Akinci et al. BMC Geriatrics (2022) 22:673 https://doi.org/10.1186/s12877-022-03233-x RESEARCH Open Access How different are objective operationalizations of walkability for older adults compared to the general population? A systematic review Zeynep S. Akinci1*, Xavier Delclòs‑Alió2, Guillem Vich1,3, Deborah Salvo4, Jesús Ibarluzea5,6,7,8 and Carme Miralles‑Guasch1,9 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 envi‑ ronment, the literature still lacks comparison reviews focusing specifically on objective operationalizations of walkabil‑ ity for older adults vs. the general population. Methods: We conducted a systematic review of 146 empirical studies that measured walkability objectively in rela‑ tion 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 propor‑ tion 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 *Correspondence: zeynepsila.akinci@uab.cat 1 Grup d’Estudis en Mobilitat, Transport i Territori (GEMOTT), Departament de Geografia, Universitat Autònoma de Barcelona, Edifici B, Campus de Bellaterra, 08193 Cerdanyola del Vallès, Barcelona, Spain Full list of author information is available at the end of the article © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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Keywords: Walkability, Older adults, Walking, Physical activity, Systematic literature review, Built environment Introduction variations for different pedestrian groups, such as chil- Walking is one of the most accessible, economically via- dren, adults, older adults, or impaired pedestrians, are ble, democratic, communal, sustainable, environmentally also highlighted [12, 15]. Some studies have employed friendly, and healthiest forms of transportation [1–4]. It subjective measures (e.g., perceptions), while others have is also the easiest way of including physical activity (PA) preferred measuring walkability objectively (e.g., by using into daily life routines while helping to achieve recom- Geographic Information Systems - GIS). Although some mendations for a physically and mentally healthy life (i.e., studies on adults presented partial agreement between 150–300 minutes/ week of moderate-intensity activity for subjective and objective measures of walkability [16], adults aged 18–64 years, and a minimum of 150 minutes/ high misperception levels were also highlighted in other week for persons ≥65 years) [5, 6]. Additionally, for spe- studies [17]. Studies on older adults that used objective cific population groups, such as older adults (≥65 years), measures in their analysis generally presented stronger walking is the most common, if not the only, type of PA associations [12, 18]. [7]. Yet, engaging in this activity is related to various Various reviews on walkability studies have to date factors. focused on how differently walkability is defined in the Among many other factors, walking depends on who literature [11, 13], how it is operationalized, and how is undertaking this activity (i.e., the characteristics of it could contribute to more PA engagement [19–23], individuals). Some population groups, for instance, or on the trends that walkability research has followed older adults, are less involved in this activity due to fac- throughout the years [14]. Some reviews narrowed down tors such as increased physical limitations compared their scope to specific groups such as adults [24] or chil- to other age groups. Walking also depends on where it dren [15]. Despite the high importance of walking among takes place, since the characteristics of an environment older adults and theirs being the most sedentary group could encourage or limit this activity. Some environmen- (with about 60 to 80% of their daily time spent physi- tal features, such as dimly lit streets, steps, steep hills, cally inactive), to the best of our knowledge, none of the or broken pavements might become a barrier for walk- systematic reviews on the PA of older adults [25–29] ing among some groups such as older adults more than focused specifically on walkability, but rather included others [8], due to the decrease in the level of “individual various built environment characteristics in their stud- competence” [9] to cope with the “environmental press” ies. Only one systematic review focused on the relation- ([9], pp.25, [10], pp385–396). Thus, some environments ship between walkability and the PA of older adults [30]; could be more “walking-friendly” or walkable than oth- however, their specific aim was to examine the impacts ers, for different types of individuals. of stairs on this relationship. Thus, we believe that there The definition of walkability varies vastly in the litera- is a need for a systematic review which summarizes how ture, and depends on “who is asking” [11] or personal objective walkability has been operationalized to date, its perspective. The most common definition has been the relationship with walking outcomes, and how these dif- walking/ pedestrian friendliness of a given place [12]. fered for older adults, for whom walking is particularly However, more detailed definitions such as how travers- essential. By detecting the gaps in the literature, and able, compact, safe, lively and sociable, physically entic- summarizing the methodologies of previous studies, this ing, or exercise-inducing an environment is, have also review could help to inform future literature reviews and been used [13]. Walkability has also been defined as a empirical analyses that share similar aims. Additionally, complex and multidimensional concept, whose dimen- by highlighting how objective walkability measures differ sions are measurable “individually or combined into an for older adults compared to the general population, this index” [13]. Studies measuring walkability of a place have review could also offer insight for urban designers, plan- received greater scholarly attention in the last decades in ners, and/or local governments. different countries, under the scope of various research Following this introduction, the next section provides fields, and using a wide array of variables and opera- a description of the methodology employed for this sys- tionalization methods [14]. Many studies have associ- tematic literature review. Then in the results section, we