TY - JOUR
T1 - Different effects of meteorological factors on hand, foot and mouth disease in various climates
T2 - A spatial panel data model analysis
AU - Wang, Chao
AU - Cao, Kai
AU - Zhang, Yingjie
AU - Fang, Liqun
AU - Li, Xia
AU - Xu, Qin
AU - Huang, Fangfang
AU - Tao, Lixin
AU - Guo, Jin
AU - Gao, Qi
AU - Guo, Xiuhua
N1 - Publisher Copyright:
© 2016 Wang et al.
PY - 2016/5/26
Y1 - 2016/5/26
N2 - Background: Major outbreaks of hand, foot and mouth disease (HFMD) have been reported in China since 2008, posing a great threat to the health of children. Although many studies have examined the effect of meteorological variables on the incidence of HFMD, the results have been inconsistent. This study aimed to quantify the relationship between meteorological factors and HFMD occurrence in different climates of mainland China using spatial panel data models. Methods: All statistical analyses were carried out according to different climate types. We firstly conducted a descriptive analysis to summarize the epidemic characteristics of HFMD from May 2008 to November 2012 and then detected the spatial autocorrelation of HFMD using a global autocorrelation statistic (Moran's I) in each month. Finally, the association between HFMD incidence and meteorological factors was explored by spatial panel data models. Results: The 353 regions were divided into 4 groups according to climate (G1: subtropical monsoon climate; G2: temperate monsoon climate; G3: temperate continental climate; G4: plateau mountain climate). The Moran's I values were significant with high correlations in most months of group G1 and G2 and some months of group G3 and G4. This suggested the existence of a high spatial autocorrelation with HFMD. Spatial panel data models were more appropriate to describe the data than fixed effect models. The results showed that HFMD incidences were significantly associated with average atmospheric pressure (AAP), average temperature (AT), average vapor pressure (AVP), average relative humidity (ARH), monthly precipitation (MP), average wind speed (AWS), monthly total sunshine hours (MSH), mean temperature difference (MTD), rain day (RD) and average temperature distance (ATD), but the effect of meteorological factors might differ in various climate types. Conclusions: Spatial panel data models are useful and effective when longitudinal data are available and spatial autocorrelation exists. Our findings showed that meteorological factors were related to the occurrence of HFMD, which were also affected by climate type.
AB - Background: Major outbreaks of hand, foot and mouth disease (HFMD) have been reported in China since 2008, posing a great threat to the health of children. Although many studies have examined the effect of meteorological variables on the incidence of HFMD, the results have been inconsistent. This study aimed to quantify the relationship between meteorological factors and HFMD occurrence in different climates of mainland China using spatial panel data models. Methods: All statistical analyses were carried out according to different climate types. We firstly conducted a descriptive analysis to summarize the epidemic characteristics of HFMD from May 2008 to November 2012 and then detected the spatial autocorrelation of HFMD using a global autocorrelation statistic (Moran's I) in each month. Finally, the association between HFMD incidence and meteorological factors was explored by spatial panel data models. Results: The 353 regions were divided into 4 groups according to climate (G1: subtropical monsoon climate; G2: temperate monsoon climate; G3: temperate continental climate; G4: plateau mountain climate). The Moran's I values were significant with high correlations in most months of group G1 and G2 and some months of group G3 and G4. This suggested the existence of a high spatial autocorrelation with HFMD. Spatial panel data models were more appropriate to describe the data than fixed effect models. The results showed that HFMD incidences were significantly associated with average atmospheric pressure (AAP), average temperature (AT), average vapor pressure (AVP), average relative humidity (ARH), monthly precipitation (MP), average wind speed (AWS), monthly total sunshine hours (MSH), mean temperature difference (MTD), rain day (RD) and average temperature distance (ATD), but the effect of meteorological factors might differ in various climate types. Conclusions: Spatial panel data models are useful and effective when longitudinal data are available and spatial autocorrelation exists. Our findings showed that meteorological factors were related to the occurrence of HFMD, which were also affected by climate type.
KW - Climate type
KW - Hand, foot and mouth disease
KW - Meteorological factors
KW - Spatial panel data model
UR - http://www.scopus.com/inward/record.url?scp=84973338754&partnerID=8YFLogxK
U2 - 10.1186/s12879-016-1560-9
DO - 10.1186/s12879-016-1560-9
M3 - Article
C2 - 27230283
AN - SCOPUS:84973338754
SN - 1471-2334
VL - 16
SP - 233
JO - BMC Infectious Diseases
JF - BMC Infectious Diseases
IS - 1
M1 - 233
ER -