Temperature changes between neighboring days and mortality in summer: a distributed lag non-linear time series analysis

Effect of various temperature indicators on patients' hospitalization with cardiovascular diseases in Zhangye city, China

This study assessed the impact of various temperature indices, including mean temperature (MT), diurnal temperature range (DTR), and temperature changes between neighboring days (TCN) on hospitalization rates for cardiovascular system diseases among residents of Zhangye City, a typical western city in China. The Quasi-Poisson generalized additive regression model (GAM) in conjunction with a distributed lag nonlinear model (DLNM) was applied to estimate the association of temperature indices with CVD hospitalization rates in Zhangye City during the periods of 2015-2021. The exposure-response relationship and relative risk were discussed and stratified analyses by age and gender were conducted. We found that the hospitalization rates of cardiovascular disease (CVD) patients in Zhangye City was significantly related to different temperature indicators (MT, DTR, TCN). Both low and high MT, DTR, and TCN increased the risk of cardiovascular disease (CVD) among residents. Besides, different demographic populations exhibited distinct sensitivities to temperature conditions. Relevant authorities should devise corresponding preventive and control measures to protect vulnerable populations.

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.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The effect of ambient temperature on hand, foot and mouth disease in Qingdao, China, 2014-2018

Hand, foot, and mouth disease (HFMD) is a kind of infection gastrointestinal disease. The present study aims to explore the association between ambient temperature and HFMD in Qingdao. A distributed lag nonlinear model with Poisson distribution was adopted to explore the effects of daily mean temperature on HFMD incidence. Our results found that the high temperature had acute and short-term effects and then declined rapidly along the lag days, with the maximum risk occurring 0 day of exposure. Compared with low temperature, higher effects were observed for high-temperature exposure. Overall, we found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "J" shape, with peak value occurring at 30.5℃ (RR = 2.208, 95% CI: 1.995-2.444). Our findings suggest that ambient temperature is significantly associated with the incidence of HFMD in Qingdao. Monitoring ambient temperature changes is an appropriate recommendation to prevent HFMD.

Fire-Pollutant-Atmosphere Components and Its Impact on Mortality in Portugal During Wildfire Seasons

This study analyzed fire-pollutant-meteorological variables and their impact on cardio-respiratory mortality in Portugal during wildfire season. Data of burned area, particulate matter with a diameter of 10 or 2.5 μm (μm) or less (PM10, PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, relative humidity, wind speed, aerosol optical depth and mortality rates of Circulatory System Disease (CSD), Respiratory System Disease (RSD), Pneumonia (PNEU), Chronic Obstructive Pulmonary Disease, and Asthma (ASMA), were used. Only the months of 2011-2020 wildfire season (June-July-August-September-October) with a burned area greater than 1,000 ha were considered. Principal component analysis was used on fire-pollutant-meteorological variables to create two indices called Pollutant-Burning Interaction (PBI) and Atmospheric-Pollutant Interaction (API). PBI was strongly correlated with the air pollutants and burned area while API was strongly correlated with temperature and relative humidity, and O3. Cluster analysis applied to PBI-API divided the data into two Clusters. Cluster 1 included colder and wetter months and higher NO2 concentration. Cluster 2 included warmer and dried months, and higher PM10, PM2.5, CO, and O3 concentrations. The clusters were subjected to Principal Component Linear Regression to better understand the relationship between mortality and PBI-API indices. Cluster 1 showed statistically significant (p-value < 0.05) correlation (r) between RSDxPBI (r RSD = 0.58) and PNEUxPBI (r PNEU = 0.67). Cluster 2 showed statistically significant correlations between RSDxPBI (r RSD = 0.48), PNEUxPBI (r PNEU = 0.47), COPDxPBI (r COPD = 0.45), CSDxAPI (r CSD = 0.70), RSDxAPI (r CSD = 0.71), PNEUxAPI (r PNEU = 0.49), and COPDxAPI (r PNEU = 0.62). Cluster 2 analysis indicates that the warmest, driest, and most polluted months of the wildfire season were associated with cardio-respiratory mortality.

Association Between Exposure to Ozone (O3) and the Short-Term Effect on Tuberculosis Outpatient Visits: A Time-Series Study in 16 Cities of Anhui Province, China

Introduction

Evidence has shown that air pollutant exposure plays a vital role in the progression of tuberculosis (TB). The aim of this research was to assess the short-term effects of ozone (O₃) exposure and TB outpatient visits in 16 prefecture-level cities of Anhui, China, 2015-2020.

Methods

Distributed lag nonlinear model (DLNM), Poisson generalized linear regression model and random effects model were applied in this study. The effects of different age and gender on TB were investigated by stratified analysis, and then we performed sensitivity analyses to verify the stability of the results.

Results

A total of 186,623 active TB cases were registered from January 1, 2015 to December 31,2020 in Anhui. The average concentration of ozone is 92.77 ± 42.95 μg/m³. The maximum lag-specific and cumulative relative risk (RR) of TB outpatient visits was 1.0240 (95% CI: 1.0170-1.0310, lag 28 days) for each 10 µg/m³ increase in O₃ in the single-pollutant model. Estimation for 16 prefecture-level cities indicated that the strong association between O₃ and the risk of TB outpatient visits was in tongling (RR = 1.0555, 95% CI: 1.0089-1.1042), Suzhou (RR = 1.0475, 95% CI: 1.0268-1.0687), wuhu (RR = 1.0358, 95% CI: 1.0023-1.0704). Stratified analysis showed that the health effects of ozone exposure remained significant in male and older adults, and there was no significant association between exposure to ozone in children and adolescents and the risk of tuberculosis.

Discussion

We found that ozone exposure increases the risk of TB infection in outpatient patients, with males and the elderly being more susceptible, and it is necessary for government departments to develop targeted publicity and prevention measures in response to the local air quality conditions.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Hospital admission tendencies caused by day-to-day temperature changes during summer: a case study for the city of Novi Sad (Serbia)

Increased temperature risk in cities threatens the health and well-being of urban population and is fueled by climate change and intensive urbanization. Consequently, further steps must be taken for assessing temperature conditions in cities and their association with public health, in order to improve public health prevention at local or regional level. This study contributes to solving the problems by analyzing the connection between extreme temperatures and the tendencies of all-cause hospital admissions. The analyses used (a) 1-h air temperature data, and (b) daily data of all-cause hospital admissions. The datasets include the summer period (June, July, August) for the years 2016 and 2017. We tested the effects of two temperature indices, day-to-day change in maximum temperature - T_max,c and daily temperature range - T_r, with all-cause hospital admission subgroups, such as all-cause cases - H_a, hospital admissions in the population below 65 - H_a<65, and hospital admissions in the population aged 65 and over - H_a≥65. The results show the highest values of H_a when T_max,c is between 6 and 10 °C. Therefore, more intensive hospital admissions can be expected when T_max increases from day-to-day (positive values of T_max,c), and it is more visible for H_a and H_a<65 (1 °C = 1% increase in hospital admissions). Also, T_r values between 10 °C and 14 °C cause an increase in the number of hospital admissions, and it is more noticeable for H_a≥65.

