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Background: Health outcomes in India are characterized by pervasive inequities due to deeply entrenched socio-economic gradients amongst the population. Therefore, it is imperative to investigate these systematic disparities in health, however, evidence of inequities does not commensurate with its policy objectives in India. Thus, our paper aims to examine the magnitude of and trends in horizontal inequities in self-reported morbidity and untreated morbidity in India over the period of 2004 to 2017–18. Methods: The study used cross-sectional data from nationwide healthcare surveys conducted in 2004, 2014 and 2017–18 encompassing sample size of 3,85,055; 3,35,499 and 5,57,887 individuals respectively. Erreygers concentration indices were employed to discern the magnitude and trend in horizontal inequities in self-reported morbidity and untreated morbidity. Need standardized concentration indices were further used to unravel the inter-regional and intra-regional income related inequities in outcomes of interest. Additionally, regression based decomposition approach was applied to ascertain the contributions of both legitimate and illegitimate factors in the measured inequalities. Results: Estimates were indicative of profound inequities in self-reported morbidity as inequity indices were positive and significant for all study years, connoting better-off reporting more morbidity, given their needs. These inequities however, declined marginally from 2004(HI: 0.049, p< 0.01) to 2017–18(HI: 0.045, P< 0.01). Untreated morbidity exhibited pro-poor inequities with negative concentration indices. Albeit, significant reduction in horizontal inequity was found from 2004(HI= − 0.103, p< 0.01) to 2017–18(HI = − 0.048, p< 0.01) in treatment seeking over the years. The largest contribution of inequality for both outcomes stemmed from illegitimate variables in all the study years. Our findings also elucidated inter-state heterogeneities in inequities with high-income states like Andhra Pradesh, Kerala and West Bengal evincing inequities greater than all India estimates and Northeastern states divulged equity in reporting morbidity. Inequities in untreated morbidity converged for most states except in Punjab, Chhattisgarh and Himachal Pradesh where widening of inequities were observed from 2004 to 2017–18. Conclusions: Pro-rich and pro-poor inequities in reported and untreated morbidities respectively persisted from 2004 to 2017–18 despite reforms in Indian healthcare. Magnitude of these inequities declined marginally over the years. Health policy in India should strive for targeted interventions closing inequity gap. [ABSTRACT FROM AUTHOR]

Background: Health outcomes in India are characterized by pervasive inequities due to deeply entrenched socio-economic gradients amongst the population. Therefore, it is imperative to investigate these systematic disparities in health, however, evidence of inequities does not commensurate with its policy objectives in India. Thus, our paper aims to examine the magnitude of and trends in horizontal inequities in self-reported morbidity and untreated morbidity in India over the period of 2004 to 2017–18. Methods: The study used cross-sectional data from nationwide healthcare surveys conducted in 2004, 2014 and 2017–18 encompassing sample size of 3,85,055; 3,35,499 and 5,57,887 individuals respectively. Erreygers concentration indices were employed to discern the magnitude and trend in horizontal inequities in self-reported morbidity and untreated morbidity. Need standardized concentration indices were further used to unravel the inter-regional and intra-regional income related inequities in outcomes of interest. Additionally, regression based decomposition approach was applied to ascertain the contributions of both legitimate and illegitimate factors in the measured inequalities. Results: Estimates were indicative of profound inequities in self-reported morbidity as inequity indices were positive and significant for all study years, connoting better-off reporting more morbidity, given their needs. These inequities however, declined marginally from 2004(HI: 0.049, p< 0.01) to 2017–18(HI: 0.045, P< 0.01). Untreated morbidity exhibited pro-poor inequities with negative concentration indices. Albeit, significant reduction in horizontal inequity was found from 2004(HI= − 0.103, p< 0.01) to 2017–18(HI = − 0.048, p< 0.01) in treatment seeking over the years. The largest contribution of inequality for both outcomes stemmed from illegitimate variables in all the study years. Our findings also elucidated inter-state heterogeneities in inequities with high-income states like Andhra Pradesh, Kerala and West Bengal evincing inequities greater than all India estimates and Northeastern states divulged equity in reporting morbidity. Inequities in untreated morbidity converged for most states except in Punjab, Chhattisgarh and Himachal Pradesh where widening of inequities were observed from 2004 to 2017–18. Conclusions: Pro-rich and pro-poor inequities in reported and untreated morbidities respectively persisted from 2004 to 2017–18 despite reforms in Indian healthcare. Magnitude of these inequities declined marginally over the years. Health policy in India should strive for targeted interventions closing inequity gap. [ABSTRACT FROM AUTHOR]

Background: Equity and justice in healthcare payment form an integral part of health policy and planning. In the majority of low and middle-income countries (LMICs), healthcare inequalities are further aggravated by Out of Pocket Expenditure (OOPE). This paper examines the pattern of health equity and regional disparities in healthcare spending among Indian states by applying Andersen's behavioural model of healthcare utilization. Methods: The present study uses data from the 66th quinquennial round of Consumer Expenditure Survey, of the National Sample Survey Organization (NSSO), conducted in 2009-10 by Ministry of Statistics and Programme Implementation (MoSPI), Government of India (GoI). To measure equity and regional disparities in healthcare expenditure, states have been categorized under three heads on the basis of monthly OOPE i.e., Category A (OOPE > =INR 100); Category B (OOPE between INR 50 to 99) and Category C (OOPE < INR 50). Multiple Generalised Linear Regression Model (GLRM) has been employed to explore the effect of various socio-economic covariates on the level of OOPE. Results: The gap in the ratio of average healthcare spending between the poorest and richest households was maximum in Category A states Category B (richest/poorest = 14.60), followed by (richest/poorest 11.70) and Category C (richest/poorest 11.40). Results also indicate geographical concentration of lower level healthcare spending among Indian states (e.g., Odisha, Chhattisgarh and all the north-eastern states). Results from the multivariate analysis suggest that people residing in urban areas, having higher economic status, belonging to non-Muslim communities, non-Scheduled Tribes (STs), and non-poor households spend more on healthcare than their counterparts. Conclusions: In spite of various efforts by the government to reduce the burden of healthcare spending, widespread inequalities in healthcare expenditure are prevalent. Households with high healthcare needs (SCs/STs, and the poor) are in a more disadvantaged position in terms of spending on health care. It has also been observed that spending on healthcare was comparatively lower among backward or isolated states. No doubt, the overall social security measures should be enhanced, but at the same time, looking at the regional differences, more priority should be assigned to the disadvantaged states to reduce the burden of OOPE. It is proposed that there is need to increase government spending, especially for the disadvantaged states and population, to minimise the burden of OOPE. [ABSTRACT FROM AUTHOR]