[Show abstract][Hide abstract] ABSTRACT: Objectives:
To investigate whether walking mediates neighborhood built environment associations with weight status in middle- and older-aged women.
Participants (N=5085; mean age=64±7.7; 75.4% White non-Hispanic) were from the Women's Health Initiative San Diego cohort baseline visits. Body mass index (BMI) and waist circumference were measured objectively. Walking was assessed via survey. The geographic information system (GIS)-based home neighborhood activity supportiveness index included residential density, street connectivity, land use mix, and number of parks.
BMI was 0.22 units higher and the odds ratio for being obese (vs. normal or overweight) was 8% higher for every standard deviation decrease in neighborhood activity supportiveness. Walking partially mediated these associations (22-23% attenuation). Findings were less robust for waist circumference.
Findings suggest women who lived in activity-supportive neighborhoods had a lower BMI than their counterparts, in part because they walked more. Improving neighborhood activity supportiveness has population-level implications for improving weight status and health.
[Show abstract][Hide abstract] ABSTRACT: Background:
Excessive sitting has been linked to poor health. It is unknown whether reducing total sitting time or increasing brief sit-to-stand transitions is more beneficial. We conducted a randomized pilot study to assess whether it is feasible for working and non-working older adults to reduce these two different behavioral targets.
Thirty adults (15 workers and 15 non-workers) age 50-70 years were randomized to one of two conditions (a 2-hour reduction in daily sitting or accumulating 30 additional brief sit-to-stand transitions per day). Sitting time, standing time, sit-to-stand transitions and stepping were assessed by a thigh worn inclinometer (activPAL). Participants were assessed for 7 days at baseline and followed while the intervention was delivered (2 weeks). Mixed effects regression analyses adjusted for days within participants, device wear time, and employment status. Time by condition interactions were investigated.
Recruitment, assessments, and intervention delivery were feasible. The 'reduce sitting' group reduced their sitting by two hours, the 'increase sit-to-stand' group had no change in sitting time (p < .001). The sit-to-stand transition group increased their sit-to-stand transitions, the sitting group did not (p < .001).
This study was the first to demonstrate the feasibility and preliminary efficacy of specific sedentary behavioral goals.
[Show abstract][Hide abstract] ABSTRACT: Weight loss and metformin are hypothesized to improve breast cancer outcomes; however the joint impacts of these treatments have not been investigated. Reach for Health is a randomized trial using a 2×2 factorial design to investigate the effects of weight loss and metformin on biomarkers associated with breast cancer prognosis among overweight/obese postmenopausal breast cancer survivors. This paper describes the trial recruitment strategies, design, and baseline sample characteristics. Participants were randomized in equal numbers to (1) placebo, (2) metformin, (3) weight loss intervention and placebo, or (4) weight-loss intervention and metformin. The lifestyle intervention was a personalized, telephone-based program targeting a 7% weight-loss in the intervention arm. The metformin dose was 1500 mg/day. The duration of the intervention was 6 months. Main outcomes were biomarkers representing 3 metabolic systems putatively related to breast cancer mortality: glucoregulation, inflammation, and sex hormones. Between August 2011 and May 2015, we randomized 333 breast cancer survivors. Mass mailings from the California Cancer Registry were the most successful recruitment strategy with over 25000 letters sent at a cost of $191 per randomized participant. At baseline, higher levels of obesity were significantly associated with worse sleep disturbance and impairment scores, lower levels of physical activity and higher levels of sedentary behavior, hypertension, hypercholesterolemia, and lower quality of life (p <0.05 for all). These results illustrate the health burden of obesity. Results of this trial will provide mechanistic data on biological pathways and circulating biomarkers associated with lifestyle and pharmacologic interventions to improve breast cancer prognosis.
No preview · Article · Dec 2015 · Contemporary clinical trials
[Show abstract][Hide abstract] ABSTRACT: Purpose:
Accelerometers are a valuable tool for objective measurement of physical activity (PA). Wrist-worn devices may improve compliance over standard hip placement, but more research is needed to evaluate their validity for measuring PA in free-living settings. Traditional cut-point methods for accelerometers can be inaccurate, and need testing in free-living with wrist-worn devices. In this study we developed and tested the performance of machine learned (ML) algorithms for classifying PA types from both hip and wrist accelerometer data.
