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Prevalence and recognition of obesity and its associated comorbidities: cross-sectional analysis of electronic health record data from a large US integrated health system.
Pantalone, Kevin M; Hobbs, Todd M; Chagin, Kevin M; Kong, Sheldon X; Wells, Brian J; Kattan, Michael W; Bouchard, Jonathan; Sakurada, Brian; Milinovich, Alex; Weng, Wayne; Bauman, Janine; Misra-Hebert, Anita D; Zimmerman, Robert S; Burguera, Bartolome.
  • Pantalone KM; Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, Ohio, USA.
  • Hobbs TM; Diabetes, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
  • Chagin KM; Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
  • Kong SX; Health Economics and Outcomes Research, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
  • Wells BJ; Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
  • Kattan MW; Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
  • Bouchard J; Health Economics and Outcomes Research, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
  • Sakurada B; Medical Affairs, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
  • Milinovich A; Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
  • Weng W; Health Economics and Outcomes Research, Novo Nordisk Inc., Plainsboro, New Jersey, USA.
  • Bauman J; Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
  • Misra-Hebert AD; Medicine Institute, Cleveland Clinic, Cleveland, Ohio, USA.
  • Zimmerman RS; Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, Ohio, USA.
  • Burguera B; Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, Ohio, USA.
BMJ Open ; 7(11): e017583, 2017 Nov 16.
Article en En | MEDLINE | ID: mdl-29150468
ABSTRACT

OBJECTIVE:

To determine the prevalence of obesity and its related comorbidities among patients being actively managed at a US academic medical centre, and to examine the frequency of a formal diagnosis of obesity, via International Classification of Diseases, Ninth Revision (ICD-9) documentation among patients with body mass index (BMI) ≥30 kg/m2.

DESIGN:

The electronic health record system at Cleveland Clinic was used to create a cross-sectional summary of actively managed patients meeting minimum primary care physician visit frequency requirements. Eligible patients were stratified by BMI categories, based on most recent weight and median of all recorded heights obtained on or before the index date of 1July 2015. Relationships between patient characteristics and BMI categories were tested.

SETTING:

A large US integrated health system.

RESULTS:

A total of 324 199 active patients with a recorded BMI were identified. There were 121 287 (37.4%) patients found to be overweight (BMI ≥25 and <29.9), 75 199 (23.2%) had BMI 30-34.9, 34 152 (10.5%) had BMI 35-39.9 and 25 137 (7.8%) had BMI ≥40. There was a higher prevalence of type 2 diabetes, pre-diabetes, hypertension and cardiovascular disease (P value<0.0001) within higher BMI compared with lower BMI categories. In patients with a BMI >30 (n=134 488), only 48% (64 056) had documentation of an obesity ICD-9 code. In those patients with a BMI >40, only 75% had an obesity ICD-9 code.

CONCLUSIONS:

This cross-sectional summary from a large US integrated health system found that three out of every four patients had overweight or obesity based on BMI. Patients within higher BMI categories had a higher prevalence of comorbidities. Less than half of patients who were identified as having obesity according to BMI received a formal diagnosis via ICD-9 documentation. The disease of obesity is very prevalent yet underdiagnosed in our clinics. The under diagnosing of obesity may serve as an important barrier to treatment initiation.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Índice de Masa Corporal / Registros Electrónicos de Salud / Obesidad Tipo de estudio: Clinical_trials / Observational_studies / Prevalence_studies / Prognostic_studies Límite: Adult / Humans / Male / Middle aged Idioma: En Año: 2017 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Índice de Masa Corporal / Registros Electrónicos de Salud / Obesidad Tipo de estudio: Clinical_trials / Observational_studies / Prevalence_studies / Prognostic_studies Límite: Adult / Humans / Male / Middle aged Idioma: En Año: 2017 Tipo del documento: Article