Diurnal temperature range and short-term mortality in large US communities

Associations between various types of mortality and temperature variability distinguishing the intraday and interday effects in South Korea

BACKGROUND

The association between temperature variability (TV) and elevated mortality risks is widely known. Yet, few studies investigated the distinct effects of intraday and interday temperature fluctuations considering age-specific, gender-specific, and cause-specific mortality stratified by four seasons.

OBJECTIVES

We investigate the associations between total, intraday, and interday temperature variabilities and total, age-specific, gender-specific, cardiovascular, and respiratory mortality year-round and also stratified by four seasons.

METHODS

We collected district-level daily data for temperature and total, age-specific, gender-specific, cardiovascular, and respiratory mortality in South Korea from 2011 to 2021 (N = 3,113,425). TV indices (i.e., total TV, intraday TV, and interday TV) were computed as the standard deviations of daily minimum, maximum, and mean temperatures over a lag of one to seven days. The associations between TV and mortality were evaluated by a space-time-stratified case-crossover design with quasi-Poisson regression.

RESULTS

Mortality risks varied based on the type of TV index. The associations also differed depending on the mortality type and the season. Year-round associations showed interday TV was generally associated with elevated mortality risks (total mortality: 0.30% (95% CI: 0.07%, 0.52%), 65+ mortality: 0.32% (95% CI: 0.07%, 0.58%), female mortality: 0.49% (95% CI: 0.16%, 0.82%), CVD mortality: 0.47% (95% CI: 0.02%, 0.92%) on lag0-7) while intraday TV was not significantly associated with increased risk of mortality except for the male mortality, 0.68% (95% CI: 0.04%, 1.32%) on lag0-7. Season-stratified analysis revealed that TV-related mortality risks were high consistently in the spring season and generally in the summer season while the associations were generally negative in fall and insignificant in winter.

CONCLUSION

This study provided evidence on the season-stratified, independent impacts of intraday and interday temperature variabilities on total, age-specific, gender-specific, and cause-specific mortality risks in South Korea drawing attention to the need of targeted policies to alleviate the impacts on human health.

The association between short-term temperature variability and mortality in Virginia

The objective of this study is to determine the relationship between short-term temperature variability on neighboring days and mortality. The change in maximum temperature in Northern Virginia, Richmond, Roanoke, and Norfolk, Virginia, on neighboring days was calculated from airport observations and associated with total mortality over a multi-county area surrounding each weather station. The association between day-to-day temperature change and mortality, lagged over a 28-day period, was analyzed using distributed lag non-linear models that controlled for air quality, temporal trends, and other factors. Days following large temperature declines were associated with an increased risk of mortality in three of the four locations, and temperature increases were linked to higher mortality risk in two cities. For example, the relative risk of mortality for a 12°C daily temperature decline (1st percentile) was 1.74 [0.92, 3.27] in Roanoke and 1.16 [0.70, 1.92] in Richmond. The net effect of short-term temperature increases was smaller, with the largest relative risk of 1.03 [0.58, 1.83] for a 12°C increase (99th percentile) in maximum temperature in Norfolk. In Richmond and Roanoke, there was an observed lagged effect of increased mortality (maximum relative risks varying from 1.08 to 1.10) that extended from 5 to 25 days associated with large temperature declines of 15°C or more. In contrast, there was a strong and immediate (lag 0-3 day) increase in the risk of mortality (1.10 to 1.15) in northern Virginia and Norfolk when the temperature increase exceeded 10°C (short-term warming). In general, consecutive day warming had a more immediate mortality impact than short-term cooling, when the peak mortality is lagged by one week or more. However, cooling of at least 10°C after a hot (summer) day reduced mortality relative to comparable cooling following a cold (winter) day, which is associated with high mortality. This differential mortality response as a function of temperature suggests that there is some relationship between average temperature, temperature variability, and season. The findings of this study may be useful to public health officials in developing mitigation strategies to reduce the adverse health risks associated with short-term temperature variability.

Time-series analysis of temperature variability and cardiovascular emergency department visits in Atlanta over a 27-year period

BACKGROUND

Short-term temperature variability, defined as the temperature range occurring within a short time span at a given location, appears to be increasing with climate change. Such variation in temperature may influence acute health outcomes, especially cardiovascular diseases (CVD). Most research on temperature variability has focused on the impact of within-day diurnal temperature range, but temperature variability over a period of a few days may also be health-relevant through its impact on thermoregulation and autonomic cardiac functioning. To address this research gap, this study utilized a database of emergency department (ED) visits for a variety of cardiovascular health outcomes over a 27-year period to investigate the influence of three-day temperature variability on CVD.

METHODS

For the period of 1993-2019, we analyzed over 12 million CVD ED visits in Atlanta using a Poisson log-linear model with overdispersion. Temperature variability was defined as the standard deviation of the minimum and maximum temperatures during the current day and the previous two days. We controlled for mean temperature, dew point temperature, long-term time trends, federal holidays, and day of week. We stratified the analysis by age group, season, and decade.

RESULTS

All cardiovascular outcomes assessed, except for hypertension, were positively associated with increasing temperature variability, with the strongest effects observed for stroke and peripheral vascular disease. In stratified analyses, adverse associations with temperature variability were consistently highest in the moderate-temperature season (October and March-May) and in the 65 + age group for all outcomes.

CONCLUSIONS

Our results suggest that CVD morbidity is impacted by short-term temperature variability, and that patients aged 65 and older are at increased risk. These effects were more pronounced in the moderate-temperature season and are likely driven by the Spring season in Atlanta. Public health practitioners and patient care providers can use this knowledge to better prepare patients during seasons with high temperature variability or ahead of large shifts in temperature.

Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China

As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental pollutants and death data of common MetS (hypertension, hyperlipidemia and diabetes), as well as a total number of 15,272 MetS deaths. To examine the relationship between meteorological factors, air pollutants, and MetS mortality, we used a generalized additive model (GAM) combined with a distributed delay nonlinear model (DLNM) for time series analysis. The relationship between the above factors and death outcomes was preliminarily evaluated using Spearman analysis and structural equation modeling (SEM). As per out discovery, diurnal temperature range (DTR) and daily mean temperature (T mean) increased the MetS mortality risk notably. The ultra low DTR raised the MetS mortality risk upon the general people, with the highest RR value of 1.033 (95% CI: 1.002, 1.065) at lag day 14. In addition, T mean was also significantly associated with MetS death. The highest risk of ultra low and ultra high T mean occured on the same day (lag 14), RR values were 1.043 (95% CI: 1.010, 1.077) and 1.032 (95% CI: 1.003, 1.061) respectively. Stratified analysis's result showed lower DTR had a more pronounced effect on women and the elderly, and ultra low and high T mean was a risk factor for MetS mortality in women and men. The elderly need to take extra note of temperature changes, and different levels of T mean will increase the risk of death. In warm seasons, ultra high RH and T mean can increase the mortality rate of MetS patients.

Short-term impact of diurnal temperature range on cardiovascular diseases mortality in residents in northeast China

It has been reported that cardiovascular disease (CVD) has become one of the major threats to global public health and is associated with climate change. Several previous studies have shown the influence of ambient temperature on CVD, but lack some evidence for the short-term effect of diurnal temperature range (DTR) on CVD mortality in northeast China. This is the first study to assess the correlation between DTR and CVD mortality in Hulunbuir located in northeast China. Daily CVD mortality data and meteorological data were collected from 2014 to 2020. A quasi-Poisson generalized linear regression with a distributed lag non-linear model (DLNM) was applied to exploring the short-term impact of DTR on CVD mortality. Stratified analyses by gender, age, and season were conducted and the short-term impacts of extremely high DTR on CVD mortality were investigated. In this study, a total of 21,067 CVD mortality cases were recorded in Hulunbuir, China from 2014 to 2020. Compared to the reference value (11.20 [Formula: see text]C, 50[Formula: see text] percentile), a "U-shaped" non-linear relationship between DTR and CVD mortality was observed, and extremely high DTR increased the risk of CVD mortality. The short-term effect of extremely high DTR occurred immediately and lasted up to 6 days. In addition, the male and the age [Formula: see text] 65 groups were more likely to be affected by extremely high DTR compared with the female and the age < 65 groups, respectively. The results also showed that extremely high DTR in cold season had a more adverse effect on CVD mortality than warm season. This study suggests that extremely high DTR for cold season should be paid enough attention to for residents in northeast China. The male and the age [Formula: see text] 65 groups were more vulnerable to the impacts of DTR. The study results may provide some suggestions for decision-making by local public health authorities to avoid the adverse impacts of high DTR, and improve the health of residents, especially vulnerable groups in cold season.

