Heat waves and health outcomes in Alabama (USA): the importance of heat wave definition

Preterm and Early-Term Delivery After Heat Waves in 50 US Metropolitan Areas

Importance

Heat waves are increasing in frequency, intensity, and duration and may be acutely associated with pregnancy outcomes.

Objective

To examine changes in daily rates of preterm and early-term birth after heat waves in a 25-year nationwide study.

Design, Setting, and Participants

This cohort study of singleton births used birth records from 1993 to 2017 from the 50 most populous US metropolitan statistical areas (MSAs). The study included 53 million births, covering 52.8% of US births over the period. Data were analyzed between October 2022 and March 2023 at the National Center for Health Statistics.

Exposures

Daily temperature data from Daymet at 1-km2 resolution were averaged over each MSA using population weighting. Heat waves were defined in the 4 days (lag, 0-3 days) or 7 days (lag, 0-6 days) preceding birth.

Main Outcomes and Measures

Daily counts of preterm birth (28 to <37 weeks), early-term birth (37 to <39 weeks), and ongoing pregnancies in each gestational week on each day were enumerated in each MSA. Rate ratios for heat wave metrics were obtained from time-series models restricted to the warm season (May to September) adjusting for MSA, year, day of season, and day of week, and offset by pregnancies at risk.

Results

There were 53 154 816 eligible births in the 50 MSAs from 1993 to 2017; 2 153 609 preterm births and 5 795 313 early-term births occurring in the warm season were analyzed. A total of 30.0% of mothers were younger than 25 years, 53.8% were 25 to 34 years, and 16.3% were 35 years or older. Heat waves were positively associated with daily rates of preterm and early-term births, showing a dose-response association with heat wave duration and temperatures and stronger associations in the more acute 4-day window. After 4 consecutive days of mean temperatures exceeding the local 97.5th percentile, the rate ratio for preterm birth was 1.02 (95% CI, 1.00-1.03), and the rate ratio for early-term birth was 1.01 (95% CI, 1.01-1.02). For the same exposure, among those who were 29 years of age or younger, had a high school education or less, and belonged to a racial or ethnic minority group, the rate ratios were 1.04 (95% CI, 1.02-1.06) for preterm birth and 1.03 (95% CI, 1.02-1.05) for early-term birth. Results were robust to alternative heat wave definitions, excluding medically induced deliveries, and alternative statistical model specifications.

Conclusions and Relevance

In this cohort study, preterm and early-term birth rates increased after heat waves, particularly among socioeconomically disadvantaged subgroups. Extreme heat events have implications for perinatal health.

Heat-related mortality in Frankfurt am Main, Germany, from 2000 to 2023

Background

The major heatwave in Europe in August 2003 resulted in 70,000 excess deaths. In Frankfurt am Main, a city with 767,000 inhabitants in the south-west of Germany, around 200 more people died in August 2003 than expected. Soon afterwards, the city introduced adaptation measures to prevent heat-related health problems and subsequently established further mitigation measures to limit climate change. Frankfurt is rated as being one of the cities in Germany to have implemented the best climate adaptation and mitigation measures. This study addressed the following questions: is there already a downward trend in mortality from heat and can this be attributed to the measures taken?

Materials and methods

The age-standardized mortality rate (ASR) was calculated for the months of June to August and for calendar weeks 23 to 34 of the individual years on the basis of population data and deaths of the inhabitants of Frankfurt am Main for the years 2000 to 2023. This was related to the meteorological data from the Frankfurt measuring station of the German National Meteorological Service. For four different heat exposure indicators (heat days, days in heat weeks, days in heatwaves and days with heat warnings), the incidence rate (death cases per 1 million person days) (IR) was calculated for days with and without exposure, and the incidence rate difference and the incidence rate ratio (IRR) were estimated to compare days with vs days without exposure.

Results

Over the years, the mean daily temperatures tended to increase, and the standardized mortality rate decreased. An increase in ASR was observed during heatwaves up to 2015, but no longer in the later ones. In the summer of 2003, the incidence rate was 16.0 (95% confidence interval (CI) 12.2-19.9) per 1 million person days greater on heat days than on days not classified as heat days, and the corresponding incidence rate ratio was 1.64 (95% CI 1.48-1.82). Although the weather data for the summers of 2018 and 2022 were comparable with the record-breaking heat summer of 2003, the incidence rate differences (2018: 3.8, 95% CI 0.9-6.7; 2022: 2.3, 95% CI -0.3-4.9) and the IRR (2018: 1.20, 95% CI 1.05-1.37; 2022: 1.12, 95% CI 0.99-1.26) were considerably lower. Similar results were also obtained when comparing mortality in heat weeks and heatwaves as well as on days with heat warnings.

Discussion

In summary, our study in Frankfurt am Main not only showed a decrease in heat-related mortality in the population as a whole over the years, but also a decrease in excess mortality during various heat periods (day, week, wave, warning), especially in comparison with the years with very high heat stress and drought (2003, 2018 and 2022). However, whether this development represents success of the intensive prevention measures that have been implemented in the city for years or merely describes a general trend cannot be answered with certainty by the present study. To answer this question, a comparative study should be carried out in various municipalities in the Rhine-Main region with different levels of intensity in dealing with the heat problem.

Revisiting the importance of temperature, weather and air pollution variables in heat-mortality relationships with machine learning

Extreme heat events have significant health impacts that need to be adequately quantified in the context of climate change. Traditionally, heat-health association methods have relied on statistical models using a single air temperature index, without considering other heat-related variables that may influence the relationship and their potentially complex interactions. This study aims to introduce and compare different machine learning (ML) models, which naturally consider interactions between predictors and non-linearities, to re-examine the importance of temperature, weather and air pollution predictors in modeling the heat-mortality relationship. ML approaches based on tree ensembles and neural networks, as well as non-linear statistical models, were used to model the heat-mortality relationship in the two most populated metropolitan areas of the province of Quebec, Canada. The models were calibrated using a comprehensive database of heat-related predictors including various lagged temperature indices, temperature variations, meteorological and air pollution variables. Performance was evaluated based on out-of-sample summer mortality predictions. For the two studied regions, models relying only on lagged temperature indices performed better, or equally well, than models considering more heat-related predictors such as temperature variations, weather and air pollution variables. The temperature index with the best performance differed by region, but both mean temperature and humidex were among the best indices. In terms of modeling approaches, non-linear statistical models were as competent as more advanced ML models for predicting out-of-sample summer mortality. This research validated the current use of non-linear statistical models with the appropriate lagged temperature index to model the heat-mortality relationship. Although ML models have not improved the performance of all-cause mortality modeling, these approaches should continue to be explored, particularly for other health effects that may be more directly linked to heat exposure and, in the future, when more data become available.

Disparities of Heatwave-Related Preterm Birth in Climate Types - China, 2012-2019

What is already known about this topic?

An association between prenatal heatwave exposure and the risk of preterm birth was found. However, the disparities in heatwave-related preterm birth across different climate types have not been examined.

What is added by this report?

This nationwide case-crossover study investigated the association between heatwave exposure and preterm birth across different Köppen-Geiger climate types. Among pregnant women residing in the arid-desert-cold climate type, exposure to compound heatwaves was found to be associated with a significantly higher risk of preterm birth {adjusted odds ratios (AORs) ranged from 1.55 [95% confidence interval ( CI): 1.21-1.97] to 2.11 (95% CI: 1.35-3.31)}. In contrast, among pregnant women residing in the tropical monsoonal climate type, exposure to daytime-only heatwaves was associated with an increased risk of preterm birth [AORs ranged from 1.25 (95% CI: 1.03-1.51) to 1.37 (95% CI: 1.05-1.77)].

What are the implications for public health practice?

Specific interventions should be implemented in China to mitigate the risk of preterm birth related to heatwaves, particularly for pregnant women residing in arid-desert-cold and tropical monsoonal climates.

Development and validation of a prognostic model of survival for classic heatstroke patients: a multicenter study

Classic heatstroke (CHS) is a life-threatening illness characterized by extreme hyperthermia, dysfunction of the central nervous system and multiorgan failure. Accurate predictive models are useful in the treatment decision-making process and risk stratification. This study was to develop and externally validate a prediction model of survival for hospitalized patients with CHS. In this retrospective study, we enrolled patients with CHS who were hospitalized from June 2022 to September 2022 at 3 hospitals in Southwest Sichuan (training cohort) and 1 hospital in Central Sichuan (external validation cohort). Prognostic factors were identified utilizing least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis in the training cohort. A predictive model was developed based on identified prognostic factors, and a nomogram was built for visualization. The areas under the receiver operator characteristic (ROC) curves (AUCs) and the calibration curve were utilized to assess the prognostic performance of the model in both the training and external validation cohorts. The Kaplan‒Meier method was used to calculate survival rates. A total of 225 patients (median age, 74 [68-80] years) were included. Social isolation, self-care ability, comorbidities, body temperature, heart rate, Glasgow Coma Scale (GCS), procalcitonin (PCT), aspartate aminotransferase (AST) and diarrhea were found to have a significant or near-significant association with worse prognosis among hospitalized CHS patients. The AUCs of the model in the training and validation cohorts were 0.994 (95% [CI], 0.975-0.999) and 0.901 (95% [CI], 0.769-0.968), respectively. The model's prediction and actual observation demonstrated strong concordance on the calibration curve regarding 7-day survival probability. According to K‒M survival plots, there were significant differences in survival between the low-risk and high-risk groups in the training and external validation cohorts. We designed and externally validated a prognostic prediction model for CHS. This model has promising predictive performance and could be applied in clinical practice for managing patients with CHS.

