Jacqueline Kerr’s research while affiliated with University of California, San Diego and other places

Background A better understanding of the extent to which psychosocial and environmental correlates of physical activity are specific to locations would inform intervention optimization. Purpose To investigate cross-sectional associations of location-general and location-specific variables with physical activity and sedentary time in three common locations adolescents spend time. Methods Adolescents (N = 472,Mage = 14.1,SD = 1.5) wore an accelerometer and global positioning systems (GPS) tracker and self-reported on psychosocial (e.g., self-efficacy) and environmental (e.g., equipment) factors relevant to physical activity and sedentary time. We categorized each survey item based on whether it was specific to a location to generate psychosocial and environmental indices that were location-general or specific to either school, non-school, or home location. Physical activity (MVPA) and sedentary time were based on time/location match to home, school, or all “other” locations. Mixed-effects models investigated the relation of each index with location-specific activity. Results The location-general and non-school physical activity psychosocial indices were related to greater MVPA at school and “other” locations. The school physical activity environment index was related to greater MVPA and less sedentary time at school. The home activity environment index was related to greater MVPA at home. The non-school sedentary psychosocial index was related to less sedentary time at home. Interactions among indices revealed adolescents with low support on one index benefited (i.e., exhibited more optimal behavior) from high support on another index (e.g., higher scores on the location-general PA psychosocial index moderated lower scores on the home PA environment index). Concurrent high support on two indices did not provide additional benefit. Conclusions No psychosocial or environment indices, including location-general indices, were related to activity in all locations. Most of the location-specific indices were associated with activity in the matching location(s). These findings provide preliminary evidence that psychosocial and environmental correlates of activity are location specific. Future studies should further develop location-specific measures and evaluate these constructs and whether interventions may be optimized by targeting location-specific psychosocial and environmental variables across multiple locations.

Introduction Built and natural environments may provide opportunities for physical activity. However, studies are limited by primarily using residential addresses to define exposure and self-report to measure physical activity. We quantified associations between global positioning systems (GPS)-based activity space measures of environmental exposure and accelerometer-based physical activity. Methods Using a nationwide sample of working female adults (N=354), we obtained seven days of GPS and accelerometry data. We created Daily Path Area activity spaces using GPS data and linked these activity spaces to spatial datasets on walkability (EPA Smart Location Database at the Census block group level) and greenness (satellite vegetation at 250m resolution). We utilized generalized additive models to examine nonlinear associations between activity space exposures and accelerometer-derived physical activity outcomes adjusted for demographic characteristics, socioeconomic factors, and self-rated health. Results Higher activity space walkability was associated with higher levels of moderate-vigorous physical activity, and higher activity space greenness was associated with greater numbers of steps per week. No strong relationships were observed for sedentary behavior or light physical activity. Highest levels of moderate-vigorous physical activity were observed for participants with both high walkability and high greenness in their activity spaces. Conclusion This study contributes evidence that higher levels of physical activity occur in environments with more dense, diverse, and well-connected built environments, and with higher amounts of vegetation. These data suggest that urban planners, landscape architects, and policy makers should implement and evaluate environmental interventions to encourage higher levels of physical activity.

Older adults with obesity spend the majority of their waking hours sedentary. Given substantial barriers to regular physical activity in this population, approaches to reduce sedentary time could be an effective health promotion strategy. We present the protocol of a randomized controlled trial to reduce sitting time in older adults with a body mass index of 30 kg/m² or above. Participants (N = 284) will be randomized to receive a sitting reduction intervention (termed I-STAND) or a healthy living focused attention control condition. I-STAND includes 10 contacts with a health coach (10 sessions total) and participants receive a wrist-worn prompting device and portable standing desk. The healthy living condition includes 10 sessions with a health coach to set goals around various topics relating to healthy aging. Participants receive their assigned intervention for 6 months. After 6 months, those receiving the I-STAND condition are re-randomized to receive five booster health coaching sessions by ‘phone or no further contact; healthy living participants receive no further contact and those in both conditions are followed for an additional 6 months. Measurements initially included wearing an activPAL device and completing several biometric tests (e.g., blood pressure, HbA1c), at baseline, 3 months, 6 months, and 12 months; however, during the COVID-19 pandemic we shifted to remote assessments and were unable to collect all of these measures. The primary outcomes remained activPAL-assessed sitting time and blood pressure. Recruitment is anticipated to be completed in 2022.

