Older Adults’ Walking Behavior and the Associated Built Environment in Medium-Income Central Neighborhoods of Santiago, Chile

Abstract

The prevalence of car dependence and sedentary lifestyles has created concern in the transportation and health sectors. Walking is the most popular and practical kind of exercise that can significantly enhance health. In Chile, more than half of older adults have health issues and almost 72% of the elderly population never engages in physical activity. This study aims to investigate the relationship between older adults’ walking behavior and the built environment along the streets and parks in Santiago’s middle-income neighborhoods. Six medium-income central and pericentral neighborhoods of Santiago were selected. The average number of older persons who walk along the paths and two modified audit forms were used to measure walking behavior and built environment features, respectively. Both correlation analysis and backward regression were used to examine the associations. While elements like the existence of bus stops, pedestrian streets, and general cleanliness contribute to the enhanced number of older adults who walk along street segments, the presence of insecurity signs was found to be negatively associated with the number of older adults who walk in the neighborhood parks. Furthermore, complexity and mystery showed a negative association with the number of older adults in the neighborhood parks. Urban policymakers might use these findings to encourage older adults to walk more in Santiago’s medium-income neighborhoods.

1. Introduction

The preponderance of sedentary lifestyles and car dependence has raised concerns in both health and transportation fields [1]. Walking is among the most popular and practical of all physical exercises since it does not require any specific equipment, locations, or abilities and can be easily integrated into daily life [2,3,4]. Regular walking has been shown to significantly improve health by lowering the risk of obesity and stroke and enhancing bone health and cognitive function [5,6]. In addition, walking is essential for sustainable mobility, active living, and urban vitality [7,8,9]. Chile is one of the countries with the largest older adult populations in Latin America [10] and more than 82% of the older adult population in this country lives in urban areas in line with global trends [11,12]. Furthermore, in Chile, older persons aged ≥65 years has a higher prevalence of physical inactivity than the younger age groups [13,14]. Almost 72% of the elderly population never engages in physical activity, more than half (51.3%) have health issues that make it difficult for them to perform daily tasks, and less than 5% walk more than 14 blocks (almost 1.5 km) each day [15].

In addition, there has been a growing focus on the built environment’s function in encouraging walking behavior, and related research has shown conclusively that built environment features can influence walking [16,17]. The built environment plays an important role in the improvement in the walking behavior of older adults since they are more sensitive to the suitability of the built environment for walking than other people [16]. The five D variables—Density, Diversity, Design, Destination accessibility, and Distance to transit—can be used to operationalize the characteristics of the macro-scale built environment [18,19]. Researchers usually focus on the individual’s duration and frequency of individual-level walking trips on the neighborhood scale [20] and the precise geographical contexts of individual walking trips are usually unknown in such studies. Accordingly, some studies concentrated on micro-scale streetscape elements (such as sidewalks and vegetation), emphasizing the value of aesthetic features and micro-design elements along paths in enhancing the walking behavior of older persons [21]. At the street level, these environmental factors are more accessible to investigate than at the neighborhood level. Given that numerous studies have shown that Chilean public places are inhospitable to senior citizens, the emphasis on the street scale becomes even more crucial [22,23,24,25]. Moreover, population-level walking behavior, such as pedestrian volume in street segments, can provide a more precise picture regarding the geographical context of the built environment that influences the walking behavior of older adults. It also stimulates urban vitality more effectively in addition to bringing many social, economic, and environmental benefits [5,6].

Furthermore, older individuals mostly use parks and plazas for their daily walking experiences, in addition to the streets and sidewalks. Several studies have examined how older persons walk in these areas [26]. According to Kaplan and Kaplan [27], pedestrians’ visual preferences in such natural and semi-natural environments were typically assessed using the four visual qualities of legibility, complexity, coherence, and mystery [28,29,30]. The visual preferences of older persons along their pathways are likewise associated with their walking experiences in these semi-natural settings [21]. This study aims to investigate the relationships between older persons’ walking behavior and the related street-level built environment features in the central and pericentral communes of Santiago, Chile. These relationships are analyzed in the parks and plazas in the selected neighborhoods as well as on the sidewalks on streets. Additionally, it was demonstrated that these associations may be impacted by the socioeconomic status of neighborhoods [31]. To decrease the impact of neighborhoods with varying socioeconomic status on these relationships, this study focuses on medium-income neighborhoods in Santiago, Chile. The following are this study’s research questions:

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What features of the built environment are linked to the number of senior citizens who walk along Santiago’s median-income neighborhood street segments?

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Are there any design-related aspects associated with older persons’ walking behavior along neighborhood park pathways in Santiago’s median-income neighborhoods?

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Which visual qualities associated with visual preferences are linked to older persons’ walking behavior on local park pathways?

2. Literature Review

2.1. The Built Environment Factors Associated with the Walking Behavior of Older Adults

According to ecological models and previous empirical studies, the built environment plays an important role in improving the walking behavior of older adults [32,33,34]. This is partly because older persons are more sensitive than other groups regarding the appropriateness of the built environment for walking [16]. This sensitivity comes from the vulnerability of older adults and their need for more suitability in built environments such as comfort-related aspects during walking. Previous studies have shown the associations of several built environment factors with the walking behavior of older adults, including population/housing density [35], access to different facilities and attractive places such as retail outlets and restaurants, as well as recreational spaces such as parks and playgrounds in Singapore, England, and the United States [36,37,38]; access to parks and green spaces in Latin American countries such as Brazil and Chile [39,40,41]; the presence of public transit facilities such as proximity to public transport/bus stops [42]; mixed land use in Canada, China, and Hong Kong [43,44,45]; the infrastructure and the functional aspects of walking environments, such as the presence of sidewalks, sidewalk width, sidewalk continuity, well-connected street network, street density, and topography [46]; walking facilities, such as sidewalk quality and benches [47]; safety, including both traffic safety and personal security [48,49]; perceived insecurity in Santiago, Chile [50]; the environmental features that relate to personal security/insecurity including street lighting, the presence of other people, signs of disorders, physical incivilities, and stray animals [39,51,52]; and perceived traffic safety as well as actual safety, including factors such as the percentage of street lengths with speed limits [42,53,54].

