Background: Intentional weight loss in obese older adults is a risk factor for muscle loss and sarcopenia.Objective: The objective was to examine the

As the population is aging rapidly, there is a strong increase in the number of individuals with chronic disease and physical limitations. The decrease in skeletal muscle mass and function (sarcopenia) and the increase in fat mass (obesity) are important contributors to the development of physical limitations, which aggravates the chronic diseases prognosis. The combination of the two conditions, which is referred to as sarcopenic obesity, amplifies the risk for these negative health outcomes, which demonstrates the importance of preventing or counteracting sarcopenic obesity. One of the main challenges is the preservation of the skeletal muscle mass and function, while simultaneously reducing the fat mass in this population. Exercise and nutrition are two key components in the development, as well as the prevention and treatment of sarcopenic obesity. The main aim of this narrative review is to summarize the different, both separate and combined, exercise and nutrition strategies so as to prevent and/or counteract sarcopenic obesity. This review therefore provides a current update of the various exercise and nutritional strategies to improve the contrasting body composition changes and physical functioning in sarcopenic obese individuals.

Intentional weight loss in obese older adults is a risk factor for accelerated muscle mass loss. We investigated whether a high protein diet and/or resistance exercise preserves fat free mass (FFM) during weight loss in overweight and obese older adults. We included 100 overweight and obese adults (55–80 year) in a randomized controlled trial (RCT) with a 2 × 2 factorial design and intention-to-treat analysis. During a 10-week weight loss program all subjects followed a hypocaloric diet. Subjects were randomly allocated to either a high protein (1.3 g/kg body weight) or normal protein diet (0.8 g/kg), with or without a resistance exercise program 3 times/week. FFM was assessed by air displacement plethysmography. At baseline, mean (±SD) BMI was 32 ± 4 kg/m2. During intervention, protein intake was 1.13 ± 0.35 g/kg in the high protein groups vs. 0.98 ± 0.29 in the normal protein groups, which reflects a 16.3 ± 5.2 g/d higher protein intake in the high protein groups. Both high protein diet and exercise did not significantly affect change in body weight, FFM and fat mass (FM). No significant protein*exercise interaction effect was observed for FFM. However, within-group analysis showed that high protein in combination with exercise significantly increased FFM (+0.6 ± 1.3 kg, p = 0.011). A high protein diet, though lower than targeted, did not significantly affect changes in FFM during modest weight loss in older overweight and obese adults. There was no significant interaction between the high protein diet and resistance exercise for change in FFM. However, only the group with the combined intervention of high protein diet and resistance exercise significantly increased in FFM. Dutch Trial Register, number NTR4556, date 05-01-2014.

In dietary practice, it is common to estimate protein requirements on actual bodyweight, but corrected bodyweight (in cases with BMI <20 kg/m² and BMI ≥30 kg/m²) and fat free mass (FFM) are also used. Large differences on individual level are noticed in protein requirements using these different approaches. To continue this discussion, the answer is sought in a large population to the following question: Will choosing actual bodyweight, corrected bodyweight or FFM to calculate protein requirements result in clinically relevant differences? This retrospective database study, used data from healthy persons ≥55 years of age and in- and outpatients ≥18 years of age. FFM was measured by air displacement plethysmography technology or bioelectrical impedance analysis. Protein requirements were calculated as 1) 1.2 g (g) per kilogram (kg) actual bodyweight or 2) corrected bodyweight or 3) 1.5 g per kg FFM. To compare these three approaches, the approach in which protein requirement is based on FFM, was used as reference method. Bland-Altman plots with limits of agreement were used to determine differences, analyses were performed for both populations separately and stratified by BMI category and gender. In total 2291 subjects were included. In the population with relatively healthy persons (n = 506, ≥55 years of age) mean weight is 86.5 ± 18.2 kg, FFM is 51 ± 12 kg and in the population with adult in- and outpatients (n = 1785, ≥18 years of age) mean weight is 72.5 ± 18.4 kg, FFM is 51 ± 11 kg. Clinically relevant differences were found in protein requirement between actual bodyweight and FFM in most of the participants with overweight, obesity or severe obesity (78-100%). Using corrected bodyweight, an overestimation in 48-92% of the participants with underweight, healthy weight and overweight is found. Only in the Amsterdam UMC population, protein requirement is underestimated when using the approach of corrected bodyweight in participants with severe obesity. The three approaches in estimation of protein requirement show large differences. In the majority of the population protein requirement based on FFM is lower compared to actual or corrected bodyweight. Correction of bodyweight reduces the differences, but remain unacceptably large. It is yet unknown which method is the best for estimation of protein requirement. Since differences vary by gender due to differences in body composition, it seems more accurate to estimate protein requirement based on FFM. Therefore, we would like to advocate for more frequent measurement of FFM to determine protein requirements, especially when a deviating body composition is to be expected, for instance in elderly and persons with overweight, obesity or severe obesity.