Diurnal temperature range and hospital admission due to cardiovascular and respiratory diseases in Dezful, a city with hot climate and high DTR fluctuation in Iran: an ecological time-series study

The results of previous studies have indicated the effects of temperature changes on health status. The present study was conducted to investigate the effects of diurnal temperature range (DTR) and hospital admission on cardiovascular and respiratory diseases in Dezful, in Iran. In this ecological time-series study, data related to hospital admissions based on ICD-10, meteorological, and climatological data were gathered over a period of six years from 2014 to 2019. A distributed lag nonlinear model combined with a quasi-Poisson regression was then used to assess the impact of DTR on cardiovascular and respiratory hospital admissions. Potential confounders, including wind speed, air pollution, seasonality, time trend, weekends and holidays, days of week, and humidity were controlled. In extreme low DTRs, the cumulative effects of cardiovascular admissions significantly increased in total, and in warm and cold seasons (Lag_0-21, P ≤ 0.05). In addition, in extreme high DTRs, the cumulative effects of cardiovascular significantly decreased in total (Lag_0-13 and Lag_0-21, P ≤ 0.05), and in warm (Lag_0-21, P ≤ 0.05) and cold seasons (Lag_0-21, P ≤ 0.05). Moreover, respiratory admissions significantly decreased in total (Lag_0-21, P ≤ 0.05) and in warm season (Lag_0-21, P ≤ 0.05).Our result indicates that extreme low DTRs could increase the risk of daily cardiovascular admissions, and extreme high DTRs may cause a protective effect on daily respiratory and cardiovascular admissions in some regions with high fluctuations in DTR.

Analysis of the heat- and cold-related cardiovascular mortality in an urban mediterranean environment through various thermal indices

During the last decades the effects of thermal stress on public health have been a great concern worldwide. Thermal stress is determined by air temperature in combination with other meteorological parameters, such as relative humidity and wind speed. The present study is focused on the Mediterranean city of Thessaloniki, Greece and it aims to explore the association between thermal stress and mortality from cardiovascular diseases, using both air temperature and other thermal indices as indicators. For that, an over-dispersed Poisson regression function was used, in combination with distributed lag non-linear models, in order to capture the delayed and nonlinear effects of temperature. Our results revealed a reverse J-shaped exposure-response curve for the total population and females and a U-shaped association for males. In all cases examined, the minimum mortality temperature was identified around the 80th percentile of each distribution. It is noteworthy that despite the fact that the highest risks of cardiovascular mortality were estimated for exposure to extreme temperatures, moderate temperatures were found to cause the highest burden of mortality. On the whole, our estimations demonstrated that the population in Thessaloniki is more susceptible to cold effects and in regard with gender, females seem to be more vulnerable to ambient thermal conditions.

An analysis of past and future heatwaves based on a heat-associated mortality threshold: towards a heat health warning system

Heatwaves can have severe impacts on human health extending from illness to mortality. These health effects are related to not only the physical phenomenon of heat itself but other characteristics such as frequency, intensity, and duration of heatwaves. Therefore, understanding heatwave characteristics is a crucial step in the development of heat-health warning systems (HHWS) that could prevent or reduce negative heat-related health outcomes. However, there are no South African studies that have quantified heatwaves with a threshold that incorporated a temperature metric based on a health outcome. To fill this gap, this study aimed to assess the spatial and temporal distribution and frequency of past (2014 - 2019) and future (period 2020 - 2039) heatwaves across South Africa. Heatwaves were defined using a threshold for diurnal temperature range (DTR) that was found to have measurable impacts on mortality. In the current climate, inland provinces experienced fewer heatwaves of longer duration and greater intensity compared to coastal provinces that experienced heatwaves of lower intensity. The highest frequency of heatwaves occurred during the austral summer accounting for a total of 150 events out of 270 from 2014 to 2019. The heatwave definition applied in this study also identified severe heatwaves across the country during late 2015 to early 2016 which was during the strongest El Niño event ever recorded to date. Record-breaking global temperatures were reported during this period; the North West province in South Africa was the worst affected experiencing heatwaves ranging from 12 to 77 days. Future climate analysis showed increasing trends in heatwave events with the greatest increases (80%-87%) expected to occur during summer months. The number of heatwaves occurring in cooler seasons is expected to increase with more events projected from the winter months of July and August, onwards. The findings of this study show that the identification of provinces and towns that experience intense, long-lasting heatwaves is crucial to inform development and implementation of targeted heat-health adaptation strategies. These findings could also guide authorities to prioritise vulnerable population groups such as the elderly and children living in high-risk areas likely to be affected by heatwaves.

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.

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.

Effects of diurnal temperature range on cardiovascular disease hospital admissions in farmers in China's Western suburbs

Cardiovascular disease (CVD), reported to relate with climate change, is the leading cause of global mortality and morbidity. Since the relevant information is quite limited from suburbs and countryside in developing and underdeveloped countries, there are no studies that focused on morbidity through diurnal temperature range (DTR) for these regions. This is the first study to evaluate the short-term effect of DTR on CVD hospital admission in suburban farmers, as well as to identify vulnerable subpopulations. Daily time series data of CVD hospital admissions on suburban farmers of Qingyang, China, and meteorological data from 2011 to 2015 were collected, and a distributed lag non-linear model (DLNM) combined with a quasi-Poisson generalized additive regression model (GAM) was used to examine the exposure-response relationship and delayed effect between DTR and CVD hospital admissions. Stratified analyses by age and gender were performed and extreme DTR effects were examined. Non-linear relation between DTR and CVD hospital admissions was observed, and whether DTR lower or higher than the reference (13 °C, 50^th percentile) had adverse effect while lower DTR have slightly higher impact. Also, both extreme low and extreme high DTR had adverse effect. Besides, adults (age < 65) and males were more vulnerable to the effects of DTR compared with the old (age ≥ 65) and females, respectively. This study provides evidence that not only high DTR but also low DTR had adverse effects on CVD which should be paid attention to. Adults and males were more vulnerable among suburban farmers. The results are inconsistent with the studies from urban and indicate differences between urban and suburban residents. Multiple factors such as occupations, risk awareness, and lifestyles could have a significant influence on CVD morbidity, and further study is needed to explore more evidence.

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.

The effect and prediction of diurnal temperature range in high altitude area on outpatient and emergency room admissions for cardiovascular diseases

PURPOSE

Diurnal temperature range (DTR) is a meteorological indicator closely associated with global climate change. Thus, we aim to explore the effects of DTR on the outpatient and emergency room (O&ER) admissions for cardiovascular diseases (CVDs), and related predictive research.

METHODS

The O&ER admissions data for CVDs from three general hospitals in Jinchang of Gansu Province were collected from 2013 to 2016. A generalized additive model (GAM) with Poisson regression was employed to analyze the effect of DTR on the O&ER admissions for all cardiovascular diseases, hypertension, ischemic heart disease (IHD) and stoke. GAM was also used to preform predictive research of the effect of DTR on the O&ER admissions for CVDs.

