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Purpose: Higher levels of sedentary behavior are associated with early mortality, but the distribution of sedentary time by classes of behavior and demographic groups is poorly described in U.S. adults. To quantify the amount and sources of sedentary time in U.S. adults, we conducted a nationwide survey using a novel validated self-administered previous-day recall method and compared these values with a commonly used sitting time question., Methods: Participants from the AmeriSpeak panel 20 to 75 yr of age (N = 2640) completed up to two activities completed over time in 24 h (ACT24) previous-day recalls. Recalls were conducted on randomly selected days in October and November 2019. Survey sample designs were applied to reflect the U.S. population., Results: Mean age was 45.3 yr, 51% were female, 67% non-Hispanic White, and 37% had a body mass index of ≥30 kg·m-2. U.S. adults reported a mean 9.5 h·d-1 of sedentary time (95% confidence interval = 9.4, 9.7 h·d-1), which was 34% more than reported using a common surveillance measure (P < 0.01). Most daily sedentary time was accumulated in the leisure and work life domains, with leisure accounting for 47% (4.3 h·d-1, 95% confidence interval = 4.2, 4.5 h·d-1) of the total sedentary time. Eighty-two percent of leisure time was spent sedentary, mainly watching television/videos or engaged in Internet/computer use., Conclusions: U.S. adults appear to spend more time in sedentary behavior than previously thought, and the majority of this time is accumulated at work and in leisure time. Reducing sedentary screen time during leisure in favor of physically active could be an important intervention target in the effort to increase physical activity in U.S. adults., (Copyright © 2021 by the American College of Sports Medicine.)

Background: Surveillance of domain-specific physical activity in the United States is lacking. Thus, the authors describe domain-specific moderate to vigorous physical activity (MVPA) in a nationwide sample of US adults., Methods: Participants from the AmeriSpeak panel (n = 2649; 20-75 y; 50% female) completed the Activities Completed Over Time in 24-Hours previous-day recall. The authors estimated average MVPA duration (in hours per day) overall and in major life domains by sex, age, race/ethnicity, and education. They also described the most commonly reported MVPAs and timing of MVPA during the day., Results: Across all life domains, participants reported an average of 2.5 hours per day in MVPA. Most MVPA was accumulated during work (50% of total, 1.2 h/d) and household activities (28%, 0.7 h/d) with less MVPA reported in leisure time (15%, 0.4 h/d). Time reported in MVPA varied by sex, and race/ethnicity (P < .05). Walking at work and for exercise, childcare, and walking for transportation were the most commonly reported domain-specific MVPAs. A greater proportion of MVPA took place in the morning (∼06:00 h) and evening (∼18:00 h)., Conclusions: Work and household activities accounted for 78% of overall MVPA reported, while leisure-time MVPA accounted for only 15% of the total. Encouraging MVPA during leisure time and transportation remain important targets for promoting MVPA in US adults.

Background: Physical activity is associated with lower risk for endometrial cancer, but the extent to which the association is mediated by body mass index (BMI) in midlife is unclear. This study describes the physical activity-endometrial cancer association and whether BMI mediates this relationship., Methods: Participants were 67 705 women in the National Institutes of Health-AARP Diet and Health Study (50-71 years) who recalled their physical activity patterns starting at age 15-18 years. We identified 5 long-term physical activity patterns between adolescence and cohort entry (ie, inactive, maintained low, maintained high, increasers, decreasers). We used Cox regression to assess the relationship between these patterns and midlife BMI and endometrial cancer, adjusting for covariates. Mediation analysis was used to estimate the proportion of the physical activity-endometrial cancer association that was mediated by midlife BMI., Results: During an average 12.4 years of follow-up 1468 endometrial cancers occurred. Compared with long-term inactive women, women who maintained high or increased activity levels had a 19% to 26% lower risk for endometrial cancer (maintained high activity: hazard ratio = 0.81, 95% confidence interval [CI] = 0.67 to 0.98; increasers: hazard ratio = 0.74, 95% CI = 0.61 to 0.91). They also had a 50% to 77% lower risk for obesity in midlife (eg, maintained high activity: odds ratio for a BMI of 30-39.9 kg/m 2 = 0.50, 95% CI = 0.46 to 0.55; and maintained high activity, odds ratio for a BMI of ≥40 kg/m 2 = 0.32, 95% CI = 0.26 to 0.39). BMI was a statistically significant mediator accounting for 55.5% to 62.7% of the physical activity-endometrial cancer associations observed., Conclusions: Both maintaining physical activity throughout adulthood and adopting activity later in adulthood can play a role in preventing obesity and lowering the risk for endometrial cancer., (Published by Oxford University Press 2021. This work is written by US Government employees and is in the public domain in the US.)

