Abstract
Background
Walking is an essential activity for everyone and for older adults in particular, given that it is the most accessible form of physical activity and one of the healthiest transportation modes. Understanding how walkability (the potential of the environment to enable and/or encourage walking) has been objectively measured and analyzed for older adults is critical to create more inclusive, healthy, and sustainable environments and to promote healthy aging. Despite the numerous reviews on physical activity among older adults and its relationship with the built environment, the literature still lacks comparison reviews focusing specifically on objective operationalizations of walkability for older adults vs. the general population.
Methods
We conducted a systematic review of 146 empirical studies that measured walkability objectively in relation to walking-related outcomes. We compared studies focused on older adults (n = 24) and the general population (n = 122). Content analysis included the characteristics of the study design, walkability measures, spatial extent, and associations found between walkability and walking-related outcomes.
Results
In both groups of publications, the majority of studies were conducted in the US, Canada, and Europe, and largely in high-income countries. They were mostly published in health-related journals and used cross-sectional designs, operationalized walkability by using indexes, employed self-reported measures for walking-related outcomes, and found positive associations between walkability and walking outcomes. However, we observed some differences among studies focusing on older adults. Compared to studies focusing on the general population, a larger proportion of studies on older adults was conducted in the Middle East and Asia, and they used longitudinal designs, mixed methods to measure walking-related outcomes, variables related with land-use characteristics, safety from traffic and crime, and greenery, and a larger proportion found positive, as well as no associations between walkability and walking-related outcomes.
Conclusion
Although there is a promising increase in interest in older adults-focused walkability studies in the last decade, there is still a need for more studies focusing on different settings, using wider spatial extents, longitudinal designs, objective or mixed methods to collect outcome data, and specific variables and/or specially created indexes for older adults and for settings.
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Introduction
Walking is one of the most accessible, economically viable, democratic, communal, sustainable, environmentally friendly, and healthiest forms of transportation [1,2,3,4]. It is also the easiest way of including physical activity (PA) into daily life routines while helping to achieve recommendations for a physically and mentally healthy life (i.e., 150–300 minutes/ week of moderate-intensity activity for adults aged 18–64 years, and a minimum of 150 minutes/ week for persons ≥65 years) [5, 6]. Additionally, for specific population groups, such as older adults (≥65 years), walking is the most common, if not the only, type of PA [7]. Yet, engaging in this activity is related to various factors.
Among many other factors, walking depends on who is undertaking this activity (i.e., the characteristics of individuals). Some population groups, for instance, older adults, are less involved in this activity due to factors such as increased physical limitations compared to other age groups. Walking also depends on where it takes place, since the characteristics of an environment could encourage or limit this activity. Some environmental features, such as dimly lit streets, steps, steep hills, or broken pavements might become a barrier for walking among some groups such as older adults more than others [8], due to the decrease in the level of “individual competence” [9] to cope with the “environmental press” ([9], pp.25, [10], pp385–396). Thus, some environments could be more “walking-friendly” or walkable than others, for different types of individuals.
The definition of walkability varies vastly in the literature, and depends on “who is asking” [11] or personal perspective. The most common definition has been the walking/ pedestrian friendliness of a given place [12]. However, more detailed definitions such as how traversable, compact, safe, lively and sociable, physically enticing, or exercise-inducing an environment is, have also been used [13]. Walkability has also been defined as a complex and multidimensional concept, whose dimensions are measurable “individually or combined into an index” [13]. Studies measuring walkability of a place have received greater scholarly attention in the last decades in different countries, under the scope of various research fields, and using a wide array of variables and operationalization methods [14]. Many studies have associated walkability with PA outcomes, and while the results generally show a positive association between the two, variations for different pedestrian groups, such as children, adults, older adults, or impaired pedestrians, are also highlighted [12, 15]. Some studies have employed subjective measures (e.g., perceptions), while others have preferred measuring walkability objectively (e.g., by using Geographic Information Systems - GIS). Although some studies on adults presented partial agreement between subjective and objective measures of walkability [16], high misperception levels were also highlighted in other studies [17]. Studies on older adults that used objective measures in their analysis generally presented stronger associations [12, 18].
Various reviews on walkability studies have to date focused on how differently walkability is defined in the literature [11, 13], how it is operationalized, and how it could contribute to more PA engagement [19,20,21,22,23], or on the trends that walkability research has followed throughout the years [14]. Some reviews narrowed down their scope to specific groups such as adults [24] or children [15]. Despite the high importance of walking among older adults and theirs being the most sedentary group (with about 60 to 80% of their daily time spent physically inactive), to the best of our knowledge, none of the systematic reviews on the PA of older adults [25,26,27,28,29] focused specifically on walkability, but rather included various built environment characteristics in their studies. Only one systematic review focused on the relationship between walkability and the PA of older adults [30]; however, their specific aim was to examine the impacts of stairs on this relationship. Thus, we believe that there is a need for a systematic review which summarizes how objective walkability has been operationalized to date, its relationship with walking outcomes, and how these differed for older adults, for whom walking is particularly essential. By detecting the gaps in the literature, and summarizing the methodologies of previous studies, this review could help to inform future literature reviews and empirical analyses that share similar aims. Additionally, by highlighting how objective walkability measures differ for older adults compared to the general population, this review could also offer insight for urban designers, planners, and/or local governments.
Following this introduction, the next section provides a description of the methodology employed for this systematic literature review. Then in the results section, we first present the pattern of demographic groups included in all reviewed publications, and then we compare the descriptive results from papers focusing only on older adults and those exploring the general population. Finally, we discuss these results, and end the paper with concluding remarks.
Methods
Search strategy
This systematic review followed the PRISMA (Preferred Reporting Items of Systematic Review and Meta-Analysis) guidelines [31]. First, we defined a query logic based on keywords related to walkability and walking-related PA. Second, we ran initial tests in different databases, and conducted the final search on June 25, 2019, in three electronic databases: PubMed, Scopus, and Web of Science (WoS) (Fig. 1). In order to include the seminal publications meeting our criteria, we did not set a start date for the search.
PRISMA flow chart for systematic literature search and search terms used in the three databases
Inclusion and exclusion criteria
Papers were included only if they were, 1) focusing on measuring walkability (i.e., only those with an explicit mention of walkability in their titles or abstracts, methods, and results sections, excluding those using walkability only for sample recruitment, for instance); 2) measuring walkability objectively (with GIS, or environmental/ street audits conducted by trained people); 3) having subjectively or objectively measured (e.g., by using self-reports or accelerometers) walking-related outcomes (excluding those combining different types of PA, such as cycling, gardening, skating, etc., under one category such as total PA or active commuting); 4) relating these walking-related outcomes with walkability; 5) original empirical research published in peer-reviewed journals; and 6) written in English.
Study selection
Study selection was conducted in four phases for the first part of the review (Fig. 1). After removing the duplicates from the total records retrieved from the database search (n = 3279), we first included 2008 manuscripts in the phase of title screening and then abstract screening for relevance. According to the selection criteria, a total of 1625 papers were excluded at these phases. Then full texts of the remaining papers (n = 383) were reviewed. Given the detailed information gathered at this stage, a further 237 papers were excluded. Finally, the remaining 146 papers were included in the content analysis. For consistency, all phases were completed by the first author (ZSA). After each phase, the second and third authors (XDA and GV, respectively) individually screened a random selection of 20% of the publications to eliminate the risk of bias and confirm the correctness of the selection. In case of doubt or disagreement, discussions of the papers among the authors took place until a joint decision was made.
Data extraction and content analysis
For all included publications (n = 146) data were extracted and assessed under five main categories. The reasons and details of the categorization and coding used in these categories are explained briefly below, and in detail in Supplementary Material.
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1)
General study characteristics: Publication year, Journal field, Geographical context (study setting), Demographic group under study.
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2)
Characteristics of the study design: Research design (cross-sectional, longitudinal, or mixed), Spatial data collection method (GIS or audit), Outcome data collection method (objective, subjective, or mixed methods).
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3)
Characteristics of walkability measures: Operationalization of walkability (indexes or separate variables), Walkability variables used.
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4)
Spatial extent and unit: Spatial extent (residential area, school site, etc.), Spatial unit (administrative units, statistical units, buffers, etc.), Buffer type (circular, street network, or sausage buffer), and buffer size.
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5)
Associations found between walkability and walking-related outcomes (coded as positive, negative, no association, mixed -for studies providing results for different population groups or settings- or partial -for studies providing results for different buffer sizes or different walking-related outcomes and/or, studies providing different associations for each walkability variable used, and when this difference is not acute, e.g., two no associations, two positive, and three negative associations).
After analyzing the contents of all publications meeting our criteria (n = 146) according to the abovementioned fields, we stratified the analysis to compare publications focusing only on older adults (n = 24), and the general population (n = 122).
Results
Among all publications included in the content analysis (n = 146), 50.7% (n = 74) focused on adults, although the definition of this group varied vastly across studies (See Supplementary Material, Section 1.1.4 for further information). 17.8% (n = 26) focused on “all population” in their analysis while 15.1% focused on young people (n = 22). Finally, publications focusing on older adults formed 16.4% of the analyzed studies, with 24 publications.
The results of the content analysis are presented in Table 1, Table 2, and Table 3. In addition, Table 4 presents detailed list of publications in relation to all variables included in the content analysis.
General study characteristics
Publication year
Most of the studies focusing on both older adults and the general population were published in the last decade, and the number of publications in both groups increased remarkably in this period (Table 1). The oldest publications meeting our criteria dated from 2007 among studies focusing on older adults, and from 2005 among general population-focused studies.
Journal field
More than half of the studies in both literature groups were published in health-related journals (Table 1), followed by inter- or multi-disciplinary journals, transportation or urban studies, and environment- or geography-related journals.
Geographical context
The most used settings in walkability studies among both older adults- and general population-focused publications were the US and Canada (50 and 55.7% respectively) (Table 1). This was followed by Europe in both groups (29.2 and 20.5% respectively). However, among publications focusing on older adults, 16.7% were conducted in the Middle East and Asia, while the share among general population-focused literature was only 3.3%. The third most used setting among studies focusing on the general population was Oceania with 17.2% of the studies included in this group, while only one study focusing on older adults was conducted in this geographical context with a share of 4.2%.
