Study population
In a cross-sectional design, fifty-four active older adults (mean ± SD: age 58.9 ± 6.8 years, BM 74.2 ± 14.58 kg, height 1.72 ± 0.10 m, FM 27.9 ± 8.9 %) volunteered to participate in the study. Participants were eligible if they were ≥50 years, performed exercise training for recreational fitness and/or sports competitions ≥3/week, for ≥90 min/week, had no functional limitations, were free from chronic disease/disorders, were not taking medications that could interfere with SMM structure and/or function (e.g., corticosteroids, testosterone replacement or anabolic drugs), were not undergoing immunosuppressive therapy or hormone replacement therapy, and were not adhering to structured resistance training program/s. Participants were grouped based on age; middle age (50-59 years) and older (≥60years) and biological sex (males and females). All participants gave written informed consent. The study protocol obtained approval from the local ethics committee (Project number 12812). Data was collected during the period of September 2018 to January 2020, See Figure1 for participant flow.
Exercise volume
Prior to commencing any physical activity participants filled out a physical activity readiness questionnaire (PAR-Q). They self-reported their level of physical activity including exercise intensity and volume per week, and the modality of exercise. All participants were categorised into low (≤149 min/week), moderate (≥150-299 min/week) or high (≥300 min/week) exercise volume [7].
Dietary assessment
Participants were educated and asked to complete a three days food-fluid diary prior to their baseline visit, as previously described (28, 29). Food-fluid diaries were analysed using FoodWorks v10.0 nutritional analysis software (Xyris Software, Brisbane, Australia, 2019) based on Australian food composition tables from Australian Food Composition Database (AFCD) 2019. Based on preliminary data participants were then categorised into low (<0.8 g/kgBM/day), moderate (0.8-1.19 g/kgBM/day), and high (≥1.2 g/kgBM/day) protein intake to assess the effects that daily dietary protein intake alone has on outcomes of SMM, strength, power, and physical performance markers (30).
Experimental procedure and measurement of outcomes
For measurements of outcome variables, participants were required to attend the laboratory for the period between 07.00am to 09.00am in a fasted and euhydrated state (296 ± 5.6 mOsmol/kg; 53.4±19.9% TBW; Seca 515 MBCA, Seca Group, Hamburg, Germany), and after avoiding strenuous exercise for a 24 h period. Height was assessed using a fixed stadiometer (Holtain, Crosswell, Crymych, UK). BM was measured (Seca 515 MBCA) to the nearest 0.1 kg, using standardised anthropometrical procedures. Total (kg) and relative (%) FM and FFM, and bone mineral content were assessed by a trained radiographer using a dual-energy X-ray absorptiometry (Prodigy, GE Lunar, Madison, WI; with analysis software 14.10). Appendicular lean mass (ALM) was determined by adding the total arm and trunk lean mass and then it was adjusted for height (ASM/height2). Resting metabolic rate (RMR) was determined by indirect calorimeter (Vmax Encore Metabolic Cart; Carefusion, San Diego, CA) in temperate ambient conditions (22.2 ± 1.4°C), and in accordance with best practice guidelines (31). To comply with ethical procedures, prior to commencing the strength, power, and performance measures, participants were provided with a standardised breakfast (1.4 MJ, 15.3 g protein, 51.7 g carbohydrates, 6.8 g total fat). Physical assessment measures commenced ~30 min thereafter.
Blood collection and analysis
The remaining heparin whole blood samples were centrifuged at 4,000 rpm for 10 min within 15 min of sample collection. Aliquots of heparin plasma were places in 1.5 ml microstorage tubes and frozen at -80°C until analysis, except 2 x µl plasma was used to determine POsmol in duplicate (CV 1.0%), using a freeze point osmometry (Osmomat 030; Gonotec, Berlin, Germany).
Circulating concentrations of cortisol (DiaMetra, Perugia, Italy), insulin- like growth factor-1 (IGF-1) (Crux Biolab, Scoresby, Australia), insulin (Crux Biolab, Scoresby, Australia), testosterone (17b-OH-4-androstene-3-one; DiaMetra, Perugia, Italy), estradiol (17ꞵ-Estradiol; DiaMetra, Perugia, Italy) were measured by enzyme-linked immunosorbent assay (ELISA). Plasma concentrations of interleukin (IL)-2, IL-6, IL-1β, tumor necrosis factor (TNF)-α, IL-8, and IL-10 were determined by high sensitivity multiplex ELISA (HCYTOMAG-28SK; EMD Millipore, Darmstadt, Germany). All assays were performed as per manufacturer’s specifications, with standards and controls on each plate. The CV for analysed circulating biomarkers was ≤7.2%, and for systemic inflammatory cytokines was ≤13.5%.