ated walkability with PA outcomes, and while the results first present the pattern of demographic groups included generally show a positive association between the two, in all reviewed publications, and then we compare the Akinci et al. BMC Geriatrics (2022) 22:673 Page 3 of 22 descriptive results from papers focusing only on older papers among the authors took place until a joint deci- adults and those exploring the general population. sion was made. Finally, we discuss these results, and end the paper with concluding remarks. Data extraction and content analysis For all included publications (n = 146) data were Methods extracted and assessed under five main categories. The Search strategy reasons and details of the categorization and coding used This systematic review followed the PRISMA (Preferred in these categories are explained briefly below, and in Reporting Items of Systematic Review and Meta-Analy- detail in Supplementary Material. sis) guidelines [31]. First, we defined a query logic based on keywords related to walkability and walking-related 1) General study characteristics: Publication year, PA. Second, we ran initial tests in different databases, Journal field, Geographical context (study setting), and conducted the final search on June 25, 2019, in three Demographic group under study. electronic databases: PubMed, Scopus, and Web of Sci- 2) Characteristics of the study design: Research design ence (WoS) (Fig. 1). In order to include the seminal pub- (cross-sectional, longitudinal, or mixed), Spatial data lications meeting our criteria, we did not set a start date collection method (GIS or audit), Outcome data for the search. collection method (objective, subjective, or mixed methods). Inclusion and exclusion criteria 3) Characteristics of walkability measures: Operational- Papers were included only if they were, 1) focusing on ization of walkability (indexes or separate variables), measuring walkability (i.e., only those with an explicit Walkability variables used. mention of walkability in their titles or abstracts, meth- 4) Spatial extent and unit: Spatial extent (residential ods, and results sections, excluding those using walk- area, school site, etc.), Spatial unit (administrative ability only for sample recruitment, for instance); 2) units, statistical units, buffers, etc.), Buffer type (cir- measuring walkability objectively (with GIS, or environ- cular, street network, or sausage buffer), and buffer mental/ street audits conducted by trained people); 3) size. having subjectively or objectively measured (e.g., by using 5) Associations found between walkability and walk- self-reports or accelerometers) walking-related outcomes ing-related outcomes (coded as positive, negative, no (excluding those combining different types of PA, such as association, mixed -for studies providing results for cycling, gardening, skating, etc., under one category such different population groups or settings- or partial as total PA or active commuting); 4) relating these walk- -for studies providing results for different buffer sizes ing-related outcomes with walkability; 5) original empiri- or different walking-related outcomes and/or, studies cal research published in peer-reviewed journals; and 6) providing different associations for each walkability written in English. variable used, and when this difference is not acute, e.g., two no associations, two positive, and three neg- Study selection ative associations). Study selection was conducted in four phases for the first part of the review (Fig. 1). After removing the dupli- After analyzing the contents of all publications meeting cates from the total records retrieved from the database our criteria (n = 146) according to the abovementioned search (n = 3279), we first included 2008 manuscripts in fields, we stratified the analysis to compare publications the phase of title screening and then abstract screening focusing only on older adults (n = 24), and the general for relevance. According to the selection criteria, a total population (n = 122). of 1625 papers were excluded at these phases. Then full texts of the remaining papers (n = 383) were reviewed. Results Given the detailed information gathered at this stage, a Among all publications included in the content analy- further 237 papers were excluded. Finally, the remain- sis (n = 146), 50.7% (n = 74) focused on adults, although ing 146 papers were included in the content analysis. For the definition of this group varied vastly across studies consistency, all phases were completed by the first author (See Supplementary Material, Section 1.1.4 for further (ZSA). After each phase, the second and third authors information). 17.8% (n = 26) focused on “all population” (XDA and GV, respectively) individually screened a ran- in their analysis while 15.1% focused on young peo- dom selection of 20% of the publications to eliminate ple (n = 22). Finally, publications focusing on older the risk of bias and confirm the correctness of the selec- adults formed 16.4% of the analyzed studies, with 24 tion. In case of doubt or disagreement, discussions of the publications. Akinci et al. BMC Geriatrics (2022) 22:673 Page 4 of 22 Fig. 1 PRISMA flow chart for systematic literature search and search terms used in the three databases The results of the content analysis are presented in remarkably in this period (Table 1). The oldest publica- Table 1, Table 2, and Table 3. In addition, Table 4 pre- tions meeting our criteria dated from 2007 among studies sents detailed list of publications in relation to all vari- focusing on older adults, and from 2005 among general ables included in the content analysis. population-focused studies. General study characteristics Journal field Publication year More than half of the studies in both literature groups were Most of the studies focusing on both older adults and published in health-related journals (Table 1), followed by the general population were published in the last decade, inter- or multi-disciplinary journals, transportation or urban and the number of publications in both groups increased studies, and environment- or geography-related journals. Akinci et al. BMC Geriatrics (2022) 22:673 Page 5 of 22 Table 1 Proportion of different variables