Changes in Intraset Repetitions in Reserve Prediction Accuracy During Six Weeks of Bench Press Training in Trained Men.

In this study we investigated whether the accuracy of intraset repetitions in reserve (RIR) predictions changes over time. Nine trained men completed three bench press training sessions per week for 6 weeks (following a 1-week familiarization). The final set of each session was performed until momentary muscular failure, with participants verbally indicating their perceived 4RIR and 1RIR. RIR prediction errors were calculated as raw differences (RIRDIFF), with positive and negative values indicating directionality, and absolute RIRDIFF (absolute value of raw RIRDIFF) indicating error scores. We constructed mixed effect models with time (i.e., session) and proximity to failure as fixed effects, repetitions as a covariate, and random intercepts per participant to account for repeated measures, with statistical significance set at p ≤ .05. We observed a significant main effect for time on raw RIRDIFF (p < .001), with an estimated marginal slope of -.077 repetitions, indicating a slight decrease in raw RIRDIFF over time. Further, the estimated marginal slope of repetitions was -.404 repetitions, indicating a decrease in raw RIRDIFF as more repetitions were performed. There were no significant effects on absolute RIRDIFF. Thus, RIR rating accuracy did not significantly improve over time, though there was a greater tendency to underestimate RIR in later sessions and during higher repetition sets.

Accuracy of Predicted Intraset Repetitions in Reserve (RIR) in Single- and Multi-Joint Resistance Exercises Among Trained and Untrained Men and Women.

We assessed the accuracy of intraset repetitions in reserve (RIR) predictions on single-joint machine-based movements of trained and untrained men and women. Participants were 27 men (M age = 22, SE = 0.6 years; M weight = 90.8, SE = 4.0 kg; M height = 182.3, SE = 1.4 cm; M training experience = 66, SE = 9 months) and 31 women (M age = 20, SE = 0.4 years; M weight = 67.8, SE = 2.3 kg; M height = 167.6, SE = 1.1 cm; M training experience = 22, SE = 4 months). In one session, participants performed a five-repetition maximum (5RM) test on biceps curl, triceps pushdown, and seated row exercises; we then estimated one repetition maximum (1RM). Participants then performed four sets of each exercise, in a randomized order, to the point of momentary muscular failure at 72.5% of 1RM. During each set, participants indicated when they first perceived 5RIR and then predicted RIR on every repetition thereafter until failure. The difference between actual repetitions performed and predicted repetitions at each intraset prediction was determined to be the RIR difference (RIRDIFF). A 3-way repeated measures ANCOVA found that a 3-way interaction was not statistically significant (p = 0.435) and no covariates of sex (p = 0.917), training experience (p = 0.462) nor experience rating RIR significantly affected RIRDIFF (p = 0.462-0.917). There were significant main effects for the proximity to failure of the prediction and the set number (p < 0.01) but not for exercise (p = 0.688). Thus, intraset RIR predictions were more accurate when closer to failure and in later sets, but sex, training experience, and experience rating RIR did not significantly influence RIR prediction accuracy on machine-based single-joint exercises.

Submaximal Testing to Estimate Aerobic Capacity Using a Matrix C5x Stepmill.

The primary purpose of this study was to determine if the Matrix C5x stepmill's preprogrammed submaximal test is able to accurately predict maximal oxygen uptake. Sixteen participants completed a maximal treadmill test and a preprogrammed submaximal test on a Matrix C5x stepmill. Oxygen uptake was measured using a Cosmed K5 during both tests. Maximal oxygen uptake (VO2max) was calculated from submaximal data using a multi-stage calculation and compared against measured VO2max from the maximal test and estimated VO2max from the submaximal stepmill test. METs were also measured during the submaximal test and compared to the METs estimated by the stepmill and METs calculated using submaximal stepping equations. Measured VO2max (39.18 α 6.6 ml.kg-1.min-1) was significantly higher (p < 0.001) than estimated VO2max (28.06 α 3.2 ml.kg-1.min-1) and calculated VO2max (35.58 α 8.0 ml.kg-1.min-1). Measured METs were significantly (p = 0.04) higher than estimated METs in all stages, and higher than calculated METs in stage 1 of the submaximal test. The C5x did not provide accurate estimations of METs or maximal oxygen uptake. Calculating maximal oxygen uptake from submaximal stepmill data may provide an alternative, although development of a new equation may be warranted.

