Prompts to disrupt sitting time and increase physical activity at work, 2011-2012.

INTRODUCTION: The objective of this study was to assess change in sitting and physical activity behavior in response to a workplace intervention to disrupt prolonged sitting time. METHODS: Sixty office workers were randomized to either a Stand group (n = 29), which received hourly prompts (computer-based and wrist-worn) to stand up, or a Step group (n = 31), which received the same hourly prompts and an additional prompt to walk 100 steps or more upon standing. An ActivPAL monitor was used to assess sitting and physical activity behavior on the same 3 consecutive workdays during baseline and intervention periods. Mixed-effect models with random intercepts and random slopes for time were performed to assess change between groups and across time. RESULTS: Both groups significantly reduced duration of average sitting bouts (Stand group, by 16%; Step group, by 19%) and the number of sitting bouts of 60 minutes or more (Step group, by 36%; Stand group, by 54%). The Stand group significantly reduced total sitting time (by 6.6%), duration of the longest sitting bout (by 29%), and number of sitting bouts of 30 minutes or more (by 13%) and increased the number of sit-to-stand transitions (by 15%) and standing time (by 23%). Stepping time significantly increased in the Stand (by 14%) and Step (by 29%) groups, but only the Step group significantly increased (by 35%) the number of steps per workday. Differences in changes from baseline to intervention between groups were not significant for any outcome. CONCLUSION: Interventions that focus on disrupting sitting time only in the workplace may result in less sitting. When sitting time disruptions are paired with a physical activity prompt, people may be more likely to increase their workday physical activity, but the effect on sitting time may be attenuated.

Measured and perceived environmental characteristics are related to accelerometer defined physical activity in older adults.

BACKGROUND: Few studies have investigated both the self-perceived and measured environment with objectively determined physical activity in older adults. Accordingly, the aim of this study was to examine measured and perceived environmental associations with physical activity of older adults residing across different neighborhood types. METHODS: One-hundred and forty-eight older individuals, mean age 64.3 ± 8.4, were randomly recruited from one of four neighborhoods that were pre-determined as either having high- or low walkable characteristics. Individual residences were geocoded and 200 m network buffers established. Both objective environment audit, and self-perceived environmental measures were collected, in conjunction with accelerometer derived physical activity behavior. Using both perceived and objective environment data, analysis consisted of a macro-level comparison of physical activity levels across neighborhood, and a micro-level analysis of individual environmental predictors of physical activity levels. RESULTS: Individuals residing in high-walkable neighborhoods on average engaged in 11 min of moderate to vigorous physical activity per day more than individuals residing in low-walkable neighborhoods. Both measured access to non-residential destinations (b = .11, p < .001) and self-perceived access to non-residential uses (b = 2.89, p = .031) were significant predictors of time spent in moderate to vigorous physical activity. Other environmental variables significantly predicting components of physical activity behavior included presence of measured neighborhood crime signage (b = .4785, p = .031), measured street safety (b = 26.8, p = .006), and perceived neighborhood satisfaction (b = .5.8, p = .003). CONCLUSIONS: Older adult residents who live in high-walkable neighborhoods, who have easy and close access to nonresidential destinations, have lower social dysfunction pertinent to crime, and generally perceive the neighborhood to a higher overall satisfaction are likely to engage in higher levels of physical activity behavior. Efforts aimed at promoting more walkable neighborhoods could influence activity levels in older adults.

Prediction of body fat in older adults by time spent in sedentary behavior.

The purpose of the study was to determine the relationship between sedentary behavior (SB), physical activity (PA), and body fat (total, abdominal) or body size (body-mass index [BMI], waist circumference [WC]) in community-dwelling adults 50 yr old and over. This study included 232 ambulatory adults (50-87 yr, 37.4% ± 9.6% body fat [BF]). Average daily time spent in SB (<100 counts/min) and light (100-759 counts/min), lifestyle-moderate (760-1,951 counts/min), walking-moderate (1,952-5,724 cts/min), and vigorous-intensity (≥ 5,725 counts/min) PA were determined by accelerometer and corrected for wear time. BF was measured with dual-energy X-ray absorptiometry. SB was positively related to measures of BF. Measures of SB, PA, and gender accounted for 55.6% of the variance in total BF, 32.4% of the variance in abdominal fat, and 28.0% of the variance in WC. SB, PA, and age accounted for 27.1% of the variance in BMI. Time spent in SB should be considered when designing obesity interventions for adults 50 yr old and over.

