Joint effect of heat and air pollution on mortality in 620 cities of 36 countries

The synergistic and mediating effects of ozone on associations between high temperature, heatwaves and mortality in the Greater London area between 2010 and 2018

The health impacts of increasing heat exposure are alarming, especially in a climate change era. The role of ozone in the extreme temperature-mortality association remains unclear. We examined the mechanisms through which ozone influences extreme temperature-mortality association in Greater London, UK, from 2010 to 2018. Employing a time-series analysis with generalized linear quasi-Poisson models, we quantified the effects of daily 8-h maximum ozone concentrations, heatwaves, and extreme temperature on all-cause, respiratory and cardiovascular mortality. Interaction analyses were applied to assess the synergistic effects of ozone and heat-related exposures. A causal mediation analysis was utilised to decompose the total effect of high temperature/heatwave on mortality into direct and indirect effects. The risk of all-cause mortality during the warm season (May to September) increased by 1.3 % (95 % Confidence Interval (CI): 1.1 %, 1.6 %) for each 1 °C increment in daily mean temperature. Heatwave days (two or more days with unusually high temperatures) were associated with an 8.6 % (95 % CI: 6.9 %, 10.4 %) increase in all-cause mortality compared to non-heatwave days. These effects were more pronounced for respiratory mortality, i.e. 1.6 % (95 % CI: 1.0 %, 2.2 %) increase per 1 °C increment in temperature and 9.6 % (95 % CI: 4.6 %, 15.0 %) increase during heatwaves. The risk of heat-related mortality increased on high ozone days, and high temperatures amplified the risk of ozone-related mortality. The proportion of the total effect of extreme temperature and heatwaves on all-cause mortality mediated by ozone was 8.5 % and 8.8 %, respectively. For respiratory mortality and heatwaves, the proportion mediated was 14.9 %. Our findings show synergistic effects of ozone and extreme temperature on mortality, as well as mediating effects of ozone in the heat-mortality associations.

Effects of co-exposure to heat and ozone on lipid metabolism in the liver and adipose tissue of C57BL/6J male mice

Although the effects of ozone and heat on health have been studied independently, the impact of combined exposure remains poorly understood. In this study, C57BL/6 J male mice were individually exposed to ozone (1 ppm), heat (34°C), or both in combination for 4 weeks (5 days/week, 3 h/day). In the Co-exposure group, stress hormones were increased, intensifying the activation of both the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic-adrenal-medullary (SAM) axis. Co-exposure to ozone and heat disrupted lipid homeostasis, as evidenced by elevated low-density lipoprotein cholesterol (LDL-C) and free fatty acids (FFA). Additionally, the combined exposure promoted hepatic lipid accumulation and oxidative stress. Co-exposure also induced the whitening of brown adipose tissue, reducing its capacity for thermogenesis and potentially worsening lipid dysregulation in the liver and systemic circulation. Transcriptomic analysis of the liver identified perturbations in key pathways related to cellular stress response and lipid metabolism. Notably, key enzymes responsible for cholesterol clearance, such as cholesterol 7α-hydroxylase (Cyp7a1), and ATP-binding cassette transporters G5 (Abcg5) and G8 (Abcg8) were suppressed in the Co-exposure group. These findings underscore the additive effects of simultaneous ozone and heat exposure in lipid metabolism, highlighting the increased risk of metabolic disorders under environmental stress.

Environmental exposure assessment in the German National Cohort (NAKO)

We aimed to assess the exposure to multiple environmental indicators and compare the spatial variation across participants of the German National Cohort (NAKO) to lay the foundation for health analyses. We collected highly resolved German-wide data to capture the following environmental drivers: urbanisation by population density; outdoor air pollution by particulate matter (PM2.5), nitrogen dioxide (NO2), ozone; road traffic noise; meteorology by air temperature, relative humidity; and the built environment by greenspace and land cover. All assessed exposures were assigned to the NAKO participants based on their baseline residential addresses. The NAKO study regions ranged from highly urbanised areas (Berlin, Hamburg) to rural regions (Neubrandenburg). This large variation is reflected in the individual environmental exposures at the place of residence. In 2019, annual PM2.5 and NO2 levels ranged from 6.0 to 14.6 and 3.7-33.6 μg/m3, respectively. Annual mean air temperature ranged between 7.8 and 12.7 °C. Noise data was available for a subset of urban residents (22 %), of which 42 % fell into the lowest and 1.8 % into the highest category of Lden 55-59 and Lden >75 dB(A), respectively. Greenspace also showed considerable differences (Normalised Difference Vegetation Index between 0.08 and 0.84). Spearman correlation was moderate to high within the different exposure groups, but mostly low to moderate between the groups. For the first time, a comprehensive population-based dataset with high quality environmental indicators is available for the whole of Germany. Expanding the database by adding innovative indicators such as light pollution, walkability, biodiversity as well as contextual socioeconomic factors will further increase its usefulness for science and public health.

Synergistic associations of ambient air pollution and heat on daily mortality in India

BACKGROUND

Limited studies have evaluated the interaction between ambient air pollution and heat on mortality, especially in regions such as India, where extreme levels of both exposures occur frequently. Accordingly, we aimed to investigate the potential synergistic effects between ambient air pollution and heat on daily mortality in India.

METHODS

We applied a time-series analysis for ten cities in India between 2008-2019. We assessed city-wide daily particulate matter ≤ 2.5 μm (PM2.5) and temperature levels using two nationwide spatiotemporal models. We estimated city-specific exposure-outcome associations through generalised additive Poisson regression models, and meta-analysed the associations. To evaluate the interaction between PM2.5 and air temperature (modelled at lag 0-1), a product term was incorporated between linear PM2.5 and non-linear air temperature. From this model, we estimated the effect of air pollution for increasing levels of temperature, and vice versa.

FINDINGS

Among ∼ 3.6 million deaths, we found that the association of PM2.5 on mortality was particularly stronger beyond the 75th percentile of temperature. When we compared the associations of PM2.5-mortality at the 75th and 99th temperature percentile, we observed an increase from 0.8 % (95 % CI: -0.3 %, 1.9 %) to 4.6 % (95 % CI: 2.9 %, 6.5 %) increase in mortality per 10 μg/m3 increments, respectively. In addition, we observed a 22.0 % (95 % CI: 13.5 %, 31.2 %) increase in daily mortality risk due to an increase in temperature from the 75th to the 99th city-specific percentiles. Percent change in mortality risk increased linearly from 8.3 % (95 % CI: 2.2 %, 14.9 %) when daily PM2.5 was 20 μg/m3 to 63.9 % (95 % CI: 38.7.%, 93.7 %) at 100 μg/m3.

