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

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.

Association between ambient temperature and genitourinary emergency ambulance dispatches in Japan: A nationwide case-crossover study

Background

Although the effects of temperature on genitourinary morbidity and mortality have been investigated in several countries, it remains largely unexplored in Japan. We investigated the association between ambient temperature and genitourinary emergency ambulance dispatches (EADs) in Japan and the modifying roles of sex, age, and illness severity.

Methods

We conducted a time-stratified case-crossover study with conditional quasi-Poisson regression to estimate the association between mean temperature and genitourinary EADs in all prefectures of Japan between 2015 and 2019. A mixed-effects meta-analysis was used to pool the association at the country level. Subgroup analyses were performed to explore differences in associations stratified by sex, age, and illness severity.

Results

We found an increased risk of genitourinary EAD associated with higher temperatures. The cumulative relative risk (RR) at the 99th temperature percentile compared with that at the 1st percentile was 1.74 (95% confidence interval (CI) = [1.60, 1.89]). We observed higher heat-related RRs in males (RR = 1.89; 95% CI = [1.73, 2.07]) than females (RR = 1.56; 95% CI = [1.37, 1.76]), and in the younger (RR = 2.13; 95% CI = [1.86, 2.45]) than elderly (RR = 1.39; 95% CI = [1.22, 1.58]). We found a significant association for those with mild or moderate cases (RR = 1.77; 95% CI = [1.62, 1.93]), but not for severe or life-threatening cases (RR = 1.20; 95% CI = [0.80, 1.82]).

Conclusion

Our study revealed heat effects on genitourinary EADs in Japan. Men, youth, and mild-moderate illnesses were particularly vulnerable subgroups. These findings underscore the need for preventative measures aimed at mitigating the impact of temperature on genitourinary emergencies.

Modification effects of long-term air pollution levels on the relationship between short-term exposure to meteorological factors and hand, foot, and mouth disease: A distributed lag non-linear model-based study in Shandong Province, China

The occurrence of hand, foot, and mouth disease (HFMD) is closely related to meteorological factors. However, location-specific characteristics, such as persistent air pollution, may increase the complexity of the impact of meteorological factors on HFMD, and studies across different areas and populations are largely lacking. In this study, a two-stage multisite time-series analysis was conducted using data from 16 cities in Shandong Province from 2015 to 2019. In the first stage, we obtained the cumulative exposure-response curves of meteorological factors and the number of HFMD cases for each city. In the second stage, we merged the estimations from the first stage and included city-specific air pollution variables to identify significant effect modifiers and how they modified the short-term relationship between HFMD and meteorological factors. High concentrations of air pollutants may reduce the risk effects of high average temperature on HFMD and lead to a distinct peak in the cumulative exposure-response curve, while lower concentrations may increase the risk effects of high relative humidity. Furthermore, the effects of average wind speed on HFMD were different at different levels of air pollution. The differences in modification effects between subgroups were mainly manifested in the diversity and quantity of significant modifiers. The modification effects of long-term air pollution levels on the relationship between sunshine hours and HFMD may vary significantly depending on geographical location. The people in age＜3 and male groups were more susceptible to long-term air pollution. These findings contribute to a deepening understanding of the relationship between meteorological factors and HFMD and provide evidence for relevant public health decision-making.

Extreme temperatures increase the risk of pediatric pneumonia: a systematic review and meta-analysis

Introduction

The impact of climate change on ambient temperatures threatens to worsen pediatric pneumonia-related outcomes considerably. This study examined the associations of temperature variation and extreme temperature with pediatric pneumonia-related events using a meta-analysis.

Methods

We systematically searched PubMed, Medline, Embase, and Web of Science databases for relevant literature, and the quality of evidence was assessed. Fixed and random-effects meta-analyses were performed to calculate the pooled relative risks (RRs) of the associations with pneumonia-related events.

Results

We observed that a 1°C temperature variation increased the RR of pneumonia events by 1.06-fold (95% confidence interval (CI): 1.03-1.10). A 1°C temperature variation increased the RR by 1.10-fold of the pediatric pneumonia hospital admissions (95% CI: 1.00-1.21) and 1.06-fold of the pediatric pneumonia emergency department visits (95% CI: 1.01-1.10). Extreme cold increased the RR by 1.25-fold of the pediatric pneumonia events (95% CI: 1.07-1.45). A 1°C temperature variation increased the RR of pneumonia events in children by 1.19-fold (95% CI: 1.08-1.32), girls by 1.03-fold (95% CI: 1.02-1.05), and in temperate climate zones by 1.07-fold (95% CI: 1.03-1.11). Moreover, an increase in extreme cold increased the RR of pneumonia events in children by 2.43-fold (95% CI: 1.72-3.43), girls by 1.96-fold (95% CI: 1.29-2.98) and in temperate climate zones by 2.76-fold (95% CI: 1.71-4.47).