Controlled and free-living evaluation of objective measures of sedentary and active behaviors.

BACKGROUND: Emerging interest in the health impacts of sedentary behaviors has driven the exploration of objective instrumentation capable of capturing these behaviors. The purpose was to compare (under laboratory conditions) outputs from ActiGraph (AG), Intelligent Device for Energy Expenditure and Physical Activity (IDEEA), and activPAL Professional (AP) against direct observation (DO) in sedentary, standing, and active behaviors; and assess convergent validity of instrument outputs under free-living conditions. METHODS: Participants (13 males/16 females; 28.9 ± 6.2 years) wore instruments concurrently during laboratory and free-living studies. AG cutpoints of ≤50, <100, and ≤259 counts/minute were used to determine time in sedentary behaviors. Laboratory data were evaluated using mean percent error. Free-living data were analyzed using dependent t tests and RM ANOVA. RESULTS: AP precisely measured all identified DO behaviors under laboratory conditions; IDEEA precisely identified sitting and standing. For the free-living study, there was no difference in sedentary time detected by AP and IDEEA but a significant difference was observed in standing time. No difference was apparent between AP and AG259 in sit/lie/stand or ambulatory activity time. CONCLUSIONS: In a laboratory setting, the utility of all instruments to classify activities into behavioral categories was confirmed. This may enhance research on sedentary behaviors and health-related outcomes.

How many days of monitoring predict physical activity and sedentary behaviour in older adults?

BACKGROUND: The number of days of pedometer or accelerometer data needed to reliably assess physical activity (PA) is important for research that examines the relationship with health. While this important research has been completed in young to middle-aged adults, data is lacking in older adults. Further, data determining the number of days of self-reports PA data is also void. The purpose of this study was to examine the number of days needed to predict habitual PA and sedentary behaviour across pedometer, accelerometer, and physical activity log (PA log) data in older adults. METHODS: Participants (52 older men and women; age = 69.3 ± 7.4 years, range= 55-86 years) wore a Yamax Digiwalker SW-200 pedometer and an ActiGraph 7164 accelerometer while completing a PA log for 21 consecutive days. Mean differences each instrument and intensity between days of the week were examined using separate repeated measures analysis of variance for with pairwise comparisons. Spearman-Brown Prophecy Formulae based on Intraclass Correlations of .80, .85, .90 and .95 were used to predict the number of days of accelerometer or pedometer wear or PA log daily records needed to represent total PA, light PA, moderate-to-vigorous PA, and sedentary behaviour. RESULTS: Results of this study showed that three days of accelerometer data, four days of pedometer data, or four days of completing PA logs are needed to accurately predict PA levels in older adults. When examining time spent in specific intensities of PA, fewer days of data are needed for accurate prediction of time spent in that activity for ActiGraph but more for the PA log. To accurately predict average daily time spent in sedentary behaviour, five days of ActiGraph data are needed. CONCLUSIONS: The number days of objective (pedometer and ActiGraph) and subjective (PA log) data needed to accurately estimate daily PA in older adults was relatively consistent. Despite no statistical differences between days for total PA by the pedometer and ActiGraph, the magnitude of differences between days suggests that day of the week cannot be completely ignored in the design and analysis of PA studies that involve < 7-day monitoring protocols for these instruments. More days of accelerometer data were needed to determine typical sedentary behaviour than PA level in this population of older adults.

Markers of sedentarism: the joint Canada/U.S. Survey of health.

