Temperature, temperature extremes, and mortality: a study of acclimatisation and effect modification in 50 US cities

Spatiotemporal distribution and lag effect of extreme temperature exposure on mortality of residents in Jiangsu, China

Background

With the ever-increasing occurrence of extreme weather events as a result of global climate change, the impact of extreme temperatures on human health has become a critical area of concern. Specifically, it is imperative to investigate the impact of extreme weather conditions on the health of residents.

Methods

In this study, we analyze the daily death data from 13 prefecture-level cities in Jiangsu Province from January 2014 to September 2022, using the distributed lag nonlinear model (DLNM) to comprehensively account for factors such as relative humidity, atmospheric pressure, air pollutants, and other factors to evaluate the lag and cumulative effects of extreme low temperature and high temperature on the death of residents across different age groups. Additionally, we utilize the Geographical Detector to analyze the effects of various meteorological and environmental factors on the distribution of resident death in Jiangsu Province. This provides valuable insights that can guide health authorities in decision-making and in the protection of residents.

Results

The experimental results indicate that both extreme low and high temperatures increase the mortality of residents. We observe that the impact of extreme low temperatures has a delayed effect, peaking after 3-5 days and lasting up to 11-21 days. In contrast, the impact of extreme high temperature is greatest on the first day, and lasts only 2-4 days.

Conclusion

Both extreme high and low temperatures increase the mortality of residents, with the former being more transient and stronger and the latter being more persistent and slower. Furthermore, residents over 75 years of age are more vulnerable to the effects of extreme temperatures. Finally, we note that the spatial distribution of resident deaths is most closely associated consistent with the spatial distribution of daily mean temperature, and there is significant spatial heterogeneity in deaths among residents in Jiangsu Province.

Aging in climate change: Unpacking residential mobility and changes of social determinants of health in southern United States

The southern coastal states of the United States are susceptible to extreme weather and climate events. With growing move-in and -out older populations in the region, health implications of their residential mobility lack sufficient knowledge. Using 126,352 person-level records from 2012 to 2021, we examined geospatial and temporal patterns of older populations' residential mobility, considering the changing social determinants of health and disparities. We found the moves of older populations with socioeconomic or health disadvantages were related to increased exposure to environmental hazards and reduced access to health resources. The findings inform targeted strategies for climate adaptation that address the needs of vulnerable aging populations.

Heatstroke presentations to urban hospitals during BC's extreme heat event: lessons for the future

BACKGROUND

Climate change is leading to more extreme heat events in temperate climates that typically have low levels of preparedness. Our objective was to describe the characteristics, treatments, and outcomes of adults presenting to hospitals with heatstroke during BC's 2021 heat dome.

METHODS

We conducted a review of consecutive adults presenting to 7 hospitals in BC's Lower Mainland. We screened the triage records of all patients presenting between June 25th and 30th, 2021 for complaints related to heat, and reviewed the full records of those who met heatstroke criteria. Our primary outcome was in-hospital mortality. We used Mann-Whitney U tests and logistic regression to investigate associations between patient and treatment factors and mortality.

RESULTS

Among 10,247 consecutive presentations to urban hospitals during the extreme heat event, 1.3% (139; 95% confidence intervals [CI] 1.1-1.6%) met criteria for heatstroke. Of heatstroke patients, 129 (90.6%) were triaged into the two highest acuity levels. Patients with heatstroke had a median age of 84.4 years, with 122 (87.8%) living alone, and 101 (84.2%) unable to activate 911 themselves. A minority (< 5, < 3.6%) of patients presented within 48 h of the onset of extreme heat. Most patients (107, 77.0%) required admission, and 11.5% (16) died in hospital. Hypotension on presentation was associated with mortality (odds ratio [OR] 5.3).

INTERPRETATION

Heatstroke patients were unable to activate 911 themselves, and most presented with a 48-h delay. This delay may represent a critical window of opportunity for pre-hospital and hospital systems to prepare for the influx of high-acuity resource-intensive patients.

Temperature variability associated with respiratory disease hospitalisations, hospital stays and hospital expenses the warm temperate sub-humid monsoon climate

OBJECTIVES

The abrupt change of climate has led to an increasing trend of hospitalised patients in recent years. This study aimed to analyse the temperature variability (TV) associated with respiratory disease (RD) hospitalisations, hospital stays and hospital expenses.

STUDY DESIGN

The generalized linear model combined with distributed lag non-linear model was used to investigate the association between TV and RD hospitalisations.

METHODS

TV was determined by measuring the standard deviation of maximum and minimum temperatures for the current day and the previous 7 days. RD hospitalisations data were obtained from three major tertiary hospitals in Huaibei City, namely, the Huaibei People's Hospital, the Huaibei Hospital Of Traditional Chinese Medicine and the Huaibei Maternal and Child Health Care Hospital. First, using a time series decomposition model, the seasonality and long-term trend of hospitalisations, hospital stays and hospital expenses for RD were explored in this warm temperate sub-humid monsoon climate. Second, robust models were used to analyse the association between TV and RD hospitalisations, hospital stays and hospital expenses. In addition, this study stratified results by sex, age and season. Third, using the attributable fraction (AF) and attributable number (AN), hospitalisations, hospital stays and hospital expenses for RD attributed to TV were quantified.

RESULTS

Overall, 0.013% of hospitalisations were attributed to TV0-1 (i.e. TV at the current day and previous 1 day), corresponding to 220 cases, 1603 days of hospital stays and 1,308,000 RMB of hospital expenses. Females were more susceptible to TV than males, and the risk increased with longer exposure (the highest risk was seen at TV0-7 [i.e. TV at the current day and previous 7 days] exposure). Higher AF and AN were observed at ages 0-5 years and ≥65 years. In addition, it was also found that TV was more strongly linked to RD in the cool season. The hot season was positively associated with hospital stays and hospital expenses at TV0-3 to TV0-7 exposure.

CONCLUSIONS

Exposure to TV increased the risk of hospitalisations, longer hospital stays and higher hospital expenses for RD. The findings suggested that more attention should be paid to unstable weather conditions in the future to protect the health of vulnerable populations.

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.

The role of insurance status in the association between short-term temperature exposure and myocardial infarction hospitalizations in New York State

Myocardial infarction (MI) is a leading cause of morbidity and mortality in the United States and its risk increases with extreme temperatures. Climate change causes variability in weather patterns, including extreme temperature events that disproportionately affect socioeconomically disadvantaged communities. Many studies on the health effects of extreme temperatures have considered community-level socioeconomic disadvantage.

Objectives

To evaluate effect modification of the relationship between short-term ambient temperature and MI, by individual-level insurance status (insured vs. uninsured).

Methods

We identified MI hospitalizations and insurance status across New York State (NYS) hospitals from 1995 to 2015 in the New York Department of Health Statewide Planning and Research Cooperative System database, using International Classification of Diseases codes. We linked short-term ambient temperature (averaging the 6 hours preceding the event [MI hospitalization]) or nonevent control period in patient residential zip codes. We employed a time-stratified case-crossover study design for both insured and uninsured strata, and then compared the group-specific rate ratios.

Results

Over the study period, there were 1,095,051 primary MI admissions, 966,475 (88%) among insured patients. During extremely cold temperatures (<5.8 °C) insured patients experienced reduced rates of MI; this was not observed among the uninsured counterparts. At warmer temperatures starting at the 65th percentile (15.7 °C), uninsured patients had higher rates than insured patients (e.g., for a 6-hour pre-event average temperature increase from the median to the 75th percentile, the rate of MI increased was 2.0% [0.0%-4.0%] higher in uninsured group).

Conclusions

Uninsured individuals may face disproportionate rates of MI hospitalization during extreme temperatures.

Seasonal Temperature Variability and Mortality in the Medicare Population

BACKGROUND

Seasonal temperature variability remains understudied and may be modified by climate change. Most temperature-mortality studies examine short-term exposures using time-series data. These studies are limited by regional adaptation, short-term mortality displacement, and an inability to observe longer-term relationships in temperature and mortality. Seasonal temperature and cohort analyses allow the long-term effects of regional climatic change on mortality to be analyzed.

OBJECTIVES

We aimed to carry out one of the first investigations of seasonal temperature variability and mortality across the contiguous United States. We also investigated factors that modify this association. Using adapted quasi-experimental methods, we hoped to account for unobserved confounding and to investigate regional adaptation and acclimatization at the ZIP code level.

