Spatiotemporal and demographic variation in the association between temperature variability and hospitalizations in Brazil during 2000-2015: A nationwide time-series study

Daily temperature variability and mental health-related hospital visits in New York State

BACKGROUND

Despite plausible behavioral and physiological pathways, limited evidence exists on how daily temperature variability is associated with acute mental health-related episodes.

OBJECTIVES

We aimed to explore associations between daily temperature range (DTR) and mental health-related hospital visits using data of all hospital records in New York State during 1995-2014. We further examined factors that may modify these associations, including age, sex, hospital visit type and season.

METHODS

Using a case-crossover design with distributed lag non-linear DTR terms (0-6 days), we estimated associations between ZIP Code-level DTR and hospital visits for mood (4.6 million hospital visits), anxiety (2.4 million), adjustment (∼368,000), and schizophrenia disorders (∼211,000), controlling for daily mean temperature, via conditional logistic regression models. We assessed potential heterogeneity by age, sex, hospital visit type (in-patient vs. out-patient), and season (summer, winter, and transition seasons).

RESULTS

For all included outcomes, we observed positive associations from period minimum DTR (0.1 °C) until 25th percentile (5.2 °C) and between mean DTR (7.7 °C) and 90th percentile (12.2 °C), beyond which we observed negative associations. For mood disorders, an increase in DTR from 0.1 °C to 12.2 °C was associated with a cumulative 16.0% increase (95% confidence interval [CI]: 12.8, 19.2%) in hospital visit rates. This increase was highest during transition seasons (32.5%; 95%CI: 26.4, 39.0%) compared with summer (10.7%; 95%CI: 4.8, 16.8%) and winter (-1.6%; 95%CI: -7.6, 4.7%). For adjustment and schizophrenia disorders, the strongest associations were seen among the youngest group (0-24 years) with almost no association in the oldest group (65+ years). We observed no evidence for modification by sex and hospital visit type.

DISCUSSION

Daily temperature variability was positively associated with mental health-related hospital visits within specific DTR ranges in New York State, after controlling for daily mean temperature. Given uncertainty on how climate change modifies temperature variability, additional research is crucial to comprehend the implications of these findings, particularly under different scenarios of future temperature variability.

Effects of intra- and inter-day temperature change on acute upper respiratory infections among college students, assessments of three temperature change indicators

Background

Acute upper respiratory infection (AURI) is a significant disease affecting all age groups worldwide. The differences in the impacts of different temperature change indicators, such as diurnal temperature range (DTR), temperature variation (TV), and temperature change between neighboring days (TCN), on AURI morbidity, are not clear.

Methods

We collected data on 87,186 AURI patients during 2014-2019 in Zhengzhou. Distributed lag non-linear model was adopted to examine the effects of different temperature change indicators on AURI. We calculated and compared the attributable fractions (AF) of AURI morbidity caused by various indicators. We used stratified analysis to investigate the modification effects of season and gender.

Results

With the increase in DTR and TV, the risk of AURI tended to increase; the corresponding AF values (95% eCI) higher than the references (5% position of the DTR or TV distribution) were 24.26% (15.46%, 32.05%), 23.10% (15.59%, 29.20%), and 19.24% (13.90%, 24.63%) for DTR, TV0 - 1, and TV0 - 7, respectively. The harmful effects of TCN on AURI mainly occurred when the temperature dropped (TCN < 0), and the AF value of TCN below the reference (0°C) was 3.42% (1.60%, 5.14%). The harm of DTR and TV were statistically significant in spring, autumn and winter, but not in summer, while the harm of TCN mainly occurred in winter. Three indicators have statistically significant effects on both males and females.

Conclusions

High DTR and TV may induce AURI morbidity, while the harm of TCN occurs when the temperature drops. The impacts of DTR and TV on AURI are higher than that of TCN, and the impact of few-day TV is higher than that of multi-day TV. The adverse effects of DTR and TV are significant except in summer, while the hazards of TCN mainly occur in winter.

Comparison for the effects of different components of temperature variability on mortality: A multi-country time-series study

BACKGROUND

Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects.

OBJECTIVES

We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality.

METHODS

We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates.

RESULTS

Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0-7 (0.9 °C). An IQR increase in inter-day TV0-7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0-7 and inter-day TV0-7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type.

CONCLUSIONS

Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.

How climate change degrades child health: A systematic review and meta-analysis

BACKGROUND

Children are more vulnerable than adults to climate-related health threats, but reviews examining how climate change affects human health have been mainly descriptive and lack an assessment of the magnitude of health effects children face. This is the first systematic review and meta-analysis that identifies which climate-health relationships pose the greatest threats to children.

OBJECTIVES

We reviewed epidemiologic studies to analyse various child health outcomes due to climate change and identify the relationships with the largest effect size. We identify population-specific risks and provide recommendations for future research.

METHODS

We searched four large online databases for observational studies published up to 5 January 2023 following PRISMA (systematic review) guidelines. We evaluated each included study individually and aggregated relevant quantitative data. We used quantitative data in our meta-analysis, where we standardised effect sizes and compared them among different groupings of climate variables and health outcomes.

RESULTS

Of 1301 articles we identified, 163 studies were eligible for analysis. We identified many relationships between climate change and child health, the strongest of which was increasing risk (60 % on average) of preterm birth from exposure to temperature extremes. Respiratory disease, mortality, and morbidity, among others, were also influenced by climate changes. The effects of different air pollutants on health outcomes were considerably smaller compared to temperature effects, but with most (16/20 = 80 %) pollutant studies indicating at least a weak effect. Most studies occurred in high-income regions, but we found no geographical clustering according to health outcome, climate variable, or magnitude of risk. The following factors were protective of climate-related child-health threats: (i) economic stability and strength, (ii) access to quality healthcare, (iii) adequate infrastructure, and (iv) food security. Threats to these services vary by local geographical, climate, and socio-economic conditions. Children will have increased prevalence of disease due to anthropogenic climate change, and our quantification of the impact of various aspects of climate change on child health can contribute to the planning of mitigation that will improve the health of current and future generations.

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

OBJECTIVES

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

STUDY DESIGN

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Relationship between temperature variability and daily hospitalisations in Hong Kong over two decades

Background

Studies have highlighted the impacts of temperature variability (TV) on mortality from respiratory diseases and cardiovascular diseases, with inconsistent results specifically in subtropical urban areas than temperate ones. We aimed to fully determine TV-associated health risks over a spectrum of diseases and various subgroups in a subtropical setting.

Methods

Using inpatient data from all public hospitals in Hong Kong from 1999 to 2019, we examined the TV-hospitalisation associations by causes, ages, and seasons by fitting a quasi-Poisson regression. We presented the results as estimated percentage changes of hospitalisations per interquartile range (IQR) of TV.

Results

TVs in exposure days from 0-5 days (TV0-5) to 0-7 days (TV0-7) had detrimental effects on hospitalisation risks in Hong Kong. The overall population was significantly affected over TV0-5 to TV0-7 in endocrine, nutritional and metabolic (from 0.53% to 0.58%), respiratory system (from 0.38% to 0.53%), and circulatory systems diseases (from 0.47% to 0.56%). While we found no association with seasonal disparities, we did observe notable disparities by age, highlighting older adults' vulnerability to TVs. For example, people aged ≥65 years experienced the highest change of 0.88% (95% CI = 0.34%, 1.41%) in hospitalizations for injury and poisoning per IQR increase in TV0-4.

Conclusions

Our population-based study highlighted that TV-related health burden, usually regarded as minimal compared to other environmental factors, should receive more attention and be addressed in future relevant health policies, especially for vulnerable populations during the cold seasons.

Identifying gaps on health impacts, exposures, and vulnerabilities to climate change on human health and wellbeing in South America: a scoping review

There is an important gap in regional information on climate change and health, limiting the development of science-based climate policies in South American countries. This study aims to identify the main gaps in the existing scientific literature on the impacts, exposure, and vulnerabilities of climate change on population health. A scoping review was performed guided by four sub-questions focused on the impacts of climate change on physical and mental health, exposure and vulnerability factors of population to climate hazards. The main findings showed that physical impacts mainly included infectious diseases, while mental health impacts included trauma, depression, and anxiety. Evidence on population exposure to climate hazards is limited, and social determinants of health and individual factors were identified as vulnerability factors. Overall, evidence on the intersection between climate change and health is limited in South America and has been generated in silos, with limited transdisciplinary research. More formal and systematic information should be generated to inform public policy.

