The Effects of Coexposure to Extremes of Heat and Particulate Air Pollution on Mortality in California: Implications for Climate Change

Combined effect of heatwaves and residential greenness on the risk of stroke among Chinese adults: A national cohort study

Heatwaves have been associated with an increased risk of stroke, while residential greenness may offer protective benefits. This prospective cohort study examined 22,702 participants aged 35 years or older, with no prior history of cardiovascular disease (CVD), from the China Hypertension Survey (CHS) conducted between 2012 and 2015. Participants were followed up between 2018 and 2019. Heatwaves were defined as daily maximum temperatures exceeding the 92.5th percentile of the warm season for at least three consecutive days. Residential greenness was quantified using the Normalized Difference Vegetation Index (NDVI) within buffers of 300, 500, and 1000 m from participants' residences. Multivariable Cox proportional hazards models evaluated the independent and combined effects of heatwaves and greenness on stroke risk, while restricted cubic spline analyses explored nonlinear relationships. Interaction effects were assessed using both multiplicative and additive Cox regression models. During follow-up, 597 stroke events occurred. Each additional 3-day increase in heatwave days was associated with an increased stroke risk (HR: 1.19, 95 % CI: 1.08-1.31). Interaction analyses demonstrated a synergistic effect between heatwaves and lower residential greenness (NDVI300 m, NDVI500 m and NDVI1000 m) on stroke risk, with significant additive(RERI > 0, P < 0.05) and multiplicative interactions (HR > 1, P < 0.05). The strongest protective effects of greenness were observed within a 500 m buffer zone, particularly for individuals under 60 years, rural residents, and those with higher educational attainment. This study highlights the potential benefits of enhancing greenness for cardiovascular health and provides valuable insights for environmental governance and public health policy in China.

Associations of wildfire-derived particulate matter with hospitalization, emergency department visits and mortality: A systematic review and meta-analysis

Epidemiological studies on wildfire smoke exposure and its associated disease morbidities and mortalities are rapidly accumulating in recent years. However, the findings of the existing studies have not been quantitatively evaluated with a conclusion. We conducted a systematic review and meta-analysis for the studies focused on associations of wildfire-sourced particles (PM2.5 and PM10) with cardiorespiratory diseases and mortality. We reviewed all literatures related to wildfire particles (PM2.5 and PM10) and cardiorespiratory disease morbidities [hospital admission, emergency department (ED) visits] and mortality (all-cause and cause-specific) from January 1, 2000 to August 1, 2024. Meta-analyses were conducted to summarize Relative Risks (RRs) and 95% confidence intervals (CIs) across studies when at least three studies were available for a particular exposure-outcome. All articles were assessed for risk of bias using a standard tool (Grading of Recommendations Assessment, Development and Evaluation, GRADE) for quality assurance. Studies (N = 45) were increasingly published between the years of 2020-2024 and from North America (N = 21) and Australia (N = 11) where wildfires are common. In the meta-analysis of over 124 million patients, wildfire smoke was consistently associated with increased risk of all-cause mortality (RR: 1.02, 95% CI 1.01-1.03 for PM2.5 per 10 μg/m3) and respiratory outcomes, including hospital admission (1.04, 95% CI 1.02-1.05 for wildfire PM2.5 and 1.01, 95% CI 1.00-1.02 for wildfire PM10) and ED visits (1.04, 95% CI 1.02-1.06 for wildfire PM2.5). Associations between wildfire PM2.5 and cardiovascular diseases were inconclusive (mortality: 1.02, 95% CI 1.01-1.03; hospital admission: 1.01, 95% CI 1.00-1.02; ED visit: 1.01, 95%CI: 0.98-1.04). Current studies provide evidence of an increased risk of hospitalization and ED visits for respiratory diseases and all-cause mortality due to wildfire PM2.5 and PM10 exposures worldwide. Future research is needed to explore health effects of wildfire exposure on cardiovascular diseases.

Low and high air temperature and cardiovascular risk

Temperature extremes are one facet of global warming caused by climate change. They have a broad impact on population health globally. Due to specific individual- and area-level factors, some subgroups of the population are at particular risk. Observational data has demonstrated that the association between temperature and mortality and cardiovascular mortality is U- or J-shaped. This means that beyond an optimal temperature, both low and high temperatures increase cardiovascular risk. In addition, there is emerging epidemiological data showing that climate change-related temperature fluctuations may be particularly challenging for cardiovascular health. Biological plausibility for these observations comes from the effect of cold, heat, and temperature fluctuations on risk factors for cardiovascular disease. Shared mechanisms of heat and cold adaptation include sympathetic activation, changes in vascular tone, increased cardiac strain, and inflammatory and prothrombotic stimuli. The confluence of these mechanisms can result in demand ischemia and/or atherosclerotic plaque rupture. In conclusion, public health and individual-level measures should be taken to protect susceptible populations, such as patients with risk factors and/or pre-existing cardiovascular disease, from the adverse effects of non-optimal temperatures. This review aims to provide an overview of the association between temperature extremes and cardiovascular disease through the lens of pathophysiology and observational data. It also highlights some specific meteorological aspects, gives insight to the interplay of air temperature and air pollution, touches upon social dimensions of climate change, and tries to give a brief outlook into what to expect from the future.

Trends in population exposure to compound extreme-risk temperature and air pollution across 35 European countries: a modelling study

BACKGROUND

Despite ongoing efforts to reduce air pollution, the complex relationship between air pollution and climate change presents additional multifaceted challenges. The spatiotemporal co-occurrence of extreme temperatures and air pollution episodes remains understudied. Furthermore, current studies typically employ uniform temperature thresholds across broad areas, overlooking regional differences in health vulnerability. We aim to present a comprehensive assessment of extreme temperatures and air pollution, and to incorporate location-specific risk thresholds.

METHODS

In this time series modelling study we analysed the changes in extreme-risk temperature (ERT) days for heat and cold in Europe from Jan 1, 2003 to Dec 31, 2020, considering time-varying temperature-mortality relationships based on regional mortality data (from Eurostat) from 35 European countries (543 million people). We used daily estimates of PM2·5, PM10, NO2, and O3 concentrations from quantile machine learning estimations at 0·1-degree to identify of heat-compound and cold-compound days co-occurring with air pollution levels exceeding WHO guidelines.

FINDINGS

Cold-related mortality risk decreased over the study period across Europe, and adaptation to heat-related mortality was less pronounced. Between 2003 and 2020, annual cold-ERT days had decreased by 20·7 days per decade and annual heat-ERT days increased by 2·8 days per decade. Southeastern Europe had higher frequencies of both heat-ERT and cold-ERT days. Heat-O3 events were the only increasing heat-compound episodes, with 2·6 more days per decade. Conversely, cold-compound episodes decreased by 15·2 days per decade with cold-PM2·5 events remaining the predominant threat. Around 349 million Europeans were exposed to at least 1 cold-compound day annually, and around 295 million experienced at least one heat-compound day, including nearly 235 million affected by heat-O3 compound episodes.

INTERPRETATION

By identifying region-specific risk thresholds, our study reveals spatial disparities and changes in ERT events, particularly when coupled with air pollution. These findings are essential for developing targeted adaptation strategies, facilitating subsequent health assessments, and implementing effective measures to safeguard public health.

FUNDING

European Research Council and Ministerio de Ciencia e Innovación.

Personalized heat stress early warning system for an urban area

Extreme heat events have led to significant human mortality and morbidity across all regions of the world, with the risk of heat stress among residents steadily increasing. In response, there is a growing need for early warning systems to help individuals plan their activities to mitigate these risks. This study aims to develop a Heat Stress Risk Index Forecast (HSRIF) system, currently being prototyped for the municipal boundary of Delhi (India). HSRIF is a novel Universal Thermal Climate Index (UTCI)-based personalised early warning system, developed to provide customized heat stress risk value to the user for the upcoming 5 days. The system leverages a novel approach by utilizing meteorological data generated through an open source numerical weather prediction model 'Weather Research and Forecasting model's Urban Canopy Model (WRF-UCM)' to calculate the UTCI at a high resolution of 333 m over the study area. The calculated UTCI is then categorically normalized to derive a hazard index. This hazard index is layered over a personalized vulnerability and exposure index tailored to individual users. The vulnerability and exposure indices are designed based on personal user information, categorized into three levels of severity derived from the literature. These parameters are further refined through expert opinions from both medical and non-medical fields, incorporating their insights using the Bayesian Best-Worst Method (BBWM). By amalgamating the hazard, vulnerability, and exposure indices, the system forms the UTCI-based HSRIF. This forecast is presented to users via an interactive dashboard, providing a detailed assessment of their heat stress risk over the upcoming five days.

Combined effects of ambient air pollution and temperature on mortality in Thailand

This study aimed to investigate the combined effects of air pollution and temperature on mortality in 34 provinces of Thailand by modeling temperature as a confounding factor and effect modifier, estimating the effects of air pollution at low, moderate, and high temperature categories defined by the 1st and 99th province-specific temperature percentiles. When the temperature was modeled as a confounding factor, the relative risk (RR) of mortality associated with a 10 µg/m3 increase in PM10 and PM2.5 (lag 0-2), and a 10-ppb increase in NO2 (lag 0-2) and O3 (lag 0-7) was respectively 1.0096 (95% Confidence Interval (CI): 1.0073, 1.0118), 1.0134 (95% CI: 1.0099, 1.0170), 1.0172 (95% CI: 1.0122, 1.0222), and 1.0164 (95% CI: 1.0093, 1.0236). Regarding temperature as an effect modifier, the combined effects of air pollution and temperature were observed as a U-shaped pattern, where the effects of PM10, PM2.5, NO2, and O3 on mortality were greater at low (< 1st percentile) and high (> 99th percentile) temperature days compared to those at moderate temperature days (1st - 99th percentile). The pattern of combined effects of air pollution and temperature remained robust even when different temperature percentiles were employed, except for that of NO2. Furthermore, the estimated effects of PM10, PM2.5, NO2, and O3 on mortality at high-temperature days were mitigated by high green density. Findings of this study revealed that extreme temperature (both hot and cold) could exacerbate the effect of air pollution on mortality, and higher green density mitigate the combined effects of air pollution and high temperature.