Low Muscular Strength, Weight Status, and Metabolic Syndrome in Adolescents: National Health and Nutrition Examination Survey 2011-2014.

PURPOSE: To investigate the association between muscular strength and metabolic syndrome (MetS), with a specific focus on the role of weight status, using a nationally representative sample of US youth. METHODS: The analysis included 409 boys and 415 girls from the 2011 to 2014 National Health and Nutrition Examination Survey between 12 and 18 years of age. The prevalence of MetS was defined using age- and sex-specific criteria for abdominal obesity, elevated triglycerides, blood pressure, fasting glucose, and low high-density lipoprotein (HDL) cholesterol. Strength was assessed via handgrip dynamometer and expressed as age- and sex-specific z scores of relative strength. Low strength was defined as a relative strength below the 25th percentile. Analyses controlled for age, sex, race/ethnicity, physical activity, and weight status. RESULTS: The sample prevalence of MetS was approximately 5.3%. However, MetS prevalence was 18.5% in overweight/obese youth with low strength. The adjusted odds of MetS were 3.1 (95% confidence interval, 1.5-6.3, P < .001) times higher for overweight/obese youth with low strength versus sufficient strength. CONCLUSION: Muscular strength is predictive of adolescent MetS, specifically in those with unhealthy weight status. Approximately one in 5 overweight/obese youth with low strength had MetS. These findings highlight the relevance of muscular strength in youth cardiometabolic morbidities.

Vitamin D status is associated with muscular strength in a nationally representative sample of US youth.

AIM: To evaluate the association between serum 25-hydroxyvitamin D (25OHD) and muscular strength in a nationally representative sample of US youth. METHODS: Participants (n = 3350) were 6- to 18-y-olds from 2011 to 2014 National Health and Nutrition Examination Survey. Relative handgrip strength was quantified using age- and sex-specific z-scores. Poor strength was defined as those <25th percentile. Multivariate general linear and logistic models were used to compare strength and poor strength status by clinically relevant groupings of 25OHD. RESULTS: Approximately 20.2% of youth had 25OHD <50 nmol/L. Mean relative strength was highest for those at ≥75 nmol/L of 25OHD. The percentage of boys/girls with poor strength in the <50 nmol/L, 50-74.9 nmol/L and ≥75 nmol/L groups was 34.9%/32.3%, 25.8%/28.2% and 14.0%/15.8%, respectively. The odds of boys and girls with <50 nmol/L 25OHD having poor strength were 2.8 (95% CI: 1.4, 5.5) and 3.4 (1.7, 6.8) times higher compared to those with ≥75 nmol/L, respectively. CONCLUSION: Higher levels of circulating vitamin D were associated with higher relative strength, and poor strength was more prevalent when 25OHD was <75 nmol/L. These findings highlight the value of vitamin D for the muscle-bone unit and potential extraskeletal ramifications.

Socioeconomic status and physical fitness in youth: Findings from the NHANES National Youth Fitness Survey.

This study examined the associations between socioeconomic status (SES) and musculoskeletal (MSF) and cardiorespiratory fitness (CRF) in youth.  The sample consisted of boys and girls between 3-15 years.  SES was categorized utilizing family-income-to-poverty ratio (FIPR).  All analyses were standardized for age and sex.  For each test of physical fitness, SES was used to estimate mean fitness test percentile and 95% confidence intervals, controlling for race/ethnicity and physical activity.  Odds ratios were calculated for the likelihood of having low fitness by SES category.  In general, the high SES group had a better composite MSF, body composition, and CRF profiles than low and moderate SES groups.  Statistically significant differences were identified for relative grip strength, plank, body mass index, and cardiovascular endurance time (all p < 0.05).  Additionally, the odds of low/poor MSF fitness were 1.7 and 1.6 times higher in the low and moderate SES groups (respectively) compared to the children from high SES families.  The moderate SES group had an odds of poor CRF 1.6 times higher than the high SES group as well.  Children and adolescents from high SES families tend to have higher mean fitness and were less likely to have low/poor fitness.

