Distribution of comorbidities as primary diagnoses by obesity class among patients in a large US paediatric healthcare system.
Brandon M NussbaumMatthew Sunil MathewFolefac AtemSarah E BarlowOlga T GuptaSarah E MessiahPublished in: Clinical obesity (2021)
There is little documentation of the distribution of specific health conditions across obesity classes (I, II, III), especially for paediatric populations who are seen for routine care in large United States US healthcare systems. The aim of this study was to assess the odds of presenting ≥2 obesity-related comorbidities as well as assess the overall distribution of these co-morbidities in children by class I/II/III obesity status controlling for key sociodemographic characteristics. This retrospective (2015-2019) electronic health record review analysed 49 276 patients from the Children's Health System of Texas diagnosed with obesity-related health conditions by obesity status (no obesity, class I, II, III). Crude and adjusted logistic regression models examined the association between obesity class and the likelihood of ≥2 comorbidities as primary diagnoses. Patients with class I obesity were 22% more likely (OR 1.22, 95% CI, 1.16, 1.27), patients with class II obesity were almost 50% more likely (OR 1.44, 95% CI, 1.35, 1.53) and those with class III obesity twice as likely (OR 2.04, 95% CI 1.91, 2.18) to be diagnosed with ≥2 comorbidities as primary diagnoses, compared with patients classified with no obesity. Children with obesity, particularly severe obesity, should be monitored closely by paediatricians for possible diagnoses of risk factors that could lead to adult chronic disease.
Keyphrases
- insulin resistance
- metabolic syndrome
- weight loss
- type diabetes
- high fat diet induced
- weight gain
- healthcare
- risk factors
- public health
- adipose tissue
- electronic health record
- newly diagnosed
- intensive care unit
- mental health
- skeletal muscle
- young adults
- body mass index
- palliative care
- end stage renal disease
- risk assessment
- social media
- peritoneal dialysis
- health insurance
- cross sectional
- clinical practice
- clinical decision support
- human health
- patient reported