title: Spatial analysis of gender variation in the prevalence of hypertension among the middle-aged and elderly population in Zhejiang Province, China.
abstract: Previous studies have shown that there may be gender disparities in the prevalence of hypertension; however, these studies do not address the spatial information contained in the sample which may limit the analytical results. Our study extends the existing Shared Component Model (SCM) and compares its utility with a logistic regression model to evaluate the significance of spatial information for identifying risk factors for hypertension and other non-rare diseases.
  
  
  
  A total of 1267 residents aged 45 years of age and over were included in our study, of which 48.1 % were males. The overall prevalence of hypertension was 33.2 %, with females experiencing a higher prevalence than males (35.5 % vs. 30.6 %). The research variables included body mass index (BMI), Waist -to-Height Ratio (WHtR), smoking status, alcohol consumption etc. The extended SCM is employed to investigate regional gender variations in the risk of hypertension and assess the gender variation in the middle-aged and elderly populations of Zhejiang Province in eastern China and then its performance is compared with that of a traditional multiple logistic regression model.
  
  
  
  Our SCM analysis determined that the spatial pattern of hypertension risk for the middle-aged and elderly populations of Zhejiang Province in eastern China is quite different for males and females. Furthermore, Waist -to-Height Ratio (WHtR) continues to be a simple and effective predictor of hypertension risk for males at the regional level.
  
  
  
  We believe that the extended SCM spatial model is a useful tool for identifying risk factors at the regional level.
authors.affiliation: Department of Statistics, School of Economics and Trade, Guangdong University of ForeignStudies, Guangzhou, 510006, Peoples Republic of China.
authors.forename: Li
authors.initials: L
authors.lastname: Xu
authors.affiliation: Division of Biostatistics, University of Texas Health Science Center at Houston (UTHealth), School of Public Health, Houston, Texas, 77030, USA.
authors.forename: Dejian
authors.initials: D
authors.lastname: Lai
authors.affiliation: State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Key Laboratory of Health Technology Assessment of Fujian Province University, School of Public Health, Xiamen University, Xiamen, 361102, Peoples Republic of China. fangya@xmu.edu.cn.
authors.forename: Ya
authors.initials: Y
authors.lastname: Fang
mesh_terms: D000368:Aged; D002681:China / Q000453:epidemiology; D005260:Female; D006299:Health Services for the Aged; D006801:Humans; D006973:Hypertension / Q000453:epidemiology* / Q000209:etiology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D012307:Risk Factors; D012737:Sex Factors; D062206:Spatial Analysis
keywords: Gender variation; Hypertension; Middle-aged and elderly; Shared Component Model (SCM); Spatial analysis