title: [Identifying Factors Associated with Visits to Doctors using a Multilevel Zero-inflated Poisson Model].
abstract: OBJECTIVE
  To determine factors influencing patient visits to doctors using a multilevel zero-inflated Poisson model with count data with excessive zero.
  
  
  METHODS
  The data in relation to rural health services collected in Sichuan Province as part of the Fifth National Health Service Survey (2013) were used in this study. A multilevel random intercept zero-inflated Poisson model was established to identify factors associated with visits to doctors in two weeks.
  
  
  RESULTS
  The logistic regression showed that gender, age and presence of chronic diseases were the main factors associated with the likelihood of visiting doctors in two weeks. The Poisson regression revealed that travel time to the nearest medical facility, ethnicity, marital status and educational attainment were associated with numbers of visits to doctors in two weeks.
  
  
  CONCLUSIONS
  Rural residents with a high level of education, unmarried, and living close to medical facility are more likely to visit doctors than others. The multilevel zero-inflated Poisson model can be used for analyzing data with zero extra.
authors.forename: Di
authors.initials: D
authors.lastname: Li
authors.forename: Hua-ying
authors.initials: HY
authors.lastname: Xiong
authors.forename: Ting
authors.initials: T
authors.lastname: Dong
authors.forename: Jun-yang
authors.initials: JY
authors.lastname: Liu
authors.forename: Ju-ying
authors.initials: JY
authors.lastname: Zhang
mesh_terms: D000367:Age Factors; D002681:China; D002908:Chronic Disease; D006801:Humans; D016015:Logistic Models; D009819:Office Visits / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012424:Rural Population; D012737:Sex Factors