Neighborhood and Family Characteristics Associated with Adiposity and Physical Activity Engagement among Preschoolers in a Small Rural Community.

The purpose of this study was to evaluate family and home/neighborhood characteristics associated with physical activity (PA) and adiposity among young children living in a small rural community. METHODS: Participants were 30 parents and their youngest child aged 2-5 years. Children wore accelerometers for 7 days. Parents completed questionnaires about family lifestyle behaviors, parenting practices, and home/neighborhood characteristics. RESULTS: None of the family lifestyle behaviors were associated with child BMI percentile. Backyard size was inversely associated with moderate to vigorous physical activity on weekday afternoons (rho = -0.488, p = 0.006), as was perception of neighborhood dangers (rho = -0.388, p = 0.034). Perceived neighborhood safety (rho = 0.453, p = 0.012), the presence of sidewalks (rho = 0.499, p = 0.012), and public playground use (rho = 0.406, p = 0.026) were each associated with higher weekday afternoon MVPA. CONCLUSIONS: Findings suggest neighborhood safety, sidewalks, and use of public playgrounds are positively associated with MVPA among preschoolers, while backyard size and access to play equipment at home are not. These findings have implications for rural communities where space is plentiful but access to community space and sidewalks may be limited.

Impact of COVID-19 Stay-at-Home Restrictions on Employment Status, Physical Activity, and Sedentary Behavior.

BACKGROUND: North Americans report insufficient moderate-to-vigorous physical activity (MVPA) and ample sedentary behaviors (SBs), suggesting possible barriers to an active lifestyle. This study compared self-reported MVPA and SB before and during COVID-19 "Stay-at-Home" restrictions as a potential barrier across North America. METHODS: Questionnaires were distributed from 21 April to 9 May 2020. ANOVAs compared data overall and by group (age, sex, race, income, education, employment status). RESULTS: During restrictions, 51.4% (n = 687) of the 1336 responses (991 female, 1187 Caucasian, 634 18-29 years) shifted to work from home and 12.1% (n = 162) lost their job. Overall, during restrictions, 8.3% (n = 110) fewer reported work-related MVPA (-178.6 ± 20.9 min/week). Similarly, 28.0% (n = 374) fewer reported travel-related MVPA, especially females and younger age groups. While the 7.3% (n = 98) fewer reporting recreational MVPA was not statistically significant (-30.4 ± 11.5 min/week), there was an increase in SB (+94.9 ± 4.1 min/week) in all groups, except the oldest age group (70+ years). Locomotive activities and fitness class remained the predominant MVPA mode. Of those reportedly using facilities (68%; n = 709) before COVID, 31.3% (n = 418) would not return due to it "being unsafe". CONCLUSION: While barriers related to pandemic restrictions had a negative short-term impact on MVPA and SB in North America, the long-term impact is unknown.

Feasibility of Using Bioelectrical Impedance Analysis for Assessing Youth Weight and Health Status: Preliminary Findings.