LSTM model for predicting the daily number of asthma patients in Seoul, South Korea, using meteorological and air pollution data

Asthma is a common respiratory disease that is affected by air pollutants and meteorological factors. In this study, we developed models that predict the daily number of patients receiving treatment for asthma using air pollution and meteorological data. A neural network with long short-term memory (LSTM) and fully connected (FC) layers was used. The daily number of asthma patients in the city of Seoul, the capital of South Korea, was collected from the National Health Insurance Service. The data from 2015 to 2018 were used as the training and validation datasets for model development. Unseen data from 2019 were used for testing. The daily number of asthma patients per 100,000 inhabitants was predicted. The LSTM-FC neural network model achieved a Pearson correlation coefficient of 0.984 (P < 0.001) and root mean square error of 3.472 between the predicted and original values on the unseen testing dataset. The factors that impacted the prediction were the number of asthma patients in the previous time step before the predicted date, type of day (regular day and day after a holiday), minimum temperature, SO₂, daily changes in the amount of cloud, and daily changes in diurnal temperature range. We successfully developed a neural network that predicts the onset and exacerbation of asthma, and we identified the crucial influencing air pollutants and meteorological factors. This study will help us to establish appropriate measures according to the daily predicted number of asthma patients and reduce the daily onset and exacerbation of asthma in the susceptible population.

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSION

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

Health Risks of Temperature Variability on Hospital Admissions in Cape Town, 2011-2016

Epidemiological studies have provided compelling evidence of associations between temperature variability (TV) and health outcomes. However, such studies are limited in developing countries. This study aimed to investigate the relationship between TV and hospital admissions for cause-specific diseases in South Africa. Hospital admission data for cardiovascular diseases (CVD) and respiratory diseases (RD) were obtained from seven private hospitals in Cape Town from 1 January 2011 to 31 October 2016. Meteorological data were obtained from the South African Weather Service (SAWS). A quasi-Poisson regression model was used to investigate the association between TV and health outcomes after controlling for potential effect modifiers. A positive and statistically significant association between TV and hospital admissions for both diseases was observed, even after controlling for the non-linear and delayed effects of daily mean temperature and relative humidity. TV showed the greatest effect on the entire study group when using short lags, 0-2 days for CVD and 0-1 days for RD hospitalisations. However, the elderly were more sensitive to RD hospitalisation and the 15-64 year age group was more sensitive to CVD hospitalisations. Men were more susceptible to hospitalisation than females. The results indicate that more attention should be paid to the effects of temperature variability and change on human health. Furthermore, different weather and climate metrics, such as TV, should be considered in understanding the climate component of the epidemiology of these (and other diseases), especially in light of climate change, where a wider range and extreme climate events are expected to occur in future.

Mortality burden attributable to temperature variability in China

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

SIGNIFICANCE

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

IMPACT

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

Health effect of temperature change on respiratory diseases in opposite phase in semi-arid region

The impact of temperature variation on health has attracted increasing attention under global climate change. A distributed lag non-linear model (DLNM) was performed to estimate the risk of two indicators of temperature change (diurnal temperature range (DTR) and temperature change between neighboring days (TCN)) on respiratory hospital visits in Lanzhou, a semi-arid climate city in western China from 2012 to 2018. The whole year is divided into two different temperature change periods according to the TCN of each solar term. The results showed that extreme high DTR can apparently enlarge respiratory risk, and it indicated strong cumulative relative risk (RR) in the temperature drop period. Extreme low TCN had strong adverse effects on respiratory diseases especially in temperature rise period, with the greatest RR of 1.068 (95% CI 1.004, 1.136). The effect of extreme high TCN was more obvious in temperature drop period, with a RR of 1.082 (95% CI 1.021, 1.148) at lag 7. Females were more affected by extreme temperature changes. Young people were more vulnerable to DTR, while TCN has a greater impact on the elderly.

Protective effect of pneumococcal conjugate vaccination on the short-term association between low temperatures and childhood pneumonia hospitalizations: Interrupted time-series and case-crossover analyses in Matlab, Bangladesh

Studies have shown that ambient extreme temperatures (heat and cold) were associated with an increased risk of childhood pneumonia, but the evidence is very limited in low-middle-income countries. It also remains unknown whether pneumococcal conjugate vaccine (PCV) could prevent temperature-related childhood pneumonia. This study collected data on ambient temperature and hospitalizations for childhood pneumonia in Matlab, Bangladesh from 2012 to 2016. Interrupted time series (ITS) analysis was employed to assess the impact of PCV (10-valent) intervention on childhood pneumonia hospitalizations. A time-stratified case-crossover analysis with a conditional logistic regression was performed to examine the association of childhood pneumonia hospitalizations with extreme temperatures and heatwaves before and after PCV10 intervention. Subgroup analyses were conducted to explore the modification effects of seasons, age, gender, and socioeconomic levels on temperature-related childhood pneumonia hospitalizations. We found that after PCV10 intervention, there was a sharp decrease in hospitalizations for childhood pneumonia (relative risk (RR): 0.59, 95% confidence interval (CI): 0.43-0.83). During the study period, heat effects on childhood pneumonia appeared immediately on the current day (odds ratio (OR): 1.28; 95% CI: 1.02-1.60, lag 0), while cold effects appeared 4 weeks later (OR: 1.53, 95% CI: 1.06-2.22, lag 28). Importantly, cold effects decreased significantly after PCV10 (p-value＜0.05), but heat and heatwave effects increased after PCV10 (p-value＜0.05). Particularly, children from families with a middle or low socioeconomic level, boys, and infants were more susceptible to heat-related pneumonia. This study suggests that PCV10 intervention in Bangladesh may help decrease cold-related not heat-related childhood pneumonia.

Impact of temperature changes between neighboring days on cardiovascular disease hospital admissions among suburban farmers in Qingyang, Northwest China

BACKGROUND

No studies focused on impact of temperature changes between neighboring days (TCN) on cardiovascular disease (CVD) hospital admissions among suburban farmers although CVD has been the main cause to global mortality and disability especially in undeveloped and developing countries/areas.

METHOD

Daily data of CVD hospital admissions on suburban farmers and daily data of meteorology in Qingyang (China) were collected during 2011-2015. A distributed lag non-linear model (DLNM) was applied to explore the exposure-response relations and lagged effects between TCN and CVD hospital admissions with stratified analyses by age and gender. Extreme low TCN effects and burden analysis were conducted.