Characteristics of the study design
Research design
Most studies in both groups of literature were designed as cross-sectional (75% among older adults- and 86.1% among general population-focused studies) (Table 1). Among publications focusing on older adults the share of longitudinal studies showed a higher percentage (20.8%) compared to that among general population-focused publications (13.1%).
Spatial data collection method
The vast majority of studies focusing on both older adults (91.7%) and the general population (93.4%) used GIS to collect their spatial data (Table 1). The share of audit usage among older adults-focused studies (8.3%) was slightly higher compared to the share among studies focusing on the general population (6.6%).
Outcome data collection method
Most of the outcome data was collected by self-reports in both literature groups (Table 1). Among studies focusing on the general population, device usage showed a higher share (25.4%) compared to the share among publications focusing on older adults (12.5%). However, using mixed methods to collect walking-related outcome data presented a higher share among older adults-focused studies (29.2%).
Characteristics of the walkability measures
Operationalization of walkability
Studies mostly used indexes to operationalize walkability among older adults and the general population, with a higher share among the latter (79.2 and 91.8%, respectively) (Table 1). The share of using separate variables, however, was higher among studies focusing on older adults (20.8%) compared to the share among the general population literature (8.2%). The most used indexes among older adults-focused publications were the walkability index of Frank et al. (2010) [58], the WalkScore index, and the walkability index of Frank et al. (2005) [59], respectively (data not shown). Among studies focusing on the general population the most preferred index was WalkScore. This was followed by the walkability index of Frank et al. (2010) [58], and new indexes created by the publications.
Walkability variables used
In 24 publications focusing on older adults, a total of 167 walkability variables were used. Most of the variables in this group of publications (33.5%) related to land use characteristics (Table 2). This was followed by safety from traffic category with 12%. Following this, street connectivity (11.4%), street design (11.4%), and activity and destination density (10.8%) were the next most used categories of walkability variables among publications focusing on older adults. Population density presented a share of 9%, while greenery and safety from crime each formed 4.8%, respectively, of the publications in this group. Variables related with transportation accessibility and topographic characteristics were the least preferred, while no variables related to socioeconomic characteristics were used among older adults-focused publications.
Among publications focusing on the general population (n = 122), a total of 518 variables were used to measure walkability. The most common variables were related to street connectivity (22.4%), and activity and destination density (17.8%). Following these, 16.6% of the walkability variables used in this literature group were related to population density, and 16.4% to land use characteristics. Variables related to street design formed 10.6%, while safety from traffic had 5% share. Greenery (3.9%), transportation accessibility (3.1%), safety from crime (2.7%), topographic (1.2%) and socio-economic characteristics (0.4%) were also used but to a lower extent compared to other categories among this group of publications.
See Supplementary Material, Table S2. for walkability variables used in each study.
Spatial extent and unit
Spatial extent
All publications on older adults focused on residential areas to measure walkability (Table 1). Among publications on the general population, residential areas were also the most preferred spatial extent with 87.7%. Notwithstanding, 4.1% of the publications in this group used school sites, while some had more than one spatial extent in their studies such as residential and workplace or residential and school site. Lastly, other spatial extents such as daily walking itineraries or routes to parks were also used among studies on the general population.
Spatial unit
Most of the publications in both groups used buffers to measure walkability in their studies (Table 1). This was followed by statistical units (e.g., census block groups, statistical areas/sectors/tracts, etc.) (16.7% among older adults-focused publications and 20.5% among the general population literature) and administrative units (e.g., zip/postal codes, neighborhood boundaries, etc.) (12.5 and 7.4%, respectively).
Buffer type and size
Among 17 older adults-focused studies using buffers, 53% used street network buffers while the rest used circular buffers (Table 3). Some studies used more than one buffer size in this group of publications. Among the 20 buffer sizes used, the most common were 1000 m and 2500 m (25% each) (Table 3). This was followed by 400 m- and 500 m-buffers, each presenting 15% of the total. Buffers equal to or less than 1000 m were preferred more (65%) than those greater than 1000 m in this group (35%) (See Supplementary Material, Section 1.4.3 for detailed information on the selection of 1000 m as a threshold).
Among 82 papers using buffers in publications focusing on the general population, a total of 91 buffer types were used. Among these, 51.6% were street network buffers, 46.2% were circular buffers, and 2.2% were sausage buffers. Similar to older adults-focused publications, some of the papers focusing on the general population used more than one buffer size in their studies. Among the total of 125 buffer sizes used, buffers less or greater than 1000 m were almost equally preferred among the publications in this group. Due to the high usage of the WalkScore index among the publications focusing on the general population, the most common buffer size was 2500 m (≈1.5 miles) (30%) (See Supplementary Material, Section 1.4.3 for buffer sizes of WalkScore indexes). This was followed by 1000 m (25%), 1600 m (≈1 mile) (11%,) and 800 m (≈0.5 mile) (9%).
Associations found between walkability and walking-related outcomes
Most of the publications focusing on both older adults (62.5%) and the general population (60.7%) found positive associations between walkability and walking-related outcomes (Table 1). One fifth of the publications on older adults found no association while the share was lower among papers focusing on the general population (14.8%). There was no paper with a negative association in the literature on older adults, whereas 4.1% of the publications on the general population found negative associations between walkability and walking-related outcomes. Partial associations were found among 12.5% of studies focusing on older adults, while this proportion was 16.4% among studies on the general population.
Discussion
Understanding, defining and/or measuring walkability is essential for creating more democratic, sustainable, and healthy environments. These benefits are particularly important for older adults, for whom walking is one of the easiest ways to achieve the recommended daily physical activity levels. Therefore, a review of the operationalization of objective walkability, how it related to walking outcomes, and how this relationship differed for older adults compared to the general population, could shed light to the gaps in the literature and thus be useful for academics interested in this field of research, as well as being insightful for urban designers, planners, and decision makers to create more inclusive places that consider the differences of individuals and settings.
In our results, the increase in the number of walkability studies in the last decade is promising. This applies for studies focusing on older adults but also the general population, as mentioned in previous reviews [20, 27, 28]. However, the fact that in our review many walkability studies in both groups focused on similar geographic settings (the US, Canada, and Europe) is of concern in terms of generalization of the results, despite the higher proportion observed in the number of studies focusing on older adults conducted in the Middle East and Asia. As it was also highlighted in previous studies, translating findings from these most common settings could be misleading, considering the differences in morphologies and land-use configuration between urban contexts across the globe, and the high proportion of studies conducted in high-income countries [12, 20, 26]. For this reason, the literature also lacks examples from middle- and low-income countries or cities, where walking is not only an important and a low-cost type of PA for a healthier life, but also one of the most accessible ways of transportation [3]. To this end, instead of following a one-size-fits-all approach, more studies conducted in different countries and even different cities of the same country, would bring new perspectives to walkability studies by highlighting the differences among settings, and their relationship with walking behavior of the general population and older adults in particular.
In terms of research design, cross-sectional studies were the most common among both groups of literature, as was also previously pointed out by other reviews [27,28,29, 178]. However, compared to studies focusing on the general population, it is promising that we observed a higher ratio of longitudinal studies among older adults-focused publications in our review. As is suggested in studies of aging, longitudinal designs are essential to understand complicated relationships among events or risks and outcomes, as well as to reduce possible biases, such as selection bias in sampling [179]. Thus, more longitudinal studies focusing on older adults would bring a more comprehensive understanding of walkability for this age group in the future, besides providing more reliable results.
In terms of data collection, most of the analyzed studies focusing on older adults used self-report measures to obtain walking-related outcomes. The ratio of use of technological devices for outcome data collection among older adults-focused studies presented a lower proportion than that of studies focusing on the general population, as was also mentioned in previous reviews [28, 178]. This could be due to the methodological challenges of these devices to capture older adults’ mobility, such as low battery life, underestimation of PA due to body-placement of the device, or difficulties encountered by participants when using these devices [180]. However, self-report measures have various disadvantages, especially among studies focusing on older adults, such as not capturing all daily activity patterns since individuals may not consider some activities, like dancing, as a type of PA, possibility of changes in older adults’ health status and/or mood, or problems with memory and cognition that could affect accurate recall of PA on a survey [181]. Thus, as previous studies suggested, the optimal reliability of results, especially in older adults’ mobility research, could be gathered from the use of objective or mixed methods [182, 183], which promisingly presented a higher proportion among older adults-focused papers included in our review.
Regarding the operationalization of walkability, most studies in both groups used indexes. The most preferred index in studies focusing on the general population was WalkScore, as it was also mentioned [21], and criticized previously for being an “insufficient metric for population health studies”, and for not capturing “the experiential nature of walking nor walkability” since it excludes recreational walking ( [14], pp. 3, 8), as well as the lack of consideration of attributes that would contribute to walking [20], such as measures related with safety [13]. Also, this index is only validated in the US and Canada, as stated on their website. Thus, its use in other settings could be highly misleading. Among studies focusing on older adults, the most common index was the walkability index of Frank et al. (2010) [58]. Although the variables used in this index (net residential density, retail floor area ratio, land use mix, and intersection density) could be meaningful to some extent to measure walkability in some other settings, this study was based on the data from two US cities and was not created specifically for older adults. Thus, although the values assigned for each variable in the formula were modified for adaptation in some of the reviewed papers [154, 177], its use to study this age group and in different settings could also be misleading. Although walkability differed widely for older adults compared to other pedestrians, as highlighted in an empirical research [12] as well as in a recent study proposing a “walkability index for elderly health” [184], in our review, the proportion of publications among older adults-focused studies creating their own indexes was lower than that among publications focusing on the general population. However, the ratio of the usage of separate variables was higher among older adults-focused studies. Depending on the selection of variables, this measure could provide more meaningful results for walkability and its relationship with older adults’ walking, rather than using an index which was not designed specifically for this age group. We believe that by using more specific variables or indexes, not only for the age groups under study but also for the settings, walkability measures could become more precise, and this would help create more walkable areas and promote walking for all.
The most used category of walkability variables among studies focusing on older adults were those related to land use characteristics in our review. This was followed by variables related to safety from traffic, which are intuitively believed to be specifically relevant to older adults' walking and used widely, as stated in a previous review [26]. The ratio of the usage of variables related with street design was similar for publications focusing on older adults and the general population. Although this category included variables found by previous studies to be specifically essential for older adults’ walking, such as sidewalk availability/ width/ material [185], presence of benches [186, 187] or restrooms [28] plus many other examples, usage of these variables did not present considerably higher proportions among publications focusing on older adults. The ratio of using greenery-related variables was slightly higher among studies focusing on older adults compared to the general population. This is perhaps due to the numerous studies in the literature highlighting the positive relationship found between the presence of green areas (including parks or street trees) and older adults’ walking [188,189,190]. However, the proportion of using these variables among older adults-focused studies was still low compared to the importance of this variable for their PA.
