Youngwon Kim

Validity of consumer-based physical activity monitors.

BACKGROUND Many consumer-based monitors are marketed to provide personal information on the levels of physical activity and daily energy expenditure (EE), but little or no information is available to substantiate their validity. PURPOSE This study aimed to examine the validity of EE estimates from a variety of consumer-based, physical activity monitors under free-living conditions. METHODS Sixty (26.4 ± 5.7 yr) healthy males (n = 30) and females (n = 30) wore eight different types of activity monitors simultaneously while completing a 69-min protocol. The monitors included the BodyMedia FIT armband worn on the left arm, the DirectLife monitor around the neck, the Fitbit One, the Fitbit Zip, and the ActiGraph worn on the belt, as well as the Jawbone Up and Basis B1 Band monitor on the wrist. The validity of the EE estimates from each monitor was evaluated relative to criterion values concurrently obtained from a portable metabolic system (i.e., Oxycon Mobile). Differences from criterion measures were expressed as a mean absolute percent error and were evaluated using 95% equivalence testing. RESULTS For overall group comparisons, the mean absolute percent error values (computed as the average absolute value of the group-level errors) were 9.3%, 10.1%, 10.4%, 12.2%, 12.6%, 12.8%, 13.0%, and 23.5% for the BodyMedia FIT, Fitbit Zip, Fitbit One, Jawbone Up, ActiGraph, DirectLife, NikeFuel Band, and Basis B1 Band, respectively. The results from the equivalence testing showed that the estimates from the BodyMedia FIT, Fitbit Zip, and NikeFuel Band (90% confidence interval = 341.1-359.4) were each within the 10% equivalence zone around the indirect calorimetry estimate. CONCLUSIONS The indicators of the agreement clearly favored the BodyMedia FIT armband, but promising preliminary findings were also observed with the Fitbit Zip.

Everything you wanted to know about selecting the “right” Actigraph accelerometer cut-points for youth, but…: A systematic review

OBJECTIVES The purpose of this study is to provide an overview of the evidence on the calibration of ActiGraph accelerometers to quantify moderate-to-vigorous physical activity (MVPA) for youth through the use of cut-points and describe the independent validation studies comparing the accuracy of the developed cut-points to a criterion measure. DESIGN A systematic review. METHODS Studies were identified that: (a) developed ActiGraph accelerometer cut-points for children and youth (calibration study); or (b) performed an independent validation of already established cut-points (validation study). Both calibration studies and independent validation studies were retrieved through a systematic search of online databases. According to proposed guidelines for designing accelerometer calibration studies, each calibration study was evaluated on the following criteria: quality of a criterion measure employed; epoch length; inclusion of a variety of activities; and sample size. RESULTS A total of 11 calibration studies were identified. Two studies met all four criteria for a calibration study. A total of 4 independent validation studies were identified. Three of them reported that no cut-points accurately classified moderate-to-vigorous physical activity (MVPA) across all ranges of physical activity intensity levels in comparison to a criterion measure. The fourth study reported two sets of cut-points that under laboratory conditions, accurately classified moderate-to-vigorous physical activity (MVPA) compared to indirect calorimetry. CONCLUSIONS Limited evidence suggests that two sets of cut-points correctly classify ActiGraph counts into moderate-to-vigorous physical activity (MVPA). However, limitations with calibration and validation studies indicate greater efforts aimed at designing high quality studies are needed to confirm these findings.

Comparison of Consumer and Research Monitors under Semistructured Settings.

