Background: Assessment of park characteristics that may support physical activity (PA) can guide the design of more activity-supportive parks. Direct-observation measures are seldom used due to time and resource restraints. Methods: The authors developed shortened versions of the original Environmental Assessment of Public Recreation Spaces (EAPRS) tool and tested their construct validity by comparing scores from 40 parks in San Diego, CA to observe park use and PA. Results: PA elements were positively associated with park use and park PA across all versions, with the highest correlations for trails (.45 for use and .51 for PA using EAPRS-Original; .57 use and .62 PA using Abbreviated; and .38 use and .43 PA using Mini). Presence of amenities, using Abbreviated and Mini versions, was correlated with park use (.71, .64) and PA (.67, .59). The overall park quality score using Abbreviated and Mini had similar correlations (adjusted for park size) with park use (.74, .72) and PA (.72, .70) as EAPRS-Original (.71 use and .73 PA). Conclusion: In all 3 versions, EAPRS overall park scores were strongly related to observed park use and PA. Shorter versions of EAPRS make it more feasible to use park observations in research and practice.
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Carrie M. Geremia, Kelli L. Cain, Terry L. Conway, James F. Sallis, and Brian E. Saelens
Kelli L. Cain, James F. Sallis, Terry L. Conway, Delfien Van Dyck, and Lynn Calhoon
In 2005, investigators convened by the National Cancer Institute recommended development of standardized protocols for accelerometer use and reporting decision rules in articles. A literature review was conducted to document accelerometer methods and decision rule reporting in youth physical activity articles from 2005−2010.
Nine electronic databases identified 273 articles that measured physical activity and/or sedentary behavior using the most-used brand of accelerometer (ActiGraph). Six key methods were summarized by age group (preschool, children, and adolescents) and trends over time were examined.
Studies using accelerometers more than doubled from 2005−2010. Methods included 2 ActiGraph models, 6 epoch lengths, 6 nonwear definitions, 13 valid day definitions, 8 minimum wearing day thresholds, 12 moderate-intensity physical activity cut points, and 11 sedentary cut points. Child studies showed the most variation in methods and a trend toward more variability in cut points over time. Decision rule reporting improved, but only 54% of papers reported on all methods.
The increasing diversity of methods used to process and score accelerometer data for youth precludes comparison of results across studies. Decision rule reporting is inconsistent, and trends indicate declining standardization of methods. A methodological research agenda and consensus process are proposed.
Ugo Lachapelle, Larry Frank, Brian E. Saelens, James F. Sallis, and Terry L. Conway
Most public transit users walk to and from transit. We analyzed the relationship between transit commuting and objectively measured physical activity.
Adults aged 20 to 65 working outside the home (n = 1237) were randomly selected from neighborhoods in Seattle and Baltimore regions. Neighborhoods had high or low median income and high or low mean walkability. Mean daily minutes of accelerometer-measured moderate-intensity physical activity (MPA) were regressed on frequency of commuting by transit and neighborhood walkability, adjusting for demographic factors and enjoyment of physical activity. Interaction terms and stratification were used to assess moderating effect of walkability on the relation between transit commuting and MPA. Associations between transit commuting and self-reported days walked to destinations near home and work were assessed using Chi Square tests.
Regardless of neighborhood walkability, those commuting by transit accumulated more MPA (approximately 5 to 10 minutes) and walked more to services and destinations near home and near the workplace than transit nonusers. Enjoyment of physical activity was not associated with more transit commute, nor did it confound the relationships between MPA and commuting.
Investments in infrastructure and service to promote commuting by transit could contribute to increased physical activity and improved health.