Purpose: The present study estimated the long-term reproducibility of accelerometer-based measures over 6 months in adults and the implications for statistical power, and attenuation in regression coefficients for future activity-disease studies., Methods: We used data from 914 adults in the Interactive Diet and Activity Tracking in AARP study. Participants wore an activPAL 3 (AP) and an ActiGraph GT3X (AG) twice, 6 months apart. AP measures included time spent sitting or lying, standing, and stepping, whereas AG measures included time spent in sedentary, light, and moderate-to-vigorous physical activity (PA). Reproducibility of each metric and implications for epidemiological studies were determined based on intraclass correlation coefficients (ICC; 95% confidence interval)., Results: The ICC values for AP estimates were 0.58 (95% confidence interval, 0.53-0.63) for sitting, 0.62 (0.57-0.67) for standing, and 0.57 (0.51-0.62) for stepping. The ICC values for AG were 0.56 (0.50-0.61) for sedentary, 0.54 (0.49-0.60) for light PA, and 0.58 (0.52-0.63) for moderate-to-vigorous PA. Modeling showed that increasing the number of replicate administrations to two or three resulted in the most noticeable increases in ICC values, statistical power, and reductions in attenuation coefficients. For example, administering the AP twice reduced within-subject variability by half and resulted in an increase in the ICC associated with sitting time from 0.58 to 0.74. Similar comparisons for AG and measure of sedentary time resulted in an increase in ICC values from 0.56 to 0.72. Increasing the number of replicate administrations from one to two reduced the attenuation in activity-outcome associations from 40% to 25%., Conclusion: Accelerometer-based classifications of activity are moderately stable over time, but there is considerable within-subject variability that needs to be considered when estimating usual activity in future studies.

Background: Lowering endogenous estrogen levels is one mechanism whereby physical activity may lower postmenopausal breast cancer risk. Several prospective studies have suggested that increased 2-hydroxylation of estrogens may also reduce postmenopausal breast cancer risk, but whether or not exercise alters estrogen metabolism through this mechanism is unclear., Methods: We measured total circulating concentrations of parent estrogens (estrone and estradiol) and 13 estrogen metabolites, including glucuronidated, sulfated, and unconjugated forms, by stable isotope dilution LC/MS-MS in 153 postmenopausal women randomized to 12 months of moderate-to-vigorous exercise and 153 controls. We also explored associations with cardiorespiratory fitness measured by treadmill., Results: Although women randomized to exercise averaged 178 minutes/week of exercise over 12 months, their cardiorespiratory fitness was 13% greater than controls at 12 months ( P = 0.0001), and total estradiol was reduced by 10% ( P = 0.04); there were no statistically significant effects of exercise on circulating concentrations of estrogen metabolites in the 2-, 4-, or 16-pathways, or on the 2-pathway/parent estrogens ratio. However, we observed a statistically significant association between increased fitness and reduced concentration of 2-pathway metabolites ( P < 0.05)., Conclusions: We found no evidence that 12 months of moderate-to-vigorous exercise or increased fitness changed estrogen metabolism in a way that might reduce breast cancer risk., Impact: The protective effect of exercise on postmenopausal breast cancer is unlikely to be mediated by changes in estrogen metabolism., (©2018 American Association for Cancer Research.)

