title: Analyzing disparity trends for health care insurance coverage among non-elderly adults in the US: evidence from the Behavioral Risk Factor Surveillance System, 1993-2009.
abstract: OBJECTIVE
  To explore the changing disparities in access to health care insurance in the United States using time-varying coefficient models.
  
  
  METHODS
  Secondary data from the Behavioral Risk Factor Surveillance System (BRFSS) from 1993 to 2009 was used.
  
  
  METHODS
  A time-varying coefficient model was constructed using a binary outcome of no enrollment in health insurance plan versus enrolled. The independent variables included age, sex, education, income, work status, race, and number of health conditions. Smooth functions of odds ratios and time were used to produce odds ratio plots.
  
  
  RESULTS
  Significant time-varying coefficients were found for all the independent variables with the odds ratio plots showing changing trends except for a constant line for the categories of male, student, and having three health conditions. Some categories showed decreasing disparities, such as the income categories. However, some categories had increasing disparities in health insurance enrollment such as the education and race categories.
  
  
  CONCLUSIONS
  As the Affordable Care Act is being gradually implemented, studies are needed to provide baseline information about disparities in access to health insurance, in order to gauge any changes in health insurance access. The use of time-varying coefficient models with BRFSS data can be useful in accomplishing this task.
authors.affiliation: Demographic and Health Surveys Program, ICF International, Rockville, MD, USA.
authors.forename: Shireen
authors.initials: S
authors.lastname: Assaf
authors.affiliation: Department of Economics, Ca' Foscari University of Venice, Venice, Italy.
authors.forename: Stefano
authors.initials: S
authors.lastname: Campostrini
authors.affiliation: Department of Economics and Management, University of Pavia, Via San Felice, 5, 27100, Pavia, Italy. cinzia.dinovi@unipv.it.|Health, Econometrics and Data Group, University of York (UK). LCSR, National Research University Higher School of Economics, Russian Federation, Moscow, Russia. cinzia.dinovi@unipv.it.
authors.forename: Cinzia
authors.initials: C
authors.lastname: Di Novi
authors.affiliation: Northrop Grumman Corporation, Atlanta, GA, USA.
authors.forename: Fang
authors.initials: F
authors.lastname: Xu
authors.affiliation: Department of Biostatistics and Bioinformatics, Rollins School of Public Health Emory University, Atlanta, USA.
authors.forename: Carol
authors.initials: C
authors.lastname: Gotway Crawford
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D040343:Behavioral Risk Factor Surveillance System; D005260:Female; D006304:Health Status; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data*; D007348:Insurance, Health / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D058991:Patient Protection and Affordable Care Act / Q000331:legislation & jurisprudence*; D017678:Sex Distribution; D012959:Socioeconomic Factors; D014481:United States; D055815:Young Adult
keywords: Disparities; Health insurance; Health surveillance data; P-splines; Temporal trends; Varying coefficient model