PURPOSE This study evaluated the relative validity of different consumer and research activity monitors during semistructured periods of sedentary activity, aerobic exercise, and resistance exercise. METHODS Fifty-two (28 male and 24 female) participants age 18-65 yr performed 20 min of self-selected sedentary activity, 25 min of aerobic exercise, and 25 min of resistance exercise, with 5 min of rest between each activity. Each participant wore five wrist-worn consumer monitors [Fitbit Flex, Jawbone Up24, Misfit Shine (MS), Nike+ Fuelband SE (NFS), and Polar Loop] and two research monitors [ActiGraph GT3X+ on the waist and BodyMedia Core (BMC) on the arm] while being concurrently monitored with Oxycon Mobile (OM), a portable metabolic measuring system. Energy expenditure (EE) on different activity sessions was measured by OM and estimated by all monitors. RESULTS Mean absolute percent error (MAPE) values for the full 80-min protocol ranged from 15.3% (BMC) to 30.4% (MS). EE estimates from ActiGraph GT3X+ were found to be equivalent to those from OM (± 10% equivalence zone, 285.1-348.5). Correlations between OM and the various monitors were generally high (ranged between 0.71 and 0.90). Three monitors had MAPE values lower than 20% for sedentary activity: BMC (15.7%), MS (18.2%), and NFS (20.0%). Two monitors had MAPE values lower than 20% for aerobic exercise: BMC (17.2%) and NFS (18.5%). None of the monitors had MAPE values lower than 25% for resistance exercise. CONCLUSION Overall, the research monitors and Fitbit Flex, Jawbone Up24, and NFS provided reasonably accurate total EE estimates at the individual level. However, larger error was evident for individual activities, especially resistance exercise. Further research is needed to examine these monitors across various activities and intensities as well as under real-world conditions.

Examination of Different Accelerometer Cut-Points for Assessing Sedentary Behaviors in Children

Background Public health research on sedentary behavior (SB) in youth has heavily relied on accelerometers. However, it has been limited by the lack of consensus on the most accurate accelerometer cut-points as well as by unknown effects caused by accelerometer position (wrist vs. hip) and output (single axis vs. multiple axes). The present study systematically evaluates classification accuracy of different Actigraph cut-points for classifying SB using hip and wrist-worn monitors and establishes new cut-points to enable use of the 3-dimensional vector magnitude data (for both hip and wrist placement). Methods A total of 125 children ages 7–13 yrs performed 12 randomly selected activities (from a set of 24 different activities) for 5 min each while wearing tri-axial Actigraph accelerometers on both the hip and wrist. The accelerometer data were categorized as either sedentary or non-sedentary minutes using six previously studied cut-points: 100counts-per-minute (CPM), 200CPM, 300CPM, 500CPM, 800CPM and 1100CPM. Classification accuracy was evaluated with Cohens Kappa (κ) and new cut-points were identified from Receiver Operating Characteristic (ROC). Results Of the six cut-points, the 100CPM value yielded the highest classification accuracy (κ = 0.81) for hip placement. For wrist placement, all of the cut-points produced low classification accuracy (ranges of κ from 0.44 to 0.67). Optimal sedentary cut-points derived from ROC were 554.3CPM (ROC-AUC of 0.99) for vector magnitude for hip, 1756CPM (ROC-AUC of 0.94) for vertical axis for wrist, and 3958.3CPM (ROC-AUC of 0.93) for vector magnitude for wrist placement. Conclusions The 100CPM was supported for use with vertical axis for hip placement, but not for wrist placement. The ROC-derived cut-points can be used to classify youth SB with the wrist and with vector magnitude data.

The effect of reintegrating Actigraph accelerometer counts in preschool children: Comparison using different epoch lengths