Regarding the spatial extent for measuring walkability, different from publications on the general population, studies on older adults focused only on residential areas in their research. Similarly, the most used spatial units among studies on older adults were buffers which are equal to or smaller than 1000m, and administrative units (e.g., neighborhood boundaries/ units, zip/postal codes, etc,) presented a higher share among this group of literature. These results were expected considering that the range of activity among older adults mostly decreases to the immediate vicinity of their residences [191], and doubtless this sheds more importance on the characteristics of the built environment in the neighborhoods. However, this also limits the range of walkability studies by underestimating individual differences, since not all older adults’ activity range or levels are the same. Additionally, different types of walking, such as recreational walking, could take place farther than the residential areas, and limiting studies with these extents could easily exclude these types of walking [192]. Thus, more studies using wider spatial extents and units in the future would provide more detailed information on walkability and its relationship with different types of walking, settings, and individuals.
Finally, most of the papers included in our review found a positive association between walkability and walking-related outcomes in both groups of publications. Among studies focusing on older adults, publications which found a positive association, as well as those which did not find any associations showed a higher proportion compared to publications focusing on the general population. The higher proportion of the latter could be explained by the lack of age-specific index usage among publications focusing on older adults [184]. Using indexes which are not created while considering specific needs of this age group could be limited or even misleading in understanding the relationship between walkability and walking. Regarding the high percentage of positive associations found between walking and walkability, previous reviews also presented similar results [28, 29]. A review on the general population explained the reason for this as the high number of studies conducted in high-income countries, since these settings are less likely to have deficiencies in the built environment, such as poor sidewalk infrastructures, or safety issues, such as high crime rates, compared to middle- or low-income settings [20, 193]. Thus, more studies conducted in different countries and even in different cities of a country, especially taking into consideration the possible socioeconomic differences between cities, would bring a wider perspective to the research on walkability, be helpful to overcome the uncertainties in the literature, as well as inform governments to create solutions for creating more walkable places for various population groups, and promoting walking in settings with different characteristics.
Strengths and limitations
The first strength of our systematic review is that it focuses particularly on walkability studies. Second, it provides results for older adults and the general population separately, which highlights the differences more and helps to find solutions for creating better environments for everyone. Third, this review includes only objective operationalization of walkability. Considering the main focus on older adults, this is accepted as one of the most precise methods [12, 18, 182]; thus we believe that the studies included in this review provided high reliability results. Finally, this review provided comprehensive information about not only how objective walkability has been defined and measured, which could be insightful for governments, but also scrutinized the methodologies used in walkability studies, which could be useful for researchers interested in conducting both literature reviews and empirical analyses on walkability. However, this systematic review is not exempt from limitations. First, although we included numerous characteristics of the studies in the content analysis, we did not cover other characteristics, such as sample size, which could provide different insights. Future research could consider including this variable in their reviews to enrich the body of literature. Second, selecting papers published only in English could have resulted in a language-based bias. However, we believe that the reviewed studies and the analysis presented here are representative, since the majority of empirical studies worldwide are published in English [194]. Finally, as mentioned in other reviews [13, 195] other types of biases, such as spatial selection bias (e.g., residential selection bias, whether people who walk more choose to live in highly walkable areas), or recall bias (e.g., studies using self-reported PA) among the included studies could have impacted their results and thus the results of our review and our interpretations, even indirectly.
Conclusion
This review draws attention to how objective walkability has been operationalized, how it is related to walking outcomes, and how these differed among studies focusing on older adults and the general population. Despite the promising increase in the last decade in the number of publications focusing on walkability for all sorts of population groups, the literature still lacks studies 1) focusing on different settings, especially low- and middle-income settings, 2) using wider spatial extents rather than only neighborhood scale, 3) using longitudinal designs, 4) using objective or mixed methods to collect their outcome data related with walking, and 5) creating indexes or using separate variables which are specific for settings and population groups, such as older adults. With future studies aiming to address these points, walkability studies could become more comprehensive and provide better answers to urban design and planning problems.
The methodologies used and the gaps found in the walkability literature highlighted in this review could be useful for researchers to conduct future reviews, as well as empirical analyses on walkability. Additionally, the differences in the definition and operationalization of objective walkability for older adults versus the general population summarized in this study could be insightful for not only researchers interested in the field, but also urban designers, planners, or local governments aiming to create more walkable places that would meet the needs of most population groups, but specifically older adults’, in different settings. These would enrich the walkability literature and contribute to more democratic, sustainable, and healthy environments, as well as the societies in general.
Availability of data and materials
The Table 4 in manuscript and Table S2 in supplementary material, could be used for any related purposes required here (e.g., replication, interpretation). When analyzing publications included in the review, we also gathered other types of information which are not presented in this manuscript. However, original complete datasets could also be provided on request. For this, please contact corresponding author.
References
Gunnarsson OS. Principles towards a walking-friendly and human city. The pedestrian association of Sweden (FOT); 1996.
Le HTK, Buehler R, Hankey S. Correlates of the built environment and active travel: evidence from 20 US metropolitan areas. Environ Health Perspect. 2018;126(7):1–13.
Litman TA. Economic value of walkability. Transp Res Rec. 2003;1828:3–11.
Pucher J, Buehler R. Walking and cycling for healthy cities. Built Environ. 2010;36(4):391–414.
World Health Organization. Physical activity fact sheets: World Health Organization; 2021. Available from: https://www.who.int/news-room/fact-sheets/detail/physical-activity
World Health Organization. Global recommendations on physical activity for health: 65 years and above. Geneva: World Health Organization; 2011. Available from: https://www.who.int/dietphysicalactivity/physical-activity-recommendations-65years.pdf?ua=1%0Ahttp://medcontent.metapress.com/index/A65RM03P4874243N.pdf%5Cnhttp://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Global+Recomendations+on+physical+act
DiPietro L. Physical activity in aging: changes in patterns and their relationship to health and function. Journals Gerontol - Ser a biol Sci. Med Sci. 2001;56(SPEC. ISS. 2):13–22.
Garvin T, Nykiforuk CIJ, Johnson S. Can we get old here? Seniors’ perceptions of seasonal constraints of neighbourhood built environments in a northern, winter city. Geogr Ann Ser B Hum Geogr. 2012;94(4):369–89.
Nahemow L, Lawton MP. Toward an ecological theory of adaptation and aging. Environ Des Res. 1973;1:24–32.
Murray HA. Explorations in personality. 70th Anniv. New York: Oxford University Press; 2008.
Lo RH. Walkability: what is it? J Urban. 2009;2(2):145–66.
Moura F, Cambra P, Gonçalves AB. Measuring walkability for distinct pedestrian groups with a participatory assessment method: a case study in Lisbon. Landsc Urban Plan. 2017;157:282–96.
Forsyth A. What is a walkable place? The walkability debate in urban design. URBAN Des Int. 2015;20(4):274–92 Available from: http://link.springer.com/10.1057/udi.2015.22.
Shields R, Gomes da Silva EJ, Lima e Lima T, Osorio N. Walkability: a review of trends. J Urban. 2021;00(00):1–23. https://doi.org/10.1080/17549175.2021.1936601.
Ubiali A, Gori D, Rochira A, Raguzzoni G, Fantini MP. Measure of walkability in the pediatric population: a qualitative review of the literature. Ann di Ig Med Prev e di Comunita. 2021;33(1):67–85.
Gebel K, Bauman A, Owen N. Correlates of non-concordance between perceived and objective measures of walkability. Ann Behav Med. 2009;37(2):228–38.
Gebel K, Bauman AE, Sugiyama T, Owen N. Mismatch between perceived and objectively assessed neighborhood walkability attributes: prospective relationships with walking and weight gain. Health Place. 2011;17(2):519–24.
Lin L, Moudon AV. Objective versus subjective measures of the built environment, which are most effective in capturing associations with walking? Heal Place. 2010;16(2):339–48 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-73249149696&doi=10.1016%2Fj.healthplace.2009.11.002&partnerID=40&md5=433997cc32a0a3263f6bb3d0ce523b07.
Talen E, Koschinsky J. The walkable neighborhood : a literature review. 2013;1(1):42–63.
Wang H, Yang Y. Neighbourhood walkability: a review and bibliometric analysis. Cities. 2019;93(April):43–61 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064979153&doi=10.1016%2Fj.cities.2019.04.015&partnerID=40&md5=d0994591be537cf21b62d96439cb24ca.
Hall CM, Ram Y. Walk score® and its potential contribution to the study of active transport and walkability: a critical and systematic review. Transp Res Part D Transp Environ. 2018;61(March 2017):0–1. https://doi.org/10.1016/j.trd.2017.12.018.
Ewing R, Handy S. Measuring the unmeasurable: urban design qualities related to walkability. J Urban Des. 2009;14(1):65–84.
Ariffin RNR, Abd Rahman NH, Zahari RK. Systematic literature review of walkability and the built environment. J Policy Gov. 2021;01(1):1–20.
Grasser G, Van Dyck D, Titze S, Stronegger W, Van DD, Van Dyck D, et al. Objectively measured walkability and active transport and weight-related outcomes in adults: a systematic review. Int J Public Health. 2013;58(4):615–25 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880917099&doi=10.1007%2Fs00038-012-0435-0&partnerID=40&md5=26dec39135439144654b43d3918375ab.
Moran M, Van Cauwenberg J, Hercky-Linnewiel R, Cerin E, Deforche B, Plaut P. Understanding the relationships between the physical environment and physical activity in older adults: a systematic review of qualitative studies. Int J Behav Nutr Phys Act. 2014;11(1):1–12.
Van Cauwenberg J, De Bourdeaudhuij I, De Meester F, Van Dyck D, Salmon J, Clarys P, et al. Relationship between the physical environment and physical activity in older adults: a systematic review. Heal Place. 2011;17(2):458–69 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952489837&doi=10.1016%2Fj.healthplace.2010.11.010&partnerID=40&md5=f0775087ed49f9e580916b00f49adae3.