RESULTS

Based on 25,984 cases in Qingyang (China) during 2011-2015 among suburban farmers, we found that, first, nonlinear relationship was observed between TCN and CVD hospital admissions and adverse impact in negative TCN (temperature dropping between neighboring days) while protective effect in positive TCN (temperature rising between neighboring days) were discovered; third, during lag0-27, the cumulative relative risk (RR) for extreme low TCN (5th percentile, - 3.5 °C) and extreme high TCN (95th percentile, 3 °C) was 29.55 (95% CI 4.709-185.436) and 0.040 (95% CI 0.009-0.169), respectively; fourth, the age < 65 and females were more vulnerable to negative TCN than the age ≥ 65 and males among suburban farmers, respectively; last, moderate low TCN contributed the most fractions and numbers on CVD hospital admissions.

CONCLUSIONS

Among Qingyang suburban farmers in Northwest China, negative TCN should be paid more attention.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Effects of different heat exposure patterns (accumulated and transient) and schizophrenia hospitalizations: a time-series analysis on hourly temperature basis

Growing studies have shown that high temperature is a potential risk factor of schizophrenia occurrence. Therefore, elaborate analysis of different temperature exposure patterns, such as cumulative heat exposure within a time period and transient exposure at a particular time point, is of important public health significance. This study aims to utilize hourly temperature data to better capture the effects of cumulative and transient heat exposures on schizophrenia during the warm season in Hefei, China. We included the daily mean temperature and daily schizophrenia hospitalizations into the distributed lag non-linear model (DLNM) to simulate the exposure-response curve and determine the heat threshold (19.4 °C). We calculated and applied a novel indicator-daily excess hourly heat (DEHH)-to examine the effects of cumulative heat exposure over a day on schizophrenia hospitalizations. Temperature measurements at each time point were also incorporated in the DLNM as independent exposure indicators to analyze the impact of transient heat exposure on schizophrenia. Each increment of interquartile range (IQR) in DEHH was associated with elevated risk of schizophrenia hospitalizations from lag 1 (RR = 1.036, 95% confidence interval (CI): 1.016, 1.057) to lag 4 (RR = 1.025, 95% CI: 1.005, 1.046). Men and people over 40 years old were more susceptible to DEHH. Besides, we found a greater risk of heat-related schizophrenia hospitalizations between 0 a.m. and 6 a.m. This study revealed the adverse effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our findings need to be further tested in other regions with distinct regional features.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

An effect of 24-hour temperature change on outpatient and emergency and inpatient visits for cardiovascular diseases in northwest China

Some studies suggested that 24-h temperature change (TC24) was one of the potential risk factors for human health. However, evidence of the short-term effect of TC24 on outpatient and emergency department (O&ED) visits and hospitalizations for cause-specific cardiovascular diseases (CVDs) is still limited. The aim of this study is to explore the short-term effects of TC24 on O&ED visits and hospitalizations for CVDs in northwest China which is an area with large temperature variation. The O&ED visits records for CVDs of 3 general hospitals and the inpatient records for CVDs of 4 general hospitals were collected from January 1, 2013, to December 31, 2016, in Jinchang City, northwest China. Meteorological and air pollution data were also obtained during the same study period from local meteorological monitoring station and environmental monitoring station, respectively. A generalized additive model (GAM) with Poisson regression was employed to analyze the effects of TC24 on O&ED visits and hospitalizations for CVDs. V-shaped relationship were found between TC24 and O&ED visits and hospitalizations for CVDs, including total CVD, hypertension, coronary heart disease (CHD) and stroke. Stratified analysis showed that men and patients over 65 years old were more susceptible to temperature changes. The estimates in non-heating months were higher than in full year. TC24 can affect the O&ED visits and hospitalizations for CVDs in this study. This study provides useful data for policy makers to better prepare local responses to the impact of changes in temperature on population health.

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

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

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.

Temperature changes between neighboring days and childhood asthma: a seasonal analysis in Shanghai, China

Few evidences are available about the impact of temperature variation on childhood asthma in different seasons. This study aimed to assess the influence of temperature changes between neighboring days (TCN) on the exacerbation of asthma among children. Daily outpatient visits for childhood asthma (DOVCA) were collected from 17 main hospitals in Shanghai, China, from 2016 to 2018. A quasi-Poisson regression combined with distributed lagged nonlinear models was employed to estimate the association between TCN and asthma visits in cool or warm seasons, after controlling for short- and long-term trends, day of week, holidays, daily mean temperature, daily mean relative humidity, and air pollutants. The TCN varied from - 9.6 to 6.7 °C. The relationship between TCN and DOVCA greatly varied by season. In warm seasons, positive TCN (temperature rise) was associated with higher risks of asthma outpatient visits and negative TCN (temperature drop) was associated with lower risks; the associations were present on lag 1 day and lasted for 2 weeks; the cumulative relative risk of childhood asthma over 0 to 14 days was 1.98 (95% confidence interval: 1.42, 2.76) and 0.31 (95% confidence intervals: 0.21, 0.44) comparing a TCN of 2.5 °C (5th percentile) and - 3.2 °C (95th percentile) with 0 °C, respectively. In cool seasons, neither negative nor positive TCN showed significant risks. In conclusion, temperature rise might increase the risk of childhood asthma exacerbation and temperature drop might decrease the risks in warm seasons. There were no statistically significant influences in cool seasons.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

ALTERNATIVE

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

Analysis of Pneumonia Occurrence in Relation to Climate Change in Tanga, Tanzania

In 2018, 70% of global fatalities due to pneumonia occurred in about fifteen countries, with Tanzania being among the top eight countries contributing to these deaths. Environmental and individual factors contributing to these deaths may be multifaceted, but they have not yet been explored in Tanzania. Therefore, in this study, we explore the association between climate change and the occurrence of pneumonia in the Tanga Region, Tanzania. A time series study design was employed using meteorological and health data of the Tanga Region collected from January 2016 to December 2018 from the Tanzania Meteorological Authority and Health Management Information System, respectively. The generalized negative binomial regression technique was used to explore the associations between climate indicators (i.e., precipitation, humidity, and temperature) and the occurrence of pneumonia. There were trend differences in climate indicators and the occurrence of pneumonia between the Tanga and Handeni districts. We found a positive association between humidity and increased rates of non-severe pneumonia (incidence rate ratio (IRR) = 1.01; 95% CI: 1.01–1.02; p ≤ 0.05) and severe pneumonia (IRR = 1.02; 95% CI: 1.01–1.03; p ≤ 0.05). There was also a significant association between cold temperatures and the rate of severe pneumonia in Tanga (IRR = 1.21; 95% CI: 1.11–1.33; p ≤ 0.001). Other factors that were associated with pneumonia included age and district of residence. We found a positive relationship between humidity, temperature, and incidence of pneumonia in the Tanga Region. Policies focusing on prevention and control, as well as promotion strategies relating to climate change-related health effects should be developed and implemented.

The association between ambient temperature and mortality of the coronavirus disease 2019 (COVID-19) in Wuhan, China: a time-series analysis

Background

The COVID-19 has caused a sizeable global outbreak and has been declared as a public health emergency of international concern. Sufficient evidence shows that temperature has an essential link with respiratory infectious diseases. The objectives of this study were to describe the exposure-response relationship between ambient temperature, including extreme temperatures, and mortality of COVID-19.