Given the need to evaluate older persons’ walking experiences in urban public places with more attention, the aesthetic-and-design-related aspects of path context become especially important [49]. These aesthetic-and-design-related aspects of path context may help to create a more enjoyable walking experience [32] and such interesting or delightful daily walking experiences should be increased on a street scale to improve older persons’ health. Numerous aesthetic-and-design-related factors of path context have been shown to be associated with the walking behavior of older adults including the presence of parks and green spaces and the presence of natural features [38,55,56]; trees along the walkways, front gardens, and levels of greenery [57,58,59]; littering along the sidewalks [59]; the type of building facades and their maintenance [52,60]; the visibility of landmarks, the degree of enclosure, the scale of street space and transparent facades [61]; the length of street sections, off-street parking lot spaces, building height, and articulation in building design in Temuco, Chile [62]; and greater pathway width, more vegetation, tranquility along the pathways, and more comfortable pathway environments for pets in Cautin Park, the biggest urban park in the Araucanian Region of Chile [21]. These aesthetic and design-related path context elements have been studied at both the street and neighborhood scales concerning older adults’ walking experiences. However, studies that concentrated on the street scale provide more accurate data about how these factors affect older adults’ walking experiences.

Regarding the studies conducted in Chile on the walking behavior of older adults, Herrmann-Lunecke et al. [15] found that wide and unobstructed sidewalks, well-designed curb ramps, and pedestrian-friendly crossings encourage walking among older persons. Greenery, trees, benches, public restrooms, and public drinking fountains enhance their walking experience as well. In another study, Herrmann-Lunecke et al. [63], who investigated older persons walking behavior in central neighborhoods of Santiago, found that the presence/absence of greenery, the conditions of the facades, and the level of cleanliness of the streets affect older persons’ walking experience and can increase/diminish their willingness to walk. Also, damaged and poorly designed pedestrian infrastructure can cause fear, provoke accidents, and become serious hazards. Paydar and Kamani Fard [62], who examined the association between the built environment and the walking behavior of older adults in Temuco, Chile, found the associations between the walking behavior of older adults and several built environment factors including destination (the number of parks and the land use mix), functionality (street connectivity, length of street sections, and off-street parking lots), and aesthetics (views of nature, building height, and articulation in building design). Other problems that impede older individuals’ ability to walk in Chilean cities include poorly maintained, narrow sidewalks [64], unfriendly street crossings, and traffic lights with short pedestrian cycles [65]. Other studies have highlighted how the lack of services (e.g., public restrooms) and benches makes walking unpleasant [66]. Furthermore, recent studies also showed an increase in perceived insecurity in different areas of Santiago during the pandemic [67]. Due to security issues, people in Santiago now avoid going out at night (87.5%), implement security measures in their homes (68%), or adjust their departure times (65.7%) [68]. Gajardo et al. [69] and Herrmann-Lunecke et al. [70] concluded that older people travel through Santiago, not because of the amenities they encounter but rather because of the support they receive from friends and family and the individual strategies they have developed to cope with the many obstacles they face.

2.2. The Qualities That Contribute to Visual Landscape Preferences

There is evidence from experimental and empirical studies that exposure to natural surroundings and urban greenery is associated with restoration from stress and mental fatigue [71,72,73]. The scientific underpinnings for this restorative impact of engagement with the natural environment and urban greenery are provided by “Psycho-Physiological Stress Reduction Theory” and “Attention Restoration Theory” [74]. According to the “Psycho-Physiological Stress Reduction Theory,” people who are under significant amounts of stress may benefit from exposure to nature, such as views of natural environments since it can help them feel happier [75,76]. As per Kaplan and Kaplan [27], the “Attention Restoration Theory” posits that involuntary attention to rich and captivating stimuli in natural environments might enhance performance in demanding cognitive tasks.

Studies on visual landscape preferences could also consider the relationship between walking experiences and environmental design elements. One of the most important theories in visual landscape preference research [77,78] is information-processing theory, which argues that two fundamental human reactions to an environment—the need to comprehend and the need to explore—determine a scene’s preference. Kaplan and Kaplan [27] argue that four important information variables—complexity, coherence, mystery, and legibility—determine users’ preferences for visual landscapes. These four important visual preference predictors provide information to understand why people prefer such environments and how comfortable people are in such places. Zhang [30] found that the most favored visual images in public areas are influenced by specific landscape elements including vegetation, such as trees, seasonal flowers, and open grassland, as well as elements of perceived landscape aesthetics, such as coherence and legibility. Cheng [28] discovered that visual landscape preferences are influenced by four aspects of perceived landscape aesthetics: complexity, mystery, coherence, and legibility. Moreover, studies on restorative environments have revealed the role of urban nature in increasing the restorative potential of urban settings as well as the preference for natural overbuilt urban settings [79,80]. According to Pazhouhanfar et al. [81], perceived restorativeness in urban natural settings was positively explained by coherence, complexity, and mystery. These visual qualities might also influence older adults’ walking behavior in local parks.