Children Who Are Overweight Display Altered Vertical Jump Kinematics and Kinetics From Children Who Are Not Overweight.

PURPOSE: Children who are overweight typically do not perform motor skills as well as normal-weight peers. This study examined whether vertical jump kinetics and kinematics of children who are overweight differ from nonoverweight peers. METHODS: Thirty-nine children completed maximum-effort countermovement vertical jumps. Motion capture was used to complete lower extremity kinematic and kinetic analyses. RESULTS: The overweight group (body mass index ≥ 85th percentile; N = 11; age = 6.5 [1.6] y) jumped lower relative to their mass (0.381 cm/kg lower; P < .001) than normal-weight peers (N = 28; age = 6.4 [1.7] y). Compared with children who are normal weight, children who were overweight exhibited a shallower countermovement (knee: 12° less flexion, P = .02; hip: 10° less flexion, P = .045), lower hip torque (0.06 N·m/kg lower, P = .01) and hip work (40% less work, P = .01), and earlier peak joint angular velocities (knee: 9 ms earlier, P = .001; hip: 14 ms earlier, P = .004). CONCLUSION: Children who are overweight do not achieve optimal jumping mechanics and exhibit jumping characteristics of an earlier developmental stage compared with their peers. Interventions should help children who are overweight learn to execute a proper countermovement.

Muscle strength field-based tests to identify European adolescents at risk of metabolic syndrome: The HELENA study.

OBJECTIVES: To determine whether handgrip strength (HG) and/or standing long jump (SLJ) are capable of detecting risk of metabolic syndrome (MetS) in European adolescents, and to identify age- and sex-specific cut points for these tests. DESIGN: Cross-sectional study. METHODS: Participants included 969 (aged 12.5-17.5 years old) adolescents from 9 European countries (n = 520 girls). Absolute and relative HG and SLJ tests were used to assess upper and lower muscle strength, respectively. MetS status was determined using the age- and sex-specific cut points proposed by Jolliffe and Janssen´s, Additionally, we computed a continuous cardiometabolic risk index with the average z-score of four cardiometabolic risk factors: Wait circumference, mean arterial pressure, triglycerides/high-density lipoprotein cholesterol, and fasting insulin. RESULTS: The prevalence of MetS was 3.1% in European adolescents. Relative HG and absolute SLJ were the best tests for detecting the presence of MetS (Area under the receiver operating characteristic (AUC) = 0.799, 95%CI:0.773-0.824; and AUC = 0.695 95%CI:0.665-0.724), respectively) and elevated cardiometabolic risk index (AUC = 0.873, 95%CI:0.838-0.902; and AUC = 0.728 95%CI:0.698-0.756), respectively) and, regardless of cardiorespiratory fitness. We provide age- and sex-specific cut points of upper and lower muscle strength for European adolescents to identify the presence of MetS and elevated cardiometabolic risk index. CONCLUSIONS: The proposed health-related cut points could be used as a starting point to define health-related levels of upper and lower muscle strength in adolescents. Likewise, the diagnostic statistics provided herein can be used to offer feedback to adolescents, parents, and education and health professionals about what it means to meet or fail test standards.

Physical Activity, BMI, and Blood Pressure in US Youth: NHANES 2003-2006.