Conclusion

Our study demonstrated that pediatric pneumonia events are more prevalent among children, particularly girls, and individuals residing in temperate climate zones. Climate change represents an emergent public health threat, affecting pediatric pneumonia treatment and prevention..

Systematic Review Registration

PROSPERO (CRD42022378610).

Distribution of water turnover by sex and age as estimated by prediction equation in Japanese adolescents and adults: the 2016 National Health and Nutrition Survey, Japan

BACKGROUND

Although water is essential to the maintenance of health and life, standard values for human water requirements are yet to be determined. This study aimed to evaluate the distribution of water turnover (WT) according to sex and age, estimated using a prediction equation, in Japanese adolescents and adults.

METHODS

This cross-sectional study used data from the 2016 National Health and Nutrition Survey, Japan. Data were obtained from electronically available aggregated reports in the survey's official website. Participants aged between 15 and 80 years (10,546 men, 12,355 women) were selected using stratified random sampling. WT was calculated considering lifestyle and environmental factors, and using an equation (coefficient of determination = 0.471) previously developed by the international doubly labelled water (DLW) database group. As data on physical activity levels (PAL) were not collected in the survey, we used two evaluation methods: (1) energy intake assessed by dietary records and (2) total energy expenditure measured by the DLW method reported in previous Japanese studies, divided by basal metabolic rate predicted using the equation. We evaluated the relationship between WT and age using a restricted cubic spline model.

RESULTS

The average WT for the 15-19, 20-29, 30-39, 40-49, 50-59, 60-69, and ≥ 70 years was 3291, 3151, 3213, 3243, 3205, 3104, and 2790 ml/day, respectively in men, and 2641, 2594, 2741, 2739, 2753, 2707, and 2482 ml/day, respectively in women. In the spline model, WT showed an inverse association with age in men older than 50 years, whereas women showed a reverse U-shaped relationship between WT and age (p for non-linearity < 0.001), although results differed with body weight adjustment. Similar results were found for both PAL evaluation methods, and the range of WT per body weight was 45-56 ml/day for both sexes.

CONCLUSIONS

We determined the standard values of WT in Japanese population using a prediction equation and national large-scale survey data. These findings may be useful for setting water requirements for dietary guidelines in future.

Cause-specific mortality and burden attributable to temperature variability in China

BACKGROUND

Few large-scale, nationwide studies have assessed cause-specific mortality risks and burdens associated with temperature variability (TV).

OBJECTIVE

To estimate associations between TV and cause-specific mortality and quantify the mortality burden in China.

METHODS

Data on daily total and cause-specific mortality in 272 Chinese cities between 2013 and 2015 were recorded. TVs were computed as the standard deviations of daily minimum and maximum temperatures over a duration of 2 to 7 days. The time-series quasi-Poisson regression model with adjustment of the cumulative effects of daily mean temperature over the same duration was applied to evaluate the city-specific associations of TV and mortality. Then, we pooled the effect estimates using a random-effects meta-analysis and calculated the mortality burdens.

RESULTS

Overall, TV showed significant and positive associations with total and cause-specific mortality. The TV-mortality associations were generally stronger when using longer durations. A 1 °C increase in TV at 0-7 days (TV0-7) was associated with a 0.79 % [95 % confidence interval (CI): 0.55 %, 0.96 %] increase in total mortality. Mortality fractions attributable to TV0-7 were 4.37 % for total causes, 4.75 % for overall cardiovascular disease, 4.37 % for coronary heart disease, 5.05 % for stroke, 8.28 % for ischaemic stroke, 1.08 % for haemorrhagic stroke, 6.93 % for respiratory disease, and 6.81 % for COPD, respectively. The mortality risk and burden were generally higher in the temperate monsoon zone, females, and elders.

CONCLUSION

This nationwide study indicated that TV was an independent risk factor of mortality, and could result in significant burden for main cardiorespiratory diseases.

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.

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.

Ambient temperature variability and blood pressure in a prospective cohort of 50,000 Chinese adults

Blood pressure has been shown to change by outdoor temperature, but whether intra- and inter-day temperature variability (TV) will bring higher effect on BP is not clear. Based on a prospective cohort study, the mixed effect model was selected to estimate the relationship between TV (daily temperature variability (DTV) and hourly temperature variability (HTV)) and BP (systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), and mean arterial pressure (MAP)) after adjusting for confounding variables. We found that there was a positive linear correlation between TV and BP. The results of DTV and HTV were basically consistent, but the effect estimates of HTV seemed to be larger. Gender, age, BMI, education level and BP status may modify the relationship between TV and BP. The effect of TV on BP was greater in non-heating season than in heating season. Our work contributes to a further macro mechanism evidence for the TV-CVDs association.

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.

