Dataset Information

Effect of temperature on accidental human mortality: A time-series analysis in Shenzhen, Guangdong Province in China.

ABSTRACT: Health-risk assessments of temperature are central to determine total non-accidental human mortality; however, few studies have investigated the effect of temperature on accidental human mortality. We performed a time-series study combined with a distributed lag non-linear model (DLNM) to quantify the non-linear and delayed effects of daily mean temperature on accidental human mortality between 2013 and 2017 in Shenzhen, China. The threshold for effects of temperature on accidental human mortality occurred between 5.6?°C and 18.5?°C. Cold exposures, but not hot exposures, were significantly associated with accidental human mortality. All of the observed groups were susceptible to cold effects, with the strongest effects presented in females (relative risk [RR]: 3.14, 95% confidence interval (CI) [1.44-6.84]), followed by poorly educated people (RR: 2.63, 95% CI [1.59-4.36]), males (RR: 1.79, 95% CI [1.10-2.92]), and well-educated people (RR: 1.20, 95% CI [0.58-2.51]). Pooled estimates for cold effects at a lag of 0-21 days (d) were also stronger than hot effects at a lag of 0-2 d. Our results indicate that low temperatures increased the risk of accidental human mortality. Females and poorly educated people were more susceptible to the low temperatures. These findings imply that interventions which target vulnerable populations during cold days should be developed to reduce accidental human mortality risk.

SUBMITTER: Lian T

PROVIDER: S-EPMC7242478 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Effect of temperature on accidental human mortality: A time-series analysis in Shenzhen, Guangdong Province in China.

Lian Tingyu T Fu Yingbin Y Sun Mingwei M Yin Mingjuan M Zhang Yan Y Huang Lingfeng L Huang Jingxiao J Xu Ziqian Z Mao Chen C Ni Jindong J Liu Gang G

Scientific reports 20200521 1

Health-risk assessments of temperature are central to determine total non-accidental human mortality; however, few studies have investigated the effect of temperature on accidental human mortality. We performed a time-series study combined with a distributed lag non-linear model (DLNM) to quantify the non-linear and delayed effects of daily mean temperature on accidental human mortality between 2013 and 2017 in Shenzhen, China. The threshold for effects of temperature on accidental human mortali ...[more]

PMID: 32439880

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Project description: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.

Project description:ObjectiveTo examine the total non-accidental mortality burden attributable to ambient temperatures and assess the effect modification of the burden by specific causes of death and individual characteristics in a high plateau area in southwest China.MethodsUsing daily mortality and meteorological data from 2009 to 2016, we applied a quasi-Poisson model combined with a distributed lag non-linear model to estimate the temperature-mortality association with the assessment of attributable fraction and number. We calculated attributable fractions and deaths with 95% empirical CIs (eCIs), that were due to cold and heat, defined as temperatures below and above the median temperature, and for mild and extreme temperatures, defined by cut-offs at the 2.5th and 97.5th temperature percentiles.ResultsWe analysed 89 467 non-accidental deaths; 4131 were attributable to overall temperatures, with an attributable fraction of 4.75% (95% eCI 2.33% to 6.79%). Most of the mortality burden was caused by cold (4.08%; 0.86% to 7.12%), whereas the burden due to heat was low and non-significant (0.67%; -2.44% to 3.64%). Extreme cold (1.17%; 0.58% to 1.69%) was responsible for 24.6% (ie, 1.17% divided by 4.75%) of the total death burden. In the stratification analyses, attributable risk due to cold was higher for cardiovascular than respiratory disease (6.18% vs 3.50%). We found a trend of risk of increased death due to ambient temperatures with increasing age, with attributable fractions of 1.83%, 2.27% and 6.87% for age ≤64, 65-74 and ≥75 years old, respectively. The cold-related burden was slightly greater for females, farmers, ethnic minorities and non-married individuals than their corresponding categories.ConclusionsMost of the burden of death was attributable to cold, and specific causes and individual characteristics might modify the mortality burden attributable to ambient temperatures. The results may help make preventive measures to confront climate change for susceptible population in this region.

Dataset Information

Effect of temperature on accidental human mortality: A time-series analysis in Shenzhen, Guangdong Province in China.

Publications

Effect of temperature on accidental human mortality: A time-series analysis in Shenzhen, Guangdong Province in China.

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