Far from the walking pace. Ecological and evolutionary consequences of the suboptimal locomotion speeds in non-adult humans.

INTRODUCTION: Locomotion activities are part of most human daily tasks and are the basis for subsistence activities, particularly for hunter-gatherers. Therefore, differences in speed walking-related variables may have an effect, not only on the mobility of the group, but also on its composition. Some anthropometric parameters related to body length could affect walking speed-related variables and contribute to different human behaviors. However, there is currently little information on the influence of these parameters in nonadult individuals. METHODS: Overall, 11 females and 17 male child/adolescents, 8-17 years of age, volunteered to participate in this cross-sectional study. Five different pace walking tests were performed on a treadmill to calculate the optimal locomotion speed (OLS) and U-shaped relationship between the walking energy expenditure and speed (χ2 cost of transport [CoT]) (i.e., energetic walking flexibility). RESULTS: The mean OLS was 3.05 ± 0.13 miles per hour (mph), with no differences between sexes. Similarly, there were no sex differences in walking flexibility according to the χ2 CoT. Body height (p < .0001) and femur length (p < .001) were positively correlated with χ2 CoT; however, female child/adolescents mitigated the effect of height and femur length when walking at suboptimal speeds. CONCLUSION: Consistent with prior observations in adults, our findings suggest that anthropometric parameters related to body stature are associated with reduced suboptimal walking flexibility in children and adolescents. Taken together, these results suggest that children and adolescents can adapt their pace to the one of taller individuals without a highly energetic penalty, but this flexibility decreases with increasing body size.

Micronutrient supplement intakes among collegiate and masters athletes: A cross-sectional study.

Objective: In our cross-sectional study, we evaluated micronutrient supplementation intake among Collegiate and Masters Athletes. Methods: We conducted a cross-sectional study to assess micronutrient supplementation consumption in Collegiate and Masters Athletes, comparing sex and sport classification within each respective group. Micronutrient supplement consumption data were measured using a Food Frequency Questionnaire. A two-way analysis of variance was used to explore the differences among Collegiate and Masters Athletes' supplement intakes of the following vitamins and minerals: vitamins A, B6, B12, C, E, D, and calcium, folate, iron, magnesium niacin, riboflavin, selenium, thiamine, and zinc. When significant differences were found, a Bonferroni post hoc test was performed to identify specific group differences. The significance level was set a priori at p < 0.05. Results: A total of 198 athletes (105 females and 93 males) were included in the study. Participants were 36.16 ± 12.33 years of age. Collegiate male athletes had significantly greater vitamin A [1,090.51 ± 154.72 vs. 473.93 ± 233.18 mg retinol activity equivalents (RAE)/day] (p < 0.036), folate [337.14 ± 44.79 vs. 148.67 ± 67.50 mcg dietary folate equivalents (DFE)/day] (p < 0.027), and magnesium (65.35 ± 8.28 vs. 31.28 ± 12.48 mg/day) (p < 0.031) intakes compared to Collegiate female athletes. Collegiate CrossFit Athletes (940.71 ± 157.54 mg/day) had a significantly greater vitamin C intake compared to Collegiate General Athletes (156.34 ± 67.79 mg/day) (p < 0.005), Collegiate Triathletes (88.57 ± 148.53 mg/day) (p < 0.027), Collegiate Resistance Training Athletes (74.28 ± 143.81 mg/day) (p < 0.020), and Collegiate Powerlifters (175.71 ± 128.63 mg/day) (p < 0.044). Masters females had significantly greater calcium intakes compared to Masters males (494.09 ± 65.73 vs.187.89 ± 77.23 mg/day, respectively) (p < 0.002). Collegiate Runners (41.35 ± 6.53 mg/day) had a significantly greater iron intake compared to Collegiate Powerlifters (4.50 ± 6.53 mg/day) (p < 0.024). Masters Swimmers (61.43 ± 12.10 mg/day) had significantly greater iron intakes compared to Masters General Athletes (13.97 ± 3.56 mg/day) (p < 0.014), Masters Runners (17.74 ± 2.32 mg/day) (p < 0.03), Masters Triathletes (11.95 ± 3.73 mg/day) (p < 0.008), Masters CrossFit Athletes (15.93 ± 5.36 mg/day) (p < 0.043), Masters Rowers (9.10 ± 3.36 mg/day) (p < 0.003), and Masters Cyclists (1.71 ± 9.88 mg/day) (p < 0.011). Masters Powerlifters (47.14 ± 9.65 mg/day) had significantly greater zinc intakes compared to Masters General Athletes (9.57 ± 2.84 mg/day) (p < 0.015), Masters Runners (10.67 ± 1.85 mg/day) (p < 0.017), Masters Triathletes (10.24 ± 2.98 mg/day) (p < 0.020), Masters Rowers (9.33 ± 2.68 mg/day) (p < 0.013), and Masters Cyclists (1.43 ± 7.88 mg/day) (p < 0.019). There were no other significant differences among the other micronutrient supplement intakes between the sexes or among the sport classification. Conclusion: We reported significant differences among female and male Collegiate and Masters Athletes. Additionally, we reported significant differences among Collegiate and Masters Athletes sport classifications. Further research should examine both dietary and micronutrient supplement intake among Collegiate and Masters Athletes to examine the extent that athletes exceed the Recommended Dietary Allowances (RDA), and the potential effects on health and performance.

