Baser, O.; Baser, E.; Samayoa, G. Relationship between Body Mass Index and Diagnosis of Overweight or Obesity in Veterans Administration Population. Healthcare2023, 11, 1529.
Baser, O.; Baser, E.; Samayoa, G. Relationship between Body Mass Index and Diagnosis of Overweight or Obesity in Veterans Administration Population. Healthcare 2023, 11, 1529.
Baser, O.; Baser, E.; Samayoa, G. Relationship between Body Mass Index and Diagnosis of Overweight or Obesity in Veterans Administration Population. Healthcare2023, 11, 1529.
Baser, O.; Baser, E.; Samayoa, G. Relationship between Body Mass Index and Diagnosis of Overweight or Obesity in Veterans Administration Population. Healthcare 2023, 11, 1529.
Abstract
Background: This paper examined the gap between obesity and its diagnosis for cohorts of patients with overweight, obesity, and morbid obesity in the Veterans Administration (VA) population. Using the risk adjustment models, it also identified factors associated with the underdiagnosis of obesity.
Methods: Analysis was performed on a VA data set. We identified diagnosed patients and undiag-nosed patients (identified through BMI but not diagnosed by ICD-10 codes). The groups’ de-mographics were compared using nonparametric chi-square tests. We used logistic regression analysis to predict the likelihood of the omission of diagnosis.
Results: Of the 2,900,067 veterans with excess weight, 46% were overweight, 46% had obesity, and 8% of them had morbid obesity. The overweight patients were the most underdiagnosed (96%), followed by the obese (75%) and morbidly obese cohorts (69%). Older, male, and White patients were more likely to be undiagnosed as overweight and obese; younger males were more likely to be undiagnosed as morbidly obese. (p<.05) Comorbidities significantly contributed to diagnosis.
Conclusion: Underdiagnosis of obesity continues to be a significant problem despite its prevalence. Diagnosing obesity accurately is necessary to provide effective management and treatment.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
