Temperature and mortality in nine US cities

Temperature and myocardial infarction among migrants in Kuwait

BACKGROUND

Kuwait, one of the world's hottest countries, faces increasing temperatures due to climate change. With a large migrant population predominantly employed in physically demanding jobs, the exact effects and burdens of temperature exposure on cardiovascular risk among this population remain unknown. This study aimed to investigate the relationship between temperature and myocardial infarction (MI) risk among migrants in Kuwait.

METHODS

MI hospital admissions data from 17 public hospitals in Kuwait from 2000 to 2017 were collected. Meteorological data, including daily temperatures and humidity, were obtained from monitoring stations. A time series analysis was conducted to examine the association between temperature and MI hospitalisation. A distributed lag non-linear model was used to study the lagged association of temperature. Seasonality, relative humidity and day of the week were adjusted for in the model. Excess hospitalisations attributed to temperature variations were calculated.

RESULTS

A total of 26 839 MI cases were examined. The optimal temperature with the lowest MI cases was 39.2°C. Elevated MI risks were associated with both hot and cold temperatures above or below this threshold, particularly at shorter lag days. Hot temperatures showed a pronounced association at lag 0, while cold temperatures demonstrated a weak effect at lag 7. The cumulative risk of MI for cold temperatures was higher than the risk for hot temperatures. Annually, 300 (20.1%) MI cases can be attributed to all cool days (below 39.2°C). Very hot days (above 39.2°C) contributed to about 9 (0.6%) MI cases each year among migrants in Kuwait.

CONCLUSION

The study revealed a substantial burden of both hot and cold ambient temperatures and the risk of MI at shorter lag days among the migrant population in Kuwait. This study provides valuable insights for government officials to mitigate exposure to extreme temperatures, especially in occupational settings.

Impact of rapid temperature fluctuations on acute stroke risk: a nationwide case-crossover study from 2001 to 2020

Background

Climate factors greatly affect cardiovascular health, with stroke ranking among serious global concerns. However, the impact of rapid temperature fluctuations on stroke risk remains underexplored. Given Taiwan's aging population and the intensifying effects of climate change, understanding influence of ambient temperatures on stroke risk is crucial for public health protection. This study aimed to explore the link between ambient temperature, sudden day-to-day temperature changes, and stroke onset in Taiwan, taking air pollutants into consideration.

Methods

We conducted a time-stratified case-crossover study from 2001 to 2020 using Distributed Lag Nonlinear Models (DLNM) within conditional logistic regression to examine lagged associations between temperature parameters and stroke risk. We analyzed associations separately for total stroke, ischemic stroke, and hemorrhagic stroke to identify potential differences in risk patterns, using odds ratios (ORs) relative to the temperature associated with the lowest stroke risk. Data from the National Health Insurance Research Database (NHIRD) identified the study population, including 1,100,074 first-time stroke emergency events and self-matched with 2,200,148 non-stroke onset dates as controls. The primary exposure assessments included daily temperatures (mean, maximum, and minimum) and temperature fluctuations (diurnal temperature range (DTR), sudden day-to-day temperature increases (TDI), and sudden day-to-day temperature decrease (TDD)), adjusted for air pollutants (PM2.5, O3, SO2, and NO2), and rainfall. Lag periods up to 13 days prior to the corresponding event or control days were used to examine the lag effect of stroke risk.

Findings

Through DLNM exposure-lag-response effect analysis after adjustment for PM2.5, O3, SO2, NO2, and rainfall, the study revealed that when TDI exceeded 6 °C, the risk of ischemic stroke more than doubled compared to the lowest risk temperature (OR: 2.173, 95% CI: 1.887, 2.501). The risk continued to rise until 9 °C, with a second peak observed when TDI exceeded 16 °C (OR: 2.096, 95% CI: 1.733, 2.535). Conversely, TDD exceeding 14 °C was linked to heightened hemorrhagic stroke risk (OR: 2.187, 95% CI: 2.055, 2.326). Additionally, daily maximum temperature exceeding 35 °C was associated with an increased stroke risk, primarily affecting ischemic stroke, while daily minimum temperature below 16 °C was strongly associated with a doubled risk of hemorrhagic stroke.

Interpretation

Our findings indicate that sudden day-to-day temperature increases and decreases are significant predictors of stroke onset. These results emphasize a noteworthy relationship between temperature and stroke risk over consecutive days, supporting interventions aimed at reducing stroke incidence.

Funding

This research was supported by the National Science and Technology Council (NSTC), Executive Yuan, Taiwan, grant No. NSTC-111-2119-M-865-002.

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.

Association between nighttime and daytime ambient temperature and insomnia using national emergency department database in the capital city of South Korea

Insomnia is a growing health concern globally, with significant implications for public health. Most studies have primarily focused on the effects of nighttime temperatures on sleep problems. However, there is a lack of studies comparing nighttime temperatures with daytime temperatures, which are more closely related to daily life activities. This study aimed to explore a short-term association of nighttime and daytime ambient temperature with emergency department (ED) visits for insomnia in the capital city of South Korea. A time-stratified case-crossover design was employed using a conditional logistic regression model. A distributed lag non-linear model was utilized to explore potential non-linear and lag effects of ambient temperature on ED visits for insomnia. Odds ratio (OR) for temperature with maximum ED visits for insomnia (MaxIT) and that for temperature with minimum ED visits for insomnia (MinIT) were calculated and compared. We observed significant associations at high temperatures for both nighttime and daytime (nighttime: 25.0℃ (94.1%) [OR: 1.82, 95% CIs: 1.31-2.55], daytime: 30.6℃ (99.0%) [OR: 2.13, 95% CIs: 1.49-3.06]) compared to MinIT (-8.5℃ (2.7%) and - 8.4℃ (1.0%), respectively). Subgroup analyses found significant associations at high temperatures in females, individuals aged 35-49, and those without comorbidities, and during spring, fall, and winter, for both daytime and nighttime. Our findings provide insights for proactive public health strategies for managing insomnia during global temperature rise.

Effect modification of air pollution on the association between heat and mortality in five European countries

BACKGROUND

Evidence suggests that air pollution modifies the association between heat and mortality. However, most studies have been conducted in cities without rural data. This time-series study examined potential effect modification of particulate matter (PM) and ozone (O3) on heat-related mortality using small-area data from five European countries, and explored the influence of area characteristics.

METHODS

We obtained daily non-accidental death counts from both urban and rural areas in Norway, England and Wales, Germany, Italy, and the Attica region of Greece during the warm season (2000-2018). Daily mean temperatures and air pollutant concentrations were estimated by spatial-temporal models. Heat effect modification by air pollution was assessed in each small area by over-dispersed Poisson regression models with a tensor smoother between temperature and air pollution. We extracted temperature-mortality relationships at the 5th (low), 50th (medium), and 95th (high) percentiles of pollutant distributions. At each air pollution level, we estimated heat-related mortality for a temperature increase from the 75th to the 99th percentile. We applied random-effects meta-analysis to derive the country-specific and overall associations, and mixed-effects meta-regression to examine the influence of urban-rural and coastal typologies and greenness on the heat effect modification by air pollution.

RESULTS

Heat-related mortality risks increased with higher PM levels, rising by 6.4% (95% CI: -2.0%-15.7%), 10.7% (2.6%-19.5%), and 14.1% (4.4%-24.6%) at low, medium, and high PM levels, respectively. This effect modification was consistent in urban and rural regions but more pronounced in non-coastal regions. In addition, heat-mortality associations were slightly stronger at high O3 levels, particularly in regions with low greenness.

CONCLUSION

Our analyses of both urban and rural data indicate that air pollution may intensify heat-related mortality, particularly in non-coastal and less green regions. The synergistic effect of heat and air pollution implies a potential pathway of reducing heat-related health impacts by improving air quality.

Temperature-mortality associations by age and cause: a multi-country multi-city study

Background

Heterogeneity in temperature-mortality relationships across locations may partly result from differences in the demographic structure of populations and their cause-specific vulnerabilities. Here we conduct the largest epidemiological study to date on the association between ambient temperature and mortality by age and cause using data from 532 cities in 33 countries.

Methods

We collected daily temperature and mortality data from each country. Mortality data was provided as daily death counts within age groups from all, cardiovascular, respiratory, or noncardiorespiratory causes. We first fit quasi-Poisson regression models to estimate location-specific associations for each age-by-cause group. For each cause, we then pooled location-specific results in a dose-response multivariate meta-regression model that enabled us to estimate overall temperature-mortality curves at any age. The age analysis was limited to adults.

Results

We observed high temperature effects on mortality from both cardiovascular and respiratory causes compared to noncardiorespiratory causes, with the highest cold-related risks from cardiovascular causes and the highest heat-related risks from respiratory causes. Risks generally increased with age, a pattern most consistent for cold and for nonrespiratory causes. For every cause group, risks at both temperature extremes were strongest at the oldest age (age 85 years). Excess mortality fractions were highest for cold at the oldest ages.

Conclusions

There is a differential pattern of risk associated with heat and cold by cause and age; cardiorespiratory causes show stronger effects than noncardiorespiratory causes, and older adults have higher risks than younger adults.

