Author
Listed:
- Mengya Yang
(School of Public Health, School of Medicine, Zhejiang University, Hangzhou 310058, China
These authors contributed equally to this work.)
- Can Chen
(State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China
These authors contributed equally to this work.)
- Xiaobao Zhang
(State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China)
- Yuxia Du
(State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China)
- Daixi Jiang
(State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China)
- Danying Yan
(State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China)
- Xiaoxiao Liu
(State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China)
- Cheng Ding
(State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China)
- Lei Lan
(State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China)
- Hao Lei
(School of Public Health, School of Medicine, Zhejiang University, Hangzhou 310058, China)
- Shigui Yang
(School of Public Health, School of Medicine, Zhejiang University, Hangzhou 310058, China
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital College of Medicine, Zhejiang University, Hangzhou 310003, China
These authors contributed equally to this work.)
Abstract
Meteorological factors and the increase in extreme weather events are closely related to the incidence rate of infectious diarrhea. However, few studies have explored whether the impact of the same meteorological factors on the incidence rate of infectious diarrhea in different climate regions has changed and quantified these changes. In this study, the time series fixed-effect Poisson regression model guided by climate was used to quantify the relationships between the incidence rate of various types of infectious diarrhea and meteorological factors in different climate regions of China from 2004 to 2018, with a lag of 0–2 months. In addition, six social factors, including per capita Gross Domestic Product (GDP), population density, number of doctors per 1000 people, proportion of urbanized population, proportion of children aged 0–14 years old, and proportion of elderly over 65 years old, were included in the model for confounding control. Additionally, the intercept of each province in each model was analyzed by a meta-analysis. Four climate regions were considered in this study: tropical monsoon areas, subtropical monsoon areas, temperate areas and alpine plateau areas. The results indicate that the influence of meteorological factors and extreme weather in different climate regions on diverse infectious diarrhea types is distinct. In general, temperature was positively correlated with all infectious diarrhea cases (0.2 ≤ r ≤ 0.6, p < 0.05). After extreme rainfall, the incidence rate of dysentery in alpine plateau area in one month would be reduced by 18.7% (95% confidence interval (CI): −27.8–−9.6%). Two months after the period of extreme sunshine duration happened, the incidence of dysentery in the alpine plateau area would increase by 21.9% (95% CI: 15.4–28.4%) in that month, and the incidence rate of typhoid and paratyphoid in the temperate region would increase by 17.2% (95% CI: 15.5–18.9%) in that month. The meta-analysis showed that there is no consistency between different provinces in the same climate region. Our study indicated that meteorological factors and extreme weather in different climate areas had different effects on various types of infectious diarrhea, particularly extreme rainfall and extreme sunshine duration, which will help the government develop disease-specific and location-specific interventions, especially after the occurrence of extreme weather.
Suggested Citation
Mengya Yang & Can Chen & Xiaobao Zhang & Yuxia Du & Daixi Jiang & Danying Yan & Xiaoxiao Liu & Cheng Ding & Lei Lan & Hao Lei & Shigui Yang, 2022.
"Meteorological Factors Affecting Infectious Diarrhea in Different Climate Zones of China,"
IJERPH, MDPI, vol. 19(18), pages 1-15, September.
Handle:
RePEc:gam:jijerp:v:19:y:2022:i:18:p:11511-:d:913529
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