Introduction: The goal of this study was to describe differences in time use and energy expenditure associated with exercise, prolonged TV viewing, and work days in a longitudinal study of older adults., Methods: Participants were 1,020 adults who completed previous-day recalls that provided a profile of the use of time in sedentary and physical activity. Time use and physical activity energy expenditure were predicted for each type of day (exercise, prolonged TV, work) using linear mixed models, adjusting for age, sex, season of the year, and day of the week. Data were collected in 2012-2013; analysis was completed in 2017., Results: Exercise days had less sedentary time (-0.37 hours/day) and light activity (-0.29 hours/day), and less household, work, and shopping activities, such that the increase in total physical activity energy expenditure on exercise days (2.83 MET-hours/day) was only about half that expended during exercise (5.98 MET-hours/day). Prolonged TV viewing days had more total sedentary time (0.86 hours/days) and less light (-0.45 hours/day) and moderate-vigorous intensity activity (-0.41 hours/day), and thus lower total physical activity energy expenditure (-2.43 MET-hours/day). Work days had less sleep (-0.91 hours/day) and more total sedentary time (1.32 hours/day)., Conclusions: Exercise days had more physical activity energy expenditure, but because of reductions in other activities, only about half of the energy expended during exercise was added to total daily physical activity energy expenditure. Prolonged TV viewing days had less physical activity energy expenditure and less moderate-vigorous activity. These findings provide new insights into possible compensation associated with exercise, and suggest a strong link between TV viewing and physical inactivity., (Published by Elsevier Inc.)

Introduction/purpose: To assess the utility of measurement methods that may be more accurate and precise than traditional questionnaire-based estimates of habitual physical activity and sedentary behavior we compared the measurement properties of a past year questionnaire (AARP) and more comprehensive measures: an internet-based 24-h recall (ACT24), and a variety of estimates from an accelerometer (ActiGraph)., Methods: Participants were 932 adults (50-74 yr) in a 12-month study that included reference measures of energy expenditure from doubly labeled water (DLW) and active and sedentary time via activPAL., Results: Accuracy at the group level (mean differences) was generally better for both ACT24 and ActiGraph than the AARP questionnaire. The AARP accuracy for energy expenditure ranged from -4% to -13% lower than DLW, but its accuracy was poorer for physical activity duration (-48%) and sedentary time (-18%) versus activPAL. In contrast, ACT24 accuracy was within 3% to 10% of DLW expenditure measures and within 1% to 3% of active and sedentary time from activPAL. For ActiGraph, accuracy for energy expenditure was best for the Crouter 2-regression method (-2% to -7%), and for active and sedentary time the 100 counts per minute cutpoint was most accurate (-1% to 2%) at the group level. One administration of the AARP questionnaire was significantly correlated with long-term average from the reference measures (ρTX = 0.16-0.34) overall, but four ACT24 recalls had higher correlations (ρTX = 0.48-0.60), as did 4 d of ActiGraph assessment (ρTX = 0.54-0.87)., Conclusions: New exposure assessments suitable for use in large epidemiologic studies (ACT24, ActiGraph) were more accurate and had higher correlations than a traditional questionnaire. Use of better more comprehensive measures in future epidemiologic studies could yield new etiologic discoveries and possibly new opportunities for prevention.