Disparities in preterm birth following the July 1995 Chicago heat wave

PURPOSE

To evaluate if changes in preterm birth (PTB, <37 weeks of gestation) incidence differed between non-Hispanic (NH) Black and NH white births following the July 1995 Chicago heat wave-among the most severe U.S. heat waves since 1950.

METHODS

We used an ecologic study design. We obtained birth data from January 1990-December 1996 from the National Vital Statistics File to calculate the mean monthly PTB incidence in Chicago's Cook County, Illinois. Births between July 1995 and February 1996 were potentially exposed to the heat wave in utero. We generated time series models for NH Black and NH white births, which incorporated synthetic controls of Cook County based on unexposed counties. We ran a secondary analysis considering socioeconomic status (SES).

RESULTS

From 1990-1996, the mean monthly PTB incidence among NH Black births was 18.6% compared to 7.8% among NH white births. The mean monthly PTB incidence among NH Black births from August 1995-January 1996 was 16.7% higher than expected (three additional PTBs per 100 live births per month [95% confidence interval (CI): 1, 5]). A similar increase occurred among low-SES NH Black births. No increase appeared among NH white births.

CONCLUSIONS

Severe heat waves may increase racial disparities in PTB incidence.

The Impact of Heat Waves on Health Care Services in Low- or Middle-Income Countries: Protocol for a Systematic Review

BACKGROUND

Heat waves significantly impact ecosystems and human health, especially that of vulnerable populations, and are associated with increased morbidity and mortality. Besides being directly related to climate-sensitive health outcomes, heat waves have indirectly increased the burden on our health care systems. Although the existing literature examines the impact of heat waves and morbidity, past research has mostly been conducted in high-income countries (HICs), and studies on the impact of heat waves on morbidity in low- or middle-income countries (LMICs) are still scarce.

OBJECTIVE

This paper presents the protocol for a systematic review that aims to provide evidence of the impact of heat waves on health care services in LMICs.

METHODS

We will identify peer-reviewed studies from 3 online databases, including the Web of Science, PubMed, and SCOPUS, published from January 2002 to April 2023, using the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines. Quality assessment will be conducted using the Navigation Guide checklist. Key search terms include heatwaves, extreme heat, hospitalization, outpatient visit, burden, health services, and morbidity.

RESULTS

This systematic review will provide insight into the impact of heat waves on health care services in LMICs, especially on emergency department visits, ambulance call-outs, hospital admissions, outpatient department visits, in-hospital mortality, and health care operational costs.

CONCLUSIONS

The results of this review are anticipated to help policymakers and key stakeholders obtain a better understanding of the impact of heat waves on health care services and prioritize investments to mitigate the effects of heat waves in LMICs. This entails creating a comprehensive heat wave plan and ensuring that adequate infrastructure, capacity, and human resources are allocated in the health care sector. These measures will undoubtedly contribute to the development of resilience in health care systems and hence protect the health and well-being of individuals and communities.

TRIAL REGISTRATION

PROSPERO CRD42022365471; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=365471.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/44702.

Extreme Temperature Exposure and Risks of Preterm Birth Subtypes Based on a Nationwide Survey in China

BACKGROUND

Previous studies have reported that ambient temperature may affect perinatal outcomes. However, whether extreme temperature affects the risk of preterm birth (PTB) remains controversial. Studies on the associations of extreme temperature with PTB subtypes are lacking.

OBJECTIVES

We aimed to investigate the associations of extreme climate events with the risks of PTB and its subtypes, discerning possible modifiers.

METHODS

Data on all singleton deliveries were obtained from the China Labor and Delivery Survey (CLDS), a nationwide investigation implemented in 2015 and 2016. PTB was defined as gestational weeks < 37 and then categorized as early (24-34 wk) and late PTBs (35-36 wk), and clinical subtypes [spontaneous PTB, preterm premature rupture of the fetal membranes (PPROM), iatrogenic PTB]. Ambient temperature data were provided by the China National Weather Data Sharing System. Five heat indexes and five cold indexes were used to define heat waves and cold spells. Generalized linear mixed models with a random term by hospital unit were used to assess the associations of short-term prenatal extreme temperature exposure. The Cox proportional hazard regression model was applied to assess the nonlinear associations of low- or high-temperature exposure at the whole and different trimesters of pregnancy with the risk of PTB. Stratified analyses were conducted to assess the possible modification by geographic region and fetal sex.

RESULTS

A total of 70,818 singleton births from 96 hospitals in China were included, among which 4,965 (7.01%) were PTBs. Exposure to extreme cold events 1 wk before delivery was associated with an increased PTB risk, with an adjusted odds ratio (aOR) [95% confidence intervals (CIs)] of 1.07 (95% CI: 1.04, 1.10) and 1.06 (1.04, 1.09) for the total days when the daily average temperature below the fifth percentile (fifth-days) and the 10th percentile (10th-days), 1.18 (1.04, 1.34) for the cold spells when the daily average temperature below the fifth percentile for two consecutive days (fifth-2D), 1.09 (1.03, 1.16) and 1.12 (1.06, 1.19) for the cold spells when the daily average temperature below the 10th percentile for three and two consecutive days (10th-3D and 10th-2D), respectively. Results of extreme temperature exposure during 2 weeks before delivery showed similarly significant associations. The association between cold spells and PTB tended to be stronger for late PTB than for early PTB. Cold spells were mainly associated with spontaneous PTB and late PPROM. A stratified analysis indicated that pregnant women in western and northern regions tended to be more sensitive to cold spells, and pregnant women with a female fetus appeared to be at a higher risk of PTB when exposed to cold spells. Pregnant women in late pregnancy were more susceptible to extreme temperatures. No significant or stable association was found between heat waves and preterm birth.

DISCUSSION

Exposure to cold spells was associated with an increased risk of PTB, especially late, spontaneous PTB and PPROM. The associations appeared to be more pronounced in the north and west regions and in pregnancies with female fetuses. https://doi.org/10.1289/EHP10831.

Exploration of the preterm birth risk-related heat event thresholds for pregnant women: a population-based cohort study in China

Background

Heat events increase the risk of preterm birth (PTB), and identifying the risk-related event thresholds contributes to developing early warning system for pregnant women and guiding their public health response. However, the event thresholds that cause the risk remain unclear. We aimed to investigate the effects of heat events defined with different intensities and durations on PTB throughout pregnancy, and to determine thresholds for the high-risk heat events.

Methods

Using a population-based birth cohort data, we included 210,798 singleton live births in eight provinces in China during 2014-2018. Daily meteorological variables and inverse distance weighted methods were used to estimate exposures at a resolution of 1 km × 1 km. A series of cut off temperature intensities (50th-97.5th percentiles, or 18 °C-35 °C) and durations (at least 1, 2, 3, 4 or 5 consecutive days) were used to define the heat events. Cox regression models were used to estimate the effects of heat events on PTB in various gestational weeks during the entire pregnancy, and event thresholds were determined by calculating population attributable fractions.

Findings

The hazard ratios of heat event exposure on PTB ranged from 1.07 (95% CI: 1.00, 1.13) to 1.43 (1.15, 1.77). Adverse effects of heat event exposure were prominently detected in gestational week 1-4, week 21-32 and the four weeks before delivery. The heat event thresholds were determined to be daily maximum temperature at the 90th percentile of the distribution or 30 °C lasting for at least one day. If pregnant women were able to avoid the heat exposures from the early warning systems triggered by these thresholds, approximately 15% or 17% of the number of total PTB cases could have been avoided.

Interpretation

Exposure to heat event can increase the risk of PTB when thermal event exceeds a specific intensity and duration threshold, particularly in the first four gestational weeks, and between week 21 and the last four weeks. This study provides compelling evidence for the development of heat-health early warning systems for pregnant women that could substantially mitigate the risk of PTB.

Funding

National Key R&D Program of China (No. 2018YFA0606200), National Natural Science Foundation of China (No. 42175183), Sanming Project of Medicine in Shenzhen (No. SZSM202111001).

Association of Daytime-Only, Nighttime-Only, and Compound Heat Waves With Preterm Birth by Urban-Rural Area and Regional Socioeconomic Status in China

Importance

Associations between heat waves and preterm birth (PTB) have been reported. However, associations of daytime-only, nighttime-only, and compound heat waves with PTB have yet to be explored at a national level. Furthermore, possible heterogeneity across urban-rural communities with different socioeconomic statuses needs to be explored.

Objective

To examine the association between daytime-only, nighttime-only, and compound heat waves and PTB in China and to find variations between urban and rural regions.

Design, Setting, and Participants

This case-crossover study used nationwide representative birth data between January 1, 2012, and December 31, 2019, from China's National Maternal Near Miss Surveillance System. This multisite study covered 30 provinces in China and ensured the representation of urban and rural populations across 3 socioeconomic regions. Singleton live births delivered in the warm seasons from April to October during the study period were included. Exclusion criteria consisted of gestational age younger than 20 or older than 45 weeks, maternal ages younger than 13 or older than 50 years, conception dates earlier than 20 weeks before January 1, 2012, and later than 45 weeks before December 31, 2019, and an inconsistent combination of birthweight and gestational age according to growth standard curves of Chinese newborns. Data were analyzed from September 10, 2021, to April 25, 2023.

Exposures

Eighteen definitions of heat waves by 3 distinct types, including daytime only (only daily maximum temperature exceeds thresholds), nighttime only (only daily minimum temperature exceeds thresholds), and compound (both daily maximum and minimum temperature exceeds thresholds) heat waves, and 6 indexes, including 75th percentile of daily temperature thresholds for 2 or more (75th-D2), 3 or more (75th-D3), or 4 or more (75th-D4) consecutive days and 90th percentile of daily temperature thresholds for 2 or more (90th-D2), 3 or more (90th-D3), and 4 or more (90th-D4) consecutive days.

