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. Author manuscript; available in PMC: 2019 Nov 1.
Published in final edited form as: Prev Med. 2018 Aug 6;116:60–67. doi: 10.1016/j.ypmed.2018.08.008

Neighborhood walkability and physical activity among older women: Tests of mediation by environmental perceptions and moderation by depressive symptoms☆

Stephanie L Orstad a,*, Meghan H McDonough b, Peter James c, David B Klenosky d, Francine Laden c,e,f, Marifran Mattson g, Philip J Troped h
PMCID: PMC6260982  NIHMSID: NIHMS1506185  PMID: 30092314

Abstract

Features that enhance neighborhood walkability (higher population density, street connectivity and access to destinations) are associated with higher levels of physical activity among older adults. The perceived neighborhood environment appears to mediate associations between the objective built environment and physical activity. The role of depressed mood in these associations is poorly understood. We examined the degree to which depressive symptoms moderated indirect associations between the objective neighborhood environment and physical activity via the perceived neighborhood environment in older women. We analyzed data on 60,133 women (mean age = 73.1 ± 6.7 years) in the U.S. Nurses’ Health Study cohort who completed the 2008 questionnaire. Self-reported measures included the Geriatric Depression Scale, perceived presence of recreational facilities, retail destinations, sidewalks, and crime, and participation in recreational physical activity and neighborhood walking. We created an objective walkability index by summing z-scores of intersection and facility counts within 1200-meter residential network buffers and census tract-level population density. We used multiple regression with bootstrap-generated 95% bias-corrected confidence intervals (BC CIs) to test for mediation and moderated mediation. Objective walkability was associated with 1.99 times greater odds of neighborhood walking (95% BC CI = 1.92, 2.06) and 1.38 times greater odds of meeting physical activity recommendations (95% BC CI = 1.34, 1.43) via the perceived neighborhood environment. These indirect associations were weaker among women with higher depressive symptom scores. Positive associations between objective neighborhood walkability and physical activities such as walking among older women may be strengthened with a reduction in their depressive symptoms.

1. Introduction

Physically active older adults have a lower risk for many chronic health conditions compared to those who are less physically active (Nelson et al., 2007; Chodzko-Zajko et al., 2009). They also live with fewer functional limitations (e.g., in walking or activities of daily living) and greater health-related quality of life (Motl and McAuley, 2010). Conceptual models and empirical evidence suggest that as adults age and their mobility worsens, the design of their neighborhood becomes particularly important in attenuating declines in physical function (Glass and Balfour, 2003; Clarke and George, 2005; Yen et al., 2009; Balfour and Kaplan, 2002; King et al., 2011; Eronen et al., 2014). Older adults who live in more walkable neighborhoods, characterized by higher population density, street connectivity, and access to destinations (Cervero and Kockelman, 1997; Frank et al., 2010), engage in more moderate-vigorous physical activity (MVPA) (King et al., 2011; Van Holle et al., 2014, 2015; Carlson et al., 2012) and walk more for leisure and transport (King et al., 2011; Van Holle et al., 2014, 2015; Carlson et al., 2012; Kerr et al., 2014; Winters et al., 2015; Berke et al., 2007; Nagel et al., 2008; Gauvin et al., 2012; Troped et al., 2014; Nathan et al., 2014) compared to those who live in less walkable neighborhoods. Also, perceived proximity to retail destinations (Shigematsu et al., 2009), access to recreation facilities (Shigematsu et al., 2009; Li et al., 2005; Adams et al., 2012), and safety from traffic and crime (Li et al., 2005) have been associated with walking among older adults.

