Child Undernutrition in the States of India: An Analysis Based on Change in Composite Index of Anthropometric Failure from 2006 to 2016

2021 ◽  
pp. 097226612110103
Author(s):  
J. R. Jith ◽  
Rajshree Bedamatta
Keyword(s):  
Child Nutrition ◽  
Composite Index ◽  
Family Health ◽  
Wealth Index ◽  
Household Wealth ◽  
Population Projections ◽  
Indian Children ◽  
Indian States ◽  
Child Undernutrition ◽  
Low Weight

Stunting, wasting and underweight—the three traditional indicators of undernourishment among children—provide mutually non-exclusive categories of anthropometric failures: low height for age, low weight for height and low weight for age. Although these indicators are essential for designing specific clinical and child nutrition policy interventions, they fall short of estimating the prevalence of overall anthropometric failure, which provides a sense of the scale of the nutrition problem. This article estimates the alternative, more comprehensive measure Composite Index of Anthropometric Failure (CIAF) for Indian states, based on data from the National Family Health surveys of 2006 and 2016, for children under five years (Ch–U5). The CIAF-based undernutrition estimates show significantly high anthropometric failure levels among Indian children compared to only stunting, wasting and underweight. Based on population projections for Ch–U5, we also show that a sizeable number of states may have seen an increase in child undernutrition between 2006 and 2016. We also correlated CIAF with household wealth index scores and found a positive relationship with children facing no anthropometric failure.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick

2020 ◽  
Author(s):  
Ayushi Jain ◽  
Satish Balram Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background: India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern issue. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition in children below five years. While considerable efforts are being made to address this challenging issue, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, and hence not incentivising a balanced improvement. signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. Methodology: Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. Result: MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly discounting cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p<0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission. Conclusion: MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

scholarly journals Changes in Child Nutrition in India: A Decomposition Approach

2019 ◽  
Vol 16 (10) ◽  
pp. 1815 ◽  
Author(s):  
Peng Nie ◽  
Anu Rammohan ◽  
Wencke Gwozdz ◽  
Alfonso Sousa-Poza
Keyword(s):  
Child Nutrition ◽  
Survey Methods ◽  
Composite Index ◽  
Household Wealth ◽  
Maternal Body Mass Index ◽  
Indian Children ◽  
Decomposition Approach ◽  
Non Linear ◽  
Nutritional Status Of Children ◽  
Maternal Autonomy

Background: Improvements in child health are a key indicator of progress towards the third goal of the United Nations’ Sustainable Development Goals. Poor nutritional outcomes of Indian children are occurring in the context of high economic growth rates. The aim of this paper is to conduct a comprehensive analysis of the demographic and socio-economic factors contributing to changes in the nutritional status of children aged 0–5 years in India using data from the 2004–2005 and 2011–2012 Indian Human Development Survey. Methods: To identify how much the different socio-economic conditions of households contribute to the changes observed in stunting, underweight and the Composite Index of Anthropometric Failure (CIAF), we employ both linear and non-linear decompositions, as well as the unconditional quantile technique. Results: We find the incidence of stunting and underweight dropping by 7 and 6 percentage points, respectively. Much of this remarkable improvement is encountered in the Central and Western regions. A household’s economic situation, as well as maternal body mass index and education, account for much of the change in child nutrition. The same holds for CIAF in the non-linear decomposition. Although higher maternal autonomy is associated with a decrease in stunting and underweight, the contribution of maternal autonomy to improvements is relatively small. Conclusions: Household wealth consistently makes the largest contribution to improvements in undernutrition. Nevertheless, maternal autonomy and education also play a relatively important role.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick

2020 ◽  
Author(s):  
Ayushi Jain ◽  
Satish Balram Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern issue. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition in children below five years. While considerable efforts are being made to address this challenging issue, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, and hence not incentivising a balanced improvement. signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. Methodology Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. Result MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p<0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission in India. Conclusion MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick

2020 ◽  
Author(s):  
Ayushi Jain ◽  
Satish Balram Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background: India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition among children below five years. While considerable efforts are being made to address this challenge, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, and hence not incentivising a balanced improvement. signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. Methodology: Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. Result: MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p<0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission in India. Conclusion: MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH—a more sensitive yardstick