Barnett DW, Barnett A, Nathan A, Van Cauwenberg J, Cerin E. Built environmental correlates of older adults’ total physical activity and walking: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):1–24 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027136801&doi=10.1186%2Fs12966-017-0558-z&partnerID=40&md5=47e9886803fae8476bfe90ed7c29d340.
Cerin E, Nathan A, van Cauwenberg J, Barnett DW, Barnett A. The neighbourhood physical environment and active travel in older adults: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):1–23 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011681600&doi=10.1186%2Fs12966-017-0471-5&partnerID=40&md5=bbba0df3c72e402b9194f5a9dc3beeba.
Van Cauwenberg J, Nathan A, Barnett A, Barnett DW, Cerin E, Environment the C on, et al. Relationships between Neighbourhood physical Environmental attributes and Older adults’ leisure-time physical activity: a systematic review and meta-analysis Sport Med 2018;48(7):1635–1660. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048543548&doi=10.1007%2Fs40279-018-0917-1&partnerID=40&md5=be22d2734fc91de8ed669580ec981d53
Edwards N, Dulai J. Examining the relationships between walkability and physical activity among older persons: what about stairs? BMC Public Health. 2018;18:1025. https://doi.org/10.1186/s12889-018-5945-0.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:2020–1.
Adams MA, Todd M, Kurka J, Conway TL, Cain KL, Frank LD, et al. Patterns of walkability, transit, and recreation environment for physical activity. Am J Prev Med. 2015;49(6):878–87.
Althoff T, Sosič R, Hicks JL, King AC, Delp SL, Leskovec J. Large-scale physical activity data reveal worldwide activity inequality. Nature. 2017;547(7663):336–9 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025128546&doi=10.1038%2Fnature23018&partnerID=40&md5=7c907e5e76f9817f487f4ece5e81ee5d.
Eriksson U, Arvidsson D, Gebel K, Ohlsson H, Sundquist K. Walkability parameters, active transportation and objective physical activity: moderating and mediating effects of motor vehicle ownership in a cross-sectional study. Int J Behav Nutr Phys Act. 2012;9:123. https://doi.org/10.1186/1479-5868-9-123.
Hajna S, Ross NA, Joseph L, Harper S, Dasgupta K. Neighbourhood walkability, daily steps and utilitarian walking in Canadian adults. BMJ Open. 2015;5(11):e008964. https://doi.org/10.1136/bmjopen-2015-008964.
Learnihan V, Van Niel KP, Giles-Corti B, Knuiman M. Effect of scale on the links between walking and Urban Design. Geogr Res. 2011;49(2):183–91 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955521869&doi=10.1111%2Fj.1745-5871.2011.00689.x&partnerID=40&md5=b529604a6563b7553ec5d545677da175.
Lee H, Kang H-M, Ko Y-J, Kim H-S, Kim Y-J, Bae WK, et al. Influence of urban neighbourhood environment on physical activity and obesity-related diseases. Public Health. 2015;129(9):1204–10.
Li X, Santi P, Courtney TK, Verma SK, Ratti C. Investigating the association between streetscapes and human walking activities using Google street view and human trajectory data. Trans GIS. 2018;22(4):1029–44 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052506201&doi=10.1111%2Ftgis.12472&partnerID=40&md5=ef9ecfb755444ad476207218a91361d2.
Li Y, Yatsuya H, Hanibuchi T, Hirakawa Y, Ota A, Uemura M, et al. The association between objective measures of residence and worksite neighborhood environment, and self-reported leisure-time physical activities: the Aichi workers’ cohort study. Prev Med Reports. 2018;11:282–9 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050875582&doi=10.1016%2Fj.pmedr.2018.07.007&partnerID=40&md5=8b54fc0d8b4dd5b2e18618aff2524e99.
McGowan EL, Fuller D, Cutumisu N, North S, Courneya KS. The role of the built environment in a randomized controlled trial to increase physical activity among men with prostate cancer: the PROMOTE trial. Supp Care Cancer. 2017;25(10):2993–6 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021298995&doi=10.1007%2Fs00520-017-3798-1&partnerID=40&md5=0d1e74f0db34d5898933e93bc2cbc59a.
Reyer M, Fina S, Siedentop S, Schlicht W. Walkability is only part of the story: walking for transportation in Stuttgart, Germany. Int J Environ Res Public Health. 2014;11(6):5849–65.
Rundle AG, Sheehan DM, Quinn JW, Bartley K, Eisenhower D, Bader MMD, et al. Using GPS data to study neighborhood walkability and physical activity. Am J Prev Med. 2016;50(3):E65–72.
Sallis JF, Cerin E, Conway TL, Adams MA, Frank LD, Pratt M, et al. Physical activity in relation to urban environments in 14 cities worldwide: a cross-sectional study. Lancet. 2016;387(10034):2207–17 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961877396&doi=10.1016%2FS0140-6736%2815%2901284-2&partnerID=40&md5=88a30379b8f983d3fa4032b013dba9b8.
Arvidsson D, Eriksson U, Lonn SL, Sundquist K. Neighborhood walkability, income, and hour-by-hour physical activity patterns. Med Sci Sports Exerc. 2013;45(4):698–705.
Shay E, Khattak AJ. Household travel decision chains: residential environment, automobile ownership, trips and mode choice. Int J Sustain Transp. 2012;6(2):88–110 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052546206&doi=10.1080%2F15568318.2011.560363&partnerID=40&md5=58857cd3888202975072cbd057469a7f.
Thielman J, Manson H, Chiu M, Copes R, Rosella LC. Residents of highly walkable neighbourhoods in Canadian urban areas do substantially more physical activity: a cross-sectional analysis. C Open. 2016;4(4):E720–8.
Villanueva K, Knuiman M, Nathan A, Giles-Corti B, Christian H, Foster S, et al. The impact of neighborhood walkability on walking: Does it differ across adult life stage and does neighborhood buffer size matter? Heal Place. 2014;25:43–6. https://doi.org/10.1016/j.healthplace.2013.10.005.
Wasfi RA, Dasgupta K, Eluru N, Ross NA. Exposure to walkable neighbourhoods in urban areas increases utilitarian walking: longitudinal study of Canadians. J Transp Heal. 2015;3(4):440–7.
Wei YD, Xiao W, Wen M, Wei R. Walkability, land use and physical activity. Sustainability. 2016;8(1):65. https://doi.org/10.3390/su8010065.
Yang Y, Diez-Roux AV. Adults’ daily walking for travel and leisure: interaction between attitude toward walking and the neighborhood environment. Am J Heal Promot. 2017;31(5):435–43 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028347122&doi=10.1177%2F0890117116669278&partnerID=40&md5=b96029ef43494f7edea580a295421fc5.
Arvidsson D, Kawakami N, Ohlsson H, Sundquist K. Physical activity and concordance between objective and perceived walkability. Med Sci Sports Exerc. 2012;44(2):280–7.
Badland H, Mavoa S, Boulangé C, Eagleson S, Gunn L, Stewart J, et al. Identifying, creating, and testing urban planning measures for transport walking: findings from the Australian national liveability study. J Transp Heal. 2016;5:151–62 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011103517&doi=10.1016%2Fj.jth.2016.08.010&partnerID=40&md5=e2c3d93956ef5eeb2c675b5cead6b2cb.
Boisjoly G, Wasfi R, El-Geneidy A. How much is enough? Assessing the influence of neighborhood walkability on undertaking 10-minute walks. J Transp Land Use. 2018;11(1):143–51.
Chiu M, Shah BR, Maclagan LC, Rezai M-R, Austin PC, Tu JV. Walk score® and the prevalence of utilitarian walking and obesity among Ontario adults: a cross-sectional study. Heal Reports. 2015;26(7):3–10 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937691427&partnerID=40&md5=0308900f95834c7d4f49581bf4f16adf.
Cho G-H, Rodríguez DA. Neighborhood design, neighborhood location, and three types of walking: results from the Washington DC area. Environ Plan B Plan Des. 2015;42(3):526–40 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929334246&doi=10.1068%2Fb130222p&partnerID=40&md5=aaeb52bc8a09bfbdf229401de70ba2ae.
Christian HE, Bull FC, Middleton NJ, Knuiman MW, Divitini ML, Hooper P, et al. How important is the land use mix measure in understanding walking behaviour? Results from the RESIDE study. Int J Behav Nutr Phys Act. 2011;8 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79957861655&doi=10.1186%2F1479-5868-8-55&partnerID=40&md5=e81fc1ccc86e1050ddf215f8c7144d54.
Curl A, Kearns A, Macdonald L, Mason P, Ellaway A. Can walking habits be encouraged through area-based regeneration and relocation? A longitudinal study of deprived communities in Glasgow, UK. J Transp Heal. 2018;10:44–55 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049337692&doi=10.1016%2Fj.jth.2018.06.004&partnerID=40&md5=d31b1d871a8e8a8a743ee0e965aaa899.
Frank LD, Sallis JF, Saelens BE, Leary L, Cain L, Conway TL, et al. The development of a walkability index: application to the neighborhood quality of life study. Br J Sports Med. 2010;44(13):924–33.
Frank LD, Schmid TL, Sallis JF, Chapman J, Saelens BE. Linking objectively measured physical activity with objectively measured urban form: findings from SMARTRAQ. Am J Prev Med. 2005;28(2 SUPPL. 2):117–25.
Dills JE, Rutt CD, Mumford KG. Objectively measuring route-To-Park walkability in Atlanta. Georgia Environ Behav. 2012;44(6):841–60.
Doyle S, Kelly-Schwartz A, Schlossberg M, Stockard J. Active community environments and health: the relationship of walkable and safe communities to individual health. J Am Plan Assoc. 2006;72(1):19–31.
Duncan DT, Méline J, Kestens Y, Day K, Elbel B, Trasande L, et al. Walk score, transportation mode choice, and walking among french adults: a GPS, accelerometer, and mobility survey study. Int J Environ Res Public Health. 2016;13(6):1–14 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84975291140&doi=10.3390%2Fijerph13060611&partnerID=40&md5=2a8c65b914893d518eacee500671547c.
Dygryn J, Mitas J, Stelzer J. The influence of built environment on walkability using geographic information system. J Hum Kinet. 2010;24:93–9.
Eom HJ, Cho GH. Exploring thresholds of built environment characteristics for walkable communities: empirical evidence from the Seoul metropolitan area. Transp Res Part D Transp Environ. 2015;40:76–86 Available from: https://doi.org/10.1016/j.trd.2015.07.005.
