGROUND: Malnutrition is the most common cause of mortality and morbidity of children in low and middle income countries including Ethiopia and household wealth index shares the highest contribution. Thus, in this study it is aimed to conduct bivariate binary logistic regression analysis by accounting the possible dependency of child composite index anthropometric failure and household wealth index. METHODS: In this study the data from Ethiopian Demographic and Health Survey (EDHS) 2016 involved 9411 under five children was considered. Child Composite Index Anthropometric Failure (CIAF) measures the aggregate child undernourished derived from the conventional anthropometric indices (stunting, underweight and wasting). The correlation between CIAF and wealth index was checked and significant correlation found. To address the dependency between the two outcome variables bivariate binary logistic regression was used to analyze the determinants of child CAIF and household wealth index jointly. RESULTS: Study results show that region, place of residence, religion, education level of women and husband/partner, sex of child, source of drinking water, household size and number of under five children in the household, mothers body mass index, multiple birth and anemia level of child had significant association with child CIAF. Female children were 0.82 times less likely to be CIAF compared to male and multiple birth children were more likely to be CIAF compared to single birth. Children from Oromia, Somalie, Gambela, SNNPR, Harari and Addis Ababa region were 0.6, 0.56, 0.67, 0.52, 0.6 and 0.44 times less likely to be CIAF compared to Tigray. A household from rural area were 15.49 times more likely poor compared to a household. The estimated odds of children whose mothers attended primary, and secondary and higher education was 0.82, and 0.52 times respectively the estimated odds of children from mothers who had never attended formal education. CONCLUSION: The prevalence of children with composite index anthropometric failure was high and closely tied with the household wealth index. Among the determinants, region, religion, family education level, and anemia level of child were statistically significant determinants of both CIAF and household wealth index. Thus, the authors recommend to concerned bodies and policymakers work on household wealth index to reduce the prevalence of child composite anthropometric failure.

A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones.

BACKGROUND: Undernutrition is the main cause of child death in developing countries. This paper aimed to explore the efficacy of machine learning (ML) approaches in predicting under-five undernutrition in Ethiopian administrative zones and to identify the most important predictors. METHOD: The study employed ML techniques using retrospective cross-sectional survey data from Ethiopia, a national-representative data collected in the year (2000, 2005, 2011, and 2016). We explored six commonly used ML algorithms; Logistic regression, Least Absolute Shrinkage and Selection Operator (L-1 regularization logistic regression), L-2 regularization (Ridge), Elastic net, neural network, and random forest (RF). Sensitivity, specificity, accuracy, and area under the curve were used to evaluate the performance of those models. RESULTS: Based on different performance evaluations, the RF algorithm was selected as the best ML model. In the order of importance; urban-rural settlement, literacy rate of parents, and place of residence were the major determinants of disparities of nutritional status for under-five children among Ethiopian administrative zones. CONCLUSION: Our results showed that the considered machine learning classification algorithms can effectively predict the under-five undernutrition status in Ethiopian administrative zones. Persistent under-five undernutrition status was found in the northern part of Ethiopia. The identification of such high-risk zones could provide useful information to decision-makers trying to reduce child undernutrition.

Mother's education level is associated with anthropometric failure among 3- to 12-year-old rural children in Purba Medinipur, West Bengal, India.

Maternal education plays a central role in children's health and nutrition. Living conditions and socioeconomic status are linked with mother's education, which in turn determines the health and development of a child. The Composite Index of Anthropometric Failure (CIAF) is a single indicator that reflects overall rate of three conventional indices of undernutrition: underweight, stunting and wasting. The study was undertaken among 621 rural Bengalee children (308 boys and 313 girls) aged 3-12 years from the Purba Medinipur district of West Bengal, India. Height (cm) and weight (kg) were recorded and NCHS standard values used to calculate z-scores (<-2SD). The same data were used to calculate CIAF as an indicator of 'anthropometric failure' (AF) or undernutrition. The prevalence of AF among the children was 59.40%. Chi-squared analysis was employed to evaluate the significance of differences in the prevalence of CIAF between the sexes and the association between nutritional indicators and socioeconomic parameters in the two sexes. Multiple binary logistic regression (MBLR) analyses (including the forward stepwise method) were also performed. Odds ratios with 95% confidence intervals were used to assess the risk of having AF. Results showed that mother's education was significantly associated with undernutrition (AF) controlling for the other factors considered. A very high prevalence of undernutrition is persisting in this region of India despite national nutritional supplementation programmes being operational. More attention to the improvement of living conditions and hygiene, and more particularly the education of women, in this population might be effective in attaining improved child growth and health.