OBJECTIVES The purpose of this study was to determine whether ActiGraph accelerometer activity counts and estimates of moderate-to-vigorous physical activity collected at a single larger epoch are comparable to those collected at smaller epochs reintegrated into a larger epoch. DESIGN A cross-sectional study design. METHODS Thirty-one preschoolers (3-5years) concurrently wore four accelerometers that were each initialized at four different epoch lengths (1s, 15s, 30s, and 60s) during a full preschool day. Counts collected at 1s, 15s, and 30s epoch were each reintegrated and compared to those collected at a larger epoch (e.g., counts from one 15s epoch vs. consecutive sum of counts from fifteen 1s epochs). Six sets of cut-points (Pate, Freedson, Sirard, Van Cauwenberghe, Evenson and Puyau) were applied to estimate moderate-to-vigorous physical activity minutes. Paired t-test and Cohens d were used to compare group mean differences. Absolute percent errors Bland-Altman plots with limits of agreement were used to compare individual differences. RESULTS Minimal group mean differences were found for counts and moderate-to-vigorous physical activity estimates between larger and reintegrated epochs. Relatively smaller absolute percent errors (6.2-9.2%) and limits of agreements (-15.52%, 18.00% to -28.27%, 28.02%) were observed for counts than absolute percent errors (10.1-50.3%) and limits of agreements (-27.3%, 33.3% to -156.9%, 137.9%) for moderate-to-vigorous physical activity estimates. CONCLUSIONS Smaller individual differences in activity counts tended to yield larger individual variations in moderate-to-vigorous physical activity estimates, despite minimal group mean differences. Therefore, researchers reintegrating smaller epochs into a larger epoch should be conscious of possible differences in moderate-to-vigorous physical activity estimates obtained from a single larger epoch.

Validity of 24-h physical activity recall: physical activity measurement survey.

PURPOSE The primary purpose of this study was to evaluate the validity of an interviewer-administered, 24-h physical activity recall (PAR) compared with that of the SenseWear Armband (SWA) for estimation of energy expenditure (EE) and moderate-to-vigorous physical activity (MVPA) in a representative sample of adults. A secondary goal was to compare measurement errors for various demographic subgroups (gender, age, and weight status). METHODS A sample of 1347 adults (20-71 yr, 786 females) wore an SWA for a single day and then completed a PAR, recalling the previous days physical activity. The participants each performed two trials on two randomly selected days across a 2-yr time span. The EE and MVPA values for each participant were averaged across the 2 d. Group-level and individual-level agreement were evaluated using 95% equivalence testing and mean absolute percent error, respectively. Results were further examined for subgroups by gender, age, and body mass index. RESULTS The PAR yielded equivalent estimates of EE (compared with those in the SWA) for almost all demographic subgroups, but none of the comparisons for MVPA were equivalent. Smaller mean absolute percent error values were observed for EE (ranges from 10.3% to 15.0%) than those for MVPA (ranges from 68.6% to 269.5%) across all comparisons. The PAR yielded underestimates of MVPA for younger, less obese people but overestimates for older, more obese people. CONCLUSIONS For EE measurement, the PAR demonstrated good agreement relative to the SWA. However, the use of PAR may result in biased estimates of MVPA both at the group and individual level in adults.

Validation of the SenseWear mini armband in children during semi-structure activity settings

OBJECTIVES The purpose of the study is to evaluate the validity of different SenseWear software (algorithms v5.2 vs. algorithm v2.2) for estimating energy expenditure (EE) in children. DESIGN Original research. METHODS Forty-five children aged 7-13 years performed 12 randomly assigned activities (out of a set of 24) while wearing a SWA with simultaneous monitoring via portable calorimetry (IC). Each activity lasted 5min, with a 1min break between activities. The estimated EE values from the SWA were compared to the measured EE values from the IC using 3-way (Method×Algorithm×Activity) mixed model ANOVA. RESULTS The analyses revealed a significant method (IC vs. SWA)×Algorithm (v5.2 vs. v2.2) interaction, with significantly smaller errors (IC-SWA) for the newer v5.2 algorithms (0.25±0.09kcalmin(-1)) than the older v2.2 algorithms (1.04±0.09kcalmin(-1)). The mean absolute percent error (MAPE) was 17.0±12.1% for SWA5.2 algorithm and 31.4±11.1% for SWA2.2 algorithm. The v5.2 algorithms yielded non-significant (p>0.5) differences in EE estimates for most of the walking related activities as well as for stationary cycling at moderate intensity (MAPE=14.5%). CONCLUSIONS The smaller errors in estimated EE with the SenseWear v5.2 algorithms (compared to v2.2) demonstrate continued incremental improvements in estimates of EE for monitoring free-living activities in children.