Random Forest and Feature Importance Measures for Discriminating the Most Influential Environmental Factors in Predicting Cardiovascular and Respiratory Diseases

BACKGROUND

Several studies suggest that environmental and climatic factors are linked to the risk of mortality due to cardiovascular and respiratory diseases; however, it is still unclear which are the most influential ones. This study sheds light on the potentiality of a data-driven statistical approach by providing a case study analysis.

METHODS

Daily admissions to the emergency room for cardiovascular and respiratory diseases are jointly analyzed with daily environmental and climatic parameter values (temperature, atmospheric pressure, relative humidity, carbon monoxide, ozone, particulate matter, and nitrogen dioxide). The Random Forest (RF) model and feature importance measure (FMI) techniques (permutation feature importance (PFI), Shapley Additive exPlanations (SHAP) feature importance, and the derivative-based importance measure (κALE)) are applied for discriminating the role of each environmental and climatic parameter. Data are pre-processed to remove trend and seasonal behavior using the Seasonal Trend Decomposition (STL) method and preliminary analyzed to avoid redundancy of information.

RESULTS

The RF performance is encouraging, being able to predict cardiovascular and respiratory disease admissions with a mean absolute relative error of 0.04 and 0.05 cases per day, respectively. Feature importance measures discriminate parameter behaviors providing importance rankings. Indeed, only three parameters (temperature, atmospheric pressure, and carbon monoxide) were responsible for most of the total prediction accuracy.

CONCLUSIONS

Data-driven and statistical tools, like the feature importance measure, are promising for discriminating the role of environmental and climatic factors in predicting the risk related to cardiovascular and respiratory diseases. Our results reveal the potential of employing these tools in public health policy applications for the development of early warning systems that address health risks associated with climate change, and improving disease prevention strategies.

Temperature-related neonatal deaths attributable to climate change in 29 low- and middle-income countries

Exposure to high and low ambient temperatures increases the risk of neonatal mortality, but the contribution of climate change to temperature-related neonatal deaths is unknown. We use Demographic and Health Survey (DHS) data (n = 40,073) from 29 low- and middle-income countries to estimate the temperature-related burden of neonatal deaths between 2001 and 2019 that is attributable to climate change. We find that across all countries, 4.3% of neonatal deaths were associated with non-optimal temperatures. Climate change was responsible for 32% (range: 19-79%) of heat-related neonatal deaths, while reducing the respective cold-related burden by 30% (range: 10-63%). Climate change has impacted temperature-related neonatal deaths in all study countries, with most pronounced climate-induced losses from increased heat and gains from decreased cold observed in countries in sub-Saharan Africa. Future increases in global mean temperatures are expected to exacerbate the heat-related burden, which calls for ambitious mitigation and adaptation measures to safeguard the health of newborns.

Evaluating the temperature-mortality relationship over 16 years in Cyprus

In many regions of the world, the relationship between ambient temperature and mortality is well-documented, but little is known about Cyprus, a Mediterranean island country where climate change is progressing faster than the global average. We Examined the association between daily ambient temperature and all-cause mortality risk in Cyprus. We conducted a time-series analysis with quasipoisson distribution and distributed lag non-linear models to investigate the association between temperature and all-cause mortality from 1 January 2004 to 31 December 2019 in five districts in Cyprus. We then performed a meta-analysis to estimate the overall temperature-mortality dose-response relationship in Cyprus. Excess mortality was computed to determine the public health burden caused by extreme temperatures. We did not find evidence of heterogeneity between the five districts (p = 0.47). The pooled results show that for cold effects, comparing the 1st, 2.5th, and 5th percentiles to the optimal temperature (temperature associated with least mortality, 25 ℃), the overall relative risks of mortality were 1.55 (95% CI: 1.32, 1.82), 1.41 (95% CI: 1.21, 1.64), and 1.32 (95% CI: 1.15, 1.52), respectively. For heat effects, the overall relative risks of mortality at the 95th, 97.5th and 99th percentiles were 1.10 (95% CI: 1.04, 1.16), 1.17 (95% CI: 1.07, 1.29), and 1.29 (95% CI: 1.11, 1.5), respectively. The excess mortality attributable to cold days accounted for 8.0 deaths (95% empirical CI: 4.5-10.8) for every 100 deaths, while the excess mortality attributable to heat days accounted for 1.3 deaths (95% empirical CI: 0.7-1.7) for every 100 deaths. The results prompt additional research into environmental risk prevention in this under-studied hot and dry region that could experience disproportionate climate change related exposures.Implications: The quantification of excess mortality attributable to temperature extremes shows an urgent need for targeted public health interventions and climate adaptation strategies in Cyprus and similar regions facing rapid climate change. Future steps should look into subpopulation sensitivity, coping strategies, and adaptive interventions to reduce potential future risks.

Home indoor air quality and cognitive function over one year for people working remotely during COVID-19

The coronavirus disease 2019 (COVID-19) pandemic triggered an increase in remote work-from-home for office workers. Given that many homes now function as offices despite not being designed to support office work, it is critical to research the impact of indoor air quality (IAQ) in homes on the cognitive performance of people working from home. In this study, we followed 206 office workers across the U.S. over one year under remote or hybrid-remote settings during 2021-2022. Participants placed two real-time, consumer-grade indoor environmental monitors in their home workstation area and bedroom. Using a custom smartphone application geofenced to their residential address, participants responded to surveys and periodic cognitive function tests, including the Stroop color-word interference test, Arithmetic two-digit addition/subtraction test, and Compound Remote Associates Task (cRAT). Exposures assessed included carbon dioxide (CO2) and thermal conditions (indoor heat index: a combination of temperature and relative humidity) averaged over 30 minutes prior to each cognitive test. In fully adjusted longitudinal mixed models (n≤121), we found that indoor thermal conditions at home were associated with cognitive function outcomes non-linearly (p<0.05), with poorer cognitive performance on the Stroop test and poorer creative problem-solving on the cRAT when conditions were either too warm or too cool. Most indoor CO2 levels were <640 ppm, but there was still a slight association between higher CO2 and poorer cognitive performance on Stroop (p=0.09). Our findings highlight the need to enhance home indoor environmental quality for optimal cognitive function during remote work, with benefits for both employees and employers.

Long-term exposure to high perceived temperature and risk of mortality among patients with chronic kidney disease

Health risks due to climate change are emerging, particularly from high-temperature exposure. The perceived temperature is an equivalent temperature based on the complete heat budget model of the human body. Therefore, we aimed to analyze the effect of perceived temperature on overall mortality among patients with chronic kidney disease. In total, 32,870 patients with chronic kidney disease in Seoul participated in this retrospective study (2001-2018) at three medical centers. The perceived temperature during the summer season was calculated using meteorological factors, including the air temperature near the automated weather station, dew point temperature, wind velocity, and total cloud amount. We assessed the association between perceived temperature using Kriging spatial interpolation and mortality in patients with CKD in the time-varying Cox proportional hazards model that was adjusted for sex, age, body mass index, hypertension, diabetes mellitus, estimated glomerular filtration rate, smoking, alcohol consumption, and educational level. During the 6.14 ± 3.96 years of follow-up, 3863 deaths were recorded. In multivariable analysis, the average level of perceived temperature and maximum level of perceived temperature demonstrated an increased risk of overall mortality among patients with chronic kidney disease. The concordance index for mortality of perceived temperature was higher than temperature, discomfort index, and heat index. When stratified by age, diabetes mellitus, and estimated glomerular filtration rate, patients with chronic kidney disease with young age (age <65 years) showed higher hazard ratio for mortality (interaction P = 0.049). Moreover, the risk of death in the winter and spring seasons was more significant compared to that of the summer and autumn seasons. Therefore, long-term exposure to high perceived temperature during summer increases the risk of mortality among patients with chronic kidney disease.

Association between temperature and mortality: a multi-city time series study in Sichuan Basin, southwest China

BACKGROUND

There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden.

METHODS

Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status.

RESULTS

A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status.

CONCLUSIONS

Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.

Heat Stress-Induced Fetal Intrauterine Growth Restriction Is Associated with Elevated LPS Levels Along the Maternal Intestine-Placenta-Fetus Axis in Pregnant Mice

The exacerbation of the greenhouse effect has made heat stress (HS) an important risk factor for the occurrence of intrauterine growth restriction (IUGR). The experiment aims to uncover the effects of maternal HS on IUGR and its mechanisms. The results showed that HS leads to decreased maternal and fetal birth weights, accompanied by increased serum oxidative stress and cortisol levels. Moreover, HS inflicted significant damage to both the intestinal and placental barriers, altering maternal gut microbiota and increasing intestinal LPS levels. As a result, LPS levels increased in maternal serum, placenta, and fetus. Furthermore, HS damaged the intestinal structure, intensifying inflammation and disrupting the redox balance. The placenta exposed to HS exhibited changes in the placental structure along with disrupted angiogenesis and decreased levels of nutritional transporters. Additionally, the leakage of LPS triggered placental JNK and ERK phosphorylation, ultimately inducing severe placental inflammation and oxidative stress. This study suggests that LPS translocation from the maternal intestine to the fetus, due to a disrupted gut microbiota balance and compromised intestinal and placental barrier integrity, may be the primary cause of HS-induced IUGR. Furthermore, increased LPS leakage leads to placental inflammation, redox imbalance, and impaired nutrient transport, further restricting fetal growth.