As the U.S. population ages, communities must adapt to help older adults thrive. Built environment features, like safe sidewalks and crosswalks, provide the foundation for age- and physical activity-friendly communities. Controlled studies are needed to evaluate advocacy training programs that instruct and support seniors to advocate for more walkable neighborhoods. The Senior Change Makers Pilot Study evaluated an advocacy program that taught seniors to evaluate pedestrian environments using the validated MAPS-Mini audit tool, identify barriers, and advocate for improvements. Participants (n = 50) were recruited from four low-income senior housing sites in San Diego, CA, which were randomly assigned to an 8-week advocacy program or physical activity (PA) comparison intervention. Evaluation included surveys, accelerometers to assess PA, and direct observation. Primary outcomes were seniors' advocacy confidence and skills. Main analyses used repeated measures ANOVAs. Seniors in the advocacy condition (n = 17) increased their advocacy outcome efficacy (p = .03) and knowledge of resources (p = .04) more than seniors in the PA condition (n = 33). Most seniors in the advocacy condition completed a street audit (84%), submitted an advocacy request (79%), or made an advocacy presentation to city staff (58%). Environmental changes included repairs to sidewalks and crosswalks. City staff approved requests for lighting, curb cuts, and crosswalk markings. Seniors' accelerometer-measured PA did not significantly increase, but self-reported transportation activity increased in the PA condition (p = .04). This study showed the potential of advocacy training to empower seniors to make communities more age- and activity-friendly.

Objective: To evaluate whether sedentary time (ST) and/or sedentary behavior patterns are related to incident diabetes in the U.S.'s oldest age-groups. Research design and methods: Women without physician-diagnosed diabetes (n = 4,839, mean ± SD age = 79 ± 7 years) wore accelerometers for ≥4 days and were followed up to 6 years for self-reported newly diagnosed diabetes requiring treatment with medications. Hazard ratios (HRs) for incident diabetes were estimated across quartiles of accelerometer-measured ST and mean bout duration with use of Cox proportional hazards models. We conducted isotemporal substitution analyses using Cox regression and tested associations with risk for diabetes after statistically replacing ST with light physical activity (PA) or moderate-to-vigorous PA (MVPA) and after replacing light PA with MVPA. Results: During 20,949 person-years, 342 diabetes cases were identified. Women in ST quartile (Q)2, Q3, and Q4 (vs. Q1) had incident diabetes HR 1.20 (95% CI 0.87-1.65), 1.33 (0.97-1.82), and 1.21 (0.86-1.70); Ptrend = 0.04. Respective HRs following additional adjustment for BMI and MVPA were 1.04 (95% CI 0.74-1.47), 1.04 (0.72-1.50), and 0.85 (0.56-1.29); Ptrend = 0.90. Fully adjusted isotemporal substitution results indicated that each 30 min of ST replaced with MVPA (but not light PA) was associated with 15% lower risk for diabetes (HR 0.85 [95% CI 0.75-0.96]; P = 0.01); the HR for replacing 30 min of light PA with MVPA was 0.85 (95% CI 0.73-0.98); P = 0.03. Mean bout duration was not associated with incident diabetes. Conclusions: Statistically replacing ST or light PA with MVPA was associated with lower diabetes risk in older women. While reducing ST is important for several health outcomes, results indicate that to reduce diabetes risk among older adults, the primary public health focus should be on increasing MVPA.

