Indirect Nutrition and Mobility Risks during Hospitalization: An Architectural Perspective on the nutritionDay Study Findings

Nutrients. 2023 Mar 22;15(6):1527. doi: 10.3390/nu15061527.

Abstract

Nutrition and mobility risks include complex and interrelated physiological, medical, and social factors. A growing body of evidence demonstrates that the built environment can affect patients' well-being and recovery. Nevertheless, the relationship between the built environment, nutrition, and mobility in general hospitals is largely unexplored. This study examines the implications of the nutritionDay study's results for the architectural design of hospital wards and nutrition environments. This one-day annual cross-sectional study uses online questionnaires in 31 different languages to collect ward-specific and patient-specific variables. The main findings relevant to the design of hospital wards were: (1) 61.5% of patients (n = 48,700) could walk before hospitalization and (2) this number dropped to 56.8% on nutritionDay (p < 0.0001), while the number of bedridden patients increased from 6.5% to 11.5% (p < 0.0001), (3) patients who needed more assistance had a much longer mean LOS than mobile patients, (4) mobility was associated with changes in eating, and (5) 72% of units (n = 2793) offered additional meals or snacks, but only 30% promoted a positive eating environment. The built environment may indirectly affect hospitalized patients' mobility, independence, and nutritional intake. Possible future study directions are suggested to further investigate this relationship.

Keywords: architectural design; built environment; hospital; hospital ward; hospitalized patients; mobility; nutrition; nutritionDay; risk.

MeSH terms

  • Cross-Sectional Studies
  • Hospitalization
  • Humans
  • Malnutrition*
  • Nutritional Status
  • Surveys and Questionnaires

Grants and funding

The nutritionDay project is funded by the European Society for Clinical Nutrition and Metabolism (ESPEN) with an annual grant to the Center of Medical Data Science of Medical University Vienna. The actual analysis did not receive any external funding.