title: Impacts of temperature change on ambulance dispatches and seasonal effect modification.
abstract: Ambulance dispatch is a proxy of acute health outcomes, and growing epidemiological evidence documented its relation to extreme temperature events. Research, however, on short-term temperature change and ambulance dispatches is scarce. We aimed to investigate the effect of short-term temperature change on ambulance dispatches and potential modification by season. Daily data on ambulance dispatch and weather factors were collected in Huainan, a Chinese inland city from December 2011 through December 2013. A Poison generalized linear regression model combined with distributed lag nonlinear model was constructed to examine the association of temperature change between neighboring days (TCN) with ambulance dispatches. The effect modification by season was also examined. There were 48,700 ambulance attendances during the study period. A statistically significant association of TCN with ambulance dispatches was observed. Temperature rise between neighboring days (TCN > 0) was associated with elevated adverse risk of ambulance dispatches, and the effects appeared to be acute (lag0, on the current day) and could last for at least a week, while temperature drop between neighboring days (TCN < 0) had a protective effect. For a 1 °C increase of TCN at lag0 and lag06 (on the 7-day moving average), the risk of ambulance dispatches increased by 2 % (95 % CI 1-3 %) and 7 (95 % CI 1-13 %), respectively. Extreme TCN increase (95th percentile, 3.3 °C vs. 0 °C) at lag0 and lag05 was accompanied by 6 (95 % CI 3-8 %) and 27 % (95 % CI 12-44 %) increase in ambulance dispatches. Ambulance dispatches were more vulnerable to extremely great temperature rise in summer and autumn. TCN was adopted for the first time to quantify the impact of short-term temperature change on ambulance dispatches. Temperature drop between neighboring days (TCN < 0) had a protective effect on ambulance dispatches, while temperature rise between neighboring days (TCN > 0) could acutely trigger the increase in ambulance dispatches, and TCN effect differs by season.
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Cheng
authors.affiliation: School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Brisbane, Queensland, 4509, Australia.
authors.forename: Zhiwei
authors.initials: Z
authors.lastname: Xu
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
authors.forename: Desheng
authors.initials: D
authors.lastname: Zhao
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
authors.forename: Mingyu
authors.initials: M
authors.lastname: Xie
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
authors.forename: Huihui
authors.initials: H
authors.lastname: Yang
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
authors.forename: Liying
authors.initials: L
authors.lastname: Wen
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
authors.forename: Kesheng
authors.initials: K
authors.lastname: Li
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. suhong5151@sina.com.
authors.forename: Hong
authors.initials: H
authors.lastname: Su
mesh_terms: D000552:Ambulances / Q000706:statistics & numerical data*; D002681:China; D002947:Cities; D006801:Humans; D006813:Humidity; D017711:Nonlinear Dynamics; D011891:Rain; D012044:Regression Analysis; D012621:Seasons; D013696:Temperature
keywords: Ambulance dispatches; Climate change; Temperature change