Funding

None.

A study of temperature variability on admissions and deaths for cardiovascular diseases in Northwestern China

OBJECTIVE

To explore the effect of temperature variability (TV) on admissions and deaths for cardiovascular diseases (CVDs).

METHOD

The admissions data of CVDs were collected in 4 general hospitals in Jinchang City, Gansu Province from 2013 to 2016. The monitoring data of death for CVDs from 2013 to 2017 were collected through the Jinchang City Center for Disease Control and Prevention. Distributed lag nonlinear model (DLNM) was combined to analyze the effects of TV (daily temperature variability (DTV) and hourly temperature variability (HTV)) on the admissions and deaths for CVDs after adjusting confounding effects. Stratified analysis was conducted by age and gender. Then the attribution risk of TV was evaluated.

RESULTS

There was a broadly linear correlation between TV and the admissions and deaths for CVDs, but only the association between TV and outpatient and emergency room (O&ER) visits for CVDs have statistically significant. DTV and HTV have similar lag effect. Every 1 ℃ increase in DTV and HTV was associated with a 3.61% (95% CI: 1.19% ~ 6.08%), 3.03% (95% CI: 0.27% ~ 5.86%) increase in O&ER visits for CVDs, respectively. There were 22.75% and 14.15% O&ER visits for CVDs can attribute to DTV and HTV exposure during 2013-2016. Males and the elderly may be more sensitive to the changes of TV. Greater effect of TV was observed in non-heating season than in heating season.

CONCLUSION

TV was an independent risk factor for the increase of O&ER visits for CVDs, suggesting effective guidance such as strengthening the timely prevention for vulnerable groups before or after exposure, which has important implications for risk management of CVDs.

Effect modification of the association between temperature variability and hospitalization for cardiovascular disease by comorbid diabetes mellitus: A nationwide time-stratified case-crossover analysis

AIMS

We aimed to explore the association between short-term exposure to temperature variability (TV), and cardiovascular hospitalization stratified by the presence of comorbid diabetes.

METHODS

We collected data on nationwide hospitalization for cardiovascular diseases and daily weather conditions during 2011-2018 in Japan. TV was calculated as the standard deviation of daily minimum and maximum temperatures within 0-7 lag days. We applied a two-stage time-stratified case-crossover design to estimate the association between TV and cardiovascular hospitalization with and without comorbid diabetes, adjusting for temperature and relative humidity. Furthermore, specific cardiovascular disease causes, demographic characteristics, and seasons were used for stratification.

RESULTS

In 3,844,910 hospitalizations for cardiovascular disease, each 1 °C increase in TV was associated with a 0.44% (95% CI: 0.22%, 0.65%) increase in the risk of cardiovascular admission. We observed a 2.07% (95% CI: 1.16%, 2.99%) and 0.61% (95% CI: -0.02%, 1.23%) increase per 1 °C in risk of heart failure admission in individuals with and those without diabetes, respectively. The higher risk among individuals with diabetes was mostly consistent in the analyses stratified by age, sex, body mass index, smoking status, and season.

CONCLUSION

Comorbid diabetes may increase susceptibility to TV in relation to acute cardiovascular disease hospitalization.

A new method to separate the impacts of interday and intraday temperature variability on mortality

BACKGROUND

Temperature variability (TV) is associated with increased mortality risks. However, the independent impacts of interday and intraday are still unknown.

METHODS

We proposed a new method to decompose TV into interday TV and intraday TV through algebra derivation. Intraday TV was defined as the weighted average standard deviation (SD) of minimum temperature and maximum temperature on each day. Interday TV was defined as the weighted SD of daily mean temperatures during the exposure period. We then performed an illustrative analysis using data on daily mortality and temperature in France in 2019-2021.

RESULTS

The novel interday and intraday TV indices were good proxies for existing indicators, inlcluding diurnal temperature range (DTR) and temperature change between neighbouring days (TCN). In the illustrative analyses, interday and intraday TVs showed differentiated mortality risks. Mortality burden related to TV was mainly explained by the intraday component, accounting for an attributable fraction (AF) of 1.81% (95% CI: 0.64%, 2.97%) of total mortality, more than twice the AF of interday TV (0.86%, 95% CI: 0.47%, 1.24%).

CONCLUSIONS

This study proposed a novel method for identifying and isolating the different components of temperature variability and offered a comprehensive way to investigate their health impacts.

Long-term exposure to PM2.5 and O3 with cardiometabolic multimorbidity: Evidence among Chinese elderly population from 462 cities

Cardiometabolic multimorbidity (CMM) refers to the presence of multiple cardiovascular and metabolic diseases (CMDs), such as hypertension, diabetes, and cardio-cerebrovascular diseases (CCVD), in the same individual, and has emerge as a significant global health concern due to population aging. Although previous research has demonstrated the association between cardiovascular and metabolic diseases and air pollutants, evidence on the link between CMM and air pollution exposure among Chinese older adults is limited. To address this research gap, we conducted a national representative survey of 222,179 adults aged 60 and older to investigate the epidemiology of CMM and its association with long-term exposure to PM_2.5 and O₃ in China's elderly population. We found that the prevalence of CMM among Chinese older adults was 16.9%, and hypertension and CCVD were the most common CMM cluster (10.8%). After adjusting for confounding variables, we observed a significant positive association between PM_2.5 exposure and the prevalence of hypertension, diabetes, and CCVD, with a respective excess risk increase of 3.2%, 3.6%, and 5.5% for every 10-unit increase. Moreover, every 10-unit increase in PM_2.5 was linked to a higher risk of hypertension and diabetes (2.2%), hypertension and CCVD (5.4%), diabetes and CCVD (5.6%), and hypertension, diabetes, and CCVD combined (7.6%). We also found a U-shaped curve relationship between O₃ exposure and the occurrence of hypertension, diabetes, and CCVD, as well as different subtypes of CMM, with the lowest risk of O₃ exposure was observed near 75-80 μg/m³. Furthermore, we identified that female and rural residents are more vulnerable to the health risks of air pollution than male and urban residents. Given the increasing aging of the population and rising prevalence of multimorbidity, policymakers should focus more attention on the female and rural elderly population to prevent and control CMM. This study provides compelling evidence that reducing air pollution levels can be an effective strategy to prevent and manage CMM among older adults.

Temperature variability and birthweight: Epidemiological evidence from Africa

BACKGROUND

Mounting evidence supports an association between nonoptimal ambient temperatures (i.e., heat or cold) and risk of low birthweight (LBW) (<2500 g), while the effect of temperature variability (TV) is largely unknown. We aimed to quantify the association between TV and risk of LBW in Africa.

METHODS

Data on birthweight in 37 countries during 1990-2020 were collected from the Demographic and Health Surveys program. We calculated overall, intraday, and interday TV during the entire pregnancy and each trimester using hourly temperatures at ∼ 9 km resolution from ERA5-Land. We employed generalized linear mixed logistic regression, with random effects for country and survey cluster, to quantify the association between LBW and three separate TV metrics.

RESULTS

In total there were 33,863 (10.2%) LBW births out of 333,618 records. We found a J-shaped association between TV and LBW. Compared to the reference TV where the lowest risk was observed, extremely high (97.5th percentile) overall, intraday, and interday TV during the entire pregnancy increased the odds of LBW birth by 37.3% (26.7-48.8%), 24.1% (16.4-32.3%), and 15.1% (6.9-24.0%), respectively. In total, 7.3% of all LBW births in Africa were attributable to elevated overall TV. These associations were observed in dry climate zones, but not in tropical or temperate zones.

CONCLUSIONS

Our study suggests an adverse impact of TV on the risk of LBW in Africa, according to three different TV definitions, underlining the significance of climate-health risk assessment in those most vulnerable to climate change.