Forjuoh SN, Ory MG, Won J, Towne SD, Wang S, Lee C. Determinants of walking among middle-aged and older overweight and obese adults: sociodemographic, Health, and Built Environmental Factors. J Obes. 2017;2017 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024498461&doi=10.1155%2F2017%2F9565430&partnerID=40&md5=4e7c5f3afa812434b62b48c3c9ab05bb.
Frank LD, Kershaw SE, Chapman JE, Campbell M, Swinkels HM. The unmet demand for walkability: Disparities between preferences and actual choices for residential environments in Toronto and Vancouver. Can J Public Heal - Rev Can sante publique. 2015;106(1, 1):ES12–20.
Frank LD, Saelens BE, Powell KE, Chapman JE. Stepping towards causation: do built environments or neighborhood and travel preferences explain physical activity, driving, and obesity? Soc Sci Med. 2007;65(9):1898–914.
Gell NM, Rosenberg DE, Carlson J, Kerr J, Belza B. Built environment attributes related to GPS measured active trips in mid-life and older adults with mobility disabilities. Disabil Health J. 2015;8(2):290–5.
Grasser G, van Dyck D, Titze S, Stronegger WJ. A European perspective on GIS-based walkability and active modes of transport. Eur J Pub Health. 2016;27(1):145–51.
Barnes R, Winters M, Ste-Marie N, McKay H, Ashe MC. Age and retirement status differences in associations between the built environment and active travel behaviour. J Transp Heal. 2016;3(4):513–22 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962144853&doi=10.1016%2Fj.jth.2016.03.003&partnerID=40&md5=d29dd67ed5d8a19984cbc97182dc3514.
Hajna S, Kestens Y, Daskalopoulou SS, Joseph L, Thierry B, Sherman M, et al. Neighbourhood walkability and home neighbourhood-based physical activity: an observational study of adults with type 2 diabetes. BMC Public Health. 2016;16(1):957. https://doi.org/10.1186/s12889-016-3603-y.
Hajna S, Ross NA, Joseph L, Harper S, Dasgupta K. Neighbourhood walkability and daily steps in adults with type 2 diabetes. Plos One. 2016;11(3).
Han M, Ye X, Preciado P, Williams S, Campos I, Bonner M, et al. Relationships between neighborhood walkability and objectively measured physical activity levels in hemodialysis patients. Blood Purif. 2018;45(1–3):236–44.
Hirsch JA, Roux AVD, Moore KA, Evenson KR, Rodriguez DA. Change in walking and body mass index following residential relocation: the multi-ethnic study of atherosclerosis. Am J Public Health. 2014;104(3):e49–56 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894092502&doi=10.2105%2FAJPH.2013.301773&partnerID=40&md5=4220c38ff73121985aab3b1bb9b3042a.
Hirsch JA, Moore KA, Evenson KR, Rodriguez DA, Roux AVD. Walk score® and transit score® and walking in the multi-ethnic study of atherosclerosis. Am J Prev Med. 2013;45(2):158–66 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880323998&doi=10.1016%2Fj.amepre.2013.03.018&partnerID=40&md5=29ec3f2a8242aebf3bdd7675f8192f45.
Hirsch JA, Winters M, Clarke PJ, Ste-Marie N, McKay HA. The influence of walkability on broader mobility for Canadian middle aged and older adults: an examination of walk score™ and the mobility over varied environments scale (MOVES). Prev Med (Baltim). 2017;95:S60–7.
Hosler AS, Gallant MP, Riley-Jacome M, Rajulu DT. Relationship between objectively measured walkability and exercise walking among adults with diabetes. J Environ Public Health. 2014:542123. https://doi.org/10.1155/2014/542123.
Huang R, Moudon AV, Zhou C, Saelens BE. Higher residential and employment densities are associated with more objectively measured walking in the home neighborhood. J Transp Heal. 2019;12:142–51 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060235448&doi=10.1016%2Fj.jth.2018.12.002&partnerID=40&md5=b5f926e3dea4c491f374122e90eaa92e.
Hwang L-D, Hurvitz PM, Duncan GE. Cross sectional association between spatially measured walking bouts and neighborhood walkability. Int J Environ Res Public Health. 2016;13(4):412. https://doi.org/10.3390/ijerph13040412.
Jack E, McCormack GR. The associations between objectively-determined and self-reported urban form characteristics and neighborhood-based walking in adults. Int J Behav Nutr Phys Act. 2014;11(1) Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902084844&doi=10.1186%2F1479-5868-11-71&partnerID=40&md5=37f5cf23430d3c60a305a2c2813f33de.
Brown SC, Pantin H, Lombard J, Toro M, Huang S, Plater-Zyberk E, et al. Walk score® : associations with purposive walking in recent Cuban immigrants. Am J Prev Med. 2013;45(2):202–6 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880283726&doi=10.1016%2Fj.amepre.2013.03.021&partnerID=40&md5=28dc1625343faedce174d2f80851ffbc.
James P, Hart JE, Hipp JA, Mitchell JA, Kerr J, Hurvitz PM, et al. GPS-based exposure to greenness and walkability and Accelerometry-based physical activity. Cancer Epodemiol Biomarkers Prev. 2017;26(4):525–32.
Jensen WA, Brown BB, Smith KR, Brewer SC, Amburgey JW, McIff B. Active transportation on a complete street: perceived and audited walkability correlates. Int J Environ Res Public Health. 2017;14(9):1014. https://doi.org/10.3390/ijerph14091014.
Kelley EA, Kandula NR, Kanaya AM, Yen IH. Neighborhood walkability and walking for transport among south Asians in the masala study. J Phys Act Health. 2016;13(5):514–9.
Kelly C, Lian M, Struthers J, Kammrath A. Walking to work: the roles of neighborhood walkability and socioeconomic deprivation. J Phys Act Health. 2015;12(1):S70–5.
Kerr J, Norman GJ, Adams MA, Ryan S, Frank LD, Sallis JF, et al. Do neighborhood environments moderate the effect of physical activity lifestyle interventions in adults? Heal Place. 2010;16(5):1–7.
Kerr J, Norman G, Millstein R, Adams MA, Morgan C, Langer RD, et al. Neighborhood environment and physical activity among older women: findings from the San Diego cohort of the women’s health initiative. J Phys Act Heal. 2014;11(6):1070–7 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910006911&doi=10.1123%2Fjpah.2012-0159&partnerID=40&md5=b3e75e53de1e7538a874b4f797a61dcb.
Koohsari MJ, Owen N, Cerin E, Giles-Corti B, Sugiyama T. Walkability and walking for transport: characterizing the built environment using space syntax. Int J Behav Nutr Phys Act. 2016;13:121. https://doi.org/10.1186/s12966-016-0448-9.
Lo BK, Graham ML, Folta SC, Paul LC, Strogatz D, Nelson ME, et al. Examining the associations betweenwalk score, perceived built environment, and physical activity behaviors among women participating in a community-randomized lifestyle change intervention trial: strong hearts, healthy communities. Int J Environ Res Public Health. 2019;16(5) Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062817386&doi=10.3390%2Fijerph16050849&partnerID=40&md5=ea334b6f5e7133b06069b81bfaa658bb.
Marquet O, Hipp AJ. Worksite built environment and objectively measured physical activity while at work: an analysis using perceived and objective walkability and greenness. J Environ Health. 2019;81(7):20–6.
Mayne DJ, Morgan GG, Jalaludin BB, Bauman AE. The contribution of area-level walkability to geographic variation in physical activity: a spatial analysis of 95,837 participants from the 45 and up study living in Sydney, Australia. Popul Health Metrics. 2017;15:38. https://doi.org/10.1186/s12963-017-0149-x.
Carter P, Bodicoat DH, Jones A, Khunti K, Davies MJ, Edwardson CL, et al. The impact of neighbourhood walkability on the effectiveness of a structured education programme to increase objectively measured walking. J Public Health (Bangkok). 2017;40(1):82–9.
Mayne DJ, Morgan GG, Willmore A, Rose N, Jalaludin B, Bambrick H, et al. An objective index of walkability for research and planning in the Sydney metropolitan region of New South Wales, Australia: an ecological study. Int J Health Geogr. 2013;12:61. https://doi.org/10.1186/1476-072X-12-61.
McCormack GR, McLaren L, Salvo G, Blackstaffe A. Changes in objectively-determined walkability and physical activity in adults: a quasi-longitudinal residential relocation study. Int J Environ Res Public Health. 2017;14(5):551. https://doi.org/10.3390/ijerph14050551.
McCormack GR, Shiell A, Doyle-Baker PK, Friedenreich CM, Sandalack BA. Subpopulation differences in the association between neighborhood urban form and neighborhood-based physical activity. Heal Place. 2014;28:109–15 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84899884707&doi=10.1016%2Fj.healthplace.2014.04.001&partnerID=40&md5=1e70ffe872a3c7ad08e75430bb319c9f.
McCormack GR, Shiell A, Giles-Corti B, Begg S, Veerman JL, Geelhoed E, et al. The association between sidewalk length and walking for different purposes in established neighborhoods. Int J Behav Nutr Phys Act. 2012;9 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864405616&doi=10.1186%2F1479-5868-9-92&partnerID=40&md5=76c711b394310953e7b10f8044ae3fbe.
Méline J, Chaix B, Pannier B, Ogedegbe G, Trasande L, Athens J, et al. Neighborhood walk score and selected Cardiometabolic factors in the French RECORD cohort study. BMC Public Health. 2017;17(1):960 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038427730&doi=10.1186%2Fs12889-017-4962-8&partnerID=40&md5=d32f02cd7d6c7c39618a5661564fee80.
Norman GJ, Carlson JA, O’Mara S, Sallis JF, Patrick K, Frank LD, et al. Neighborhood preference, walkability and walking in overweight/obese men. Am J Health Behav. 2013;37(2):277–82.
Oluyomi AO, Whitehead LW, Burau KD, Symanski E, Kohl HW, Bondy M. Physical activity guideline in Mexican-Americans: Does the built environment play a role? J Immigr Minor Heal. 2014;16(2):244–55 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84896392799&doi=10.1007%2Fs10903-012-9724-1&partnerID=40&md5=7c3a60bfc3490eedcaa03c023febc63a.