Does socioeconomic and environmental burden affect vulnerability to extreme air pollution and heat? A case-crossover study of mortality in California

BACKGROUND

Extreme heat and air pollution is associated with increased mortality. Recent evidence suggests the combined effects of both is greater than the effects of each individual exposure. Low neighborhood socioeconomic status ("socioeconomic burden") has also been associated with increased exposure and vulnerability to both heat and air pollution. We investigated if neighborhood socioeconomic burden or the combination of socioeconomic and environmental exposures ("socioenvironmental burden") modified the effect of combined exposure to extreme heat and particulate air pollution on mortality in California.

METHODS

We used a time-stratified case-crossover design to assess the impact of daily exposure to extreme particulate matter <2.5 μm (PM2.5) and heat on cardiovascular, respiratory, and all-cause mortality in California 2014-2019. Daily average PM2.5 and maximum temperatures based on decedent's residential census tract were dichotomized as extreme or not. Census tract-level socioenvironmental and socioeconomic burden was assessed with the CalEnviroScreen (CES) score and a social deprivation index (SDI), and individual educational attainment was derived from death certificates. Conditional logistic regression was used to estimate associations of heat and PM2.5 with mortality with a product term used to evaluate effect measure modification.

RESULTS

During the study period 1,514,292 all-cause deaths could be assigned residential exposures. Extreme heat and air pollution alone and combined were associated with increased mortality, matching prior reports. Decedents in census tracts with higher socioenvironmental and socioeconomic burden experienced more days with extreme PM2.5 exposure. However, we found no consistent effect measure modification by CES or SDI on combined or separate extreme heat and PM2.5 exposure on odds of total, cardiovascular or respiratory mortality. No effect measure modification was observed for individual education attainment.

CONCLUSION

We did not find evidence that neighborhood socioenvironmental- or socioeconomic burden significantly influenced the individual or combined impact of extreme exposures to heat and PM2.5 on mortality in California.

IMPACT

We investigated the effect measure modification by socioeconomic and socioenvironmental of the co-occurrence of heat and PM2.5, which adds support to the limited previous literature on effect measure modification by socioeconomic and socioenvironmental burden of heat alone and PM2.5 alone. We found no consistent effect measure modification by neighborhood socioenvironmental and socioeconomic burden or individual level SES of the mortality association with extreme heat and PM2.5 co-exposure. However, we did find increased number of days with extreme PM2.5 exposure in neighborhoods with high socioenvironmental and socioeconomic burden. We evaluated multiple area-level and an individual-level SES and socioenvironmental burden metrics, each estimating socioenvironmental factors differently, making our conclusion more robust.

Synergistic effects of air pollution and cold spells on ischemic heart disease hospitalization risk: a case-crossover study in Xinxiang, China

Air pollution and extreme weather events pose a serious threat to human health. We collected atmospheric pollution, meteorological factors, and hospitalisation data for ischemic heart disease (IHD) in Xinxiang, Henan Province, from 2016 to 2021. Using a time-stratified case-crossover design and conditional Poisson regression analysis, we explored the association between atmospheric pollutants (particulate matter with diameter ≤ 2.5 μm [PM2.5], particulate matter with diameter ≤ 10 μm [PM10], nitrogen dioxide [NO2], carbon monoxide [CO]), meteorological factors, and IHD hospitalizations. We evaluated synergistic effects using relative excess risk due to interaction (RERI), attribute proportion (AP), and synergy index (S). PM2.5, PM10, NO2, CO, relative humidity, and cold spells were significantly associated with IHD hospitalization risk. Significant interaction effects (RERI > 0, AP > 0, S > 1) were found in PM2.5-PM10-NO2 combinations. The attributable fractions were 3.4-7.3% for pollutant combinations and 8-17% during cold spells with different PM2.5 levels. Males and individuals aged ≥ 65 were more susceptible to pollutants, while females and elderly individuals showed higher sensitivity to cold spells. These findings provide evidence for optimizing extreme weather warning systems and reducing air pollution exposure to protect public health.

Imperatives and co-benefits of research into climate change and neurological disease

Evidence suggests that anthropogenic climate change is accelerating and is affecting human health globally. Despite urgent calls to address health effects in the context of the additional challenges of environmental degradation, biodiversity loss and ageing populations, the effects of climate change on specific health conditions are still poorly understood. Neurological diseases contribute substantially to the global burden of disease, and the possible direct and indirect consequences of climate change for people with these conditions are a cause for concern. Unaccustomed temperature extremes can impair the systems of resilience of the brain, thereby exacerbating or increasing susceptibility to neurological disease. In this Perspective, we explore how changing weather patterns resulting from climate change affect sleep - an essential restorative human brain activity, the quality of which is important for people with neurological diseases. We also consider the pervasive and complex influences of climate change on two common neurological conditions: stroke and epilepsy. We highlight the urgent need for research into the mechanisms underlying the effects of climate change on the brain in health and disease. We also discuss how neurologists can respond constructively to the climate crisis by raising awareness and promoting mitigation measures and research - actions that will bring widespread co-benefits.

Efficiency of case-crossover versus time-series study designs for extreme heat exposures

Background

Time-stratified case-crossover (CC) and Poisson time series (TS) are two popular methods for relating acute health outcomes to time-varying ubiquitous environmental exposures. Our aim is to compare the performance of these methods in estimating associations with rare, extreme heat exposures and mortality-an increasingly relevant exposure in our changing climate.

Methods

Daily mortality data were simulated in various scenarios similar to observed Los Angeles County data from 2014 to 2019 (N = 367,712 deaths). We treated observed temperature as either a continuous or dichotomized variable and controlled for day of week and a smooth function of time. Five temperature dichotomization cutoffs between the 80th and 99th percentile were chosen to investigate the effects of extreme heat events. In each of 10,000 simulations, the CC and several TS models with varying degrees of freedom for time were fit to the data. We reported bias, variance, and relative efficiency (ratio of variance for a "reference" TS method to variance of another method) of temperature association estimates.

Results

CC estimates had larger uncertainty than TS methods, with the relative efficiency of CC ranging from 91% under the 80th percentile cutoff to 80% under the 99th percentile cutoff. As previously reported, methods best capturing data-generating time trends generally had the least bias. Additionally, TS estimates for observed Los Angeles data were larger with less uncertainty.

Conclusions

We provided new evidence that, compared with TS, CC has increasingly poor efficiency for rarer exposures in ecological study settings with shared, regional exposures, regardless of underlying time trends. Analysts should consider these results when applying either TS or CC methods.

A Fuzzy-Based Model to Detect Hotspots of Air Pollutants During Heatwaves in Urban Settlements

High concentrations of pollutants in urban areas generate cardiovascular and respiratory problems in citizens; these are aggravated by the persistence of summer heatwaves. For this reason, in this research, we propose a fuzzy-based method for detecting air pollutant hotspots and determining critical urban areas for air pollution during heatwaves. After acquiring the pollutant concentration values recorded by monitoring stations during heatwaves, a spatial interpolation method is applied to obtain the distribution of the pollutant concentration during heatwaves and, subsequently, a fuzzification process is performed to determine urban hotspots in which the pollutant concentration assumes critical values. Finally, the critical urban areas are determined, consisting of the areas within hotspots with a high population density exposed to health risks. The method was implemented in a GIS platform and tested on an urban study area in the Lombardy region, Italy, to determine the urban areas with high criticality during the heatwaves that occurred in the summer months of 2024. The test results show that the method can provide valid support for decision makers and local administrators when evaluating which urban areas are most critical for the population due to the high rate of air pollution during heatwaves.

Climate warming may undermine sleep duration and quality in repeated-measure study of 23 million records

The impact of rising ambient temperatures on sleep and its phases under climate change is becoming increasingly concerning but remains underexplored. Sleep, consisting of non-rapid eye movement and rapid eye movement phases, is crucial for health, and insufficient sleep in either phase could have significant implications. Based on sleep monitoring data of 23 million days from 214,445 participants across mainland China, we investigated how daily average temperature affected sleep. For each 10 °C increase in ambient temperature, the odds of sleep insufficiency increased by 20.1%, while total sleep duration decreased by 9.67 minutes, with deep sleep declining the most (by 2.82%). Projections under the unrestricted (SSP5-8.5) greenhouse gas emission scenario suggest that by the end of the century, sleep insufficiency could rise by 10.50%, with an annual loss of 33.28 hours of sleep per person. These findings highlight the potential of climate warming to exacerbate sleep deprivation and degrade sleep quality, especially for the elderly, women, individuals with obesity, and regions of South, Centre and East.