METHODS

We examined the mean and standard deviation (SD) of daily temperature in the warm (April-September) and cold (October-March) season in the Medicare cohort from 2000 to 2016. This cohort comprised 622,427,230 y of person-time in all adults over the age of 65 y from 2000 to 2016. We used daily mean temperature obtained from gridMET to develop yearly seasonal temperature variables for each ZIP code. We used an adapted difference-in-difference approach model with a three-tiered clustering approach and meta-analysis to observe the relationship between temperature variability and mortality within ZIP codes. Effect modification was assessed with stratified analyses by race and population density.

RESULTS

For every 1°C increase in the SD of warm and cold season temperature, the mortality rate increased by 1.54% [95% confidence interval (CI): 0.73%, 2.15%] and 0.69% (95% CI: 0.22%, 1.15%) respectively. We did not see significant effects for seasonal mean temperatures. Participants who were classified by Medicare into an "other" race group had smaller effects than those classified as White for Cold and Cold SD and areas with lower population density had larger effects for Warm SD.

DISCUSSION

Warm and cold season temperature variability were significantly associated with increased mortality rates in U.S. individuals over the age of 65 y, even after controlling for seasonal temperature averages. Warm and cold season mean temperatures showed null effects on mortality. Cold SD had a larger effect size for those who were in the racial subgroup other, whereas Warm SD was more harmful for those living in lower population density areas. This study adds to the growing calls for urgent climate mitigation and environmental health adaptation and resiliency. https://doi.org/10.1289/EHP11588.

Mortality Risk of Hot Nights: A Nationwide Population-Based Retrospective Study in Japan

BACKGROUND

The health effects of heat are well documented; however, limited information is available regarding the health risks of hot nights. Hot nights have become more common, increasing at a faster rate than hot days, making it urgent to understand the characteristics of the hot night risk.

OBJECTIVES

We estimated the effects of hot nights on the cause- and location-specific mortality in a nationwide assessment over 43 y (1973-2015) using a unified analytical framework in the 47 prefectures of Japan.

METHODS

Hot nights were defined as days with a) minimum temperature ≥ 25 ° C (HN 25 ) and b) minimum temperature ≥ 95 th percentile (HN 95 th ) for the prefecture. We conducted a time-series analysis using a two-stage approach during the hot night occurrence season (April-November). For each prefecture, we estimated associations between hot nights and mortality controlling for potential confounders including daily mean temperature. We then used a random-effects meta-analytic model to estimate the pooled cumulative association.

RESULTS

Overall, 24,721,226 deaths were included in this study. Nationally, all-cause mortality increased by 9%-10% [HN 25 relative risk ( RR ) = 1.09 , 95% confidence interval (CI): 1.08, 1.10; HN 95 th RR = 1.10 , 95% CI: 1.09, 1.11] during hot nights in comparison with nonhot nights. All 11 cause-specific mortalities were strongly associated with hot nights, and the corresponding associations appeared to be acute and lasted a few weeks, depending on the cause of death. The strength of the association between hot nights and mortality varied among prefectures. We found a higher mortality risk from hot nights in early summer in comparison with the late summer in all regions.

CONCLUSIONS

Our findings support the evidence of mortality impacts from hot nights in excess of that explicable by daily mean temperature and have implications useful for establishing public health policy and research efforts estimating the health effects of climate change. https://doi.org/10.1289/EHP11444.

Association of Temperature Thresholds with Heat Illness- and Cardiorespiratory-Related Emergency Visits during Summer Months in Alaska

BACKGROUND

Recent record-breaking hot temperatures in Alaska have raised concerns about the potential human health implications of heat exposure among this unacclimated population.

OBJECTIVES

We estimated cardiorespiratory morbidity associated with days above summer (June-August) heat index (HI, apparent temperature) thresholds in three major population centers (Anchorage, Fairbanks, and the Matanuska-Susitna Valley) for the years 2015-2019.

METHODS

We implemented time-stratified case-crossover analyses of emergency department (ED) visits for International Classification of Diseases, 10^th Revision codes indicative of heat illness and major cardiorespiratory diagnostic codes using data from the Alaska Health Facilities Data Reporting Program. Using conditional logistic regression models, we tested maximum hourly HI temperature thresholds between 21.1°C (70°F) and 30°C (86°F) for a single day, 2 consecutive days, and the absolute number of previous consecutive days above the threshold, adjusting for the daily average concentration of particulate matter ≤2.5μg.

RESULTS

There were increased odds of ED visits for heat illness above a HI threshold as low as 21.1°C (70°F) [odds ratio (OR)=13.84; 95% confidence interval (CI): 4.05, 47.29], and this increased risk continued for up to 4 d (OR=2.43; 95% CI: 1.15, 5.10). Asthma and pneumonia were the only respiratory outcomes positively associated with the HI: ED visits for both were highest the day after a heat event (Asthma: HI>27°C(80°F) OR=1.18; 95% CI: 1.00, 1.39; Pneumonia: HI>28°C(82°F) OR=1.40; 95% CI: 1.06, 1.84). There was a decreased odds of bronchitis-related ED visits when the HI was above thresholds of 21.1-28°C (70-82°F) across all lag days. We found stronger effects for ischemia and myocardial infarction (MI) than for respiratory outcomes. Multiple days of warm weather were associated with an increased risk of health impacts. For each additional preceding day above a HI of 22°C (72°F), the odds of ED visits related to ischemia increased 6% (95% CI: 1%, 12%); for each additional preceding day above a HI of 21.1°C (70°F), the odds of ED visits related to MI increased 7% (95% CI: 1%, 14%).

DISCUSSION

This study demonstrates the importance of planning for extreme heat events and developing local guidance for heat warnings, even in areas with historically mild summertime climates. https://doi.org/10.1289/EHP11363.

Heat-related mortality in U.S. state and private prisons: A case-crossover analysis

Rising temperatures and heatwaves increase mortality. Many of the subpopulations most vulnerable to heat-related mortality are in prisons, facilities that may exacerbate temperature exposures. Yet, there is scare literature on the impacts of heat among incarcerated populations. We analyzed data on mortality in U.S. state and private prisons from 2001-2019 linked to daily maximum temperature data for the months of June, July, and August. Using a case-crossover approach and distributed lag models, we estimated the association of increasing temperatures with total mortality, heart disease-related mortality, and suicides. We also examined the association with extreme heat and heatwaves (days above the 90th percentile for the prison location) and assessed effect modification by personal, facility, and regional characteristics. There were 12,836 deaths during summer months. The majority were male (96%) and housed in a state-operated prison (97%). A 10°F increase was associated with a 5.2% (95% CI: 1.5%, 9.0%) increase in total mortality and a 6.7% (95% CI: -0.6%, 14.0%) increase in heart disease mortality. The association between temperature and suicides was delayed, peaking around lag 3 (exposure at three days prior death). Two- and three-day heatwaves were associated with increased total mortality of 5.5% (95% CI: 0.3%, 10.9%) and 7.4% (95% CI: 1.6%, 13.5%), respectively. The cumulative effect (lags 1-3) of an extreme heat day was associated with a 22.8% (95% CI: 3.3%, 46.0%) increase in suicides. We found the greatest increase in mortality among people ≥ 65 years old, incarcerated less than one year, held in the Northeast region, and in urban or rural counties. These findings suggest that warm temperatures are associated with increased mortality in prisons, yet this vulnerable population's risk has largely been overlooked.

Extreme Heat and COVID-19 in New York City: An Evaluation of a Large Air Conditioner Distribution Program to Address Compounded Public Health Risks in Summer 2020

In summer 2020, New York City (NYC) implemented a free air conditioner (AC) distribution program in response to the threats of extreme heat and COVID-19. The program distributed and installed ACs in the homes of nearly 73,000 older, low-income residents of public and private housing. To evaluate the program's impact, survey data were collected from October 2020 to February 2021 via mail and online from 1447 program participants and 902 non-participating low-income NYC adults without AC as a comparison group. Data were examined by calculating frequencies, proportions, and logistic regression models. Participants were 3 times more likely to report staying home during hot weather in summer 2020 compared to non-participants (adjusted odds ratio [AOR] = 3.0, 95% confidence interval [CI] = 2.2, 4.1), with no difference between groups in summer 2019 (AOR = 1.0, CI = 0.8, 1.3). Participants were less likely to report that 2020 hot weather made them feel sick in their homes compared to non-participants (AOR = 0.2, CI = 0.2, 0.3). The program helped participants-low-income residents and primarily people of color-stay home safely during hot weather. These results are relevant for climate change health-adaptation efforts and heat-health interventions.