INTERPRETATION

Our findings reveal a substantial synergistic interaction between ambient air pollution and temperature in India. This calls for efforts to tangibly reduce common sources of air pollution and climate change to immediately lower their combined effects on daily mortality and mitigate their long-term health consequences.

Climate change and air pollution can amplify vulnerability of glucose metabolism: The mediating effects of biological aging

Climate change and air pollution pose significant global health threats, including impacts on diabetes risk; however, their long-term effects on insulin resistance (IR), a key determinant in diabetes pathophysiology, remain unclear. This study investigated whether exposure to heatwaves, temperature fluctuations, and warm-season ozone (O3) contributes to or exacerbates IR and explored the potential mediating role of biological aging. The study enrolled 6901 participants and assessed both traditional and novel IR indicators: estimated glucose disposal rate (eGDR), triglyceride-glucose (TyG) index, triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-c), metabolic score for IR (METS-IR), TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), waist-to-height ratio (WHtR), TyG-WHtR, and lipid accumulation product (LAP). Ordinary least squares regression models were applied to evaluate the long-lasting effects of heatwaves, temperature fluctuation, and warm-season O3 on IR, incorporating Huber-White robust standard errors for model stability. Causal mediation analysis was utilized to investigate the mediating effects of biological aging. We found that exposure to heatwaves and higher concentrations of warm-season O3 was associated with elevated IR levels, with males, smokers, drinkers, and low-income individuals being more vulnerable. Accelerated biological aging (including body age, metabolomic aging rate, etc.) could significant mediate the long-lasting effects of heatwaves and warm-season O3. Our findings suggest that climate change and air pollution could amplify the vulnerability of glucose metabolism, particularly in males, smokers, drinkers, and individuals with low-income. More importantly, our findings reveal the importance of mitigating biological aging to prevent IR in the future, as global diabetes prevalence escalates rapidly.

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.

How air pollution and extreme temperatures affect emergency hospital admissions due to various respiratory causes in Spain, by age group: A nationwide study

This study set out to use specifically calculated dose-response functions to analyse how air pollution and extreme temperatures affected short-term daily emergency admissions due to respiratory diseases (asthma, upper respiratory tract infections and pneumonias) in the general population, children under 14 years of age and adults over 65 years of age, in all Spanish provinces across the period January 1, 2013─December 31, 2018. The following independent variables were used: mean daily NO2, PM10, PM2.5 and O3 concentrations recorded at all air pollution monitoring stations situated in the respective provinces; and maximum and minimum daily temperatures measured at reference observatories. Using generalised linear models (GLM) with a Poisson link, and controlling for trend, seasonalities and the autoregressive nature of the series, we calculated the relative risks for statistically significant associations. These were then used to calculate attributable risks and attributable cases, for the purpose of drawing up an economic estimate. Overall, chemical air pollution was linked to 33063 (95 %CI: 13536-55404) respiratory-cause admissions, which accounted for 7.8 % of total admissions in Spain. Respiratory-cause admissions attributable to heat- and cold-wave temperatures totalled 5754 (95 %CI: 2506, 8611), i.e., a lower order of magnitude. Nationwide, the impact of NO2 and O3 was greater than that of PM. The percentage of attributable admissions was higher in the under-14 than in the 65-year age group for all pollutants except ozone. This shows that the implementation of health-prevention plans that included temperature-pollution factors would be an effective way of mitigating the impacts which extreme temperatures and pollution have on population health.

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.

Economic estimation and impact of air pollution and temperature extremes on emergency hospital admissions in Spain

Air pollution and extreme temperatures are important public health problems but their effects on morbidity are not usually measured jointly. The objective was thus to analyse the effect of short-term exposure to both air pollution and to heat and cold waves on emergency hospital admissions at a provincial level, and estimate the economic cost. Time series study analysing emergency hospital admissions due to natural causes (ICD-9:1-799 and ICD-10: A00-R99) across the period 2013-2018. The independent variables were daily mean concentrations of NO2, PM2.5, PM10 and ozone, the maximum daily temperature in heat waves, and the minimum daily temperature in cold waves. Generalised linear models with a Poisson regression link were used to calculate the relative risks and attributable risks and estimated the related economic cost. In relation to air pollution, exposure to NO2 showed the greatest association with the number of provinces (39 %) and the highest number of attributable admissions (27,823;95%CI:14181-42,610) and an annual cost of €393,25 million. For the O3, the association with attributable admissions was 22,858; 95%CI:5986-39,683 and an annual cost of €312,76 million. The exposure to PM showed the lowest association with the attributable admissions, 11,203 (95%CI:4470-17,504) and an annual cost of €152,95 million. In the case of extreme temperatures their impact was very much less (5377; 95CI:2347-8373) than that of air pollution and their annual cost of €76.0 million. According the results found, a considerable number of emergency hospital admissions are mainly attributable to short-term exposure to air pollution instead of the extreme temperatures. The extreme temperatures prevention plans should be implemented to address the impact on health of air pollution and temperatures jointly.

Independent effects of long and short-term exposures to non-optimal increased temperature on mortality

Although the short-term heat effects are well-established, longer-term effects, beyond those, have recently received attention, in the context of climate change. Our study aims to investigate the potential effects of long-term exposure to non-optimal warm period temperatures on all-cause mortality in four large regions in the UK, Norway, Italy, and Greece. Daily all-cause mortality counts from 1996 to 2018 for four European NUTS-2 regions including 52-662 small areas were collected and associated with spatiotemporal temperature estimates. A NUTS-2 region-specific mixed quasi-Poisson over-dispersed model, with a random intercept per small area within NUTS-2 regions, was applied to investigate the association between long-term temperature exposure and mortality during the warm period (May to September), adjusting for short-term temperature, seasonality, long-term trends, and small-area population characteristics. As long-term temperature exposure indices per small area, we considered: 1) the warm period annual average temperature, 2) the annual standard deviation (SD) of warm period temperature, and 3) the coefficient of variation of warm period temperature (CV). We found consistent results following short-term temperature exposure on mortality, with higher effects in southern areas. Results on the shape of the long-term association between average temperature and mortality differed by country, while the different temperature metrics produced inconsistent findings. Increased mortality was associated with increased annual warm season temperature, lower SD and increased CV in Greece, with higher SD and decreased CV in Italy and with decreased annual temperature and CV in Norway. Effects in the UK did not reach the nominal level of statistical significance. Although our study implies an impact on mortality resulting from longer-term temperature exposure, its direction varied across areas and on the temperature metric used. Further research is warranted, applying non-ecological study designs and covering various geographical areas to capture the impact of individual and area-specific characteristics.

