A Social Ecological Assessment of Physical Activity among Urban Adolescents Alice Fang Yan, MD, PhD; Carolyn C. Voorhees, MS, PhD; Kenneth H. Beck, PhD, FAAHB; Min Qi Wang, PhD, FAAHB

Objectives: To examine the physical, social and temporal contexts of physical activity, as well as sex variations of the associations among 314 urban adolescents. Methods: Three-day physical activity recall measured contextual information of physical activities. Logistic regressions and generalized estimating equation models examined associations among physical activity types and contexts, and sex differences. Results: Active transportation was the most common physical activity. Home/neighborhood and school were the most common physical activity locations. School was the main location for organized physical

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he Physical Activity Guidelines for Americans recommends that children and adolescents participate in at least 60 minutes of moderate-to-vigorous physical activity (MVPA) each day.1 However, a national study2 indicated that only 15.3% of high school students met the national recommendations for aerobic physical activity. This figure is well below the Healthy People 2020 national objective of 20.2% (physical activity – 3. 1). When further examining the high school students subgroups, only 8.4% of the girls (as opposed to 21.9% of the boys), and 15% of the non-Hispanic African Americans2 met the aerobic physical activity objective, indicating major differences within these subpopulations. Racial/ethnic disparities in overweight grow as the rates accelerate among African Americans.3 Indeed, 27% of African-American girls ages12 to 19 are overweight compared to the 15.5% national statistic of the same age group.4 Research indicates that inadequate physical activity is one of the major contributors of obesity Alice Fang Yan, Assistant Professor, Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI. Carolyn C. Voorhees, Research Associate Professor, Kenneth H. Beck, Professor and Min Qi Wang, Professor, Maryland School of Public Health, College Park, MD. Correspondence Dr Yan; [email protected]

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activity. Boys spent more time on recreational physical activity, regardless of the social context, compared to girls. The average physical activity level was significantly lower for girls than for boys after school. Conclusions: Physical activity promotion interventions need to target physical activity environments and social contexts in a sex-specific manner. Key words: social-ecological assessment; physical activity contexts; neighborhood environment; high school students; African American Am J Health Behav. 2014;38(3):379-391 DOI: http://dx.doi.org/10.5993/AJHB.38.3.7

among African Americans. In particular, problems of low accessibility to physical activity facilities and safety are more pronounced in urban, low-income neighborhoods. African-American adolescents, who are more likely to live in these locales, are less likely to have available facilities/locations that facilitate physical activity such as parks, school yards or community centers.5 Assessing physical activity in this subpopulation can provide policymakers, healthcare providers, health educators, and public health officials with important information to guide the distribution of initiatives and resources to reduce or eliminate health disparities. A common framework for examining physical activity is the social ecological model.6-9 Ecological models9 depict reciprocal interactions in multiple levels, including intrapersonal, interpersonal, organizational, community, and public policy. This model is well suited for studying physical activity patterns, because physical activity is often conducted in specific physical environments (eg, locations) under certain social environments at a given time.6 The physical environment or location of physical activity indicates where (eg, home, neighborhood, community, or school) an individual spends time and engages in physical activity.10,11 Social environmental factors, including seeing other adolescents performing physical activities12

