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    Associations of protein intake, sources and distribution on muscle strength in community-dwelling older adults living in Auckland, New Zealand.
    (Cambridge University Press, 2023-08-23) Hiol AN; von Hurst PR; Conlon CA; Beck KL
    Protein intake, sources and distribution impact on muscle protein synthesis and muscle mass in older adults. However, it is less clear whether dietary protein influences muscle strength. Data were obtained from the Researching Eating Activity and Cognitive Health (REACH) study, a cross-sectional study aimed at investigating dietary patterns, cognitive function and metabolic syndrome in older adults aged 65-74 years. Dietary intake was assessed using a 4-d food record and muscle strength using a handgrip strength dynamometer. After adjusting for confounders, in female older adults (n 212), total protein intake (β = 0⋅22, P < 0⋅01); protein from dairy and eggs (β = 0⋅21, P = 0⋅03) and plant food sources (β = 0⋅60, P < 0⋅01); and frequently consuming at least 0⋅4 g/kg BW per meal (β = 0⋅08, P < 0⋅01) were associated with higher BMI-adjusted muscle strength. However, protein from meat and fish intake and the coefficient of variance of protein intake were not related to BMI-muscle strength in female older adults. No statistically significant associations were observed in male participants (n = 113). There may be sex differences when investigating associations between protein intake and muscle strength in older adults. Further research is needed to investigate these sex differences.
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    Muscle strength and muscle mass in older adults : a focus on protein intake, distribution, and sources : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Nutritional Science at Massey University, Albany, New Zealand
    (Massey University, 2023) Hiol, Anne Nadine
    Background: Ageing and obesity, which impair muscle protein synthesis (MPS), are associated with muscle mass and muscle strength loss in older adults. It is recognised that adequate protein intake, distribution and sources contribute to increased MPS and muscle mass in older adults. However, little is known about protein intake, distribution, and sources in New Zealand (NZ) older adults. Furthermore, it is unclear whether dietary protein influences muscle strength. Objectives: This thesis explored muscle strength, muscle mass and dietary protein intake, distribution and sources in community-dwelling older adults living in NZ. To meet this objective, the role of obesity in the relationship between muscle mass and muscle strength was examined. This was followed by an investigation of protein intake, distribution and sources, and their association with muscle strength. Methods: Data were obtained from the Researching Eating Activity and Cognitive Health (REACH) study, a cross-sectional study aimed at investigating dietary patterns and associations with cognitive function and metabolic syndrome in older adults aged 65 to 74 years. Isometric grip strength was measured using a hand grip strength dynamometer (JAMAR HAND). Body fat percentage and appendicular skeletal muscle mass (ASM) (sum of lean mass in the arms and legs) were assessed using dual-energy X-ray absorptiometry (Hologic, QDR Discovery A). The ASM index was calculated by ASM (kilograms, kg) divided by height (meters, m) squared. Dietary intake was collected using a 4-day food record, and the data was entered into FoodWorks 10. Data on absolute daily protein intake (grams, g) were generated. According to the peaks of protein consumption throughout the day, days were divided into three meals: breakfast, mid-day, and the evening meals. Protein sources were classified as meat and fish; plant; or dairy and egg protein sources based on the primary type of protein found in food. The relative protein intakes (g/kg) per day, meal, and source were calculated by dividing the absolute protein intake (g) by each participant's body weight (kg). Statistical analyses: A linear regression analysis was performed to determine the association between muscle mass and muscle strength. This analysis was conducted on males and females based on obesity classifications using body fat percentage (obesity ≥ 30% males, ≥ 40% females). The relative protein intake was compared against a cut-off value of 1.2 g of protein per kg body weight (g/kg BW) per day. The distribution of protein across the three meals was expressed as the coefficient of variance (CV), the average of total protein intake per main meal and the number of meals exceeding 0.4 g/kg BW of protein across the day. Sources of protein intake were assessed at breakfast, mid-day and the evening meals. Results are presented as a percentage of the total protein intake for each meal. Finally, linear regression analyses were conducted separately in males and females to investigate the relationships between BMI- muscle strength and protein intake, distribution and sources, accounting for relevant confounders. Results: Muscle mass was a significant predictor of muscle strength in non-obese participants. However, in participants with