Heat wave, fine particulate matter, and cardiovascular disease mortality: A time-stratified case-crossover study in Shenzhen, China

BACKGROUND

In the context of global warming, the frequency of heat wave and the concentration of fine particulate matter (PM2.5) have increased, and more people are co-exposed to air pollution and extreme heat. However, the interaction between heat wave and PM2.5 on cardiovascular disease (CVD) mortality remained largely unknown.

METHODS

We conducted a time-stratified case-crossover study of 40,169 CVD deaths in Shenzhen, China between 2013 and 2022. Meteorological data and air pollutants information were obtained based on the residential addresses from the validated grid datasets. A total of 21 heat wave definitions were constructed using various relative temperature thresholds and durations. Conditional logistic regression was used to evaluate the independent and interactive effects of exposure to heat wave and PM2.5 on CVD mortality.

RESULTS

The odds ratios (ORs) and 95 % confidence intervals (CIs) for CVD mortality associated with heat waves ranged from 1.17 (95 % CI: 1.001,1.36) to 1.91 (95 % CI: 1.42, 2.56). For every increase of 10 µg/m³ in PM2.5 exposure, the ORs (95 % CI) for CVD mortality ranged from 1.0283 (95 % CI: 1.0162, 1.0406) to 1.029 (95 % CI: 1.0169, 1.0413). There was a synergistic effect between heat wave and PM2.5 exposures on CVD mortality. It was estimated that up to 2.03 % of CVD deaths were attributable to heat wave and PM2.5 levels exceeding the interim target 4 in the World Health Organization air quality guidelines (≥ 25 μg/m3), resulting in 816 premature deaths. Females and individuals over 75 years old were vulnerable populations.

CONCLUSIONS

Heat wave and PM2.5 exposures individually and synergistically contributed to increased risks of CVD mortality. Our findings indicate that reducing exposure to both heat wave and PM2.5 may yield significant health benefits and prevent a significant portion of premature deaths from CVDs.

Interventions to reduce the effects of air pollution and of extreme heat on maternal, newborn, and child health outcomes: a mapping of the literature

Background

There is an increasing awareness of the ongoing and projected impacts of air pollution and of extreme heat on maternal, newborn, and child health (MNCH) outcomes, showing significant short and long-term health problems. There is a dearth of information available for policy makers on interventions that have been implemented to reduce the impact on MNCH, impeding the integration of action into health planning. This paper presents an inventory of interventions aimed at reducing the effects of these two climate hazards on MNCH.

Methods

We conducted a scoping review of articles published in three databases and grey literature to identify and map interventions implemented to address the impact of air pollution and/or extreme heat on MNCH. Items were included if published between January 2016 and November 2022, regardless of language, and as this is an inventory, regardless of if the intervention was evaluated. Over 32 700 journal items were reviewed for inclusion and a sample of grey literature from web-based searches.

Results

A final inventory of 76 items were included. Interventions identified were primarily based in the Global North (n = 51), with the largest proportion in the USA (n = 17), while 32 items were based in the Global South. Fifty-seven items focused on air pollution, 18 on extreme heat, and one on both. Interventions were categorised in four adapted socioecological components: (i) individual and household interventions (n = 30), (ii) community and service interventions (n = 18), (iii) structural interventions and urban landscape interventions (n = 15), (iv) policy interventions (n = 16). Most items were focused on child health outcomes (n = 65); 61 items were evaluated.

Conclusions

This scoping review maps interventions implemented and proposes a categorisation of these to initiate reflections and dialogue on what has been done and how to start building an evidence base. The review also highlights gaps in interventions and the knowledge base, with most interventions implemented to address air pollution, in the Global North and most addressing child health need. As country programmes seek to address the impact of climate change on MNCH, additional efforts are needed to better understand what has been done, document lessons learned, agree on common outcome measurements and feasible study designs for evaluation to start building the evidence base.

Air pollution, temperature and mumps: A time-series study of independent and interaction effects

Understanding the associations of air pollutants and temperature with the incidence of mumps, and exploring the interaction effects of heat index (HI) and air pollutants, are crucial for disease intervention under the context of climate change. This time-series study was conducted in Jining city using data on daily mumps cases, meteorological factors and air pollutants obtained from 2015 to 2021. Distributed lag models combined with quasi-Poisson regressions were applied to examine these associations. The findings indicated a heightened risk of mumps in correlation with elevated exposure to PM2.5, PM10, and NO2. Specifically, the precent changes in the risk of mumps were 0.6 % and 0.3 % associated with per 10 μg/m3 increment in PM2.5 and PM10 at lag0 day, respectively. The cumulative effects of temperature were significantly associated with mumps, showing a "U"-shape pattern. Compared to the minimum effect value of 4 ℃, relative risk (RRs) of mumps for high and low temperature (at the 90th and 10th percentiles) were 1.961 (1.106-3.477) and 1.058 (0.976-1.158), respectively. There were significant synergistic effects between particulate matters (PMs) and HI. Compared to the low concentrations of PMs and normal heat index (NHI), co-exposure to high PMs and high heat index (HHI) has the highest risk (RRPM2.5: 1.32 and, RRPM10: 1.30). Individuals aged over 5 years was susceptible to particulate matters (PMs). Our results suggested that mitigating both PM and high temperature exposure may bring more health benefits for mumps incidence.

The interactive effect of extreme weather events and PM2.5 on respiratory health among the elderly: a case-crossover study in a high-altitude city

With climate change posing increasing threats and aging populations, understanding the complex relationship between extreme temperatures, PM2.5 pollution, and respiratory health among the elderly is crucial. While some research exists, there remains a significant gap in studying the combined effects of heat waves, cold spells, and PM2.5 on elderly respiratory health in high-altitude regions. We collected data from Xining (2016-2021), including respiratory disease outpatient visits, meteorological, and pollutant data. Employing a case-crossover design and conditional Poisson regression analysis, we investigated the individual and interactive impacts of heat wave, cold spell, and PM2.5 on outpatient visits for respiratory disease among the elderly. We used the relative excess odds due to interaction (REOI), proportion attributable to interaction (AP), and synergy index (S) as quantitative indicators of interaction. Our analysis revealed significant associations between heat wave, cold spell, PM2.5 exposure, and outpatient visits for respiratory disease among the elderly, with odds ratios of 1.10 (95%CI: 1.06, 1.15) and 1.16 (95%CI: 1.13, 1.20), respectively. Moreover, a synergistic effect between cold spell and PM2.5 was observed, particularly affecting vulnerable groups such as female and those aged ≥ 80. The combined exposure to cold spell and elevated PM2.5 levels was estimated to contribute to up to 0.18 (95%CI: 0.17, 0.27) of respiratory outpatient visits. This study underscores the need for urgent interventions, such as reducing PM2.5 exposure and enhancing extreme weather warning systems, to protect the respiratory health of the elderly, especially in high-altitude regions.

Short-term effects of combined environmental factors on respiratory disease mortality in Qingdao city: A time-series investigation

BACKGROUND

It is crucial to comprehend the interplay between air pollution and meteorological conditions in relation to population health within the framework of "dual-carbon" targets. The purpose of this study was to investigate the impact of intricate environmental factors, encompassing both meteorological conditions and atmospheric pollutants, on respiratory disease (RD) mortality in Qingdao, a representative coastal city in China.

METHODS

The RD mortality cases were collected from the Chronic Disease Surveillance Monitoring System in Qingdao during Jan 1st, 2014 and Dec 31st, 2020. The distributed-lag nonlinear model and generalized additivity model were used to assess the association between daily mean temperature (DMT), air pollutant exposure and RD mortality. To ascertain the robustness of the model and further investigate this relationship, a stratified analysis and sensitivity analysis were conducted to mitigate potential confounding factors.

RESULTS

A total of 19,905 mortalities from RD were recorded. The minimum mortality temperature (MMT) was determined to be 23.5°C, and DMT and RD mortality showed an N-shaped relationship. At the MMT of 23.5°C, the cumulative relative risk (cumRR) for mortality within a lag period of 0-14 days from the highest temperature (31°C) was estimated at 2.114 (95% confidence interval [CI]: 1.475 ~ 3.028). The effect value of particulate matter (PM) also increased with a longer cumulative lag time. In the single pollutant model, the highest risk of RD mortality was observed on the lag1-day of per 10 μg/m3 increase in PM2.5 exposure, with an excess risk ratio (ER) of 0.847% (95% CI: 0.335% ~ 1.362%). The largest cumulative effect was found at a lag of 8 days, with an ER of 1.546% (95% CI: 0.483% ~ 2.621%). A similar trend was found for PM10. For O3 exposure, the highest risk was observed on the lag1-day of per 10 μg/m3 increase, with an ER of 1.073% (95% CI: 0.502% ~ 1.647%), and the largest cumulative effect occurred at a lag of 2 days with an ER of 1.113% (95%CI: 0.386% ~ 1.844%). Results from the dual-pollutants model demonstrated that the effect of PM on the risk of RD mortality remained significant and slightly increased in magnitude. Moreover, composite pollutants exhibited a higher risk effect, reaching its peak after one week; however, there was a decrease in single-day cumulative effects as more pollutant types were included. Subgroup analysis showed that females, elderly individuals, and those exposed during warm seasons demonstrated greater susceptibility to PM exposure.

CONCLUSION

The present study revealed a significant association between short-term exposure to high temperature, PM2.5, PM10 and O3 and the risk of RD mortality in Qingdao, even in dual- and composite-pollutants models. Furthermore, our findings indicate that females, the elderly population, and warm seasons exhibit heightened sensitivity to PM exposure.