Temperature variability and common diseases of the elderly in China: a national cross-sectional study

BACKGROUND

In the context of climate change, it has been well observed that short-term temperature variability (TV) could increase the overall and cause-specific mortality and morbidity. However, the association between long-term TV and a broader spectrum of diseases is not yet well understood, especially in the elderly.

METHODS

Our study used data from the fourth Urban and Rural Elderly Population (UREP) study. Long-term TV was calculated from the standard deviation (SD) of daily minimum and maximum temperatures within the study periods (2010-2014, 2011-2014, 2012-2014, 2013-2014, and 2014). Ten self-reported diseases and conditions were collected by questionnaire, including cataract, hypertension, diabetes, cardio-cerebrovascular diseases, stomach diseases, arthritis, chronic lung disease, asthma, cancer, and reproductive diseases. The province-stratified logistic regression model was used to quantify the association between long-term TV and the prevalence of each disease.

RESULTS

A total of 184,047 participants were included in our study. In general, there were significant associations between TV and the prevalence of most diseases at the national level. Cardio-cerebrovascular disease (OR: 1.16, 95% CI: 1.13, 1.20) generated the highest estimates, followed by stomach diseases (OR: 1.15, 95% CI: 1.10, 1.19), asthma (OR: 1.14, 95% CI: 1.06, 1.22), chronic lung diseases (OR: 1.08, 95% CI: 1.03, 1.13), arthritis (OR: 1.08, 95% CI: 1.05, 1.11), and cataract (OR: 1.06, 95% CI: 1.02, 1.10). Moreover, the associations varied by geographical regions and across subgroups stratified by sex, household income, physical activity, and education.

CONCLUSIONS

Our study showed that long-term exposure to TV was associated with the prevalence of main diseases in the elderly. More attention should be paid to the elderly and targeted strategies should be implemented, such as an early warning system.

Epigenome-wide association study of short-term temperature fluctuations based on within-sibship analyses in Australian females

BACKGROUND

Temperature fluctuations can affect human health independent of the effect of mean temperature. However, no study has evaluated whether short-term temperature fluctuations could affect DNA methylation.

METHODS

Peripheral blood DNA methylation for 479 female siblings of 130 families were analysed. Gridded daily temperatures data were obtained, linked to each participant's home address, and used to calculate nine different metrics of short-term temperature fluctuations: temperature variabilities (TVs) within the day of blood draw and preceding one to seven days (TV 0-1 to TV 0-7), diurnal temperature range (DTR), and temperature change between neighbouring days (TCN). Within-sibship design was used to perform epigenome-wide association analyses, adjusting for daily mean temperatures, and other important covariates (e.g., smoking, alcohol use, cell-type proportions). Differentially methylated regions (DMRs) were further identified. Multiple-testing comparisons with a significant threshold of 0.01 for cytosine-guanine dinucleotides (CpGs) and 0.05 for DMRs were applied.

RESULTS

Among 479 participants (mean age ± SD, 56.4 ± 7.9 years), we identified significant changes in methylation levels in 14 CpGs and 70 DMRs associated with temperature fluctuations. Almost all identified CpGs were associated with exposure to temperature fluctuations within three days. Differentially methylated signals were mapped to 68 genes that were linked to human diseases such as cancer (e.g., colorectal carcinoma, breast carcinoma, and metastatic neoplasms) and mental disorder (e.g., schizophrenia, mental depression, and bipolar disorder). The top three most significantly enriched gene ontology terms were Response to bacterium (TV 0-3), followed by Hydrolase activity, acting on ester bonds (TCN), and Oxidoreductase activity (TV 0-3).

CONCLUSIONS

Short-term temperature fluctuations were associated with differentially methylated signals across the human genome, which provides evidence on the potential biological mechanisms underlying the health impact of temperature fluctuations. Future studies are needed to further clarify the roles of DNA methylation in diseases associated with temperature fluctuations.

Effect of ambient temperature variability on sperm quality: A retrospective population-based cohort study

BACKGROUNDS

Abnormal sperm quality in men is one of the common causes of infertility. Both ambient temperature and extreme heat exposure have been shown to be associated with sperm quality, but there is no epidemiological evidence for the effect of ambient temperature variability. Our aim was to investigate the association between ambient temperature variability exposure and a decline in sperm quality at different stages of sperm development.

METHODS

A total of 4912 semen samples collected from the Guangdong Human Sperm Bank between 1 January 2019 and 31 December 2019 were analyzed. We selected three exposure periods: the full-stage (0-90 lag days), early-stage (34-77 lag days) and late-stage (0-37 lag days) of sperm development, and then calculated the standard deviation of daily temperature (TVSD), the maximum day-to-day temperature difference (TVD_max) and the mean day-to-day temperature difference (TVD_mean) for the three exposure periods. A linear mixed model was used to explore the exposure response relationship between temperature variability exposure and sperm quality indicators (including sperm concentration, sperm count and sperm motility).

RESULTS

There was a significant negative association of decreased sperm count with the exposure to temperature variability during 0-90 days prior to sperm collection. (TVD_max: -0.041; -0.063, -0.019; TVD_mean: -0.237; -0.386, -0.088; TVSD: -0.103; -0.196, -0.011). We observed a significant association between the decline in sperm concentration, sperm count and per 1 °C increase in TVD_mean during early spermatogenesis. No significant association of temperature variability with sperm motility was found.

CONCLUSIONS

The results indicate that exposure to temperature variability during the entire period of sperm development is significantly associated with a decline in sperm counts. We found that mean day-to-day temperature differences had a detrimental effect on sperm counts in the early-stage. Our findings provide a scientific basis for public health policy and further mechanistic studies.

High ambient temperature and risk of hospitalization for gastrointestinal infection in Brazil: A nationwide case-crossover study during 2000-2015

BACKGROUND

The burden of gastrointestinal infections related to hot ambient temperature remains largely unexplored in low-to-middle income countries which have most of the cases globally and are experiencing the greatest impact from climate change. The situation is particularly true in Brazil.

OBJECTIVES

Using medical records covering over 78 % of population, we quantify the association between high temperature and risk of hospitalization for gastrointestinal infection in Brazil between 2000 and 2015.

METHODS

Data on hospitalization for gastrointestinal infection and weather conditions were collected from 1814 Brazilian cities during the 2000-2015 hot seasons. A time-stratified case-crossover design was used to estimate the association. Stratified analyses were performed by region, sex, age-group, type of infection and early/late study period.

RESULTS

For every 5 °C increase in mean daily temperature, the cumulative odds ratio (OR) of hospitalization over 0-9 days was 1.22 [95 % confidence interval (CI): 1.21, 1.23] at the national level, reaching its maximum in the south and its minimum in the north. The strength of association tended to decline across successive age-groups, with infants < 1 year most susceptible. The effect estimates were similar for men and women. Waterborne and foodborne infections were more associated with high temperature than the 'others' and 'idiopathic' groups. There was no substantial change in the association over the 16-year study period.

DISCUSSION

Our findings indicate that exposure to high temperature is associated with increased risk of hospitalization for gastrointestinal infection in the hot season, with the strength varying by region, population subgroup and infection type. There was no evidence to indicate adaptation to heat over the study duration.

Short-term exposure to ozone and economic burden of premature mortality in Italy: A nationwide observation study

Italy is among the countries with the highest ozone concentration in Europe. However, the mortality burden of ozone and related economic loss has not been fully characterized. This study aimed to estimate the ozone-mortality association in Italy and evaluate attributable mortality burden and related economic loss in 2015-2019. We collected daily all-cause mortality data stratified by age and sex from 2015 to 2019 in 107 provinces of Italy. A two-stage time-series framework was applied to estimate the association between daily maximum eight-hour average ozone and mortality as well as economic loss. An overall increase in the risk of mortality (RR=1.0043, 95% CI: 1.0029, 1.0057) was associated with every 10 µg/m³ increase in ozone. Generally, a total of 70,060 deaths and $65 billion economic loss were attributed to ozone exposure, corresponding to 3.11% of mortality and about 0.5% of the national GDP during the study period, respectively. The highest ozone-related mortality burden (30,910 deaths) and economic loss ($29.24 billion) were observed in the hot season. This nationwide study suggested considerable mortality burden and economic loss were associated with exposure to ozone. More actions and policies should be proposed to reduce ozone levels and help the public protect their health.

