Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000-2017

Spatial variation and risk factors of the dual burden of childhood stunting and underweight in India: a copula geoadditive modelling approach

India has one of the highest burdens of childhood undernutrition in the world. The two principal dimensions of childhood undernutrition, namely stunting and underweight can be significantly associated in a particular population, a fact that is rarely explored in the extant literature. In this study, we apply a copula geoadditive modelling framework on nationally representative data of 104,021 children obtained from the National Family Health Survey 5 to assess the spatial distribution and critical drivers of the dual burden of childhood stunting and underweight in India while accounting for this correlation. Prevalence of stunting, underweight and their co-occurrence among under 5 children were 35.37%, 28.63% and 19.45% respectively with significant positive association between the two (Pearsonian Chi square = 19346, P-value = 0). Some of the factors which were significantly associated with stunting and underweight were child gender (Adjusted Odds Ratio (AOR) = 1.13 (1.12) for stunting (underweight)), birthweight (AOR = 1.46 (1.64) for stunting (underweight)), type of delivery (AOR = 1.12 (1.19) for stunting (underweight)), prenatal checkup (AOR = 0.94 (0.96) for stunting (underweight)) and maternal short-stature (AOR = 2.19 (1.85) for stunting (underweight)). There was significant spatial heterogeneity in the dual burden of stunting and underweight with highest prevalence being observed in eastern and western states while northern and southern states having relatively lower prevalence. Overall, the results are indicative of the inadequacy of a "one-size-fits-all" strategy and underscore the necessity of an interventional framework that addresses the nutritional deficiency of the most susceptible regions and population subgroups of the country.

Prevalence and factors contributing to stunted growth in young children of Khordha district, Odisha: A cross-sectional study

Background

Stunting, indicating chronic malnutrition in children, remains a pressing concern globally, especially in low- and middle-income countries. India, despite substantial efforts, continues to grapple with high rates of stunting, impacting child development and health outcomes. Understanding the multifaceted factors contributing to stunting is crucial for targeted interventions and policy formulation.

Methods

This descriptive cross-sectional study was conducted in Balipatana, Khordha district, Odisha, India among 400 children. A survey employing structured questionnaires and WHO Anthropometric guidelines for data collection was used. Statistical analyses including Chi-square tests and logistic regression models were used to uncover significant associations.

Results

The study revealed a stunting prevalence of 28% among children under five, with 7% severe and 21% moderate stunting. Regression analysis revealed key risk factors included low birth weight (1.5-2.5 kg), parental illiteracy, lower household income (Rs. 1000-15000), inadequate toilet facilities, and specific drinking water sources.

Conclusion

The findings align with global concerns about stunting, emphasizing the complex interplay of socioeconomic and environmental factors. Interventions targeting parental education, household economic status, and improving sanitation and drinking water facilities are imperative. By addressing these factors, focused efforts can be made to reduce childhood stunting, ensuring a healthier future for the nation's children.

Undernutrition among children and its determinants across the parliamentary constituencies of India: a geospatial analysis

In India, undernutrition among children has been extremely critical for the last few decades. Most analyses of undernutrition among Indian children have used the administrative boundaries of a state or a district level as a unit of analysis. This paper departs from such a practice and focuses instead on the political boundaries of a parliamentary constituency (PC) as the unit of analysis. The PC is a critical geopolitical unit where political parties and party candidates make election promises and implement programmes to improve the socio-economic condition of their electorate. A focus on child undernutrition at this level has the potential for greater policy and political traction and could lead to a paradigm shift in the strategy to tackle the problem by creating a demand for political accountability. Different dimensions and new approaches are also required to evaluate the socio-economic status and generate concrete evidence to find solutions to the problem. Given the significance of advanced analytical methods and models embedded into geographic information system (GIS), the current study, for the first time, uses GIS tools and techniques at the PC level, conducting in-depth analysis of undernutrition and its predictors. Hence, this paper examines the spatial heterogeneity in undernutrition across PCs by using geospatial techniques such as univariate and bivariate local indicator of spatial association and spatial regression models. The analysis highlights the high-low burden areas in terms of local hotspots and identifies the potential spatial risk factors of undernutrition across the constituencies. Striking variations in the prevalence of undernutrition across the constituencies were observed. Most of these constituencies that performed poorly both in terms of child nutrition and socio-economic indicators were located in the northern, western, and eastern parts of India. A statistically significant association of biological, socio-economic, and environmental factors such as women's body mass index, anaemia in children, poverty, household sanitation facilities, and institutional births was established. The results highlight the need to bring in a mechanism of political accountability that directly connects elected representatives to maternal and child health outcomes. The spatial variability and pattern of undernutrition indicators and their correlates indicate that priority setting in research may also be greatly influenced by the neighbourhood association.

