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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]

Introduction: Although India has made significant progress in institutional delivery after the implementation of the National Rural Health Mission under which the Janani Suraksha Yojana (JSY) is a sub-programme which played a vital role in the increase of institutional delivery in public facilities. Therefore, this paper aims to provide an understanding of the JSY coverage at the district level in India. Further, it tries to carve out the factors responsible for the regional disparity of JSY coverage at district levels. Methods: The study used the National Family Health Survey data, which is a cross-sectional survey conducted in 2015–16, India. The sample size of this study was 148,145 women aged 15–49 years who gave last birth in the institution during 5 years preceding the survey. Bivariate and multivariate regression analysis was used to fulfill the study objectives. Additionally, Moran's I statistics and bivariate Local Indicator for Spatial Association (LISA) maps were used to understand spatial dependence and clustering of JSY coverage. Ordinary least square, spatial lag and spatial error models were used to examine the correlates of JSY utilization. Results: The value of spatial-autocorrelation for JSY was 0.71 which depicts the high dependence of the JSY coverage over districts of India. The overall coverage of JSY in India is 36.4% and it highly varied across different regions, districts, and even socioeconomic groups. The spatial error model depicts that if in a district the women with no schooling status increase by 10% then the benefits of JSY get increased by 2.3%. Similarly, if in a district the women from poor wealth quintile, it increases by 10% the benefits of JSY also increased by 4.6%. However, the coverage of JSY made greater imperative to understand it due to its clustering among districts of specific states only. Conclusion: It is well reflected in the EAGs states in terms of spatial-inequality in service coverage. There is a need to universalize the JSY programme at a very individual level. And, it is required to revisit the policy strategy and the implementation plans at regional or district levels. [ABSTRACT FROM AUTHOR]

Background: Family caregivers are vital for long-term care for persons with serious health-related suffering in Kerala. Long-term caregiving and ageing may become burdensome and detrimental to patients and caregivers. We compared the caregiver burden and quality-of-life of ageing caregivers with younger caregivers. We also explored the palliative care nurses' perceptions of the family caregivers' issues. Methods: We did a mixed method study focusing on two groups: (i) three in-depth interviews and a cross-sectional survey among 221 caregivers of palliative care patients in five randomly selected panchayats (most peripheral tier of three-tier local self-government system in India concerned with governance of a village or small town) of Kollam district, Kerala, as part of development and validation of the Achutha Menon Centre Caregiver Burden Inventory; (ii) five in-depth interviews with purposively selected primary palliative care nurses as part of a study on local governments and palliative care. We used a structured interview schedule to collect cross-sectional data on sociodemographic and caregiving-related characteristics, caregiver burden, and health-related quality of life using the EuroQol EQ5D5L and interview guidelines on caregiver issues tailored based on participant type for qualitative interviews. Results: Older caregivers comprised 28.1% of the sample and had significantly poorer health and quality-of-life attributes. More senior caregivers experiencing caregiver burden had the lowest mean scores of 0.877 (Standard deviation (SD 0.066, 95% confidence intervals (CI) 0.854–0.899) followed by younger caregivers with high burden (0.926, SD 0.090, 95% CI 0.907–0.945), older caregivers with low burden (0.935, SD 0.058, 95% CI 0.912–0.958) and younger caregivers with low burden (0.980, SD 0.041, 95% CI 0.970–0.990). Caregivers faced physical, psychological, social, and financial issues, leading to a caregiver burden. The relationships between the palliative care nurses and family caregivers were complex, and nurses perceived caregiver burden, but there were no specific interventions to address this. Conclusion: In our study from Kollam, Kerala, three out of ten caregivers of palliative care patients were 60 years of age or older. They had significantly lower health-related quality of life, particularly if they perceived caregiver burden. Despite being recognized by palliative care nurses, caregiver issues were not systematically addressed. Further research and suitable interventions must be developed to target such problems in the palliative care programme in Kerala. [ABSTRACT FROM AUTHOR]

