Impact of ambient temperature on hospital admissions for cardiovascular disease in Hefei City, China

Cui, Longjiang; Geng, Xiya; Ding, Tao; Tang, Jing; Xu, Jixiang; Zhai, Jinxia

doi:10.1007/s00484-019-01687-0

Cited by 56 publications

(50 citation statements)

References 68 publications

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“…Among the GAM, two distributions were tested: Poisson and negative binomial, which are widely used distributions in epidemiological studies involving counting data. The latter one distribution have a parameter that corrects the overdispersion of the data, which is expected in this type of study [19,33,50]. It was also considered an extension of the Poisson distribution, called the quasi-Poisson model, including of a dispersion parameter [51].…”

Section: Methodsmentioning

confidence: 99%

Risk assessment of temperature and air pollutants on hospitalizations for mental and behavioral disorders in Curitiba, Brazil

et al. 2020

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Background: Extreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil. Methods: A time series study was carried out to explore the associations between daily air pollutants (SO 2 , NO 2 , O 3 , and PM 10) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM). Results: Significant associations between environmental conditions (10 μg/m 3 increase in air pollutants and temperature°C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009-1.0357) for men, and 1.0407 (95% CI: 1.0230-1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165-1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213-1.1117) for women, and 1.0215 (95% CI: 1.0195-1.0716) for men. Conclusions: This study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure.

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Section: Methodsmentioning

confidence: 99%

Risk assessment of temperature and air pollutants on hospitalizations for mental and behavioral disorders in Curitiba, Brazil

et al. 2020

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“…The health effects of extreme temperature including extreme high temperature and extreme low temperature, as an extreme weather event, are complex and far-reaching. The potential public health impacts of extreme temperature can be significant and multifaceted, such as mortality [4,5], disease of cardiovascular system [6,7] and respiratory diseases [8,9]. And beyond that, extreme temperature has an impact on infectious diseases, such as mumps [10], hand-foot-mouth disease [11], etc.…”

Section: Introductionmentioning

confidence: 99%

The association between extreme temperature and pulmonary tuberculosis in Shandong Province, China, 2005–2016: a mixed method evaluation

Chen¹,

Lu²,

Zhang³

et al. 2021

BMC Infect Dis

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Background The effects of extreme temperature on infectious diseases are complex and far-reaching. There are few studies to access the relationship of pulmonary tuberculosis (PTB) with extreme temperature. The study aimed to identify whether there was association between extreme temperature and the reported morbidity of PTB in Shandong Province, China, from 2005 to 2016. Methods A generalized additive model (GAM) was firstly conducted to evaluate the relationship between daily reported incidence rate of PTB and extreme temperature events in the prefecture-level cities. Then, the effect estimates were pooled using meta-analysis at the provincial level. The fixed-effect model or random-effect model was selected based on the result of heterogeneity test. Results Among the 446,016 PTB reported cases, the majority of reported cases occurred in spring. The higher reported incidence rate areas were located in Liaocheng, Taian, Linyi and Heze. Extreme low temperature had an impact on the reported incidence of PTB in only one prefecture-level city, i.e., Binzhou (RR = 0.903, 95% CI: 0.817–0.999). While, extreme high temperature was found to have a positive effect on reported morbidity of PTB in Binzhou (RR = 0.924, 95% CI: 0.856–0.997) and Weihai (RR = 0.910, 95% CI: 0.843–0.982). Meta-analysis showed that extreme high temperature was associated with a decreased risk of PTB (RR = 0.982, 95% CI: 0.966–0.998). However, extreme low temperature was no relationship with the reported incidence of PTB. Conclusion Our findings are suggested that extreme high temperature has significantly decreased the risk of PTB at the provincial levels. The findings have implications for developing strategies to response to climate change.

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“…3a), and COVID-19 cases, determine a temperature of 20 °C and relative humidity of 60% as reference values. Set the 5th (defined as low), 25th (defined as lower), 75th (defined as higher), and 95th percentile (defined as high) of daily temperature and relative humidity as different groups to study delayed effects of specific temperature and humidity on daily new confirmed COVID-19 cases [23].…”

Section: Discussionmentioning

confidence: 99%

Risk effects of low temperature and high humidity on the spread of COVID-19 in California: Time series study

Fang

Wang

Pan

2020

Preprint

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Background Previous researches inferred that ‘summer’ might weaken COVID-19 transmission. However, with the warming weather coming, the COVID-19 pandemic was still intensifying. Methods This study aimed to investigate the associations between temperature, relative humidity, and COVID-19 cases using the Distributed Lag Non-linear Model (DLNM) from Jan 27th to July 15th, 2020, in California, US. Results It showed that as of July 15, 2020, there were 355 285 reported cases in California, where the temperature was between 6.33 °C and 30.72 °C and the relative humidity was between 23% and 100%. Temperature from 6.33 °C to 9 °C, relative humidity from 80–98% were the risky factors of COVID-19 transmission. It increased the risk of 95.4% at 6.33 °C (RR:1.954; CI: 1.032–3.701). It increased the risk of 70.3% when the humidity was 98% (RR: 1.703, CI: 1.049–2.765). When the temperature > 9 °C and the relative humidity < 80%, there was no statistical association. Conclusions This suggested that in winter with low temperature and high humidity, the spread of the COVID-19 would be severe due to weather factors. However, temperature and humidity were not related to the COVID-19 pandemic in summer. It did not mean that ‘summer’ would weaken the spread of COVID-19 in California. Therefore, special attention should be paid to the prevention and treatment of COVID-19 in the winter. And it cannot be ignored in summer, otherwise, it will also cause a counterattack against the epidemic.

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Impact of ambient temperature on hospital admissions for cardiovascular disease in Hefei City, China

Cited by 56 publications

References 68 publications

Risk assessment of temperature and air pollutants on hospitalizations for mental and behavioral disorders in Curitiba, Brazil

Risk assessment of temperature and air pollutants on hospitalizations for mental and behavioral disorders in Curitiba, Brazil

The association between extreme temperature and pulmonary tuberculosis in Shandong Province, China, 2005–2016: a mixed method evaluation

Risk effects of low temperature and high humidity on the spread of COVID-19 in California: Time series study

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