Pediatric Weight Management

Child Nutrition and Environment


Evenson KR, Scott MM, Cohen DA, Voorhees CC. Girls Perception of Neighborhood Factors on Physical Activity, Sedentary Behavior and Body Mass Index. Obesity, 2007 (Feb); 15 (2): 430-445.

PubMed ID: 17299117
Study Design:
Cross-Sectional Study
D - Click here for explanation of classification scheme.
Quality Rating:
Positive POSITIVE: See Quality Criteria Checklist below.
Research Purpose:

This cross-sectional study examined the association of neighborhood factors (specifically neighborhood safety, neighborhood esthetics and access to physical activity facilities near home) and physical activity, sedentary behavior (both after school and on weekends) and body mass index among sixth-grade girls.

Inclusion Criteria:
  • Participants were girls in sixth grade who were participating in the Trial of Activity in Adolescent Girls (TAAG)
  • Parents or guardians of the participants provided written informed consent; the girls participating also provided written assent
  • Participants needed to be able to read and understand English and have no exercise or other medical contraindication.
Exclusion Criteria:
  • Participants were excluded if they did not have parental or guardian consent or their own assent, were unable to read and understand English, were told by a doctor not to exercise or had another medical contraindication
  • Participants' data were not included in analyses if there were incomplete accelerometer data, incomplete questionnaires and if home addresses could not be geocoded.
Description of Study Protocol:


  • Girls in the sixth grade attending schools participating in the Trial of Activity in Adolescent Girls (TAAG) were recruited
  • The 36 schools involved were located in Arizona, California, Louisiana, Maryland, Minnesota and South Carolina.


Cross-sectional study.

  • Participants wore accelerometers for six days, removing them only for sleeping, bathing and swimming. To see the effect of neighborhood factors on non-school activity, data from accelerometers were only used after school hours (2:00 p.m. to 12:00 a.m.) and on weekends.
  • Participants also completed a self-administered questionnaire of neighborhood factors at school
    • Using a five-point scale, ranging from "disagree a lot" to "agree a lot," the 10 items in the questionnaire measured perceived safety, esthetics and access to facilities near home
    • Participants were also asked "Is it easy to get to and from this place from home or school?" and answered "yes" or "no" to a list of 14 facilities, such as a recreation center, swimming pool or hiking trail.

Statistical Analysis

  • Analyses were conducted using the mixed procedure in SAS version 9.1
    • The data are hierarchical, where the girls (Level One) are nested within schools and schools (Level Two) are nested within study sites
    • School and site were treated as random effects in a hierarchical linear model to determine if neighborhood factors were associated with outcomes
    • Level One fixed-effect covariates included: The race or ethnicity of participants, defined with indicator variables; each girl's neighborhood socio-economic index; body mass index for the physical activity outcomes or non-school metabolic equivalent weighted moderate-to-vigorous physical activity for models with body mass index as the outcome
    • The percentage of students at each school on free or reduced-price lunch was included as a school Level Two fixed-effect
    • Because body mass index and non-school metabolic equivalent weighted moderate-to-vigorous physical activity might be causal, all models were re-examined without non-school metabolic equivalent weighted moderate-to-vigorous physical activity or body mass index as a girl-level fixed-effect covariate.
  • Odds ratios using multi-level logistic models using SAS GLIMMIX function were also calculated with two outcomes: Overweight and at risk of becoming overweight
  • Neighborhood variables with significance of at least P<0.10 were selected and checked for collinearity among variables and each outcome. The neighborhood variables were dropped one-by-one until only significant neighborhood variables (P<0.10) remained in a final model.
  • Adjustment for multiple tests was not performed, as the normality assumption appeared valid based on examination of the RxP plots for all models presented.
Data Collection Summary:

Timing of Measurements

  • Data were collected at baseline of the Trial of Activity in Adolescent Girls (TAAG) in Fall 2003
  • Participants were given accelerometers and instructions by TAAG staff members on how and when to wear accelerometers over a six-day period
  • Trained TAAG staff members collected participants' height and weight data: Height and weight were each measured twice and the average of the two measures was calculated
  • Participants also completed a self-administered questionnaire on neighborhood factors, administered at school and supervised by data collectors.

Dependent Variables

  • Non-school metabolic equivalent weighted moderate-to-vigorous physical activity, measured using an accelerometer 
  • Non-school sedentary behavior, measured using an accelerometer
  • Body mass index.

Independent Variables

Neighborhood factors

  • Safe to walk or jog in neighborhood
  • See walkers or bicyclists from homes on street
  • Traffic
  • Crime
  • Other children playing outdoors
  • Lighting
  • Many interesting things to look at while walking in neighborhood
  • Many places to go within easy walking distance of home
  • Sidewalks on most streets
  • Bicycling or walking trails in neighborhood.

Facilities in neighborhood

  • Park
  • Playing field
  • Swimming pool
  • Walking, biking or hiking path or trail
  • Basketball court
  • Tennis court
  • Track
  • Skating rink (ice, roller or inline)
  • Recreation center
  • Beach or lake
  • Dance or gymnastics club
  • Golf course
  • Health club
  • Martial arts studio.