Temperature variability associations with cardiovascular and respiratory emergency department visits in Dhaka, Bangladesh

BACKGROUND

Greenhouse gas emissions are changing the Earth's climate, most directly by modifying temperatures and temperature variability (TV). Residents of low- and middle-income countries (LMICs) are likely more adversely affected, due to lack of air conditioning to compensate. To date, there is no local epidemiological evidence documenting the cardio-respiratory health effects of TV in Dhaka, Bangladesh, one of the most climate change vulnerable cities in the world.

OBJECTIVES

We assessed short-term TV associations with daily cardiovascular disease (CVD) and respiratory emergency department (ED) visits, as well as effect modification by age and season.

METHODS

TV was calculated from the standard deviations of the daily minimum and maximum temperatures over exposure days. Time-series regression modeling was applied to daily ED visits for respiratory and CVD from January 2014 through December 2017. TV effect sizes were estimated after controlling for long-term trends and seasonality, day-of-week, holidays, and daily mean relative humidity and ambient temperature.

RESULTS

A 1 °C increase in TV was associated with a 1.00% (95 %CI: 0.05%, 1.96%) increase in CVD ED visits at lag 0-1 days (TV0-1) and a 2.77% (95 %CI: 0.24%, 5.20%) increase in respiratory ED visits at lag 0-7 days (TV0-7). TV-CVD associations were larger in the monsoon and cold seasons. Respiratory ED visit associations varied by age, with older adults more affected by the TV across all seasons. A 1 °C increase in TV at lag 0-7 days (TV0-7) was associated with a 7.45% (95 %CI: 2.33%, 12.57%) increase in respiratory ED visits among patients above 50 years of age.

CONCLUSION

This study provided novel and important evidence that cardio-pulmonary health in Dhaka is adversely affected year-round by day-to-day increases in TV, especially among older adults. TV is a key factor that should be considered in evaluating the potential human health impacts of climate change induced temperature changes.

Global, regional, and national burden of mortality associated with short-term temperature variability from 2000-19: a three-stage modelling study

BACKGROUND

Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000-19.

METHODS

In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000-19. Temperature variability was calculated as the SD of the average of the same and previous days' minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades.

FINDINGS

An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901-2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2-4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7-5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3-10·4), followed by Europe (4·4%, 2·2-5·6) and Africa (3·3, 1·9-4·6).

INTERPRETATION

Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability.

FUNDING

Australian Research Council, Australian National Health & Medical Research Council.

Fluctuating temperature modifies heat-mortality association in the globe

Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous days’ minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: −0.33 to 1.69), 1.34% (95% CI: −0.14 to 2.73), 1.99% (95% CI: 0.29–3.57), and 2.73% (95% CI: 0.76–4.50) of total deaths for Q1–Q4 (first quartile–fourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25–9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: −0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health.

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Increased temperature variability (TV) poses a greater mortality risk due to heat

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TV has a more profound modification effect on extreme heat-mortality association

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Strategies against heat and TV simultaneously would benefit public health

Association between ambient temperature and hospitalization for renal diseases in Brazil during 2000-2015: A nationwide case-crossover study

Background

Climate change is increasing the risks of injuries, diseases, and deaths globally. However, the association between ambient temperature and renal diseases has not been fully characterized. This study aimed to quantify the risk and attributable burden for hospitalizations of renal diseases related to ambient temperature.

Methods

Daily hospital admission data from 1816 cities in Brazil were collected during 2000 and 2015. A time-stratified case-crossover design was applied to evaluate the association between temperature and renal diseases. Relative risks (RRs), attributable fractions (AFs), and their confidence intervals (CIs) were calculated to estimate the associations and attributable burden.

Findings

A total of 2,726,886 hospitalizations for renal diseases were recorded during the study period. For every 1°C increase in daily mean temperature, the estimated risk of hospitalization for renal diseases over lag 0-7 days increased by 0·9% (RR = 1·009, 95% CI: 1·008-1·010) at the national level. The associations between temperature and renal diseases were largest at lag 0 days but remained for lag 1-2 days. The risk was more prominent in females, children aged 0-4 years, and the elderly ≥ 80 years. 7·4% (95% CI: 5·2-9·6%) of hospitalizations for renal diseases could be attributable to the increase of temperature, equating to 202,093 (95% CI: 141,554-260,594) cases.

Interpretation

This nationwide study provides robust evidence that more policies should be developed to prevent heat-related hospitalizations and mitigate climate change.

Funding

China Scholarship Council, and the Australian National Health and Medical Research Council.

Comparative analysis of daily and hourly temperature variability in association with all-cause and cardiorespiratory mortality in 45 US cities

Temperature variability (TV) has been widely associated with increased mortality risk and burden. Extensive researches have used the standard deviations of several days' daily maximum and minimum temperatures or hourly mean temperatures as daily and hourly TV measures (TV_daily and TV_hourly). However, comparative analysis of daily and hourly TV related to cardiorespiratory mortality is still limited. We collected daily mortality and meteorological data in 45 US metropolises, 1987-2000. A three-stage analysis was adopted to investigate TV-mortality associations using TV_daily and TV_hourly as exposure metrics. We first applied a time-series quasi-Poisson regression to estimate location-specific TV-mortality relationships, which were then pooled using random-effects meta-analysis with maximum likelihood estimation. We additionally calculated attributable fraction (AF) as a reflection of mortality burden associated with TV. Stratified analyses by age were also performed to identify the susceptible group to TV-related risks. There were a total of 15.4 million all-cause deaths, of which 6.1 million were from cardiovascular causes and 1.2 million were from respiratory causes. Per 1 °C increase in TV_daily and TV_hourly was associated with an increase of 0.53% (95% confidence interval: 0.31-0.76%) and 0.52% (0.26-0.79%) in cardiovascular mortality risks, 0.62% (0.26-0.98%) and 0.53% (0.13-0.94%) in respiratory mortality risks. Estimates of cardiovascular AF for TV_daily and TV_hourly were 2.43% (1.42-3.43%) vs. 1.63% (0.82-2.43%), whereas estimates of respiratory AF were 3.07% (1.11-4.99%) vs. 1.89% (0.43-3.34%). Both daily and hourly TV indexes showed approximately linear relationships with different mortality categories and similar lag patterns, but greater fractions were estimated using TV_daily than those using TV_hourly. People over 75 years old were relatively more vulnerable to TV-induced risks of mortality. In conclusion, both TV_daily and TV_hourly significantly increased all-cause and cardiorespiratory mortality risks and burden. Daily and hourly TV metrics exhibited comparable effects of mortality risk, while greater mortality burden was estimated using TV_daily than TV_hourly. Our findings may add significance to TV-mortality research and help to promote optimal health management strategies to better mitigate TV-related health effects.

Congenital anomalies associated with ambient temperature variability during fetal organogenesis period of pregnancy: Evidence from 4.78 million births

BACKGROUNDS

Evidence for the effects of temperature variability on risk of congenital anomalies is lacking. We aimed to examine the association of temperature variability during fetal organogenesis period (weeks 3-8 post-conception) with major congenital anomalies.

METHODS

A retrospective cohort study comprising 4,787,356 singleton live-births and stillbirths in China was performed. We defined two temperature variability indices within gestational week i: the standard deviation (SD) of daily temperature (TVSD_i) and the maximum day-to-day temperature difference (TVD_i). At 6-week long timescales, we computed the SD of daily temperature (TVSD_3-8) and the average value of TVD_i (TVD_3-8). We matched two temperature variability indices, pollutant exposure levels over entire exposure window and data of each mother-infant pairs. An extended generalized estimating equation log-binomial regression model was constructed to explore their associations after adjusting for individual characters, temperature extremes and air pollutants. Stratified and sensitivity analyses were also performed.

RESULTS

59,571 neonates were registered as major congenital anomalies besides genetic and chromosomal anomalies. At weekly levels, the highest risk estimates of two temperature variability indices occurred at the 5th week for most anomaly groups. All TVSD₅, TVD₅, and maximum weekly TVSD and TVD were significantly associated with all anomaly groups; with the increment of 1 °C, the estimated risk ratio (RR) and corresponding 95% confidence interval (CI) ranges from 1.03 (1.01-1.05) to 1.19 (1.08-1.31). At 6-week scales, TVSD_3-8 and TVD_3-8 were associated with most anomaly subgroups. Overall, the strongest associations were estimated for isolated defects among morphology subgroups and cardiac defects among type subgroups.