Stunting in infancy is associated with atypical activation of working memory and attention networks

Stunting is associated with poor long-term cognitive, academic and economic outcomes, yet the mechanisms through which stunting impacts cognition in early development remain unknown. In a first-ever neuroimaging study conducted on infants from rural India, we demonstrate that stunting impacts a critical, early-developing cognitive system-visual working memory. Stunted infants showed poor visual working memory performance and were easily distractible. Poor performance was associated with reduced engagement of the left anterior intraparietal sulcus, a region involved in visual working memory maintenance and greater suppression in the right temporoparietal junction, a region involved in attentional shifting. When assessed one year later, stunted infants had lower problem-solving scores, while infants of normal height with greater left anterior intraparietal sulcus activation showed higher problem-solving scores. Finally, short-for-age infants with poor physical growth indices but good visual working memory performance showed more positive outcomes suggesting that intervention efforts should focus on improving working memory and reducing distractibility in infancy.

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.

Assessment of height growth in Indian children using growth centiles and growth curves

BACKGROUND

Growth centiles and growth curves are two ways to present child anthropometry; however, they differ in the type of data used, the method of analysis, the biological parameters fitted and the form of interpretation.

AIM

To fit and compare height growth centiles and curves in Indian children.

SUBJECTS AND METHODS

1468 children (796 boys) from Pune India aged 6-18 years with longitudinal data on age and height (n = 7781) were analysed using GAMLSS (Generalised Additive Models for Location Scale and Shape) for growth centiles, and SITAR (SuperImposition by Rotation and Translation) for growth curves.

RESULTS

SITAR explained 98.7% and 98.8% of the height variance in boys and girls, with mean age at peak height velocity 13.1 and 11.0 years, and mean peak velocity 9.0 and 8.0 cm/year, respectively. GAMLSS (Box-Cox Cole Green model) also captured the pubertal growth spurt but the centiles were shallower than the SITAR mean curve. Boys showed a mid-growth spurt at age 8 years.

CONCLUSION

GAMLSS displays the distribution of height in the population by age and sex, while SITAR effectively and parsimoniously summarises the pattern of height growth in individual children. The two approaches provide distinct, useful information about child growth.

Childhood deprivations predict late-life cognitive impairment among older adults in India

Large population-based studies on the associations of childhood factors with late-life cognition are lacking in many low and middle income countries including India. In this study, we assessed the prevalence of late-life cognitive impairment and examined the associations of childhood socioeconomic status (SES) and health conditions with cognitive impairment among older adults in India. Data for this study were derived from the Longitudinal Ageing Study in India conducted in 2017-18. The effective sample size was 31,464 older adults aged 60 years and above. Cognitive functioning was measured through five global domains (memory, orientation, arithmetic function, executive function, and object naming). The overall score ranged between 0 and 43, and the score was reversed indicating cognitive impairment. Descriptive statistics along with mean scores of cognitive impairment were presented. Additionally, moderated multivariable linear regression models were employed to examine the association between explanatory variables, including childhood SES and health conditions and late-life cognitive impairment. The mean score of cognitive functioning among the study participants was 21.72 (CI 2.64-21.80). About 15% of older adults had poor health conditions, and 44% had lower financial status during their childhood. Older adults who had a fair health during their childhood were more likely to suffer from cognitive impairment in comparison to older adults who had good health during their childhood (Coef: 0.60; CI 0.39, 0.81). In comparison to older adults who had good childhood financial status, those who had poor childhood financial status were more likely to suffer from cognitive impairment (Coef: 0.81; CI 0.56, 1.07). Older adults who had fair childhood health status and poor childhood financial status were more likely to suffer from cognitive impairment in comparison to older adults who had good childhood health and good financial status (Coef: 1.26; CI 0.86, 1.66). Social policies such as improving educational and financial resources in disadvantaged communities and socioeconomically poor children and their families, would help to enhance a better cognitive ageing and a healthy and dignified life in old age.