Background: The use of hygienic products, such as sanitary napkins, tampons, and menstrual cups, to absorb menstrual blood is vital for the health and well-being of adolescent girls in India. However, the degree of inequity in the use of such products among this subpopulation remains inadequately explored. To fill this critical knowledge gap, this study aims to investigate the spatiotemporal dynamics of hygienic product use among adolescent girls in India from 2015 to 2020. Methods: In this cross-sectional study, we analyzed data from 117,749 to 114,839 adolescent girls aged 15–19, obtained from two consecutive rounds of the National Family Health Survey (NFHS) conducted in India during 2015-16 and 2019-21. Our approach involved utilizing Erreygers' Concentration Index (ECI) and Concentration Curve to quantitatively assess and visually represent socioeconomic inequality in hygienic product usage. Additionally, we investigated the spatiotemporal variation in this inequality over the study period and decomposed the ECI to identify the key contributing factors. Results: The findings reveal that hygienic product usage among adolescent girls in India has increased by 13 percentage points (PP), from 37% in 2015-16 to 50% in 2019-21. This increase is also visible across all household wealth quintiles. However, the bottom quintiles experienced a greater rise (+ 15 to 16 PP) than the top quintile (+ 8 PP). During the study period, the ECI reduced marginally, from 0.48 in 2015-16 to 0.43 in 2019-21. However, the extent of this reduction varied across different states. The greatest reduction in ECI was recorded in Punjab (-0.23 points), Telangana (-0.16 points), and West Bengal (-0.14 points). In contrast, there were a number of states with high socioeconomic inequality (ECI > 0.30) in 2015-16, where inequality reduction was minimal (< 0.05 points) over the study period. This included more developed states of Kerala, Karnataka, Maharashtra and Gujarat and relatively less developed states of Odisha, Jharkhand, Chhattisgarh, Uttar Pradesh, and Assam. Some states, such as Bihar and Madhya Pradesh, recorded an increase in socioeconomic inequality over the study period, with ECI rising to 0.31 and 0.46 (highest in the country) in 2019-21. The decomposition analysis revealed that the inequality in using hygienic products was primarily explained by place of residence, exposure to mass-media, education, and region of residence. Conclusions: The findings suggest the need for targeted policies to reduce existing socioeconomic inequality in the usage of hygienic products among adolescent girls in India. Specifically, interventions should target regions with low use of hygienic products, economically disadvantaged groups, and poor and vulnerable populations. State-specific policies and programs are also necessary to address the disparities in socioeconomic inequality. Additionally, efforts to reduce inequality should address the underlying factors contributing to inequality. [ABSTRACT FROM AUTHOR]

Background: Increasing financial risk protection is a key feature of Universal Health Coverage and the path towards health for all. Publicly Funded Health Insurance Schemes (PFHIS) have been considered as one of the pathways to safeguard against financial shocks and potentially reduce Out-of-Pocket Expenditure (OOPE). The south Indian state of Kerala has roughly a decade-long experience in implementing PFHIS. To date, there have been very few assessments of the coverage of these schemes and their impact on expenditure. Aiming to fill this gap, we explored the extent of and inequalities in insurance coverage, as well as choice of providers, and median cost of hospitalization in Kerala among insured and uninsured individuals. Methods: A cross-sectional household survey was conducted in four districts of Kerala as part of a larger health systems research study from July–October 2019. We employed multistage random sampling to collect data from 13,064 individuals covering 3234 households in the catchment area of eight primary health care facilities. We used descriptive statistics, bivariate and multivariate analysis. We evaluated socioeconomic disparities using an absolute measure of inequality—the Slope Index of Inequality (SII) and a relative measure—the Relative Concentration Index (RCI). Results: A substantial proportion of our study respondents reported that they were covered by PFHIS (45.8%). Respondents belonging to lowest and middle wealth quintiles of household had significantly greater odds of being covered by insurance than respondents belonging to the richest wealth quintile. The negative magnitude of RCI [-16.8% (95%CI: -25.3, -8.4)] and SII [-21.5% (95%CI: -36.1, -7.0)] suggest a higher concentration of PFHIS coverage among the poor. Median OOPE for hospitalisation at private health facilities was INR 9000 (approx. USD 108.70) among those covered by PFHIS, whereas it was INR 10500 (approx. USD 126.82) at private health facilities among those not covered by insurance. Conclusion: While PFHIS seems to be appropriately targeting poorer populations, among the insured, OOPE for hospitalization persists. Among the uninsured, population subgroups with advantage are spending the greatest amount, raising questions about whether those facing relative disadvantage are forgoing care altogether or seeking care using cheaper, public avenues. Further policy action to more effectively reduce financial burden among left behind eligible populations under PFHIS will be essential to UHC progress in the state. [ABSTRACT FROM AUTHOR]

