title: Utilization of infertility services: how much does money matter?
abstract: OBJECTIVE
  To estimate the effects of financial access and other individual characteristics on the likelihood that a woman pursues infertility treatment and the choice of treatment type.
  
  
  METHODS
  The 1995 National Survey of Family Growth.
  
  
  METHODS
  We use a binomial logit model to estimate the effects of financial access and individual characteristics on the likelihood that a woman pursues infertility treatment. We then use a multinomial logit model to estimate the differential effects of these variables across treatment types.
  
  
  METHODS
  This study analyzes the subset of 1,210 women who meet the definition of infertile or subfecund from the 1995 National Survey of Family Growth.
  
  
  RESULTS
  We find that income, insurance coverage, age, and parity (number of previous births) all significantly affect the probability of seeking infertility treatment; however, the effect of these variables on choice of treatment type varies significantly. Neither income nor insurance influences the probability of seeking advice, a relatively low cost, low yield treatment. At the other end of the spectrum, the choice to pursue assisted reproductive technologies (ARTs)-a much more expensive but potentially more productive option-is highly influenced by income, but merely having private insurance has no significant effect. In the middle of the spectrum are treatment options such as testing, surgery, and medications, for which "financial access" increases their probability of selection.
  
  
  CONCLUSIONS
  Our results illustrate that for the sample of infertile of subfecund women of childbearing age studied, and considering their options, financial access to infertility treatment does matter.
authors.affiliation: Department of Economics, University of the Pacific, Stockton, CA 95211, USA.
authors.forename: J
authors.initials: J
authors.lastname: Farley Ordovensky Staniec
authors.forename: Natalie J
authors.initials: NJ
authors.lastname: Webb
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000554:Ambulatory Care Facilities; D002755:Choice Behavior; D005260:Female; D017048:Health Care Costs; D019538:Health Care Surveys; D006297:Health Services Accessibility / Q000191:economics*; D006801:Humans; D007247:Infertility, Female / Q000191:economics* / Q000628:therapy; D019458:Insurance Coverage; D016015:Logistic Models; D015233:Models, Statistical; D010298:Parity; D010342:Patient Acceptance of Health Care / Q000523:psychology*; D011247:Pregnancy; D034121:Reproductive Health Services / Q000191:economics* / Q000706:statistics & numerical data*; D027724:Reproductive Techniques, Assisted / Q000706:statistics & numerical data; D014481:United States