Research Study Abstract

A Preliminary Investigation of Residential Self-Selection in Smart Growth Versus Urban Sprawl

  • Added on June 14, 2012

Background Determining the relation of built environment characteristics to physical activity and obesity remains an ongoing public health concern. Recent literature suggests that environment characteristics of smart growth planning (e.g., walkability, preservation of open space) may promote physical activity. However, the majority of studies examining associations between these environmental features and activity levels utilize cross-sectional research designs, which are not able to rule out neighborhood self-selection (i.e., individuals with higher levels of physical activity move to activity-friendly neighborhoods, which allow them to continue their higher activity levels). Reverse causation – physical activity levels influence neighborhood choice instead of neighborhood built environmental characteristics influencing physical activity – is a widespread concern in active living studies. Thus, understanding whether neighborhood self-selection is at play in natural experiments, such as the evaluation of the effects of new smart growth communities on physical activity and obesity, is a research priority. To date, information is lacking about the reasons why individuals choose to move into smart growth communities and whether these reasons for moving are associated with initial physical activity levels and Body Mass Index (BMI).

Objectives The present study sought to (1) determine whether reasons for moving to a smart growth community differ from reasons for moving to urban sprawl control communities and (2) investigate how reasons for moving relate to baseline physical activity levels and BMI among adults who have recently moved to a smart growth community.

Methods This research uses baseline data from a subsample of adults (N = 79) participating in a quasi-experimental evaluation study of the impact of a smart growth community on physical activity and obesity. Of these individuals, 46 had recently (within 3-19 months) moved into a smart growth community and 33 lived in urban sprawl control communities (median time in residence = 102 months). Physical activity was measured using Actigraph G T2M (30-sec. epochs). Data collected from the accelerometers were classified as moderate-to-vigorous physical activity (MVPA) according to established thresholds. Participants were also asked to complete a self-report paper survey that contains the Reasons for Moving Survey and have their height and weight measured. The Reasons for Moving Survey included 11 items assessing reasons for moving to one’s neighborhood (e.g., affordability/value, sense of community) and utilized a 5-point Likert-type response format ranging from 1 “not at all important” to 5 “very important.” Three items from the Reasons for Moving Scale (i.e., desire for nearby shops and services, ease of walking, closeness to recreational facilities) were combined into a walkability subscale (Sallis, et al., 2009). Independent sample tests were used to compare each individual question on the Reasons for Moving Survey to adults who had recently moved to a smart growth community and to adults living in control communities and to compare scores for individual items and the walkability subscale between adults residing in both the smart growth community and control communities. Pearson correlation tests were used to examine the correlation of each individual question on the Reasons for Moving Survey and the walkability subscale with average MVPA minutes and BMI. Results Participants’ age ranged from 27 to 73 years, 78.5% of the participants’ were females and 45.6% were White/Caucasian. Participants’ mean BMI was 28.25 (SD = 7.34). Independent sample tests indicated that the importance of affordability/value as a reason for moving differed significantly between the smart growth (M = 4.28, SD = 1.00) and the control group (M = 4.76, SD = 0.502), t (69.90) = -2.76, p < 0.01. None of the other reasons for moving differed significantly between the two groups. For the smart growth group, Pearson correlation tests indicated that the importance of nearby shops and services was positively associated with MVPA (r = 0.299, p = 0.048), the quality of schools was marginally positively associated with MVPA (r = 0.271, p = 0.075), and MVPA was positively but not significantly related to the walkability subscale (r = 0.235, p = 0.129). BMI was also determined to be marginally related to the importance of closeness to open space (r = -0.249, p = 0.095) in the smart growth group.

Conclusions These preliminary results suggest that residential self-selection may exist in the smart growth group. Individuals who were more physically active or had a lower BMI after recently moving to a smart growth community indicated that having nearby shops and services, open space, and walkability were important reasons for moving. These findings imply that residential self-selection may play a role in natural experiments that examine the effects of the built environment on physical activity and obesity. Future research should seek to replicate these findings in a larger sample and utilize longitudinal data to determine if residential self-selection plays a role in subsequent MVPA and BMI change among individuals living in smart growth communities.

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