Comparison of life loss per death attributable to ambient temperature among various development regions: a nationwide study in 364 locations in China

Associations of ambient temperature with the CO poisoning risk in China

Although studies have explored the relationship between temperature and CO poisoning, the results are not consistent, and there is still a lack of early warning criteria of temperature related to CO poisoning. In order to comprehensively study the exposure-response relationship between daily average temperature and CO poisoning, and to further explore the early warning criteria of temperature related to CO poisoning, we used daily cases of CO poisoning in 31 National Injury Surveillance System (NISS) surveillance sites in seven administrative geographical regions of China and daily meteorological data obtained from the China Meteorological Science Data Sharing Service Platform from 2009 to 2019 to do the analysis. Daily meteorological data of 698 weather stations across China were interpolated at a 0.01° × 0.01°spatial resolution, which were then applied to extract the daily meteorological data of all included NISS sites. The Distributed Lag Non-linear Model (DLNM) model was applied to estimate the exposure-response associations (relative risk, RR) of daily mean temperature with CO poisoning, which was then further used to identify early warning criteria of temperature related to CO poisoning. A total of 10,618 CO poisoning cases were included in this study, with an average of 0.4 cases per day. There was generally a reverse J-shaped association between temperature and CO poisoning risk, indicating that both low and high temperature may increase the risk of CO poisoning, but low temperature usually has a longer lagged effects than high temperature. Spatialy, the exposure-response associations between temperatue and CO poisoning largely varied among regions, with greater effects of low temperatures in Southern China than in Northern China. The cumulative effects (RR, lag0-6 days) of 10 % percentile temperature ranged from 1.13 (95%CI: 1.01,1.26) in East China to 1.73 (95%CI:1.63,1.83) in South China. We also observed significant spatial variations in the early warning criteria of temperature related to CO poisoning across China. However, the patterns of high temperature effects on CO poisoning and the warning criteria of high temperature were mixed across China. In conclusions, both low temperature and high temperature may increase the risk of CO poisoning in China, and the effect of low temperature is more obvious, especially in South China, Northeast China, and North China. In addition, there is an urgent need to establish air temperature early warning and grading criteria for CO poisoning in different areas of China.

The comparison of mortality burden between exposure to dry-cold events and wet-cold events: A nationwide study in China

BACKGROUND

Most previous studies have focused on the health effect of temperature or humidity, and few studies have explored the combined health effects of exposure to temperature and humidity. This study aims to estimate the relationship between humidity-cold events and mortality, and then to compare the mortality burden between exposure to dry-cold events and wet-cold events, and finally to explore whether there was an additive interaction of temperature and humidity on mortality.

METHODS

In the study, Daily mortality data during 2006-2017 were collected from Centers for Disease Control and Prevention in China, and daily mean temperature and daily mean relative humidity data from 698 weather stations in China were obtained from the China Meteorological Data Sharing Service system. We first employed time-series design with a distributed lag nonlinear model and a multivariate meta-analysis model to examine the association between humidity-cold events with mortality.

RESULTS

We found that humidity-cold events significantly increased mortality risk, and the effect of wet-cold events (RR:1.24, 95%CI:1.20,1.29) was higher than that of dry-cold events (RR:1.14, 95%CI:1.10,1.18). Dry-cold events and wet-cold events accounted for 2.41 % and 2.99 % excess deaths, respectively with higher burden for the elderly ≥85 years old, Central China and CVD. In addition, there is a synergistic additive interaction between low temperature and high humidity in winter.

CONCLUSION

This study showed that humidity-cold events significantly increased mortality risk, and the effect of wet-cold events was higher than that of dry-cold events.

Heat exposure and hospitalizations for chronic kidney disease in China: a nationwide time series study in 261 major Chinese cities

BACKGROUND

Climate change profoundly shapes the population health at the global scale. However, there was still insufficient and inconsistent evidence for the association between heat exposure and chronic kidney disease (CKD).

