This review included 72 studies dealing with the association between social environment, PA, and opportunities for PA within the four types of built environments. Of these, 28 studies were from European countries, one from South Africa, five from Asia, 16 from North America, three from South America, and nine from Oceania. Studies that include more than one country count of 10 are mainly conducted across European, Oceania, and American countries. The country where we find most studies is England, followed by the USA and Australia (Table 1). The selected studies were published between 2002 and 2022 and included both quantitative and qualitative studies (Appendix 2).
Based on our thematic analysis, all 72 studies were categorised into four types of built environment, as shown in Table 2. Some studies could be categorised into more than one category, which is why the total number of studies was greater than 72.
In studies exploring opportunities for PA within the four types of built environments in association with PA and social environments, a range of indices and measures were employed. The measurements of PA encompassed a comprehensive range of methods, including self-reported cross-sectional surveys, objective measures using accelerometers, qualitative interviews, observations, environmental assessments, interventions, and social determinants analysis. Methods employed to assess and measure various aspects of the built environments included walkability scores, geospatial/GIS analyses, audio-visual narratives and park audit tools. Finally, we also included a number of review studies which also spans various methods and measures relating PA.
Below, we provide an overview of the selected studies and their results organised by the four types of built environments. For each built environment, we further divided sections up between results that focus on area and individual specific variables.
Walking infrastructure (including street and pedestrian connectivity, land use, density, transit proximity and access, aesthetics and design)
Results focusing on area variables
When looking into walking infrastructure in the context of societal or area factors of the social environment, and how it is related to opportunities for PA, we found four studies at the community level, indicating that high-SES areas tended to have higher walkability scores than low-SES areas [25,26,27,28]. A walkability score is a measure of how conducive an area is to walking and is influenced by the walking infrastructure factors. Having a higher walkability score indicate neighborhoods where walking is more convenient, safe, and enjoyable [20]. Jacobs et al. [29] did, however, find variations across their studies included in their review, with some studies highlighting that areas with higher SES tend to have superior walking infrastructure and greater amount of walking tracks, while other studies find the opposite. The presence and accessibility of walking facilities are generally identified as supporting walking [30, 31]. In contrast to studies suggesting higher walkability scores in high-SES areas, an inverse relationship was found in studies by Choi and Yoon [32] and Conderino et al. [2]. The last study reported that on average, low-income neighbourhoods had higher walking scores than high-income ones. Notably, most white neighbourhoods generally had lower walk scores than other racial/ethnic majority neighbourhoods, except for the majority of black neighbourhoods, where tracts in lower income tertiles had the lowest walkability.
Perceptions within neighbourhoods also affect objective walkability measurements. Higher-income areas are often perceived as more aesthetically pleasing, with higher quality, fewer physical barriers to walking, and lower levels of crime and traffic [33, 34]. Conversely, low-SES areas tend to have poorer perceived built environmental experiences [30, 31, 34]. Giles-Corti and Donovan [30] suggest that the quality of the built walking environment may be more important than the SES of the area of residence, as a correlate of walking behaviour. Other findings is also highlighting the built environmental factors, such as pedestrian bridges over large roads, well-maintain pavements, and illuminated walk-and-bike paths, as encouraging and crucial for walking behaviour [31, 35].
Another aspect related to walking infrastructure opportunities for PA is the density of the area. Remote areas tend to have poorer walking and bicycle infrastructure, lower walkability scores, and less favourable structural attributes for PA [36]. Two studies found that areas with higher intersection density and connectivity, often urban, with multiple destinations and branched road networks, tend to promote walking and meeting PA recommendations [37, 38]. The same result was observed among low-SES adults in a study by Christie et al. [39]. In contrast, Boone-Heinonen and Gordon-Larsen [40] found that higher landscape diversity was associated with higher PA, and for females, higher street connectivity was linked to lower PA. Furthermore, Isiagi, Okop, and Lambert [41] observed a negative association between intersection density and PA regardless of group. Wang et al. [42] also inversely observed a positive association between the built environment and PA in neighbourhoods characterised by low housing density, low road coverage, less land-use diversity (e.g. single land use of residence), high car dependency, poor access to public transport, longer distances to the city, and more green space coverage. Similarly, Frost et al. [43] found positive associations between aesthetics, pathways, safety from crime and traffic, parks, the ease of walking between destinations in the environment, and PA among adults in rural areas.
