Neighborhood environment profiles related to physical activity and weight status: a latent profile analysis.

BACKGROUND Neighborhood built environments (BE) include combinations of co-existing stimuli influencing physical activity (PA). Dealing with numerous environmental variables and complexity presents a significant challenge. The current analysis explored whether a range of reported BE features associated with adults' physical activity produced distinct multivariate patterns, and tested whether adults' PA and body mass differed by BE profiles. METHODS Participants (20-65 years, 48.2% female, 26% ethnic minority) were recruited between 2002 and 2005 from 32 neighborhoods from Seattle-King County, WA (N=1287) and Baltimore, MD-Washington, DC regions (N=912). Independent Latent Profile Analyses were conducted in each region with 11 environmental variables from the Neighborhood Environment Walkability Scale. Validity of the neighborhood profiles was examined by their relationship to PA (accelerometer-derived moderate-to-vigorous minutes/day, self-reported minutes/week of walking for transportation and leisure) and self-reported BMI using ANCOVA models. RESULTS Neighborhood profiles for Seattle and Baltimore regions were visually similar, suggesting generalizability. High-walkable recreationally-dense neighborhoods differed significantly from other neighborhood types by as much as 13 MVPA minutes/day, almost 60 minutes/week of walking for transportation, and 75 min/week of leisure-time activity. Neighborhood profiles also differed significantly for BMI. DISCUSSION These findings could help identify optimal patterns of environmental attributes that facilitate physical activity and improve weight status.

[1]  Aaron Kofner,et al.  The effect of light rail transit on body mass index and physical activity. , 2010, American journal of preventive medicine.

[2]  Lawrence D Frank,et al.  Validation of the Neighborhood Environment Walkability Scale (NEWS) items using geographic information systems. , 2009, Journal of physical activity & health.

[3]  Stephanie T. Lanza,et al.  Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences , 2009 .

[4]  James F Sallis,et al.  Measuring the environment for friendliness toward physical activity: a comparison of the reliability of 3 questionnaires. , 2004, American journal of public health.

[5]  J. Sallis,et al.  Ecological models of health behavior. , 2008 .

[6]  G. Welk,et al.  Reliability of accelerometry-based activity monitors: a generalizability study. , 2004, Medicine and science in sports and exercise.

[7]  R. Crosby,et al.  Emerging theories in health promotion practice and research , 2002 .

[8]  K. Glanz,et al.  Health behavior and health education : theory, research, and practice , 1991 .

[9]  Michael Duncan,et al.  Walking, bicycling, and urban landscapes: evidence from the San Francisco Bay Area. , 2003, American journal of public health.

[10]  K. Clifton,et al.  Erratum to ““Do you see what I see?” – Correlates of multidimensional measures of neighborhood types and perceived physical activity–related neighborhood barriers and facilitators for urban youth” [Preventive Medicine 50 (2010) S18-S23] , 2010 .

[11]  J. Sallis,et al.  The development of a walkability index: application to the Neighborhood Quality of Life Study , 2009, British Journal of Sports Medicine.

[12]  J. Sallis,et al.  Neighborhood Environment Walkability Scale: validity and development of a short form. , 2006, Medicine and science in sports and exercise.

[13]  Jacqueline Kerr,et al.  Neighborhood Environment Walkability Scale for Youth (NEWS-Y): reliability and relationship with physical activity. , 2009, Preventive medicine.

[14]  B. Ainsworth,et al.  International physical activity questionnaire: 12-country reliability and validity. , 2003, Medicine and science in sports and exercise.

[15]  Adrian Bauman,et al.  Correlates of Non-Concordance between Perceived and Objective Measures of Walkability , 2009, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[16]  Lawrence D Frank,et al.  A latent profile analysis of neighborhood recreation environments in relation to adolescent physical activity, sedentary time, and obesity. , 2010, Journal of public health management and practice : JPHMP.

[17]  A. Kaczynski,et al.  Parks and recreation settings and active living: a review of associations with physical activity function and intensity. , 2008, Journal of physical activity & health.

[18]  Gregory J. Welk,et al.  Physical Activity Assessments for Health-Related Research , 2002 .

[19]  Kelly Clifton,et al.  "Do you see what I see?" - correlates of multidimensional measures of neighborhood types and perceived physical activity-related neighborhood barriers and facilitators for urban youth. , 2010, Preventive medicine.

[20]  J. Sallis,et al.  International Journal of Behavioral Nutrition and Physical Activity Cross-validation of the Factorial Structure of the Neighborhood Environment Walkability Scale (news) and Its Abbreviated Form (news-a) , 2022 .

[21]  Penny Gordon-Larsen,et al.  Built and social environments associations with adolescent overweight and activity. , 2006, American journal of preventive medicine.

[22]  J. Sallis,et al.  Neighborhood-based differences in physical activity: an environment scale evaluation. , 2003, American journal of public health.

[23]  Jeffrey Kenworthy,et al.  Urban Design to Reduce Automobile Dependence , 2006 .

[24]  Rocío Rivadeneyra,et al.  Do You See What I See? , 2006 .

[25]  J. Sallis,et al.  Neighborhood built environment and income: examining multiple health outcomes. , 2009, Social science & medicine.

[26]  P S Freedson,et al.  Calibration of the Computer Science and Applications, Inc. accelerometer. , 1998, Medicine and science in sports and exercise.

[27]  K. Neckerman,et al.  Built environments and obesity in disadvantaged populations. , 2009, Epidemiologic reviews.

[28]  Lilah M. Besser,et al.  Walking to public transit: steps to help meet physical activity recommendations. , 2005, American journal of preventive medicine.