Background Excessive sedentary time is ubiquitous in Westernized societies. Previous studies have relied on self-report to evaluate the total volume of sedentary time as a prognostic risk factor for mortality and have not examined whether the manner in which sedentary time is accrued (in short or long bouts) carries prognostic relevance. Objective To examine the association of objectively-measured sedentary behavior (its total volume and accrual in prolonged, uninterrupted bouts) with all-cause mortality. Design Prospective cohort study. Setting Contiguous United States Participants 7,985 black and white adults ≥45 years. Measurements Sedentary time was measured using a hip-mounted accelerometer. Prolonged, uninterrupted sedentariness was expressed as mean sedentary bout length. Hazard ratios [HRs] were calculated comparing quartiles 2-4 to quartile 1 for each exposure (quartile cutpoints: 689.7, 746.5, and 799.4 min/day for total sedentary time; 7.7, 9.6, and 12.4 min/bout for sedentary bout duration) in models that included moderate-vigorous physical activity. Results Over a median follow-up of 4.0 years, there were 340 deaths. In multivariable adjusted models, greater total sedentary time (HR [95% CI]: 1.22 [0.74-2.02], 1.61 [0.99-2.63], and 2.63 [1.60-4.30]; P-trend <0.001) and longer sedentary bout duration (HR [95% CI]: 1.03 [0.67-1.60], 1.22 [0.80-1.85], and 1.96 [1.31-2.93]; P-trend <0.001) were each associated with a higher all-cause mortality risk. Evaluation of their joint association showed that participants classified as high for both sedentary characteristics (e.g. high sedentary time [≥12.5 h/day] and high bout duration [≥10 min/bout]) had the highest morality risk. Limitations Participants may not be representative of the general US population. Conclusions The total volume of sedentary time as well as how one accrues sedentary time are both associated with all-cause mortality; suggestive that physical activity guidelines should target reducing and interrupting sedentary time to reduce mortality risk. Primary Funding Source National Institutes of Health

Despite interest in the built food environment, little is known about the validity of commonly used secondary data. The authors conducted a comprehensive field census identifying the locations of all food outlets using a handheld global positioning system in 8 counties in South Carolina (2008–2009). Secondary data were obtained from 2 commercial companies, Dun & Bradstreet, Inc. (D&B) (Short Hills, New Jersey) and InfoUSA, Inc. (Omaha, Nebraska), and the South Carolina Department of Health and Environmental Control (DHEC). Sensitivity, positive predictive value, and geospatial accuracy were compared. The field census identified 2,208 food outlets, significantly more than the DHEC (n = 1,694), InfoUSA (n = 1,657), or D&B (n = 1,573). Sensitivities were moderate for DHEC (68%) and InfoUSA (65%) and fair for D&B (55%). Combining InfoUSA and D&B data would have increased sensitivity to 78%. Positive predictive values were very good for DHEC (89%) and InfoUSA (86%) and good for D&B (78%). Geospatial accuracy varied, depending on the scale: More than 80% of outlets were geocoded to the correct US Census tract, but only 29%–39% were correctly allocated within 100 m. This study suggests that the validity of common data sources used to characterize the food environment is limited. The marked undercount of food outlets and the geospatial inaccuracies observed have the potential to introduce bias into studies evaluating the impact of the built food environment.

OBJECTIVE -The purpose of this study was to determine the independent and joint associations of cardiorespiratory fitness (CRF) and BMI with the incidence of type 2 diabetes in women.RESEARCH DESIGN AND METHODS -An observational cohort of 6,249 women aged 20 -79 years was free of baseline cardiovascular disease, cancer, and diabetes. CRF was measured using a maximal treadmill exercise test. BMI was computed from measured height and weight. The incidence of type 2 diabetes was identified primarily by 1997 American Diabetes Association criteria.RESULTS -During a 17-year follow-up, 143 cases of type 2 diabetes occurred. Compared with the least fit third, the multivariate (including BMI)-adjusted hazard ratio (HR) (95% CI) was 0.86 (0.59 -1.25) for the middle third and 0.61 (0.38 -0.96) for the upper third of CRF. For BMI, the multivariate (including CRF)-adjusted HR (95% CI) was 2.34 (1.55-3.54) for overweight individuals and 3.70 (2.12-6.44) for obese individuals, compared with normal-weight patients. In the combined analyses, overweight/obese unfit (the lowest one-third of CRF) women had significantly higher risks compared with normal-weight fit (the upper two-thirds of CRF) women.CONCLUSIONS -Low CRF and higher BMI were independently associated with incident type 2 diabetes. The protective effect of CRF was observed in individuals who were overweight or obese, but CRF did not eliminate the increased risk in these groups. These findings underscore the critical importance of promoting regular physical activity and maintaining normal weight for diabetes prevention. Diabetes Care 31:550-555, 2008

The EAPRS instrument provides comprehensive assessment of parks' and playgrounds' physical environment, with generally high reliability.

