Elsevier

Health & Place

Volume 21, May 2013, Pages 148-155
Health & Place

Neighbourhood walkability and physical activity among family members of people with heart disease who participated in a randomized controlled trial of a behavioural risk reduction intervention

https://doi.org/10.1016/j.healthplace.2013.01.010Get rights and content

Abstract

This study adds to the current literature investigating the relationship between individuals' physical activity (PA) and the built environment. Self-reported PA from a prospective behavioural risk reduction intervention was explored in the context of objectively measured Walk Score® and neighbourhood walkability in Ottawa, Canada. Participants in the intervention arm had significantly higher odds of meeting PA guidelines at 12-weeks compared to the standard care control group. This was not influenced by Walk Score® or walkability. This individual-level intervention was effective in assisting participants to overcome potential structural barriers presented by their neighbourhood to meet PA guidelines at 12-weeks.

Highlights

► Physical activity from a prospective behavioural intervention was explored. ► We calculated Walk Score® and neighbourhood walkability for each participant. ► Interactions between intervention and neighbourhood characteristics were examined. ► Participants in the intervention group reported significantly more physical activity.

Introduction

The benefits of physical activity (PA) are extensive and well documented (Bauman, 2004), including decreased morbidity and mortality associated with numerous chronic diseases (Blair et al., 1996, Meyerhardt et al., 2006, Smith et al., 2007, Heitmann et al., 2009), greater longevity (Leitzmann et al., 2007, Hakim et al., 1998) and improved functioning in old age (Van Gelder et al., 2004, Vogel et al., 2009, Seguin and Nelson, 2003). Despite these benefits, physical inactivity continues to present a serious challenge for public health. In 2005, almost half (48%) of Canadians were considered inactive (equivalent to less than 30 min of walking per day) in their leisure time (Gilmour, 2007).

Physical inactivity is an independent risk factor for the development of coronary heart disease (CHD) (Paffenbarger et al., 1978, Manson et al., 1999, Rodriguez et al., 1994, Kannel and Sorlie, 1979, Leon and Connett, 1991). Family history is another risk factor: first-degree relatives of those with CHD have a 1.5- to two-fold increase in risk (Sivapalaratnam et al., 2010, Yarnell et al., 2003, Nasir et al., 2007, Andresdottir et al., 2002, Hopkins et al., 1988). Family members of people with CHD may be a key group to target with interventions to increase PA since they carry an excessive burden of CHD risk associated with both a positive family history and physical inactivity. Even in the presence of a family history of CHD, participation in at least moderate-level PA can significantly decrease the odds of developing CHD compared to remaining sedentary (Chen and Millar, 2001).

Interventions to increase PA are essential components of health promotion strategies. A Cochrane systematic review of randomized controlled trials of interventions to encourage PA among sedentary individuals with a minimum of six months of follow-up found that the evidence supports a positive, moderate sized effect on increasing self-reported PA (Foster et al., 2005). This suggests that PA is amenable to improvements with appropriate intervention.

It is important to understand PA behaviour change in terms of a social ecological perspective, which permits the exploration of PA in the context of personal, behaviour-specific, socio-environmental and physical environmental factors (Giles-Corti et al., 2005). Social ecological theory considers the various levels of influence on health behaviours, including individual, interpersonal, organizational, community and public policy factors that facilitate or impede behaviour change (Sallis and Owen, 2002). PA interventions need to be examined from a social ecological perspective to gain a better understanding of the broader context in which PA behaviour change is achieved.

A substantial body of research has examined the attributes of the built environment that are conducive to PA; several reviews have demonstrated the relationship between neighbourhood characteristics and PA outcomes (Mccormack and Shiell, 2011, Saelens et al., 2003, Wendel-Vos et al., 2007, Saelens and Handy, 2008). Higher density, greater connectivity, greater land use mix, accessibility of recreational facilities and local destinations, safety and visual quality are associated with greater self-reported walking and cycling (Saelens et al., 2003). Similarly, land use mix, connectivity, population density and overall neighbourhood design are significant determinants of PA (Mccormack and Shiell, 2011). Social support, connectivity of trails, and availability of recreation facilities have also demonstrated associations with PA (Wendel-Vos et al., 2007). Density, distance to non-residential destinations and land use mix were positively associated with walking for transport, but findings for route/network connectivity, parks and open space, and personal safety were less consistent (Saelens and Handy, 2008). These reviews highlight some of the important characteristics of neighbourhoods that are associated with PA; however, the majority of the existing research is largely based on cross-sectional or longitudinal research. An examination of how neighbourhood characteristics influence PA outcomes in the context of an individual-level behavioural risk reduction intervention is warranted.