BACKGROUND: The Joint Canada/United States Survey of Health (JCUSH) was a one-time collaborative survey undertaken by Statistics Canada and the National Center for Health Statistics. METHODS: This analysis provides country-, sex-, and age-specific comparative markers of adult obesity and sedentarism, defined as independent and collective groupings of self-reported leisure-time inactivity (<1.5 MET-hours/day), usual occupational sitting, and no/low active transportation (<1 hour/week). Logistic regression assessed the likelihood of sedentarism in U.S. vs. Canada, with and without adjusting for BMI-defined obesity categories: healthy weight (18.5 ≤ BMI <25 kg/m2; n = 3542), overweight (25 ≤ BMI < 30 kg/m2; n = 2,651), and obesity (BMI ≥ 30 kg/m2; n = 1470). RESULTS: Compared with Canadians, U.S. adults are 24% more likely to be overweight/ obese, 59% more likely to be inactive in leisure-time, 19% more likely to report no/low active transportation, and 39% more likely to collectively report all sedentarism markers, adjusting for sex and age. Focusing on obese individuals in both countries, obese U.S. residents were 90% more likely to be inactive during leisure-time, 41% more likely to report no/low active transportation, and 73% more likely to report all sedentarism markers. CONCLUSIONS: This ecological analysis sheds light on differential risks of obesity and sedentarism in these neighboring countries.

Effectiveness of long and short bout walking on increasing physical activity in women.

BACKGROUND: The accumulation of physical activity (PA) throughout the day has been suggested as a means to increase PA behavior. It is not known, however, if accumulated PA results in equivalent increases in PA behavior compared with one continuous session. The purpose of this investigation was to compare changes in PA between participants assigned to walk daily in accumulated shorter bouts vs. one continuous session. METHODS: In this 8-week randomized controlled trial, 60 inactive women were randomly assigned to one of the following: (1) control group, (2) 30 minutes a day of walking 5 days a week in one continuous long bout (LB), or (3) three short 10-minute bouts (SB) of walking a day, all at a prescribed heart rate intensity. Walking was assessed by pedometer and self-reported walking log. Before and after measures were taken of average steps/day, resting systolic and diastolic blood pressure (SBP, DBP), resting heart rate (RHR), six-minute walk test (6MWT) distance, height, weight, body mass index (BMI), and hip and waist circumference. RESULTS: Both walking groups significantly increased PA measured as steps/day compared to controls (p < 0.001), and no significant differences were found between LB and SB groups. The LB group demonstrated significant decreases in hip circumference and significant increases in 6MWT distance compared to the control group. CONCLUSIONS: Both walking groups significantly increased PA participation. LB group participants completed more walking at a higher intensity than the SB and control groups, which resulted in significant increases in health benefits.

Objective and subjective measures of sedentary behavior and physical activity.

PURPOSE: To examine the convergent validity of the ActiGraph and activPAL accelerometers with the Bouchard Activity Record (BAR) in adults. Sedentary behavior and walking were evaluated in all instruments; standing and moderate-to-vigorous physical activity (MVPA) was evaluated only in those that detected such variables. METHODS: Thirty-two participants wore the accelerometers and completed the BAR concurrently for 1 d. Descriptive statistics and delta values were reported for all instruments. Summary time spent in sedentary behavior and walking was compared between all instruments using repeated-measures ANOVA. Dependent t-tests were used to analyze summary time in 1) standing between activPAL and BAR and 2) MVPA between ActiGraph and BAR. Bland-Altman plots were interpreted for systematic bias. On a detailed level, concurrent time interval data were compared using mean percent agreement and κ statistics. RESULTS: There was a significant difference found in summary time spent in sedentary behavior apparent between ActiGraph and activPAL as well as between ActiGraph and BAR. There was also a significant difference detected in time spent in walking, apparent between ActiGraph and activPAL, and between ActiGraph and BAR. In the time interval analysis, mean percent agreement ranged from 54.0% (for walking detected by ActiGraph and activPAL) to 86.7% (for MVPA by ActiGraph and BAR). κ values ranged from 0.25 (for walking by ActiGraph and activPAL) to 0.70 (for sedentary behavior between activPAL and BAR). Differences were also found in standing and MVPA. CONCLUSIONS: The activPAL and BAR showed convergence on both summary and concurrent time interval levels in both sedentary behavior and walking. The comparative discordance between activPAL and BAR with ActiGraph was likely a function of different approaches used to distinguish sedentary behavior from walking.