Modeling the potential impacts of improved monthly income on child stunting in India: a subnational geospatial perspective

OBJECTIVES

Approximately one-third of the world's stunted (low height-for-age) preschool-aged children live in India. The success of interventions designed to tackle stunting appears to vary by location and depth of poverty. We developed small-area estimation models to assess the potential impact of increments in household income on stunting across the country.

DESIGN

Two nationally representative cross-sectional datasets were used: India's National Family Health Survey 4 (2015-2016) and the 68th round of the National Sample Survey on consumer expenditure. The two datasets were combined with statistical matching. Gaussian process regressions were used to perform geospatial modelling of 'stunting' controlling for household wealth and other covariates.

SETTING AND PARTICIPANTS

The number of children in this sample totalled 259 627. Children with implausible height-for-age z-scores (HAZs) >5 or <-5, or missing data on drinking water, sanitation facility, mother's education, or geolocation and children not residing in mainland India were excluded, resulting in 207 695 observations for analysis.

RESULTS

A monthly transfer of ~$7 (500 Indian rupees) per capita to every household (not targeted or conditional) was estimated to reduce stunting nationally by 3.8 percentage points on average (95% credible interval: 0.14%-10%), but with substantial variation by state. Estimated reduction in stunting varied by wealth of households, with the poorest quintile being likely to benefit the most.

CONCLUSION

Improving household income, which can be supported through cash transfers, has the potential to significantly reduce stunting in parts of India where the burdens of both stunting and poverty are high. Modelling shows that for other regions, income transfers may raise incomes and contribute to improved nutrition, but there would be a need for complementary activities for alleviating stunting. While having value for the country as a whole, impact of income gained could be variable, and underlying drivers of stunting need to be tackled through supplementary interventions.

Determinants of severe acute malnutrition among children aged 6-36 months in Kalafo district (riverine context) of Ethiopia

Malnutrition remains prevalent and existing health problem globally. Particularly Undernutrition is a major public health issue in developing countries. Globally the causes of severe acute undernutrition varies across context. The aim of this study was to identify the determinants of severe acute malnutrition to uncover contextual factors based on UNICEF conceptual framework, as there was no study done in a similar context in Ethiopia. Health facility based (health post) un-matched case control study with Key informant interview was conducted to identify determinant factors of severe acute malnutrition (SAM) among children between 6 and 36 months. 246 children (82 cases and 164) with their mothers or care takers participated the study which was conducted between December 20, 2019 to January 20, 2020 in Kalafo district in Shebele River. Odds ratio with 95% confidence interval was calculated to identify the determinants of SAM among children aged 6-36 months using multivariate logistic regression. The odds of severe acute malnutrition was 2.28 (1.22, 4.26); 4.68 (2.29, 9.58); 2.85 (1.26, 6.45); 2.39 (1.16, 4.96) and 3.262 (1.46, 7.31) and 3.237 (1.45, 7.23); respectively for mothers with three or more under five children, Children with inadequate dietary diversity, experienced diarrhea in past 2 weeks, their mothers had not nutrition counselling during pregnancy and younger (6-11 and 12-17 months) children as compared to controls. The finding of this study reveals the main determinants of severe acute malnutrition in riverine context are multi-level. In addition to this, poor childcare and polygamy identified in qualitative finding. Decisive and multi-sectoral approach is required to addressing SAM in the riverine area.

