Journal of Epidemiology and Community Health

BackgroundDrowning remains a major global public health challenge. This study examined whether the timing and trajectories of urbanisation--beyond the current built environment--are associated with subnational drowning mortality. MethodsWe linked satellite-derived measures of built-environment change (GHSL), population crowding (WorldPop), surface water exposure (JRC Global Surface Water), and infrastructure proxies (VIIRS/DMSP nighttime lights) to GBD 2021 drowning mortality estimates across 203 ADM1 regions in 12 countries (2006-2021; 3,248 region-year observations). Temporal predictors captured recent expansion, development "newness" ([≤]10-year built share), acceleration/volatility, and a crowdingxgrowth interaction. We screened predictors using LASSO (10-fold cross-validation) and fitted mixed-effects models with region random intercepts. Distributed-lag models tested temporal precedence and development age, and income-stratified models assessed heterogeneity. ResultsAdding temporal predictors improved fit beyond contemporaneous built-environment measures ({Delta}AIC=177; {Delta}BIC=147). In adjusted models, crowdingxgrowth was strongly positively associated with drowning mortality, and a higher share of recent development was associated with higher mortality. Lag models showed a development age gradient: older built environment was most protective. Associations differed by income group, with several key coefficients reversing sign across strata. DiscussionDrowning mortality appears shaped by development histories as well as present-day conditions, with risk concentrated in rapidly changing, dense settings and the newest built environments. Cross-context heterogeneity suggests mechanisms and prevention priorities are unlikely to be uniform. ConclusionsDevelopment timing and trajectories help explain subnational drowning mortality beyond current built form alone. Prevention and planning should prioritise transition-period safety strategies in newly developing and rapidly densifying areas.

Abstract Importance Stigma and discrimination against transgender and gender-diverse people are prevalent across many settings and may contribute to substantial health disparities. Objective To synthesize global evidence on the prevalence of stigma, discrimination, and resilience among transgender (trans) and gender-diverse adults. Data Sources A systematic search was conducted in PubMed, Embase, CINAHL, Cochrane Central, LILACS, and PsycInfo for articles published between January 1, 2010 and January 2, 2023. This database search was supplemented by grey literature and secondary reference searches. Article Selection Studies were eligible if they presented primary quantitative data on prevalence of stigma, discrimination, and/or resilience among trans and gender-diverse adults (aged 18 and over), with no restrictions on study design, language, or geographic region. Data Extraction and Synthesis Two independent reviewers extracted data using standardized forms, with discrepancies resolved by consensus. The JBI Critical Appraisal Checklist for Prevalence Articles was used to assess risk of bias. Random effects meta-analysis was conducted for dichotomous prevalence measures using inverse variance weighting and logit transformation; non-dichotomous prevalence data were summarized descriptively. Main Outcomes and Measures Outcomes included prevalence estimates for various forms of stigma (anticipated, perceived, internalized, and experienced), discrimination in legal/institutional settings (housing, healthcare, employment, police/prison), and resilience. Results A total of 97 articles, with data from 72,158 unique trans and gender-diverse participants across 26 countries, met inclusion criteria. Studies showed moderate levels of anticipated stigma, perceived stigma, and internalized stigma. Meta-analyses of 36 studies provided pooled estimates of discrimination prevalence across multiple domains: 21.4% in housing (e.g., eviction, rental denial), 24.6% in healthcare (e.g., denial of care, mistreatment), 32.8% in employment (e.g., hiring bias, workplace harassment), and 39.1% in police/prison settings (e.g., profiling, mistreatment). High heterogeneity was observed across studies, reflecting regional and methodological differences. Resilience scores ranged from moderate to high, indicating variation within trans and gender-diverse communities. Conclusions and Relevance This systematic review and meta-analysis found that stigma and discrimination against trans and gender-diverse adults are pervasive globally. Variation in stigma and discrimination across settings and regions underscores the need for targeted interventions and policy reforms. Funding World Health Organization through a grant from the Elton John AIDS Foundation and the Bill and Melinda Gates Foundation.