Does Nonsteroidal Anti-inflammatory Drug Use Modify All-Cause and Cause-Specific Mortality Associated with PM2.5 and Its Components? A Nationally Representative Cohort Study (2007-2017)

Several studies reported that nonsteroidal anti-inflammatory drug (NSAID) use could alleviate subclinical effects of short-term exposure to fine particulate matter (PM2.5). However, whether chronic NSAID use could mitigate the long-term effects of PM2.5 and its components on population mortality has been unknown. Based on a national representative survey of 47,086 adults (2007-2010) with follow-up information on the primary cause of death (until 2017), we investigated the long-term associations of PM2.5 and its major components, including black carbon (BC), ammonium (NH4 +), nitrate (NO3 -), organic matter (OM), and sulfate (SO4 2-), with all-cause and cause-specific mortality using the Cox proportional hazards model. We also evaluated the effect modification by NSAID use (including broad NSAIDs, aspirin, or ibuprofen) on the associations using interaction models. Long-term exposures to PM2.5 and its components were associated with increased risks of all-cause and cause-specific mortality, where BC, OM, and SO4 2- showed stronger associations. Ibuprofen use could mitigate the associations of PM2.5 and its components with mortality risks, while no significant modifying effects of aspirin were observed. For instance, along with per interquartile range increment in PM2.5 concentration (34.8 μg/m3), the hazard ratios (HRs) of all-cause mortality were 1.21 (95% CI: 1.19, 1.22) and 1.10 (95% CI: 1.01, 1.19) in nonibuprofen and ibuprofen use groups (P for interaction = 0.026), respectively. Cause-specific analyses indicated that ibuprofen use could mainly mitigate risks of cardiovascular disease (CVD) especially ischemic heart disease (IHD) mortality attributable to PM2.5 components. Stratified analyses found more apparent mitigating effects of ibuprofen use among participants without chronic diseases, participants ≤50 years, female participants, rural residents, and those with lower education levels. Our findings suggested potential implications in reducing population mortality caused by long-term exposures to PM2.5 and its components through personalized interventions.

Exposure to submicron particulate matter and long-term survival: Cross-cohort analysis of 3 Chinese national surveys

BACKGROUND

Cohort evidence linking increased mortality with airborne fine particulate matter (PM2.5, particulate matter [PM] with aerodynamic diameter ≤2.5 μm) exposure was extensively validated worldwide. Nevertheless, long-term survival associated with submicron particulate matter (PM1, PM with aerodynamic diameter ≤1 μm) exposure remained largely unstudied, particularly in highly exposed populations.

METHODS

We performed a population-based investigation involving 86844 adults aged 16+ years from 3 national dynamic cohorts spanning from 2005 to 2018. Residential annual exposure to PM1 and PM2.5 was assigned for each follow-up year using satellite-derived spatiotemporal estimates at a 1-km2 resolution. The concentration of PM1-2.5 (PM with aerodynamic diameter between 1 and 2.5 μm) was calculated by subtracting PM1 from PM2.5. Time-independent Cox proportional hazards regression models were applied to assess the associations of all-cause mortality with long-term exposure to size-specific particles. To investigate the effect of PM1 on PM2.5-mortality associations, we categorized participants into low, medium, and high groups based on PM1/PM2.5 ratio and examined the risk of PM2.5-associated mortality in each stratum. Effect modifications were checked via subgroup analyses.

RESULTS

A total of 18722 deaths occurred during 497069.2 person-years of follow-up (median 5.7 years). Participants were exposed to an average annual concentration of 31.8 μg/m³ (range: 7.6-66.8 μg/m³) for PM1, 56.3 μg/m³ (range: 19.8-127.2 μg/m³) for PM2.5, and 24.5 μg/m³ (range: 7.3-60.3 μg/m³) for PM1-2.5. PM1, PM2.5, and PM1-2.5 were consistently associated with elevated mortality risks, with a hazard ratio (HR) of 1.029 (95% confidence interval [CI]: 1.013-1.046), 1.014 (95% CI: 1.005-1.023), and 1.019 (95% CI: 1.001-1.038) for each 10-μg/m3 increase in exposure, respectively. Compared with low (HR = 0.986, 95% CI: 0.967-1.004) and medium (HR = 1.015, 95% CI: 1.002-1.029) PM1/PM2.5 ratio groups, PM2.5-related risk of mortality was more pronounced in high PM1/PM2.5 ratio stratum (HR = 1.041, 95% CI: 1.019-1.064). Greater risks of mortality associated with size-specific particles were found among the elderly (>80 years old), southeastern participants, and those living in warmer areas.

CONCLUSIONS

This study demonstrated that long-term exposure to PM1, PM2.5, and PM1-2.5 was associated with heightened mortality, and PM1 may play a predominant role in PM2.5-induced risk. Our results emphasized the population health implications of establishing ambient PM1 air quality guidelines to mitigate the burden of premature mortality stemming from particulate air pollution.

The impact of exposure assessment on associations between air pollution and cardiovascular mortality risks in the city of Rio de Janeiro, Brazil

Despite a growing literature for complex air quality models, scientific evidence lacks of the influences of varying exposure assessments and air quality data sources on the estimated mortality risks. This case-crossover study estimated cardiovascular mortality risks from fine particulate matter (PM2.5) and ozone (O3) exposures, using varying exposure methods, to aid understanding of the impact of exposure methods in the health risk estimation. We used individual-level cardiovascular mortality data in the city of Rio de Janeiro, 2012-2016. PM2.5 and O3 exposure levels (from the date of death to seven prior days [lag0-7]) were estimated at the individual level or district level using either the WRF-Chem modeling data or monitoring data, resulting in a total of 10 exposure methods. The exposure-response relationships were estimated using multiple logistic regressions. The changes in cardiovascular mortality were represented as an odds ratio (OR) and 95% confidence intervals (CIs) for an interquartile range (IQR) increase in the exposures. Results showed that socioeconomically more advantaged populations had lower access to the stationary monitoring networks. Higher variance in the estimated exposure levels across the 10 exposure methods was found for PM2.5 than O3. PM2.5 exposure was not associated with mortality risk in any exposure methods. WRF-Chem-based O3 exposure estimated for each individual of the entire population found a significant mortality risk (OR = 1.06, 95% CI: 1.01, 1.11), but not the other exposure methods. Higher risks for females and older populations were suggested for O3 estimates estimated for each individual using the WRF-Chem data. Findings indicate that decisions on exposure methods and data sources can lead to substantially varying implications for air pollution risks and highlight the need for comprehensive exposure and health impact assessments to aid local decision-making for air pollution and public health.

