Short-term effects of cold spells on hospitalisations for acute exacerbation of chronic obstructive pulmonary disease: a time-series study in Beijing, China

Abstract

ObjectivesOur work aimed at exploring the relationship between cold spells and acute exacerbation of chronic obstructive pulmonary disease (AECOPD) hospitalisations in Beijing, China, and assessing the moderating effects of the intensities and the durations of cold spells, as well as identifying the vulnerable.DesignA time-series study.SettingWe obtained time-series data of AECOPD hospitalisations, meteorological variables and air quality index in Beijing, China during 2012–2016.ParticipantsAll AECOPD hospitalisations among permanent residents in Beijing, China during the cold seasons (November–March) of 2012–2016 were included (n=84 571).Primary and secondary outcome measuresA quasi-Poisson regression with a distributed lag model was fitted to investigate the short-term effects of cold spells on AECOPD hospitalisations by comparing the counts of AECOPD admissions during cold spell days with those during non-cold spell days.ResultsCold spells under different definitions were associated with increased risk of AECOPD hospitalisations, with the maximum cumulative relative risk (CRR) over 3 weeks (lag0–21). The cumulative effects at lag0–21 increased with the intensities and the durations of cold spells. Under the optimal definition, the most significant single-day relative risk (RR) was found on the days of cold spells (lag0) with an RR of 1.042 (95% CI 1.013 to 1.072), and the CRR at lag0–21 was 1.394 (95% CI 1.193 to 1.630). The elderly (aged ≥65) were more vulnerable to the effects of cold spells on AECOPD hospitalisations.ConclusionCold spells are associated with increased AECOPD hospitalisations in Beijing, with the cumulative effects increased with intensities and durations. The elderly are at particular risk of AECOPD hospitalisations triggered by cold spells.

Exploring Health Effects under Specific Causes of Mortality Based on 90 Definitions of PM2.5 and Cold Spell Combined Exposure in Shanghai, China

“…7,12,15,45 When exposed to cold temperature or air pollution, the airway epithelium is irritated, which causes the body to respond with coughing, bronchoconstriction, and mucosal secretion. 1,46 Cold stress and PM 2.5 experiments in adulthood of mice showed that coexposure may promote the deterioration of asthma symptoms by increasing inflammatory cytokines, ROS formation, Th2/Th1 imbalance, and suppressing the differentiation of Th17 toward Treg cells. 47,48 Further deaths from respiratory disease will occur in sensitive individuals (e.g., elderly people, etc.).…”

“…Therefore, there is a need for a warning system with local characteristics. According to the Q-AIC, the best definition of all-cause mortality was P2T4, the threshold of which was the same as cold spell research in China processed by Chen et al, , and the air pollution research processed by Zhang et al ,,, However, the combined event defined by P1T5 showed the highest cumulative relative risk, which means that an early warning should be triggered on the first exposure day when the temperature is lower than the 2.5th percentile and lasts for at least 48 h. The stricter definition showed a higher relative risk, but the protective ability was quite limited. The loose definition could capture more exposure events with wider protection, though its relative risk was relatively lower .…”

Effects of Cold Spells on Mortality — Ningbo City, Zhejiang Province, China, 2014–2018

“…This is consistent with the research of Liang et al, that is, the optimal cold wave was defined as temperature threshold ≤P 5 and duration ≥2 days ( 4 ). However, Liu et al found that the optimal cold wave was defined as the days with temperature threshold ≤P 10 and duration ≥4 days for COPD hospitalized population in Beijing ( 7 ). This suggested that different definitions may apply to different regions, climates, and health outcomes.…”

Association between winter cold spells and acute myocardial infarction in Lithuania 2000–2015

“…( 1 ): where Z denotes the Z-test; E 1 and E 2 are the effect estimates (i.e. ln (RR)) of two subgroups; SE (E 1 ) and SE (E 2 ) are corresponding Standard Errors of E 1 and E 2 45 .…”