MENG Xiang-yan, ZHENG Shan, WEI Xing-fu, NIE Yong-hong, WANG Min-zhen, MI Xiu-ying, LI Hai-yan, BAI Ya-na. Effects of cold waves on hospital admissions for hypertension in Jinchang, Gansu Province: A case-crossover study[J]. Journal of Environmental and Occupational Medicine, 2020, 37(1): 36-43. DOI: 10.13213/j.cnki.jeom.2020.19463
Citation: MENG Xiang-yan, ZHENG Shan, WEI Xing-fu, NIE Yong-hong, WANG Min-zhen, MI Xiu-ying, LI Hai-yan, BAI Ya-na. Effects of cold waves on hospital admissions for hypertension in Jinchang, Gansu Province: A case-crossover study[J]. Journal of Environmental and Occupational Medicine, 2020, 37(1): 36-43. DOI: 10.13213/j.cnki.jeom.2020.19463

Effects of cold waves on hospital admissions for hypertension in Jinchang, Gansu Province: A case-crossover study

  • Background Cold waves may have potential impact on the occurrence of hypertension. Therefore, studying the relationship between extreme temperature and hospital admissions for hypertension is of great importance for the prevention of hypertension and early warning of extreme weather in high-altitude cold regions.
    Objective This study investigates the impacts of cold waves on hospital admissions for hypertension and the potential confounding factors in Jinchang, Gansu Province.
    Methods Daily hospital admissions for hypertension from three general hospitals, meteorological factors, and air pollution data in Jinchang were all collected from 2011 to 2016. Correlation analysis was performed for meteorological factors, air pollutants, and the admissions for hypertension. Data from a two-way symmetric case-crossover design with three matching ratios (1:2, 1:4, and 1:6) were used to establish a Cox regression model on cold waves associated with hospital admissions for hypertension after controlling day-of-the-week effect, holiday effect, meteorological factor (relative humidity), and air pollutants (SO2, NO2, and PM10). Using the optimal lag day effect estimate, sensitivity analysis of the Cox model and age and sex stratified analysis were conducted, and the effects of different durations (24, 48, and 72h) of cold waves on hospital admissions for hypertension were evaluated; the 24-48h cold wave effect combined the effects of 24h cold wave and the 48 h cold wave.
    Results A total of nine cold waves were included from 2011 to 2016. During the cold waves, the hospital admissions for hypertension showed different trends with the variation of temperature and presented a lag effect. The greatest effect of cold waves on hypertension admissions was observed on single lag 5 d in the two-way symmetric 1:2 case-crossover study (OR=1.142, 95% CI:1.053-1.237). The 24, 48, and 72 h cold waves all had effects on the hospital admissions for hypertension on single lag 5 d, and the effects of 24-48 h cold wave were stronger (OR=1.218, 95% CI:1.072-1.385). The stratified analysis results found that cold waves had significant effects on the hospital admissions for hypertension in both males and females on single lag 5 d, and the estimate for males was higher than that for females (OR=1.191, 95% CI:1.041-1.364); the estimate was also higher for the age group under 65 years than for those at 65 years and over (OR=1.201, 95% CI:1.043-1.383). The sensitivity analysis results showed that the proposed model was generally robust with less fluctuated OR values.
    Conclusion There are significant effects of cold waves on the hospital admissions for hypertension in Jinchang City. Age, gender, and cold wave duration can modify the effects of cold waves.
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