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American Journal of Epidemiology Advance Access originally published online on January 27, 2008
American Journal of Epidemiology 2008 167(8):944-953; doi:10.1093/aje/kwm391
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American Journal of Epidemiology © The Author 2008. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

ORIGINAL CONTRIBUTIONS

Association between Neighborhood Active Living Potential and Walking

Lise Gauvin1,2,3, Mylène Riva1,2,3, Tracie Barnett1,2,3,4, Lucie Richard1,2,5, Cora Lynn Craig6, Michaël Spivock1,2,3, Sophie Laforest1,7, Suzanne Laberge7, Marie-Chantal Fournel8, Hélène Gagnon9 and Suzie Gagné10

1 Groupe de Recherche Interdisciplinaire en Santé, University of Montreal, Montreal, Quebec, Canada
2 The Léa-Roback Research Center on Social Inequalities of Health in Montreal, University of Montreal, Montreal, Quebec, Canada
3 Department of Social and Preventive Medicine, University of Montreal, Montreal, Quebec, Canada
4 Centre Hospitalier Universitaire Ste-Justine, Montreal, Quebec, Canada
5 Faculty of Nursing, University of Montreal, Montreal, Quebec, Canada
6 Canadian Fitness and Lifestyle Research Institute, Ottawa, Ontario, Canada
7 Department of Kinesiology, University of Montreal, Montreal, Quebec, Canada
8 Direction de la Santé Publique, Régie Régionale de la Santé et des Services Sociaux—Montréal-Centre, Montreal, Quebec, Canada
9 Direction de la Santé Publique, Régie Régionale de la Santé et des Services Sociaux— Montérégie, Quebec, Canada
10 Service des Loisirs, Ville de Montréal, Montreal, Quebec, Canada

Correspondence to Dr. Lise Gauvin, Department of Social and Preventive Medicine, University of Montreal, P.O. Box 6128, Downtown Station, Montreal, Quebec H3C 3J7, Canada (e-mail: lise.gauvin.2{at}umontreal.ca).

Received for publication September 21, 2006. Accepted for publication December 11, 2007.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
This paper examines the association between neighborhood active living potential and walking among middle-aged and older adults. A sample of 2,614 (61.1% women) persons aged 45 years or older and living in one of 112 census tracts in Montreal, Canada, were recruited between February and May of 2005 to participate in a 20-minute telephone survey. Data were linked to observational data on neighborhood active living potential in the 112 census tracts and analyzed through multilevel modeling. Greater density of destinations in the census tract was associated with greater likelihoods of walking for any reason at least 5 days per week for at least 30 minutes (odds ratio = 1.53, 95% confidence interval: 1.21, 1.94). Associations were attenuated but remained statistically significant after controlling for socioeconomic, health, lifestyle, and other physical activity characteristics. Sensitivity analyses showed that associations were robust across smaller and larger volumes of walking. No associations were found between dimensions of neighborhood active living potential and walking for recreational reasons. The authors conclude that a larger number and variety of neighborhood destinations in one's residential environment are associated with more walking and possibly more utilitarian walking among middle-aged or older adults.

exercise; physical fitness; residence characteristics; social conditions; social environment

Abbreviations: CI, confidence interval; OR, odds ratio


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Promoting regular involvement in walking is one strategy for overcoming the public health burden of physical inactivity in industrialized nations (1–3). Understanding neighborhood determinants of walking has emerged as an important theme in epidemiologic research (4–9) on neighborhoods and health (10). Studies examining the influence of area socioeconomic characteristics on walking provide inconsistent results, with some studies showing that walking is more likely in more deprived neighborhoods (11–13) and others showing opposite findings (14, 15). More recent research suggests (16–33) that higher population density, greater connectivity, greater number and variety of destinations, and mixed land use in residential neighborhoods are associated with greater frequencies and duration of walking, and that lack of neighborhood safety is associated with lower volumes of walking in selected subsamples (34, 35).

