Lag effect and influencing factors of temperature on other infectious diarrhea in Zhejiang province
10.3760/cma.j.issn.0254-6450.2019.08.016
- VernacularTitle: 浙江省气温对其他感染性腹泻的滞后效应及影响因素
- Author:
Haitao WANG
1
;
Zhidong LIU
1
;
Jiahui LAO
1
;
Zhe ZHAO
1
;
Baofa JIANG
1
,
2
Author Information
1. Department of Epidemiology, School of Public Health, Shandong University, Jinan 250012, China
2. Shandong University Climate Change and Health Center, Jinan 250012, China
- Publication Type:Journal Article
- Keywords:
Temperature;
Other infectious diarrhea;
Two-stage model
- From:
Chinese Journal of Epidemiology
2019;40(8):960-964
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To study the lag effect of temperature and the source of heterogeneity on other infectious diarrhea (OID) in Zhejiang province, so as to identify related vulnerable populations at risk.
Methods:Data on OID and meteorology in Zhejiang province from 2014 to 2016 were collected. A two-stage model was conducted, including: 1) using the distributed lag non-linear model to estimate the city-specific lag effect of temperature on OID, 2) applying the multivariate Meta- analysis to pool the estimated city-specific effect, 3) using the multivariate Meta-regression to explore the sources of heterogeneity.
Results:There were 301 593 cases of OID in Zhejiang province during the study period. At the provincial level, temperature that corresponding to the lowest risk of OID was 16.7 ℃, and the temperature corresponding to the highest risk was 6.2℃ (RR=2.298, 95%CI: 1.527- 3.459). 16.7 ℃ was recognized as the reference temperature. P5 and P95 of the average daily temperature represented low and high temperature respectively. When the temperature was cold, the risk was delayed by 2 days, with the highest risk found on the 5th day (RR=1.057, 95%CI: 1.030-1.084) before decreasing to the 23rd day. When the temperature got hot, the risk of OID occurred on the first day (RR=1.081, 95%CI: 1.045-1.118) and gradually decreasing to the 8th day. Differences on heterogeneous sources related to the risks of OID in different regions, presented on urban latitude and the rate of ageing in the population.
Conclusions:Both high or low temperature could increase the risk of OID, with a lag effect noticed. Prevention program on OID should be focusing on populations living in the high latitude and the elderly population at the low temperature areas.