Interactive effects between extreme temperatures and PM2.5 on cause-specific mortality in thirteen U.S. states

The extent and robustness of the interaction between exposures to heat and ambient PM2.5 is unclear and little is known of the interaction between exposures to cold and ambient PM2.5. Clarifying these interactions, if any, is crucial due to the omnipresence of PM2.5 in the atmosphere and increasing scope and frequency of extreme temperature events. To investigate both of these interactions, we merged 6 073 575 individual-level mortality records from thirteen states spanning seventeen years with 1 km daily PM2.5 predictions from sophisticated prediction model and 1 km meteorology from Daymet V4. A time-stratified, bidirectional case-crossover design was used to control for confounding by individual-level, long-term and cyclic weekly characteristics. We fitted conditional logistic regressions with an interaction term between PM2.5 and extreme temperature events to investigate the potential interactive effects on mortality. Ambient PM2.5 exposure has the greatest effect on mortality by all internal causes in the 2 d moving average exposure window. Additionally, we found consistently synergistic interactions between a 10 μg m-3 increase in the 2 d moving average of PM2.5 and extreme heat with interaction odds ratios of 1.013 (95% CI: 1.000, 1.026), 1.024 (95% CI: 1.002, 1.046), and 1.033 (95% CI: 0.991, 1.077) for deaths by all internal causes, circulatory causes, and respiratory causes, respectively, which represent 75%, 156%, and 214% increases in the coefficient estimates for PM2.5 on those days. We also found evidence of interactions on the additive scale with corresponding relative excess risks due to interaction (RERIs) of 0.013 (95% CI: 0.003, 0.021), 0.020 (95% CI: 0.008, 0.031), and 0.017 (95% CI: -0.015, 0.036). Interactions with other PM2.5 exposure windows were more pronounced. For extreme cold, our results were suggestive of an antagonistic relationship. These results suggest that ambient PM2.5 interacts synergistically with exposure to extreme heat, yielding greater risks for mortality than only either exposure alone.

Bidirectional effect modifications of temperature and PM2.5 on myocardial infarction morbidity and mortality in Beijing, China from 2007 to 2021

BACKGROUND

Ambient temperatures and PM2.5 can trigger myocardial infarction (MI), while little is known about the complex interplay between these two factors on MI, especially morbidity.

OBJECTIVES

To investigate bidirectional effect modifications of temperature and PM2.5 on MI morbidity and mortality.

METHODS

A time-stratified case-crossover study was conducted utilizing high-resolution data of temperature and PM2.5, along with 498,077 MI cases from the citywide registry in Beijing, China from 2007 to 2021. A conditional logistic regression model combined with a distributed lag non-linear model was used to examine linear and categorical effect modifications of temperature and PM2.5 on MI morbidity and mortality.

RESULTS

The PM2.5 effect on MI morbidity, modified by temperature, showed a progressive increase of odds ratio from 1.013 (95 % CI: 1.001, 1.025) to 1.027 (95 % CI: 1.012, 1.042) with rising temperatures. Stratified analysis revealed a greater PM2.5 effect in high temperature strata (1.049, 95 % CI: 1.029, 1.069) compared with low strata (1.007, 95 % CI: 0.993, 1.021) on MI morbidity (PZ test<0.001). The temperature effect on MI morbidity was also modified by PM2.5, with a gradual upward risk trend observed with increasing PM2.5 concentration. Specifically, the heat wave effect was greater at high PM2.5 concentration strata (1.097, 95 % CI: 1.042, 1.155) than at low strata (0.954, 95 % CI: 0.890, 1.023) (PZ test=0.002). The cold spell effect was greater at high PM2.5 concentration strata (1.181, 95 % CI: 1.117, 1.249) than at low strata (0.883, 95 % CI: 0.740, 1.053) (PZ test=0.002). A similar bidirectional effect modification of temperature and PM2.5 was also found in MI mortality.

CONCLUSIONS

Temperature and PM2.5 bidirectionally modify their effect on MI morbidity and mortality. Elevated temperatures exacerbate PM2.5 effect, while increased concentrations of PM2.5 amplify temperature effect. The combined effect of temperatures and PM2.5 should be stressed, encompassing not only extreme conditions but also the entire range of exposures.

The graded heat-health risk forecast and early warning with full-season coverage across China: a predicting model development and evaluation study

Background

Due to global climate change, high temperature and heatwaves have become critical issues that pose a threat to human health. An effective early warning system is essential to mitigate the health risks associated with high temperature and heatwaves. However, most of the current heatwave early warning systems are not adequately developed based on the heat-health risk model, and the health impact of hot weather has not been well managed in most countries.

Methods

This study proposed a "full-season coverage and population health-oriented graded early-warning" concept and developed a heat-health surveillance, forecast and early warning (HHSEW) model. The exposure-response (E-R) relationship between temperature and mortality was analyzed through a two-stage approach using time-series analysis data from 323 counties across China for the period 2013-2018. The premature mortality curve at each temperature percentile was plotted and four temperature-percentile points on the curve were determined as the thresholds of the pre-warning and warning levels 1-3 based on the variations in the rates of the segmental slopes on the curve. The HHSEW model was evaluated by comparing the frequency, the mortality risk of all-cause and cause-specific diseases, the predicted numbers of premature deaths, and the heat-related health economic burden at each warning level with those of the current high temperature early warning systems.

Findings

The HHSEW model determined five levels, including seasonal surveillance, pre-warning, and warning levels 1-3. There was a gradual increase in the mortality risks of all-cause and cause-specific diseases along with the increase of warning levels. The risk of all-cause mortality increased by 9.79% (95% CI: 8.59%-11.01%), 22.62% (95% CI: 19.49%-25.83%), 28.36% (95% CI: 24.72%-32.10%), and 33.87% (95% CI: 28.89%-39.06%) at the pre-warning level, warning level 1, warning level 2, and warning level 3, respectively. Through our HHSEW model, 94,008 heat-related all-cause deaths were predicted annually in the 337 major cities of China, which was much larger than the number (14,858) of the China Meteorological Administration (CMA) heatwave early-warning system currently used in China. It was estimated that the proper implementation of the HHSEW-based early warning system would save 220 billion CNY in heat-related health burden compared to the current heatwave early-warning system.

Interpretation

The HHSEW model has been proven to surpass the current heatwave early warning system. With its full-season coverage and graded warning levels for heat-related health risks, the HHSEW model and system can provide timely early warnings to the public, leading to significant health benefits. This methodology, labeled "full-season coverage and population health-oriented graded early-warning", should be implemented globally to mitigate the escalating health risks associated with high temperature.

Funding

National Natural Science Foundation of China (82425051, 42071433, 42305196, 82241051) and the Special Foundation of Basic Science and Technology Resources Survey of Ministry of Science and Technology of China (2017FY101204).

Interactive effects of atmospheric oxidising pollutants and heat waves on the risk of residential mortality

BACKGROUND

The impact of heat waves and atmospheric oxidising pollutants on residential mortality within the framework of global climate change has become increasingly important.

OBJECTIVE

In this research, the interactive effects of heat waves and oxidising pollutants on the risk of residential mortality in Fuzhou were examined. Methods We collected environmental, meteorological, and residential mortality data in Fuzhou from 1 January 2016, to 31 December 2021. We then applied a generalised additive model, distributed lagged nonlinear model, and bivariate three-dimensional model to investigate the effects and interactions of various atmospheric oxidising pollutants and heat waves on the risk of residential mortality.

RESULTS

Atmospheric oxidising pollutants increased the risk of residential mortality at lower concentrations, and O3 and Ox were positively associated with a maximum risk of 2.19% (95% CI: 0.74-3.66) and 1.29% (95% CI: 0.51-2.08). The risk of residential mortality increased with increasing temperature, with a strong and long-lasting effect and a maximum cumulative lagged effect of 1.11% (95% CI: 1.01, 1.23). Furthermore, an interaction between atmospheric oxidising pollutants and heat waves may have occurred: the larger effects in the longest cumulative lag time on residential mortality per 10 µg/m3 increase in O3, NO2 and Ox during heat waves compared to non-heat waves were [-3.81% (95% CI: -14.82, 8.63)]; [-0.45% (95% CI: -2.67, 1.81)]; [67.90% (95% CI: 11.55, 152.71)]; 16.37% (95% CI: 2.43, 32.20)]; [-3.00% (95% CI: -20.80, 18.79)]; [-0.30% (95% CI: -3.53, 3.04)]. The risk on heat wave days was significantly higher than that on non-heat wave days and higher than the separate effects of oxidising pollutants and heat waves.

CONCLUSIONS

Overall, we found some evidence suggesting that heat waves increase the impact of oxidising atmospheric pollutants on residential mortality to some extent.

Independent and compound characteristics of PM2.5, ozone, and extreme heat pollution events in Korea

In the context of global warming and rapid urbanization, the frequency of simultaneous occurrence of extreme high temperature, ozone pollution, and particulate matter pollution has increased. However, independent and composite characterization of PM2.5, ozone, and extreme heat pollution events has not been systematically analyzed so far. This study combines meteorological and pollutant data with the GTWR model in an attempt to reveal the patterns of independent heat days (IHD), compound PM2.5-ozone pollution (CPOP), and composite heat-PM2.5-ozone pollution (CHPOP). In this study, we found that in July and August in South Korea, the frequency of CPOP events, the frequency of CHPOP events, and the composite proportion of CHPOP events all show an overall pattern of east-high and west-low; the atmospheric circulation patterns of the three extreme events have brought about more stagnation conditions, which may be related to cyclone activity; the occurrence of CPOP events is mainly accompanied by a continuous decrease in relative humidity and cloud cover, both IHD and CHPOP events occur with increasing temperatures, decreasing cloudiness, and anomalously high pressures; under the same events, excluding relative humidity, PM2.5 and ozone showed similar conditions with respect to the dependence on temperature, wind speed, barometric pressure, cloudiness, and nitrogen dioxide. This study identified the independent and composite characteristics of PM2.5, ozone, and extreme heat pollution events, which can enhance early prediction and pollution prevention of these extreme events.

