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Levels of child undernutrition and its correlates exhibit considerable spatial variation at different levels of granularity. In India, such variations and their interrelation have not been studied at the sub-district level primarily due to the non-availability of good quality granular data. Given the sheer regional diversity in India, it is essential to develop a region-specific evidence base at the micro-level. The current study utilised, for the first time, a sub-district level survey data (Concurrent Child Monitoring Survey-II, 2014-15) to investigate the statistically significant clusters and spatial patterns of burden of undernutrition among children. The emergence of distinct patterns at the level of natural geographical regions of the state-coastal, southern and northern regions, lead to a region-specific analysis to measure the impact of various demographic, socio-economic and maternal factors on the prevalence of undernutrition specific to the three regions, using the National Family Health Survey-IV unit-level data. The spatial dependence and clustering of child undernourishment across sub-districts in Odisha were studied using various spatial statistical techniques, including spatial econometric models. Binary logistic regression was applied in the region-specific analysis. Findings indicated statistically significant spatial clustering of undernutrition among children in specific geographic pockets with poor sanitation, low institutional and skilled deliveries, poor maternal health reinforcing the need for inter-sectoral coordination. Disparities across the three natural-regions, suggest that the parameters requiring priority for intervention may differ across levels of overall development. The spatial clustering of different socio-demographic indicators in specific geographic pockets highlights the differential impact of these determinants on child undernutrition thereby reinforcing a strong need for targeted intervention in these areas. Present analysis and the evidence-based micro-level analysis can be utilised as a model for other Indian states and low-resource countries, making interventions more effective through multiple, synergistic and a multi-sectoral approach.

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.

Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick [RAW_REF_TEXT] Ayushi Jain1 & [/RAW_REF_TEXT] [RAW_REF_TEXT] Satish B. Agnihotri 1 [/RAW_REF_TEXT] International Journal for Equity in Health volume 19, Article number: 176 (2020) Cite this article [RAW_REF_TEXT] 81 Accesses [/RAW_REF_TEXT] [RAW_REF_TEXT] 2 Altmetric [/RAW_REF_TEXT] [RAW_REF_TEXT] Metrics details [/RAW_REF_TEXT] [RAW_REF_TEXT] The original article was published in International Journal for Equity in Health 2020 19:138 [/RAW_REF_TEXT] Correction to: Note: On the y-axis, the value in brackets indicates the number of districts in that particular state Full size image Correction Open Access Published:07 October 2020 [/RAW_REF_TEXT] Correction to: Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick [RAW_REF_TEXT] Ayushi Jain1 & Satish B. Agnihotri 1 [/RAW_REF_TEXT] International Journal for Equity in Health volume 19, Article number: 176 (2020) Cite this article [RAW_REF_TEXT] 81 Accesses 2 Altmetric Metrics details The original article was published in International Journal for Equity in Health 2020 19:138

Stillbirth is a major public health problem across the world as well as in India. The programmatic interventions to tackle stillbirth require granular data upto local levels. The Health Management Information System (HMIS) in India is one of the best sources of granular data on stillbirth. This analysis was conducted using HMIS stillbirth data of three pre-pandemic years 2017-2020 to study the geo-spatial patterns of stillbirth at district level in nine states of India, forming a high burden cluster of four central Indian states and a low burden cluster of five southern states. Geo-spatial variation at sub-district level was studied for Maharashtra given the ready availability of sub-district shapefiles required for such analysis. The analysis also explores the seasonal variations in stillbirths at all-India level. A granular intra-cluster spatial pattern of stillbirth was observed in all states analyzed, with a clear hotspot across a few districts in Odisha and Chhattisgarh (>20 stillbirths/1,000 total births in 2019-20). Even in the southern cluster, the hotspots (8-20 stillbirths/1,000 total births) were found. Availability of sub-district level data in Maharashtra helped to identify intra-state regional variations in stillbirth with high prevalence in certain district clusters. In temporal terms, stillbirths exhibit a regular peak during August-October and a dip during February-April which is inclined with the birth seasonality patterns. This review and analysis underscore the need for more granular data availability, regular analysis of such data by expert and program managers, more decentralized and context specific programme intervention both in locational and seasonal terms.

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.