Milk consumption and childhood anthropometric failure in India: Analysis of a national survey.

Dairy milk has been shown to contribute to child growth in many countries, but the relationship between milk intake and anthropometric outcomes among Indian children has not been studied. The objectives were to describe children aged 6-59 months who consume dairy milk in India and determine if dairy milk consumption was associated with lower odds of stunting, underweight and anthropometric failure among Indian children. This was a cross-sectional study based on the fourth Indian National Family Health Survey (NFHS-4), which was a national survey conducted between 2015 and 2016 by the Ministry of Health and Family Welfare. The primary exposure was the consumption of dairy milk within the past day or night. The primary outcomes were stunting (height-for-age z score < -2), underweight (weight-for-age z score < -2) and the composite index of anthropometric failure (CIAF), which is a combination of weight-for-age, weight-for-height and height-for-age. Multivariable logistic regression models and coarsened exact matching (CEM) were used to determine the relationship between dairy milk and odds ratios of each outcome. Setting was in India. Participants were children (N = 107,639) aged 6-59 months. Children who consumed dairy milk in the past day or night had an odds ratio of 0.95 for underweight (95% CI 0.92-0.98, P = .0005), 0.93 for stunting (95% CI 0.90-0.96, P < .0001) and 0.96 for CIAF (95% CI 0.93-0.99, P = .004), compared with children who did not consume dairy milk after adjusting for relevant covariates. When CEM was used among a subset (n = 28,207), evidence for relationships between dairy milk and anthropometric outcomes was consistent but slightly weaker. Widespread, equitable access to dairy milk among childhood may be part of an effort to lower the risk of anthropometric failure among children in India.

Extended composite index of anthropometric failure in Argentinean preschool and school children.

OBJECTIVE: The Composite Index of Anthropometric Failure (CIAF) can only be applied to children under 5 years of age and does not contemplate obesity. The aim of this study was to propose an Extended CIAF (ECIAF) that combines the characterization of malnutrition due to undernutrition and excess weight, and apply it in six Argentine provinces. DESIGN: ECIAF excludes children not in anthropometric failure (group A) and was calculated from a percentage of children included in malnutrition categories B: wasting only; C: wasting and underweight; D: wasting, stunting and underweight; E: stunting and underweight; F: stunting only; Y: underweight only; G: only weight excess; and H: stunting and weight excess. SETTING: Cross-sectional study conducted in Buenos Aires, Catamarca, Chubut, Jujuy, Mendoza and Misiones (Argentina). PARTICIPANTS: 10 879 children of both sexes aged between 3 and 13·99. RESULTS: ECIAF in preschool children (3 to 4·99 years) was 15·1 %. The highest prevalence was registered in Mendoza (16·7 %) and the lowest in Misiones (12·0 %). In school children (5 to 13·99 years) ECIAF was 28·6 %. Mendoza also recorded the highest rate (30·7 %), while Catamarca and Chubut had the lowest values (27·0 %). In the whole sample, about 25 % of the malnutrition was caused by undernutrition and 75 % by excess weight. CONCLUSIONS: The ECIAF summarizes anthropometric failure by both deficiency and excess weight and it highlights that a quarter of the malnutrition in the Argentine population was caused by undernutrition, although there are differences between Provinces (P < 0·05). ECIAF estimates are higher than those of CIAF or under-nutrition.

Assessment of undernutrition using Composite Index of Anthropometric Failure among children aged < 5 years in rural Yemen.

