Sociodemographic and geographic variation in mortality attributable to air pollution in the United States.

There are large differences in premature mortality in the USA by racial/ethnic, education, rurality, and social vulnerability index groups. Using existing concentration-response functions, particulate matter (PM2.5) air pollution, population estimates at the tract level, and county-level mortality data, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in mortality attributable to PM2.5 were consistently more pronounced between racial/ethnic groups than by education, rurality, or social vulnerability index, with the Black American population having by far the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic White population was attributable to PM2.5 in the years 2000 to 2011.

The impact of climate change and related extreme weather on people with limb loss.

The human health consequences of climate change and extreme weather events are well documented. Published literature details the unique effects and necessary adaptation planning for people with physical disabilities in general; however, the specific impacts and plans for people with limb loss have yet to be explored. In this article, we discuss the impacts related to threats due to heat, cold, severe storms, and power outages. We describe how climate change uniquely affects people with limb loss and underscore the need for rehabilitation care providers and researchers to: (1) study the health impacts of climate change on people with lower limb loss; (2) educate themselves and patients on the climate crisis and climate preparedness; (3) co-develop resiliency strategies with patients, governments, and community organizations to improve adaptive capacity; and (4) advocate for policy changes that will enact protections for this at-risk population.

Association between particulate air pollution and hypertensive disorders in pregnancy: A retrospective cohort study.

BACKGROUND: Epidemiological findings regarding the association of particulate matter ≤2.5 µm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP) are inconsistent; evidence for HDP risk related to PM2.5 components, mixture effects, and windows of susceptibility is limited. We aimed to investigate the relationships between HDP and exposure to PM2.5 during pregnancy. METHODS AND FINDINGS: A large retrospective cohort study was conducted among mothers with singleton pregnancies in Kaiser Permanente Southern California from 2008 to 2017. HDP were defined by International Classification of Diseases-9/10 (ICD-9/10) diagnostic codes and were classified into 2 subcategories based on the severity of HDP: gestational hypertension (GH) and preeclampsia and eclampsia (PE-E). Monthly averages of PM2.5 total mass and its constituents (i.e., sulfate, nitrate, ammonium, organic matter, and black carbon) were estimated using outputs from a fine-resolution geoscience-derived model. Multilevel Cox proportional hazard models were used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of PM2.5 constituents. The distributed lag model was applied to estimate the association between monthly PM2.5 exposure and HDP risk. This study included 386,361 participants (30.3 ± 6.1 years) with 4.8% (17,977/373,905) GH and 5.0% (19,381/386,361) PE-E cases, respectively. In single-pollutant models, we observed increased relative risks for PE-E associated with exposures to PM2.5 total mass [adjusted hazard ratio (HR) per interquartile range: 1.07, 95% confidence interval (CI) [1.04, 1.10] p < 0.001], black carbon [HR = 1.12 (95% CI [1.08, 1.16] p < 0.001)] and organic matter [HR = 1.06 (95% CI [1.03, 1.09] p < 0.001)], but not for GH. The population attributable fraction for PE-E corresponding to the standards of the US Environmental Protection Agency (9 µg/m3) was 6.37%. In multi-pollutant models, the PM2.5 mixture was associated with an increased relative risk of PE-E ([HR = 1.05 (95% CI [1.03, 1.07] p < 0.001)], simultaneous increase in PM2.5 constituents of interest by a quartile) and PM2.5 black carbon gave the greatest contribution of the overall mixture effects (71%) among all individual constituents. The susceptible window is the late first trimester and second trimester. Furthermore, the risks of PE-E associated with PM2.5 exposure were significantly higher among Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods (p < 0.05 for Cochran's Q test). Study limitations include potential exposure misclassification solely based on residential outdoor air pollution, misclassification of disease status defined by ICD codes, the date of diagnosis not reflecting the actual time of onset, and lack of information on potential covariates and unmeasured factors for HDP. CONCLUSIONS: Our findings add to the literature on associations between air pollution exposure and HDP. To our knowledge, this is the first study reporting that specific air pollution components, mixture effects, and susceptible windows of PM2.5 may affect GH and PE-E differently.

WASH interventions and child diarrhea at the interface of climate and socioeconomic position in Bangladesh.