Owen N, Cerin E, Leslie E, duToit L, Coffee N, Frank LD, et al. Neighborhood walkability and the walking behavior of Australian adults. Am J Prev Med. 2007;33(5):387–95.
Reid RER, Carver TE, Reid TGR, Picard-Turcot M-AM-A, Andersen KM, Christou NV, et al. Erratum to: effects of neighborhood walkability on physical activity and sedentary behavior long-term post-bariatric surgery. Obes Surg. 2017;27(6):1595 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006467491&doi=10.1007%2Fs11695-016-2512-6&partnerID=40&md5=8842e01c86e017f9251644854e6d03a7.
Ribeiro AI, Hoffimann E. Development of a neighbourhood walkability index for Porto metropolitan area. How strongly is walkability associated with walking for transport? Int J Environ Res Public Health. 2018;15(12):2767. https://doi.org/10.3390/ijerph15122767.
Cerin E, Frank LD, Sallis JF, Saelens BE, Conway TL, Chapman JE, et al. From neighborhood design and food options to residents’ weight status. Appetite. 2011;56(3):693–703 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952984863&doi=10.1016%2Fj.appet.2011.02.006&partnerID=40&md5=566c7a89f09ec65bdf9f2f45e1f352c9.
Richardson AS, Troxel WM, Ghosh-Dastidar MB, Beckman R, Hunter GP, DeSantis AS, et al. One size doesn’t fit all: cross-sectional associations between neighborhood walkability, crime and physical activity depends on age and sex of residents. BMC Public Health. 2017;17:97. https://doi.org/10.1186/s12889-016-3959-z.
Riley DL, Mark AE, Kristjansson E, Sawada MC, Reid RD. Neighbourhood walkability and physical activity among family members of people with heart disease who participated in a randomized controlled trial of a behavioural risk reduction intervention. Heal Place. 2013;21:148–55.
Rundle AG, Chen Y, Quinn JW, Rahai N, Bartley K, Mooney SJ, et al. Development of a neighborhood walkability index for studying neighborhood physical activity contexts in communities across the U.S. over the past three decades. J Urban Health. 2019;96(4):583–90. https://doi.org/10.1007/s11524-019-00370-4.
Sallis JF, Saelens BE, Frank LD, Conway TL, Slymen DJ, Cain KL, et al. Neighborhood built environment and income: examining multiple Health outcomes. Soc Sci Med. 2009;68(7):1285–93 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-62249147570&doi=10.1016%2Fj.socscimed.2009.01.017&partnerID=40&md5=35f2de2afdb47e703142557e17b28029.
Salvo D, Reis RS, Stein AD, Rivera J, Martorell R, Pratt M. Characteristics of the built environment in relation to objectively measured physical activity among Mexican adults, 2011. Prev Chronic Dis. 2014;11 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84916638294&doi=10.5888%2Fpcd11.140047&partnerID=40&md5=f6e719f8858a26cb30a8c6feae88acce.
Salvo G, Lashewicz BM, Doyle-Baker PK, McCormack GR. A mixed methods study on the barriers and facilitators of physical activity associated with residential relocation. J Environ Public Health. 2018;2018 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062414054&doi=10.1155%2F2018%2F1094812&partnerID=40&md5=68c07c2b79c023a82364468ea4f45ac5.
Shimura H, Sugiyama T, Winkler E, Owen N. High neighborhood walkability mitigates declines in middle-to-Older aged adults’ walking for transport. J Phys Act Health. 2012;9(7):1004–8.
Shimura H, Winkler E, Owen N. Individual, psychosocial, and environmental correlates of 4-year declines in walking among middle-to-older aged adults. J Phys Act Heal. 2014;11(6):1078–84 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910006471&doi=10.1123%2Fjpah.2012-0244&partnerID=40&md5=d7d4cfc10fcd5c9864b42f3dcdbedc25.
Siqueira Reis R, Hino AAF, Rech CR, Kerr J, Hallal PC. Walkability and physical activity: findings from Curitiba, Brazil. Am J Prev Med. 2013;45(3):269–75 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883025841&doi=10.1016%2Fj.amepre.2013.04.020&partnerID=40&md5=f1f73c3233c59235f1d233ce645c8b9c.
Smith L, Panter J, Ogilvie D. Characteristics of the environment and physical activity in midlife: Findings from UK biobank. Prev Med (Baltim). 2019;118:150–8 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055677100&doi=10.1016%2Fj.ypmed.2018.10.024&partnerID=40&md5=91bf3170f66ada98ad72e562356c9bae.
Christiansen LB, Madsen T, Schipperijn J, Ersboll AK, Troelsen J. Variations in active transport behavior among different neighborhoods and across adult lifestages. J Transp Heal. 2014;1(4):316–25 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84919332846&doi=10.1016%2Fj.jth.2014.10.002&partnerID=40&md5=c4c8ccc33c7528b4161907cef80eca62.
Sugiyama T, Cole R, Koohsari MJ, Kynn M, Sallis JF, Owen N. Associations of local-area walkability with disparities in residents’ walking and car use. Prev Med (Baltim). 2019;120:126–30.
Sugiyama T, Howard NJ, Paquet C, Coffee NT, Taylor AW, Daniel M. Do relationships between Environmental attributes and recreational walking vary according to area-level socioeconomic status? J Urban Heal. 2015;92(2):253–64 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84939939245&doi=10.1007%2Fs11524-014-9932-1&partnerID=40&md5=08f8dc07fcfddd8d273cdcc162a9c8b3.
Sundquist K, Eriksson U, Kawakami N, Skog L, Ohlsson H, Arvidsson D. Neighborhood walkability, physical activity, and walking behavior: the Swedish neighborhood and physical activity (SNAP) study. Soc Sci Med. 2011;72(8):1266–73.
Tamura K, Wilson JS, Goldfeld K, Puett RC, Klenosky DB, Harper WA, et al. Accelerometer and GPS data to analyze built environments and physical activity. Res Q Exerc Sport. 2019;90(3):395–402. https://doi.org/10.1080/02701367.2019.1609649.
Towne SD, Won J, Lee S, Ory MG, Forjuoh SN, Wang S, et al. Using walk score™ and neighborhood perceptions to assess walking among middle-aged and Older adults. J Community Health. 2016;41(5):977–88 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961208535&doi=10.1007%2Fs10900-016-0180-z&partnerID=40&md5=986da26b89a48cb2164f8868ff84c0db.
Towne SD, Lopez ML, Li Y, Smith ML, Warren JL, Evans AE, et al. Examining the role of income inequality and neighborhood walkability on obesity and physical activity among low-income Hispanic adults. J Immigr Minor Heal. 2018;20(4):854–64 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025458124&doi=10.1007%2Fs10903-017-0625-1&partnerID=40&md5=2e62667620326324883d02f558af16fb.
Tuckel P, Milczarski W, Peter Tuckel PD, William MP. Walk score (TM), perceived neighborhood walkability, and walking in the US. Am J Health Behav. 2015;39(2):242–56.
Twardzik E, Judd S, Bennett A, Hooker S, Howard V, Hutto B, et al. Walk score and objectively measured physical activity within a national cohort. J Epidemiol Community Health. 2019;73(6):549–56 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063937766&doi=10.1136%2Fjech-2017-210245&partnerID=40&md5=4d44334696301354590dd108f6a3443e.
Van Dyck D, Cardon G, Deforche B, De Bourdeaudhuij I, Van Dyck D, Cardon G, et al. Do adults like living in high-walkable neighborhoods? Associations of walkability parameters with neighborhood satisfaction and possible mediators. Heal Place. 2011;17(4):971–7 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79958072347&doi=10.1016%2Fj.healthplace.2011.04.001&partnerID=40&md5=537e6c03af476718cdd4dc4bb7813abd.
Van Dyck D, Cardon G, Deforche B, Sallis JF, Owen N, De Bourdeaudhuij I. Neighborhood SES and walkability are related to physical activity behavior in Belgian adults. Prev Med (Baltim). 2010;50(SUPPL):74–9.
Chum A, Atkinson P, O’Campo P. Does time spent in the residential neighbourhood moderate the relationship between neighbourhood walkability and transport-related walking? A cross-sectional study from Toronto, Canada. BMJ Open. 2019;9(4) Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063953906&doi=10.1136%2Fbmjopen-2018-023598&partnerID=40&md5=dea48f5d9fde4e0ba5fe0cc8fad269da.
Van Dyck D, Cerin E, Cardon G, Deforche B, Sallis JF, Owen N, et al. Physical activity as a mediator of the associations between neighborhood walkability and adiposity in Belgian adults. Heal Place. 2010;16(5):952–60. https://doi.org/10.1016/j.healthplace.2010.05.011.
Wasfi R, Steinmetz-Wood M, Kestens Y. Place matters: a longitudinal analysis measuring the association between neighbourhood walkability and walking by age group and population center size in Canada. PLos One. 2017;12(12):e0189472. https://doi.org/10.1371/journal.pone.0189472.
Witten K, Blakely T, Bagheri N, Badland H, Ivory V, Pearce J, et al. Neighborhood built environment and transport and leisure physical activity: findings using objective exposure and outcome measures in New Zealand. Environ Health Perspect [Internet]. 2012;120(7):971–7 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864121850&doi=10.1289%2Fehp.1104584&partnerID=40&md5=2e3cd9eb4fb40f9b2c02bb00709f38f7.
Yi LY, Samat N, Wan Muda WM. Accelerometer-measured physical activity and its relationship with body mass index (BMI) and waist circumference (WC) measurements: a cross-sectional study on Malaysian adults. Malays J Nutr. 2017;23(3):397–408 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040450954&partnerID=40&md5=1b7d7b6d9f0d50aaadfdeb13eebb62fb.
Cole R, Dunn P, Hunter I, Owen N, Sugiyama T. Walk score and Australian adults’ home-based walking for transport. Heal Place. 2015;35:60–5 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84939201361&doi=10.1016%2Fj.healthplace.2015.06.011&partnerID=40&md5=8f27078ae4b84a49aed709966edb9db9.
Cruise SM, Hunter RF, Kee F, Donnelly M, Ellis G, Tully MA. A comparison of road- and footpath-based walkability indices and their associations with active travel. J Transp Heal. 2017;6(July 2016):119–27.
Buck C, Tkaczick T, Pitsiladis Y, De Bourdehaudhuij I, Reisch L, Ahrens W, et al. Objective measures of the built environment and physical activity in children: from walkability to Moveability. J Urban Heal. 2014;92(1):24–38.