Association of exposure to air pollutants and risk of mortality among people living with HIV: a systematic review

BACKGROUND

People living with HIV (PLWH) are more vulnerable to infectious and non-infectious comorbidities due to chronic inflammation and immune dysfunction. Air pollution is a major global health risk, contributing to millions of deaths annually, primarily from cardiovascular and respiratory diseases. However, the link between air pollution and mortality risk in PLWH is underexplored. This systematic review assesses the association between exposure to pollutants such as particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO) and mortality risk in PLWH.

METHODS

A systematic search of PubMed, Web of Science, and Embase was conducted for studies published up to August 2024. Eligibility criteria included cohort, case-control, and cross-sectional studies assessing air pollution exposure and mortality in PLWH. Nested-Knowledge software was used for screening and data extraction. The Newcastle-Ottawa Scale was applied for quality assessment. A narrative approach and tabular summarization were used for data synthesis and presentation.

RESULTS

Nine studies, mostly from China, demonstrated a significant association between long-term exposure to PM1, PM2.5, and PM10 and increased risks of AIDS-related and all-cause mortality in PLWH. Hazard ratios for mortality increased by 2.38-5.13% per unit increase in PM concentrations, with older adults (> 60), females, and those with lower CD4 counts (< 500 cells/µL) being more vulnerable. Short-term exposure to ozone and sulfur dioxide also increased mortality risks, particularly during the warm season and in older populations. Specific pollutants like ammonium (NH4⁺) and sulfate (SO4²⁻) had the strongest links to elevated mortality.

CONCLUSION

Air pollution, especially fine particulate matter and ozone, is associated with a higher risk of mortality in PLWH. Targeted interventions to reduce pollution exposure in vulnerable subgroups are crucial. Further research is needed to confirm these findings in diverse regions and develop effective mitigation strategies.

The impact of climate and demographic changes on future mortality in Brussels, Belgium

OBJECTIVES

City populations are particularly vulnerable to climate change, but it is difficult to reliably estimate the impact on health due to the lack of high-resolution data. We used recently developed regional climate model projections at kilometre resolution combined with demographic projections to estimate the future mortality burden associated with temperatures in the region of Brussels, Belgium.

STUDY DESIGN

The study incorporated a time-series analysis.

METHODS

Based on quasi-Poisson regression with distributed-lag non-linear models for the historical temperature-mortality relationship, we derive the mortality burden for the near (2020-2044) and mid (2045-2069) future and disaggregated the contributions of demographic and climate changes.

RESULTS

The cold-related attributable fraction of deaths is expected to decrease from 6.22% (95% empirical confidence interval: 1.76%; 10.52%) in 1994-2019 to 5.17% (1.08%; 9.09%) in 2045-2069, whereas for heat, this fraction will increase from 1.02% (0.59%; 1.47%) to 1.83% (0.82%; 2.96%), with contributions of both climate and demographic changes. In stratified analyses by age, we found that because of demographic changes, the number of cold-attributable deaths will increase for people aged above 85 years, with 6815 (95% empirical confidence interval: 1424; 12,003) deaths expected in 2045-2069 compared to 5245 (1462; 8867) deaths in 1994-2019. For people aged below 65 years, on the other hand, the number of heat-related deaths will decrease from 456 (265; 658) to 344 (154; 561) deaths.

CONCLUSIONS

Public health policies that especially target the elderly and the summer-time period are needed to limit the impact of climate change on health.

Exploration of Geographical Environmental Factors Influencing Regional Population Mortality Patterns in China

OBJECTIVES

The regional population mortality patterns in China exhibit substantial geographical distribution characteristics. This paper aims to explore the impact and mechanisms of geographical environmental factors on regional population mortality patterns.

METHODS

This study first utilized the data from China's Seventh Population Census to obtain mortality patterns for the 31 provincial-level administrative regions. Subsequently, a functional regression method was employed to explore the geographical environmental driving factors of regional mortality patterns.

RESULTS

The study provides a detailed explanation of the mechanisms and marginal contributions of key geographical environmental factors at different age groups.

CONCLUSIONS

(1) The impact of geographical environmental factors on mortality patterns shows distinct phased characteristics. Mortality patterns before the age of 40 years are hardly influenced by geographical environmental factors, with a noticeable impact beginning at ages 40-69 years and reaching the maximum influence after the age of 70 years. (2) In mortality patterns at ages 40-69 years, average altitude have the most substantial impact, followed by extreme low-temperature days and PM2.5 concentration. In mortality patterns at ages 70-94 years, high-temperature days have the greatest influence, followed by the impact of SO2 concentration. (3) In comparisons based on gender, socioeconomic factors, and geographical environmental factors, gender and urban-rural differences have the most significant impact on regional population mortality patterns, followed by the influence of other socioeconomic factors, with geographical environmental factors having a relatively smaller impact.

The combined effects of heatwaves, air pollution and greenery on the risk of frailty: a national cohort study

The associations between heatwaves and frailty, as well as the joint effects of heatwaves with air pollution and greenery, are currently unknown. This study leverages data from the China Health and Retirement Longitudinal Study (CHARLS), which collected information from 6,400 older adults between 2011 and 2018. Our outcome variable was frailty, as measured by the frailty index (FI > 0.21). Heatwaves were defined based on maximum temperature, incorporating four thresholds (≥ 97.5%, 97.5%, 92.5%, and 90%) and three durations (≥ 2, 3, and 4 days). These variables were considered as time-varying variables, representing the one-year exposure preceding survival events. Fine particulate matter (PM2.5) and greenery (normalized difference vegetation index (NDVI)) were utilized as indicators of air pollution and greenery exposure, respectively, and were treated as time-varying indicators concurrent with heatwaves.Time-varying Cox proportional hazards models were employed to assess the independent effects, as well as the multiplicative and additive interactions of heatwaves, air pollution, and greenery on the risk of frailty. These effects were quantified using hazard ratios (HRs), a traditional product term representing the ratio of HRs, and the relative excess risk due to interaction (RERI). Our findings indicate that heatwaves are associated with an increased risk of frailty, with HRs ranging from 1.035 (95% CI: 1.006-1.064) to 1.063 (95% CI: 1.028-1.101). We observed both a positive multiplicative interaction (HRs > 1) and an additive interaction (RERI > 0) between high level PM2.5 concentration, lack of greenery, and heatwaves. This study reveals that the combined effects exacerbate the adverse impact of heatwaves on the risk of frailty. Moreover, the combined effects of heatwaves, air pollution, and greenery exposure on frailty risk vary across age, gender, and educational attainment.