2.3. Walking Behavior and Socioeconomic Status (SES)

Physical activity and the socioeconomic condition of the neighborhood can be significantly correlated [82]. By reviewing 17 studies, Adkins et al. [31] concluded that socioeconomic status likely influences how the built environment affects walking and physical activity. People who lived in supportive built environments were more likely to walk and be physically active than those who did not, and neighborhoods with higher socioeconomic levels had more walking amenities [31]. On the other hand, neighborhoods with lower income levels are more likely to have low-quality micro-scale features [83]. Despite being among the most prosperous countries in the area, Chile continues to rank among the most unequal in Latin America [84]. Herrmann-Lunecke et al. [84] found that respondents who lived in low-income districts in Santiago reported feeling four times more stressed than those who lived in high-income neighborhoods, highlighting the lack of green spaces and trees in these areas. According to Paydar and Kaman Fard [85], compared to Temuco’s higher-income neighborhoods, there are many more pathways in lower-income areas that people avoid when walking. The inequality, which is apparent in several Chilean cities, emphasizes how the socioeconomic level of neighborhoods influences walking behavior and the social and built environment aspects that are associated with it. Therefore, it is preferable to control the influence of socioeconomic level on such assessment when analyzing the correlations between walking behavior and the street-scale built environment.

2.4. The Literature Review-Based Research Gap

According to the literature review, even though previous studies worldwide demonstrated the importance of 5D-related variables (Density, Diversity, Design, Distance to Destination Accessibility, and Distance to Transit) in the walking behavior of older adults, the studies conducted in Chile demonstrated the greater significance of the aesthetic-and-design-related aspects of path context concerning the walking experience of older adults due to the general lack of appeal of public spaces for walking among older adults in Chile. The population-level walking behavior of senior citizens along the streets and paths of local parks could be used to assess this. Additionally, the significance of specific urban design elements—such as legibility, complexity, coherence, and mystery—that are linked to visual preferences in nearby parks encourages research on the connections between these elements and how older adults walk along park pathways. Furthermore, it is necessary to adjust for the impact of socioeconomic status on the connections between older individuals’ walking habits and the related built environment characteristics. To lessen the impact of neighborhoods with varying socioeconomic status on these relationships, this study selects the neighborhoods with a medium level of socioeconomic status.

3. Methodology

Santiago is the capital and largest city of Chile and one of the largest cities in the Americas. It is located in the country’s central valley and is the center of the Santiago Metropolitan Region, which has a population of seven million, representing 40% of Chile’s total population. Even though Chile is one of the wealthiest nations in Latin America, there is still a great deal of inequality in the country, with the wealthy enjoying high living standards while the rest of the country lags far behind. Six neighborhoods were selected for this study from a map of Santiago neighborhoods with median income status located in the central and pericentral communes of this city (Figure 1). These neighborhoods have a high proportion of middle-income individuals in terms of their socioeconomic status. The city center is home to the selected neighborhoods of “Barrio Universitario”, “Barrio Yungai”, “Barrio Lastarria”, and “Barrio Brazil”. The remaining neighborhoods, such as “Villa Portales” and “Villa Olimpica”, are located in the surrounding districts of the city center.

Founded as a colonial town in 1541 using a square grid of peripheral blocks, Santiago Center was the earliest developed area of the city [86]. Town planning was governed by these rules, which also governed the social, political, and economic facets of the Spanish colonies. According to these rules, Santiago Center was designed with a rectilinear grid of 118 × 118 m blocks and 10.25 m-wide roadways [86]. Beginning in the 20th century, roadways were paved and pedestrian and vehicle traffic was segregated to improve the safety and speed of motorized transportation [86]. In Santiago Center, sidewalks are typically paved with cement, asphalt, or tiles and range in width from 2.50 to 4 m, with exceptions where sidewalks can be as wide as 6 m.

With respect to street audit, firstly, different audit tools—developed in different contexts around the world—were considered including the Irvine–Minnesota Inventory (I–M), Walking Suitability Assessment Form (WSAF), Pedestrian Environment Data Scan (PEDS), Systematic Pedestrian and Cycling Environmental Scan (SPACES), Walkable Places Survey (WPS), and Analytic Audit Tool. By comparing and adjusting the previously mentioned audit tools within this context, it was found that the Pedestrian Environment Data Scan (PEDS) is a more appropriate audit tool to measure built environment factors of street segments in our context [87]. This is because the majority of environmental factors included in this kind of audit are strongly linked with the environmental variables shown by the selected neighborhoods in this study. As a result, the factors along the street segments were measured using the PEDS as the foundation. Inter and intra-rater reliability of items in the instrument has previously been found to be high [87]. However, the PEDS was modified by adding some items taken from the Systematic Pedestrian and Cycling Environmental Scan (SPACES) due to certain requirements in this context. For example, “maintenance of green spaces”, “building height”, and “surveillance (visibility) from the windows” were taken from the SPACES and incorporated into the PEDS. Inter and intra-rater reliability of items in the SPACES instrument has previously been found to be high as well [88]. Finally, a factor called all signs of insecurity—which includes all physical and social aspects of insecurity observed in the selected neighborhoods—was added to the audit tool because of the recent decline in perceived security in Santiago and the failure to measure social aspects of insecurity through factors like overall cleanliness. To offer this item with all of these likely indicators of insecurity that exist in the segments, we conducted an observation to collect all of the observed signs of insecurity in the selected neighborhoods. These signs of insecurity were graffiti with unpleasant messages; abandoned buildings with an unpleasant appearance; vacant/undeveloped land; the presence of drunken, street people, or aggressive people; and finally stray dogs. There were forty-two items in the final audit instrument.