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A Social Ecological Assessment of Physical Activity among Urban Adolescents and exercising with peers and friends,13,14 are positively associated with adolescent physical activity behaviors. Out-of-school temporal factors such as before- and after-school time provide a challenge and an opportunity for physical activity promotion, because students accrue 70%–80% of their daily physical activity away from school.15,16 Therefore, it is important to examine collectively the physical, social, and temporal contexts of physical activity patterns17 for high school students, given the steadily declining rate of physical activity in this age group.18 A systematic examination of physical activity location, time of day, and social interaction may inform the development of effective intervention, and is likely to result in successfully promoting physical activity for high school youth. Healthy People 2020 encourages using a multidisciplinary approach to increase the physical activity levels and improve health in the United States.19 As a result, a burgeoning area of research related to active living has emerged. Active living is a broader concept that promotes the incorporation of all domains of physical activity including recreation, transportation, occupation, and household activities into daily routines.6,20 Traditional exercise assessment studies21-23 examined the “where,” “when,” and “with whom” questions on relatively limited types of physical activity such as leisure time exercise and walking.22 Furthermore, although research consistently demonstrated that girls engaged in lower levels of physical activity than boys,18,24 fewer studies have examined whether there are sex differences in the context of social, physical and temporal factors. As promoting active living becomes a national priority, a better understanding of how adolescents incorporate these active living domains6 and how the effects of these contextual factors may differ for boys and girls will assist physical activity promotion scientists in refining sex-specific intervention strategies. Using the social-ecological framework,25 the purpose of the current study was 3-fold: (1) to examine physical activity domains; (2) to investigate the extent to which the frequency of physical activities occurs within these physical (where), social (with whom) and temporal (when) contexts; and (3) to examine how these associations vary by sex, in a sample of predominately urban African-American adolescents. METHODS Participants and Procedure Participants were enrolled in the Baltimore Active Living Teens Study (BALTS), a cross-sectional study that investigated the effects of multifactor risks and protective factors on physical activity.26-28 The sample contained 350 urban high school students (grades 9 through 12). Students in grades 9 to 12 were eligible to participate and were recruited from 2 high schools in Baltimore, Maryland.26 Exclusion criteria were: (1) cannot read and understand the survey questions, which will be in

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English; (2) a doctor saying that exercise is contraindicated; (3) has any condition, including a heart problem that requires a limited physical activity; fainting with exercise in the past 6 months; uncontrolled asthma; high blood pressure that is not controlled by medication; diabetes with frequent low or high blood glucose levels (sugars); thyroid problems that are not controlled by medication; seizures that are not controlled by medication; or sickle cell disease, cystic fibrosis, anorexia nervosa, severe kidney problems or severe liver problems. At both schools, students in 29 non-core classes were recruited for study participation. The school administration selected these classes. In deciding which would be the participating classes, they chose to include non-core classes to avoid using class time during required courses. Classes were also chosen in a manner that addressed the principal investigator’s request to recruit students from all 4 grades. The trained research assistants solicited participants through in-class presentations about the project and explanations of the study purpose. The recruitment rate was 54%.29 This was based on 649 students who were recruited and 350 who agreed to participate.28 A comparison of the demographic variables including grades and sexes of those who declined and those who participated suggested no difference between the 2 groups.28 Based on this research team’s experience, we estimated that the effect size of this study for most independent variables would be considered medium, ranging from .47 to .55. This is consistent with the common practice of using a value of 0.5, as it indicates a moderate difference.9 The statistical power is, therefore, between .85 - .90.9 Physical activity was measured by accelerometers (ActiGraph, Pensacola, FL). Students’ physical activity context information was measured by Stanford 3-Day Physical Activity Recall (3DPAR).28 Physical activity was also measured objectively by accelerometers (ActiGraph, Pensacola, FL). Participants’ self-reported sociodemographic information was also obtained through a survey. Trained research team members also measured height and weight and calculated each participant’s body mass index (BMI) (kg/m2) from these numbers. Each participant’s parent or guardian provided written informed consent and subjects assented to participation. Each subject received $15 incentives during each measurement visit. The data were collected from January to June 2006. Instruments Physical activity domains; physical, social and temporal contexts of physical activity. The Stanford 3-Day Physical Activity Recall (3DPAR)28,30 measured contextual information of the participants’ physical activities. The Stanford 3-Day Physical Activity Recall questionnaire has been regarded as a reliable and valid instrument to capture the type and context of adolescent ac-

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Figure 1 Intensity Scale

• Light - Slow breathing, little or no movement.

   

 

 

•Moderate - Normal breathing and some movement.

• Hard - Increased breathing and moderate movement.

• Very Hard - Hard breathing and quick movement.          