Many diarrhea-causing pathogens are climate-sensitive, and populations with the lowest socioeconomic position (SEP) are often most vulnerable to climate-related transmission. Household Water, Sanitation, and Handwashing (WASH) interventions constitute one potential effective strategy to reduce child diarrhea, especially among low-income households. Capitalizing on a cluster randomized trial population (360 clusters, 4941 children with 8440 measurements) in rural Bangladesh, one of the world's most climate-sensitive regions, we show that improved WASH substantially reduces diarrhea risk with largest benefits among children with lowest SEP and during the monsoon season. We extrapolated trial results to rural Bangladesh regions using high-resolution geospatial layers to identify areas most likely to benefit. Scaling up a similar intervention could prevent an estimated 734 (95% CI 385, 1085) cases per 1000 children per month during the seasonal monsoon, with marked regional heterogeneities. Here, we show how to extend large-scale trials to inform WASH strategies among climate-sensitive and low-income populations.

Exploring spatial heterogeneity in synergistic effects of compound climate hazards: Extreme heat and wildfire smoke on cardiorespiratory hospitalizations in California.

Extreme heat and wildfire smoke events are increasingly co-occurring in the context of climate change, especially in California. Extreme heat and wildfire smoke may have synergistic effects on population health that vary over space. We leveraged high-resolution satellite and monitoring data to quantify spatially varying compound exposures to extreme heat and wildfire smoke in California (2006-2019) at ZIP Code Tabulation Area (ZCTA) level. We found synergistic effects between extreme heat and wildfire smoke on daily cardiorespiratory hospitalizations at the state level. We also found spatial heterogeneity in such synergistic effects across ZCTAs. Communities with lower education attainment, lower health insurance coverage, lower income, lower proportion of automobile ownership, lower tree canopy coverage, higher population density, and higher proportions of racial/ethnic minorities experienced higher synergistic effects. This study highlights the need to incorporate compound hazards and environmental justice considerations into evidence-based policy development to protect populations from increasingly prevalent compound hazards.

Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden.

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 µg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 µg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Differential Participation, a Potential Cause of Spurious Associations in Observational Cohorts in Environmental Epidemiology.

Differential participation in observational cohorts may lead to biased or even reversed estimates. In this article, we describe the potential for differential participation in cohorts studying the etiologic effects of long-term environmental exposures. Such cohorts are prone to differential participation because only those who survived until the start of follow-up and were healthy enough before enrollment will participate, and many environmental exposures are prevalent in the target population and connected to participation via factors such as geography or frailty. The relatively modest effect sizes of most environmental exposures also make any bias induced by differential participation particularly important to understand and account for. We discuss key points to consider for evaluating differential participation and use causal graphs to describe two example mechanisms through which differential participation can occur in health studies of long-term environmental exposures. We use a real-life example, the Canadian Community Health Survey cohort, to illustrate the non-negligible bias due to differential participation. We also demonstrate that implementing a simple washout period may reduce the bias and recover more valid results if the effect of interest is constant over time. Furthermore, we implement simulation scenarios to confirm the plausibility of the two mechanisms causing bias and the utility of the washout method. Since the existence of differential participation can be difficult to diagnose with traditional analytical approaches that calculate a summary effect estimate, we encourage researchers to systematically investigate the presence of time-varying effect estimates and potential spurious patterns (especially in initial periods in the setting of differential participation).

Disparities in the impact of heat wave definitions on emergency department visits during the first year of life among preterm and full-term infants in California.

INTRODUCTION: Heat waves will be aggravated due to climate change, making this a critical public health threat. However, heat wave definitions to activate alert systems can be ambiguous, highlighting the need to assess a range of definitions to identify those that contribute to the most adverse health outcomes. Additionally, children are highly susceptible to the impacts of heat waves, especially infants, despite the lack of focus on this subpopulation. We aimed to assess the relationship between 30 heat wave definitions and the first all-cause emergency department (ED) visits for California infants. We also examined modification of this relationship by preterm birth status and demographic characteristics to identify possible health disparities. METHODS: Live-born, singleton deliveries from the Study of Outcomes in Mothers and Infants born in 2014-2018 were included. Thirty heat wave definitions were assessed based on temperature metrics (minimum/maximum temperatures), thresholds (90th; 92.5th; 95th; 97.5th; 99th percentiles), and duration (1-; 2-; 3-days). A time-stratified case-crossover design assessed heat wave impacts on ED visits using infants with a warm season ED visit (May-October) within the first year of life (n = 228,250). Effect modification by preterm birth status, age, sex, race/ethnicity, education, and delivery payment type was also investigated. RESULTS: Infants demonstrated increased risk of an ED visit with exposure to all heat definitions. The 3-day minimum temperature 99th percentile definition had the highest adjusted odds ratio (AOR: 1.14; 95% CI: 1.05-1.23) for the total population. Term infants were more affected by some heat waves than preterm infants. Effect modification was additionally identified, such as by maternal education. DISCUSSION: This study provides insight on the heat wave definitions that lead to adverse health outcomes and the identification of the most susceptible infants to these impacts, which has implications on heat-related interventions.