Wildfire Smoke: Health Effects, Mechanisms, and Mitigation

Wildfires are becoming more frequent and intense on a global scale, raising concerns about their acute and long-term effects on human health. We conducted a systematic review of the current epidemiological evidence on wildfire health risks and a meta-analysis to investigate the association between wildfire smoke exposure and various health outcomes. We discovered that wildfire smoke increases the risk of premature deaths and respiratory morbidity in the general population. Meta-analysis of cause-specific mortality and morbidity revealed that wildfire smoke had the strongest associations with cardiovascular mortality (RR: 1.018, 95% CI: 1.014-1.021), asthma hospitalization (RR: 1.054, 95% CI: 1.026-1.082), and asthma emergency department visits (RR: 1.117, 95% CI: 1.035-1.204) in the general population. Subgroup analyses of age found that adults and elderly adults were more susceptible to the cardiopulmonary effects of wildfire smoke. Next, we systematically addressed the toxicological mechanisms of wildfire smoke, including direct toxicity, oxidative stress, inflammatory reactions, immune dysregulation, genotoxicity and mutations, skin allergies, inflammation, and others. We discuss wildfire smoke risk mitigation strategies including public health interventions, regulatory measures, and personal actions. We conclude by highlighting current research limitations and future directions for wildfire research, such as elucidating the complex interactions of wildfire smoke components on human health, developing personalized risk assessment tools, and improving resilience and adaptation strategies to mitigate the health effects of wildfires in changing climate.

Short-term exposure to PM2.5 constituents, extreme temperature events and stroke mortality

BACKGROUND

Fine particulate matter (PM2.5) pollution and extreme temperature events (ETEs) are main environmental threats to human health. Elevated stroke mortality has been growingly linked to PM2.5 mass exposure, while its relationship with PM2.5 constituents was extensively unstudied across the globe. Additionally, no prior assessments have investigated the interactive effects of PM2.5 constituents and ETEs on stroke mortality.

METHODS

Province-wide records of 320,372 stroke deaths collected in eastern China during 2016-2019 were analyzed using an individual-level time-stratified case-crossover design. Daily gridded estimates of PM2.5 mass and its major constituents (i.e., black carbon [BC], organic matter [OM], ammonium [NH4+], sulfate [SO42-], and nitrate [NO3-]) were assigned to stroke cases on case days and control days at the residential address. We assessed 12 ETEs defined by multiple combinations of air temperature thresholds (2.5-10th percentiles for cold spell, 90-97.5th percentiles for heat wave) and durations (2-4 days). Conditional logistic regression model was applied to investigate associations of short-term exposure to PM2.5 constituents and ETEs with stroke mortality. Odds ratio and its 95% confidence interval (CI) were assessed for an interquartile range (IQR) increase in each PM2.5 constituent and on ETEs days compared with non-ETEs days. Additive interactive effects were quantitatively evaluated via relative excess odds due to interaction (REOI), attributable proportion due to interaction (AP), and synergy index (SI).

RESULTS

Elevated overall stroke mortality was significantly related to PM2.5 constituents, with the largest odds observed for NO3- (1.04, 95% CI: 1.03-1.04, IQR = 11.25 μg/m3), followed by OM (1.03, 1.03-1.04, IQR = 7.97 μg/m3), NH4+ (1.03, 1.02-1.04, IQR = 6.66 μg/m3), BC (1.03, 1.02-1.03, IQR = 1.41 μg/m3), and SO42- (1.03, 1.02-1.03, IQR = 6.67 μg/m3). Overall, higher risks of stroke mortality were identified in analyses using more rigorous thresholds and lengthened durations of ETEs definitions, ranging from 1.19 (1.17-1.21) to 1.55 (1.51-1.60) for heat wave, and 1.03 (1.02-1.05) to 1.11 (1.08-1.15) for cold spell, respectively. We observed consistent evidence for the synergistic effects of heat wave and PM2.5 constituents on both ischemic and hemorrhagic stroke mortality, where compound exposures to heat wave and secondary inorganic aerosols (i.e., NO3-, SO42-, and NH4+) posed greater increases in risk (0.23< REOI <0.81, 0.16< AP <0.39, and 2.63< SI <8.19).

CONCLUSIONS

Short-term exposure to both PM2.5 constituents and ETEs were associated with heightened stroke mortality, and heat wave may interact synergistically with PM2.5 constituents to trigger stroke deaths.

Challenges posed by climate hazards to cardiovascular health and cardiac intensive care: implications for mitigation and adaptation

Global warming, driven by increased greenhouse gas emissions, has led to unprecedented extreme weather events, contributing to higher morbidity and mortality rates from a variety of health conditions, including cardiovascular disease (CVD). The disruption of multiple planetary boundaries has increased the probability of connected, cascading, and catastrophic disasters with magnified health impacts on vulnerable populations. While the impact of climate change can be manifold, non-optimal air temperatures (NOTs) pose significant health risks from cardiovascular events. Vulnerable populations, especially those with pre-existing CVD, face increased risks of acute cardiovascular events during NOT. Factors such as age, socio-economic status, minority populations, and environmental conditions (especially air pollution) amplify these risks. With rising global surface temperatures, the frequency and intensity of heatwaves and cold spells are expected to increase, emphasizing the need to address their health impacts. The World Health Organization recommends implementing heat-health action plans, which include early warning systems, public education on recognizing heat-related symptoms, and guidelines for adjusting medications during heatwaves. Additionally, intensive care units must be prepared to handle increased patient loads and the specific challenges posed by extreme heat. Comprehensive and proactive adaptation and mitigation strategies with health as a primary consideration and measures to enhance resilience are essential to protect vulnerable populations and reduce the health burden associated with NOTs. The current educational review will explore the impact on cardiovascular events, future health projections, pathophysiology, drug interactions, and intensive care challenges and recommend actions for effective patient care.

Inequities in air pollution on stroke mortality among Older Americans: a U.S. nationwide analysis

Background

Air pollution is a known risk factor for cardiovascular diseases, including stroke. This study examines the impact of county-level air pollution on ischemic and hemorrhagic stroke mortality among U.S. individuals aged 65 and older, emphasizing racial and socioeconomic disparities.

Methods

Using data from the Center for Disease Control (CDC) Interactive Atlas of Heart Disease and Stroke, we analyzed county-level ischemic stroke mortality rates for older residents between 2016 and 2020. The data on air pollution at the county level, specifically particulate matter (PM2.5) levels, were obtained from the CDC. We applied multivariable linear and logistic regression models to examine the association between PM2.5 levels and stroke mortality, as well as the probability of meeting the Environmental Protection Agency (EPA) air quality standards.

Results

County-level analysis revealed a significant correlation (R = 0.68, R2 = 0.48, p < 0.001) between PM2.5 levels and overall stroke mortality. For every 1 μg/m3 increase in PM2.5, there was an increase of 1.89 ischemic stroke deaths per 100,000 residents. Racial and socioeconomic disparities were evident. Counties with predominantly Black populations exhibited a stark disparity, with each 1 μg/m3 increase in PM2.5 correlating with a significant rise in mortality, amounting to 5.81 additional deaths per 100,000 residents. Persistently poor counties displayed vulnerability, experiencing a 4.05 increase in ischemic stroke deaths per 100,000 residents for every 1 μg/m3 increase in PM2.5 levels. Conversely, in counties with a White majority and counties without a persistent state of poverty, the associated increases in stroke mortality per 100,000 residents for every 1 μg/m3 rise in county-level PM2.5 were 1.85 and 1.60, respectively. Counties with a majority of Black residents were over twice as likely to be non-compliant with EPA air quality standards compared to predominantly White counties (aOR 2.36 95% CI: 1.27-4.38, p = 0.006).

Conclusion

This study underscores the significant impact of county-level air pollution, particularly PM2.5, on ischemic stroke mortality among older U.S. residents. Our findings indicate that counties with predominantly Black populations and those experiencing persistent poverty not only suffer from higher mortality rates but also are more likely to be non-compliant with EPA air quality standards. Targeted interventions and policies are urgently needed to reduce air pollution in these vulnerable communities and promote equitable public health outcomes.

Does the morphology of residential greenspaces contribute to the development of a cardiovascular-healthy city?

BACKGROUNDS

Greenspaces are indispensable for the construction of a healthy city. Research has shown that greenspaces contribute to the reduction of cardiovascular risks. However, the role of greenspace morphology in the development of a healthy city is not well understood.

METHODS

Our study utilized data from a cardiovascular disease screening cohort comprising 106,238 residents in Anhui Province, China, aged between 35 and 75 years. We calculated landscape indices of each participant using high-resolution land cover data to measure the greenness, fragmentation, connectivity, aggregation, and shape of greenspaces. We used a multivariate linear regression model to assess the associations between these landscape indices and triglyceride risk, and employed a structural equation model to explore the potential contributions of heatwaves and fine particulate matter (PM2.5) to this association.

