Association between meteorological factors and varicella incidence: a multicity study in Yunnan Province, China

• Published in: Environmental science and pollution research international Vol. 30; no. 55; pp. 117817 - 117828
• Main Authors: Wang, Hao, Huang, Shanjun, Wang, Zhaohan, Zhen, Hua, Li, Zhuo, Fan, Wenqi, Lu, Menghan, Han, Xin, Du, Lanping, Zhao, Meifang, Yan, Yuke, Zhang, Xinyao, Zhen, Qing, Shui, Tiejun
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2023; Springer Nature B.V
• Subjects: Air pollution; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Chicken pox; Cities; Diurnal; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Geographical locations; Heterogeneity; Humidity; Particulate matter; Population density; Rainfall; Relative humidity; Research Article; Sunlight; Temperature; Temperature gradients; Varicella; Velocity; Waste Water Technology; Water Management; Water Pollution Control; Wind; Wind speed; China; Yunnan China; Varicella; Meta; Meteorological; Multicity; DLNM
• ISSN: 1614-7499; 0944-1344; 1614-7499
• DOI: 10.1007/s11356-023-30457-0

This multicenter study aimed to investigate the relationship between varicella incidence and meteorological factors including mean temperature, relative humidity, sunshine duration, diurnal temperature difference, wind speed, and rainfall, as previous studies have produced varying results. Our study also sought to identify potential sources of heterogeneity. Data on reported daily varicella numbers and meteorological factors were collected for 14 cities in Yunnan Province from 2017 to 2021. A distribution-lagged nonlinear model was constructed to explore the relationship between meteorological conditions and varicella incidence in each included city. We then used multiple meta-regression to explore sources of heterogeneity using demographic economics indicators, air pollutants, and geographic location as potential modifiers. The cumulative hazard effect plot showed an inverted S-shape for the relationship between temperature and varicella, with the smallest RR (relative risk) (0.533, 95% CI: 0.401–0.708) at temperatures up to 27.2 °C. The maximum RR (1.171, 95% CI: 1.001–1.371) was obtained when the relative humidity was equal to 98.5%. The RR (1.164, 95% CI: 1.002–1.352) was greatest at a diurnal temperature range of 2 °C (1.164, 95% CI: 1.002–1.352) and least (0.913, 95% CI: 0.834–0.999) at a diurnal temperature range of 16.1 °C. The maximum RR (1.214, 95% CI: 1.089–1.354) was obtained at 0 h of sunshine, and the minimum RR (0.808, 95% CI: 0.675–0.968) was obtained at 12.4 h of sunshine. The RR (0.792, 95% CI: 0.633–0.992) was minimum at a wind velocity of 4.8 m/s. Residual heterogeneity ranged from 1 to 42.7%, with PM 10 (particles with an aerodynamic diameter less than 10 μm), GDP (gross domestic product), and population density explaining some of this heterogeneity. The temperature has a dual effect on varicella incidence. Varicella cases are negatively correlated with diurnal temperature range, sunshine duration, and wind speed, and positively correlated with relative humidity. GDP and PM 10 may have a significant role in altering the association between temperature and varicella, while PM 10 and population density may alter the association between wind velocity and varicella.