title: Geographic distribution of urologists throughout the United States using a county level approach.
abstract: OBJECTIVE
  The adequacy of the urologist work force in absolute numbers and relative distribution is unclear. To develop effective policies addressing the needs of an aging population we must better understand the urologist work force. We assessed the geographic distribution of urologists throughout the United States at the county level and determined the county characteristics associated with increased urologist density.
  
  
  METHODS
  County level data from the Department of Health and Human Services Area Resource File and the United States Census were analyzed in this ecological study. Logistic regression and ordinal logistic regression models were built to identify predictors of urologist density, defined as the number of urologists per 100,000 individuals. National patterns of urologist density were mapped graphically at the county level.
  
  
  RESULTS
  Overall 63% of the counties in the United States lack a urologist. Based on multivariate models urologists were less likely to be found in nonmetropolitan counties (OR 0.57, 95% CI 0.46-0.72) and rural counties (OR 0.03, 95% CI 0.02-0.06) than in metropolitan counties, which confirmed visually mapped models. Patterns of urologist density also appeared to be influenced by climate and county education levels rather than by traditional socioeconomic measures. Urologists younger than 45 years old were 3 times less likely to be located in nonmetropolitan and rural counties than their older counterparts.
  
  
  CONCLUSIONS
  The uneven distribution of urologists throughout the United States is likely to worsen as younger physicians continue to cluster in urban areas. Governing bodies must consider this distribution in their calls for increasing the number of training positions.
authors.affiliation: Department of Urology, Helen Diller Family Comprehensive Cancer Center, University of California-San Francisco, San Francisco, California 94143-1695, USA.
authors.forename: Anobel Y
authors.initials: AY
authors.lastname: Odisho
authors.forename: Vincent
authors.initials: V
authors.lastname: Fradet
authors.forename: Matthew R
authors.initials: MR
authors.lastname: Cooperberg
authors.forename: Ardalan E
authors.initials: AE
authors.lastname: Ahmad
authors.forename: Peter R
authors.initials: PR
authors.lastname: Carroll
mesh_terms: D000328:Adult; D002321:Career Choice; D016001:Confidence Intervals; D016208:Databases, Factual; D019538:Health Care Surveys; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D020380:Needs Assessment; D016017:Odds Ratio; D010820:Physicians / Q000600:supply & distribution*; D011336:Probability; D011365:Professional Practice Location / Q000706:statistics & numerical data*; D019035:Rural Health Services / Q000706:statistics & numerical data*; D014481:United States; D019037:Urban Health Services / Q000706:statistics & numerical data*; D014572:Urology; D000078329:Workforce