Three issues warrant further research. First, at least two groups of researchers (36–38) have suggested that there is a need to study determinants of different types of walking, namely, utilitarian and recreational. Recreational walking consists of episodes of walking performed for the purposes of maintaining health/fitness or for enjoyment. Utilitarian walking is generally used as a form of transportation for the purpose of fulfilling other life tasks (e.g., running errands, commuting). Second, only a few studies (31, 39) have examined whether or not associations are present for volumes of walking that are sufficient for meeting minimum public health recommendations (40, 41) for involvement in physical activity (30 minutes of moderate physical activity five times per week). Third, much of the extant research on neighborhoods and health has used neighborhood-level income and education as proxies for other exposures (42) even though their association with more specific exposures is poorly understood. There is a need to develop conceptually based explanations regarding how specific exposures in neighborhood environments are associated with health outcomes (43–46). In this regard, active living communities (9, 17) and neighborhood active living potential (47) represent relevant exposure constructs composed of at least three dimensions. First, density of destinations emerges from physical and social characteristics of neighborhoods related to land use mix, with low density of destinations neighborhoods having a restricted number and variety of destinations for engaging in personal or collective pursuits (e.g., purchasing consumer goods), whereas high density of destinations neighborhoods offers a wide variety of such destinations. Second, activity friendliness emerges from physical characteristics of neighborhoods (e.g., sidewalks) and renders neighborhoods favorable or unfavorable to human-powered activities such as walking. Third, safety relates to physical (vehicular burden) and social (potential for crime) characteristics of the neighborhood and either elicits a sense of threat or security among people ambulating through the neighborhood.

We examined the association between density of destinations, activity friendliness, and safety and the likelihood of walking in a sample of middle-aged or older adults. On the basis of previous work (21–33, 48–50), we hypothesized that persons living in areas with greater density of destinations, activity friendliness, and safety would be more likely to walk at least five times per week for at least 30 minutes. In an effort to disentangle associations with different types of walking, we also examined associations between exposures and walking for recreational reasons. Given previous research (9, 17, 47), we hypothesized that activity friendliness and safety would be related to recreational walking. We also examined whether or not any associations were attenuated by controlling for a series of individual variables, because previous research (3, 20, 21, 32) shows that greater affluence, more healthful lifestyle behaviors, healthful weight status, and better health status are associated with more walking and because other research (42) shows that individuals with similar socioeconomic characteristics often aggregate into similar neighborhoods. As a result, associations between neighborhood-level exposures and walking could be confounded by individual characteristics or by patterns of clustering of people across locations (22, 46). Finally, in addition to establishing associations with walking volumes sufficient for meeting public health recommendations, we performed sensitivity analyses to determine whether or not any associations were statistically significant across smaller and larger volumes of walking. We also examined whether or not associations with neighborhood dimensions were present for a subset of persons who could be characterized as utilitarian walkers (i.e., people who report walking five times per week at least 30 minutes but who report little or no recreational walking).


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Neighborhoods
Census tracts were the proxy for neighborhoods and were selected on the Island of Montreal, Canada, an urban center with 1,812,723 inhabitants. At the time of data collection, the Island of Montreal was divided into 521 census tracts (511 tracts including residential buildings), which were nested unevenly into 27 boroughs (minimum = four, maximum = 48 census tracts per borough). Tracts located within the same borough were stratified as a function of tertile of average income, and a random sample of 20 percent of tracts within each borough stratum was selected.

Respondents
A two-step procedure was used to create a list of telephone numbers to recruit participants. First, a list of postal codes within each selected census tract was established through use of specialized software (51), and a list of telephone numbers in the tracts was created from public telephone records linked to postal code information. Second, another list of telephone numbers likely to be located within the selected tracts was generated to account for known proportions of unlisted numbers. Participants were recruited by a recognized polling firm between February and May of 2005 through random selection of phone numbers in the combined list. There were four eligibility criteria: 1) being aged 45 years or older; 2) living in one of the 112 neighborhoods as confirmed by the verification of the six-digit postal code; 3) having lived at the current address for at least 1 year; 4) being able to respond in either French or English. Only one respondent per household participated.

Measures
Walking.
We used questions pertaining to walking from the International Physical Activity Questionnaire (IPAQ) (52), a seven-item questionnaire which has been shown to have good test-retest reliability (r = 0.80) and moderate convergent validity (r = 0.30) with accelerometers. Others have used the International Physical Activity Questionnaire to establish population estimates of different walking patterns (53, 54). Respondents indicated on how many days they walked (e.g., walking to get around, walking for health) for at least 10 minutes at a time in the previous 7 days. Those indicating having walked at least 1 day for at least 10 minutes were asked to estimate the amount of time per day spent walking. We created three dummy variables to identify participants reporting that they had walked for at least 30 minutes on at least 3, 5, and 7 days.

