title: Using Electronic Health Records to Examine Disease Risk in Small Populations: Obesity Among American Indian Children, Wisconsin, 2007-2012.
abstract: BACKGROUND
  Tribe-based or reservation-based data consistently show disproportionately high obesity rates among American Indian children, but little is known about the approximately 75% of American Indian children living off-reservation. We examined obesity among American Indian children seeking care off-reservation by using a database of de-identified electronic health records linked to community-level census variables.
  
  
  METHODS
  Data from electronic health records from American Indian children and a reference sample of non-Hispanic white children collected from 2007 through 2012 were abstracted to determine obesity prevalence. Related community-level and individual-level risk factors (eg, economic hardship, demographics) were examined using logistic regression.
  
  
  RESULTS
  The obesity rate for American Indian children (n = 1,482) was double the rate among non-Hispanic white children (n = 81,042) (20.0% vs 10.6%, P < .001). American Indian children were less likely to have had a well-child visit (55.9% vs 67.1%, P < .001) during which body mass index (BMI) was measured, which may partially explain why BMI was more likely to be missing from American Indian records (18.3% vs 14.6%, P < .001). Logistic regression demonstrated significantly increased obesity risk among American Indian children (odds ratio, 1.8; 95% confidence interval, 1.6-2.1) independent of age, sex, economic hardship, insurance status, and geographic designation.
  
  
  CONCLUSIONS
  An electronic health record data set demonstrated high obesity rates for nonreservation-based American Indian children, rates that had not been previously assessed. This low-cost method may be used for assessing health risk for other understudied populations and to plan and evaluate targeted interventions.
authors.affiliation: University of Wisconsin, College of Agricultural and Life Sciences, Department of Nutritional Sciences, Madison, Wisconsin.
authors.forename: Emily J
authors.initials: EJ
authors.lastname: Tomayko
authors.affiliation: University of Wisconsin, School of Medicine and Public Health, Department of Pediatrics and Department of Family Medicine and Community Health, Madison, Wisconsin.
authors.forename: Bethany A
authors.initials: BA
authors.lastname: Weinert
authors.affiliation: UW Health, Madison, Wisconsin.
authors.forename: Liz
authors.initials: L
authors.lastname: Godfrey
authors.affiliation: University of Wisconsin, School of Medicine and Public Health, Department of Family Medicine and Community Health, Madison, Wisconsin.
authors.forename: Alexandra K
authors.initials: AK
authors.lastname: Adams
authors.affiliation: University of Wisconsin, School of Medicine and Public Health, Department of Family Medicine and Community Health, 1100 Delaplaine Ct, Madison, WI 53715. Email: larry.hanrahan@fammed.wisc.edu.
authors.forename: Lawrence P
authors.initials: LP
authors.lastname: Hanrahan
mesh_terms: D000293:Adolescent; D015992:Body Mass Index; D001835:Body Weight; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007198:Indians, North American; D008297:Male; D063766:Pediatric Obesity / Q000208:ethnology*; D011203:Poverty; D012111:Residence Characteristics; D012307:Risk Factors; D014922:Wisconsin / Q000208:ethnology