Within a 400 m radius of the geometric center of each selected neighborhood, which is the acceptable distance used in several studies to measure the effects of environmental factors on walking [89,90], trained auditors carried out an objective environmental audit on each segment—both sides—by filling in a modified version of the Pedestrian Environment Data Scan (PEDS) as explained previously. Data were collected from March to July of 2024. In all the neighborhoods that were selected, 494 street segments and 36 park or plaza segments were labeled. The parks were small neighborhood parks and two of the selected neighborhoods lacked any parks or plazas. A reliability audit was conducted where three field auditors re-audited the segments of each zone. All the items, except three—which showed low inter-rater reliability (kappa < 0.40)—had moderate to high inter-rater reliability (kappa > 0.40) [91]. The items with low inter-rater reliability were excluded from the summary environmental measures. These items are “sidewalk completeness”, “the level of front yard gardens,” and “the percentage of blind walls in the segment”. The final thirty-nine items—used for summary measures (

Table 1. The summary measures regarding the built environment through audit instruments in the street segments.

Domain	Variable (Factor)	Variable Description	Mean (in Total Zones) [SD]
Destinations
Presence of destinations (access to destinations)
	Housing	1 = present, 0 = not present	0.67 [0.47]
	Office/institutional	1 = present, 0 = not present	0.15 [0.39]
	Restaurant/café/commercial	1 = present, 0 = not present	0.31 [0.49]
	Industrial	1 = present, 0 = not present	0.09 [0.28]
	Vacant/undeveloped	1 = present, 0 = not present	0.07 [0.25]
	Parks and plazas	1 = present, 0 = not present	0.23 [0.42]
Diversity
	Mixed land use	The proportion of segments with the mix of residential and commercial land uses to the whole street segments in each buffer	0.37 [0.48]
		The proportion of segments with the mix of residential and institutional land uses to the whole street segments in each buffer	0.17 [0.37]
		The proportion of segments with the mix of residential, institutional, and commercial land uses to the whole street segments in each buffer	0.09 [0.28]
Functionality (Design)
Walkway’s structural features
	Presence of a pathway for pedestrians	1 = present, 0 = not present	0.91 [0.28]
	Quality of pavement	1 = poor, 2 = fair, 3 = good	2.29 [0.54]
	Sidewalk width	1 < 4 feet, 2 = between 4 and 8 feet, 3 > 8 feet	1.60 [0.59]
	Physical barriers/path obstructions	1 = present, 0 = not present	0.48 [0.50]
	The buffer between the road and the path	1 = present, 0 = not present	0.77 [0.42]
	Curb cuts	1 = none, 2 = 1–4, 3 > 4	1.70 [0.85]
	Slope	1 = slight hilly, 0 = flat	0.11 [0.31]
	Amenities (All types)	1 = present, 0 = not present	0.43 [0.49]
	Presence of benches	1 = present, 0 = not present	0.26 [0.43]
Street’s structural features
	Low volume street	1 = yes, 0 = no	0.71 [0.45]
	High volume street	1 = yes, 0 = no	0.22 [0.41]
	Wayfinding (are there wayfinding aids?)	1 = yes, 0 = no	0.79 [0.40]
	On-street parking	1 = parallel or diagonal, 0 = none	0.50 [0.50]
	Off-street parking lot spaces	1 = yes, 0 = no	0.20 [0.40]
	Presence of bicycle lanes (are there bicycle lanes on the segment?)	1 = yes, 0 = no	0.11 [0.30]
	Presence of bus stations	1 = yes, 0 = no	0.16 [0.36]
Permeability (street connectivity)
	Street connectivity	1 = the segment with two intersections, 0 = dead end	0.94 [0.24]
Safety
Traffic safety
	Traffic control devices	1 = present, 0 = not present	0.64 [0.48]
	Crossing aids	1 = present, 0 = not present	0.43 [0.49]
	Posted speed limit	1 = present, 0 = not present	0.03 [0.15]
	Crosswalks	1 = none, 2 = 1–2, 3 = 3–4, 4 > 4	1.68 [0.64]
Personal security
	Surveillance (visibility) (can be observed from a window, verandah, porch, and garden)	1 = can be observed from less than 50% of buildings 2 = can be observed from between 50–74% of buildings 3 = can be observed from more than 75% of buildings	2.18 [0.68]
	Roadway/path lighting	1 = yes, 0 = no	0.95 [0.22]
	Presence of all signs of insecurity whether physical or social aspects	1 = yes, 0 = no	0.78 [0.41]
Aesthetics of the Streetscape
	Number of trees	1 = non for very few, 2 = some, 3 = many/dense	2.06 [0.65]
	Presence of flowers	1 = yes, 0 = no	0.19 [0.39]
	General cleanliness (can you see trash, graffiti, broken windows, discarded objects, etc.?)	1 = none or almost (no trash/bad graffiti/broken facilities) 2 = yes, a little (little trash/bad graffiti/broken facilities) 3 = yes, a lot (a lot of trash/bad graffiti/broken facilities)	1.72 [0.58]
	Maintenance and cleanliness of green spaces	1 = poor (much litter/ no grass cutting) 2 = fair (some litter/grass cutting in some places) 3 = good (no litter/grass cutting in many places)	2.18 [0.55]
	Building maintenance	1 = poor (much unrepaired and unmaintained facade is observed) 2 = fair (to some extent, the unrepaired and unmaintained facade is observed) 3 = good (unrepaired and unmaintained facade is not observed)	2.32 [0.52]
	Building height	1 = short, 2 = medium, 3 = tall	1.77 [0.61]
	Articulation in building designs	1 = little or no articulation, 2 = some articulation, 3 = highly articulated	1.82 [0.62]
	Public art (is there public art that is visible in this segment?)	1 = yes, 0 = no	0.37 [0.47]
	Degree of enclosure	1 = little or no enclosure, 2 = some enclosure, 3 = highly enclosed	2.02 [0.71]

