Distributed lag nonlinear model-based analysis of effects of apparent temperature on the number of hypertension-associated hospitalizations in Urumqi,China
Objective To investigate the relationship between apparent temperature and the number of hypertension-associated hospitalizations as well as the lag effects,and to analyze the effects of apparent temperature for different grades of hypertension.Methods The information on hypertension-associated hospitalizations in 10 hospitals in Urumqi,China from 2019 to 2021 as well as the meteorological and air pollution data(daily average barometric pressure,ambient temperature,relative humidity,wind speed,sun-shine duration,NO2,SO2,CO,O3,PM10,and PM2.5)from Urumqi Meteorological Service and Environmental Monitoring Station were collected.A distributional lag nonlinear model was used to explore the exposure-lag-response relationship between apparent tem-perature and the number of hypertension-associated hospitalizations.Results The exposure-response curves revealed nonlinear associa-tions of daily average apparent temperature with the total number of hypertension-associated hospitalizations,the number of grade-2 hy-pertension-associated hospitalizations,and the number of grade-3 hypertension-associated hospitalizations.At the extreme low daily av-erage apparent temperature(P5=-17.2 ℃),the cumulative lag effects of daily average apparent temperature on daily total hyperten-sion-associated hospitalizations and grade-3 hypertension-associated hospitalizations increased with the number of lag days,reaching the highest cumulative relative risks(CRRs)at lag 14 days,which were 2.025(95％confidence interval[CI]:1.191-3.442)and 2.171(95％CI:1.268-3.716),respectively.At the extreme high apparent temperature(P95=25.0 ℃),the daily average apparent temperature had an impact on daily total hypertension-associated hospitalizations for hypertension,the number of hospitalizations for grade-2 hypertension,and the number of hospitalizations for grade-3 hypertension.The cumulative lag effect reached its strongest on day 2,day 9,and day 2,with CRRs of 0.72(95％CI:0.55-0.94),0.57(95％CI:0.33-0.99),and 0.69(95％CI:0.53-0.91),respectively.Conclusion Apparent temperature has a lagged and nonlinear association with the number of hypertension-asso-ciated hospitalizations.Public health departments can formulate hypertension warnings based on predicted apparent temperature to in-form populations susceptible to hypertension to take precautions against apparent temperature changes,providing new ideas for reducing the incidence of hypertension.
hypertensionmeteorological factordistributed lag nonlinear modelair pollution
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