Short-term association of air pollution with lung cancer mortality in Osaka, Japan

Long-term air pollution exposure has been linked to increased lung cancer mortality. However, little is known about whether day-to-day fluctuations in air pollution levels are in relation to lung cancer mortality, particularly in low-exposure settings. This study aimed to evaluate the short-term associations between air pollution and lung cancer mortality. Daily data on lung cancer mortality, fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and weather conditions were collected from Osaka Prefecture, Japan, from 2010 to 2014. Generalized linear models were combined with quasi-Poisson regression were applied to evaluate the associations between each air pollutant and lung cancer mortality after adjusting for potential confounders. Mean (standard deviation) concentrations of PM_2.5, NO₂, SO₂, and CO were 16.7 (8.6) μg/m³, 36.8 (14.2) μg/m³, 11.1 (4.0) μg/m³, and 0.51 (0.16) mg/m³, respectively. Interquartile range increases in concentrations of PM_2.5, NO₂, SO₂, and CO (2-d moving average) were associated with 2.65% (95% confidence intervals [CIs]: 0.96%-4.37%), 4.28% (95% CIs: 2.24%-6.36%), 3.35% (95% CIs: 1.03%-5.73%), and 4.60% (95% CIs: 2.19%-7.05%) increased risk of lung cancer mortality, respectively. Stratified analyses showed that the associations were strongest in the older population and men. Exposure‒response curves showed a continuously increasing mortality risk from lung cancer with elevation of air pollution levels, without discernible thresholds. In summary, we found evidence of increased lung cancer mortality in relation to short-term elevations in ambient air pollution. These findings may merit further research to better understand this issue.

Seasonal characteristics of ambient temperature variation (DTR, TCN, and TV0-t) and air pollutants on childhood asthma attack in a dry and cold city in China

Very few researches have concentrated on a variety of time scales to evaluate the association between temperature variation (TV) and childhood asthma (CA), and the evidence for the interaction of air pollutants on this association is lacking. In this study, we aim to estimate the relative risks (RRs) of CA due to TV by following metrics: diurnal temperature range (DTR), temperature changes between neighboring days (TCN), and temperature variability (TV_0-t); to quantify the seasonal attributable fraction (AF) and number (AN) of CA due to TV; to examine the interactive effects of the TV and air pollutants on CA in different seasons. We mainly applied distributed lagged nonlinear model (DLNM) and conditional Poisson models to evaluate the associations between TV and outpatient visits for CA during 2014-2019 in Lanzhou, China. Additionally, the bivariate response surface model was used to examine the interplay effect of air pollutants. We found that in warm season, the risks of DTR maximum at lag5 (RR = 1.073, 95% CI: 1.017-1.133); TCN showed protective effect. In cold season, the risks of DTR peaked at lag8 (RR = 1.063, 95% CI: 1.027-1.100); the risks of TCN maximum at lag0 (RR = 1.058 95% CI: 1.009-1.109); the estimation of total cases maximized at TV_0-4 in cold season (RR = 1.039 at TV_0-3, 95% CI: 1.001, 1.077) and was the lowest at TV_0-1 in warm season (RR = 0.999, 95% CI: 0.969, 1.030). In addition, the response surface model graphically pictured ambient air pollutants enhanced the DTR/TV_0-4-CA effect for girls. In conclusion, the RRs of CA are markedly increased by TV exposure, particularly during the colder months. A combined evaluation of DTR, TCN, TV_0-5∼TV_0-6, NO₂, SO₂, and PM_2.5 should be used to identify the adverse effects of TV on CA.

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.

Mortality burden attributable to temperature variability in China

BACKGROUND

Several studies have investigated the associations between temperature variability (TV) and death counts. However, evidence of TV-attributable years of life lost (YLL) is scarce.

OBJECTIVES

To investigate the associations between TV and YLL rates (/100,000 population), and quantify average life loss per death (LLD) caused by TV in China.

METHODS

We calculated daily YLL rates (/100,000 population) of non-accidental causes and cardiorespiratory diseases by using death data from 364 counties of China during 2006-2017, and collected meteorological data during the same period. A distributed lag non-linear model (DLNM) and multivariate meta-analysis were used to estimate the effects of TV at national or regional levels. Then, we calculated the LLD to quantify the mortality burden of TV.

RESULTS

U-shaped curves were observed in the associations of YLL rates with TV in China. The minimum YLL TV (MYTV) was 2.5 °C nationwide. An average of 0.89 LLD was attributable to TV in total, most of which was from high TV (0.86, 95% CI: 0.56, 1.16). However, TV caused more LLD in the young (<65 years old) (1.87, 95% CI: 1.03, 2.71) than 65-74 years old (0.85, 95% CI: 0.40-1.31) and ≥75 years old (0.40, 95% CI: 0.21-0.59), cerebrovascular disease (0.74, 95% CI: 0.36, 1.11) than respiratory disease (0.54, 95% CI: 0.21, 0.87), South (1.23, 95% CI: 0.77, 1.68) than North (0.41, 95% CI: -0.7, 1.52) and Central China (0.40, 95% CI: -0.02, 0.81). TV-attributed LLD was modified by annual mean temperature, annual mean relative humidity, altitude, latitude, longitude, and education attainment.