included in the analysis among papers focusing on older adults vs. the general population General study characteristics Older adults n = 24 (100%) General population n = 122 (100%) Publication year 2016–2019 11 (45.8) 57 (46.7) 2011–2015 10 (41.7) 53 (43.4) 2005–2010 3 (12.5) 12 (9.8) Journal field Health 13 (54.2) 77 (63.1) Inter- or multi-disciplinary 9 (37.5) 38 (31.1) Transportation or urban studies 1 (4.2) 4 (3.3) Environment or geography 1 (4.2) 3 (2.5) Geographical context US and Canada 12 (50.0) 68 (55.7) Europe 7 (29.2) 25 (20.5) Middle East and Asia 4 (16.7) 4 (3.3) Oceania 1 (4.2) 21 (17.2) Latin America 0 (0.0) 2 (1.6) Multiple country 0 (0.0) 2 (1.6) Characteristics of the study design Research design Cross-sectional 18 (75.0) 105 (86.1) Longitudinal 5 (20.8) 16 (13.1) Mixed 1 (4.2) 1 (0.8) Spatial data collection method GIS 22 (91.7) 114 (93.4) Audits 2 (8.3) 8 (6.6) Outcome data collection method Self-reported 14 (58.3) 70 (57.4) Device 3 (12.5) 31 (25.4) Mixed 7 (29.2) 21 (17.2) Characteristics of the walkability measures Operationalization of walkability Index 19 (79.2) 112 (91.8) Separate variables 5 (20.8) 10 (8.2) Spatial extent and unit Spatial extent Residential 24 (100.0) 107 (87.7) School site 0 (0.0) 5 (4.1) Residential + Workplace 0 (0.0) 4 (3.3) Residential + School site 0 (0.0) 3 (2.5) Other 0 (0.0) 3 (2.5) Spatial unit Buffer 17 (70.8) 82 (67.2) Statistical units 4 (16.7) 25 (20.5) Administrative units 3 (12.5) 9 (7.4) Combination 0 (0.0) 3 (2.5) Other 0 (0.0) 3 (2.5) Associations found between walkability and walking-related outcomes Positive 15 (62.5) 74 (60.7) No association 5 (20.8) 18 (14.8) Akinci et al. BMC Geriatrics (2022) 22:673 Page 6 of 22 Table 1 (continued) General study characteristics Older adults n = 24 (100%) General population n = 122 (100%) Partial 3 (12.5) 20 (16.4) Mixed 1 (4.2) 5 (4.1) Negative 0 (0.0) 5 (4.1) Table 2 Proportion of walkability variables used among papers focusing on older adults vs. the general population Older adults (n = 167 variables used in 24 studies) General population (n = 518 n (%) variables used in 122 studies) n (%) Land use characteristics 56 (33.5) 85 (16.4) Safety from traffic 20 (12) 26 (5) Street connectivity 19 (11.4) 116 (22.4) Street design 19 (11.4) 55 (10.6) Activity and destination density and access to services 18 (10.8) 92 (17.8) Population density 15 (9) 86 (16.6) Safety from crime 8 (4.8) 14 (2.7) Greenery 8 (4.8) 20 (3.9) Transportation accessibility 3 (1.8) 16 (3.1) Topographic characteristics 1 (0.6) 6 (1.2) Socioeconomic characteristics 0 (0) 2 (0.4) Geographical context Spatial data collection method The most used settings in walkability studies among both The vast majority of studies focusing on both older adults older adults- and general population-focused publica- (91.7%) and the general population (93.4%) used GIS tions were the US and Canada (50 and 55.7% respectively) to collect their spatial data (Table 1). The share of audit (Table 1). This was followed by Europe in both groups usage among older adults-focused studies (8.3%) was (29.2 and 20.5% respectively). However, among publica- slightly higher compared to the share among studies tions focusing on older adults, 16.7% were conducted in focusing on the general population (6.6%). 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 gen- Outcome data collection method eral population was Oceania with 17.2% of the studies Most of the outcome data was collected by self-reports in included in this group, while only one study focusing on both literature groups (Table 1). Among studies focusing older adults was conducted in this geographical context on the general population, device usage showed a higher with a share of 4.2%. share (25.4%) compared to the share among publications focusing on older adults (12.5%). However, using mixed Characteristics of the study design methods to collect walking-related outcome data pre- Research design sented a higher share among older adults-focused studies Most studies in both groups of literature were designed (29.2%). 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 Characteristics of the walkability measures longitudinal studies showed a higher percentage (20.8%) Operationalization of walkability compared to that among general population-focused Studies mostly used indexes to operationalize walkabil- publications (13.1%). ity among older adults and the general population, with Akinci et al. BMC Geriatrics (2022) 22:673 Page 7 of 22 Table 3 Proportion of buffer types and sizes used among connectivity (11.4%), street design (11.4%), and activity studies focusing on older adults vs. general population and destination density (10.8%) were the next most used Buffer type Older adults (n = 17 General population categories of walkability variables among publications buffer types used (n = 91 buffer types focusing on older adults. Population density presented a in 17 studies using used in 82 studies share of 9%, while greenery and safety from crime each buffers) n (%) using buffers) n (%) formed 4.8%, respectively, of the publications in this Street network buffer 9 (53) 47 (51.6) group. Variables related with transportation accessibility Circular buffer 8 (47) 42 (46.2) and topographic characteristics were the least preferred, Sausage buffer 0 (0) 2 (2.2) while no variables related to socioeconomic characteris- Buffer size Older adults (n = 20 General population tics were used among older adults-focused publications. buffer sizes used in 17 (n = 125 buffer sizes Among publications focusing on the general population studies using buffers) used in 82 studies n (%) using buffers) n (%) (n = 122), a total of 518 variables were used to measure 50 m 0 (0) 1 (1) walkability. The most common variables were related to 200 m 1 (5) 1 (1) street connectivity (22.4%), and activity and destination 250 m 0 (0) 1 (1) density (17.8%). Following these, 16.6% of the walkabil- 400 m 3 (15) 9 (7) ity variables used in this literature group were related to 500 m 3 (15) 9 (7) population density, and 16.4% to land use characteristics. 