Exploring Overnutrition, Overweight, and Obesity in the Hospital Setting-A Point Prevalence Study.
Andrea ElliottSimone Jane GibsonJudith D BauerAnna CardamisZoe E DavidsonPublished in: Nutrients (2023)
Malnutrition is an international healthcare concern associated with poor patient outcomes, increased length of stay, and healthcare costs. Although malnutrition includes both under and overnutrition, there is a large body of evidence that describes the impacts of undernutrition with limited data on overnutrition in hospitalized patients. Obesity itself is a modifiable risk factor associated with hospital-associated complications. However, there is limited reporting of the prevalence of obesity in hospitals. This one-day cross-sectional study ( n = 513) captures the prevalence of both under and overnutrition in a hospitalized population and explores dietetic care provided compared to the Nutrition Care Process Model for hospitalized patients who have obesity. The main findings were: (1) the largest proportion of patients were in the overweight and obese classifications (57.3%, n = 294/513); 5.3% of these patients had severe obesity (class III); (2) patients who were overweight and obese had lower malnutrition risk profiles as well as the prevalence of malnutrition; (3) 24.1% of patients who had obesity ( n = 34/141) were receiving dietetic intervention; (4) 70.6% ( n = 24/34) did not have a nutrition diagnosis that followed the Nutrition Care Process Model. Study results provide valuable clinical insight into the prevalence of overnutrition and opportunities to improve nutrition care for this vulnerable patient group.
Keyphrases
- healthcare
- risk factors
- insulin resistance
- metabolic syndrome
- weight loss
- type diabetes
- high fat diet induced
- end stage renal disease
- palliative care
- weight gain
- physical activity
- newly diagnosed
- chronic kidney disease
- quality improvement
- prognostic factors
- ejection fraction
- randomized controlled trial
- pain management
- adipose tissue
- body mass index
- acute care
- affordable care act
- big data
- machine learning
- chronic pain
- artificial intelligence
- data analysis