While the gender disparity in health and mortality in various stages of life in India is well documented, there is limited evidence on female disadvantage in health-care expenditure (HCE). Examine the gender difference in HCE in short-term and major morbidity in India, and understand the role of factors underlying the difference. Using two rounds of nationally representative panel data—the India Human Development Survey (IHDS) 2004–2005 and 2011–2012 (IHDS I & II)—we calculate morbidity prevalence rate and mean HCE by gender, and examine the adjusted effect of gender on major morbidity-related HCE by using a two-part regression model. Further, we performed Oaxaca-Blinder decomposition of the gender gap in HCE in major morbidity to understand the contribution of demographic and socio-economic factors. Health-care expenditure on females was systematically lower than on males across all demographic and socio-economic groups. Multivariate analysis confirms that female HCE is significantly lower than male HCE even after controlling demographic and socio-economic factors (β = -0.148, p = 0.000, CI:-0.206–0.091). For both short-term and major morbidity, a female disadvantage on HCE increased from IHDS I to IHDS II. For instance, the male–female gap in major morbidity related expenditure increased from INR 1298 to INR 4172. A decomposition analysis of gender gap in HCE demonstrates that about 48% of the gap is attributable to differences in demographic and socio-economic factors (endowment effect), whereas 50% of the gap is due to the differential effect of the determinants (coefficient effect). Indians spend less on female health care than on male health care. Most of the gender gap in HCE is not due to differential distribution of factors affecting HCE.

India contributes the highest global share of deaths among the under-fives. Continuous monitoring of the reduction in the under-five mortality rate (U5MR) at local level is thus essential to set priorities for policy-makers and health professionals. In this study, we aimed to provide an update on district-level disparities in the neonatal mortality rate (NMR) and the U5MR with special reference to Sustainable Development Goal 3 (SDG3) on preventable deaths among new-borns and children under five. We used recently released population-based cross-sectional data from the National Family Health Survey (NFHS) conducted in 2015–2016. We used the synthetic cohort probability approach to analyze the full birth history information of women aged 15–49 to estimate the NMR and U5MR for the ten years preceding the survey. Both the NMR and U5MR vary enormously across Indian districts. With respect to the SDG3 target for 2030 for the NMR and the U5MR, the estimated NMR for India for the period studied is about 2.4 times higher, while the estimated U5MR is about double. At district level, while 9% of the districts have already reached the NMR targeted in SDG3, nearly half (315 districts) are not likely to achieve the 2030 target even if they realize the NMR reductions achieved by their own states between the last two rounds of National Family Health Survey of India. Similarly, less than one-third of the districts (177) of India are unlikely to achieve the SDG3 target on the U5MR by 2030. While the majority of high-risk districts for the NMR and U5MR are located in the poorer states of north-central and eastern India, a few high-risk districts for NMR also fall in the rich and advanced states. About 97% of districts from Chhattisgarh and Uttar Pradesh, for example, are unlikely to meet the SDG3 target for preventable deaths among new-borns and children under age five, irrespective of gender. To achieve the SDG3 target on preventable deaths by 2030, the majority of Indian districts clearly need to make a giant leap to reduce their NMR and U5MR.

The extant literature on gender differentials in health in developed countries suggests that women outlive men at all ages, but women report poorer health than men. It is well established that Indian women live longer than men, but few studies have been conducted to understand the gender dimension in self-rated health and self-reported disability. The present study investigates gender differentials in self-rated health (SRH) and self-reported disability (SRD) among adults in India, using a nationally representative data. Using data on 10,736 respondents aged 18 and older in the 2007 WHO Study on Global Ageing and Adult Health in India, prevalence estimates of SRH are calculated separately for men and women by socio-economic and demographic characteristics. The association of SRH with gender is tested using a multinomial logistic regression method. SRD is assessed using 20 activities of daily living (ADL). Further, gender differences in total life expectancy (TLE), disability life expectancy (DLE) and the proportion of life spent with a disability at various adult ages are measured. The relative risk of reporting poor health by women was significantly higher than men (relative risk ratio: 1.660; 95% confidence Interval (CI): 1.430–1.927) after adjusting for socio-economic and demographic characteristics. Women reported higher prevalence of severe and extreme disability than men in 14 measures out of a total20 ADL measures. Women aged less than 60 years reported two times more than men in SRD ≥ 5 ADLs. Finally, both DLE and proportion of life spent with a disability were substantially higher for women irrespective of their ages. Indian women live longer but report poorer health than men. A substantial gender differential is found in self-reported disability. This makes for an urgent call to health researchers and policy makers for gender-sensitive programs.