CONCLUSIONS

Exposure to temperature variability during fetal organogenesis period of pregnancy is associated with increased risk of major congenital defects. Our findings provide a research foundation for public health policies, and further mechanism investigation.

Hourly temperature variability and mortality in 31 major Chinese cities: Effect modification by individual characteristics, season and temperature zone

BACKGROUND

In the context of ongoing climate change, temperature variability (TV) has been considered as an important trigger of death. However, evidence of association between mortality and hourly temperature variability (HTV) is scarce at the multi-city level, and the time window of health effects of HTV is lack of investigation. This study aims at quantifying the mortality risk and burden of HTV and exploring subpopulations susceptible to HTV from a large-scale multi-city perspective.

METHODS

Data on daily number of deaths and meteorology were collected for 31 Chinese major cities during 2007-2013. HTV was calculated as the standard deviation of hourly temperature within a few days. The optimal exposure period of HTV was chosen according to multiple scientific criteria. A quasi-Poisson regression combined with distributed lag nonlinear model was used to assess the city-specific HTV-mortality associations. Then, meta-analysis was further applied to pool city-specific effect estimates. Finally, we calculated the fraction of mortality attributable to HTV. Stratification analyses were conducted by individual characteristics (i.e. age, sex, and educational attainment), season, and region.

RESULTS

HTV calculated in a relatively long-time window like 18 d (HTV_0-17) could capture the impact of HTV adequately. Per 1 °C raise of HTV_0-17 associated with 1.38% (95%CI: 0.77, 1.99) increase of non-accidental mortality. During the study period, 5.47% (95%CI: 1.06, 9.64) of non-accidental mortality could be attributed to HTV. The females, the elderly, and individuals with low education level were more susceptible to HTV than their counterparts, respectively. Moreover, a stronger HTV-mortality association was observed in individuals who live in warmer season and temperature zone.

CONCLUSION

HTV is associated with a considerable mortality burden, which may be modified by season, geographic and individual-level factors. Our findings highlight the practical importance of establishing early warning systems and promoting health education to mitigate the impacts of temperature variability.

Attributable risks of hospitalizations for urologic diseases due to heat exposure in Queensland, Australia, 1995-2016

BACKGROUND

Heat exposure is a risk factor for urologic diseases. However, there are limited existing studies that have examined the relationship between high temperatures and urologic disease. The aim of this study was to examine the associations between heat exposure and hospitalizations for urologic diseases in Queensland, Australia, during the hot seasons of 1995-2016 and to quantify the attributable risks.

METHODS

We obtained 238 427 hospitalized cases with urologic diseases from Queensland Health between 1 December 1995 and 31 December 2016. Meteorological data were collected from the Scientific Information for Land Owners-a publicly accessible database of Australian climate data that provides daily data sets for a range of climate variables. A time-stratified, case-crossover design fitted with the conditional quasi-Poisson regression model was used to estimate the associations between temperature and hospitalizations for urologic diseases at the postcode level during each hot season (December-March). Attributable rates of hospitalizations for urologic disease due to heat exposure were calculated. Stratified analyses were performed by age, sex, climate zone, socio-economic factors and cause-specific urologic diseases.

RESULTS

We found that a 1°C increase in temperature was associated with a 3.3% [95% confidence interval (CI): 2.9%, 3.7%] increase in hospitalization for the selected urologic diseases during the hot season. Hospitalizations for renal failure showed the strongest increase 5.88% (95% CI: 5.25%, 6.51%) among the specific causes of hospital admissions considered. Males and the elderly (≥60 years old) showed stronger associations with heat exposure than females and younger groups. The sex- and age-specific associations with heat exposure were similar across specific causes of urologic diseases. Overall, nearly one-fifth of hospitalizations for urologic diseases were attributable to heat exposure in Queensland.

CONCLUSIONS

Heat exposure is associated with increased hospitalizations for urologic disease in Queensland during the hot season. This finding reinforces the pressing need for dedicated public health-promotion campaigns that target susceptible populations, especially for those more predisposed to renal failure. Given that short-term climate projections identify an increase in the frequency, duration and intensity of heatwaves, this public health advisory will be of increasing urgency in coming years.

Increased susceptibility to temperature variation for non-accidental emergency ambulance dispatches in Shenzhen, China

Most studies focused on the temporal trend of mortality risk associated with temperature exposure. The relative role of heat, cold, and temperature variation (TV) on morbidity and its temporal trends are explored insufficiently. This study aims to investigate the temporal trends of emergency ambulance dispatch (EAD) risk and the attributable burden of heat, cold, and hourly temperature variation (HTV). We collected time-series data of daily EAD and ambient temperature in Shenzhen from 2010 to 2017. HTV was calculated as the standard deviation of the hourly temperatures between 2 consecutive days. Quasi-Poisson generalized additive models (GAM) with a time-varying distributed lag nonlinear model (DLNM) were applied to examine temporal trends of the HTV-, heat-, and cold-EAD association. The temporal variation of the attributable fraction (AF%) and attributable number (AN) for different temperature exposures was also calculated. The largest RR was observed in extreme cold [1.30 (95% CI: 1.18, 1.43)] and moderate cold [1.25 (95% CI: 1.17, 1.34)]. Significant increasing trends in HTV-related effects and burden were observed, especially for the extreme HTV effects (P for interaction < 0.05). Decreasing trends were observed in the heat-related effect and burden, though it showed no significance (P for interaction = 0.46). There was no clear change pattern of cold-related effects and burdens. Overall, the three temperature exposure caused 13.7% of EAD, of which 4.1%, 4.3%, and 5.3% were attributed to HTV, heat, and cold, respectively. All the temperature indexes in this study, especially the cold effect, are responsible for the increased risk of EAD. People have become more susceptible to HTV over the recent decade. However, there is no clear evidence to support the temporal change of the population's susceptibility to heat and cold. Thus, in addition to heat and cold, the emergency ambulance service department should pay more attention to HTV under climate change.

Temperature variability and asthma hospitalisation in Brazil, 2000-2015: a nationwide case-crossover study

BACKGROUND

Both cold and hot temperature have been associated with the onset of asthma, but it remains largely unknown about the risk of asthma hospitalisation associated with short-term temperature fluctuation or temperature variability (TV).

OBJECTIVE

To explore the association between short-term exposure to TV and asthma hospitalisation in Brazil.

METHODS

Data for asthma hospitalisation and weather conditions were collected from 1816 Brazilian cities between 2000 and 2015. TV was calculated as the SD of all daily minimum and maximum temperatures within 0-7 days prior to current day. A time-stratified case-crossover design was performed to quantify the association between TV and hospitalisation for asthma.

RESULTS

A total of 2 818 911 hospitalisations for asthma were identified during the study period. Each 1°C increase in 0-7 days' TV exposure was related to a 1.0% (95% CI 0.7% to 1.4%) increase in asthma hospitalisations. The elderly were more vulnerable to TV than other age groups, while region and season appeared to significantly modify the associations. There were 159 305 (95% CI 55 293 to 2 58 054) hospitalisations, US$48.41 million (95% CI US$16.92 to US$78.30 million) inpatient costs at 2015 price and 450.44 thousand inpatient days (95% CI 156.08 to 729.91 thousand days) associated with TV during the study period. The fraction of asthma hospitalisations attributable to TV increased from 5.32% in 2000 to 5.88% in 2015.

CONCLUSION

TV was significantly associated with asthma hospitalisation and the corresponding substantial health costs in Brazil. Our findings suggest that preventive measures of asthma should take TV into account.

Air temperature variability and high-sensitivity C reactive protein in a general population of China

BACKGROUND

Along with global climate change, the relationship between temperature variability (TV) and cardiovascular hospitalization and deaths have been well established. However, limited studies were conducted to reveal the underlying mechanism for TV-related cardiovascular diseases.