Eco-geographic patterns of child malnutrition in India and its association with cereal cultivation: An analysis using demographic health survey and agriculture datasets

Background: High prevalence of maternal malnutrition, low birth-weight and child malnutrition in India contribute substantially to the global malnutrition burden. Rural India has disproportionately higher levels of child malnutrition. Stunting and wasting are the primary determinants of child malnutrition and their district-level distribution shows clustering in different geographies and regions. Cereals, particularly millets, constitute the bulk of protein intake among the poor, especially in rural areas in India where high prevalence of wasting persists. Methods: The previous round of National Family Health Survey (NFHS4) has disaggregated data by district, enabling a more fine-scale characterisation of the prevalence of markers of malnutrition. We used data from NFHS4 and agricultural statistics datasets to analyse relationship of prevalence of malnutrition at the district level and area under cereal cultivation. We analysed malnutrition through data on under-5 stunting and wasting by district.  Results: Stunting and wasting patterns across districts show a distinct geographical and age distribution; districts with higher wasting showed relatively higher prevalence at six months of age. Wasting prevalence at district level was associated with higher cultivation of millets, with a stronger association seen for jowar and other millets (Kodo millet, little millet, proso millet, barnyard millet and foxtail millet). District level stunting was associated with higher district level cultivation of wheat. In multivariable analysis, wasting was positively associated with women's body mass index and stunting with women's short stature. Conclusions: Well-designed intervention studies will be required to confirm causal pathways contributing to ecogeographic patterns of child malnutrition. The cultivation of other millets has a strong association with prevalence of wasting. State-of-the-art studies that improve our understanding of bio-availability of amino acids and other nutrients from the prevalent dietary matrices of rural poor communities will be needed to confirm causal pathways contributing to potential eco-geographic patterns.

Mapping the prevalence of severe acute malnutrition in Papua, Indonesia by using geostatistical models

Background

Severe acute malnutrition (SAM) is the most life-threatening form of malnutrition, and in 2019, approximately 14.3 million children under the age of 5 were considered to have SAM. The prevalence of child malnutrition is recorded through large-scale household surveys run at multi-year intervals. However, these surveys are expensive, yield estimates with high levels of aggregation, are run over large time intervals, and may show gaps in area coverage. Geospatial modelling approaches could address some of these challenges by combining geo-located survey data with geospatial data to produce mapped estimates that predict malnutrition risk in both surveyed and non-surveyed areas.

Methods

A secondary analysis of cluster-level program evaluation data (n = 123 primary sampling units) was performed to map severe acute malnutrition (SAM) in Papuan children under 2 years (0–23 months) of age with a spatial resolution of 1 × 1 km in Papua, Indonesia. The approach used Bayesian geostatistical modelling techniques and publicly available geospatial data layers.

Results

In Papua, Indonesia, SAM was predicted in geostatistical models by using six geospatial covariates related primarily to conditions of remoteness and inaccessibility. The predicted 1-km spatial resolution maps of SAM showed substantial spatial variation across the province. By combining the predicted rates of SAM with estimates of the population under 2 years of age, the prevalence of SAM in late 2018 was estimated to be around 15,000 children (95% CI 10,209–26,252). Further tests of the predicted levels suggested that in most areas of Papua, more than 5% of Papuan children under 2 years of age had SAM, while three districts likely had more than 15% of children with SAM.

Conclusions

Eradication of hunger and malnutrition remains a key development goal, and more spatially detailed data can guide efficient intervention strategies. The application of additional household survey datasets in geostatistical models is one way to improve the monitoring and timely estimation of populations at risk of malnutrition. Importantly, geospatial mapping can yield insights for both surveyed and non-surveyed areas and can be applied in low-income country contexts where data is scarce and data collection is expensive or regions are inaccessible.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40795-022-00504-z.

Understanding the Change in the Prevalence and Factors Influencing the Childhood Stunting Using District-Level Data from NFHS-4 and NFHS-5 in India

To compare the district level prevalence of childhood stunting between NFHS-4 and NFHS-5 and to explore the correlates of it at the district level. Although malnutrition rates in India have decreased over a period, country is still a home for the highest number of stunted and wasted children in the world. Among the South Asian countries, India has the second highest number of stunted children. An ecological study conducted by using the data from fourth and fifth round of National Family Health Survey. Study concentrated on percentage of children who were stunted across 692 Indian districts during 2 survey periods and its correlates from NFHS-5. District level change in childhood stunting was calculated by differencing the NFHS-5 estimates from NFHS-4. Descriptive statistics were used to understand the nature of the variables and Moran’s I statistic was calculated to check for the spatial autocorrelation in the childhood stunting. Spatial error regression model was used to identify the correlates of childhood stunting. Among the Indian districts considered, 243 districts showed the increase in childhood stunting between the time periods considered. Currently, about 33.56% of children in India are stunted and there is high spatial disparity in the prevalence of childhood stunting among the districts of it. Major hotspots of childhood stunting were found in the parts of UP, Bihar, Jharkhand, and West Bengal. Households access to improved sanitation facility, iodized salt, clean fuel, women 10 plus years of schooling, post-natal care of mother were found to be the significant protective factors. Closed spacing of births, teenage pregnancy, low BMI of women, childhood diarrhea, and anemia were found to be the significant risk factors of childhood stunting. Stunting depends on several other factors apart from poverty, working on these factors will help in reducing childhood stunting in India.