PURPOSE: The objective of this study was to examine the independent and combined association of physical activity and body mass index (BMI) with blood pressure in youth. METHODS: Youth aged 8-18 years from the 2003-2006 National Health and Nutrition Examination Survey (NHANES) with BMI, blood pressure, and physical activity (accelerometer) were included in the analyses. A total of 2585 subjects (1303 males; 47% of all 8- to 18-year-olds) met these criteria. RESULTS: Obese youth had a systolic blood pressure that was 8 mm Hg higher than normal weight youth. A significant interaction between BMI and physical activity on blood pressure was found (P < .001), and group differences among the BMI/activity groups showed that the 3 obese groups and the overweight/least active group had significantly higher systolic blood pressure than the normal weight/active group across all analyses. The overweight/least active and normal weight/least active groups had significantly higher diastolic blood pressure than the normal weight/active group as well. CONCLUSIONS: This study showed a significant independent and combined association of BMI and physical activity with blood pressure in youth. Interventions need to focus on the reduction of fatness/BMI as a way to reduce the cardiovascular risk in youth.

Calculating a Continuous Metabolic Syndrome Score Using Nationally Representative Reference Values.

OBJECTIVE: The prevalence of metabolic syndrome in youth varies on the basis of the classification system used, prompting implementation of continuous scores; however, the use of these scores is limited to the sample from which they were derived. We sought to describe the derivation of the continuous metabolic syndrome score using nationally representative reference values in a sample of obese adolescents and a national sample obtained from National Health and Nutrition Examination Survey (NHANES) 2011-2012. METHODS: Clinical data were collected from 50 adolescents seeking obesity treatment at a stage 3 weight management center. A second analysis relied on data from adolescents included in NHANES 2011-2012, performed for illustrative purposes. The continuous metabolic syndrome score was calculated by regressing individual values onto nationally representative age- and sex-specific standards (NHANES III). Resultant z scores were summed to create a total score. RESULTS: The final sample included 42 obese adolescents (15 male and 35 female subjects; mean age, 14.8 ± 1.9 years) and an additional 445 participants from NHANES 2011-2012. Among the clinical sample, the mean continuous metabolic syndrome score was 4.16 ± 4.30, while the NHANES sample mean was quite a bit lower, at -0.24 ± 2.8. CONCLUSIONS: We provide a method to calculate the continuous metabolic syndrome by comparing individual risk factor values to age- and sex-specific percentiles from a nationally representative sample.

Reference Curves for Field Tests of Musculoskeletal Fitness in U.S. Children and Adolescents: The 2012 NHANES National Youth Fitness Survey.

Laurson, KR, Saint-Maurice, PF, Welk, GJ, and Eisenmann, JC. Reference curves for field tests of musculoskeletal fitness in U.S. children and adolescents: The 2012 NHANES National Youth Fitness Survey. J Strength Cond Res 31(8): 2075-2082, 2017-The purpose of the study was to describe current levels of musculoskeletal fitness (MSF) in U.S. youth by creating nationally representative age-specific and sex-specific growth curves for handgrip strength (including relative and allometrically scaled handgrip), modified pull-ups, and the plank test. Participants in the National Youth Fitness Survey (n = 1,453) were tested on MSF, aerobic capacity (via submaximal treadmill test), and body composition (body mass index [BMI], waist circumference, and skinfolds). Using LMS regression, age-specific and sex-specific smoothed percentile curves of MSF were created and existing percentiles were used to assign age-specific and sex-specific z-scores for aerobic capacity and body composition. Correlation matrices were created to assess the relationships between z-scores on MSF, aerobic capacity, and body composition. At younger ages (3-10 years), boys scored higher than girls for handgrip strength and modified pull-ups, but not for the plank. By ages 13-15, differences between the boys and girls curves were more pronounced, with boys scoring higher on all tests. Correlations between tests of MSF and aerobic capacity were positive and low-to-moderate in strength. Correlations between tests of MSF and body composition were negative, excluding absolute handgrip strength, which was inversely related to other MSF tests and aerobic capacity but positively associated with body composition. The growth curves herein can be used as normative reference values or a starting point for creating health-related criterion reference standards for these tests. Comparisons with prior national surveys of physical fitness indicate that some components of MSF have likely decreased in the United States over time.

Obesity and Insulin Resistance Screening Tools in American Adolescents: National Health and Nutrition Examination Survey (NHANES) 1999 to 2010.

