Individuals experiencing homelessness are highly vulnerable to urban environmental hazards, such as heat and air pollution, due to a lack of stable housing and limited access to indoor or cooled spaces. These risks are heightened for older adults and individuals with preexisting health conditions. With intensifying summer heat in the American Southwest and the persistence of urban homelessness, this study explores how older adults experiencing homelessness in Phoenix, Arizona perceive and interact with heat and air pollution as well as the adequacy of available coping resources and information. A survey was co-produced with community members with lived experience. A sub-group of community members assisted in proctoring the surveys among adults 55 and older at a downtown service agency. Survey results informed the location of data collection using MaRTy-a mobile biometeorological cart-and remotely sensed fine particulate matter (PM2.5). Findings reveal that heat and air pollution significantly influence travel decisions and contribute to health issues for many respondents. Midday and evening thermal radiation levels regularly exceeded safe thresholds, while PM2.5 concentrations often surpassed annual air quality guidelines, though they posed less acute health risks. Most participants reported awareness of health risks and employed strategies to reduce exposure. However, many expressed that city-level, public resources are insufficient to prevent heat- and air pollution-related health issues. Findings underscore the need for targeted interventions-such as better access to transportation and essential healthcare and extended hours of operation for service providers-to enhance resource accessibility and mitigate environmental health risks for vulnerable populations.

No abstract is available for this article.

Exposure to air pollution and excessive heat during hot-and-polluted episodes (HPEs) may synergistically cause higher health risks globally. Nevertheless, long-term global spatiotemporal characteristics of HPEs and their health impacts remain unclear. Herein, we conducted statistical analyses using reanalysis data of fine particulate matter (PM2.5) and climate together with our derived concentration-response function for HPEs to assess global HPE variations from 1990 to 2019, and to estimate the PM2.5-associated premature mortality during HPEs. Our results reveal that HPE frequency increased significantly globally. HPE PM2.5 intensity in the Global North continuously increased, overpassing the Global South after 2010, indicating a recurred risk of air pollution under climate change in the Global North after several years of emission control endeavors. Globally, we estimated approximately 694,440 (95% CI: 687,996-715,311) total mortalities associated with acute PM2.5 exposure during HPEs from 1990 to 2019, with the Global South accounting for around 80% of these deaths. Among the most vulnerable 15 countries, India had by far the highest mortality burden, and the United States, Russia, Japan, and Germany were particularly highlighted as having higher burdens within the Global North. Our findings highlight the importance of considering environmental inequality between the Global North and the Global South, and co-benefits of air pollution-climate change mitigation during policymaking processes.

The increasing threat of heat stress poses significant risks to human health globally. To quantify heat exposure more effectively, integrated heat stress indicators (HSIs) have been developed to simplify the classification of heat stress severity and assist in public heat warnings. However, their ability to accurately predict daily heat stroke cases has not been fully assessed. In this study, we evaluated the performance of multiple HSIs in forecasting the number of heat stroke-related emergency ambulance dispatches (HT-EADs) across 47 prefectures in Japan and compared their accuracy to models using raw meteorological variables. Ourresults indicate that, while HSIs simplify the process of assessing heat stress, they generally show lower performances than models based on raw meteorological data. Among the eight HSIs tested, the Wet Bulb Globe Temperature (T WBG) showed the strongest predictive power, with median R 2 values of 0.77 and 0.70 for the calibration and validation periods, respectively. However, models incorporating air temperature, relative humidity, wind speed, and solar radiation outperformed T WBG, achieving R 2 values of 0.85 and 0.74. We also observed spatial variability in HSI performance, particularly in cooler regions like Hokkaido, where HSIs provided no improvement over temperature alone. Given these findings, we recommend that HSIs be rigorously evaluated with local health data before being used in heat warning systems for specific locations. For predictions requiring high accuracy, raw meteorological variables could be prioritized to ensure greater precision.

Little evidence is available about how temperature variability (TV) may modify the association between ambient heat and health conditions, especially in less developed countries, for example, Brazil. This study explored the change in heat-hospitalization association from days with low to high temperature variabilities (TVs) in Brazil. We collected data on daily hospitalization and weather from 1,814 Brazilian cities during the 2000-2015 hot seasons. For each city, the heat-hospitalization association was estimated using the quasi-Poisson regression with constrained lag model on days with low and high TVs, respectively. City-specific effect estimates were then pooled using random-effect meta-analysis. Stratified analyses were performed by region, sex, age-group and cause category. Our results showed that at the national level the risk of hospitalization increased by 4.4% [95% confidence interval (CI): 4.0%-4.7%] and 2.7% (95%CI: 2.4%-3.0%) per 5°C increase in daily mean temperature on days with low and high TVs, respectively. The effect modification of TV on heat-hospitalization association was significant in the northeast, southeast and south, and for most population groups except for the children aged 0-4years and the elderly aged≥80years. Significant effect modification of TV was observed in injury and poisoning, respiratory and cardiovascular diseases. Our findings suggest that in Brazil, the heat-health association is substantially modified by exposure to TV. The high heat susceptibility on the day with low TV warrants particular concern in order reducing the risk of disease burden.

