Protein Intake among Community-Dwelling Older Adults: The Influence of (Pre-) Motivational Determinants

• Published in: Nutrients Vol. 14; no. 2; p. 293
• Main Authors: Verwijs, Marije H, Haveman-Nies, Annemien, Borkent, Jos W, Linschooten, Joost O, Roodenburg, Annet J C, de Groot, Lisette C P G M, de van der Schueren, Marian A E
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 11.01.2022; MDPI
• Subjects: Adults; Aged; Aged, 80 and over; Aging; Behavior; Body weight; Cross-Sectional Studies; diet; Diet - psychology; Diet - statistics & numerical data; Diet Surveys; Dietary Proteins - analysis; Eating - psychology; Female; Food; Humans; Independent Living; Influence; Knowledge; Likert scale; Male; Malnutrition; Motivation; Netherlands - epidemiology; Older people; Perceptions; Poisson Distribution; Population; Prevalence; Protein-Energy Malnutrition - epidemiology; Protein-Energy Malnutrition - psychology; Proteins; Questionnaires; Regression Analysis; Risk perception; Social interactions; Sociodemographics; Netherlands; aged; diet; behavior; proteins
• ISSN: 2072-6643; 2072-6643
• DOI: 10.3390/nu14020293

An adequate protein intake is important for healthy ageing, yet nearly 50% of Dutch community-dwelling older adults do not meet protein recommendations. This study explores protein intake in relation to eight behavioral determinants (I-Change model) among Dutch community-dwelling older adults. Data were collected through an online questionnaire from October 2019-October 2020. Protein intake was assessed by the Protein Screener 55+, indicating a high/low chance of a low protein intake (<1.0 g/kg body weight/day). The behavioral determinants of cognizance, knowledge, risk perception, perceived cues, attitude, social support, self-efficacy and intention were assessed by evaluating statements on a 7-point Likert scale. A total of 824 Dutch community-dwelling older adults were included, recruited via online newsletters, newspapers and by personal approach. Poisson regression was performed to calculate quartile-based prevalence ratios (PRs). Almost 40% of 824 respondents had a high chance of a low protein intake. Univariate analyses indicated that lower scores for all different behavioral determinants were associated with a higher chance of a low protein intake. Independent associations were observed for knowledge (Q4 OR = 0.71) and social support (Q4 OR = 0.71). Results of this study can be used in future interventions aiming to increase protein intake in which focus should lie on increasing knowledge and social support.