Can fruit and vegetable aggregation systems better balance improved producer livelihoods with more equitable distribution?

The need for food systems to generate sustainable and equitable benefits for all is a global imperative. However, whilst ample evidence exists linking smallholder farmer coordination and aggregation (i.e. the collective transport and marketing of produce on behalf of multiple farmers) to improved market participation and farmer incomes, the extent to which interventions that aim to improve farmer market engagement may co-develop equitable consumer benefits remains uncertain. This challenge is pertinent to the horticultural systems of South Asia, where the increasing purchasing power of urban consumers, lengthening urban catchments, underdeveloped rural infrastructures and inadequate local demands combine to undermine the delivery of fresh fruits and vegetables to smaller, often rural or semi-rural markets serving nutritionally insecure populations. To this end, we investigate the potential for aggregation to be developed to increase fruit and vegetable delivery to these neglected smaller markets, whilst simultaneously improving farmer returns. Using an innovative system dynamics modelling approach based on an aggregation scheme in Bihar, India, we identify potential trade-offs between outcomes relating to farmers and consumers in smaller local markets. We find that changes to aggregation alone (i.e. scaling-up participation; subsidising small market transportation; mandating quotas for smaller markets) are unable to achieve significant improvements in smaller market delivery without risking reduced farmer participation in aggregation. Contrastingly, combining aggregation with the introduction of market-based cold storage and measures that boost demand improves fruit and vegetable availability significantly in smaller markets, whilst avoiding farmer-facing trade-offs. Critically, our study emphasises the benefits that may be attained from combining multiple nutrition-sensitive market interventions, and stresses the need for policies that narrow the fruit and vegetable cold storage deficits that exist away from more lucrative markets in developing countries. The future pathways and policy options discovered work towards making win-win futures for farmers and disadvantaged consumers a reality.

Mapping Geographical Differences and Examining the Determinants of Childhood Stunting in Ethiopia: A Bayesian Geostatistical Analysis

Understanding the specific geographical distribution of stunting is essential for planning and implementing targeted public health interventions in high-burdened countries. This study investigated geographical variations in the prevalence of stunting sub-nationally, and the determinants of stunting among children under 5 years of age in Ethiopia. We used the 2016 Ethiopia Demographic and Health Survey (EDHS) dataset for children aged 0–59 months with valid anthropometric measurements and geographic coordinates (n = 9089). We modelled the prevalence of stunting and its determinants using Bayesian geospatially explicit regression models. The prevalence of stunting among children under five years was 36.3% (95% credible interval (CrI); 22.6%, 51.4%) in Ethiopia, with wide variations sub-nationally and by age group. The prevalence of childhood stunting ranged from 56.6% (37.4–74.6%) in the Mekelle Special zone of the Tigray region to 25.5% (10.5–48.9%) in the Sheka zone of the Southern Nations, Nationalities and Peoples region. Factors associated with a reduced likelihood of stunting in Ethiopia included non-receipt of breastmilk, mother’s BMI (overweight/obese), employment status (employed), and higher household wealth, while the enablers were residence in the “arid” geographic areas, small birth size of the child, and mother’s BMI (underweight). The prevalence and determinants of stunting varied across Ethiopia. Efforts to reduce the burden of childhood stunting should consider geographical heterogeneity and modifiable risk factors.

