Abstract
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 PM10 (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 PM10 may have a significant role in altering the association between temperature and varicella, while PM10 and population density may alter the association between wind velocity and varicella.
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Data availability
Data for the study are available from the corresponding author with the approval of the Yunnan Provincial CDC.
Abbreviations
- DTR:
-
diurnal temperature range
- RR:
-
relative risk
- SSH:
-
sunshine hours
- PRE:
-
precipitation
- PRS:
-
pressure
- Min:
-
minimum
- Max:
-
maximum
- DLNM:
-
distributed lag non-linear model
- QAIC:
-
Quasi-Akaike Information Criterion
- PM2.5 :
-
particles with an aerodynamic diameter less than 2.5 μm
- PM10 :
-
particles with an aerodynamic diameter less than 10 μm
- SO2 :
-
sulfur dioxide
- NO2 :
-
nitrogen dioxide
- GDP:
-
gross domestic product
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Funding
This study was supported by a competitive grant from the Science and Technology Department of Jilin Province, China (Project Number: 20191102007YY).
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Authors and Affiliations
Contributions
Conceptualization: H. W., Q. Z., T. S., X. Z.
Data curation: H. W., S. H.
Formal analysis: H. W., S. H., Z. W.
Funding acquisition: Q. Z., X. Z., T. S.
Investigation: H. W., S. H., Z. W.
Methodology: H. W., S. H., Z. L.
Supervision: M. Z., H. Z., W. F., Y. Y.
Validation: L. D., W. F.
Writing—original draft: H. W., S. H.
Writing—review and editing: H. Z., M. L., X. H., Z. L.
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The morbidity data used in this study were approved for use by the Yunnan Provincial CDC and did not involve private patient information and ethical issues.
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Wang, ., Huang, S., Wang, Z. et al. Association between meteorological factors and varicella incidence: a multicity study in Yunnan Province, China. Environ Sci Pollut Res 30, 117817–117828 (2023). https://doi.org/10.1007/s11356-023-30457-0
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DOI: https://doi.org/10.1007/s11356-023-30457-0