Main Outcomes and Measures

Preterm births with less than 37 completed weeks of gestation.

Results

Among the 5 446 088 singleton births in the final analytic sample (maternal mean [SD] age, 28.8 [4.8] years), 310 384 were PTBs (maternal mean [SD] age, 29.5 [5.5] years). Compared with unexposed women, exposure of pregnant women to compound heat waves in the last week before delivery was associated with higher risk for PTB, with the adjusted odds ratios (AORs) ranging from 1.02 (95% CI, 1.00-1.03) to 1.04 (95% CI, 1.01-1.07) in 6 indexes. For daytime-only heat wave exposures, AORs ranged from 1.03 (95% CI, 1.01-1.05) to 1.04 (95% CI, 1.01-1.08) in the 75th-D4, 90th-D2, 90th-D3, and 90th-D4 indexes. Such associations varied by rural (AOR range, 1.05 [95% CI, 1.01-1.09] to 1.09 [95% CI, 1.04-1.14]) and urban (AOR range, 1.00 [95% CI, 0.98-1.02] to 1.01 [95% CI, 0.99-1.04]) regions during exposure to daytime-only heat waves in the 75th-D3 and 90th-D3 indexes.

Conclusions and Relevance

In this case-crossover study, exposure to compound and daytime-only heat waves in the last week before delivery were associated with PTB, particularly for pregnant women in rural regions exposed to daytime-only heat waves. These findings suggest that tailored urban-rural preventive measures may improve maternal health in the context of climate change.

Optimal heat stress metric for modelling heat-related mortality varies from country to country

Combined heat and humidity is frequently described as the main driver of human heat-related mortality, more so than dry-bulb temperature alone. While based on physiological thinking, this assumption has not been robustly supported by epidemiological evidence. By performing the first systematic comparison of eight heat stress metrics (i.e., temperature combined with humidity and other climate variables) with warm-season mortality, in 604 locations over 39 countries, we find that the optimal metric for modelling mortality varies from country to country. Temperature metrics with no or little humidity modification associates best with mortality in ~40% of the studied countries. Apparent temperature (combined temperature, humidity and wind speed) dominates in another 40% of countries. There is no obvious climate grouping in these results. We recommend, where possible, that researchers use the optimal metric for each country. However, dry-bulb temperature performs similarly to humidity-based heat stress metrics in estimating heat-related mortality in present-day climate.

The impact of cold waves and heat waves on mortality: Evidence from a lower middle-income country

We estimate the impact of temperature extremes on mortality in Vietnam, using daily data on temperatures and monthly data on mortality during the 2000-2018 period. We find that both cold and heat waves cause higher mortality, particularly among older people and those living in the hot regions in Southern Vietnam. This effect on mortality tends to be smaller in provinces with higher rates of air-conditioning and emigration, and provinces with higher public spending on health. Finally, we estimate economic cost of cold and heat waves using a framework of willingness to pay to avoid deaths, then project the cost to the year 2100 under different Representative Concentration Pathway scenarios.

A Comprehensive Review on Hot Ambient Temperature and its Impacts on Adverse Pregnancy Outcomes

INTRODUCTION

High workplace/ambient temperatures have been associated with Adverse Pregnancy Outcomes (APO). Millions of women working in developing nations suffer due to the rising temperatures caused by climate change. There are few pieces of research linking occupational heat stress to APO, and fresh evidence is required.

METHODOLOGY

We used databases including PubMed, Google Scholar, and Science Direct to search for research on high ambient/workplace temperatures and their effects. Original articles, newsletters, and book chapters were examined. The literature we analysed was categorised as follows: Heat, strain, and physical activity harming both mother and fetus. After categorising the literature, it was examined to identify the major results.

RESULTS

We found a definite association between heat stress and APOs such as miscarriages, premature birth, stillbirth, low birthweight, and congenital abnormalities in 23 research articles. Our work provides important information for future research into the biological mechanisms that create APOs and various prevention measures.

CONCLUSION

Our data suggest that temperature has long-term and short-term effects on maternal and fetal health. Though small in number, this study stressed the need for bigger cohort studies in tropical developing countries to create evidence for coordinated policies to safeguard pregnant women.

Ambient Air Pollution and All-Cause and Cause-Specific Mortality in an Analysis of Asian Cohorts

INTRODUCTION

Much of what is currently known about the adverse effects of ambient air pollution comes from studies conducted in high-income regions, with relatively low air pollution levels. The aim of the current project is to examine the relationship between exposure to ambient air pollution (as predicted from satellite-based models) and all-cause and cause-specific mortality in several Asian cohorts.

METHODS

Cohorts were recruited from the Asia Cohort Consortium (ACC). The geocoded residences of participants were assigned levels of ambient particulate material with aerodynamic diameter of 2.5 μm or less (PM2.5) and nitrogen dioxide (NO2) utilizing global satellite-derived models and assigned for the year of enrollment (or closest available year). The association between ambient exposure and mortality was established with Cox proportional hazard models, after adjustment for common confounders. Both single- and two-pollutant models were generated. Model robustness was evaluated, and hazard ratios were calculated for each cohort separately and combined via random effect meta-analysis for pooled risk estimates.

RESULTS

Six cohort studies from the ACC participated: the Community-based Cancer Screening Program (CBCSCP, Taiwan), the Golestan Cohort Study (Iran), the Health Effects for Arsenic Longitudinal Study (HEALS, Bangladesh), the Japan Public Health Center-based Prospective Study (JPHC), the Korean Multi-center Cancer Cohort Study (KMCC), and the Mumbai Cohort Study (MCS, India). The cohorts represented over 340,000 participants.

Mean exposures to PM2.5 ranged from 8 to 58 μg/m3. Mean exposures to NO2 ranged from 7 to 23 ppb. For PM2.5, a positive, borderline nonsignificant relationship was observed between PM2.5 and cardiovascular mortality. Other relationships with PM2.5 tended toward the null in meta-analysis. For NO2, an overall positive relationship was observed between exposure to NO2 and all cancers and lung cancer. A borderline association between NO2 and nonmalignant lung disease was also observed. The findings within individual cohorts remained consistent across a variety of subgroups and alternative analyses, including two-pollutant models.

CONCLUSIONS

In a pooled examination of cohort studies across Asia, ambient PM2.5 exposure appears to be associated with an increased risk of cardiovascular mortality and ambient NO2 exposure is associated with an increased cancer (and lung cancer) mortality. This project has shown that satellite-derived models of pollution can be used in examinations of mortality risk in areas with either incomplete or missing air pollution monitoring.

Heatwave and urinary hospital admissions in China: Disease burden and associated economic loss, 2014 to 2019

BACKGROUND

Many studies have shown that heatwaves are associated with an increased prevalence of urinary diseases. However, few national studies have been undertaken in China, and none have considered the associated economic losses. Such information would be useful for health authorities and medical service providers to improve their policy-making and medical resource allocation decisions.

OBJECTIVES

To explore the association between heatwaves and hospital admissions for urinary diseases and assess the related medical costs and indirect economic losses in China from 2014 to 2019.

METHODS

Daily meteorological and hospital admission data from 2014 to 2019 were collected from 23 study sites with different climatic characteristics in China. We assessed the heatwave-hospitalization associations and evaluated the location-specific attributable fractions (AFs) of urinary-related hospital admissions due to heatwaves by using a time-stratified case-crossover method with a distributed lag nonlinear model. We then pooled the AFs in a meta-analysis and estimated the national excess disease burden and associated economic losses. We also performed stratified analyses by sex, age, climate zone, and urinary disease subtype.

RESULTS

A significant association between heatwaves and urinary-related hospital admissions was found with a relative risk of 1.090 (95 % confidence interval (CI): 1.050, 1.132). The pooled AF was 8.27 % (95%CI: 4.77 %, 11.63 %), indicating that heatwaves during the warm season (May to September) caused 248,364 urinary-related hospital admissions per year, with 2.42 (95%CI: 1.35, 3.45) billion CNY in economic losses, including 2.23 (95%CI: 1.29, 3.14) billion in direct losses and 0.19 (95%CI, 0.06, 0.31) billion in indirect losses, males, people aged 15-64 years, residents of temperate continental climate zones, and patients with urolithiasis were at higher risk.

CONCLUSION

Tailored community health campaigns should be developed and implemented to reduce the adverse health effects and economic losses of heatwave-related urinary diseases, especially in the context of climate change.

Does the meteorological origin of heat waves influence their impact on health? A 6-year morbidity and mortality study in Madrid (Spain)

BACKGROUND

In Spain, two synoptic-scale conditions influence heat wave formation. The first involves advection of warm and dry air masses carrying dust of Saharan origin (North African Dust (NAF) = 1). The second entails anticyclonic stagnation with high insolation and stability (NAF) = 0). Some studies show that the meteorological origin of these heat waves may affect their impact on morbidity and mortality.

OBJECTIVE

To determine whether the impact of heat waves on health outcomes in Madrid (Spain) during 2013-2018 varied by synoptic-scale condition.

METHODOLOGY

Outcome data consist of daily mortality and daily hospital emergency admissions (morbidity) for natural, circulatory, and respiratory causes. Predictors include daily maximum and minimum temperatures and daily mean concentrations of NO₂, PM₁₀, PM_2.5, NO₂, and O₃. Analyses adjust for insolation, relative humidity, and wind speed. Generalized linear models were performed with Poisson link between the variables controlling for trend, seasonality, and auto-regression in the series. Relative Risks (RR) and Attributable Risks (AR) were determined. The RRs for mortality attributable to high temperatures were similar regardless of NAF status. For hospital admissions, however, the RRs for hot days with NAF = 0 are higher than for days with NAF = 1. We also found that atmospheric pollutants worsen morbidity and mortality, especially PM₁₀ concentrations when NAF = 1 and O₃ concentrations when NAF = 0.

