Abstract
Background
Identifying environmental factors that can influence physical activity is a public health priority. We examined associations of perceived environmental attributes with walking for four different purposes: general neighborhood walking, walking for exercise, walking for pleasure, and walking to get to and from places.
Methods
Participants (n =399; 57% women) were surveyed by mail. They reported place of residence, walking behaviors, and perceptions of neighborhood environmental attributes.
Results
Men with the most positive perceptions of neighborhood “aesthetics” were significantly more likely (odds ratio [OR]=7.4) to be in the highest category of neighborhood walking. Men who perceived the weather as not inhibiting their walking were much more likely (OR=4.7) to be high exercise walkers. Women who perceived the weather as not inhibiting their walking were significantly more likely to be high neighborhood walkers (OR=3.8) and those with moderate perceptions of “accessibility” were much more likely to do more walking for pleasure (OR=3.5).
Conclusions
Different environmental attributes were associated with different types of walking and these differed between men and women. Approaches to increasing physical activity might usefully focus on those attributes of the local environment that might influence particular subsets of walking behavior.
Introduction
Physical activity is now central to population strategies for chronic disease prevention.
1
, 2
Studies to identify factors that influence population levels of physical activity are needed to inform intervention development and public health policy.3
To guide such studies, ecologic models of health behavior4
help to systematize the plethora of factors that are known to be associated with variations in physical activity habits in particular groups and in whole populations.5
A range of studies has examined the variety of factors that can act to influence physical activity. Most often, these have been in the psychological and social domains.
3
, 5
Broader physical environment, societal, and organizational influences are less well understood.3
, 4
, 6
, 7
A key feature of ecologic models of health behavior is the role ascribed to physical environment factors in the network of causality of physical activity participation.4
, 5
, 6
, 7
Specific environmental factors are likely to influence particular physical activity behaviors, given that different types of activity typically take place in distinct settings.
4
, 6
For Australian adults, walking is the most common form of moderate-intensity activity reported in population surveys.8
Walking can readily be incorporated into daily routines and is convenient and accessible to all segments of the community.9
, 10
Research that identifies environmental factors associated with physical activity is accumulating.
5
, 11
, 12
, 13
, 14
There are also studies identifying environmental factors that are specifically related to walking.15
, 16
, 17
, 18
, 19
A recent review12
found consistent evidence that perceived aesthetic attributes, accessibility of facilities, and opportunities were associated with physical activity. Safety and the weather had less strong associations. In an Australian study,20
the specific behavior of neighborhood walking demonstrated stronger associations with environmental attributes than did measures of total walking or of total physical activity. Aesthetics, convenience of facilities, and access to services were positively associated with the neighborhood walking for men; convenience was associated with neighborhood walking for women.This study reports the patterns of association of an extended range of perceived neighborhood attributes with walking for particular purposes. The primary aim was to examine whether the attributes of local environments found to be associated with general neighborhood walking
20
are associated also with more-specific walking purposes: walking for exercise, walking for pleasure, and walking to get to and from places. Given that consistent gender differences were found in previous studies,20
, 21
associations of environmental attributes with walking were examined separately for men and women.Methods
Participants
Participants were clients aged >40 years from a health insurance organization that also provides telephone-delivered prevention and disease-management services. They were drawn from a regional coastal Australian city (population 180,000) and its surrounding suburbs. The mail-out survey was sent in the spring. From 982 potential respondents, the initial response was 282 (29%). A reminder letter was then sent out to participants who had not responded within 2 weeks. A total of 429 (43%) returned the survey. Of these, 30 surveys were incomplete, resulting in a final sample of 399.
Measures
The survey included questions on age, educational attainment, gender, walking behaviors, perceptions of the neighborhood environment, and participants' postal code. Table 1 provides sample characteristics.