Three additional questions specifically addressed walking for recreational reasons. Participants indicated if any walking episodes in the previous week were performed specifically to maintain health/fitness. Those responding affirmatively were asked to estimate the number of days and the average amount of time per day spent in this type of walking. We created another three dummy variables to identify persons who walked recreationally for at least 30 minutes on at least 3, 5, and 7 days. Although it would have been ideal to address a further set of questions on walking for strictly utilitarian walking, pilot testing showed that such questioning over the telephone was unwieldy and resulted in participant confusion. For exploratory purposes, we created a dummy variable that identified participants who could be characterized as utilitarian walkers, that is, participants reporting walking for any motive at least 5 days per week for 30 minutes but reporting walking for recreational reasons less than 3 days per week. Utilitarian walkers were compared with all other participants.

Neighborhood-level indicators.
We used an 18-item observation grid (47) to tap into density of destinations (e.g., "large number of people-oriented destinations": eight items, reliability = 0.83), activity friendliness (e.g., "pedestrian system addresses pedestrian needs": six items, reliability = 0.78), and safety (e.g., "safety/feeling comfortable with the potential for crime": four items, reliability = 0.76). Following training (refer to "Training Manual" at http://www.cflri.ca plus English plus Environments), one of four pairs of trained observers who completed their trek through census tract areas by following a predetermined walking route visited each census tract area. For each route, observers from a pair started at opposite ends of the route and rated areas along the 18 items using a 10-point rating scale. The resulting hierarchically structured data (4,032 observations: 112 tracts x 2 observers x 18 items) were analyzed through multilevel modeling from which interobserver and interitem variances were removed to produce empirical Bayes estimates of neighborhood-level density of destinations, activity friendliness, and safety for each of the 112 census tracts (47). Extreme groups on neighborhood exposures were created by categorizing empirical Bayes estimates into high (highest quintile), average (second, third, or fourth quintiles), and low (lowest quintile) groupings. Estimation of Spearman's rank order correlations across quintile groupings revealed that safety and activity friendliness were negatively associated with density of destinations (r = –0.80, p < 0.001; r = –0.34, p < 0.001).

Health status and lifestyle.
Participants indicated whether or not they had smoked cigarettes in the previous 30 days and self-reported height and weight from which body mass index (weight (kg)/height (m)2) was estimated and recategorized (normal: ≤25.0, overweight: 25.1–29.9, or obese: ≥30.0). Participants reported the frequency and duration of their involvement in vigorous physical activities and were categorized as being vigorously active (≥3 days for at least 30 minutes). The presence of walking disabilities was established if participants indicated that they needed supports (e.g., cane, walker) to move around. Participants reported on their perceived health, and persons with average or bad perceived health were contrasted with others. Participants also indicated whether or not their health had improved, worsened, or stayed about the same over the previous year.

Socioeconomic characteristics.
Persons reported their highest academic degree: less than high school, high school diploma, trade diploma or college diploma, and university degree completed; average annual family income in Canadian dollars: <20,000, 20,000–60,000, >60,000, or refusal to provide income information; marital status: living with a spouse (common law) or not; and immigration status: being born in Canada or elsewhere. Age was computed from participants' reported birth year and recategorized: 44–54, 55–64, or ≥65 years. Employment status was categorized according to whether or not participants were retired and if they held any regular paid or volunteer activities. Participants indicated whether or not they held a valid driver's license and for how many years they had lived at their current address (1–5, 6–10, 11–20, or >20 years).

Survey
The survey was conducted in 2005 in three waves (mid-February to mid-March, mid-March to mid-April, and mid-April to mid-May) with about 10 interviews per tract during each wave to monitor differential response rates and to control for possible seasonal effects. Polling occurred between 10 a.m. and 9 p.m. on weekdays and between noon and 9 p.m. on weekends. Professional interviewers were trained by the research team, and telephone monitoring occurred throughout data collection. The protocol was approved by the Research Ethics Committee of the Faculty of Medicine of the University of Montreal.

Statistical analysis
Descriptive statistics were used to characterize the sample of census tracts and participants. Then, participants' categorizations as walking for any motive or for recreational reasons for at least 30 minutes on at least 5 days were analyzed as two dichotomous outcome variables, and census tract categorizations of density of destinations, activity friendliness, and safety were used as the main exposure variables in a first series of multilevel models. After testing a null model to establish presence/absence of between-tract variations in outcome variables, we built successive multilevel models with one random term on the intercept including the following: main exposures tested separately (model 1); main exposures tested separately but controlling for individual-level characteristics (model 2); and main exposures tested simultaneously and controlling for all individual-level characteristics (model 3).