A higher protein intake is suggested to preserve muscle mass during aging and may therefore reduce the risk of sarcopenia. We explored whether the amount and type (animal or vegetable) of protein intake were associated with 5-y change in mid-thigh muscle cross-sectional area (CSA) in older adults (n = 1561). Protein intake was assessed at year 2 by a Block food-frequency questionnaire in participants (aged 70–79 y) of the Health, Aging, and Body Composition (Health ABC) Study, a prospective cohort study. At year 1 and year 6 mid-thigh muscle CSA in square centimeters was measured by computed tomography. Multiple linear regression analysis was used to examine the association between energy-adjusted protein residuals in grams per day (total, animal, and vegetable protein) and muscle CSA at year 6, adjusted for muscle CSA at year 1 and potential confounders including prevalent health conditions, physical activity, and 5-y change in fat mass. Mean (95% CI) protein intake was 0.90 (0.88, 0.92) g · kg^–1 · d^–1 and mean (95% CI) 5-y change in muscle CSA was −9.8 (−10.6, −8.9) cm². No association was observed between energy-adjusted total (β = −0.00; 95% CI: −0.06, 0.06 cm²; P = 0.982), animal (β = −0.00; 95% CI: −0.06, 0.05 cm²; P = 0.923), or plant (β = +0.07; 95% CI: −0.06, 0.21 cm²; P = 0.276) protein intake and muscle CSA at year 6, adjusted for baseline mid-thigh muscle CSA and potential confounders. This study suggests that a higher total, animal, or vegetable protein intake is not associated with 5-y change in mid-thigh muscle CSA in older adults. This conclusion contradicts some, but not all, previous research. This trial was registered at www.trialregister.nl as NTR6930.

Background: A protein intake of 30‐40 g per meal is suggested to maximally stimulate muscle protein synthesis in older adults and could therefore contribute to the prevention of sarcopenia. Protein intake at breakfast and lunch is often low and offers a great opportunity to improve daily protein intake. Protein, however, is known for its satiating effects. Therefore, we explored the association between the amount of protein intake at breakfast and lunch and total daily protein intake in older adults.Methods: Protein intake was assessed by a 3‐day food record in 498 community dwelling older adults (≥55 years) participating different lifestyle interventions. Linear mixed model analysis was used to examine the association between protein intake at breakfast or lunch and total daily protein intake, adjusted for sex, age, body mass index, smoking status, study and total energy intake.Results: After adjustment for potential confounders, a 10 g higher protein intake at breakfast was associated with a 3.2 g higher total daily protein intake (P = 0.008) for males and a 4.9 g (P < 0.001) higher total daily protein intake for females. A 10 g higher protein intake at lunch was associated with a 3.7 g higher total daily protein intake (P < 0.001) for males, and a 5.8 g higher total daily protein intake (P < 0.001) for females.Conclusions: A higher protein intake at breakfast and lunch is associated with a higher total daily protein intake in community dwelling older adults. Stimulating a higher protein intake at breakfast and lunch might represent a promising nutritional strategy to optimise the amount of protein per meal without compromising total daily protein intake.