Built Environments and Cardiovascular Health: REVIEW AND IMPLICATIONS

KEY PERSPECTIVE: The built environment of neighborhoods where people live is recognized as a social determinant of cardiovascular health. Built environments that facilitate physical activity and discourage sedentary behavior could help in the prevention of cardiovascular disease. Clinical professionals involved in cardiovascular disease prevention are encouraged to incorporate this knowledge into patient counseling and be involved in research and advocacy for creating “heart-healthy” built environments.

The global burden of cardiovascular disease (CVD) is rising.1 It is increasingly recognized that CVD prevention strategies need to address the multilevel, complex range of factors impacting the health of an individual on a daily basis (ie, the social determinants of health).2,3 The social determinants of health broadly include the social and physical conditions in which people live, work, travel, and play.4

A key social determinant of health for which research interest has grown substantially in the past two decades is built environment, consisting of human-made features such as road networks, buildings, landscapes, and transportation systems.5 One of the pathways through which the built environment can affect cardiovascular health relates to active living behaviors, that is, whether built environments facilitate or impede physical activity (PA) and sedentary behavior (SB; put simply, too much sitting). It is well established that PA has broad-ranging cardiovascular health benefits.6 More recently, evidence has also demonstrated the adverse cardiovascular health effects of SB.7

Clinical professionals (physicians, exercise physiologists, physiotherapists, and nurses) involved in the prevention and management of CVD are encouraged to prescribe exercise as a primary and secondary disease prevention approach.8,9 However, despite best efforts, individual-focused behavior change interventions (eg, self-monitoring) are often recognized as unsustainable over time.10 This is because many health behaviors occur as an automatic response to some stimuli in the surrounding environment of people, with limited conscious processing.11 Recommendations from clinicians to become physically active may be hard for individuals to follow if they live in environments that are not supportive of active living behaviors. The built environment of the local neighborhoods in which residents go about their daily lives may be a particularly influential determinant for active living.12 Therefore, to complement existing clinical and behavioral approaches to reduce CVD risk, it is important to understand how the neighborhood built environment can be related to cardiovascular health.

This article aimed to present an overview of the state of evidence on the relationships between built environment attributes and cardiovascular health outcomes (CVD and its main precursors: obesity, hypertension, and type 2 diabetes mellitus [T2DM]) in the general adult population (≥18 yr). The conceptual framework of this review is shown in the Figure. We also briefly summarized current knowledge on the associations between built environment attributes and active living behaviors (PA and SB), because they are conceptualized as key behavioral pathways through which the built environment may influence cardiovascular health. There have been several excellent reviews published on these topics in the past two decades. In this article, we focused on providing a general overview of systematic reviews published recently. Also, where appropriate, we presented findings of some key empirical studies.

F1Figure.:

Conceptual framework of the review. Abbreviation: CVD, cardiovascular disease.

KEY CONCEPTS OF BUILT ENVIRONMENT

The potential influence of the built environment on active living behaviors first started to be explored in the late 1990s by the transportation researchers.13 The concept of 3Ds, which captures environmental attributes relevant to active modes of transport, is still useful today. The 3Ds refer to (1) Density (counts of individuals or dwellings within a unit area), (2) Diversity (presence of different types of land uses), and (3) Design (spatial layout of the streets).13 Additional Ds such as Destinations and Distance to transit have also been introduced recently,14,15 but they can be considered as subcomponents of the original 3Ds. A glossary of the built environment attributes discussed in this review is provided in Table 1. They are categorized by the dimension to which they belong.

Table 1 - A Glossary of Built Environment Attributes Dimension Attribute Definition Density Population density The number of people living per unit area (eg, 1 hectare or 1 km2) within a neighborhood. Residential density The number of dwellings per unit within a neighborhood. Diversity Land use mix The presence of different types of land uses (eg, residential, commercial, and recreational) within a neighborhood. It ranges from no diversity (single land use) to complete diversity (all land uses exist equally). Destinations The access to different types of destinations within a neighborhood. Destinations include places to which people travel regularly (retail, supermarkets, service, and public transit stops). Parks (public greenspaces) The availability of publicly accessible greenspaces such as parks in the neighborhood in which people can engage in recreational activities. It is often measured as density, size, or proximity. Design Street connectivity It refers to how well streets are connected for a direct (easier) trip from one place to another within an area. It is often measured using the number of road intersections per unit area within a neighborhood. Pedestrian/cyclist infrastructure It refers to the active travel supportive features of streets, such as the availability/length of sidewalks or cycling lanes. Composite measures Walkability It is a measure of how conducive an area is for walking. A walkability index for an area is calculated as a combination of 3D components (generally using residential density, land use mix, and street connectivity measures). Urban sprawl It refers to the expansion of the geographic boundaries of cities with low-density residential developments. An urban sprawl index is calculated similar to a walkability index using 3D components but also additionally includes a measure of the level of access to urban centers.

