Of Sound Mind and Body: Exploring the Diet-Strength Interaction in Healthy Aging.

Strength is a vital component of healthy aging. However, "strength" comes in different forms (includes both physical and mental aspects) and can look different at various phases of adult life. Healthy eating and regular exercise are clearly important pillars for strength. This paper proposes a framework that underlines the value of protein foods and resistance exercise for aging strong.

Individual differences influence exercise behavior: how personality, motivation, and behavioral regulation vary among exercise mode preferences.

Personality traits, participatory motives, and behavior regulation have been linked to physical activity engagement. It is possible that these dimensions are associated with the type of physical activity one chooses to engage. Thus, the purpose of this study was to examine individual differences in those participating in various primary modes of physical activity (PMA) and determine which individual differences are predictive of exercise frequency. METHODS: 403 adults (36.3 ± 11.6 yrs, 35.5% male) completed an online survey. The survey included questions related to their PMA, items for the Big Five Inventory (BFI), Exercise Motivation Inventory (EMI-2), and the Behavioral Regulation in Exercise Questionnaire (BREQ-3). PMAs were divided into 5 main groups: CrossFit® Training (n = 89), Group Exercise (n = 59), Aerobic Training (n = 97), Resistance Training (n = 127), and Sport (n = 31). RESULTS: A multivariate ANOVA revealed significant differences in exercise motivation [p s ≤ .001, η 2 p = .05 - .22] and behavior regulation [p s ≤ .05, η 2 p = .03 - .06] between PMAs, but personality dimensions did not differ. A linear regression revealed that differences in motivation and regulation explained 17.1% (p = .001) variance in exercise behavior. CONCLUSIONS: These findings support the notion that individual differences exist between motivational dimensions and individuals' preference to engage in a particular physical activity mode. Further, these differences in motivation influence physical activity engagement (i.e., frequency).

High Intensity Functional Training (HIFT) and competitions: How motives differ by length of participation.

High Intensity Functional Training (HIFT) is a unique fitness method that promotes an active lifestyle and has seen exponential and continual growth over the last two decades. Motivation to exercise is likely to change over time as individuals' motives to initiate exercise may be different than those which motivate them to maintain an exercise program. The purpose of this study was to examine the motivational factors reported by individuals who actively engage in HIFT with varying length of participation and competition levels. 737 adults (32.4 ± 8.2 years) with more than three-months of HIFT experience completed an online version of the Exercise Motivation Inventory (EMI-2) survey. Those who had greater length of participation reported more motives associated with relatedness (i.e., affiliation, competition) and enjoyment, while those with less HIFT participation were more motivated by body-related variables (i.e., weight management). Further, motivational variables (e.g., social recognition, affiliation, challenge) varied depending on whether or not individuals had competed in an online qualifier. Understanding these differences in motivation may aid in exercise promotion, initiation, and adherence, and moreover promote long-term physical and mental health benefits.

Testosterone and Cortisol Responses to Five High-Intensity Functional Training Competition Workouts in Recreationally Active Adults.

To determine the salivary steroid response to high-intensity functional training (HIFT) competition workouts, saliva samples were collected from ten recreationally trained male and female competitors during a 5-week (WK1⁻WK5) international competition. Competitors arrived at their local affiliate and provided samples prior to (PRE) their warm-up, immediately (IP), 30-min (30P), and 60-min (60P) post-exercise. Samples were analyzed for concentrations of testosterone (T), cortisol (C), and their ratio (TC). Generalized linear mixed models with repeated measures revealed significant main effects for time (p < 0.001) for T, C, and TC. Compared to PRE-concentrations, elevated (p < 0.05) T was observed at IP on WK2⁻WK5 (mean difference: 135⁻511 pg·mL-1), at 30P on WK3 (mean difference: 81.0 ± 30.1 pg·mL-1) and WK5 (mean difference: 56.6 ± 22.7 pg·mL-1), and at 60P on WK3 (mean difference: 73.5 ± 29.7 pg·mL-1) and WK5 (mean difference: 74.3 ± 28.4 pg·mL-1). Compared to PRE-concentrations, elevated (p < 0.05) C was noted on all weeks at IP (mean difference: 9.3⁻15.9 ng·mL-1) and 30P (mean difference: 6.0⁻19.9 ng·mL-1); significant (p < 0.006) elevations were noted at 60P on WK1 (mean difference: 9.1 ± 3.0 ng·mL-1) and WK5 (mean difference: 12.8 ± 2.9 ng·mL-1). Additionally, TC was significantly reduced from PRE-values by 61% on WK1 at 60P (p = 0.040) and by 80% on WK5 at 30P (p = 0.023). Differences in T, C, and TC were also observed between weeks at specific time points. Although each workout affected concentrations in T, C, and/or the TC ratio, changes appeared to be modulated by the presence of overload and workout duration. During periods of elevated training or competition, athletes and coaches may consider monitoring these hormones for consistency and as a means of assessing workout difficulty.

Mood State Changes Accompanying the Crossfit Open™ Competition in Healthy Adults.

BACKGROUND: Specific mood states were examined during the CrossFit Open, a consecutive 5-week fitness competition involving five separate CrossFit® workouts, to determine whether the unique design or strenuous workouts of the competition resulted in acute and/or chronic mood state alterations. METHODS: Participants (n = 8) completed the Profile of Mood States (POMS) questionnaire one-week prior to the competition (baseline), prior to (PRE), immediately post (IP), 30-min post- (30P) and 60-min post-workout (60P) each week. Tension, depression, anger, confusion, fatigue and vigor were derived from the POMS, as was Total Mood Disturbance (TMD) and an Energy Index (EI). RESULTS: Workout intensity exceeded 93% HRmax each week. No differences were observed between baseline and PRE-workout mood states across weeks, indicating little effect of the unique competition design. Significant (week x time) interactions were observed for TMD (p = 0.037), EI (p = 0.038) and fatigue (p = 0.005). Acute mood state fluctuations were consistent across each week, where mood states improved to and beyond PRE values 60-min post-workout. CONCLUSIONS: In competitors, the differences in workout design between each week did not influence mood states. This may be related to adaptation to this style of training, while the acute mood state alterations are likely due to the workout intensity.