Forty overweight or obese women (mean age = 55.2 ±15.3 yrs; BMI = 32.0 ± 3.7) wore two ActiGraph GT3X+ accelerometers (right hip, non-dominant wrist) for seven free-living days. Wearable cameras captured ground truth activity labels. A classifier consisting of a random forest and hidden Markov model classified the accelerometer data into four activities (sitting, standing, walking/running, riding in a vehicle). Free-living wrist and hip ML classifiers were compared to each other, to traditional accelerometer cut points, and to an algorithm developed in a laboratory setting.
The ML classifier obtained an average of 89.4% and 84.6% balanced accuracy over the four activities using the hip and wrist accelerometer, respectively. In our dataset with an average of 28.4 minutes of walking or running per day, the ML classifier predicted an average of 28.5 minutes and 24.5 minutes of walking or running using the hip and wrist accelerometer, respectively. Intensity-based cutpoints and the laboratory algorithm significantly underestimated walking minutes.
Our results demonstrate the superior performance of our PA type classification algorithm, particularly in comparison to traditional cut-points. While the hip algorithm performed better, additional compliance achieved with wrist devices might justify using a slightly lower performing algorithm.
No preview · Article · Dec 2015 · Medicine and science in sports and exercise
[Show abstract][Hide abstract] ABSTRACT: Objectives:
To compare adolescents' physical activity at home, near home, at school, near school, and at other locations.
Adolescents (N = 549) were ages 12 to 16 years (49.9% girls, 31.3% nonwhite or Hispanic) from 447 census block groups in 2 US regions. Accelerometers and Global Positioning System devices assessed minutes of and proportion of time spent in moderate to vigorous physical activity (MVPA) in each of the 5 locations. Mixed-effects regression compared MVPA across locations and demographic factors.
Forty-two percent of adolescents' overall MVPA occurred at school, 18.7% at home, 18.3% in other (nonhome, nonschool) locations, and 20.6% near home or school. Youth had 10 more minutes (30% more) of overall MVPA on school days than on nonschool days. However, the percentage of location time spent in MVPA was lowest at school (4.8% on school days) and highest near home and near school (9.5%-10.4%). Girls had 2.6 to 5.5 fewer minutes per day of MVPA than boys in all locations except near school.
Although a majority of adolescents' physical activity occurred at school, the low proportion of active time relative to the large amount of time spent at school suggests potential for increasing school-based activity. Increasing time spent in the neighborhood appears promising for increasing overall physical activity, because a high proportion of neighborhood time was active. Increasing youth physical activity to support metabolic health requires strategies for increasing use of physical activity-supportive locations (eg, neighborhoods) and environmental and program improvements in unsupportive locations (eg, schools, homes).
[Show abstract][Hide abstract] ABSTRACT: Objective:
Excess sedentary time predicts negative health outcomes independent of physical activity. The present investigation examined informal caregiving duties and transportation-related factors as potential correlates of sedentary behavior in older adults.
Average daily sedentary time was measured via accelerometer in adults ages 66 years and older (N = 861). Caregiving variables included dog ownership and informal family caregiving status. Transportation variables included driver status, walking distance to public transit, and reported presence of pedestrians and bicyclists in one's neighborhood.
In multivariate models, owning a dog and being a driver were associated with less sedentary time (p ≤ .01). Educational status and geographic region modified the association between dog ownership and sedentary time, and age modified the association between driver status and sedentary time.
This study identified that older adult dog owners and drivers were less sedentary. Both factors may create opportunities for older adults to get out of their homes.
No preview · Article · Nov 2015 · Journal of Aging and Health
[Show abstract][Hide abstract] ABSTRACT: This study used objective Global Positioning Systems (GPS) to investigate the relationship between pedestrian and vehicle trips to physical, cognitive, and psychological functioning in older adults living in retirement communities. Older adults (N = 279; mean age = 83 ± 6 years) wore a GPS and accelerometer for 6 days. Participants completed standard health measures. The Personal Activity and Location Measurement System (PALMS) was used to calculate the average daily number of trips, distance, and minutes traveled for pedestrian and vehicle trips from the combined GPS and accelerometer data. Linear mixed effects regression models explored relationships between these transportation variables and physical, psychological and cognitive functioning. Number, distance, and minutes of pedestrian trips were positively associated with physical and psychological functioning but not cognitive functioning. Number of vehicle trips was negatively associated with fear of falls; there were no other associations between the vehicle trip variables and functioning. Vehicle travel did not appear to be related to functioning in older adults in retirement communities except that fear of falling was related to number of vehicle trips. Pedestrian trips had moderate associations with multiple physical and psychological functioning measures, supporting a link between walking and many aspects of health in older adults.