Background. This study assessed the accuracy of bioimpedance analysis (BIA) for measuring body composition and resting metabolic rate (RMR) in fasted and non-fasted state and the prospect of using phase angle (PA) to indicate cellular health in youth. Methods. BIA body composition, RMR, and hydration measures were compared to dual-energy x-ray absorptiometry (DXA), MedGem metabolic analyzer, and urine specific gravity, respectively, at baseline in a fasted state using one-way ANOVAs. Repeated BIAs at 0, 30, 60, 90, and 120 min post-prandial were compared to baseline using repeated-measures ANOVA. Correlations were used to assess the relationship among PA and health (blood lipids and glucose, resting BP) and fitness (grip strength and a 3 min step test) measures. Results. BIA scans (N = 58; 11.4 ± 2.9 y) measured lower body fat % (BF%) in healthy weight youth (BMI < 85th percentile; 16.4 ± 1.1 vs. 25.1 ± 1.0%) and lower visceral adipose tissue (VAT) in males (44.5 ± 2.9 vs. 34.1 ± 6.0 cm2) than DXA and higher RMR in all youth (1244 ± 41 vs. 1104 ± 39 kcals/day), healthy weight (1231 ± 48 vs. 1049 ± 44 kcals/day), and teens (1541 ± 62 vs. 1234 ± 72 kcals/day) than MedGem. Compared to baseline, immediate post-prandial values were significantly higher for BF% (21.4 ± 1.4 vs. 22.0 ± 1.4%) and VAT (45.4 ± 6.1 vs. 46.2 ± 6.2 cm2). PA was significantly correlated with BF% (r = -0.33; p = 0.01), fat-free mass (r = 0.59; p < 0.001), grip strength (r = 0.56; p < 0.001). Conclusions. While more data are needed to confirm these preliminary findings, the results suggest caution is necessary in using BIA to assess aspects of youth health and weight status, especially in males, healthy weight, and teens. However, these preliminary findings do indicate that phase angle maybe be a valuable, non-invasive tool for identifying youth who are heading towards obesity and/or obesity-related health consequences.

Behavioral classes related to physical activity and sedentary behavior on the evaluation of health and mental outcomes among Brazilian adolescents.

Latent Class Analysis can assist researchers interested in a better understanding of behavioral patterns and their association with health outcomes. This study aimed to identify lifestyle latent classes related to distinct domains of physical activity (PA) and sedentary behavior (SB) among adolescents and their association with health outcomes. This cross-sectional study included 217 Brazilian adolescents (15 to 18 years old, 49.3% female). The classes were based on moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), number of steps, sedentary behavior (SB), and screen time (ST). To assess these behaviors, participants wore an accelerometer for one week. ST, demographic characteristics, socioeconomic status, and signs of common mental disorders (CMD) were evaluated through questionnaires. Latent Class Analysis was used to identify lifestyle classes. Three classes were recognized: "Active-Non-sedentary" (class 1) with 28.1% of adolescents; "Inactive-Non-sedentary" (class 2), 48.85%; and "Inactive-Sedentary" (class 3), 23.04%. Sex and signs of CMD were associated with the prevalence of the classes. Female adolescents presented 4.48 (95% CI 2.04-9.77) times more chance of belonging to the "Inactive-Sedentary" (class 3). Adolescents who presented CMD had 11.35 (95% CI 3.45-101.1) times more chance of belonging to the "Inactive-Non-sedentary" (class 2). The interaction between sex and signs of CMD showed that girls with signs of CMD were 9.20 (95% CI 1.17-71.52) more likely to belong to the Inactive-Sedentary class than the "Active-Non-sedentary". Results indicate that sex and signs of CMD can affect the prevalence of the classes. Our findings highlight that physical inactivity and SB can be associated with signs of CMD, especially in female adolescents.

Measurement of Children's Real-Time Physical Activity Enjoyment Using a New Visual Analog Scale.

Background: This study validated the How(e) Happy Scale (HHS) for measuring children's real-time physical activity (PA) enjoyment across PA type, intensity, sex, and weight status and compared state versus trait enjoyment. Methods: Children's (N = 31; 9.7 [1.7] y) PA intensity was measured during sport, play, and locomotive PA. Following each activity, children rated their perceived state (HHS) of enjoyment across 4 constructs (social engagement). Questionnaires measured trait PA enjoyment prior to play. Rasch Rating Scale analysis assessed model-data fit and probability distribution of HHS responses. Analyses of variance compared state versus trait PA enjoyment across main effects, and correlations assessed relationships between measured PA intensity versus state and trait PA enjoyment. Results: Trait PA enjoyment was neither different across sex and weight status nor correlated with PA intensity (r = -.16 to .22). By contrast, HHS responses differed across sex, weight status, and PA type and intensity and correlated with PA type (r = -.56 to -.28) and intensity (r = -.29 to -.32). HHS responses were ordered along the probability curve and showed good infit (0.76-1.22) and outfit (0.71-1.28) statistics and good person (r = .62) and item (r = .88) reliability. Conclusion: HHS is valid for detecting differences in real-time enjoyment across PA type and intensity in all children.