BACKGROUND: Impaired nutritional status is a major health problem affecting young children in developing countries that has a significant impact on child morbidity and mortality. AIMS: This study aimed to assess the prevalence of undernutrition among children aged < 5 years, using conventional indices and the Composite Index of Anthropometric Failure (CIAF), and then comparing their estimated results. METHODS: A community-based cross-sectional study was conducted and information was collected through house-tohouse visits using precoded structured records. We analysed data from 1292 children aged 6-59 months, from Ahwar and Al-Mahfed rural districts in Abyan Governate, South Yemen, with reference to the 2006 World Health Organization growth standards. RESULTS: CIAF identified undernutrition in 70.1% of children, while conventional anthropometric indices revealed 38.5% stunting, 39.9% wasting, and 55.1% underweight. Compared with conventional indices, CIAF aggregate recognized 31.6%, 30.2% and 15% more undernourished children than stunting, wasting and underweight separately. According to CIAF, 21% had a single anthropometric failure and 49.2% exhibited multiple failures. Stunting Index, Wasting Index and Underweight Index were 0.55, 0.57 and 0.79, respectively. CONCLUSIONS: CIAF gives a better estimate of undernutrition than currently used conventional indices; identifies more children with multiple anthropometric failures; and reflects a wider view of the extent and pattern of undernutrition of children living in communities with limited resource settings.

Are household food security, nutrient adequacy, and childhood nutrition clustered together? A cross-sectional study in Bankura, West Bengal.

BACKGROUND: Research on different measures of food security and their interrelation in order to identify vulnerable households are scarce in India. OBJECTIVES: The objective was to assess household food security (HHFS), nutrient adequacy, dietary diversity, and nutritional status of under-five children along with their interrelation in the slums of Bankura Municipality, West Bengal. METHODS: A cross-sectional study was conducted during 2016-2017 among 240 households using two-stage 30-cluster random sampling. Information regarding socioeconomic characteristics, availability, and utilization of different poverty alleviation schemes was collected. HHFS was assessed by a validated HHFS scale-short form in Bengali and nutrient adequacy with 24-h recall method. The eldest under-five child in the family was measured for anthropometry using standard procedure and for dietary diversity with the Individual Dietary Diversity Score. RESULTS: Overall, 74 (29.1%) households had "food security," whereas 102 (44.3%) and 64 (26.6%) had, respectively, low and very low food security. Among 190 under-five children, 63 (35.3%) had single and 50 (25.5%) had multiple anthropometric failures. Overall, 89 (36.1%) households were deficient for both energy and protein and 111 (47.6%) had deficiency of either of these two. Indicators on the utilization of different poverty alleviation schemes were associated with low/very low food security. A "Composite Index of Food Scarcity" comprising of HHFS, nutrient adequacy, and dietary diversity was proposed which was found to have dose-response relationship with grades of anthropometric failure of under-five children. CONCLUSIONS: An index comprising of three indicators might help identify the vulnerable households in relation to food security more effectively than a single indicator.

Decomposition of body mass growth into linear and ponderal growth in children with application to India.

In this paper, we decompose the difference between the weight of a child and the weight of a reference child into the difference between the height of the child and the height of the reference child and the difference between the weight per unit height of the child and the weight per unit height of the reference child. The decomposition provides the theoretical justification to the classification of the nutritional status proposed by Svedberg and by Nandy et al. An application of the decomposition framework to the Indian data shows that the level, depth and severity of the faltering of the growth of the body mass in Indian children are primarily due to the level, depth and severity of the faltering of the ponderal growth.

Risk factors of child malnutrition under 5 years: Evidence from Pakistan using the Composite Index of Anthropometric Failure.