RESULTS

There were similar positive linear relationships between DTR and the O&ER visits with the four cardiovascular diseases. And the cumulative lag effects were higher than the single lag effects. A 1 °C increase in DTR corresponded to a 1.30% (0.99-1.62%) increase in O&ER admissions for all cardiovascular diseases. Males and elderly were more sensitivity to DTR. The estimates in non-heating season were higher than in heating season. The trial prediction accuracy rate of CVDs based on DTR was between 59.32 and 74.40%.

CONCLUSIONS

DTR has significantly positive association with O&ER admissions for CVDs, which can be used as a prediction index of the admissions of O&ER with CVDs.

Mortality risk attributable to diurnal temperature range: a multicity study in Yunnan of southwest China

We aimed to estimate the non-accidental and cause-specific mortality burden attributed to diurnal temperature range (DTR) and the relative contributions of low, high, and extremely low and extremely high DTR in Yunnan, southwest China. Furthermore, we explored the possible effect modification of the DTR-mortality association by season, sex, age, ethnicity, marital status, and occupation. A standard time-series quasi-Poisson regression model combined with a distributed lag nonlinear model was used to derive estimates of city-specific DTR-mortality associations, then random effects meta-analysis was used to pool the estimated city-specific overall cumulative DTR-mortality association, estimating empirical confidence intervals (eCIs). The overall fraction of non-accidental mortality caused by DTR was 11.00% (95% eCI 3.40-17.28): high DTR accounted for most of burden (total estimate 10.03%, 95% eCI 2.59-16.32). The estimated mortality risk attributable to DTR was significantly associated with cardiovascular and respiratory mortality, with attributable fractions of 13.61% (95% eCI 3.91-21.13) and 14.32% (95% eCI 0.47-21.44), respectively. The estimated risk attributable to DTR was slightly greater for males, people ≥75 years old, married people, and non-farmers than their corresponding categories. Most of the DTR-related mortality burden was attributable to high DTR, and the mortality risk attributable to DTR might be modified by specific causes, sex, age, marital status, and occupation.

Effect of diurnal temperature change on cardiovascular risks differed under opposite temperature trends

Temperature change between neighboring days (TCN) is an important trigger for cardiovascular diseases, but the modulated effects by seasonal temperature trends have been barely taken into account. A quantified comparison between impacts of positive TCNs (temperature rise) and negative situations (temperature drop) is also needed. We evaluated the associations of TCNs with emergency room (ER) visits for coronary heart disease (CHD) and cerebral infarction (CI) in Beijing, China, from 2008 to 2012. A year was divided into two segments dominated by opposite temperature trends, quasi-Poisson regression with distributed lag nonlinear models estimating TCN-morbidity relations were employed, separately for each period. High morbidities of CHD and CI both occurred in transitional seasons accompanied by large TCNs. Under warming backgrounds, positive TCNs increased CHD risk in patients younger than 65 years, and old people showed limited sensitivity. In the cooling periods, negative TCNs induced CHD risk in females and the elderly; the highest RR showed on lag 6 d. In particular, a same diurnal temperature decrease (e.g., - 2°C) induced greater RR (RR = 1.113, 95% CIs: 1.033-1.198) on old people during warming periods than cooling counterparts (RR = 1.055, 95% CIs: 1.011-1.100). Moreover, positive TCNs elevated CI risk regardless of background temperatures, and males were particularly vulnerable. Seasonal temperature trends modify TCN-cardiovascular morbidity associations significantly, which may provide new insights into the health impact of unstable weathers.

Effect modification of the association between diurnal temperature range and hospitalisations for ischaemic stroke by temperature in Hefei, China

OBJECTIVES

Diurnal temperature range (DTR) is an important indicator of global climate change. Many epidemiological studies have reported the associations between high DTR and human health. This study investigated the association between DTR and hospitalisations for ischaemic stroke in Hefei, China.

STUDY DESIGN

This is an ecological study.

METHODS

Data of daily hospital admissions for ischaemic stroke and meteorological variables from 1 January 2009 to 31 December 2017 were collected in Hefei, China. A generalised additive model combined with distributed lag non-linear model was used to quantify the effects of DTR on ischaemic stroke. The interactive effect between DTR and temperature was explored with a non-parametric bivariate response surface model.

RESULTS

High DTR was associated with hospitalisations for ischaemic stroke. The adverse effect of extremely high DTR (99th percentile [17.1 °C]) occurred after 8 days (relative risk [RR] = 1.021, 95% confidence interval [CI] = 1.002, 1.041) and the maximum effect appeared after 12 days (RR = 1.029, 95% CI = 1.011, 1.046). The overall trend of the effect of DTR on ischaemic stroke was decreasing. In addition, there was a significant interactive effect of high DTR and low temperature on ischaemic stroke.

CONCLUSIONS

This study suggests that the impact of high DTR should be considered when formulating targeted measures to prevent ischaemic stroke, especially for those days with high DTR and low mean temperature.

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.

What Are the Effects of Meteorological Factors on Exacerbations of Chronic Obstructive Pulmonary Disease?

Chronic obstructive pulmonary disease (COPD) is one of the greatest global public health challenges. Acute exacerbations of COPD lead to the accelerated deterioration of lung function, reduced quality of life, a higher number of hospitalizations, and increased mortality. The factor causing the exacerbation is usually an infectious agent, but the impact of environmental factors is being studied more thoroughly. Among them, meteorological factors are the least examined. Multiple studies have shown that lower temperatures during the cold season, as well as sudden temperature changes regardless of the season, have the most significant negative effect on patients with COPD. However, higher temperatures, especially during summer heatwaves, can also cause COPD exacerbation and it is expected that this will be an even more important health problem in the future considering climate changes. The effects of other meteorological factors on acute exacerbation of COPD, such as atmospheric pressure, solar radiation, rainfall, wind speed, and humidity are far less investigated and opposing results have been obtained in different studies. Thus, there is a need for further research in this area that would result in clinical recommendations and public health interventions that could decrease the global burden of COPD.

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.

Suicide and apparent temperature in the two capitals cities in the iberian peninsula

Different authors have identified geographic variations in the rates of suicide. This study aims to discuss the limitations of the officially recorded suicide data and to evaluate the statistical relationship between a biometeorological index, Apparent Temperature (AT), and suicide in Madrid and Lisbon. We performed a time-series study. The association was analyzed using a quasi-Poisson regression model. To assess potential delayed and non-linear effects of AT on suicides, a lag non-linear model was fitted in a generalized additive model. There was an average rate of 3.30 suicides/100,000 inhabitants in Madrid and of 7.92 suicides/100,000 inhabitants in Lisbon, and a downward trend was found throughout the period. In Madrid, there is no statistically significant association between AT and suicide. However, in Lisbon, under higher AT, there was a higher risk of suicide. The highest accumulated statistically significant Relative Risk (RR) of suicide was detected at 7 days after the exposure, when at 38 °C, the risk of suicide is 2.7 times that existing at the median AT, 20.62°. The average mortality rate recorded in Lisbon was 41.6% higher than that registered in Madrid. However, the limitations of suicide record databases in Spain and Portugal have to be taken into account when analyzing incidence and especially when comparing data from different countries. It is necessary to improve the filing systems of violent deaths in order to perform reliable epidemiological studies.

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.

Interactive Effect of Diurnal Temperature Range and Temperature on Mortality, Northeast Asia

BACKGROUND

The diurnal temperature range (DTR) represents temperature variability within a day and has been reported as a potential risk factor for mortality. Previous studies attempted to identify the role of temperature in the DTR-mortality association, but results are inconclusive. The aim of this study was to investigate the interactive effect of temperature and DTR on mortality using a multicountry time series analysis.

