寒潮对甘肃省金昌市高血压住院人数影响的病例交叉研究

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

  • 摘要:
    背景 寒潮对高血压疾病的发生可能具有潜在风险。在高海拔寒冷地区开展极端气温对高血压住院人数影响的关联研究对高血压疾病的预防及极端天气的预警具有参考意义。
    目的 探讨甘肃省金昌市寒潮对高血压疾病住院人数的影响及潜在混杂因素。
    方法 收集2011-2016年金昌市3所综合医院每日高血压住院信息及同期气象资料和大气污染物资料,分析寒潮期间高血压住院人数的变化。对气象因素、大气污染物与高血压住院人数进行相关性分析,采用3种匹配比例(1:2、1:4、1:6)的双向对称病例交叉研究设计,在控制星期几效应、节假日效应、气象因素(平均相对湿度)和环境污染物(SO2、NO2、PM10)等混杂因素后,建立寒潮与高血压住院人数的Cox回归模型。选择滞后效应最大的滞后天数,进行敏感度分析及对年龄、性别进行分层分析,并分析不同寒潮持续时间(24、48、72h)对高血压住院人数的影响,其中24 h寒潮和48 h寒潮合并后简称为24、48h寒潮。
    结果 在2011-2016年间共纳入9次寒潮事件。寒潮期间,高血压住院人数随温度变化而出现不同变化趋势,且存在一定滞后效应。其中,双向对称1:2病例交叉研究在单滞后5 d时对高血压住院人数影响的效应值最大,OR值为1.142(95% CI:1.053~1.237)。在单滞后5 d时,24、48 h寒潮和72 h寒潮均对高血压住院人数具有影响,且24、48 h寒潮对高血压住院人数影响更大OR(95% CI)=1.218(1.072~1.385)。分层分析发现,在单滞后5 d时,寒潮对男性、女性高血压住院人数均具有影响,且对男性的影响更大OR(95% CI)=1.191(1.041~1.364);相比65岁以上人群,65岁以下人群更易受寒潮影响OR(95% CI)=1.201(1.043~1.383)。敏感度分析结果显示,模型基本稳健,OR波动范围小。
    结论 寒潮对金昌市居民高血压疾病住院人数的增加具有一定的影响。不同年龄、性别及寒潮持续时间对寒潮的影响均存在修饰作用。

     

    Abstract:
    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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