METHODS

In the present study, we studied the association of heat exposure with hospitalizations for cause-specific CKD using a national inpatient database in China during the study period of hot season from 2015 to 2018. Standard time-series regression models and random-effects meta-analysis were developed to estimate the city-specific and national averaged associations at a 7 lag-day span, respectively.

RESULTS

A total of 768,129 hospitalizations for CKD was recorded during the study period. The results showed that higher temperature was associated with elevated risk of hospitalizations for CKD, especially in sub-tropical cities. With a 1 °C increase in daily mean temperature, the cumulative relative risks (RR) over lag 0-7 d were 1.008 [95% confidence interval (CI) 1.003-1.012] for nationwide. The attributable fraction of CKD hospitalizations due to high temperatures was 5.50%. Stronger associations were observed among younger patients and those with obstructive nephropathy. Our study also found that exposure to heatwaves was associated with added risk of hospitalizations for CKD compared to non-heatwave days (RR = 1.116, 95% CI 1.069-1.166) above the effect of daily mean temperature.

CONCLUSIONS

Short-term heat exposure may increase the risk of hospitalization for CKD. Our findings provide insights into the health effects of climate change and suggest the necessity of guided protection strategies against the adverse effects of high temperatures.

Effect of Meteorological Factors and Air Pollutants on Daily Hospital Admissions for Ischemic Heart Disease in Lanzhou, China

INTRODUCTION

Meteorological factors and air pollutants are believed to be associated with cardiovascular disease. Ischemic heart disease (IHD) is a major public health issue worldwide. Few studies have investigated the associations among meteorological factors, air pollutants, and IHD daily hospital admissions in Lanzhou, China.

METHODS

We conducted a distributed lag nonlinear model on the basis of 5-year data, aiming at disentangling the impact of meteorological factors and air pollutants on IHD hospital admissions. All IHD daily hospital admissions recorded from January 1, 2015, and December 31, 2019, were obtained from three hospitals in Lanzhou, China. Daily air pollutant concentrations and meteorological data were synchronously collected from Gansu Meteorological Administration and Lanzhou Environmental Protection Administration. Stratified analyses were performed by sex and two age groups.

RESULTS

A total of 23,555 IHD hospital admissions were recorded, of which 10,477 admissions were for coronary artery disease (CAD) and 13,078 admissions were for acute coronary syndrome. Our results showed that there was a nonlinear (J-shaped) relationship between temperature and IHD hospital admissions. The number of IHD hospital admissions was positively correlated with NO2, O3, humidity, and pressure, indicating an increased risk of hospital admissions for IHD under NO2, O3, humidity, and pressure exposure. Meanwhile, both extremely low (-12°C) and high (30°C) temperatures reduced IHD hospital admissions, but the harmful effect increased with the lag time in Lanzhou, China, while the cold effect was more pronounced and long-lasting than the heat effect. Subgroup analysis demonstrated that the risk on CAD hospital admissions increased significantly in females and <65 years of age at -12°C.

CONCLUSION

Our findings added to the growing evidence regarding the potential impact of meteorological factors and air pollutants on policymaking from the perspective of hospital management efficiency.

The association of ambient temperature variability with blood pressure in southern China

OBJECTIVES

Numerous studies have shown a positive relationship between temperature variability and mortality, but few studies have investigated the effect of temperature variability on blood pressure (BP). We aimed to estimate the effect of temperature variability on BP in Guangdong Province, southern China.

METHODS

Data on meteorological factors were obtained from the Guangdong Meteorological Center, and BP was collected from a series of cross-sectional surveys conducted in Guangdong Province, China, from 2004 to 2015. There were 38 088 participants aged 18 years and over. A generalized additive model was used to estimate the association between temperature variability and BP after adjusting for confounding variables.