RESULTS

The effect of heat waves on morbidity and mortality depends on the synoptic situation. The impact is greater under anticyclonic stagnation conditions than under Saharan dust advection. Further, the health impact of pollutants such as PM₁₀ and O₃ varies according to the synoptic situation.

CONCLUSIONS

Based on these findings, we strongly recommend prevention plans to include data on the meteorological situation originating the heat wave, on a synoptic-scale, as well as comprehensive preventive measures against the compounding effect of high temperatures and pollution.

Comparison of various heat waves definitions and the burden of heat-related mortality in France: Implications for existing early warning systems

INTRODUCTION

In France, a heat warning system (HWS) has been implemented almost two decades ago and rely on some official heat wave (HW) definitions. However, no study has compared the burden associated with a large set of alternative HW definitions to the official definitions. Such comparison could be particularly helpful to identify HW conditions for which effective HWS would minimize the health burden across various geographical contexts and possibly update thresholds to trigger HWS. The aim of this study is to identify (and rank) definitions that drive the highest health burden in terms of mortality to inform future HWS across multiple cities in France.

METHODS

Based on weather data for 16 French cities, we compared the two official definitions used in France to: i) the Excess Heat Factor (EHF) used in Australia, and ii) 18 alternative hypothetical HW definitions based on various combinations of temperature metrics, intensity, and duration. Propensity score matching and Poisson regressions were used to estimate the effect of each HW exposure on non-accidental mortality for the May-September period from 2000 to 2015.

RESULTS

The associations between HW and mortality differed greatly depending on the definition. The greatest burden of heat was 1,055 (95% confidence interval "CI": [856; 1,302]) deaths per summer and was obtained with the EHF. The EHF identified HW with 2.46 (95% CI: [1.92; 3.58]) or 8.18 (95% CI: [6.63; 10.61]) times the global burden at the national level obtained with the climatological indicator of the French national weather service and the HW indicator of the French national HWS, respectively and was the most impactful definition pattern for both temperate oceanic and Mediterranean climate types.

CONCLUSION

Identifying the set of extreme heat conditions that drive the highest health burden in a given geographical context is particularly helpful when designing or updating heat early warning systems.

Systematic identification of heat events associated with emergency admissions to enhance the heat-health action plan in a subtropical city: a data-driven approach

According to the United Nations Office for Disaster Risk Reduction (UNDRR), a heat-health action plan should address various impacts of hazards at different levels, including an early warning system to monitor risks and behaviour enhancement to increase disaster preparedness. It is necessary to comply with guidelines regarding heat duration/intensity. In this study, we developed a data-driven approach to rapidly and systematically estimate the impacts of various heat events on emergency admissions among the adult population (n = 7,086,966) in Hong Kong in order to enhance the heat-health action plan. Immediate, short-term, and long-term impacts determined by 1-day, 4-day, and 8-day windows were estimated to identify specific heat events suitable for early warnings. In addition, underestimated risk, determined by a continuous increase in heat risk after days without significant emergency admissions, was estimated to evaluate potential maladaptive behaviours among a specific subpopulation. Based on age- and gender-specific analyses, 1D, 1D1N, and 2D2N were observed to have a stronger immediate impact on emergency admissions. 1D1N and 2D2N also showed notable short-term and long-term impacts. Based on heat vulnerability factors (age and gender), 2D2N was a higher-priority extreme heat event for early warning measures than 1D1N. Furthermore, men aged 19 to 64 had the highest underestimated risk. Specifically, they had IRR values of 1.113 [1.087, 1.140], 1.061 [1.035, 1.087], and 1.069 [1.043, 1.095] during lag days 3-5 of 3D2N, respectively, possibly due to a lack of adaptive behaviour. By adopting our approach, the duration of heat events with significant health impacts can be identified in order to further enhance relevant heat stress information. This framework can be applied to other cities with a similar background for rapid assessment.

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.

Extreme environmental temperatures and motorcycle crashes: a time-series analysis

Extreme temperature could affect traffic crashes by influencing road safety, vehicle performance, and drivers' behavior and abilities. Studies evaluating the impacts of extreme temperatures on the risk of traffic crashes have mainly overlooked the potential role of vehicle air conditioners. The aim of this study, therefore, was to evaluate the effect of exposure to extreme cold and hot temperatures on seeking medical attention due to motorcycle crashes. The study was conducted in Iran by using medical attendance for motorcycle crashes from March 2011 to June 2017. Data on daily minimum, mean and maximum temperature (°C), relative humidity (%), wind velocity (km/h), and precipitation (mm/day) were collected. We developed semi-parametric generalized additive models following a quasi-Poisson distribution with the distributed nonlinear lag model to estimate the immediate and lagged associations (reported as relative risk [RR], and 95% confidence interval [CI]). Between March 2011 and June 2017, 36,079 medical attendances due to motorcycle road traffic crashes were recorded (15.8 ± 5.92 victims per day). In this time period, the recorded temperature ranged from -11.2 to 45.4 °C (average: 25.5 ± 11.0 °C). We found an increased risk of medical attendance for motorcycle crashes (based on maximum daily temperature) at both extremely cold (1st percentile) and hot (99th percentile) temperatures and also hot (75th percentile) temperatures, mainly during lags 0 to 3 days (e.g., RR: 1.12 [95% CI: 1.05: 1.20]; RR: 1.08 [95% CI: 1.01: 1.16]; RR: 1.20 [95% CI: 1.09: 1.32] at lag0 for extremely cold, hot, and extremely hot conditions, respectively). The risk estimates for extremely hot temperatures were larger than hot and extremely cold temperatures. We estimated that 11.01% (95% CI: 7.77:14.06) of the medical attendance for motorcycle crashes is estimated to be attributable to non-optimal temperature (using mean temperature as exposure variable). Our findings have important public health messaging, given the considerable burden associated with road traffic injury, particularly in low- and middle-income countries.

Compound Risk of Air Pollution and Heat Days and the Influence of Wildfire by SES across California, 2018-2020: Implications for Environmental Justice in the Context of Climate Change

Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018-2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 μg/m3 showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.

Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions

Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011−2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.

Knowledge Gaps and Research Priorities on the Health Effects of Heatwaves: A Systematic Review of Reviews

Although extreme weather events have played a constant role in human history, heatwaves (HWs) have become more frequent and intense in the past decades, causing concern especially in light of the increasing evidence on climate change. Despite the increasing number of reviews suggesting a relationship between heat and health, these reviews focus primarily on mortality, neglecting other important aspects. This systematic review of reviews gathered the available evidence from research syntheses conducted on HWs and health. Following the PRISMA guidelines, 2232 records were retrieved, and 283 reviews were ultimately included. Information was extracted from the papers and categorized by topics. Quantitative data were extracted from meta-analyses and, when not available, evidence was collected from systematic reviews. Overall, 187 reviews were non-systematic, while 96 were systematic, of which 27 performed a meta-analysis. The majority evaluated mortality, morbidity, or vulnerability, while the other topics were scarcely addressed. The following main knowledge gaps were identified: lack of a universally accepted definition of HW; scarce evidence on the HW-mental health relationship; no meta-analyses assessing the risk perception of HWs; scarcity of studies evaluating the efficacy of adaptation strategies and interventions. Future efforts should meet these priorities to provide high-quality evidence to stakeholders.

Impact of low-intensity heat events on mortality and morbidity in regions with hot, humid summers: a scoping literature review

The objective of this study is to determine the impacts of low-intensity heat on human health in regions with hot, humid summers. Current literature has highlighted an increase in mortality and morbidity rates during significant heat events. While the impacts on high-intensity events are established, the impacts on low-intensity events, particularly in regions with hot, humid summers, are less clear. A scoping review was conducted searching three databases (PubMed, EMBASE, Web of Science) using key terms based on the inclusion criteria. We included papers that investigated the direct human health impacts of low-intensity heat events (single day or heatwaves) in regions with hot, humid summers in middle- and high-income countries. We excluded papers written in languages other than English. Of the 600 publications identified, 33 met the inclusion criteria. Findings suggest that low-intensity heatwaves can increase all-cause non-accidental, cardiovascular-, respiratory- and diabetes-related mortality, in regions experiencing hot, humid summers. Impacts of low-intensity heatwaves on morbidity are less clear, with research predominantly focusing on hospitalisation rates with a range of outcomes. Few studies investigating the impact of low-intensity heat events on emergency department presentations and ambulance dispatches were found. However, the data from a limited number of studies suggest that both of these outcome measures increase during low-intensity heat events. Low-intensity heat events may increase mortality. There is insufficient evidence of a causal effect of low-intensity heat events on increasing morbidity for a firm conclusion. Further research on the impact of low-intensity heat on morbidity and mortality using consistent parameters is warranted.

Interactive effects of cold spell and air pollution on outpatient visits for anxiety in three subtropical Chinese cities

BACKGROUND

Although low temperature and air pollution exposures have been associated with the risk of anxiety, their combined effects remain unclear.

OBJECTIVE

To investigate the independent and interactive effects of low temperature and air pollution exposures on anxiety.

METHOD

Using a case-crossover study design, the authors collected data from 101,636 outpatient visits due to anxiety in three subtropical Chinese cities during the cold season (November to April in 2013 through 2018), and then built conditional logistic regression models based on individual exposure assessments [temperature, relative humidity, particulate matter (PM_2.5, PM₁₀), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂)] and twelve cold spell definitions. Additive-scale interactions were assessed using the relative excess risk due to interaction (RERI).