Introduction: The way physical activity (PA) and sedentary behavior (SB) are accumulated throughout the day (i.e., patterns) may be important for health, but identifying measurable and meaningful metrics of behavioral patterns is challenging. This study evaluated accelerometer-derived metrics to determine whether they predicted PA and SB patterns and were reliably measured., Methods: We defined and measured 55 metrics that describe daily PA and SB using data collected by using the activPAL monitor in four studies. The first two studies were randomized crossover designs that included recreationally active participants. Study 1 experimentally manipulated time spent in moderate-to-vigorous-intensity PA and sedentary time, and study 2 held time in exercise constant and manipulated SB. Study 3 included inactive participants who increased exercise, decreased sedentary time, or both. The study conditions induced distinct behavioral patterns; thus, we tested whether the new metrics could improve the prediction of an individual's study condition after adjusting for the overall volume of PA or SB using conditional logistic regression. In study 4, we measured the 3-month reliability for the pattern metrics by calculating intraclass correlation coefficients in a community-dwelling sample who wore the activPAL monitor twice for 7 d., Results: In each of the experimental studies, we identified new metrics that could improve the accuracy for predicting condition beyond SB and moderate-to-vigorous-intensity PA volume. In study 1, 23 metrics were predictive of a highly active condition, and in study 2, 24 metrics were predictive of a highly sedentary condition. In study 4, the median intraclass correlation coefficients (25-75th percentiles) of the metrics were 0.59 (0.46-0.65)., Conclusions: Several new metrics were predictive of patterns of SB, exercise, and nonexercise behavior and are moderately reliable for a 3-month period. Applying these metrics to determine whether daily behavioral patterns are associated with health-outcomes is an important area of future research., Competing Interests: The authors declare no conflicts of interest.

Background: Physical activity is associated with a variety of health benefits, but the biological mechanisms that explain these associations remain unclear. Metabolomics is a powerful tool to comprehensively evaluate global metabolic signature associated with physical activity and helps to pinpoint the pathways that mediate the health effects of physical activity. There has been limited research on metabolomics and habitual physical activity, and no metabolomics study has examined sedentary behaviour and physical activity of different intensities., Methods: In a group of Chinese adults (N = 277), we used an untargeted approach to examine 328 plasma metabolites in relation to accelerometer-measured physical activity, including overall volume of physical activity (physical activity energy expenditure (PAEE) and duration of physically active time) and sedentary time, and measures related to different intensities of physical activity (moderate-to-vigorous activity (MVPA), light activity, average physical activity intensity)., Results: We identified 11 metabolites that were associated with total activity, with a false discovery rate of 0.2 or lower. Notably, we observed generally lower levels of amino acids in the valine, leucine and isoleucine metabolism pathway and of carbohydrates in sugar metabolism among participants with higher activity levels. Moreover, we found that PAEE, time spent in light activity and duration of physically active time were associated with a similar metabolic pattern, whereas the metabolic signature associated with sedentary time mirrored this pattern. In contrast, average activity intensity and time spent in MVPA appeared to be associated with somewhat different metabolic patterns., Conclusions: Overall, the metabolomics patterns support a beneficial role of higher volume of physical activity in cardiometabolic health. Our findings identified candidate pathways and provide insight into the mechanisms underlying the health effects of physical activity., (Published by Oxford University Press on behalf of the International Epidemiological Association 2016. This work is written by US Government employees and is in the public domain in the United States.)