SIGNIFICANCE

Our findings indicate that high and low TVs are both associated with increases in premature death, however the majority of LLD was attributable to high TV. TV-related LLD was modified by county level characteristics. TV should be considered in planning adaptation to climate change or variability.

IMPACT

(1) We estimated the associations of TV with YLL rates, and quantified the life loss per death (LLD) caused by TV. (2) An average of 0.89 years of LLD were attributable to TV, most of which were from high TVs. (3) TV caused more LLD in the young, cerebrovascular disease, and southern China. (4) The mortality burdens were modified by county level characteristics.

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.

Seasonal variation in association between temperature change and emergency department visits: A multi-site study in China

BACKGROUND

There is limited evidence of effects and seasonal variation of temperature change on emergency department visits (EDVs).

OBJECTIVE

To investigate the association between diurnal temperature range (DTR), temperature change between neighboring days (TCN) and a comprehensive collection of cause-specific EDVs in China.

METHODS

We collected EDVs, weather, and air pollution data in 20 sites in China from 2014 to 2018. We applied a quasi-Poisson regression with distributed lag nonlinear model to evaluate DTR- and TCN-EDVs association. We used meta-analysis to pool site-specific estimates. We also conducted seasonal analysis and assess effects of modifiers.

RESULTS

A 1 °C increase of DTR and TCN was associated with 0.29% [95% confidence interval (CI): 0.07%, 0.51%)] and 1.44% (95% CI: 0.93%, 1.96%) increase of total EDVs, respectively. People aged 18-44 were sensitive to DTR and TCN, while the elderly population was sensitive to TCN only in spring and autumn. In seasonal analysis, effects of temperature change on total EDVs were lower in summer. TCN increased risks of genitourinary diseases in summer, respiratory diseases in winter, injury in autumn, and mental diseases in spring. DTR increased the risk of respiratory diseases in autumn.

CONCLUSION

Exposure to DTR and TCN was associated with elevated risk of EDVs but with great seasonal variations. Our results provided potential time and target populations for adaptive strategies and preventive measures.

Long-term air pollution levels modify the relationships between short-term exposure to meteorological factors, air pollution and the incidence of hand, foot and mouth disease in children: a DLNM-based multicity time series study in Sichuan Province, China

BACKGROUND

Epidemiological studies have investigated the short-term effects of meteorological factors and air pollution on the incidence of hand, foot, and mouth disease (HFMD). Several meteorological indicators, such as relative humidity and the diurnal temperature range (DTR), significantly modify the relationship between short-term exposure to temperature and HFMD incidence. However, it remains unclear whether (and how) long-term air pollution levels modify the short-term relationships of HFMD incidence with meteorological factors and air pollution.

METHODS

We obtained daily data on meteorological factors, air pollutants, and HFMD counts in children from 21 prefecture-level cities in Sichuan Province in Southwest China from 2015 to 2017. First, we constructed a distributed lag nonlinear model (DLNM) at each prefecture-level site to evaluate the short-term impacts of meteorological variables and air pollutants on HFMD incidence. Then, we assessed the pooled effects of the exposures and incorporated long-term city-specific air pollutant indicators as meta-predictors to examine their potential modification effects by performing multivariate meta-regression models.

RESULTS

We found that long-term SO₂ and CO concentrations significantly modified the short-term relationships between climatic variables and HFMD incidence. Specifically, high concentrations of CO (P = 0.027) and SO₂ (P = 0.039) reduced the risk of HFMD at low temperatures. The relationship between relative humidity and HFMD incidence was weakened at high SO₂ concentrations (P = 0.024), especially when the relative humidity was below the median level. When the minimum relative humidity (32%) was compared to the median relative humidity (77%), the risk ratio (RR) was 0.77 (95% CI: 0.51-1.17) in the 90^th percentile of SO₂ (19.6 μg/m³) and 0.41 (95% CI: 0.27-0.64) in the 10^th percentile of SO₂ (10.6 μg/m³).

CONCLUSION

Our results indicated that long-term SO₂ and CO levels modified the short-term associations between HFMD incidence in children and meteorological variables. These findings may inform health authorities to optimize targeted public health policies including reducing ambient air pollution and reinforcing self-protective actions to weaken the adverse health impacts of environmental factors on HFMD incidence.

Temperature Change between Neighboring Days Contributes to Years of Life Lost per Death from Respiratory Disease: A Multicounty Analysis in Central China

BACKGROUND

Many epidemiological studies have recently assessed respiratory mortality attributable to ambient temperatures. However, the associations between temperature change between neighboring days and years of life lost are insufficiently studied. Therefore, we assessed the attributable risk of temperature change between neighboring days on life loss due to respiratory disease.