Daily temperature effects on under-five mortality in a tropical climate country and the role of local characteristics

BACKGROUND

Climate change and its subsequent effects on temperature have raised global public health concerns. Although numerous epidemiological studies have shown the adverse health effects of temperature, the association remains unclear for children aged below five years old and those in tropical climate regions.

METHODS

We conducted a two-stage time-stratified case-crossover study to examine the association between temperature and under-five mortality, spanning the period from 2014 to 2018 across all six regions in Malaysia. In the first stage, we estimated region-specific temperature-mortality associations using a conditional Poisson regression and distributed lag nonlinear models. We used a multivariate meta-regression model to pool the region-specific estimates and examine the potential role of local characteristics in the association, which includes geographical information, demographics, socioeconomic status, long-term temperature metrics, and healthcare access by region.

RESULTS

Temperature in Malaysia ranged from 22 °C to 31 °C, with a mean of 27.6 °C. No clear seasonality was observed in under-five mortality. We found no strong evidence of the association between temperature and under-five mortality, with an "M-" shaped exposure-response curve. The minimum mortality temperature (MMT) was identified at 27.1 °C. Among several local characteristics, only education level and hospital bed rates reduced the residual heterogeneity in the association. However, effect modification by these variables were not significant.

CONCLUSION

This study suggests a null association between temperature and under-five mortality in Malaysia, which has a tropical climate. The "M-" shaped pattern suggests that under-fives may be vulnerable to temperature changes, even with a small temperature change in reference to the MMT. However, the weak risks with a large uncertainty at extreme temperatures remained inconclusive. Potential roles of education level and hospital bed rate were statistically inconclusive.

Mortality Risk Related to Heatwaves in Dezful City, Southwest of Iran

BACKGROUND

We aimed to evaluate the impact of heatwaves on daily deaths due to non-accidental, cardiovascular and respiratory causes in the city of Dezful in Iran from 2013 to 2019.

METHOD

We collected daily ambient temperature and mortality and defined 2 types of heatwaves by combining daily temperature ⩾90th in each month of the study period or since 30 years with duration ⩾2 and 3 days. We used a distributed lag non-linear model to study the association between each type of heatwave definition, and deaths due to non-accidental, cardiovascular and respiratory causes with lags up to 13 days.

RESULTS

There was no discernible correlation in this area, despite the fact that heatwaves raised the risk of death from cardiovascular causes and lowered the risk from respiratory causes. On the other hand, the risk of total non-accidental mortality on days with the heatwaves is significantly higher than normal days. In main effects, the heatwaves have a significant relationship with the risk of total non-accidental mortality (in the first heatwave definition, Cumulative Excess Risk (CER) in lag_0-2 was 10.4 and in second heatwave definition, CER values in lag_{0, 0-2, and 0-6} were 12.4, 29.2, and 38.8 respectively). Also, in added effects, heatwaves have a significant relationship with the risk of total non-accidental mortality (in the first heatwave definition, CER in lag_{0 and 0-2} were 1.79 and 4.11 and in the second heatwave definition, CER values in lag_{0, 0-2, and 0-6} were 7.76, 18.35 and 24.87 respectively). In addition, heatwaves appeared to contribute to a cumulative excess risk of non-accidental death among the male group as well as the older adults.

CONCLUSION

However, the results showed that heatwaves could have detrimental effects on health, even in populations accustomed to the extreme heat. Therefore, early warning systems which monitor heatwaves should provide the necessary warnings to the population, especially the most vulnerable groups.

Effects of ambient temperature on mortality among elderly residents of Chengdu city in Southwest China, 2016-2020: a distributed-lag non-linear time series analysis

BACKGROUND

With complex changes in the global climate, it is critical to understand how ambient temperature affects health, especially in China. We aimed to assess the effects of temperature on daily mortality, including total non-accidental, cardiovascular disease (CVD), respiratory disease, cerebrovascular disease, and ischemic heart disease (IHD) mortality between 2016 and 2020 in Chengdu, China.

METHODS

We obtained daily temperature and mortality data for the period 2016-2020. A Poisson regression model combined with a distributed-lag nonlinear model was used to examine the association between temperature and daily mortality. We investigated the effects of individual characteristics by sex, age, education level, and marital status.

RESULTS

We found significant non-linear effects of temperature on total non-accidental, CVD, respiratory, cerebrovascular, and IHD mortality. Heat effects were immediate and lasted for 0-3 days, whereas cold effects persisted for 7-10 days. The relative risks associated with extreme high temperatures (99th percentile of temperature, 28 °C) over lags of 0-3 days were 1.22 (95% confidence interval [CI]: 1.17, 1.28) for total non-accidental mortality, 1.40 (95% CI: 1.30, 1.50) for CVD morality, 1.34 (95% CI: 1.24, 1.46) for respiratory morality, 1.33 (95% CI: 1.20, 1.47) for cerebrovascular mortality, and 1.38 (95% CI: 1.20, 1.58) for IHD mortality. The relative risks associated with extreme cold temperature (1st percentile of temperature, 3.0 °C) over lags of 0-14 days were 1.32 (95% CI: 1.19, 1.46) for total mortality, 1.45 (95% CI: 1.24, 1.68) for CVD morality, 1.28 (95% CI: 1.09, 1.50) for respiratory morality, 1.36 (95% CI: 1.09, 1.70) for cerebrovascular mortality, and 1.26 (95% CI: 0.95, 1.68) for IHD morality. We found that hot and cold affects were greater in those over 85 years of age, and that women, individuals with low education levels, and those who were widowed, divorced, or never married, were more vulnerable.

CONCLUSIONS

This study showed that exposure to hot and cold temperatures in Chengdu was associated with increased mortality, with people over 85 years old, women, those with low education levels, and unmarried individuals being more affected by hot and cold temperatures.

The influence of heat and cold waves on mortality in Russian subarctic cities with varying climates

Publications on ambient temperature-related mortality among Arctic or subarctic populations are extremely rare. While circumpolar areas cover large portions of several European countries, Canada, and the USA, the population of these territories is relatively small, and the data needed for statistical analysis of the health impacts of extreme temperature events are frequently insufficient. This study utilizes standard time series regression techniques to estimate relative increases in cause- and age-specific daily mortality rates during heat waves and cold spells in four Russian cities with a subarctic climate. The statistical significance of the obtained effect estimates tends to be greater in the continental climate than in the marine climate. A small meta-analysis was built around the obtained site-specific health effects. The effects were homogeneous and calculated for the selected weather-dependent health outcomes. The relative risks of mortality due to ischemic heart disease, all diseases of the circulatory system, and all non-accidental causes during cold spells in the age group ≥ 65 years were 1.20 (95% CI: 1.11-1.29), 1.14 (1.08-1.20), and 1.12 (1.07-1.17), respectively. Cold spells were more harmful to the health of the residents of Murmansk, Archangelsk, and Magadan than heat waves, and only in Yakutsk, heat waves were more dangerous. The results of this study can help the public health authorities develop specific measures for the prevention of excess deaths during cold spells and heat waves in the exposed subarctic populations.

The burden of heat-related stroke mortality under climate change scenarios in 22 East Asian cities

BACKGROUND

Stroke is a leading cause of death and disability in East Asia. Owing to the aging population and high prevalence of stroke, East Asia might suffer a disproportionately heavy burden of stroke under the changing climate. However, the evidence relevant is still limited in this area.

OBJECTIVE

To evaluate the stroke mortality risk due to heat exposure in East Asia and predict its burden under various future climate change scenarios.

METHODS

We conducted a multi-center observational study and collected data from 22 representative cities in three main East Asian countries (i.e., China, Japan, and South Korea) from 1972 to 2015. The two-stage time-series analyses were applied to estimate the effects of heat on stroke mortality at the regional and country level. We further projected the burden of heat-related stroke mortality using 10 global climate models (GCMs) under four shared socioeconomic pathway and representative concentration pathway (SSP-RCP) scenarios, including SSP1-RCP1.9, SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios.

RESULTS

In the present study, a total of 287,579 stroke deaths were collected during the warm season. Heat was significantly associated with an increased risk of stroke mortality. Overall, compared with the 2010 s, the heat-related attributable fraction (AF) was projected to increase in the 2090 s, with increments ranging from 0.8 % to 7.5 % across various climate change scenarios. The heat-related AF was projected to reach 11.9 % (95 % empirical confidence interval [eCI]: 6.1 %, 17.5 %) in the 2090 s under the SSP5-RCP8.5 scenario in China, while the corresponding estimates were 6.6 % (95 % eCI: 2.5 %, 11.0 %) and 5.1 % (95 % eCI: 1.2 %, 9.1 %) for Japan and South Korea, respectively.