Background. Vietnam's disease burden has shifted from communicable, maternal, neonatal, and nutritional (CMNN) causes to non-communicable diseases (NCDs), but the tempo, drivers, and regional positioning of this transition have not been jointly quantified. We characterised Vietnam's epidemiological transition 1990-2023 against ten Southeast-Asian (SEA) peers. Methods. Using Global Burden of Disease 2023 data, we computed joinpoint-regression AAPC with 95% CI (BIC-penalised, up to three break-points) for age-standardised DALY rates and cause-composition shares. We applied Das Gupta three-factor decomposition to 1990-2023 absolute DALY change (population-size, age-structure, age-specific-rate effects) and benchmarked Vietnam's NCD share against an SDI-conditional peer trajectory via leave-one-out quadratic regression. Premature mortality was quantified as WHO 30q70 under both broad NCD and strict SDG 3.4.1 definitions, using Chiang II life-table adjustment identically across all eleven countries. Findings. The CMNN age-standardised DALY rate fell from 13,295.9 to 4,022.1 per 100,000 (AAPC -4.63%/year; 95% CI -4.80 to -4.46); the NCD rate fell only from 21,688.2 to 19,282.8 (AAPC -0.37; -0.45 to -0.30). NCD share of total DALYs rose from 52.99% to 70.67% (+17.67 pp; AAPC +1.09). Vietnam ranked fourth of eleven SEA countries in 2023 (up from sixth in 1990) and sat 5.3% above the SDI-expected trajectory. Das Gupta decomposition attributed the +10.63 million NCD DALY increase to population growth (+6.26 M) and ageing (+6.08 M); rate change removed only 1.71 M. Premature NCD mortality fell from 25.02% to 21.80% (broad, 12.9% reduction) and from 22.17% to 19.50% (SDG 3.4.1, 12.0%; Vietnam sixth of eleven) - far short of the SDG 3.4 one-third-reduction target. Interpretation. Vietnam has entered a disability- and ageing-dominated NCD phase. Meeting SDG 3.4 by 2030 requires population-scale primary prevention sized to demographic momentum.

Objectives Concerns about COVID-19 were a key driver of infection-prevention behaviour during the pandemic. The aim of this study was to gain an in-depth longitudinal understanding of the type and frequency of concerns experienced throughout the first two years of the COVID-19 pandemic. Design Content analysis of qualitative descriptions provided in a prospective longitudinal online survey as part of the COVID-19 UK Public Experiences (COPE) Study. Method At baseline (March/April 2020), when the UK entered its first national lockdown, 11,113 adults completed the COPE survey. Follow-up surveys were conducted at 3, 12, 18 and 24 months. Participants were recruited via the HealthWise Wales research registry and social media. Baseline surveys collected demographic and health data, and all waves included an open-ended question about COVID-19 concerns. Content analysis was used to identify the type and frequency of concerns at each time point. Results A total of 41,564 open-text responses were coded into six categories: personal harm (n=16,353), harm to others (n=11,464), social/economic impact (n=6,433), preventing transmission (n=4,843), government/media (n=1,048), and general concerns (n=1,423). The proportion of respondents reporting any concern declined from 75.3% at baseline to 65.8% at 24 months. Over time, concerns about personal harm increased (baseline 41.8% vs. 24-months 52.7%) whereas concerns about harm to others decreased (baseline 48.5% vs. 24-months 28.6%). Concerns about harm were also expressed in relation to clinical vulnerability, lack of trust in government/media, and perceived lack of adherence by others. These were balanced against concerns about wider social and economic impacts of restrictions. Conclusions Public concerns about COVID-19 evolved substantially over the first two years of the pandemic, reflecting changing perceptions of risk and responsibility. Monitoring concerns longitudinally is vital to help guide effective communication and behavioural interventions during future pandemics.

Socioeconomic inequalities in health and well-being are a major public health concern, particularly in ageing populations. Education is a key determinant shaping multiple aspects of health outcomes. We used cross-sectional data from wave 9 of the German sample (n=4,148) of the Survey of Health, Ageing and Retirement in Europe (SHARE) to test whether formal education is associated with well-being in later adulthood, with health literacy, self-rated health, and preventive health behaviours as possible mediators. Our results showed that education was positively associated with greater well-being, but only via indirect pathways. Specifically, self-rated health, health literacy, and fruit and vegetable consumption mediated the relationship between education and well-being accounting for 54.7, 24.7, and 12.6 percent of the total effect, respectively. In addition, there were significant positive correlations between education and health literacy, as well as high-intensity physical activity, daily fruit and vegetable consumption, more preventive health check-ups, and less smoking. In contrast, alcohol consumption was more common among those with higher levels of education. All health behaviours and health literacy were correlated directly or indirectly (i.e., mediated by health) with well-being. These findings highlight the importance of examining indirect pathways linking education to well-being in later life. Interventions aimed at improving health literacy and promoting healthy behaviours may help reduce educational inequalities in quality of life among older adults.

