» Articles » PMID: 29734606

Meteorological Factors and the Incidence of Mumps in Fujian Province, China, 2005-2013: Non-linear Effects

Overview
Date 2018 May 9
PMID 29734606
Citations 22
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Mumps is still an important public health issue in the world with several recent outbreaks. The seasonable distribution of the disease suggested that meteorological factors may influence the incidence of mumps. The aim of this study was to explore the possible association between meteorological factors and the incidence of mumps, and to provide scientific evidence to relevant health authorities for the disease control and prevention.

Methods: We obtained the data of mumps cases and daily meteorological factors in Fujian Province in Eastern China over the period of 2005-2013. Using distributed lag non-linear model (DLNM) approach, we assessed the relationship between the meteorological factors and mumps incidence.

Results: The effects of meteorological factors on the mumps incidence were all non-linear. Compared with the lowest risk values, the upper level of precipitation, atmospheric pressure and relative humidity could increase the risk of mumps, whereas the low level of wind velocity, temperature, diurnal temperature range and sunshine duration may also increase the risk. Moderate atmospheric pressure and low wind velocity had larger cumulative effects within 30lagdays and the relative risks were 10.02 (95%CI: 2.47-40.71) and 12.45 (95%CI: 1.40-110.78). For temperature, the cumulative effect within 30lagdays of minimum temperature was higher than that from maximum temperature in most populations. The cumulative effects of minimum temperature for males, children aged 10-14 and students were higher than those in other populations.

Conclusions: Meteorological factors, especially temperature and wind velocity, should be taken into consideration in the prevention and warning of possible mumps epidemic. Special attention should be paid to the vulnerable populations, such as teenagers and young adults.

Citing Articles

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

Xiong X, Xiang L, Chang L, Wu I, Deng S J Med Internet Res. 2025; 27:e66072.

PMID: 39913179 PMC: 11843052. DOI: 10.2196/66072.


Long- and short-run asymmetric impacts of climate variation on tuberculosis based on a time series study.

Wang Y, Xue C, Xue B, Zhang B, Xu C, Ren J Sci Rep. 2024; 14(1):23565.

PMID: 39384889 PMC: 11464594. DOI: 10.1038/s41598-024-73370-3.


The impact of temperature, humidity and closing school on the mumps epidemic: a case study in the mainland of China.

Li X, Zhang L, Tan C, Wu Y, Zhang Z, Ding J BMC Public Health. 2024; 24(1):1632.

PMID: 38898424 PMC: 11186224. DOI: 10.1186/s12889-024-18819-w.


Risk effects of meteorological factors on human brucellosis in Jilin province, China, 2005-2019.

Huang S, Wang H, Li Z, Wang Z, Ma T, Song R Heliyon. 2024; 10(8):e29611.

PMID: 38660264 PMC: 11040064. DOI: 10.1016/j.heliyon.2024.e29611.


Short-Term Effects of Extreme Meteorological Factors on Hand, Foot, and Mouth Disease Infection During 2010-2017 in Jiangsu, China: A Distributed Lag Non-Linear Analysis.

Yang X, Wang J, Zhang G, Yu Z Geohealth. 2024; 8(4):e2023GH000942.

PMID: 38562664 PMC: 10982542. DOI: 10.1029/2023GH000942.


References
1.
Polderman K . Application of therapeutic hypothermia in the intensive care unit. Opportunities and pitfalls of a promising treatment modality--Part 2: Practical aspects and side effects. Intensive Care Med. 2004; 30(5):757-69. DOI: 10.1007/s00134-003-2151-y. View

2.
Wang Z, Yan R, He H, Li Q, Chen G, Yang S . Difficulties in eliminating measles and controlling rubella and mumps: a cross-sectional study of a first measles and rubella vaccination and a second measles, mumps, and rubella vaccination. PLoS One. 2014; 9(2):e89361. PMC: 3930734. DOI: 10.1371/journal.pone.0089361. View

3.
Mukaka M . Statistics corner: A guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2013; 24(3):69-71. PMC: 3576830. View

4.
Wei J, Li Y . Airborne spread of infectious agents in the indoor environment. Am J Infect Control. 2016; 44(9 Suppl):S102-8. PMC: 7115322. DOI: 10.1016/j.ajic.2016.06.003. View

5.
Wang C, Cao K, Zhang Y, Fang L, Li X, Xu Q . Different effects of meteorological factors on hand, foot and mouth disease in various climates: a spatial panel data model analysis. BMC Infect Dis. 2016; 16:233. PMC: 4881061. DOI: 10.1186/s12879-016-1560-9. View