CONCLUSIONS

Climate change will exacerbate the burden of heat-related stroke mortality but with considerable geographical heterogeneity in East Asia.

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.

Temperature, cardiovascular mortality, and the role of hypertension and renin-angiotensin-aldosterone axis in seasonal adversity: a narrative review

Environmental temperature is now well known to have a U-shaped relationship with cardiovascular (CV) and all-cause mortality. Both heat and cold above and below an optimum temperature, respectively, are associated with adverse outcomes. However, cold in general and moderate cold specifically is predominantly responsible for much of temperature-attributable adversity. Importantly, hypertension-the most important CV risk factor-has seasonal variation such that BP is significantly higher in winter. Besides worsening BP control in established hypertensives, cold-induced BP increase also contributes to long-term BP variability among normotensive and pre-hypertensive patients, also a known CV risk factor. Disappointingly, despite the now well-stablished impact of temperature on BP and on CV mortality separately, direct linkage between seasonal BP change and CV outcomes remains preliminary. Proving or disproving this link is of immense clinical and public health importance because if seasonal BP variation contributes to seasonal adversity, this should be a modifiable risk. Mechanistically, existing evidence strongly suggests a central role of the sympathetic nervous system (SNS), and secondarily, the renin-angiotensin-aldosterone axis (RAAS) in mediating cold-induced BP increase. Though numerous other inflammatory, metabolic, and vascular perturbations likely also contribute, these may also well be secondary to cold-induced SNS/RAAS activation. This review aims to summarize the current evidence linking temperature, BP and CV outcomes. We also examine underlying mechanisms especially in regard to the SNS/RAAS axis, and highlight possible mitigation measures for clinicians.

Mapping the gaps between cooling benefits of urban greenspace and population heat vulnerability

We provide a novel method to assess the heat mitigation impacts of greenspace though studying the mechanisms of ecosystems responsible for benefits and connecting them to heat exposure metrics. We demonstrate how the ecosystem services framework can be integrated into current practices of environmental health research using supply/demand state-of-the-art methods of ecological modeling of urban greenspace. We compared the supply of cooling ecosystem services in Boston measured through an indicator of high resolution evapotranspiration modeling, with the demand for benefits from cooling measured as a heat exposure risk score based on exposure, hazard and population characteristics. The resulting evapotranspiration indicator follows a pattern similar to conventional greenspace indicators based on vegetation abundance, except in warmer areas such as those with higher levels of impervious surface. We identified demand-supply mismatch areas across the city of Boston, some coinciding with affordable housing complexes and long term care facilities. This novel ES-framework provides cross-disciplinary methods to prioritize urban areas where greenspace interventions can have the most impact based on heat-related demand.

A comparative analysis of SARS-CoV-2 viral load across different altitudes

SARS-CoV-2 has spread throughout the world, including areas located at high or very high altitudes. There is a debate about the role of high altitude hypoxia on viral transmission, incidence, and COVID-19 related mortality. This is the first comparison of SARS-CoV-2 viral load across elevations ranging from 0 to 4300 m. To describe the SARS-CoV-2 viral load across samples coming from 62 cities located at low, moderate, high, and very high altitudes in Ecuador. An observational analysis of viral loads among nasopharyngeal swap samples coming from a cohort of 4929 patients with a RT-qPCR test positive for SARS-CoV-2. The relationship between high and low altitude only considering our sample of 4929 persons is equal in both cases and not significative (p-value 0.19). In the case of low altitude, adding the sex variable to the analysis, it was possible to find a significative difference between men and women (p-value < 0.05). Considering initially sex and then altitude, it was possible to find a significative difference between high and low altitude for men (p-value 0.05). There is not enough evidence to state that viral load is affected directly by altitude range but adding a new variable as sex in the analysis shows that the presence of new variables influences the relationship of altitude range and viral load. There is no evidence that viral loads (Ct and copies/ml) differ at low or high altitude. Using sex as a co-factor, we found that men have higher viral loads than women at low and moderate altitude locations, while living at high altitude, no differences were found. When Ct values were aggregated by low, moderate, and high viral load, we found no significant differences when sex was excluded from the analysis. We conclude that viral load is not directly affected by altitude, but COVID-19 incidence and mortality are rather affected by socio-demographic and idiosyncratic dynamics.

Extreme Temperature and Mortality by Educational Attainment in Spain, 2012-2018

Extreme temperatures are a threat to public health, increasing mortality in the affected population. Moreover, there is substantial research showing how age and gender shape vulnerabilities to this environmental risk. However, there is only limited knowledge on how socioeconomic status (SES), operationalized using educational attainment, stratifies the effect of extreme temperatures on mortality. Here, we address this link using Poisson regression and administrative data from 2012 to 2018 for 50 Spanish Provinces on individuals aged above 65 matched with meteorological data provided by the E-OBS dataset. In line with previous studies, results show that hot and cold days increase mortality. Results on the interaction between SES and extreme temperatures show a positive and significant effect of exposure to heat and cold for individuals with medium and low SES level. Conversely, for high SES individuals we do not find evidence of a robust association with heat or cold. We further investigate how the local climate moderates these associations. A warmer climate increases risks with exposures to low temperatures and vice versa for hot temperatures in the pooled sample. Moreover, we observe that results are mostly driven by low SES individuals being particularly vulnerable to heat in colder climates and cold in warmer climates. In conclusion, results highlight how educational attainment stratifies the effect of extreme temperatures and the relevance of the local climate in shaping risks of low SES individuals aged above 65.

The effects of temperature variability on mortality in patients with chronic obstructive pulmonary disease: a time-series analysis in Hangzhou, China

Chronic obstructive pulmonary disease (COPD) is a leading cause of death in people aged over 60 years old. Research has been reported that ambient temperature and diurnal temperature range (DTR), as representative indices of temperature variability, are contributors to the development and exacerbation of COPD. However, few studies are available in Chinese population. In this study, we aimed to assess the associations of temperature variability on COPD mortality in a fast developing city in China. Using the mortality surveillance system, we obtained a total of 7,863 deaths attributed to COPD from 2014 to 2016. Quasi-Poisson generalized linear regression with distributed lag non-linear model was applied to explore the associations between temperature variability and COPD deaths, after controlling for the potential confounders, including relative humidity, day of week, public holiday, and long-term trend. A J-shaped association of DTR and a reversely J-shaped association of temperature for COPD mortality were observed. Risk estimates showed that the relative risks (RRs) of COPD mortality with extreme high DTR at lag 0 and 0-7 days were 1.045 (95% CI: 0.949-1.151) and 1.460 (95% CI: 1.118-1.908), and the extreme high temperature at lag 0 and 0-7 days were 1.090 (95% CI: 0.945-1.256) and 1.352 (95% CI: 1.163-1.572). Our findings suggest that short-term exposure to extreme temperature was associated with mortality for COPD in Hangzhou. The evidence has implications for policy decision-making and targeted interventions.

The synergy between diurnal temperature range and calcium concentration help to predict hospital mortality in patients with acute myocardial infarction

Epidemiological studies have suggested that cold is an important contributor to acute cardiovascular events and mortality. However, little is known about the Diurnal Temperature Range (DTR) impact on mortality of the patients with myocardial infarction. Calcium ions (Ca²⁺) play a vital role in the human body, such as cardiac electrophysiology and contraction. To investigate whether DTR on admission moderates the association between serum calcium and in-hospital mortality in patients with acute myocardial infarction (AMI). This retrospective study enrolled consecutive adult patients with AMI at a single center in China (2003–2012). Patients were divided into four groups (Ca-Q1–4) according to serum calcium concentration quartiles. Multivariate logistic regression modeling was used to assess whether DTR moderated the association between serum calcium and in-hospital mortality. The predictive value of serum calcium was evaluated by receiver operating characteristic (ROC) curve and net reclassification improvement (NRI) analyses. The study included 3780 patients. In-hospital mortality was 4.97% (188/3780). DTR moderated the association between serum calcium and in-hospital mortality (P-interaction = 0.020). Patients with low serum calcium in the highest DTR quartile exhibited an increased risk of in-hospital mortality (odds ratio for Ca-Q4 vs. Ca-Q1, 0.03; 95% confidence interval [95% CI], 0.01–0.20). In the highest DTR quartile, adding serum calcium concentration to the risk factor model increased the area under the ROC curve (0.81 vs. 0.76; P < 0.001) and increased NRI by 20.2% (95% CI 7.5–32.9; P = 0.001). Low serum calcium was an independent risk factor for in-hospital mortality in patients with AMI, and this association was moderated by DTR. Careful attention should be paid to patients with low serum calcium who experience a higher DTR on admission.