BackgroundWomens autonomy in healthcare decision-making has become one of the most critical yet inequitably distributed determinants of health outcomes, gender equity, and sustainable development worldwide. In Northern Nigeria, the presence of ethnic and socio-cultural inequality is frequently concealed by the aggregated statistics of a region. MethodsThis cross-sectional secondary analysis utilized the 2024 Nigeria Demographic and Health Survey. The sample included 9,998 married women (15-49 years) identifying as Hausa, Fulani, or Kanuri in Northern Nigeria. Healthcare autonomy was categorized as husband/partner alone, respondent alone, or joint decision-making. Analysis included weighted descriptive statistics, Rao-Scott adjusted chi-square tests for residential associations, and complex sample multinomial logistic regression to identify multivariable correlates while adjusting for sampling weights, strata, and clusters. ResultsMean age was 30.38 years. Most participants lacked formal education (69.6%) and resided in rural areas (72.0%). Husband-only decision-making predominated (72.6%), while 22.5% reported joint and 4.9% independent autonomy. Joint decision-making was significantly higher in urban (33.3%) than rural areas (18.3%; Adjusted F=50.892, p<0.001). In adjusted models (Reference: Kanuri), Hausa and Fulani women had substantially lower odds of joint decision-making relative to husband-only outcomes. Rural residence correlated with lower odds of both independent and joint agency. Notably, wealth status was not a significant predictor after adjustment (p > 0.05). ConclusionsEthnicity and residence are robust determinants of healthcare autonomy among women in Northern Nigeria, persisting regardless of education or wealth. This "socio-cultural paradox" suggests that economic interventions alone are insufficient. Policies must complement socioeconomic approaches with culturally responsive strategies addressing household power dynamics and entrenched social norms.

BackgroundIn England, the burden of respiratory infections varies by ethnicity, contributing to health inequalities, but the role of additional demographic factors remains underexplored. We quantified how differences in social mixing and demographic characteristics between ethnic groups cause inequalities in transmission dynamics. MethodsWe analysed the association between the ethnicity and the number of contacts of 12,484 participants in the 2024-2025 Reconnect social contact survey, using a negative binomial regression model. We simulated respiratory pathogen epidemics using a compartmental model stratified by age, ethnicity, and contact levels, at a national level and in major cities in England. FindingsAfter adjusting for demographic variables, participants of Black and Mixed ethnicities had more contacts than those of White ethnicity (rate ratios (RR): 1.18 [95% Credible Interval (CI): 1.11-1.26], and 1.31 [95% CI: 1.14-1.52]). Participants of Asian ethnicity had fewer contacts (RR: 0.85 [95% CI: 0.79-0.91]). In national-level simulations, individuals of White ethnicity had the lowest attack rates due to demographic differences and mixing patterns. Local demographic structures changed simulated dynamics: attack rates in individuals of Black and Mixed ethnicities were approximately double those of White ethnicity in Birmingham, but less than 60% higher in Liverpool. InterpretationDemographic characteristics and mixing patterns create inequalities in transmission dynamics between ethnicities, while local demographic characteristics and pathogen infectiousness change the expected relative burden. To ensure mitigation strategies are effective and equitable, their evaluation must explicitly account for inequalities arising from local context. FundingMedical Research Council, National Institute for Health and Care Research, Wellcome Trust Research in context Evidence before this studyWe searched PubMed for population-based studies quantifying differences in respiratory infections between ethnic groups, up to 1 April 2026, with no language restrictions. Keywords included: (respiratory pathogens OR influenza OR COVID-19) AND (ethnic* OR race) AND (inequ*) AND (compartmental model OR incidence rate ratio OR hazard ratio). We excluded studies that focused on non-respiratory pathogens (e.g. looking at consequences of COVID-19 on incidence of other pathogens). A population-based cohort study showed that influenza infection risk was higher in South Asian, Black, and Mixed ethnic groups compared to White ethnicity in England. Another population-based cohort study highlighted that during the first wave of COVID-19 in England, the South Asian, Black, and Mixed ethnic groups were more likely to test positive and to be hospitalised than the White ethnic group. Census data in England showed that the distributions of age, household size, household income and employment status differed between ethnic groups, and the recent Reconnect social contact surveys highlighted the impact of each demographic factor on the participants number of contacts. Added value of this studyOur study shows that social contact patterns, mixing, and demographic structure all lead to unequal infection risk between ethnic groups in respiratory pathogen epidemics. Using the largest available social contact survey in England, we show that both the average number of contacts and the proportion of high-contact individuals varied by ethnic group, even after adjusting for participants demographics. These differences, together with mixing patterns and age structure, led to lower expected incidence among individuals of White ethnicity than in all other ethnic groups in simulated outbreaks. The level of inequality between ethnic groups changed when we used different values of pathogen transmissibility. Finally, as ethnic composition and population structure differ between cities in England, our results show differences in expected inequalities at a local level. Implications of all the available evidenceInequalities in infection risk between ethnic groups are context- and pathogen-dependent. They arise from both local population structure and contact patterns. Detailed information on mixing between groups and population structure is needed to accurately measure group-specific infection risk. These findings indicate that public health interventions based only on national-level estimates conceal regional variation in risk and may ultimately increase inequalities. Public health interventions need to be tailored to local contexts to be equitable and effective. Finally, our findings provide a foundation for understanding the progression from infection-risk inequalities to disparities in disease presentation and clinical outcomes.

Background Individuals experiencing or at risk of homelessness face substantial barriers to preventive eye care that are poorly addressed by standard service models. Interdisciplinary optometry-social work collaboration offers a rights-based approach to improving engagement and continuity of care. Methods A convergent mixed-methods study was conducted between February and August 2024 at a multidisciplinary community centre. Clients experiencing or at risk of homelessness received integrated optometry and social work assessment and were prioritised as high, medium, or low based on combined clinical and social risk. Social work follow-up was guided by the Triple Mandate and W-Questions framework. Quantitative data were summarised using mean (SD), median [IQR], or n (%). Qualitative case notes were analysed using content analysis with inductive coding and secondary review for consistency. Results A total of 165 clients had priority categories coded (high: 68; medium: 47; low: 154). Demographic data were available for 132 clients (60% male; mean age 49.5 years [SD 16]); 27% had not completed high school, 89% reported weekly income below AUD 1000, and 28% had vision impairment. Two hundred forty-five case-note entries were consolidated into 146 unique records. SMS (46%) and phone calls (38%) were the most documented contact methods, although only 21% of calls were answered; missed calls (13%) and disconnected numbers (7%) were common. Multi-modal contact was more frequently documented for higher-priority clients. Appointment assistance was the most recorded facilitator (71%), while rights-based supports, including interpreter and transport assistance, were infrequently documented (<=5%). Qualitative analysis identified unstable communication, reliance on informal supports, and service fragmentation as key influences on recall outcomes. Conclusion This study supports an interdisciplinary, rights-based optometry-social work model to address barriers to preventive eye care among people experiencing or at risk of homelessness. Embedding structured handovers and tiered recall processes within community-based services may strengthen continuity and accountability for high-priority clients. Future implementation should evaluate outcomes related to equity of reach, service integration, and sustained engagement in care.

Objective To analyse sociodemographic determinants of maternal health indicators in Kenyas conflict-affected regions. Methods A cross-sectional secondary analysis of the 2022 Kenya Demographic and Health Survey (KDHS) was conducted. Conflict-affected counties were identified using ACLED (>25 fatalities). The sample included 1,060 women aged 15-49 years. Outcomes were adequate antenatal care (ANC 4+), facility delivery, and skilled birth attendance (SBA). Predictors included age, education, wealth, employment, residence, and county; intimate partner violence was adjusted for. Weighted descriptive statistics, chi-square tests, and multivariable logistic regression were applied (p<0.05). Results Six counties met conflict criteria. While 90.2% of women attended at least one ANC visit, only 53.5% achieved ANC 4+. Facility delivery and SBA were 68.2% and 72.2%, respectively. Adolescents (15-19) were least likely to attain adequate ANC; women aged 20-24 had higher odds (aOR=1.83; 95% CI: 1.01-3.34). Education strongly predicted outcomes: higher education increased ANC 4+ (aOR=2.74; 95% CI: 1.19-6.34) and facility delivery (aOR=2.72; 95% CI: 1.15-6.47). Wealth showed strong gradients: middle quintile increased facility delivery (aOR=5.50; 95% CI: 2.14-14.14), while richer quintile increased SBA (aOR=11.04; 95% CI: 2.06-59.25). Rural residence reduced facility delivery (aOR=0.32) and SBA (aOR=0.22). County disparities persisted. IPV was not independently associated. Conclusion Maternal health indicators in conflict-affected Kenya follow a marked inequity gradient. Adolescents, rural residents, and socioeconomically disadvantaged women are most excluded. Strengthening adolescent ANC continuity, reducing rural access barriers, and investing in education and economic empowerment are critical for improving outcomes.

