Problems accessing health care and under-5 mortality: a pooled analysis of 50 low- and middle-income countries.

BACKGROUND: Access to health care remains suboptimal in low- and middle-income countries (LMICs) and continues to hinder survival in early childhood. We systematically assessed the association between problems accessing health care (PAHC) and under-five mortality (U5M). METHODS: Child mortality data on 724 335 livebirths came from the latest Demographic and Health Surveys of 50 LMICs (2013-2021). Reasons for PAHC were classified into three domains: 'money needed for treatment' (economic), 'distance to health facility' (physical), 'getting permission' or 'not wanting to go alone' (socio-cultural). Multivariable logistic regression was used to estimate the association between PAHC (any and by each type) and U5M. RESULTS: In our pooled sample, 47.3 children per 1000 livebirths died before age of 5, and 57.1% reported having experienced PAHC (ranging from 45.3% in Europe & Central Asia to 72.7% in Latin America & Caribbean). Children with any PAHC had higher odds of U5M (OR: 1.05, 95% CI: 1.02, 1.09), and this association was especially significant in sub-Saharan Africa. Of different domains of PAHC, socio-cultural PAHC was found to be most significant. CONCLUSIONS: Access to health care in LMICs needs to be improved by expanding health care coverage, building health facilities, and focusing more on context-specific socio-cultural barriers.

Spousal multimorbidity and depressive symptoms among older Indian couples: Do one's own health status and sex matter?

With the aging population, increases in non-communicable diseases that require chronic management pose a substantial economic and social burden to individuals with multimorbid conditions and their spousal caregivers. However, little is known about the crossover effect of spousal multimorbidity on mental health outcomes in the context of low- and middle-income countries, and whether it depends on one's own health status and sex. We examined the association between spousal multimorbidity and depressive symptoms using data on 6,158 older couples (12,316 individuals aged 60 years or above) from the Longitudinal Aging Study in India (LASI) 2017-18. Overall, 23.4% of the sample were multimorbid and 27.0% reported having depressive symptoms in the past week. Multivariable logistic regression models showed that spousal multimorbidity was associated with depressive symptoms, even after accounting for one's own multimorbidity status (OR: 1.23; 95% CI: 1.06-1.44). However, this association varied by sex. Among males, their own multimorbidity status was associated with 60% higher odds of having depressive symptoms (OR: 1.60; 95% CI: 1.28-2.00), but spousal multimorbidity was not. Furthermore, for males, the association between spousal multimorbidity and depressive symptoms was contingent upon the presence of their own multimorbidity. Among females, spousal multimorbidity was significantly associated with depressive symptoms, regardless of their own multimorbidity status. Our findings indicate that interventions to promote healthy aging should expand the formal caregiving system and consider family-based approaches to minimize the crossover health consequences of chronic morbidity in conjugal relationships, especially for females.

An environmental justice analysis of air pollution in India.

Due to the lack of timely data on socioeconomic factors (SES), little research has evaluated if socially disadvantaged populations are disproportionately exposed to higher PM2.5 concentrations in India. We fill this gap by creating a rich dataset of SES parameters for 28,081 clusters (villages in rural India and census-blocks in urban India) from the National Family and Health Survey (NFHS-4) using a precision-weighted methodology that accounts for survey-design. We then evaluated associations between total, anthropogenic and source-specific PM2.5 exposures and SES variables using fully-adjusted multilevel models. We observed that SES factors such as caste, religion, poverty, education, and access to various household amenities are important risk factors for PM2.5 exposures. For example, we noted that a unit standard deviation increase in the cluster-prevalence of Scheduled Caste and Other Backward Class households was significantly associated with an increase in total-PM2.5 levels corresponding to 0.127 µg/m3 (95% CI 0.062 µg/m3, 0.192 µg/m3) and 0.199 µg/m3 (95% CI 0.116 µg/m3, 0.283 µg/m3, respectively. We noted substantial differences when evaluating such associations in urban/rural locations, and when considering source-specific PM2.5 exposures, pointing to the need for the conceptualization of a nuanced EJ framework for India that can account for these empirical differences. We also evaluated emerging axes of inequality in India, by reporting associations between recent changes in PM2.5 levels and different SES parameters.

Small Area Geographic Estimates of Cardiovascular Disease Risk Factors in India.