METHODS

We collected time series data for mortality and weather variables for 57 communities of three countries (Taiwan, Korea, and Japan) in Northeast Asia (1972-2012). Two-stage time series regression with a distributed lag nonlinear model and meta-analysis was used to estimate the DTR-mortality association changing over temperature strata (six strata were defined based on community-specific temperature percentiles). We first investigated the whole population and then, the subpopulations defined by temperature distribution (cold and warm regions), sex, and age group (people <65 and ≥65 years of age), separately.

RESULTS

The DTR-mortality association changed over temperature strata. The relative risk (RR) of mortality for 10°C increase in DTR was larger for high-temperature strata compared with cold-temperature strata (e.g., = 1.050; 95% confidence interval [CI] = 1.040, 1.060 at extreme-hot stratum and RR = 1.040; 95% CI = 1.031, 1.050 at extreme-cold stratum); extreme-hot and -cold strata were defined as the days with daily mean temperature above 90th and below 10th percentiles each community's temperature distribution. Such increasing pattern was more pronounced in cold region and in people who were 65 years or older.

CONCLUSIONS

We found evidence that the DTR-related mortality may increase as temperature increases.

Short-term effects of diurnal temperature range on hospital admission in Bangkok, Thailand

Diurnal temperature range (DTR) is a key indicator reflecting climate stability. Many previous studies have examined the effects of ambient temperature, both hot and cold, on human morbidity and mortality, but few studies have evaluated health effects of DTR, especially those in developing countries. This study aimed to investigate the association between short-term exposure to DTR and hospital admissions for cardiovascular and respiratory diseases in Bangkok, Thailand. We obtained daily meteorological variables from the Thai Meteorological Department from January 2006 through December 2014 and daily hospital admissions from the National Health Security Office during the same period. Quasi-Poisson generalized linear regression model combined with distributed lag non-linear model was used to examine the association between DTR and cardiovascular and respiratory hospital admissions controlling for daily average temperature, relative humidity, day of the week, public holiday, and seasonal and long-term trend. A J-shape relationship between DTR and hospital admissions was observed. With 7.8 °C DTR as a reference value, the relative risks for cardiovascular and respiratory hospital admission associated with extremely high DTR (11.6 °C) at cumulative lag 0-21 (21-day cumulative effects) were 1.206 (95% CI: 1.002-1.452) and 1.021 (95% CI: 0.856-1.218), respectively. The effects of extremely high DTR relative to a reference value did not significantly differ between males and females, as well as between young people (<65 years) and the elderly (≥65 years) for both cardiovascular and respiratory admission. When stratifying the effects by season, the effect of extremely high DTR in winter was greater than that in summer and rainy season. This study showed that short-term exposure to extremely high DTR was significantly associated with increased risk of hospital admissions for cardiovascular disease in Bangkok, especially during winter. Results from this study could provide important scientific evidence for policy decision making to protect populations from adverse health effects of DTR.

Examining the diurnal temperature range enigma: why is human health related to the daily change in temperature?

An increasing number of epidemiological studies are finding statistical evidence that diurnal temperature range (DTR) is positively correlated to human morbidity and mortality despite the lack of clear clinical understanding. We examine a 14-year daily time series of emergency department (ED) admissions to the University of Virginia Medical Center in Charlottesville, Virginia, relative to long-term climate records from the Charlottesville/Albemarle County Airport weather station and the Spatial Synoptic Classification. DTR has a consistent strong positive correlation (r ~ 0.5) with maximum temperature in all months but only a weak, negative correlation (r ~- 0.1) with minimum temperature except in late summer (r ~- 0.4). Warm season DTR is highest on dry air mass days with low dew point temperatures. Cool season DTR is unrelated to morning temperature. Using a distributed lag non-linear model with an emphasis on DTR and its seasonal variation, after stratifying the models by season, we find that ED visits are linked to extreme cold events (cold days and nights) and high DTR in the cold season. In the warm season, ED visits are also linked to high DTR, but these are cool, dry, and pleasant days. The existing confusion regarding interpretation of DTR impacts on health might be rectified through a more careful analysis of the underlying physical factors that drive variations in DTR over the course of a year.

Effect of diurnal temperature range on outpatient visits for common cold in Shanghai, China

To evaluate the correlations between diurnal temperature range (DTR) and the number of outpatient visits for common cold from Jan. 1, 2008, to Dec. 31, 2010, in the Shanghai metro area; we used a distributed lag non-linear model together with a Poisson regression model. The controlling factors included long-term trends and day of the week in outpatient visits for common cold and the selected weather elements. The entire study group was divided into three different age subgroups, including ≤ 15, 15-65, and ≥ 65 years old. We found some non-linear J-patterns between DTR and daily outpatient visits for common cold. At lag 0 day, the number of outpatient visits for common cold would increase by 11.1% per 1 °C increase in DTR. The greater the DTR, the more it affects outpatient visits for common cold, especially for the ≥ 65 years age group. In addition, DTR plays a more important role in outpatient visits for common cold in spring and winter compared with other seasons of the year. Our study showed that DTR is a risk factor that contributes to common cold. Results in this study can provide scientific evidence for the local authorities in improving preventive measures of the healthcare system.

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.

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.

Spatiotemporal or temporal index to assess the association between temperature variability and mortality in China?

Epidemiological studies increasingly provide evidence about the adverse health effects of temperature variability (TV), which reflects short-term intra- and inter-day temperature change. However, calculation of TV only considers the temporal variability and lacks spatial variability. This study intends to investigate whether the lack of spatial variability in TV calculations has biased the health effect estimates. We collected daily data from the fine-gridded hourly temperatures and more than 2 million all-cause mortality counts in Zhejiang province in China from 2009 to 2015. A spatiotemporal TV index was developed by calculating the standard deviation of the hourly temperatures based on records from multiple sites. This new index could be compared to the two typical temporal TV indices that are calculated based on the hourly temperatures from one-site and area-average records. The three types of TV are compared using a three-stage analytical approach: district-specific time series Poisson regression, meta-analysis, and calculation of attributable mortality fraction. We observe that both spatiotemporal and temporal TVs produce very similar TV-mortality associations, attributable mortality fractions, and model fits at the district level. For example, the mortality increase associated for every increase of 1 °C during 0-7 exposure days is 1.53% (95% CI: 1.31, 1.73) in spatiotemporal TV, whereas it is 1.48% (95% CI: 1.27, 1.68) and 1.45% (95% CI: 1.24, 1.67) in the one-site and area-average temporal TV, respectively. Thus, time series models using temporal TV index are equally good at estimating the associations between TV and mortality as spatiotemporal TV at the district level in population-based epidemiological studies in China. Epidemiological studies using temperature from one site or the averages of multiple sites in TV calculation will not bias the effect estimates of TV. Our study could provide an important guidance method for future TV-related research in China and even in other countries.

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.

Temperature variability and mortality in rural and urban areas in Zhejiang province, China: An application of a spatiotemporal index

BACKGROUND

Temperature variability (TV) is a potential trigger for death in urban areas, but there is little evidence of this in rural areas. In addition, a typical TV index only considers the temporal variability of temperature and ignores its spatial variability, which should be considered due to the effects of human mobility. Here this study aimed to 1) develop a novel spatiotemporal TV index accounting for human mobility; and 2) based on this index, explore the urban-rural differences in TV-mortality associations in China.

METHODS

We collected daily data on fine-gridded hourly temperatures and >2 million deaths that occurred in Zhejiang province, China from 2009 to 2015. A spatiotemporal TV index was developed by calculating the standard deviation of the hourly temperatures from multi-site records over the course of several exposure days. A three-stage analysis was performed to estimate the mortality risks and mortality burdens of TV. Stratified analyses were performed by cause-specific mortality, urban/rural district, age and gender.

RESULTS

Significant associations were found between TV and all types of targeted diseases, age groups, and genders. Percentage increase in mortality associated with a 1 °C increase in TV at 0-7 exposure days were found to be higher for rural dwellers than urban dwellers in the warm season [for all-cause mortality, 2.07% (95% CI: 1.49%, 2.64%) vs. 1.16% (95%CI: 0.70%, 1.62%)]. An estimated all-cause mortality fraction of 5.33% was attributable to TV, with 4.99% in urban areas and 6.02% in rural areas. The elderly (aged 65+ years) and females were more sensitive to TV than young people and males, respectively.