)—are related to destinations including the presence of different types of destinations (6 items), land use mix (3 items), functionality including the design of the walkway’s structural features (9 items), design of the street’s structural features (7 items), design related to permeability (street connectivity) (1 item), safety, including traffic safety (4 items), personal security (3 items), and finally aesthetics of the streetscape (9 items).

A simplified audit tool was used concerning the parks and plaza paths in the selected neighborhoods. Since they are absent from parks and plazas, a number of the criteria that were measured in the street segments were first eliminated from the audit tool. Second, several components’ values were modified to reflect their situation in parks and plazas. One component was created in the audit in this regard since, for example, the walkways in Chilean parks and plazas might be classified as either “having pavement” or “without pavement”. Third, the audit tool was updated to include a few park and plaza-related elements that had been clarified by previous studies. These factors were “number of benches”, “the level of shade”, “visual connections with landmarks,” and “visual connections with water”.

Thus, the surrounding environment includes the park environment surrounding the pathway, which includes both spatial and visual dimensions, such as the degree of enclosure and visual connections with water. Pathway attributes, on the other hand, refer to the characteristics of the pathway itself within or along its boundaries, such as pavement, width, and number of benches. Pathway characteristics were measured using an approach similar to that of the street segments. It was modified, nevertheless, by several current park environment assessment instruments [92,93,94]. Each pathway section was traversed by the observer, who noted its characteristics. Three observations were made of each pathway segment. There were eighteen items in the final audit instrument. A reliability audit was conducted where three field auditors re-audited the segments of each zone. All the items had moderate to high inter-rater reliability (kappa > 0.40). These items—used for summary measures—are shown in

Table 2. The summary measures of the park’s attributes through the audit instrument.

Variable (Factor)	Variable Description	Mean (in Total Zones) [SD]
Floor material	1 = pathway with pavement (concrete) 0 = pathway without any specific pavement (with sand)	0.67 [0.47]
Quality of pavement	1 = good, 0 = fair	0.69 [0.46]
Sidewalk width	1 < 4 feet, 2 = between 4 and 8 feet, 3 > 8 feet	1.97 [0.44]
Physical barriers/path obstructions	1 = present, 0 = not present	0.44 [0.50]
Slope	1 = slight hilly, 0 = flat	0.25 [0.43]
The presence of flowers	1 = present, 0 = not present (flowers planted in any form and any amount was considered)	0.50 [0.50]
Number of benches	1 = no benches 2 = 1–3 benches 3 = 4–7 benches	2.69 [0.58]
The level of shade	1 = the shaded area is less than 30% of the pathway 2 = the shaded area is between 30%and 70% of the pathway 3 = the shaded area is more than 70% of the pathway (the degree of shade is measured by the percentage of shade (projected on the ground) to the total area of the pathway segment for all the pathways between 10:00 a.m.–11:00 a.m. on sunny days)	2.00 [0.54]
Visual connectivity with landmarks	1 = yes, 0 = no	0.81 [0.40]
Visual connectivity with water	1 = yes, 0 = no	0.36 [0.48]
Presence of bicycle lanes (are there bicycle lanes on the segment?)	1 = yes, 0 = no	0.17 [0.37]
Number of trees	1 = many/dense, 0 = few/some	0.53 [0.50]
Maintenance and cleanliness of green spaces	1 = poor (much litter/no grass cutting) 2 = fair (some litter/grass cutting in some places) 3 = good (no litter/grass cutting in many places)	2.28 [0.56]
Public art (is there public art that is visible in this segment?)	1= yes, 0 = no	0.31 [0.46]
Degree of enclosure	1 = no lateral visibility (the entire lateral sightlines are blocked on both sides) 2 = moderate lateral visibility (the lateral sightlines are interrupted at some parts of the pathway on both sides) 3 = continuous lateral visibility (the lateral sightlines are not interrupted on the whole pathway on both sides)	1.78 [0.79]
Presence of all signs of insecurity whether physical or social aspects	1 = yes, 0 = no	0.47 [0.50]

.

Concerning the measurements of the four primary visual qualities along the routes (legibility, coherence, complexity, and mystery), we talked with three experts in the field of urban planning about the description of the qualities and the criteria to assess them.

Table 3. The indicators for measurements of the visual qualities.

The Visual Quality	The Indicators for Measurements
Coherence	Unity or harmony in color and texture along the pathways
Complexity	Variety of objects, shapes, colors, and textures along the pathways
Legibility	Visual access along the pathways and the visibility of the landmarks along the pathways
Mystery	The presence of places with limited visual connectivity with surroundings along the pathways and the number of obstructing elements along the pathways

outlines the consensus standards for each visual quality [95,96]. We then asked these three experts to judge the level of each walkway by walking down it and using the criteria for each visual quality. The final degree of each visual quality was determined using the average measurements made by these three experts along every path.