RESULTS

Both cold spell and air pollution were significantly associated with outpatients for anxiety. The effects of cold spell increased with its intensity, ranging from 8.98% (95% CI: 2.02%, 16.41%) to 15.24% (95% CI: 6.75%, 24.39%) in Huizhou. Additionally, each 10 μg/m³ increase of PM_2.5, PM₁₀, NO₂ and SO₂ was associated with a 1.51% (95% CI: 0.61%, 2.43%), 1.58% (95% CI: 0.89%, 2.28%), 13.95% (9.98%, 18.05%) and 11.84% (95% CI: 8.25%, 15.55%) increase in outpatient visits for anxiety. Synergistic interactions (RERI >0) of cold spell with all four air pollutants on anxiety were observed, especially for more intense cold spells. For particulate matters, these interactions were found even under mild cold spell definitions [RERI: 0.11 (95% CI: 0.02, 0.21) for PM_2.5, and 0.24 (95% CI: 0.14, 0.33) for PM₁₀]. Stratified analyses yielded a pronounced results in people aged 18-65 years.

CONCLUSIONS

These findings indicate that both cold spell and air pollution are important drivers of the occurrence of anxiety, and simultaneous exposure to these two factors might have synergistic effects on anxiety. These findings highlight the importance of controlling air pollution and improving cold-warning systems.

Extreme Heat and Pregnancy Outcomes: A Scoping Review of the Epidemiological Evidence

Background: Extreme heat caused by climate change is a major public health concern, disproportionately affecting poor and racialized communities. Gestational heat exposure is a well-established teratogen in animal studies, with a growing body of literature suggesting human pregnancies are similarly at risk. Characterization of extreme heat as a pregnancy risk is problematic due to nonstandard definitions of heat waves, and variable study designs. To better focus future research in this area, we conducted a scoping review to assess the effects of extreme heat on pregnancy outcomes. Methods: A scoping review of epidemiological studies investigating gestational heat-exposure and published 2010 and 2020, was conducted with an emphasis on study design, gestational windows of sensitivity, adverse pregnancy outcomes and characterization of environmental temperatures. Results: A sample of 84 studies was identified, predominantly set in high-income countries. Preterm birth, birthweight, congenital anomalies and stillbirth were the most common pregnancy outcome variables. Studies reported race/ethnicity and/or socioeconomic variables, however these were not always emphasized in the analysis. Conclusion: Use of precise temperature data by most studies avoided pitfalls of imprecise, regional definitions of heat waves, however inconsistent study design, and exposure windows are a significant challenge to systematic evaluation of this literature. Despite the high risk of extreme heat events and limited mitigation strategies in the global south, there is a significant gap in the epidemiological literature from these regions. Greater consistency in study design and exposure windows would enhance the rigor of this field.

The Role of Temperature in Modifying the Risk of Ozone-Attributable Mortality under Future Changes in Climate: A Proof-of-Concept Analysis

Air pollution risk assessments typically estimate ozone-attributable mortality counts using concentration-response (C-R) parameters from epidemiologic studies that treat temperature as a potential confounder. However, some recent epidemiologic studies have indicated that temperature can modify the relationship between short-term ozone exposure and mortality, which has potentially important implications when considering the impacts of climate change on public health. This proof-of-concept analysis quantifies counts of temperature-modified ozone-attributable mortality using temperature-stratified C-R parameters from a multicity study in which the pooled ozone-mortality effect coefficients change in concert with daily temperature. Meteorology downscaled from two global climate models is used with a photochemical transport model to simulate ozone concentrations over the 21st century using two emission inventories: one holding air pollutant emissions constant at 2011 levels and another accounting for reduced emissions through the year 2040. The late century climate models project increased summer season temperatures, which in turn yields larger total counts of ozone-attributable deaths in analyses using temperature-stratified C-R parameters compared to the traditional temperature confounder approach. This analysis reveals substantial heterogeneity in the magnitude and distribution of the temperature-stratified ozone-attributable mortality results, which is a function of regional variability in both the C-R relationship and the model-predicted temperature and ozone.

Retrospection of heatwave and heat index

The frequency and intensity of extreme events especially heat waves (HW) are growing all around the world which ultimately poses a serious threat to the health of individuals. To quantify the effects of extreme temperature, appropriate information, and the importance of HW and heat index (HI) are carefully discussed for different parts of the world. Varied definitions of the HW and HI formula proposed and used by different countries are carried out systematically continent-wise. Different studies highlighted the number of definitions of HW; however, mostly used Steadman's formulae, which was developed in the late 1970s, for the calculation of HI that uses surface air temperature and relative humidity as climatic fields. Since then, dramatic changes in climatic conditions have been observed as evident from the ERA5 datasets which need to be addressed; likewise, the definition of HW, which is modified by the researchers as per the geographic conditions. It is evident from the ERA5 data that the temperature has increased by 1-2 °C as compared to the 1980s. There is a threefold increase in the number of heatwave days over most of the continents in the last 40 years. This study will help the researcher community to understand the importance of HW and HI. Furthermore, it opens the scope to develop an equation based on the present scenario keeping in mind the basics of an index as considered by Steadman.

The association between drought conditions and increased occupational psychosocial stress among U.S. farmers: An occupational cohort study

BACKGROUND

Drought represents a globally relevant natural disaster linked to adverse health. Evidence has shown agricultural communities to be particularly susceptible to drought, but there is a limited understanding of how drought may impact occupational stress in farmers.

METHODS

We used repeated measures data collected in the Musculoskeletal Symptoms among Agricultural Workers Cohort study, including 498 Midwestern U.S. farmers surveyed with a Job Content Questionnaire (JCQ) at six-month intervals in 312 counties from 2012 through 2015. A longitudinal linear mixed effects model was used to estimate the change in job strain ratio, a continuous metric of occupational psychosocial stress, during drought conditions measured with a 12-month standardized precipitation index. We further evaluated associations between drought and psychological job demand and job decision latitude, the job strain components, and applied a stratified analysis to evaluate differences by participant sex, age, and geography.

RESULTS

During the growing season, the job strain ratio increased by 0.031 (95% CI: 0.012, 0.05) during drought conditions, an amount equivalent to a one-half standard deviation change (Cohen's D = 0.5), compared to non-drought conditions. The association between drought and the job strain ratio was driven mostly by increases in the psychological job demand (2.09; 95% CI: 0.94, 3.24). No risk differences were observed by sex, age group, or geographic region.

CONCLUSIONS

Our results suggest a previously unidentified association between drought and increased occupational psychosocial stress among farmers. With North American climate anticipated to become hotter and drier, these findings could provide important health effects data for federal drought early warning systems and mitigation plans.

The risks of warm nights and wet days in the context of climate change: assessing road safety outcomes in Boston, USA and Santo Domingo, Dominican Republic

Background

There remains a dearth of cross-city comparisons on the impact of climate change through extreme temperature and precipitation events on road safety. We examined trends in traffic fatalities, injuries and property damage associated with high temperatures and heavy rains in Boston (USA) and Santo Domingo (Dominican Republic).

Methods

Official publicly available data on daily traffic outcomes and weather conditions during the warm season (May to September) were used for Boston (2002–2015) and Santo Domingo (2013–2017). Daily maximum temperatures and mean precipitations for each city were considered for classifying hot days, warm days, and warm nights, and wet, very wet, and extremely wet days. Time-series analyses were used to assess the relationship between temperature and precipitation and daily traffic outcomes, using a quasi-Poisson regression.

Results

In Santo Domingo, the presence of a warm night increased traffic fatalities with a rate ratio (RR) of 1.31 (95% CI [confidence interval]: 1.00,1.71). In Boston, precipitation factors (particularly, extremely wet days) were associated with increments in traffic injuries (RR 1.25, 95% CI: 1.18, 1.32) and property damages (RR 1.42, 95% CI: 1.33, 1.51).

Conclusion

During the warm season, mixed associations between weather conditions and traffic outcomes were found across Santo Domingo and Boston. In Boston, increases in heavy precipitation events were associated with higher traffic injuries and property damage. As climate change-related heavy precipitation events are projected to increase in the USA, the associations found in this study should be of interest for road safety planning in a rapidly changing environment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40621-021-00342-w.

Using logic regression to characterize extreme heat exposures and their health associations: a time-series study of emergency department visits in Atlanta

Background

Short-term associations between extreme heat events and adverse health outcomes are well-established in epidemiologic studies. However, the use of different exposure definitions across studies has limited our understanding of extreme heat characteristics that are most important for specific health outcomes or subpopulations.

Methods

Logic regression is a statistical learning method for constructing decision trees based on Boolean combinations of binary predictors. We describe how logic regression can be utilized as a data-driven approach to identify extreme heat exposure definitions using health outcome data. We evaluated the performance of the proposed algorithm in a simulation study, as well as in a 20-year time-series analysis of extreme heat and emergency department visits for 12 outcomes in the Atlanta metropolitan area.

Results

For the Atlanta case study, our novel application of logic regression identified extreme heat exposure definitions that were associated with several heat-sensitive disease outcomes (e.g., fluid and electrolyte imbalance, renal diseases, ischemic stroke, and hypertension). Exposures were often characterized by extreme apparent minimum temperature or maximum temperature over multiple days. The simulation study also demonstrated that logic regression can successfully identify exposures of different lags and duration structures when statistical power is sufficient.

Conclusion

Logic regression is a useful tool for identifying important characteristics of extreme heat exposures for adverse health outcomes, which may help improve future heat warning systems and response plans.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01278-x.

Acute associations between heatwaves and preterm and early-term birth in 50 US metropolitan areas: a matched case-control study

BACKGROUND

The effect of heatwaves on adverse birth outcomes is not well understood and may vary by how heatwaves are defined. The study aims to examine acute associations between various heatwave definitions and preterm and early-term birth.