         

tivity.30-33 The instrument can be completed during a single 30–45 minute session. Consistent with the literature,30-32 study participants reported their physical activity in terms of type and context during the past 3 days. The physical activity self-report provided a list of 70 types of activities and their code numbers. These included sedentary activities, walking or biking for transportation, work (eg, a part-time job, or household chores

and yard work), school, physical education, leisure time, play/recreation, exercise and working out.28 For the purpose of this study, we examined physical activity types in 4 domains common for adolescents.6,10 They were (1) school-related physical activities including club and student activities, marching band, or flag line and physical education class (offered during off-school time); (2) active transportation including travel by riding in a bus,

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A Social Ecological Assessment of Physical Activity among Urban Adolescents trolley or boat, walking and bicycle travel; (3) occupational- or house chore-related physical activity, including a part-time job, child care, house chores (eg, vacuuming, dusting, washing dishes, animal care, etc.) and yard work (eg, mowing, raking); and (4) recreational physical activity, including aerobics, basketball, hiking, dancing and running or jogging.2,6 Sedentary activities were included, in addition to the 4 physical activity domains. Participants recorded the code number of their predominant activity, during each 30-minute block of time. For each 30-minute block of physical activity, the participant also provided an intensity level (ie, light, moderate, hard and very hard) at which he or she performed the activity.28 Intensity levels were used to calculate the metabolic equivalent value for each activity.34 To help students accurately report their activity intensity levels, we provided visual (ie, pictures) and written definitions for each of the 4 intensity levels and examples of exercises corresponding to the appropriate level. (Figure 1) For example, the definition for “light intensity” was slow breathing and little or no movement; the definition for “moderate intensity” was normal breathing and some movement. Physical and social contexts, in which physical activity occurred, also were collected, using the Stanford 3-Day Physical Activity Recall. For the physical context (ie, location), participants identified the activity location during each 30-minute block of time. The original response included 5 categories: (1) participant’s or friend’s home or neighborhood; (2) school; (3) community facility (eg, park, playground, recreation center, church, dance studio, field or gym); (4) other outdoor public areas (eg, beach, river, levee, ski area or camping area); and (5) other places (eg, shopping mall, doctor’s office or movie theater). For the social context, participants identified who accompanied them during a 30-minute segment of recreational physical activities. Four response options were: (1) by yourself; (2) with one other person; (3) with several people but not an organized program, class or team; and (4) with an organized program, class or team.28 Particularly, we examined the social context of recreational physical activities with the focus of examining social interaction factors such as conducting recreational physical activities “by yourself,” “unorganized” and “organized,” as suggested by the literature.35 In the Stanford 3-Day Physical Activity Recall, each day was divided into 30-minute blocks from 6 a.m. to midnight. Therefore, each day contained 36 blocks of time. The blocks started from 6 a.m. to 6:30 a.m. and ended with 11:30 p.m. to midnight. In evaluating the temporal factor of the adolescent’s activity, the 36 blocks (from 6 a.m. to midnight; each block contained 30 minutes) were divided into 3 periods: before school (6 a.m. to 8:30 a.m.), during school (8:30 a.m. to 3 p.m.) and after school (3 p.m. to midnight). Physical activity level measured by metabolic equivalent (MET) value. MET values for the re-