RESULTS

Overall, triglyceride was expected to increase by 0.046% (95% CI: 0.040%, 0.052%) with a 1% increase in the percentage of built-up area. Conversely, an increase in the percentage of greenspace was associated with a 0.270% (95% CI: 0.337%, -0.202%) decrease in triglyceride levels. Furthermore, when the total greenspace was held constant, the shape, connectedness, and aggregation of greenspace were inversely correlated with triglyceride levels, with effects of -0.605% (95% CI: 1.012%, -0.198%), -0.031% (95% CI: 0.039%, -0.022%), and -0.049% (95% CI: 0.058%, -0.039%), respectively. Likewise, the protective effect of the area-weighed mean shape index was higher than that of the total amount of greenspace. The stratification results showed that urban residents benefited more from greenspace exposure. Greenspace morphology can minimize triglyceride risk by reducing pollutant and heatwaves, with aggregation having the greatest effect on reducing pollutants whereas fragmentation is more efficient at reducing heatwaves.

CONCLUSION

Exposure to the greenspaces morphology is associated with a reduction in triglyceride risk. The study has important practical and policy implications for early health monitoring and the spatial layout of greenspace and will provide scientific information for healthy urban planning by reducing unfavorable health consequences.

Media-Based Post-Event Impact Analysis of the 2021 Heat Dome in Canada

The unprecedented 2021 Heat Dome caused wide-ranging and long-lasting impacts in western Canada, including 619 confirmed heat-related deaths in British Columbia, a doubling of emergency medical calls, increased hospitalisations, infrastructure failures and stress on plants and animals. However, such varied socio-economic consequences of extreme heat can be challenging to capture using a single post-event analysis method. Therefore, there is a need to explore alternative approaches and data sources. Using the 2021 Heat Dome as a case study, a post-event analysis using online news media articles (n = 2909) from 5 subscription news databases and a grey literature search was conducted to identify the socio-economic impacts of the extreme heat event in Canada. The articles reported a wide range of effects to the natural environment (n = 1366), social infrastructure and services (n = 1121), human health (n = 1074), critical infrastructure (n = 988) and the private sector (n = 165). The media-based post-event analysis captured various impacts, some of which have not been identified through other data sources and approaches. Overall, we show that media analysis can complement traditional post-event analysis methods and provide additional perspectives to governments and public health and safety officials.

Extreme temperatures, PM2.5 and trajectories of impaired thyroid hormone sensitivity: A longitudinal study of patients with schizophrenia

BACKGROUND

The climate change scenario has witnessed an increase in extreme temperature events (ETEs), including heat waves and cold spells, and a heightened occurrence of compounding with fine particulate matter (PM2.5). However, the impact of this phenomenon on the sensitivity to thyroid hormones (THs) in humans is unclear, especially in a group as specific as schizophrenia.

METHODS

A longitudinal study was constructed using longitudinal measurements of thyroid function in schizophrenia in the Anhui Mental Health Center. The latent growth mixture model was applied to assess the optimal trajectory of change in impaired THs sensitivity. We then used logistic regression to explore associations between heat waves, cold spells, and PM2.5 with impaired THs sensitivity trajectories in the total population and different gender and age subgroups. Furthermore, the effect of the frequency, intensity, and duration of ETEs in the above associations was explored, as well as an assessment of the interaction between ETEs and PM2.5.

RESULTS

Among 931 participants, we identified two classifications of trajectories of impaired THs sensitivity: "Low-stable" (n = 836, 89.80 %) and "Rise-slight down" (n = 95, 10.20 %). Logistic regression showed significant associations between each additional day of heat waves (≥3 days with temperature thresholds above the 95th percentile) and cold spells (≥3 days with temperature thresholds below the 5th percentile) and "Rise-slight down" trajectory, with odds ratios (95 % confidence intervals) of 1.06 (1.02, 1.10) and 1.19 (1.14, 1.24), respectively, and the strength of this association increased with the intensity and duration of ETEs. Subgroup analyses indicated that the association was more pronounced in males and the age group above 40 years. Furthermore, PM2.5 was found to interact with heat waves, with high concentrations exacerbating the effects of heat waves.

CONCLUSIONS

Our findings suggest that mitigating both ETEs and PM2.5 exposures may bring health co-benefits in preventing thyroid impairment in schizophrenia.

Climate change and public health in California: A structured review of exposures, vulnerable populations, and adaptation measures

California faces several serious direct and indirect climate exposures that can adversely affect public health, some of which are already occurring. The public health burden now and in the future will depend on atmospheric greenhouse gas concentrations, underlying population vulnerabilities, and adaptation efforts. Here, we present a structured review of recent literature to examine the leading climate risks to public health in California, including extreme heat, extreme precipitation, wildfires, air pollution, and infectious diseases. Comparisons among different climate-health pathways are difficult due to inconsistencies in study design regarding spatial and temporal scales and health outcomes examined. We find, however, that the current public health burden likely affects thousands of Californians each year, depending on the exposure pathway and health outcome. Further, while more evidence exists for direct and indirect proximal health effects that are the focus of this review, distal pathways (e.g., impacts of drought on nutrition) are more uncertain but could add to this burden. We find that climate adaptation measures can provide significant health benefits, particularly in disadvantaged communities. We conclude with priority recommendations for future analyses and solution-driven policy actions.

Effects of Coexposure to Air Pollution from Vegetation Fires and Extreme Heat on Mortality in Upper Northern Thailand

Background: understanding the effects of coexposure to compound extreme events, such as air pollution and extreme heat, is important for reducing current and future health burdens. This study investigated the independent and synergistic effects of exposure to air pollution from vegetation fires and extreme heat on all-cause mortality in Upper Northern Thailand. Methods: we used a time-stratified case-crossover study design with a conditional quasi-Poisson model to examine the association between mortality and coexposure to air pollution due to vegetation fire events (fire-PM2.5) and extreme heat. Extreme heat days were defined using the 90th and 99th percentile thresholds for daily maximum temperature. Results: we observed a significant positive excess risk of mortality due to independent exposure to fire-PM2.5 and extreme heat, but not an interactive effect. All-cause mortality risk increased by 0.9% (95% confidence interval (CI): 0.1, 1.8) for each 10 μg/m3 increase in fire-PM2.5 on the same day and by 12.8% (95% CI: 10.5, 15.1) on extreme heat days (90th percentile) relative to nonextreme heat days. Conclusion: this study showed that exposure to PM2.5 from vegetation fires and extreme heat independently increased all-cause mortality risk in UNT. However, there was no evidence of a synergistic effect of these events.

A Review of the Interactive Effects of Climate and Air Pollution on Human Health in China

PURPOSE OF REVIEW

Through a systematic search of peer-reviewed epidemiologic studies, we reviewed the literature on the human health impacts of climate and ambient air pollution, focusing on recently published studies in China. Selected previous literature is discussed where relevant in tracing the origins.

RECENT FINDINGS

Climate variables and air pollution have a complex interplay in affecting human health. The bulk of the literature we reviewed focuses on the air pollutants ozone and fine particulate matter and temperatures (including hot and cold extremes). The interaction between temperature and ozone presented substantial interaction, but evidence about the interactive effects of temperature with other air pollutants is inconsistent. Most included studies used a time-series design, usually with daily mean temperature and air pollutant concentration as independent variables. Still, more needs to be studied about the co-occurrence of climate and air pollution. The co-occurrence of extreme climate and air pollution events is likely to become an increasing health risk in China and many parts of the world as climate changes. Climate change can interact with air pollution exposure to amplify risks to human health. Challenges and opportunities to assess the combined effect of climate variables and air pollution on human health are discussed in this review. Implications from epidemiological studies for implementing coordinated measures and policies for addressing climate change and air pollution will be critical areas of future work.

Cold waves and fine particulate matter in high-altitude Chinese cities: assessing their interactive impact on outpatient visits for respiratory disease

BACKGROUND

Extreme weather events like heatwaves and fine particulate matter (PM2.5) have a synergistic effect on mortality, but research on the synergistic effect of cold waves and PM2.5 on outpatient visits for respiratory disease, especially at high altitudes in climate change-sensitive areas, is lacking.

METHODS

we collected time-series data on meteorological, air pollution, and outpatient visits for respiratory disease in Xining. We examined the associations between cold waves, PM2.5, and outpatient visits for respiratory disease using a time-stratified case-crossover approach and distributional lag nonlinear modeling. Our analysis also calculated the relative excess odds due to interaction (REOI), proportion attributable to interaction (AP), and synergy index (S). We additionally analyzed cold waves over time to verify climate change.

RESULTS

Under different definitions of cold waves, the odds ratio for the correlation between cold waves and outpatient visits for respiratory disease ranged from 0.95 (95% CI: 0.86, 1.05) to 1.58 (1.47, 1.70). Exposure to PM2.5 was significantly associated with an increase in outpatient visits for respiratory disease. We found that cold waves can synergize with PM2.5 to increase outpatient visits for respiratory disease (REOI > 0, AP > 0, S > 1), decreasing with stricter definitions of cold waves and longer durations. Cold waves' independent effect decreased over time, but their interaction effect persisted. From 8.1 to 21.8% of outpatient visits were due to cold waves and high-level PM2.5. People aged 0-14 and ≥ 65 were more susceptible to cold waves and PM2.5, with a significant interaction for those aged 15-64 and ≥ 65.