Objective and perceived neighborhood environment measures that assess conceptually comparable features (e.g., self-reported and GIS-based park proximity) exhibit low agreement, suggesting they may capture related but distinct constructs that predict unique variance in the same physical activity outcome (Sallis, 2009; Nasar, 2008; Orstad et al., 2016). Ecological models of health behavior suggest environmental perceptions mediate associations between the objective built environment and physical activity (King et al., 2002; Sallis et al., 2008; Ewing and Handy, 2009; Ding and Gebel, 2012). However, few studies examining associations between objective walkability and physical activity among older adults have examined mediation by the perceived neighborhood environment (Carlson et al., 2012; Ding et al., 2014). The few studies conducted have demonstrated that perceived access to retail destinations and places to be physically active mediate associations between objective measures of intersection and destination density and walking for transport (Koohsari et al., 2014; Van Dyck et al., 2013).

Depression affects up to 13.5% of older U.S. adults, and older women are particularly susceptible (CDC, 2015; Barry et al., 2008). While physical activity can alleviate depressive symptoms (Rosenbaum et al., 2014; Conn, 2010; Krogh et al., 2011; Huang et al., 2015), prospective associations between physical activity and depressive symptoms appear to be bidirectional (Lindwall et al., 2011). That is, older adults with clinically diagnosed depression (Wassink-Vossen et al., 2014; Morey et al., 2003; McKee et al., 2015) or higher levels of depressive symptoms (Krämer et al., 2014a; Wilcox et al., 2003; van Gool et al., 2003; Shaw and Spokane, 2008) engage in less physical activity, which may further increase chronic disease risk. Depression may impact adults’ physical activity through lower levels of motivation (e.g., behavioral intention) and volitional capacities (i.e., ability to transform their intention into behavior) (Krämer et al., 2014a,b; Scarapicchia et al., 2014). Since environmental perceptions form through cognitive, affective, and social processes (Nasar, 2008; Bandura, 1978; Davies, 2009), depressive symptoms may also influence physical activity by interacting with individuals’ perceptions of their neighborhood environment. For example, individuals with more distress, hopelessness, or depressed mood report worse perceptions of their neighborhood than those with less depressed mood (Bailey et al., 2014), even when controlling for objective neighborhood features (Latkin et al., 2009; Mair et al., 2012; Kamphuis et al., 2010). As a result, depressive symptoms may dampen positive associations between neighborhood walkability and physical activity.

We examined whether objective measures of neighborhood walkability were 1) directly associated with neighborhood walking and meeting physical activity recommendations, and 2) indirectly associated with neighborhood walking and meeting physical activity recommendations via the perceived neighborhood environment, among older U.S. women. We also examined the degree to which depressive symptoms moderated these direct and indirect associations (see Fig. 1 for conceptual framework).

Fig. 1.

Fig. 1.

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Conceptual model of indirect and direct associations between objective neighborhood walkability and physical activity outcomes moderated by depressive symptoms among U.S. women nurses in 2008.

Note: Model depicts perceived neighborhood environment as a potential mediator of the association between objective neighborhood walkability and physical activity.

2. Methods

2.1. Study design and sample

For this cross-sectional analysis we examined data in 2013 from the Nurses’ Health Study (NHS), a prospective cohort study of registered nurses across the United States (Belanger et al., 1978). The NHS originated in 1976 with over 121,700 women to examine risk factors for breast cancer and other chronic diseases. Participants complete a questionnaire every two years and response rates are approximately 90% over follow-up. The 2008 questionnaire included questions on the perceived neighborhood environment. We included women (N = 60,133) who completed the 2008 questionnaire and had complete data for key study variables. We excluded women who were unable to walk and/or who were in an assisted living facility or nursing home. Human research protection committees at Brigham and Women’s Hospital and Purdue University approved study protocols.