Furthermore, three studies found that living in high-SES areas is closely related to increased active transportation, higher PA levels, or more steps pr. day [35, 44, 45]. However, Seguin-Fowler et al. [44] found no association between the walk score and PA for those living in low-SES neighbourhoods. Isiagi, Okop, and Lambert [41] inversely found that residents in low-SES/high walkable neighbourhoods reported more transport-related PA compared to high-SES/low walkable neighbourhoods. Similar results were found by Besor et al. [46], who stated that areas characterised by lower-SES residents and a higher proportion of Arab minorities had better-performing health programmes (higher PA). Zang et al. [45] found that the PA of people living in low-SES areas was more dependent on the built environment, whereas the association was limited in high-SES areas. In studies of interventions in both high- and low-SES areas, a positive change in neighbourhood walkability was associated with increased PA, especially in adults in low-SES areas [27, 47, 48]. In a study by Clary et al. [27], improvements in walkability scores were mostly driven by increases in residential density and land-use mix. In contrast, Adkins et al. [49] concluded that the built environment has weaker effects on walking and physical activity in disadvantaged groups than in advantaged ones.
In summary, area-specific studies had different indications. Some studies found varying associations between walking infrastructure factors, there walkability score and PA (including transportation walking) [50, 51], whereas others reported clear associations between higher walkability scores and increased PA across different SES areas [28, 52]. Finally, Hillsdon et al. [53] found that most people engage in PA beyond an 800-metre radius from their homes, suggesting that neighbourhood characteristics alone may not predict PA levels.
Results focusing on individual variables
At the individual level, multiple studies have shed light on the interplay between determinants of the social environment, walking infrastructure, and PA. Gullon et al. [54] indicated that individuals with lower income levels tend to have more accessible walking destinations nearby. Furthermore, Christe et al. [47] revealed that the percentage change in walkability scores was positively associated with increased walking, particularly among those with lower income and education levels. Conversely, Cerin and Leslie [33] found that individuals with higher education and income may choose and afford to live in more PA-friendly built environments, including areas conducive for walking. Similarly, Andrade et al. [48] observed that individuals with higher incomes have better access to free or low-cost recreational facilities (including walking trails), a pattern that is also prevalent among those with higher education and more working hours. When examining the use of newly built walking and cycling infrastructure, Smith et al. [55] found that lower educational level and income, rather than ethnicity, were associated with reduced usage.
Dias et al. [56] explored the associations between built environmental factors (objectively and subjectively) and leisure walking among boys and girls with different SES backgrounds. For girls with low SES, access to services and shorter distance to parks and squares were positively associated with leisure walking. For boys, perceived environmental factors such as crime safety, land-use mix, neighbourhood recreation facilities, and places for walking are crucial factors for leisure walking. Another relevant study by Burton et al. [57] revealed that participants across income groups (low, intermediate, and high) place equal importance on similar factors, such as low crime, friendly neighbours, streetlights, and good paths, according to PA. Individuals with higher incomes only marginally emphasised these factors in their PA considerations. Similarly, Cleland et al. [58] found that individual factors, especially those of women with low SES, outweighed environmental factors. Specifically, higher PA levels among low-SES women were associated with interesting local walking opportunities and busy roads to cross during walking.
Cycling infrastructure (including biking paths, trails, path connectivity and quality)
Results focusing on area variables
At the area level, low-SES areas tend to have fewer biking paths compared to their high-SES counterparts [25, 29, 36]. Additionally, Darcy et al. [36] discovered that areas with more disadvantages, often residential areas, within the same local government area have lower quality PA opportunities than less disadvantaged areas. Remote areas also tend to have fewer functional PA opportunities (including walking and bicycle infrastructure) because of poorer structural aspects affecting streets and pathways [36]. The quality of infrastructure, including connected pathways, is considered crucial for transport-biking [31]. In Sweden, shortcomings in structural aspects, quality, and supportive features such as narrow bike paths, inadequate lightning, and concerns about personal safety were found to hinder cycling activity, especially for low-SES citizens [25]. This observation aligns with another Swedish survey study, indicating that active transport to and from school is nearly three times more common among adolescents (16–19 years) living in neighbourhoods with illuminated walking and bike paths than among those without [35]. The same study found that adolescents living in high-SES areas were 80% more likely to bike or walk to school than adolescents living in low-SES areas, and active transportation was 50% less common among adolescents from middle-SES areas than among those in low-SES areas.