METHODS

Using national vital records from 50 metropolitan statistical areas (MSAs) between 1982 and 1988, singleton preterm (< 37 weeks) and early-term births (37-38 weeks) were matched (1:1) to controls who completed at least 37 weeks or 39 weeks of gestation, respectively. Matching variables were MSA, maternal race, and maternal education. Sixty heatwave definitions including binary indicators for exposure to sustained heat, number of high heat days, and measures of heat intensity (the average degrees over the threshold in the past 7 days) based on the 97.5th percentile of MSA-specific temperature metrics, or the 85th percentile of positive excessive heat factor (EHF) were created. Odds ratios (OR) for heatwave exposures in the week preceding birth (or corresponding gestational week for controls) were estimated using conditional logistic regression adjusting for maternal age, marital status, and seasonality. Effect modification by maternal education, age, race/ethnicity, child sex, and region was assessed.

RESULTS

There were 615,329 preterm and 1,005,576 early-term case-control pairs in the analyses. For most definitions, exposure to heatwaves in the week before delivery was consistently associated with increased odds of early-term birth. Exposure to more high heat days and more degrees above the threshold yielded higher magnitude ORs. For exposure to 3 or more days over the 97.5th percentile of mean temperature in the past week compared to zero days, the OR was 1.027 for early-term birth (95%CI: 1.014, 1.039). Although we generally found null associations when assessing various heatwave definitions and preterm birth, ORs for both preterm and early-term birth were greater in magnitude among Hispanic and non-Hispanic black mothers.

CONCLUSION

Although associations varied across metrics and heatwave definitions, heatwaves were more consistently associated with early-term birth than with preterm birth. This study's findings may have implications for prevention programs targeting vulnerable subgroups as climate change progresses.

Hot under the collar: A 14-year association between temperature and violent behavior across 436 U.S. counties

OBJECTIVES

Violent behavior is influenced by individual and societal characteristics, but the role of environmental factors is less understood. Our aims were to use national-level data to identify the association between criminal behavior and short-term temperature conditions, including the departure of daily temperatures from normal conditions.

METHODS

We conducted a multi-stage hierarchical time-series model across 436 U.S. counties and 14-years representing 100.4 million people to investigate the association between daily mean temperature and daily mean temperatures departing from normal conditions with violent and non-violent crime counts. First-stage comparisons were made within counties to control for population and geographic heterogeneities, while a second stage combined estimates. We evaluated differences in risk based on county sociodemographic characteristics and estimated non-linear exposure-response relationships.

RESULTS

We observed a total of 9.0 million violent crimes and 20.9 million non-violent property crimes between 2000 through 2013. We estimated that each 10 °C increase in daily temperature or daily departure from long-term normal temperatures were associated with 11.92% (95% PI: 11.57, 12.27) and 10.37% (95% PI: 10.05, 10.69) increase in the risk of violent crime, respectively. Similar, but lower in magnitude trends, were observed for property crime risks. We found that crime risk plateaus and decreases at high daily temperatures, but for temperatures departing from normal, the association with crime increased linearly. Seasonal variations showed that anomalously warm temperatures days during cool months had the greatest risk.

CONCLUSIONS

Our study revealed an association between higher temperatures and high departure from normal temperatures with both violent and non-violent crime risk, regardless of community-type. However, our findings on seasonal and daily trends suggest that daily mean temperature may impact crime by affecting routine activities and behavior, as opposed to a temperature-aggression relationship. These results may advance public response and planning to prevent violent behavior.

Intensity-duration-frequency relationship of WBGT extremes using regional frequency analysis in South Korea

The risk levels of heat-related extreme events need to be estimated for prediction and real-time monitoring to mitigate their impacts on air quality, public health, the ecosystem, and critical infrastructure. Many countries have adopted meteorological variable base thresholds for assessing the risk level of heat-related extreme events. These thresholds provide an approximate risk level for a specific event but do not consider its intensity and duration in the risk assessment. The current study provides a statistical tool to assess the risk of heat-related extreme events while concurrently considering their intensities and durations based on the wet-bulb globe temperature (WBGT). To this end, the intensity-duration-frequency (IDF) relationship of the extreme WBGT in South Korea was derived. Regional frequency analysis was employed to understand the IDF relationship. Return levels of heat-related extreme events in South Korea were calculated and their characteristics were investigated based on the annual maximum WBGT observations. The results showed that the IDF relationship could provide the risks of heat-related extreme events while concurrently considering their intensities and durations. The extreme WBGT in South Korea was used to categorize two regions such as coastal and inland based on their statistical characteristics. The return levels of the annual maximum WBGT events were found to vary largely by location. The return levels corresponding to 32 °C with 3-h duration for stations in the coastal and inland regions ranged from 1- to 100-years and 3- to 1000-years, respectively. Mean values of return levels for heatwave events in Seoul, Incheon, Daejon, Gwangju, Daegu, and Busan were 2.8-, 8.4-, 15.3-, 2.8-, 1.6-, and 2.2-years, respectively. The return levels of heatwaves for the warmer cities are smaller than those for cooler cities. The return levels of the heatwave events in South Korea showed a significant increasing trend in several cities, supporting the notion that the impact of heatwave events on South Korea might become more severe in the future.

Examining the joint effects of heatwaves, air pollution, and green space on the risk of preterm birth in California

BACKGROUND

Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy.

OBJECTIVES

To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB.

METHODS

California birth certificate records for singleton births (2005-2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB.

RESULTS

In total, 1,967,300 births were included in this study. For PM2.5, PM10 and O3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e., shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves.

CONCLUSION

This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.

Explicit Spatializing Heat-Exposure Risk and Local Associated Factors by coupling social media data and automatic meteorological station data

Extremely high temperatures, a major cause for weather-related public health issues, are projected to intensify and become more frequent. To mitigate the adverse effects, a low-cost and effective risk assessment method should be developed. Therefore, we applied automatic meteorological station data and population mobility data to develop a high spatiotemporal resolution temperature risk assessment method. The population mobility analysis results showed the working/residential complex pattern in Tianhe District, with hotspots of spatial clustering located in the north, southwest, and southeast of the study area. Taking the population mobility patterns into consideration, high-temperature risk assessment results with a resolution of 100 m were obtained. The total mortality cases in 2014 and 2015 were used to validate this result. The validation showed that the total mortality in the high-temperature risk areas accounted for over 36% of that in Tianhe District. Thus, the method introduced in this study is capable of reflecting weather-related risk. Furthermore, the high-temperature risk assessment results showed that most of the risky areas were located in the southwest of the study area. Two peak times of the risk areas were determined, being before dawn and in the evening. Compared with the risk areas during weekdays, those at weekends expanded. In addition, we used the geographically weighted regression model to investigate the potential influencing factors. Individual factor contributed more than 22.4% to the spatial distribution of heat exposure. Catering services, transportation services, and living services were higher than others, with mean R² values of 0.28, 0.23, and 0.25, respectively. More than 47.9% of spatial distribution of heat exposure was attributed to joint function of influencing factors, with global R² ranged from 0.23 to 0.34. Our research introduces a spatial-specific method to quantitatively assess high-temperature risk. Moreover, the mechanisms behind the spatial distribution of the high-temperature risk were discussed. The theoretical and management implications can help urban designers and energy governors to develop useful strategies to mitigate weather-related public health risks.

Durational effect of particulate matter air pollution wave on hospital admissions for schizophrenia

BACKGROUND

Short-term exposure to high level of ambient particulate matters (PM) concentrations has been linked with increased hospital admissions (HA) for schizophrenia. However, evidence is inconclusive about the added effect of multi-day exposure to high-level PM concentration on schizophrenia. This study aims to evaluate the durational effect of PM air pollution wave on schizophrenia.

METHOD

Data on daily HA for schizophrenia, PM (PM_2.5 and PM₁₀) and meteorological variables over the period of 2014-2017 was collected in Jining, Shandong, China. Air pollution wave of PM was defined as ≥2 or ≥3 or ≥4 consecutive days with PM concentration ≥90th or ≥92.5th or ≥95th or ≥97.5th percentiles, respectively. A time-series Poisson regression model with duration as the variable of interest was used to evaluate the associations of PM air pollution wave with HA for schizophrenia.

RESULTS

A total of 14650 hospital admissions for schizophrenia were identified. Under various air pollution wave definitions, both PM_2.5 and PM₁₀ had significant adverse effects on schizophrenia HA. PM_2.5 wave defined as ≥2 consecutive days with concentration ≥90th, ≥92.5th, ≥95th and ≥97.5th percentile was associated with 4.8% (2.0%-7.6%), 4.9% (1.9%-7.9%), 5.5% (2.0%-9.2%), and 7.6% (2.9%-12.6%) increase of HA for schizophrenia at lag 6. PM_2.5 waves defined as ≥3 consecutive days with concentration ≥90th, ≥92.5th, ≥95th and ≥97.5th percentile respectively corresponded to 5.0% (2.3%-7.8%), 5.1% (1.9%-8.4%), 6.9% (3.0%-10.8%) and 12.0% (5.3%-19.1%) increases in HA for schizophrenia at lag 6. The most significant associations were observed on the sixth day in different lag models.

CONCLUSIONS

PM air pollution wave was associated with increased risk of hospital admissions for schizophrenia, with stronger associations among married and female patients.

Defining heat waves and extreme heat events using sub-regional meteorological data to maximize benefits of early warning systems to population health

BACKGROUND

Extreme heat events have been consistently associated with an increased risk of hospitalization for various hospital diagnoses. Classifying heat events is particularly relevant for identifying the criteria to activate early warning systems. Heat event classifications may also differ due to heterogeneity in climates among different geographic regions, which may occur at a small scale. Using local meteorological data, we identified heat waves and extreme heat events that were associated with the highest burden of excess hospitalizations within the County of San Diego and quantified discrepancies using county-level meteorological criteria.

