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  • Author: Kelli L. Cain x
  • Psychology and Behavior in Sport/Exercise x
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Kelli L. Cain, James F. Sallis, Terry L. Conway, Delfien Van Dyck and Lynn Calhoon

Background:

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.

Methods:

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.

Results:

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.

Conclusion:

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.

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Carrie M. Geremia, Kelli L. Cain, Terry L. Conway, James F. Sallis and Brian E. Saelens

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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Christina M. Thornton, Kelli L. Cain, Terry L. Conway, Jacqueline Kerr, Brian E. Saelens, Lawrence D. Frank, Karen Glanz and James F. Sallis

Background:

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.

Methods:

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.

Results:

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).

Conclusions:

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.

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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.

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Eric B. Hekler, Matthew P. Buman, William L. Haskell, Terry L. Conway, Kelli L. Cain, James F. Sallis, Brian E. Saelens, Lawrence D. Frank, Jacqueline Kerr and Abby C. King

Background:

Recent research highlights the potential value of differentiating between categories of physical activity intensities as predictors of health and well-being. This study sought to assess reliability and concurrent validity of sedentary (ie, 1 METs), low-light (ie, >1 and ≤2 METs; eg, playing cards), high-light (ie, >2 and <3 METs; eg, light walking), moderate-to-vigorous physical activity (MVPA, ≥3 METs), and “total activity” (≥2 METs) from the CHAMPS survey. Further, this study explored over-reporting and double-reporting.

Methods:

CHAMPS data were gathered from the Seniors Neighborhood Quality of Life Study, an observational study of adults aged 65+ years conducted in 2 US regions.

Results:

Participants (N = 870) were 75.3 ± 6.8 years old, with 56% women and 71% white. The CHAMPS sedentary, low-light, high-light, total activity, and MVPA variables had acceptable test-retest reliability (ICCs 0.56−0.70). The CHAMPS high-light (ρ = 0.27), total activity (ρ = 0.34), and MVPA (ρ = 0.37) duration scales were moderately associated with accelerometry minutes of corresponding intensity, and the sedentary scale (ρ = 0.12) had a lower, but significant correlation. Results suggested that several CHAMPS items may be susceptible to over-reporting (eg, walking, housework).

Conclusions:

CHAMPS items effectively measured high-light, total activity, and MVPA in seniors, but further refinement is needed for sedentary and low-light activity.

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Christina M. Patch, Caterina G. Roman, Terry L. Conway, Ralph B. Taylor, Kavita A. Gavand, Brian E. Saelens, Marc A. Adams, Kelli L. Cain, Jessa K. Engelberg, Lauren Mayes, Scott C. Roesch and James F. Sallis

Background: A common hypothesis is that crime is a major barrier to physical activity, but research does not consistently support this assumption. This article advances research on crime-related safety and physical activity by developing a multilevel conceptual framework and reliable measures applicable across age groups. Methods: Criminologists and physical activity researchers collaborated to develop a conceptual framework. Survey development involved qualitative data collection and resulted in 155 items and 26 scales. Intraclass correlation coefficients (ICCs) were computed to assess test–retest reliability in a subsample of participants (N = 176). Analyses were conducted separately by age groups. Results: Test–retest reliability for most scales (63 of 104 ICCs across 4 age groups) was “excellent” or “good” (ICC ≥ .60) and only 18 ICCs were “poor” (ICC < .40). Reliability varied by age group. Adolescents (aged 12–17 y) had ICCs above the .40 threshold for 21 of 26 scales (81%). Young adults (aged 18–39 y) and middle-aged adults (aged 40–65 y) had ICCs above .40 for 24 (92%) and 23 (88%) scales, respectively. Older adults (aged 66 y and older) had ICCs above .40 for 18 of 26 scales (69%). Conclusions: The conceptual framework and reliable measures can be used to clarify the inconclusive relationships between crime-related safety and physical activity.

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Ding Ding, James F. Sallis, Gregory J. Norman, Lawrence D. Frank, Brian E. Saelens, Jacqueline Kerr, Terry L. Conway, Kelli Cain, Melbourne F. Hovell, C. Richard Hofstetter and Abby C. King

Some attributes of neighborhood environments are associated with physical activity among older adults. This study examined whether the associations were moderated by driving status. Older adults from neighborhoods differing in walkability and income completed written surveys and wore accelerometers (N = 880, mean age = 75 years, 56% women). Neighborhood environments were measured by geographic information systems and validated questionnaires. Driving status was defined on the basis of a driver’s license, car ownership, and feeling comfortable to drive. Outcome variables included accelerometer-based physical activity and self-reported transport and leisure walking. Multilevel generalized linear regression was used. There was no significant Neighborhood Attribute × Driving Status interaction with objective physical activity or reported transport walking. For leisure walking, almost all environmental attributes were positive and significant among driving older adults but not among nondriving older adults (five significant interactions at p < .05). The findings suggest that driving status is likely to moderate the association between neighborhood environments and older adults’ leisure walking.