OBJECTIVE: To identify which feasible obesity and insulin resistance (IR) screening tools are most strongly associated in adolescents by using a nationally representative sample. METHODS: Adolescents aged 12.0 to 18.9 years who were participating in the National Health and Nutrition Examination Survey (NHANES) (n=3584) and who were measured for height, weight, waist circumference (WC), triceps and subscapular skinfold thickness, glycated hemoglobin, fasting glucose (FG) and fasting insulin (FI) level were included. Adolescents were split by gender and grouped by body mass index (BMI) percentile. Age- and gender-specific classifications were constructed for each obesity screening tool measure to account for growth and maturation. General linear models were used to establish groups objectively for analysis based on when IR began to increase. Additional general linear models were used to identify when IR significantly increased for each IR measure as obesity group increased and to identify the variance accounted for among each obesity-IR screening tool relationship. RESULTS: As the obesity group increased, homeostasis model assessment-insulin resistance (HOMA-IR) and FI significantly increased, while FG increased only (above the referent) in groups with BMI percentiles ≥95.0, and glycated hemoglobin level did not vary across obesity groups. The most strongly associated screening tools were WC and FI in boys (R(2)=0.253) and girls (R(2)=0.257). FI had the strongest association with all of the obesity measures. BMI associations were slightly weaker than WC in each in relation to IR. CONCLUSIONS: Our findings show that WC and FI are the most strongly associated obesity and IR screening tool measures in adolescents. These feasible screening tools should be utilized in screening practices for at-risk adolescents.

The Associations of Youth Physical Activity and Screen Time with Fatness and Fitness: The 2012 NHANES National Youth Fitness Survey.

The purpose of the study is to examine the associations of youth physical activity and screen time with weight status and cardiorespiratory fitness in children and adolescents, separately, utilizing a nationally representative sample. A total of 1,113 participants (692 children aged 6-11 yrs; 422 adolescents aged 12-15 yrs) from the 2012 NHANES National Youth Fitness Survey. Participants completed physical activity and screen time questionnaires, and their body mass index and cardiorespiratory fitness (adolescents only) were assessed. Adolescents completed additional physical activity questions to estimate daily MET minutes. Children not meeting the screen time guideline had 1.69 times the odds of being overweight/obese compared to those meeting the screen time guideline, after adjusting for physical activity and other control variables. Among adolescent, screen time was significantly associated with being overweight/obese (odds ratio = 1.82, 95% confidence interval: 1.06-3.15), but the association attenuated toward the borderline of being significant after controlling for physical activity. Being physically active was positively associated with cardiorespiratory fitness, independent of screen time among adolescents. In joint association analysis, children who did not meet physical activity nor screen time guidelines had 2.52 times higher odds of being overweight/obese than children who met both guidelines. Adolescents who did not meet the screen time guideline had significantly higher odds ratio of being overweight/obese regardless of meeting the physical activity guideline. Meeting the physical activity guideline was also associated with cardiorespiratory fitness regardless of meeting the screen time guideline in adolescents. Screen time is a stronger factor than physical activity in predicting weight status in both children and adolescents, and only physical activity is strongly associated with cardiorespiratory fitness in adolescents.

Cross-Validation of FITNESSGRAM® Health-Related Fitness Standards in Hungarian Youth.

PURPOSE: The purpose of this study was to cross-validate FITNESSGRAM® aerobic and body composition standards in a representative sample of Hungarian youth. METHOD: A nationally representative sample (N = 405) of Hungarian adolescents from the Hungarian National Youth Fitness Study (ages 12-18.9 years) participated in an aerobic capacity assessment via treadmill test to maximum to determine peak oxygen consumption (VO2peak) and a bioelectrical impedance assessment to estimate percent body fat (%BF). Additionally, metabolic syndrome status was assessed via finger-stick blood sample. Youth were categorized into Healthy Fitness Zone (HFZ) and Needs Improvement (NI) groups based on Fitnessgram standards. Prevalence of metabolic syndrome was calculated and logistic regression was used to estimate odds of metabolic syndrome. RESULTS: Hungarian youth were generally fit with a low prevalence of metabolic syndrome. Approximately 69% to 77% of boys and 55% to 57% of girls were classified into the HFZ based on %BF and VO2peak. Youth in the NI health risk zones for VO2peak and %BF were 4 times to 5 and 2 times to 3 times more likely to have metabolic syndrome than children in the lower-risk groups, respectively. CONCLUSIONS: Fitnessgram standards for aerobic capacity and body composition were associated with metabolic syndrome status, though odds ratios were larger for VO2peak than for %BF and varied by sex. Even though these standards were developed in U.S. youth, they can be applied in Hungary and still provide a criterion-referenced indication of fitness.