600 m 0 (0) 1 (1) Variables related to street design formed 10.6%, while 800 m 1 (5) 11 (9) safety from traffic had 5% share. Greenery (3.9%), trans- 1000 m 5 (25) 31 (25) portation accessibility (3.1%), safety from crime (2.7%), 1200 m 0 (0) 1 (1) topographic (1.2%) and socio-economic characteristics 1500 m 0 (0) 2 (2) (0.4%) were also used but to a lower extent compared to 1600 m 0 (0) 14 (11) other categories among this group of publications. See Supplementary Material, Table S2. for walkability 1700 m 0 (0) 1 (1) variables used in each study. 2000 m 1 (5) 4 (3) 2500 m 1 (5) 1 (1) 3000 m 5 (25) 37 (30) Spatial extent and unit 4830 m 0 (0) 1 (1) Spatial extent Buffer size ≤ 1000 m or > 1000 m n (%) All publications on older adults focused on residential ≤ 1000 m 13 (65) 64 (51) areas to measure walkability (Table 1). Among publica- > 1000 m 7 (35) 61 (49) tions on the general population, residential areas were also the most preferred spatial extent with 87.7%. Not- withstanding, 4.1% of the publications in this group used a higher share among the latter (79.2 and 91.8%, respec- school sites, while some had more than one spatial extent tively) (Table 1). The share of using separate variables, in their studies such as residential and workplace or resi- however, was higher among studies focusing on older dential and school site. Lastly, other spatial extents such adults (20.8%) compared to the share among the gen- as daily walking itineraries or routes to parks were also eral population literature (8.2%). The most used indexes used among studies on the general population. among older adults-focused publications were the walk- ability index of Frank et al. (2010) [58], the WalkScore Spatial unit index, and the walkability index of Frank et al. (2005) Most of the publications in both groups used buffers to [59], respectively (data not shown). Among studies focus- measure walkability in their studies (Table 1). This was ing on the general population the most preferred index followed by statistical units (e.g., census block groups, was WalkScore. This was followed by the walkability statistical areas/sectors/tracts, etc.) (16.7% among index of Frank et al. (2010) [58], and new indexes created older adults-focused publications and 20.5% among the by the publications. general population literature) and administrative units (e.g., zip/postal codes, neighborhood boundaries, etc.) Walkability variables used (12.5 and 7.4%, respectively). In 24 publications focusing on older adults, a total of 167 walkability variables were used. Most of the vari- ables in this group of publications (33.5%) related to land Buffer type and size use characteristics (Table 2). This was followed by safety Among 17 older adults-focused studies using buffers, from traffic category with 12%. Following this, street 53% used street network buffers while the rest used Table 4 Content analysis of the reviewed publications Demographic group under study # of articles Reference All population 26 [32–57] Adults 74 [58–131] Akinci et al. BMC Geriatrics Young people 22 [132–153] Older adults 24 [154–177] Publication period # of articles Reference Older adults General population 2005–2010 Older adults: 3 [157, 165, 170] [58, 59, 61, 63, 67, 86, 100, 107, 124, 126, 135, 137] (2022) 22:673 General population: 12 2011–2015 Older adults: 10 [158–160, 162, 167, 171, 172, 174–176] [32, 34–37, 41, 44, 45, 47, 48, 51, 54–56, 60, 64, 66, 68, General population: 53 74, 75, 77, 80, 81, 85, 87, 93, 95, 96, 98, 99, 103, 105, 108, 110–112, 114, 116, 117, 121, 123, 128, 130, 132, 134, 136, 138, 142, 144, 147–149, 152] 2016–2019 Older adults: 11 [154–156, 161, 163, 164, 166, 168, 169, 173, 177] [33, 38–40, 42, 43, 46, 49, 50, 52, 53, 57, 62, 65, 69–73, 76, General population: 57 78, 79, 82–84, 88–92, 94, 97, 101, 102, 104, 106, 109, 113, 115, 118–120, 122, 125, 127, 129, 131, 133, 139–141, 143, 145, 146, 150, 151, 153] Journal field # of articles Reference Older adults General population Health Older adults: 13 [155, 157, 159, 160, 162–165, 170–172, 174, 175] [32, 34, 35, 37, 39, 40, 42, 43, 46, 50, 54, 56, 58, 59, 65, 66, General population: 77 68, 69, 71, 73–77, 80–82, 84, 85, 87, 88, 90–92, 96–101, 103, 104, 106, 108–113, 115, 116, 118–122, 124, 125, 128, 129, 132, 133, 135–141, 143, 144, 146, 148, 150–153] Inter- or multi-disciplinary Older adults: 9 [154, 158, 161, 166–169, 173, 177] [33, 41, 44, 47–49, 51, 52, 55, 57, 62, 63, 67, 70, 72, 78, 79, General population: 38 83, 86, 89, 93–95, 102, 105, 107, 114, 117, 123, 126, 127, 130, 131, 134, 142, 145, 147, 149] Transportation or urban studies Older adults: 1 [176] [45, 53, 61, 64] General population: 4 Environment or geography Older adults:1 [156] [36, 38, 60] General population: 3 Geographical context # of articles Reference Older adults General population US and Canada US Older adults: 9 [155, 157, 162, 165, 167, 170, 171, 174, 175] [32, 38, 42, 45, 49, 50, 55, 58–61, 65, 67, 68, 73–75, 77–79, General population: 46 81–87, 89, 90, 98, 99, 103, 104, 106, 107, 118–122, 135, 136, 143, 145, 146, 150] Canada Older adults: 3 [160, 163, 164] [35, 40, 46, 48, 53, 54, 66, 70–72, 76, 80, 94, 95, 101, 105, General population: 22 109, 125, 127, 134, 152, 153] Europe Austria General population: 1 – [69] Page 8 of 22 Table 4 (continued) Demographic group under study # of articles Reference Belgium Older adults: 3 [158, 159, 177] [123, 124, 126, 133, 144, 147, 148] General population: 7 Czech Republic General population: 1 – [63] Akinci et al. BMC Geriatrics Denmark General population: 1 – [114] Finland Older adults: 1 [173] – France General population: 2 – [62, 97] Germany Older adults: 1 [154] [41, 132] General population: 2 (2022) 22:673 Ireland General population: 1 – [131] Portugal General population: 1 – [102] Spain Older adults: 1 [169] [140, 141] General population: 2 Sweden General population: 4 – [34, 44, 51, 117] United Kingdom Older adults: 1 [161] [57, 92, 113] General population: 3 Middle East and Asia Iran Older adults: 1 [176] – Japan Older adults: 1 [166] [39] General population: 1 Malaysia General population: 1 – [129] Singapore Older adults: 1 [172] – South Korea General population: 2 – [37, 64] Taiwan Older adults: 1 [168] – Oceania Australia Older adults: 1 [156] [36, 47, 52, 56, 88, 91, 93, 96, 100, 110, 111, 115, 116, 130, General population: 16 138, 149] New Zealand General population: 5 – [128, 137, 139, 142, 151] Latin America Brazil General