Control Variables

  • Participants' race or ethnicity were self-reported and their date of birth was given on the parental consent form
  • To control for affect of income, a neighborhood socio-economic index was created using neighborhood-level US census data.
Description of Actual Data Sample:
  • Initial N: 60 eligible sixth grade girls per school from 36 schools were invited to participate, for a total of 2,160 eligible girls
  • Attrition (final N): 1,554 girls provided parental consent and student assent, complete accelerometer data, home addresses that could be geocoded and a completed questionnaire
  • Age: The average age was 11.8 years old
  • Ethnicity: Of the 1,554 girls in the study
    • Asian, Pacific Islander or Native Hawaiian: 3.9%
    • Black: 21.0%
    • Native American: 0.7%
    • Multi-racial: 7.2%
    • Hispanic: 22.0%
    • White: 45.2%
    • Missing: 0.1%.
  • Other relevant demographics: The average percentage of students on free or reduced-price lunch was 36.9%
  • Anthropometrics
    • The average body mass index was 20.9kg/m2
    • 34.5% (N=547) of girls were at risk of being overweight (at least the 85th percentile) and 16.9% (N=268) were overweight (at least the 95th percentile).
  • Location: The 36 schools attended by participating girls were in Tucson, Arizona; San Diego, California; New Orleans, Louisiana; Baltimore, Maryland; Minneapolis, Minnesota; Columbia, South Carolina.
Summary of Results:

Key Findings

  • Perceptions that crime was not a problem were associated with lower levels of non-school metabolically-weighted moderate to vigorous physical activity
  • Perceptions that traffic is not a problem were associated with lower body mass index
  • Agreeing that other kids were seen playing outside was associated with lower body mass index and lower odds of being at risk for overweight
  • Aesthetics of the neighborhood (having interesting things to look at) was not associated with any outcome of the study
  • No neighborhood factor studied was associated with non-school sedentary behavior. However, agreeing that there were many places within easy walking distance of home approached significance for less sedentary behavior.
  • Agreeing that their neighborhood had sidewalks on most streets was associated with an average of 28.9 more minutes of non-school metabolically-weighted moderate-to-vigorous physical activity per six days
  • Agreeing that their neighborhood had trails was associated with an average of 45.8 more minutes of non-school metabolically-weighted moderate-to-vigorous physical activity per six days
  • Reporting bicycle or walking trails in the neighborhood was inversely associated with body mass index.


Mean Difference in Non-School Metabolically Weighted Moderate to Vigorous Physical Activity Difference in Non-School Sedentary Behavior Mean Difference in Body Mass Index


P-value Minutes


kg/m2 P-value

Agree that it is safe to walk or jog in my neighborhood

Disagree that there is a lot of crime in my neighborhood





Agree that my neighborhood streets are well lit at night




Disagree that there is so much traffic that it makes it hard to walk in my neighborhood
Agree that I often see other girls or boys playing outdoors in my neighborhood
Agree that there are sidewalks on most of the streets in my neighborhood
Agree that there are bicycle or walking trails in my neighborhood
Access to facilities sum score

Quartile 2 (5-6)






Quartile 3 (7-8)
Quartile 4 (9-14)

Author Conclusion:
  • Higher levels of non-school metabolically-weighted moderate-to-vigorous physical activity was associated with having more destinations for physical activity, reporting trails, sidewalks and well-lit streets in the neighborhood, and perceiving the neighborhood as being safe to walk
  • Having places to go for physical activity was most strongly associated with non-school metabolically-weighted moderate-to-vigorous physical activity
  • Lower body mass index was associated with having more destinations for physical activity and being able to see other children play outside
  • None of the factors explored were associated with non-school sedentary behavior. Further research is needed to understand why. Additional studies of this type for different age groups and geographies could be useful and longitudinal studies are needed to study the temporality of the measures and what might influence perceptions about neighborhoods.
Funding Source:
Government: NIH/NHLBI
Reviewer Comments:
  • The authors reviewed many limitations to this study
  • Confounders could exist that were not accounted for: No adjustment was made for multiple testing, significance should be interpreted with caution and replication of results is needed and physical activity facilities were measured for their proximity and not cost, safety, age-appropriateness and the like
  • The authors also report that some of the self-reported items under study showed only moderate reliability from pilot work and the safety scale showed only moderate internal consistency
  • Another limitation is the design of the study: As this was a cross-sectional study, the direction of the relationships is not known.
Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) Yes
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) Yes
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? Yes
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? Yes
3. Were study groups comparable? Yes
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) Yes
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? Yes
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) N/A
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? Yes
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) Yes
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? Yes
  4.1. Were follow-up methods described and the same for all groups? Yes
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? Yes
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? No
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) N/A
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? No
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? Yes
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? N/A
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? Yes
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? Yes
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? Yes
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? N/A
  6.6. Were extra or unplanned treatments described? N/A
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? Yes
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? Yes
  7.1. Were primary and secondary endpoints described and relevant to the question? Yes
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? Yes
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? ???
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? N/A
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? Yes
10. Is bias due to study's funding or sponsorship unlikely? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes