The association between temperature and mortality has been widely reported. However, it remains largely unclear whether inflammation-related diseases, caused by excessive or inappropriate inflammatory reaction, may be affected by ambient temperature, particularly in low-income areas.
To explore the association between ambient temperature and clinical visits for inflammation-related diseases in rural villages in the Ningxia Hui Autonomous Region, China, during 2012─2015.
Daily data on inflammation-related diseases and weather conditions were collected from 258 villages in Haiyuan (161 villages) and Yanchi (97 villages) counties during 2012─2015. A Quasi-Poisson regression with distributed lag non-linear model was used to examine the association between temperature and clinical visits for inflammation-related diseases. Stratified analyses were performed by types of diseases including arthritis, gastroenteritis, and gynecological inflammations.
During the study period, there were 724,788 and 288,965 clinical visits for inflammation-related diseases in Haiyuan and Yanchi, respectively. Both exposure to low (RR: 2.045, 95% CI: 1.690, 2.474) and high temperatures (RR: 1.244, 95% CI: 1.107, 1.399) were associated with increased risk of total inflammation-related visits in Haiyuan county. Low temperatures were associated with increased risks of all types of inflammation-related diseases in Yanchi county (RR: 4.344, 95% CI: 2.887, 6.535), while high temperatures only affected gastroenteritis (RR: 1.274, 95% CI: 1.040, 1.561). Moderate temperatures explained approximately 26% and 33% of clinical visits due to inflammation-related diseases in Haiyuan and Yanchi, respectively, with the burden attributable to cold exposure higher than hot exposure. The reference temperature values ranged from 17 to 19 in Haiyuan, and 12 to 14 in Yanchi for all types of clinical visits.
Our findings add additional evidence for the adverse effect of suboptimal ambient temperature and provide useful information for public health programs targeting people living in rural villages.

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