Exploring the impact of environmental exposure changes on metabolic biomarkers: A 6-month GPS-GIS study among women with overweight or obesity.

BACKGROUND: Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements. METHODS: Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time. RESULTS: Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (ß -0.010, 95%CI -0.025, 0.005; ß -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (ß -1.001, 95%CI -1.888, -0.131). CONCLUSIONS: The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.

Excess risk in infant mortality among populations living in flood-prone areas in Bangladesh: A cluster-matched cohort study over three decades, 1988 to 2017.

The Ganges-Brahmaputra-Meghna river basin, running through Tibet, Nepal, Bhutan, Bangladesh, and northern India, is home to more than 618 million people. Annual monsoons bring extensive flooding to the basin, with floods predicted to be more frequent and extreme due to climate change. Yet, evidence regarding the long-term impacts of floods on children's health is lacking. In this analysis, we used high-resolution maps of recent large floods in Bangladesh to identify flood-prone areas over the country. We then used propensity score techniques to identify, among 58,945 mothers interviewed in six demographic population-based surveys throughout Bangladesh, matched cohorts of exposed and unexposed mothers and leverage data on 150,081 births to estimate that living in flood-prone areas was associated with an excess risk in infant mortality of 5.3 (95% CI 2.2 to 8.4) additional deaths per 1,000 births compared to living in non-flood-prone areas over the 30-y period between 1988 and 2017, with higher risk for children born during rainy (7.9, 95% CI: 3.3 to 12.5) vs. dry months (3.1, 95% CI: -1.1 to 7.2). Finally, drawing on national-scale, high-resolution estimates of flood risk and population distribution, we estimated an excess of 152,753 (64,120 to 241,386) infant deaths were attributable to living in flood-prone areas in Bangladesh over the past 30 y, with marked heterogeneity in attributable burden by subdistrict. Our approach demonstrates the importance of measuring longer-term health impacts from floods and provides a generalizable example for how to study climate-related exposures and long-term health effects.

Investigating inequalities in HIV testing in sub-Saharan Africa: spatial analysis of cross-sectional population-based surveys in 25 countries.

OBJECTIVES: We aim to explore spatial variations in socioeconomic inequalities in HIV testing uptake in sub-Saharan Africa (SSA) at different geographical scales to identify potential geographical hotspots of inequalities. Additionally, to evaluate the potential benefits of HIV testing programmes, we assess whether local levels of HIV testing match the local levels of HIV prevalence. DESIGN: A multi-country analysis of population-based cross-sectional surveys in SSA. SETTING: We analysed data from 25 SSA countries with Demographic and Health Surveys between 2011 and 2019. PARTICIPANTS: Country-level analysis included 473 775 participants (312 104 women and 161 671 men) and cluster-level analysis included 328 283 individuals (241 084 women and 87 199 men). Women aged 15-49 years and men aged 15-54/59 years in selected households who were tested for HIV in the last 12 months were eligible. We quantified inequalities in self-reported recent HIV testing with the Slope Index of Inequality (SII) and the Relative Index of Inequality (RII) across geographical scales to capture sex-specific within-country spatial variations. We also conducted local Getis-Ord Gi* statistics to consider the autocorrelation in fine-scale SII and RII across countries. To assess the efficiency of HIV testing programmes, we measured the correlation between recent HIV testing and HIV prevalence through Spearman correlation across geographical scales. RESULTS: We observed varying inequalities in recent HIV testing in magnitude and spatial distribution on both absolute and relative scales in many countries for both sexes at national and subnational levels. Hotspots of absolute and relative inequalities were mostly observed in Western and Central Africa with a few regions in Eastern and Southern Africa. Despite significant sex-specific correlations between testing and prevalence in all countries when assessed at the national level, we report an absence of such a correlation at fine scale in 17 of 50 sex-country combinations. CONCLUSIONS: We highlight the importance of investigating the spatial variability of various HIV indicators and related inequalities across different geographical levels. Results may help inform an equitable distribution of HIV testing services.