CONCLUSIONS

A spatiotemporal TV index was developed, considering both the temporal and spatial variability of temperatures. TV is an independent health risk factor. In China, rural areas generally suffer greater TV-related mortality risks than urban areas in the warm season. Our findings have important implications for developing area-, cause-, and group-specific adaptation strategies and emergency planning to reduce TV-related mortality.

Socio-geographic disparity in cardiorespiratory mortality burden attributable to ambient temperature in the United States

Compared with relative risk, attributable fraction (AF) is more informative when assessing the mortality burden due to some environmental exposures (e.g., ambient temperature). Up to date, however, available AF-based evidence linking temperature with mortality has been very sparse regionally and nationally, even for the leading mortality types such as cardiorespiratory deaths. This study aimed to quantify national and regional burden of cardiorespiratory mortality (CRM) attributable to ambient temperature in the USA, and to explore potential socioeconomic and demographic sources of spatial heterogeneity between communities. Daily CRM and weather data during 1987-2000 for 106 urban communities across the mainland of USA were acquired from the publicly available National Morbidity, Mortality and Air Pollution Study (NMMAPS). We did the data analysis using a three-stage analytic approach. We first applied quasi-Poisson regression incorporated with distributed lag nonlinear model to estimate community-specific temperature-CRM associations, then pooled these associations at the regional and national level through a multivariate meta-analysis, and finally estimated the temperature-AF of CRM and performed subgroup analyses stratified by community-level characteristics. Both low and high temperatures increased short-term CRM risk, while temperature-CRM associations varied by regions. Nationally, the fraction of cardiorespiratory deaths caused by the total non-optimum, low, and high temperatures was 7.58% (95% empirical confidence interval, 6.68-8.31%), 7.15% (6.31-7.85%), and 0.43% (0.37-0.46%), respectively. Greater temperature-AF was identified in two northern regions (i.e., Industrial Midwest and North East) and communities with lower temperature and longitude, higher latitude, and moderate humidity. Additionally, higher vulnerability appeared in locations with higher urbanization level, more aging population, less White race, and lower socioeconomic status. Ambient temperature may be responsible for a large fraction of cardiorespiratory deaths. Also, temperature-AF of CRM varied considerably by geographical and climatological factors, as well as community-level disparity in socioeconomic status.

High Temperatures and Kidney Disease Morbidity: A Systematic Review and Meta-analysis

Objectives

In recent years, serious concerns have been raised regarding the impacts of rising temperatures on health. The present study was conducted to investigate the relationship between elevated temperatures and kidney disease through a systematic review and meta-analysis.

Methods

In October 2017, 2 researchers independently searched related studies in PubMed and Embase. A meta-analysis was conducted using a random-effects model, including only studies that presented odds ratios, relative risks, or percentage changes, along with 95% confidence intervals (CIs). The characteristics of each study were summarized, and the Egger test and funnel plots were used to evaluate publication bias.

Results

Eleven studies that met the criteria were included in the final analysis. The pooled results suggest an increase of 30% (95% CI, 20 to 40) in kidney disease morbidity with high temperatures. In a disease-specific subgroup analysis, statistically significant results were observed for both renal colic or kidney stones and other renal diseases. In a study design–specific subgroup analysis, statistically significant results were observed in both time-series analyses and studies with other designs. In a temperature measure–specific subgroup analysis, significant results were likewise found for both studies using mean temperature measurements and studies measuring heat waves or heat stress.

Conclusions

Our results indicate that morbidity due to kidney disease increases at high temperatures. We also found significant results in subgroup analyses. However, further time-series analyses are needed to obtain more generalizable evidence.

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

BACKGROUND

Extreme temperature events are known to be adversely associated with a range of health outcomes, but little is known about the effect of less extreme, but more frequent fluctuation in temperature. We examined the spatiotemporal and demographic variation in the effect of temperature variability (TV) on nationwide hospitalizations in Brazil during 2000-2015.

METHODS

Data on daily hospitalizations and weather variables were collected from 1814 cities, comprising 78.4% of Brazilian population. TV was defined as the standard deviation of daily minimum and maximum temperatures during exposure days. City-specific TV effect was estimated using a quasi-Poisson regression model, and then pooled at the national and regional level using meta-analysis. Stratified analyses were performed by sex, 10 age-groups, and 11 cause categories. Meta-regression was applied to city-year-specific estimates to examine the temporal change.

RESULTS

The estimate of TV effect peaked on 0-1 days' exposure, contributing to 3.5% [95% confidence interval (CI): 3.1-3.8%] of hospitalizations nationwide, equalling 221 (95%CI: 200-242) cases per 100,000 population annually. The effect estimate varied across 11 cause categories, which was strongest for respiratory admissions. Males, particular those 10-49 year old were more affected than females but there was no sex difference for the attributable hospitalization rate. The attributable rate for the under-fives was twice as high as for the elderly, and five times higher than in adults. The majority of the most affected cities were located in the central west and the inland of northeast. The risk of hospitalization related to TV showed a significant increase over the 16-year period at the national level.

CONCLUSIONS

In Brazil, the effect of TV on hospitalization is acute, and varies by spatial, sex, age, and cause category. Given there is no evidence regarding TV adaptation, hospitalization burden associated with TV is likely to further increase and warrants consideration when developing future public health policies in the context of climate change.

Association between diurnal temperature range and mortality modified by temperature in Japan, 1972-2015: Investigation of spatial and temporal patterns for 12 cause-specific deaths

Many previous literatures suggested that high temperature and diurnal temperature range (DTR) are prominent risk factors to increase risk of mortality. However, the role of effect modification of temperature on the DTR-related mortality is unclear. We examined whether temperature was an effect modifier on the DTR-mortality association and how the modification patterns differed by cause of deaths and different regional climates using a nationwide 47 prefecture data in Japan (1972-2015). We used a two-stage analysis. For the first stage, we used a time-series regression with a distributed lag model to estimate the DTR-mortality association according to five levels of temperature (extreme cold, cold, moderate, hot, and extreme hot days) for each prefecture stratified by twelve cause-specific deaths. Then, we applied a meta-analysis to pool the estimates across the 47 prefectures in Japan and separately by cooler vs. warmer regions. Our findings showed that the risk of mortality associated with DTR was strongly modified by temperature for all causes and cardiovascular deaths (p < 0.001) in the total population, suggesting that the influence of DTR on mortality increases at higher levels of temperature. These findings were consistent across warmer and cooler regions. Similar patterns were observed for respiratory and renal disease deaths which demonstrated the associations with DTR were the highest during extreme hot days, although it was statistically not significant and varied depending on the climate regions. Our findings suggest that the DTR-related mortality may be modified by daily mean temperature and the most elevated during extremely hot temperatures.

Vulnerability to the impact of temperature variability on mortality in 31 major Chinese cities

Few studies have analyzed the health effects of temperature variability (TV) accounting for both interday and intraday variations in ambient temperature. In this study, TV was defined as the standard deviations of the daily minimum and maximum temperature during different exposure days. Distributed lag non-linear Poisson regression model was used to examine the city-specific effect of TV on mortality in 31 Chinese municipalities and provincial capital cities. The national estimate was pooled through a meta-analysis based on the restricted maximum likelihood estimation. To assess effect modification on TV-mortality association by individual characteristics, stratified analyses were further fitted. Potential effect modification by city characteristics was performed through a meta-regression analysis. In total, 259 million permanent residents and 4,481,090 non-accidental deaths were covered in this study. The effect estimates of TV on mortality were generally increased by longer exposure days. A 1 °C increase in TV at 0-7 days' exposure was associated with a 0.60% (95% CI: 0.25-0.94%), 0.65% (0.24-1.05%), 0.82% (0.29-1.36%), 0.86% (0.42-1.31%), 0.98% (0.57-1.39%) and 0.54% (-0.11-1.20%) increase in non-accidental, cardiovascular, IHD, stroke, respiratory and COPD mortalities, respectively. Those with lower levels of educational attainment were significantly susceptible to TV. Cities with dense population, higher mean temperatures, and relative humidity and lower diurnal temperature ranges also had higher mortality risks caused by TV. This study demonstrated that TV had considerable health effects. An early warning system to alert residents about large temperature variations is recommended, which may have a significant impact on the community awareness and public health.