Does Wearing a Portable Metabolic Unit Affect Youth's Physical Activity or Enjoyment During Physically Active Games or Video Games?

Portable metabolic units (PMUs) are used to assess energy expenditure, with the assumption that physical activity level and enjoyment are unaffected due to the light weight and small size. PURPOSE: To assess differences in physical activity level and enjoyment while wearing and not wearing a PMU. METHOD: Youth (8-17 y; N = 73) played children's games or active video games while wearing and not wearing a PMU (crossover design). Participants wore an accelerometer and heart rate monitor and responded to questions about enjoyment on a facial affective scale. A repeated-measures analysis of variance was used to determine if accelerometer measures, heart rate, or enjoyment differed between conditions overall and by sex and weight status. RESULTS: Steps per minute were lower while wearing the PMU than not wearing the PMU (40 vs 44, P = .03). There was an interaction between PMU condition and weight status for enjoyment (P = .01), with overweight participants reporting less enjoyment when wearing the PMU compared with not wearing the PMU (72 vs 75 out of 100). Heart rate, vector magnitude, and counts per minute were not different. CONCLUSION: There may be psychosocial effects of wearing the PMU, specifically in overweight participants. Activity level was minimally affected, but the practical significance for research is still unknown.

Comparison of Accelerometer-Based Cut-Points for Children's Physical Activity: Counts vs. Steps.

Background: Accelerometers measure complex movements of children's free play moderate-vigorous physical activity (MVPA), including step and non-step movements. Current accelerometer technology has introduced algorithms to measure steps, along with counts. Precise interpretation of accelerometer-based cadence (steps/min) cut-points is necessary for accurately measuring and tracking children's MVPA. The purpose of this study was to assess the relationships and agreement between accelerometer-based cut-points (cadence and counts/min) to estimate children's MVPA compared to measured values. Methods: Forty children (8⁻12 years; 25 boys) played 6⁻10 games while wearing a portable metabolic analyzer and GT3X⁺ to measure and estimate MVPA, respectively. Correlation, kappa, sensitivity, and specificity assessed the relationships and agreement between measured and estimated MVPA. Results: Games elicited, on average, 6.3 ± 1.6 METs, 64.5 ± 24.7 steps/min, and 3318 ± 1262 vertical (V) and 5350 ± 1547 vector-magnitude (VM) counts/min. The relationship between measured and estimated MVPA intensity was higher for cadence (r = 0.50) than V and VM counts/min (r = 0.38 for both). Agreement using V and VM counts/min for measuring PA intensity varied by cut-points (range: 6.8% (κ = -0.02) to 97.6% (κ = 0.49)), while agreement was low using cadence cut-points (range: 4.0% (κ = 0.0009) to 11.3% (κ = 0.001)). Conclusion: While measured and estimated values were well correlated, using cadence tended to misclassify children's free-play MVPA.

Regional Variations in Physical Fitness and Activity in Healthy and Overweight Ecuadorian Adolescents.

Background: Insufficient physical activity (PA) and excessive sedentary behavior (SB) are the main contributors to adolescent obesity. However, it is uncertain whether recent economic growth and urbanization in Ecuador are contributing to an obesogenic environment. This study assessed the relationships among fitness, PA, SB, and perceived social support for PA in adolescents from urban (Quito) and rural (Loja) Ecuador. Methods: Fitness was estimated using 3-min step test and PA and SB participation and social support for PA were self-reported in 407 adolescents. T-tests and analysis of variance assessed differences by sex, obesity status, and region of Ecuador. Pearson correlations assessed relationships among PA, SB, fitness, and social support. Results: Males and rural adolescents (48.3 ± 9.4 and 47.1 ± 9.6 mL/kg/min) were more fit than females and urban adolescents (41.1 ± 7.5 and 39.7 ± 6.1 mL/kg/min). Fitness was negatively correlated with obesity only in rural Ecuador. Few adolescents reported ≥60 min/day of PA (8.4%) or ≤2 h/day of SB (30.2%), with greater SB participation in rural Ecuador. Weak correlations were observed among fitness, PA, SB, and parental/peer support for PA (r = -0.18 to 0.19; p < 0.05). Conclusion: While fitness varied by sex, weight status, and region, SB participation and parent/peer support for PA, not PA participation itself, predicted fitness in rural Ecuadorean adolescents.

