title: Association between individual and geographic factors and nonadherence to mammography screening guidelines.
abstract: BACKGROUND
  This study investigates factors that are associated with nonadherence to mammography screening guidelines in Utah, a state where mammography screening rates have remained consistently lower than national averages.
  
  
  METHODS
  We examined data on reported mammography use among women aged 40-74 years from the 2008 and 2010 Utah Behavioral Risk Factor Surveillance System (n=5,197, weighted n=417,064). Logistic regression models were used to estimate the effects of individual-level and geographic (travel time to nearest mammography facility, geographic accessibility, and rural/urban residence) factors on the odds of a woman not reporting receiving a mammogram in the last 2 years.
  
  
  RESULTS
  In 2008 and 2010, a disproportionate number of women aged 40-49 (43.1%, 95% confidence interval [CI] 39.9%-46.3%) reported not receiving a mammogram within the last 2 years compared to women 50-74 (26.8%, 95% CI 24.9%-28.7%). None of the geographic factors were significant predictors of screening adherence. Based on covariate adjusted models, statistically significant (p<0.05) factors associated with increased odds of not receiving mammogram within the last 2 years included not having a regular physician, no health insurance, being aged 40-49, income less than $25,000, and the presence of three or more children in the home.
  
  
  CONCLUSIONS
  Mammography screening efforts in Utah should focus on improving access to insurance or a regular source of health care. Future research should also consider how best to address extreme time demands and competing priorities that present potential barriers for women with large families, resulting in lower screening levels among these women.
authors.affiliation: 1 Department of Epidemiology and the Rutgers Cancer Institute of New Jersey, Rutgers School of Public Health, Rutgers University , New Brunswick, New Jersey.
authors.forename: Kevin A
authors.initials: KA
authors.lastname: Henry
authors.forename: Kaila
authors.initials: K
authors.lastname: McDonald
authors.forename: Recinda
authors.initials: R
authors.lastname: Sherman
authors.forename: Anita Y
authors.initials: AY
authors.lastname: Kinney
authors.forename: Antoinette M
authors.initials: AM
authors.lastname: Stroup
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001294:Attitude to Health; D040343:Behavioral Risk Factor Surveillance System; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000453:epidemiology / Q000517:prevention & control; D055088:Early Detection of Cancer; D005260:Female; D019538:Health Care Surveys; D006297:Health Services Accessibility; D006801:Humans; D019458:Insurance Coverage; D007348:Insurance, Health; D016015:Logistic Models; D008327:Mammography / Q000706:statistics & numerical data*; D008403:Mass Screening / Q000706:statistics & numerical data*; D008875:Middle Aged; D010342:Patient Acceptance of Health Care; D012111:Residence Characteristics; D012424:Rural Population; D012959:Socioeconomic Factors; D014505:Urban Population; D014589:Utah / Q000453:epidemiology; D055815:Young Adult