The effects of excess degree-hours on mortality in Guangzhou, China

Lin, Qiaoxuan; Lin, Hualiang; Liu, Tao; Lin, Ziqiang; Lawrence, Wayne R.; Zeng, Weilin; Xiao, Jianpeng; Li, Xing; Zhang, Bing; Lin, Shao

doi:10.1016/j.envres.2019.05.041

Cited by 10 publications

(28 citation statements)

References 28 publications

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“…DLNM is a regression model based on cross basis functions to study the exposure response relationship, and at the same time, it also takes into account the lag response of exposure-response factors and the non-linearity of the exposure-response relationship [ 28 ]. Due to its flexibility in use, DLNM has been widely used to study the effects of meteorological and air pollution factors on human health [ 8 , 29 ]. Before constructing DLNM model, Spearman rank correlation was conducted to analyze the correlation degree between daily death from respiratory diseases and meteorological and air pollution variables in Guangzhou, so as to exclude some variables that had no substantial influence on the model relationship (see Table S 1 ).…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, we changed the degree of freedom of natural spline function of meteorological factors and air pollution in the model from 3 to 5 successively in order to control their confounding influence. The degree of freedom of the temporal natural spline function in the model is changed from 6 to 8 successively in order to control the trend of time [ 8 , 34 ]. In the dimension of expose-response maintenance and expose-lag, the location and number of knots fitted by absolute humidity and lag parameters are changed by changing degree of freedom [ 11 ].…”

Section: Methodsmentioning

confidence: 99%

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The role of absolute humidity in respiratory mortality in Guangzhou, a hot and wet city of South China

Chen

Liu

Lin

et al. 2021

Environ Health Prev Med

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Background For the reason that many studies have been inconclusive on the effect of humidity on respiratory disease, we examined the association between absolute humidity and respiratory disease mortality and quantified the mortality burden due to non-optimal absolute humidity in Guangzhou, China. Methods Daily respiratory disease mortality including total 42,440 deaths from 1 February 2013 to 31 December 2018 and meteorological data of the same period in Guangzhou City were collected. The distributed lag non-linear model was used to determine the optimal absolute humidity of death and discuss their non-linear lagged effects. Attributable fraction and population attributable mortality were calculated based on the optimal absolute humidity, defined as the minimum mortality absolute humidity. Results The association between absolute humidity and total respiratory disease mortality showed an M-shaped non-linear curve. In total, 21.57% (95% CI 14.20 ~ 27.75%) of respiratory disease mortality (9154 deaths) was attributable to non-optimum absolute humidity. The attributable fractions due to high absolute humidity were 13.49% (95% CI 9.56 ~ 16.98%), while mortality burden of low absolute humidity were 8.08% (95% CI 0.89 ~ 13.93%), respectively. Extreme dry and moist absolute humidity accounted for total respiratory disease mortality fraction of 0.87% (95% CI − 0.09 ~ 1.58%) and 0.91% (95% CI 0.25 ~ 1.39%), respectively. There was no significant gender and age difference in the burden of attributable risk due to absolute humidity. Conclusions Our study showed that both high and low absolute humidity are responsible for considerable respiratory disease mortality burden, the component attributed to the high absolute humidity effect is greater. Our results may have important implications for the development of public health measures to reduce respiratory disease mortality.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The role of absolute humidity in respiratory mortality in Guangzhou, a hot and wet city of South China

Chen

Liu

Lin

et al. 2021

Environ Health Prev Med

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“…We used a novel index-DEHH (daily excess hourly heat) in this study. DEHH is a cumulative temperature variable generated by adding the temperature values that exceed the speci c heat threshold per hour within a day (Jiao et al 2019;Lin et al 2019). The calculation formula is as follows:…”

Section: De Nition and Calculation Of Hourly Excess Heat Exposure Within A Daymentioning

confidence: 99%

“…Some heat-related assessments usually focus on days when the daily mean temperature is above the temperature threshold, which may not examine the practical effects of heat on disease, as hourly extreme high temperatures of these days can also have an adverse effect (Jiao et al 2019). Thus, many studies suggested that the usage of hourly temperature data to assess the risk of morbidity and mortality is necessary (Lin et al 2019 (Lin et al 2019). Most of previous studies on the relationship between temperature and schizophrenia hospitalizations used daily mean temperature as exposure indicator (Sung et al 2011;Wang et al 2018;Pan et al 2019), which may underestimate the impact of high temperature on schizophrenia.…”

Section: Introductionmentioning

confidence: 99%

“…Most of previous studies on the relationship between temperature and schizophrenia hospitalizations used daily mean temperature as exposure indicator (Sung et al 2011;Wang et al 2018;Pan et al 2019), which may underestimate the impact of high temperature on schizophrenia. Therefore, it is necessary to apply a novel index -daily excess hourly heat (DEHH, similar to △DH HOT ) (Lin et al 2019;Jiao et al 2019) to make full use of the information of hourly temperature to explore the precise effect of accumulated high temperature within a day on hospitalization for schizophrenia.…”

Section: Introductionmentioning

confidence: 99%

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Effects of Accumulated And Transient Heat Exposure On Schizophrenia Hospitalizations: A Time-Series Analysis On Hourly Temperature Basis

Tang

et al. 2021

Preprint

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Background: 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. Methods: 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℃). We calculated and applied a novel indictor–daily excess heat hourly (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. Results: 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 am and 6 am.Conclusions: This study revealed the negative effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our findings need to be further tested in other regions with distinct regional features.

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

Tang

et al. 2021

Environ Sci Pollut Res

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Background: 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 signi cance. 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.Methods: We included the daily mean temperature and daily schizophrenia hospitalizations into the distributed lag nonlinear model (DLNM) to simulate the exposure-response curve and determine the heat threshold (19.4℃). We calculated and applied a novel indictor-daily excess heat hourly (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.Results: Each increment of interquartile range (IQR) in DEHH was associated with elevated risk of schizophrenia hospitalizations from lag 1 (RR=1.036, 95% con dence 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 am and 6 am.Conclusions: This study revealed the negative effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our ndings need to be further tested in other regions with distinct regional features.

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The effects of excess degree-hours on mortality in Guangzhou, China

Cited by 10 publications

References 28 publications

The role of absolute humidity in respiratory mortality in Guangzhou, a hot and wet city of South China

The role of absolute humidity in respiratory mortality in Guangzhou, a hot and wet city of South China

Effects of Accumulated And Transient Heat Exposure On Schizophrenia Hospitalizations: A Time-Series Analysis On Hourly Temperature Basis

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

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