Table 1Characteristics of sample and distribution by location
| Men % (n) | Women % (n) | |
|---|---|---|
| Gender | 42.6 (170) | 57.4 (229) |
| Age | ||
| 40–59 years | 44.6 (75) | 56.6 (128) |
| ≥60 years | 55.4 (93) | 43.4 (98) |
| Education | ||
| ≤12 years | 27.3 (45) | 56.5 (122) |
| Trade/technical | 46.7 (77) | 23.6 (51) |
| University | 26.1 (43) | 19.9 (43) |
| Location | ||
| Noncoastal | 28.7 (48) | 26.0 (59) |
| Coastal | 71.3 (119) | 74.0 (168) |
Walking
For neighborhood walking, participants were asked: “How many times a week do you go for a walk for any reason in and around your neighborhood?” “How much time would you usually spend when you do go for a walk in and around your neighborhood?” For walking for exercise, participants were asked: “What is the average number of times per week you spend walking in your neighborhood or elsewhere, for exercise for at least 10 minutes at a time?” “What is the average number of minutes you spend walking each time?” This was repeated for walking for pleasure and for walking to get to and from places. Reported frequency of walking was multiplied by the number of usual minutes, to give an index of estimated minutes of walking each week, for each specific walking type. Reliability of the neighborhood walking item had been examined previously.
20
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Neighborhood walking included all walking that occurred in the neighborhood for any purpose; walking for exercise, pleasure, and to get to and from places could have occurred in the neighborhood or elsewhere.Perceived environmental attributes
There were 24 neighborhood environment attribute items, based on findings from a review of studies that assessed relationships between environment attributes and physical activity behaviors,
12
previous studies,20
, 21
and also items from the Neighborhood Environment Walkability Scale.22
Items were based on semantic differential principles,23
where the anchors were the most negative and the most positive result for that situation. Participants were asked to check the most appropriate value on a ten-point scale (see Appendix for a full list of study items, factor groupings, and response options). Previously, test–retest reliability had been examined for eight of the environmental attribute items.21
Intra-class correlations (absolute agreement) for these items ranged from 0.73 to 0.91.Principal component analysis using varimax rotation was used to identify groups of related environmental attributes. The analysis identified four factors accounting for 56% of the variance. Four items were excluded from further analysis as they cross-loaded across several of the factors or did not fit with the interpretation of the factors. One factor (and its eigenvalues) was interpreted as “accessibility” of facilities for walking (eight items, 6.1). Factors interpreted as influences on walking included “aesthetics” (four items, 2.3); “safety” (four items, 1.36); and “weather” (four items, 2.0). Loadings ranged from 0.49 to 0.89 across the four factors. Cronbach's alpha coefficient of internal consistency was calculated for each subscale. All scores were above the 0.70 recommended level: aesthetics=0.81; accessibility=0.88; safety=0.73; and weather=0.77.
Location by postal code
Previous Australian studies have found physical activity to be higher among coastal residents, after adjusting for educational attainment and other demographic factors.
20
, 21
, 24
In Australia, a postal code district is a mail delivery area identified by four digits, used functionally in the same way as are ZIP codes in the United States. A structured query language (SQL) function used Australian Bureau of Statistics 1996 Census data to identify postal areas that intersect the coastline. This variable was coded into noncoastal (27%) and coastal (73%) location. The high proportion of participants with a coastal location is due to the survey area being a long narrow strip between mountains and the ocean.Data analysis
Items in each factor were summed to provide a total score for each category of environmental attribute. These summed scores were then divided by the number of items in each category. This facilitated comparison across the categories, with all having a final score out of ten (Table 2). The scores of aesthetics, accessibility, safety, and weather were transformed into categorical variables with three levels: low (a less positive perception of the environment); moderate; or high (a highly positive perception of the environment). A high score for weather meant that the weather did not inhibit walking. The cutoff points used for these levels were those that most closely approximated the tertiles of the distributions.