Background Investigation of physical activity and dietary behaviors across locations can inform “setting-specific” health behavior interventions and improve understanding of contextual vulnerabilities to poor health. This study examined how physical activity, sedentary time, and dietary behaviors differed across home, school, and other locations in young adolescents. Methods Participants were adolescents aged 12–16 years from the Baltimore-Washington, DC and the Seattle areas from a larger cross-sectional study. Participants (n = 472) wore an accelerometer and Global Positioning Systems (GPS) tracker (Mean days = 5.12, SD = 1.62) to collect location-based physical activity and sedentary data. Participants (n = 789) completed 24-h dietary recalls to assess dietary behaviors and eating locations. Spatial analyses were performed to classify daily physical activity, sedentary time patterns, and dietary behaviors by location, categorized as home, school, and “other” locations. Results Adolescents were least physically active at home (2.5 min/hour of wear time) and school (2.9 min/hour of wear time) compared to “other” locations (5.9 min/hour of wear time). Participants spent a slightly greater proportion of wear time in sedentary time when at school (41 min/hour of wear time) than at home (39 min/hour of wear time), and time in bouts lasting ≥30 min (10 min/hour of wear time) and mean sedentary bout duration (5 min) were highest at school. About 61% of daily energy intake occurred at home, 25% at school, and 14% at “other” locations. Proportionately to energy intake, daily added sugar intake (5 g/100 kcal), fruits and vegetables (0.16 servings/100 kcal), high calorie beverages (0.09 beverages/100 kcal), whole grains (0.04 servings/100 kcal), grams of fiber (0.65 g/100 kcal), and calories of fat (33 kcal/100 kcal) and saturated fat (12 kcal/100 kcal) consumed were nutritionally least favorable at “other” locations. Daily sweet and savory snacks consumed was highest at school (0.14 snacks/100 kcal). Conclusions Adolescents’ health behaviors differed based on the location/environment they were in. Although dietary behaviors were generally more favorable in the home and school locations, physical activity was generally low and sedentary time was higher in these locations. Health behavior interventions that address the multiple locations in which adolescents spend time and use location-specific behavior change strategies should be explored to optimize health behaviors in each location.

Background: The authors tested the efficacy of the "I-STAND" intervention for reducing sitting time, a novel and potentially health-promoting approach, in older adults with obesity. Methods: The authors recruited 60 people (mean age = 68 ± 4.9 years, 68% female, 86% White; mean body mass index = 35.4). The participants were randomized to receive the I-STAND sitting reduction intervention (n = 29) or healthy living control group (n = 31) for 12 weeks. At baseline and at 12 weeks, the participants wore activPAL devices to assess sitting time (primary outcome). Secondary outcomes included fasting glucose, blood pressure, and weight. Linear regression models assessed between-group differences in the outcomes. Results: The I-STAND participants significantly reduced their sitting time compared with the controls (-58 min per day; 95% confidence interval [-100.3, -15.6]; p = .007). There were no statistically significant changes in the secondary outcomes. Conclusion: I-STAND was efficacious in reducing sitting time, but not in changing health outcomes in older adults with obesity.

Creating more physical activity–supportive built environments is recommended by the World Health Organization for controlling noncommunicable diseases. The IPEN (International Physical Activity and Environment Network) Adult Study was undertaken to provide international evidence on associations of built environments with physical activity and weight status in 12 countries on 5 continents ( n > 14,000). This article presents reanalyzed data from eight primary papers to identify patterns of findings across studies. Neighborhood environment attributes, whether measured objectively or by self-report, were strongly related to all physical activity outcomes (accelerometer-assessed total physical activity, reported walking for transport and leisure) and meaningfully related to overweight/obesity. Multivariable indexes of built environment variables were more strongly related to most outcomes than were single-environment variables. Designing activity-supportive built environments should be a higher international health priority. Results provide evidence in support of global initiatives to increase physical activity and control noncommunicable diseases while achieving sustainable development goals.