Objective sleep and cardiometabolic biomarkers: results from the community of mine study.

Study Objectives: Examining multiple dimensions of sleep health may better capture associations between sleep and health risks, including cardiometabolic disease (CMD). Hispanics have elevated risk for inadequate sleep and CMD biomarkers. Few studies have explored whether associations between sleep and CMD differ by Hispanic ethnicity. Methods: Leveraging data from the Community of Mine (CoM) study, a cross-sectional investigation of 602 ethnically diverse participants, we derived accelerometer-measured sleep duration and efficiency, and self-reported sleep quality. Accelerometer-measured sleep exposures were analyzed both as continuous and categorical variables. Multivariate and quantile regression models were used to assess associations between sleep and CMD biomarkers (insulin resistance, systolic blood pressure, and low-density-lipoprotein cholesterol), controlling for age, sex, ethnicity, education, smoking status, and body mass index. We examined the potential effect modification of Hispanic ethnicity. Results: We observed mixed results based on CMD biomarkers and sleep exposure. Increased sleep duration was significantly related to low-density lipoprotein cholesterol in adjusted models (estimate = 0.06; 95% CI: 0.02, 0.11). Poor sleep efficiency was associated with greater insulin resistance in the adjusted quantile (estimate = 0.20; 95% CI: 0.04, 0.36) model at the 90th percentile. Self-reported sleep quality was not associated with CMD outcomes. There was no evidence of effect modification by Hispanic ethnicity. Conclusions: In this cohort, sleep health measures were found to have mixed and at times opposing effects on CMD outcomes. These effects did not demonstrate an interaction with Hispanic ethnicity.

Declines in cigarette smoking among US adolescents and young adults: indications of independence from e-cigarette vaping surge.

OBJECTIVE: To compare trends in cigarette smoking and nicotine vaping among US population aged 17-18 years and 18-24 years. METHODS: Regression analyses identified trends in ever and current use of cigarettes and e-cigarettes, using three US representative surveys from 1992 to 2022. RESULTS: From 1997 to 2020, cigarette smoking prevalence among those aged 18-24 years decreased from 29.1% (95% CI 27.4% to 30.7%) to 5.4% (95% CI 3.9% to 6.9%). The decline was highly correlated with a decline in past 30-day smoking among those aged 17-18 years (1997: 36.8% (95% CI 35.6% to 37.9%; 2022: 3.0% (95% CI 1.8% to 4.1%). From 2017 to 2019, both ever-vaping and past 30-day nicotine vaping (11.0% to 25.5%) surged among those 17-18 years, however there was no increase among those aged 18-24 years. Regression models demonstrated that the surge in vaping was independent of the decline in cigarette smoking. In the 24 most populous US states, exclusive vaping did increase among those aged 18-24 years, from 1.7% to 4.0% to equivalent to 40% of the decline in cigarette smoking between 2014-15 and 2018-19. Across these US states, the correlation between the changes in vaping and smoking prevalence was low (r=0.11). In the two US states with >US$1/fluid mL tax on e-cigarettes in 2017, cigarette smoking declined faster than the US average. CONCLUSIONS: Since 1997, a large decline in cigarette smoking occurred in the US population under age 24 years, that was independent of the 2017-19 adolescent surge in past 30-day e-cigarette vaping. Further research is needed to assess whether the 2014-15 to 2018-19 increase in exclusive vaping in those aged 18-24 years is a cohort effect from earlier dependence on e-cigarette vaping as adolescents.

Does domestic violence legislation reduce permissive attitudes about intimate partner violence? Longitudinal evidence from men and women from 61 countries.