Methods

The Poisson distributed lag non-linear model (DLNM) was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020, in Wuhan, China.

Results

During the period mentioned above, the average daily number of COVID-19 deaths was approximately 45.2. Poisson distributed lag non-linear model showed that there was a non-linear relationship (U-shape) between the effect of ambient temperature and mortality. With confounding factors controlled, the daily cumulative relative death risk decreased by 12.3% (95% CI [3.4, 20.4%]) for every 1.0 °C increase in temperature. Moreover, the delayed effects of the low temperature are acute and short-term, with the most considerable risk occurring in 5–7 days of exposure. The delayed effects of the high temperature appeared quickly, then decrease rapidly, and increased sharply 15 days of exposure, mainly manifested as acute and long-term effects. Sensitivity analysis results demonstrated that the results were robust.

Conclusions

The relationship between ambient temperature and COVID-19 mortality was non-linear. There was a negative correlation between the cumulative relative risk of death and temperature. Additionally, exposure to high and low temperatures had divergent impacts on mortality.

A review of the impact of outdoor and indoor environmental factors on human health in China

The Intergovernmental Panel on Climate Change (IPCC) reported that global climate change has led to the increased occurrence of extreme weather events. In the context of global climate change, more evidence indicates that abnormal meteorological conditions could increase the risk of epidemiological mortality and morbidity. In this study, using a systematic review, we evaluated a total of 175 studies (including 158 studies on outdoor environment and 17 studies on indoor environment) to summarize the impact of outdoor and indoor environment on human health in China using the database of PubMed, Web of Science, the Cochrane Library, and Embase. In particular, we focused on studies about cardiovascular and respiratory mortality and morbidity, the prevalence of digestive system diseases, infectious diseases, and preterm birth. Most of the studies we reviewed were conducted in three of the metropolises of China, including Beijing, Guangzhou, and Shanghai. For the outdoor environment, we summarized the effects of climate change-related phenomena on health, including ambient air temperature, diurnal temperature range (DTR), temperature extremes, and so on. Studies on the associations between temperature and human health accounted for 79.7% of the total studies reviewed. We also screened out 19 articles to explore the effect of air temperature on cardiovascular diseases in different cities in the final meta-analysis. Besides, modern lifestyle involves a large amount of time spent indoors; therefore, indoor environment also plays an important role in human health. Nevertheless, studies on the impact of indoor environment on human health are rarely reported in China. According to the limited reports, adverse indoor environment could impose a high health risk on children.

The Influence of Apparent Temperature on Mortality in the Kintampo Health and Demographic Surveillance Area in the Middle Belt of Ghana: A Retrospective Time-Series Analysis

Globally, studies have shown that diurnal changes in weather conditions and extreme weather events have a profound effect on mortality. Here, we assessed the effect of apparent temperature on all-cause mortality and the modifying effect of sex on the apparent temperature-mortality relationship using mortality and weather data archived over an eleven-year period. An overdispersed Poisson regression and distributed lag nonlinear models were used for this analysis. With these models, we analysed the relative risk of mortality at different temperature values over a 10-day lag period. By and large, we observed a nonlinear association between mean daily apparent temperature and all-cause mortality. An assessment of different temperature values over a 10-day lag period showed an increased risk of death at the lowest apparent temperature (18°C) from lag 2 to 4 with the highest relative risk of mortality (RR = 1.61, 95% CI: 1.2, 2.15, p value = 0.001) occurring three days after exposure. The relative risk of death also varied between males (RR = 0.31, 95% CI: 0.10, 0.94) and females (RR = 4.88, 95% CI: 1.40, 16.99) by apparent temperature and lag. On the whole, males are sensitive to both temperature extremes whilst females are more vulnerable to low temperature-related mortality. Accordingly, our findings could inform efforts at reducing temperature-related mortality in this context and other settings with similar environmental and demographic characteristics.

Impact of temperature changes between neighboring days on COPD in a city in Northeast China

Sudden temperature changes between neighboring days (T_24h) have adverse effects on human health. In this study, we used a time series analysis to evaluate the impact of T_24h on the number of hospital admissions for chronic obstructive pulmonary disease (COPD) from 2009 to 2012 in Changchun (the capital of Northeast China's Jilin province). We performed the analysis in a generalized additive model (GAM), and the controlling factors included long-term trends, day of the week effect, and the selected weather elements. We divided the entire study group into two gender subgroups (males and females) and two age subgroups (aged < 65 years and aged ≥ 65 years). T_24h showed the greatest effect on the entire study group at lag 3 days. In particular, the greatest effect of T_24h on females (males) occurred at lag 1 day (lag 3 days); the greatest effect of T_24h on the aged ≥ 65 years (aged < 65 years) occurred at lag 1 day (lag 6 days). This indicates that temperature changes between neighboring days have a relatively more acute effect on the elderly and the females than on the younger people and the males. When T_24h is less than zero, the highest RR of the number of hospital admissions for COPD occurred at lag 4 days during the warm season (1.025, 95% CI: 0.981, 1.069) and lag 3 days during the cold season (1.019, 95% CI: 0.988, 1.051). When T_24h is greater than zero, the highest RR of the number of hospital admissions for COPD occurred at lag 6 days during the warm season (1.026, 95% CI: 0.977, 1.077) and lag 5 days during the cold season (1.021, 95% CI: 0.986, 1.057). The results of this study could be provided to local health authorities as scientific guidelines for controlling and preventing COPD in Changchun, China.

Health impact of climate change in cities of middle-income countries: the case of China

BACKGROUND

This review examines the human health impact of climate change in China. Through reviewing available research findings under four major climate change phenomena, namely extreme temperature, altered rainfall pattern, rise of sea level and extreme weather events, relevant implications for other middle-income population with similar contexts will be synthesized.

SOURCES OF DATA

Sources of data included bilingual peer-reviewed articles published between 2000 and 2018 in PubMed, Google Scholar and China Academic Journals Full-text Database.

AREAS OF AGREEMENT

The impact of temperature on mortality outcomes was the most extensively studied, with the strongest cause-specific mortality risks between temperature and cardiovascular and respiratory mortality. The geographical focuses of the studies indicated variations in health risks and impacts of different climate change phenomena across the country.

AREAS OF CONTROVERSY

While rainfall-related studies predominantly focus on its impact on infectious and vector-borne diseases, consistent associations were not often found.

GROWING POINTS

Mental health outcomes of climate change had been gaining increasing attention, particularly in the context of extreme weather events. The number of projection studies on the long-term impact had been growing.