2020 ◽  
Author(s):  
Ayushi Jain ◽  
Satish Balram Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background: India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent issue. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition in children below five years. While considerable efforts are being made to address this challenging issue, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH.Methodology: Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Through the use of maps and spatial tools, we gauged the existence of neighbourhood dependency, the formation of clusters, within and across states.Result: MANUSH method succeeds over its counterparts – linear aggregation and geometric mean, by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising when, improvement in worst-off dimension is less or not proportionate to improvement in best-off dimension, or when, even with overall improvement, the gap between dimensions remain same. MANUSH scores helped in revealing the changing paradigm in the improvement of nutrition outcomes and the rising inequalities within and across states and districts in India. Significant clusters (p<0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. The usefulness of MANUSH index in context-specific planning and prioritising actions is also brought out using the case of the National Nutrition Mission.Conclusion: MANUSH indexing depicts balanced development effectively, hence finds relevance in bringing out inequality in a diverse and developing economy like India.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Ayushi Jain ◽  
Satish B. Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition among children below 5 years. While considerable efforts are being made to address this challenge, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, and hence not incentivising a balanced improvement. Signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. Methodology Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005–06), NFHS-4 (2015–16) and CNNS (2106–18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. Result MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p < 0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission in India. Conclusion MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

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

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Demeke Lakew Workie ◽  
Lijalem Melie Tesfaw
Keyword(s):  
Logistic Regression ◽  
Composite Index ◽  
Binary Logistic Regression ◽  
Wealth Index ◽  
Household Wealth ◽  
Education Level ◽  
Multiple Birth ◽  
Under Five ◽  
Under Five Children ◽  
Study Results

Abstract 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.

scholarly journals Application of Quantile Regression to Examine Changes in the Distribution of Stunting of Indian Children Aged 0-36 Months Using Four Rounds of NFHS Data.

2021 ◽  
Author(s):  
Thirupathi Mokalla ◽  
VISHNU VARDHANA MENDU
Keyword(s):  
Quantile Regression ◽  
Family Health ◽  
Wealth Index ◽  
Negative Association ◽  
Indian Children ◽  
Final Study ◽  
Determining Factors ◽  
Lms Method ◽  
Health Survey Data ◽  
Size At Birth

Abstract Background: In India, it has been observed that the prevalence of stunting among under-five children decreased, but the prevalence is still alarmingly high. In previous studies, traditional (linear and logistic) regression analyses were used, and these analyses were limited to encapsulated cross-distribution variations. Our study's objective was to examine how the different determinants are heterogenous in various percentiles. Methods: This article examined the change in the stunting distribution of children and examined the relationships between the key covariate's trends and patterns in stunting among children aged <3 years over a period of 24 years. Four successive rounds of the National Family Health Survey data 1992-93, 1998-99, 2005-06, and 2015-16 were used for analysis. The final study included 206579 children aged <3 years (N= 106136 male, 100443 female). To explain and analyze differences in the stunting distribution, the lambda-mu-sigma (LMS) method was used. Trends in stunting distribution over time were analysed using separate sex-stratified quantile regression (QR). The selected socioeconomic, demographic and other predictors considered for this analysis. Results: The quantile regressions have clearly indicated that mothers who have higher than primary level education were beneficial to decrease child malnutrition at the lower end of the distribution. The age, birth order, mother's body-mass-index (BMI) and wealth, among others, were some more determining factors for HAZ. Results of selected quantile regression estimated at 5th, 10th, 25th, 50th, 75th, 90th, and 95th quantiles. The wealth index was a highly negative association with lower quantiles compared to upper quantiles in stunting However, in the age classification, as the age increases, there was a negative association in the upper quantiles of stunting. Small size at birth was having a negative association in all the quantiles of stunting. Conclusions: The outcome of various covariates working differently across the stunting distribution was suggested by quantile regression. The major discrepancies in different aspects were underlined by socioeconomic and demographic aspects of India. The heterogeneity of this effect was shown using quantile regression.

scholarly journals Stunting among Preschool Children in India: Temporal Analysis of Age-Specific Wealth Inequalities