2.2. Measures

2.2.1. Physical activity

We examined two physical activity outcomes. Neighborhood walking was based on the item, “I walk around my neighborhood twice a week or more for leisure or exercise (yes/no).” Meeting physical activity recommendations was derived from the question, “During the past year, what was your average time per week spent at each of the following recreational activities?” Response options ranged from 0 to ≥11 h/week. Activities included walking, jogging, running, bicycling, racquet sports, swimming, stair climbing, aerobics/dance, weight training and other vigorous activities. Consistent with prior NHS analyses, a metabolic equivalent task (MET) value was assigned to each activity (Ainsworth et al., 2000, 2011). MET values were assigned to walking based on usual walking pace outdoors (< 2 mph = 0, 2–2.9 mph = 3.0, 3–3.9 mph = 4.0, and ≥4 mph = 4.5). Activities of less-than-moderate intensity (i.e., < 3.0 METs) were excluded. We multiplied MET values by the midpoint of the range of hours reported for a given activity (e.g., 2–3 h = 2.5 h) to calculate MET hours/week. We multiplied the total MET hours/week across all activities by 60 to yield the average MET minutes/week of recreational physical activity. We then created a binary outcome (< 500 versus ≥500 MET min/ week, the latter which approximates the recommended 150 min of moderate-vigorous intensity physical activity per week) (Buchner et al., 2008). NHS physical activity items have adequate two-year reproducibility and validity compared to seven-day physical activity diaries (Wolf et al., 1994).

2.2.2. Objective neighborhood walkability

We used geographic information systems (GIS) data and software to measure neighborhood walkability. Consistent with prior NHS analyses demonstrating associations between walkability and physical activity (Troped et al., 2014), we created a 1200-meter line-based road network buffer around each geocoded home address. A line-based or “sausage” buffer refers to the resulting shape when a line is traced a set distance on either side of a street and extends a certain distance along the street network from a starting point (Oliver et al., 2007; Forsyth et al., 2012). Using a line-based buffer delimits the observations to areas accessible by walking. Highways and on-ramps were excluded from the observed road network. We used a 1200-meter buffer because the results of a sensitivity analysis suggest that it is the most relevant spatial context for physical activity in the NHSII cohort (James et al., 2014). The walkability index (James et al., 2015a) was derived by z-transforming and summing scores from three variables shown to support pedestrian behavior: intersection count, facility count, and population density (Cervero and Kockelman, 1997; Lovasi et al., 2012). Intersection count, defined as the number of three-way or greater intersections within the buffer, was derived from ArcGIS StreetMap USA™ road network data (Environmental Systems Research Institute, Inc., 2008). Higher values indicate a more connected street network. Facility count (number of facilities within the buffer) was derived from the ArcGIS 2009 InfoUSA™ public and commercial facilities database, which includes retail, food, service, cultural, recreational, and other establishments. InfoUSA™ and similar databases have shown good validity when facilities were verified on-site (James et al., 2014; Paquet et al., 2008). Higher values indicate a greater mix of residential and commercial land use, more walking destinations, and more places for active recreation. Population density was defined as the number of persons per square mile within the census tract of residence during the 2000 U.S. Census.

2.2.3. Perceived neighborhood environment

Women responded yes or no to four statements adapted from the Physical Activity Neighborhood Environment Survey (PANES) about the presence of “free or low cost recreation facilities”, “shops, stores, and markets”, “sidewalks on most streets”, and “the crime rate makes it unsafe” (Alexander et al., 2006). The PANES has demonstrated good test-retest reliability (Alexander et al., 2006) and construct validity (Sallis et al., 2009). We reverse coded the crime item so that a “no” response indicated a favorable perception of safety. We created a composite measure of the perceived neighborhood environment by summing the number of favorable responses, with values ranging from 0 to 4; an approach utilized in previous research (Troped et al., 2011).

2.2.4. Depressive symptoms

Women responded to the 15-item Geriatric Depression Scale (GDS-15), a valid and reliable measure of depressive symptomology in the older adult population (Korner et al., 2006). Women were prompted to choose the best answer (yes/no) for how they felt during the past month regarding a list of 15 clinically relevant symptoms. A score ≥5 may suggest clinical depression (Almeida and Almeida, 1999). However, because depressive symptoms may also influence neighborhood perceptions at subclinical levels (Latkin et al., 2009), we used a continuous scale (0–15) to capture the depressive symptomology represented in non-clinical populations.