In sensitivity analyses, we examined whether or not associations between dimensions of neighborhood active living potential and walking for any motive or for recreational reasons remained statistically significant when the weekly frequency of walking was set at 3 or 7 rather than 5 days per week. For these analyses, main exposures were entered simultaneously. Models were tested with and without controlling for individual-level characteristics.

In a final set of ancillary analyses, we explored associations between dimensions of neighborhood active living potential and the dummy variable that contrasted utilitarian walkers with the rest of the sample. Models were tested with the main exposures entered simultaneously, with and without controlling for individual-level characteristics.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Neighborhood and participant characteristics
Safer and more activity-friendly census tracts were larger and populated by fewer families with low income. Census tracts characterized by greater density of destinations were more compact and included a mix of income and educational levels (table 1). From a list of 21,533 telephone numbers, 11,739 (54.5 percent) were found either to be outside the 112 census tracts or nonresidential or to include only dwellers not meeting eligibility requirements. Calls to the remaining 9,794 telephone numbers resulted in 4,783 respondents (48.8 percent) declining to participate without providing information to establish eligibility, 2,088 (21.3 percent) households did not answer or rerouted the call to an answering machine, and 2,923 (response rate: 2,923/9,794 = 29.8 percent; cooperation rate: 2,923/5,011 = 58.33 percent) participated. Response rates are commensurate with current survey response rates that range between 22 percent and 48 percent (55–57). The proportions of the sample with an annual household income below $20,000 and with a university education were correlated at 0.67 (p < 0.001) and 0.83 (p < 0.001), respectively, with corresponding indicators obtained from Statistics Canada (58) generated for each of the census tracts, suggesting that the sample obtained was aligned with the characteristics of populations living in census tracts.


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  		TABLE 1. Characteristics of 112 census tract areas in Montreal, Canada, according to the 2001 Statistics Canada census*

 
After listwise deletion due to incomplete or missing responses, data from 2,614 (89.4 percent) participants were analyzed. The sample was diverse in terms of age, sex, health status, and socioeconomic status (table 2). There was substantial variation on all walking variables. Those reporting walking at least 10 minutes in the previous 7 days (n = 2,228) walked, on average, 5.12 days (median = 6, interquartile range = 3–7), for 41.9 minutes per day (median = 30, interquartile range = 20–45). Those reporting recreational walking (n = 1,226) did so, on average, 4.25 days (median = 4, interquartile range = 2–7), for 40.0 minutes per day (median = 30, interquartile range = 20–45).


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  		TABLE 2. Characteristics of 2,614 residents surveyed during the winter and spring of 2005 in Montreal, Canada

 
Multilevel modeling
Null models revealed significant between-tract variability in the likelihood of walking at least 30 minutes on 5 days for any motive (p < 0.004). The estimated proportion of persons walking at this volume was 38.1 percent. There was no significant variability across tracts for walking for recreational reasons, and the estimated proportion of persons walking recreationally for at least 30 minutes on 5 days was 16.1 percent.

The first series of multilevel analyses (table 3) showed that greater density of destinations in comparison with average levels was associated with greater likelihood of walking for any motive (model 1: odds ratio (OR) = 1.53, 95 percent confidence interval (CI): 1.21, 1.94). The addition of confounding variables attenuated the odds ratio, which remained statistically significant (model 2). Activity friendliness was not associated with walking (models 1 and 2). Furthermore and somewhat counterintuitively, a lower in comparison with an average level of safety was associated with greater likelihood of walking at least 30 minutes for 5 days for any reason (OR = 1.37, 95 percent CI: 1.08, 1.74), and higher safety in comparison with average safety was associated with a lower likelihood of walking at this volume (OR = 0.79, 95 percent CI: 0.62, 1.00). The addition of confounding variables attenuated odds ratios, which remained statistically significant (model 2). In the model (model 3) including all dimensions of neighborhood active living potential simultaneously, higher in comparison with average levels of density of destinations emerged as the strongest predictor. Specifically, walking for any motive at least 30 minutes on 5 days was predicted by living in a tract in the highest quintile of density of destinations (OR = 1.40, 95 percent CI: 1.00, 1.95) in comparison with the middle quintiles. No other associations reached statistical significance. Overall, walking for recreational reasons was not associated with dimensions of neighborhood active living potential in either separate or combined models.