CONCLUSION

Our study fills the gap on how extreme weather and PM2.5 synergistically affect respiratory disease outpatient visits in high-altitude regions. The synergy of cold waves and PM2.5 increases outpatient visits for respiratory disease, especially in the elderly. Cold wave warnings and PM2.5 reduction have major public health benefits.

Effects of the interaction between cold spells and fine particulate matter on mortality risk in Xining: a case-crossover study at high altitude

Background

With global climate change, the health impacts of cold spells and air pollution caused by PM2.5 are increasingly aggravated, especially in high-altitude areas, which are particularly sensitive. Exploring their interactions is crucial for public health.

Methods

We collected time-series data on meteorology, air pollution, and various causes of death in Xining. This study employed a time-stratified case-crossover design and conditional logistic regression models to explore the association between cold spells, PM2.5 exposure, and various causes of death, and to assess their interaction. We quantitatively analyzed the interaction using the relative excess odds due to interaction (REOI), attributable proportion due to interaction (AP), and synergy index (S). Moreover, we conducted stratified analyses by average altitude, sex, age, and educational level to identify potential vulnerable groups.

Results

We found significant associations between cold spells, PM2.5, and various causes of death, with noticeable effects on respiratory disease mortality and COPD mortality. We identified significant synergistic effects (REOI>0, AP > 0, S > 1) between cold spells and PM2.5 on various causes of death, which generally weakened with a stricter definition of cold spells and longer duration. It was estimated that up to 9.56% of non-accidental deaths could be attributed to concurrent exposure to cold spells and high-level PM2.5. High-altitude areas, males, the older adults, and individuals with lower educational levels were more sensitive. The interaction mainly varied among age groups, indicating significant impacts and a synergistic action that increased mortality risk.

Conclusion

Our study found that in high-altitude areas, exposure to cold spells and PM2.5 significantly increased the mortality risk from specific diseases among the older adults, males, and those with lower educational levels, and there was an interaction between cold spells and PM2.5. The results underscore the importance of reducing these exposures to protect public health.

Grouped mixtures of air pollutants and seasonal temperature anomalies and cardiovascular hospitalizations among U.S. Residents

BACKGROUND

Air pollution is a recognized risk factor for cardiovascular disease (CVD). Temperature is also linked to CVD, with a primary focus on acute effects. Despite the close relationship between air pollution and temperature, their health effects are often examined separately, potentially overlooking their synergistic effects. Moreover, fewer studies have performed mixture analysis for multiple co-exposures, essential for adjusting confounding effects among them and assessing both cumulative and individual effects.

METHODS

We obtained hospitalization records for residents of 14 U.S. states, spanning 2000-2016, from the Health Cost and Utilization Project State Inpatient Databases. We used a grouped weighted quantile sum regression, a novel approach for mixture analysis, to simultaneously evaluate cumulative and individual associations of annual exposures to four grouped mixtures: air pollutants (elemental carbon, ammonium, nitrate, organic carbon, sulfate, nitrogen dioxide, ozone), differences between summer and winter temperature means and their long-term averages during the entire study period (i.e., summer and winter temperature mean anomalies), differences between summer and winter temperature standard deviations (SD) and their long-term averages during the entire study period (i.e., summer and winter temperature SD anomalies), and interaction terms between air pollutants and summer and winter temperature mean anomalies. The outcomes are hospitalization rates for four prevalent CVD subtypes: ischemic heart disease, cerebrovascular disease, heart failure, and arrhythmia.

RESULTS

Chronic exposure to air pollutant mixtures was associated with increased hospitalization rates for all CVD subtypes, with heart failure being the most susceptible subtype. Sulfate, nitrate, nitrogen dioxide, and organic carbon posed the highest risks. Mixtures of the interaction terms between air pollutants and temperature mean anomalies were associated with increased hospitalization rates for all CVD subtypes.

CONCLUSIONS

Our findings identified critical pollutants for targeted emission controls and suggested that abnormal temperature changes chronically affected cardiovascular health by interacting with air pollution, not directly.

Climate Change, Landscape Fires, and Human Health: A Global Perspective

Landscape fires are an integral component of the Earth system and a feature of prehistoric, subsistence, and industrial economies. Specific spatiotemporal patterns of landscape fire occur in different locations around the world, shaped by the interactions between environmental and human drivers of fire activity. Seven distinct types of landscape fire emerge from these interactions: remote area fires, wildfire disasters, savanna fires, Indigenous burning, prescribed burning, agricultural burning, and deforestation fires. All can have substantial impacts on human health and well-being directly and indirectly through (a) exposure to heat flux (e.g., injuries and destructive impacts), (b) emissions (e.g., smoke-related health impacts), and (c) altered ecosystem functioning (e.g., biodiversity, amenity, water quality, and climate impacts). Minimizing the adverse effects of landscape fires on population health requires understanding how human and environmental influences on fire impacts can be modified through interventions targeted at individual, community, and regional levels.

Extreme Heat and Occupational Health Risks

Climate change poses a significant occupational health hazard. Rising temperatures and more frequent heat waves are expected to cause increasing heat-related morbidity and mortality for workers across the globe. Agricultural, construction, military, firefighting, mining, and manufacturing workers are at particularly high risk for heat-related illness (HRI). Various factors, including ambient temperatures, personal protective equipment, work arrangements, physical exertion, and work with heavy equipment may put workers at higher risk for HRI. While extreme heat will impact workers across the world, workers in low- and middle-income countries will be disproportionately affected. Tracking occupational HRI will be critical to informing prevention and mitigation strategies. Renewed investment in these strategies, including workplace heat prevention programs and regulatory standards for indoor and outdoor workers, will be needed. Additional research is needed to evaluate the effectiveness of interventions in order to successfully reduce the risk of HRI in the workplace.

Heat and Cardiovascular Mortality: An Epidemiological Perspective

As global temperatures rise, extreme heat events are projected to become more frequent and intense. Extreme heat causes a wide range of health effects, including an overall increase in morbidity and mortality. It is important to note that while there is sufficient epidemiological evidence for heat-related increases in all-cause mortality, evidence on the association between heat and cause-specific deaths such as cardiovascular disease (CVD) mortality (and its more specific causes) is limited, with inconsistent findings. Existing systematic reviews and meta-analyses of epidemiological studies on heat and CVD mortality have summarized the available evidence. However, the target audience of such reviews is mainly limited to the specific field of environmental epidemiology. This overarching perspective aims to provide health professionals with a comprehensive overview of recent epidemiological evidence of how extreme heat is associated with CVD mortality. The rationale behind this broad perspective is that a better understanding of the effect of extreme heat on CVD mortality will help CVD health professionals optimize their plans to adapt to the changes brought about by climate change and heat events. To policymakers, this perspective would help formulate targeted mitigation, strengthen early warning systems, and develop better adaptation strategies. Despite the heterogeneity in evidence worldwide, due in part to different climatic conditions and population dynamics, there is a clear link between heat and CVD mortality. The risk has often been found to be higher in vulnerable subgroups, including older people, people with preexisting conditions, and the socioeconomically deprived. This perspective also highlights the lack of evidence from low- and middle-income countries and focuses on cause-specific CVD deaths. In addition, the perspective highlights the temporal changes in heat-related CVD deaths as well as the interactive effect of heat with other environmental factors and the potential biological pathways. Importantly, these various aspects of epidemiological studies have never been fully investigated and, therefore, the true extent of the impact of heat on CVD deaths remains largely unknown. Furthermore, this perspective also highlights the research gaps in epidemiological studies and the potential solutions to generate more robust evidence on the future consequences of heat on CVD deaths.

Exposure to Concurrent Heatwaves and Ozone Pollution and Associations with Mortality Risk: A Nationwide Study in China

BACKGROUND

Concurrent extreme events are projected to occur more frequently under a changing climate. Understanding the mortality risk and burden of the concurrent heatwaves and ozone (O 3 ) pollution may support the formulation of adaptation strategies and early warning systems for concurrent events in the context of climate change.

OBJECTIVES

We aimed to estimate the mortality risk and excess deaths of concurrent heatwaves and O 3 pollution across 250 counties in China.

METHODS

We collected daily mortality, meteorological, and air pollution data for the summer (1 June to 30 September) during 2013-2018. We defined heatwaves and high O 3 pollution days, then we divided the identified days into three categories: a) days with only heatwaves (heatwave-only event), b) days with only high O 3 pollution (high O 3 pollution-only event), and c) days with concurrent heatwaves and high O 3 pollution (concurrent event). A generalized linear model with a quasi-Poisson regression was used to estimate the risk of mortality associated with extreme events for each county. Then we conducted a random-effects meta-analysis to pool the county-specific estimates to derive the overall effect estimates. We used mixed-effects meta-regression to identify the drivers of the heterogeneity. Finally, we estimated the excess death attributable to extreme events (heatwave-only, high O 3 pollution-only, and concurrent events) from 2013 to 2020.

RESULTS

A higher all-cause mortality risk was associated with exposure to the concurrent heatwaves and high O 3 pollution than exposure to a heatwave-only or a high O 3 pollution-only event. The effects of a concurrent event on circulatory and respiratory mortality were higher than all-cause and nonaccidental mortality. Sex and age significantly impacted the association of concurrent events and heatwave-only events with all-cause mortality. We estimated that annual average excess deaths attributed to the concurrent events were 6,249 in China from 2017 to 2020, 5.7 times higher than the annual average excess deaths attributed to the concurrent events from 2013 to 2016. The annual average proportion of excess deaths attributed to the concurrent events in the total excess deaths caused by three types of events (heatwave-only events, high O 3 pollution-only events, and concurrent events) increased significantly in 2017-2020 (31.50%; 95% CI: 26.73%, 35.53%) compared with 2013-2016 (9.65%; 95% CI: 5.67%, 10.81%). Relative excess risk due to interaction revealed positive additive interaction considering the concurrent effect of heatwaves and high O 3 pollution.