2.2.5. Covariates

We controlled for demographic and health-related covariates that may confound associations between objective and perceived neighborhood environment, depressive symptoms, and physical activity. Covariates were age, race, Hispanic ethnicity, nurse’s education, husband’s education, marital status, employment status, body mass index (BMI; kg/m2), and previous chronic disease (i.e., cancer, diabetes or heart disease). Since socioeconomic status is an important factor in health status, we considered nurse’s and husband’s education to reflect household income and adjusted for census tract-level household income, a proxy for neighborhood socioeconomic status. To account for the potential influence of missing data, we created indicator variables for covariates with missing observations.

2.3. Statistical analysis

The data met the assumptions of multivariate analysis, including linearity and homoscedasticity, except that logarithmic (log10) transformation of the walkability index was necessary to address positive skewness and ensure that residuals were normally distributed (Tabachnick and Fidell, 2013). No multicollinearity among predictor variables was detected. We used multiple linear regression (Hayes, 2013; Preacher et al., 2007) with objective walkability as the independent variable, perceived neighborhood environment as the mediator, depressive symptoms as the moderator, and neighborhood walking and meeting physical activity recommendations as the outcomes. We also conducted a sensitivity analysis to separately examine associations between the three objective built environment variables that comprised the walkability index and each physical activity outcome.

To test for mediation we used bootstrap resampling (k = 5000) with 95% bias-corrected confidence intervals (BC CIs) of the indirect effects using PROCESS© v2.13 for SAS® 9.3 (Hayes, 2013). A BC CI that did not include zero indicated statistically significant mediation. To determine which mediation pathways were moderated by depressive symptoms, we examined a preliminary model in which depressive symptoms moderated all pathways in the model (see Fig. 1). If an effect was not moderated (i.e., p ≥ .05 for the interaction term), we removed the nonsignificant interaction term from the model (Hayes, 2013). We repeated this process until only statistically significant interaction terms remained. Since the final models contained a significant interaction term, we employed a parameter estimate of the function linking the indirect effect to values of depressive symptoms called the index of moderated mediation (Hayes, 2015). A BC CI that did not include zero for the index of moderated mediation indicated that an indirect effect significantly varied across levels of depressive symptoms (Hayes, 2015).

We tested and plotted moderated indirect and direct effects at the M ± 1SD of depressive symptoms. Since the M − 1SD was outside of the range of data, we used the minimum value (0) instead (data not shown). We employed the Johnson-Neyman technique to identify the value of depressive symptoms at which a moderated association transitioned from nonsignificant to statistically significant (Hayes, 2013). All variables in the interaction terms were mean-centered prior to analysis. We reported unstandardized regression weights for associations with perceived neighborhood environment, and the exponents of unstandardized logistic regression coefficients (i.e., odds ratios) for associations with the two dichotomous physical activity outcomes.

3. Results

As shown in Table 1, participants’ average age was 73.1 ± 6.7 years. The majority of women were white, married, and not working outside of the home. About 50% did not meet physical activity recommendations, 20.1% were obese (BMI ≥ 30) and 38.5% had a history of chronic disease. Eight percent reported depressive symptom scores suggestive of mild clinical depression or higher (≥5). Supplemental Table 1 shows means and Pearson correlations among study variables.

Table 1.

Demographic and health-related characteristics of 60,133 U.S. women nurses in 2008.