Short- and medium-term cumulative effects of traffic-related air pollution on resting heart rate in the elderly: A wearable device study

BACKGROUND

Epidemiological evidence regarding the association between air pollution and resting heart rate (RHR), a predictor of cardiovascular disease and mortality, is limited and inconsistent.

OBJECTIVES

We used wearable devices and time-series analysis to assess the exposure-response relationship over an extended lag period.

METHODS

Ninety-seven elderly individuals (>65 years) from the Taipei Basin participated from May to November 2020 and wore Garmin® smartwatches continuously until the end of 2021 for heart rate monitoring. RHR was defined as the daily average of the lowest 30-min heart rate. Air pollution exposure data, covering lag periods from 0 to 60 days, were obtained from nearby monitoring stations. We used distributed lag non-linear models and linear mixed-effect models to assess cumulative effects of air pollution. Principal component analysis was utilized to explore underlying patterns in air pollution exposure, and subgroup analyses with interaction terms were conducted to explore the modification effects of individual factors.

RESULTS

After adjusting for co-pollutants in the models, an interquartile range increase of 0.18 ppm in carbon monoxide (CO) was consistently associated with increased RHR across lag periods of 0-1 day (0.31, 95 % confidence interval [CI]: 0.24-0.38), 0-7 days (0.68, 95 % CI: 0.57-0.79), and 0-50 days (1.02, 95 % CI: 0.82-1.21). Principal component analysis identified two factors, one primarily influenced by CO and nitrogen dioxide (NO2), indicative of traffic sources. Increases in the varimax-rotated traffic-related score were correlated with higher RHR over 0-1 day (0.36, 95 % CI: 0.25-0.47), 0-7 days (0.62, 95 % CI: 0.46-0.77), and 0-50 days (1.27, 95 % CI: 0.87-1.67) lag periods. Over a 0-7 day lag, RHR responses to traffic pollution were intensified by higher temperatures (β = 0.80 vs. 0.29; interaction p-value [P_int] = 0.011). Males (β = 0.66 vs. 0.60; P_int < 0.0001), hypertensive individuals (β = 0.85 vs. 0.45; P_int = 0.028), diabetics (β = 0.96 vs. 0.52; P_int = 0.042), and those with lower physical activity (β = 0.70 vs. 0.54; P_int < 0.0001) also exhibited stronger responses. Over a 0-50 day lag, males (β = 0.99 vs. 0.96; P_int < 0.0001), diabetics (β = 1.66 vs. 0.69; P_int < 0.0001), individuals with lower physical activity (β = 1.49 vs. 0.47; P_int = 0.0006), and those with fewer steps on lag day 1 (β = 1.17 vs. 0.71; P_int = 0.029) showed amplified responses.

CONCLUSIONS

Prolonged exposure to traffic-related air pollution results in cumulative cardiovascular risks, persisting for up to 50 days. These effects are more pronounced on warmer days and in individuals with chronic conditions or inactive lifestyles.

The Multi-Country Multi-City Collaborative Research Network: An international research consortium investigating environment, climate, and health

Research on the health risks of environmental factors and climate change requires epidemiological evidence on associated health risks at a global scale. Multi-center studies offer an excellent framework for this purpose, but they present various methodological and logistical problems. This contribution illustrates the experience of the Multi-Country Multi-City Collaborative Research Network, an international collaboration working on a global research program on the associations between environmental stressors, climate, and health in a multi-center setting. The article illustrates the collaborative scheme based on mutual contribution and data and method sharing, describes the collection of a huge multi-location database, summarizes published research findings and future plans, and discusses advantages and limitations. The Multi-Country Multi-City represents an example of a collaborative research framework that has greatly contributed to advance knowledge on the health impacts of climate change and other environmental factors and can be replicated to address other research questions across various research fields.

Individual and joint exposure to air pollutants and patterns of multiple chronic conditions

Existing research on the detrimental effects of air pollution and its mixture on multiple chronic conditions (MCC) is not yet fully recognized. Our objective was to examine if individual and joint exposure to air pollution is associated with the incidence and patterns of MCC. Totally 10,231 CHARLS 2015 participants aged over 45 years and 1,938 without MCC were followed up in 2018 and 2020. Residential-levelcumulative personal exposure concentrations of PM1, PM10, PM2.5, CO, O3, NO2, SO2, NO3-, Cl-, NH4+, and SO42- at the residential level were determined utilizing a spatio-temporal random forest model with a spatial resolution of 0.1° × 0.1°. In the cross-sectional and longitudinal research, logistic regression, cox regression analysis, and quantile g-computation were utilized to estimate the single and joint effect with MCC and its patterns, respectively. Interaction analyses and stratified analyses were also performed. A correlation was observed between the prevalence of cardiovascular illnesses and the presence of all 11 major air pollutants. PM2.5, PM10, NH4+, NO3-, CO, and SO42- are associated with an increased frequency of respiratory disorders. An increase of PM2.5, PM1, PM10, NO2, and SO2 (a 10 µg/m3 rise), CO (a 0.1 mg/m3 rise), and PMCs (Cl-, NH4+, NO3-, and SO42-) (a 1 µg/m3 rise) corresponded to the HRs (95% CI) for developing MCC of 1.194 (95% CI: 1.043, 1.367), 1.362 (95% CI: 1.073, 1.728), 1.115 (95% CI: 1.026, 1.212), 1.443 (95% CI: 1.151, 1.808), 3.175 (95% CI: 2.291, 4.401), 1.272 (95% CI: 1.149,1.410), 1.382 (95% CI: 1.011, 1.888), 1.107 (95% CI: 1.003, 1.222), 1.035 (95% CI: 0.984, 1.088), and 1.122 (95% CI: 1.086, 1.160), respectively. SO2 was the predominant contributor to the combined effect (HR: 2.083, 95% CI: 1.659-2.508). Gender, age, drinking, and health status could modify the effects of air pollutants on MCC patterns. Long-term exposure to air pollution is correlated to the incidence and patterns of MCC in middle-aged and elderly Chinese individuals. Preventive methods are essential to safeguarding those susceptible to MCC.