METHODS

We obtained daily mortality and weather data and calculated crude rates of years of life lost for 70 counties in Hunan Province, Central China, from 2013 to 2017. A time-series design with distributed lag nonlinear model and multivariate meta-regression was used to pool the relationships between temperature change between neighboring days and rates of years of life lost. Then, we calculated the temperature change between neighboring days related to average life loss per death from respiratory disease.

RESULTS

The total respiratory disease death was 173,252 during the study period. The association between temperature change and years of life lost rates showed a w-shape. The life loss per death attributable to temperature change between neighboring days was 2.29 (95% CI: 0.46-4.11) years, out of which 1.16 (95% CI: 0.31-2.01) years were attributable to moderately high-temperature change between neighboring days, and 0.99 (95% CI: 0.19-1.79) years were attributable to moderately low-temperature change between neighboring days. The temperature change between neighboring days related to life loss per respiratory disease death for females (2.58 years, 95% CI: 0.22-4.93) and the younger group (2.97 years, 95% CI: -1.51-7.44) was higher than that for males (2.21 years, 95% CI: 0.26-4.16) and the elderly group (1.96 years, 95% CI: 0.85-3.08). An average of 1.79 (95% CI: 0.18-3.41) life loss per respiratory disease death was related to non-optimal ambient temperature.

CONCLUSIONS

The results indicated that more attention should be given to temperature change, and more public health policies should be implemented to protect public health.

Seasonal characteristics of temperature variability impacts on childhood asthma hospitalization in Hefei, China: Does PM2.5 modify the association?

OBJECTIVES

Evidence of childhood asthma hospitalizations associated with temperature variability (TV) and the attributable risk are limited in China. We aim to use a comprehensive index that reflected both intra- and inter-day TV to assess the TV-childhood asthma relationship and disease burden, further to identify seasonality vulnerable populations, and to explore the effect modification of PM_2.5.

METHODS

A quasi-distributed lagged nonlinear model (DLNM) combined with a linear threshold function was applied to estimate the association between TV and childhood asthma hospitalizations during 2013-2016 in Hefei, China. Subgroup analysis was conducted by age and sex. Disease burden is reflected by the attributable fraction and attributable number. Besides, modifications of PM_2.5 were tested by introducing the cross-basis of TV and binary PM_2.5 as an interaction term.

RESULTS

The risk estimates peaked at TV_0-3 and TV_0-4 in the cool and the warm season separately, with RR of 1.051 (95%CI: 1.021-1.081) and 1.072 (95%CI: 1.008-1.125), and the effects lasted longer in the cool season. The school-age children in the warm season and all subgroups except pre-school children in the cool season were vulnerable to TV. It is estimated that the disease burden related to TV account for 6.2% (95% CI: 2.7%-9.4%) and 4% (95% CI: 0.6%-7.1%) during the cool and warm seasons in TV_0-3. In addition, the risks of TV were higher under the high PM_2.5 level compared with the low PM_2.5 level in the cool season, although no significant differences between them.

CONCLUSIONS

TV exposure significantly increases the risk and disease burden of childhood asthma hospitalizations, especially in the cool season. More medical resources should be allocated to school-age children. Giving priority to pay attention to TV in the cool season in practice could obtain the greatest public health benefits and those days with high TV and high PM_2.5 need more attention.

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.

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.

Temporal trends of the association between temperature variation and hospitalizations for schizophrenia in Hefei, China from 2005 to 2019: a time-varying distribution lag nonlinear model

Along with climate change, unstable weather patterns are becoming more frequent. However, the temporal trend associated with the effect of temperature variation on schizophrenia (SCZ) is not clear. Daily time-series data on SCZ and meteorological factors for 15-year between January 1, 2005 and December 31, 2019 were collected. And we used the Poisson regression model combined with the time-varying distribution lag nonlinear model (DLNM) to explore the temporal trend of the association between three temperature variation indicators (diurnal temperature range, DTR; temperature variability, TV; temperature change between neighboring days, TCN) and SCZ hospitalizations, respectively. Meanwhile, we also explore the temporal trend of the interaction between temperature and temperature variation. Stratified analyses were performed in different gender, age, and season. Across the whole population, we found a decreasing trend in the risk of SCZ hospitalizations associated with high DTR (from 1.721 to 1.029), TCN (from 1.642 to 1.066), and TV (TV0-1, from 1.034 to 0.994; TV0-2, from 1.041 to 0.994, TV0-3, from 1.044 to 0.992, TV0-4, from 1.049 to 0.992, TV0-5, from 1.055 to 0.993, TV0-6, from 1.059 to 0.991, TV0-7, from 1.059 to 0.990), but an increasing trend in low DTR (from 0.589 to 0.752). Subgroup analysis results further revealed different susceptible groups. Besides, the interactive effect suggests that temperature variation may cause greater harm under low-temperature conditions. There was a synergy between TCN and temperature on the addition and multiplication scales, which were 1.068 (1.007, 1.133) and 0.067 (0.009, 0.122), respectively. Our findings highlight public health interventions to mitigate temperature variation effects needed to focus not only on high temperature variations but also moderately low temperature variations. Future hospitalizations for SCZ associated with temperature variation may be more severely affected by temperature variability from low temperature environments. The temporal trend is associated with the effect of temperature variation on schizophrenia (SCZ).