Using Video Direct Observation to Assess Children's Physical Activity During Recess.

PURPOSE: Traditional direct observation cannot provide continuous, individual-level physical activity (PA) data throughout recess. This study piloted video direct observation to characterize children's recess PA overall and by sex and weight status. METHODS: Children (N = 23; 11 boys; 6 overweight; third to fifth grade) were recorded during 2 recess periods, coding for PA duration, intensity, location, and type. Duration of PA type and intensity across sex and weight status overall and between/within locations were assessed using 1- and 2-way analysis of variances. RESULTS: The field elicited more sedentary behavior (39% of time) and light PA (17%) and less moderate to vigorous PA (41%) compared with the fixed equipment (13%, 7%, and 71%, respectively) or the court (21%, 7%, and 68%, respectively). Boys engaged in significantly more vigorous-intensity activity on the court (35%) than girls (14%), whereas girls engaged in more moderate to vigorous PA on the fixed equipment (77% vs 61%) and field (46% vs 35%) than boys (all Ps > .05). PA type also differed by sex and weight status. CONCLUSION: Video direct observation was capable of detecting and characterizing children's entire recess PA while providing valuable context to the behavior. The authors confirmed previous findings that PA intensity was not uniform by schoolyard location and further differences exist by sex and weight status.

First-Year Osteopathic Medical Students' Knowledge of and Attitudes Toward Physical Activity.

CONTEXT: Current guidelines recommend that primary care physicians provide physical activity counseling as part of routine preventive health care. However, education regarding physical activity counseling often is not included or is inadequately covered in medical school curriculum, and it is unclear whether future physicians are prepared to offer effective counseling in this area. OBJECTIVE: To examine first-year medical students' knowledge of and attitudes toward physical activity and the importance of physical activity in patient counseling. METHODS: An anonymous electronic survey was distributed to all first-year students enrolled at the Ohio University Heritage College of Osteopathic Medicine. The survey assessed students' knowledge, beliefs, and behavior regarding physical activity and physical activity counseling for patients. The frequencies of students' weekly physical activity were computed to assess students' physical activity behaviors. Attitudes toward personal importance of physical activity and physical activity counseling in primary care were also assessed by response frequency. The relationship between students' knowledge of and participation in physical activity and the priority placed on exercise for future patients were assessed by correlation. RESULTS: Of 243 potential participants, 144 students (59.3%) returned the survey. The majority of students (131 of 144 [91.0%]) indicated that living a healthy lifestyle was very or extremely important to them, and 125 of 144 (86.9%) prioritized physical activity as moderately, very, or extremely important. Of 122 students, 81 (66.4%) exercised for at least 30 minutes on 3 or more of the past 7 days, and 36 (29.5%) reported doing so on 5 or more of the past 7 days. Nearly all of the students (127 of 133 [95.5%]) indicated that exercise is important for their future patients, 97 of 133 (72.9%) indicated feeling moderately or extremely comfortable counseling patients on exercise, and 113 of 134 (84.3%) desired to include physical activity counseling in their practice. Fifty of 134 students (40.3%) indicated that they were aware of current physical activity recommendations for adults in the United States; however, of these 50 students, 1 (2.0%) provided a correct definition of the national recommendations. CONCLUSION: Although students prioritized healthy lifestyles for themselves and their future patients and indicated a desire to include physical activity counseling as part of routine clinical care, the majority were unaware of the current physical activity recommendations. Thus, there is a need to address physical activity recommendations in the medical school curriculum.