Variables Number (proportion)
All participants		 Number (proportion)
Walkers < 2 times/week		 Number (proportion)
Walkers ≥ 2 times/week
N 60,133 33,211 26,922
Age (years) (M ± SD; range) M = 73.1 ± 6.7;
Range = 61.5–88.8		 M = 73.6 ± 6.8;
Range = 61.5–88.8		 M = 72.5 ± 6.5;
Range = 61.5–88.5
Race/ethnicity
 White 58,675 (97.6) 32,346 (97.4) 26,329 (97.8)
 Black 792 (1.3) 518 (1.6) 274 (1.0)
 Asian 489 (0.8) 242 (0.7) 247 (0.9)
 Othera 177 (0.3) 105 (0.3) 72 (0.3)
Hispanic/Latino
 Yes 528 (0.9) 299 (0.9) 229 (0.9)
Education
 Registered nurse 36,842 (61.3) 21,150 (63.7) 15,692 (58.3)
 Bachelors 11,498 (19.1) 5900 (17.8) 5598 (20.8)
 Masters 5205 (8.7) 2566 (7.7) 2639 (9.8)
 Doctorate 597 (1.0) 274 (0.8) 323 (1.2)
 Not reported 5991 (10.0) 3321 (10.0) 2670 (9.9)
Husband’s education
 High school graduate or less 20,048 (33.3) 12,139 (36.6) 7909 (29.4)
 College graduate 13,799 (23.0) 7330 (22.1) 6469 (24.0)
 Graduate school 11,877 (19.8) 5855 (17.6) 6022 (22.4)
 Not reported or not married 14,409 (24.0) 7887 (23.8) 6522 (24.2)
Marital status
 Married or domestic partner 39,054 (65.0) 21,016 (63.3) 18,038 (67.0)
 Divorced or separated 4765 (7.9) 2548 (7.7) 2217 (8.2)
 Widowed 16,162 (26.9) 9561 (28.8) 6601 (24.5)
 Not reported or never married 152 (0.3) 86 (0.3) 66 (0.2)
Employment status
 Retired or homemaker 49,169 (81.8) 27,131 (81.7) 22,038 (81.9)
 Working full- or part-time 10,566 (17.6) 5806 (17.5) 4760 (17.7)
 Not reported 398 (0.7) 274 (0.8) 124 (0.5)
Census tract-level median household income (M ± SD; range) M = $63,504 ± 23,725;
Range = $0–200,001		 M = $62,339 ± 22,972;
Range = $0–200,001		 M = $64,942 ± 24,548;
Range = $0–200,001
Body mass index (BMI)
 < 30 43,198 (71.8) 22,032 (66.3) 21,166 (78.6)
 ≥30 12,074 (20.1) 8456 (25.5) 3618 (13.4)
 Not reported 4861 (8.1) 2723 (8.2) 2138 (7.9)
Previous chronic diseaseb
 Yes 23,124 (38.5) 13,738 (41.4) 9386 (34.9)
Depressive symptomsc
 < 5 55,312 (92.0) 29,785 (89.7) 25,527 (94.8)
 ≥5 4821 (8.0) 3426 (10.3) 1395 (5.2)
Recreational physical activity
 Meeting recommendationsd 29,784 (49.5) 11,922 (35.9) 9060 (33.7)
 Not meeting recommendations 30,349 (50.5) 21,289 (64.1) 17,862 (66.4)
Neighborhood walking
 < 2 times/week 33,211 (55.2) 33,211 (100.0) 0 (0.0)
 ≥2 times/week 26,922 (44.8) 0 (0.0) 26,922 (100.0)
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Notes: Proportions may not total 100.0 due to rounding to the nearest tenth of a percentage.

a

Other category includes American Indian and Hawaiian.

b

Includes self-reported prior incidence of clinician-diagnosed cancer, diabetes and/or heart disease.

c

A Geriatric Depression Scale (GDS-15) score ≥5 may suggest clinical depression.

d

Based on an average of ≥500 MET min/week, which approximates the recommended 150 min of moderate-vigorous intensity physical activity per week.

3.1. Associations between objective neighborhood walkability and physical activity outcomes via perceived neighborhood environment

3.1.1. Neighborhood walking

The odds of a woman walking in her neighborhood was two times the odds of a woman whose neighborhood was one unit lower in objective walkability via perceptions of the neighborhood environment (95% BC CI = 1.92, 2.06). As shown in Fig. 2, a one unit higher objective walkability score was associated with a 1.59 (out of 4) point higher perceived neighborhood environment score (95% CI = 1.56,1.63). In turn, having more positive perceptions was associated with 1.54 times greater odds of neighborhood walking (95% CI = 1.51, 1.57). This positive indirect association between objective walkability and neighborhood walking via perceived neighborhood environment seemed to be driven largely by significant positive indirect associations between two of the three walkability components (facility count and population density) and neighborhood walking via perceived neighborhood environment, whereas intersection count was not significantly indirectly associated with neighborhood walking (Supplemental Table 2).