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ported intensity level of each activity were obtained from the Compendium of Physical Activities.21 MET values are expressed as multiples of the resting metabolic rate (RMR) or the ratio of the metabolic cost of a given activity divided by the RMR. For example, a MET value of 1 is roughly equal to the RMR (1 kcal (kg hr)-1 for a 70 kg person); a MET value of 3 would indicate a metabolic cost 3 times that of the RMR. The average physical activity level (PAL) per individual for each period of day was expressed as average METs over that specific period of the day, adopting the previous method.34 Objective measure of physical activity duration and data reduction. Physical activity was objectively measured by ActiGraph accelerometers. Initialized monitors were secured on belts to be worn around the waist above the participant’s right hip. Participants were asked to wear it during waking hours for 7 consecutive monitoring days, except at night while sleeping and while bathing or swimming. Activity counts were stored in 30-second time intervals. ActiGraph counts were summarized by quantifying the time (minutes) spent at different intensity levels. To convert the total activity counts into sedentary (< 2 MET, less than 50.99 counts), light (2–3 METs, 51–578.99 counts), moderate (3.0–5.9 METs, 579–2, 599.99 counts), and vigorous intensity activity (> 6.0 METs, greater than 2,600 counts), the accelerometer count cutoffs of previous youth studies36-40 were used. Accelerometer data reduction methods incorporated the procedures common in the literature.41-43 The accelerometer-measured physical activity duration was converted to average time (in minutes) per day spent on sedentary, light, moderate and vigorous activity levels, respectively. Socio-demographic variables and anthropometric assessments. Information on each participant’s self-reported race and ethnicity, sex and grade was obtained from a self-report survey. Trained research team members measured height and weight to the nearest centimeter and 0.1 kg, following standard protocol.44 Each participant’s body mass index (BMI) (kg/m2) was then calculated as weight in kilograms divided by the square of height in meters for age and sex. The definition of overweight among children and adolescents is a statistical definition, based on the 2000 Centers for Disease Control and Prevention growth charts for the United States.45 Overweight is defined as at or above the 95th percentile of BMI. At risk for overweight is defined as at or above the 85th percentile but less than 95th percentile of BMI. Data Analysis Descriptive statistics were calculated initially to describe the participants’ characteristics, and physical activity levels, measured by the accelerometer. Inferential statistics were used to examine associations between physical, social, and temporal contextual factors, and physical activity domains, and to investigate the possible sex differ-

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Table 1 Characteristics of Study Participants and Physical Activity Levels Characteristics (N = 314)

Percentage

Sex

p value a .002*

Girls (N = 185)

58.8

Boys (N = 129)

41.2

Race/ethnicity

.000*

Black

69.1

White, non-Hispanic

16.6

Other

14.3

Grade ( 9 -12 ) th

.000*

th

9

32.6

th

10th

23.4

th

11

13.1

12th

30.9

Body Mass Index (BMI)

.000*

Normal weight

59

Overweight or obese

41

Accelerometer-measured physical activity duration by intensity and sex (Average minutes per day)c

mean (s.d)b

Sedentary Sedentary (Boys vs. Girls)

480.9 (44.2) 481.4 (3.06) vs. 595.3 (5.89)

Light Light (Boys vs. Girls)

101.3 (30.5) 100.5 (2.17) vs. 126.7 (3.82)

Moderate Moderate (Boys vs. Girls)

.000*

46.0 (20.1) 45.9 (1.37) vs. 48.9 (2.08)

Vigorous Vigorous (Boys vs. Girls)

.000*

NSd

2.2 (3.7) 2.4 (0.27) vs. 1.5 (0.23)

NSd

*p < .05 Note. a = One-sample binomial test was used to test the hypothesis of equal distribution for binary variables. Chi-square tests were used to examine the distributions of categorical variables. b = Mean and standard deviation were provided for continuous variables. c = Intensities of physical activity were measured by accelerometer. The number represents the average minutes per day spent on sedentary, light, and moderate activity by sex for the weekday. d = NS: Not significant (p > .05)

ence of the associations. The units of analysis were at the 30-minute block levels and at the individual student’s level. We excluded blocks when participants were sleeping or taking a shower. This analytical strategy has been established elsewhere.35,46 BMI was controlled for as covariate in the individual level analyses, as suggested by the literature.47,48 Frequency distributions of 30-minutes blocks were examined for all domains of physical activity. Multinomial logistic regressions were used to determine if there was a sex difference in the

likelihood of engaging 4 domains of physical activity, using the sedentary activity as a reference category. The associations between the blocks of the day and domains of physical activities were assessed with multinomial logistic regressions. We also conducted analyses at the individual level to investigate how average physical activity level (PAL), estimated by average METs level (per 30 minutes), vary by time of day (eg, before school, and after school) and by sex. Because the same

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Table 2 Frequency of Reported Physical Activity Domains and Social Context of Recreational Physical Activity Activity Domains Activities Total

Total blocks (%)

Male blocks N (%)

Female blocks N (%)

Odds Ratio (Boys vs. Girls), 95% CI

25,772

10,775

14,997

426 (1.7)

171 (1.6)

255 (1.7)

1.014 (.827 - 1.243 )

2770 (10.7)

1093 (10.1)

1677 (11.2)

0.926 (.852 - 1.005)

Occupational- or house chorerelated physical activity

882 (3.4)

300 (2.8)

582 (3.9)

0.738 (.639 - .854)*

Recreational physical activity by yourself, or with one other

236 (0.9)

142 (1.3)

94 (0.6)

2.260 (1.735 - 2.943)*

Recreational physical activity with several people (unorganized)

305 (1.2)

198 (1.8)

107 (0.7)

2.759 (2.175 - 3.501)*

Recreational physical activity with organized program/class

349 (1.4)

206 (1.9)

143 (1.0)

1.911 (1.534-2.381)*

20,804 (80.7)

8665 (80.4)

12,139 (80.9)

1.00

School- related physical activity Active Transportation

Sedentary activities * p < .05

Note. Multinomial logistic regression was used for analyses. For odds ratio, the reference category is sedentary activities. Odds ratio was the odds of boys versus odds of girls.

individual’s data was measured over time, the generalized estimating equation (GEE) model was used for the analysis of correlated data.10,49 Specific contrasts in pairwise fashion were conducted as ad hoc tests. Bonferroni adjustment was used for multiple comparisons. The robust Huber-White Sandwich estimate of variance was adopted.50 As noted, the GEE model has been recommended for longitudinal data analysis.49 It has several advantages over traditional ANOVA with repeated measures.50 GEE produces a robust estimation of standard errors, even when the variance structure is misspecified under mild regularity conditions. Also, it is more flexible when missing data are present.51 Differences in the distribution of 30-minute blocks of 4 domains of physical activities in the physical context of physical activity were tested using chi-square tests for the total sample and for boys and girls, respectively. All analyses were undertaken, using SAS version 9.2 (SAS Institute Inc., Cary, NC). Statistical significance was set at p ≤ .05. RESULTS Characteristics of Participants and Accelerometer-measured Physical Activity Levels This multi-ethnic sample of adolescents (N = 314) was more than half African-American (69.1%,

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p = .001) and female (58.8%, p = .002) with a fairly equal distribution across grades 9, 10 and 12 with the exception of fewer 11th grade participants (p = .001). Approximately 59% of the participants had normal weight, whereas 41% of them were overweight or obese. For the accelerometer-measured physical activity, participants averaged 480.9 minutes per day in sedentary activity, 101.3 minutes in light physical activity, 46 minutes in moderate physical activity and 2.2 minutes in vigorous physical activity. Sex-specific average minutes per day spent on sedentary, light, moderate and vigorous physical activities were reported in Table 1. The average minutes per day spent on sedentary activities were significantly more (p < .001) for girls (Mean = 595.3, sd = 5.89) than for boys (Mean = 481.4, sd=3.06). Similarly, girls also spent more (p < .001) average minutes per day on light-level activities (Mean=126.7, sd= 3.82) than boys (Mean = 100.5, sd = 2.17). Descriptive statistics are reported in Table 1. Summary of 30-minute Blocks for Physical Activity Domain and Contexts In this study, each day contained 36 blocks of time. The blocks started from 6 a.m. to 6:30 a.m. and ended with 11:30 p.m. to midnight. Given that an individual has a total of 36 30-minute blocks per day, a participant could have 108 blocks for 3-day measurement time (36 blocks per day x 3

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Table 3 Frequency of Reported Physical Activities and Sedentary Activities by Blocks of the Day Activity Domains Activities Total School-related physical activity Active transportation

Total blocks (%)

Beforeschool blocks N (%)

Afterschool blocks N (%)

Duringschool blocks N (%)

Odds Ratio (Before-school vs. During-school), 95% CI

Odds Ratio (After-school vs. During-school), 95% CI

25,772

3613

12,794

9365

426 (1.7)

19 (0.5)

175 (1.4)