Table 2Mean minutes of walking, by type and by scores on environmental attribute categories
| Men Mean (SD) | Women Mean (SD) | |
|---|---|---|
| Walking | ||
| Neighborhood | 187 (181) | 171 (128) |
| Exercise | 124 (124) | 137 (113) |
| Pleasure | 32 (58) | 31 (62) |
| To get to places | 32 (56) | 29 (48) |
| Environment | ||
| Aesthetics | 8.19 (1.6) | 8.33 (1.7) |
| Accessibility | 6.37 (1.9) | 6.45 (2.0) |
| Safety | 7.88 (1.7) | 7.72 (1.8) |
| Weather | 6.28 (2.0) | 6.06 (2.2) |
SD, standard deviation.
a The summed environmental scores were divided by the number of items in each category to facilitate comparison across the categories.
All four walking outcome measures were dichotomized at the median score and analyzed separately. The median score for neighborhood walking was 150 minutes per week, and for exercise walking, 120 minutes per week. For walking for pleasure and to get to and from places, the median score was 0 minutes resulting in any, or no walking categories for these two outcomes. Because the study asked about walking for different purposes separately, and an overlap in reporting was a likely consequence, no analyses were conducted using a total measure of walking.
A series of logistic regression models was used to examine the association between location and the four perceived environment categories, with the four walking outcome variables. All models were adjusted for age and education level. As past studies have found that physical activity differs for men and women,
1
, 3
, 20
all models were stratified by gender.Results
Characteristics of participants are in Table 1. The mean age of the sample was 60 (standard deviation [SD]=11) years with 57.4% being women. The participants were overall a relatively active group, with the mean minutes of neighborhood walking for both men and women being above the recommended “sufficient” activity for health benefits of 150 minutes per week.
1
Table 2 shows mean minutes of types of walking for men and women. There were no statistically significant gender differences.A significant difference between the age groups was found for walking for pleasure. The proportion of those aged >60 years (28.8%) who walked for pleasure was significantly less than for those <60 years (46.2%) (χ2=12.24, p <0.001).
A higher proportion of those with the most positive perceptions for all four environmental perception categories reported more neighborhood walking. Higher proportions of neighborhood walkers were found among those with high perceptions for aesthetics (66.7%; χ2=17.08, p <0.001) and among those reporting that weather is not an influence (67.4%; χ2=27.98, p <0.001). Significantly higher proportions of those walking for exercise were found among those with the most positive perceptions for all four environmental perception categories. For example, 74.8% (χ2=39.85, p <0.001) of those reporting that weather did not inhibit walking were high exercise walkers. A higher proportion of those with the most positive perceptions for accessibility reported more walking for pleasure (45.2%; χ2=7.28, p <0.05). No significant differences in proportions were found for walking to get from place to place.
Place of residence
No significant gender or education differences were found for specific coastal versus noncoastal location identified by postal code. The proportion of participants aged >60 years living in a coastal location (78.0%) was significantly higher than for those aged <60 years (68.7%; χ2=4.37, p <0.05). A higher proportion of coastal than noncoastal residents were in the higher-level group for each type of walking. This difference was significant for neighborhood walking, with 57.5% coastal participants and 38.5% noncoastal participants reporting a high level of neighborhood walking (χ2=11.01, p <0.001).
Participants living in coastal locations (mean [M]=189 minutes) walked significantly more minutes in their neighborhood (F(1,382)=5.10, p <0.05) than did participants in noncoastal locations (M=149 minutes). Coastal residents (M=139 minutes) reported more minutes of walking for exercise (F(1,385)=5.10, p <0.05) compared to noncoastal (M=109 minutes). Differences in location for mean scores for the environmental attributes of aesthetics, accessibility, safety, and weather were nonsignificant. Since coastal location implies that a beach is nearby, the item asking about walking distance to a beach or lake was analyzed separately (see Appendix, item 3). Participants reporting that a beach/lake was within easy walking distance reported significantly more neighborhood walking minutes (M=224) than did those reporting a beach/lake was not within walking distance (M=139; F(2,379)=11.00, p <0.000); significantly more exercise walking (M=163 compared to M=100 minutes; F(2,382)=9.72, p <0.00); and significantly more walking for pleasure compared to those perceiving that a beach/lake is not within walking distance (M=33 and M=21, respectively; F(2,380)=3.88, p <0.02).