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.

Effects of high-frequency temperature variabilities on the morbidity of chronic obstructive pulmonary disease: Evidence in 21 cities of Guangdong, South China

BACKGROUND

While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported.

OBJECTIVES

To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization.

METHODS

We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities.

RESULTS

A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12-38%) increase in COPD admissions. An IQR increase in IITV_0-1 was associated with 18% (95% CI: 7-27%) increase in COPD admissions. Males and people aged 0-64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality.

CONCLUSIONS

The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.

Short-Term Effect of Temperature Change on Non-Accidental Mortality in Shenzhen, China

Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.

Cold Spells and Cause-Specific Mortality in 47 Japanese Prefectures: A Systematic Evaluation

BACKGROUND

Many studies have investigated the devastating health effects of heat waves, but less is known about health risks related to cold spells, despite evidence that extreme cold may contribute to a larger proportion of deaths.

OBJECTIVES

We aimed to systematically investigate the association between cold spells and mortality in Japan.

METHODS

Daily data for weather conditions and 12 common causes of death during the 1972-2015 cold seasons (November-March) were obtained from 47 Japanese prefectures. Cold spells were defined as ≥2 consecutive days with daily mean temperatures ≤5th percentile for the cold season in each prefecture. Quasi-Poisson regression was combined with a distributed lag model to estimate prefecture-specific associations, and pooled associations at the national level were obtained through random-effects meta-analysis. The potential influence of cold spell characteristics (intensity, duration, and timing in season) on associations between cold spells and mortality was examined using a similar two-stage approach. Temporal trends were investigated using a meta-regression model.

RESULTS

A total of 18,139,498 deaths were recorded during study period. Mortality was significantly higher during cold spell days vs. other days for all selected causes of death. Mortality due to age-related physical debilitation was more strongly associated with cold spells than with other causes of death. Associations between cold spells and mortality from all causes and several more specific outcomes were stronger for longer and more intense cold spells and for cold spells earlier in the cold season. However, although all outcomes were positively associated with cold spell duration, findings for cold spell intensity and seasonal timing were heterogeneous across the outcomes. Associations between cold spells and mortality due to cerebrovascular disease, cerebral infarction, and age-related physical debility decreased in magnitude over time, whereas temporal trends were relatively flat for all-cause mortality and other outcomes.

DISCUSSION

Our findings may have implications for establishing tailored public health strategies to prevent avoidable cold spell-related health consequences. https://doi.org/10.1289/EHP7109.

Disparities of weather type and geographical location in the impacts of temperature variability on cancer mortality: A multicity case-crossover study in Jiangsu Province, China

BACKGROUND

Considering the serious health burden caused by adverse weather events, increasing researches focused on the relationship between temperature variability (TV) and cause-specific mortality, but its association with cancer was not well explored. We aimed to investigate the impacts of TV on cancer mortality and examine the modifying effects of weather type and geographical location as well as other characteristics.

MATERIALS AND METHODS

Daily city-specific data of cancer deaths, mean temperature (Tmean), maximum and minimum temperatures (Tmax and Tmin), relative humidity (RH), rainfall, and air pollutants were collected during 2016-2017 in 13 cities in Jiangsu Province, China. TV_0-t was defined as the standard deviation of the daily Tmax and Tmin on the exposure 0-t days. A two-stage analysis was applied. First, a time-stratified case-crossover design was used to examine the odds ratio (OR) and attributable fraction of cancer mortality per 1 °C increase in TV by adjusting for potential confounders. Random effect meta-analysis was used to summarize the pooled ORs. Second, stratified analysis was performed for weather type, geographical location, demographics, and other city-level characteristics. The weather was defined as four types according to days during warm or cold season combined with high or low RH.

RESULTS

A total of 303670 cases were included in our study. Meta-analysis showed that the ORs of cancer mortality per 1 °C increase in TV_0-t significantly increased and peaked in TV_0-2 (OR=1.0098, 95% CI: 1.0039-1.0157). The attributable fraction of TV_0-2 on cancer mortality was 4.74%, accounting for 14395 deaths in the study period. Significant ORs of TV-related cancer mortality were found during the warm season combined with high RH and in the northern region of Jiangsu. Susceptible groups of TV-related cancer mortality were identified as female patients, patients aged 45-65 years, and those living in cities with lower per capita green area.

CONCLUSIONS

TV can significantly increase the risk of cancer mortality, especially during warm and humid days and in the northern region of Jiangsu. Findings are of great significance to formulate urban planning, resource allocation, and health intervention to prolong the life of cancer patients.