Influenza epidemics, a major contributor to global morbidity and mortality, are influenced by climate factors including absolute humidity and temperature. Climate change is expected to increase the frequency and severity of climate extremes, potentially impacting the duration and magnitude of future influenza epidemics. However, the extent of these projected effects on influenza outbreaks remains understudied. Here, we use an epidemiologic model adapted for temperate and tropical climates to explore how climate variability may affect seasonal influenza. Using climate anomalies derived from historical data, we found that simulated periods of anomalous climate conditions impacted both the projected influenza outbreak peak size and the total proportion infected, with the strongest effects observed when the anomaly was included just before the typical peak. Effects varied by climate: temperate regions showed a unimodal relationship, while tropical climates exhibited a nonlinear pattern. Our results emphasize that the intensity of weather extremes is key to understanding how climate change may affect influenza outbreaks, laying the groundwork for utilizing weather variability as a potential early warning for influenza activity.

High ambient temperature poses significant health risk globally. However, the relative importance of different exposure pathways leading to health risks remains unclear. For 9 US states during 2016-2018, ED visit records for heat exhaustion and heat stroke (HEAT), fluid and electrolyte imbalance (FEI), volume depletion (VD), and acute kidney injury (AKI) were identified via diagnosis codes. Co-diagnosed Y92 subcodes (Y codes) were used to categorize the patient's location at the time of injury or condition. Logistic regressions were used to estimate nonlinear associations between same-day temperature and Y codes for 11 non-residential versus residential locations among heat-related ED visits, including stratified analyses by patient age, race, and ethnicity. Odds ratios (OR) were calculated between the 95th versus 50th percentile of temperature. Overall, higher temperature was associated with increased risks of ED visits with Y codes for non-residential locations. HEAT ED visits were more likely to have Y codes for streets compared to residential locations (OR:1.68, 95% CI: 1.12-2.51). Similarly, VD visits were more likely to have Y codes for industrial area (OR: 2.68, 95% CI: 1.98-3.63), farms (OR:7.66, 95% CI: 4.05-14.50), recreation areas (OR:2.25, 95% CI: 1.78-2.84), and streets (OR:1.54, 95% CI: 1.39-1.70), but were less likely to have Y codes for public places (OR: 0.89, 95% CI: 0.84, 0.94). Similar associations were observed for FEI and AKI ED visits. Locations associated with higher heat risks may be due to exposure outdoor temperature and activities, supporting the need to develop strategies and interventions that minimize heat exposure in these areas.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder with significant negative health and economic implications for individuals, families and society. This study utilized an individual-level time-stratified case-crossover study design to investigate the relationship between ambient temperatures and PD mortality among the elderly in China. A combination of conditional logistic regression and distributed lag non-linear model was employed to analyze the data, and the mortality burden attributed to ambient temperatures was quantified. The study included a total of 59,397 deceased PD patients aged 60years and above who died between 2013 and 2020. Findings revealed that the effects of extremely low temperature (-1°C) could persist for up to 14days, while the impacts of extremely high temperature (30°C) were acute and last for 4days and showing a significant harvest effect. For the overall population, the high temperatures significantly increased the risk of death, where low temperature did not. A lag0-14 cumulative odds ratios (COR) of extremely low temperature compared to the reference temperature (15°C) was 1.024 (95% CI: 0.971, 1.080). The lag0-14 COR of extremely high temperature was 1.206 (95% CI: 1.116, 1.304). Additionally, high temperatures attributed greater AF of 4.013 (95% eCI: 1.990, 5.894) comparing to low temperatures did of 0.762 (95% eCI: -0.624, 2.017). Significant differences were found across regions. No statistically significant differences were found between the sex and age. This nationwide study provides evidence for tailored interventions in specific regions and populations to reduce temperature-related PD mortality among the elderly in China.

Extreme heat has been linked to many health outcomes, including preterm and early term birth. We examine associations between acute heat wave exposure and risk of preterm (PTB) (28-36weeks) or early term (ETB) (37-38weeks) birth, stratified by individual-level and area-level factors. Daily ambient mean temperature was linked to maternal residence in state vital records for preterm and early term births in California, Florida, Georgia, Kansas, Nevada, New Jersey, North Carolina, and Oregon between 1990 and 2017. Heat waves were identified during the four-day exposure window preceding birth using the 97.5th percentile mean temperature for zip code tabulation areas (ZCTA). We used a time-stratified case-crossover design, restricted to the warm season (May through September) and stratified by maternal age, maternal education, ZCTA-level impervious land cover or social deprivation index. We pooled estimated odds ratios across states using inverse-variance weighting. The PTB and ETB analyses included up to 945,836 and 2,966,661 cases, respectively. Heat-related ETB risk was consistently highest among women <25years of age, women with ≤high school education, and women living in areas of higher social deprivation and impervious land cover. PTB associations were also elevated in these subgroups, but positive associations were also observed among older, more educated mothers, and in areas with less social deprivation. Across all subgroups and outcomes, the change in odds associated with heat waves ranged from no increase to a 7.9% increase. Heat-related early term birth risk is enhanced among subgroups associated with socioeconomic disadvantage, but patterns of vulnerability were less consistent for preterm birth.