Multivariate models of walking behaviors
Neighborhood walking
Men with the most positive perceptions about the aesthetic nature of the environment were more than seven times more likely to be high neighborhood walkers (Table 3). Those men who reported that the weather was not inhibiting their walking habits were more than four times as likely to be high neighborhood walkers. Accessibility of facilities for walking demonstrated a negative relationship with neighborhood walking for men. Women who reported that the weather was not inhibiting their walking habits were more than three times as likely to be in the high neighborhood walking category (Table 4). Women living in a coastal location were three times more likely to be high neighborhood walkers. Men evidenced the same pattern regarding location, although the odds ratio was nonsignificant. No evidence of a relationship between safety and neighborhood walking was found for men or women.
Table 3Odds ratios (95% CI) for environmental variables and likelihood of men being high walkers
| Neighborhood walking | Exercise walking | Pleasure (social) walking | Walking to get to and from places | |
|---|---|---|---|---|
| Location | ||||
| Noncoast | 1.00 | 1.00 | 1.00 | 1.00 |
| Coast | 1.69 (0.69–4.18) | 1.72 (0.70–4.19) | 1.59 (0.64–3.95) | 0.94 (0.40–2.19) |
| Aesthetics | ||||
| Low | 1.00 | 1.00 | 1.00 | 1.00 |
| Moderate | 1.92 (0.63–5.86) | 2.06 (0.68–6.26) | 1.47 (0.78–4.57) | 0.94 (0.33–2.64) |
| High | 7.43 (1.92–28.82) | 3.86 (1.03–14.46) | 1.45 (0.38–5.49) | 0.64 (0.19–2.17) |
| Accessibility | ||||
| Low | 1.00 | 1.00 | 1.00 | 1.00 |
| Moderate | 1.14 (0.39–3.29) | 2.57 (0.89–7.46) | 0.91 (0.33–2.51) | 1.10 (0.43–2.85) |
| High | 0.30 (0.09–0.91) | 0.70 (0.25–2.01) | 2.02 (0.68–5.98) | 1.40 (0.50–3.87) |
| Safety | ||||
| Low | 1.00 | 1.00 | 1.00 | 1.00 |
| Moderate | 0.98 (0.31–3.01) | 1.23 (0.40–3.82) | 0.54 (0.18–1.65) | 0.58 (0.20–1.68) |
| High | 0.91 (0.27–3.06) | 1.04 (0.31–3.58) | 0.22 (0.06–0.78) | 0.54 (0.17–1.67) |
| Weather | ||||
| Strong influence | 1.00 | 1.00 | 1.00 | 1.00 |
| Moderate | 4.09 (1.44–11.66) | 4.08 (1.42–11.74) | 1.37 (0.51–3.68) | 0.92 (0.59–4.29) |
| Not an influence | 4.71 (1.60–13.91) | 5.48 (1.83–16.38) | 0.58 (0.20–1.69) | 1.60 (0.40–2.19) |
| Age | ||||
| 40–59 years | 1.00 | 1.00 | 1.00 | 1.00 |
| ≥60 years | 1.59 (0.66–3.87) | 0.95 (0.40–2.25) | 0.33 (0.14–0.81) | 1.90 (0.84–4.31) |
CI, confidence interval.
* p < 0.05.