Mapping changes in district level prevalence of childhood stunting in India 1998-2016: An application of small area estimation techniques

The four rounds of National Family Health Survey (NFHS) conducted during 1992-93, 1998-99, 2005-06 and 2015-16 is main source to track the health and development related indicators including nutritional status of children at national and state level in India. Except NFHS-4, first three rounds of NFHS were unable to provides district-level estimates of childhood stunting due to the insufficient sample sizes. The small area estimation (SAE) techniques offer a viable solution to overcome the problem of small sample size. Therefore, this study uses SAE techniques to derive district level prevalence of childhood stunting corresponding to NFHS-2 (1998-99). Study further estimated GIS maps, univariate Local indicator of spatial autocorrelation (LISA) and Moran's I to understand the trend in district level childhood stunting between NFHS-2 and NFHS-4. Estimates obtained by SAE techniques suggest that prevalence of childhood stunting ranges from 20.7% (95% CI: 18.8-22.7) in South Goa district of Goa to 64.4% (95%CI: 63.1-65.7) in Dhaulpur district of Rajasthan during 1998-99. The diagnostic measures used to validate the reliability of estimates obtained by SAE techniques indicate that the model-based estimates are reliable and representative at district level. Results of geospatial analysis indicates substantial reduction in childhood stunting between 1998 and 2016. Out of 640 district,about 81 district experience reduction of more than 50%. At the same time 60 district experience less than 10% of reduction between 1998 and 2016. Spatial clustering of childhood stunting remains same over the study period except few additional cluster in Maharashtra, Andhra and Meghalaya in 2016. The district level estimates obtained from this study might be helpful in framing decentralized policies and implementation of vertical programs to enhance the efficacy of various nutrition interventions in priority districts of the country.

Determinants of minimum acceptable diet feeding among children aged 6-23 months in Odisha, India

OBJECTIVE

To assess the level, pattern and determinants of minimum acceptable diet (MAD) feeding in Odisha, India.

DESIGN

Utilising cross-sectional data, the MAD was estimated through a dietary assessment method wherein the child's mother was asked to recall all the food intake of the youngest child the previous day and night of the surveyed date.

SETTING

National Family Health Survey 2015-2016.

PARTICIPANTS

Children aged 6-23 months, living with mother and for whom complete information on MAD was available (n 3073).

RESULTS

Only 8·4 % of the children aged 6-23 months were fed MAD, and the MAD feeding varies considerably by socio-demographic characteristics. Children aged 12-17 months had two times (OR: 2·51, 95 % CI (1·48, 4·26)) and those aged 18-23 months had three times (OR: 3·77, 95 % CI (2·25, 6·30)) higher odds of having a MAD than their counterparts aged 6-8 months. Children whose mother was exposed to any mass media had a higher chance of MAD feeding (OR: 1·46, 95 % CI (1·01, 2·11)).

CONCLUSIONS

The children of higher age, second or higher-order births, with mother exposed to mass media are significantly more likely to be fed with a MAD. At the same time, children from scheduled caste (SC) households have a lower probability of MAD feeding. The lower MAD feeding among the SC households suggests strengthening the ongoing programmes with a higher emphasis on the inclusion of this disadvantaged and marginalised group. Findings from the current study would assist policymakers, and public health managers improve MAD feeding practices in Odisha, India, in a targeted manner.

Multilevel analysis of geographic variation among correlates of child undernutrition in India

Prior research has identified a number of risk factors ranging from inadequate household sanitation to maternal characteristics as important determinants of child malnutrition and health in India. What is less known is the extent to which these individual‐level risk factors are geographically distributed. Assessing the geographic distribution, especially at multiple levels, matters as it can inform where, and at what level, interventions should be targeted. The three levels of significance in the Indian context are villages, districts, and states. Thus, the purpose of this paper was to (a) examine what proportion of the variation in 21 risk factors is attributable to villages, districts, and states in India and (b) elucidate the specific states where these risk factors are clustered within India. Using the fourth National Family Health Survey dataset, from 2015 to 2016, we found that the proportion of variation attributable to villages ranged from 14% to 63%, 10% to 29% for districts and 17% to 62% for states. Furthermore, we found that Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh were in the highest risk quintile for more than 10 of the risk factors included in our study. This is an indication of geographic clustering of risk factors. The risk factors that are clustered in states such as Bihar, Jharkhand, Madhya Pradesh and Uttar Pradesh underscore the need for policies and interventions that address a broader set of child malnutrition determinants beyond those that are nutrition specific.

