Background/purpose: For prevention of sarcopenia and functionaldecline in community-dwelling older adults, a higher daily proteinintake is needed. A new e-health strategy for dietary counselling wasused with the aim to increase total daily protein intake to optimallevels (minimal 1.2 g/kg/day, optimal 1.5 g/kg/day) through use ofregular food products.Methods: The VITAMIN (VITal Amsterdam older adults IN the city)RCT included 245 community-dwelling older adults (age ≥ 55y):control, exercise, and exercise plus dietary counselling (protein)group. The dietary counselling intervention was based on behaviourchange and personalization. Dietary intake was measured by a 3ddietary record at baseline, after 6-month intervention and 12-monthfollow-up. The primary outcome was average daily protein intake(g/kg/day). Sub-group analysis and secondary outcomes includeddaily protein distribution, sources, product groups. A Linear MixedModels (LMM) of repeated measures was performed with STATAv13.Results: Mean age of the 224 subjects was 72.0(6.5) years, a BMI of26.0(4.2). The LMM showed a significant effect of time and time*group(p<0.001). The dietary counselling group showed higher protein intakethan either control (1.41 vs 1.13 g/kg/day; β +0.32; p<0.001) or exercisegroup (1.41 vs 1.11 g/kg/day; β +0.33; p<0.001) after 6-month interventionand 12-month follow-up.Conclusions and implications: This study shows digitally supporteddietary counselling improves protein intake sufficiently in communitydwellingolder adults with use of regular food products. Protein intakeincrease by personalised counselling with e-health is a promising strategyfor dieticians.
Optimizing protein intake is a novel strategy to prevent age associated loss of muscle mass and strength in older adults. Such a strategy is still missing for older adults from ethnic minority populations. Protein intake in these populations is expected to be different in comparison to the majority of the population due to several socio-cultural factors. Therefore, the present study examined the dietary protein intake and underlying behavioral and environmental factors affecting protein intake among older adults from ethnic minorities in the Netherlands. We analyzed frequency questionnaire (FFQ) data from the Healthy Life in an Urban Setting (HELIUS) cohort using ANCOVA to describe dietary protein intake in older adults from ethnic minorities in the Netherlands (N = 1415, aged >55 years, African Surinamese, South Asian Surinamese, Moroccan, and Turkish). Additionally, we performed focus groups among older adults from the same ethnic minority populations (N = 69) to discover behavioral and environmental factors affecting protein intake; 40-60% of the subjects did not reach minimal dietary protein recommendations needed to maintain muscle mass (1.0 g/kg bodyweight per day (BW/day)), except for Turkish men (where it was 91%). The major sources of protein originated from animal products and were ethnic specific. Participants in the focus groups showed little knowledge and awareness about protein and its role in aging. The amount of dietary protein and irregular eating patterns seemed to be the major concern in these populations. Optimizing protein intake in these groups requires a culturally sensitive approach, which accounts for specific protein product types and sociocultural factors.
BACKGROUND & AIMS: Sufficient protein intake is of great importance in hemodialysis (HD) patients, especially for maintaining muscle mass. Daily protein needs are generally estimated using bodyweight (BW), in which individual differences in body composition are not accounted for. As body protein mass is best represented by fat free mass (FFM), there is a rationale to apply FFM instead of BW. The agreement between both estimations is unclear. Therefore, the aim of this study is to compare protein needs based on either FFM or BW in HD patients.METHODS: Protein needs were estimated in 115 HD patients by three different equations; FFM, BW and BW adjusted for low or high BMI. FFM was measured by multi-frequency bioelectrical impedance spectroscopy and considered the reference method. Estimations of FFM x 1.5 g/kg and FFM x 1.9 g/kg were compared with (adjusted)BW x 1.2 and x 1.5, respectively. Differences were assessed with repeated measures ANOVA and Bland-Altman plots.RESULTS: Mean protein needs estimated by (adjusted)BW were higher compared to those based on FFM, across all BMI categories (P < 0.01) and most explicitly in obese patients. In females with BMI >30, protein needs were 69 ± 17.4 g/day higher based on BW and 45 ± 9.3 g/day higher based on BMI adjusted BW, compared to FFM. In males with BMI >30, protein needs were 51 ± 20.4 g/day and 23 ± 20.9 g/day higher compared to FFM, respectively.CONCLUSIONS: Our data show large differences and possible overestimations of protein needs when comparing BW to FFM. We emphasize the importance of more research and discussion on this topic.