Diurnal temperature range in relation to death from stroke in China

BACKGROUND

Stroke is the second leading cause of death in the world. It has multiple risk factors of which some, such as ambient temperature, are less well documented.

OBJECTIVE

We aimed to examine the association between diurnal temperature range (DTR) and stroke mortality, and to test the possible effect modification of this association according to gender, age and educational level.

METHODS

Daily data on weather and stroke mortality from 16 provincial capital cities in China for the years 2007-2013 were obtained, with a total of 788,783 deaths from stroke. A quasi-Poisson generalized linear regression combined with a distributed lag non-linear model was used to examine the city-specific DTR effect on stroke mortality. The pooled effects of DTR on stroke mortality were then obtained using a meta-analysis, which was based on restricted maximum likelihood estimation.

RESULTS

The DTR impacts were generally limited to a period of eight days, while significant effects during lag 0-8 days were only found in the cities of Beijing, Zhengzhou, Nanjing, Hefei, Chongqing and Changsha. The DTR effects were significantly and negatively associated with latitudes at lag 0-10 days (r_s = - 0.640, P = 0.008). An increase of 1 °C in DTR was associated with pooled estimate of 0.66% (95%CI: 0.28-1.05%), 0.12% (- 0.26% to 0.51%) and 0.67% (0.26-1.07%) increases in stroke mortality at lag 0-10 days during the total, hot and cold days, respectively. The impact of DTR was much higher in southern China than in northern China [1.02% (0.62% to 1.43%) versus 0.10% (-0.27% to 0.47%) ]. For the individual characteristics, only females, the elderly aged ≥ 65 years, and those with lower educational attainment were vulnerable to DTR.

CONCLUSIONS

DTR has considerable effects on risk of mortality from stroke in various cities in China, especially among the elderly, females, those with low educational level, and people living in southern China. The results can inform decisions on developing programs to protect vulnerable subpopulations from adverse impacts of DTR.

Temporal and seasonal variations of mortality burden associated with hourly temperature variability: A nationwide investigation in England and Wales

BACKGROUND

Sudden temperature change may elevate short-term mortality and remains an important global health threat in the context of climate change. To date, however, little available temperature-mortality evidence has taken into account both intra- and inter-day temperature variability (TV), thus largely limiting the comprehensive understanding of mortality burden due to unstable weather. Moreover, seasonal and temporal patterns in TV-mortality associations were sparsely discussed, nationally and regionally.

OBJECTIVES

We aimed to assess the nationwide association of all-cause mortality with hourly temperature variability (HTV), quantify HTV-attributable mortality, and further explore the temporal and seasonal variations of mortality burden due to HTV in United Kingdom.

METHODS

Fourteen-year time-series data on temperature and mortality were collected from 10 regions in England and Wales during 1993-2006, totally including 7,573,716 all-cause deaths. HTV was calculated from the standard deviation of hourly temperature records within two neighboring days. A three-stage analytic approach was adopted to assess HTV-associated mortality burden. We first applied a time-series quasi-Poisson regression to estimate region-specific HTV-mortality associations, then pooled these associations at the national level using a multivariate meta-analysis, and finally estimated the HTV-attributable mortality fraction and illustrated its seasonal and temporal variations by conducting season- and period-specific analyses based on time-varying distributed lag models.

RESULTS

We found strong evidence that large HTV exposure elevated short-term mortality risk in England and Wales, with a pooled estimate of 1.13% (95% confidence interval (CI): 0.88, 1.39) associated with a 1-°C increase in HTV. During the whole study period, HTV accounted for a national average attributable fraction of 2.52% (95% empirical confidence interval (eCI): 2.27, 2.76) of the total deaths. This HTV-attributable mortality estimate showed a significant temporal decrease (p < 0.001) from 2.72% (95% eCI: 2.58, 2.87) in 1993-99 to 2.28% (95% eCI: 2.13, 2.43) in 2000-06. Additionally, clear seasonal variations were observed for HTV-attributable mortality burden, with the largest estimate of 3.08% (95% eCI: 2.80, 3.38) in summer, followed by 2.71% (95% eCI: 2.44, 2.98) in spring, 2.40% (95% eCI: 2.16, 2.63) in autumn, and 2.00% (95% eCI: 1.81, 2.20) in winter.

CONCLUSIONS

Despite clear evidence observed for the reduction, mortality burden caused by temperature variability remained a great public health threat, especially in warm seasons. It highlighted the importance of specific interventions targeted to unstable weather as well as temperature extremes, so as to reduce climate-related mortality burden.

The relationship between diurnal temperature range and COPD hospital admissions in Changchun, China

Diurnal temperature range (DTR) has been suggested to be an adverse health factor especially related to respiratory and cardiovascular diseases. In the current study, we investigated the association between DTR and chronic obstructive pulmonary disease (COPD) hospital admissions during 2009 to 2012 in northeast city of Changchun, China. Based on generalized additive model (GAM), the effects were expressed as relative risk (RR) values of COPD with 95% confidence intervals (CIs) with each 1 °C increase in DTR. And they were significantly increased with an increment of 1 °C in DTR, modified by season, age, and sex. The elderly were more vulnerable, with relative risk values of 1.048 (1.029, 1.066) in cold season and 1.037 (1.021, 1.053) in warm season. Regarding the gender, the DTR effect on females was greater during cold season and the RR value was 1.051 (1.033, 1.069) on the current day (lag 0). The greater estimates for males appeared at lag 7 days, with RR of 1.019 (0.998, 1.040). A season-specific effect was detected that the relative risk values with per 1 °C increase in DTR were greater in cold season than in warm season. These findings support the hypothesis of significant relationship between DTR and COPD in Changchun, one northeast city of China.

Effects of diurnal temperature range on mortality in Hefei city, China

Although several studies indicated an association between diurnal temperature range (DTR) and mortality, the results about modifiers are inconsistent, and few studies were conducted in developing inland country. This study aims to evaluate the effects of DTR on cause-specific mortality and whether season, gender, or age might modify any association in Hefei city, China, during 2007-2016. Quasi-Poisson generalized linear regression models combined with a distributed lag non-linear model (DLNM) were applied to evaluate the relationships between DTR and non-accidental, cardiovascular, and respiratory mortality. We observed a J-shaped relationship between DTR and cause-specific mortality. With a DTR of 8.3 °C as the reference, the cumulative effects of extremely high DTR were significantly higher for all types of mortality than effects of lower or moderate DTR in full year. When stratified by season, extremely high DTR in spring had a greater impact on all cause-specific mortality than other three seasons. Male and the elderly (≥ 65 years) were consistently more susceptible to extremely high DTR effect than female and the youth (< 65 years) for non-accidental and cardiovascular mortality. To the contrary, female and the youth were more susceptible to extremely high DTR effect than male and the elderly for respiratory morality. The study suggests that extremely high DTR is a potential trigger for non-accidental mortality in Hefei city, China. Our findings also highlight the importance of protecting susceptible groups from extremely high DTR especially in the spring.