Association of summer temperatures and acute kidney injury in South Korea: a case-crossover study

BACKGROUND

Due to climate change, days with high temperatures are becoming more frequent. Although the effect of high temperature on the kidneys has been reported in research from Central and South America, Oceania, North America and Europe, evidence from Asia is still lacking. This study aimed to examine the association between short-term exposure to high temperatures and acute kidney injury (AKI) in a nationwide study in South Korea.

METHODS

We used representative sampling data from the 2002-2015 National Health Insurance Service-National Sample Cohort in South Korea to link the daily mean temperatures and AKI cases that occurred in the summer. We used a bidirectional case-crossover study design with 0-7 lag days before the emergency room visit for AKI. In addition, we stratified the data into six income levels to identify the susceptible population.

RESULTS

A total of 1706 participants were included in this study. The odds ratio (OR) per 1°C increase at 0 lag days was 1.051, and the ORs per 1°C increase at a lag of 2 days were both 1.076. The association between exposure to high temperatures and AKI was slightly greater in the low-income group (OR = 1.088; 95% CI: 1.049-1.128) than in the high-income group (OR = 1.065; 95% CI: 1.026-1.105).

CONCLUSIONS

In our study, a relationship between exposure to high temperatures and AKI was observed. Precautions should be taken at elevated temperatures to minimize the risk of negative health effects.

Health Disparity Resulting from the Effect of Built Environment on Temperature-Related Mortality in a Subtropical Urban Setting

Whereas previous studies have assessed the overall health impact of temperature in Hong Kong, the aim of this study was to investigate whether the health impact is modified by local temperature of small geographic units, which may be related to the diverse socioeconomic characteristics of these units. The effects of local temperature on non-accidental and cause-specific mortality were analyzed using Bayesian spatial models at a small-area level, adjusting for potential confounders, i.e., area-level air pollutants, socioeconomic status, and green space, as well as spatial dependency. We found that a 10% increase in green space density was associated with an estimated 4.80% decrease in non-accidental mortality risk and a 5.75% decrease in cardiovascular disease mortality risk in Hong Kong, whereas variation in local annual temperature did not significantly contribute to mortality. We also found that the spatial variation of mortality within this city could be explained by the geographic distribution of green space and socioeconomic factors rather than local temperature or air pollution. The findings and methodology of this study may help to further understanding and investigation of social and structural determinants of health disparities, particularly place-based built environment across class-based small geographic units in a city, taking into account the intersection of multiple factors from individual to population levels.

Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019

BACKGROUND

Non-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019.

METHODS

The global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019.

FINDINGS

We estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level.

INTERPRETATION

A substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China.

FUNDING

National Key Research and Development Program.

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.

Wet-Bulb Globe Temperature, Universal Thermal Climate Index, and Other Heat Metrics for US Counties, 2000-2020

Epidemiologic research on extreme heat consistently finds significant impacts on human morbidity and mortality. However, most of these analyses do not use spatially explicit measures of heat (typically assessing exposures at major cities using the nearest weather station), and they frequently consider only ambient temperature or heat index. The field is moving toward more expansive analyses that use spatially resolved gridded meteorological datasets and alternative assessments of heat, such as wet-bulb globe temperature (WBGT) and universal thermal climate index (UTCI), both of which require technical geoscientific skills that may be inaccessible to many public health researchers. To facilitate research in this domain, we created a database of population-weighted, spatially explicit daily heat metrics - including WBGT, UTCI, heat index, dewpoint temperature, net effective temperature, and humidex - for counties in the conterminous United States derived from the ERA5-Land gridded data set and using previously validated equations and algorithms. We also provide an R package to calculate these metrics, including gold-standard algorithms for estimating WBGT and UTCI, to facilitate replication.

The effect of ambient temperature on in-hospital mortality: a study in Nanjing, China

To reduce the inpatient mortality and improve the quality of hospital management, we explore the relationship between temperatures and in-hospital mortality in a large sample across 10 years in Nanjing, Jiangsu. We collected 10 years’ data on patient deaths from a large research hospital. Distributed lag non-linear model (DLNM) was used to find the association between daily mean temperatures and in-hospital mortality. A total of 6160 in-hospital deaths were documented. Overall, peak RR appeared at 8 °C, with the range of 1 to 20 °C having a significantly high mortality risk. In the elderly (age ≥ 65 years), peak RR appeared at 5 °C, with range − 3 to 21 °C having a significantly high mortality risk. In males, peak RR appeared at 8 °C, with the range 0 to 24 °C having a significantly high mortality risk. Moderate cold (define as 2.5th percentile of daily mean temperatures to the MT), not extreme temperatures (≤ 2.5th percentile or ≥ 97.5th percentile of daily mean temperatures), increased the risk of death in hospital patients, especially in elderly and male in-hospital patients.

Heat-induced SIRT1-mediated H4K16ac deacetylation impairs resection and SMARCAD1 recruitment to double strand breaks

Hyperthermia inhibits DNA double-strand break (DSB) repair that utilizes homologous recombination (HR) pathway by a poorly defined mechanism(s); however, the mechanisms for this inhibition remain unclear. Here we report that hyperthermia decreases H4K16 acetylation (H4K16ac), an epigenetic modification essential for genome stability and transcription. Heat-induced reduction in H4K16ac was detected in humans, Drosophila, and yeast, indicating that this is a highly conserved response. The examination of histone deacetylase recruitment to chromatin after heat-shock identified SIRT1 as the major deacetylase subsequently enriched at gene-rich regions. Heat-induced SIRT1 recruitment was antagonized by chromatin remodeler SMARCAD1 depletion and, like hyperthermia, the depletion of the SMARCAD1 or combination of the two impaired DNA end resection and increased replication stress. Altered repair protein recruitment was associated with heat-shock-induced γ-H2AX chromatin changes and DSB repair processing. These results support a novel mechanism whereby hyperthermia impacts chromatin organization owing to H4K16ac deacetylation, negatively affecting the HR-dependent DSB repair.

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H4K16ac deacetylation during hyperthermia is conserved in human, Drosophila, and yeast

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Dynamic regulation of the chromatin functions during hyperthermia is SIRT1-dependent

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SIRT1 function is negatively impacted by SMARCAD1

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Hyperthermia increases replication stress and impacts DNA resection, impairing DSB repair

Comparison of health outcomes from heat-related injuries by National Weather Service reported heat wave days and non-heat wave days - Illinois, 2013-2019

It is predicted that heat waves will increase as climate changes. Related public health interventions have expanded over the past decades but are primarily targeted at health outcomes occurring during heat waves. However, heat adaptation is dynamic and adverse outcomes related to heat injuries occur with moderate increases in temperature throughout the summertime. We analyzed outpatient and inpatient heat related injuries from 2013 to 2019. National Weather Service event summaries were used to characterize reported heat wave days and weather data was linked to individual cases. Despite the higher rate of heat injury on heat wave days, only 12.7% of the 17,662 heat-related injuries diagnosed from 2013 to 2019 occurred during reported heat waves. In addition, the National Weather Service surveillance system monitoring heat related injuries only captured 2.1% of all heat related injuries and 30.6% of heat related deaths. As climate changes and warmer conditions become more common, public health response to moderate increases in temperature during summertime needs to be strengthened as do the surveillance systems used to monitor adverse heat related health events. Improved surveillance systems, long-term interventions and strategies addressing climate change may help mitigate adverse health outcomes attributable to heat related injuries over the summertime.

Heat-Related Mortality in Two Regions of Poland: Focus on Urban and Rural Areas during the Most Severe and Long-Lasting Heatwaves

The vast majority of studies on heat-related mortality are focused on large cities. The aim of this study is to fill this research gap and to estimate the impact of high temperatures on the risk of death in smaller towns and villages. The results show that increased mortality is not only a problem in large cities. The risk of death, although usually slightly lower than in highly populated areas, may be higher for the age-related risk group. At temperatures above 35 °C, it may exceed 1.3 in smaller towns and even 1.6 in villages. The increase in mortality during five selected heat waves of high intensity and long duration was also studied for two regions of Poland: Małopolska and Wielkopolska. Towns with a population of less than 10,000 in Małopolska region, during the 2006 heatwave, experienced an increase in the number of deaths by as much as 18%. At the same time in the largest city of Małopolska-Kraków, the death toll rose by 4%. This paper also presents some differences between regions in terms of the impact of heat waves: in the lowland region of Wielkopolska, the mortality rate is generally higher than in the upland region of Małopolska.