Evaluation of low-cost, objective instruments for assessing physical activity in 10-11-year-old children.

This study compared step counts detected by four, low-cost, objective, physical-activity-assessment instruments and evaluated their ability to detect moderate-to-vigorous physical activity (MVPA) compared to the ActiGraph accelerometer (AG). Thirty-six 10-11-year-old children wore the NL-1000, Yamax Digiwalker SW 200, Omron HJ-151, and Walk4Life MVP concurrently with the AG during school hours on a single day. AG MVPA was derived from activity count data using previously validated cut points. Two of the evaluated instruments provided similar group mean MVPA and step counts compared to AG (dependent on cut point). Low-cost instruments may be useful for measurement of both MVPA and steps in children's physical activity interventions and program evaluation.

Convergent validity of 3 low cost motion sensors with the ActiGraph accelerometer.

BACKGROUND: This study evaluated the utility of several lower cost physical activity (PA) assessment instruments for detecting PA volume (steps) and intensity (time in MVPA or activity time) using convergent methods of assessment. METHODS: Participants included 26 adults (9 male) age 27.3 ± 7.1 years with a BMI of 23.8 ± 2.8 kg/m2. Instruments evaluated included the Omron HJ-151 (OM), New Lifestyles NL-1000 (NL), Walk4Life W4L Pro (W4L), and ActiGraph GT1M (AG). Participants wore all instruments during a laboratory phase, consisting of 10 single minute treadmill walking bouts ranging in speed from 40 to 112 m/min, and immediate following the laboratory phase and during the remainder of their free-living day (11.3 ± 1.5 hours). Previously validated AG MVPA cutpoints were used for comparison with OM, NL, and W4L MVPA or activity time outputs during the laboratory and free-living phase. RESULTS: OM and NL produced similar MVPA estimates during free-living to commonly used AG walking cutpoints, and W4L activity time estimates were similar to one AG lifestyle cutpoint evaluated. CONCLUSION: Current findings indicate that the OM, NL, and W4L, ranging in price from $15 to $49, can provide reasonable estimates of free-living MVPA or activity time in comparison with a range of AG walking and lifestyle cutpoints.

Correction: Expected values for pedometer-determined physical activity in older populations.

Correction to Tudor-Locke C, Hart TL, Washington TL: Expected values for pedometer-determined physical activity in older populations. International Journal of Behavioral Nutrition and Physical Activity 2009, 6:59.

Expected values for pedometer-determined physical activity in older populations.

The purpose of this review is to update expected values for pedometer-determined physical activity in free-living healthy older populations. A search of the literature published since 2001 began with a keyword (pedometer, "step counter," "step activity monitor" or "accelerometer AND steps/day") search of PubMed, Cumulative Index to Nursing & Allied Health Literature (CINAHL), SportDiscus, and PsychInfo. An iterative process was then undertaken to abstract and verify studies of pedometer-determined physical activity (captured in terms of steps taken; distance only was not accepted) in free-living adult populations described as >/= 50 years of age (studies that included samples which spanned this threshold were not included unless they provided at least some appropriately age-stratified data) and not specifically recruited based on any chronic disease or disability. We identified 28 studies representing at least 1,343 males and 3,098 females ranging in age from 50-94 years. Eighteen (or 64%) of the studies clearly identified using a Yamax pedometer model. Monitoring frames ranged from 3 days to 1 year; the modal length of time was 7 days (17 studies, or 61%). Mean pedometer-determined physical activity ranged from 2,015 steps/day to 8,938 steps/day. In those studies reporting such data, consistent patterns emerged: males generally took more steps/day than similarly aged females, steps/day decreased across study-specific age groupings, and BMI-defined normal weight individuals took more steps/day than overweight/obese older adults. The range of 2,000-9,000 steps/day likely reflects the true variability of physical activity behaviors in older populations. More explicit patterns, for example sex- and age-specific relationships, remain to be informed by future research endeavors.