Background: Non-Communicable Diseases (NCDs) constitute a significant danger to the nation's public health system, both in terms of morbidity and mortality, as well as the financial burden they inflict. Kerala is undergoing an epidemiologic transition, which has significantly impacted the state's morbidity and mortality figures. For decades, the state has been putting in place myriad programs to reduce the burden of NCDs across population groups. Socioeconomic inequalities in NCD testing have been documented in India, although they are understudied in Kerala. The study aimed to estimate and characterize districtwise socioeconomic inequality in Blood Pressure (BP) and Blood Glucose (BG) testing. Methods: A cross-sectional household survey was conducted between July–October 2019 in Kasaragod, Alappuzha, Kollam and Thiruvananthapuram districts of Kerala, India. A total of 6383 participants aged 30 years and above were interviewed using multistage random sampling. Descriptive statistics were derived district-wise. We computed ratios, differences, equiplots, and Erreygers concentration indices for each district to measure socioeconomic inequality in BP and BG testing. Erreygers decomposition techniques were used to estimate the relative contribution of covariates to socioeconomic inequality. Results: There was a significant concentration of BP and BG testing favouring wealthier quintiles in Alappuzha, Kollam, and Thiruvananthapuram districts. The inequality in BP and BG testing was highest in Thiruvananthapuram (0.087 and 0.110), followed by Kollam (0.077 and 0.090), Alappuzha (0.083 and 0.073) and Kasaragod (0.026 and 0.056). Decomposition analysis revealed that wealth quintile and education contributed substantially to socioeconomic inequality in BP and BG testing in all four districts. It was also found that family history of NCDs significantly contributed to observed socioeconomic inequality in BP testing (29, 11, 16, and 27% in Kasaragod, Alappuzha, Kollam, and Thiruvananthapuram, respectively). Similarly, in BG testing, family history of NCDs substantially contributed to observed socioeconomic inequality, explaining 16–17% in Kasaragod, Alappuzha, Kollam, and Thiruvananthapuram respectively of the total inequality. Conclusion: While the magnitude of socioeconomic inequality in NCD risk factor testing did not appear to be very high in four Kerala districts, although levels were statistically significant in three of them. Greater exploration is needed on how education and caste contribute to these inequalities and their relationship to NCD risk factors such as family history. From such analyses, we may be able to identify entry points to mitigate inequalities in testing access, as well as burden. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity in primary care is a challenge not only for developing countries but also for low and medium income countries (LMIC). Health services in LMIC countries are being provided by both public and private health care providers. However, a critical knowledge gap exists on understanding the true extent of multimorbidity in both types of primary care settings. Methods: We undertook a study to identify multimorbidity prevalence and healthcare utilization among both public and private primary care attendees in Odisha state of India. A total of 1649 patients attending 40 primary care facilities were interviewed using a structured multimorbidity assessment questionnaire collecting information on 22 chronic diseases, medication use, number of hospitalization and number of outpatient visits. Result: The overall prevalence of multimorbidity was 28.3% and nearly one third of patients of public facilities and one fourth from private facilities had multimorbidity. Leading diseases among patients visiting public facilities included acid peptic diseases, arthritis and chronic back pain. No significant difference in reporting of hypertension and diabetes across the facilities was seen. Besides age, predictors of multimorbidity among patients attending public facilities were, females [AOR: 1.6; 95% CI 1.1–1.3] and non-aboriginal groups [AOR: 1.6; 95%CI 1.1–2.3] whereas, in private females [AOR: 1.6; 95%CI 1.1–2.4], better socioeconomic conditions [AOR 1.4; 95% CI 1.0–2.1] and higher educational status [primary school completed [AOR 2.6; 95%CI 1.6–4.2] and secondary schooling and above [AOR 2.0; 95%CI 1.1–3.6] with reference to no education were seen to be the determinants of multimorbidity. Increased number of hospital visits to public facilities were higher among lower educational status patients [IRR: 1.57; 95% CI 1.13–2.18] whereas, among private patients, the mean number of hospital visits was 1.70 times more in higher educational status [IRR: 1.70; 95%CI 1.01–3.69]. The mean number of medicines taken per day was higher among patients attending private hospitals. Conclusion: Our findings suggest that, multimorbidity is being more reported in public primary care facilities. The pattern and health care utilization in both types of settings are different. A comprehensive care approach must be designed for private care providers. [ABSTRACT FROM AUTHOR]