Importance: With an aging population, India is facing a growing burden of cardiovascular diseases (CVDs). Existing programs on CVD risk factors are mostly based on state and district data, which overlook health disparities within macro units. Objective: To quantify and geovisualize the extent of small area variability within districts in CVD risk factors (hypertension, diabetes, and obesity) in India. Design, Setting, and Participants: This cross-sectional study analyzed nationally representative data from the National Family Health Survey 2019-2021, encompassing individuals aged 15 years or older, for hypertension (n = 1 715 895), diabetes (n = 1 807 566), and obesity (n = 776 023). Data analyses were conducted from July 1, 2022, through August 1, 2023. Exposures: Geographic units consisting of more than 30 000 small areas, 707 districts, and 36 states or Union Territories across India. Main Outcomes and Measures: For primary outcomes, CVD risk factors, including hypertension, diabetes, and obesity, were considered. Four-level logistic regression models were used to partition the geographic variability in each outcome by state or Union Territory (level 4), district (level 3), and small area (level 2) and compute precision-weighted small area estimates. Spatial distribution of district-wide means, within-district small area variability, and their correlation were estimated. Results: The final analytic sample consisted of 1 715 895 individuals analyzed for hypertension (mean [SD] age, 39.8 [17.3] years; 921 779 [53.7%] female), 1 807 566 for diabetes (mean [SD] age, 39.5 [17.2] years; 961 977 [53.2%] female), and 776 023 for obesity (mean [SD] age, 30.9 [10.2] years; 678 782 [87.5%] women). Overall, 21.2% of female and 24.1% of male participants had hypertension, 5.0% of female and 5.4% of men had diabetes, and 6.3% of female and 4.0% of male participants had obesity. For female participants, small areas (32.0% for diabetes, 34.5% for obesity, and 56.2% for hypertension) and states (30.0% for hypertension, 46.6% for obesity, and 52.8% for diabetes) accounted for the majority of the total geographic variability, while districts accounted for the least (13.8% for hypertension, 15.2% for diabetes, and 18.9% for obesity). There were moderate to strong positive correlations between district-wide mean and within-district variability (r = 0.66 for hypertension, 0.94 for obesity, and 0.96 for diabetes). For hypertension, a significant discordance between district-wide mean and within-district small area variability was found. Results were largely similar for male participants across all categories. Conclusions and Relevance: This cross-sectional study found a substantial small area variability, suggesting the necessity of precise policy attention specifically to small areas in program formulation and intervention to prevent and manage CVD risk factors. Targeted action on policy-priority districts with high prevalence and substantial inequality is required for accelerating India's efforts to reduce the burden of noncommunicable diseases.

Patterns in Child Health Outcomes Before and After the COVID-19 Outbreak in India.

This cross-sectional study examines prepandemic-to-postpandemic changes in mortality, nutrition and feeding practices, anthropometry, vaccination, and other measures in a sample of children from the Indian National Family Health Survey.

Small area variations in low birth weight and small size of births in India.

The states and districts are the primary focal points for policy formulation and programme intervention in India. The within-districts variation of key health indicators is not well understood and consequently underemphasised. This study aims to partition geographic variation in low birthweight (LBW) and small birth size (SBS) in India and geovisualize the distribution of small area estimates. Applying a four-level logistic regression model to the latest round of the National Family Health Survey (2015-2016) covering 640 districts within 36 states and union territories of India, the variance partitioning coefficient and precision-weighted prevalence of LBW (<2.5 kg) and SBS (mother's self-report) were estimated. For each outcome, the spatial distribution by districts of mean prevalence and small area variation (as measured by standard deviation) and the correlation between them were computed. Of the total valid sample, 17.6% (out of 193,345 children) had LBW and 12.4% (out of 253,213 children) had SBS. The small areas contributed the highest share of total geographic variance in LBW (52%) and SBS (78%). The variance of LBW attributed to small areas was unevenly distributed across the regions of India. While a strong correlation between district-wide percent and within-district standard deviation was identified in both LBW (r = 0.88) and SBS (r = 0.87), they were not necessarily concentrated in the aspirational districts. We find the necessity of precise policy attention specifically to the small areas in the districts of India with a high prevalence of LBW and SBS in programme formulation and intervention that may be beneficial to improve childbirth outcomes.