Frequency of anemia and micronutrient deficiency among children with cleft lip and palate: a single-center cross-sectional study from Uttarakhand, India

Background

Children with cleft lip and/or palate can be undernourished due to feeding difficulties after birth. A vicious cycle ensues where malnutrition and low body weight precludes the child from having the corrective surgery, in the absence of which the child fails to gain weight. This study aimed to identify the proportion of malnutrition, including the deficiency of major micronutrients, namely iron, folate and vitamin B₁₂, in children with cleft lip and/or palate and thus help in finding out what nutritional interventions can improve the scenario for these children.

Methods

All children less than 5 years with cleft lip and/or cleft palate attending our institute were included. On their first visit, following were recorded: demographic data, assessment of malnutrition, investigations: complete blood count and peripheral blood film examination; serum albumin, ferritin, iron, folate, and vitamin B₁₂ levels.

Results

Eighty-one children with cleft lip and/or palate were included. Mean age was 25.37± 21.49 months (range, 3–60 months). In 53% of children suffered from moderate to severe wasting, according to World Health Organization (WHO) classification. Iron deficiency state was found in 91.6% of children. In 35.80% of children had vitamin B₁₂ deficiency and 23.45% had folate deficiency. No correlation was found between iron deficiency and the type of deformity.

Conclusion

Iron deficiency state is almost universally present in children with cleft lip and palate. Thus, iron and folic acid supplementation should be given at first contact to improve iron reserve and hematological parameters for optimum and safe surgery.

Changes in socio-economic inequality in nutritional status among children in EAG states, India

OBJECTIVE

The primary purpose of this study is to examine changes in socio-economic inequality in nutritional status (stunting and underweight) among children in Empowered Action Group (EAG) states.

DESIGN

The study is based on the most recent two wave's cross-sectional data from the National Family Health Survey (NFHS) conducted in 2005-2006 (NFHS-3) and 2015-2016 (NFHS-4). The study used height-for-age (stunting) and weight-for-age (underweight) of children as anthropometric indicators.

SETTING

EAG states including Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Odisha, Rajasthan, Uttarakhand and Uttar Pradesh in India.

PARTICIPANTS

The study includes a total of 11 858 (NFHS-3) and 92 630 (NFHS-4) children under 5 years of age.

RESULT

The socio-economic inequality in stunting remained unchanged in all EAG states. At the same time, the inequality in underweight decreased during 2005-2016. On decomposing, the factors contributing to socio-economic inequality revealed that household wealth index, mother's education and mother's nutritional status were the largest contributors to stunting (47 %, 24 % and 8 %) and underweight (51 %, 21 % and 16 %), respectively, in 2015-2016.

CONCLUSION

The study concluded the socio-economic inequality in underweight among children under 5 years of age increased over the years in EAG states in India. Altogether, household wealth index, mother's education and mother's nutritional status contributed to nearly 80 % to inequality in stunting and 90 % to inequality in underweight in 2015-2016. Hence, efforts should be made to minimise the socio-economic inequality in the nutritional status of children, particularly in EAG states in India.

Geospatial estimation of reproductive, maternal, newborn and child health indicators: a systematic review of methodological aspects of studies based on household surveys

BACKGROUND

Geospatial approaches are increasingly used to produce fine spatial scale estimates of reproductive, maternal, newborn and child health (RMNCH) indicators in low- and middle-income countries (LMICs). This study aims to describe important methodological aspects and specificities of geospatial approaches applied to RMNCH coverage and impact outcomes and enable non-specialist readers to critically evaluate and interpret these studies.

METHODS

Two independent searches were carried out using Medline, Web of Science, Scopus, SCIELO and LILACS electronic databases. Studies based on survey data using geospatial approaches on RMNCH in LMICs were considered eligible. Studies whose outcomes were not measures of occurrence were excluded.

RESULTS

We identified 82 studies focused on over 30 different RMNCH outcomes. Bayesian hierarchical models were the predominant modeling approach found in 62 studies. 5 × 5 km estimates were the most common resolution and the main source of information was Demographic and Health Surveys. Model validation was under reported, with the out-of-sample method being reported in only 56% of the studies and 13% of the studies did not present a single validation metric. Uncertainty assessment and reporting lacked standardization, and more than a quarter of the studies failed to report any uncertainty measure.