D’Haese S, Gheysen F, De Bourdeaudhuij I, Deforche B, Van Dyck D, Cardon G. The moderating effect of psychosocial factors in the relation between neighborhood walkability and children’s physical activity. Int J Behav Nutr Phys Act. 2016;13(1):1–16. https://doi.org/10.1186/s12966-016-0452-0.
Janssen I, King N. Walkable school neighborhoods are not playable neighborhoods. Heal Place. 2015;35:66–9.
Kligerman M, Sallis JF, Ryan S, Frank LD, Nader PR. Association of neighborhood design and recreation environment variables with physical activity and body mass index in adolescents. Am J Heal Promot. 2007;21(4):274–7 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-33947205048&doi=10.4278%2F0890-1171-21.4.274&partnerID=40&md5=84fc91bb3a78ea5d52439228d97ceed6.
Lovasi GS, Jacobson JS, Quinn JW, Neckerman KM, Ashby-Thompson MN, Rundle A. Is the environment near home and school associated with physical activity and adiposity of urban preschool children? J Urban Heal. 2011;88(6):1143–57 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84855256118&doi=10.1007%2Fs11524-011-9604-3&partnerID=40&md5=da0ac15c6a6a44c624367148783f6e67.
Maddison R, Hoorn SV, Jiang Y, Mhurchu CN, Exeter D, Dorey E, et al. The environment and physical activity: the influence of psychosocial, perceived and built environmental factors. Int J Behav Nutr Phys Act. 2009;6 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-66149156287&doi=10.1186%2F1479-5868-6-19&partnerID=40&md5=30ece99f4521edd5a1e36c7c2e1123b5.
McCormack GR, Giles-Corti B, Timperio A, Wood G, Villanueva K. A cross-sectional study of the individual, social, and built environmental correlates of pedometer-based physical activity among elementary school children. Int J Behav Nutr Phys Act. 2011;8:30.
McGrath LJ, Hinckson EA, Hopkins WG, Mavoa S, Witten K, Schofield G. Associations between the neighborhood environment and moderate-to-vigorous walking in New Zealand children: findings from the URBAN study. Sport Med. 2016;46(7):1003–17 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964335433&doi=10.1007%2Fs40279-016-0533-x&partnerID=40&md5=cd90742b34242d7a52159a95e33df5a1.
Molina-Garcia J, Queralt A, Adams MA, Conway TL, Sallis JF. Neighborhood built environment and socioeconomic status in relation to multiple health outcomes in adolescents. Prev Med (Baltim). 2017;105:88–94 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028953352&doi=10.1016%2Fj.ypmed.2017.08.026&partnerID=40&md5=d08570d3dddd0f352faca0291c68ae3e.
Molina-García J, Queralt A. Neighborhood built environment and socioeconomic status in relation to active commuting to School in Children. J Phys Act Health. 2017;14(10):761–5 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028998736&doi=10.1123%2Fjpah.2017-0033&partnerID=40&md5=099bb187734dd8e2fa221d6d0d61e8c7.
Oliver M, Mavoa S, Badland H, Parker K, Donovan P, Kearns RA, et al. Associations between the neighbourhood built environment and out of school physical activity and active travel: an examination from the kids in the City study. Heal Place. 2015;36:57–64 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942769038&doi=10.1016%2Fj.healthplace.2015.09.005&partnerID=40&md5=c8885b7e8b876049c21b9b667499a438.
Perez LG, Conway TL, Arredondo EM, Elder JP, Kerr J, McKenzie TL, et al. Where and when adolescents are physically active: neighborhood environment and psychosocial correlates and their interactions. Prev Med (Baltim). 2017;105:337–44 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030850491&doi=10.1016%2Fj.ypmed.2017.10.010&partnerID=40&md5=8fcb96d40f4058ed5568d3d8b9df09e0.
D’Haese S, Van Dyck D, De Bourdeaudhuij I, Deforche B, Cardon G. The association between objective walkability, neighborhood socio-economic status, and physical activity in Belgian children. Int J Behav Nutr Phys Act. 2014;11(1):7–14.
Ross SET, Clennin MN, Dowda M, Colabianchi N, Pate RR, Taverno Ross SE, et al. Stepping it up: walking behaviors in children transitioning from 5th to 7th grade. Int J Environ Res Public Health. 2018;15(2) Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041480364&doi=10.3390%2Fijerph15020262&partnerID=40&md5=28bea1895347d6b8e4ca6e05cb046b8a.
Wang X, Conway TL, Cain KL, Frank LD, Saelens BE, Geremia C, et al. Interactions of psychosocial factors with built environments in explaining adolescents’ active transportation. Prev Med (Baltim). 2017;100:76–83 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017630623&doi=10.1016%2Fj.ypmed.2017.04.008&partnerID=40&md5=91938048ec32c9fa5066f8205bb4942f.
De Meester F, Van Dyck D, De Bourdeaudhuij I, Deforche B, Cardon G. Do psychosocial factors moderate the association between neighborhood walkability and adolescents’ physical activity? Soc Sci Med. 2013;81:1–9.
De Meester F, Van Dyck D, De Bourdeaudhuij I, Deforche B, Sallis JF, Cardon G. Active living neighborhoods: is neighborhood walkability a key element for Belgian adolescents? BMC Public Health. 2012;12(1):7 Available from: http://www.biomedcentral.com/1471-2458/12/7.
Giles-Corti B, Wood G, Pikora T, Learnihan V, Bulsara M, Van Niel K, et al. School site and the potential to walk to school: the impact of street connectivity and traffic exposure in school neighborhoods. Heal Place. 2011;17(2):545–50 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952539236&doi=10.1016%2Fj.healthplace.2010.12.011&partnerID=40&md5=116a7445625554c66f0185511745d8e1.
Graziose MM, Gray HL, Quinn J, Rundle AG, Contento IR, Koch PA. Association between the built environment in school neighborhoods with physical activity among new York City children. Prev Chronic Dis. 2016;13(110):1–11 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991492496&doi=10.5888%2Fpcd13.150581&partnerID=40&md5=8caedf3fb0627a70b493463466e8e219.
Hinckson E, Cerin E, Mavoa S, Smith M, Badland H, Stewart T, et al. Associations of the perceived and objective neighborhood environment with physical activity and sedentary time in New Zealand adolescents. Int J Behav Nutr Phys Act. 2017;14(1):145 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85043360385&doi=10.1186%2Fs12966-017-0597-5&partnerID=40&md5=6a17527e93e54cb71e470f5d45df77fd.
Hobin E, Leatherdale S, Manske S, Dubin J, Elliott S, Veugelers P. A multilevel examination of factors of the school environment and time spent in moderate to vigorous physical activity among a sample of secondary school students in grades 9-12 in Ontario, Canada. Int J Public Health. 2012;57(4):699–709 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864050139&doi=10.1007%2Fs00038-012-0336-2&partnerID=40&md5=f1fab57efc2082df14a683066e31ee08.
Hunter S, Rosu A, Hesketh KD, Rhodes RE, Rinaldi CM, Rodgers W, et al. Objectively measured environmental correlates of toddlers’ physical activity and sedentary behavior. Pediatr Exerc Sci. 2019;31(4):480–7. https://doi.org/10.1123/pes.2018-0270.
Bodeker M. Walking and walkability in pre-set and self-defined neighborhoods: a mental mapping study in Older adults. Int J Environ Res Public Health. 2018;15(7) Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049466191&doi=10.3390%2Fijerph15071363&partnerID=40&md5=a6c4dd4fd88153d1b62a2db742895819.
Todd M, Adams MA, Kurka J, Conway TL, Cain KL, Buman MP, et al. GIS-measured walkability, transit, and recreation environments in relation to older adults’ physical activity: a latent profile analysis. Prev Med (Baltim). 2016;93(1):57–63 Available from: https://linkinghub.elsevier.com/retrieve/pii/S0091743516302778.
Travers C, Dixon A, Laurence A, Niblett S, King K, Lewis P, et al. Retirement Health and lifestyle study: Australian neighborhood environments and physical activity in Older adults. Environ Behav. 2018;50(4):426–53 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044950409&doi=10.1177%2F0013916517707294&partnerID=40&md5=0436c04ba7977ffc7e6a86711fc8bdc1.
Berke EM, Koepsell TD, Moudon AV, Hoskins RE, Larson EB. Association of the built environment with physical activity and obesity in older persons. Am J Public Health. 2007;97(3):486–92 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847729863&doi=10.2105%2FAJPH.2006.085837&partnerID=40&md5=d3b67d7f5edc5916cb1ee6b2b3e4d5ae.
Van Holle V, Van Cauwenberg J, Deforche B, Van de Weghe N, De Bourdeaudhuij I, Van Dyck D. Do psychosocial factors moderate the association between objective neighborhood walkability and older adults’ physical activity? Heal Place. 2015;34:118–25.
Van Holle V, Van Cauwenberg J, Van Dyck D, Deforche B, Van de Weghe N, De Bourdeaudhuij I. Relationship between neighborhood walkability and older adults’ physical activity: results from the Belgian Environmental physical activity study in seniors (BEPAS seniors). Int J Behav Nutr Phys Act. 2014;11(1):1–9.
Winters M, Barnes R, Venners S, Ste-Marie N, McKay H, Sims-Gould J, et al. Older adults’ outdoor walking and the built environment: Does income matter? Environmental health. BMC Public Health. 2015;15(1):876. https://doi.org/10.1186/s12889-015-2224-1.
Zandieh R, Flacke J, Martinez J, Jones P, van Maarseveen M. Do inequalities in neighborhood walkability drive disparities in Older adults’ outdoor walking? Int J Environ Res Public Health. 2017;14(7):740. https://doi.org/10.3390/ijerph14070740.
Carlson JA, Sallis JF, Saelens BE, Frank LD, Kerr J, Cain KL, et al. Interactions between psychosocial and built environment factors in explaining Older adults’ physical activity. Prev Med (Baltim). 2012;54(1):68–73 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84855506359&doi=10.1016%2Fj.ypmed.2011.10.004&partnerID=40&md5=ee6711efac0b5f7302f44a3284f4ed07.
Chudyk AM, McKay HA, Winters M, Sims-Gould J, Ashe MC. Neighborhood walkability, physical activity, and walking for transportation: a cross-sectional study of older adults living on low income. BMC Geriatr. 2017;17(1):1–14.