Background: Intimate partner violence (IPV) is highly prevalent and has substantial implications for women's health. Changing IPV attitudes is one pathway to reduce IPV. While evidence suggests that interventions targeting individuals may change IPV attitudes, the effect of wider-scale interventions, such as legislation, remain unknown. Methods: We used individual-level IPV attitudes information collected between 1997 and 2020 by the Demographic and Health Surveys (DHS) and the Multiple Indicator Cluster Surveys (MICS), which we linked with national-level domestic violence (DV) legislation information. We evaluated the effect of adoption of DV legislation on changes in IPV attitudes using a difference-in-differences study design that controlled for time-varying country-level confounding and accounted for staggered timing of legislation adoption. Findings: Our sample included 2,184,047 women from 60 countries and 390,877 men from 40 countries. After controlling for country-level confounders, adoption of DV legislation reduced IPV acceptability among women (average treatment effect among treated (ATT) = -0.07, 95% CI: -0.16, 0.06) and men (ATT = -0.11, 95% CI: -0.22, 0.03) although estimates were imprecise and included the null. Interpretation: DV legislation may reduce permissive IPV attitudes, especially among men, although conclusions should be interpreted cautiously due to imprecise estimates. Funding: Eunice Kennedy Shriver National Institute of Child Health and Human Development (5R00HD104896).

Association of Antepartum and Postpartum Air Pollution Exposure With Postpartum Depression in Southern California.

Importance: Women are especially vulnerable to mental health matters post partum because of biological, emotional, and social changes during this period. However, epidemiologic evidence of an association between air pollution exposure and postpartum depression (PPD) is limited. Objective: To examine the associations between antepartum and postpartum maternal air pollution exposure and PPD. Design, Setting, and Participants: This retrospective cohort study used data from Kaiser Permanente Southern California (KPSC) electronic health records and included women who had singleton live births at KPSC facilities between January 1, 2008, and December 31, 2016. Data were analyzed between January 1 and May 10, 2023. Exposures: Ambient air pollution exposures were assessed based on maternal residential addresses using monthly averages of particulate matter less than or equal to 2.5 µm (PM2.5), particulate matter less than or equal to 10 µm (PM10), nitrogen dioxide (NO2), and ozone (O3) from spatial interpolation of monitoring station measurements. Constituents of PM2.5 (sulfate, nitrate, ammonium, organic matter, and black carbon) were obtained from fine-resolution geoscience-derived models based on satellite, ground-based monitor, and chemical transport modeling data. Main Outcomes and Measures: Participants with an Edinburgh Postnatal Depression Scale score of 10 or higher during the 6 months after giving birth were referred to a clinical interview for further assessment and diagnosis. Ascertainment of PPD was defined using a combination of diagnostic codes and prescription medications. Results: The study included 340 679 participants (mean [SD] age, 30.05 [5.81] years), with 25 674 having PPD (7.54%). Increased risks for PPD were observed to be associated with per-IQR increases in antepartum and postpartum exposures to O3 (adjusted odds ratio [AOR], 1.09; 95% CI, 1.06-1.12), PM10 (AOR, 1.02; 95% CI, 1.00-1.04), and PM2.5 (AOR, 1.02; 95% CI, 1. 00-1.03) but not with NO2; PPD risks were mainly associated with PM2.5 organic matter and black carbon. Overall, a higher risk of PPD was associated with O3 during the entire pregnancy and postpartum periods and with PM exposure during the late pregnancy and postpartum periods. Conclusions and Relevance: The study findings suggest that long-term exposure to antepartum and postpartum air pollution was associated with higher PPD risks. Identifying the modifiable environmental risk factors and developing interventions are important public health issues to improve maternal mental health and alleviate the disease burden of PPD.

The role of cardiovascular health and vascular events in the relationship between excessive daytime sleepiness and dementia risk.

Many studies suggest a relationship between excessive daytime sleepiness (EDS) and dementia incidence, but the underlying mechanisms remain uncertain. The study aimed to investigate the role of cardiovascular burden in the relationship between EDS and dementia incidence over a 12-year follow-up in community-dwelling older adults. We performed analyses on 6171 subjects (aged ≥65 years) free of dementia and vascular disease at baseline. Participants self-reported EDS at baseline and an expert committee validated both prevalent and incident dementia. We defined cardiovascular burden by a low Cardiovascular Health score, constructed using the American Heart Association metrics, and incident vascular events. To explore the potential role of the cardiovascular burden in the relationship between EDS and dementia, we conducted mediation analyses with inverse odds ratio-weighted estimation, using multivariable-adjusted proportional hazard Cox and logistic regression models. Subjects with EDS had a higher risk of all-cause dementia (hazard ratio [HR] 1.39, 95% confidence interval [CI] 1.13-1.69) and dementia with vascular component (DVC) (HR 2.14, 95% CI 1.30-3.51), but not Alzheimer's disease (HR 1.18, 95% CI 0.93-1.51). Cardiovascular burden explained 5% (95% CI 4.1-5.2) and 11% (95% CI 9.7-11.3) of the relationship between EDS and all-cause dementia and DVC, respectively. These findings confirm that EDS may be implicated in the development of dementia and indicate a weaker than expected role of cardiovascular burden in the relationship between EDS and DVC.