Full-text · Article · Oct 2015 · International Journal of Environmental Research and Public Health
[Show abstract][Hide abstract] ABSTRACT: Background:
Total sedentary time varies across population groups with important health consequences. Patterns of sedentary time accumulation may vary and have differential health risks. The purpose of this study is to describe sedentary patterns of older adults living in retirement communities and illustrate gender and age differences in those patterns.
Baseline accelerometer data from 307 men and women (mean age = 84±6 years) who wore ActiGraph GT3X+ accelerometers for ≥ 4 days as part of a physical activity intervention were classified into bouts of sedentary time (<100 counts per minute). Linear mixed models were used to account for intra-person and site-level clustering. Daily and hourly summaries were examined in mutually non-exclusive bouts of sedentary time that were 1+, 5+, 10+, 20+, 30+, 40+, 50+, 60+, 90+ and 120+ minutes in duration. Variations by time of day, age and gender were explored.
Men accumulated more sedentary time than women in 1+, 5+, 10+, 20+, 30+, 40+, 50+ and 60+ minute bouts; the largest gender-differences were observed in 10+ and 20+ minute bouts. Age was positively associated with sedentary time, but only in bouts of 10+, 20+, 30+, and 40+ minutes. Women had more daily 1+ minute sedentary bouts than men (71.8 vs. 65.2), indicating they break up sedentary time more often. For men and women, a greater proportion of time was spent being sedentary during later hours of the day than earlier. Gender differences in intra-day sedentary time were observed during morning hours with women accumulating less sedentary time overall and having more 1+ minute bouts.
Patterns identified using bouts of sedentary time revealed gender and age differences in the way in which sedentary time was accumulated by older adults in retirement communities. Awareness of these patterns can help interventionists better target sedentary time and may aid in the identification of health risks associated with sedentary behavior. Future studies should investigate the impact of patterns of sedentary time on healthy aging, disease, and mortality.
[Show abstract][Hide abstract] ABSTRACT: Background. We examined the relationships between objective and self-reported sedentary time and health indicators among older adults residing in retirement communities.
Methods. Our cross-sectional analysis used data from 307 participants who completed baseline measurements of a physical activity trial in 11 retirement communities in San Diego County. Sedentary time was objectively measured with devices (accelerometers) and using self-reports. Outcomes assessed included emotional and cognitive health, physical function, and physical health (eg, blood pressure). Linear mixed-effects models examined associations between sedentary behavior and outcomes adjusting for demographics and accelerometer physical activity.
Results. Higher device-measured sedentary time was associated with worse objective physical function (Short Physical Performance Battery, balance task scores, 400-m walk time, chair stand time, gait speed), self-reported physical function, and fear of falling but with less sleep disturbance (all ps < .05). TV viewing was positively related to 400-m walk time (p < .05). Self-reported sedentary behavior was related to better performance on one cognitive task (trails A; p < .05).
Conclusions. Sedentary time was mostly related to poorer physical function independently of moderate-to-vigorous physical activity and may be a modifiable behavior target in interventions aiming to improve physical function in older adults. Few associations were observed with self-reported sedentary behavior measures.
Full-text · Article · Aug 2015 · The Journals of Gerontology Series A Biological Sciences and Medical Sciences
[Show abstract][Hide abstract] ABSTRACT: Physical activity monitoring in free-living populations has many applications for public health research, weight-loss interventions, context-aware recommendation systems and assistive technologies. We present a system for physical activity recognition that is learned from a free-living dataset of 40 women who wore multiple sensors for seven days. The multi-level classification system first learns low-level codebook representations for each sensor and uses a random forest classifier to produce minute-level probabilities for each activity class. Then a higher-level HMM layer learns patterns of transitions and durations of activities over time to smooth the minute-level predictions. [Formula: see text].
[Show abstract][Hide abstract] ABSTRACT: Prevalence of walking and cycling for transport is low, varying greatly across countries. Few studies have examined neighborhood perceptions related to walking and cycling for transport in different countries. Therefore it is challenging to prioritize appropriate built environment interventions. The aim of this study was to examine the strength and shape of the relationship between adults' neighborhood perceptions and walking and cycling for transport across diverse environments.
As part of the International Physical activity and Environment Network (IPEN) adult project, self-report data were taken from 13,745 adults (18 - 65 years) living in physically and socially diverse neighborhoods in 17 cities across 12 countries. Neighborhood perceptions were measured using the Neighborhood Environment Walkability Scale, and walking and cycling for transport were measured using the International Physical Activity Questionnaire - Long Form. Generalized additive mixed models were used to model walking or cycling for transport during the last seven days with neighborhood perceptions. Interactions by city were explored.