Analyzing the Interactions between Environmental Parameters and Cardiovascular Diseases Using Random Forest and SHAP Algorithms

Background

Cardiovascular diseases (CVD) remain the predominant global cause of mortality, with both low and high temperatures increasing CVD-related mortalities. Climate change impacts human health directly through temperature fluctuations and indirectly via factors like disease vectors. Elevated and reduced temperatures have been linked to increases in CVD-related hospitalizations and mortality, with various studies worldwide confirming the significant health implications of temperature variations and air pollution on cardiovascular outcomes.

Methods

A database of daily Emergency Room admissions at the Giovanni XIII Polyclinic in Bari (Southern Italy) was developed, spanning from 2013 to 2019, including weather and air quality data. A Random Forest (RF) supervised machine learning model was used to simulate the trend of hospital admissions for CVD. The Seasonal and Trend decomposition using Loess (STL) decomposition model separated the trend component, while cross-validation techniques were employed to prevent overfitting. Model performance was assessed using specific metrics and error analysis. Additionally, the SHapley Additive exPlanations (SHAP) method, a feature importance technique within the eXplainable Artificial Intelligence (XAI) framework, was used to identify the feature importance.

Results

An R 2 of 0.97 and a Mean Absolute Error of 0.36 admissions were achieved by the model. Atmospheric pressure, minimum temperature, and carbon monoxide were found to collectively contribute about 74% to the model's predictive power, with atmospheric pressure being the dominant factor at 37%.

Conclusions

This research underscores the significant influence of weather-climate variables on cardiovascular diseases. The identified key climate factors provide a practical framework for policymakers and healthcare professionals to mitigate the adverse effects of climate change on CVD and devise preventive strategies.

The effects of summer ambient temperature on total mortality in Serbia

In the context of recent climate change, temperature-attributable mortality has become an important public health threat worldwide. A large number of studies in Europe have identified a relationship between temperature and mortality, while only a limited number of scholars provided evidence for Serbia. In order to provide more evidence for better management of health resources at the regional and local level, this study aims to assess the impact of summer temperature on the population in Serbia, using daily average temperature (Ta) and mortality (CDR (crude death rate) per 100,000). The analysis was done for five areas (Belgrade, Novi Sad, Niš, Loznica, and Vranje), covering the summer (June-August) period of 2001-2015. In order to quantify the Ta-related CDR, a generalized additive model (GAM) assuming a quasi-Poisson distribution with log as the link function was used. Five regression models were constructed, for each area, revealing a statistically significant positive relationship between Ta and CDR in four areas. The effect of Ta on CDR was defined as the relative risk (RR), which was obtained as the exponential regression coefficient of the models. RR indicates that a 1 °C increase in Ta at lag0 was associated with an increase in CDR of 1.7% for Belgrade, Novi Sad, and Niš and 2% for Loznica. The model for Vranje did not quantify a statistically significant increase in CDR due to Ta (RR=1.006, 95% CI 0.991-1.020). Similar results were confirmed for gender, with a slightly higher risk for women. Analysis across lag structure showed different exposure, but the highest effect of Ta mainly occurs over the short term and persists for 3 days.

Associations of solar activity and related exposures with fetal growth

BACKGROUND

Solar and geomagnetic activity have been shown to suppress melatonin and to degrade folate levels, important hormones for fetal development. We examined whether solar and geomagnetic activity were associated with fetal growth.

METHODS

We included 9573 singleton births with 26,879 routine ultrasounds at an academic medical center in Eastern Massachusetts from 2011 through 2016. Sunspot number and Kp index were obtained from the NASA Goddard Space Flight Center. Three exposure windows were considered, including the first 16 weeks of pregnancy, one month prior to fetal growth measurement, and conception until fetal growth measurement (cumulative). Ultrasound scans from which we extracted biparietal diameter, head circumference, femur length, and abdominal circumference measurements were categorized as anatomic (<24 weeks' gestation) or growth scans (≥24 weeks' gestation) based on clinical practice. Ultrasound parameters and birth weight were standardized, and linear mixed models adjusted for long-term trends were fitted.

RESULTS

Prenatal exposures were positively associated with larger head parameters measured <24 weeks' gestation, negatively associated with smaller fetal parameters measured ≥24 weeks' gestation, and not associated with birth weight. The strongest associations were observed for cumulative exposure in growth scans, where an interquartile range increase in sunspot number (32.87 sunspots) was associated with a -0.17 (95 % CI: -0.26, -0.08), -0.25 (-0.36, -0.15), and -0.13 (95 % CI: -0.23, -0.03) difference in mean biparietal diameter, head circumference, and femur length z-score, respectively. An interquartile range increase in cumulative Kp index (0.49) was associated with a -0.11 (95 % CI: -0.22, -0.01) and -0.11 (95 % CI: -0.20, -0.02) difference in mean head circumference and abdominal circumference z-score, respectively, in growth scans.

CONCLUSIONS

Solar and geomagnetic activity were associated with fetal growth. Future studies are needed to better understand the impact of these natural phenomena on clinical endpoints.

Heat-related cardiorespiratory mortality: Effect modification by air pollution across 482 cities from 24 countries

BACKGROUND

Evidence on the potential interactive effects of heat and ambient air pollution on cause-specific mortality is inconclusive and limited to selected locations.

OBJECTIVES

We investigated the effects of heat on cardiovascular and respiratory mortality and its modification by air pollution during summer months (six consecutive hottest months) in 482 locations across 24 countries.

METHODS

Location-specific daily death counts and exposure data (e.g., particulate matter with diameters ≤ 2.5 µm [PM2.5]) were obtained from 2000 to 2018. We used location-specific confounder-adjusted Quasi-Poisson regression with a tensor product between air temperature and the air pollutant. We extracted heat effects at low, medium, and high levels of pollutants, defined as the 5th, 50th, and 95th percentile of the location-specific pollutant concentrations. Country-specific and overall estimates were derived using a random-effects multilevel meta-analytical model.

RESULTS

Heat was associated with increased cardiorespiratory mortality. Moreover, the heat effects were modified by elevated levels of all air pollutants in most locations, with stronger effects for respiratory than cardiovascular mortality. For example, the percent increase in respiratory mortality per increase in the 2-day average summer temperature from the 75th to the 99th percentile was 7.7% (95% Confidence Interval [CI] 7.6-7.7), 11.3% (95%CI 11.2-11.3), and 14.3% (95% CI 14.1-14.5) at low, medium, and high levels of PM2.5, respectively. Similarly, cardiovascular mortality increased by 1.6 (95%CI 1.5-1.6), 5.1 (95%CI 5.1-5.2), and 8.7 (95%CI 8.7-8.8) at low, medium, and high levels of O3, respectively.

DISCUSSION

We observed considerable modification of the heat effects on cardiovascular and respiratory mortality by elevated levels of air pollutants. Therefore, mitigation measures following the new WHO Air Quality Guidelines are crucial to enhance better health and promote sustainable development.

Hourly personal temperature exposure and heart rate variability: A multi-center panel study in populations at intermediate to high-risk of cardiovascular disease

BACKGROUND

Several studies reported temperature exposure was associated with altered cardiac automatic function, while this effect of temperature on hourly heart rate variability (HRV) among populations with cardiovascular risks was seldom addressed.

METHODS

We conducted this panel study in four Chinese cities with three repeated visits among 296 participants at intermediate to high-risk of cardiovascular disease (CVD). Real-time temperature level and 24-h ambulatory electrocardiogram were monitored during each seasonal visit. Linear mixed-effects models were used to investigate associations between individual temperature and HRV parameters, and the seasonal effects and circadian effect were also evaluated.

RESULTS

We found the overall downward trend of hourly HRV associated with acute exposure to higher temperature. For each 1 °C increment in temperature of 1-3 h prior to HRV measurements (lag 1-3 h), hourly standard deviation of normal-to-normal intervals (SDNN) decreased by 0.38% (95% confidence interval [CI]: 0.22, 0.54), 0.28% (95% CI: 0.12, 0.44), and 0.20% (95% CI: 0.04, 0.36), respectively. Similar inverse associations between temperature and HRV were observed in stratified analyses by temperature level. Inverse associations for cold and warm seasons were also observed, despite some effects gradually decreased and reversed in the warm season as lag times extended. Moreover, HRV showed a more significant reduction with increased temperature during daytime than nighttime. Percent change of hourly SDNN was -0.41% (95% CI: -0.62, -0.21) with 1 °C increment of lag 1 h during daytime, while few obvious changes were revealed during nighttime.

CONCLUSIONS

Generally, increasing temperature was significantly associated with reduced HRV. Inverse relationships for cold and warm seasons were also observed. Associations during daytime were much more prominent than nighttime. Our findings clarified the relationship of temperature with HRV and provided evidence for prevention approaches to alleviate cardiac automatic dysfunction among populations at intermediate to high-risk of CVD.