Furthermore, pedestrian flows were surveyed using a technique called “gate counts”, which consists of setting up a series of imaginary lines (or gates) in the urban space and then counting the number of people passing in both directions through these lines [86]. The researcher stood in the middle of a pathway segment during the observations and counted the number of pedestrians who crossed an imaginary line at the researcher’s position, which was perpendicular to the pathway’s direction. Digital counters were utilized by the observer to keep track of how many people were passing the gate. We conducted the on-site observations over two months in March and April 2024. Four randomly chosen weekdays and two weekend days were chosen each week for observations. For management convenience, we divided observations into two sessions, the morning period and the evening period. For every street segment and park path, we made 20 rounds of observations. Each segment was observed for two minutes in each observation round. Thus, each pathway segment was observed 20 times, each time for two minutes.

Table 4. The summary measures of the number of older adults in the street segments and the pathways along the neighborhood parks.

Variable (Factor)	Variable Description	Mean (in Total Zones) [SD]
		In the Street Segments	In the Pathways of Parks
Number of older adults	Continuous	5.92 [5.8]	25.70 [32.30]

shows the mean and standard deviations of the number of senior citizens for the roadway segments and parks in all the selected neighborhoods.

Finally, SPSS software version 23.0 was used to analyze the data. To implement a model validation technique, the street segments were randomly divided into training (70%) and testing (30%) subsets before the modeling process [97,98]. The walking behavior associated with street segment $l$ is considered to be a linear combination of its physical attributes ($X_{n,l}$):

$$fl=a_0+{\displaystyle \sum _{n=1}^N}{a}_n{X}_{n,l}$$

Initially, the distribution of $fl$ was examined. The second step was to find the Pearson univariate correlations between each street feature and $fl$. Third, a calculation was made of the inter-correlation matrix of the Pearson correlations between the street features. To limit potential multicollinearity, if the inter-correlation between two street features was larger than half (i.e., r > 0.5), only the street feature with the highest correlation with $fl$ was retained for additional analysis. Then, all retained street features were added as independent variables to the multivariate model. A stepwise backward procedure was used to determine the independent variables for the final model (i.e., exclusion criterion: pout > 0.05). Each link characteristic was estimated by the final multivariate model’s unstandardized (B) regression coefficients, which can then be used to model older adults’ walking behavior. In addition, the associations between the average number of pedestrians observed and the features of the pathway design in the park segments were also examined using correlation analysis. This is because there are only 36 path segments in all of the parks in the selected neighborhoods which restricted regression analysis from being performed.

4. Results

4.1. Relationships Between Older Adults’ Walking Behavior and Street Segments’ Characteristics

The results show that average numbers of older adults are significantly larger on pathways with certain design characteristics.

Table 5. The results of backward regression analysis for predicting the number of older adults along the street segments (N = 494).

	Variables	B	Std. Error
Functionality (Design)
Walkway’s structural features	Presence of benches	0.667 *	0.332
Street’s structural features	Low volume street	−1.349 *	0.563
	High volume street	−1.246 *	0.629
	Existence of bus stations	1.503 **	0.402
	Are there any orientation aids?	0.783 *	0.404
Destinations
Access to destinations	Presence of parks and plazas	0.686 *	0.346
Diversity
	Mixed land use: residential + office	−0.917 *	0.372
Aesthetics of the streetscape
	General cleanliness	0.560 *	0.256
	Presence of flowers	0.842 *	0.350

* p < 0.05; ** p < 0.01. Dependent variable: average number of older adults in the street segment; adjusted R square: 0.204.

shows these pathway design features that significantly correlate with the average of older persons who walk in the street segments. The adjusted R² of the multivariate linear model is 0.204. This shows that the independent variables explain 20.4% of the variance in older adults’ walking behavior. According to the findings, there are more elderly pedestrians when there are more benches. The number of older adults has a negative association with both low- and high-volume streets when compared to pedestrian streets. This demonstrates that when there are no cars on the road, elderly individuals walk a lot more. According to functional considerations, the presence of bus stops and orientation tools results in a higher proportion of elderly pedestrians who walk. Among the parameters that are connected with the number of senior pedestrians, the presence of bus stations has the highest coefficient. There are also more elderly pedestrians where parks and plazas are present. The number of elderly pedestrians is inversely correlated with mixed land use, which is determined by the proportion of office and residential land uses. Finally, among aesthetic considerations, the quantity of elderly pedestrians is strongly correlated with overall cleanliness and the availability of flowers.

4.2. Relationships Between Older Adults’ Walking Behavior and the Pathways in the Parks and Plazas

Table 6. The results of Pearson correlation analysis between the average number of older adults and the characteristics of parks’ pathways (N = 36).

