Determinants of Nutritional Risk among Community-Dwelling Older Adults with Social Support

Abstract

Background: It is well established that older adults are at risk for malnutrition due to several social and non-social determinants, namely physiological, psychosocial, dietary and environmental determinants. The progression to malnutrition is often insidious and undetected. Thus, nutritional assessment should consider a complex web of factors that can impact nutritional status (NS). The primary objective of this study was to assess the NS of older adults attending senior centres (SCs) and to identify its predictors. Methods: This cross-sectional study enrolled a sample of community-dwelling older adults in Lisbon. NS was assessed using Mini Nutritional Assessment (MNA®). Malnutrition or malnutrition risk (recategorised into a single group) was predicted using binary logistic regression models, considering those participants classified as having a normal NS as the reference group. Data were collected through face-to-face interviews and anthropometric indices were measured according to Isak procedures. Results: A sample of 337 older adults, with an average age of 78.4 years old (range 66–99), mostly women (n = 210; 62.3%), were enrolled. Older adults at risk of malnutrition accounted for 40.7% of the sample. Being older (OR = 1.045, CI 95% [1.003–1.089], p = 0.037), having a worse perception of health status (OR = 3.395, CI 95% [1.182–9.746], p = 0.023), having or having had depression (OR = 5.138, CI 95% [2.869–9.201], p < 0.001), and not having or having had respiratory tract problems (OR = 0.477, CI 95% [0.246–0.925], p = 0.028) were independent predictors of malnutrition or malnutrition risk. An intermediate time of SC attendance was associated with a lower probability of malnutrition or risk (OR = 0.367, CI 95% [0.191–0.705], p = 0.003). Conclusions: NS among older adults has a multifactorial aetiology, with a strongly social component and is related to health circumstances. Further research is needed to timely identify and understand nutritional risk among this population.