Abstract

To evaluate the correlations between diurnal temperature range (DTR) and the number of outpatient visits for common cold from Jan. 1, 2008, to Dec. 31, 2010, in the Shanghai metro area; we used a distributed lag non-linear model together with a Poisson regression model. The controlling factors included long-term trends and day of the week in outpatient visits for common cold and the selected weather elements. The entire study group was divided into three different age subgroups, including ≤ 15, 15-65, and ≥ 65 years old. We found some non-linear J-patterns between DTR and daily outpatient visits for common cold. At lag 0 day, the number of outpatient visits for common cold would increase by 11.1% per 1 °C increase in DTR. The greater the DTR, the more it affects outpatient visits for common cold, especially for the ≥ 65 years age group. In addition, DTR plays a more important role in outpatient visits for common cold in spring and winter compared with other seasons of the year. Our study showed that DTR is a risk factor that contributes to common cold. Results in this study can provide scientific evidence for the local authorities in improving preventive measures of the healthcare system.

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