Synergy of Urban Heat, Pollution, and Social Vulnerability in One of America's Most Rapidly Growing Cities: Houston, We Have a Problem

During the first two decades of the twenty-first century, we analyze the expansion of urban land cover, urban heat island (UHI), and urban pollution island (UPI) in the Houston Metropolitan Area (HMA) using land cover classifications derived from Landsat and land/aerosol products from NASA's Moderate Resolution Imaging Spectroradiometer. Our approach involves both direct utilization and fusion with in situ observations for a comprehensive characterization. We also examined how social vulnerability within the HMA changed during the study period and whether the synergy of UHI, UPI, and social vulnerability enhances environmental inequalities. We found that urban land cover within the HMA increased by 1,345.09 km2 and is accompanied by a 171.92 (73.93) % expansion of the daytime (nighttime) UHI. While the UPI experienced an overall reduction in particulate pollution, the magnitude of change is smaller compared to the surroundings. Further, the UPI showed localized enhancement in particulate pollution caused by increases in vehicular traffic. Our analysis found that the social vulnerability of the HMA urban regions increased during the study period. Overall, we found that the urban growth during the first two decades of the twenty-first century resulted in a synergy of UHI, UPI, and social vulnerability, causing an increase in environmental inequalities within the HMA.

Combined impact of heat and dust on diabetes hospitalization in Kuwait

INTRODUCTION

In Kuwait, a severe diabetes and obesity epidemic coexists with intense dust storms and harsh summer heat. While, theoretically, this interplay between dust, heat, and diabetes presents a serious public health problem, the empirical understanding of the actual risks remains limited. We hypothesized that increased exposure to heat and dust, independently and jointly, exacerbates the risk of hospitalization for diabetes patients.

RESEARCH DESIGN AND METHODS

We placed custom-designed particle samplers in Kuwait to collect daily dust samples for 2 years from 2017 to 2019. Samples were analyzed for elemental concentrations to identify and quantify dust pollution days. Temperature data were collected from meteorological stations. We then collected hospitalization data for unplanned diabetic admissions in all public hospitals in Kuwait. We used a case-crossover study design and conditional quasi-Poisson models to compare hospitalization days to control days within the same subject. Finally, we fitted generalized additive models to explore the smoothed interaction between temperature and dust days on diabetes hospitalization.

RESULTS

There were 11 155 unplanned diabetes hospitalizations over the study period. We found that each year, there was an excess of 282 diabetic admissions attributed to hot days (95% CI: -14 to 473). Additionally, for every 10 µg/m3 increase in dust levels, there were about 114 excess diabetic admissions annually (95% CI: 11 to 219). Compared with mild non-dusty days (33°C (0 µg/m3)), hot-dusty days jointly increased the relative risk of diabetic admissions from 1.11 at 42°C (85 µg/m3) to 1.36 at 42°C (150 µg/m3).

CONCLUSIONS

Both heat and dust seem to contribute to the increased diabetes morbidity, with combined hot-dusty conditions exacerbating these risks even further.

Systemic inequalities in heat risk for greater London

The temperature rise and increases in extreme heat events related to global climate change is a growing public health threat. Populations in temperate climates, including the UK, must urgently adapt to increased hot weather as current infrastructure primarily focusses on resilience to cold. As we adapt, care should be taken to ensure existing health inequalities are reduced. Lessons can be learned from regions that experience warmer climates and applied to adaptation in the UK. We identified known indicators of heat-health risk and explored their distribution across area level income for London. Understanding these indicators and their distributions across populations can support the development of interventions that have the dual aim of improving health and reducing inequalities. An exploratory analysis was conducted for each indicator at neighbourhood level to assess existence of disparities in their distributions across London. A systems-thinking approach was employed to deduce if these amount to systemic inequalities in heat risk, whereby those most exposed to heat are more susceptible and less able to adapt. Using this information, we proposed interventions and made recommendations for their implementation. We find inequalities across indicators relating to exposure, vulnerability, and adaptive capacity. Including inequalities in urban greening and access to greenspace, physical and mental health and access to communication and support. Through a system diagram we demonstrate how these indicators interact and suggest that systemic inequalities in risk exist and will become more evident as exposure increases with rising temperatures, depending on how we adapt. We use this information to identify barriers to the effective implementation of adaptation strategies and make recommendations on the implementation of interventions. This includes effective and wide-reaching communication considering the various channels and accessibility requirements of the population and consideration of all dwelling tenures when implementing policies relating to home improvements in the context of heat.

Integration of ten years of daily weather, traffic, and air pollution data from Norway's six largest cities

This study integrates ten years of daily weather, traffic, and air pollution data across the six largest Norwegian cities, utilizing data from the Norwegian Public Roads Administration, the Norwegian Institute of Air Research, and the Norwegian Meteorological Institute. The compilation of this dataset involved detailed selection and verification of monitoring stations to ensure consistency and accuracy. Initial data collection focused on the top ten most populous cities in Norway, with the subsequent examination of traffic and air pollution monitoring sites. Weather variables were then matched to the selected sites, resulting in a comprehensive dataset from 2009 to 2018. The resulting dataset encompasses extensive information, including harmful pollutants such as Nitric oxide (NO), Nitrogen dioxide (NO2), Nitrogen oxides (NOx), Particulate Matter less than 2.5 micrometers in diameter (PM2.5), and Particulate Matter less than 10 micrometers in diameter (PM10). The dataset's potential for further analysis and its utility in informing policy decisions underscore its significance. This integrated dataset is a valuable resource for researchers and policymakers alike, facilitating comprehensive studies on the intersection of weather, traffic, and air pollution in urban environments.

Identification of individual-level clinical factors associated with increased risk of death during heatwaves: a time-stratified case-crossover study using national primary care records in England

Background

Despite an increase in heat-related deaths occurring in England in recent years, one of the key recommended actions of identifying individuals at risk and deploying targeted interventions is not routinely undertaken. A major contributing factor to this is a lack of understanding of the individual-level risk factors that would support an evidence-based approach to targeted prevention.

Objective

To identify individual-level clinical risk factors for heat-related mortality in England by using primary care records and to estimate potential effect modification of a range of pre-existing conditions, clinical measurements and prescribed medications.

Methods

A time-stratified case-crossover analysis was undertaken of 37 individual-level clinical risk factors. Patient's data were obtained from the Clinical Practice Research Datalink. Conditional logistic regression was used to characterise associations between temperature and the risk of death on hot days.