Walkability is a commonly measured characteristic in studies examining neighbourhood influences on health outcomes (Berry et al., 2010, De Greef et al.,, Frank et al., 2008, Frank et al., 2010, Frank et al., 2005, Hoehner et al., 2011, Sundquist et al., 2011, Van Dyck et al., 2011, Van Dyck et al., 2010a, Van Dyck et al., 2010b). In general, walkability indices incorporate measures of several neighbourhood characteristics (e.g. land use mix, residential density, etc.) into one scale and use geospatial mapping techniques to link walkability to individual areas (e.g. the area surrounding an individual's home address). One of the most commonly used walkability indices is that proposed by Frank and colleagues (2010), which incorporates measures of intersection density, residential density, retail floor area ratio and land use mix (Frank et al., 2010). A simpler, readily available, cost-free approach for measuring neighbourhood walkability is Walk Score (available at walkscore.com), which uses data from multiple sources to estimate the walkability of the local area based on distance to amenities (e.g. grocery stores, restaurants, parks, libraries, fitness centres, retail establishments) and two pedestrian-friendly metrics, intersection density and average block length (Walk Score Advisory Group, 2011). Walk Score has recently been validated as a neighbourhood measurement tool (Carr et al., 2010, Carr et al., 2011, Duncan et al., 2011); however, it has not been applied in the context of a PA behaviour change intervention.

Few studies have examined whether or not the neighbourhood environment influences the effectiveness of interventions to increase PA. The purpose of the current study was to (1) create a walkability index using an existing built environment dataset from the Ottawa Neighbourhood Study (ONS), (2) compare walkability to Walk Score®, and (3) to link both walkability and Walk Score® to PA outcomes from the Family Heart Health: Randomized Controlled Trial (FHH-RCT). The analyses examined (1) whether or not FHH-RCT participants met the PA guidelines (≥150 min moderate-vigorous PA per week); (2) the effect of the intervention arm (family risk reduction (FRR) vs. standard care (SC)), (3) individual level Walk Score® (high vs. low) and aggregate walkability of participants' home residential neighbourhood (high vs. low) on the dichotomous PA outcome (met PA guidelines vs. not) at baseline and at the end of the intervention period (12-weeks); (4) and the interaction between these conditions. It was hypothesized that (1) participants living in high walkability neighbourhoods would be more likely to meet PA guidelines at baseline compared to participants living in low walkability neighbourhoods and (2) that participants in the FRR intervention arm living in high walkability neighbourhoods would be most likely to meet PA guidelines at 12-weeks.

Section snippets

Participants

To be included in the current analysis, participants were required to (i) be enroled in the FHH-RCT, (ii) live in an Ottawa neighbourhood and (iii) provide verbal informed consent for the data linkage. The University of Ottawa Heart Institute (UOHI) Human Research Ethics Board approved the FHH-RCT and this data linkage study.

Between January 2008 and October 2010, 423 participants were recruited for the FHH-RCT through a hospital-based prevention and wellness centre. In addition to being the

Results

Baseline characteristics of participants (n=292) are presented in Table 1a. There were no significant differences in demographic characteristics at baseline between the FRR and SC intervention arms.

Variables from the ONS used to derive the neighbourhood walkability scores are presented in Table 2. At baseline, participants (n=292) lived in 84 unique neighbourhoods; 16 out of the 84 neighbourhoods had only one participant living there. The mean walkability was 0.54±3.09 (range=−5.85–11.63). One

Discussion

These analyses demonstrate that the FHH-RCT intervention is effective for increasing self-reported PA. The individual-level intervention appears to have a stronger effect on PA outcomes than either measure of neighbourhood walkability; participants with both high and low walk scores or living in high versus low walkability neighbourhoods were more likely to achieve the PA targets if allocated to the FRR intervention. This may be a reflection of the PA measure used in the current study, which

Conclusion

This study found that the intervention was effective for increasing PA among participants with both high and low Walk Score® and neighbourhood walkability. These results are promising, given that neighbourhood redevelopments to create more walkable environments are both time-consuming and expensive (Sundquist et al., 2011). Future interventions and policies to promote PA should consider the social ecological context in which PA takes place. Additional research using objective measures of PA,

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