Expected values for pedometer-determined physical activity in youth.

This review assembles pedometry literature focused on youth, with particular attention to expected values for habitual, school day, physical education class, recess, lunch break, out-of-school, weekend, and vacation activity. From 31 studies published since 1999, we constructed a youth habitual activity step-curve that indicates: (a) from ages 6 to 18 years, boys typically take more steps per day than girls; (b) for both sexes the youngest age groups appear to take fewer steps per day than those immediately older; and (c) from a young age, boys decline more in steps per day to become more consistent with girls at older ages. Additional studies revealed that boys take approximately 42-49% of daily steps during the school day; girls take 41-47%. Steps taken during physical education class contribute to total steps per day by 8.7-23.7% in boys and 11.4-17.2% in girls. Recess represents 8-11% and lunch break represents 15-16% of total steps per day. After-school activity contributes approximately 47-56% of total steps per day for boys and 47-59% for girls. Weekdays range from approximately 12,000 to 16,000 steps per day in boys and 10,000 to 14,000 steps perday in girls. The corresponding values for weekend days are 12,000-13,000 steps per day in boys and 10,000-12,000 steps per day in girls.

Pedometry methods for assessing free-living youth.

The purpose of this review is to integrate and summarize specific measurement topics (instrument and metric choice, validity, reliability, how many and what types of days, reactivity, and data treatment) appropriate to the study of youth physical activity. Research quality pedometers are necessary to aid interpretation of steps per day collected in a range ofyoung populations under a variety of circumstances. Steps per day is the most appropriate metric choice, but steps per minute can be used to interpret time-in-intensity in specifically delimited time periods (e.g., physical education class). Reported intraclass correlations (ICC) have ranged from .65 over 2 days (although higher values also have been reported for 2 days) to .87 over 8 days (although higher values have been reported for fewer days). Reported ICCs are lower on weekend days (.59) versus weekdays (.75) and lower over vacation days (.69) versus school days (.74). There is no objective evidence of reactivity at this time. Data treatment includes (a) identifying and addressing missing values, (b) identijfying outliers and reducing data appropriately if necessary, and (c) transforming the data as required in preparation for inferential analysis. As more pedometry studies in young populations are published, these preliminary methodological recommendations should be modified and refined.

Expected values for steps/day in special populations.

OBJECTIVE: To assemble expected values for free-living steps/day in special populations living with chronic illnesses and disabilities. METHOD: Studies identified since 2000 were categorized into similar illnesses and disabilities, capturing the original reference, sample descriptions, descriptions of instruments used (i.e., pedometers, piezoelectric pedometers, accelerometers), number of days worn, and mean and standard deviation of steps/day. RESULTS: Sixty unique studies represented: 1) heart and vascular diseases, 2) chronic obstructive lung disease, 3) diabetes and dialysis, 4) breast cancer, 5) neuromuscular diseases, 6) arthritis, joint replacement, and fibromyalgia, 7) disability (including mental retardation/intellectual difficulties), and 8) other special populations. A median steps/day was calculated for each category. Waist-mounted and ankle-mounted instruments were considered separately due to fundamental differences in assessment properties. For waist-mounted instruments, the lowest median values for steps/day are found in disabled older adults (1214 steps/day) followed by people living with COPD (2237 steps/day). The highest values were seen in individuals with Type 1 diabetes (8008 steps/day), mental retardation/intellectual disability (7787 steps/day), and HIV (7545 steps/day). CONCLUSION: This review will be useful to researchers/practitioners who work with individuals living with chronic illness and disability and require such information for surveillance, screening, intervention, and program evaluation purposes.