The association between ambient temperature variability and myocardial infarction in a New York-State-based case-crossover study: An examination of different variability metrics

BACKGROUND

Short-term temperature variability has been consistently associated with mortality, with limited evidence for cardiovascular outcomes. Previous studies have used multiple metrics to measure temperature variability; however, those metrics do not capture hour-to-hour changes in temperature.

OBJECTIVES

We assessed the correlation between sub-daily temperature-change-over-time metrics and previously-used metrics, and estimated associations with myocardial infarction (MI) hospitalizations.

METHODS

Hour-to-hour change-over-time was measured via three metrics: 24-hr mean absolute hourly first difference, 24-hr maximum absolute hourly first difference, and 24-hr mean hourly first difference. We first assessed the Spearman correlations between these metrics and four previously-used metrics (24-hr standard deviation of hourly temperature, 24-hr diurnal temperature range, 48-hr standard deviation of daily minimal and maximal temperatures, and 48-hr difference of daily mean temperature), using hourly data from the North America Land Data Assimilation System-2 Model. Subsequently, we estimated the association between these metrics and primary MI hospitalization in adult residents of New York State for 2000-2015 using a time-stratified case-crossover design.

RESULTS

The hour-to-hour change-over-time metrics were correlated, but not synonymous, with previously-used metrics. We observed 809,259 MI, 45% of which were among females and the mean (standard deviation) age was 70 (15). An increase from mean to 90th percentile in mean absolute first difference of temperature was associated with a 2.04% (95% Confidence Interval [CI]: 1.30-2.78%) increase in MI rate. An increase from mean to 90th percentile in mean first difference also yielded a positive association (1.86%; 95%CI: 1.09-2.64%). We observed smaller- or similar-in-magnitude positive associations for previously-used metrics.

DISCUSSION

First, short-term hour-to-hour temperature change was positively associated with MI risk. Second, all other variability metrics yielded positive associations with MI, with varying magnitude. In future research on temperature variability, researchers should define their research question, including which aspects of variability they intend to measure, and apply the appropriate metric.

ALTERNATIVE

All metrics of temperature variability, including short-term hour-to-hour temperature changes, were positively associated with MI risk, though the magnitude of effect estimates varied by metric.

The Mortality Effect of Apparent Temperature: A Multi-City Study in Asia

(1) Background: The health effect of temperature has become a rising public health topic. The objective of this study is to assess the association between apparent temperature and non-accidental deaths, and the mortality burden attributed to cold and heat temperature; (2) Methods: The daily data on temperature and deaths were collected from 10 cities in Thailand, Korea and China. We fitted a time-series regression with a distributed lag nonlinear model (DLNM) to derive the health risk of temperature for each city and then pooled them to get the overall cumulative risk by multivariate meta-analysis. Additionally, we calculated the attributable fraction of deaths for heat and cold, which was defined as temperatures above and below minimum-mortality temperature (MMT); (3) Results: There are regional heterogeneities in the minimum mortality percentiles (MMP) and attributable fractions for different countries. The MMP varied from about the 5-10th percentile in Thailand to 63-93rd percentile in China and Korea. The attributable fractions of the total deaths due to short-term exposure to temperature in Asia is 7.62%, of which the cold effect (6.44%) is much higher than the heat effect (1.18%); (4) Conclusions: Our study suggested that apparent temperature was associated with an increase in non-accidental mortality. Most of the temperature-related mortality burden was attributable to cold, except for Thailand.

The acute effects of temperature variability on heart rate variability: A repeated-measure study

BACKGROUND

The impacts of temperature variability on cardiac autonomic function remain unclear.

OBJECTIVE

To explore the short-term associations between daily temperature variability and parameters of heart rate variability (HRV).

METHODS

This is a repeated-measure study among 78 eligible participants in Shanghai, China. We defined temperature variability as diurnal temperature range (DTR), the standard-deviation of temperature (SDT) and temperature variability (TV). We evaluated 3 frequency-domain HRV parameters (VLF, LF and HF) and 4 time-domain parameters (SDNN, SDANN, rMSSD and pNN50). We used linear mixed-effect models to analyze the data after controlling for environmental and individual confounders.

RESULTS

Temperature variability was significantly associated with decreased HRV, especially on the concurrent day. The exposure-response relationships were almost inversely linear for most parameters. Every one interquartile range (IQR) increase of DTR was associated with a decrease of 3.92% for VLF, 6.99% for LF, 5.88% for HF, 3.94% for rMSSD and 1.30% for pNN50. Each IQR increase of SDT was associated with a decline of 6.48% for LF, 5.91% for HF, 4.26% for rMSSD and 1.87% for pNN50. Every IQR increase of SDT was associated with a decrease of 4.39% for VLF, 7.67% for LF, 6.52% for HF, 3.22% for SDNN, 2.98% for SDANN, 4.05% for rMSSD, and 1.41% for pNN50. The decrements in HRV associated with temperature variability were more prominent in females.