Results

Heat mortality risk was modified by a large range of pre-existing conditions, with cardiorespiratory, mental health and cognitive function conditions, diabetes and Parkinson's, all increasing risk. The most striking increase was observed for depression with an OR of 1.25 (95% CI 1.09 to 1.44), the highest observed for pre-existing conditions. Individuals prescribed medications to treat heart failure and high blood pressure also have increased odds of death during heatwaves. There appears to be evidence of an increasing trend in ORs for diastolic blood pressure (DBP) categories, with ORs increasing from low DBP up to prehypertensive DBP group.

Conclusions

This is the first study to explore a comprehensive set of individual-level clinical risk factors and heat using primary care records in England. Results presented have important implications for patient medication management during heat events, incorporating heat-risk considerations into other health policies such as suicide prevention plans and highlighted potential differences between clinical vulnerability and patients at risk.

External exposome and all-cause mortality in European cohorts: the EXPANSE project

Background

Many studies reported associations between long-term exposure to environmental factors and mortality; however, little is known on the combined effects of these factors and health. We aimed to evaluate the association between external exposome and all-cause mortality in large administrative and traditional adult cohorts in Europe.

Methods

Data from six administrative cohorts (Catalonia, Greece, Rome, Sweden, Switzerland and the Netherlands, totaling 27,913,545 subjects) and three traditional adult cohorts (CEANS-Sweden, EPIC-NL-the Netherlands, KORA-Germany, totaling 57,653 participants) were included. Multiple exposures were assigned at the residential addresses, and were divided into three a priori defined domains: (1) air pollution [fine particulate matter (PM2.5), nitrogen dioxide (NO₂), black carbon (BC) and warm-season Ozone (warm-O3)]; (2) land/built environment (Normalized Difference Vegetation Index-NDVI, impervious surfaces, and distance to water); (3) air temperature (cold- and warm-season mean and standard deviation). Each domain was synthesized through Principal Component Analysis (PCA), with the aim of explaining at least 80% of its variability. Cox proportional-hazards regression models were applied and the total risk of the external exposome was estimated through the Cumulative Risk Index (CRI). The estimates were adjusted for individual- and area-level covariates.

Results

More than 205 million person-years at risk and more than 3.2 million deaths were analyzed. In single-component models, IQR increases of the first principal component of the air pollution domain were associated with higher mortality [HRs ranging from 1.011 (95% CI: 1.005-1.018) for the Rome cohort to 1.076 (1.071-1.081) for the Swedish cohort]. In contrast, lower levels of the first principal component of the land/built environment domain, pointing to reduced vegetation and higher percentage of impervious surfaces, were associated with higher risks. Finally, the CRI of external exposome increased mortality for almost all cohorts. The associations found in the traditional adult cohorts were generally consistent with the results from the administrative ones, albeit without reaching statistical significance.

Discussion

Various components of the external exposome, analyzed individually or in combination, were associated with increased mortality across European cohorts. This sets the stage for future research on the connections between various exposure patterns and human health, aiding in the planning of healthier cities.

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.

Heat Exposure and Cause-Specific Hospital Admissions in Spain: A Nationwide Cross-Sectional Study

BACKGROUND

More frequent and intense exposure to extreme heat conditions poses a serious threat to public health. However, evidence on the association between heat and specific diagnoses of morbidity is still limited. We aimed to comprehensively assess the short-term association between cause-specific hospital admissions and high temperature, including the added effect of temperature variability and heat waves and the effect modification by humidity and air pollution.

METHODS

We used data on cause-specific hospital admissions, weather (i.e., temperature and relative humidity), and air pollution [i.e., fine particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ), fine particulate matter with aerodynamic diameter ≤ 10 μ m (PM 10 ), NO 2 , and ozone (O 3 )] for 48 provinces in mainland Spain and the Balearic Islands between 1 January 2006 and 31 December 2019. The statistical analysis was performed for the summer season (June-September) and consisted of two steps. We first applied quasi-Poisson generalized linear regression models in combination with distributed lag nonlinear models (DLNM) to estimate province-specific temperature-morbidity associations, which were then pooled through multilevel univariate/multivariate random-effect meta-analysis.

RESULTS

High temperature had a generalized impact on cause-specific hospitalizations, while the added effect of temperature variability [i.e., diurnal temperature range (DTR)] and heat waves was limited to a reduced number of diagnoses. The strongest impact of heat was observed for metabolic disorders and obesity [relative risk (RR) = 1.978; 95% empirical confidence interval (eCI): 1.772, 2.208], followed by renal failure (1.777; 95% eCI: 1.629, 1.939), urinary tract infection (1.746; 95% eCI: 1.578, 1.933), sepsis (1.543; 95% eCI: 1.387, 1.718), urolithiasis (1.490; 95% eCI: 1.338, 1.658), and poisoning by drugs and nonmedicinal substances (1.470; 95% eCI: 1.298, 1.665). We also found differences by sex (depending on the diagnosis of hospitalization) and age (very young children and the elderly were more at risk). Humidity played a role in the association of heat with hospitalizations from acute bronchitis and bronchiolitis and diseases of the muscular system and connective tissue, which were higher in dry days. Moreover, heat-related effects were exacerbated on high pollution days for metabolic disorders and obesity (PM 2.5 ) and diabetes (PM 10 , O 3 ).

DISCUSSION

Short-term exposure to heat was found to be associated with new diagnoses (e.g., metabolic diseases and obesity, blood diseases, acute bronchitis and bronchiolitis, muscular and connective tissue diseases, poisoning by drugs and nonmedicinal substances, complications of surgical and medical care, and symptoms, signs, and ill-defined conditions) and previously identified diagnoses of hospital admissions. The characterization of the vulnerability to heat can help improve clinical and public health practices to reduce the health risks posed by a warming planet. https://doi.org/10.1289/EHP13254.