High-resolution spatiotemporal modeling of daily near-surface air temperature in Germany over the period 2000-2020

The commonly used weather stations cannot fully capture the spatiotemporal variability of near-surface air temperature (T_air), leading to exposure misclassification and biased health effect estimates. We aimed to improve the spatiotemporal coverage of T_air data in Germany by using multi-stage modeling to estimate daily 1 × 1 km minimum (T_min), mean (T_mean), maximum (T_max) T_air and diurnal T_air range during 2000-2020. We used weather station T_air observations, satellite-based land surface temperature (LST), elevation, vegetation and various land use predictors. In the first stage, we built a linear mixed model with daily random intercepts and slopes for LST adjusted for several spatial predictors to estimate T_air from cells with both T_air and LST available. In the second stage, we used this model to predict T_air for cells with only LST available. In the third stage, we regressed the second stage predictions against interpolated T_air values to obtain T_air countrywide. All models achieved high accuracy (0.91 ≤ R² ≤ 0.98) and low errors (1.03 °C ≤ Root Mean Square Error (RMSE) ≤ 2.02 °C). Validation with external data confirmed the good performance, locally, i.e., in Augsburg for all models (0.74 ≤ R² ≤ 0.99, 0.87 °C ≤ RMSE ≤ 2.05 °C) and countrywide, for the T_mean model (0.71 ≤ R² ≤ 0.99, 0.79 °C ≤ RMSE ≤ 1.19 °C). Annual T_mean averages ranged from 8.56 °C to 10.42 °C with the years beyond 2016 being constantly hotter than the 21-year average. The spatial variability within Germany exceeded 15 °C annually on average following patterns including mountains, rivers and urbanization. Using a case study, we showed that modeling leads to broader T_air variability representation for exposure assessment of participants in health cohorts. Our results indicate the proposed models as suitable for estimating nationwide T_air at high resolution. Our product is critical for temperature-based epidemiological studies and is also available for other research purposes.

The joint and interaction effect of high temperature and humidity on mortality in China

BACKGROUND

Although many studies have reported the mortality effect of temperature, there were few studies on the mortality risk of humidity, let alone the joint effect of temperature and humidity. This study aimed to investigate the joint and interaction effect of high temperature and relative humidity on mortality in China, which will deepen understanding the health risk of mixture climate exposure.

METHODS

The mortality and meteorological data were collected from 353 locations in China (2013-2017 in Jilin, Hunan, Guangdong and Yunnan provinces, 2009-2017 in Zhejiang province, and 2006-2011 in other Provinces). We defined location-specific daily mean temperature ≥ 75th percentile of distribution as high temperature, while minimum mortality relative humidity as the threshold of high relative humidity. A time-series model with a distributed lag non-linear model was first employed to estimate the location-specific associations between humid-hot events and mortality, then we conducted meta-analysis to pool the mortality effect of humid-hot events. Finally, an additive interaction model was used to examine the interactive effect between high temperature and relative humidity.

RESULTS

The excess rate (ER) of non-accidental mortality attributed to dry-hot events was 10.18% (95% confidence interval (CI): 8.93%, 11.45%), which was higher than that of wet-hot events (ER = 3.21%, 95% CI: 0.59%, 5.89%). The attributable fraction (AF) of mortality attributed to dry-hot events was 10.00% (95% CI: 9.50%, 10.72%) with higher burden for females, older people, central China, cardiovascular diseases and urban city. While for wet-hot events, AF was much lower (3.31%, 95% CI: 2.60%, 4.30%). We also found that high temperature and low relative humidity had synergistic additive interaction on mortality risk.

CONCLUSION

Dry-hot events may have a higher risk of mortality than wet-hot events, and the joint effect of high temperature and low relative humidity may be greater than the sum of their individual effects.

Residential and Race/Ethnicity Disparities in Heat Vulnerability in the United States

Adverse health outcomes caused by extreme heat represent the most direct human health threat associated with the warming of the Earth's climate. Socioeconomic, demographic, health, land cover, and temperature determinants contribute to heat vulnerability; however, nationwide patterns of residential and race/ethnicity disparities in heat vulnerability in the United States are poorly understood. This study aimed to develop a Heat Vulnerability Index (HVI) for the United States; to assess differences in heat vulnerability across geographies that have experienced historical and/or contemporary forms of marginalization; and to quantify HVI by race/ethnicity. Principal component analysis was used to calculate census tract level HVI scores based on the 2019 population characteristics of the United States. Differences in HVI scores were analyzed across the Home Owners' Loan Corporation (HOLC) "redlining" grades, the Climate and Economic Justice Screening Tool (CEJST) disadvantaged versus non-disadvantaged communities, and race/ethnicity groups. HVI scores were calculated for 55,267 U.S. census tracts. Mean HVI scores were 17.56, 18.61, 19.45, and 19.93 for HOLC grades "A"-"D," respectively. CEJST-defined disadvantaged census tracts had a significantly higher mean HVI score (19.13) than non-disadvantaged tracts (16.68). The non-Hispanic African American or Black race/ethnicity group had the highest HVI score (18.51), followed by Hispanic or Latino (18.19). Historically redlined and contemporary CEJST disadvantaged census tracts and communities of color were found to be associated with increased vulnerability to heat. These findings can help promote equitable climate change adaptation policies by informing policymakers about the national distribution of place- and race/ethnicity-based disparities in heat vulnerability.

Impact of environmental factors on heat-associated mortalities in an urban desert region

The troubling trend of rising heat-associated mortalities in an urban desert region (Maricopa County, AZ, USA) has motivated us to explore the extent to which environmental factors may contribute to increased heat-health risks. Summertime data from 2010 to 2019 were used to construct a suite of models for daily heat-associated mortalities. The best-performing full model included the following predictors, ordered from strongest to weakest influence: daily average air temperature, average of previous 5 days daily average air temperature, year, day of year, average of previous 5 days daily average dew point temperature, average of previous 5 days daily average PM_2.5, and daily average PM₁₀. This full model exhibited a 5.39% reduction in mean absolute error in daily heat-associated mortalities as compared to the best-performing model that included only air temperature as an environmental predictor. The extent to which issued and modeled excessive heat warnings (from both the temperature only and full models) corresponded with heat-associated mortalities was also examined. Model hindcasts for 2020 and 2021 showed that the models were able to capture the high number of heat-associated mortalities in 2020, but greatly undercounted the highest yet observed number of heat-associated mortalities in 2021. Results from this study lend insights into environmental factors corresponding to an increased number of heat-associated mortalities and can be used for informing strategies towards reducing heat-health risks. However, as the best-performing model was unable to fully capture the observed number of heat-associated mortalities, continued scrutiny of both environmental and non-environmental factors affecting these observations is needed.

Analysis of land surface temperature with land use and land cover and elevation from NASA MODIS satellite data: a case study of Bali, Indonesia

The Moderate Resolution Imaging Spectroradiometer (MODIS) of the National Aeronautics and Space Administration (NASA) offers numerous land products of the Earth's datasets. On the other hand, researchers find it difficult to retrieve this data for specific places. The methods for extracting and analyzing land surface temperature (LST), land use and land cover (LULC), and elevation are presented in this study. The R commands provided make the time-consuming process of extracting data for specific places much more accessible. As a result, a statistical study of LST over Bali is shown as an example. Over the 15 regions of Bali, a quadratic polynomial identified five possible warming patterns, while a logistic regression model assessed the probability of warming. The findings suggest that 25.2% of Bali has warmed during the last two decades, with temperatures being highest in urban and built-up areas and deciduous forests and inversely associated with elevation. Global warming has sparked a lot of academic interest and has become a serious climate problem. The techniques proposed in this work simplify the extraction of LST, LULC, and elevation data from MODIS satellites. These approaches can also be used on other datasets with identical topologies, such as the normalized difference vegetation index (NDVI), aerosol optical depth (AOD), and night light data.

Research on adaption to air pollution in Chinese cities: Evidence from social media-based health sensing

Air pollution seriously threats to human health. Understanding the health effects of air pollution is of great importance for developing countermeasures. However, little is known about the real-time impacts of air pollution on the human heath in a comprehensive way in developing nations, like China. To fill this research gap, the Chinese urbanites' health were sensed from more than 210.82 million Weibo (Chinese Twitter) data in 2017. The association between air pollution and the health sensing were quantified through generalized additive models, based on which the sensitivities and adaptions to air pollution in 70 China's cities were assessed. The results documented that the Weibo data can well sense urbanites' health in real time. With the different geographical characteristics and socio-economic conditions, the Chinese residents have adaption to air pollution, indicated by the spatial heterogeneity of the sensitivities to air pollution. Cities with good air quality in South China and East China were more sensitive to air pollution, while cities with worse air quality in Northwest China and North China were less sensitive. This research provides a new perspective and methodologies for health sensing and the health effect of air pollution.

Global Health Impacts for Economic Models of Climate Change: A Systematic Review and Meta-Analysis

Rationale: Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts. Objectives: In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models. Methods: Regionally resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review. Results: Effect estimates and associated uncertainties varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1% to 1.1% per 1°C) were estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel and included the following: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socioeconomic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models. Conclusions: This work provides an example of how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates.

