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• Multidimensional child poverty is notably more prevalent among STs and SCs. • Standard of living, ECD, and WASH are the dimensions that need committed thrust. • STs and SCs contribute more to the national MCP than their share of the population. • Head of household characterised by female gender, older age, and higher level of education is associated with a lower likelihood of MCP. • MCP tends to be more pronounced in nuclear families, households with 7+ members, rural areas, and central and eastern regions. Children are among the most vulnerable groups worldwide, bearing a disproportionate share of the burden of poverty. One-third of children, compared to one-sixth of adults, are multidimensionally poor. Experiencing poverty in childhood can have long-term negative consequences across generations. As a result, multidimensional poverty measures have recently been investigated in the child poverty literature. This study analysed multidimensional poverty among children (0–59 months) in India using the Alkire-Foster's counting approach and looked into how it differs across the country's well-known social stratification, the Caste system. The determinants of multidimensional child poverty (MCP) have been determined using multiple logistic regression. By using National Family Health Survey, 2019–21 data, the study revealed that the incidence of MCP in India is 32 %; highest among Scheduled Tribes (STs) (50 %), followed by Scheduled Castes (SCs) (37 %), Other Backward Classes (OBCs) (30 %) and 'Others' (22 %). Across all the Castes highest rates of deprivation were recorded in the indicators of standard of living and early childhood development (ECD) dimensions; together, they contribute more than 50 % to the MCP index (MCPI). The contribution of the water, sanitation, and hygiene (WASH) dimension in MCPI of STs is also noticeably higher (20.2 %). Of the 15 indicators considered, availability of TV/Radio, followed by immunisation, sanitation, cooking fuel, housing condition, and stunting, are the leading contributors with a combined contribution of more than 55 %. A child being a male, of higher birth order and born to a mother with higher years of schooling was more likely to experience multidimensional poverty. The household head's sex, age, and years of schooling were significantly associated with MCP. Across all castes, children from nuclear families, 7 + household members, higher number of children per woman, rural areas, central, eastern and north-eastern (except STs) regions were more likely to experience multidimensional poverty. [ABSTRACT FROM AUTHOR]

• Around 59% of the children are suffering from anaemia in India. • Overall, 36.8% of mother–child pairs are suffering from anaemia. • In India, higher double burden of anaemia is seen in Jharkhand and Haryana states and lowest in Mizoram state. • After controlling for significant background factors, poor household at higher risk of double burden of anaemia in India. The prevalence of anaemia among pregnant women in India continues to be high despite efforts to address the issue through iron-folic acid supplements under the national health program. It is estimated that about 50% of pregnant women, adolescent girls and children are anaemic. Anaemic women are at a significantly higher risk of morbidity, mortality, postpartum haemorrhage, and low birth outcomes, in addition to low birth weight and preterm birth of their babies due to poor intrauterine growth. The purpose of this study is to investigate anaemia among mother–child pairs — known as a double burden — in poor and non-poor households in India. The study uses data from the fourth round of the National Family Health Survey (NFHS). The survey collects information on the haemoglobin levels in mothers and children. Bivariate and multivariate analyses were used to determine the risk of anaemia in mother–child pairs among poor and non-poor households. Our survey found that, respectively, 57.1% and 58.7% of the mothers and children were suffering from anaemia; and the double burden was 36.8%. The double burden of anaemia was much higher among poor households (41.0%) as compared to the prevalence in non-poor households (33.1%). This pattern was observed across the background characteristics of the mothers, such as age, place of residence, education, caste, religion, Body Mass Index (BMI) and selected child factors. The adjusted odds for poor households, after controlling for significant background factors of the mothers and children, was found to 11% (OR:1.11, p-value:<0.001; 95%, CI:1.09–1.14) with higher odds of double burden as compared to non-poor households. The findings of the study point to the need for policies that are targeted at addressing the double burden of anaemia in poor households in India. [ABSTRACT FROM AUTHOR]

In India, “non-notified” slums are not officially recognized by city governments; they suffer from insecure tenure and poorer access to basic services than “notified” (government-recognized) slums. We conducted a study in a non-notified slum of about 12,000 people in Mumbai to determine the prevalence of individuals at high risk for having a common mental disorder (i.e., depression and anxiety), to ascertain the impact of mental health on the burden of functional impairment, and to assess the influence of the slum environment on mental health. We gathered qualitative data (six focus group discussions and 40 individual interviews in July–November 2011), with purposively sampled participants, and quantitative data (521 structured surveys in February 2012), with respondents selected using community-level random sampling. For the surveys, we administered the General Health Questionnaire-12 (GHQ) to screen for common mental disorders (CMDs), the WHO Disability Assessment Schedule 2.0 (WHO DAS) to screen for functional impairment, and a slum adversity questionnaire, which we used to create a composite Slum Adversity Index (SAI) score. Twenty-three percent of individuals have a GHQ score ≥5, suggesting they are at high risk for having a CMD. Psychological distress is a major contributor to the slum's overall burden of functional impairment. In a multivariable logistic regression model, household income, poverty-related factors, and the SAI score all have strong independent associations with CMD risk. The qualitative findings suggest that non-notified status plays a central role in creating psychological distress—by creating and exacerbating deprivations that serve as sources of stress, by placing slum residents in an inherently antagonistic relationship with the government through the criminalization of basic needs, and by shaping a community identity built on a feeling of social exclusion from the rest of the city. [ABSTRACT FROM AUTHOR]

Abstract: Community-Based Health Insurance (CBHI) (a.k.a. micro health insurance) is a contributory health insurance among rural poor in developing countries. As CBHI schemes typically function with no subsidy income, the schemes'' expenditures cannot exceed their premium income. A good estimate of Willingness-To-Pay (WTP) among the target population affiliating on a voluntary basis is therefore essential for package design. Previous estimates of WTP reported materially and significantly different WTP levels across locations (even within one state), making it necessity to base estimates on household surveys. This is time-consuming and expensive. This study seeks to identify a coherent anchor for local estimation of WTP without having to rely on household surveys in each CBHI implementation. Using data collected in 2008–2010 among rural poor households in six locations in India (total 7874 households), we found that in all locations WTP expressed as percentage of income decreases with household income. This reminds of Engel''s law on food expenditures. We checked several possible anchors: overall income, discretionary income and food expenditures. We compared WTP expressed as percentage of these anchors, by calculating the Coefficient of Variation (for inter-community variation) and Concentration indices (for intra-community variation). The Coefficient of variation was 0.36, 0.43 and 0.50 for WTP as percent of food expenditures, overall income and discretionary income, respectively. In all locations the concentration index for WTP as percentage of food expenditures was the lowest. Thus, food expenditures had the most consistent relationship with WTP within each location and across the six locations. These findings indicate that like food, health insurance is considered a necessity good even by people with very low income and no prior experience with health insurance. We conclude that the level of WTP could be estimated based on each community''s food expenditures, and that this information can be obtained everywhere without having to conduct household surveys. [Copyright &y& Elsevier]