			Average Number of Older Adults
Safety (personal security/insecurity)
	Presence of all signs of insecurity	Pearson correlation	−0.362 *
		sig. (2-tailed)	0.030
		N	36
Aesthetic
	Enclosure level	Pearson correlation	0.323
		sig. (2-tailed)	0.050
		N	36
Visual Qualities
	Complexity	Pearson correlation	−0.367 *
		sig. (2-tailed)	0.028
		N	36
	Mystery	Pearson correlation	−0.536 **
		sig. (2-tailed)	0.001
		N	36

** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

shows the features of park pathways that have a significant association with the average number of senior citizens using the parks’ pathways in the selected neighborhoods. As previously mentioned, four out of the six selected neighborhoods have parks at the neighborhood level, while the other two lack any parks or plazas. The table shows that the number of elderly pedestrians in parks and plazas is negatively associated with the existence of any indications of insecurity. Additionally, the number of senior citizens as pedestrians in the local parks has a positive association with the pathways’ enclosure level. Finally, among the visual attributes, the number of elderly pedestrians has a negative correlation with complexity and mystery. Among the factors linked to the number of elderly pedestrians in the local parks, mystery also has the greatest negative correlation (correlation: −0.536).

5. Discussion

5.1. The Variables Linked to the Number of Elderly People Who Walk in the Street Segments

The first research question in this study was to identify the built environment variables that are linked to the number of elderly pedestrians in street segments. Bus stations have a favorable relationship with the average number of elderly pedestrians. According to Jia et al. [42], closeness to bus stops and public transportation was the characteristic most strongly linked to older persons’ walking behavior. Bus stations serve as an attraction for older pedestrians, increasing their walking rates in the selected neighborhoods. This research shows that older pedestrians depend on buses for their daily travels. Therefore, the bus transit system should be strengthened by the city’s transportation and urban policymakers to encourage elderly persons in Santiago’s middle-class neighborhoods to walk more.

Additionally, the number of elderly pedestrians in the street segments is inversely correlated with both low- and high-volume streets when compared to pedestrian streets. Compared to low-volume street segments (70.6%) and high-volume street segments (22.3%) in the selected neighborhoods, pedestrian streets make up a small portion of all street segments (7.1%). Nonetheless, elderly people prefer to use pedestrian-only streets rather than sidewalks on the roadways. This may have to do with senior pedestrians’ safety worries when they are in front of cars or even more comfortable pedestrian situations made possible by the route’s low vehicle density. Previous studies have demonstrated that older people’s walking behavior in both macro- and micro-scale walking environments is related to the safety-related features of crossing the streets [48,49]. Older individuals’ walking habits are positively correlated with the proportion of streets with speed limits [42,53]. In Santiago, Chile, Herrmann-Lunecke et al. [15] found that pedestrian-friendly crossings promote walking among senior citizens. One of the issues that hinder older people’s capacity to walk in Chilean cities is unfriendly street crossings and traffic signals with short pedestrian cycles [65]. To encourage older people to walk in Santiago’s medium-income areas, this study highlights the necessity of creating or expanding pedestrian streets in addition to the necessity of improving safety-related aspects along the streets.

Additionally, there was a favorable correlation between the number of elderly pedestrians and the presence of benches. Previous studies in various countries have frequently noted the use of a bench to improve older people’s walking [99,100]. For example, Herrmann-Lunecke et al. [15] found that the walking experience of senior citizens in Santiago, Chile, is enhanced by the availability of benches, public restrooms, and drinking fountains. Walking is unpleasant when there are no benches, according to other studies [66]. These results are supported by this study as well. Moreover, the presence of signs at each intersection showing the names of the streets reinforces older people’s walking behavior. The presence of these signs helps elderly people find their way more easily when they are walking, and it usually helps visitors rather than locals. This result demonstrates that the elderly residents of the selected communities also depend on these signs to guide their walking around. This might have something to do with the gradual loss of spatial and directional skills that come with aging [101]. Older persons are more likely to rely on navigational signals when walking because their ability to do so is weakening with age.

Furthermore, there is a favorable correlation between the presence of parks and plazas and the number of elderly pedestrians. According to earlier research, older adults were walking more frequently since there were more parks and green areas [38]. The presence of parks and green spaces, trees along the walkways, the levels of greenery, and the presence of natural features contribute to enhancing the walking behavior of older adults [38,55,56,57,58]. It has been shown that older persons’ walking habits are improved by having access to parks and green areas in Latin American nations like Brazil and Chile [4,39,41]. In Santiago, Chile, for example, Herrmann-Lunecke et al. [63] found that the presence or lack of greenery influences older people’s walking experiences and can either boost or decrease their willingness to walk. In a different study, Paydar and Kamani Fard [62] found correlations between the number of parks and older individuals’ walking habits. Therefore, this result supports the findings of earlier research, particularly in Chile.

Among the several mixed land use metrics this study looked at, mixed land use resulting from homes and offices contributes to reducing the amount of older persons walking on foot. Prior research in various settings demonstrated the beneficial effects of mixed land use on older adults’ walking habits [43,44,45]. The opposite relationship observed in this study may be due to older adults’ lower involvement with offices in comparison to those who are more involved with such office buildings. Government buildings, libraries, and schools are examples of such institutional buildings, and it appears that older persons use them less frequently. Therefore, the amount of elderly persons who walk in these neighborhoods is negatively impacted when such institutional buildings are mixed with residential areas. The related urban policymakers can prevent future land use regulations that create such mixed land use to enhance older individuals’ walking and physical activity in these neighborhoods.

Finally, when it comes to aesthetics, the quantity of older persons who walk is positively correlated with overall cleanliness and the availability of flowers. Previous studies have also shown these characteristics as being associated with older individuals’ improved walking behavior. For instance, a factor that deters older individuals from walking is littering the sidewalks [102]. According to Herrmann-Lunecke et al. [63], older people’s propensity for walking in Santiago’s central neighborhoods is influenced by how clean the streets are. Older persons may become afraid of damaged or inadequately designed pedestrian infrastructure [63]. In earlier research, the presence of flowers was also frequently cited as a factor influencing older individuals’ micro-scale walking experiences. For example, elderly persons in Temuco, Chile, walk more when there is more vegetation and flowers around [103].