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  		TABLE 3. Results of multilevel models examining associations between dimensions of neighborhood active living potential and walking for any motive and for recreational reasons at least five times per week for an average of at least 30 minutes among 2,614 residents of 112 census tracts in Montreal, Canada, surveyed during the winter and spring of 2005

 
Sensitivity analyses revealed that associations between the density of destinations and walking were statistically significant when volumes of walking for any motive were smaller (3 days per week at least 30 minutes: OR = 1.40, 95 percent CI: 1.02, 1.94) and larger (7 days per week at least 30 minutes: OR = 1.75, 95 percent CI: 1.24, 2.47) than the cutoff used in the main analyses (5 days per week at least 30 minutes: OR = 1.46, 95 percent CI: 1.06, 2.03). Addition of individual-level characteristics to the model reduced the size of associations just below the level of statistical significance for smaller volumes (OR = 1.36, 95 percent CI: 0.98, 1.90) but not for larger volumes (OR = 1.66, 95 percent CI: 1.18, 2.35).

The final set of ancillary analyses revealed that a higher density of destinations was associated with a greater likelihood of being a utilitarian walker (OR = 1.70, 95 percent CI: 1.14, 2.54). This association remained statistically significant when controlling for individual-level characteristics (OR = 1.56, 95 percent CI: 1.05, 2.32).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
The purpose of this investigation was to examine the association between density of destinations, activity friendliness, and safety and walking among middle-aged or older adults. We hypothesized that greater density of destinations, activity friendliness, and safety would be associated with greater likelihood of walking for any motive at least 5 times per week for at least 30 minutes, whereas walking for recreational motives at this volume would be associated with greater activity friendliness and safety. Results showed that exposure to greater density of destinations in the neighborhood was associated with greater likelihood of walking for any motive. Findings also showed that these associations were not confounded by individual-level characteristics. The findings support other reports (24, 26, 29, 49) showing that the presence of opportunities for engaging in life tasks is associated with greater likelihood of walking. Results extend the literature by demonstrating that these associations hold true for volumes of activity that are sufficient for meeting public health recommendations for physical activity.

Furthermore, current findings do not support research reported elsewhere (21, 22, 29–31) that greater activity friendliness and safety are associated with greater likelihood of total or recreational walking. One explanation is that the current data were collected in one urban setting wherein urban development has led to a landscape in which greater density of destinations is associated with lower activity friendliness and safety. In other settings where urban planning has rendered environments dense with destinations as well as safe and activity friendly, the pattern of findings might differ. Similarly, other researchers have examined the role of parks and pedestrian walkways in promoting walking (21, 22, 31). In the current investigation, we did not examine the association of specific destinations with walking. It is also noteworthy to underscore that, since walking for recreational reasons was not associated with any neighborhood variables, it is likely that associations between density of destinations and total walking are due to greater involvement in walking for utilitarian purposes. Results of the exploratory analyses among participants characterized as utilitarian walkers provide some support for this inference. However, further investigations allowing for a more fine-grained analysis of walking for different motives are required.

Results of sensitivity analyses showed that the associations between greater density of destinations and walking for any motive remained statistically significant when the weekly frequency of walking was set at 3 or 7 days rather than 5 days per week. In fact, the odds ratios were slightly higher for walking for any motive 7 days per week. These findings suggest that associations between density of destinations and walking are robust across different cutoff points.

Regarding strengths and limitations, one of the strengths of this study is that exposure data were collected in a large number of neighborhoods using observational data (59, 60). Also, the sample of respondents was large and corresponded to characteristics of persons living in the area. The main limitation pertains to the self-reported measure of walking. As mentioned by other authors (38, 61–63), further psychometric investigations are required to disentangle how best to tap into differential walking motives and patterns in population-based samples. Investigations into the specific locations where walking is performed (e.g., people drive out to a park outside their neighborhood to have a walk but walk to the convenience store in the neighborhood to buy a newspaper) are also warranted (38) as are investigations corroborating findings with accelerometer data.

Cross-sectional data limit our ability to establish whether or not neighborhood characteristics were the catalyst for walking and whether or not persons involved in greater amounts of walking chose to live in an active living neighborhood. Finally, in the present study, we used census tracts as a proxy for neighborhoods. It is unclear if neighborhood exposures are homogeneous within tracts and if census tracts represent the most appropriate operationalization of neighborhoods (64, 65).

We conclude that greater neighborhood density of destinations is associated with more walking and possibly utilitarian walking among middle-aged or older adults. Additional investigations integrating psychometrically valid measures of walking for different motives are required as are longitudinal investigations wherein associations between changing walking patterns and neighborhood environments can be ascertained.


   ACKNOWLEDGMENTS
 
Research was supported by Canadian Institutes of Health Research grant 200203 MOP 57805.

Conflict of interest: none declared.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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