Results focusing on individual variables
At the individual level, a study conducted in London found that cycling for transportation was more common among white Britain (5.8% vs. 3.0% for ethnic minorities) and people with shorter transportation distances. After accounting for individual and area characteristics, this study also revealed that women and ethnic minorities are less likely to cycle. In contrast to England as a whole, cycling in London became increasingly concentrated among higher-SES groups over time, and increased infrastructure expenditure was associated with more cycling [59]. Similarly, a review by Smith et al. (2017) found in one study that newly built walking and cycling paths were used more by people with higher incomes, higher educational levels, and employment. [55]. Most of these patterns were consistent with Andrade et al. [48], who found that 24% of those with access to free or low-cost recreational facilities (including bicycle infrastructure) had a household income of at least USD 100,000 per year compared to 15.1% of those without access. Similar patterns were observed among those with higher educational levels and working hours.
In summary, a common feature across many studies is that access, length of the bike paths, and quality are associated with physical activity [25, 35, 46, 48]. However, some studies investigating the association between cycle infrastructure, physical activity, and social environment have also found moderators pointing in different directions, leading to no clear conclusions [50, 56].
Neighbourhood parks and open spaces
Results focusing on area variables
Two review studies indicated positive links between PA and neighbourhood parks, open spaces, and general green spaces, potentially reducing socioeconomic PA inequalities [31, 43]. However, Giles et al. [51] presented a contrasting view on the limited benefits of green spaces in low-SES areas, highlighting the complexity of the relationship between green spaces and PA. Doiron et al. [26] observed that high-deprivation neighbourhoods had less access to greenness, affecting PA. Mears et al. [60] showed that residents from deprived areas in Sheffield made shorter, less active visits to green spaces. In contrast, Garrett et al. [61] found that access to green spaces significantly boosts PA through non-recreational activities, such as walking or jogging, particularly for low- and middle-income groups. Zhang et al. [62] underscores the importance of park safety in influencing adolescents’ PA, especially in low-income neighbourhoods, suggesting that perceived safety is a crucial determinant of park utilisation. This is complemented by Sun and Lu [34], who noted significant variations in safety perceptions across income groups affecting park use and the types of activities undertaken. Fontan-Vela et al. [63] and Schneider et al. [64] discussed how residents in higher-SES areas report more park use and fewer barriers, suggesting that these areas might offer better-maintained facilities and safer environments. Conversely, residents in lower SES areas cite limitations such as job constraints, perceived insecurity, and lack of suitable facilities, which hinder their park use and PA engagement. Wang et al. [42] revealed that neighbourhoods with more green spaces in high-SES areas correlate with higher levels of PA, emphasising the role of built environmental quality and accessibility in promoting active lifestyles. However, the proportion of green spaces also tends to be higher in high-SES areas than in low-SES areas, where the distance to and number of green spaces varies across SES areas according to the country in which the studies were conducted [29]. Fontan-Vela et al. [63] reported higher PA in parks within neighbourhoods with high socioeconomic status, citing fewer barriers than in lower-status areas. Schneider et al. [64] found equitable access to parkrun events across deprivation levels in England, but participation from local residents was low, highlighting the need for additional activation measures. Cohen et al. [65] in Los Angeles found that park use in low-income neighbourhoods was gendered, with women’s activities more sedentary compared to men’s. García-Pérez et al. [66] showed that park presence had little influence on women’s leisure-time PA. Finally, Jayasinghe et al. [67] highlighted the challenges in enhancing access to PA infrastructure and natural amenities across socioeconomic disparities.
Results focusing on individual variables
A review indicated that SES impacts greenspace use for PA, with complex influences from built environment characteristics. Older adults with a higher SES engage more in PA in neighbourhoods with safe and pleasant built environments and abundant recreational facilities [68]. Anthun et al. [69] found no significant PA changes in a Norwegian suburb over three years, highlighting the importance of location, availability, and social spaces for motivation, with lower SES groups frequently using greenspaces, but dissatisfied with their quality. Clary et al. [28] linked daily moderate-to-vigorous physical activity (MVPA) to the distance to local parks in England, suggesting that travelling to parks boosts PA levels because of limited park facilities. A follow-up study by Clary et al. [27] found no evidence that improved greenspace access affects PA changes across SES groups. Gullon et al. [54] observed that low-income individuals had more green land cover nearby, but might perceive these areas as unsafe for PA, indicating socioeconomic disparities in PA engagement and greenspace perception. This is supported by Compernolle et al. [50], who stated that adults who perceive a greater number of destinations, such as recreational facilities, and those who live in neighbourhoods with more objectively measured aesthetic features, such as trees, green spaces, and parks, are more active.
