摘要
目的 分析广西百色市极端气象因素对当地居民高血压病就诊的影响,为疾病的区域性防控提供循证依据。方法 收集2020—2022年期间到百色市两家三级甲等综合性医院就诊的高血压病例资料及同期当地气象因素、空气污染物数据。运用广义加性模型(generalized additive model, GAM)结合分布滞后非线性模型(distributed lag nonlinear model, DLNM),以气象因素的第5百分位数(P_(5))和第95百分位数(P_(95))来评估极端气象因素在不同滞后天数对高血压病就诊的滞后效应(RR)及累积滞后效应(CumRR)。结果 研究期间,共58 139例患者因高血压病就诊,日均就诊量53人。Spearman相关性分析显示,温度和压强均与高血压就诊存在相关性,两者与高血压患者就诊的暴露-反应曲线分别呈近似线性和近似“J”型。在单日滞后效应中,极端低温和极高气压表现出危害延迟效应,两者均在lag21 d时影响最显著,RR值分别为1.026(95%CI:1.013,1.040)和1.025(95%CI:1.015,1.035);极低气压表现急性危害效应,不利影响在lag0 d时最显著,RR为1.016(95%CI:1.003,1.029),随后危害效应逐渐下降。极端低温和极高气压的累积效应在lag0-21 d时最强,极低气压的累积效应在lag0-4 d时最强;而极端高温对人群高血压病就诊量的影响无统计学意义。结论 高血压病易受环境气象因素影响,极端低温、极低气压和极高气压均能增加高血压病就诊风险并且存在不同程度的滞后性。
Objective To analyze the impact of extreme meteorological factors on outpatient visits for hypertension among residents in Baise City,Guangxi,and to provide evidence-based support for regional disease prevention and control.Methods Data on hypertension cases presenting to two Grade A tertiary general hospitals in Baise City,along with concurrent local meteorological factors and air pollutant data,were collected for the period between 2020 and 2022.A generalized additive model(GAM)combined with a distributed lag nonlinear model(DLNM)was employed.The 5th(P_(5))and 95th(P_(95))percentiles of meteorological factors were used to evaluate the lag effects(Relative Risk,RR)and cumulative lag effects(Cumulative RR,CumRR)of extreme meteorological factors on hypertension outpatient visits across different lag days.Results During the study period,a total of 58139 hypertensive outpatient visits were recorded,with a daily average of 53 visits.Spearman correlation analysis showed that both temperature and atmospheric pressure were correlated with hypertensive outpatient visits.The exposure-response curves of temperature and atmospheric pressure with hypertensive visits were approximately linear and“J”-shaped,respectively.In terms of single-day lag effects,extreme low temperature and extremely high atmospheric pressure exhibited delayed harmful effects,with the most significant impacts observed at lag 21 days(RR=1.026,95%confidence interval CI:1.013~1.040;RR=1.025,95%CI:1.015~1.035,respectively).Extremely low atmospheric pressure showed an acute harmful effect,with the strongest adverse impact at lag 0 days(RR=1.016,95%CI:1.003~1.029),followed by a gradual decline in the effect.The cumulative effects of extreme low temperature and extremely high atmospheric pressure were most pronounced at lag 0-21 days,while the cumulative effect of extremely low atmospheric pressure was strongest at lag 0-4 days.In contrast,the impact of extreme high temperature on hypertensive outpatient visits was not statistically significant.Conclusion Hypertension is susceptible to environmental meteorological factors.Extreme low temperature,extremely low atmospheric pressure,and extremely high atmospheric pressure can increase the risk of hypertensive outpatient visits,with varying degrees of lag effects.
作者
辛孟东
商铭梅
梁建成
韦肖肖
郭蕊
邓树嵩
XIN Mengdong;SHANG Mingmei;LIANG Jiancheng;WEI Xiaoxiao;GUO Rui;DENG Shusong(School of Public Health,Youjiang Medical University for Nationalities,Baise 533000,Guangxi,China)
出处
《右江民族医学院学报》
2025年第6期1013-1019,共7页
Journal of Youjiang Medical University for Nationalities
基金
广西研究生教育计划创新项目(YCSW2024541)。
关键词
高血压
气象因素
时间序列分析
分布滞后非线性模型
广义加性模型
hypertension
meteorological factors
time series analysis
distributed lag nonlinear model
generalized additive model