Understanding the socioeconomic and regional divides in disability prevalence in India has considerable relevance for designing public health policies and programs. The aim of the present study is to quantify the prevalence of disability by gender, region (rural and urban; states and districts), and caste. We also examine the association between disability prevalence and the major socio-demographic and socioeconomic characteristics of the districts in India. Age-standardized disability prevalence (ASDP) was calculated using 2011 census data and applying the WHO World Standard Population. A regression analysis was carried out to examine the association between disability prevalence and demographic and socioeconomic characteristics across districts of India. The study found that ASDP varies substantially across districts and is higher among women, rural dwellers, and members of scheduled tribes (STs) and scheduled castes (SCs). The regression model showed that the disability rate in districts rises with increasing proportions of the population who are urban dwellers, aged 65 or older, members of STs, and living in dilapidated housing; and that the disability prevalence decreases with increasing proportions of the female population who are literate, and of the general population who are working and have access to safe drinking water. As the burden of disability falls disproportionately across geographic regions and socioeconomic groups, public health policies in India should take this variation into account. The definition of disability used in the census should be modified to generate internationally comparable estimates of disability prevalence.

Excess female mortality causes half of the missing women (estimated deficit of women in countries with suspiciously low proportion of females in their population) today. Globally, most of these avoidable deaths of women occur during childhood in China and India. We aimed to estimate excess female under-5 mortality rate (U5MR) for India's 35 states and union territories and 640 districts. Using the summary birth history method (or Brass method), we derived district-level estimates of U5MR by sex from 2011 census data. We used data from 46 countries with no evidence of gender bias for mortality to estimate the effects and intensity of excess female mortality at district level. We used a detailed spatial and statistical analysis to highlight the correlates of excess mortality at district level. Excess female U5MR was 18·5 per 1000 livebirths (95% CI 13·1-22·6) in India 2000-2005, which corresponds to an estimated 239 000 excess deaths (169 000-293 000) per year. More than 90% of districts had excess female mortality, but the four largest states in northern India (Uttar Pradesh, Bihar, Rajasthan, and Madhya Pradesh) accounted for two-thirds of India's total number. Low economic development, gender inequity, and high fertility were the main predictors of excess female mortality. Spatial analysis confirmed the strong spatial clustering of postnatal discrimination against girls in India. The considerable effect of gender bias on mortality in India highlights the need for more proactive engagement with the issue of postnatal sex discrimination and a focus on the northern districts. Notably, these regions are not the same as those most affected by skewed sex ratio at birth. None.

Despite the vast literature on health care expenditures (HCE) and health care financing strategies (HCFS) in low- and middle-income countries, there is limited evidence of gender disparity in HCFS for inpatient care. We examined gender disparities in HCE and HCFS for inpatient care among adults aged 15 and older in India which is widely known for gender-based discrimination in sex-selective abortion, nutrition, and access to health care. Using data from a nationally representative large-scale population-based survey, we investigated the relationship between the gender of adult patients and HCE as well as sources of health care financing. Simple percentage distribution, cross-tabulation, a two-level random intercept model, and multinomial logit regression were used to examine the role of gender in HCE and sources of health care financing for inpatient care. Average HCE is lower for women in adult age groups, regardless of the type of disease and duration of stay in the hospital. This result remained unchanged after controlling for other background variables of the patients. Women are also discriminated against more when health care has to be paid for by borrowing, sale of assets, or contributions from friends and relatives (distressed financing). Multinomial logit results show that the probability of distressed financing is less for females than for males (borrowing: β = -0.27; confidence interval [CI], -0.37 to -0.17; P = .001; selling assets/contribution from friends and relatives: β = -0.27; CI, -0.39 to -0.14; P = .001). The predicted probability of using health care financing implies that the health of adult men is considered to be more important, in terms of resorting to distressed financing, than that of adult women HCE on adult women inpatients is systematically lower than that of adult men inpatients. Further, women in India have less access to inpatient care through distressed HCFS.