BACKGROUND:Wearable activity monitors are widely used to measure daily step counts, a simple and health-relevant metric of physical activity. However, differences in sensor technologies, algorithms, and wear locations across devices can result in substantial variability in step count estimates, creating challenges for comparing and harmonizing data across studies and populations. This study aims to compare free-living daily step counts across commonly used activity monitoring devices in adults using network meta-analysis. METHODS:We systematically searched PubMed, Scopus, and PsycINFO through November 2025 for studies reporting concurrent daily step measurements using at least 2 devices from our target list of 13 manufacturers of research- and consumer-grade accelerometers and pedometers. Network meta-analysis estimated the ratio of means (ROMs) and mean differences in daily steps between devices. RESULTS:Across 59 studies, most consumer devices, pedometers, and the thigh (ActivPAL) and hip-worn research devices (ActiGraph GT, Axivity, and Actical) were within 10% ROM and <700 steps/day. Wear location was the primary source of variation, with wrist-worn and ankle-worn (StepWatch) research-grade accelerometers estimating 15‒30% more daily steps (+1000 to 2200 steps/day) than hip-worn devices, while consumer-grade wrist devices showed smaller differences (3‒15% higher or +200 to 1000 steps/day). CONCLUSION:These findings provide researchers with evidence-based guidance for selecting appropriate step devices, interpreting step count data across studies, and considerations when combining data from multiple device types and wear locations.

Non-Hispanic Black (NHB) men engage in less aerobic physical activity (PA) and are less likely to meet national guidelines than non-Hispanic White men, despite PA's protective benefits against chronic disease. This study examined psychosocial factors associated with meeting PA guidelines among NHB men. A total of 134 participants (M = 36.7 years, SD = 9.8) were recruited via social media and completed validated measures of motivation, psychological needs, and self-efficacy. Forward stepwise logistic regression identified scheduling self-efficacy as the strongest independent correlate of meeting PA guidelines (OR = 2.31, 95% CI: 1.49-3.57), above intrinsic motivation, autonomy, and competence. These findings suggest that the ability to manage time and integrate PA into daily routines may be more critical than motivation alone. PA interventions for NHB men may benefit from focusing on planning strategies, self-regulatory skills, and culturally relevant community support to improve engagement and reduce health disparities.

Background: A shift from self-reports to wearable sensors for global physical activity (PA) surveillance has been recommended. The conventional use of a generic cut-point to assess moderate-to-vigorous PA (MVPA) is problematic as these cut-points are often derived from non-representative samples under non-ecological laboratory conditions. This study aimed to develop age- and sex- (age-sex) specific cut-points for MVPA based on population-standardized values as a feasible approach to assess the adherence to PA guidelines and to investigate its associations with all-cause mortality. Methods: A total of 7601 participants (20-85+ years) were drawn from the 2003-2004 and 2005-2006 National Health and Nutrition Examination Surveys (NHANES). Minutes per week of MVPA were assessed with a hip-worn accelerometer. Counts per minute (CPM) were used to define an age-sex specific target intensity, representing the intensity each person should be able to reach based on their age and sex. Age-sex specific MVPA cut-points were defined as any activity above 40% of the target intensity. These population- and free-living-based age-sex specific cut-points overcome many of the limitations of the standard generic cut-point approach. For comparison, we also calculated MVPA with a generic cut-point of 1952 CPM. Both approaches were compared for assessing adherence to PA guidelines and association of MVPA with all- cause mortality (ascertained through December 2015). Results: Both approaches indicated that 37% of the sample met the 150+ min/week guideline. The generic cut-point approach showed a trend to inactivity with age, which was less pronounced using the age-sex specific cut-points. Overall mortality rates were comparable using generic cut- point (hazard ratio (HR) = 0.61, 95% confidence interval (95%CI): 0.50-0.73) or age-sex specific cut-points (HR = 0.57, 95%CI: 0.50-0.66) for the entire sample. The generic cut-point method revealed an age- and sex-related gap in the benefits of achieving 150+ min/week of MVPA, with older adults showing an 18% greater reduction in mortality rates than younger adults, and a larger difference in women than in men. This disparity disappeared when using age-sex specific cut-points. Conclusion: Our findings underscore the value of age-sex specific cut-points for global PA surveillance. MVPA defined with age-sex specific thresholds was associated with all-cause mortality and the dose-response was similar for all ages and sexes. This aligns with the single recommendation of accumulating 150+ min/week MVPA for all adults, irrespective of age and sex. This study serves as a proof of concept to develop this methodology for PA surveillance over more advanced open-source acceleration metrics and other national and international cohorts.

ABSTRACT Purpose The primary aim of this study was to compare steps per day across ActiGraph models, wear locations, and filtering methods. A secondary aim was to compare ActiGraph steps per day to those estimated by the ankle-worn StepWatch. Methods We conducted a systematic literature review to identify studies of adults published before May 12, 2022, that compared free-living steps per day of ActiGraph step counting methods and studies that compared ActiGraph to StepWatch. Random-effects meta-analysis compared ActiGraph models, wear locations, filter mechanisms, and ActiGraph to StepWatch steps per day. A sensitivity analysis of wear location by younger and older age was included. Results Twelve studies, with 46 comparisons, were identified. When worn on the hip, the AM-7164 recorded 123% of the GT series steps (no low-frequency extension (no LFE) or default filter). However, the AM-7164 recorded 72% of the GT series steps when the LFE was enabled. Independent of the filter used (i.e., LFE, no LFE), ActiGraph GT series monitors captured more steps on the wrist than on the hip, especially among older adults. Enabling the LFE on the GT series monitors consistently recorded more steps, regardless of wear location. When using the default filter (no LFE), ActiGraph recorded fewer steps than StepWatch (ActiGraph on hip 73% and ActiGraph on wrist 97% of StepWatch steps). When LFE was enabled, ActiGraph recorded more steps than StepWatch (ActiGraph on the hip, 132%; ActiGraph on the wrist, 178% of StepWatch steps). Conclusions The choice of ActiGraph model, wear location, and filter all impacted steps per day in adults. These can markedly alter the steps recorded compared with a criterion method (StepWatch). This review provides critical insights for comparing studies using different ActiGraph step counting methods.

Transportation modes that involve physical activity are referred to as active transportation; these include walking and bicycling, as well as the use of public transport. Ecological, cross-sectional, and longitudinal studies have shown that active transportation can help individuals meet physical activity recommendations and reduce their risk of developing obesity. However, transportation policies impact the use of active transportation. Laws, regulations, and rules vary around the world and as a result, the percentage of individuals using active transportation for trips also varies greatly. Not surprisingly, in nations that are more reliant on personal automobiles, obesity rates are far higher compared to those nations where more individuals use walking and bicycling for transportation. Some nations have federal policies that promote walking, cycling, and public transit use and actively discourage the use of personal automobiles. These policies have been found to influence active transportation and as a result, have led to lower obesity rates. This chapter discusses the research on active transport as a means for decreasing the risk of obesity as well as how government policies can increase the use of active transport.

Background: Taking fewer than the widely promoted “10 000 steps per day” has recently been associated with lower risk of all-cause mortality. The relationship of steps and cardiovascular disease (CVD) risk remains poorly described. A meta-analysis examining the dose–response relationship between steps per day and CVD can help inform clinical and public health guidelines. Methods: Eight prospective studies (20 152 adults [ie, ≥18 years of age]) were included with device-measured steps and participants followed for CVD events. Studies quantified steps per day and CVD events were defined as fatal and nonfatal coronary heart disease, stroke, and heart failure. Cox proportional hazards regression analyses were completed using study-specific quartiles and hazard ratios (HR) and 95% CI were meta-analyzed with inverse-variance–weighted random effects models. Results: The mean age of participants was 63.2±12.4 years and 52% were women. The mean follow-up was 6.2 years (123 209 person-years), with a total of 1523 CVD events (12.4 per 1000 participant-years) reported. There was a significant difference in the association of steps per day and CVD between older (ie, ≥60 years of age) and younger adults (ie, <60 years of age). For older adults, the HR for quartile 2 was 0.80 (95% CI, 0.69 to 0.93), 0.62 for quartile 3 (95% CI, 0.52 to 0.74), and 0.51 for quartile 4 (95% CI, 0.41 to 0.63) compared with the lowest quartile. For younger adults, the HR for quartile 2 was 0.79 (95% CI, 0.46 to 1.35), 0.90 for quartile 3 (95% CI, 0.64 to 1.25), and 0.95 for quartile 4 (95% CI, 0.61 to 1.48) compared with the lowest quartile. Restricted cubic splines demonstrated a nonlinear association whereby more steps were associated with decreased risk of CVD among older adults. Conclusions: For older adults, taking more daily steps was associated with a progressively decreased risk of CVD. Monitoring and promoting steps per day is a simple metric for clinician–patient communication and population health to reduce the risk of CVD.

INTRODUCTION:Conflicting evidence exists on whether physical activity (PA) levels of humans have changed over the last quarter-century. The main objective of this study was to determine if there is evidence of time trends in PA, from cross-sectional studies that assessed PA at different time points using wearable devices (e.g., pedometers and accelerometers). A secondary objective was to quantify the rate of change in PA. METHODS:A systematic literature review was conducted of English-language studies indexed in PubMed, SPORTDiscus, and Web of Science (1960-2020) using search terms (time OR temporal OR secular) AND trends AND (steps per day OR pedometer OR accelerometer OR MVPA). Subsequently, a meta-analytic approach was used to aggregate data from multiple studies and to examine specific factors (i.e., sex, age-group, sex and age-group, and PA metric). RESULTS:Based on 16 peer-reviewed scientific studies conducted between 1995 and 2017, levels of ambulatory PA are trending downward in developed countries. Significant declines were seen in both males and females (P < 0.001) as well as in children (P = 0.020), adolescents (P < 0.001), and adults (P = 0.004). The average study duration was 9.4 yr (accelerometer studies, 5.3 yr; pedometer studies, 10.8 yr). For studies that assessed steps, the average change in PA was -1118 steps per day over the course of the study (P < 0.001), and adolescents had the greatest change in PA at -2278 steps per day (P < 0.001). Adolescents also had the steepest rate of change over time, expressed in steps per day per decade. CONCLUSIONS:Evidence from studies conducted in eight developed nations over a 22-yr period indicates that PA levels have declined overall, especially in adolescents. This study emphasizes the need for continued research tracking time trends in PA using wearable devices.

Department of Kinesiology, Recreation, and Sport Studies, The University of Tennessee, Knoxville, TN Address for Correspondence: David R. Bassett Jr., Ph.D., Department of Kinesiology, Recreation, and Sport Studies, University of Tennessee, 1914 Andy Holt Avenue, Knoxville, TN 37996; E-mail: [email protected]. Submitted for publication August 2022. Accepted for publication August 2022.

Introduction: The goal of 10,000 steps/day is widely promoted. There is limited evidence, however, of the number of steps/day associated with risk of developing cardiovascular disease (CVD). Hypothesis: We hypothesize a dose-response association between higher device-measured steps/day with lower CVD incidence. Methods: The Steps for Health Collaborative conducted a meta-analysis of seven prospective studies with device-measured steps/day and followed participants for CVD events. Participants without CVD at baseline were included. CVD was defined as coronary heart disease, stroke, and/or heart failure. Data were analyzed at the study level. Study-specific associations of quartiles of steps/day with incident CVD was assessed using Cox proportional hazards regression models and summarized using random effects meta-analysis. Models were adjusted for age, race/ethnicity, sex, body mass index, device wear time, and study-specific indicators for education or income, smoking, alcohol intake, blood pressure, dysglycemia, and hyperlipidemia. Study heterogeneity was assessed using I2 statistic. Results: The meta-analysis included 16,906 adults (mean age 62 years; 51% women), with median follow-up of 6.3 years (limits 2.9-10.7 years) and 1370 (8.1%) CVD events. Medians of study-specific steps/day were 1,951 (first quartile, Q1), 3,823 (second quartile, Q2), 5,685 (third quartile, Q3), and 9,487 (fourth quartile, Q4). Compared with Q1, summary hazard ratios for CVD were 0.83 (Q2, 95% confidence interval 0.72-0.95), 0.68 (Q3, 0.58-0.80), and 0.60 (Q4, 0.47-0.78) (Figure). There was low to moderate heterogeneity; I2 values were 0% for Q2, 2% for Q3, and 37% for Q4. Conclusions: Higher steps/day were associated with progressively lower risk of CVD. Monitoring and promoting steps/day can be a simple, easy to interpret metric used for clinician-patient communication and population health to reduce the risk of CVD.

ABSTRACT This study aimed 1) to determine the step count accuracy of numerous wrist-, hip-, and thigh-worn consumer and research monitors (and their corresponding algorithms) compared with the StepWatch (SW) across all waking hours under free-living conditions and 2) to develop correction methods to calibrate all monitors to the SW. Forty-eight participants 28 ± 12 yr old (mean ± SD) wore monitors across two waking days. Different wrist (Apple Watch Series 2, Fitbit Alta, Garmin vivofit 3, and ActiGraph GT9X), hip (Yamax Digiwalker SW-200, Omron HJ-325, GT9X, and Fitbit Zip), and thigh (activPAL) monitors were worn across 2 d, with the exception of the SW, which was worn on both days. Monitor estimates were compared with SW to compute percent of SW steps, absolute percent error, mean difference, root-mean-square error, and Pearson correlations. Monitor-specific correction factor linear regression models were fit to estimate SW steps and evaluated using leave-one-subject-out cross validation. All monitors were significantly different from the SW ( P < 0.05). Consumer wrist and hip monitors underestimated SW steps (72%–91% of SW steps per day), whereas step estimates from research monitors ranged widely (67%–189%). Mean absolute percent error across all devices were greater than 10%. After a correction method was applied, all monitor estimates were not significantly different from SW steps. Overall, some consumer monitors produced step estimates that are closer to the validated SW than research-grade monitors (and their corresponding algorithms) and could be used to measure steps for healthy adults under free-living conditions. The specific correction methods may facilitate comparisons across studies and support research efforts using consumer and research monitors for large-scale population surveillance and epidemiological studies.

Active transportation is defined as self-propelled, human-powered transportation modes, such as walking and bicycling. In this article, we review the evidence that reliance on gasoline-powered transportation is contributing to global climate change, air pollution, and physical inactivity and that this is harmful to human health. Global climate change poses a major threat to human health and in the future could offset the health gains achieved over the last 100 yr. Based on hundreds of scientific studies, there is strong evidence that human-caused greenhouse gas emissions are contributing to global climate change. Climate change is associated with increased severity of storms, flooding, rising sea levels, hotter climates, and drought, all leading to increased morbidity and mortality. Along with increases in atmospheric CO2, other pollutants such as nitrogen dioxide, ozone, and particulate matter (e.g., PM2.5) are released by combustion engines and industry, which can lead to pulmonary and cardiovascular diseases. Also, as car ownership and vehicle miles traveled have increased, the shift toward motorized transport has contributed to physical inactivity. Each of these global challenges has resulted in, or is projected to result in, millions of premature deaths each year. One of the ways that nations can mitigate the health consequences of climate change, air pollution, and chronic diseases is through the use of active transportation. Research indicates that populations that rely heavily on active transportation enjoy better health and increased longevity. In summary, active transportation has tremendous potential to simultaneously address three global public health challenges of the 21st century.

PURPOSE: The simplicity of steps/day as a metric makes it appealing for physical activity promotion in clinical and population settings. Summarizing the association of steps and health can advance health promotion guidelines. The Steps for Health Collaborative is compiling data from cohort studies for meta-analysis with device-measured steps and prospective health outcomes. To harmonize data, it is important to examine how step estimates may differ by device and demographic characteristics. Our objective was to describe daily steps in the participating cohort studies by age, sex and step-counting device. METHODS: Steps/day were summarized from 11 cohorts in 6 countries. We report the cohort-specific steps/day measured from pedometers (2 studies; waist worn) or accelerometers (9 studies; 8 waist, 1 thigh worn). Medians and interquartile ranges (IQRs) of steps/day were calculated for each study for the total sample and by sex. RESULTS: Median steps ranged from 4398 to 9418 steps/day (Figure). Cohorts with older participants (age ≥ 60 years) generally had lower median steps/day compared to younger aged cohorts. Cohorts of comparable ages, using the same device, had similar estimates of median steps/day for totals and by sex. Similar steps/day for total samples were observed for CARDIA (9146 [IQR: 7307-11162]) and NHANES (8055 [IQR: 5489-10681]) using the ActiGraph 7164, HCHS/SOL (7318 [IQR: 4985-10525]) and FHS (7312 [IQR: 5362-9901]) using the Actical, and WHS (5094 [IQR:3609-6927]) and BRHS (4398 [IQR:2842-6316]) using the ActiGraph GT3X. CONCLUSIONS: Daily steps were consistently reported in studies using similar devices and in men and women. Many of the cohorts are predominantly white, limiting generalizability. Across all studies, there was about 5000 steps/day range in medians, which may be influenced by device, country, and age. Further understanding these study-level variables across prospective cohorts will benefit meta-analyses of steps and health.

Previous studies suggest that the magnitude of morbidity/mortality reduction may differ between race-ethnic groups despite equated dose of physical activity (PA). The purpose of this study was to compare the potential racial-ethnic differences in cardiometabolic risk factors (CMRF) across quartiles of accelerometer-derived total activity counts/day (TAC/d) among US adults. The final sample (n=4144) included adults who participated in the 2003–2006 National Health and Nutrition Examination Survey (NHANES). CMRF included fasting glucose (FG), fasting insulin (FI), HOMA-IR, resting systolic (SBP) and diastolic blood pressure (DBP), waist circumference (WC), BMI, CRP, HDL-C, LDL-C, and triglycerides. Race-ethnic groups examined included non-Hispanic white (NHW), non-Hispanic black (NHB), and Mexican American (MA). In the highest quartile, NHW had significantly lower values of HOMA-IR, FI, SBP, BMI, WC, and HDL-C when compared to NHB. Compared to MA in the highest quartile, NHW had significantly lower values of HOMA-IR, FI, BMI, and triglycerides. Significant race-ethnic differences were found for several CMRF, especially among those who were in the top quartile of PA (e.g., the most active adults). It is probable that the protective effect of higher volumes of PA on CMRF is moderated by other non-PA factors distinct to NHB and MA.

Background: Active commuting is inversely related with cardiovascular disease (CVD) risk factors yet associations with CVD prevalence in the US population are unknown. Methods: Aggregate data from national surveys conducted in 2017 provided state-level percentages of adults who have/had coronary heart disease, myocardial infarction, and stroke, and who actively commuted to work. Associations between active commuting and CVD prevalence rates were assessed using Pearson correlations and generalized additive models controlling for covariates. Results: Significant correlations were observed between active commuting and all CVD rates (r range = -.31 to -.47; P < .05). The generalized additive model analyses for active commuting (walking, cycling, or public transport) in all adults found no relationships with CVD rates; however, a significant curvilinear association was observed for stroke within men. The generalized additive model curves when examining commuting via walking or cycling in all adults demonstrated nuanced, generally negative linear or curvilinear associations between coronary heart disease, myocardial infarction, and stroke. Conclusion: Significant negative correlations were observed between active commuting and prevalence rates of coronary heart disease, myocardial infarction, and stroke. Controlling for covariates influenced these associations and highlights the need for future research to explore the potential of active commuting modes to reduce CVD in the United States.

Introduction: Previous studies have revealed a significant, inverse dose-response relationship between total activity counts/day (TAC/d) and several cardiometabolic risk factors (CMRF). An ongoing line of research is the examination of the contributions of behavioral, environmental, and physiological factors to CMRF differences across race-ethnicity. However, it is unknown if these differences exist among the most physically active adults. Hypothesis: Among the most active U.S. adults, we hypothesize that CMRF measures will differ across race-ethnic groups. Methods: Study sample (n=1,059) included adult (20-79 years of age) participants from the 2003-2006 NHANES who wore an ActiGraph model 7164 accelerometer on the right hip. The top quartile of accelerometer-derived age- and gender-specific TAC/d was used as a cutpoint to define the “most active”. All participants were without T2D (fasting glucose <126 mg/dL, no medication, no self-reported diagnosis) and without CVD (self-report). CMRF included HOMA-IR, fasting insulin and glucose, systolic (SBP) and diastolic blood pressure (DBP), HDL, LDL, triglycerides, BMI, waist circumference (WC) and C-reactive protein (CRP). Multiple linear regression was used to examine CMRF differences between non-Hispanic white (NHW), non-Hispanic black (NHB) and Mexican American (MA) participants. Regression models were adjusted for age, sex, education, smoking, wear time, BMI (except BMI and WC models), objectively-measure MVPA (≥760 counts/min) and race-ethnicity. Results: No significant differences were found in mean TAC/d across race-ethnicity. When compared to NHW, NHB had significantly higher HOMA-IR, fasting insulin, SBP, WC, and BMI. Compared to NHW, MA had significantly higher HOMA-IR, fasting insulin, triglycerides, WC and BMI. When comparing NHB to MA, MA had significantly higher triglycerides and HDL and significantly lower SBP. Conclusions: It has been proposed that the race-ethnic differences in PA participation could be contributing to disparities in elevated CMRF, but even among U.S. adults in the 75th percentile for total activity volume (i.e. TAC/d), race-ethnic differences in CMRF still exist. It is probable that other social, environmental, and genetic factors are responsible for moderating the beneficial effects PA has on CMRF specifically among NHB and MA adults.

IMPORTANCE It is unclear whether the number of steps per day and the intensity of stepping are associated with lower mortality. OBJECTIVE Describe the dose-response relationship between step count and intensity and mortality. DESIGN, SETTING, AND PARTICIPANTS Representative sample of US adults aged at least 40 years in the National Health and Nutrition Examination Survey who wore an accelerometer for up to 7 days ( from 2003-2006). Mortality was ascertained through December 2015. EXPOSURES Accelerometer-measured number of steps per day and 3 step intensity measures (extended bout cadence, peak 30-minute cadence, and peak 1-minute cadence [steps/min]). Accelerometer data were based on measurements obtained during a 7-day period at baseline. MAIN OUTCOMES AND MEASURES The primary outcome was all-cause mortality. Secondary outcomes were cardiovascular disease (CVD) and cancer mortality. Hazard ratios (HRs), mortality rates, and 95% CIs were estimated using cubic splines and quartile classifications adjusting for age; sex; race/ethnicity; education; diet; smoking status; body mass index; self-reported health; mobility limitations; and diagnoses of diabetes, stroke, heart disease, heart failure, cancer, chronic bronchitis, and emphysema. RESULTS A total of 4840 participants (mean age, 56.8 years; 2435 [54%] women; 1732 [36%] individuals with obesity) wore accelerometers for a mean of 5.7 days for a mean of 14.4 hours per day. The mean number of steps per day was 9124. There were 1165 deaths over a mean 10.1 years of follow-up, including 406 CVD and 283 cancer deaths. The unadjusted incidence density for all-cause mortality was 76.7 per 1000 person-years (419 deaths) for the 655 individuals who took less than 4000 steps per day; 21.4 per 1000 person-years (488 deaths) for the 1727 individuals who took 4000 to 7999 steps per day; 6.9 per 1000 person-years (176 deaths) for the 1539 individuals who took 8000 to 11 999 steps per day; and 4.8 per 1000 person-years (82 deaths) for the 919 individuals who took at least 12 000 steps per day. Compared with taking 4000 steps per day, taking 8000 steps per day was associated with significantly lower all-cause mortality (HR, 0.49 [95% CI, 0.44-0.55]), as was taking 12 000 steps per day (HR, 0.35 [95% CI, 0.28-0.45]). Unadjusted incidence density for all-cause mortality by peak 30 cadence was 32.9 per 1000 person-years (406 deaths) for the 1080 individuals who took 18.5 to 56.0 steps per minute; 12.6 per 1000 person-years (207 deaths) for the 1153 individuals who took 56.1 to 69.2 steps per minute; 6.8 per 1000 person-years (124 deaths) for the 1074 individuals who took 69.3 to 82.8 steps per minute; and 5.3 per 1000 person-years (108 deaths) for the 1037 individuals who took 82.9 to 149.5 steps per minute. Greater step intensity was not significantly associated with lower mortality after adjustment for total steps per day (eg, highest vs lowest quartile of peak 30 cadence: HR, 0.90 [95% CI, 0.65-1.27]; P value for trend =.34). CONCLUSIONS AND RELEVANCE Based on a representative sample of US adults, a greater number of daily steps was significantly associated with lower all-cause mortality. There was no significant association between step intensity and mortality after adjusting for total steps per day.

PURPOSE: In preparation for a behavioral physical activity (PA) intervention promoting walking/stepping in place in women diagnosed with gestational diabetes mellitus (GDM), this study sought to assess the accuracy of the Fitbit Charge 3 in recording steps during walking and stepping at three cadences in pregnant women. The study also sought to elicit women’s thoughts and feelings on the proposed walking/stepping intervention. METHODS: Women diagnosed with GDM (N=15) were recruited in the third trimester. Participants wore a Fitbit Charge 3 on the non-dominant wrist and completed a total of six 2-minute bouts that varied by mode (walking vs. stepping in place) and cadence (67, 84, and 100 steps/minute). Bout sequence was randomized. Actual steps were determined by hand-tally, the criterion, in duplicate. One-way and two-way ANOVA were used to examine differences in the mean percentage of steps recorded, by mode and cadence. Participants also completed a 20-minute semi-structured interview with questions on opportunities for PA, challenges to PA, PA preferences, and use of a FitBit to track steps and set goals during walking/stepping. Interviews were audio-recorded and transcribed, then analyzed using descriptive and interpretive coding to identify themes. RESULTS: There was a statistically significant difference in the percentage of steps recorded by cadence (p< .01), but not by mode (p=.23); no interaction was detected between mode and cadence (p=.17). Analyses of cadence only suggested that 67 steps/minutes (lowest) may differ significantly from the other cadences (67 steps/minute = 113%, 84 steps/minute 97%, 100 steps/minute = 95%; p=.05). In the interviews, most reflected on the complexity of their lives making daily PA difficult, and indicated preference for three 10-minute bouts of walking/stepping over one 30-minute bout per day. CONCLUSIONS: The Fitbit Charge 3 may overestimate steps at lower cadences. However, step count did not differ with respect to mode at the cadences examined. Results suggest that the Fitbit Charge 3’s step count is suitable for use in a behavioral PA intervention promoting walking/stepping by tracking and goal setting. Interview data additionally suggested that walking/stepping interventions for women with GDM should afford convenience and flexibility to participants.

Purpose: To assess changes in criterion validity when modifying cut-points for use in different epoch lengths. Method: Simulated free-living data came from 42 adolescents (2-hr each) and 29 adults (6-hr each) wearing a hip-worn accelerometer and portable indirect calorimeter (Cosmed K4b2). K4b2 data were classified as sedentary behavior (SB), light physical activity (LPA), or moderate-to-vigorous physical activity (MVPA), and compared to estimates from accelerometer data processed with three youth and three adult cut-points in six epoch lengths (1, 5, 10, 15, 30, and 60-s). A cut-point of 100 counts per minute was used for all SB estimates. Results: For both adolescents and adults, SB estimates in all but 60-s epochs were significantly higher than the criterion, by 18.4%-78.4% (all p < .02). CPS had varied effects on youth LPA, ranging from favorable effects for one cut-point (1.9% underestimation in 1-s epochs, versus 40.2% overestimation in the originally-calibrated epoch length; p < .01 and p = .91, respectively) to unfavorable effects for another (41.8% underestimation in 1-s epochs, versus 9.8% underestimation in the originally-calibrated epoch length; p < .01 and p = .39, respectively). Adult LPA estimates in 30-s or 60-s epochs were closest to the criterion (within 5.2%-37.3%, p = .0001-0.49). Youth MVPA estimates in 60-s epochs were closest to the criterion (within 9.5%-53.2%, all p < .05), whereas adult MVPA estimates in 1-s epochs were closest to the criterion (within 6.6%-34.2%, p = .02-0.59). Conclusion: Cut-point modification is not universally beneficial, and thus it is not recommended.

Supplemental digital content is available in the text. ABSTRACT Youth metabolic equivalents (METy) are sometimes operationally defined as multiples of predicted basal metabolic rate (METyBMR) and other times as multiples of measured resting metabolic rate (METyRMR). Purpose This study aimed to examine the comparability of METyBMR and METyRMR. Methods Indirect calorimetry data (Cosmed K4b2) were analyzed from two studies, with a total sample of 245 youth (125 male participants, 6–18 yr old, 37.4% overweight or obese). The Schofield equations were used to predict BMR, and K4b2 data from 30 min of supine rest were used to assess RMR. Participants performed structured physical activities (PA) of various intensities, and steady-state oxygen consumption was divided by predicted BMR and measured RMR to calculate METyBMR and METyRMR, respectively. Two-way (activity–METy calculation) analysis of variance was used to compare METyBMR and METyRMR (α = 0.05), with Bonferroni-corrected post hoc tests. Intensity classifications were also compared after encoding METyBMR and METyRMR as sedentary behavior (≤1.50 METy), light PA (1.51–2.99 METy), moderate PA (3.00–5.99 METy), or vigorous PA (≥6.00 METy). Results There was a significant interaction (F(30) = 3.6, P < 0.001), and METyBMR was significantly higher than METyRMR for 28 of 31 activities (P < 0.04), by 15.6% (watching television) to 23.1% (basketball). Intensity classifications were the same for both METy calculations in 69.0% of cases. Conclusions METyBMR and METyRMR differ considerably. Greater consensus is needed regarding how metabolic equivalents should be operationally defined in youth, and in the meantime, careful distinction is necessary between METyBMR and METyRMR.

BACKGROUND:This study sought to compare three sensor-based wear-time estimation methods to conventional diaries for ActiGraph wGT3X-BT accelerometers worn on the non-dominant wrist in early pregnancy.METHODS:Pregnant women (n= 108) wore ActiGraph wGT3X-BT accelerometers for 7 days and recorded their device on and off times in a diary (criterion). Average daily wear-time estimates from the Troiano and Choi algorithms and the wGT3X-BT accelerometer wear sensor were compared against the diary. The Hibbing 2-regression model was used to estimate time spent in activity (during periods of device wear) for each method. Wear-time and time spent in activity were compared with multiple repeated measures ANOVAs. Bland Altman plots assessed agreement between methods.RESULTS:Compared to the diary [825.5 minutes (795.1, 856.0)], the Choi [843.0 (95% CI 812.6, 873.5)] and Troiano [839.1 (808.7, 869.6)] algorithms slightly overestimated wear-time, whereas the sensor [774.4 (743.9, 804.9)] underestimated it, although only the sensor differed significantly from the diary (P < .0001). Upon adjustment for average daily wear-time, there were no statistically significant differences between the wear-time methods in regards to minutes per day of moderate to vigorous physical activity (MVPA), vigorous PA, and moderate PA. Bland Altman plots indicated the Troiano and Choi algorithms were similar to the diary and within ≤ 0.5% of each other for wear-time and MVPA.CONCLUSIONS:The Choi or Troiano algorithms offer a valid and efficient alternative to diaries for the estimation daily wear-time in larger-scale studies of MVPA during pregnancy, and reduce burden for study participants and research staff.