RESULTS

Our study found a significant positive association between temperature variability and SBP, and this effect increased with the increment of exposure days in total population. The highest estimate was for temperature variability at 7 days lag (TV 0-7 ) with a 0.497 (95% confidence interval, 0.335-0.660) mmHg rise of SBP for each 1°C increase of TV 0-7 . The effects of TV 0-1 and TV 0-2 on SBP were higher for hypertensives than that for normotensives, and in warm season higher than that in cold season. However, we did not observe statistical significance between temperature variability and DBP.

CONCLUSIONS

There was a positive association between temperature variability and SBP in Guangdong Province, which should be considered in clinical management and epidemiological survey of hypertension.

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.

Burden of diabetes and kidney disease attributable to non-optimal temperature from 1990 to 2019: A systematic analysis from the Global Burden of Disease Study 2019

INTRODUCTION

This study quantitatively described the disease burden of diabetes and kidney disease attributable to non-optimal temperatures and explored the influencing factors.

METHODS

We quantitatively described the mortality burden of diabetes and kidney disease attributable to non-optimal temperatures in six countries (China, USA, South Africa, Australia, Iraq, Portugal), and compare trends in mortality in six countries from 1990 to 2019. We used the APC model to analyse age, period, and cohort effects on mortality in six countries. We used restricted cubic splines and quantile regression to analyse the association of SDI with mortality and YLL using data from 21 regions in the world.

RESULTS

The mortality rates of diabetes and kidney disease in the six countries in 2019 were 1.72% (Australia), 1.83% (China), 2.99% (USA), 3% (Portugal), 7.45% (South Africa) and 8.71% (Iraq) attributable to non-optimal temperatures. Cold was more harmful than heat. The mortality, YLLs of diabetes and kidney disease of male were higher than females. The mortality rate showed an upwards trend with age. The period effect had little changes or showed a slight upwards trend. The cohort effect showed a downwards trend. The regions with higher mortality or YLLs rates were mainly had SDI values of 0.45-0.80.

CONCLUSIONS

Among the death burdens of diabetes and kidney disease attributed to non-optimal temperatures, cold had a greater burden than heat. The burden of death was affected by sex, age, period, cohort, and SDI.

Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019

BACKGROUND

Non-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019.

METHODS

The global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019.

FINDINGS

We estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level.

INTERPRETATION

A substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China.

FUNDING

National Key Research and Development Program.

Analysis of vulnerability to heat in rural and urban areas in Spain: What factors explain Heat's geographic behavior?

INTRODUCTION

There is currently little knowledge and few published works on the subject of vulnerability to heat in rural environments at the country level. Therefore, the objective of this study was to determine whether rural areas are more vulnerable to extreme heat than urban areas in Spain. This study aimed to analyze whether a pattern of vulnerability depends on contextual, environmental, demographic, economic and housing variables.

METHODS

An ecological, longitudinal and retrospective study was carried out based on time series data between January 01, 2000 and December 31, 2013 in 42 geographic areas in 10 provinces in Spain. We first analyzed the functional relationship between the mortality rate per million inhabitants and maximum daily temperature (Tmax). We then determined the summer temperature threshold (Pthreshold) (June-September) at which increases in mortality are produced that are attributable to heat. In a second phase, based on Pthreshold, a vulnerability variable was calculated, and its distribution was analyzed using mixed linear models from the Poisson family (link = log). In these models, the dependent variable was vulnerability, and the independent variables were exposure to high temperatures, aridity of the climate, deprivation index, percentage of people over age 65, rurality index, percentage of housing built prior to 1980 and condition of dwellings.

RESULTS

Rurality was a protective factor, and vulnerability in urban areas was six times greater. In contrast, risk factors included aridity (RR = 5.89 (2.26 15.36)), living in cool summer zones (2.69 (1.23, 5.91)), poverty (4.05 (1.91 8.59)) and the percentage of dysfunctional housing (1.13 (1.04 1.24)).

CONCLUSIONS

Rural areas are less vulnerable to extreme heat than the urban areas analyzed. Also, population groups with worse working conditions and higher percentages of dwellings in poor conditions are more vulnerable.