population: 1 – [112] Mexico General population: 1 – [108] Multiple country General population: 2 – [33, 43] Reference Research design # of articles Older adults General population Cross-sectional Older adults: 18 [154–156, 158–165, 168, 169, 172, 174–177] [33–35, 37–39, 41–47, 49–56, 58–71, 73, 75–85, 88, 90, General population: 105 91, 93, 95–105, 107, 108, 110–121, 123–126, 128–144, 146–153] Page 9 of 22 Table 4 (continued) Demographic group under study # of articles Reference Longitudinal Older adults: 5 [157, 166, 167, 170, 171] [32, 36, 40, 48, 57, 72, 74, 86, 87, 89, 94, 106, 109, 122, 127, General population: 16 145] Mixed Older adults: 1 [173] [92] Akinci et al. BMC Geriatrics General population: 1 Spatial data collection method # of articles Reference Older adults General population GIS Older adults: 22 [154, 155, 157–173, 175–177] [32–71, 73–76, 78–82, 84–103, 105–127, 129–138, 140, General population: 114 141, 143–145, 147–153] (2022) 22:673 Audits Older adults: 2 [156, 174] [72, 77, 83, 104, 128, 139, 142, 146] General population: 8 Outcome data collection method # of articles Reference Older adults General population Self-reported Older adults: 14 [154, 156, 157, 160, 164–166, 168–172, 175, 176] [35, 37, 39–41, 45, 47–50, 52–58, 60, 61, 64–67, 69, 70, General population: 70 75–77, 80, 81, 84–88, 91, 93–100, 102, 103, 105, 109–112, 114–116, 119–121, 123, 125, 127, 128, 130, 131, 134, 141, 145, 146, 149, 150, 152] Mixed Older adults: 7 [155, 158, 159, 163, 167, 173, 177] [34, 36, 51, 59, 62, 68, 89, 90, 106, 107, 113, 117, 124, 126, General population: 21 133, 137, 140, 142–144, 153] Device Older adults: 3 [161, 162, 174] [32, 33, 38, 42–44, 46, 63, 71–74, 78, 79, 82, 83, 92, 101, General population: 31 104, 108, 118, 122, 129, 132, 135, 136, 138, 139, 147, 148, 151] Operationalization of walkability # of articles Reference Older adults General population Index Older adults: 19 [154, 157–160, 162–170, 172, 173, 175–177] [33–36, 38–51, 53, 54, 56–59, 61–67, 69–77, 79, 81, 82, General population: 112 84–135, 137–153] Separate variables Older adults: 5 [155, 156, 161, 171, 174] [32, 37, 52, 55, 60, 68, 78, 80, 83, 136] General population: 10 Spatial domain # of articles Reference Older adults General population Residential Older adults: 24 [154–177] [32, 34–37, 40–59, 62–89, 91, 92, 94–133, 135, 138–140, General population: 107 143–148, 151, 153] School site General population: 5 – [134, 137, 149, 150, 152] Residential + Workplace General population: 4 – [39, 61, 90, 93] Residential + School site General population: 3 – [136, 141, 142] Other (whole city, routes to parks, daily walking itinerar‑ General population: 3 – [33, 38, 60] ies) Spatial extent # of articles Reference Older adults General population Page 10 of 22 Table 4 (continued) Demographic group under study # of articles Reference Buffer Older adults: 17 [154–157, 160–166, 168, 170, 172–175] [32–35, 37, 39–44, 46–54, 56, 57, 59, 62, 63, 65–69, 71–76, General population: 82 78–81, 83, 84, 86, 87, 89, 92, 94–98, 101–106, 108, 109, 113, 115, 116, 118–122, 127, 130–132, 134–136, 138, 142, 143, 145, 146, 149, 151, 152] Akinci et al. BMC Geriatrics Statistical units Older adults: 4 [158, 159, 171, 177] [55, 58, 64, 82, 85, 88, 93, 100, 110–112, 114, 123–126, 128, General population: 25 133, 137, 139–141, 144, 147, 148] Administrative units Older adults: 3 [167, 169, 176] [45, 70, 77, 91, 99, 107, 117, 129, 153] General population: 9 Combination General population: 3 – [36, 38, 90] (2022) 22:673 Other (street segments, country level, enrollment General population: 3 – [60, 61, 150] zones) Reference Buffer type # of articles Older adults General population Street network buffer Older adults: 9 [154, 155, 160, 162–166, 174] [32, 34, 36, 37, 39–44, 46, 47, 49, 50, 54, 56, 57, 59, 63, 66, General population: 47 67, 69, 71, 75, 76, 79, 80, 83, 86, 87, 92, 95, 96, 98, 102–104, 108, 113, 116, 131, 132, 135, 138, 142, 143, 146] Circular buffer Older adults: 8 [156, 157, 161, 168, 170, 172, 173, 175] [33, 35, 38, 41, 42, 48, 51, 53, 62, 65, 68–70, 72–75, 78, 79, General population: 42 81, 84, 89, 90, 94, 97, 101, 105, 106, 109, 115, 118–122, 127, 130, 134, 136, 145, 149, 152] Sausage buffer General population: 2 – [52, 151] Combination General population: 4 – [41, 42, 69, 75] *References are also included in related categories above Buffer size # of articles Reference Older adults General population 50 m General population: 1 – [118] 200 m Older adults: 1 [174] [47] General population: 1 250 m General population: 1 – [151] 400 m Older adults: 3 [154, 156, 170] [47, 49, 52, 73, 83, 92, 102, 104, 135] General population: 9 500 m Older adults: 3 [162, 166, 172] [35, 40, 43, 71, 72, 108, 131, 136, 151] General population: 9 600 m General population: 1 – [49] 800 m Older adults: 1 [170] [47, 49, 52, 57, 78, 87, 90, 92, 102, 135, 142] General population: 11 1000 m Older adults: 5 [155, 157, 165, 166, 173] [32, 34, 37, 39, 40, 42–44, 49, 51, 59, 63, 66–69, 79, 103, General population: 31 106, 108, 113, 115, 116, 131, 132, 134, 142, 143, 146, 151, 152] Page 11 of 22 Table 4 (continued) Akinci et al. BMC Geriatrics Demographic group under study # of articles Reference 1200 m General population: 1 – [49] 1500 m General population: 2 – [49, 69] 1600 m General population: 14 – [41, 47, 49, 52, 56, 76, 80, 86, 87, 92, 95, 96, 98, 135] 1700 m General population: 1 – [49] (2022) 22:673 2000 m Older adults: 1 [161] [79, 138, 149, 151] General population: 4 2500 m Older adults: 5 [160, 163, 164, 168, 175] [33, 35, 38, 41, 46, 48, 50, 53, 54, 62, 65, 68, 70, 72–76, 79, General population: 37 81, 84, 89, 90, 94, 97, 101, 105, 106, 109, 115, 119–122, 127, 130, 145] 3000 m Older adults: 1 [157] [79] General population: 1 4830 m General population: 1 – [87] Associations found between walkability and # of articles Reference walking-related outcomes Older adults General population Positive Older adults: 15 [154, 155, 158, 160, 162, 164–167, 169, 171, 173, 174, [33, 34, 36–38, 41–49, 51, 52, 55, 58–64, 66–70, 73–76, General population: 74 176, 177] 78–82, 84, 85, 88, 91, 93–95, 97, 102, 106, 107, 112–117, 119, 120, 123–133, 135, 140–142, 146, 149] No association Older adults: 5 [156, 168, 170, 172, 175] [35, 39, 40, 56, 57, 65, 71, 72, 83, 89, 99, 