Strength Outcomes
Strength was assessed by performing a 1 repetition maximal strength (1-RM) in accordance with previously described procedures (32). During a familiarisation trial, proper lifting technique was demonstrated, then participants were familiarised with each resistance machine (Hammer strength; LifeFitness, Sydney, Australia) by performing 8-10 repetitions of a light load (~50% of predicted 1-RM). After the successful completion of a further five to six repetitions at a heavier weight selected by the instructor, the workload was increased incrementally until only one repetition with correct technique could be completed. Participants were given 3-5 min rest in-between attempts (33). The value indicative of 1-RM was the highest load that could be raised in one single repetitions using correct technique for leg press, latissimus dorsi (lat) pull down, and bench press. The 1-RMs were normalised by BM (1-RM/BM). Hand grip strength (HGS) was measured using a digital hand dynamometer (Jamar® Plus+ Digital hand dynamometer; Sammons Preston, Bolingbrook, IL, USA). HGS was measured in a standing position with the participants elbow by their side and flexed to a 90° angle and a neutral wrist position. Participants were asked to apply the maximum grip strength three times with both left and right hands, HGS was defined as the highest value for their dominant hand (34).
Submaximal incremental bike test
Submaximal aerobic fitness was determined using an incremental bike test using a cycle ergometer (Corival, Lode, Groningen, Netherlands) and a metabolic cart (Vmax Encore Metabolic Cart; Carefusion, San Diego, CA). The initial workload began at 1 watt (W) per kilogram of Fat free mass (W/kgFFM) and increased by 0.5 W/kgFFM every 3 min until participants could not maintain the speed at 60 RPM or higher or they reached a rating of perceived exertion (RPE) of 15-17 on the Borg scale (35). Heart rate (HR) (Polar Electro, Kempele, Finland), V̇O2max, respiratory quotient (RQ), and RPE were measured every 3 min in real-time. Cardiorespiratory fitness was expressed as Watts/RQ. Procedures were adjusted from standard fitness testing procedures (36).
Countermovement jump
A Force plate (400s+ Performance Force plate; Fitness Technology, Adelaide, Australia) was used to measure relative muscle power (W/kg), jump height (cm) and velocity (m/sec) during a countermovement jump test (CMJ). Participants were asked to start in a full erect standing position in the middle of the force plate, then instructed to dip to a self-selected depth and “jump for maximal height”. Hands were kept on the hips to minimize any influence of arm swing (37). Participants were asked to perform three attempts of a CMJ with 1 min rest in-between jumps. The Force plate was interfaced with computer software (Ballistic Measurement System; Fitness Technology, Adelaide, Australia), where the mean of three jumps was selected for further analysis.
Gait speed measurement
To assess gait speed, a walking course of 4 metres long was marked on the floor. The participant was instructed to walk from one end of the course to the other at their usual walking pace. The timer began as the participant started walking and the timer was stopped with the first footfall after the 4-metre line. The test was repeated twice and the average (of two scores) was determined. Gait speed was reported at seconds/meter.
Statistical analysis
Data in text and tables are presented as either mean ± SD (descriptive experimental data) or mean and 95% confidence interval (CI) (primary and secondary variables), where indicated. Only participants with full data sets were used in analysis. All statistical analyses were performed using IBM SPSS statistics software (Verson 25.0, IBM Corp, Armonk, NY). Prior to analysis, assumptions of normality in the data were made using Shapori-Wilk test and visualisations of normality plots. Variables with multiple groups were examined using a one-way repeated measures ANOVA or non-parametric Kruskal-Wallis H test, were appropriate. A Tukey’s post-hoc test (or non-parametric equivalent) was applied to determine between group differences. Significance was accepted at P≤ 0.05. Additionally, Cohen’s d was applied to determine the magnitude of effect size for significance differences, with d ≥0.20 for small, d ≥0.50 for medium, and d ≥0.80 for large effect size.