2020 ◽  
Vol 17 (13) ◽  
pp. 4702
Author(s):  
Sunil Rajpal ◽  
Rockli Kim ◽  
William Joe ◽  
S.V. Subramanian
Keyword(s):  
Child Nutrition ◽  
Age Groups ◽  
Policy Research ◽  
Family Health ◽  
Temporal Analysis ◽  
Preschool Age ◽  
Nutritional Intake ◽  
Child Stunting ◽  
Child Undernutrition ◽  
Wealth Inequalities

Adequate nutritional intake for mothers during pregnancy and for children in the first two years of life is known to be crucial for a child’s lifelong physical and neurodevelopment. In this regard, the global nutrition community has focused on strategies for improving nutritional intake during the first 1000 day period. This is largely justified by the observed steep decline in children’s height-for-age z scores from birth to 23 months and presumed growth faltering at later ages as a reflection of earlier deprivation that is accumulated and irreversible. Empirical evidence on the age-stratified burden of child undernutrition is needed to re-evaluate the appropriate age for nutrition interventions to target among children. Using data from two successive rounds of National Family Health Surveys conducted in 2006 and 2016, the objective of this paper was to analyze intertemporal changes in the age-stratified burden of child stunting across socioeconomic groups in India. We found that child stunting in India was significantly concentrated among children entering preschool age (24 or above months). Further, the temporal reduction in stunting was relatively higher among children aged 36–47 months compared to younger groups (below 12 and 12–23 months). Greater socioeconomic inequalities persisted in stunting among children from 24 months or above age-groups, and these inequalities have increased over time. Children of preschool age (24 or above months) from economically vulnerable households experienced larger reductions in the prevalence of stunting between 2006 and 2016, suggesting that policy research and strategies beyond the first 1000 days could be critical for accelerating the pace of improvement of child nutrition in India.

scholarly journals Association between Non-Typhoidal Salmonella Infection and Growth in Children under 5 Years of Age: Analyzing Data from the Global Enteric Multicenter Study

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 392
Author(s):  
Rina Das ◽  
Md. Ahshanul Haque ◽  
Mohammod Jobayer Chisti ◽  
Abu Sayed Golam Faruque ◽  
Tahmeed Ahmed
Keyword(s):  
Multicenter Study ◽  
Child Nutrition ◽  
Wealth Index ◽  
Asymptomatic Infection ◽  
Sub Saharan Africa ◽  
Outcome Variable ◽  
P Value ◽  
Severe Diarrhea ◽  
Number Of Children ◽  
Child Undernutrition

Non-typhoidal Salmonella (NTS) is one of the less focused on infections and is often associated with faulty child nutrition in the developing world. This study aimed to evaluate the association of NTS infection with growth faltering among children under the age of five. We analyzed data from 378 fecal NTS positive children with both moderate-to-severe diarrhea (MSD) and asymptomatic infection from the seven countries of South Asia and sub-Saharan Africa during enrolment and on day 60 follow up in the Global Enteric Multicenter Study (GEMS) for the period of December 2007 to March 2011. Children not associated with fecal NTS (n = 1134) were randomly selected from the same dataset (1:3 ratio) as a comparison group. The association between an explanatory variable and the outcome variable was longitudinally tested using generalized estimating equations (GEE), where the dependent variables were height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) z-score, and the independent variable was the presence of fecal NTS. The GEE multivariable model identified a negative association between fecal NTS and WAZ (coefficient: −0.19; 95% CI (confidence interval): −0.33, −0.04, and p value = 0.010), WHZ (coef: −0.19; 95% CI: −0.34, −0.05, and p value = 0.007), and HAZ (coef: −0.13; 95% CI: −0.27, −0.01, and p value = 0.073) after adjusting for age, gender, diarrhea, breastfeeding status, mothers’ education, number of children under the age of five, household size by the number of people regularly sleep at the home, handwashing practice, source of drinking water, wealth index, presence of co-pathogens, comorbidity, and study sites. In the GEMS, where children were followed during 50–90 days of enrolment, the presence of fecal NTS harmed the child’s anthropometric outcomes. Minimizing potential exposure to NTS is needed to curb worsening child undernutrition.

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