AREAS TIMELY FOR DEVELOPING RESEARCH

The lack of studies on the health implications of rising sea levels and on comorbidity and injury outcomes warrants immediate attention. Evidence is needed to understand health impacts on vulnerable populations living in growing urbanized cities and urban enclaves, in particular migrant workers. Location-specific climate-health outcome thresholds (such as temperature-mortality threshold) will be needed to support evidence-based clinical management plans and health impact mitigation strategies to protect vulnerable communities.

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.

Warm Front Passage on the Previous Day Increased Ischemic Stroke Events

BACKGROUND AND PURPOSE

The influence of a weather front passage is rarely evaluated on stroke events. We hypothesized that a weather front passage on the stroke onset day or during the previous days may play an important role in the incidence of stroke.

METHODS

A multicenter retrospective study was conducted to evaluate the frequency of stroke events and their interaction with weather front passages. Consecutive acute stroke patients (n = 3935, 73.5 ± 12.4 years, 1610 females) who were admitted to 7 stroke hospitals in 3 cities from January 2012 to December 2013 were enrolled in this study. Multivariate Poisson regression models involving time lag variables were used to compare the daily rates of stroke events with the day of a weather front passage and the previous 6 days, adjusting for considerable influences of ambient temperature and atmospheric pressure.

RESULTS

There were a total of 33 cold fronts and 13 warm fronts that passed over the 3 cities during the study period. The frequency of ischemic stroke significantly increased when a warm front passed on the previous day (risk ratio 1.34, 95% confidence interval 1.07-1.69, P= .016).

CONCLUSIONS

This study indicated that a weather front passage on the previous days may be associated with the occurrence of stroke.

Impact of summer heat on mortality and years of life lost: Application of a novel indicator of daily excess hourly heat

BACKGROUND

Previous studies have widely assessed heat-mortality relationships across global regions, while the epidemiological evidence regarding the heat effect on years of life lost (YLL) is relatively sparse. Current investigations using daily mean data cannot take hourly temperature variation into consideration and may underestimate heat effects. We developed a novel indicator, daily excess hourly heat (DEHH), to precisely evaluate the potential heat effects on mortality and YLL.

METHODS

Hourly data on temperature and daily information, including concentrations of air pollutants, relative humidity, and records of all registered deaths were obtained in Wuhan, China during the warm seasons (May-September) of 2009-2012. DEHH, developed in this study, is defined as daily total hourly temperatures that exceed a specific heat threshold. By performing time series regression analyses, we assessed the changes in daily mortality and YLL per interquartile range (IQR) increase in DEHH across different lag days.

RESULTS

The heat threshold evaluated by the Akaike Information Criterion for DEHH calculation is 30 °C (92th percentile of whole-year mean temperature distribution). Daily average DEHH was 13.9 °C, with an IQR of 19.9 °C. Linear exposure-response curves were found between DEHH and two health outcomes. Generally, heat effects lasted for 2-3 days and DEHH at lag 0-1 was most strongly associated with increased mortality and YLL. The effects were especially remarkable for stroke and ischemic heart disease mortality. Most intense effect on YLL was found in non-accidental deaths (20.11, 95% confidence interval: 8.90-31.33) at lag 0-1. More DEHH-related mortality and YLL from cardiovascular deaths were observed among males. People aged 0-74 years and males suffered more from YLL burden due to high temperatures.

CONCLUSIONS

Our study demonstrated that DEHH may be an alternative indicator to precisely measure heat effects on daily mortality and YLL. Further DEHH-based evidence from large scale investigations is needed so as to better understand heat-associated health burden and improve public response to extremely high temperatures.

Impact of heat on mortality and morbidity in low and middle income countries: A review of the epidemiological evidence and considerations for future research

Heat waves and high air temperature are associated with increased morbidity and mortality. However, the majority of research conducted on this topic is focused on high income areas of the world. Although heat waves have the most severe impacts on vulnerable populations, relatively few studies have studied their impacts in low and middle income countries (LMICs). The aim of this paper is to review the existing evidence in the literature on the impact of heat on human health in LMICs. We identified peer-reviewed epidemiologic studies published in English between January 1980 and August 2018 investigating potential associations between high ambient temperature or heat waves and mortality or morbidity. We selected studies according to the following criteria: quantitative studies that used primary and/or secondary data and report effect estimates where ambient temperature or heat waves are the main exposure of interest in relation to human morbidity or mortality within LMICs. Of the total 146 studies selected, eighty-two were conducted in China, nine in other countries of East Asia and the Pacific, twelve in South Asia, ten in Sub-Saharan Africa, eight in the Middle East and North Africa, and seven in each of Latin America and Europe. The majority of studies (92.9%) found positive associations between heat and human morbidity/mortality. Additionally, while outcome variables and study design differed greatly, most utilized a time-series study design and examined overall heath related morbidity/mortality impacts in an entire population, although it is notable that the selected studies generally found that the elderly, women, and individuals within the low socioeconomic brackets were the most vulnerable to the effects of high temperature. By highlighting the existing evidence on the impact of extreme heat on health in LMICs, we hope to determine data needs and help direct future studies in addressing this knowledge gap. The focus on LMICs is justified by the lack of studies and data studying the health burden of higher temperatures in these regions even though LMICs have a lower capacity to adapt to high temperatures and thus an increased risk.

Association between apparent temperature and acute coronary syndrome admission in Rasht, Iran

Objective

Our objective was to assess the relations between apparent temperature and incidence of acute coronary syndrome (ACS) in Rasht, Iran.

Methods

We used a time-series analysis to investigate the relationship between apparent temperature and hospital admission from 2005 to 2014. Distributed lag non-linear models were used to estimate the association between ACS hospitalisation and apparent temperature. To examine the high-temperature effect on ACS hospital admission, the relative risk of ACS hospital admission associated with high temperature, the 99th percentile of temperature (34.7°C) compared with the 75th percentile of temperature (26.9°C), was calculated. To assess the cold effect on ACS hospital admission, the relative risk of ACS hospital admission associated with cold temperature, the first percentile of temperature (-0.2°C) compared with the 25th percentile of temperature (8.2°C), was evaluated.

Results

The cumulative effect of hot exposure on ACS admissions was statistically significant, with a relative risk of 2.04 (95% CI 1.06 to 4.16). The cumulative effect of cold temperature on ACS admissions was found to be non-significant. The highest risk of ACS admission in women was in 38°C (RR, 2.03, 95%  CI 1.04 to 4.18). The effect of hot temperature on ACS admission occurred immediately (lag 0) (RR, 1.09, 95%  CI 1.001 to 1.19).

Conclusions

The high apparent temperature is correlated with a higher ACS admission especially on the same day. These findings may have implications for developing intervention strategies to reduce and prevent temperature-related morbidity especially in the elderly.