Cardiometabolic risk factors, metabolic syndrome and pre-diabetes in adolescents in the Sierra region of Ecuador.

BACKGROUND: Excess weight (overweight and obesity) is the major modifiable risk factor for type 2 diabetes mellitus (T2DM) and other non-communicable diseases. However, excess weight may not be as predictive of diabetes risk as once thought. While excess weight and other obesity-related non-communicable diseases are of growing concern in low-middle income countries in Latin America, there is limited research on risk factors associated with T2DM in adolescents. This study investigated prevalence of overweight, obesity, prediabetes, diabetes and metabolic syndrome in adolescents in Ecuador. METHODS: A cross-sectional study was conducted with 433 adolescents from two schools in a small urban center in southern Ecuador and two schools in a large urban center in Quito. Risk factors were measured, including: height, weight, BMI, waist-to-hip ratio, fasting glucose, lipid panel, and HbA1c. Multivariate analysis of variance (MANOVA) was separately applied to risk factors and demographic factors as a set of dependent variables with sex, location and their interaction included as predictors. An independent t test was run on the data at 95% confidence intervals for the mean difference. The values for the triglycerides, LDL and VLDL were positively skewed. A Mann-Whitney U test was run on these data. RESULTS: Using IOTF standards, 9.8% were overweight and 1.9% were obese. Only 1.6% of the sample met the criteria for prediabetes by fasting glucose but 12.4% of the sample met the criteria for prediabetes by HbA1c. None of the participants met criteria for diabetes. There were 2.3% of the participants that met the IDF criteria for metabolic syndrome. Adolescents from the larger urban center had higher rates of prediabetes, higher mean HbA1c, blood pressure, lipid values, and lower HDL levels. CONCLUSIONS: Use of HbA1c identified more adolescents with prediabetes than FBG. The HbA1c measure is an attractive screening tool for prediabetes in developing countries. Although rates of obesity in Ecuadorian adolescents are low there is significant evidence to suggest that prediabetes is permeating the smaller urban centers. Traditional screening tools may underestimate this risk.

Effect of Prior Game Experience on Energy Expenditure During Xbox Kinect in Children and Teens.

OBJECTIVE: To examine the effect of game-specific and overall Kinect experience and overall gaming habits on energy expenditure (EE) and enjoyment of children and adolescents (8-17 years) while playing Xbox® Kinect exergames. MATERIALS AND METHODS: Participants (N = 55) played four active videogames for 6-10 minutes. Height, weight, and resting metabolic rate were measured and participants completed a survey on gaming habits and previous experience. Habit (none, low, moderate, or high) was based on the number of game systems at home, frequency, and duration of game play. Game-specific experience was classified as either inexperienced or experienced. A composite score was created for how much experience they had with each game, classified as none, low, or high. The participant wore a portable metabolic analyzer (total and physical activity energy expenditure [PAEE]), heart rate (HR) monitor, and accelerometer (waist, counts/min). Enjoyment was measured after each game using a three-item face scale. Bonferroni-adjusted three-way ANOVA assessed PAEE, intensity, and enjoyment across overall and game-specific experience and habits (P < 0.05). RESULTS: Intensity, PAEE, and HR were greater in experienced versus inexperienced players (5.1 ± 0.2 vs. 4.4 ± 0.2 metabolic equivalents [METs]; 4.1 ± 0.2 vs. 3.3 ± 0.2 kcal/min; 138 ± 2.5 vs. 130 ± 1.9 bpm). Higher game-specific experience levels elicited greater counts/min compared with no experience. Moderate gaming habits elicited greater PAEE and METs than low gaming habits. Enjoyment was equal in all groups. CONCLUSION: Participants with more game-specific Kinect experience or overall gaming habits elicited greater PA energy and intensity. This study supports that children and adolescents can play Xbox Kinect without decrements in PAEE or enjoyment.

