An electronic medical records study of population obesity prevalence in El Paso, Texas.
BMC Med Inform Decis Mak
; 22(1): 46, 2022 02 22.
Article
em En
| MEDLINE
| ID: mdl-35193581
BACKGROUND: In this study, we determine the feasibility of using electronic medical record (EMR) data to determine obesity prevalence at the census tract level in El Paso County, Texas, located on the U.S.-Mexico border. METHODS: 2012-2018 Body Mass Index (BMI kg/m2) data from a large university clinic system in was geocoded and aggregated to a census tract level. After cleaning and removing duplicate EMR and unusable data, 143,524 patient records were successful geocoded. Maps were created to assess representativeness of EMR data across census tracts, within El Paso County. Additionally, maps were created to display the distribution of obesity across the same geography. RESULTS: EMR data represented all but one El Paso census tract. Representation ranged from 0.7% to 34.9%. Greatest representation were among census tracts in and around clinics. The mean EMR data BMI (kg/m2) was 30.1, this is approximately 6% less than the 36.0% estimated for El Paso County using the Behavioral Risk Factor Surveillance Study (BRFSS) estimate. At the census tract level, obesity prevalence ranged from 26.6 to 57.6%. The highest obesity prevalence were in areas that tended to be less affluent, with a higher concentration of immigrants, poverty and Latino ethnic concentration. CONCLUSIONS: EMR data use for obesity surveillance is feasible in El Paso County, Texas, a U.S.-Mexico border community. Findings indicate substantial obesity prevalence variation between census tracts within El Paso County that may be associated with population distributions related to socioeconomics.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Hispânico ou Latino
/
Registros Eletrônicos de Saúde
Tipo de estudo:
Prevalence_studies
/
Risk_factors_studies
Limite:
Humans
País/Região como assunto:
Mexico
Idioma:
En
Revista:
BMC Med Inform Decis Mak
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos