Differences in Physical Activity During Walking and Two Pokémon Go Playing Styles.

Objective: Two self-selected playing styles of Pokémon Go (PG) have been observed: intermittent and continuous. However, it is unknown how playing style impacts volume and pattern of physical activity (PA) compared with a traditional walking bout. Materials and Methods: Twenty experienced PG players followed a 1.77 km walking loop during two randomly ordered, 30-minute walking conditions: PG and traditional walking. Objective measurement tools (pedometer, accelerometer, heart rate monitor, GPS watch) were used to measure steps, caloric expenditure, intensity, heart rate, and distance traveled, and direct observation was used to determine number of stops and playing style. Results: Most PG players used the intermittent playing style (60%). Traditional walking resulted in significantly greater PA than PG. There was a significant interaction between the PG playing style (continuous, intermittent) and condition (PG, traditional walking). There was no difference in PA variables between continuous and intermittent PG during traditional walking; however, total steps (3394.3 ± 255.8 vs. 2779.1 ± 317.5), aerobic steps (3314.3 ± 318.9 vs. 2387.5 ± 771.8), caloric expenditure (146.00 [130.0-201.3] vs. 110.0 [89.3-132.3 Kcals]), distance (2.4 [2.3-2.6] vs. 2.0 [1.8-2.1 km]), and moderate minutes (29.7 [27.5-29.8] vs. 25.8 [23.1-27.1]) were significantly greater, while sedentary minutes (0.2 [0-1.0] vs. 2.7 [1.7-4.3]) and number of stops (0 [0-0.8] vs. 4.5 [2.3-7.0]) were less, for continuous compared with intermittent PG. There was a main effect of condition on PA for intermittent PG players, but not continuous PG players. Conclusion: Continuous PG produced similar PA to traditional walking, while intermittent PG reduced PA, nevertheless PG may be a strategy for increasing PA participation.

Physical activity patterns and multimorbidity burden of older adults with different levels of functional status: NHANES 2003-2006.

BACKGROUND: Physical function and physical activity decrease with age, but differences in physical activity patterns within different physical functioning groups are unknown. OBJECTIVES: To describe physical activity patterns and multimorbidity burden by physical function group and age. METHODS: Actigraph accelerometer-derived physical activity patterns were compared by physical function (high functioning, activity limitations, activity of daily living disabled) determined by questionnaire and age among 2174 older adults (mean age = 70.9, sd = 0.2 years) from the cross-sectional 2003-2006 National Health and Nutrition Examination Survey. Associations between physical function, physical activity, and multimorbidity were examined. RESULTS: Reduced physical function and increased age were associated with lower physical activity, increased sedentary time and a compressed activity profile. During the most active hour of the day (11:00 a.m.), the oldest, lowest physical functioning group was 82% less active than the youngest, highest physical functioning group. High functioning had over 30% more total activity counts, over 56% more time in moderate-to-vigorous activity, about 8% less time sedentary and took approximately one more sedentary break/hour than lower physical functioning groups. Gender differences in physical activity variables were prevalent for high functioning, but limited within reduced physical functioning groups. Physical function, age, total activity counts/day, and breaks in sedentary time/day were independently associated with multimorbidity (p < 0.005). CONCLUSIONS: Reduced physical function and increased age are associated with physical activity levels, and all three are associated with multimorbidity. Understanding physical activity differences by physical function is important for designing interventions for older individuals at increased risk for mobility disability.

The Physical Activity Patterns of Greenway Users Playing Pokémon Go: A Natural Experiment.

OBJECTIVE: The aim of the study was to compare objectively measured physical activity (PA) between greenway users playing and not playing Pokémon Go. MATERIALS AND METHODS: A sample of 100 participants walking on a greenway wore an Omron pedometer and ActiGraph accelerometer and provided demographic data through an intercept survey during a natural experiment. Mann-Whitney U tests and multiple regression compared greenway PA variables between Pokémon Go (n = 13) and non-Pokémon Go (n = 87). RESULTS: Pokémon Go users were significantly younger (P < 0.01) than non-Pokémon Go users. Despite no differences in greenway walking time (42 ± 18 minutes), Pokémon Go users took fewer aerobic steps (2361 ± 1663 steps vs. 4144 ± 2591 steps; P = 0.03), walked shorter distances (1.38 ± 0.68 miles vs. 1.98 ± 1.05 miles; P = 0.049), burned fewer calories (119 ± 79 kcal vs. 202 ± 158 kcal; P = 0.04), spent more time in sedentary (16% ± 12% vs. 2% ± 7%; P < 0.01) and light (29% ± 24% vs. 15% ± 21%; P < 0.01) intensity activity, less time in moderate (52% ± 30% vs. 71 ± 29%; P = 0.02) and moderate-to-vigorous PA (MVPA) (55% ± 29% vs. 82% ± 23%; P < 0.01), and took fewer steps/min (67 ± 24 steps/min vs. 103 ± 23 steps/min; P < 0.01) than non-Pokémon Go users. Pokémon Go step rate rarely exceeded 100 steps/min for >5 minutes at a time. Multiple regression confirmed differences in sedentary, light, vigorous, MVPA, and steps/min between Pokémon Go and non-Pokémon Go users after controlling for covariates (P < 0.05). Age was significantly positively associated with aerobic steps, steps, walking distance and time, more light, but less vigorous, and MVPA (P < 0.05). CONCLUSION: While playing Pokémon Go greenway users are likely stopping more and walking at a slower pace than walkers not playing Pokémon Go.

Daily Physical Activity by Occupational Classification in US Adults: NHANES 2005-2006.

BACKGROUND: Little is known about the daily physical activity (PA) levels of people employed in different occupational categories. METHODS: Nine ActiGraph accelerometer-derived daily PA variables are presented and ranked for adults (N = 1465, 20-60 y) working in the 22 occupational categories assessed by NHANES 2005-2006. A composite score was generated for each occupational category by summing the rankings of 3 accelerometer-derived daily PA variables known to have strong associations with health outcomes (total activity counts [TAC], moderate to vigorous PA minutes per week in modified 10-minute bouts [MVPA 10], and percentage of time spent in sedentary activity [SB%]). RESULTS: Classified as high-activity occupational categories, "farming, fishing, forestry," and "building & grounds cleaning, maintenance" occupations had the greatest TAC (461 996 and 449 452), most MVPA 10 (149.6 and 97.8), most steps per day (10 464 and 11 602), and near the lowest SB% (45.2% and 45.4%). "Community, social services" occupations, classified as low-activity occupational categories, had the second lowest TAC (242 085), least MVPA 10 (12.1), fewest steps per day (5684), and near the highest SB% (64.2%). CONCLUSIONS: There is a strong association between occupational category and daily activity levels. Objectively measured daily PA permitted the classification of the 22 different occupational categories into 3 activity groupings.

Video-Recorded Validation of Wearable Step Counters under Free-living Conditions.

PURPOSE: The purpose of this study was to determine the accuracy of 14-step counting methods under free-living conditions. METHODS: Twelve adults (mean ± SD age, 35 ± 13 yr) wore a chest harness that held a GoPro camera pointed down at the feet during all waking hours for 1 d. The GoPro continuously recorded video of all steps taken throughout the day. Simultaneously, participants wore two StepWatch (SW) devices on each ankle (all programmed with different settings), one activPAL on each thigh, four devices at the waist (Fitbit Zip, Yamax Digi-Walker SW-200, New Lifestyles NL-2000, and ActiGraph GT9X (AG)), and two devices on the dominant and nondominant wrists (Fitbit Charge and AG). The GoPro videos were downloaded to a computer and researchers counted steps using a hand tally device, which served as the criterion method. RESULTS: The SW devices recorded between 95.3% and 102.8% of actual steps taken throughout the day (P > 0.05). Eleven step counting methods estimated less than 100% of actual steps; Fitbit Zip, Yamax Digi-Walker SW-200, and AG with the moving average vector magnitude algorithm on both wrists recorded 71% to 91% of steps (P > 0.05), whereas the activPAL, New Lifestyles NL-2000, and AG (without low-frequency extension (no-LFE), moving average vector magnitude) worn on the hip, and Fitbit Charge recorded 69% to 84% of steps (P < 0.05). Five methods estimated more than 100% of actual steps; AG (no-LFE) on both wrists recorded 109% to 122% of steps (P > 0.05), whereas the AG (LFE) on both wrists and the hip recorded 128% to 220% of steps (P < 0.05). CONCLUSIONS: Across all waking hours of 1 d, step counts differ between devices. The SW, regardless of settings, was the most accurate method of counting steps.

Energy Expenditure for 70 Activities in Children and Adolescents.

BACKGROUND: Thirty-five percent of the activities assigned MET values in the Compendium of Energy Expenditures for Youth were obtained from direct measurement of energy expenditure (EE). The aim of this study was to provide directly measured EE for several different activities in youth. METHODS: Resting metabolic rate (RMR) of 178 youths (80 females, 98 males) was first measured. Participants then performed structured activity bouts while wearing a portable metabolic system to directly measure EE. Steady-state oxygen consumption data were used to compute activity METstandard (activity VO2/3.5) and METmeasured (activity VO2/measured RMR) for the different activities. RESULTS: Rates of EE were measured for 70 different activities and ranged from 1.9 to 12.0 METstandard and 1.5 to 10.0 METmeasured. CONCLUSION: This study provides directly measured energy cost values for 70 activities in children and adolescents. It contributes empirical data to support the expansion of the Compendium of Energy Expenditures for Youth.

Association between Objectively Measured Physical Activity and Mortality in NHANES.

PURPOSE: We examined total activity, light activity, and moderate-to-vigorous physical activity (MVPA) as predictors of mortality in a nationally representative sample of older adults. Then we explored the theoretical consequences of replacing sedentary time with the same duration of light activity or MVPA. METHODS: Using accelerometer-measured activity, the associations between total activity, light activity (100-2019 counts per minute), and MVPA (>2019 counts per minute) counts and mortality were examined in adults age 50 to 79 yr in the National Health and Nutrition Examination Survey, 2003-2006 (n = 3029), with mortality follow-up through December 2011. Cox proportional hazard models were fitted to estimate mortality risks. An isotemporal substitution model was used to examine the theoretical consequences of replacing sedentary time with light activity or MVPA on mortality. RESULTS: After adjusting for potential confounders, including age, sex, race/ethnicity, education, BMI, and the presence of comorbid conditions, those in the highest tertile of total activity counts had one fifth the risk of death of those in the lowest tertile (hazard ratio [HR] = 0.21, 95% confidence interval [CI] = 0.12-0.38), and those in the middle tertile had one third the risk of death (HR = 0.36, 95% CI = 0.30-0.44). In addition, replacing 30 min of sedentary time with light activity was associated with significant reduction in mortality risk (after 5 yr of follow-up: HR = 0.80, 95% CI = 0.75-0.85). Replacing 30 min of sedentary time with MVPA was also associated with reduction in mortality risk (HR = 0.49, 95% CI = 0.25-0.97). CONCLUSIONS: Greater total activity is associated with lower all-cause mortality risk. Replacing sedentary time with light activity or MVPA may reduce mortality risk for older adults.

Physical Activity With and Without TV Viewing: Effects on Enjoyment of Physical Activity and TV, Exercise Self-Efficacy, and Barriers to Being Active in Overweight Adults.

BACKGROUND: Physical activity (PA) is enjoyable, but there are barriers to participation. TV viewing is highly enjoyable with limited barriers. Exercising while viewing TV may impact enjoyment, exercise self-efficacy, and barriers to PA, compared with exercising without TV. METHODS: 58 sedentary, overweight adults were randomized to 1 of 2 PA prescriptions: one that increased PA during TV viewing (TV Commercial Stepping), and another that focused solely on PA (Walking). Random effects models tested changes in enjoyment of TV and PA, exercise self-efficacy, and barriers to PA across time (baseline, 3, and 6 months) and PA prescription during a 6-month PA intervention. RESULTS: At baseline, TV was more enjoyable than PA. Over the 6-month intervention, enjoyment of TV viewing did not change, but enjoyment of PA and exercise self-efficacy significantly increased, while barriers to PA significantly decreased for both groups compared with baseline (P < .05). CONCLUSIONS: While enjoyment of TV viewing remained constant, PA became more enjoyable, confidence to exercise increased, and barriers to being active were reduced for previously sedentary adults participating in a behavioral PA intervention. These findings highlight the importance of encouraging inactive adults to engage in some form of PA, whether it occurs with or without TV viewing.

Depressive Trajectories and Risk of Disability and Mortality in Older Adults: Longitudinal Findings From the Health, Aging, and Body Composition Study.

BACKGROUND: Depression and disability are closely linked. Less is known regarding clinical and subclinical depressive symptoms over time and risk of disability and mortality. METHODS: Responses to the Center for Epidemiologic Studies Short Depression scale (CES-D10) were assessed over a 4-year period in men (n = 1032) and women (n = 1070) aged 70-79 years initially free from disability. Depressive symptom trajectories were defined with group-based models. Disability (2 consecutive reports of severe difficulty walking one-quarter mile or climbing 10 steps) and mortality were determined for 9 subsequent years. Hazard ratios (HRs) were estimated using Cox proportional hazards adjusted for covariates. RESULTS: Three trajectories were identified: persistently nondepressed (54% of men, 54% of women, mean baseline CES-D10: 1.16 and 1.46), mildly depressed and increasing (40% of men, 38% of women, mean baseline CES-D10: 3.60 and 4.35), and depressed and increasing (6% of men, 8% of women, mean baseline CES-D10: 7.44 and 9.61). Disability and mortality rates per 1,000 person years were 41.4 and 60.3 in men and 45.8 and 41.9 in women. Relative to nondepressed, men in the mildly depressed (HR = 1.45, 95% confidence interval [CI] 1.11-1.89) and depressed trajectories (HR = 2.12, 95% CI 1.33-3.38) had increased disability; women in the depressed trajectory had increased disability (HR = 2.02, 95% CI 1.37-2.96). Men in the mildly depressed (HR = 1.24, 95% CI 1.01-1.52) and depressed trajectories (HR = 1.63, 95% CI 1.10-2.41) had elevated mortality risk; women exhibited no mortality risk. CONCLUSIONS: Trajectories of depressive symptoms without recovery may predict disability and mortality in apparently healthy older populations, thus underscoring the importance of monitoring depressive symptoms in geriatric care.

Classification of occupational activity categories using accelerometry: NHANES 2003-2004.

BACKGROUND: An individual's occupational activity (OA) may contribute significantly to daily physical activity (PA) and sedentary behavior (SB). However, there is little consensus about which occupational categories involve high OA or low OA, and the majority of categories are unclassifiable with current methods. The purpose of this study was to present population estimates of accelerometer-derived PA and SB variables for adults (n = 1112, 20-60 years) working the 40 occupational categories collected during the 2003-2004 National Health and Nutrition Examination Survey (NHANES). METHODS: ActiGraph accelerometer-derived total activity counts/day (TAC), activity counts/minute, and proportion of wear time spent in moderate-to-vigorous PA [MVPA], lifestyle, and light PA organized by occupational category were ranked in ascending order and SB was ranked in descending order. Summing the ranks of the six accelerometer-derived variables generated a summary score for each occupational category, which was re-ranked in ascending order. Higher rankings indicated higher levels of OA, lower rankings indicated lower levels of OA. Tertiles of the summary score were used to establish three mutually exclusive accelerometer-determined OA groupings: high OA, intermediate OA, and low OA. RESULTS: According to their summary score, 'farm and nursery workers' were classified as high OA and 'secretaries, stenographers, and typists' were classified as low OA. Consistent with previous research, some low OA occupational categories (e.g., 'engineers, architects, and scientists', 'technicians and related support occupations', 'management related occupations', 'executives, administrators, and managers', 'protective services', and 'writers, artists, entertainers, and athletes') associated with higher education and income had relatively greater amounts of MVPA compared to other low OA occupational categories, likely due to the greater percentage of men in those occupations and/or the influence of higher levels of leisure time PA. Men had more TAC, activity counts/minute and time in MVPA, but similar proportions of SB compared to women in all three OA groupings. CONCLUSIONS: Objectively measured PA allowed for a more precise estimate of the amount of PA and SB associated with different occupations and facilitated systematic classification of the 40 different occupational categories into three distinct OA groupings. This information provides new opportunities to explore the relationship between OA and health outcomes.

Physical activity and sedentary behavior in breast cancer survivors: New insight into activity patterns and potential intervention targets.

BACKGROUND: Inactivity and sedentary behavior are related to poorer health outcomes in breast cancer survivors. However, few studies examining these behaviors in survivors have used objective measures, considered activities other than moderate-to-vigorous intensity activity (MVPA) and/or sedentary behavior (i.e. low intensity activities) or compared survivors to healthy controls. The purpose of the present study is to compare accelerometer-measured activity of various intensities (total, light, lifestyle, MVPA) and sedentary behavior between breast cancer survivors and non-cancer controls. METHODS: An imputation-based approach of independent sample t-tests adjusting for multiple comparisons was used to compare estimates of participation in each activity and sedentary behavior between survivors [n=398; M(SD)age=56.95 (9.11)] and block-matched non-cancer controls [n=1120; M(SD)age=54.88 (16.11)]. Potential moderating effects of body mass index (BMI), age, and education were also examined. RESULTS: Breast cancer survivors registered less daily total (282.8 v. 346.9) light (199.1 v. 259.3) and lifestyle (62.0 v. 71.7) activity minutes and more MVPA (21.6 v. 15.9) and sedentary behavior (555.7 v. 500.6) minutes than controls (p<0.001 for all). These relationships were largely consistent across BMI, age and education. On average, survivors spent an estimated 66.4% of their waking time sedentary and 31.1% in light/lifestyle activity and 2.6% in MVPA. CONCLUSIONS: Breast cancer survivors are more sedentary and participate in less low intensity activity than controls. Although survivors registered more MVPA, these levels were insufficient. Future research should explore these differences and potential benefits of targeting low intensity activities and reducing sedentary time in this population.

Daily Patterns of Physical Activity by Type 2 Diabetes Definition: Comparing Diabetes, Prediabetes, and Participants with Normal Glucose Levels in NHANES 2003-2006.

OBJECTIVE: Diabetes is associated with low levels of physical activity (PA), but detailed objective information about how PA patterns vary by diabetes definition is lacking. METHODS: PA was measured with Actigraph accelerometers in older (60+) adults from the 2003-2006 National Health and Nutrition Examination Survey (n= 1,043) and analyzed in 2014. Diabetes definition (normal glucose levels, prediabetes, diabetes) was assessed (fasting glucose, hemoglobin A1C, and self-report). Accelerometer data were used to characterize total activity counts (TAC) per day and hour-by-hour activity counts by diabetes definition. Multiple linear regression models explored the relationship between diabetes definition and TAC. RESULTS: Despite similar patterns of PA, diabetes participants had significantly lower TAC compared to participants with normal glucose levels and prediabetes. Diabetes participants' activity counts per hour declined more rapidly after 12 pm, with the biggest differences between the groups occurring at 4 pm. Participants with normal glucose levels and prediabetes had similar TAC and daily PA profiles. CONCLUSION: Our novel methodology provides information about PA patterns by diabetes definition. Significantly lower TAC in the diabetes group, their significant drop in afternoon PA, and the similarity of PA between participants with normal glucose levels and prediabetes provide insight into potential targets for intervention.

Women Workers and Women at Home Are Equally Inactive: NHANES 2003-2006.

PURPOSE: The prevalence of female homemakers (those who stay at home to care for the home or family) has increased to 29%. Homemakers may be more active than employed women (EW). Limited data are available for domestic-related activity; therefore, the assessment of the activity levels of homemakers has been sparse. This study compared objectively measured activity (total activity counts, counts per minute, and percent time in various activity intensity levels) of homemakers and EW. METHODS: Women's (18-60 yr) accelerometer data from the 2003-2006 National Health and Nutrition Examination Survey were analyzed in 2014 (n = 1763). Daily (hour-by-hour) profiles of activity were compared between homemakers and EW. RESULTS: Women spent most of their day in sedentary (∼55%) and light (∼32%) activity, with limited lifestyle (∼11%) and moderate vigorous physical activity (MVPA; ∼2%); and there were no differences between the homemakers and EW. Hour-by-hour analysis showed that the homemakers had more light and less sedentary activity than EW during the afternoon (P < 0.002), whereas EW had more MVPA at times corresponding to commuting to and from work and midday (P < 0.002). On weekdays, EW initiated activity earlier than homemakers but not on weekends. On weekends, both groups had less MVPA than weekdays. Employed women with child(ren) younger than 18 yr had greater counts per minute and lifestyle activity and less sedentary activity than EW without child(ren) younger than 18 yr. CONCLUSION: Our hourly analysis delineated important differences in activity between the groups. Homemakers accumulate enough light activity throughout the day to be as active as EW who are highly sedentary during the workday, but seem to acquire activity through commuting. Interventions to reduce sedentary behavior and increase activity are highly desirable and should take into consideration the temporality of homemakers and EW activity patterns.

Physicians' personal beliefs about weight-related care and their associations with care delivery: The U.S. National Survey of Energy Balance Related Care among Primary Care Physicians.

BACKGROUND: Overweight and obesity are major health risks in the United States (US) and primary care physicians (PCPs) are uniquely positioned to address them. However, their personal beliefs about weight-related care may influence their delivery of care. METHODS: A nationally representative sample of 2022 physicians completed the National Survey of Energy Balance-Related Care among Primary Care Physicians. Physicians responded to questions regarding their beliefs and clinical practices associated with weight control including assessment, counselling, referral and follow-up for diet, physical activity, and weight. Multivariate logistic regression was used to examine associations between physician characteristics and personal beliefs, and associations between personal beliefs and care delivery, adjusting for specialty, age, gender, race, region, urban/rural location, and patient population. RESULTS: Most physicians feel a responsibility (97%) to promote weight-related care, but over half (53%) have concerns about their effectiveness and almost two-thirds feel they lack effective strategies to help patients (63%). Demographics and medical specialty were associated with beliefs (female, Asian-American, Midwest and Southern location, and internal medicine physicians were more likely to have stronger positive beliefs about weight-related care). Personal beliefs about weight-related care were associated with the likelihood of its delivery. However, two practices, regular BMI assessment and referring patients for further evaluation and management, were less related to PCP beliefs than were other care practices. CONCLUSIONS: PCPs' beliefs may be important to their practice of weight-related care. Training in behavioural counselling, and providing physician's tools and resources may help to address their concerns about helping patients with weight-related care.

Ability of thigh-worn ActiGraph and activPAL monitors to classify posture and motion.

PURPOSE: This study compared sitting, standing, and stepping classifications from thigh-worn ActiGraph and activPAL monitors under laboratory and free-living conditions. METHODS: Adults wore both monitors on the right thigh while performing activities (six sitting, two standing, nine stepping, and one cycling) and writing on a whiteboard with intermittent stepping under laboratory conditions (n = 21) and under free-living conditions for 3 d (n = 18). Percent time correctly classified was calculated under laboratory conditions. Between-monitor agreement and weighted κ were calculated under free-living conditions. RESULTS: In the laboratory, both monitors correctly classified 100% of standing time and >95% of the time spent in four of six sitting postures. Both monitors demonstrated misclassification of laboratory stool sitting time (ActiGraph 14% vs. activPAL 95%). ActivPAL misclassified 14% of the time spent sitting with legs outstretched; ActiGraph was 100% accurate. Monitors were >95% accurate for stepping, although ActiGraph was less so for descending stairs (86%), ascending stairs (92%), and running at 2.91 m·s(-1) (93%). Monitors classified whiteboard writing differently (ActiGraph 83% standing/15% stepping vs. activPAL 98% standing/2% stepping). ActivPAL classified 93% of cycling time as stepping, whereas ActiGraph classified <1% of cycling time as stepping. During free-living wear, monitors had substantial agreement (86% observed; weighted κ = 0.77). Monitors classified similar amounts of time as sitting (ActiGraph 64% vs. activPAL 62%). There were differences in time recorded as standing (ActiGraph 21% vs. activPAL 27%) and stepping (ActiGraph 15% vs. activPAL 11%). CONCLUSIONS: Differences in data processing algorithms may have resulted in the observed disagreement in posture and activity classification between thigh-worn ActiGraph and activPAL. Despite between-monitor agreement in classifying sitting time under free-living conditions, ActiGraph appears to be more sensitive to free-living upright walking motions than activPAL.

Physical activity variety, energy expenditure, and body mass index.

OBJECTIVES: To examine if physical activity (PA) variety was associated with moderate- to vigorous-intensity PA (MVPA) energy expenditure and body mass index (BMI) at 18 months during an obesity intervention. METHODS: Participants with ≥ 10 minutes/week of MVPA at 6 months and complete PA data were included. Participants were classified into Variety (N = 30), ≥ 2 different activities/week, or Less Variety (N = 65), only 1 activity/week. RESULTS: Weekly MVPA-related energy expenditure was higher for Variety than Less Variety (3674.7 ± 1934.6 kcal/week vs 2197.3 ± 1841.4 kcal/week, p < .05) at 18 months, with no difference in BMI. CONCLUSIONS: Greater weekly PA variety during obesity treatment was related to greater 18-month MVPA energy expenditure.

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.

Can sedentary behavior be made more active? A randomized pilot study of TV commercial stepping versus walking.

BACKGROUND: There is a growing problem of physical inactivity in America, and approximately a quarter of the population report being completely sedentary during their leisure time. In the U.S., TV viewing is the most common leisure-time activity. Stepping in place during TV commercials (TV Commercial Stepping) could increase physical activity. The purpose of this study was to examine the feasibility of incorporating physical activity (PA) into a traditionally sedentary activity, by comparing TV Commercial Stepping during 90 min/d of TV programming to traditional exercise (Walking). METHODS: A randomized controlled pilot study of the impact of 6 months of TV Commercial Stepping versus Walking 30 min/day in adults was conducted. 58 sedentary, overweight (body mass index 33.5 ± 4.8 kg/m2) adults (age 52.0 ± 8.6 y) were randomly assigned to one of two 6-mo behavioral PA programs: 1) TV Commercial Stepping; or 2) Walking 30 min/day. To help facilitate behavior changes participants received 6 monthly phone calls, attended monthly meetings for the first 3 months, and received monthly newsletters for the last 3 months. Using intent-to-treat analysis, changes in daily steps, TV viewing, diet, body weight, waist and hip circumference, and percent fat were compared at baseline, 3, and 6 mo. Data were collected in 2010-2011, and analyzed in 2011. RESULTS: Of the 58 subjects, 47 (81%) were retained for follow-up at the completion of the 6-mo program. From baseline to 6-mo, both groups significantly increased their daily steps [4611 ± 1553 steps/d vs. 7605 ± 2471 steps/d (TV Commercial Stepping); 4909 ± 1335 steps/d vs. 7865 ± 1939 steps/d (Walking); P < 0.05] with no significant difference between groups. TV viewing and dietary intake decreased significantly in both groups. Body weight did not change, but both groups had significant decreases in percent body fat (3-mo to 6-mo), and waist and hip circumference (baseline to 6-mo) over time. CONCLUSIONS: Participants in both the TV Commercial Stepping and Walking groups had favorable changes in daily steps, TV viewing, diet, and anthropometrics. PA can be performed while viewing TV commercials and this may be a feasible alternative to traditional approaches for increasing daily steps in overweight and obese adults. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov, NCT01342471.

The Relationship between Physical Activity Variety and Objectively Measured Moderate-to-Vigorous Physical Activity Levels in Weight Loss Maintainers and Normal-Weight Individuals.

Given the importance of physical activity (PA) for weight control, identifying strategies to achieve higher PA levels is imperative. We hypothesized that performing a greater variety of self-reported moderate-to-vigorous activities (MVPAs) would relate to higher objectively measured MVPA minutes in two groups who were successfully maintaining their body weight: weight loss maintainers (WLM/n = 226) and normal-weight individuals (NW/n = 169). The Paffenbarger Questionnaire and RT3 accelerometer were used to determine variety/number of different MVPAs performed and MVPA minutes, respectively. The variety/number of different activities performed by WLM and NW was similar (1.8 ± 1.2 versus 1.7 ± 1.2, P = 0.52). Regression analyses showed that greater variety (P < 0.01) and WLM status (P < 0.05) were each positively related to greater MVPA minutes/day and meeting the ≥250 MVPA minutes/week guideline for long-term weight maintenance. The association between greater variety and higher MVPA was similar in NW and WLM. Future studies should test whether variety can facilitate engagement in higher MVPA levels for more effective weight control.