Time trends in cardiovascular disease mortality attributable to non-optimal temperatures in China: An age-period-cohort analysis using the Global Burden of Disease Study 2019

Background

Associations between non-optimal temperatures and cardiovascular disease (CVD) mortality risk have been previously reported, yet the trends of CVD mortality attributable to non-optimal temperatures remain unclear in China. We analyzed trends in CVD mortality attributable to non-optimal temperatures and associations with age, period, and birth cohort.

Methods

Data were obtained from the Global Burden of Disease Study (GBD) 2019. Joinpoint regression analysis was used to calculate annual percent change (APC) and average annual percent change (AAPC) from 1990 to 2019. We used the age-period-cohort model to analyze age, period, and cohort effects in CVD mortality attributable to non-optimal temperatures between 1990 and 2019.

Results

The age-standardized mortality rate (ASMR) of CVD attributable to non-optimal temperature generally declined in China from 1990 to 2019, whereas ischemic heart disease (IHD) increased slightly. Low temperatures have a greater death burden than high temperatures, but the death burden from high temperatures showed steady increases. Joinpoint regression analysis showed that CVD mortality decreased in all age groups except for IHD, and the decreases were greater in females than in males. The mortality of CVD attributable to non-optimal temperatures of males was higher than females. The mortality rate showed an upwards trend with age across all CVD categories. Period risks were generally found in unfavorable trends. The cohort effects showed a progressive downward trend during the entire period.

Conclusion

Although there have been reductions in CVD mortality attributable to non-optimum temperatures, the mortality of IHD has increased and the burden from non-optimal temperatures remains high in China. In the context of global climate change, our results call for more attention and strategies to address climate change that protect human health from non-optimal temperatures.

Investigating the cellular responses of osteosarcoma to cisplatin by confocal Raman microspectroscopy

Confocal Raman Microspectroscopy (CRM) was employed to clarify the cellular response of cisplatin in osteosarcoma (OS) cells with different dosages and incubation times. The K7M2 mouse osteosarcoma cells were treated by cisplatin in 0 μM (UT group), 20 μM (20 T group), and 40 μM (40 T group) doses for 24-h (24H group) and 48-h (48H group), respectively. Raman spectroscopy was utilized to analyze the drug induced variations of intracellular biochemical components in osteosarcoma cells. The spectral results shows that the main changes in its biochemical composition come from nucleic acids. By adopting three different kernel functions (linear, polynomial, and Gaussian radial basis function (RBF)), principal component analysis combined with support vector machine models (PCA-SVM) was built to address the spectral variations among all investigated groups. Meanwhile, multivariate curve resolution alternating least squares (MCR-ALS) was further utilized to discuss on the chemical interpretation on the acquired spectral results. Moreover, Raman spectral images, which is reconstructed by K-means cluster analysis (KCA) with point-scanned hyperspectral dataset, was applied to illustrate the drug induced compositional and morphological variations in each subcellular region. The achieved results not only prove the application potential of Raman based analytical technique in non-labeled intracellular studies, but also illustrate the detailed compositional and structural information of cisplatin induced OS cell responses from the perspective of multivariate analysis and imaging of Raman spectroscopy.

Age-specific disparity in life loss per death attributable to ambient temperature: A nationwide time-series study in China