METHODS

Eighteen event classifications were created using various combinations of temperature metric, percentile, and duration for both county-level and climate zone level meteorological data within San Diego County. Propensity score matching and Poisson regressions were utilized to ascertain the association between heat wave exposure and risk of hospitalization for heat-related illness and dehydration for the 1999-2013 period. We estimated both relative and absolute risks for each heat event classification in order to identify optimal definitions of heat waves and extreme heat events for the whole city and in each climate zone to target health impacts.

RESULTS

Heat-related illness differs vastly by level (county or zone-specific), definition, and risk measure. We found the county-level definitions to be systematically biased when compared to climate zone definitions with the largest discrepancy of 56 attributable hospitalizations. The relative and attributable risks were often minimally correlated, which exemplified that relative risks alone are not adequate to optimize heat waves definitions.

CONCLUSIONS

Definitions based on county-level defined thresholds do not provide an accurate picture of the observed health effects and will fail to maximize the potential effectiveness of heat warning systems. Absolute rather than relative risks are a more appropriate measure to define the set of criteria to activate early warnings systems and thus maximize public health benefits.

Building an interdisciplinary framework to advance conceptual and technical aspects of population-environment research focused on women's and children's health

Great gains have been made in providing researchers geo-spatial data that can be combined with population health data. This development is crucial given concerns over the human health outcomes associated with a changing climate. Merging population and environmental data remains both conceptually and technically challenging because of a large range of temporal and spatial scales. Here we propose a framework that addresses and advances both conceptual and technical aspects of population-environment research. This framework can be useful for considering how any time or space-based environmental occurrence influences population health outcomes and can be used to guide different data aggregation strategies. The primary consideration discussed here is how to properly model the space and time effects of environmental context on individual-level health outcomes, specifically maternal, child and reproductive health outcomes. The influx of geospatial health data and highly detailed environmental data, often at daily scales, provide an opportunity for population-environment researchers to move towards a more theoretically and analytically sound approach for studying environment and health linkages.

Time series analysis of total and direct associations between high temperatures and preterm births in Detroit, Michigan

OBJECTIVES

Preterm births (PTBs) represent significant health risks, and several studies have found associations between high outdoor temperatures and PTB. We estimated both the total and natural direct effects (independent of particulate matter, ozone and nitrogen dioxide air pollutants) of the prior 2-day mean apparent temperature (AT) on PTB. We evaluated effect modification by maternal age, race, education, smoking status and prenatal care.

DESIGN AND SETTING

We obtained birth records and meteorological data for the Detroit, Michigan, USA area, for the warm months (May to September), 1991 to 2001. We used a time series Poisson regression with splines of AT, wind speed, solar radiation and citywide average precipitation to estimate total effects. To accommodate multiple mediators and exposure-mediator interactions, AT inverse odds weights, predicted by meteorological and air pollutant covariates, were added in a subsequent model to estimate direct effects.

RESULTS

At 24.9°C relative to 18.6°C, 10.6% (95% CI: 3.8% to 17.2%) of PTBs were attributable to the total effects of AT, and 10.4% (95% CI: 2.2% to 17.5%) to direct effects. Relative excess risks of interaction indicated that the risk of PTB with increasing temperature above 18.6°C was significantly lower among black mothers and higher among mothers less than 19, older than 30, with late or no prenatal care and who smoked.

CONCLUSION

This additional evidence of a direct association between high temperature and PTB may motivate public health interventions to reduce extreme heat exposures among pregnant women, particularly among those who may have enhanced vulnerability.

Independent and Combined Effects of Heatwaves and PM2.5 on Preterm Birth in Guangzhou, China: A Survival Analysis

BACKGROUND

Both extreme heat and air pollution exposure during pregnancy have been associated with preterm birth; however, their combined effects are unclear.

OBJECTIVES

Our goal was to estimate the independent and joint effects of heatwaves and fine particulate matter [PM <2.5μm in aerodynamic diameter (PM2.5)], exposure during the final gestational week on preterm birth.

METHODS

Using birth registry data from Guangzhou, China, we included 215,059 singleton live births in the warm season (1 May-31 October) between January 2015 and July 2017. Daily meteorological variables from 5 monitoring stations and PM2.5 concentrations from 11 sites were used to estimate district-specific exposures. A series of cut off temperature thresholds and durations (2, 3, and 4 consecutive d) were used to define 15 different heatwaves. Cox proportional hazard models were used to estimate the effects of heatwaves and PM2.5 exposures during the final week on preterm birth, and departures from additive joint effects were assessed using the relative excess risk due to interaction (RERI).

RESULTS

Numbers of preterm births increased in association with heatwave exposures during the final gestational week. Depending on the heatwave definition used, hazard ratios (HRs) ranged from 1.10 (95% CI: 1.01, 1.20) to 1.92 (1.39, 2.64). Associations were stronger for more intense heatwaves. Combined effects of PM2.5 exposures and heatwaves appeared to be synergistic (RERIs>0) for less extreme heatwaves (i.e., shorter or with relatively low temperature thresholds) but were less than additive (RERIs<0) for more intense heatwaves.

CONCLUSIONS

Our research strengthens the evidence that exposure to heatwaves during the final gestational week can independently trigger preterm birth. Moderate heatwaves may also act synergistically with PM2.5 exposure to increase risk of preterm birth, which adds new evidence to the current understanding of combined effects of air pollution and meteorological variables on adverse birth outcomes. https://doi.org/10.1289/EHP5117.

Heatwave Events and Mortality Outcomes in Memphis, Tennessee: Testing Effect Modification by Socioeconomic Status and Urbanicity

Heatwave studies typically estimate heat-related mortality and morbidity risks at the city level; few have addressed the heterogeneous risks by socioeconomic status (SES) and location within a city. This study aimed to examine the impacts of heatwaves on mortality outcomes in Memphis, Tennessee, a Mid-South metropolitan area top-ranked in morbidity and poverty rates, and to investigate the effects of SES and urbanicity. Mortality data were retrieved from the death records in 2008-2017, and temperature data from the Applied Climate Information System. Heatwave days were defined based on four temperature metrics. Heatwave effects on daily total-cause, cardiovascular, and respiratory mortality were evaluated using Poisson regression, accounting for temporal trends, sociodemographic factors, urbanicity, and air pollution. We found higher cardiovascular mortality risk (cumulative RR (relative risk) = 1.25, 95% CI (confidence interval): 1.01-1.55) in heatwave days defined as those with maximum daily temperature >95th percentile for more than two consecutive days. The effects of heatwaves on mortality did not differ by SES, race, or urbanicity. The findings of this study provided evidence to support future heatwave planning and studies of heatwave and health impacts at a coarser geographic resolution.

Characterising the impact of heatwaves on work-related injuries and illnesses in three Australian cities using a standard heatwave definition- Excess Heat Factor (EHF)

BACKGROUND AND AIMS

Heatwaves have potential health and safety implications for many workers, and heatwaves are predicted to increase in frequency and intensity with climate change. There is currently a lack of comparative evidence for the effects of heatwaves on workers' health and safety in different climates (sub-tropical and temperate). This study examined the relationship between heatwave severity (as defined by the Excess Heat Factor) and workers' compensation claims, to define impacts and identify workers at higher risk.

METHODS

Workers' compensation claims data from Australian cities with temperate (Melbourne and Perth) and subtropical (Brisbane) climates for the years 2006-2016 were analysed in relation to heatwave severity categories (low and moderate/high severity) using time-stratified case-crossover models.

RESULTS

Consistent impacts of heatwaves were observed in each city with either a protective or null effect during heatwaves of low-intensity while claims increased during moderate/high-severity heatwaves compared with non-heatwave days. The highest effect during moderate/high-severity heatwaves was in Brisbane (RR 1.45, 95% CI: 1.42-1.48). Vulnerable worker subgroups identified across the three cities included: males, workers aged under 34 years, apprentice/trainee workers, labour hire workers, those employed in medium and heavy strength occupations, and workers from outdoor and indoor industrial sectors.

CONCLUSION

These findings show that work-related injuries and illnesses increase during moderate/high-severity heatwaves in both sub-tropical and temperate climates. Heatwave forecasts should signal the need for heightened heat awareness and preventive measures to minimise the risks to workers.

Does Particulate Matter Modify the Short-Term Association between Heat Waves and Hospital Admissions for Cardiovascular Diseases in Greater Sydney, Australia?

Little is known about the potential interactive effects of heat waves and ambient particulate matter on cardiovascular morbidity. A time-stratified case-crossover design was used to examine whether particulate matter (PM₁₀) modifies the association between heat waves and emergency hospital admissions for six cardiovascular diseases in Greater Sydney, Australia during the warm season for 2001–2013. We estimated and compared the effect of heat waves on high- and low-level PM₁₀ days at lag₀–lag₂, adjusting for dew-point temperature, ambient ozone, ambient nitrogen dioxide, and public holidays. We also investigated the susceptibility of both younger (0–64 years) and older populations (65 years and above), and tested the sensitivity of three heat wave definitions. Stronger heat wave effects were observed on high- compared to low-level PM₁₀ days for emergency hospital admissions for cardiac arrest for all ages combined, 0–64 years and 65 years and above; conduction disorders for 0–64 years; and hypertensive diseases for all ages combined and 0–64 years. Overall, we found some evidence to suggest that PM₁₀ may modify the association between heat waves and hospital admissions for certain cardiovascular diseases, although our findings largely differed across disease, age group, lag, and heat wave definition.