Energy Cost and Enjoyment of Active Videogames in Children and Teens: Xbox 360 Kinect.

OBJECTIVE: New active videogames (AVGs) may provide youth an alternative to traditional play. The purpose of this study was to compare the physical activity energy expenditure (PAEE), intensity, and enjoyment of AVGs with those of seated videogames (SVGs). MATERIALS AND METHODS: Youth (8-17 years old) volunteered to play a random selection of six (two SVGs, four AVGs) videogames for 6-10 minutes each. Prior to participation, height, weight, and resting metabolic rate (RMR) were measured. A portable metabolic analyzer was worn during the games to measure total energy expenditure, and PAEE was calculated as (total energy expenditure - measured RMR). An accelerometer was worn on the right hip to measure intensity in counts/minute and steps/minute. Youth were classified as child (8-12 years old) versus teen (13-17 years old), healthy weight (body mass index [BMI] <85th percentile) versus overweight (BMI ≥85th percentile), and male versus female. A three-way mixed-model analysis of variance was used to compare differences in PAEE (metabolic equivalents [METs] and kcal/minute) with sex, weight status, and age group as main effects, including Bonferroni's adjustment. RESULTS: Most AVGs were moderate to vigorous intensity (4.6±0.1 METs; range, 2.8-6.6 METs), where steps/minute (lower-body movement) was positively related to PAEE (R(2)=0.68). All SVGs were classified as light intensity (1.7±0.0 METs). PAEE (kcal/minute) was significantly higher during AVGs and for teens, males, and overweight youth. There was no significant difference in enjoyment between AVGs and SVGs. CONCLUSIONS: AVGs elicited sufficient energy cost to be a suitable alternative for traditional play and may contribute to the recommended dose of physical activity, particularly in teens, males, and overweight youth.

The physical activity energy cost of the latest active video games in young adults.

BACKGROUND: Although promoted for weight loss, especially in young adults, it has yet to be determined if the physical activity energy expenditure (PAEE) and intensity of the newest active video games (AVGs) qualifies as moderate-to-vigorous physical activity (MVPA; > 3.0 METs). This study compared the PAEE and intensity of AVGs to traditional seated video games (SVGs). METHODS: Fifty-three young adults (18-35 y; 27 females) volunteered to play 6 video games (4 AVGs, 2 SVGs). Anthropometrics and resting metabolism were measured before testing. While playing the games (6-10 min) in random order against a playmate, the participants wore a portable metabolic analyzer for measuring PAEE (kcal/min) and intensity (METs). A repeated-measures ANOVA compared the PAEE and intensity across games with sex, BMI, and PA status as main effects. RESULTS: The intensity of AVGs (6.1 ± 0.2 METs) was significantly greater than SVGs (1.8 ± 0.1 METs). AVGs elicited greater PAEE than SVGs in all participants (5.3 ± 0.2 vs 0.8 ± 0.0 kcal/min); PAEE during the AVGs was greater in males and overweight participants compared with females and healthy weight participants (p's < .05). CONCLUSIONS: The newest AVGs do qualify as MVPA and can contribute to the recommended dose of MVPA for weight management in young adults.

Cross-validation of waist-worn GENEA accelerometer cut-points.

PURPOSE: The purpose of this study was to determine the classification accuracy of the waist gravity estimator of normal everyday activity (GENEA) cut-points developed by Esliger et al. for predicting intensity categories across a range of lifestyle activities. METHODS: Each participant performed one of two routines, consisting of seven lifestyle activities (home/office, ambulatory, and sport). The GENEA was worn on the right waist, and oxygen uptake was continuously measured using the Oxycon mobile. A one-way chi-squared test was used to determine the classification accuracy of the GENEA cut-points. Cross-tabulation tables provided information on under- and overestimations, and sensitivity and specificity analyses of the waist cut-points were also performed. RESULTS: Spearman rank order correlation for the GENEA gravity-subtracted signal vector magnitude and Oxycon mobile MET values was 0.73. For all activities combined, the GENEA accurately predicted intensity classification 55.3% of the time, and it increased to 58.3% when stationary cycling was removed from the analysis. The sensitivity of the cut-points for the four intensity categories ranged from 0.244 to 0.958, and the specificity ranged from 0.576 to 0.943. CONCLUSION: In this cross-validation study, the proposed GENEA cut-points had a low overall accuracy rate for classifying intensity (55.3%) when engaging in 14 different lifestyle activities.

