Abstract

Increasing total protein intake and a spread protein intake distribution are potential strategies to attenuate sarcopenia related loss of physical function and quality of life. The aim of this cross-sectional study was to investigate whether protein intake and protein intake distribution are associated with muscle strength, physical function and quality of life in community-dwelling elderly people with a wide range of physical activity. Dietary and physical activity data were obtained from two studies (N = 140, age 81 ± 6, 64% male), with the following outcome measures: physical functioning (Short Physical Performance Battery (SPPB), comprising balance, gait speed and chair rise tests), handgrip strength and quality of life (EQ-5D-5L). Protein intake distribution was calculated for each participant as a coefficient of variance (CV = SD of grams of protein intake per main meal divided by the average total amount of proteins (grams) of the main meals). Based on the CV, participants were divided into tertiles and classified as spread, intermediate or pulse. The average total protein intake was 1.08 ± 0.29 g/kg/day. Total protein intake was not associated with outcome measures using multivariate regression analyses. Individuals with a spread protein diet during the main meals (CV < 0.43) had higher gait speed compared to those with an intermediate diet (CV 0.43–0.62) (β = −0.42, p = 0.035), whereas a spread and pulse protein diet were not associated with SPPB total score, chair rise, grip strength and Quality-Adjusted Life Year (QALY). The interaction of higher physical activity and higher total protein intake was significantly associated with higher quality of life (β = 0.71, p = 0.049). While this interaction was not associated with SPPB or grip strength, the association with quality of life emphasizes the need for a higher total protein intake together with an active lifestyle in the elderly.

Highlights

  • Sarcopenia is defined as the age-related loss of muscle mass and muscle strength, resulting in impaired physical function [1] and loss of independence for daily life activities [2], which is associatedNutrients 2018, 10, 506; doi:10.3390/nu10040506 www.mdpi.com/journal/nutrientsNutrients 2018, 10, 506 with a decreased quality of life and an increased health care expenditure [3,4]

  • Protein intake distribution was calculated for each participant as a coefficient of variance (CV = SD of grams of protein intake per main meal divided by the average total amount of proteins of the main meals)

  • Total physical activity was estimated at 8.4 METhr/day (IQR: 5.1–13.7), with most of the activities performed during leisure time, followed by household activities and sport activities (Table 1)

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Summary

Introduction

Sarcopenia is defined as the age-related loss of muscle mass and muscle strength, resulting in impaired physical function [1] and loss of independence for daily life activities [2], which is associatedNutrients 2018, 10, 506; doi:10.3390/nu10040506 www.mdpi.com/journal/nutrientsNutrients 2018, 10, 506 with a decreased quality of life and an increased health care expenditure [3,4]. Based on the age-related decline in protein utilization for muscle protein synthesis [7,8,9], Bauer et al proposed a protein intake for the elderly of 1.0–1.2 g protein per kilogram body weight per day (g/kg/day) [6], a dose which is well above the current recommendations of 0.8 g/kg/day for all adults [10,11]. Some studies support a pulse-feeding pattern in which a high protein meal might saturate the splanchnic sequestration leading to a higher availability of amino acids for muscle protein synthesis [12,13]. Participants were stratified into two groups based on protein intake with a cut-off 1.0 g/kg/day and differences between these groups were tested with an independent samples t-test for parametric variables, Kruskal-Wallis test for non-parametric variables, or Chi-square test for categorical data. Differences between tertiles were tested using an ANOVA for parametric variables, a Kruskal-Wallis test for non-parametric variables and a Chi-square test for categorical data

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