A Comparison of Substrate Utilization Profiles During Maximal and Submaximal Exercise Tests in Athletes.

Background: Exercise is primarily sustained by energy derived from lipids (plasma free fatty acids and intramuscular triglycerides), and glucose (plasma glucose and muscle glycogen). Substrate utilization is the pattern by which these fuel sources are used during activity. There are many factors that influence substrate utilization. We aim to delineate the effect of exercise intensity and body composition on substrate utilization. Objective: The objective of our study was to discern the differences in substrate utilization profiles during a maximal and submaximal graded exercise test, and to determine the extent to which body composition influences substrate utilization during the exercise tests. Methods: A total of 27 male athletes, 32.5 ± 11 years of age, were recruited for this study. Body composition was analyzed using a bioelectrical impedance analyzer. Maximal and submaximal exercise tests were performed on a treadmill. A novel graded submaximal treadmill protocol was used for the submaximal test. Results: Average percent body fat (PBF) was 15.8 ± 5%. Average maximal oxygen consumption (VO2max) was 47.6 ± 9 mL/kg/min, while the average exercise intensity (percent VO2max) at which participants were shifting to glucose predominance for energy during the maximal and submaximal tests were 76 ± 8.3% and 58.4 ± 21.1%, respectively. A paired-samples t-test was conducted to compare percent VO2max at crossover point in maximal and submaximal graded exercise tests. There was a significant difference in percent VO2max at the crossover point for maximal (76 ± 8.3%) and submaximal (58 ± 21.1%) tests (t = 4.752, p = 0.001). A linear regression was performed to elucidate the interaction between exercise intensity at the crossover point and body composition during a maximal and submaximal graded exercise test. There was a significant effect of PBF on percent VO2max at crossover point during the maximal graded exercise test [F(1,24) = 9.10, P = 0.006] with an R2 of 0.245. However, there was no significant effect of PBF on percent VO2max at crossover point during the submaximal graded exercise test (P > 0.05). Conclusion: Substrate utilization, represented by the crossover point, is dependent on the rate of increase in exercise intensity. At maximal efforts, the crossover to carbohydrates from fats as the predominant fuel source occurs at a significantly later stage of percent VO2max than at submaximal efforts. Furthermore, body composition represented by PBF is a significant predictor of substrate utilization during maximal efforts. Athletes with a relatively higher PBF are more likely to have increased lipid oxidation during high intensity exercises than those with a lower body fat percentage.

