Temperature may be an important environmental factor affecting psoriasis. This study aimed to determine the potential association between apparent temperature (AT) and outpatient visits for psoriasis in Hefei, China. Daily psoriasis clinic visits in Hefei were collected from January 1, 2016 to December 31, 2020. A Poisson generalized linear regression model (PGLM) combined with a distributional lagged nonlinear model (DLNM) was used to analyze the impact of AT on psoriasis outpatient visits; the model was adjusted for relative humidity, wind speed, precipitation, PM2.5, NO2, SO2, time trends, Sundays, and holidays. The analyses were stratified by age and sex. A total of 24,351 patients with psoriasis were included in this study. Only a low AT showed a delayed and strong risk effect. Referring to the median AT (16.8°C), the effect of low AT started at lag 2 days and showed an increasing and then decreasing trend for approximately 5 days; the effect of extreme cold (1st percentile) and cold (5th percentile) peaked at lag 4 days with a relative risk (RR) of 1.117 (95% CI:1.065 to 1.171) and 1.081 (95% CI:1.044 to 1.119), respectively. The effect of mild cold (25th percentile) reached a maximum RR of 1.033 (95% CI:1.017 to 1.048) at lag 6 days. Subgroup analysis showed that low AT risk was more pronounced and longer-lasting in men and individuals aged < 45 years. Our study provides evidence that a low AT increases the risk of psoriasis. Men and young people are vulnerable to potential adverse effects. There is a need for enhanced health interventions, medical care, and early warnings for patients.

Background: At present, the effect of apparent temperature (AT) on epilepsy has not been confirmed. Therefore, we conducted this study in Hefei, China, a city in a humid subtropical region, to investigate the effects of AT on the daily number of epilepsy-related clinic visits. Methods: A time-series analysis of the number of daily epilepsy clinic visits during 2015-2020 was performed using a quasi-Poisson regression model combined with a distributed lag nonlinear model (DLNM). Time trends, days of the week, relative humidity, and PM2.5 concentration were adjusted for in the model. Subgroup analyses were performed by sex and age. Results: A total of 28,020 epilepsy-related clinic visits were reported by the hospital during the study period. Low AT showed significant negative and delayed effects on the number of epilepsy clinic visits, but no such effects were observed with high AT. The median apparent temperature (17 °C) was used as the reference, and the single-day lag effect of low AT (5th percentile, -1.5 °C) on the number of epilepsy clinic visits peaked on lag day 1, with a relative risk (RR) of 1.055 (95% CI: 1.015–1.097). The cumulative effect of low AT was most obvious on lag days 0-12, with a maximum RR of 1.451 (95% CI: 1.180–1.783). Males and young adults (0-14 years and 15-29 years) were more likely to be affected by low AT. Conclusions: We found that low AT led to an increase in the number of epilepsy-related clinic visits. This result provides an important scientific basis for the allocation of outpatient medical resources and the development of interventions.