Relationship between Depressive Symptoms and Weather Conditions

Background: Weather is a well-known factor worldwide in psychiatric problems such as depression, with the elderly and females being particularly susceptible. The aim of this study was to detect associations between the risk of depressive symptoms (DS) and weather variables. Methods: 6937 participants were assessed in the baseline survey of the Health Alcohol Psychosocial Factors in Eastern Europe (HAPIEE) study during 2006−2008. To assess the risk of DS, a multivariate logistic model was created with predictors such as socio-demographic factors, health behaviors, and weather variables. Results: DS were found in 23.4% of the respondents, in 15.6% of males and in 29.9% in females. A higher risk of DS (by 25%) was associated with November−December, a rising wind speed, and relative humidity (RH) < 94% and snowfall during the cold period occurring 2 days before the survey. A higher air temperature (>14.2 °C) predominant during May−September had a protective impact. A higher risk of DS in males was associated with lower atmospheric pressure (<1009 hPa) 2 days before. Females were more sensitive to the monthly variation, snowfall, and RH. Conclusions: The findings of our study suggest that some levels of weather variables have a statistically significant effect on DS.

Effect of Cold Spells and Their Different Definitions on Mortality in Shenzhen, China

A high premium has been put on researching the effects of cold spells because of their adverse influence on people's daily lives and health. The study aimed to find the most appropriate definition of the cold spell in Shenzhen and quantify the impact of cold spells on mortality. Based on the daily mortality data in Shenzhen from 2013 to 2017 and the meteorological and pollutant data from the same period, we quantified the effect of cold spells using eight different definitions in the framework of a distributed lag non-linear model with a quasi-Poisson distribution. In Shenzhen, low temperatures increase the risk of death more significantly than high temperatures (using the optimal temperature as the cut-off value). Comparing the quasi-Akaike information criterion value, attribution fraction (b-AF), and attribution number (b-AN) for all causes of deaths and non-accidental deaths, the optimal definition of the cold spell was defined as the threshold was 3rd percentile of the daily average temperature and duration for 3 or more consecutive days (all causes: b-AF = 2.31% [1.01–3.50%], b-AN = 650; non-accidental: b-AF = 1.92% [0.57–3.17%], b-AN = 471). For cardiovascular deaths, the best definition was the temperature threshold as the 3rd percentile of the daily average temperature with a duration of 4 consecutive days (cardiovascular: b-AF = 1.37% [0.05–2.51%], b-AN = 142). Based on the best definition in the model, mortality risk increased in cold spells, with a statistically significant lag effect occurring as early as the 4th day and the effect of a single day lasting for 6 days. The maximum cumulative effect occurred on the 14th day (all-cause: RR = 1.54 [95% CI, 1.20–1.98]; non-accidental: RR = 1.43 [95% CI, 1.11–1.84]; cardiovascular: RR = 1.58 [95% CI, 1.00–2.48]). The elderly and females were more susceptible to cold spells. Cold spells and their definitions were associated with an increased risk of death. The findings of this research provide information for establishing an early warning system, developing preventive measures, and protecting susceptible populations.

The interplay between heated environment and active standing test on cardiovascular autonomic control in healthy individuals

Objective.To investigate the interplay between active standing and heat stress on cardiovascular autonomic modulation in healthy individuals.Approach.Blood pressure (BP) and ECG were continuously recorded during 30 min in supine (SUP) and 6 min in orthostatic position (ORT) under thermal reference (TC; ∼24 °C) or heated environment (HOT; ∼36 °C) conditions, in a randomized order. All data collection was performed during the winter and spring seasons when typical outdoor temperatures are ∼23 °C. Spectral analysis was employed by the autoregressive model of R-R and systolic blood pressure (SBP) time series and defined, within each band, in low (LF, 0.04 to 0.15 Hz) and high (0.15-0.40 Hz) frequencies. The indices of cardiac sympathetic (LF) and cardiac parasympathetic (HF) were normalized (nu) dividing each band power by the total power subtracted the very-low component (<0.04 Hz), obtaining the cardiac autonomic balance (LF/HF) modulation. The gain of the relationship between SBP and R-R variabilities within the LF band was utilized for analysis of spontaneous baroreflex sensitivity (alpha index;αLF). Nonlinear analysis was employed through symbolic dynamics of R-R, which provided the percentage of sequences of three heart periods without changes in R-R interval (0V%; cardiac sympathetic modulation) and two significant variations (2UV% and 2LV%; cardiac vagal modulation).Main results.HOT increased 0V% and HR, and decreasedαLF and 2UV% during SUP compared to TC. During ORT, HOT provokes a greater increment on HR, LF/HF and 0V%, indexes compared to ORT under TC.Significance.At rest, heat stress influences both autonomic branches, increasing sympathetic and decreasing vagal modulation and spontaneous baroreflex sensitivity. The augmented HR during active standing under heat stress seems to be mediated by a greater increment in cardiac sympathetic modulation, showing an interplay between gravitational and thermal stimulus.

Assessing mortality risk attributable to high ambient temperatures in Ahmedabad, 1987 to 2017

BACKGROUND

Studies on high temperatures and mortality have not focused on underdeveloped tropical regions and have reported the associations of different temperature metrics without conducting model selection.

METHODS

We collected daily mortality and meteorological data including ambient temperatures and humidity in Ahmedabad during summer, 1987-2017. We proposed two cross-validation (CV) approaches to compare semiparametric quasi-Poisson models with different temperature metrics and heat wave definitions. Using the fittest model, we estimated heat-mortality associations among general population and subpopulations. We also conducted separate analyses for 1987-2002 and 2003-2017 to evaluate temporal heterogeneity.

FINDINGS

The model with maximum and minimum temperatures and without heat wave indicator gave the best performance. With this model, we found a substantial and significant increase in mortality rate starting from maximum temperature at 42 °C and from minimum temperature at 28 °C: 1 °C increase in maximum and minimum temperatures at lag 0 were associated with 9.56% (95% confidence interval [CI]: 6.64%, 12.56%) and 9.82% (95% CI: 6.33%, 13.42%) increase in mortality risk, respectively. People aged ≥65 years and lived in South residential zone where most slums were located, were more vulnerable. We observed flatter increases in mortality risk associated with high temperatures comparing the period of 2003-2017 to 1987-2002.

INTERPRETATION

The analyses provided better understanding of the relationship of high temperatures with mortality in underdeveloped tropical regions and important implications in developing heat warning system for local government. The proposed CV approaches will benefit future scientific work.

A spatiotemporal reconstruction of daily ambient temperature using satellite data in the Megalopolis of Central Mexico from 2003 to 2019

While weather stations generally capture near-surface ambient air temperature (Ta) at a high temporal resolution to calculate daily values (i.e., daily minimum, mean, and maximum Ta), their fixed locations can limit their spatial coverage and resolution even in densely populated urban areas. As a result, data from weather stations alone may be inadequate for Ta-related epidemiology particularly when the stations are not located in the areas of interest for human exposure assessment. To address this limitation in the Megalopolis of Central Mexico (MCM), we developed the first spatiotemporally resolved hybrid satellite-based land use regression Ta model for the region, home to nearly 30 million people and includes Mexico City and seven more metropolitan areas. Our model predicted daily minimum, mean, and maximum Ta for the years 2003-2019. We used data from 120 weather stations and Land Surface Temperature (LST) data from NASA's MODIS instruments on the Aqua and Terra satellites on a 1 × 1 km grid. We generated a satellite-hybrid mixed-effects model for each year, regressing Ta measurements against land use terms, day-specific random intercepts, and fixed and random LST slopes. We assessed model performance using 10-fold cross-validation at withheld stations. Across all years, the root-mean-square error ranged from 0.92 to 1.92 K and the R 2 ranged from .78 to .95. To demonstrate the utility of our model for health research, we evaluated the total number of days in the year 2010 when residents ≥65 years old were exposed to Ta extremes (above 30°C or below 5°C). Our model provides much needed high-quality Ta estimates for epidemiology studies in the MCM region.

Association between ambient temperature and heat waves with mortality in South Asia: Systematic review and meta-analysis

BACKGROUND

South Asia is highly vulnerable to climate change and is projected to experience some of the highest increases in average annual temperatures throughout the century. Although the adverse impacts of ambient temperature on human health have been extensively documented in the literature, only a limited number of studies have focused on populations in this region.

OBJECTIVES

Our aim was to systematically review the current state and quality of available evidence on the direct relationship between ambient temperature and heat waves and all-cause mortality in South Asia.

METHODS

The databases Pubmed, Web of Science, Scopus and Embase were searched from 1990 to 2020 for relevant observational quantitative studies. We applied the Navigation Guide methodology to assess the strength of the evidence and performed a meta-analysis based on a novel approach that allows for combining nonlinear exposure-response associations without access to data from individual studies.

RESULTS

From the 6,759 screened papers, 27 were included in the qualitative synthesis and five in a meta-analysis. Studies reported an association of all-cause mortality with heat wave episodes and both high and low daily temperatures. The meta-analysis showed a U-shaped pattern, with increasing mortality for both high and low temperatures, but a statistically significant association was found only at higher temperatures - above 31° C for lag 0-1 days and above 34° C for lag 0-13 days. Effects were found to vary with cause of death, age, sex, location (urban vs. rural), level of education and socio-economic status, but the profile of vulnerabilities was somewhat inconsistent and based on a limited number of studies. Overall, the strength of the evidence for ambient temperature as a risk factor for all-cause mortality was judged as limited and for heat wave episodes as inadequate.