Background and Hypothesis During waking hours, older adults spend the most time sitting and are least likely to meet physical activity guidelines. Such a sedentary lifestyle is associated with cardiovascular and coronary heart disease mortality risk, particularly in postmenopausal Hispanic/Latino women. The deleterious impact of prolonged sitting includes endothelial dysfunction, which favors atherosclerotic initiation. Extracellular vesicles (EVs) are potential biomarkers of physiologic function, which carry molecular cargo from the parent cell, including metabolites, proteins, and nucleic acids, that reflect the cell’s biological health status. Some EV cargo, such as microRNAs (miRs), are capable of mediating cell‐to‐cell communication. We hypothesize that miRs encapsulated in endothelial cell (EC)‐derived EVs serve as molecular transducers bridging prolonged sitting with cardiovascular disease (CVD) risk. Objective Identify potential miR transducers associated with prolonged sitting durations. Materials, Methods, and Results Archival behavior data and plasma samples were used from a population of 518 women participants, aged ≥55 years and BMI ≥25kg/m ² , from the UCSD Metabolic, Exercise, and Nutrition, Reach for Health, and Community of Mine studies. Objective measures of sitting posture and moderate‐to‐vigorous physical activity (MVPA) were collected from participants using waist‐worn ActiGraph. We identified subpopulations of women who had low MVPA and the shortest or longest mean sitting bout duration across quartiles as Interrupted Sitters (IS, n=18) or Super Sitters (SS, n=53), respectively. CD144 ⁺ EVs representing EC‐EVs were immunoprecipitated from archival plasma samples for miR profiling. Five target miRs (miR‐199a‐5p, let‐7d‐5p, miR‐140‐5p, miR‐142‐3p, miR‐133b) potentially associated with sitting patterns were identified using Qiagen miScript miR PCR Array Human Cardiovascular disease, employing propensity score balance for confounding factors. Technical validation by qPCR corroborated that 3 miRs had significantly greater expressions in EC‐EVs from SS, compared to IS. The significance of this expression difference was sustained in the non‐Hispanic subpopulation, but only miR‐133b was still significantly different between the two groups in the Hispanic subpopulation. Moreover, miR‐133b expression, but not miR‐199a‐5p, let‐7d‐5p, or miR‐140‐5p expression, in the SS Hispanic group decreased with increased MVPA. Conclusion EC‐EVs carrying CVD‐related miRs may be promising for monitoring prolonged sitting patterns in overweight postmenopausal women, which may differ by ethnicity. Support or Funding Information American Heart Association Go Red For Women Strategically Focused Network grant (16SFRN28420000) and the National Institutes of Health: Community of Mine (R01 CA179977), Reach for Health (U54 CA155435) and Metabolism, Exercise and Nutrition at UCSD (MENU; U54 CA155435 and also the California Walnut Commission), and training grant from NHLBI (T32 HL079891).

Purpose: To test the validity of the Ecological Video Identification of Physical Activity (EVIP) computer vision algorithms for automated video-based ecological assessment of physical activity in settings such as parks and schoolyards. Methods: 27 hours of video were collected from stationary overhead video cameras across 22 visits in 9 sites capturing organized activities. Each person in the setting wore an accelerometer and each second was classified as moderate-to-vigorous physical activity (MVPA) or sedentary/light activity. 57,987 seconds of data were used to train and test computer vision algorithms for estimating the total number of people in the video and number of people active (in MVPA) each second. In the testing dataset (38,658 seconds), video-based System for Observing Play and Recreation in Communities (SOPARC) observations were conducted every 5-minutes (130 observations). Concordance correlation coefficients (CCC) and mean absolute errors (MAE) assessed agreement between (1) EVIP and ground truth (people counts+accelerometry) and (2) SOPARC observation and ground truth. Site and scene-level correlates of error were investigated. Results: Agreement between EVIP and ground truth was high for number of people in the scene (CCC=0.88; MAE=2.70) and moderate for number of people active (CCC=0.55; MAE=2.57). EVIP error was uncorrelated with camera placement, presence of obstructions or shadows, and setting type. For both number in scene and number active, EVIP outperformed SOPARC observations in estimating ground truth values (CCCs were larger by 0.11-0.12 and MAEs smaller by 41%-48%). Conclusion: Computer vision algorithms are promising for automated assessment of setting-based physical activity. Such tools would require less manpower than human observation, produce more and potentially more accurate data, and allow for ongoing monitoring and feedback to inform interventions.