Fig. 2.

Fig. 2.

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Direct associations between objective neighborhood walkability, perceived neighborhood environment, and neighborhood walking among U.S. women nurses in 2008.

Notes: Unstandardized regression weights (B) and the exponents of unstandardized logistic regression coefficients or odds ratios (OR) reported. Neighborhood walking defined as < 2 times or ≥2 times per week. Model adjusted for age, race, Hispanic ethnicity, nurse’s education, husband’s education, marital status, employment status, body mass index, previous chronic disease, and census tract-level household income.

*Significant direct effect, tested using 95% confidence intervals (95% CIs) or significant indirect effect, tested using 95% bias-corrected confidence intervals (95% BC CIs).

Depressive symptoms significantly moderated the indirect association between objective walkability and neighborhood walking via perceived neighborhood environment (index of moderated mediation = −0.02; SE = 0.00; 95% BC CI = −0.03, −0.02). The Johnson-Neyman technique, which indicated the value of depressive symptoms at which an association transitioned from nonsignificant to statistically significant, showed that this indirect association was statistically significant throughout the range of depressive symptoms. As shown in Fig. 2, women who lived in more walkable neighborhoods tended to have more positive perceptions of their neighborhood for physical activity than women who lived in less walkable neighborhoods, however, this positive association was weaker among those with higher depressive symptom scores (βwalkability×depressive = −0.05, SE = 0.01; p < .0001). In turn, a woman’s positive perceptions did not translate to greater odds of neighborhood walking to the same extent as other women living in the neighborhood if she reported higher depressive symptoms. In addition, among the 8.0% of women with depressive symptoms scores > 4.05 (which approach levels suggestive of mild clinical depression), intersection count was inversely associated with perceived neighborhood environment scores.

3.1.2. Meeting physical activity recommendations

The odds of a woman meeting physical activity recommendations was 1.38 times the odds of a woman whose neighborhood was one unit lower in objective walkability via perceptions of the neighborhood environment (95% BC CI = 1.34, 1.43). As shown in Fig. 3, a one unit higher objective walkability score was associated with a 1.59 point higher perceived neighborhood environment score (95% CI = 1.56, 1.63) which, in turn, was associated with 1.23 times greater odds of meeting physical activity recommendations (95% CI = 1.20, 1.25).

Fig. 3.

Fig. 3.

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Direct associations between objective neighborhood walkability, perceived neighborhood environment, and meeting physical activity recommendations among U.S. women nurses in 2008. Notes: Unstandardized regression weights (B) and the exponents of unstandardized logistic regression coefficients or odds ratios (OR) reported. Meeting physical activity recommendations defined as weekly average of < 500 or ≥500 MET minutes. Model adjusted for age, race, Hispanic ethnicity, nurse’s education, husband’s education, marital status, employment status, body mass index, previous chronic disease, and census tract-level household income.

*Significant direct effect, tested using 95% confidence intervals (95% CIs) or significant indirect effect, tested using 95% bias-corrected confidence intervals (95% BC CIs).

Depressive symptoms significantly moderated the indirect association between objective walkability and meeting physical activity recommendations (index of moderated mediation = −0.01; SE = 0.00; 95% BC CI = −0.01, −0.01). This indirect association was statistically significant throughout the range of depressive symptoms. As shown in Fig. 3, women who lived in more walkable neighborhoods tended to have more positive perceptions of their neighborhood than women who lived in less walkable neighborhoods, however, this positive association was weaker among those with higher depressive symptom scores (βwalkability×depressive = −0.05, SE = 0.01; p < .0001). In turn, a woman’s positive perceptions did not translate to greater odds of meeting physical activity recommendations to the same extent as other women living in the neighborhood if she experienced higher depressive symptoms.