Age-specific discrepancy of mortality burden attributed to temperature, measured as years of life lost (YLL), has been rarely investigated. We investigated age-specific temperature-YLL rates (per 100,000) relationships and quantified YLL per death caused by non-optimal temperature in China. We collected daily meteorological data, population data and daily death counts from 364 locations in China during 2006-2017. YLL was divided into three age groups (0-64 years, 65-74 years, and ≥75 years). A distributed lag non-linear model was first employed to estimate the associations of temperature with age-specific YLL rates in each location. Then we pooled the associations using a multivariate meta-analysis. Finally, we calculated age-specific average YLL per death caused by temperature by cause of death and region. We observed greater effects of cold and hot temperature on YLL rates for the elderly compared with the young population by region or cause of death. However, YLL per death due to non-optimal temperature for different regions or causes of death decreased with age, with 2.0 (95 % CI:1.5, 2.5), 1.2 (1.1, 1.4) and 1.0 years (0.9, 1.2) life loss per death for populations aged 0-64 years, 65-74 years and over 75 years, respectively. Most life loss per death results from moderate temperature, especially moderate cold for all age groups. The effect of non-optimal temperature on YLL rates is smaller for younger populations than older ones, while the temperature-related life loss per death was more prominent for younger populations.

Low ambient temperature shortened life expectancy in Hong Kong: A time-series analysis of 1.4 million years of life lost from cardiorespiratory diseases

Ambient temperature is an important contributor to mortality burden worldwide, most of which is from cold exposure. However, little is known about the cold impact on life expectancy loss. This paper aimed to estimate cold-related life expectancy loss from cause-, age-, and gender-specific cardiovascular and respiratory diseases. Daily deaths from cardiovascular and respiratory diseases and weather records were acquired for Hong Kong, China during 2000-2016. Years of life lost (YLL) that considers life expectancy at the time of death was calculated by matching each death by age and sex to annual life tables. Using a generalized additive model that fits temperature-YLL association, we estimated loss of years in life expectancy from cold. Cold was estimated to cause life expectancy loss of 0.9 years in total cardiovascular disease, with more years of loss in males than in females and in people aged 65 years and older than in people aged up to 64 years. Cold-related life expectancy loss in total respiratory diseases was 1.2 years, with more years of loss in females than in males and comparable years of loss in people aged up to 64 years and in people aged 65 years and older. Among cause-specific diseases, we observed the greatest life expectancy loss in pneumonia (1.5 years), followed by ischaemic heart disease (1.2 years), COPD (1.1 years), and stroke (0.3 years). Between two periods of 2000-2007 and 2008-2016, cold-related life expectancy loss due to cardiovascular disease did not decrease and cold-related life expectancy loss due to respiratory disease even increased by five times. Our findings suggest an urgent need to develop prevention measures against adverse cold effects on cardiorespiratory disease in Hong Kong.

Analysis of the impact of heat waves on daily mortality in urban and rural areas in Madrid

The objective of this study was to analyze and compare the effect of high temperatures on daily mortality in the urban and rural populations in Madrid. Data were analyzed from municipalities in Madrid with a population of over 10,000 inhabitants during the period from January 1, 2000 to December 31, 2020. Four groups were generated: Urban Metropolitan Center, Rural Northern Mountains, Rural Center, and Southern Rural. The dependent variable used was the rate of daily mortality due to natural causes per million inhabitants (CIE-X: A00-R99) between the months of June and September for the period. The primary independent variable was maximum daily temperature. Social and demographic "context variables" were included: population >64 years of age (%), deprivation index and housing indicators. The analysis was carried out in three phases: 1) determination of the threshold definition temperature of a heat wave (Tumbral) for each study group; 2) determination of relative risks (RR) attributable to heat for each group using Poisson linear regression (GLM), and 3) calculation of odds ratios (OR) using binomial family GLM for the frequency of the appearance of heat waves associated with context variables. The resulting percentiles (for the series of maximum daily temperatures for the summer months) corresponding to Tthreshold were: 74th percentile for Urban Metropolitan Center, 76th percentile for Southern Rural, 83rd for Rural Northern Mountains and 98th percentile for Center Rural (98). Greater vulnerability was found for the first two. In terms of context variables that explained the appearance of heat waves, deprivation index level, population >64 years of age and living in the metropolitan area were found to be risk factors. Rural and urban areas behaved differently, and socioeconomic inequality and the composition of the population over age 64 were found to best explain the vulnerability of the Rural Center and Southern Rural zones.