Background The association between temperature and cardio-respiratory disease in urban areas has been widely reported but there is limited information from populations living in rural areas that may be disproportionately affected by climate change. Objectives To quantify the associations between daily temperature and clinical visits due to cardiovascular and/or respiratory disease in rural villages in the Ningxia Hui Autonomous Region, China over 2012–2015. Methods Daily data on clinical visits and weather conditions were collated from 203 villages. A quasi-Poisson regression with distributed lag non-linear model was used to examine the associations between daily temperature and clinical visits up to 28 days, after controlling for potential confounders. Results Over three years, 158,733 and 1,272,212 clinical visits were recorded for cardiovascular and respiratory diseases, respectively. Both low and high temperatures were associated with an increased risk of clinical visits for cardiovascular-related conditions, whereas only low temperatures were associated with increased clinical visits related to respiratory illness. The cold effect on cardiovascular visits appeared at the lag 6th day and persisted until the 22nd day, resulting in a cumulative relative risk (RR) 1.55 (95% CI: 1.26–1.92), compared with the minimum-clinical visit temperature. The cold effect on respiratory visits appeared immediately and lasted over the lag 0–28 days, with a cumulative RR 2.96 (2.74–3.21). Suboptimal temperature accounted for approximately 13% and 26% of clinic visits due to cardiovascular and respiratory disorders, respectively, with the majority of cases attributable to moderate – rather than extreme – cold temperature. Conclusions In rural settings, sub-optimal temperatures explained nearly one quarter of all clinical visits due to cardiovascular and respiratory diseases. Although extreme cold temperature had a stronger, more immediate, prolonged effect on respiratory disease than for cardiovascular disease, moderately cold temperatures accounted for most of the overall burden of clinical visits.
- Ambient temperature
- Cardio-respiratory diseases
- Distributed lag non-linear model
- Rural China