title: Multistate analysis of factors associated with intimate partner violence.
abstract: BACKGROUND
  Reports on prevalence estimates and risk factors of intimate partner violence (IPV) are limited in that they (1) focus on specific subgroup populations that are not representative of all women or (2) involve long questionnaires that are not useful as surveillance tools.
  
  
  OBJECTIVE
  To report prevalence estimates and identify demographic and lifestyle factors associated with IPV in a large population-based sample of U.S. women using surveillance data.
  
  
  METHODS
  Behavioral Risk Factor Surveillance System (BRFSS) data from eight U.S. states were analyzed individually and as a pooled sample (N=18,415). Multivariate logistic regression models were used to examine associations between IPV and the factors of interest.
  
  
  RESULTS
  Factors consistently associated with IPV across the majority of states and in the pooled analysis included young age (pooled adjusted odds ratio [aOR], 3.07), single marital status (pooled aOR, 2.89), divorced/separated marital status (pooled aOR, 4.67), and annual household income <$25,000 (pooled aOR, 1.89). In addition, lack of health insurance, receipt of Medicaid, cigarette smoking, presence of children in the home, self-reported fair/poor health, and frequent mental distress were associated with IPV after adjustment for covariates.
  
  
  CONCLUSIONS
  This study provides population-based estimates of IPV prevalence and factors associated with IPV using surveillance data. By pooling BRFSS data from individual states, the resulting large sample has adequate power to detect significant associations and has increased precision in the estimates of IPV risk. In addition, this study identifies high-risk populations to target for education and intervention programs and demonstrates the need for improved IPV surveillance.
authors.affiliation: Saint Louis University School of Public Health, Department of Community Health, St. Louis, Missouri 63104-1314, USA.
authors.forename: Joshua R
authors.initials: JR
authors.lastname: Vest
authors.forename: Tegan K
authors.initials: TK
authors.lastname: Catlin
authors.forename: John J
authors.initials: JJ
authors.lastname: Chen
authors.forename: Ross C
authors.initials: RC
authors.lastname: Brownson
mesh_terms: D000293:Adolescent; D000328:Adult; D018585:Battered Women / Q000193:education / Q000523:psychology / Q000706:statistics & numerical data; D040343:Behavioral Risk Factor Surveillance System; D017579:Domestic Violence / Q000208:ethnology / Q000523:psychology / Q000706:statistics & numerical data; D005260:Female; D006306:Health Surveys; D006801:Humans; D016015:Logistic Models; D017533:Marital Status / Q000208:ethnology / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D011159:Population Surveillance / Q000379:methods; D015995:Prevalence; D044469:Racial Groups; D012307:Risk Factors; D012725:Sexual Behavior / Q000523:psychology / Q000706:statistics & numerical data; D012747:Sexual Partners / Q000523:psychology; D012959:Socioeconomic Factors; D013179:Spouse Abuse / Q000208:ethnology / Q000523:psychology / Q000706:statistics & numerical data; D018454:Spouses / Q000193:education / Q000208:ethnology / Q000523:psychology / Q000706:statistics & numerical data; D011795:Surveys and Questionnaires; D014481:United States / Q000453:epidemiology; D014754:Violence / Q000208:ethnology / Q000523:psychology / Q000706:statistics & numerical data*