CONCLUSIONS

The evidence base on temperature impacts on mortality in South Asia is limited due to the small number of studies, their skewed geographical distribution and methodological weaknesses. Understanding the main determinants of the temperature-mortality association as well as how these may evolve in the future in a dynamic region such as South Asia will be an important area for future research. Studies on viable adaptation options to high temperatures for a region that is a hotspot for climate vulnerability, urbanisation and population growth are also needed.

Short-Term Exposure to Fine Particulate Matter and Hospitalizations for Acute Lower Respiratory Infection in Korean Children: A Time-Series Study in Seven Metropolitan Cities

Although several studies have evaluated the association between fine particulate matter (PM_2.5) and acute lower respiratory infection (ALRI) in children, their results were inconsistent Therefore, we aimed to evaluate the association between short-term exposure to PM_2.5 and ALRI hospitalizations in children (0–5 years) living in seven metropolitan cities of Korea. The ALRI hospitalization data of children living in seven metropolitan cities of Korea from 2008 to 2016 was acquired from a customized database constructed based on National Health Insurance data. The time-series data in a generalized additive model were used to evaluate the relationship between ALRI hospitalization and 7-day moving average PM_2.5 exposure after adjusting for apparent temperature, day of the week, and time trends. We performed a meta-analysis using a two-stage design method. The estimates for each city were pooled to generate an average estimate of the associations. The average PM_2.5 concentration in 7 metropolitan cities was 29.0 μg/m³ and a total of 713,588 ALRI hospitalizations were observed during the 9-year study period. A strong linear association was observed between PM_2.5 and ALRI hospitalization. A 10 μg/m³ increase in the 7-day moving average of PM_2.5 was associated with a 1.20% (95% CI: 0.71, 1.71) increase in ALRI hospitalization. While we found similar estimates in a stratified analysis by sex, we observed stronger estimates of the association in the warm season (1.71%, 95% CI: 0.94, 2.48) compared to the cold season (0.31%, 95% CI: −0.51, 1.13). In the two-pollutant models, the PM_2.5 effect adjusted by SO₂ was attenuated more than in the single pollutant model. Our results suggest a positive association between PM_2.5 exposure and ALRI hospitalizations in Korean children, particularly in the warm season. The children need to refrain from going out on days when PM_2.5 is high.

Short-Term Effects of Atmospheric Pollution on Daily Mortality and Their Modification by Increased Temperatures Associated with a Climatic Change Scenario in Northern Mexico

Short-term effects of air pollution on the health of residents in the Metropolitan Area of Monterrey, Mexico were assessed from 2012–2015 using a time-series approach. Guadalupe had the highest mean concentrations for SO₂, CO and O₃; whereas Santa Catarina showed the highest NO₂ concentrations. Escobedo and Garcia registered the highest levels for PM₁₀. Only PM₁₀ and O₃ exceeded the maximum permissible values established in the Mexican official standards. Most of pollutants and municipalities showed a great number of associations between an increase of 10% in their current concentrations and mortality, especially for people >60 years. Different scenarios resulting from climatic change were built (increases of 5–25% in daily mean temperature), but only the increase of 25% (5 °C) showed a significant association with air pollutant concentrations and mortality. All pollutants and municipalities showed significant increases in relative risk indexes (RRI) resulting from an increase of 5 °C when people >60 years was considered. Results were comparable to those reported by other authors around the world. The RRI were low but significant, and thus are of public concern. This study demonstrated that the elderly is strongly threatened not only by atmospheric pollution but also by climatic change scenarios in warm and semiarid places.

A review of the impact of outdoor and indoor environmental factors on human health in China

The Intergovernmental Panel on Climate Change (IPCC) reported that global climate change has led to the increased occurrence of extreme weather events. In the context of global climate change, more evidence indicates that abnormal meteorological conditions could increase the risk of epidemiological mortality and morbidity. In this study, using a systematic review, we evaluated a total of 175 studies (including 158 studies on outdoor environment and 17 studies on indoor environment) to summarize the impact of outdoor and indoor environment on human health in China using the database of PubMed, Web of Science, the Cochrane Library, and Embase. In particular, we focused on studies about cardiovascular and respiratory mortality and morbidity, the prevalence of digestive system diseases, infectious diseases, and preterm birth. Most of the studies we reviewed were conducted in three of the metropolises of China, including Beijing, Guangzhou, and Shanghai. For the outdoor environment, we summarized the effects of climate change-related phenomena on health, including ambient air temperature, diurnal temperature range (DTR), temperature extremes, and so on. Studies on the associations between temperature and human health accounted for 79.7% of the total studies reviewed. We also screened out 19 articles to explore the effect of air temperature on cardiovascular diseases in different cities in the final meta-analysis. Besides, modern lifestyle involves a large amount of time spent indoors; therefore, indoor environment also plays an important role in human health. Nevertheless, studies on the impact of indoor environment on human health are rarely reported in China. According to the limited reports, adverse indoor environment could impose a high health risk on children.

Predicted impact of increasing average ambient temperature over the coming century on mortality from cardiovascular disease and stroke in the USA

BACKGROUND AND AIMS

Future climate change may adversely impact human health. The direct effects of extreme hot temperatures on mortality are well established, and their future impact well modelled. However, less extreme changes in ambient temperature (Ta) have been previously associated with increased mortality from circulatory and metabolic diseases, but their future impact is less clear.

METHODS

We evaluated the spatial association between cardiovascular diseases (CVD) and stroke mortality with average Ta across the US mainland, and then used this relationship to model future temporal trends in mortality from CVD and stroke until the end of the century (2099), using different warming scenarios for each US county.

RESULTS

Ta was significantly associated with crude levels of CVD mortality (R² = 0.269) and stroke mortality (R² = 0.264). Moreover, there was a strong positive link between Ta and physical inactivity (PIA) (R² = 0.215). Once adjusted for PIA the associations between Ta and CVD and stroke mortality were much reduced (R² = 0.054 and R² = 0.091 respectively) but still highly significant.

CONCLUSIONS

By 2099 modelling suggests between 8844 and 25,486 extra deaths each year from CVD, and between 2,063 and 13,039 extra deaths for stroke, beyond the increases expected from population expansion. Mortality due to changes in the mean Ta may be as, or more, significant than the impacts of extreme hot weather events.

The Influence of Apparent Temperature on Mortality in the Kintampo Health and Demographic Surveillance Area in the Middle Belt of Ghana: A Retrospective Time-Series Analysis

Globally, studies have shown that diurnal changes in weather conditions and extreme weather events have a profound effect on mortality. Here, we assessed the effect of apparent temperature on all-cause mortality and the modifying effect of sex on the apparent temperature-mortality relationship using mortality and weather data archived over an eleven-year period. An overdispersed Poisson regression and distributed lag nonlinear models were used for this analysis. With these models, we analysed the relative risk of mortality at different temperature values over a 10-day lag period. By and large, we observed a nonlinear association between mean daily apparent temperature and all-cause mortality. An assessment of different temperature values over a 10-day lag period showed an increased risk of death at the lowest apparent temperature (18°C) from lag 2 to 4 with the highest relative risk of mortality (RR = 1.61, 95% CI: 1.2, 2.15, p value = 0.001) occurring three days after exposure. The relative risk of death also varied between males (RR = 0.31, 95% CI: 0.10, 0.94) and females (RR = 4.88, 95% CI: 1.40, 16.99) by apparent temperature and lag. On the whole, males are sensitive to both temperature extremes whilst females are more vulnerable to low temperature-related mortality. Accordingly, our findings could inform efforts at reducing temperature-related mortality in this context and other settings with similar environmental and demographic characteristics.

Extreme temperatures and mortality in Kuwait: Who is vulnerable?

BACKGROUND

Previous climate change temperature-related health studies have been performed mostly in western countries with relatively cooler temperatures than the Gulf region. Regions that are inherently hot, like Kuwait, are witnessing soaring temperatures unlike ever before. Meanwhile, Kuwait and other Gulf countries are unique in their demographic profiles due to the large number of non-national migrant workers.

OBJECTIVE

To examine the associations of hot and cold temperature extremes on the risk of mortality across gender, age groups and nationality in Kuwait.

METHODS

We investigated daily variations of all-cause non-accidental and cardiovascular mortality death counts and ambient temperatures from 2010 to 2016 in a time-series design using a negative binomial distribution. The temperature lag was modeled with distributed lag non-linear models.

RESULTS

A total of 33,472 all-cause non-accidental deaths happened during the study period. For the extreme hot temperatures and over the entire lag period, comparing the 99th percentile of temperature to the minimum mortality temperature, the risk of dying among males was 2.08 (95% CI: 1.23-3.52). Among non-Kuwaitis, males and working age group (15-64 year) had relative risks of death from extreme hot temperatures of 2.90 (1.42-5.93), and 2.59 (1.20-5.59), respectively. For extreme cold temperatures and over the entire lag period, comparing the 1st percentile of temperature to the minimum mortality temperature, the relative risk of death among Kuwaitis was 2.03 (1.05-3.93). Elderly Kuwaitis (65+ year) exposed to extreme cold temperatures had a relative risk of 2.75 (1.16-6.52).