Classification accuracy of the wrist-worn gravity estimator of normal everyday activity accelerometer.

PURPOSE: The purpose of this study was to determine whether the published left-wrist cut points for the triaxial Gravity Estimator of Normal Everyday Activity (GENEA) accelerometer are accurate for predicting intensity categories during structured activity bouts. METHODS: A convenience sample of 130 adults wore a GENEA accelerometer on their left wrist while performing 14 different lifestyle activities. During each activity, oxygen consumption was continuously measured using the Oxycon mobile. Statistical analysis used Spearman's rank correlations to determine the relationship between measured and estimated intensity classifications. Cross tabulations were constructed to show the under- or overestimation of misclassified intensities. One-way χ2 tests were used to determine whether the intensity classification accuracy for each activity differed from 80%. RESULTS: For all activities, the GENEA accelerometer-based physical activity monitor explained 41.1% of the variance in energy expenditure. The intensity classification accuracy was 69.8% for sedentary activities, 44.9% for light activities, 46.2% for moderate activities, and 77.7% for vigorous activities. The GENEA correctly classified intensity for 52.9% of observations when all activities were examined; this increased to 61.5% with stationary cycling removed. CONCLUSIONS: A wrist-worn triaxial accelerometer has modest-intensity classification accuracy across a broad range of activities when using the cut points of Esliger et al. Although the sensitivity and the specificity are less than those reported by Esliger et al., they are generally in the same range as those reported for waist-worn, uniaxial accelerometer cut points.

METs and accelerometry of walking in older adults: standard versus measured energy cost.

PURPOSE: This study aimed to measure the metabolic cost (METs) of walking activities in older adults, to examine the relationship between accelerometer output and METs across walking activities, and to compare measured MET values in older adults with the MET values in the compendium. METHODS: Twenty older adults (mean age = 75, range = 60-90 yr) completed eight walking activities (five treadmill based, three free living) for 6 min each. Oxygen consumption (V˙O2) and resting metabolic rate (RMR) were measured using a portable metabolic system, and motion was recorded using a waist-mounted ActiGraph accelerometer (GT3X; ActiGraph, Pensicola, FL). Energy expenditure across activities was defined as kilocalories per minute and measured as METs (V˙O2 / RMR) and standard METs (V˙O2 / 3.5 mL·kg-1·min-1). Mixed modeling was used to assess differences in counts per minute and kilocalories per minute by weight status, sex, comorbidity status, and functional status. Linear regression analysis was applied to develop a prediction equation for kilocalories per minute. Energy costs of walking were subsequently compared with METs in the compendium of physical activities. RESULTS: Average measured RMR was 2.6 mL·kg-1·min-1, 31.6% less than the standard RMR of 3.5 mL·kg-1·min-1. On average, standard METs were 71% lower than the measured METs across all walking activities. Measured MET levels differed from previously reported values in the literature and values listed in the compendium, resulting in misclassification of activity intensities for 60% of the walking conditions. Average counts for the walking activities ranged from 809 (treadmill = 1.5 mph) to 4593 counts per minute (treadmill = 3.5 mph). Previous regression equations consistently overestimate all activities compared with the measured energy cost in this sample of older adults. CONCLUSION: This study identifies the need for equations and cut points specific to older adults.

Cardiometabolic biomarkers in young black girls: relations to body fatness and aerobic fitness, and effects of a randomized physical activity trial.