101, 105, 137, 138, General population: 18 145, 150, 153] Partial Older adults: 3 [159, 161, 163] [50, 53, 54, 77, 87, 90, 92, 96, 98, 100, 103, 110, 111, 121, General population: 20 122, 136, 144, 147, 148, 151] Mixed Older adults: 1 [157] [32, 86, 104, 109, 143] General population: 5 Negative General population: 5 – [108, 118, 134, 139, 152] Page 12 of 22 Akinci et al. BMC Geriatrics (2022) 22:673 Page 13 of 22 circular buffers (Table 3). Some studies used more than operationalization of objective walkability, how it related one buffer size in this group of publications. Among the to walking outcomes, and how this relationship differed 20 buffer sizes used, the most common were 1000 m for older adults compared to the general population, and 2500 m (25% each) (Table 3). This was followed by could shed light to the gaps in the literature and thus be 400 m- and 500 m-buffers, each presenting 15% of the useful for academics interested in this field of research, as total. Buffers equal to or less than 1000 m were pre- well as being insightful for urban designers, planners, and ferred more (65%) than those greater than 1000 m in decision makers to create more inclusive places that con- this group (35%) (See Supplementary Material, Sec- sider the differences of individuals and settings. tion 1.4.3 for detailed information on the selection of In our results, the increase in the number of walkabil- 1000 m as a threshold). ity studies in the last decade is promising. This applies Among 82 papers using buffers in publications focus- for studies focusing on older adults but also the general ing on the general population, a total of 91 buffer types population, as mentioned in previous reviews [20, 27, were used. Among these, 51.6% were street network 28]. However, the fact that in our review many walkabil- buffers, 46.2% were circular buffers, and 2.2% were ity studies in both groups focused on similar geographic sausage buffers. Similar to older adults-focused pub- settings (the US, Canada, and Europe) is of concern in lications, some of the papers focusing on the general terms of generalization of the results, despite the higher population used more than one buffer size in their proportion observed in the number of studies focusing studies. Among the total of 125 buffer sizes used, buff- on older adults conducted in the Middle East and Asia. ers less or greater than 1000 m were almost equally As it was also highlighted in previous studies, translating preferred among the publications in this group. Due to findings from these most common settings could be mis- the high usage of the WalkScore index among the pub- leading, considering the differences in morphologies and lications focusing on the general population, the most land-use configuration between urban contexts across common buffer size was 2500 m (≈1.5 miles) (30%) (See the globe, and the high proportion of studies conducted Supplementary Material, Section 1.4.3 for buffer sizes in high-income countries [12, 20, 26]. For this reason, of WalkScore indexes). This was followed by 1000 m the literature also lacks examples from middle- and low- (25%), 1600 m (≈1 mile) (11%,) and 800 m (≈0.5 mile) income countries or cities, where walking is not only an (9%). 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 Associations found between walkability approach, more studies conducted in different countries and walking‑related outcomes and even different cities of the same country, would bring Most of the publications focusing on both older adults new perspectives to walkability studies by highlighting (62.5%) and the general population (60.7%) found posi- the differences among settings, and their relationship tive associations between walkability and walking-related with walking behavior of the general population and outcomes (Table 1). One fifth of the publications on older adults in particular. older adults found no association while the share was In terms of research design, cross-sectional studies lower among papers focusing on the general population were the most common among both groups of litera- (14.8%). There was no paper with a negative association ture, as was also previously pointed out by other reviews in the literature on older adults, whereas 4.1% of the [27–29, 178]. However, compared to studies focusing on publications on the general population found negative the general population, it is promising that we observed associations between walkability and walking-related a higher ratio of longitudinal studies among older adults- outcomes. Partial associations were found among 12.5% focused publications in our review. As is suggested in of studies focusing on older adults, while this proportion studies of aging, longitudinal designs are essential to was 16.4% among studies on the general population. understand complicated relationships among events or risks and outcomes, as well as to reduce possible biases, Discussion such as selection bias in sampling [179]. Thus, more lon- Understanding, defining and/or measuring walkability gitudinal studies focusing on older adults would bring a is essential for creating more democratic, sustainable, more comprehensive understanding of walkability for and healthy environments. These benefits are particu- this age group in the future, besides providing more reli- larly important for older adults, for whom walking is able results. one of the easiest ways to achieve the recommended In terms of data collection, most of the analyzed stud- daily physical activity levels. Therefore, a review of the ies focusing on older adults used self-report measures Akinci et al. BMC Geriatrics (2022) 22:673 Page 14 of 22 to obtain walking-related outcomes. The ratio of use of adults-focused studies creating their own indexes was technological devices for outcome data collection among lower than that among publications focusing on the gen- older adults-focused studies presented a lower propor- eral population. However, the ratio of the usage of sepa- tion than that of studies focusing on the general popu- rate variables was higher among older adults-focused lation, as was also mentioned in previous reviews [28, studies. Depending on the selection of variables, this 178]. This could be due to the methodological