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Background: Reduction of multidimensional poverty and tuberculosis are priority development agenda worldwide. The SDGs aims to eradicate poverty in all forms (SDG 1.2) and to end tuberculosis (SDG 3.3.2) by 2030. While poverty is increasingly being measured across multiple domains, reduction of tuberculosis has been an integral part of public health programmes. Though literature suggests a higher prevalence of tuberculosis among the economically poor, no attempt has been made to understand the association between multidimensional poverty and tuberculosis in India. The objective of this paper is to examine the association of multidimensional poverty and tuberculosis in India.Methods: The unit data from the National Family Health Survey-4, conducted in 2015-16 covering 628,900 households and 2,869,043 individuals across 36 states and union territories of India was used in the analysis. The survey collected information on the self-reported tuberculosis infection of each member of a sample household at the time of the survey. Multidimensional poverty was measured in the domains of education, health, and standard of living, with a set of 10 indicators. The prevalence of tuberculosis was estimated among the multidimensional poor and non-poor populations across the states of India. A binary logistic regression model was used to understand the association of tuberculosis and multidimensional poverty.Results: Results suggest that about 29.3% population of India was multidimensional poor and that the multidimensional poverty index was 0.128. The prevalence of tuberculosis among the multidimensional poor was 480 (95% CI: 464-496) per 100,000 population compared to 250 (95% CI: 238-262) among the multidimensional non-poor. The prevalence of tuberculosis among the multidimensional poor was the highest in the state of Kerala (1590) and the lowest in the state of Himachal Pradesh (220). Our findings suggest a significantly higher prevalence of tuberculosis among the multidimensional poor compared to the multidimensional non-poor in most of the states in India. The odds of having tuberculosis among the multidimensional poor were 1.82 times higher (95% CI, 1.73-1.90) compared to the non-poor. Age, sex, smoking, crowded living conditions, caste, religion, and place of residence are significant socio-demographic risk factors of tuberculosis.Conclusion: The prevalence of tuberculosis is significantly higher among the multidimensional poor compared to the multidimensional non-poor in India. [ABSTRACT FROM AUTHOR]

Background: Economic burden to households due to out-of-pocket expenditure (OOPE) is large in many Asian countries. Though studies suggest increasing household poverty due to high OOPE in developing countries, studies on association of multidimensional poverty and household health spending is limited. This paper tests the hypothesis that the multidimensionally poor are more likely to incur catastrophic health spending cutting across countries. Data and methods: Data from the Poverty and Vulnerability Assessment (PVA) Survey carried out by the International Center for Integrated Mountain Development (ICIMOD) has been used in the analyses. The PVA survey was a comprehensive household survey that covered the mountainous regions of India, Nepal and Myanmar. A total of 2647 households from India, 2310 households in Nepal and 4290 households in Myanmar covered under the PVA survey. Poverty is measured in a multidimensional framework by including the dimensions of education, income and energy, water and sanitation using the Alkire and Foster method. Health shock is measured using the frequency of illness, family sickness and death of any family member in a reference period of one year. Catastrophic health expenditure is defined as 40% above the household's capacity to pay. Results: Results suggest that about three-fifths of the population in Myanmar, two-fifths of the population in Nepal and one-third of the population in India are multidimensionally poor. About 47% of the multidimensionally poor in India had incurred catastrophic health spending compared to 35% of the multidimensionally non-poor and the pattern was similar in both Nepal and Myanmar. The odds of incurring catastrophic health spending was 56% more among the multidimensionally poor than among the multidimensionally non-poor [95% CI: 1.35-1.76]. While health shocks to households are consistently significant predictors of catastrophic health spending cutting across country of residence, the educational attainment of the head of the household is not significant. Conclusion: The multidimensionally poor in the poorer regions are more likely to face health shocks and are less likely to afford professional health services. Increasing government spending on health and increasing households' access to health insurance can reduce catastrophic health spending and multidimensional poverty. [ABSTRACT FROM AUTHOR]

Background: In recent years, supported by non-governmental organizations (NGOs), a number of community-based health insurance (CBHI) schemes have been operating in rural India. Such schemes design their benefit packages according to local priorities. This paper examines healthcare seeking behaviour among self-help group households with a view to understanding the implications for the benefit packages offered by such schemes.Methods: We use cross-sectional data collected from two of India's poorest states and estimate an alternative-specific conditional logit model to examine healthcare seeking behaviour.Results: We find that the majority of respondents do access some form of care and that there is overwhelming use of private providers. Non-degree allopathic providers (NDAP) also called rural medical practitioners are the most popular providers. In the case of acute illnesses, proximity plays an important role in determining provider choice. For chronic illnesses, cost of care influences provider choice.Conclusion: Given the importance of proximity in determining provider choice, benefit packages offered by CBHI schemes should consider coverage of transportation costs and reimbursement of foregone earnings. [ABSTRACT FROM AUTHOR]

Background: India launched a national conditional cash transfer program, Janani Suraksha Yojana (JSY), aimed at reducing maternal mortality by promoting institutional delivery in 2005. It provides a cash incentive to women who give birth in public health facilities. This paper studies the extent of program uptake, reasons for participation/ non participation, factors associated with non uptake of the program, and the role played by a program volunteer, accredited social health activist (ASHA), among mothers in Ujjain district in Madhya Pradesh, India. Methods: A cross-sectional study was conducted from January to May 2011 among women giving birth in 30 villages in Ujjain district. A semi-structured questionnaire was administered to 418 women who delivered in 2009. Socio-demographic and pregnancy related characteristics, role of the ASHA during delivery, receipt of the incentive, and reasons for place of delivery were collected. Multinomial regression analysis was used to identify predictors for the outcome variables; program delivery, private facility delivery, or a home delivery. Results: The majority of deliveries (318/418; 76%) took place within the JSY program; 81% of all mothers below poverty line delivered in the program. Ninety percent of the women had prior knowledge of the program. Most program mothers reported receiving the cash incentive within two weeks of delivery. The ASHA's influence on the mother's decision on where to deliver appeared limited. Women who were uneducated, multiparious or lacked prior knowledge of the JSY program were significantly more likely to deliver at home. Conclusion: In this study, a large proportion of women delivered under the program. Most mothers reporting timely receipt of the cash transfer. Nevertheless, there is still a subset of mothers delivering at home, who do not or cannot access emergency obstetric care under the program and remain at risk of maternal death. [ABSTRACT FROM AUTHOR]

Background: Rising health spending is associated with high out-of-pocket expenditure (OOPE), catastrophic health spending (CHS), increasing poverty, and impoverishment. Though studies have examined poverty and impoverishment effect of health spending in India, there is limited research on the regional patterns of health spending by type of health centers. This paper tests the hypothesis that the poor people from the poorer states of India pay significantly more for hospitalization in public health centers than those in the richer states of India.Methods: Data from the Social Consumption of Health Survey (71st round, 2014), carried out by the National Sample Survey (NSS) is used in the analyses. Descriptive statistics, log-linear regression model and tobit model were used to examine the determinants and variations in health spending.Results: Inter-state variations in the utilization of public health services and the OOPE on hospitalization are high in India. States with high levels of poverty make higher use of the public health centers and yet incur high OOPE. In 2014, the mean OOPE per episode of hospitalization in public health centers in India was ₹5688 and ₹4264 for the economically poor households. It was lowest in the economically developed state of Tamil Nadu and highest in the economically poorer state of Bihar. The OOPE per episode of hospitalization in public health centers among the poor in the poorer states was at least twice that in Tamil Nadu. Among the poor using public health centers, the share of direct cost account 24% in Tamil Nadu compared to over 80% in Bihar, Odisha and other poorer states. Adjusting for socio-economic correlates, the cost of hospitalization per episode (CHPE) among the poor using public health centers was 51% lower than for the non-poor using private health centers in India.Conclusion: The poor people in the poorer states in India pay significantly more to avail hospitalization in public health centers than those in the developed states. Provision of free medicines, surgery and free diagnostic tests in public health centers may reduce the high OOPE and medical poverty in India. [ABSTRACT FROM AUTHOR]

Background: Despite sustained economic growth and reduction in money metric poverty in last two decades, prevalence of malnutrition remained high in India. During 1992-2016, the prevalence of underweight among children had declined from 53% to 36%, stunting had declined from 52% to 38% while that of wasting had increased from 17% to 21% in India. The national average in the level of malnutrition conceals large variation across districts of India. Using data from the recent round of National Family Health Survey (NFHS), 2015-16 this paper examined the spatial heterogeneity and meso-scale correlates of child malnutrition across 640 districts of India.Methods: Moran's I statistics and bivariate LISA maps were used to understand spatial dependence and clustering of child malnutrition. Multiple regression, spatial lag and error models were used to examine the correlates of malnutrition. Poverty, body mass index (BMI) of mother, breastfeeding practices, full immunization, institutional births, improved sanitation and electrification in the household were used as meso scale correlates of malnutrition.Results: The univariate Moran's I statistics was 0.65, 0.51 and 0.74 for stunting, wasting and underweight respectively suggesting spatial heterogeneity of malnutrition in India. Bivariate Moran's I statistics of stunting with BMI of mother was 0.52, 0.46 with poverty and - 0.52 with sanitation. The pattern was similar with respect to wasting and underweight suggesting spatial clustering of malnutrition against the meso scale correlates in the geographical hotspots of India. Results of spatial error model suggested that the coefficient of BMI of mother and poverty of household were strong and significant predictors of stunting, wasting and underweight. The coefficient of BMI in spatial error model was largest found for underweight (β = 0.38, 95% CI: 0.29-0.48) followed by stunting (β = 0.23, 95% CI: 0.14-0.33) and wasting (β = 0.11, 95% CI: 0.01-0.22). Women's educational attainment and breastfeeding practices were also found significant for stunting and underweight.Conclusion: Malnutrition across the districts of India is spatially clustered. Reduction of poverty, improving women's education and health, sanitation and child feeding knowledge can reduce the prevalence of malnutrition across India. Multisectoral and targeted intervention in the geographical hotspots of malnutrition can reduce malnutrition in India. [ABSTRACT FROM AUTHOR]