obesity, muscle mass was no longer a significant predictor of muscle strength. More than half of the participants had a protein intake of < 1.2 g/kg BW per day (62% females, 57% males). Protein intake was unevenly distributed throughout the day (CV = 0.48 for males and females) and was inadequate for reaching 0.4 g/kg BW at breakfast (for both males and females) and at the mid-day meal for males. The main sources of protein at breakfast were milk (28%), breakfast cereals (22%), and bread (12%); at the mid-day meal, bread (18%), cheese (10%) and milk (9%); and at the evening meal, meat provided over half the protein (56%). In females, relative protein intake was positively associated with muscle strength adjusted BMI (BMI-muscle strength) (r2 = 0.15, ρ < 0.01). Protein derived from either dairy and egg (ρ = 0.03); and plant sources (ρ < 0.01) was related to BMI-muscle strength but not protein from meat and fish (ρ = 0.55). Greater frequency of protein consumption of at least 0.4 g/kg BW per meal was associated with BMI-muscle strength (ρ = 0.01), but the coefficient of variance for protein intake distribution was not related to BMI-muscle strength (ρ = 0.47). There was no relationship between BMI-muscle strength and total daily protein intake, protein from meat and fish; dairy and egg; and plant-based sources, or distribution defined as frequency of protein consumption of at least 0.4 g/kg BW per meal or CV in male older adults. Conclusions: Obesity should be considered when measuring associations between muscle mass and muscle strength in older adults. A higher BMI-adjusted muscle strength was associated with consuming more protein each day and a higher frequency of consumption of a meal containing at least 0.4 g/kg BW; and from dairy and egg; and plant food sources in female older adults. There was no correlation between protein intake, distribution and sources and muscle strength in males. Protein intake was less than 1.2 g/kg BW per day and 0.4 g/kg BW per meal for a large proportion of older adults. At breakfast and the mid-day meals the main sources of protein were from cereals and dairy products, and from meat sources at the evening meal. Further research is needed to investigate how best to optimise protein intake to increase and maintain muscle mass and muscle strength in older adults from the general population.
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    A comparison between a traditionally periodised programme and a load autoregulated periodised programme for maximal strength gain in the squat, bench press, and deadlift in weight-trained males : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Exercise and Sport Science at Massey University, Manawatū, New Zealand
    (Massey University, 2016) Fraser, Jeremy
    Background: Training towards the goal of improving maximal strength is commonly undertaken; particularly by athletes involved in contact sports, powerlifters, and recreational body builders. Multiple methods of programming exist, with autoregulated (AR) training being a popular topic within the training community. AR training involves day to day fluctuations in volume and/or intensity in order to accommodate the athlete’s performance on a given day. This could potentially allow for greater gains in strength due to fine tuning of the fatigue-fitness interaction. However, scant research exists on AR training, with the vast majority being carried out on individuals during rehabilitation therapy. Aim: To examine whether a load-autoregulated strength training programme is more effective in improving maximal strength in the squat, bench press, and dead lift than a traditionally periodised program, in experienced weight-trained individuals. Methods: Eight healthy, recreationally trained males agreed to participate and completed this study. Each participant completed a traditionally (TD) programme and an AR programme in a randomised, cross-over design with a 2-week wash out period between. Each programme involved baseline one-repetition-maximum testing (1RM) in the barbell squat, bench press, and deadlift followed by eight weeks of training with subsequent 1RM testing. Following warm up, participants completed one set of as many repetitions as possible (AMRAP) at 85% of baseline 1RM, followed by subsequent working sets. 1RM Prediction equations were utilised in the AR training group to dictate load used in the working sets; whereas the TD groups subsequent sets were based on baseline 1RM. Results: The squat, deadlift, and total improved significantly within each programme (all p<0.05), however no differences between programmes were present (all p>0.05). Bench press strength improvement was significantly greater in the TD programme (time x programme interaction p<0.05). Conclusions: The present study found no differences in effectiveness of programmes at producing strength gain in the squat, deadlift, or total weight lifted. However the TD programme resulted in a greater improvement in bench press strength compared to AR. Future research would also involve auto-regulated volume, as well as ensuring matched cross over design, and ideally a use of more trained participants.