DISCUSSION

Our findings may provide scientific basis for establishing a concurrent event early warning system to reduce the adverse health impact of the concurrent heatwaves and high O 3 pollution. https://doi.org/10.1289/EHP13790.

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.

Heatwave characteristics complicate the association between PM2.5 components and schizophrenia hospitalizations in a changing climate: Leveraging of the individual residential environment

BACKGROUND

In the era characterized by global environmental and climatic changes, understanding the effects of PM2.5 components and heatwaves on schizophrenia (SCZ) is essential for implementing environmental interventions at the population level. However, research in this area remains limited, which highlights the need for further research and effort. We aim to assess the association between exposure to PM2.5 components and hospitalizations for SCZ under different heatwave characteristics.

METHODS

We conducted a 16 municipalities-wide, individual exposure-based, time-stratified, case-crossover study from January 1, 2017, to December 31, 2020, encompassing 160736 hospitalizations in Anhui Province, China. Daily concentrations of PM2.5 components were obtained from the Tracking Air Pollution in China dataset. Conditional logistic regression models were used to investigate the association between PM2.5 components and hospitalizations. Additionally, restricted cubic spline models were used to identify protective thresholds of residential environment in response to environmental and climate change.

RESULTS

Our findings indicate a positive correlation between PM2.5 and its components and hospitalizations. Significantly, a 1 μg/m3 increase in black carbon (BC) was associated with the highest risk, at 1.58% (95%CI: 0.95-2.25). Exposure to heatwaves synergistically enhanced the impact of PM2.5 components on hospitalization risks, and the interaction varied with the intensity and duration of heatwaves. Under the 99th percentile heatwave events, the impact of PM2.5 and its components on hospitalizations was most pronounced, which were PM2.5 (2-4d: 4.59%, 5.09%, and 5.09%), sulfate (2-4d: 21.73%, 23.23%, and 25.25%), nitrate (2-4d: 17.51%, 16.93%, and 20.31%), ammonium (2-4d: 27.49%, 31.03%, and 32.41%), organic matter (2-4d: 32.07%, 25.42%, and 24.48%), and BC (2-4d: 259.36%, 288.21%, and 152.52%), respectively. Encouragingly, a protective effect was observed when green and blue spaces comprised more than 17.6% of the residential environment.

DISCUSSION

PM2.5 components and heatwave exposure were positively associated with an increased risk of hospitalizations, although green and blue spaces provided a mitigating effect.

Reductions in premature deaths from heat and particulate matter air pollution in South Asia, China, and the United States under decarbonization

Following a sustainable development pathway designed to keep warming below 2 °C will benefit human health. We quantify premature deaths attributable to fine particulate matter (PM2.5) air pollution and heat exposures for China, South Asia, and the United States using projections from multiple climate models under high- and low-emission scenarios. Projected changes in premature deaths are typically dominated by population aging, primarily reflecting increased longevity leading to greater sensitivity to environmental risks. Changes in PM2.5 exposure typically have small impacts on premature deaths under a high-emission scenario but provide substantial benefits under a low-emission scenario. PM2.5-attributable deaths increase in South Asia throughout the century under both scenarios but shift to decreases by late century in China, and US values decrease throughout the century. In contrast, heat exposure increases under both scenarios and combines with population aging to drive projected increases in deaths in all countries. Despite population aging, combined PM2.5- and heat-related deaths decrease under the low-emission scenario by ~2.4 million per year by midcentury and ~2.9 million by century's end, with ~3% and ~21% of these reductions from heat, respectively. Intermodel variations in exposure projections generally lead to uncertainties of <40% except for US and China heat impacts. Health benefits of low emissions are larger from reduced heat exposure than improved air quality by the late 2090s in the United States. In contrast, in South and East Asia, the PM2.5-related benefits are largest throughout the century, and their valuation exceeds the cost of decarbonization, especially in China, over the next 30 y.

A study on identifying synergistic prevention and control regions for PM2.5 and O3 and exploring their spatiotemporal dynamic in China

Air pollutants, notably ozone (O3) and fine particulate matter (PM2.5) give rise to evident adverse impacts on public health and the ecotope, prompting extensive global apprehension. Though PM2.5 has been effectively mitigated in China, O3 has been emerging as a primary pollutant, especially in summer. Currently, alleviating PM2.5 and O3 synergistically faces huge challenges. The synergistic prevention and control (SPC) regions of PM2.5 and O3 and their spatiotemporal patterns were still unclear. To address the above issues, this study utilized ground monitoring station data, meteorological data, and auxiliary data to predict the China High-Resolution O3 Dataset (CHROD) via a two-stage model. Furthermore, SPC regions were identified based on a spatial overlay analysis using a Geographic Information System (GIS). The standard deviation ellipse was employed to investigate the spatiotemporal dynamic characteristics of SPC regions. Some outcomes were obtained. The two-stage model significantly improved the accuracy of O3 concentration prediction with acceptable R2 (0.86), and our CHROD presented higher spatiotemporal resolution compared with existing products. SPC regions exhibited significant spatiotemporal variations during the Blue Sky Protection Campaign (BSPC) in China. SPC regions were dominant in spring and autumn, and O3-controlled and PM2.5-dominated zones were detected in summer and winter, respectively. SPC regions were primarily located in the northwest, north, east, and central regions of China, specifically in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Shanxi, Shaanxi, Shandong, Henan, Jiangsu, Xinjiang, and Anhui provinces. The gravity center of SPC regions was distributed in the BTH in winter, and in Xinjiang during spring, summer, and autumn. This study can supply scientific references for the collaborative management of PM2.5 and O3.

Heatwave exposure in relation to decreased sleep duration in older adults

Few studies have delved into the effects of heatwaves on sleep duration loss among older adults. Our study examined correlations between heatwave exposure and sleep duration reductions in this demographic. Utilizing data of 7,240 older adults drawn from the China Health and Retirement Longitudinal Study (CHARLS) from 2015 to 2018, we assessed sleep duration differences between the baseline year (2015) and follow-up year (2018). Absolute reductions in sleep duration were defined as differences of ≥ 1, 1.5, or 2 h. Changes in sleep duration were categorized based on cut-offs of 5 and 8 h, including excessive decrease, moderate to short and persistent short sleep duration types. 12 heatwave definitions combining four thresholds (90th, 92.5th, 95th, and 97.5th percentiles of daily minimum temperature) and three durations (≥2, ≥3 and ≥ 4 days) were used. Heatwave exposure was determined by the difference in the number of 12 preceding months' heatwave days or events in 2015 and the number of 12 preceding months' heatwave days or events in 2018. The results showed that increased heatwave events (defined as ≥ P90th percentile & lasting three days) were associated with a higher likelihood of ≥ 1-hour sleep reduction and persistent short sleep duration. An increase in heatwave event (defined as ≥ P95th percentile & lasting three days) was linked to shifts from moderate to short sleep duration. For the association between an absolute reduction in sleep duration and heatwave exposure, while higher thresholds signified greater sleep reduction risks, the effect estimates of longer durations were not uniformly consistent. We observed that air pollution and green space modified the relationship between heatwaves and sleep duration. Females, urban residents, and individuals with chronic diseases were identified as vulnerable populations. This study found that increased heatwave exposure was associated with a higher risk of sleep duration loss in older adults.

The effects of heatwave on cognitive impairment among older adults: Exploring the combined effects of air pollution and green space

The association between heatwaves and cognitive impairment in older adults, especially the joint effect of air pollution and green space on this association, remains unknown. The present cohort study used data from waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 2008 to 2018. Heatwaves were defined as having daily maximum temperature ≥ 92.5th, 95th and 97.5th percentile that continued at least two, three and four days, measured as the one-year heatwave days prior to the participants' incident cognitive impairment. Data on the annual average air pollutant concentrations of fine particulate matter (PM2.5) and ozone (O3) as well as green space exposure (according to the Normalized Difference Vegetation Index (NDVI)) were collected. Time-varying Cox proportional hazards models were constructed to examine the independent effect of heatwaves on cognitive impairment and the combined effect of heatwaves, air pollution, and green space on cognitive impairment. Potential multiplicative interactions were examined by adding a product term of air pollutants and NDVI with heatwaves in the models. The relative excess risk due to interaction (RERI) was calculated to reflect additive interactions. We found that heatwave exposure was associated with higher risks of cognitive impairment, with hazard ratios (HRs) and 95 % confidence intervals (CIs) ranging from 1.035 (95 % CI: 1.016-1.055) to 1.058 (95 % CI: 1.040-1.075). We observed a positive interaction of PM2.5 concentrations, O3 concentrations, lack of green space, and heatwave exposure on a multiplicative scale (HRs for product terms >1). Furthermore, we found a synergistic interaction of PM2.5 concentrations, O3, lack of green space, and heatwave exposure on an additive scale, with RERIs >0. These results suggest that extreme heat exposure may be a potential risk factor for cognitive impairment in older adults. Additionally, coexposure to air pollution and lack of green space exacerbated the adverse effects of heatwaves on cognitive function.