challenges measure could provide more meaningful results for walk- of these devices to capture older adults’ mobility, such ability and its relationship with older adults’ walking, as low battery life, underestimation of PA due to body- rather than using an index which was not designed spe- placement of the device, or difficulties encountered by cifically for this age group. We believe that by using more participants when using these devices [180]. However, specific variables or indexes, not only for the age groups self-report measures have various disadvantages, espe- under study but also for the settings, walkability meas- cially among studies focusing on older adults, such as not ures could become more precise, and this would help capturing all daily activity patterns since individuals may create more walkable areas and promote walking for all. not consider some activities, like dancing, as a type of PA, The most used category of walkability variables among possibility of changes in older adults’ health status and/ studies focusing on older adults were those related to or mood, or problems with memory and cognition that land use characteristics in our review. This was followed could affect accurate recall of PA on a survey [181]. Thus, by variables related to safety from traffic, which are intui- as previous studies suggested, the optimal reliability of tively believed to be specifically relevant to older adults’ results, especially in older adults’ mobility research, could walking and used widely, as stated in a previous review be gathered from the use of objective or mixed methods [26]. The ratio of the usage of variables related with street [182, 183], which promisingly presented a higher propor- design was similar for publications focusing on older tion among older adults-focused papers included in our adults and the general population. Although this category review. included variables found by previous studies to be specif- Regarding the operationalization of walkability, most ically essential for older adults’ walking, such as sidewalk studies in both groups used indexes. The most preferred availability/ width/ material [185], presence of benches index in studies focusing on the general population was [186, 187] or restrooms [28] plus many other examples, WalkScore, as it was also mentioned [21], and criticized usage of these variables did not present considerably previously for being an “insufficient metric for popula- higher proportions among publications focusing on older tion health studies”, and for not capturing “the experien- adults. The ratio of using greenery-related variables was tial nature of walking nor walkability” since it excludes slightly higher among studies focusing on older adults recreational walking ( [14], pp. 3, 8), as well as the lack compared to the general population. This is perhaps of consideration of attributes that would contribute to due to the numerous studies in the literature highlight- walking [20], such as measures related with safety [13]. ing the positive relationship found between the presence Also, this index is only validated in the US and Canada, of green areas (including parks or street trees) and older as stated on their website. Thus, its use in other settings adults’ walking [188–190]. However, the proportion of could be highly misleading. Among studies focusing on using these variables among older adults-focused studies older adults, the most common index was the walkability was still low compared to the importance of this variable index of Frank et al. (2010) [58]. Although the variables for their PA. used in this index (net residential density, retail floor Regarding the spatial extent for measuring walkability, area ratio, land use mix, and intersection density) could different from publications on the general population, be meaningful to some extent to measure walkability in studies on older adults focused only on residential areas some other settings, this study was based on the data in their research. Similarly, the most used spatial units from two US cities and was not created specifically for among studies on older adults were buffers which are older adults. Thus, although the values assigned for each equal to or smaller than 1000m, and administrative units variable in the formula were modified for adaptation in (e.g., neighborhood boundaries/ units, zip/postal codes, some of the reviewed papers [154, 177], its use to study etc,) presented a higher share among this group of lit- this age group and in different settings could also be mis- erature. These results were expected considering that the leading. Although walkability differed widely for older range of activity among older adults mostly decreases adults compared to other pedestrians, as highlighted in to the immediate vicinity of their residences [191], and an empirical research [12] as well as in a recent study doubtless this sheds more importance on the charac- proposing a “walkability index for elderly health” [184], in teristics of the built environment in the neighborhoods. our review, the proportion of publications among older However, this also limits the range of walkability studies Akinci et al. BMC Geriatrics (2022) 22:673 Page 15 of 22 by underestimating individual differences, since not all results. Finally, this review provided comprehensive older adults’ activity range or levels are the same. Addi- information about not only how objective walkability tionally, different types of walking, such as recreational has been defined and measured, which could be insight- walking, could take place farther than the residential ful for governments, but also scrutinized the methodolo- areas, and limiting studies with these extents could easily gies used in walkability studies, which could be useful exclude these types of walking [192]. Thus, more studies for researchers interested in conducting both literature using wider spatial extents and units in the future would reviews and empirical analyses on walkability. However, provide more detailed information on walkability and its this systematic review is not exempt from limitations. relationship with different types of walking, settings, and First, although we included numerous characteristics