3.2. Direct associations between objective neighborhood walkability and physical activity outcomes

A one unit higher objective walkability score was associated with 16% lower odds of neighborhood walking (OR = 0.84; 95% CI = 0.78, 0.92; see Fig. 2) and 39% lower odds of meeting physical activity recommendations (OR = 0.61; 95% CI = 0.56, 0.66; see Fig. 3), controlling for perceived neighborhood environment. The aforementioned indirect associations between objective walkability and both physical activity outcomes via perceptions were positive. However, because the direct associations between objective walkability and both physical activity outcomes held the opposite sign, perceived neighborhood environment acted as a suppressor rather than a mediator of these direct associations, suggesting that including perceptions in the model enhanced rather than attenuated the predictive validity of these inverse associations (MacKinnon et al., 2000). When perceptions and the significant interaction term were not in the models, the magnitude of positive associations between objective walkability and physical activity outcomes was greater. That is, the association between objective walkability and neighborhood walking was positive (OR = 1.71; 95% CI = 1.58, 1.85), and the inverse association between objective walkability and meeting physical activity recommendations was attenuated (OR = 0.86; 95% CI = 0.80, 0.93). Thus, perceived neighborhood environment as a mediator may explain positive but did not explain inverse associations between objective walkability and these physical activity outcomes.

4. Discussion

In recent studies, greater objective destination density (Van Dyck et al., 2013; Gebel et al., 2011), population density (Gebel et al., 2011), and street connectivity (Koohsari et al., 2014; Van Dyck et al., 2013; Gebel et al., 2011) were indirectly associated with walking for transportation via the perceived neighborhood environment. In the present study, greater objective walkability, facility counts, and population density (but not intersection count) were significantly associated with neighborhood walking and physical activity for recreation via the perceived neighborhood environment. These findings are consistent with a recent review in which objective access to destinations and residential density (but not street connectivity) were associated with total walking and physical activity among older adults (D.W. Barnett et al., 2017). The nonsignificance of intersection count in this study may be because we examined physical activity for recreation purposes as opposed to active transportation, and connectivity has been consistently associated with active transportation in adults (Bauman et al., 2012). However, even in studies examining correlates of active transport, street connectivity may be a facilitator rather than an essential factor for older adults (Cerin et al., 2017). Collectively with other recent studies (Troped et al., 2016; Orstad et al., 2017; Cerin et al., 2018), these findings begin to build an evidence base for the mediating role of environmental perceptions in associations between aspects of objectively-measured walkability and physical activity for transportation and recreation.

Women with depressed mood may use public spaces differently, thus accumulate experiences of their neighborhood that are different than residents without depressed mood (Wallace et al., 2015). The weaker positive association between objective walkability and perceived neighborhood environment, and the inverse association in the case of intersection count, among women with higher depressive symptoms may be explained by heightened perceptions of traffic danger, poor aesthetics, and unsafe or insufficient sidewalk space in highly connected areas. These processes may have consequences for physical activity levels among older women, as suggested by weaker indirect associations with physical activity outcomes. The extent to which women have favorable perceptions of their neighborhood and engage in physical activity, whether they live in low- or high-walkable neighborhoods (Gebel et al., 2011; Cerin et al., 2017; Koohsari et al., 2015), may depend in part on the supports available to alleviate depressive symptoms. Further research is warranted to examine the extent to which depressive symptoms moderate these associations in older men and other groups. Such research can inform comprehensive physical activity interventions that incorporate built environment and cognitive strategies to enhance perceptions of the neighborhood environment for physical activity and reduce symptoms of depression.