Agreement and Diagnostic Performance of FITNESSGRAM®, International Obesity Task Force, and Hungarian National BMI Standards.

PURPOSE: This study examined agreement between all 3 standards (as well as relative diagnostic associations with metabolic syndrome) using a representative sample of youth from the Hungarian National Youth Fitness Study. METHOD: Body mass index (BMI) was assessed in a field sample of 2,352 adolescents (ages 10-18.5 years) and metabolic syndrome status was assessed in a laboratory subsample of 373 youth. All youth were categorized into weight status groups based on the FITNESSGRAM®, International Obesity Task Force (IOTF), and Hungarian growth standards. Classification agreement was compared between all pairs of standards via cross-tabulation. Logistic regression was used to estimate the odds of metabolic syndrome by weight status. RESULTS: The 3 BMI standards agreed on ≥  88% of cases, with better agreement on girls' standards than boys' standards. Kappa values ranged from .65 to .89. Using the Hungarian standards over the Fitnessgram or IOTF standards resulted in 5% to 10% more youth being classified as normal weight. The overweight/obesity groups were 4 times to 6 times more likely to have metabolic syndrome than those classified as normal weight regardless of the classification standards. These odds ratios increased to 8 times to 17 times when comparing the normal-weight/overweight groups to the obesity category. Odds ratios for boys tended to be slightly larger than those for girls. CONCLUSIONS: All 3 standards provide similar information about weight status and metabolic syndrome classification. To more easily facilitate international comparisons, it may be of greater benefit to use the IOTF standards, which also had better agreement with the U.S. Fitnessgram thresholds.

Establishing Normative Reference Values for Handgrip Among Hungarian Youth.

PURPOSE: The purpose of this study was to examine age- and sex-related variation in handgrip strength and to determine reference values for the Hungarian population. METHOD: A sample of 1,086 Hungary youth (aged 11-18 years old; 654 boys and 432 girls) completed a handgrip strength assessment using a handheld dynamometer. Quantile regression was used to compute separate models for boys and girls and included a linear, cubic, and quadratic term for age to account for nonlinear patterns. These terms were tested for statistical significance using the Wald statistical test with p < .05. Age- and sex-specific centiles were generated and the 50th percentile was used to describe the overall patterns in handgrip strength. RESULTS: The linear, cubic, and quadratic terms for age fitted the data well for boys (p < .05), while both linear and quadratic terms for age were statistically significant for girls (p < .05). The 50th percentile values resulted in 21.4 kg, 21.7 kg, 25.0 kg, 30.0 kg, 35.4 kg, 40.0 kg, 42.6 kg, and 42.0 kg for boys aged 11 to 18 years old, respectively. The same percentile resulted in 20.0 kg, 19.5 kg, 19.6 kg, 20.3 kg, 21.6 kg, 23.5 kg, 26.1 kg, and 29.2 kg for girls aged 11 to 18 years old, respectively. CONCLUSIONS: Muscle strength as determined by handgrip has distinct age-related patterns in boys and girls. We have accounted for biological age differences and developed norm-referenced values that can be used to interpret handgrip assessment scores obtained from school-aged children in Hungary.

Establishing Normative Reference Values for Standing Broad Jump Among Hungarian Youth.