** p < 0.01.
Table 4Odds ratios (95% CI) for environmental variables and likelihood of women being high walkers
| Neighborhood walking | Exercise walking | Pleasure (social) walking | Walking to get to and from places | |
|---|---|---|---|---|
| Location | ||||
| Noncoast | 1.00 | 1.00 | 1.00 | 1.00 |
| Coast | 3.32 (1.51–7.29) | 1.40 (0.62–3.18) | 1.65 (0.72–3.82) | 1.83 (0.87–3.85) |
| Aesthetics | ||||
| Low | 1.00 | 1.00 | 1.00 | 1.00 |
| Moderate | 1.74 (0.65–4.62) | 1.78 (0.63–5.02) | 0.80 (0.28–2.24) | 0.59 (0.23–1.48) |
| High | 1.12 (0.41–3.12) | 0.75 (0.25–2.26) | 0.84 (0.29–2.42) | 0.84 (0.31–2.25) |
| Accessibility | ||||
| Low | 1.00 | 1.00 | 1.00 | 1.00 |
| Moderate | 1.12 (0.47–2.66) | 1.31 (0.51–3.42) | 3.51 (1.64–9.15) | 1.36 (0.58–3.19) |
| High | 1.76 (0.70–4.47) | 1.42 (0.52–3.88) | 2.61 (0.97–6.97) | 1.61 (0.67–3.86) |
| Safety | ||||
| Low | 1.00 | 1.00 | 1.00 | 1.00 |
| Moderate | 0.66 (0.26–1.63) | 0.69 (0.26–1.84) | 1.68 (0.65–4.33) | 0.74 (0.31–1.76) |
| High | 1.09 (0.40–2.96) | 2.64 (0.90–7.82) | 1.13 (0.40–3.19) | 0.56 (0.22–1.45) |
| Weather | ||||
| Strong influence | 1.00 | 1.00 | 1.00 | 1.00 |
| Moderate | 1.93 (0.86–4.36) | 1.03 (0.45–2.36) | 0.62 (0.65–4.33) | 0.77 (0.35–1.72) |
| Not an influence | 3.84 (1.68–8.77) | 7.68 (3.03–19.46) | 0.93 (0.41–2.07) | 0.73 (0.34–1.57) |
| Age | ||||
| 40–59 years | 1.00 | 1.00 | 1.00 | 1.00 |
| ≥60 years | 1.06 (0.52–2.16) | 0.45 (0.21–1.00) | 0.41 (0.19–0.87) | 1.00 (0.51–1.96) |
CI, confidence interval.
* p < 0.05.
** p < 0.01.
*** p < 0.001.
Walking for exercise
Men with a high score on aesthetics were nearly four times as likely, and those with the highest scores for weather (weather did not inhibit) were nearly six times more likely to walk for exercise (Table 3). For women, those with the highest score for weather were over seven times more likely to walk for exercise (Table 4). Whether men or women lived in a coastal location was not associated with more walking for exercise.
Walking for pleasure and to get to and from places
Men who perceived their environment as highly safe for walking were less likely to walk for pleasure (odds ratio [OR]=0.22, 95% confidence interval [CI], 0.06–0.78, p <0.05; Table 3). Age was also found to be associated with walking for men. Men aged ≥60 years were less likely to walk for pleasure (OR=0.33, CI, 0.14–0.80, p <0.05). Women (Table 4) with moderately positive perceptions about accessibility were more than three times more likely to walk for pleasure (OR=3.51, CI, 1.64–9.15, p <0.01), and women aged ≥60 were less likely to walk for pleasure (OR=0.41, CI, 0.19–0.87, p <0.05). These findings on women's walking for pleasure need to be viewed with caution as the logistic regression model reported borderline significance (χ2=20.87, p =0.052). The logistic regression model found neither perceived environmental attributes nor location to be associated with walking to get to and from places.
Discussion
Ecologic models of health behavior suggest that different environmental attributes may be associated with different physical activity behaviors.