OBJECTIVES: Child malnutrition is a very serious health issue globally, particularly in emerging countries. Among South Asian countries, Pakistan has been observed to have a high prevalence of child malnutrition. In spite of the implementation of many health strategies and preventive measures for vulnerable populations, this issue is still unresolved and needs further investigation. The purpose of this study was to investigate the role of various social-, maternal-, and child-level factors considered to be responsible for nutritional health disparities among children. METHODS: An assessment method of malnutrition, i.e., Composite Index of Anthropometric Failure (CIAF), was used to detect the prevalence of malnutrition among children under 5 years of age in Pakistan in order to present a comprehensive view that was lacking conventional indices of malnutrition. A binary logistic regression model was fitted to assess the link between malnutrition and socioeconomic, maternal, and child attributes based on CIAF data compiled from weight-for-height, weight-for-age, and height-for-age Z-scores using data from the Pakistan Demographic Health Survey (2017-2018). RESULTS: A total of 4224 children under 5 years of age were included in the analysis. Approximately half of the children (45.34%) comprised anthropometric failures for the overall prevalence of undernutrition based on CIAF. The results of this study revealed that the leading determinant associated with CIAF was the child's age in months, small birth size, lack of breastfeeding, lack of maternal education, poor economic status of the household, and poor-quality water sources. The factors associated with stunting comprised the child's age in months, small child birth size, underweight maternal body mass index, and uneducated mothers. Only one factor-low household economic profile-was significantly associated with waste. Sindh, Baluchistan, and Khyber Pakhtunkhwa provinces had a higher risk of having wasted children. On the other hand, children aged 25-36 months had higher, small child birth size, underweight maternal BMI, un-educated mother, un-educated father, low economic profile of household experiencing of being underweight. CONCLUSIONS: The findings of this study reinforce the significance of maternal health, parental education, and household economic profile in the prevention of malnutrition within young children of adequate birth size, as well as better overall health care up to adolescence in Pakistan. Well-nourished individuals are a valuable human resource and a requirement for a nation's progress and prosperity. In emerging nations such evidence-based policies are crucial for fostering children's optimal physical and mental development to ensure a healthier future generation. Therefore, the execution of national health policies aimed at the improvement of maternal and societal factors could result in improved nutrition levels among children below 5 years of age in Pakistan.

Anthropometric failure and associated factors among children aged 6-23 months in Ethiopia.

Undernutrition in childhood is a crucial public health issue in Ethiopia. Yet, more than an assessment of undernutrition using conventional index is needed to conclude the overall prevalence of undernutrition among children aged 6-23 months. Therefore, this study aimed to assess the prevalence of undernutrition using composite index of anthropometric failure and its associated factors among children aged 6-23 months in Southwest Ethiopia. A community-based cross-sectional study was employed among 440 mother-child pairs selected using a two-stage cluster sampling method in the rural Kersa district, Jimma Zone, Southwest Ethiopia. A pretested structured questionnaire was used to collect data. Multivariable logistic regression analysis was employed to identify factors associated with undernutrition. Variables with a p-value of <.05 were considered statistically significant. The proportion of undernutrition using composite indexes of anthropometric failure was 57.3% among children aged 6-23 months. Children being male [AOR = 1.55; 95% CI (1.013, 2.373)], not met minimum acceptable diet (MAD) [AOR = 2.104; 95% CI (1.05, 4.214)], larger family size [AOR = 1.699; 95% CI (1.0791, 2.675)], having comorbidity [AOR = 3.31; 95% CI (2.068, 5.327)], and being in food insecurity household [AOR = 3.12; 95% CI (2.0, 4.868)] were more likely to be in anthropometric failure, whereas children from the mother who attended higher and above schooling [AOR = 0.244; 95% CI (0.093, 0.641)] were less likely to be in anthropometric failure. More than half of children aged 6-23 months were experienced anthropometric failure. Male children, those who have not received the MAD, come from larger families, have comorbidities, live in food-insecure households, and have mothers with higher education levels were found to be at higher risk of anthropometric failure.

Decoding India's Child Malnutrition Puzzle: A Multivariable Analysis Using a Composite Index.