Outdoor thermal stress changes in South Korea: Increasing inter-annual variability induced by different trends of heat and cold stresses

Changes of thermal environment can lead to unfavorable impacts such as a decrease of thermal stratification, increase of energy consumption, and increase of thermal health risk. Investigating changes in outdoor thermal environments can provide meaningful information for addressing economic and social issues and related challenges. In this study, thermal environment changes in South Korea were investigated using a nonstationary two-component Gaussian mixture model (NSGMM) for air temperature and two thermal comfort indices. For this, the perceived temperature (PT) and universal thermal climate index (UTCI) were employed as the thermal comfort index. Thermal comfort indices were computed using observed meteorological data at 26 weather stations for 37 years in South Korea. Meanwhile, trends of thermal comforts in the warm and cool seasons were simultaneously modeled by the NSGMM. The results indicate significant increasing trends in thermal comfort indices for South Korea. The increasing trends in thermal comfort indices both the warm and cool seasons were detected while the magnitudes of the trends are significantly different. This difference between the magnitude of trends led to an increase in mean and inter-annual variability of thermal comfort indices based on PT, while an increase of mean and decrease of inter-annual variability were observed based on the UTCI. Moreover, the annual proportion of the category referring to days in comfort based on the results of PT has decreased due to the different trends of thermal comfort indices in the warm and cool seasons. This decrease may lead to an increase of thermal health risk that is larger than what would be expected from the results considering the increasing trend of the annual mean temperature in South Korea. From this result, it can be inferred that the thermal health risk in South Korea may be more adverse than what we originally expected from the current temperature trend.

The Thermal Environment of Housing and Its Implications for the Health of Older People in South Australia: A Mixed-Methods Study

Older people are often over-represented in morbidity and mortality statistics associated with hot and cold weather, despite remaining mostly indoors. The study “Improving thermal environment of housing for older Australians” focused on assessing the relationships between the indoor environment, building characteristics, thermal comfort and perceived health/wellbeing of older South Australians over a study period that included the warmest summer on record. Our findings showed that indoor temperatures in some of the houses reached above 35 °C. With concerns about energy costs, occupants often use adaptive behaviours to achieve thermal comfort instead of using cooling (or heating), although feeling less satisfied with the thermal environment and perceiving health/wellbeing to worsen at above 28 °C (and below 15 °C). Symptoms experienced during hot weather included tiredness, shortness of breath, sleeplessness and dizziness, with coughs and colds, painful joints, shortness of breath and influenza experienced during cold weather. To express the influence of temperature and humidity on perceived health/wellbeing, a Temperature Humidity Health Index (THHI) was developed for this cohort. A health/wellbeing perception of “very good” is achieved between an 18.4 °C and 24.3 °C indoor operative temperature and a 55% relative humidity. The evidence from this research is used to inform guidelines about maintaining home environments to be conducive to the health/wellbeing of older people.

Variation in estimates of heat-related mortality reduction due to tree cover in U.S. cities

Heat-related mortality is one of the leading causes of weather-related deaths in the United States. With changing climates and an aging population, effective adaptive strategies to address public health and environmental justice issues associated with extreme heat will be increasingly important. One effective adaptive strategy for reducing heat-related mortality is increasing tree cover. Designing such a strategy requires decision-support tools that provide spatial and temporal information about impacts. We apply such a tool to estimate spatially and temporally explicit reductions in temperature and mortality associated with a 10% increase in tree cover in 10 U.S. cities with varying climatic, demographic, and land cover conditions. Two heat metrics were applied to represent tree impacts on moderately and extremely hot days (relative to historical conditions). Increasing tree cover by 10% reduced estimated heat-related mortality in cities significantly, with total impacts generally greatest in the most populated cities. Mortality reductions vary widely across cities, ranging from approximately 50 fewer deaths in Salt Lake City to about 3800 fewer deaths in New York City. This variation is due to differences in demographics, land cover, and local climatic conditions. In terms of per capita estimated impacts, hotter and drier cities experience higher percentage reductions in mortality due to increased tree cover across the season. Phoenix potentially benefits the most from increased tree cover, with an estimated 22% reduction in mortality from baseline levels. In cooler cities such as Minneapolis, trees can reduce mortality significantly on days that are extremely hot relative to historical conditions and therefore help mitigate impacts during heat wave conditions. Recent studies project highest increases in heat-related mortality in the cooler cities, so our findings have important implications for adaptation planning. Our estimated spatial and temporal distributions of mortality reductions for each city provide crucial information needed for promoting environmental justice and equity. More broadly, the methods and model can be applied by both urban planners and the public health community for designing targeted, effective policies to reduce heat-related mortality. Additionally, land use managers can use this information to optimize tree plantings. Public stakeholders can also use these impact estimates for advocacy.

The association between temperature and cause-specific mortality in the Klang Valley, Malaysia

This study aims to examine the relationship between daily temperature and mortality in the Klang Valley, Malaysia, over the period 2006-2015. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM) was used to estimate the association between the mean temperature and mortality categories (natural n=69,542, cardiovascular n= 15,581, and respiratory disease n=10,119). Particulate matter with an aerodynamic diameter below 10 μm (PM₁₀) and surface ozone (O₃) was adjusted as a potential confounding factor. The relative risk (RR) of natural mortality associated with extreme cold temperature (1st percentile of temperature, 25.2 °C) over lags 0-28 days was 1.26 (95% confidence interval (CI): 1.00, 1.60), compared with the minimum mortality temperature (28.2 °C). The relative risk associated with extremely hot temperature (99th percentile of temperature, 30.2 °C) over lags 0-3 days was 1.09 (95% CI: 1.02, 1.17). Heat effects were immediate whereas cold effects were delayed and lasted longer. People with respiratory diseases, the elderly, and women were the most vulnerable groups when it came to the effects of extremely high temperatures. Extreme temperatures did not dramatically change the temperature-mortality risk estimates made before and after adjustments for air pollutant (PM₁₀ and O₃) levels.

Effect of non-optimum ambient temperature on cognitive function of elderly women in Germany

Non-optimum ambient temperature has been associated with a variety of health outcomes in the elderly population. However, few studies have examined its adverse effects on neurocognitive function. In this study, we explored the temperature-cognition association in elderly women. We investigated 777 elderly women from the German SALIA cohort during the 2007-2010 follow-up. Cognitive function was evaluated using the CERAD-Plus test battery. Modelled data on daily weather conditions were assigned to the residential addresses. The temperature-cognition association over lag 0-10 days was estimated using multivariable regression with distributed lag non-linear model. The daily mean temperature ranged between -6.7 and 26.0 °C during the study period for the 777 participants. We observed an inverse U-shaped association in elderly women, with the optimum temperature (15.3 °C) located at the 68th percentile of the temperature range. The average z-score of global cognitive function declined by -0.31 (95%CI: 0.73, 0.11) for extreme cold (the 2.5th percentile of temperature range) and -0.92 (95%CI: 1.50, -0.33) for extreme heat (the 97.5th percentile of temperature range), in comparison to the optimum temperature. Episodic memory was more sensitive to heat exposure, while semantic memory and executive function were the two cognitive domains sensitive to cold exposure. Individuals living in an urban area and those with a low educational level were particularly sensitive to extreme heat. In summary, non-optimum temperature was inversely associated with cognitive function in elderly women, with the effect size for heat exposure particularly substantial. The strength of association varied by cognitive domains and individual characteristics.

Temperature-mortality relationship in North Carolina, USA: Regional and urban-rural differences

BACKGROUND

Health disparities exist between urban and rural populations, yet research on rural-urban disparities in temperature-mortality relationships is limited. As inequality in the United States increases, understanding urban-rural and regional differences in the temperature-mortality association is crucial.

OBJECTIVE

We examined regional and urban-rural differences of the temperature-mortality association in North Carolina (NC), USA, and investigated potential effect modifiers.

METHODS

We applied time-series models allowing nonlinear temperature-mortality associations for 17 years (2000-2016) to generate heat and cold county-specific estimates. We used second-stage analysis to quantify the overall effects. We also explored potential effect modifiers (e.g. social associations, greenness) using stratified analysis. The analysis considered relative effects (comparing risks at 99th to 90th temperature percentiles based on county-specific temperature distributions for heat, and 1st to 10th percentiles for cold) and absolute effects (comparing risks at specific temperatures).