Seasonal temperature variability and emergency hospital admissions for respiratory diseases: a population-based cohort study

Background

Climate change increases global mean temperature and changes short-term (eg, diurnal) and long-term (eg, intraseasonal) temperature variability. Numerous studies have shown that mean temperature and short-term temperature variability are both associated with increased respiratory morbidity or mortality. However, data on the impact of long-term temperature variability are sparse.

Objective

We aimed to assess the association of intraseasonal temperature variability with respiratory disease hospitalisations among elders.

Methods

We ascertained the first occurrence of emergency hospital admissions for respiratory diseases in a prospective Chinese elderly cohort of 66 820 older people (≥65 years) with 10–13 years of follow-up. We used an ordinary kriging method based on 22 weather monitoring stations in Hong Kong to spatially interpolate daily ambient temperature for each participant’s residential address. Seasonal temperature variability was defined as the SD of daily mean summer (June–August) or winter (December–February) temperatures. We applied Cox proportional hazards regression with time-varying exposure of seasonal temperature variability to respiratory admissions.

Results

During the follow-up time, we ascertained 12 689 cases of incident respiratory diseases, of which 6672 were pneumonia and 3075 were COPD. The HRs per 1°C increase in wintertime temperature variability were 1.20 (95% CI 1.08 to 1.32), 1.15 (1.01 to 1.31) and 1.41 (1.15 to 1.71) for total respiratory diseases, pneumonia and COPD, respectively. The associations were not statistically significant for summertime temperature variability.

Conclusion

Wintertime temperature variability was associated with higher risk of incident respiratory diseases.

Association of diurnal temperature range with daily mortality in England and Wales: A nationwide time-series study

BACKGROUND

Diurnal temperature range (DTR) reflects within-day temperature variability and is closely associated with climate change. In comparison to temperature extremes, up-to-date DTR-health evidence at the regional and national scales has been still very limited worldwide, especially in Europe.

OBJECTIVES

This study aimed to provide nationwide estimates for DTR-associated effects on mortality, and explore whether season and regional-level characteristics modify DTR-mortality relation in United Kingdom.

METHODS

Fourteen-year time-series data on weather and mortality were collected from 10 regions in England and Wales during 1993-2006, including 7,573,716 total deaths. A quasi-Poisson regression incorporated with distributed lag non-linear model was first applied to estimate region-specific DTR-mortality relationships. Then, a multivariate meta-analysis was employed to derive the pooled DTR effects at the national level. Also, the modifying effects of some regional characteristics (e.g., geographical and climatological) were examined by conducting multivariate meta-regression.

RESULTS

A non-linear DTR-mortality relationship was identified in UK. At the national level, increasing DTR raised the mortality risk observably when DTR exposure was below 25th percentile or above 90th percentile of DTR distribution, with an intermediate risk plateau indicating no associations. Extremely high DTR exhibited greater adverse effect estimates in hot season compared with in cold and transitional season, whereas entirely different association patterns were observed for the season-specific effects of extremely low DTR. In addition to season, regional latitudes, average temperature and humidity were also found to significantly modify DTR-mortality relationship.

CONCLUSIONS

Our study added strong evidence that extremely high DTR increased short-term mortality, whereas the effects of extremely low DTR exhibited entirely different seasonal patterns. Also, mortality vulnerability to DTR extremes varied greatly by regional latitudes and climate conditions.

Mortality burden of diurnal temperature range and its temporal changes: A multi-country study

Although diurnal temperature range (DTR) is a key index of climate change, few studies have reported the health burden of DTR and its temporal changes at a multi-country scale. Therefore, we assessed the attributable risk fraction of DTR on mortality and its temporal variations in a multi-country data set. We collected time-series data covering mortality and weather variables from 308 cities in 10 countries from 1972 to 2013. The temporal change in DTR-related mortality was estimated for each city with a time-varying distributed lag model. Estimates for each city were pooled using a multivariate meta-analysis. The results showed that the attributable fraction of total mortality to DTR was 2.5% (95% eCI: 2.3-2.7%) over the entire study period. In all countries, the attributable fraction increased from 2.4% (2.1-2.7%) to 2.7% (2.4-2.9%) between the first and last study years. This study found that DTR has significantly contributed to mortality in all the countries studied, and this attributable fraction has significantly increased over time in the USA, the UK, Spain, and South Korea. Therefore, because the health burden of DTR is not likely to reduce in the near future, countermeasures are needed to alleviate its impact on human health.

An Investigation on Attributes of Ambient Temperature and Diurnal Temperature Range on Mortality in Five East-Asian Countries

Interest in the health effects of extremely low/high ambient temperature and the diurnal temperature range (DTR) on mortality as representative indices of temperature variability is growing. Although numerous studies have reported on these indices independently, few studies have provided the attributes of ambient temperature and DTR related to mortality, concurrently. In this study, we aimed to investigate and compare the mortality risk attributable to ambient temperature and DTR. The study included data of 63 cities in five East-Asian countries/regions during various periods between 1972 and 2013. The attributable risk of non-accidental death to ambient temperature was 9.36% (95% confidence interval [CI]: 8.98-9.69%) and to DTR was 0.59% (95% CI: 0.53-0.65%). The attributable cardiovascular mortality risks to ambient temperature (15.63%) and DTR (0.75%) are higher than the risks to non-accidental/respiratory-related mortality. We verified that ambient temperature plays a larger role in temperature-associated mortality, and cardiovascular mortality is susceptible to ambient temperature and DTR.

Diurnal Temperature Range in Relation to Daily Mortality and Years of Life Lost in Wuhan, China

Diurnal temperature range (DTR) is an important meteorological indicator associated with global climate change, and has been linked with mortality and morbidity in previous studies. To date, however, little evidence has been available regarding the association of DTR with years of life lost (YLL). This study aimed to evaluate the DTR-related burden on both YLL and mortality. We collected individual records of all registered deaths and daily meteorological data in Wuhan, central China, between 2009 and 2012. For the whole population, every 1 °C increase in DTR at a lag of 0–1 days was associated with an increase of 0.65% (95% CI: 0.08–1.23) and 1.42 years (−0.88–3.72) for mortality and YLL due to non-accidental deaths, respectively. Relatively stronger DTR-mortality/YLL associations were found for cardiovascular deaths. Subgroup analyses (stratified by gender, age, and education level) showed that females, the elderly (75+ years old), and those with higher education attainment (7+ years) suffered more significantly from both increased YLL and mortality due to large DTR. Our study added additional evidence that short-term exposure to large DTR was associated with increased burden of premature death using both mortality incidence and YLL.

Ambient temperature and cardiovascular mortality: a systematic review and meta-analysis

INTRODUCTION

Our study aims at identifying and quantifying the relationship between the cold and heat exposure and the risk of cardiovascular mortality through a systematic review and meta-analysis.

MATERIAL AND METHODS

A systematic review and meta-analysis were conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Peer-reviewed studies about the temperature and cardiovascular mortality were retrieved in the MEDLINE, Web of Science, and Scopus databases from January 2000 up to the end of 2015. The pooled effect sizes of short-term effect were calculated for the heat exposure and cold exposure separately. Also, we assessed the dose-response relationship of temperature-cardiovascular mortality by a change in units of latitudes, longitude, lag days and annual mean temperature by meta-regression.