Associations between heat waves and chronic kidney disease in China: The modifying role of land cover

The increasing frequency of heat waves under the global urbanization and climate change background poses elevating risks of chronic kidney disease (CKD). Nevertheless, there has been no evidence on associations between long-term exposures to heat waves and CKD as well as the modifying effects of land cover patterns. Based on a national representative population-based survey on CKD covering 47,086 adults and high spatial resolution datasets on temperature and land cover data, we found that annual days of exposure to heat waves were associated with increased odds of CKD prevalence. For one day/year increases in HW_975_4d (above 97.5 % of annual maximum temperature and lasting for at least 4 consecutive days), the odds ratio (OR) of CKD was 1.14 (95 %CI: 1.12, 1.15). Meanwhile, stronger associations were observed in regions with lower urbanicity [rural: 1.14 (95 %CI: 1.12, 1.16) vs urban: 1.07 (95 %CI: 1.03, 1.11), Pinteraction < 0.001], lower water body coverage [lower: 1.14 (95 %CI: 1.12, 1.16) vs higher: 1.02 (95 %CI: 0.98, 1.05), Pinteraction < 0.001], and lower impervious area coverage [lower: 1.16 (95 %CI: 1.14, 1.18) vs higher: 1.06 (95 %CI: 1.03, 1.10), Pinteraction = 0.008]. In addition, this study found disparities in modifying effects of water bodies and impervious areas in rural and urban settings. In rural regions, the associations between heat waves and CKD prevalence showed a consistent decreasing trend with increases in both proportions of water bodies and impervious areas (Pinteraction < 0.05). Nevertheless, in urban regions, we observed significant effect modification by water bodies, but not by impervious areas. Our study indicates the need for targeted land planning as part of adapting to the kidney impacts of heat waves, with a focus on urbanization in rural regions, as well as water body construction and utilization in both rural and urban regions.

Effects of extreme temperature events on deaths and its interaction with air pollution

BACKGROUND

Both extreme temperature events (ETEs) and air pollution affected human health, and their effects were often not independent. Previous studies have provided limited information on the interactions between ETEs and air pollution.

METHODS

We collected data on deaths (non-accidental, cardiovascular, and respiratory) in Zibo City along with daily air pollution and meteorological data from January 2015 to December 2019. Distributed lag non-linear model was used to explore the health effects of ETEs on deaths. Non-parametric binary response model, hierarchical model and joint effect model were used to further explore the interaction between ETEs and air pollution in different seasons. Meanwhile, subgroup analysis by gender and age (≥ 65 years old and < 65 years old) was conducted to identify the vulnerable population.

RESULTS

ETEs increased death risk, especially for cardiovascular and respiratory deaths. Heat waves had a stronger impact than cold spells. Cold spells had a longer lag and fluctuating trend. Heat waves had a short-term impact, followed by a decrease. Females and those aged ≥ 65 were more affected, but subgroup differences were not significant. During ETEs and non-ETEs, there were different effects on deaths with per IQR increase in air pollutant concentrations. Joint effect models revealed that there was a significant interaction between ETEs and air pollution on non-accidental deaths. The interaction between PM2.5 and cold spells was antagonistic in the cold season. In the warm season, the health effects of heat waves and high O3 concentration were enhanced. The relative excess risk due to interaction (RERI) of cold spells and PM2.5 in total population was -0.09 (95 % CI: -0.17, -0.01), and 9 % (95 % CI: 1 %, 17 %) of the total effect was attributable to interaction. Subgroup analysis confirmed the interactions in females and those aged ≥ 65.

CONCLUSIONS

Significant association observed between ETEs and deaths. Females and ≥ 65 age groups were vulnerable. There were interactions between ETEs and air pollution. The effect of PM2.5 on deaths decreased during cold spells, while the effect of O3 increased during heat waves. In addition to improving air quality, it is necessary to further strengthen the prevention and control of ETEs.

Modification of heat-related effects on mortality by air pollution concentration, at small-area level, in the Attica prefecture, Greece

BACKGROUND

The independent effects of short-term exposure to increased air temperature and air pollution on mortality are well-documented. There is some evidence indicating that elevated concentrations of air pollutants may lead to increased heat-related mortality, but this evidence is not consistent. Most of these effects have been documented through time-series studies using city-wide data, rather than at a finer spatial level. In our study, we examined the possible modification of the heat effects on total and cause-specific mortality by air pollution at municipality level in the Attica region, Greece, during the warm period of the years 2000 to 2016.

METHODS

A municipality-specific over-dispersed Poisson regression model during the warm season (May-September) was used to investigate the heat effects on mortality and their modification by air pollution. We used the two-day average of the daily mean temperature and daily mean PM10, NO2 and 8 hour-max ozone (O3), derived from models, in each municipality as exposures. A bivariate tensor smoother was applied for temperature and each pollutant alternatively, by municipality. Α random-effects meta-analysis was used to obtain pooled estimates of the heat effects at different pollution levels. Heterogeneity of the between-levels differences of the heat effects was evaluated with a Q-test.

RESULTS

A rise in mean temperature from the 75th to the 99th percentile of the municipality-specific temperature distribution resulted in an increase in total mortality of 12.4% (95% Confidence Interval (CI):7.76-17.24) on low PM10 days, and 21.25% (95% CI: 17.83-24.76) on high PM10 days. The increase on mortality was 10.09% (95% CI: - 5.62- 28.41) on low ozone days, and 14.95% (95% CI: 10.79-19.27) on high ozone days. For cause-specific mortality an increasing trend of the heat effects with increasing PM10 and ozone levels was also observed. An inconsistent pattern was observed for the modification of the heat effects by NO2, with higher heat effects estimated in the lower level of the pollutant.

CONCLUSIONS

Our results support the evidence of elevated heat effects on mortality at higher levels of PM10 and 8 h max O3. Under climate change, any policy targeted at lowering air pollution levels will yield significant public health benefits.

The effect modification of PM2.5 and ozone on the short-term associations between temperature and mortality across the urban areas of Japan

BACKGROUND

The acute effects of temperature and air pollution on mortality are well-known environmental factors that have been receiving more recognition lately. However, the health effects resulting from the interaction of air pollution and temperature remain uncertain, particularly in cities with low levels of pollution. This study aims to examine the modification effects of particulate matter with a diameter of 2.5 µm or less (PM2.5) and ozone (O3) on the association between temperature and mortality.

METHODS

We collected the daily number of all-cause, cardiovascular, and respiratory mortality from 20 major cities in Japan from 2012-2018. We obtained meteorological data from the Japan Meteorological Agency and air pollution data from the National Institute for Environmental Studies. We conducted analyses using a quasi-Poisson regression model with a distributed lag non-linear model for temperature in each city and subsequently performed a random-effects meta-analysis to derive average estimates.

RESULTS

We found that high levels of O3 might positively modify the mortality risk of heat exposure, especially for cardiovascular diseases. Subgroups such as the elderly and females were susceptible. We did not observe consistent evidence of effect modification by PM2.5, including effect modification on cold by both pollutants.

CONCLUSION

PM2.5 and O3 may positively modify the short-term association between heat and mortality in the urban areas of Japan. These results highlight the need for public health policies and interventions to address the collective impacts of both temperature and air pollution.