ObjectiveThere is little longitudinal research investigating links between violence exposure and mental disorders among children in low- and middle-income countries (LMICs), despite high rates of violence. We examined cross-sectional and longitudinal violence-mental health associations among children in a large South African birth cohort, the Drakenstein Child Health Study, including direct clinical interviews capturing childrens mental disorders. MethodIn this birth cohort (N=974), we assessed lifetime violence exposure and four subtypes (witnessed community, community victimization, witnessed domestic, domestic victimization) at ages 4.5 and 8-years via caregiver reports. At 8-years, caregivers completed the Child Behaviour Checklist; and psychiatric disorders were assessed using the Mini-International Neuropsychiatric Interview for Children and Adolescents, a self-report measure. We tested for associations using linear/logistic regressions, adjusted for confounders. ResultsMost children (91%) had experienced violence by 8-years. Cross-sectionally, total violence exposure was associated with total (B =0.49 [95% CI 0.32, 0.66]), internalizing (0.32 [0.17, 0.47]), and externalizing problems (0.46 [0.31, 0.61]), and with increased odds of disorder at 8 years (aOR=1.09 [1.05, 1.13]). Longitudinally, total violence exposure up to 4.5-years was associated with total (B=0.27 [0.03, 0.52]), internalizing (0.24 [0.04. 0.44]), and externalizing scores (0.23 [0.008, 0.45]) at 8-years, but not with increased risk of psychiatric disorders. The strongest and most consistent associations were observed for domestic versus community violence subtypes. ConclusionOur strong cross-sectional but weaker longitudinal findings suggest that recent violence exposures may be more critical than early exposures for childrens mental health. Longitudinal exploration of other violence-affected LMIC populations is urgently needed.

Drowning remains a major global public health challenge, yet how built environment characteristics shape population-level drowning risk remains poorly understood. This study linked satellite-derived built environment data to subnational drowning mortality estimates across 203 regions in 12 countries from 2006-2021. It found that built environment associations with drowning mortality are complex, non-linear, and shaped by development context. Urban extent was strongly protective, while built area near water showed protection overall but increased risk when combined with high population crowding. Almost all drowning mortality variance occurred between regions rather than within regions over time, indicating risk is predominantly determined by place-based characteristics. Income-stratified analyses revealed profound heterogeneity: crowding was protective in low-to middle-income settings but near-null in high-income regions, while waterfront development captured very different realities across contexts. These findings highlight the importance of tailoring drowning prevention strategies to local built environment configurations and development contexts.

Knowing the mortality rates associated with infection by a pathogen is essential for effective preparedness and response. Here, harnessing the flexibility of a Bayesian approach, we produce an estimate of the Infection Fatality Ratio (IFR) for A(H5N1) conditional on explicit assumptions, and quantify the uncertainty thereof. We also apply the method to first-wave COVID-19 data up to March 2020, demonstrating the estimates that could be obtained were the model available then. Our analysis uses World Development Indicators (WDI) from the World Bank, the A(H5N1) WHO confirmed cases and deaths tracker by country (2003-2024), and COVID-19 cases and deaths data from John Hopkins University (January and February 2020). Since infectious disease dynamics are typically influenced by local socio-economic factors rather than political borders, individual countries are placed within clusters of countries sharing similar WDIs relevant to respiratory viral diseases, with clusters derived by performing Hierarchical Clustering. To estimate the IFR, we fit a Negative Binomial Bayesian Hierarchical Model for A(H5N1) and COVID-19 separately. We explicitly modelled key unobserved parameters with informative priors from expert opinion and literature. By modelling underreporting, our analysis suggests lower fatality (15.3%) compared to WHO's Case Fatality Ratio estimate (54%) on lab-confirmed cases. However, credible intervals are wide ([0.5%, 64.2%] 95% CrI). Therefore, good preparedness for a potential A(H5N1) pandemic implies adopting scenario planning under our central estimate, as well as for IFRs as high as 70%. Our approach also returns a COVID-19 IFR estimate of 2.8% with [2.5%, 3.1%] 95% CrI which is consistent with literature.