PURPOSE: The purpose of this study was to examine age and sex trends in anaerobic power assessed by a standing broad jump and to determine norm-referenced values for youth in Hungary. METHOD: A sample of 2,427 Hungarian youth (1,360 boys and 1,067 girls) completed the standing broad jump twice, and the highest distance score was recorded. Quantile regression was used to fit standing broad jump trends across linear and quadratic functions of age. Statistical significance was determined with bootstrap confidence intervals and the Wald test with p < .05. Age-by-sex specific centiles were generated and the 50th percentile was used to describe the overall patterns. RESULTS: Standing broad jump scores increased steadily in boys from age 11 through 18 years with a discrete plateau at the end of adolescence. Girls' standing broad jump scores of those who performed above the median increased with age and plateaued later in the adolescence. Both linear and quadratic age terms were statistically significant predictors of standing broad jump trends across age (p < .05), but the relations varied depending on the percentile. The 50th percentile values resulted in 147.0 cm, 162.0 cm, 175.0 cm, 186.0 cm, 195.0 cm, 202.0 cm, 207.0 cm, and 210.0 cm for boys aged 11 to 18 years old, respectively, and 140.0 cm, 143.9 cm, 147.3 cm, 150.0 cm, 152.1 cm, 153.7 cm, 154.6 cm, and 155.0 cm for girls aged 11 to 18 years old, respectively. CONCLUSIONS: This study provides normative reference charts that take into account age and sex differences in standing broad jump performance. The proposed reference values can be used to interpret standing broad jump scores in Hungarian youth.

Concurrent validation of the Actigraph gt3x+, Polar Active accelerometer, Omron HJ-720 and Yamax Digiwalker SW-701 pedometer step counts in lab-based and free-living settings.

Activity monitors are frequently used to assess activity in many settings. But as technology advances, so do the mechanisms used to estimate activity causing a continuous need to validate newly developed monitors. The purpose of this study was to examine the step count validity of the Yamax Digiwalker SW-701 pedometer (YX), Omron HJ-720 T pedometer (OP), Polar Active accelerometer (PAC) and Actigraph gt3x+ accelerometer (AG) under controlled and free-living conditions. Participants completed five stages of treadmill walking (n = 43) and a subset of these completed a 3-day free-living wear period (n = 37). Manually counted (MC) steps provided a criterion measure for treadmill walking, whereas the comparative measure during free-living was the YX. During treadmill walking, the OP was the most accurate monitor across all speeds (±1.1% of MC steps), while the PAC underestimated steps by 6.7-16.0% per stage. During free-living, the OP and AG counted 97.5% and 98.5% of YX steps, respectively. The PAC overestimated steps by 44.0%, or 5,265 steps per day. The Omron pedometer seems to provide the most reliable and valid estimate of steps taken, as it was the best performer under lab-based conditions and provided comparable results to the YX in free-living. Future studies should consider these monitors in additional populations and settings.

Estimating physical activity in children: impact of pedometer wear time and metric.

BACKGROUND: The purpose of this study was to provide a practical demonstration of the impact of monitoring frame and metric when assessing pedometer-determined physical activity (PA) in youth. METHODS: Children (N = 1111) were asked to wear pedometers over a 7-day period during which time worn and steps were recorded each day. Varying data-exclusion criteria were used to demonstrate changes in estimates of PA. Steps were expressed using several metrics and criteria, and construct validity was demonstrated via correlations with adiposity. RESULTS: Meaningful fluctuations in average steps per day and percentage meeting PA recommendations were apparent when different criteria were used. Children who wore the pedometer longer appeared more active, with each minute the pedometer was worn each day accounting for an approximate increase of 11 and 8 steps for boys and girls, respectively (P < .05). Using more restrictive exclusion criteria led to stronger correlations between indices of steps per day, steps per minute, steps per leg length, steps per minute per leg length, and obesity. CONCLUSION: Wear time has a meaningful impact on estimates of PA. This should be considered when determining exclusion criteria and making comparisons between studies. Results also suggest that incorporating wear time per day and leg length into the metric may increase validity of PA estimates.