Ambient particulate matter air pollution associated with acute respiratory distress syndrome in Guangzhou, China

Limited evidence exists concerning the impact of particulate pollution on acute respiratory distress syndrome (ARDS). We examined the effects of particulate pollution on emergency ambulance dispatches (EAD) for ARDS in Guangzhou, China. Daily air pollution concentrations for PM₁₀, PM_2.5, and PM₁, as well as PM_2.5 chemical compositions, were available from a central air monitoring station. The association between incident ARDS and air pollution on the concurrent and previous 5 days was estimated by an over-dispersed Poisson generalized additive model controlling for meteorological factors, temporal trends, public holidays and day of the week. We identified a total of 17,002 EADs for ARDS during the study period. There were significant associations between concentrations of PM₁₀, PM_2.5, PM_1, and ARDS; corresponding excess risk (ER) for an interquartile range IQR increase in 1-day lagged concentration was 5.45% [95% confidence interval (CI): 1.70%, 9.33%] for PM₁₀ (45.4 μg/m³), 4.71% (95% CI: 1.09%, 8.46%) for PM_2.5 (31.5 μg/m³), and 4.45% (95% CI: 0.81%, 8.23%) for PM₁ (28.8 μg/m³), respectively. For PM_2.5 chemical compositions, we found that OC, EC, sulfate and ammonium were significantly associated with ARDS. The observed effects remained even after adjusting for potentially confounding factors. This study suggests that PM₁₀, PM_2.5, and PM₁, as well as chemical constituents from combustion and secondary aerosols might be important triggers of ARDS in Guangzhou.

Relationship of Meteorological and Air Pollution Parameters with Pneumonia in Elderly Patients

Background and Purpose

In this study, we aimed to evaluate the relationship between pneumonia and meteorological parameters (temperature, humidity, precipitation, airborne particles, sulfur dioxide (SO₂), carbon monoxide (CO), nitrogen dioxide (NO₂), nitrite oxide (NO), and nitric oxide (NOX)) in patients with the diagnosis of pneumonia in the emergency department.

Methods

Our study was performed retrospectively with patients over 65 years of age who were diagnosed with pneumonia. The meteorological variables in the days of diagnosing pneumonia were compared with the meteorological variables in the days without diagnosis of pneumonia. The sociodemographic characteristics, complete blood count of the patients, and meteorological parameters (temperature, humidity, precipitation, airborne particles, SO2, CO, NO2, NO, and NOX) were investigated.

Results

When the temperature was high and low, the number of days consulted due to pneumonia was related to low air temperature (p < 0.05). During the periods when PM 10, NO, NO2, NOX, and CO levels were high, the number of days referred for pneumonia was increased (p < 0.05).

Conclusion

As a result, climatic (temperature, humidity, pressure levels, rain, etc.) and environmental factors (airborne particles, CO, NO, and NOX) were found to be effective in the number of patients admitted to the hospital due to pneumonia.

Modeling the impacts of ambient temperatures on cardiovascular mortality in Yinchuan: evidence from a northwestern city of China

No evidence is available on whether cardiovascular mortality is affected by the ambient temperatures in Yinchuan, which is located in the northwestern region of China, with a typical continental semi-humid semi-arid climate. Daily data on cardiovascular mortality and meteorological factors was collected from Yinchuan city for the period of 2010-2015. A distributed lag non-linear model with quasi-Poisson link was used to assess the association between daily temperatures and cardiovascular deaths, after controlling for seasonality, day of the week, atmospheric pressure, humidity, sunshine duration, and wind speed. The relationship between ambient temperature and cardiovascular mortality was non-linear, with a U-shaped exposure-response curve. For all cardiovascular mortality, the effects of high temperatures appeared at lag 2-5 days, with the largest hot effect at lag 3 day (RR 1.082, 95% CI 1.021-1.146), while the effects of cold temperatures were insignificant. Both cold and high temperatures have more serious influence on the elderly (age ≥ 65) and males than the youth and females, respectively. The study has shown that both cold and high temperatures affect cardiovascular mortality. The findings may be helpful to identify the susceptible subgroups of cardiovascular mortality induced by temperatures, and to provide useful information for establishing public health programs that would better protect local population health from ambient temperatures.

Application of spatial synoptic classification in evaluating links between heat stress and cardiovascular mortality and morbidity in Prague, Czech Republic

Spatial synoptic classification (SSC) is here first employed in assessing heat-related mortality and morbidity in Central Europe. It is applied for examining links between weather patterns and cardiovascular (CVD) mortality and morbidity in an extended summer season (16 May-15 September) during 1994-2009. As in previous studies, two SSC air masses (AMs)-dry tropical (DT) and moist tropical (MT)-are associated with significant excess CVD mortality in Prague, while effects on CVD hospital admissions are small and insignificant. Excess mortality for ischaemic heart diseases is more strongly associated with DT, while MT has adverse effect especially on cerebrovascular mortality. Links between the oppressive AMs and excess mortality relate also to conditions on previous days, as DT and MT occur in typical sequences. The highest CVD mortality deviations are found 1 day after a hot spell's onset, when temperature as well as frequency of the oppressive AMs are highest. Following this peak is typically DT- to MT-like weather transition, characterized by decrease in temperature and increase in humidity. The transition between upward (DT) and downward (MT) phases is associated with the largest excess CVD mortality, and the change contributes to the increased and more lagged effects on cerebrovascular mortality. The study highlights the importance of critically evaluating SSC's applicability and benefits within warning systems relative to other synoptic and epidemiological approaches. Only a subset of days with the oppressive AMs is associated with excess mortality, and regression models accounting for possible meteorological and other factors explain little of the mortality variance.

The effects of hot nights on mortality in Barcelona, Spain

Heat-related effects on mortality have been widely analyzed using maximum and minimum temperatures as exposure variables. Nevertheless, the main focus is usually on the former with the minimum temperature being limited in use as far as human health effects are concerned. Therefore, new thermal indices were used in this research to describe the duration of night hours with air temperatures higher than the 95% percentile of the minimum temperature (hot night hours) and intensity as the summation of these air temperatures in degrees (hot night degrees). An exposure-response relationship between mortality due to natural, respiratory, and cardiovascular causes and summer night temperatures was assessed using data from the Barcelona region between 2003 and 2013. The non-linear relationship between the exposure and response variables was modeled using a distributed lag non-linear model. The estimated associations for both exposure variables and mortality shows a relationship with high and medium values that persist significantly up to a lag of 1-2 days. In mortality due to natural causes, an increase of 1.1% per 10% (CI95% 0.6-1.5) for hot night hours and 5.8% per each 10° (CI95% 3.5-8.2%) for hot night degrees is observed. The effects of hot night hours reach their maximum with 100% and lead to an increase by 9.2% (CI95% 5.3-13.1%). The hourly description of night heat effects reduced to a single indicator in duration and intensity is a new approach and shows a different perspective and significant heat-related effects on human health.