BackgroundAccess to safe, equitable, and affordable surgical and anesthesia care is critical to reducing the burden of surgical diseases in Africa. To understand the state of access in South Sudan, we conducted a baseline assessment of surgical services in Central Equatoria State (CES) in May 2024. ObjectivesThis study aimed to survey public healthcare facilities in CES capable of providing essential surgical services. We used the capacity to perform cesarean section, laparotomy, and open fracture management--Bellwether procedures--as a proxy for assessing workforce, infrastructure, financing, information management, and service delivery. MethodsWe used a validated and contextualized Surgical Assessment Tool developed by the Harvard Program on Global Surgery and Social Change and the World Health Organization. Data were collected at the facility level and summarized descriptively using percentages, means (standard deviations), medians (minimum, maximum), and visualized in graphs, charts, and tables. ResultsAll three public health facilities assessed could perform Bellwether procedures for their catchment populations. However, workforce availability, financing, and surgical infrastructure were major constraints. The surgical workforce density was 2.27 surgical, anesthesia, and obstetric specialists per 100,000 population. Specialized procedures--such as repair of cleft lip and palate, clubfoot, and hydrocephalus shunt--were unavailable at all sites. None had magnetic resonance imaging (MRI) machines. The total average annual facility budget was $918,850, ranging from $3,960 to $800,000 at the teaching hospital--insufficient for proper operations. ConclusionWhile Bellwether procedures are routinely performed, access to quality and affordable care is compromised by deficits in workforce, financing, and infrastructure. We recommend that the Ministry of Health scale this survey nationally and develop a surgical policy and strategic plan focused on improving infrastructure, workforce, and financing for surgical and anesthesia care in South Sudan.

Background: The increasing availability of routinely collected health data offers new opportunities for population-level research, yet access to comprehensive, linked, and standardised datasets remains limited. We describe EST-Health-30, a large-scale, population-representative health data resource from Estonia. Methods: EST-Health-30 comprises a random 30% sample of the Estonian population (~500,000 individuals), with longitudinal data from 2012 to 2024 and annual updates planned through 2026. Individual-level records are linked across five nationwide databases, including electronic health records, health insurance claims, prescription data, cancer registry, and cause of death records. A privacy-preserving hashing approach ensures consistent cohort inclusion over time while maintaining pseudonymisation. All data are harmonised to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (version 5.4) using international standard vocabularies. Data quality was assessed using established OMOP-based validation frameworks. Results: The dataset contains rich multimodal information on diagnoses, procedures, laboratory measurements, prescriptions, free-text clinical notes, healthcare utilisation, and costs, with high population coverage and longitudinal depth. Data quality assessment showed high completeness and consistency, with 99.2% of applicable checks passing. The age-sex distribution closely reflects the national population, supporting representativeness, though coverage is marginally below the target 30% (29.2%), primarily attributable to recent immigrants without health system contact. The dataset enables construction of detailed clinical cohorts, analysis of disease trajectories, and evaluation of healthcare utilisation and outcomes across the life course. Conclusions: EST-Health-30 is a comprehensive, standardised, and population-representative real-world data resource that supports epidemiological, clinical, and methodological research. Its alignment with the OMOP CDM facilitates reproducible analytics and participation in international federated research networks, while secure access infrastructure ensures compliance with data protection regulations.

