title: Assessing spatial gaps in sexually transmissible infection services and morbidity: an illustration with Texas county-level data from 2007.
abstract: BACKGROUND
  In the United States, sexually transmissible infection (STI) and family planning (FP) clinics play a major role in the detection and treatment of STIs. However, an examination of the spatial distribution of these service sites and their association with STI morbidity and county-level socioeconomic characteristics is lacking. We demonstrate how mapping and regression methods can be used to assess the spatial gaps between STI services and morbidity.
  
  
  METHODS
  We used 2007 county-level surveillance data on chlamydia (Chlamydia trachomatis), gonorrhoea (Neisseria gonorrhoeae) and syphilis. The geocoded STI service (STI or FP clinic) locations overlaid on the Texas county-level chlamydia, gonorrhoea and syphilis morbidity map indicated that counties with high incidence had at least one STI service site. Logistic regression was used to examine the association between having STI services and county-level socioeconomic characteristics.
  
  
  RESULTS
  Twenty-two percent of chlamydia high-morbidity counties (>365 out of 100000); 32% of gonorrhoea high-morbidity counties (>136 out of 100000) and 23% of syphilis high-morbidity counties (≥4 out of 100000 and at least two cases) had no STI services. When we controlled for socioeconomic characteristics, high-morbidity syphilis was weakly associated with having STI services. The percent of the population aged 15-24 years, the percent of Hispanic population, the crime rate and population density were significantly (P<0.05) associated with having STI services.
  
  
  CONCLUSIONS
  Our results suggest that having an STI service was not associated with high morbidity. The methods used have demonstrated the utility of mapping to assess the spatial gaps that exist between STI services and demand.
authors.affiliation: Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA. Kowusuedusei@cdc.gov
authors.forename: Kwame
authors.initials: K
authors.lastname: Owusu-Edusei
authors.forename: Sonal R
authors.initials: SR
authors.lastname: Doshi
mesh_terms: D000293:Adolescent; D000554:Ambulatory Care Facilities / Q000706:statistics & numerical data*; D002690:Chlamydia Infections / Q000453:epidemiology / Q000517:prevention & control; D005193:Family Planning Services / Q000706:statistics & numerical data*; D005260:Female; D040362:Geographic Information Systems; D005843:Geography; D006069:Gonorrhea / Q000453:epidemiology / Q000517:prevention & control; D006301:Health Services Needs and Demand; D006801:Humans; D016015:Logistic Models; D008297:Male; D012749:Sexually Transmitted Diseases / Q000453:epidemiology* / Q000517:prevention & control*; D013587:Syphilis / Q000453:epidemiology / Q000517:prevention & control; D013781:Texas / Q000453:epidemiology; D055815:Young Adult