individuals. of the studies in the content analysis, we did not cover Finally, most of the papers included in our review other characteristics, such as sample size, which could found a positive association between walkability and provide different insights. Future research could con- walking-related outcomes in both groups of publica- sider including this variable in their reviews to enrich tions. Among studies focusing on older adults, publica- the body of literature. Second, selecting papers published tions which found a positive association, as well as those only in English could have resulted in a language-based which did not find any associations showed a higher bias. However, we believe that the reviewed studies and proportion compared to publications focusing on the the analysis presented here are representative, since the general population. The higher proportion of the latter majority of empirical studies worldwide are published in could be explained by the lack of age-specific index usage English [194]. Finally, as mentioned in other reviews [13, among publications focusing on older adults [184]. Using 195] other types of biases, such as spatial selection bias indexes which are not created while considering specific (e.g., residential selection bias, whether people who walk needs of this age group could be limited or even mislead- more choose to live in highly walkable areas), or recall ing in understanding the relationship between walkability bias (e.g., studies using self-reported PA) among the and walking. Regarding the high percentage of positive included studies could have impacted their results and associations found between walking and walkability, thus the results of our review and our interpretations, previous reviews also presented similar results [28, 29]. even indirectly. A review on the general population explained the rea- son for this as the high number of studies conducted in Conclusion high-income countries, since these settings are less likely This review draws attention to how objective walkabil- to have deficiencies in the built environment, such as ity has been operationalized, how it is related to walking poor sidewalk infrastructures, or safety issues, such as outcomes, and how these differed among studies focusing high crime rates, compared to middle- or low-income on older adults and the general population. Despite the settings [20, 193]. Thus, more studies conducted in dif- promising increase in the last decade in the number of ferent countries and even in different cities of a country, publications focusing on walkability for all sorts of popu- especially taking into consideration the possible socio- lation groups, the literature still lacks studies 1) focusing economic differences between cities, would bring a wider on different settings, especially low- and middle-income perspective to the research on walkability, be helpful to settings, 2) using wider spatial extents rather than only overcome the uncertainties in the literature, as well as neighborhood scale, 3) using longitudinal designs, 4) inform governments to create solutions for creating more using objective or mixed methods to collect their out- walkable places for various population groups, and pro- come data related with walking, and 5) creating indexes moting walking in settings with different characteristics. or using separate variables which are specific for settings and population groups, such as older adults. With future Strengths and limitations studies aiming to address these points, walkability studies The first strength of our systematic review is that it could become more comprehensive and provide better focuses particularly on walkability studies. Second, it answers to urban design and planning problems. provides results for older adults and the general popula- The methodologies used and the gaps found in the tion separately, which highlights the differences more and walkability literature highlighted in this review could be helps to find solutions for creating better environments useful for researchers to conduct future reviews, as well for everyone. Third, this review includes only objective as empirical analyses on walkability. Additionally, the operationalization of walkability. Considering the main differences in the definition and operationalization of focus on older adults, this is accepted as one of the most objective walkability for older adults versus the general precise methods [12, 18, 182]; thus we believe that the population summarized in this study could be insightful studies included in this review provided high reliability for not only researchers interested in the field, but also Akinci et al. BMC Geriatrics (2022) 22:673 Page 16 of 22 urban designers, planners, or local governments aiming Universitat Rovira i Virgili, Vila‑seca, Spain. 3 ISGlobal (Barcelona Institute for Global Health), Doctor Aiguader, 88, 08003 Barcelona, Spain. 4 People, to create more walkable places that would meet the needs Health and Place Unit; Prevention Research Center in St. Louis; Brown School; of most population groups, but specifically older adults’, Washington University in St Louis , St. Louis, Missouri, USA. 5 Ministry of Health in different settings. These would enrich the walkability of the Basque Government, Sub-Directorate for Public Health and Addictions of Gipuzkoa, 20013 San Sebastian, Spain. 6 Faculty of Psychology of the Univer‑ literature and contribute to more democratic, sustain- sity of the Basque Country, 20018 San Sebastian, Spain. 7 Spanish Consortium able, and healthy environments, as well as the societies in for Research on Epidemiology and Public Health (CIBERESP), 28029 Madrid, general. Spain. 8 Biodonostia Health Research Institute, Environmental Epidemiology and Child Development Group, 20014 San Sebastian, Spain. 9 Institut de Cièn‑ cia i Tecnologia Ambientals (ICTA), Universitat Autònoma de Barcelona – Edifici Supplementary Information ICTA-ICP, Campus de Bellaterra, 08193 Cerdanyola del Vallès, Barcelona, Spain. The online version contains supplementary material available at https://​doi.​ org/​10.​1186/​s12877-​022-​03233-x. Received: 9 December 2021 Accepted: 9 June 2022 Additional file 1. 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