There is little evidence from randomized trials showing that physical activity alone influences biomarker profiles in youths. This study tested two hypotheses: (i) that elevated body fatness and poor fitness would be associated with unfavorable levels of cardiometabolic biomarkers in 8-12-y-old black girls (n = 242) and (ii) that a 10-mo PA intervention would have favorable effects on the fatness-related cardiometabolic biomarkers. At baseline, all fatness indices (i.e., percent body fat, visceral adipose tissue, BMI, and waist circumference) were significantly (P < 0.05) associated with unfavorable levels of insulin, glucose, systolic BP, diastolic BP, triglycerides, C-reactive protein (CRP), and fibrinogen. Aerobic fitness was significantly (P < 0.05) associated with favorable levels of insulin, CRP, fibrinogen, and HDL(2). The PA intervention had significant and favorable effects on fitness, fatness, and two biomarkers-resting heart rate and LDL cholesterol. More research is needed to clarify what types of interventions can enhance the cardiometabolic health of youths.

Accuracy of four resting metabolic rate prediction equations: effects of sex, body mass index, age, and race/ethnicity.

OBJECTIVE: This study compared the accuracy of four commonly used RMR prediction equations to measured RMR obtained from the MedGem(®) metabolic analyzer. DESIGN AND METHODS: Height, weight and RMR were measured in 362 healthy individuals [51% female; body mass index (BMI): 17.6-50.6 kg m(-2); ages: 18-60 years; 17.4% non-white]. Following a 4h fast, participants rested in the supine position after which RMR was measured. RMR was estimated using four commonly used prediction equations: Harris-Benedict, Mifflin-St. Jeor, Owen, and WHO/FAO/UNU. Accuracy was determined by calculating the percentage of predicted RMR values that were within ± 10% of measured RMR values. Main effects of sex, BMI, age, and race/ethnicity were assessed using repeated measures ANCOVAs. RESULTS: For all participants combined, the Harris-Benedict, Mifflin, and WHO/FAU/UNU equations similarly predicted RMR values within ± 10% of measured RMR values (57.5, 56.4, and 55.2% of the sample, respectively). When participant data were stratified by sex, BMI, age, and race/ethnicity, the accuracy of each regression equation varied dramatically. The Harris-Benedict equation over-predicted RMR in 18-29 year olds. The Owen equation under-predicted RMR in both sexes, all three BMI categories, 18-49 year olds and White participants. The Mifflin under-predicted RMR in both sexes, normal weight individuals, 40-60 year olds, and non-Hispanic White participants. The WHO/FAO/UNU over-predicted RMR in males, overweight participants, and 50-60 year olds. CONCLUSIONS: When examining the entire sample, the Harris-Benedict, Mifflin, and WHO/FAU/UNU equations yielded similar levels of agreement with the MedGem(®) measured RMR. However, clinical judgment and caution should be used when applying these prediction equations to special populations or small groups.

A 10-month physical activity intervention improves body composition in young black boys.

Objective. To determine if a 10-month after-school physical activity (PA) intervention could prevent deleterious changes in body composition and cardiovascular (CV) fitness in young black boys. Methods. Following baseline measures, 106 boys (8-12 yrs) were randomized to either a control group or an intervention group, further divided into attenders (ATT) and nonattenders (NATT), participating in ≥60% or <60% of the intervention, respectively. The daily intervention consisted of skills development (25 min), vigorous PA (VPA, 35 min), and strengthening/stretching (20 min) components. Body composition was measured by dual-energy X-ray absorptiometry. Results. Following the intervention, the ATT exhibited an increase in moderate-to-vigorous PA and a significant reduction in BMI, fat mass, and %BF compared to the control group. A significant association among the intervention energy expenditure and changes in body composition and CV fitness was observed only in the ATT group. Conclusion. An after-school PA program of sufficient length and intensity can promote healthy changes in body composition and fitness levels in black boys who attend at least 3 days/week.