Kavita A. Gavand, Kelli L. Cain, Terry L. Conway, Brian E. Saelens, Lawrence D. Frank, Jacqueline Kerr, Karen Glanz, and James F. Sallis
Background: To examine relations between parents’ perceived neighborhood recreation environments and multiple measures of adolescent physical activity (PA). Methods: Participants (N = 928; age 14.1 [1.4] y, 50.4% girls, and 33.4% nonwhite/Hispanic) and their parents were recruited. Teen moderate to vigorous PA (MVPA) was assessed with 7-day accelerometry. Self-reported total PA, PA near home, and PA at recreation locations were also assessed. Proximity of home to 8 types of recreation facilities was reported by parents. Mixed-model linear regressions relating environments to various measures of PA were adjusted for demographics and neighborhood clustering. Results: Perceiving more availability of recreation facilities around home was related to higher reports of days per week with 60+ minutes of PA (b = 0.153; P < .05), reported PA time near home (b = 0.152; P < .001), PA time at recreation facilities (b = 0.161; P < .001), accelerometer-measured total MVPA (b = 1.741; P < .05), and nonschool MVPA (b = 1.508; P < .01). Adolescents living in lowest quintile of recreation facility availability averaged 27.6 (3.2) minutes per day of total MVPA versus 49.8 (3.5) minutes per day for those living in highest quintile. Conclusions: Adolescents living in neighborhoods that parents reported having more availability of recreation facilities around homes had higher activity across 5 indicators of PA.
Christina M. Thornton, Kelli L. Cain, Terry L. Conway, Jacqueline Kerr, Brian E. Saelens, Lawrence D. Frank, Karen Glanz, and James F. Sallis
The after-school period provides an opportune context for adolescent physical activity. This study examined how characteristics of after-school recreation environments related to adolescent physical activity.
Participants were 889 adolescents aged 12 to 17 (mean = 14.1, SD = 1.4) from 2 US regions. Adolescents reported on whether their school offered after-school supervised physical activity, access to play areas/fields, and presence of sports facilities. Outcomes were accelerometer-measured after-school physical activity, reported physical activity on school grounds during nonschool hours, attainment of 60 minutes of daily physical activity excluding school physical education, and BMI-for-age z-score. Mixed regression models adjusted for study design, region, sex, age, ethnicity, vehicles/licensed drivers in household, and distance to school.
School environment variables were all significantly associated with self-reported physical activity on school grounds during non-school hours (P < .001) and attainment of 60 minutes of daily physical activity (P < .05). Adolescents’ accelerometer-measured after-school physical activity was most strongly associated with access to supervised physical activity (P = .008).
Policies and programs that provide supervised after-school physical activity and access to play areas, fields, and sports facilities may help adolescents achieve daily physical activity recommendations.
Simon J. Marshall, Stuart J.H. Biddle, James F. Sallis, Thomas L. McKenzie, and Terry L. Conway
Few studies have attempted to describe patterns of sedentary behavior among children and examine how these relate to patterns of physical activity. A group of 2,494 youth aged 11–15 years from the USA and UK completed a physical activity checklist. Low intercorrelations between sedentary behaviors suggest youth sedentariness is multifaceted and cannot be represented accurately by any one behavior such as TV viewing. Cluster analysis identified three groups of young people, differentiated by the level and type of sedentary behavior and physical activity. Physical activity and sedentary behavior are not two sides of the same coin. Further study should examine the health-related outcomes associated with sedentary behavior and the modifiable determinants of these behaviors among young people.
Kelli L. Cain, Edith Bonilla, Terry L. Conway, Jasper Schipperijn, Carrie M. Geremia, Alexandra Mignano, Jacqueline Kerr, and James F. Sallis
Purpose: The present study examined various accelerometer nonwear definitions and their impact on detection of sedentary time using different ActiGraph models, filters, and axes. Methods: In total, 61 youth (34 children and 27 adolescents; aged 5–17 y) wore a 7164 and GT3X+ ActiGraph on a hip-worn belt during a 90-minute structured sedentary activity. Data from GT3X+ were downloaded using the Normal filter (N) and low-frequency extension (LFE), and vertical axis (V) and vector magnitude (VM) counts were examined. Nine nonwear definitions were applied to the 7164 model (V), GT3X+LFE (V and VM), and GT3X+N (V and VM), and sedentary estimates were computed. Results: The GT3X+LFE-VM was most sensitive to movement and could accurately detect observed sedentary time with the shortest nonwear definition of 20 minutes of consecutive “0” counts for children and 40 minutes for adolescents. The GT3X+N-V was least sensitive to movement and required longer definitions to detect observed sedentary time (40 min for children and 90 min for adolescents). VM definitions were 10 minutes shorter than V definitions. LFE definitions were 40 minutes shorter than N definitions in adolescents. Conclusion: Different nonwear definitions are needed for children and adolescents and for different model-filter-axis types. Authors need to consider nonwear definitions when comparing prevalence rates of sedentary behavior across studies.