CONCLUSIONS

Certain subpopulations in Kuwait are vulnerable to extreme temperatures with doubling to tripling risk of mortality. Nationality is an important effect modifier in temperature-related mortality studies in Kuwait and possibly the Gulf region. To the best of our knowledge, we are the first study to examine specific subpopulation vulnerabilities to temperature in this region. Our findings could carry a potential for broader insight into similar hyper-arid and hot regions.

Heat-related mortality at the beginning of the twenty-first century in Rio de Janeiro, Brazil

Temperature record-breaking events, such as the observed more intense, longer-lasting, and more frequent heat waves, pose a new global challenge to health sectors worldwide. These threats are of particular interest in low-income regions with limited investments in public health and a growing urban population, such as Brazil. Here, we apply a comprehensive interdisciplinary climate-health approach, including meteorological data and a daily mortality record from the Brazilian Health System from 2000 to 2015, covering 21 cities over the Metropolitan Region of Rio de Janeiro. The percentage of absolute mortality increase due to summer extreme temperatures is estimated using a negative binomial regression modeling approach and maximum/minimum temperature-derived indexes as covariates. Moreover, this study assesses the vulnerability to thermal stress for different age groups and both genders and thoroughly analyzes four extremely intense heat waves during 2010 and 2012 regarding their impacts on the population. Results showed that the highest absolute mortality values during heat-related events were linked to circulatory illnesses. However, the highest excess of mortality was related to diabetes, particularly for women within the elderly age groups. Moreover, results indicate that accumulated heat stress conditions during consecutive days preferentially preceded by persistent periods of moderate-temperature, lead to higher excess mortality rather than sporadic single hot days. This work may provide directions in human health policies related to extreme climate events in large tropical metropolitan areas from developing countries, contributing to altering the historically based purely reactive response.

Outdoor Thermal Comfort and Building Energy Use Potential in Different Land-Use Areas in Tropical Cities: Case of Kuala Lumpur

High air temperature and high humidity, combined with low wind speeds, are common trends in the tropical urban climates, which collectively govern heat-induced health risks and outdoor thermal comfort under the given hygrothermal conditions. The impact of different urban land-uses on air temperatures is well-documented by many studies focusing on the urban heat island phenomenon; however, an integrated study of air temperature and humidity, i.e., the human-perceived temperatures, in different land-use areas is essential to understand the impact of hot and humid tropical urban climates on the thermal comfort of urban dwellers for an appraisal of potential health risks and the associated building energy use potential. In this study, we show through near-surface monitoring how these factors vary in distinct land-use areas of Kuala Lumpur city, characterized by different morphological features (high-rise vs. low-rise; compact vs. open), level of anthropogenic heating and evapotranspiration (built-up vs. green areas), and building materials (concrete buildings vs. traditional Malay homes in timber) based on the calculated heat index (HI), apparent temperature (TApp) and equivalent temperature (TE) values in wet and dry seasons. The results show that the felt-like temperatures are almost always higher than the air temperatures in all land-use areas, and this difference is highest in daytime temperatures in green areas during the dry season, by up to about 8 °C (HI)/5 °C (TApp). The TE values are also up to 9% higher in these areas than in built-up areas. We conclude that tackling urban heat island without compromising thermal comfort levels, hence encouraging energy use reduction in buildings to cope with outdoor conditions requires a careful management of humidity levels, as well as a careful selection of building morphology and materials.

Projected Future Temporal Trends of Two Different Urban Heat Islands in Athens (Greece) under Three Climate Change Scenarios: A Statistical Approach

This is the first study to look at future temporal urban heath island (UHI) trends of Athens (Greece) under different UHI intensity regimes. Historical changes in the Athens UHI, spanning 1971–2016, were assessed by contrasting two air temperature records from stable meteorological stations in contrasting urban and rural settings. Subsequently, we used a five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11° (~12 × 12 km) to simulate air temperature data, spanning the period 1976–2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5, and RCP8.5) were implanted in the simulations after 2005 covering the period 2006–2100. Two 20-year historical reference periods (1976–1995 and 1996–2015) were selected with contrasting UHI regimes; the second period had a stronger intensity. The daily maximum and minimum air temperature data (Tmax and Tmin) for the two reference periods were perturbed to two future periods, 2046–2065 and 2076–2095, under the three RCPs, by applying the empirical quantile mapping (eqm) bias-adjusting method. This novel approach allows us to assess future temperature developments in Athens under two UHI intensity regimes that are mainly forced by differences in air pollution and heat input. We found that the future frequency of days with Tmax > 37 °C in Athens was only different from rural background values under the intense UHI regime. Thus, the impact of heatwaves on the urban environment of Athens is dependent on UHI intensity. There is a large increase in the future frequency of nights with Tmin > 26 °C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site. This large urban amplification of the frequency of extremely hot nights is likely caused by air pollution. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be highly effective in reducing urban temperatures and extreme heat events in Athens under future climate change scenarios. Such policies directly have multiple benefits, including reduced electricity (energy) needs, improved living quality and strong health advantages (heat- and pollution-related illness/deaths).

High Temperature and Risk of Cause-Specific Mortality in China, 2013-2018

What is already known about this topic?

High temperature is a well-recognized public health threat and may increase mortality risks, especially mortality risks involving diseases of the circulatory system.

What is added by this report?

Using a six-year time series analysis, the differences of daily mean, maximum, minimum temperature were explored in assessing the health effects of high temperatures in nationwide and at climatic-zone level, and population groups susceptible to high temperatures were identified.

What are the implications for public health practice?

This study suggests that the daily mean temperature is the optimal indicator for high temperature exposure in heat-related health risk assessments and early warnings. The policy measures of heat-related public health protection should be made considering regional distribution, sensitive diseases, and vulnerable populations.

Reversal of the seasonality of temperature-attributable mortality from respiratory diseases in Spain

A growing number of epidemiological studies have recently assessed temporal variations in vulnerability and/or mortality attributable to hot and cold temperatures. However, the eventual changes in the seasonal distribution of temperature-attributable mortality remain unexplored. Here, we analyse countrywide daily time-series of temperature and mortality counts from respiratory diseases by sex, age group and province of residence during the period 1980–2016 in Spain. We show the complete reversal of the seasonality of temperature-attributable mortality, with a significant shift of the maximum monthly incidence from winter to summer, and the minimum monthly incidence from early and late summer to winter. The reversal in the seasonal distribution of the attributable deaths is not driven by the observed warming in both winter and summer temperatures, but rather by the very large decrease in the risk of death due to cold temperatures and the relatively much smaller reduction due to hot temperatures. We conclude that the projected decrease in the number of moderate and extreme cold days due to climate warming will not contribute to a further reduction of cold-attributable respiratory deaths.

Potential changes in the seasonality of temperature-attributable mortality due to climate warming have been poorly investigated. Here, the authors show that the projected decrease in the number of moderate and extreme cold days will not contribute to a further reduction of cold-attributable deaths.

At which temperature do the deleterious effects of ambient heat "kick-in" to affect all-cause mortality? An exploration of this threshold from an eastern Indian city

Despite experiencing hot weathers, limited studies from India explored relationships between ambient heat and health. We studied associations between heat and all-cause mortality to estimate heat threshold(s) affecting health, and examine other affecting dimensions. We conducted time-series analysis with daily maximum temperature and all-cause mortality data of Bhubaneswar city (March-July, 2007-2017), and explored their interactions. Mortality risks rose when daily maximum temperatures were >36.2°C (lower threshold), and even more when >40.5°C (upper threshold). Every degree above36.2°C increased the mortality risk by 2% (mortality rate ratio: 1.02; 95% CI 1.01, 1.03). The effects of maximum temperature increased on days when minimum temperatures were >25.6°C (median). The effect of heat was immediate and lasted for 0-1 day with no lagged effect. Two temperature thresholds with varying mortality risks provided an opportunity for a graded heat warning system. The accentuation of the deleterious effects of heat by the higher minimum temperature calls for its inclusion in the heat warning system in future.

The Role of Individual and Small-Area Social and Environmental Factors on Heat Vulnerability to Mortality Within and Outside of the Home in Boston, MA

Climate change is resulting in heatwaves that are more frequent, severe, and longer lasting, which is projected to double-to-triple the heat-related mortality in Boston, MA if adequate climate change mitigation and adaptation strategies are not implemented. A case-only analysis was used to examine subject and small-area neighborhood characteristics that modified the association between hot days and mortality. Deaths of Boston, Massachusetts residents that occurred from 2000–2015 were analyzed in relation to the daily temperature and heat index during the warm season as part of the case-only analysis. The modification by small-area (census tract, CT) social, and environmental (natural and built) factors was assessed. At-home mortality on hot days was driven by both social and environmental factors, differentially across the City of Boston census tracts, with a greater proportion of low-to-no income individuals or those with limited English proficiency being more highly represented among those who died during the study period; but small-area built environment features, like street trees and enhanced energy efficiency, were able to reduce the relative odds of death within and outside the home. At temperatures below current local thresholds used for heat warnings and advisories, there was increased relative odds of death from substance abuse and assault-related altercations. Geographic weighted regression analyses were used to examine these relationships spatially within a subset of at-home deaths with high-resolution temperature and humidity data. This revealed spatially heterogeneous associations between at-home mortality and social and environmental vulnerability factors.