OBJECTIVES

In the current study, a novel TV calculation, taking account for both interday and intraday TV as well as lag effects, was used to investigate the effect of short-term TV on the level of high-sensitivity C reactive protein (hs-CRP), which is a crucial preclinical predictor for cardiovascular disease (CVD).

RESULTS

Among the 11,623 Chinese population (46.0% male; mean age 49.8 years), the average hs-CRP was 1.4 mg/ L (standard deviation 1.6 mg/L). Statistical significance between TV and hs-CRP was observed for different TV exposure days (TV01-TV07) in adjusted model, with highest effect for TV06. Specifically, per 1 °C increase in TV06 led to 2.241% (95%CI: 1.552%-2.935%) increase in hs-CRP. Female, obesity and elderly population were more susceptible to TV. The largest mediator for the association of TV and hs-CRP was lipoprotein(a), accounting for 8.68%, followed by smoking status (4.78%), alcohol use (3.95%) and systolic BP (3.20%).

CONCLUSION

Short-term TV will significantly increase the level of hs-CRP, suggesting hs-CRP to be the potential biologic mechanisms underlying the cardiovascular effects of TV. And more attention should be paid to unstable weather in the global climate change context. Further developing efficient public health policies on climate change may benefit for global heath.

Socioeconomic inequality in vulnerability to all-cause and cause-specific hospitalisation associated with temperature variability: a time-series study in 1814 Brazilian cities

BACKGROUND

Exposure to temperature variability has been associated with increased risk of mortality and morbidity. We aimed to evaluate whether the association between short-term temperature variability and hospitalisation was affected by local socioeconomic level in Brazil.

METHODS

In this time-series study, we collected city-level socioeconomic data, and daily hospitalisation and weather data from 1814 Brazilian cities between Jan 1, 2000, and Dec 31, 2015. All-cause and cause-specific hospitalisation data was from the Hospital Information System of the Unified Health System in Brazil. City-specific daily minimum and maximum temperatures came from a 0·25° × 0·25° Brazilian meteorological dataset. We represented city-specific socioeconomic level using literacy rate, urbanisation rate, average monthly household income per capita (using the 2000 and 2010 Brazilian census), and GDP per capita (using statistics from the Brazilian Institute of Geography and Statistics for 2000-15), and cities were categorised according to the 2015 World Bank standard. We used quasi-Poisson regression to do time-series analyses and obtain city-specific associations between temperature variability and hospitalisation. We pooled city-specific estimates according to different socioeconomic quartiles or levels using random-effect meta-analyses. Meta-regressions adjusting for demographic and climatic characteristics were used to evaluate the modification effect of city-level socioeconomic indicators on the association between temperature variability and hospitalisation.

FINDINGS

We included a total of 147 959 243 hospitalisations (59·0% female) during the study period. Overall, we estimated that the hospitalisation risk due to every 1°C increase in the temperature variability in the current and previous day (TV_0-1) increased by 0·52% (95% CI 0·50-0·55). For lower-middle-income cities, this risk was 0·63% (95% CI 0·58-0·69), for upper-middle-income cities it was 0·50% (0·47-0·53), and for high-income cities it was 0·39% (0·33-0·46). The socioeconomic inequality in vulnerability to TV_0-1 was especially evident for people aged 0-19 years (effect estimate 1·21% [1·11-1·31] for lower-middle income vs 0·52% [0·41-0·63] for high income) and people aged 60 years or older (0·60% [0·50-0·70] vs 0·43% [0·31-0·56]), and for hospitalisation due to infectious diseases (1·62% [1·46-1·78] vs 0·56% [0·30-0·82]), respiratory diseases (1·32% [1·20-1·44] vs 0·55% [0·37-0·74]), and endocrine diseases (1·21% [0·99-1·43] vs 0·32% [0·02-0·62]).

INTERPRETATION

People living in less developed cities in Brazil were more vulnerable to hospitalisation related to temperature variability. This disparity could exacerbate existing health and socioeconomic inequalities in Brazil, and it suggests that more attention should be paid to less developed areas to mitigate the adverse health effects of short-term temperature fluctuations.

FUNDING

None.

Temperature Variability and Hospital Admissions for Chronic Obstructive Pulmonary Disease: Analysis of Attributable Disease Burden and Vulnerable Subpopulation

Purpose

Chronic obstructive pulmonary disease (COPD) is a major cause of chronic diseases causing considerable social and economic burden globally. Despite substantial evidence on temperature-COPD association, few studies have investigated the acute effect of temperature variability (TV), a potential trigger of exacerbation of COPD disease, and it remains unknown what fraction of the disease burden of COPD is attributable to TV.

Patients and Methods

Based on 71,070 COPD hospitalizations during 2013–2015 in Guangzhou, China, we conducted a time-series analysis using quasi-Poisson regression to assess the association between TV and hospital admission for COPD after adjusting for daily mean temperature. Short-term TV was captured by the standard deviation of hourly or daily temperatures across various exposure days. We also provided the fraction (total number) of COPD attributable to TV. Stratified analyses by admission route, sex, age, occupation, marital status and season were performed to identify vulnerable subpopulations.

Results

We found a linear relationship between TV and COPD hospitalization, with a 1°C increase in hourly TV and daily TV associated with 4.3% (95%CI: 2.2–6.4) and 4.0% (2.3–5.8) increases in COPD, respectively. The greater relative risks of TV identified males, people aged 0–64 years, blue collar, and divorced/widowed people as vulnerable population. There were 12.0% (8500 cases) of COPD hospitalization attributable to hourly TV during the study period. Daily TV produced similar estimates of relative effects (relative risk) but grater estimates of absolute effects (attributable fraction) than hourly TV.

Conclusion

We concluded that TV was an independent risk factor of COPD morbidity, especially among the susceptible subgroups. These findings would be helpful to guide the development of targeted public intervention.

Environmental temperature and human epigenetic modifications: A systematic review

The knowledge about the effects of environmental temperature on human epigenome is a potential key to understand the health impacts of temperature and to guide acclimation under climate change. We performed a systematic review on the epidemiological studies that have evaluated the association between environmental temperature and human epigenetic modifications. We identified seven original articles on this topic published between 2009 and 2019, including six cohort studies and one cross-sectional study. They focused on DNA methylation in elderly people (blood sample) or infants (placenta sample), with sample size ranging from 306 to 1798. These studies were conducted in relatively low temperature setting (median/mean temperature: 0.8-13 °C), and linear models were used to evaluate temperature-DNA methylation association over short period (≤28 days). It has been reported that short-term ambient temperature could affect global human DNA methylation. A total of 15 candidate genes (ICAM-1, CRAT, F3, TLR-2, iNOS, ZKSCAN4, ZNF227, ZNF595, ZNF597, ZNF668, CACNA1H, AIRE, MYEOV2, NKX1-2 and CCDC15) with methylation status associated with ambient temperature have been identified. DNA methylation on ZKSCAN4, ICAM-1 partly mediated the effect of short-term cold temperature on high blood pressure and ICAM-1 protein (related to cardiovascular events), respectively. In summary, epidemiological evidence about the impacts of environment temperature on human epigenetics remains scarce and limited to short-term linear effect of cold temperature on DNA methylation in elderly people and infants. More studies are needed to broaden our understanding of temperature related epigenetic changes, especially under a changing climate.

Mortality risk and burden associated with temperature variability in China, United Kingdom and United States: Comparative analysis of daily and hourly exposure metrics

BACKGROUND

Temperature variability (TV) is closely associated with climate change, but there is no unified TV definition worldwide. Two novel composite TV indexes were developed recently by calculating the standard deviations of several days' daily maximum and minimum temperatures (TV_daily), or hourly mean temperatures (TV_hourly).

OBJECTIVES

This study aimed to compare the mortality risks and burden associated with TV_daily and TV_hourly using large time-series datasets collected from multiple locations in China, United Kingdom and United States.

METHODS

We collected daily mortality and hourly temperature data through 1987 to 2012 from 63 locations in China (8 communities, 2006-2012), United Kingdom (10 regions, 1990-2012), and USA (45 cities, 1987-2000). TV-mortality associations were investigated using a three-stage analytic approach separately for China, UK, and USA. First, we applied a time-series regression for each location to derive location-specific TV-mortality curves. A second-stage meta-analysis was then performed to pool these estimated associations for each country. Finally, we calculated mortality fraction attributable to TV based on above-described location-specific and pooled estimates.