CONCLUSIONS

The field of geospatial estimation focused on RMNCH outcomes is clearly expanding. However, despite the adoption of a standardized conceptual modeling framework for generating finer spatial scale estimates, methodological aspects such as model validation and uncertainty demand further attention as they are both essential in assisting the reader to evaluate the estimates that are being presented.

Subnational mapping of under-5 and neonatal mortality trends in India: the Global Burden of Disease Study 2000-17

BACKGROUND

India has made substantial progress in improving child survival over the past few decades, but a comprehensive understanding of child mortality trends at disaggregated geographical levels is not available. We present a detailed analysis of subnational trends of child mortality to inform efforts aimed at meeting the India National Health Policy (NHP) and Sustainable Development Goal (SDG) targets for child mortality.

METHODS

We assessed the under-5 mortality rate (U5MR) and neonatal mortality rate (NMR) from 2000 to 2017 in 5 × 5 km grids across India, and for the districts and states of India, using all accessible data from various sources including surveys with subnational geographical information. The 31 states and groups of union territories were categorised into three groups using their Socio-demographic Index (SDI) level, calculated as part of the Global Burden of Diseases, Injuries, and Risk Factors Study on the basis of per-capita income, mean education, and total fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using the coefficient of variation. We projected U5MR and NMR for the states and districts up to 2025 and 2030 on the basis of the trends from 2000 to 2017 and compared these projections with the NHP 2025 and SDG 2030 targets for U5MR (23 deaths and 25 deaths per 1000 livebirths, respectively) and NMR (16 deaths and 12 deaths per 1000 livebirths, respectively). We assessed the causes of child death and the contribution of risk factors to child deaths at the state level.

FINDINGS

U5MR in India decreased from 83·1 (95% uncertainty interval [UI] 76·7-90·1) in 2000 to 42·4 (36·5-50·0) per 1000 livebirths in 2017, and NMR from 38·0 (34·2-41·6) to 23·5 (20·1-27·8) per 1000 livebirths. U5MR varied 5·7 times between the states of India and 10·5 times between the 723 districts of India in 2017, whereas NMR varied 4·5 times and 8·0 times, respectively. In the low SDI states, 275 (88%) districts had a U5MR of 40 or more per 1000 livebirths and 291 (93%) districts had an NMR of 20 or more per 1000 livebirths in 2017. The annual rate of change from 2010 to 2017 varied among the districts from a 9·02% (95% UI 6·30-11·63) reduction to no significant change for U5MR and from an 8·05% (95% UI 5·34-10·74) reduction to no significant change for NMR. Inequality between districts within the states increased from 2000 to 2017 in 23 of the 31 states for U5MR and in 24 states for NMR, with the largest increases in Odisha and Assam among the low SDI states. If the trends observed up to 2017 were to continue, India would meet the SDG 2030 U5MR target but not the SDG 2030 NMR target or either of the NHP 2025 targets. To reach the SDG 2030 targets individually, 246 (34%) districts for U5MR and 430 (59%) districts for NMR would need a higher rate of improvement than they had up to 2017. For all major causes of under-5 death in India, the death rate decreased between 2000 and 2017, with the highest decline for infectious diseases, intermediate decline for neonatal disorders, and the smallest decline for congenital birth defects, although the magnitude of decline varied widely between the states. Child and maternal malnutrition was the predominant risk factor, to which 68·2% (65·8-70·7) of under-5 deaths and 83·0% (80·6-85·0) of neonatal deaths in India could be attributed in 2017; 10·8% (9·1-12·4) of under-5 deaths could be attributed to unsafe water and sanitation and 8·8% (7·0-10·3) to air pollution.

INTERPRETATION

India has made gains in child survival, but there are substantial variations between the states in the magnitude and rate of decline in mortality, and even higher variations between the districts of India. Inequality between districts within states has increased for the majority of the states. The district-level trends presented here can provide crucial guidance for targeted efforts needed in India to reduce child mortality to meet the Indian and global child survival targets. District-level mortality trends along with state-level trends in causes of under-5 and neonatal death and the risk factors in this Article provide a comprehensive reference for further planning of child mortality reduction in India.

FUNDING

Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.