Occupational heat stress management: Does one size fit all?

Heat stress is a deadly occupational hazard that is projected to increase in severity with global warming. While upper limits for heat stress designed to protect all workers have been recommended by occupational safety institutes for some time, heat stress continues to compromise health and productivity. In our view, this is largely explained by the inability of existing guidelines to consider the inter-individual (age, sex, disease, others) and intra-individual (medication use, fitness, hydration, others) factors that cause extensive variability in physiological tolerance to a given heat stress. In conditions that do not exceed the recommended limits, this 'one size fits all' approach to heat stress management can lead to reductions in productivity in more heat-tolerant workers, while compromising safety in less heat-tolerant workers who may develop heat-related illness, even in temperate conditions. Herein, we discuss future directions in occupational heat stress management that consider this individual variability.

Neonatal deaths and challenges of public health: Where do We need urgent intervention in developing countries?

Neonatal death is child health problem which the global community seeks to reduce to the barest minimum by 2030. In 2017, sub-Sahara Africa's average neonatal death was 27 in every 1000 successful births, while Nigeria's neonatal death rate was 32.9. The researcher's objective is to propose public health policies needed to reduce neonatal death drastically in Nigeria by 2030. The researchers sourced data from World Bank between 1993 and 2015, and used ordinary least squares method of analysis because of its simplicity. We recommended introduction of antenatal meal plus in Nigeria based on finding that poor nutrition causes neonatal death.

The effects of excess degree-hours on mortality in Guangzhou, China

BACKGROUND

Prior studies that examined the association between temperature and mortality relied on mean temperature, maximum temperature, minimum temperature, humidex, and daily temperature variability, not accounting for variations in hourly temperature throughout the day. We proposed an indicator, excess degree-hours, to examine the association between temperature and mortality.

METHODS

A distributed lag non-linear model (DLNM) was used to determine the hot (27.8 °C) and cold (24.3 °C) threshold. Hourly temperature in Guangzhou, China were summarized with extreme heat expressed as sum of degree-hours >27.8 °C and extreme cold as sum of degree-hours <24.3 °C within one day from January 1, 2012 to December 31, 2015. We then estimated the associations of daily mortality with hot and cold degree-hours in both hot and cold season. We also calculated the mortality burden of excess degree-hours.

RESULTS

An interquartile range (IQR) increase of hot degree-hours was associated with 2.11% (95% confidence interval [95% CI]: 1.25%, 2.98%), 3.74% (95% CI: 0.71%, 6.86%), and 2.63% (95% CI: 0.70%, 4.59%) increments in non-injury related death, respiratory mortality, and cardiovascular mortality, respectively. While the corresponding excess risk for an IQR increase of cold degree-hours was 2.42% (95% CI: 1.97%, 2.88%), 3.16% (95% CI: 2.57%, 3.76%), and 2.93% (95% CI: 1.98%, 3.88%). The estimated mortality burdens for hot and cold degree-hours were 1366,2465, respectively.

CONCLUSION

The excess degree-hours reduced to a single indication in duration and intensity is an approach and shows a different perspective and significant extreme weather effects on human health.

Tens of thousands additional deaths annually in cities of China between 1.5 °C and 2.0 °C warming

The increase in surface air temperature in China has been faster than the global rate, and more high temperature spells are expected to occur in future. Here we assess the annual heat-related mortality in densely populated cities of China at 1.5 °C and 2.0 °C global warming. For this, the urban population is projected under five SSPs, and 31 GCM runs as well as temperature-mortality relation curves are applied. The annual heat-related mortality is projected to increase from 32.1 per million inhabitants annually in 1986–2005 to 48.8–67.1 per million for the 1.5 °C warming and to 59.2–81.3 per million for the 2.0 °C warming, taking improved adaptation capacity into account. Without improved adaptation capacity, heat-related mortality will increase even stronger. If all 831 million urban inhabitants in China are considered, the additional warming from 1.5 °C to 2 °C will lead to more than 27.9 thousand additional heat-related deaths, annually.

Heatwaves are expected to increase under climate change, and so are the associated deaths. Here the authors determine the regional high temperature thresholds for 27 metropolises in China and analyze the changes to heat-related mortality, showing that the additional global-warming temperature increase of 0.5°C, from 1.5°C to 2.0°C, will lead to tens of thousands of additional deaths, annually.

Trends in temperature-related age-specific and sex-specific mortality from cardiovascular diseases in Spain: a national time-series analysis

BACKGROUND

Climate change driven by human activities has increased annual temperatures in Spain by around 1°C since 1980. However, little is known regarding the extent to which the association between temperature and mortality has changed among the most susceptible population groups as a result of the rapidly warming climate. We aimed to assess trends in temperature-related cardiovascular disease mortality in Spain by sex and age, and we investigated the association between climate warming and changes in the risk of mortality.

METHODS

We did a country-wide time-series analysis of 48 provinces in mainland Spain and the Balearic Islands between Jan 1, 1980, and Dec 31, 2016. We extracted daily cardiovascular disease mortality data disaggregated by sex, age, and province from the Spanish National Institute of Statistics database. We also extracted daily mean temperatures from the European Climate Assessment and Dataset project. We applied a quasi-Poisson regression model for each province, controlling for seasonal and long-term trends, to estimate the temporal changes in the province-specific temperature-mortality associations with distributed lag non-linear models. We did a multivariate random-effects meta-analysis to derive the best linear unbiased prediction of the temperature-mortality association and the minimum mortality temperature in each province. Heat-attributable and cold-attributable fractions of death were computed by separating the contributions from days with temperatures warmer and colder than the minimum mortality temperature, respectively.

FINDINGS

Between 1980 and 2016, 4 576 600 cardiovascular deaths were recorded. For warm temperatures, the increase in relative risk (RR) of death from cardiovascular diseases was higher for women than men and higher for older individuals (aged ≥90 years) than younger individuals (aged 60-74 years), whereas for cold temperatures, RRs were higher for men than women, with no clear pattern by age group. The heat-attributable fraction of cardiovascular deaths was higher for women in all age groups, and the cold-attributable fraction was larger in men. The heat-attributable fraction increased with age for both sexes, whereas the cold-attributable fraction increased with age for men and decreased for women. Overall minimum mortality temperature increased from 19·5°C between 1980 and 1994 to 20·2°C between 2002 and 2016, which is similar in magnitude to, and occurred in parallel with, the observed mean increase of 0·77°C that occurred in Spain between these two time periods. In general, between 1980 and 2016, the risk and attributable fraction of cardiovascular deaths due to warm and cold temperatures decreased for men and women across all age groups. For all the age groups combined, between 1980-94 and 2002-16, the heat-attributable fraction decreased by -42·06% (95% empirical CI -44·39 to -41·06) for men and -36·64% (-36·70 to -36·04) for women, whereas the cold-attributable fraction was reduced by -30·23% (-30·34 to -30·05) for men and -44·87% (-46·77 to -42·94) for women.

INTERPRETATION

In Spain, the observed warming of the climate has occurred in parallel with substantial adaptation to both high and low temperatures. The reduction in the RR and the attributable fraction associated with heat would be compatible with an adaptive response specifically addressing the negative consequences of climate change. Nevertheless, the simultaneous reduction in the RR and attributable fraction of cold temperatures also highlights the importance of more general factors such as socioeconomic development, increased life expectancy and quality, and improved health-care services in the country.

FUNDING

None.

Multi-Temporal Effects of Urban Forms and Functions on Urban Heat Islands Based on Local Climate Zone Classification

Urban forms and functions have critical impacts on urban heat islands (UHIs). The concept of a “local climate zone” (LCZ) provides a standard and objective protocol for characterizing urban forms and functions, which has been used to link urban settings with UHIs. However, only a few structure types and surface cover properties are included under the same climate background or only one or two time scales are considered with a high spatial resolution. This study assesses multi-temporal land surface temperature (LST) characteristics across 18 different LCZ types in Beijing, China, from July 2017 to June 2018. A geographic information system-based method is employed to classify LCZs based on five morphological and coverage indicators derived from a city street map and Landsat images, and a spatiotemporal fusion model is adopted to generate hourly 100-m LSTs by blending Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), and FengYun-2F LSTs. Then, annual and diurnal cycle parameters and heat island and cool island (HI or CI) frequency are linked to LCZs at annual, seasonal, monthly, and diurnal scales. Results indicate that: (1) the warmest zones are compact and mid and low-rise built-up areas, while the coolest zones are water and vegetated types; (2) compact and open high-rise built-up areas and vegetated types have seasonal thermal patterns but with different causes; (3) diurnal temperature ranges are the highest for compact and large low-rise settings but the lowest for water and dense or scattered trees; and (4) HIs are the most frequent summertime and daytime events, while CIs occur primarily during winter days, making them more or less frequent for open or compact and high- or low-rise built-up areas. Overall, the distinguishable LSTs or UHIs between LCZs are closely associated with the structure and coverage properties. Factors such as geolocation, climate, and layout also interfere with the thermal behavior. This study provides comprehensive information on how different urban forms and functions are related to LST variations at different time scales, which supports urban thermal regulation through urban design.