4
, 6
This may apply to the same behavior performed for different purposes, such as walking.14
In this study, different environmental attributes were related to the different types of walking. Weather, aesthetics, accessibility, and location were associated with neighborhood walking. Weather and aesthetics were found to be associated with walking for exercise. Safety and accessibility were associated with walking for pleasure. This study supports the need to focus the broad framework of ecologic models into models for specific behaviors. By exploring behavior as specifically as possible, and not using total or generic measures of activity, more can be learned about the environment–behavior relationship. Further studies are needed on the development of appropriate measures for specific environmental attributes to build our understanding of these relationships.Safety did not prove to be an important influence on neighborhood or exercise walking for this sample of adults. This could be attributable to participants perceiving that they live in a low-crime area. An unexpected finding was that, of the four perceived environment factors, weather demonstrated the strongest association with walking for both men and women. Those participants who reported the weather as not inhibiting their walking were most likely to participate in high levels of neighborhood and exercise walking. Although the weather is often reported as a barrier to physical activity, few studies have examined this variable using multivariate models. If the strong association of perceptions of the influence of the weather can be found in other samples, this may have some implications for the promotion of physical activity. This potential determinant is not modifiable, although individual perceptions about the influence of weather may be.
The strong relationship of coastal location with neighborhood walking for women is puzzling, particularly because of the weak associations found for perceived environmental attributes. The location attribute is objectively measured and the environmental attributes are perceptions; this could perhaps be an important difference. In a previous study,
20
the location association was found for men. The gender difference in the findings of the two studies may be related to the age differences of the two samples. In the previous study the mean age was 43 years with very few participants aged >60 years, whereas in this study, the mean age was 60 years. In this sample, a larger proportion of participants aged >60 years live in a coastal location as compared to those aged <60 years. Environmental influences on walking may change for men and women with increasing age and retirement from work.Although not the main focus of this study, significant association of age with walking for pleasure was found for both men and women. But, contrary to might be expected, those aged >60 years were less likely to walk for pleasure. It may be that around retirement age and older, walking may be perceived as being more for the purpose of exercise for health reasons, as it is often the advice given by general practitioners to reduce risk factors for disease.
Australian adults have been found to be more active in coastal locations, but the reasons for this are unknown. The categories of environmental attributes used in this study did not explain the variations in walking by coastal and noncoastal participants. The specific beach or lake within easy walking distance item was found to be associated with increased neighborhood, exercise, and pleasure walking. This relationship of access to water and increased walking adds further evidence of the coastal hypothesis,
24
although it is not clear if this is the result of better aesthetics rather than better access.Limitations of this study are its cross-sectional design, reliance on self-report of walking and perceptions of environmental attributes, the relatively low response rate, and the potential for cognitive overlap in the reporting of walking for different purposes. Participants may also have unintentionally overstated their levels of walking with this multiple measurement of walking format. Even with these limitations, consistent associations in this and other studies, particularly for aesthetics, implies the possibility of a causal relationship. A further limitation may have been the primarily coastal region. The geographical nature of this district is that of a long narrow strip between the mountains and the coastline, resulting in limited variation in the environment and possibly a generally more aesthetic appeal overall. While this may have limited the variation in the sample, at this stage of research into environment–physical activity relationships, these findings add to the growing knowledge base.
Future studies could include measures of perceptions of the environment, and additionally, objectively assessed measures derived from geographic information systems (e.g., housing density, road data).
12
, 14
Measuring both perceived and objective variables may shed light on whether it is the actual supports for physical activity that are accessible in the local environment or perceptions of the environment for physical activity that are most likely to influence behavior.Although modest, the associations identified in this study do add to the body of data on the influence of perceived environmental attributes on walking. The gender differences observed emphasize that different aspects of the environment may be of differing importance for men and women. Prospective studies are needed to determine whether the cross-sectional associations of environmental attributes with physical activity that have so far been reported are likely to be cause–effect relationships.
25
Public health approaches to increasing physical activity might consider strategies that focus on the importance of particular attributes of local environments that may impact on particular physical activity behaviors such as walking. Innovative strategies are particularly needed in countries like Australia, where adults' physical activity levels are declining.
26
Acknowledgements
This study was supported by Carelink, a division of the Australian Health Management Group, a registered health benefits organization.
Appendix.
Tabled
1
| Perceived environmental attributes measured in the study, factor groupings, and response options |
|---|
 |
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Article Info
Footnotes
☆The full text of this article is available at AJPM Online via http://www.ajpm-online.net.
Identification
Copyright
© 2004 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
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