RESULTS

Our dataset totally consisted of 23, 089, 328 all-cause death cases, including 93, 750 from China, 7,573,716 from UK and 15, 421, 862 from USA, respectively. In despite of a relatively wide uncertainty in China, approximately linear relationships were consistently identified for TV_daily and TV_hourly. In the three countries, generally similar lag patterns of TV effects were consistently observed for TV_daily and TV_hourly. A 1 °C rise in TV_daily and TV_hourly at lag 0-7 days was associated with mortality increases of 0.93% (95% confidence interval [CI]: 0.12, 1.74) and 0.97% (0.18, 1.77) in China, 0.33% (0.15, 0.51) and 0.41% (0.21, 0.60) in UK, and 0.55% (0.41, 0.70) and 0.51% (0.35, 0.66) in USA, respectively. Larger attributable fractions were estimated using TV_daily than those using TV_hourly, with estimates at 0-10 days of 3.69% (0.51, 6.75) vs. 2.59% (0.10, 5.01) in China, 1.14% (0.54, 1.74) vs. 0.98% (0.55, 1.42) in UK, and 2.57% (1.97, 3.16) vs. 1.67% (1.15, 2.18) in USA, respectively. Our meta-regression analyses indicated higher vulnerability to TV-induced mortality risks in warmer locations.

CONCLUSIONS

Our study added multi-country evidence for increased mortality risk associated with short-term exposure to large temperature variability. Daily and hourly TV exposure metrics produced generally comparable risk effects, but the attributable mortality burden tended to be higher using TV_daily instead of TV_hourly.

Monthly-Term Associations Between Air Pollutants and Respiratory Morbidity in South Brazil 2013-2016: A Multi-City, Time-Series Analysis

Most air pollution research conducted in Brazil has focused on assessing the daily-term effects of pollutants, but little is known about the health effects of air pollutants at an intermediate time term. The objective of this study was to determine the monthly-term association between air pollution and respiratory morbidity in five cities in South Brazil. An ecological time-series study was performed using the municipality as the unit of observation in five cities in South Brazil (Gravataí, Triunfo, Esteio, Canoas, and Charqueadas) between 2013 and 2016. Data for hospital admissions was obtained from the records of the Hospital Information Service. Air pollution data, including PM₁₀, SO₂, CO, NO₂, and O₃ (µg/m³) were obtained from the environmental government agency in Rio Grande do Sul State. Panel multivariable Poisson regression models were adjusted for monthly counts of respiratory hospitalizations. An increase of 10 μg/m³ in the monthly average concentration of PM₁₀ was associated with an increase of respiratory hospitalizations in all age groups, with the maximum effect on the population aged between 16 and 59 years (IRR: Incidence rate ratio 2.04 (95% CI: Confidence interval = 1.97–2.12)). For NO₂ and SO₂, stronger intermediate-term effects were found in children aged between 6 and 15 years, while for O₃ higher effects were found in children under 1 year. This is the first multi-city study conducted in South Brazil to account for intermediate-term effects of air pollutants on respiratory health.

Ambient heat and hospitalisation for COPD in Brazil: a nationwide case-crossover study

Background

Heat exposure has been related to increased morbidity and mortality for several health outcomes. There is little evidence whether this is also true for COPD. This study quantified the relationship between ambient heat and hospitalisation for COPD in the Brazilian population.

Methods

Data on hospitalisations for COPD and weather conditions were collected from 1642 cities during the 2000–2015 hot seasons. A time-stratified, case-crossover design was used for city-specific analyses, which were then pooled at the regional and national levels using random-effect meta-analyses. Stratified analyses were performed by sex, age group and early/late hot season. Annual change in the association was examined using a random-effect meta-regression model.

Results

The OR of hospitalisation was 1.05 (95% CI 1.04 to 1.06) for every 5℃ increase in daily mean temperature at the national level, with the effect estimate stronger in the late hot season compared with the early hot season. The effect was similar in women and in men but was greatest for those aged ≥75 years. The association was stronger in the central west and southeast regions and minimal in the northeast. Assuming a causal relationship, 7.2% of admissions were attributable to heat exposure. There was no significant temporal decline in the impact of ambient heat over the 16-year study period.

Conclusion

In Brazil, exposure to ambient heat was positively associated with hospitalisation for COPD, particularly during the late hot season. These data add to the growing evidence base implicating global warming as being an important contributor to the future healthcare burden.

The association between temperature variability and cause-specific mortality: Evidence from 47 Japanese prefectures during 1972-2015

BACKGROUND

In the context of climate change, extreme temperature events are known to be associated with increased mortality risk. However, data about the mortality risk related to temperature variability (TV) accounting for both intra- and inter-day variations in temperature are limited.

OBJECTIVES

The present study aims to quantify the associations between TV and cause-specific mortality in Japan, evaluate whether the effects of TV are modified by prefecture-level characteristics and examine the temporal trend in mortality risk of TV.

METHODS

Data on daily all-cause and 11 cause-specific mortality and meteorological variables in 47 Japanese prefectures from 1972 to 2015 were collected. TV was defined as the standard deviation of daily minimum and maximum temperatures during exposure days. A quasi-Poisson regression model combined with a distributed lag non-linear model was firstly applied to assess the prefecture-specific mortality effects of TV, adjusting for potential confounders. The pooled effects of TV at the national level were then obtained via a meta-analysis through the restricted maximum-likelihood estimation. Potential effect modification by prefecture characteristics was firstly examined using a meta-regression analysis, and the joint modification of season and humidity was then evaluated after including product terms in two-stage analyses. Finally, the temporal trend in TV effects was evaluated by a random-effect meta regression model after obtaining the prefecture-year-specific effects.

RESULTS

TV had significant adverse effects on all-cause and cause-specific mortality. The effects of TV were more detrimental to those with asthma and senility. In general, the estimates of mortality risk increased with longer exposure days. A 1 °C increase in TV at 0-7 days of exposure was associated with a 0.9% (95% confidence intervals: 0.82%-0.98%) increase in all-cause mortality. All-cause mortality risk of TV showed a decreasing trend during our study period. TV effects were larger in densely populated prefectures and on warm and humid days.

CONCLUSIONS

TV-related death is a significant issue in Japan that requires effective interventions.

Temperature variability and hospitalization for ischaemic heart disease in Brazil: A nationwide case-crossover study during 2000-2015

BACKGROUND

Previous studies have suggested a potential relationship between temperature variability (TV) and ischaemic heart disease (IHD) but the nature and strength differ between studies. We quantify the association between TV and risk of hospitalization for IHD across Brazilian regions and examine how the relationship varies across important population subgroups.

METHODS

Data on hospitalization for IHD and meteorological parameters were collected from 1814 cities during 2000-2015. TV was defined as the standard deviation of daily minimum and maximum temperatures during exposure days. City-specific estimates were quantified using a time-stratified case-crossover approach, and then pooled at the national level using a random-effect meta-analysis. Stratified analyses were performed by region, sex and three age-groups.

RESULTS

There were 2,864,904 IHD hospitalizations during 2000-2015. The estimate of TV effect was strongest on 0-1 days' exposure: odds ratio was 1.019 [95% confidence interval (CI): 1.013-1.025] per 5 °C increase in TV. The relationship was stronger in men [1.025 (95%CI: 1.017-1.033)] than in women [1.011 (95%CI: 1.002-1.019)] and in successively older age groups [1.034 (95%CI: 1.018-1.050)]. Regional differences existed, with the association only apparent in the most ageing parts of Brazil.

CONCLUSIONS

Exposure to TV is associated with increased risk of hospitalization for IHD, particularly in men and in older age groups. Our findings add to the growing evidence regarding the potential impact of climatic factors on important health outcomes.

Temperature variability and hospitalization for cardiac arrhythmia in Brazil: A nationwide case-crossover study during 2000-2015

BACKGROUND

There is growing recognition of a potential role for environmental and climatic factors in influencing cardiovascular risk. It has been speculated that temperature variability (TV) is a risk factor for cardiac arrhythmia but evidence is limited.