Implications of climate-related disasters on refugees' health: A case study of resettled Syrian and Iraqi refugees in San Diego, California.

Background: Climate change disproportionately harms people of color and low-income communities. Despite their unprecedented numbers, being constantly on the move, and suffering extreme social vulnerability, almost nothing is known about the impact of climate change on the health of refugees. This study uses state-of-the-art mixed methods to examine the differential susceptibility of climate-sensitive exposures and environmental exposures among refugees and their links to perceived health after resettlement. Methods: Arabic-speaking refugees (N=67) from Iraq and Syria previously diagnosed with hypertension who resettled in California were recruited from a community center. Semi-structured interviews were conducted to explore participant's understanding of the impact of climate on health. Survey data were collected to inquire regarding participant's refugee journeys prior to resettlement in the US. Survey data on climate-related disasters was retrospectively geo-referenced through the Emergency Events Database (EM-DAT). Qualitative data was analyzed using inductive thematic analysis. Results: All participants stayed in at least one temporary resettlement country during their migration journey and 12% has stayed in refugee camps. The most popular resettlement sites were Turkey (most disaster-prone in the region due to frequent floods and earthquakes) and Jordan (one of the most extreme water-scarce globally). Participants reported harsh weather conditions during their migratory journeys including extreme cold in Turkey and extreme heat in Jordan. Many participants noted their exposure to dust throughout their travels, and an inability to deal with harsh weather conditions due to financial insecurity. Participants did not link their diagnosis of hypertension to their experience of extreme weather and would only link it to their exposure to stress from war. Participants did note poorer mental health due to poor weather conditions and a challenge adjusting to the climate conditions in different countries. Few participants reported residing in a refugee camp and described it as ill-equipped for the challenges of climate hazards. Conclusion: This study reveals the links between structural drivers of climate change and health inequities for refugee populations. Refugees are highly vulnerable to climate-sensitive exposures but remain not fully aware of the potential links between these exposures and health. Learnings from this study will inform clinical and public health interventions, and policies to close the climate gap without leaving this vulnerable population behind.

The Burden of Wildfire Smoke on Respiratory Health in California at the Zip Code Level: Uncovering the Disproportionate Impacts of Differential Fine Particle Composition.

Wildfires constitute a growing source of extremely high levels of particulate matter that is less than 2.5 microns in diameter (PM2.5). Recently, toxicologic and epidemiologic studies have shown that PM2.5 generated from wildfires may have a greater health burden than PM2.5 generated from other pollutant sources. This study examined the impact of PM2.5 on hospitalizations for respiratory diseases in California between 2006 and 2019 using a health impact assessment approach that considers differential concentration-response functions (CRF) for PM2.5 from wildfire and non-wildfire sources of emissions. We quantified the burden of respiratory hospitalizations related to PM2.5 exposure at the zip code level through two different approaches: (a) naïve (considering the same CRF for all PM2.5 emissions) and (b) nuanced (considering different CRFs for PM2.5 from wildfires and from other sources). We conducted a Geographically Weighted Regression to analyze spatially varying relationships between the delta (i.e., the difference between the naïve and nuanced approaches) and the Centers for Disease Control and Prevention's Social Vulnerability Index (SVI). A higher attributable number of respiratory hospitalizations was found when accounting for the larger health burden of wildfire PM2.5. We found that, between 2006 and 2019, the number of hospitalizations attributable to PM2.5 may have been underestimated by approximately 13% as a result of not accounting for the higher CRF of wildfire-related PM2.5 throughout California. This underestimation was higher in northern California and areas with higher SVI rankings. The relationship between delta and SVI varied spatially across California. These findings can be useful for updating future air pollution guideline recommendations.