Heatwaves and hospitalizations due to hyperthermia in defined climate regions in the conterminous USA

Heatwaves are one of the deadliest natural disasters that occur annually with thousands of people seeking medical attention. The spatio-temporal synchronization between peaks in disease manifestation and high temperature provides important insights into the seasonal timing of the heatwave and the response it may cause with respect to emergence, severity, and duration. The objectives of this study are to examine the association between hospitalizations due to heat stroke in older adults and heat in the United States (US) and explore synchronization with respect to heatwave sequence, time of arrival, and regional climate. Three large data sets were utilized: daily hospitalization records of the US elderly between 1991 and 2006, annual demographic summaries on Medicare beneficiaries maintained by the Centers for Medicare and Medicaid Services (CMS), and nationwide daily meteorological observations. We modeled seasonal fluctuations in health outcomes, such as the timing and intensity of the seasonal peak in hospitalizations using refined harmonic GLM for eight climatically similar regions. During the 16-year study period, there were 40,019 heat-related hospitalizations (HRH) in the conterminous  US. The rates of HRH varied substantially across eight climatic regions: with the highest rate of 7.05 cases per million residents observed in areas with temperate arid summers and winters (TaTa) and the lowest rate of 0.67-in areas with cold moderately dry summers and arid winters (CdCa), where summer temperatures are about  18.3 °C and 12.1 °C, respectively. We detected 400 heatwaves defined as any day when the night time temperature is above its 90th percentile for the current and previous nights. The first seasonal heatwave in a season resulted in 4274 hospitalizations over 342 heatwave-days: 34.3% of 12,442 hospitalizations occurred in 26% of 1308 heatwave-days. The relative risks of increased HRH associated with the first and second heatwaves were 10.4 (95%CI: 8.5; 12.3) and 11.4 (95%CI: 9.6; 13.3), respectively, indicating the disproportional effects of early heatwave arrivals. The seasonal spike in heat stroke hospitalizations in regions with relatively similar annual temperatures, e.g. in areas with temperate moderately dry summers and winters (TdTa: 12.8 °C) and (TaTa: 11.1 °C) ranged between 4.5 (95%CI: 3.3; 5.5) and 11.0 (95%CI: 8.2; 14.9) cases per million residents, respectively, indicating substantial regional differences. The differences in heat-related hospitalizations and response to heatwaves are substantial among older adults residing in different climate regions of the conterminous US. The disproportionally high response to the early seasonal heatwave deserves special attention, especially in the context of prevention and decision support frameworks.

Physical Exertion Immediately Before Early Preterm Delivery: A Case-Crossover Study

BACKGROUND

Occupational exertion is associated with a higher risk of preterm delivery, although studies of leisure time activities generally document reduced risks. Less is known about the risk of preterm delivery immediately following episodes of moderate or heavy physical exertion.

METHODS

We conducted a case-crossover study of 722 women interviewed during their hospital stay for early preterm delivery, defined by a gestational age before 34 weeks, and after 20 weeks. Interviews occurred between March 2013 and December 2015 in seven hospitals in Lima, Peru.

RESULTS

The incidence rate ratio (RR) of early preterm delivery was 5.82-fold higher (95% confidence interval [CI] = 4.29, 7.36) in the hour following moderate or heavy physical exertion compared with other times and returned to baseline in the hours thereafter. The RR of early preterm delivery within an hour of physical exertion was lower for exertion at moderate intensity (RR = 2.43; 95% CI = 1.50, 3.96) than at heavy intensity (RR = 23.62; 95% CI = 15.54, 35.91; P-homogeneity < 0.001). The RR of early preterm delivery was lower in the hour following moderate physical exertion among women who habitually engaged in physical exertion >3 times per week in the year before pregnancy (RR = 1.56; 95% CI = 0.81, 3.00) compared with more sedentary women (RR = 6.91; 95% CI = 3.20, 14.92; P-homogeneity = 0.003).

CONCLUSIONS

Our study showed a heightened risk of early preterm delivery in the hour following moderate or heavy physical exertion.

Attributing mortality from temperature extremes: A time series analysis in Varanasi, India

Climate extremes are often associated with increased human mortality and such association varies considerably with space and time. We therefore, aimed to systematically investigate the effects of temperature extremes, daily means and diurnal temperature variations (DTV) on mortality in the city of Varanasi, India during 2009-2016. Time series data on daily mortality, air quality (SO₂, NO₂, O₃ and PM₁₀) and weather variables were obtained from the routinely collected secondary sources. A semiparametric quasi-Poisson regression model estimated the effects of temperature extremes on daily all-cause mortality adjusting nonlinear confounding effects of time trend, relative humidity and air pollution; stratified by seasons. An effect modification by age, gender and place of death as semi-economic indicator were also explored. Daily mean temperature was strongly associated with excess mortality, both during summer (5.61% with 95% CI: 4.69-6.53% per unit increase in mean temperature) and winter (1.53% with 95% CI: 0.88-2.18% per unit decrease in mean temperature). Daily mortality was found to be increased by 12.02% (with 95% CI: 4.21-19.84%) due to heat wave. The DTV has exhibited downward trend over the years and showed a negative association with all-cause mortality. Significant association of mortality and different metric of temperature extreme along with decreasing trend in DTV clearly indicate the potential impact of climate change on human health in the city of Varanasi. The finding may well be useful to prioritize the government policies to curb the factors that causes the climate change and for developing early warning system.

Urban Heat Island and Future Climate Change-Implications for Delhi's Heat

UrbClim, the urban climate model, is used for short- and long-term projections of climate for Delhi. The projections are performed for RCP8.5 using an ensemble of 11 GCM model outputs. Various heat stress indices were employed to understand the role of urban heat island (UHI) in influencing the present and future urban climate of the city. UHI intensity based on 5% warmest nights (TNp95) was 4.1 °C and exhibits negligible change over time. However, the impact of UHI on other heat stress indices is very strong. Combined hot days and tropical nights (CHT) that influenced 58-70% of the reference time frame are expected to rise to 68-77% in near-future and to 91-97% in far-future time periods. For reference time period, urban areas experience 2.3 more number of heat wave days (NHWD) than rural areas per summer season. This difference increases to 7.1 in short-term and 13.8 in long-term projections. Similar to this trend, frequency of heat waves (FHW) for urban areas is also expected to increase from 0.8 each summer season in reference time frame to 2.1 and 5.1 in short- and long-term projections. The urban-rural difference for duration of heat waves (DHW) appears to increase from 1.7 days in past to 2.3 and 2.2 days in future, illustrating that DHW for cities will be higher than non-urban areas at least by 2 days. The intensity of heat wave (IHW) for urban land uses increases from 40 °C in reference time frame to 45 °C in short-term projection to 49 °C in far future. These values for non-urban land use were 33 °C during the baseline time period and are expected to increase to 42 °C and 46 °C in near- and far-future time frames. The results clearly indicate the contribution of UHI effects in intensifying the impacts of extreme heat and heat stress in the city.

Heatwaves and diabetes in Brisbane, Australia: a population-based retrospective cohort study

Background

Available data on the effects of heatwaves on hospitalizations for diabetes and the post-discharge status of diabetics are scarce. This study aimed to assess the effects of heatwaves on hospitalizations and post-discharge deaths for diabetes, and to identify the individual- and community-level characteristics [i.e. age, gender, Socio-economic Indexes for Areas (SEIFA), and normalized difference vegetation index (NDVI)] that modified heatwave effects.

Methods

Health data were extracted from a cohort study which included patients in Brisbane, Australia, who were hospitalized due to diabetes from 1st January 2005 to 31st December 2013, and died within 2 months after they were discharged. Data on community-level modifiers, including SEIFA and NDVI (i.e. urban vegetation), were obtained from Australian Bureau of Statistics and Australian Bureau of Meteorology, respectively. Case-crossover design was used to quantify the effects of heatwaves on hospitalizations and post-discharge deaths due to diabetes. Four heatwave definitions incorporating both intensity (i.e. 90th, 95th, 97th and 99th percentiles of mean temperature distribution) and duration (2 days), as well as excess heat factor (EHF), were used. A case-only design was adopted to identify the modifiers of heatwave effects.

Results

There were 10 542 hospitalizations for diabetes, and 513 patients died due to diabetes within 2 months after discharge. During low-intensity heatwave days (i.e. 90th percentile & 2 days), we did not observe a significant increase in hospitalizations for diabetes [9% at lag 0; 95% confidence interval (CI): –3%, 23%; P = 0.146], but we observed a significant increase in post-discharge deaths (46% at lag 2; 95% CI: 3%, 107%; P = 0.036). During middle-intensity heatwave days (i.e. 95th percentile & 2 days), hospitalizations for diabetes increased by 19% at lag 0 (95% CI: 2%, 39%; P = 0.026), and post-discharge deaths increased by 64% at lag 0 (95% CI: 6%, 154%; P = 0.027). During high-intensity heatwave days (i.e. 97th percentile & 2 days), hospitalizations for diabetes increased by 37% at lag 1 (95% CI: 11%, 69%; P = 0.004) and post-discharge deaths increased by 137% at lag 1 (95% CI: 39%, 303%; P = 0.002). When heatwave intensity increased to 99th percentile, we did not observe a significant increase in hospitalizations (–1% at lag 0; 95% CI: –38%, 59%; P = 0.870) or post-discharge deaths (79% at lag 0; 95% CI: –39%, 431%; P = 0.301). When we used EHF to define heatwaves, we observed significant increases of hospitalizations (7%; 95% CI: 1%, 15%; P = 0.039) and post-discharge deaths (68%, 95% CI: 10%, 158%; P = 0.017) during heatwave days, compared with non-heatwave days. Children and male diabetics were particularly vulnerable to heatwave effects, but we did not find any significant modification effect of SEIFA or NDVI on the associations of heatwaves with hospitalizations and post-discharge deaths due to diabetes.

Conclusion

Heatwaves may lead to hospitalizations of diabetics and their premature deaths. Heat-related diabetes burden in children may increase as climate warms and with increasing obesity rates in adolescents.