BACKGROUND: This study examines the levels and predictors of malnutrition in Indian children under 5 years of age. METHODS: Composite Index of Anthropometric Failure was applied to data from the India National Family Health Survey 2019-2021. A multivariable logistic regression model was used to assess the predictors. RESULTS: 52.59% of children experienced anthropometric failure. Child predictors of lower malnutrition risk included female gender (adjusted odds ratio (AOR) = 0.881) and average or large size at birth (AOR = 0.729 and 0.715, respectively, compared to small size). Higher birth order increased malnutrition odds (2nd-4th: AOR = 1.211; 5th or higher: AOR = 1.449) compared to firstborn. Maternal predictors of lower malnutrition risk included age 20-34 years (AOR = 0.806), age 35-49 years (AOR = 0.714) compared to 15-19 years, normal BMI (AOR = 0.752), overweight and obese BMI (AOR = 0.504) compared to underweight, and secondary or higher education vs. no education (AOR = 0.865). Maternal predictors of higher malnutrition risk included severe anemia vs. no anemia (AOR = 1.232). Protective socioeconomic factors included middle (AOR = 0.903) and rich wealth index (AOR = 0.717) compared to poor, and toilet access (AOR = 0.803). Children's malnutrition risk also declined with paternal education (primary: AOR = 0.901; secondary or higher: AOR = 0.822) vs. no education. Conversely, malnutrition risk increased with Hindu (AOR = 1.258) or Islam religion (AOR = 1.369) vs. other religions. CONCLUSIONS: Child malnutrition remains a critical issue in India, necessitating concerted efforts from both private and public sectors. A 'Health in All Policies' approach should guide public health leadership in influencing policies that impact children's nutritional status.

Comparison of Nutritional Status of Healthy Under-Five Indian Children Using Composite Index of Anthropometric Failure on WHO 2006 versus 2019 Indian Synthetic Growth Charts.

OBJECTIVES: To assess nutritional status of apparently-healthy under-five Indian children using Composite Index of Anthropometric Failure (CIAF) and to compare anthropometric failure prevalence using conventional indices and CIAF on World Health Organization (WHO) vs. synthetic Indian growth charts. METHODS: This observational study was conducted over 2 y. The inclusion criteria was apparently-healthy children (0-60 mo) and the exclusion criteria were acute/chronic illness and small for gestational age. RESULTS: A total of 1557 children (762 girls) were included in the study. The mean age of the subjects was 21 mo. The Z-scores for height, weight, body mass index (BMI) for age and weight for height in children were lower on WHO vs. synthetic charts (p = 0.0001). Significantly higher proportion of children were moderately and severely underweight, stunted and wasted on WHO charts. Synthetic charts identified significantly higher proportion as normal for weight, height, BMI for age, weight for height, overweight (overall), and a higher prevalence of severe stunting, and severe acute malnutrition (SAM) was noted among girls compared to boys. Using CIAF, 54.1% children were normal on WHO charts vs. 78.0% on synthetic (p = 0.0001). Larger proportion of girls (8.8%) were stunted+underweight (category-E) vs. boys (4.3%) on synthetic charts (p = 0.0003). Significantly higher proportion of children demonstrated failure (single/dual/multiple) on WHO charts except category-Y (higher proportion of underweight on synthetic charts). Maximum difference in CIAF (WHO vs. synthetic) was observed between 0-24 mo age. Of 1215 children normal on synthetic charts, 837 (68.9%) were normal on WHO charts. Of 116 underweight children (category-Y) on synthetic charts, 20 (17.2%) were underweight on WHO charts; remaining had compound failure (wasting+underweight = 49.1%, wasting+stunting+underweight = 14.7%, stunting+underweight = 12.1%) on WHO charts. Among those stunted+underweight (category-E) on synthetic charts, WHO charts classified 1/4th as wasted+stunted+underweight (category-D). CONCLUSIONS: Synthetic references are more representative of Indian growth patterns, and seem more appropriate for monitoring growth of Indian children to avoid mislabelling as malnourished.

Explaining the poor-rich gap in anthropometric failure among children in India: An econometric analysis of the NFHS, 2021 and 2016.