RESULTS

We found null effects for heat-related mortality (relative effect: 1.001 (95% CI: 0.995-1.007)). Overall cold-mortality risk for relative effects was 1.019 (1.015-1.023). All three regions had statistically significant cold-related mortality risks for relative and absolute effects (relative effect: 1.019 (1.010-1.027) for Coastal Plains, 1.021 (1.015-1.027) for Piedmont, 1.014 (1.006-1.023) for Mountains). The heat mortality risk was not statistically significant, whereas the cold mortality risk was statistically significant, showing higher cold-mortality risks in urban areas than rural areas (relative effect for heat: 1.006 (0.997-1.016) for urban, 1.002 (0.988-1.017) for rural areas; relative effect for cold: 1.023 (1.017-1.030) for urban, 1.012 (1.001-1.023) for rural areas). Findings are suggestive of higher relative cold risks in counties with the less social association, higher population density, less green-space, higher PM_2.5, lower education level, higher residential segregation, higher income inequality, and higher income (e.g., Ratio of Relative Risks 1.72 (0.68, 4.35) comparing low to high education).

CONCLUSION

Results indicate cold-mortality risks in NC, with potential differences by regional, urban-rural areas, and community characteristics.

Association between winter cold spells and acute myocardial infarction in Lithuania 2000-2015

Acute myocardial infarction (AMI) is a major public health problem. Cold winter weather increases the risk of AMI, but factors influencing susceptibility are poorly known. We conducted an individual-level case-crossover study of the associations between winter cold spells and the risk of AMI, with special focus on survival at 28 days and effect modification by age and sex. All 16,071 adult cases of AMI among the residents of the city of Kaunas in Lithuania in 2000-2015 were included in the study. Cold weather was statistically defined using the 5th percentile of frequency distribution of daily mean temperatures over the winter months. According to conditional logistic regression controlling for time-varying and time-invariant confounders, each additional cold spell day during the week preceding AMI increased the risk of AMI by 5% (95% CI 1-9%). For nonfatal and fatal cases, the risk increase per each additional cold spell day was 5% (95% CI 1-9%) and 6% (95% CI - 2-13%), respectively. The effect estimate was greater for men (OR 1.07, 95% CI 1.02-1.12) than for women (OR 1.02, 95% CI 0.97-1.08), but there was no evidence of effect modification by age. Evidence on factors increasing susceptibility is critical for targeted cold weather planning.

Effects of urbanization on vulnerability to heat-related mortality in urban and rural areas in South Korea: a nationwide district-level time-series study

BACKGROUND

Although urbanization is often an important topic in climate change studies, the complex effect of urbanization on heat vulnerability in urban and rural areas has rarely been studied. We investigated the disparate effects of urbanization on heat vulnerability in urban and rural areas, using nationwide data.

METHODS

We collected daily weather data for all 229 administrative districts in South Korea (2011-17). Population density was applied as an urbanization indicator. We calculated the heat-mortality risk using a distributed lag nonlinear model and analysed the relationship with population density. We also examined district characteristics that can be related to the spatial heterogeneity in heat-mortality risk.

RESULTS

We found a U-shaped association between population density and heat-mortality risk, with the highest risk for rural populations; in urban areas, risk increases with increasing population density. Higher heat-mortality risk was associated with a lower number of hospital beds per person and higher percentage of people requiring recuperation. The association between hospital beds and heat-mortality risk was prominent in high-density urban areas, whereas the association between the percentage of people requiring recuperation and heat-mortality risk was pronounced in rural areas.

CONCLUSIONS

Our findings indicate that the association between population density and heat-mortality risk is different in urban and rural areas, and that district characteristics related to heat-mortality risk also differ by urbanicity. These results can contribute to understanding the complex role of urbanization on heat vulnerability and can provide evidence to policy makers for prioritizing resources.

Associations between Perceptions and Measures of Weather and Walking, United States-2015

INTRODUCTION

Weather can be a barrier to walking. Understanding how perceptions of weather as a barrier and measured temperature are associated with walking can inform monitoring and promotion strategies. The objective of this study is to examine the association between perceptions of weather as a barrier to walking and measured weather with the volume of leisure and transportation walking.

METHODS

The 2015 National Health Interview Survey (NHIS) assessed participation in and volume of walking (transportation, leisure) in the past week and frequency of reporting weather as a barrier to walking. Data were collected over the entire year. In 2019, we merged month-specific temperature data from the PRISM climate group with individual NHIS records. We examined associations using logistic (participation) and linear regression models (volume).

RESULTS

Participation in walking increased as frequency of reporting weather as a barrier to walking decreased, from 'almost always' (transportation: 23%, leisure: 42%) to 'a little of the time' (transportation: 40%, leisure: 67%). Among adults reporting walking, walking volume increased as frequency of reporting weather as a barrier decreased from 'almost always' (transportation: 51 min/week, leisure: 64 min/week) to 'never' (transportation: 69 min/week, leisure: 98 min/week). Month-specific temperature was significantly associated with leisure walking with lower participation at the lowest and highest temperature quintiles, although the strength of the association differed by frequency of reporting weather as a barrier.

CONCLUSIONS

In general, prevalence and volume of leisure and transportation walking decreased as the perception of weather as a barrier increased. Low and high temperature conditions were also associated with leisure walking participation, particularly among adults with increased perceptions of weather as a barrier. Our findings highlight the importance of including strategies to help adults overcome perceived and actual weather-related barriers in walking promotion efforts.

Resilience and Equity in a Time of Crises: Investing in Public Urban Greenspace Is Now More Essential Than Ever in the US and Beyond

The intersecting negative effects of structural racism, COVID-19, climate change, and chronic diseases disproportionately affect racial and ethnic minorities in the US and around the world. Urban populations of color are concentrated in historically redlined, segregated, disinvested, and marginalized neighborhoods with inadequate quality housing and limited access to resources, including quality greenspaces designed to support natural ecosystems and healthy outdoor activities while mitigating urban environmental challenges such as air pollution, heat island effects, combined sewer overflows and poor water quality. Disinvested urban environments thus contribute to health inequity via physical and social environmental exposures, resulting in disparities across numerous health outcomes, including COVID-19 and chronic diseases such as cancer and cardiovascular diseases (CVD). In this paper, we build off an existing conceptual framework and propose another conceptual framework for the role of greenspace in contributing to resilience and health equity in the US and beyond. We argue that strategic investments in public greenspaces in urban neighborhoods impacted by long term economic disinvestment are critically needed to adapt and build resilience in communities of color, with urgency due to immediate health threats of climate change, COVID-19, and endemic disparities in chronic diseases. We suggest that equity-focused investments in public urban greenspaces are needed to reduce social inequalities, expand economic opportunities with diversity in workforce initiatives, build resilient urban ecosystems, and improve health equity. We recommend key strategies and considerations to guide this investment, drawing upon a robust compilation of scientific literature along with decades of community-based work, using strategic partnerships from multiple efforts in Milwaukee Wisconsin as examples of success.

A heat-health watch and warning system with extended season and evolving thresholds

BACKGROUND

Many countries have developed heat-health watch and warning systems (HHWWS) or early-warning systems to mitigate the health consequences of extreme heat events. HHWWS usually focuses on the four hottest months of the year and imposes the same threshold over these months. However, according to climate projections, the warm season is expected to extend and/or shift. Some studies demonstrated that health impacts of heat waves are more severe when the human body is not acclimatized to the heat. In order to adapt those systems to potential heat waves occurring outside the hottest months of the season, this study proposes specific health-based monthly heat indicators and thresholds over an extended season from April to October in the northern hemisphere.

METHODS

The proposed approach, an adoption and extension of the HHWWS methodology currently implemented in Quebec (Canada). The latter is developed and applied to the Greater Montreal area (current population 4.3 million) based on historical health and meteorological data over the years. This approach consists of determining excess mortality episodes and then choosing monthly indicators and thresholds that may involve excess mortality.

RESULTS

We obtain thresholds for the maximum and minimum temperature couple (in °C) that range from (respectively, 23 and 12) in April, to (32 and 21) in July and back to (25 and 13) in October. The resulting HHWWS is flexible, with health-related thresholds taking into account the seasonality and the monthly variability of temperatures over an extended summer season.

CONCLUSIONS

This adaptive and more realistic system has the potential to prevent, by data-driven health alerts, heat-related mortality outside the typical July-August months of heat waves. The proposed methodology is general and can be applied to other regions and situations based on their characteristics.