OBJECTIVE

To quantify the geographic and demographic variations in the association between TV and hospitalization for cardiac arrhythmia in Brazil during 2000-2015.

METHODS

Data on hospitalization for arrhythmia and weather conditions were collected from 1,814 cities. TV was calculated as the standard deviation of daily maximum and minimum temperatures during exposure days. A time-stratified case-crossover approach was applied to examine the city-specific association between TV and hospitalization for arrhythmia. City-specific estimates were pooled at the national and regional levels using a random-effect meta-analysis. Stratified analyses were conducted by sex, three age-groups (0-64, 65-74 and ≥75 years), and three arrhythmia subtypes (paroxysmal tachycardia, atrial fibrillation and flutter, and other arrhythmias).

RESULTS

There were 447,667 arrhythmia-related hospitalizations during 2000-2015. The odds ratio of hospitalization per 1 °C increase in TV peaked on 0-1 days' exposure [1.012 (95% confidence interval: 1.010-1.015)]. There were no substantial differences in effect estimates of TV_0-1 by region, age or sex, except for the non-significant association observed in the north. However, women were more affected by prolonged TV exposure than men. For the three arrhythmias subtypes, only paroxysmal tachycardia and other arrhythmias were sensitive to TV. Assuming a causal relationship, 35,813 (95%CI: 18,302-51,665) cases were attributable to TV_0-1 in Brazil during 2000-2015, accounting for 8.0% (95%CI: 4.1-11.5%) of hospitalizations for cardiac arrhythmia.

CONCLUSIONS

At a population-level exposure to TV was associated with increased risk of arrhythmia-related hospitalization in Brazil, with the relationship equally distributed across most residents but varied by arrhythmia subtypes. Our findings add to the accumulating evidence-base that climatic factors can influence cardiovascular outcomes in populations.

Assessment of Intraseasonal Variation in Hospitalization Associated With Heat Exposure in Brazil

IMPORTANCE

The onset of the hot season is known to be adversely associated with a range of health outcomes. However, little is known about whether the association is constant over the course of the hot season.

OBJECTIVE

To quantify the change in the association between heat exposure and hospitalization from the early to late hot season in the Brazilian population.

DESIGN, SETTING, AND PARTICIPANTS

This time-stratified case-crossover study used daily data on hospitalization and weather conditions during the 2000 to 2015 hot seasons in 1814 Brazilian cities. There were 49 145 997 admissions during the study period. Data analysis was conducted between May 12, 2018, and July 2, 2018.

EXPOSURES

Increase in daily mean temperature.

MAIN OUTCOMES AND MEASURES

Daily hospitalizations were recorded. Conditional quasi-Poisson regression with time-varying constrained distributed lag model was used to examine the city-specific association between heat and hospitalization in the early or late hot season. City-specific estimates were then pooled at the national level using random-effect meta-analysis. Stratified analyses were conducted by 5 regions, sex, 10 age groups, and 7 cause-specific categories.

RESULTS

Of the 49 145 997 admissions (59% women), the median (interquartile range) age was 33.3 (19.8-55.7) years. At the national level, the risk of hospitalization increased by 4.6% (95% CI, 4.3%-4.9%) and 2.3% (95% CI, 1.9%-2.6%) for every 5°C increase in daily mean temperature in the early and late hot season, respectively. Exposure to early heat was associated with greater risk of hospitalization for residents in the northeast (6.4%; 95% CI, 5.5%-7.3%) and central west (7.1%; 95% CI, 6.1%-8.2%) compared with other regions. Children aged 0 to 9 years and elderly individuals (aged ≥80 years) were most susceptible. Admissions due to endocrine, nutritional, and metabolic diseases were most strongly associated with heat exposure. There was an attenuation in the heat-associated risk of hospitalization from the early to late hot season for all subgroups except young children and patients with hospitalization caused by respiratory illness.

CONCLUSIONS AND RELEVANCE

In this study, the association between heat exposure and hospitalization attenuated temporally for most of the Brazilian population. Preventive strategies to mitigate the association of high temperature with population health should focus in particular on the first few days of heat exposure.

The association between heatwaves and risk of hospitalization in Brazil: A nationwide time series study between 2000 and 2015

BACKGROUND

To our knowledge, no study has assessed the association between heatwaves and risk of hospitalization and how it may change over time in Brazil. We quantified the heatwave-hospitalization association in Brazil during 2000-2015.

METHODS AND FINDINGS

Daily data on hospitalization and temperature were collected from 1,814 cities (>78% of the national population) in the hottest five consecutive months during 2000-2015. Twelve types of heatwaves were defined with daily mean temperatures of ≥90th, 92.5th, 95th, or 97.5th percentiles of year-round temperature and durations of ≥2, 3, or 4 consecutive days. The city-specific association was estimated using a quasi-Poisson regression with constrained distributed lag model and then pooled at the national level using random-effect meta-analysis. Stratified analyses were performed by five regions, sex, 10 age groups, and nine cause categories. The temporal change in the heatwave-hospitalization association was assessed using a time-varying constrained distributed lag model. Of the 58,400,682 hospitalizations (59% women), 24%, 34%, 21%, and 19% of cases were aged <20, 20-39, 40-59, and ≥60 years, respectively. The city-specific year-round daily mean temperatures were 23.5 ± 2.8 °C on average, varying from 26.8 ± 1.8 °C for the 90th percentile to 28.0 ± 1.6 °C for the 97.5th percentile. We observed that the risk of hospitalization was most pronounced for heatwaves characterized by high daily temperatures and long durations across Brazil, except for the minimal association in the north (the hottest region). After controlling for temperature, the association remained for severe heatwaves in the south and southeast (cold regions). Children 0-9 years, the elderly ≥70 years, and admissions for perinatal conditions were most strongly associated with heatwaves. Over the study period, the strength of the heatwave-hospitalization association declined substantially in the south, while an apparent increase was observed in the southeast. The main limitations of this study included the lack of data on individual temperature exposure and measured air pollution.

CONCLUSIONS

There are geographic, demographic, cause-specific, and temporal variations in the heatwave-hospitalization associations across the Brazilian population. Considering the projected increase in frequency, duration, and intensity of heatwaves, future strategies should be developed, such as building early warning systems, to reduce the health risk associated with heatwaves in Brazil.

Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015

BACKGROUND

Limited evidence is available regarding the association between heat exposure and morbidity in Brazil and how the effect of heat exposure on health outcomes may change over time.

OBJECTIVES

This study sought to quantify the geographic, demographic and temporal variations in the heat–hospitalization association in Brazil from 2000–2015.

METHODS

Data on hospitalization and meteorological conditions were collected from 1,814 cities during the 2000–2015 hot seasons. Quasi-Poisson regression with constrained lag model was applied to examine city-specific estimates, which were then pooled at the regional and national levels using random-effect meta-analyses. Stratified analyses were performed by sex, 10 age groups, and 11 cause categories. Meta-regression was used to examine the temporal change in estimates of heat effect from 2000 to 2015.

RESULTS

For every 5°C increase in daily mean temperature during the 2000–2015 hot seasons, the estimated risk of hospitalization over lag 0-7 d rose by 4.0% [95% confidence interval (CI): 3.7%, 4.3%] nationwide. Estimated 6.2% [95% empirical CI (eCI): 3.3%, 9.1%] of hospitalizations were attributable to heat exposure, equating to 132 cases (95% eCI: 69%, 192%) per 100,000 residents. The attributable rate was greatest in children [Formula: see text] and was highest for hospitalizations due to infectious and parasitic diseases. Women of reproductive age and those [Formula: see text] had higher heat burden than men. The attributable burden was greatest for cities in the central west and the inland of the northeast; lowest in the north and eastern coast. Over the 16-y period, the estimated heat effects declined insignificantly at the national level.

CONCLUSIONS

In Brazil's hot seasons, 6% of hospitalizations were estimated to be attributed to heat exposure. As there was no evidence indicating that thermal adaptation had occurred at the national level, the burden of hospitalization associated with heat exposure in Brazil is likely to increase in the context of global warming. https://doi.org/10.1289/EHP3889.