Walking for transport outcomes were significantly associated with perceived residential density, land use mix access, street connectivity, aesthetics, and safety. Any cycling for transport was significantly related to perceived land use mix access, street connectivity, infrastructure, aesthetics, safety, and perceived distance to destinations. Between-city differences existed for some attributes in relation to walking or cycling for transport.
Many perceived environmental attributes supported both cycling and walking; however highly walkable environments may not support cycling for transport. People appear to walk for transport despite safety concerns. These findings can guide the implementation of global health strategies.
Full-text · Article · Jul 2015 · Environmental Health Perspectives
[Show abstract][Hide abstract] ABSTRACT: In the past 15 years, a major research enterprise has emerged that is aimed at understanding associations between geographic and contextual features of the environment (especially the built environment) and elements of human energy balance, including diet, weight and physical activity. Here we highlight aspects of this research area with a particular focus on research and opportunities in the United States as an example. We address four main areas: (1) the importance of valid and comparable data concerning behaviour across geographies; (2) the ongoing need to identify and explore new environmental variables; (3) the challenge of identifying the causally relevant context; and (4) the pressing need for stronger study designs and analytical methods. Additionally, we discuss existing sources of geo-referenced health data which might be exploited by interdisciplinary research teams, personnel challenges and some aspects of funding for geospatial research by the US National Institutes of Health in the past decade, including funding for international collaboration and training opportunities.
[Show abstract][Hide abstract] ABSTRACT: Objectives:
To investigate relations of walking, bicycling and vehicle time to neighborhood walkability and total physical activity in youth.
Participants (N=690) were from 380 census block groups of high/low walkability and income in two US regions. Home neighborhood residential density, intersection density, retail density, entertainment density and walkability were derived using GIS. Minutes/day of walking, bicycling and vehicle time were derived from processing algorithms applied to GPS. Accelerometers estimated total daily moderate-to-vigorous physical activity (MVPA). Models were adjusted for nesting of days (N=2987) within participants within block groups.
Walking occurred on 33%, active travel on 43%, and vehicle time on 91% of the days observed. Intersection density and neighborhood walkability were positively related to walking and bicycling and negatively related to vehicle time. Residential density was positively related to walking.
Increasing walking in youth could be effective in increasing total physical activity. Built environment findings suggest potential for increasing walking in youth through improving neighborhood walkability.
[Show abstract][Hide abstract] ABSTRACT: We describe a study that aims to understand physical activity and sedentary behavior in free-living settings. We employed a wearable camera to record 3 to 5 days of imaging data with 40 participants, resulting in over 360,000 images. These images were then fully annotated by experienced staff with a rigorous coding protocol. We designed a deep learning based classifier in which we adapted a model that was originally trained for ImageNet . We then added a spatio-temporal pyramid to our deep learning based classifier. Our results show our proposed method performs better than the state-of-the-art visual classification methods on our dataset. For most of the labels our system achieves more than 90% average accuracy across different individuals for frequent labels and more than 80% average accuracy for rare labels.
[Show abstract][Hide abstract] ABSTRACT: The purpose of this study was to compare estimates of sedentary time on weekdays vs. weekend days in older adults and determine if these patterns vary by measurement method. Older adults (N = 230, M = 83.5, SD = 6.5 years) living in retirement communities completed a questionnaire about sedentary behavior and wore an ActiGraph accelerometer for seven days. Participants engaged in 9.4 (SD = 1.5) hours per day of accelerometer-measured sedentary time, but self-reported engaging in 11.4 (SD = 4.9) hours per day. Men and older participants had more accelerometer-measured sedentary time than their counterparts. The difference between accelerometer-measured weekday and weekend sedentary time was non-significant. However, participants self-reported 1.1 hours per day more sedentary time on weekdays compared to weekend days. Findings suggest self-reported but not accelerometer-measured sedentary time should be investigated separately for weekdays and weekend days, and that self-reports may overestimate sedentary time in older adults.
Full-text · Article · Nov 2014 · Journal of aging and physical activity
[Show abstract][Hide abstract] ABSTRACT: Global Positioning Systems (GPS) are increasingly applied in activity studies, yet significant theoretical and methodological challenges remain. This paper presents a framework for integrating GPS data with other technologies to create dynamic representations of behaviors in context. Utilizing more accurate and sensitive measures to link behavior and environmental exposures allows for new research questions and methods to be developed.
Full-text · Article · Nov 2014 · Exercise and Sport Sciences Reviews