In this study, a composite measure of perceived recreation facilities, retail destinations, sidewalks, and crime significantly suppressed (“enhanced”) inverse associations between objective walkability and physical activity outcomes. In one previous study of women, a seven-item perceived neighborhood environment scale (e.g., recreational facilities, ease of walking, and presence of other active people) also suppressed the association between a composite measure of objective connectivity and destination density and leisure-time walking, while perceptions of poor aesthetics, low personal safety, and low social cohesion mediated the association (Van Dyck et al., 2013). Older women who live in objectively walkable areas may perceive certain aspects of their neighborhood favorably, such as access to retail destinations (Koohsari et al., 2014; Jack and McCormack, 2014) and recreation facilities (Van Dyck et al., 2013; Jack and McCormack, 2014). Perhaps more vulnerable to safety hazards than younger woman, they may perceive other aspects of walkable areas less favorably, such as aesthetics (Van Dyck et al., 2013; Borst et al., 2008) and safety from traffic (Jack and McCormack, 2014) and crime (Van Dyck et al., 2013; Jack and McCormack, 2014). Sufficient evidence suggests perceived aesthetics and traffic and personal safety are consistently positively associated with total walking among older adults (D.W. Barnett et al., 2017). Therefore, this study’s inverse associations may be accounting for relevant perceptions (i.e., aesthetics and traffic safety) that were not examined. Future research should consider the ways in which older women interpret and perceive neighborhood aesthetics, traffic danger, disorder, and the condition of sidewalks, parks, and recreation facilities, which seem to be important for leisure walking even when objective conditions of walkability are met.

4.1. Strengths and limitations

Strengths of this study include the large national sample of older women living in communities ranging from urban to rural, the inclusion of the objective and perceived neighborhood environment in conceptual and statistical models, the focus on correlates of neighborhoodbased physical activity for specific recreational purposes, and the examination of depressive symptoms in physical activity and built environment research. The cross-sectional study design precludes us from making causal inferences or identifying the direction of associations. Not all potential pathways among the neighborhood environment, physical activity and depression were examined. For example, neighborhood attributes such as low SES and high crime rates are associated with depression in older adults (A. Barnett et al., 2017). Therefore, we controlled for neighborhood SES to account for some of the variance in depressive symptoms potentially explained by the environment. Women’s anxiety symptoms, which are co-morbid with depressive symptoms, were not accounted for in this study; thus, future examination of the moderating role of anxiety is needed. Women’s past experiences in their neighborhoods and vehicle ownership were not assessed as potential confounders. Nor was residential self-selection, though not considered a major source of bias in the NHS cohort (James et al., 2015b). Self-reported walking and physical activity measures may have overestimated physical activity behavior. The use of a perceived neighborhood environment measure that was not a close match conceptually to the walkability index may have underestimated indirect associations with physical activity. The use of a composite walkability measure limits practical application of these findings to built environmental and policy interventions to promote physical activity among older adults. Future studies are needed to identify innovative ways to measure the built environment that can be readily translated into action by urban planners and public health professionals. Low-income neighborhoods and other racial/ethnic minority groups are not well represented in this sample of women with nursing degrees, which may affect the generalizability of these findings to marginalized populations.

5. Conclusion

This study’s findings indicate that older women who live in objectively more walkable neighborhoods tend to have more positive perceptions and, in turn, are more active than women who live in less walkable neighborhoods. However, even subclinical levels of depressive symptoms may dampen positive associations between objective walkability and physical activity via perceptions of their neighborhood. Therefore, depressive symptoms should be factored into conceptual models that explain older adults’ physical activity and when developing physical activity interventions for older women.

Supplementary Material

1

Acknowledgments

We thank Dr. Olivia Okereke, MD, MS, for her helpful comments at early stages of this analysis.

Funding

This research was supported by the National Institutes of Health; grants R00 CA201542, R01 ES017017, and UM1 CA186107. This study was also supported by the Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School and internal research funding from the University of Massachusetts Boston.

Footnotes

☆

The authors of this paper report no conflicts of interest or financial disclosures.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.ypmed.2018.08.008.

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