Importance: Leisure-time physical activity has been associated with lower risk of heart-disease and all-cause mortality, but its association with risk of cancer is not well understood., Objective: To determine the association of leisure-time physical activity with incidence of common types of cancer and whether associations vary by body size and/or smoking., Design, Setting, and Participants: We pooled data from 12 prospective US and European cohorts with self-reported physical activity (baseline, 1987-2004). We used multivariable Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals for associations of leisure-time physical activity with incidence of 26 types of cancer. Leisure-time physical activity levels were modeled as cohort-specific percentiles on a continuous basis and cohort-specific results were synthesized by random-effects meta-analysis. Hazard ratios for high vs low levels of activity are based on a comparison of risk at the 90th vs 10th percentiles of activity. The data analysis was performed from January 1, 2014, to June 1, 2015., Exposures: Leisure-time physical activity of a moderate to vigorous intensity., Main Outcomes and Measures: Incident cancer during follow-up., Results: A total of 1.44 million participants (median [range] age, 59 [19-98] years; 57% female) and 186 932 cancers were included. High vs low levels of leisure-time physical activity were associated with lower risks of 13 cancers: esophageal adenocarcinoma (HR, 0.58; 95% CI, 0.37-0.89), liver (HR, 0.73; 95% CI, 0.55-0.98), lung (HR, 0.74; 95% CI, 0.71-0.77), kidney (HR, 0.77; 95% CI, 0.70-0.85), gastric cardia (HR, 0.78; 95% CI, 0.64-0.95), endometrial (HR, 0.79; 95% CI, 0.68-0.92), myeloid leukemia (HR, 0.80; 95% CI, 0.70-0.92), myeloma (HR, 0.83; 95% CI, 0.72-0.95), colon (HR, 0.84; 95% CI, 0.77-0.91), head and neck (HR, 0.85; 95% CI, 0.78-0.93), rectal (HR, 0.87; 95% CI, 0.80-0.95), bladder (HR, 0.87; 95% CI, 0.82-0.92), and breast (HR, 0.90; 95% CI, 0.87-0.93). Body mass index adjustment modestly attenuated associations for several cancers, but 10 of 13 inverse associations remained statistically significant after this adjustment. Leisure-time physical activity was associated with higher risks of malignant melanoma (HR, 1.27; 95% CI, 1.16-1.40) and prostate cancer (HR, 1.05; 95% CI, 1.03-1.08). Associations were generally similar between overweight/obese and normal-weight individuals. Smoking status modified the association for lung cancer but not other smoking-related cancers., Conclusions and Relevance: Leisure-time physical activity was associated with lower risks of many cancer types. Health care professionals counseling inactive adults should emphasize that most of these associations were evident regardless of body size or smoking history, supporting broad generalizability of findings.

Background: Television viewing is a highly prevalent sedentary behavior among older adults, yet the mortality risks associated with hours of daily viewing over many years and whether increasing or decreasing viewing time affects mortality is unclear. This study examined: 1) the long-term association between mortality and daily viewing time; 2) the influence of reducing and increasing in television viewing time on longevity and 3) combined effects of television viewing and moderate-to-vigorous physical activity (MVPA) on longevity., Methods: Participants included 165,087 adults in the NIH-AARP Diet and Health (aged 50-71 yrs) who completed questionnaires at two-time-points (Time 1: 1994-1996, and Time 2: 2004-2006) and were followed until death or December 31, 2011. Multivariable-adjusted Cox proportional hazards regression was used to estimate Hazard Ratios and 95% confidence intervals (CI) with self-reported television viewing and MVPA and all-cause mortality., Results: Over 6.6 years of follow-up, there were 20,104 deaths. Compared to adults who watched < 3 h/day of television at both time points, mortality risk was 28% greater (CI:1.21,1.34) those who watched 5+ h/day at both time-points. Decreasing television viewing from 5 + h/day to 3-4 h/d was associated with a 15% reduction in mortality risk (CI:0.80, 0.91) and decreasing to <3 h/day resulted in an 12% lower risk (CI:0.79, 0.97). Conversely, adults who increased their viewing time to 3-4 h/day had an 17% greater mortality risk (CI:1.10, 1.24) and those who increased to 5+ h/day had a 45% greater risk (CI:1.32, 1.58), compared to those who consistently watched <3 h/day. The lowest mortality risk was observed in those who were consistently active and watched < 3 h/day of television., Conclusions: We confirm that prolonged television viewing time was associated with greater mortality in older adults and demonstrate for the first time that individuals who reduced the amount of time they spent watching television had lower mortality. Our findings provide new evidence to support behavioral interventions that seek to reduce sedentary television viewing in favor of more physically active pursuits, preferably MVPA. Given the high prevalence of physical inactivity and prolonged television viewing in older adults, favorable changes in these two modifiable behaviors could have substantial public health impact., Trial Registration: ClinicalTrials.gov number, NCT00340015.