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.

Validation of predictive equations to estimate resting metabolic rate of females and males across different activity levels.

OBJECTIVES: Using equations to predict resting metabolic rate (RMR) has yielded different degrees of validity, particularly when sex and different physical activity levels were considered. Therefore, the purpose of the present study was to determine the validity of several different predictive equations to estimate RMR in female and male adults with varying physical activity levels. METHOD: We measured the RMR of 50 adults (26 females and 24 males) evenly distributed through activity levels varying from sedentary to ultra-endurance. Body composition was measured by dual X-ray absorptiometry and physical activity was monitored by accelerometry. Ten equations to predict RMR were applied (using Body Mass [BM]: Harris & Benedict, 1919; Mifflin et al., 1990 [MifflinBM]; Pontzer et al., 2021 [PontzerBM]; Schofield, 1985; FAO/WHO/UNU, 2004; and using Fat-Free Mass (FFM): Cunningham, 1991; Johnstone et al., 2006; Mifflin et al., 1990 [MifflinFFM]; Nelson et al. 1992; Pontzer et al., 2021 [PontzerFFM]). The accuracy of these equations was analyzed, and the effect of sex and physical activity was evaluated using different accuracy metrics. RESULTS: Equations using BM were less accurate for females, and their accuracy was influenced by physical activity and body composition. FFM equations were slightly less accurate for males but there was no obvious effect of physical activity or other sample parameters. PontzerFFM provides higher accuracy than other models independent of the magnitude of RMR, sex, activity levels, and sample characteristics. CONCLUSION: Equations using FFM were more accurate than BM equations in our sample. Future studies are needed to test the accuracy of RMR prediction equations in diverse samples.

Validity of predictive equations for total energy expenditure against doubly labeled water.

Variations in physical activity energy expenditure can make accurate prediction of total energy expenditure (TEE) challenging. The purpose of the present study was to determine the accuracy of available equations to predict TEE in individuals varying in physical activity (PA) levels. TEE was measured by DLW in 56 adults varying in PA levels which were monitored by accelerometry. Ten different models were used to predict TEE and their accuracy and precision were evaluated, considering the effect of sex and PA. The models generally underestimated the TEE in this population. An equation published by Plucker was the most accurate in predicting the TEE in our entire sample. The Pontzer and Vinken models were the most accurate for those with lower PA levels. Despite the levels of accuracy of some equations, there were sizable errors (low precision) at an individual level. Future studies are needed to develop and validate these equations.

Childhood overweight: parental perceptions and readiness for change.

Although the national health crisis of childhood obesity is a well-documented problem, few if any clinical interventions have had success in curbing its growth. In fact, childhood obesity, along with its associated morbidities, continues to climb even in the face of increased awareness. Research shows that factors contributing to obesity are almost entirely modifiable on some level. Furthermore, specific behavior changes have been shown to result in positive outcomes, yet these changes have not been widely implemented by practitioners, families, or individuals. The transtheoretical model of health behavior change offers insight into assessing individuals and targeting interventions for behavior change. This article focuses on guiding school nurses to assess parents of school-age children at risk for obesity for readiness for health behavior change, then choosing parent-focused interventions based on their stage of readiness for change.