Sports facilities
Results focusing on area variables
Two review studies initiated a discussion of area-specific results. Jacobs et al. [29] observed varied sports facility access across SES areas in 59 studies with no consistent associations found, whereas Frost et al. [43] identified positive associations between recreational facilities and PA in rural areas. Jayasinghe et al. [67] discovered good sports facility coverage in NW Tasmania, yet this did not lead to high sports participation, suggesting issues with facility visibility or activation. Eime et al. [70] reported a positive association between sports participation and facility availability in Australia adjusted for socioeconomic status and urbanisation, with higher participation in less urbanised regions. Hoekman et al. [71] explored rural-urban differences in sports participation in the Netherlands, highlighting the role of social environment in local sports engagement and the impact of facility diversity. Reimers et al. [72] found that gym availability significantly influenced rural girls’ sports participation in Germany, contrasting with urban girls and boys. Farrell et al. [73] linked the abundance of sports facilities in rural England to reduced physical inactivity, associating facility satisfaction with lower inactivity rates. Kokolakakis et al. [74] identified socio-demographic and economic factors as influencers of sports participation in England, downplaying the role of sports infrastructure in regional disparities. Billaudeau et al. [75] and Cereijo et al. [76] investigated the accessibility and quality of sports facilities in Paris and Madrid, finding mixed associations between SES and facility availability. Spanish studies by Pascual et al. [14, 77] linked local economic resources with the number of sports facilities and PA, especially among older individuals and women. Hillsdon et al. [78] and studies from Asia [32, 34] observed a positive association between SES and leisure amenity availability. Ferguson et al. [79] and Lamb et al. [80] showed that public transport access in low-income areas provides closer proximity to sports facilities, a difference nullified by car ownership. Panter et al. [81] and Hillsdon et al. [53] discussed how poor facility coverage in deprived English areas affects PA levels, with individuals often travelling beyond local areas for activity. Findings from Canada [82] and a review [38] indicate that women are more sensitive to local conditions and proximity to facilities. Australian research [18, 33] has highlighted disparities in perceived access to sports facilities by income area, with psychosocial factors influencing PA more than built environmental factors. Pascual et al. [83] and Karusisi et al. [84] emphasised socioeconomic factors’ dominance over spatial in sports facility usage, with Boone-Heinonen and Gordon-Larsen [40] noting the impact of varied built environments and safety on young adults’ PA, affected by gender and urban density.
Results focusing on individual variables
This section delves into how individual attributes such as age, gender, and socio-economic status influence sports facility utilisation, with Jacobs et al. [29] and Lee et al. [85] noting geographical and socio-demographic variations in access. Liu et al. [86] report lower SES and older individuals are less active in facility usage, highlighting complex factors behind participation. Ellaway et al. [87] found no significant link between sports facility accessibility and activity levels, factoring in SES and urbanization. Bergmann et al. [88] noted women and lower-income individuals in the South Region of Brazil frequently use outdoor gyms, suggesting mitigation of PA disparities. Gardam et al. [89] found that outdoor PA equipment in lower-income areas could reduce access disparities. Cutumisu and Spence [8] showed that objective access and personal factors, such as self-efficacy, impact PA adherence, with subjective perceptions of access not correlating with participation. Compernolle et al. [50] indicated that adults perceiving more neighbourhood destinations are less sedentary. Rovniak et al. [90] identified an ‘Active Leisure’ cluster, showing recreational facility availability boosts leisure-time PA. This is supported by Werneck et al. [91], who found that the presence of public PA facilities near a household was associated with higher leisure-time PA among all quintiles of income and educational level. Burton et al. [57] linked active lifestyles with social support, fewer activity barriers, and health issues among higher-income participants. Langøien et al. [92] highlighted the built environmental impact on PA for minority groups in Europe, emphasising the need for available, appropriate, and culturally sensitive facilities. Studies advocate comprehensive environmental improvements and increased PA knowledge and skills. An English programme providing free access to sports facilities, along with marketing and courses, significantly boosted gym and swim participation, particularly in disadvantaged groups [93].
Table 3 is a result from our narrative synthesis and summarises and integrate our research findings on the interplay between PA, the social environment, and opportunities for PA across four types of built environments: walking infrastructure, cycling infrastructure, neighbourhood parks and open spaces, and sports facilities. In synthesizing the findings of 72 studies, this narrative synthesis highlights the most typical results, focusing on the common themes and patterns that emerged across the built environments. By distilling these studies into a cohesive summary, we provide a comprehensive overview of the main trends and outcomes. However, due to the broad scope and the necessity to concentrate on overarching themes, some nuanced details and specific variations within individual studies are not fully represented, meaning that there will be studies in each of the built environments that can show contradictory results.
link