Using Electronic Health Records to Examine Disease Risk in Small Populations: Obesity Among American Indian Children, Wisconsin, 2007-2012.

Emily J Tomayko, Bethany A Weinert, Liz Godfrey, Alexandra K Adams, Lawrence P Hanrahan
Author Information
  1. Emily J Tomayko: University of Wisconsin, College of Agricultural and Life Sciences, Department of Nutritional Sciences, Madison, Wisconsin.
  2. Bethany A Weinert: University of Wisconsin, School of Medicine and Public Health, Department of Pediatrics and Department of Family Medicine and Community Health, Madison, Wisconsin.
  3. Liz Godfrey: UW Health, Madison, Wisconsin.
  4. Alexandra K Adams: University of Wisconsin, School of Medicine and Public Health, Department of Family Medicine and Community Health, Madison, Wisconsin.
  5. Lawrence P Hanrahan: 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.

Abstract

INTRODUCTION: 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.
CONCLUSION: 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.

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Grants

  1. UL1 TR000427/NCATS NIH HHS
  2. T32HP10010/PHS HHS
  3. UL1TR000427/NCATS NIH HHS
  4. 5T32DK007665/NIDDK NIH HHS
  5. T32 DK007665/NIDDK NIH HHS

MeSH Term

Adolescent
Body Mass Index
Body Weight
Child
Child, Preschool
Databases, Factual
Electronic Health Records
Female
Humans
Indians, North American
Male
Pediatric Obesity
Poverty
Residence Characteristics
Risk Factors
Wisconsin

Word Cloud

Created with Highcharts 10.0.0AmericanIndianchildrenobesityamonghealth1rateselectronicrecordsriskvsP<001datahighoff-reservationexaminedusingcommunity-levelnon-Hispanicwhiteeconomichardshipregressionraten=6%likelyBMImaydemonstratedINTRODUCTION:Tribe-basedreservation-basedconsistentlyshowdisproportionatelylittleknownapproximately75%livingseekingcaredatabasede-identifiedlinkedcensusvariablesMETHODS:Datareferencesamplecollected20072012abstracteddetermineprevalenceRelatedindividual-levelfactorsegdemographicslogisticRESULTS:482double81042200%10lesswell-childvisit559%671%bodymassindexmeasuredpartiallyexplainmissing183%14Logisticsignificantlyincreasedoddsratio895%confidenceinterval6-2independentagesexinsurancestatusgeographicdesignationCONCLUSION:recordsetnonreservation-basedpreviouslyassessedlow-costmethodusedassessingunderstudiedpopulationsplanevaluatetargetedinterventionsUsingElectronicHealthRecordsExamineDiseaseRiskSmallPopulations:ObesityAmongChildrenWisconsin2007-2012

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