Role of temperature, influenza and other local characteristics in seasonality of mortality: a population-based time-series study in Japan

OBJECTIVES

To investigate the extent to which temperature and influenza explained seasonality of mortality in Japan and to examine the association of the seasonality with prefecture-specific characteristics.

DESIGN

We conducted time-series analysis to estimate the seasonal amplitude before and after adjusting for temperature and/or influenza-like illness (ILI). Next, we applied linear mixed effect models to investigate the association of seasonal amplitudes with each indicator on prefecture-specific characteristics on climate, demographic and socioeconomic factors and adaptations.

SETTING

47 prefectures in Japan PARTICIPANTS: Deaths for all-cause, circulatory, and respiratory disease between 1999 and 2015.

OUTCOME MEASURES

Peak-to-trough ratio (PTR, a measure of seasonal amplitude).

RESULTS

The nationwide unadjusted-PTRs for all-cause, circulatory and respiratory mortality were 1.29 (95% CIs: 1.28 to 1.31), 1.55 (95% CI: 1.52 to 1.57) and 1.45 (95% CI: 1.43 to 1.48), respectively. These PTRs reduced substantially after adjusting for temperature but very little after a separate adjustment for ILI. Furthermore, seasonal amplitudes varied between prefectures. However, there was no strong evidence for the associations of PTR with the indicators on prefecture-specific characteristics.

CONCLUSIONS

Seasonality of mortality is primarily driven by temperature in Japan. The spatial variation in seasonal amplitudes was not associated with prefecture-specific characteristics. Although further investigations are required to confirm our findings, this study can help us gain a better understanding of the mechanisms underlying seasonality of mortality.

A Call for One Health in Medical Education: How the COVID-19 Pandemic Underscores the Need to Integrate Human, Animal, and Environmental Health

During the early stages of the COVID-19 pandemic in 2020, the first author, then a fourth-year student at Harvard Medical School, was enrolled in a One Health clinical experience at Zoo New England where he was introduced to a transdisciplinary approach to integrate human, animal, and ecosystem health. Seeing the vast impact of the pandemic and knowing its roots as a zoonotic disease, he realized this approach was critical to his medical education and for preparation against future novel infectious diseases. Zoonotic diseases have been emerging into human populations with increasing frequency, leading to public health emergencies such as Ebola, avian influenza, and SARS. The SARS-CoV-2 narrative, starting in bats and then mutating through an intermediate host into humans, is another striking example of the interconnectedness between human, animal, and ecosystem health that underlies these infections. Preventing future pandemics will require a transdisciplinary One Health approach, and physicians should be prepared to participate in these discussions while advocating for One Health initiatives for the benefit of their current and future patients. Integration of One Health education into medical school curricula will also prepare future physicians for other complex and urgently important health issues such as climate change, antimicrobial resistance, and the impact of biodiversity loss. As the consequences of the COVID-19 pandemic persist, education in One Health must become a priority; it is essential to break down the conventional disciplinary silos of human medicine, veterinary medicine, environmental health, public health, and the social sciences, so that future health crises can be prevented and mitigated collaboratively.

Predicting emergency department visits in a large teaching hospital

Background

Emergency department (ED) visits show a high volatility over time. Therefore, EDs are likely to be crowded at peak-volume moments. ED crowding is a widely reported problem with negative consequences for patients as well as staff. Previous studies on the predictive value of weather variables on ED visits show conflicting results. Also, no such studies were performed in the Netherlands. Therefore, we evaluated prediction models for the number of ED visits in our large the Netherlands teaching hospital based on calendar and weather variables as potential predictors.

Methods

Data on all ED visits from June 2016 until December 31, 2019, were extracted. The 2016–2018 data were used as training set, the 2019 data as test set. Weather data were extracted from three publicly available datasets from the Royal Netherlands Meteorological Institute. Weather observations in proximity of the hospital were used to predict the weather in the hospital’s catchment area by applying the inverse distance weighting interpolation method. The predictability of daily ED visits was examined by creating linear prediction models using stepwise selection; the mean absolute percentage error (MAPE) was used as measurement of fit.

Results

The number of daily ED visits shows a positive time trend and a large impact of calendar events (higher on Mondays and Fridays, lower on Saturdays and Sundays, higher at special times such as carnival, lower in holidays falling on Monday through Saturday, and summer vacation). The weather itself was a better predictor than weather volatility, but only showed a small effect; the calendar-only prediction model had very similar coefficients to the calendar+weather model for the days of the week, time trend, and special time periods (both MAPE’s were 8.7%).

Conclusions

Because of this similar performance, and the inaccuracy caused by weather forecasts, we decided the calendar-only model would be most useful in our hospital; it can probably be transferred for use in EDs of the same size and in a similar region. However, the variability in ED visits is considerable. Therefore, one should always anticipate potential unforeseen spikes and dips in ED visits that are not shown by the model.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12245-021-00357-6.

Does surrounding greenness moderate the relationship between apparent temperature and physical activity? Findings from the PHENOTYPE project

BACKGROUND

Physical activity can be affected by both meteorological conditions and surrounding greenness, but few studies have evaluated the effects of these environmental factors on physical activity simultaneously. This multi-city comparative study aimed to assess the synergetic effects of apparent temperature and surrounding greenness on physical activity in four European cities. Specifically, we aimed to identify an interaction between surrounding greenness and apparent temperature in the effects on physical activity.

METHODS

Data were collected from 352 adult residents of Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands), and Kaunas (Lithuania) as part of the PHENOTYPE study. Participants wore a smartphone for seven consecutive days between May-December 2013 and provided additional sociodemographic survey data. Hourly average physical activity (Metabolic Equivalent of Task (MET)) and surrounding greenness (NDVI) were derived from the Calfit mobile application collecting accelerometer and location data. Hourly apparent temperature was calculated from temperature and relative humidity, which were obtained from local meteorological stations along with other meteorological covariates (rainfall, windspeed, and sky darkness). We assessed the interaction effects of apparent temperature and surrounding greenness on hourly physical activity for each city using linear mixed models, while adjusting for meteorological, demographic, and time-related variables.

RESULTS

We found significant interactions between apparent temperature and surrounding greenness on hourly physical activity in three of four cities, aside from the coastal city of Barcelona. Significant quadratic effects of apparent temperature were found in the highest level of surrounding greenness for Stoke-on-Trent and Doetinchem, with 4% decrease in median MET observed for a 10°C departure from optimal temperature (15.2°C and 14.6°C, respectively). Significant linear effects were found for higher levels of surrounding greenness in Kaunas, whereby an increase of 10°C was associated with ∼4% increase in median MET.

CONCLUSION

Apparent temperature and surrounding greenness interacted in the effect on hourly physical activity across three of four European cities, with varying effect between cities. While quadratic effects of temperature suggest diminishing levels of physical activity in the highest greenness levels in cities of temperate climates, the variation in surrounding greenness between cities could be further explored, particularly by looking at indoor-outdoor locations. The study findings support the need for evidence-based physical activity promotion and urban design.

Influence of Indoor Temperature Exposure on Emergency Department Visits Due to Infectious and Non-Infectious Respiratory Diseases for Older People

Previous studies have demonstrated that outdoor temperature exposure was an important risk factor for respiratory diseases. However, no study investigates the effect of indoor temperature exposure on respiratory diseases and further assesses cumulative effect. The objective of this study is to study the cumulative effect of indoor temperature exposure on emergency department visits due to infectious (IRD) and non-infectious (NIRD) respiratory diseases among older adults. Subjects were collected from the Longitudinal Health Insurance Database in Taiwan. The cumulative degree hours (CDHs) was used to assess the cumulative effect of indoor temperature exposure. A distributed lag nonlinear model with quasi-Poisson function was used to analyze the association between CDHs and emergency department visits due to IRD and NIRD. For IRD, there was a significant risk at 27, 28, 29, 30, and 31 °C when the CDHs exceeded 69, 40, 14, 5, and 1 during the cooling season (May to October), respectively, and at 19, 20, 21, 22, and 23 °C when the CDHs exceeded 8, 1, 1, 35, and 62 during the heating season (November to April), respectively. For NIRD, there was a significant risk at 19, 20, 21, 22, and 23 °C when the CDHs exceeded 1, 1, 16, 36, and 52 during the heating season, respectively; the CDHs at 1 was only associated with the NIRD at 31 °C during the cooling season. Our data also indicated that the CDHs was lower among men than women. We conclude that the cumulative effects of indoor temperature exposure should be considered to reduce IRD risk in both cooling and heating seasons and NIRD risk in heating season and the cumulative effect on different gender.