5.2. The Factors Associated with the Number of Older Adults Who Walk in the Neighborhood Parks

The second research question of this study was to identify the design-related characteristics that are linked to the number of elderly pedestrians on local park pathways. The signs of insecurity are negatively correlated with older individuals’ walking behavior. There is evidence linking older individuals’ walking habits to their sense of personal security [48,49,50]. For example, street lighting, the presence of other people, physical incivilities, signs of disorders, and stray animals are environmental factors that are related to personal security and can affect older adults’ perceived insecurity [39,51,52]. According to recent studies, during the pandemic, there was a rise in the perception of insecurity in many parts of Santiago [67]. Due to security issues, people in Santiago now avoid going out at night (87.5%), implement security measures in their homes (68%), or adjust their departure times (65.7%) [68]. This study also found that this factor deters older people from taking walks in the local parks of the selected neighborhoods. Urban policymakers in Santiago may utilize this finding to improve the walking experience of older individuals in Santiago’s parks, particularly in medium-sized neighborhoods, by reducing the signs of insecurity.

Furthermore, increased enclosure in local parks helps to improve older persons’ walking experiences. Previous studies have demonstrated that the degree of enclosure improves older persons’ walking behavior [104]. The process by which the feeling of enclosure improves walking movement is unclear. For older individuals, it might offer a more pleasant setting, privacy, and leading pathways, which may explain why they walk along them more frequently.

5.3. The Visual Qualities Associated with the Number of Older Adults in the Street Segments and the Pathways of Neighbourhood Parks

The third research question concerns the visual characteristics that influence older persons’ walking habits on the paths found in local parks. Out of the four visual attributes that were looked at in this study, complexity has a negative correlation with older adults’ walking habits, and mystery, which has the highest coefficient of all the associated factors, has a negative correlation with the number of older adults who walk in local parks. Complexity and mystery affect how restorative urban natural settings are perceived [81], while complexity also affects visual preferences regarding a historic residential street [105]. According to this study, older adults prefer neighborhood parks with less visual complexity. Therefore, it would be inappropriate to increase the complexity of colors and patterns in urban parks’ pathways, which is in contrast to older adults’ walking habits.

Furthermore, mystery can make older people more afraid; therefore, designs that create mystery through concealed spots should be avoided to encourage older people to walk more in the parks of Santiago’s medium-sized neighborhood. Modern humans are influenced by evolution in that they have an inbuilt tendency to explore and learn about the landscape [106,107]. Therefore, scenes that give the viewer the impression that more information could be discovered by scouting that area further should be preferred. Nevertheless, because curiosity and fear have an extremely delicate balance, distorted sight lines or mystery will only be positively correlated with preference when the observer believes that new information can be learned at low risk [75,108]. This balance toward raising the fear of crime created by such concealed spaces in these local parks may also be impacted by the rise in the nation’s crime rate and fear of crime in recent years.

6. Conclusions

This study investigated the relationship between older persons’ walking behavior and built environment variables in the streets and neighborhood parks in the medium-sized neighborhoods of Santiago, Chile. The walking level of older persons was shown to be correlated with several characteristics in both street segments and neighborhood park pathways.

Older persons’ walking behavior is improved in street segments by structural and functional features such as the provision of benches, bus stations, wayfinding aids, and pedestrian streets rather than walkways along the streets. Additionally, older adults’ walking behavior is improved by the presence of parks and plazas, general cleanliness, and flowers in the street segments of Santiago’s medium-income neighborhoods.

Concerning the local parks’ pathways, correlations were found between the number of senior citizens and elements like the enclosure level and the existence of any indications of insecurity. This study also looked at the relationships between the number of older adults using neighborhood park pathways and the four characteristics of landscape visual preference. It was found that complexity and mystery have a negative association with older adults’ walking behavior in these parks.

Urban policymakers may use these findings to encourage older persons in Santiago’s medium-income neighborhoods to walk more, which would ultimately improve their mental and physical health. It should be mentioned that because there are few parks in the selected neighborhoods, and there is a limited number of paths found throughout these parks, the associations that have been found with these neighborhood parks require more research in these neighborhoods to come to more definitive conclusions.

The physical characteristics and average of older persons who walk on the street scale were measured objectively in this study. This technique assisted in addressing certain drawbacks of the self-report measures used in the survey questionnaire, such as measurement errors that can occur when self-reported data are used because of a lack of reliable memory. However, more thorough results about the relationships between older adults’ walking behavior and built environment factors may be obtained by using both subjective and objective measurements of the built environment concerning older adults’ walking behavior at both the street and neighborhood scales. In addition, three experts evaluated the park’s walkways for visual qualities, and their ratings showed good agreement. However, the corresponding section did not include the consistency rate of the assessments made by the three experts. Furthermore, this study only looked at Santiago’s center and pericentral communes, where residents can walk more easily due to the more compact layouts. Therefore, the selected neighborhoods may, at most, be representative of these communes within this city rather than the entire metropolitan area. If the right methodology is used for such an approach, future research could give a more accurate picture of the state of older persons walking throughout the entire city. Finally, the findings could only apply to the middle-income neighborhoods in these communes since we specifically designed this study to focus on this type of neighborhood to better control the effects of socioeconomic status on the associations examined in this study.