Background: This equity focused evaluation analyses change in inter-district inequity of maternal health services (MHS) in Karnataka state between 2006-07 & 2012-13, alongside association of MHS inequity with distribution of maternal deaths. Methods: Repeated cross-sectional analysis of inequity and decomposition was done on nine district level MHS indicators using Theil's T index. Data was obtained from population linked district level facility surveys and health information systems. Results: Inequity in births attended by skill birth attendants decreased the most (83.16%) among six other MHS indicators. Community provision of comprehensive emergency obstetric care strategy remained stagnant. Districts with higher complete antenatal care share and C-sections in public settings had lesser share of state's maternal deaths (R² = 0.29, p = 0.004). 5 districts suffered perpetual inequity of MHS with relatively greater burden of maternal deaths. Conclusion: First 6 years of national rural health mission increased coverage of MHS and decreased regional inequity albeit non-uniformly. Distribution of system driven interventions of complete ANC and C-sections appear to determine decrease of maternal mortality in Karnataka. [ABSTRACT FROM AUTHOR]

Background: Jharkhand, a state with substantial tribal population in Eastern India has very high rate of undernutrition. The study tries to understand the social determinants of inequities in under-nutrition (weight-for-age) among children aged less than 5 years, in Gumla District of the State. Methods: Cross sectional study of 1070 children from 32 villages of 4 Blocks of Gumla District. Results: 54.3 % (95 % CI 51.3-57.3) children were found to be underweight (less than -2SD), with insignificant difference between girls and boys. Multivariate analysis showed that poverty was the single most important predictor of undernutrition, where a child from the poorest quintile was 70 % more likely to be underweight (aOR 1.70, CI 1.13-2.57), compared to one from the least poor group (Quintile 5). While the difference in weight-for-age status between Scheduled Tribes and "OBC and other communities" was non-significant (95 % OR 1.12, CI 0.88-1. 42) in the study context; community disaggregated data revealed that there were large variations within the tribal community, and numerically smaller communities also ranked lower in wealth, and their children showed poorer nutritional status. Other factors like maternal education beyond matriculation level also had some bearing. Bivariate analysis showed that chances of a child being underweight (<-2SD) was 43 % more and being severely underweight (<-3SD) was 26 % more for mothers with less than 10 years of schooling compared to those who had attended school for more than 10 years. Educational attainment of mothers did not show any significant difference between tribal and non-tribal communities. Conclusion: Overall nutritional status of children in Gumla is very grim and calls for immediate interventions, with universal coverage. Risk was almost equal for both genders, and for tribal and non-tribal population, though within tribal communities, it was slightly higher for smaller tribal communities, calling for soft targeting. Comprehensive programme addressing poverty and higher education for girls would be important to overcome the structural barriers, and should be integral part of any intervention. The study highlights the importance of soft targeting vulnerable communities within the universal coverage of government programmes for better nutritional outcomes. [ABSTRACT FROM AUTHOR]

Introduction Despite the recognized importance of social determinants of health (SDH) in India, no compilation of the status of and inequities in SDH across India has been published. To address this gap, we assessed the levels and trends in major SDH in India from 1990 onwards and explored inequities by state, gender, caste, and urbanicity. Methods Household- and individual-level SDH indicators were extracted from national household surveys conducted between 1990 and 2011 and means were computed across population subgroups and over time. The multidimensional poverty index (MPI), a composite measure of health, education, and standard of living, was calculated for all three rounds of the National Family Health Survey, adjusting the methodology to generate comparable findings from the three datasets. Data from government agencies were analyzed to assess voting patterns, political participation, and air and water pollution. Results Changes in the MPI demonstrate progress in each domain over time, but high rates persist in important areas: the majority of households in India use indoor biomass fuel and have unimproved sanitation, and over one-third of households with a child under the age of 3 years have undernourished children. There are large, but narrowing, gender gaps in education indicators, but no measurable change in women's participation in governance or the labor force. Less than 25% of workers have job security and fewer than 15% have any social security benefit. Alarming rates of air pollution are observed, with particulate matter concentrations persistently above the critical level at over 50% of monitoring stations. Conclusions This assessment indicates that air pollution (indoor and outdoor), child undernutrition, unimproved sanitation, employment conditions, and gender inequality are priority areas for public policy related to SDH in India. [ABSTRACT FROM AUTHOR]