Background: Nigeria bears one of the highest maternal mortality burdens globally, with skilled birth attendance (SBA) remaining critically low in many regions. Understanding the independent determinants of SBA is essential for designing targeted interventions. Methods: This cross sectional study analyzed 21,465 births from the 2018 Nigeria Demographic and Health Survey (NDHS), a nationally representative household survey using stratified two stage cluster sampling. SBA was defined as delivery attended by a doctor, nurse, midwife, or auxiliary midwife. Multivariable logistic regression was used to estimate adjusted odds ratios (aOR) with 95% confidence intervals for the associations between SBA and maternal education, household wealth, place of residence, geopolitical region, maternal age, parity, and antenatal care (ANC) utilization, after accounting for confounding. Results: The overall prevalence of SBA was 44.9%. In the fully adjusted model, higher education (aOR = 7.01, 95% CI: 5.68-8.67), richest wealth quintile (aOR = 6.27, 95% CI: 5.27-7.46), and attending [&ge;]4 ANC visits (aOR = 3.80, 95% CI: 3.51-4.11) were the strongest independent predictors of SBA. Regional inequalities were pronounced, with SBA prevalence ranging from 17.7% in the North West to 85.6% in the South West. Crude effect estimates for education and wealth were substantially attenuated after adjustment, indicating large confounding by correlated socioeconomic factors. Conclusions: Maternal education, household wealth, ANC utilization, and geopolitical region are independent determinants of SBA in Nigeria. Scaling up ANC programs represents the most immediately actionable intervention, while long term gains require investment in girls' education and wealth equity. Targeted strategies for the northern regions are urgently needed. Keywords: skilled birth attendance, maternal mortality, Nigeria, DHS, antenatal care, logistic regression, health equity

IntroductionDrowning risk begins with water exposure, yet population-water relationships have rarely been quantified at scale using environmental measures. This study explored whether satellite-derived data was associated with subnational drowning mortality and whether associations differed by country income level. MethodsWe linked Global Burden of Disease (GBD 2021) age-standardised drowning mortality rates to satellite-derived exposures for 212 subnational regions across 12 countries (2006-2021; 3,392 region-years). Exposures were extracted via Google Earth Engine and standardised. Gamma-log generalised linear mixed models included region random intercepts and year fixed effects. Income-stratified models were estimated separately. Supplementary models assessed maritime vessel activity. ResultsNear-water population percentage was the strongest correlate of drowning (IRR 1.40; 95% CI 1.33-1.47). Permanent water coverage was protective (IRR 0.80; 0.73-0.88), as were nighttime lights (IRR 0.96; 0.95-0.97) and hot days [&ge;]30{degrees}C (IRR 0.95; 0.92-0.99). Mean temperature (IRR 1.17; 1.11-1.23) and precipitation (IRR 1.03; 1.01-1.04) were positively associated. Near-water effects were consistent across income strata (LIC 1.25; MIC 1.31; HIC 1.24), while other predictors showed weak or inconsistent within-strata associations. Vessel activity was modestly associated with drowning in Global Fishing Watch models (IRR 1.05; 1.01-1.09) but not in Synthetic Aperture Radar models. DiscussionSatellite-derived indicators can characterise drowning risk at scale, with population proximity to water emerging as a robust cross-context correlate. Protective associations for permanent water suggest landscape configuration may shape risk beyond proximity alone, highlighting geospatial datas value for targeting prevention where surveillance is limited.

ObjectivesRising temperatures are a major climate-related hazard for U.S. workers, increasing heat-related illness and a broad range of occupational injuries through indirect pathways often overlooked in economic evaluations. We examined the association between temperature and occupational injury and illness and quantified heat-attributable injuries (including illnesses) and costs in New York State. MethodsWe conducted a time-stratified case-crossover study of 591,257 workers compensation (WC) claims during the warm season (2016-2024). Daily maximum temperature was linked to injury date and county and modeled using natural cubic splines, with effect modification by industry and worker characteristics. ResultsInjury risk increased with temperature, becoming statistically significant at approximately 78{degrees}F. Relative to 65{degrees}F, injury odds increased to 1.06 (95% CI: 1.01-1.10) at 80{degrees}F, 1.12 (1.07-1.18) at 90{degrees}F, and 1.17 (1.11-1.23) at 95{degrees}F. Overall, 5.0% of claims (2,322 annually) were attributable to heat. At temperatures [&ge;]80{degrees}F, an estimated 1,729 excess injuries occurred annually, generating approximately $46 million in WC costs. An estimated $3.2 million to $36.1 million in medical expenditures were associated with incomplete claims, likely borne outside the WC system. ConclusionsThese findings demonstrate substantial economic costs not fully captured within WC and support workplace heat protections as a cost-containment strategy that can reduce health care spending and strengthen workforce resilience.