232 (2.5)

0.192 (.112 -.330)*

0.61 (.495-.751)*

2770 (10.7)

808 (22.4)

1605 (12.5)

357 (3.8)

6.70 (5.86-7.65)**

3.86 (3.43-4.35)*

Occupational- or house chore-related physical activity

882 (3.4)

10 (0.3)

746 (5.8)

126 (1.3)

0.242 (.122-.477)*

5.66 (4.64-6.91)**

Recreational physical activity by yourself, or with one other

236 (0.9)

3 (0.1)

198 (1.5)

35 (0.4)

0.278 (.085-.907)*

5.34 (3.688-7.726)**

Recreational physical activity with several people (unorganized)

305 (1.2)

1 (0.2)

245 (1.9)

59 (0.6)

0.052 (.007-.374)*

3.68 (2.765-4.899)*

Recreational physical activity with organized program/class

349 (1.4)

7 (0.2)

275 (2.1)

67 (0.7)

0.32 (.147-.697)*

3.40 (2.59-4.45)*

20,804 (80.7)

2765 (76.5)

9550 (74.6)

8489 (90.6)

1.00

1.00

Sedentary activities * p < .05, ** p < .01

Note. Multinomial logistic regression was used for analyses. For odds ratio, the reference category is sedentary activities. Odds ratio was the odds of after-school blocks versus odds of during-school blocks.

days = 108 blocks). If a participant is not missing a block, a maximum number of blocks should be 19,980 blocks for girls (N = 185 (people) x 108 (max per person) ) and 13,824 blocks for boys (N = 129 (people) x108 (max per person)). For the current study, a total of 10,755 30-minute blocks from boys (77.8% valid blocks) and 14,997 30-minute blocks from girls (75% valid blocks) were included in the analyses.

themselves or with one other (OR = 2.26; 95% CI = 1.735-2.943) in unorganized, recreational physical activities (OR = 2.759, 95% CI = 2.175-3.501) and organized physical activities (OR = 1.911, 95% CI = 1.534-2.381) in contrast to girls. However, boys were less likely to engage in occupational- or house chore-related physical activities (OR = 0.738, 95% CI = .639-.854) than girls.

Physical Activity Domains and Gender Differences in the Likelihood of Engaging Different Physical Activity Domains Table 2 presents the frequency distribution of 30-minute blocks in physical activity domains and the results of the multinomial logistic regression that was used to determine sex differences in the likelihood of engaging in the various domains of physical activity. Specifically, recreational physical activities were examined under great detail in social contexts. In general, participants reported spending 80.7% of their 30-minute block time on sedentary activities. Time spent on active transportation had the largest proportion (10.7%) of all physical activity domains, followed by occupational- or house chore-related physical activity (3.4%). When comparing the sex differences in engaging physical activity domains, boys were more likely to engage in recreational physical activities by

Temporal Context of Physical Activity Domains Table 3 displays the association between the blocks of day and different physical activity domains, using sedentary activity as a reference group. The multinomial logistic regression results showed that the after-school blocks were associated with increased physical activity domains such as active transportation, occupational- or house chore-related physical activity and recreational physical activities. The before-school blocks were only associated with increased active transportation. Results indicated that only self-reported active transportation was associated with beforeschool (OR = 6.70, 95% CI = 5.86-7.65) and afterschool (OR = 3.86, 95% CI = 3.43-4.35) blocks. School-related physical activity was negatively associated with before-school (OR = .192, 95% CI = .112-.330) and after-school (OR = .61, 95% CI = .495-.751) blocks.

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A Social Ecological Assessment of Physical Activity among Urban Adolescents

Figure 2 Average Physical Activity Level (PAL), Estimated by Average Metabolic Equivalent (METs 30min block-1) (N = 291)

P=.018*

NS

P=.035*

Note. NS: Not significant (p > .05)

Gender Difference in the Association between Temporal Context and Average Physical Activity Level Measured by MET Values Figure 2 illustrates the association of average physical activity level and the different blocks of day, as well as how the association varied by sex. There was a significant interaction between sex and the time of the day on the average physical activity level (Wald Chi-Square (2) = 9.351, p = .009). This indicates that sex-related physical activity levels differed across the times of the day. Specifically, the average physical activity level was similar for boys (Mean = 1.21, sd = 0.046) and girls (Mean = 1.16, sd = 0.029) before school (p > .05), whereas the average physical activity level was significantly lower for girls (M = 1.48, sd = 0.037) than for boys (Mean =1.72, sd = 0.065), after school (p = .018).