Wealth inequality in anthropometric failure is a persistent concern for policymakers in India. This necessitates a comprehensive analysis and identification of various risk factors that can explain the poor-rich gap in anthropometric failure among children in India. We analyze the fifth and fourth rounds of the Indian National Family Health Survey collected from June 2019 to April 2021 and January 2015 to December 2016, respectively. Two samples of children aged 0-59 and 6-23 months old with singleton birth, alive at the time of the survey with non-pregnant mothers, and with valid data on stunting, severe stunting, underweight, severely underweight, wasting, and severe wasting are included in the analytical samples from both rounds. We estimate the wealth gradients and distribution of wealth among children with anthropometric failure. Wealth gap in anthropometric failure is identified using logistic regression analysis. The contribution of risk factors in explaining the poor-rich gap in AF is estimated by the multivariate decomposition analysis. We observe a negative wealth gradient for each measure of anthropometric failure. Wealth distributions indicate that at least 60% of the population burden of anthropometric failure is among the poor and poorest wealth groups. Even among children with similar modifiable risk factors, children from poor and poorest backgrounds have a higher prevalence of anthropometric failure compared to children from the richest backgrounds. Maternal BMI, exposure to mass media, and access to sanitary facility are the most significant risk factors that explain the poor-rich gap in anthropometric failure. This evidence suggests that the burden of anthropometric failure and its risk factors are unevenly distributed in India. The policy interventions focusing on maternal and child health, implemented with a targeted approach prioritizing the vulnerable groups, can only partially bridge the poor-rich gap in anthropometric failure. The role of anti-poverty programs and growth is essential to narrow this gap in anthropometric failure.

Regional Distribution of the Anthropometric Failure among Under-five Children and Its Determinants in India.

Background: Undernutrition in children seems to be one of the major health issues in developing nations including India. Stunting, underweight, and wasting are the three most often used anthropometric indicators to evaluate childhood undernutrition. Children who exhibit one or more indicators of undernutrition are considered as anthropometric failure (AF). The present study aims to determine the distribution and determinants of anthropometric failure in children under the age of five in different regions of India. Methods: NFHS-5 data, collected between 2019 and 2021, were utilized for the study. Pearson's chi-square (χ2) test was used to look into the association between categorical variables. Binary logistic regression was used to find the explanatory factors that influence anthropometric failure. Results: More than half of the under-five children (52.18%) in India are suffering from anthropometric failure, out of these West (57.88%), East (56.58%), and Central (53.94%) regions have covered half of the total occurrence. State-wise, Bihar (61.66%), followed by Gujarat (60.26%), and Jharkhand (58.05%) have recorded the highest rates of anthropometric failure. Anthropometric failure is higher among anemic children, boys, parent not alives, the higher number of birth order, lower educated mothers, rural dwellers, belonging to scheduled tribes and scheduled castes communities, living in nuclear families, and having lower household wealth indexes than their other counterparts. Conclusion: These aspects imply that regional determinants should be taken into consideration when implementing child nutrition development programs.

Impact of integrated preventive and curative health package on nutritional status of children under 2 years of age in the health area of Tama, Tahoua region (Niger).

Background: Niger, relevant in light of current political coup, is one of the countries with the worst human development indicators, characterized by high fertility rates and extremely high infant mortality rates. Food insecurity in the region is alarming, leading to high malnutrition rates in children. This study aimed to evaluate an integral preventive-curative health program targeting children aged under 2 years in the health area of Tama, district of Bouza, Tahoua. Methodology: Anthropometric follow-up data of 6,962 children aged under 2 years were included in this study. These children received complete vaccination and malaria chemoprevention, and those older than 6 months received nutritional supplementation with a small quantity of lipid-based nutrient supplements. Fundamental growth indicators (height-for-age, weight-for-height, weight-for-age, and middle-upper arm circumference) and the Composite Index of Anthropometric Failure were calculated at the beginning and end of the program (mean time spent in the program: 14.5 ± 6.6 months) The evolution of these indicators was compared with those of a sample from a vertical vaccination program conducted in the neighboring region of Madarounfa on similar dates. Results: The proportion of children without anthropometric failure decreased from 59.5 to 40.2% (p < 0.001), with the categories that included stunting increasing the most. When analyzing the anthropometric indicators according to the months of compliance with the program, there was a slight improvement in the indicators of acute malnutrition, whereas those of chronic malnutrition worsened significantly. However, when compared with the Madarounfa sample, the children in the present study registered a significantly lower worsening in all three indicators: height-age (-0.46 vs. -2.44; p < 0.001), weight-height (+0.31 vs. -0.55; p < 0.001) and weight-age (-0.03 vs. -1.63; p < 0.001) difference. Conclusion: The comprehensive preventive-curative health program slightly slows the worsening of cumulative malnutrition in the early years of life in complex contexts, such as southern Niger.