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.

Criterion Validity of Competing Accelerometry-Based Activity Monitoring Devices.

PURPOSE The purpose of this study was to examine the comparative and criterion validity of the three activity monitors in relation to a portable metabolic analyzer (Oxycon Mobile (OM)) in adults. METHODS A total of 52 adults age 18-40 yr each performed a series of 15 activities for 5 min each, with 1-min resting intervals between different activities. Participants completed the trials while wearing the three activity monitors and while being measured with the OM. Estimates of energy expenditure (EE) were obtained from the ActiGraph (one based on the vertical axis and the other from vector magnitude) as well as from the activPAL (AP) and the Core Armband (CA). The EE estimates were converted into MET(RMR) values by standardizing EE values with each persons resting metabolic rate and then temporarily matched to facilitate minute-by-minute comparisons. Equivalence testing and mean absolute percent errors (MAPE) were used to evaluate the agreement. RESULTS MET(RMR) values from the CA were significantly equivalent to those from the OM for the overall group comparison (90% confidence interval (CI), 3.65 and 3.85 MET(RMR)) and vigorous intensity (90% CI, 8.27 and 10.10 MET(RMR)). The CA had the smallest MAPE for moderate (20.7%) and vigorous (14.5%) intensity, but the AP had smaller MAPE for sedentary activities (27.4%) and light (24.7%) intensity activities. CONCLUSIONS The CA showed good agreement relative to the OM for the overall group comparison and for moderate and vigorous activities. The AP, in contrast, was the most accurate for sedentary and light activities. The combined use of the CA and AP may yield more accurate estimates of EE than using a single monitor.

Risk Factors for Acute Kidney Injury after Congenital Cardiac Surgery in Infants and Children: A Retrospective Observational Study

Acute kidney injury (AKI) after pediatric cardiac surgery is associated with high morbidity and mortality. Modifiable risk factors for postoperative AKI including perioperative anesthesia-related parameters were assessed. The authors conducted a single-center, retrospective cohort study of 220 patients (aged 10 days to 19 years) who underwent congenital cardiac surgery between January and December 2012. The incidence of AKI within 7 days postoperatively was determined using the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Ninety-two patients (41.8%) developed AKI and 18 (8.2%) required renal replacement therapy within the first postoperative week. Among patients who developed AKI, 57 patients (25.9%) were KDIGO stage 1, 27 patients (12.3%) were KDIGO stage 2, and eight patients (3.6%) were KDIGO stage 3. RACHS-1 (Risk-Adjusted classification for Congenital Heart Surgery) category, perioperative transfusion and fluid administration as well as fluid overload were compared between patients with and without AKI. Multivariable logistic regression analyses determined the risk factors for AKI. AKI was associated with longer hospital stay or ICU stay, and frequent sternal wound infections. Younger age (<12 months) [odds ratio (OR), 4.01; 95% confidence interval (CI), 1.77–9.06], longer cardiopulmonary bypass (CPB) time (OR, 2.45; 95% CI, 1.24–4.84), and low preoperative hemoglobin (OR, 2.40; 95% CI, 1.07–5.40) were independent risk factors for AKI. Fluid overload was not a significant predictor for AKI. When a variable of hemoglobin concentration increase (>3 g/dl) from preoperative level on POD1 was entered into the multivariable analysis, it was independently associated with postoperative AKI (OR, 6.51; 95% CI, 2.23–19.03 compared with no increase). This association was significant after adjustment with patient demographics, medication history and RACHS-1 category (hemoglobin increase >3g/dl vs. no increase: adjusted OR, 6.94; 95% CI, 2.33–20.69), regardless of different age groups and cyanotic or non-cyanotic heart disease. Prospective trials are required to evaluate whether correction of preoperative anemia and prevention of hemoconcentration may ameliorate postoperative AKI in patients who underwent congenital cardiac surgery.