The Association Between Protein Intake and the Prevalence of Frailty Among Community-Dwelling Lebanese Older Adults

Abstract

Nutrition and in particular protein intake are shown to be key determinants of frailty. Nevertheless, the current daily protein recommendation of 0.8 g/kilogram (kg) BW has been proven to be inefficient in providing the required needs of the older population, and intake of 1 g/kg BW of protein was demonstrated to be more representative of the needs of older adults. Thus, this cross-sectional study aimed at examining the association between frailty and protein intake among Lebanese community-dwelling older adults. Dietary intake was assessed using an FFQ based on which protein intake was calculated using the USDA food database and frailty was determined via Fried’s Frailty Phenotype. A convenience sample of a total of 112 community-dwelling, older-adults were recruited through word-of-mouth, interviewed face to face, and screened in some areas of Greater Beirut and Byblos. SPSS software was used to conduct bivariate analyses and logistic regressions that either had frail or non-robust as outcomes, and protein intake was either entered as a cutoff (0.8 and 1 g/kg BW/d) or by protein source (animal protein corrected for plant protein intake, and plant protein corrected for animal protein intake). All the regressions were corrected for gender, age, educational level, BMI, number of chronic diseases, polypharmacy, dietary supplements, GDS score, RUDAS score, and MeDi score. Sixteen (14.41%) participants were identified as being frail, and the total participants, only 19.82% (n=22) reached a protein intake ≥0.8 g/kg BW and 11.7% (n=13) had an intake ≥1g/kg BW. Nevertheless, no association was found between total protein intake and the prevalence of frailty in this population. Only plant protein was positively associated with frailty with 6.2% (95% CI= 0.6% - 12.1%) higher frailty prevalence. In conclusion, it is important to further study the association between frailty and protein intake, within a larger sample size, considering protein distribution and timing as well as total energy intake, other macronutrients, physical activity, and diet quality.