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Similarly, girls had a significantly lower level (p = .035) of average physical activity (Mean = 1.10, sd = 0.027) than boys (Mean = 1.31, sd = 0.062) during school. Physical Context of Physical Activity Domains The physical context of physical activity domains (excluding sedentary activity) is shown in Table 4. There were significant differences in the distribution of 30-minute blocks of the 4 domains of physical activity in the physical context of physical activity (p < .001) for the entire sample and for both sexes. In general, time spent on active transportation equaled more than half of the total block time spent on physical activity (56.1% for whole sample). The second largest proportions of block time were spent on occupational- or house chore-relat-

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Table 4 Frequency of Physical Context of Reported Physical Activity Domains by Sex Physical Activity Location School

Community facility

Other outdoor public area

Other (mall, doctor’s office, movie)

N (%)

N (%)

N (%)

N (%)

N (%)

4919

1762 (35.8)

1437 (29.2)

310 (6.2)

229 (4.6)

1181 (23.8)

410 (8.3)

11 (2.7)

339 (82.7)

37 (9.0)

0 (0)

23 (5.6)

Active Transportation

2759 (56.1)

1194 (43.3)

751 (27.1)

102 (3.7)

149 (5.4)

563 (20.4)

Occupational- or house chore-related physical activity

870 (17.7)

275 (31.6)

22 (2.5)

19 (2.2)

18 (2.1)

536 (61.6)

Recreational physical activity by yourself or with one other

226 (4.6)

165 (73.0)

14 (6.2)

40 (17.7)

2 (0.9)

5 (2.2)

Recreational physical activity with several people (unorganized)

305 (6.2)

101 (33.1)

81 (26.6)

84 (27.5)

17 (5.6)

22 (7.2)

Recreational physical activity with organized program/class

349 (7.1)

16 (4.6)

230 (65.9)

28 (8.0)

43 (12.3)

32 (9.2)

2820

1009 (35.8)

825 (29.3)

145 (5.1)

79 (2.8)

762 (27.0)

243 (8.6)

7 (2.9)

199 (81.9)

24 (9.9)

0

13 (5.3)

Active transportation

1666 (58.8)

735 (44.1)

469 (28.2)

67 (4.0)

52 (3.1)

343 (20.6)

Occupational- or house chore-related physical activity

571 (20.2)

158 (27.7)

9 (1.6)

2 (0.4)

18 (3.2)

384 (67.3)

Recreational physical activity by yourself, or with one other

90 (3.2)

51 (56.7)

9 (10)

23 (25.6)

2 (2.2)

5 (5.6)

Recreational physical activity with several people (unorganized)

107 (3.8)

50 (46.7)

41 (38.3)

11 (10.3)

0

5 (4.7)

Recreational physical activity with organized program/class

143 (5.1)

8 (5.6)

98 (68.5)

18 (12.6)

7 (4.9)

12 (8.4)

2099

753 (35.9)

612 (29.2)

165 (7.9)

150 (7.1)

419 (20.0)

167 (8.0)

4 (2.4)/0.5

140 (83.8)/22.9

13 (7.8)/7.9

0

10 (6.0)/2.4

Active transportation

1093 (52.1)

459 (42.0)/61.0

282 (25.8)/46.1

35 (3.2)/21.2

97 (8.9)/64.7

220 (20.1)/52.5

Occupational- or house chore-related physical activity

299 (14.2)

117 (39.1)/15.5

13 (4.3)/2.1

17 (5.7)/10.3

0/0

152 (50.8)/36.3

Recreational physical activity by yourself, or with one other

136 (6.5)