CONCLUSION

Temperature variability on the concurrent day could significantly decrease cardiac autonomic function, especially in females.

Projecting heat-related excess mortality under climate change scenarios in China

Recent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2-3.3%) in the 2010s to 2.4% (0.4-4.1%) in the 2030 s and 5.5% (0.5-9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0-1.2%) and 3.6% (-0.5-7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

Association between ambient ozone pollution and mortality from a spectrum of causes in Guangzhou, China

Ambient ozone (O₃) has emerged as an important public health issue worldwide. Previous studies found an association between O₃ and cardiorespiratory mortality. However, evidence was limited regarding the risk of O₃ on mortality from other diseases. In this study, we aimed to estimate the association between O₃ and mortality from a broad spectrum of diseases in Guangzhou, China, which has experienced a rapid increase in O₃ concentration over the past decades. Daily data were obtained on cause-specific mortality, air pollutant concentrations and weather conditions during 2013-2018. A generalized additive model with quasi-Poisson regression was applied to examine the association between O₃ and mortality from 10 broad causes and 26 refined subcategories, with adjustment of long-term and seasonal trends, weather conditions, public holidays and days of the week. We found that the threshold concentrations of O₃ were 40 μg/m³ for all-cause, non-accidental, cardiovascular and respiratory mortality. Mortality risk increased monotonically with O₃ concentrations above the threshold. Per 10 μg/m³ increase of O₃ at lag 0-3 days was associated with 0.54% (95%CI: 0.34-0.74%), 0.56% (95%CI: 0.36-0.76%), 0.59% (95%CI: 0.30-0.88%), 0.78% (95%CI: 0.33-1.24%) and 0.52% (95%CI: 0.21-0.83%) elevated risk of death from all causes, non-accidental causes, cardiovascular diseases, respiratory diseases and neoplasms, respectively. Among the subcategories, the largest effect estimate was observed in people with chronic obstructive pulmonary disease. The elderly suffered from a higher mortality risk from O₃. Stringent emission control strategies and multi-sectoral collaborations are needed to reduce the detrimental impact of O₃ on vulnerable populations.

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.

Relationship between Air Temperature Parameters and the Number of Deaths Stratified by Cause in Gifu Prefecture, Japan

Objective: It is well known that air temperature is closely related to health outcomes. We investigated the relationship between air temperature parameters and the number of deaths stratified by cause in Gifu prefecture, Japan. Methods: The number of deaths stratified by cause in Gifu prefecture Japan between January 2007 and December 2016 was obtained from the official homepage of Gifu prefecture, Japan. Air temperature parameters (°C), i.e., the mean air temperature, mean of the highest air temperature, mean of the lowest air temperature, the highest air temperature, and the lowest air temperature during the same period in Gifu city were also obtained from the Japan Meteorological Agency official home page. The relationship between air temperature parameters and the number of deaths was evaluated in an ecological study. Results: The number of deaths due to heart disease, cerebrovascular disease, pneumonia, accidents, or renal failure in January (coldest winter season in Japan) was the highest among the months. Simple correlation analysis also demonstrated a significant and negative relationship between air temperature parameters and the number of deaths due to heart disease, cerebrovascular disease, senility, pneumonia, accidents, and renal failure. Conclusion: Lower air temperature may be associated with a higher number of deaths due to diseases in Gifu prefecture, Japan.

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.

Short-term effects of ambient temperature on the risk of premature rupture of membranes in Xinxiang, China: A time-series analysis

BACKGROUND

Studies on the effects of extreme ambient temperature on the risk of adverse birth outcomes are limited, and the results are inconsistent. In this study, we evaluated the short-term effects of daily mean temperature on the risk of premature rupture of membranes (PROM) in Xinxiang, China.

METHODS

Daily hospitalization data for PROM, daily meteorological data, and ambient pollution data in Xinxiang from January 1, 2015 to December 31, 2017 were collected. A quasi-Poisson generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM) was applied to assess the short-term impact of temperature on PROM. The model was adjusted for relative humidity, air pollution, time trend, day of the week, and public holidays.

RESULTS

The number of daily hospitalizations for PROM during the study period was 3255. With a reference median temperature of 17 °C, there were significant associations between the temperature deviation from the threshold temperature (2 °C, 12th percentile; 29 °C, 91st percentile) and PROM hospitalization at lag 0-2 days. Exposure to extreme cold (-2 °C, 1st percentile) or extreme heat (32 °C, 99th percentile) were associated with 0.528 (95% confidence interval [CI]: 0.278-0.986) and 2.161 (95% CI: 1.240-3.764) increased risks of PROM, respectively. Younger mothers with age <35 years were more sensitive to the impact of extreme temperature.

CONCLUSIONS

These findings suggest that heat temperature is associated with higher PROM risk, while cold temperature might be a protective factor against PROM in Xinxiang, China. Given the adverse consequences of PROM and concerns over global climate change, pregnant women should take special precautions in summer when there are sudden increases in temperature.