Objective To investigate the association between extreme temperature and non-accidental 120 emergency visits in Xining,China,and to identify vulnerable populations.Methods The data of daily emergency visits in Xining in 2016-2019 were ob-tained from Qinghai Provincial Medical Emergency Center,daily meteorological data were obtained from Qinghai Provincial Meteoro-logical Bureau,and air pollution data were collected from Xining Ecology and Environment Bureau.After controlling for the confoun-ding factors such as atmospheric pollutant concentration,humidity,and the day-of-the-week effect,a distributed lag non-linear model was used to fit the association between daily average temperature and emergency visits,including its lag effect,and subgroup analyses were performed based on sex and age.Results In 2016-2019,Qinghai Provincial Medical Emergency Center handled 48 354 non-accidental emergency visits in Xining,with a median daily number of 29 visits.Both extremely high and low temperature caused an in-crease in non-accidental emergency visits,and the effect of high temperature appeared on the same day and lasted for 6 days,while the effect of low temperature appeared after a lag of 5 days and lasted for 11 days.The maximum cumulative relative risk(cumRR)(lag 0-19 d)for the total population under extremely low temperature(P2.5=-10℃)was 1.49(95%confidence interval[CI]:1.09-2.04),while the maximum cumRR(lag 0-9 d)under extremely high temperature(P97.5=21℃)was 1.15(95%CI:1.06-1.25).There was a slight difference in cumulative effect value between different populations,with female individuals showing a higher cumulative effect from cold than male individuals and the<65 years age group showing a higher cumulative effect from heat than the≥65 years age group.Conclusion Both extremely high and low temperature can increase the risk of non-accidental emergency visits a-mong the residents of Xining,with the presence of lag effects.The health hazard effect is rapid but short-lived under extremely high temperature and is slow but long-lasting under extremely low temperature.
关键词
极端气温/非意外/120急救量/时间序列
Key words
extreme temperature/non-accidental/120 emergency visits/time series
维普
万方数据