Our world is transitioning into a new generation of governance with much greater emphasis on targeted actions and mission mode programmes to achieve global sustainable goals (SDG). India with its Twenty-point programme which directly maps national and state programmes to global SDGs has been pacing up for 2030 targets. One of the major programmes that has been the prime focus is Integrated Child Development Services Scheme. India ranked 103rd among 119 countries on global hunger index, 2018. Significant reduction in malnutrition was seen among children below 6 years but the pace of reduction has been slow over the past decade. The path of malnutrition reduction of central belt states (tribal population dominant) deviates from rest of the country. Our analysis of National Family Health Survey-4 (NFHS) found that 42% of tribal children are underweight (i.e. 1.5 times higher than non-tribal children), over 50% of prevalence of malnutrition is in tribal population. 100% Mother & Child Protection registration do not reciprocate to 100% all Anti-Natal Care visits showing faults in monitoring system indicating that the investment by government in all fronts, economic development has not translated into desired reduction in malnutrition. Their 8.6% population accounts to 30% cases of malaria translating to 50% malarial deaths indicative of higher disease burden. Malnutrition crisis among tribals begins way early manifesting in higher rates of Low Birth Weight deliveries (LBW) which is 3–4% higher compared to non-tribal population. This is due to low nutrient diet, laborious work during gestational period and high disease burden. The focus of Maternal nutrition enhancement projects by Tribal Welfare Depts in these states should include nutrition sensitive along with nutrition specific interventions targeting the population under risk as well as entering risk. Now with district level data (NFHS) available every 4 years can aid in district level planning, shifting focus from population based to prevalence and exclusive planning for tribals. Our study involves developing a robust framework to enhance maternal nutrition through strong community mobilization and partnership. It also addresses the convergence issue being faced in the current system and paves a way forward for convergence among inter departmental schemes for larger participation by people and greater coverage of the scheme and its benefits.

Background Levels of child undernutrition and its correlates exhibit considerable spatial variation at different levels of granularity. In India, such variations and their interrelation have not been studied at the sub-district level primarily due to the non-availability of good quality granular data. Given the sheer regional diversity in India, it is essential to develop a region-specific evidence base at the micro-level. Data and objectives The current study utilised, for the first time, a sub-district level survey data (Concurrent Child Monitoring Survey-II, 2014–15) to investigate the statistically significant clusters and spatial patterns of burden of undernutrition among children. The emergence of distinct patterns at the level of natural geographical regions of the state–coastal, southern and northern regions, lead to a region-specific analysis to measure the impact of various demographic, socio-economic and maternal factors on the prevalence of undernutrition specific to the three regions, using the National Family Health Survey-IV unit-level data. Methods The spatial dependence and clustering of child undernourishment across sub-districts in Odisha were studied using various spatial statistical techniques, including spatial econometric models. Binary logistic regression was applied in the region-specific analysis. Results Findings indicated statistically significant spatial clustering of undernutrition among children in specific geographic pockets with poor sanitation, low institutional and skilled deliveries, poor maternal health reinforcing the need for inter-sectoral coordination. Disparities across the three natural-regions, suggest that the parameters requiring priority for intervention may differ across levels of overall development. Conclusion The spatial clustering of different socio-demographic indicators in specific geographic pockets highlights the differential impact of these determinants on child undernutrition thereby reinforcing a strong need for targeted intervention in these areas. Present analysis and the evidence-based micro-level analysis can be utilised as a model for other Indian states and low-resource countries, making interventions more effective through multiple, synergistic and a multi-sectoral approach.

The first three chapters of the book elaborate this success story, starting from the genesis of the project (Chapter 1) to the backdrop of the nine villages of Man taluka (Chapter 2), and finally, interventions done in various sectors and their journey to completion, bearing fruit from time to time. Social Change and Project Mode In his conceptual analysis of the development process (Chapter 4), the author recognises the larger societal changes that one usually tends to ignore while working in a project mode. Another important change the author flags, is the migration of the educated rural youth to the urban areas and their not returning to the villages to improve the living conditions in the villages. The author selected a remote location in a drought-prone area, which brought home the need for basic infrastructure, roads and electricity being important among them.

In a recent issue of this journal, Klasen [1996] and Svedberg [1990, 1996] have expressed diverging opinions on the nature of gender bias in sub-Saharan Africa. The divergence arises partly out of the choice of indicators and partly out of the choice of standards. It is possible, however, to infer the existence of such bias without using referents from some external 'standard' population. Such an approach, using the infant and the under-five mortality data by sex and the data on sex ratios in the 0-4 and 5-9 age groups from the Indian population census of 1981, is described below. It is suggested that this type of approach will be useful in resolving the above debate.

Community-based management of acute malnutrition (CMAM) relies on a food-based approach. However, a comprehensive assessment of their nutrient composition and its impact on treatment outcomes is currently lacking in the extant literature. This narrative review summarises recent evidence on the efficacy of formulations that contain dairy protein and maintain the density of essential nutrients (type I and type II) in managing uncomplicated acute malnutrition at the community level. The literature used for the evidence synthesis was identified using a two-stage screening process. An electronic search was run on PubMed and Cochrane Library, followed by a backward snowball search to identify efficacy studies. A total of twenty-six efficacy studies involving food formulations used to treat uncomplicated severe and moderate acute malnutrition were identified. The review found that, while more evidence favours the inclusion of dairy in formulations as efficacious in supporting recovery from malnutrition, ambiguity in the conclusive findings between dairy and non-dairy formulations remains due to the varied percentages of dairy protein in different formulations. The type of protein source used in a formulation matters, but other approaches, including fortification, can aid in maintaining the nutrient density of formulations, thereby improving the chances of recovery. However, the inclusion of high amounts of added sugar in therapeutic formulations exceeding the World Health Organization norms is a concern that warrants more attention. Future clinical research should assess outcomes such as lean or fat mass changes to confirm the benefits of using dairy or non-dairy formulations to treat moderate and severe acute malnutrition.