Characterizing prolonged heat effects on mortality in a sub-tropical high-density city, Hong Kong

Extreme hot weather events are likely to increase under future climate change, and it is exacerbated in urban areas due to the complex urban settings. It causes excess mortality due to prolonged exposure to such extreme heat. However, there is lack of universal definition of prolonged heat or heat wave, which leads to inadequacies of associated risk preparedness. Previous studies focused on estimating temperature-mortality relationship based on temperature thresholds for assessing heat-related health risks but only several studies investigated the association between types of prolonged heat and excess mortality. However, most studies focused on one or a few isolated heat waves, which cannot demonstrate typical scenarios that population has experienced. In addition, there are limited studies on the difference between daytime and nighttime temperature, resulting in insufficiency to conclude the effect of prolonged heat. In sub-tropical high-density cities where prolonged heat is common in summer, it is important to obtain a comprehensive understanding of prolonged heat for a complete assessment of heat-related health risks. In this study, six types of prolonged heat were examined by using a time-stratified analysis. We found that more consecutive hot nights contribute to higher mortality risk while the number of consecutive hot days does not have significant association with excess mortality. For a day after five consecutive hot nights, there were 7.99% [7.64%, 8.35%], 7.74% [6.93%, 8.55%], and 8.14% [7.38%, 8.88%] increases in all-cause, cardiovascular, and respiratory mortality, respectively. Non-consecutive hot days or nights are also found to contribute to short-term mortality risk. For a 7-day-period with at least five non-consecutive hot days and nights, there was 15.61% [14.52%, 16.70%] increase in all-cause mortality at lag 0-1, but only -2.00% [-2.83%, -1.17%] at lag 2-3. Differences in the temperature-mortality relationship caused by hot days and hot nights imply the need to categorize prolonged heat for public health surveillance. Findings also contribute to potential improvement to existing heat-health warning system.

Effect modification of the association between temperature variability and daily cardiovascular mortality by air pollutants in three Chinese cities

There is limited evidence showing the mortality effects of temperature variability (TV) on cardiovascular diseases. The joint effects between TV and air pollutants are also less well-established. This study aims to assess the effect modification of TV-cardiovascular mortality by air pollutants in three Chinese cities (Beijing, Nanjing and Chengdu). Data of daily mortality, air pollutants and meteorological factors from 2008 to 2011 was collected from each city. TV was calculated as the standard deviation of daily maximum and minimum temperatures over exposure days. The city-specific effect estimates of TV on cardiovascular mortality were calculated using a quasi-Poisson regression model, adjusting for potential confounders (e.g., seasonality and temperature). An interaction term of TV and a three-level air pollutants stratum indicator was included in the models. Effect modifications by air pollutants were assessed by comparing the estimates of TV's effect between pollutant stratums and calculating the corresponding 95% confidential interval of the differences. Multivariate meta-analysis was conducted to obtain the pooled estimates. The data showed that TV was associated with increased risk of cardiovascular mortality, especially for longer TV exposure days (0-8 days, TV08). This association was still observed after adjusting for air pollutants on current day or the previous two days. Stronger estimates were observed in females, but no significant difference between males and females was detected, indicating the absence of evidence of effect modification by gender. Estimates of TV-cardiovascular mortality varied across two season periods (warm and cool season) and age groups, but the evidence of effect modification by age and seasons was absent. Regarding the effect modification of TV-cardiovascular mortality association by air pollutants, a significant effect modification was identified for PM_10, but not for NO₂ and SO₂ in the whole population for all TV exposure days. This finding also persisted in subgroups, specifically in females and the elderly.

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).

Seasonal association between ambient ozone and mortality in Zhengzhou, China

Different seasonal health effects of ambient ozone (O₃) have been reported in previous studies. This might be due to inappropriate adjustment of temperature in different seasons. We used daily data on non-accidental mortality and ambient air pollution in Zhengzhou from January 19, 2013 to June 30, 2015. Season-stratified analyses using generalized additive models were conducted to evaluate the seasonal associations with adjustment of temperature with different lagged days (lag0-1 for warm season, lag0-14 for cold season). We recorded a total of 70,443 non-accidental deaths in Zhengzhou during the study period. Significant associations were observed between ambient O₃ and mortality in cold season. Every 10-μg/m³ increment of 24-h O₃ of 1-day lagged time was associated with a 1.38% (95% CI 0.60, 2.16%) increase in all cause mortality, 1.35% (95% CI 0.41, 2.30%) increase in cardiovascular mortality, and 1.78% (95% CI 0.43, 3.14%) increase in respiratory mortality. Similar associations were observed when using daily 1- and 8-h maximum concentrations of O₃. No significant association was found during warm season. This study suggests a more pronounced ozone-mortality association in cold season in Zhengzhou, and we suggest that different lagged temperatures should be considered when examining the seasonal health effects of ambient ozone.

Association between acute gouty arthritis and meteorological factors: An ecological study using a systematic review and meta-analysis

OBJECTIVES

The aims of this study were as follows: (1) to analyze the literature systematically regarding the seasonal and monthly variation of the occurrence of episodes of acute gouty arthritis, and (2) to investigate the relationship between the occurrence of episodes of acute gouty arthritis and meteorological parameters.

METHODS

The present authors systematically reviewed databases for articles published before November 2015. Studies with quantitative data on episodes of acute gouty arthritis by months and/or seasons were included. Meteorological data such as the highest temperature, lowest temperature, diurnal temperature range, change in mean temperature between neighboring days, relative humidity and wind speed for the geographic place(s), and study period where and when each study took place were obtained from meteorological websites.

RESULTS

Ten studies published between 1920 and 2015 were included. A meta-analysis by season showed that acute gouty arthritis occurred significantly more frequently in spring than in other seasons. Analysis by month showed an increase in episodes of acute gouty arthritis from March to July, being the highest in July. The trend reversed, and episodes of acute gouty arthritis started decreasing from July to September, being the lowest in September. The change in mean temperature between neighboring days was the only meteorological parameter that was significantly correlated with the number of monthly episodes of acute gouty arthritis.

CONCLUSIONS

Acute gouty arthritis seems to develop more frequently during the period in which the temperature increases significantly between neighboring days: spring by season and between March and July by month in the northern hemisphere.

Impacts of temperature change on ambulance dispatches and seasonal effect modification

Ambulance dispatch is a proxy of acute health outcomes, and growing epidemiological evidence documented its relation to extreme temperature events. Research, however, on short-term temperature change and ambulance dispatches is scarce. We aimed to investigate the effect of short-term temperature change on ambulance dispatches and potential modification by season. Daily data on ambulance dispatch and weather factors were collected in Huainan, a Chinese inland city from December 2011 through December 2013. A Poison generalized linear regression model combined with distributed lag nonlinear model was constructed to examine the association of temperature change between neighboring days (TCN) with ambulance dispatches. The effect modification by season was also examined. There were 48,700 ambulance attendances during the study period. A statistically significant association of TCN with ambulance dispatches was observed. Temperature rise between neighboring days (TCN > 0) was associated with elevated adverse risk of ambulance dispatches, and the effects appeared to be acute (lag0, on the current day) and could last for at least a week, while temperature drop between neighboring days (TCN < 0) had a protective effect. For a 1 °C increase of TCN at lag0 and lag06 (on the 7-day moving average), the risk of ambulance dispatches increased by 2 % (95 % CI 1-3 %) and 7 (95 % CI 1-13 %), respectively. Extreme TCN increase (95th percentile, 3.3 °C vs. 0 °C) at lag0 and lag05 was accompanied by 6 (95 % CI 3-8 %) and 27 % (95 % CI 12-44 %) increase in ambulance dispatches. Ambulance dispatches were more vulnerable to extremely great temperature rise in summer and autumn. TCN was adopted for the first time to quantify the impact of short-term temperature change on ambulance dispatches. Temperature drop between neighboring days (TCN < 0) had a protective effect on ambulance dispatches, while temperature rise between neighboring days (TCN > 0) could acutely trigger the increase in ambulance dispatches, and TCN effect differs by season.