Background Childhood sensory and intellectual disabilities represent significant yet under-recognized barriers to learning and human capital development. This study analyzes prevalence and severity of these conditions among 149.3 million children aged 5-19 years across 25 countries in Latin America and the Caribbean (LAC) using Global Burden of Disease 2023 data. Methods We extracted GBD 2023 estimates for vision loss, hearing loss, and intellectual disability across 25 LAC countries, stratified by age, sex, and severity. Regional estimates were calculated using population-weighted averages. Severity distributions were compared with OECD countries to contextualize regional patterns. Results: These conditions are estimated to affected 9,282,921 children (6.22%; 95% UI: 5.89-6.54%). Hearing loss was predominant, affecting an estimated 5.42 million (3.63%, 3.41-3.86), with 87.6% mild-to-moderate. Intellectual disability estimated to affected 2.56 million (1.71%, 1.58-1.85), with 61.7% borderline-to-mild. Vision loss estimated to affected 1.30 million (0.87%, 0.79-0.96), with 89% that can be effectively addressed with spectacles. Prevalence increased with age across all conditions. Male predominance was consistent for intellectual disability (2.00% vs 1.42%). Annual economic cost totaled US$19.3-29.0 billion, while comprehensive interventions would require US$9.45-14.23 billion with benefit-cost ratios of 2:1 to 15:1. Conclusions The distribution of children across milder levels of difficulty underscores the opportunity for education and public health systems to provide timely and accessible support. With approximately 88% of sensory impairments addressable through established technologies, investments in inclusive services can yield strong social and economic returns.

Background Depressive symptoms among reproductive-aged women represent a major public health concern in low- and middle-income countries, yet systematic screening remains limited. In most population survey datasets, the low prevalence of depression results in severe class imbalance, which challenges conventional machine learning models. Therefore, we develop and evaluate a bagging-based ensemble machine learning framework to predict depressive symptoms among reproductive-aged women using highly imbalanced Bangladesh demographic and health survey (BDHS) 2022 data. Methods The sample comprised women aged 15-49 years drawn from BDHS 2022 data. Depressive symptoms were defined using the Patient Health Questionnaire (PHQ-9 [&ge;]10). Candidate predictors were drawn from sociodemographic, reproductive, nutritional, psychosocial, healthcare access, and environmental domains. Feature selection was performed using Elastic Net (EN), Random Forest (RF), and XGBoost model. Five classifiers (EN, RF, Support Vector Machine (SVM), K-nearest neighbors (KNN), and Gradient Boosting Machine (GBM)) were trained using both oversampling-based approaches and the proposed ensemble framework. Model performance was evaluated on an independent test set using accuracy, sensitivity, specificity, F1-score, and the normalized Matthews correlation coefficient (normMCC). Results Approximately 4.8% of women were identified with depressive symptoms. The proposed bagging ensemble framework consistently achieved more balanced predictive performance than oversampling-based models. Average normMCC improved from 0.540 (oversampling) to 0.557 (ensemble). RF and GBM ensembles demonstrated notable improvements in identifying depressive cases, while the EN ensemble achieved the highest overall performance and sensitivity. Threshold optimization yielded stable normMCC across models, indicating robust trade-offs between sensitivity and specificity. Conclusions Bagging-based ensemble learning provides a more robust and balanced approach than synthetic oversampling for predicting depressive symptoms in highly imbalanced population survey data. This approach has important implications for improving early identification and population-level mental health surveillance in resource-constrained settings.

Cardiovascular disease (CVD) remains the leading cause of mortality in the United States, despite being largely preventable through effective management of risk factors. This study evaluates the impact of Phase II cardiac rehabilitation (CR) on functional capacity and quality of life, using data from the Montana Outcomes Project Cardiac Rehabilitation Registry. Functional capacity improvements were assessed via the six-minute walk test (6MWT) and Dartmouth COOP questionnaire, with statistical analyses exploring the influence of CR session attendance, demographic factors, and referring diagnoses. Results demonstrated significant gains in 6MWT, with a mean improvement of 330.73 feet (p < .0001), and quality of life scores across all subgroups. A dose-response relationship was observed, indicating greater improvements with increased CR sessions (p < .0001), though diminishing returns were observed beyond 24-35 visits. Demographic factors and complex conditions influenced outcomes, underscoring the need for tailored strategies to enhance CR access and effectiveness. These findings highlight the critical role of CR in improving patient outcomes and emphasize the importance of addressing barriers to participation in underserved populations.