Search

Introduction:The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY) - potentially, the world's largest NPHI programme - has succeeded in raising health insurance coverage of the poorest two-fifths of the population of India. Methods:We used nationally representative data from the National Family Health Survey on 633 699 and 601 509 households in 2015-2016 (pre-PM-JAY) and 2019-2021 (mostly, post PM-JAY), respectively. We stratified by urban/rural and estimated NPHI coverage nationally, and by state, district and socioeconomic categories. We decomposed coverage variance between states, districts, and households and measured socioeconomic inequality in coverage. For Uttar Pradesh, we tested whether coverage increased most in districts where PM-JAY had been implemented before the second survey and whether coverage increased most for targeted poorer households in these districts. Results:We estimated that NPHI coverage increased by 11.7 percentage points (pp) (95% CI 11.0% to 12.4%) and 8.0 pp (95% CI 7.3% to 8.7%) in rural and urban India, respectively. In rural areas, coverage increased most for targeted households and pro-rich inequality decreased. Geographical inequalities in coverage narrowed. Coverage did not increase more in states that implemented PM-JAY. In Uttar Pradesh, the coverage increase was larger by 3.4 pp (95% CI 0.9% to 6.0%) and 4.2 pp (95% CI 1.2% to 7.1%) in rural and urban areas, respectively, in districts exposed to PM-JAY and the increase was 3.5 pp (95% CI 0.9% to 6.1%) larger for targeted households in these districts. Conclusion:The introduction of PM-JAY coincided with increased public health insurance coverage and decreased inequality in coverage. But the gains canno

There were no estimates of the prevalence of pain and its treatment in the older population of India obtained from face-to-face interviews with a nationally representative sample. We addressed this evidence gap by using data on 63,931 individuals aged 45 years and older from the 2017/2018 Longitudinal Ageing Study in India. We identified pain from an affirmative response to the question: Are you often troubled by pain? We also identified those who reported pain that limited usual activities and who received treatment for pain. We estimated age- and sex-adjusted prevalence of pain, pain limiting usual activity and treatment, and compared these estimates across states and sociodemographic groups. We used a multivariable probit model to estimate full adjusted differences in the probability of each outcome across states and sociodemographic groups. We estimated that 36.6% (95% confidence interval [CI]: 35.3-37.8) of older adults in India were often troubled by pain and 25.2% (95% CI: 24.2-26.1) experienced pain limiting usual activity. We estimated that 73.3% (95% CI: 71.9-74.6) of those often troubled by pain and 76.4% (95% CI: 74.9-78.0) of those with pain that limited usual activity received treatment. There was large variation in each outcome across states. Fully adjusted prevalence of pain and pain limiting usual activity were higher among individuals who were female, older, less educated, rural residents, and poorer. Prevalence of treatment among those troubled by pain was lower among socially disadvantaged groups.

Despite widespread use of unclean cooking fuels (UCF) in India, evidence from nationally representative data on its association with visual impairment was lacking. We used a population-based nationwide survey of adults aged 45 years and older that included reported UCF and measured visual impairment. We estimated that 44.8% (95% CI: 42.6, 47.1) of older adults in India lived in households that used UCF. Age- and sex-adjusted prevalence of visual impairment was estimated to be 33.0% (95% CI: 31.0, 34.9) in the older population that did not use UCF and 9.0 percentage points (pp) (95% CI: 8.9, 9.1) higher among those who did. Among those who used UCF, age- and sex-adjusted prevalence of low distance vision was 4.3 pp (95% CI: 4.2, 4.4) higher, prevalence of low near vision was 8.0 pp (95% CI: 7.9, 8.1) higher, and prevalence of blindness was 1.0 pp (95% CI: 0.9, 1.0) higher. After controlling for a rich array of sociodemographic characteristics and state fixed effects, we estimated that use of UCF was associated with higher prevalence of visual impairment by 3.2 pp (95% CI: 1.4, 5.0), low distance vision by 1.8 pp (95% CI: 0.7, 2.9), and low near vision by 3.2 pp (95% CI: 1.3, 5.0). Doubly robust estimates of these differences were slightly larger. Blindness was not significantly partially associated with use of UCF (95% CI: −0.4, 0.6). We did not find support for the hypotheses that the visual impairment risk associated with use of UCF was even larger for females and in households without a separate kitchen or ventilation. The older population of India is highly reliant on UCF that is very strongly associated with visual impairment. Impaired vision should not be overlooked among the harms associated with UCF.

Objective To assess missed opportunities for hypertension screening at health facilities in India and describe systematic differences in these missed opportunities across states and sociodemographic groups. Methods We used nationally representative survey data from the 2017–2018 Longitudinal Ageing Study in India to estimate the proportion of adults aged 45 years or older identified with hypertension and who had not been diagnosed with hypertension despite having visited a health facility during the previous 12 months. We estimated age–sex adjusted proportions of missed opportunities to diagnose hypertension, as well as actual and potential proportions of diagnosis, by sociodemographic characteristics and for each state. Findings Among those identified as having hypertension, 22.6% (95% confidence interval, CI: 21.3 to 23.8) had not been diagnosed despite having recently visited a health facility. If these opportunities had been realized, the prevalence of diagnosed hypertension would have increased from 54.8% (95% CI: 53.5 to 56.1) to 77.3% (95% CI: 76.2 to 78.5). Missed opportunities for diagnosis were more common among individuals who were poorer (P = 0.001), less educated (P < 0.001), male (P < 0.001), rural (P < 0.001), Hindu (P = 0.001), living alone (P = 0.028) and working (P < 0.001). Missed opportunities for diagnosis were more common at private than at public health facilities (P < 0.001) and varied widely across states (P < 0.001). Conclusion Opportunistic screening for hypertension has the potential to significantly increase detection of the condition and reduce sociodemographic and geographic inequalities in its diagnosis. Such screening could be a first step towards more effective and equitable hypertension treatment and control.