RESULT

After screening the titles, abstracts and full texts, a total of 26 articles were included in the meta-analysis. The risk of cardiovascular mortality increased by 5% (RR, 1.055; 95% CI [1.050-1.060]) for the cold exposure and 1.3% (RR, 1.013; 95% CI [1.011-1.015]) for the heat exposure. The short-term effects of cold and heat exposure on the risk of cardiovascular mortality in males were 3.8% (RR, 1.038; 95% CI [1.034-1.043]) and 1.1%( RR, 1.011; 95% CI [1.009-1.013]) respectively. Moreover, the effects of cold and heat exposure on risk of cardiovascular mortality in females were 4.1% (RR, 1.041; 95% CI [1.037-1.045]) and 1.4% (RR, 1.014; 95% CI [1.011-1.017]) respectively. In the elderly, it was at an 8.1% increase and a 6% increase in the heat and cold exposure, respectively. The greatest risk of cardiovascular mortality in cold temperature was in the 14 lag days (RR, 1.09; 95% CI [1.07-1.010]) and in hot temperatures in the seven lag days (RR, 1.14; 95% CI [1.09-1.17]). The significant dose-response relationship of latitude and longitude in cold exposure with cardiovascular mortality was found. The results showed that the risk of cardiovascular mortality increased with each degree increased significantly in latitude and longitude in cold exposure (0.2%, 95% CI [0.006-0.035]) and (0.07%, 95% CI [0.0003-0.014]) respectively. The risk of cardiovascular mortality increased with each degree increase in latitude in heat exposure (0.07%, 95% CI [0.0008-0.124]).

CONCLUSION

Our findings indicate that the increase and decrease in ambient temperature had a relationship with the cardiovascular mortality. To prevent the temperature- related mortality, persons with cardiovascular disease and the elderly should be targeted. The review has been registered with PROSPERO (registration number CRD42016037673).

Impact of temperature variation on mortality: An observational study from 12 counties across Hubei Province in China

BACKGROUND

Compared with cold- and heat-related health impacts, the evidence was very limited in assessing the mortality effects of temperature variation (TV) accounting for both intra-day and inter-day changes in temperature.

OBJECTIVE

We used a newly proposed composite indicator of intra-day and inter-day TV and evaluated TV-mortality associations in Hubei, China at the provincial level.

METHODS

Daily mortality and meteorological data during 2009-2012 were obtained from 12 urban and rural counties across Hubei Province in China. TV was calculated using the standard deviation of the minimum and maximum temperatures during the exposure days. A quasi-Poisson generalized linear regression combined with distributed lag non-linear model was first applied to estimate county-specific relationship between mortality and TV, adjusting for long-term trend and seasonality, mean temperature, relative humidity, public holiday, and day of the week. A meta-analysis was then conducted to pool the county-specific estimates of TV-related mortality effects.

RESULTS

A significant positive association was observed between TV and cause-specific mortality (except for respiratory mortality and ischemic heart disease mortality). The effect estimates varied by exposure days, with the highest at 0-7days. Season-stratified analyses showed similar results, while stronger TV-mortality associations were found in warm season than in cold season. The elderly were more susceptible to TV-related mortality effects than younger groups. Some slight differences in effect estimates were also observed in subgroups stratified by gender, education attainment, place of death, and urban/rural areas.

CONCLUSION

Our study strengthened the evidence that temperature variation was an independent risk factor for non-accidental mortality. Some preventive and intervention strategies should be efficiently developed in response to global climate change, so as to minimize public health burden due to unstable weather patterns.

What drives cold-related excess mortality in a south Asian tropical monsoon climate-season vs. temperatures and diurnal temperature changes

Despite the tropical climate which is characterized by generally high temperatures and persistent mild temperatures during the winter season, Bangladesh, along with many other tropical countries, experiences strong winter and cold-related excess mortality. The objective of this paper was to analyse the nature of these cold effects and understand the role of season vs. temperature and diurnal changes in temperature. For approaching these questions, we applied different Poisson regression models. Temperature as well as diurnal temperature range (DTR) were considered as predictor variables. Different approaches to seasonality adjustment were evaluated and special consideration was given to seasonal differences in atmospheric effects. Our findings show that while seasonality adjustment affected the magnitude of cold effects, cold-related mortality persisted regardless the adjustment approach. Strongest effects of low temperatures were observed at the same day (lag 1) with an increase of 1.7% (95% CI = 0.86-2.54%) per 1 °C decrease in temperature during the winter season. Diurnal temperature affected mortality with increasing levels at higher ranges. Mortality increased with 0.97% (95% CI = 0.17-1.75%) when looking at the entire season, but effects of DTR were not significant during winter when running a seasonal model. Different from effects observed in the mid-latitudes, cold effects in Bangladesh occurred on a very short time scale highlighting the role of temperature versus season. Insufficient adaptation with regard to housing and clothing might lead to such cold-related increases in mortality despite rather moderate temperature values. Although the study did not demonstrate an effect of DTR during the cold season, the strong correlation with (minimum) temperature might cause a multicollinearity problem and effects are difficult to attribute to one driver.

Temperature change between neighboring days and mortality in United States: A nationwide study

BACKGROUND

Temperature change between neighboring days (TCN), an indicator to reflect sudden temperature variation, has been identified as an independent risk factor for human health by small-scale studies. However, the adverse impact of TCN on mortality and effect modification are insufficiently studied, and a larger multi-cities analysis at national level is needed to provide an insightful knowledge.

METHODS

Using daily mortality and meteorological data from 106 communities of United States during 1987 to 2000, we employed a quasi-Poisson regression with distributed lag non-linear model to quantitatively estimate the effect of TCN on mortality for each community and a multivariate meta-analysis to pool the community-specific estimates.

RESULTS

At national level, a monotonic increasing curve of TCN-mortality association was observed, which indicated that negative TCN (temperature decrease from the previous day) was associated with reduced mortality and positive TCN (temperature increase) elevated the risk of mortality. The relative risk for lag 0-21days was 0.63 (95% confidence interval: 0.59-0.68) for extremely negative TCN (1st percentile) and 1.46 (1.39-1.54) for extremely positive TCN (99th percentile) on non-accidental mortality. We also found prominent effects of extreme TCNs on mortality for cardiovascular, respiratory, pneumonia, and COPD diseases. People ≥75years and those with respiratory disease, especially pneumonia-deaths, were identified as a particularly vulnerable population to TCN. The TCN-mortality association was modified by season and region.

CONCLUSIONS

A positive TCN was associated with an elevated risk of mortality in United States, with different effect patterns by region and season. Identification of the effect modifiers presented a significantly stronger influence on older adults and those with respiratory disease.

High diurnal temperature range and mortality: Effect modification by individual characteristics and mortality causes in a case-only analysis

BACKGROUND

Consistent evidence has shown that high diurnal temperature range (DTR) is associated with excess mortality, but little is known about the subgroups in the association. We aimed to identify the effect modifiers, including individual characteristics and specific mortality causes, of the association in a high plateau region with large DTR and extensive ethnic minorities in China.

METHODS

We conducted a case-only analysis in 77,319 non-accidental deaths in Yuxi during 2007-2014, and evaluated the effect modifiers of the association of high DTR exposure and mortality. All non-accidental deaths were divided into cardiovascular, respiratory, and "other" causes. High DTR days were defined as ≥ 90th percentile of DTR.

RESULTS

Risk of mortality on high DTR days was associated with age 75-84 years (odds ratio 1.07; 95% confidence interval 1.01-1.14) and ≥ 85 years (1.16; 1.08-1.24) as compared with age ≤ 64 years. The risk of the association was less for the Dai ethnic minority than Chinese Han (0.85; 0.75-0.96). Farmers (1.08; 1.03-1.14) and people with hypertension (1.09; 1.02-1.16) showed greater risk of dying on high DTR days than non-farmers and people without hypertension, respectively. Compared with "other" mortality causes, the risk was greater with cardiovascular causes (1.09; 1.04-1.15), notably ischemic heart disease (1.16; 1.08-1.25) and myocardial infarction (1.18; 1.08-1.29) in heart disease (1.11; 1.04-1.17), and ischemic stroke (1.17; 1.06-1.28) in stroke deaths (1.09; 1.03-1.15), as well as chronic bronchitis (1.22; 1.11-1.33) and chronic obstructive pulmonary disease (1.12; 1.05-1.20) in respiratory deaths (1.11; 1.04-1.18).

CONCLUSIONS

Individual characteristics and specific mortality causes can modify the association of high DTR and mortality. This knowledge may help in better targeting the vulnerable populations and developing more effective intervention strategies.