Emergency department visits associated with wildfire smoke events in California, 2016-2019.

Wildfire smoke has been associated with adverse respiratory outcomes, but the impacts of wildfire on other health outcomes and sensitive subpopulations are not fully understood. We examined associations between smoke events and emergency department visits (EDVs) for respiratory, cardiovascular, diabetes, and mental health outcomes in California during the wildfire season June-December 2016-2019. Daily, zip code tabulation area-level wildfire-specific fine particulate matter (PM2.5) concentrations were aggregated to air basins. A "smoke event" was defined as an air basin-day with a wildfire-specific PM2.5 concentration at or above the 98th percentile across all air basin-days (threshold = 13.5 µg/m3). We conducted a two-stage time-series analysis using quasi-Poisson regression considering lag effects and random effects meta-analysis. We also conducted analyses stratified by race/ethnicity, age, and sex to assess potential effect modification. Smoke events were associated with an increased risk of EDVs for all respiratory diseases at lag 1 [14.4%, 95% confidence interval (CI): (6.8, 22.5)], asthma at lag 0 [57.1% (44.5, 70.8)], and chronic lower respiratory disease at lag 0 [12.7% (6.2, 19.6)]. We also found positive associations with EDVs for all cardiovascular diseases at lag 10. Mixed results were observed for mental health outcomes. Stratified results revealed potential disparities by race/ethnicity. Short-term exposure to smoke events was associated with increased respiratory and schizophrenia EDVs. Cardiovascular impacts may be delayed compared to respiratory outcomes.

Analysis of Heat Exposure During Pregnancy and Severe Maternal Morbidity.

Importance: The rate of severe maternal morbidity (SMM) is continuously increasing in the US. Evidence regarding the associations of climate-related exposure, such as environmental heat, with SMM is lacking. Objective: To examine associations between long- and short-term maternal heat exposure and SMM. Design, Setting, and Participants: This retrospective population-based epidemiological cohort study took place at a large integrated health care organization, Kaiser Permanente Southern California, between January 1, 2008, and December 31, 2018. Data were analyzed from February to April 2023. Singleton pregnancies with data on SMM diagnosis status were included. Exposures: Moderate, high, and extreme heat days, defined as daily maximum temperatures exceeding the 75th, 90th, and 95th percentiles of the time series data from May through September 2007 to 2018 in Southern California, respectively. Long-term exposures were measured by the proportions of different heat days during pregnancy and by trimester. Short-term exposures were represented by binary variables of heatwaves with 9 different definitions (combining percentile thresholds with 3 durations; ie, ≥2, ≥3, and ≥4 consecutive days) during the last gestational week. Main Outcomes and Measures: The primary outcome was SMM during delivery hospitalization, measured by 20 subconditions excluding blood transfusion. Discrete-time logistic regression was used to estimate associations with long- and short-term heat exposure. Effect modification by maternal characteristics and green space exposure was examined using interaction terms. Results: There were 3446 SMM cases (0.9%) among 403 602 pregnancies (mean [SD] age, 30.3 [5.7] years). Significant associations were observed with long-term heat exposure during pregnancy and during the third trimester. High exposure (≥80th percentile of the proportions) to extreme heat days during pregnancy and during the third trimester were associated with a 27% (95% CI, 17%-37%; P < .001) and 28% (95% CI, 17%-41%; P < .001) increase in risk of SMM, respectively. Elevated SMM risks were significantly associated with short-term heatwave exposure under all heatwave definitions. The magnitude of associations generally increased from the least severe (HWD1: daily maximum temperature >75th percentile lasting for ≥2 days; odds ratio [OR], 1.32; 95% CI, 1.17-1.48; P < .001) to the most severe heatwave exposure (HWD9: daily maximum temperature >95th percentile lasting for ≥4 days; OR, 2.39; 95% CI, 1.62-3.54; P < .001). Greater associations were observed among mothers with lower educational attainment (OR for high exposure to extreme heat days during pregnancy, 1.43; 95% CI, 1.26-1.63; P < .001) or whose pregnancies started in the cold season (November through April; OR, 1.37; 95% CI, 1.24-1.53; P < .001). Conclusions and Relevance: In this retrospective cohort study, long- and short-term heat exposure during pregnancy was associated with higher risk of SMM. These results might have important implications for SMM prevention, particularly in a changing climate.