Validation of a Newly Developed Food Frequency Questionnaire to Assess Dietary Intakes of Magnesium.

Magnesium (Mg) intake is an important indication of an individual's Mg status, but no validated food frequency questionnaire (FFQ) to assess intake currently exists. The purpose of this study was to develop and investigate the validity of a semi-quantitative Mg food frequency questionnaire (MgFFQ) against a 14-day food diary to assess average daily Mg intakes. In this cross-sectional study, 135 adults aged 18 to 75 completed the 33-item MgFFQ and a 14-day food diary to assess their Mg intakes. Coefficients of variance, Pearson's correlation coefficients, and/or Spearman's rank correlation coefficient tests were used to determine the relationship between the MgFFQ and the average Mg intake from the 14-day food diary among all participants, men, women, age groups, and body mass index (BMI) groups. The correlation between the MgFFQ and the 14-day food diary was significant (p < 0.05) for all participants (r = 0.798), men (r = 0.855), women (r = 0.759), normal weight (r = 0.762), overweight (r = 0.858), and obese (r = 0.675) weight statuses, and in all age groups. The calcium to magnesium intake (Ca:Mg) ratio in all participants was higher than optimal, 3.39 (2.11). Our results suggest that the MgFFQ is a valid method to capture Mg intake over an extended period of time, therefore acting as a valuable tool to quickly determine Mg intake.

Low dietary magnesium intake alters vitamin D-parathyroid hormone relationship in adults who are overweight or obese.

Vitamin D metabolism is dependent on magnesium (Mg) as a cofactor; therefore, poor Mg status may alter the relationship between vitamin D metabolite serum 25-hydroxyvitamin D (s25OHD) and serum parathyroid hormone (sPTH). We hypothesized that low dietary Mg intake may alter sPTH response to s25OHD in a population with excess body weight, thereby leading to a worsening of cardiometabolic health. To explore this hypothesis, we conducted a cross-sectional study on adults who were either overweight or obese (owt/ob). Dietary Mg intake was measured using a Mg food frequency questionnaire (MgFFQ). Body composition information was measured using Dual Energy X-ray Absorptiometry (DXA). Blood samples were obtained for all biochemical analyses. A total of 57 participants, 22 to 65 years of age, with a body mass index between 25 to 45 kg/m2 were divided into 3 groups, according to dietary Mg intake percentiles (Low Mg Group = <33 percentile, Medium Mg Group = 33 to 66 percentile, High Mg Group = >66 percentile). Higher s25OHD was negatively associated with lower sPTH in the High Mg Intake group (r = -0.472, P = .041), but not in other groups. A positive relationship between s25OHD and serum high-molecular weight adiponectin concentrations was observed in the High Mg Group (r = 0.532, r = 0.022), but not in other groups. Serum Interleukin-6 concentrations were negatively associated with s25OHD (r = -0.316, P = .017) for the entire study group. Based on these results, our study demonstrated that a low dietary Mg intake may alter PTH response to 25OHD.

The Endocrine Role of Bone in Cardiometabolic Health.

PURPOSE OF REVIEW: The purpose of this review is to discuss the current knowledge about major bone regulating hormones vitamin D, parathyroid hormone (PTH), estrogen and bone metabolism markers osteocalcin (OC), bone-specific alkaline phosphatase (BAP), N-terminal propeptide of type 1 collagen (P1NP), and c-terminal type 1 collagen (CTX) and their mechanistic effects on cardiometabolic health. RECENT FINDINGS: Bone regulating hormones, nutrients, and turnover markers influence different aspects of cardiometabolic health including body composition, cardiovascular function, and glycemic control. While most observational research supports a relationship between bone as an endocrine organ and cardiometabolic outcomes, there are limited human clinical trials to strengthen a causal link between the two. While the associations between bone and cardiometabolic health are beginning to be understood based on findings from large observations studies, further exploration of bone's causal influence on health outcomes in humans and the underlying mechanisms of effect are necessary.