The purpose of this review was to examine the factors that predict the development of excessive fatness in children and adolescents. Medline, Web of Science and PubMed were searched to identify prospective cohort studies that evaluated the association between several variables (e.g. physical activity, sedentary behaviour, dietary intake and genetic, physiological, social cognitive, family and peer, school and community factors) and the development of excessive fatness in children and adolescents (5-18 years). Sixty-one studies met the eligibility criteria and were included. There is evidence to support the association between genetic factors and low physical activity with excessive fatness in children and adolescents. Current studies yielded mixed evidence for the contribution of sedentary behaviour, dietary intake, physiological biomarkers, family factors and the community physical activity environment. No conclusions could be drawn about social cognitive factors, peer factors, school nutrition and physical activity environments, and the community nutrition environment. There is a dearth of longitudinal evidence that examines specific factors contributing to the development of excessive fatness in childhood and adolescence. Given that childhood obesity is a worldwide public health concern, the field can benefit from large-scale, long-term prospective studies that use state-of-the-art measures in a diverse sample of children and adolescents.

Purpose The purpose of this study was to examine patterns of objectively-measured sedentary behavior in a national cohort of U.S. middle-aged and older adults and determine factors that influence prolonged sedentary behavior. Methods We studied 8,096 participants from the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study, a population-based study of black and white adults ≥45 years. Seven-day accelerometry was conducted. Prolonged sedentary behavior was defined as accumulating ≥50% of total sedentary time in bouts ≥30 min. Results The number of sedentary bouts ≥20, ≥30, ≥60, and ≥90 min were 8.8 ± 2.3, 5.5 ± 1.9, 1.9 ± 1.1, and 0.8 ± 0.7 bouts/day, respectively. Sedentary bouts ≥20, ≥30, ≥60, and ≥90 min accounted for 60.0 ± 13.9%, 48.0 ± 15.5%, 26.0 ± 15.4%, and 14.2 ± 12.9% of total sedentary time, respectively. Several factors were associated with prolonged sedentary behavior in multivariate-adjusted models (Odds Ratio [95% CI]): older age (65-74 years: 1.99 [1.55-2.57]; ≥75 years: 4.68 [3.61-6.07] vs. 45-54 years), male sex (1.41 [1.28-1.56] vs. female), residence in non-stroke belt/buckle region of U.S. (stroke belt: 0.87 [0.77-0.98]; stroke buckle: 0.86 [0.77-0.95] vs. non-belt/buckle), body mass index (BMI) (overweight: 1.33 [1.18-1.51]; obese: 2.15 [1.89-2.44] vs. normal weight), winter (1.18 [1.03-1.35] vs. summer), and low amounts of moderate-vigorous physical activity (MVPA) [0 min/week: 2.00 [1.66-2.40] vs. ≥150 min/week). Conclusions In this sample of U.S. middle-aged and older adults, a large proportion of total sedentary time was accumulated in prolonged, uninterrupted bouts of sedentary behavior as almost one-half was accumulated in sedentary bouts ≥30 min. Several sociodemographic (age, sex, BMI), behavioral (MVPA), environmental (region), and seasonal factors are associated with patterns of prolonged sedentary behavior.

(1) Physicians still need to overcome attitudinal and practical barriers to trial participation, (2) more support for physicians is needed, (3) surgeons may play a pivotal role in the recruitment of patients to adjuvant therapy trials, and (4) garnering patient enthusiasm for trial participation and involving them in the choice of adjuvant therapy may be key components to increasing trial enrollment.

BackgroundFive accelerometer-derived methods of identifying nonwear and wear time were compared with a self-report criterion in adults ≥ 56 years of age.MethodsTwo hundred participants who reported wearing an Actical™ activity monitor for four to seven consecutive days and provided complete daily log sheet data (i.e., the criterion) were included. Four variables were obtained from log sheets: 1) dates the device was worn; 2) time(s) the participant put the device on each day; 3) time(s) the participant removed the device each day; and 4) duration of self-reported nonwear each day. Estimates of wear and nonwear time using 60, 90, 120, 150 and 180 minutes of consecutive zeroes were compared to estimates derived from log sheets.ResultsCompared with the log sheet, mean daily wear time varied from -84, -43, -24, -14 and -8 min/day for the 60-min, 90-min, 120-min, 150-min and 180-min algorithms, respectively. Daily log sheets indicated 8.5 nonwear bouts per week with 120-min, 150-min and 180-min algorithms estimating 8.2-8.9 nonwear bouts per week. The 60-min and 90-min methods substantially overestimated number of nonwear bouts per week and underestimated time spent in sedentary behavior. Sensitivity (number of compliant days correctly identified as compliant) improved with increasing minutes of consecutive zero counts and stabilized at the 120-min algorithm. The proportion of wear time being sedentary and absolute and proportion of time spent in physical activity of varying intensities were nearly identical for each method.ConclusionsUtilization of at least 120 minutes of consecutive zero counts will provide dependable population-based estimates of wear and nonwear time, and time spent being sedentary and active in older adults wearing the Actical™ activity monitor.