Clarke P, Hirsch JA, Melendez R, Winters M, Gould JS, Ashe M, et al. Snow and rain modify Neighbourhood walkability for Older adults. Can J Aging. 2017;36(2):159–69.
Frank LD, Kerr J, Rosenberg D, King A. Healthy aging and where you live: community design relationships with physical activity and body weight in older Americans. J Phys Act Heal. 2010;7(SUPPL.1):S82–90 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-77749240194&partnerID=40&md5=a77f58e537c270a8b802e306c06847e1.
Kikuchi H, Nakaya T, Hanibuchi T, Fukushima N, Amagasa S, Oka K, et al. Objectively measured neighborhood walkability and change in physical activity in Older Japanese adults: a five-year cohort study. Int J Environ Res Public Health. 2018;15(9):1814. https://doi.org/10.3390/ijerph15091814.
King AC, Sallis JF, Frank LD, Saelens BE, Cain K, Conway TL, et al. Aging in neighborhoods differing in walkability and income: associations with physical activity and obesity in older adults. Soc Sci Med. 2011;73(10):1525–33.
Liao Y, Lin C-Y, Lai T-F, Chen Y-J, Kim B, Park J-H. Walk score® and its associations with older adults’ health behaviors and outcomes. Int J Environ Res Public Health. 2019;16(4) Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061972589&doi=10.3390%2Fijerph16040622&partnerID=40&md5=f9b36cb969d6e8547b340cd12aa1324f.
Marquet O, Hipp JA, Miralles-Guasch C. Neighborhood walkability and active ageing: a difference in differences assessment of active transportation over ten years. J Transp Heal. 2017;7(September):190–201 Available from: http://linkinghub.elsevier.com/retrieve/pii/S221414051730097X.
Michael YL, Carlson NE. Analysis of individual social-ecological mediators and moderators and their ability to explain effect of a randomized neighborhood walking intervention. Int J Behav Nutr Phys Act. 2009;6 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-69249117823&doi=10.1186%2F1479-5868-6-49&partnerID=40&md5=484f870f40e9773d5a5562111790c9a0.
Michael YL, Gold R, Perrin NA, Hillier TA. Built environment and lower extremity physical performance: prospective findings from the study of osteoporotic fractures in women. J Aging Health. 2011;23(8):1246–62 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-81755181122&doi=10.1177%2F0898264311412597&partnerID=40&md5=3dca5d06ee81f500bc24d8bd13baa7ca.
Nyunt MSZ, Shuvo FK, Eng JY, Yap KB, Scherer S, Hee LM, et al. Objective and subjective measures of neighborhood environment (NE): relationships with transportation physical activity among older persons. Int J Behav Nutr Phys Act. 2015;12(1):1–10 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84941646860&doi=10.1186%2Fs12966-015-0276-3&partnerID=40&md5=7c002d006e739b1936961418db9c4343.
Portegijs E, Keskinen KE, Tsai L-T, Rantanen T, Rantakokko M. Physical limitations, walkability, perceived Environmental facilitators and physical activity of Older adults in Finland. IntJ Environ Res Public Heal. 2017;14(3):333. https://doi.org/10.3390/ijerph14030333.
Strath SJ, Greenwald MJ, Isaacs R, Hart TL, Lenz EK, Dondzila CJ, et al. Measured and perceived environmental characteristics are related to accelerometer defined physical activity in older adults. Int J Behav Nutr Phys Act. 2012;9:40.
Takahashi PY, Baker MA, Cha S, Targonski PV. A cross-sectional survey of the relationship between walking, biking, and the built environment for adults aged over 70 years. Risk Manag Healthc Policy. 2012;5:35–41 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864493229&partnerID=40&md5=ab50807ea61d29162278b3ada94491d2.
Lotfi S, Koohsari MJ. Neighborhood walkability in a City within a developing country. J Urban Plan Dev -ASCE. 2011;137(4):402–8 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84855929670&doi=10.1061%2F%28ASCE%29UP.1943-5444.0000085&partnerID=40&md5=eba4b17b3dfa21ff2415561de8739901.
Van Holle V, Van Cauwenberg J, Gheysen F, Van Dyck D, Deforche B, Van De Weghe N, et al. The association between Belgian older adults’ physical functioning and physical activity: what is the moderating role of the physical environment? Plos One. 2016;11(2):1–17 Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960532651&doi=10.1371%2Fjournal.pone.0148398&partnerID=40&md5=9d57944905c7328fed5dd7ab3e695ce8.
Sun F, Norman IJ, While AE. Physical activity in older people- a systematic review. BMC Public Health. 2013;13(449):1–17.
García-Peña C, Espinel-Bermúdez C, Tella-Vega P, Pérez-Zepeda MU, Gutiérrez-Robledo LM. Longitudinal studies and older adults cohorts. In: Aging research - methodological issues. 2nd ed; 2018. p. 95–113.
Pires IM, Garcia NM, Pombo N, Flórez-Revuelta F. Limitations of the use of mobile devices and smart environments for the monitoring of ageing people. ICT4AWE 2018 - Proc 4th Int Conf Inf Commun Technol Ageing Well e-Health. 2018;2018-March (Ict4awe 2018):269–75.
Garatachea N, Luque GT, Gallego JG. Physical activity and energy expenditure measurements using accelerometers in older adults. Nutr Hosp. 2010;25(2):224–30.
Hirsch JA, Winters M, Clarke P, McKay H. Generating GPS activity spaces that shed light upon the mobility habits of older adults: a descriptive analysis. Int J Health Geogr. 2014;13:51.
Meijering L, Weitkamp G. Numbers and narratives: developing a mixed-methods approach to understand mobility in later life. Soc Sci Med. 2016;168:200–6. https://doi.org/10.1016/j.socscimed.2016.06.007.
Alves F, Cruz S, Ribeiro A, Silva AB, Martins J, Cunha I. Walkability index for elderly health: a proposal. Sustainability (Switzerland). 2020;12(18):7360. https://doi.org/10.3390/SU12187360.
Rosso AL, Harding AB, Clarke PJ, Studenski SA, Rosano C. Associations of neighborhood walkability and walking behaviors by cognitive trajectory in Older adults. Gerontologist. 2021;XX(Xx):1–9.
Ståhl A, Carlsson G, Hovbrandt P, Iwarsson S. “Let’s go for a walk!”: identification and prioritisation of accessibility and safety measures involving elderly people in a residential area. Eur J Ageing. 2008;5(3):265–73.
Akinci ZS, Delclòs-Alió X, Vich G, Miralles-Guasch C. Neighborhood urban design and outdoor later life: an objective assessment of out-of-home time and physical activity among older adults in Barcelona. J Aging Phys Act. 2021:1–12.
Jackson LE. The relationship of urban design to human health and condition. Landsc Urban Plan. 2003;64:191–200.
Vich G, Delclòs-Alió X, Maciejewska M, Marquet O, Schipperijn J, Miralles-Guasch C. Contribution of park visits to daily physical activity levels among older adults : evidence using GPS and accelerometery data. Urban For Urban Green. 2021;63(127225). https://doi.org/10.1016/j.ufug.2021.127225.
Miralles-Guasch C, Dopico J, Delclòs-Alió X, Knobel P, Marquet O, Maneja-Zaragoza R, et al. Natural landscape, infrastructure, and health: the physical activity implications of urban green space composition among the elderly. Int J Environ Res Public Health. 2019;16(20):3986. https://doi.org/10.3390/ijerph16203986.
Cao Y, Heng CK, Fung JC. Using walk-along interviews to identify environmental factors influencing older adults’ out-of-home behaviors in a high-rise, high-density neighborhood. Int J Environ Res Public Health. 2019;16(21) Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074550953&doi=10.3390%2Fijerph16214251&partnerID=40&md5=956700d0df5dca445270a0bec1db7390.
Kwan MP. The limits of the neighborhood effect: contextual uncertainties in geographic, Environmental Health, and social science research. Ann Am Assoc Geogr. 2018;108(6):1482–90.
Adkins A, Makarewicz C, Scanze M, Ingram M, Luhr G. Contextualizing walkability: do relationships between built environments and walking vary by socioeconomic context? J Am Plan Assoc. 2017;83(3):296–314. https://doi.org/10.1080/01944363.2017.1322527.
Rao VCS. The use of English language in research. J Res Sch Prof English Lang Teach. 2018;2(8):8.
Elshahat S, O’Rorke M, Adlakha D. Built environment correlates of physical activity in low- and middle-income countries: a systematic review. Plos One. 2020;15(3):1–19. https://doi.org/10.1371/journal.pone.0230454.
Acknowledgements
We would like to thank research librarian Rafael Giráldez Quesada at Universitat Autònoma de Barcelona for his recommendations. We also would like to thank Dr. Matthew Copley for his professional proofreading services and his editing suggestions.
Funding
This work was supported by “Proyectos I+D+I - Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad” by the Spanish Ministry of Science and Innovation (Ministerio de Ciencia i Innovación) (PID2019-104344RB-I00). Zeynep S. Akinci has been supported by a PhD grant by the Agency for Management of University and Research Grants (AGAUR, 2019 FI_B 00039), provided by Generalitat de Catalunya. Xavier Delclòs-Alió received funding from the Ministry of Science and Innovation of Spain under the “Ayudas para contratos Juan de la Cierva-formación 2019” (FJC2019–039725-I). Guillem Vich received financial support from the Ministry of Science and Innovation of Spain under the “Ayudas para contratos Juan de la Cierva-formación 2019” grants (FJC2019–041233-I), and the “Centro de Excelencia Severo Ochoa 2019-2023” Program (CEX2018–000806-S).
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ZSA: design of the work, analysis, interpretation of data, preparing draft of the manuscript, revisions. XDA: conception, interpretation of data, design of the work, revisions. GV: conception, design of the work, revisions. DS: conception, design of the work, revisions. JI: conception, design of the work, revisions. CMG: conception, design of the work, revisions, funding acquisition. The author(s) read and approved the final manuscript.
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Akinci, Z.S., Delclòs-Alió, X., Vich, G. et al. How different are objective operationalizations of walkability for older adults compared to the general population? A systematic review. BMC Geriatr 22, 673 (2022). https://doi.org/10.1186/s12877-022-03233-x
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DOI: https://doi.org/10.1186/s12877-022-03233-x