Temperature Variability and Mortality: A Multi-Country Study

BACKGROUND

The evidence and method are limited for the associations between mortality and temperature variability (TV) within or between days.

OBJECTIVES

We developed a novel method to calculate TV and investigated TV-mortality associations using a large multicountry data set.

METHODS

We collected daily data for temperature and mortality from 372 locations in 12 countries/regions (Australia, Brazil, Canada, China, Japan, Moldova, South Korea, Spain, Taiwan, Thailand, the United Kingdom, and the United States). We calculated TV from the standard deviation of the minimum and maximum temperatures during the exposure days. Two-stage analyses were used to assess the relationship between TV and mortality. In the first stage, a Poisson regression model allowing over-dispersion was used to estimate the community-specific TV-mortality relationship, after controlling for potential confounders. In the second stage, a meta-analysis was used to pool the effect estimates within each country.

RESULTS

There was a significant association between TV and mortality in all countries, even after controlling for the effects of daily mean temperature. In stratified analyses, TV was still significantly associated with mortality in cold, hot, and moderate seasons. Mortality risks related to TV were higher in hot areas than in cold areas when using short TV exposures (0-1 days), whereas TV-related mortality risks were higher in moderate areas than in cold and hot areas when using longer TV exposures (0-7 days).

CONCLUSIONS

The results indicate that more attention should be paid to unstable weather conditions in order to protect health. These findings may have implications for developing public health policies to manage health risks of climate change.

CITATION

Guo Y, Gasparrini A, Armstrong BG, Tawatsupa B, Tobias A, Lavigne E, Coelho MS, Pan X, Kim H, Hashizume M, Honda Y, Guo YL, Wu CF, Zanobetti A, Schwartz JD, Bell ML, Overcenco A, Punnasiri K, Li S, Tian L, Saldiva P, Williams G, Tong S. 2016. Temperature variability and mortality: a multi-country study. Environ Health Perspect 124:1554-1559; http://dx.doi.org/10.1289/EHP149.

Is standard deviation of daily PM2.5 concentration associated with respiratory mortality?

Studies on health effects of air pollution often use daily mean concentration to estimate exposure while ignoring daily variations. This study examined the health effects of daily variation of PM2.5. We calculated daily mean and standard deviations of PM2.5 in Hong Kong between 1998 and 2011. We used a generalized additive model to estimate the association between respiratory mortality and daily mean and variation of PM2.5, as well as their interaction. We controlled for potential confounders, including temporal trends, day of the week, meteorological factors, and gaseous air pollutants. Both daily mean and standard deviation of PM2.5 were significantly associated with mortalities from overall respiratory diseases and pneumonia. Each 10 μg/m(3) increment in daily mean concentration at lag 2 day was associated with a 0.61% (95% CI: 0.19%, 1.03%) increase in overall respiratory mortality and a 0.67% (95% CI: 0.14%, 1.21%) increase in pneumonia mortality. And a 10 μg/m(3) increase in standard deviation at lag 1 day corresponded to a 1.40% (95% CI: 0.35%, 2.46%) increase in overall respiratory mortality, and a 1.80% (95% CI: 0.46%, 3.16%) increase in pneumonia mortality. We also observed a positive but non-significant synergistic interaction between daily mean and variation on respiratory mortality and pneumonia mortality. However, we did not find any significant association with mortality from chronic obstructive pulmonary diseases. Our study suggests that, besides mean concentration, the standard deviation of PM2.5 might be one potential predictor of respiratory mortality in Hong Kong, and should be considered when assessing the respiratory effects of PM2.5.

Impact of temperature variation between adjacent days on childhood hand, foot and mouth disease during April and July in urban and rural Hefei, China

Previous studies have found that both high temperature and low temperature increase the risk of childhood hand, foot and mouth disease (HFMD). However, little is known about whether temperature variation between neighboring days has any effects on childhood HFMD. A Poisson generalized linear regression model, combined with a distributed lag non-linear model, was applied to examine the relationship between temperature change and childhood HFMD in Hefei, China, from 1st January 2010 to 31st December 2012. Temperature change was defined as the difference of current day's mean temperature and previous day's mean temperature. Late spring and early summer (April-July) were chosen as the main study period due to it having the highest childhood HFMD incidence. There was a statistical association between temperature change between neighboring days and childhood HFMD. The effects of temperature change on childhood HFMD increased below a temperature change of 0 °C (temperature drop). The temperature change has the greatest adverse effect on childhood HFMD at 7 days lag, with 4 % (95 % confidence interval 2-7 %) increase per 3 °C drop of temperature. Male children and urban children appeared to be more vulnerable to the effects of temperature change. Temperature change between adjacent days might be an alternative temperature indictor for exploring the temperature-HFMD relationship.

Effects of temperature variation between neighbouring days on daily hospital visits for childhood asthma: a time-series analysis

OBJECTIVES

To identify the relationship between temperature variation between neighbouring days (TVN) and hospital visits for childhood asthma in age- and sex-specific groups.

STUDY DESIGN

An ecological design was used to explore the effect of TVN on hospital visits for childhood asthma.

METHODS

A Poisson generalised linear regression model combined with a distributed lag non-linear model was used to analyse the association between TVN and hospital visits for childhood asthma. All hospital visits for childhood asthma from June 2010 to July 2013 were included (n = 17,022). Daily climate data were obtained from Hefei Meteorological Bureau.

RESULTS

A significant correlation was found between TVN and hospital visits for childhood asthma in age- and sex-specific groups. For different gender groups, the effect of TVN on childhood asthma was the greatest at 3 and 5 days lag for males and females. For different age groups, the effect of TVN on childhood asthma was the greatest at 1 and 5 days lag for 0-4 years and 5-14 years children, respectively. A 1 °C increase in TVN was associated with a 4.2% (95% confidence interval 0.9-7.6%) increase in hospital visits for childhood asthma.

CONCLUSIONS

TVN is associated with hospital visits for childhood asthma. Once the temperature change rapidly, guardians will be urged to pay more attention to their children's health, which may reduce the morbidity of childhood asthma.