title: Utilization of primary and secondary medical care among disadvantaged populations: a log-linear model analysis.
abstract: OBJECTIVE
  We examined how, where an overall population is covered by universal health insurance, characteristics of disadvantaged populations interact to influence inequality in primary and secondary medical care utilization.
  
  
  METHODS
  Disadvantaged populations, the focus of the study, were defined as populations who have lower socio-economic status (SES), who are elderly and/or reside in a peripheral area. Data from the 2009 Israeli National Health Survey were analysed using log-linear models to estimate utilization of medical care.
  
  
  RESULTS
  The main findings were: a) pro-poor utilization of primary medical care among elderly populations, with higher odds ratios for low SES populations in the periphery; (b) lack of interaction between SES and primary medical care utilization among younger populations, between SES and secondary medical care utilization among the elderly and pro-rich utilization of secondary medical care among younger populations who did not regularly visit general practitioners (GP); (c) the odds ratios of secondary medical care utilization increased as SES decreased for both elderly and younger populations who also regularly visited a GP.
  
  
  CONCLUSIONS
  Potential policy implications for disadvantaged populations, regarding possible inequality in primary and secondary medical care utilization, can be drawn using log-linear model analysis of interactions among characteristics (SES, age, location) of disadvantaged populations.
authors.affiliation: The Open University of Israel, Raanana, Israel; Faculty of Exact Sciences, Tel-Aviv University, Tel-Aviv, Israel. gregoryyd@gmail.com.
authors.forename: Gregory Yom
authors.initials: GY
authors.lastname: Din
authors.forename: Zinaida
authors.initials: Z
authors.lastname: Zugman
authors.forename: Alla
authors.initials: A
authors.lastname: Khashper
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D005260:Female; D006306:Health Surveys; D054625:Healthcare Disparities / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007557:Israel; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D011320:Primary Health Care / Q000706:statistics & numerical data*; D063127:Secondary Health Care / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D019472:Universal Health Insurance; D035862:Vulnerable Populations / Q000706:statistics & numerical data*; D055815:Young Adult