Jeanette I. Candelaria, James F. Sallis, Terry L. Conway, Brian E. Saelens, Lawrence D. Frank, and Donald J. Slymen
The study aim was to assess the relation of parent status to physical activity (PA) and the impact of parental roles, age and number of children on PA.
Data for 909 women and 965 men, aged 20–57, were analyzed. Mixed Models were used to assess differences in PA between parents and adults without children, with analyses stratified by sex. The primary outcome was accelerometer-measured total daily minutes of moderate-to-vigorous PA (MVPA).
Parenthood was not related to MVPA, but mothers reported more total PA than nonmothers. For mothers and fathers, self-reported household activity was higher and sitting time lower, compared with nonparents. Both men and women with children aged 0–5 reported the highest household activity and the lowest sitting time, with household PA higher and sitting time lower with more children. There was no evidence that leisure, transport, or occupational activity varied by parenthood.
Considering the potential impact of child-rearing on parent time demands, there was little difference in parents’ objectively measured MVPA compared with nonparents. Educational interventions or extracurricular programs for students and parents could target families with school-aged children. Development of tools to obtain parent reports of child care-specific PA behaviors would be useful.
Carolyn C. Voorhees, Dianne J. Catellier, J. Scott Ashwood, Deborah A. Cohen, Ariane Rung, Leslie Lytle, Terry L. Conway, and Marsha Dowda
Socioeconomic status (SES) has well known associations with a variety of health conditions and behaviors in adults but is unknown in adolescents.
Multilevel analysis was conducted to examine the associations between individual and neighborhood-level measures of SES and physical activity and body mass index in a sample of 1554 6th grade girls selected at random from 36 middle schools across 6 geographic regions in the United States that participated in the Trial of Activity for Adolescent Girls (TAAG). Data on parental education and employment, and receipt of subsidized school lunch were collected by questionnaire. Neighborhood-level SES was measured by the Townsend Index. Nonschool physical activity levels were measured by accelerometer and type, location and context was measured using a 3 day physical activity recall (3DPAR).
After controlling for race, lower parental education and higher levels of social deprivation were associated with higher BMI. In a model with both variables, effects were attenuated and only race remained statistically significant. None of the indices of SES were related to accelerometer measured physical activity. Bivariate associations with self-reported Moderate-Vigorous Physical Activity (MVPA) location and type (3DPAR) varied by SES.
Among adolescent girls in the TAAG Study, the prevalence of overweight is high and inversely related to individual and neighborhood SES.
Lilian G. Perez, Terry L. Conway, Adrian Bauman, Jacqueline Kerr, John P. Elder, Elva M. Arredondo, and James F. Sallis
Background: Associations between the built environment and physical activity (PA) may vary by sociodemographic factors. However, such evidence from international studies is limited. This study tested the moderating effects of sociodemographic factors on associations between perceived environment and self-reported total PA among adults from the International Prevalence Study. Methods: Between 2002 and 2003, adults from 9 countries (N = 10,258) completed surveys assessing total PA (International Physical Activity Questionnaire-short), perceived environment, and sociodemographics (age, gender, and education). Total PA was dichotomized as meeting/not meeting (a) high PA levels and (b) minimum PA guidelines. Logistic models tested environment by sociodemographic interactions (24 total). Results: Education and gender moderated the association between safety from crime and meeting high PA levels (interaction P < .05), with inverse associations found only among the high education group and men. Education and gender also moderated associations of safety from crime and the presence of transit stops with meeting minimum PA guidelines (interaction P < .05), with positive associations found for safety from crime only among women and presence of transit stops only among men and the high education group. Conclusions: The limited number of moderating effects found provides support for population-wide environment–PA associations. International efforts to improve built environments are needed to promote health-enhancing PA and maintain environmental sustainability.