荟萃分析
出版偏见
置信区间
随机效应模型
医学
热浪
心肌梗塞
元回归
内科学
相对风险
气候变化
生物
生态学
作者
Zhiying Sun,Chen Chen,Dandan Xu,Tiantian Li
标识
DOI:10.1016/j.envpol.2018.06.045
摘要
Previous studies have suggested that ambient temperature is associated with the mortality and morbidity of myocardial infarction (MI) although consistency among these investigations is lacking. We performed a meta-analysis to investigate the relationship between ambient temperature and MI. The PubMed, Web of Science, and China National Knowledge Infrastructure databases were searched back to August 31, 2017. The pooled estimates for different temperature exposures were calculated using a random-effects model. The Cochran's Q test and coefficient of inconsistency (I2) were used to evaluate heterogeneity, and the Egger's test was used to assess publication bias. The exposure-response relationship of temperature-MI mortality or hospitalization was modeled using random-effects meta-regression. A total of 30 papers were included in the review, and 23 studies were included in the meta-analysis. The pooled estimates for the relationship between temperature and the relative risk of MI hospitalization was 1.016 (95% confidence interval [CI]: 1.004-1.028) for a 1 °C increase and 1.014 (95% CI: 1.004-1.024) for a 1 °C decrease. The pooled estimate of MI mortality was 1.639 (95% CI: 1.087-2.470) for a heat wave. The heterogeneity was significant for heat exposure, cold exposure, and heat wave exposure. The Egger's test revealed potential publication bias for cold exposure and heat exposure, whereas there was no publication bias for heat wave exposure. An increase in latitude was associated with a decreased risk of MI hospitalization due to cold exposure. The association of heat exposure and heat wave were immediate, and the association of cold exposure were delayed. Consequently, cold exposure, heat exposure, and exposure to heat waves were associated with an increased risk of MI. Further research studies are required to understand the relationship between temperature and MI in different climate areas and extreme weather conditions.
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