114 (83.8)

5 (3.7)

17 (12.5)

0

0

Recreational physical activity with several people (unorganized)

198 (9.4)

51 (25.8)

40 (20.2)

73 (36.9)

17 (8.6)

17 (8.6)

Recreational physical activity with organized program/class

206 (9.8)

8 (3.9)

132 (64.1)

10 (4.9)

36 (17.5)

20 (9.7)

Home/ neighborhood Total blocks (%)

Total sample (p < .001) School-related physical activity

Activity Types a

Girls (p < .001) School-related physical activity

Boys (p 1.6 METs 24h-1 is necessary to prevent meaningful weight gain through middle age.34 An average daily PAL of 1.75 or more has been recommended as necessary to prevent obesity during the lifespan.65 Unfortunately, none of the high school adolescents in the study sample achieved the average PAL of 1.75 or more during the weekday. The results indicated that interventions are needed to increase the physical activity levels. This is particularly true in regard to the moderate-to-vigorous intensity physical activity of high school students. The after-school period may be a critical moment to introduce programming. A major strength of this study was its success in providing a comprehensive profile of active living that covers all domains of physical activity. “Active living”20 integrates physical activity into daily routines and the focus has been broadened from leisure time to include physical activity for transportation and other purposes that have been discussed in this study. Integrating all physical activity domains into daily routines offers new insight into the contextual profiling of specific physical activities, above and beyond the traditional physical activity studies that heavily focused on physical education. Due to a variety of reasons, studies using either diary or ecological momentary assessment methods only have provided a fragment of a regular weekday. This study provides an objective assessment of physical activity for a complete 5-weekday profile, which has been suggested by the literature.66 These findings should be interpreted in light of the following limitations. First, one cannot assess a causal relationship due to the cross-sectional nature of the data. Second, the 3DPAR is a self-report instrument. Thus, it may be subject to recall and

social-desirability bias. However, a study showed children as young as 5 can reliably and validly self-report their health-related quality of life with an age-appropriate instrument.67 For our sample of high school students, self-reported physical activity questionnaires are practical, convenient and affordable. Lastly, one has to be aware that the findings generated from this predominately African-American, inner-city, urban sample cannot be generalized to the larger African-American adolescent population. One of the Healthy People 2020 objectives for children and adolescents is to increase the proportion of trips of one mile or less made by walking to school. In addition, the other goals are to increase the proportion of the trips of 2 miles or less made to school by cycling.19 This study provides support for promoting opportunities for active commuting or encouraging “work and chores” among urban, high school students. The significant sex differences in physical activity levels during the “afterschool” period suggest that this could be a particularly important period to target for interventions and policy change. Given the fact that high school students in our study ranked “at home, or in the neighborhood,” and “in school,” as the top 2 most common locations for physical activity outside of school time, our findings indicated that several school-based practices can be adopted to encourage students to enjoy physical activity. First of all, physical environment changes are often necessary to improve the safety and convenience of walking and cycling routes. The state-level Safe Route to School legislation can provide competitive funds for construction projects such as sidewalks, traffic lights, pedestrian crossing improvements and bicycle paths.56,68 Active commuting reduces the number of cars and decreases traffic near schools.69 It also promotes partnerships among students, parents and community organizations and members,70 and therefore, should be encouraged. This study also suggests that communities, neighborhoods and schools should work together to share physical activity resources. We call for future studies to examine what types of policies or practices would successfully allow schools: (1) to open school facilities, which will provide physical activity programs; and (2) to share playgrounds and fitness facilities with students, families, school staff and community members in after-school venues.

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Statement of Human Subjects The study was approved by the Institutional Review Board at the University of Maryland. Conflict of Interest Statement The authors declare no conflict of interest of this study. Acknowledgments This study was supported by a research grant

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A Social Ecological Assessment of Physical Activity among Urban Adolescents from the Robert Wood Johnson Foundation’s Active Living Research Program. We also would like to thank Carrie M. O’Connor, MA, for editorial assistance. REFERENCES

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