Abbreviation: 3D, density, diversity, and design.

A key concept when considering how the built environment may influence cardiovascular health is “walkability” defined as a measure of the extent to which an area is conducive for walking (generally for transportation purposes).16 It is developed based on the concept of 3Ds. A high-walkability neighborhood is characterized as an area that has higher residential density, greater land use diversity, and better street connectivity. These supportive features can facilitate resident walking by providing easier access to various types of destinations in the neighborhood.16 The concept of walkability also (inversely) relates to the concept of urban sprawl. Due to urbanization (ie, population growth in urban areas), the geographic boundaries of many cities around the world are expanding with low-density residential developments on the outer fringes known as urban sprawling.17 This essentially creates low-walkability neighborhoods where residents depend on cars for travel. In this review, we particularly focus on walkability and its components. Where available, relevant evidence for other related attributes (ie, urban sprawl, parks, and pedestrian/cyclist infrastructure) is also presented.

BUILT ENVIRONMENT AND PHYSICAL ACTIVITY

When seeking to understand potential associations between built environment attributes and PA, distinctions are often made with regard to the domain in which PA occurs (ie, for transportation or recreation). Systematic reviews have consistently found that neighborhood walkability and its 3D components are positively associated with transport-related walking.18–21 Reviews also found evidence for a positive association of access to parks with recreational exercise.22,23 Improving the quality of neighborhood parks (ie, adding more features) was shown to be consistently associated with increases in overall PA.18,19 New infrastructure developments for walking and cycling can help to increase transport-related and overall (both transport and recreational) PA levels.18,19 Higher street connectivity and the presence of cycling paths in the neighborhood appear to be supportive of higher levels of transport-related cycling.24

It is worth highlighting an internationally unique study, IPEN (International Physical Activity and Environment Network), which was conducted using data collected from >14 000 participants recruited from 12 countries on five continents.25 This study found that residents in neighborhoods with the highest levels of walkability spent 81 additional min/wk walking for transport compared with those in neighborhoods with the lowest levels of walkability.25 This demonstrates a substantial effect of neighborhood walkability on walking for transport (ie, >50% of the recommended minimum level of PA by the World Health Organization—150 min/wk). Similar, but smaller, effects of neighborhood walkability on walking for recreation (additional 25 min/wk) and overall PA (additional 35 min/wk) were also found. Also, residents of neighborhoods with more parks were found to spend an additional 21 min/wk for overall PA compared with those with less access to parks.25

There is also evidence that people who are already at risk of CVD can benefit from active living supportive built environments. In particular, older adults (≥65 yr) are at a higher risk of CVD morbidity and mortality compared with their younger counterparts.26 Reviews synthesizing built environment and PA studies conducted among older adults have generally found similar evidence of higher walkability and access to recreational facilities can promote PA in this population group as well.27–30 More importantly, a small number of studies have investigated the associations between built environment attributes and PA among patients with CVD. For instance, a Japanese study found positive associations of the presence of sidewalks and access to recreational facilities with levels of walking among stroke survivors.31 Another study conducted in Israel investigated patients who underwent coronary artery bypass surgery and found that those who lived in areas with more greenspaces were more likely to increase their post-surgical PA than those who lived in areas with fewer greenspaces.32

BUILT ENVIRONMENT AND SEDENTARY BEHAVIOR

There has been increasing interest in understanding the cardiovascular health impacts of SB.33 Even those individuals who do sufficient amounts of PA can be at increased risk of CVD if they spend a high proportion of their waking hours sitting.33 Sitting can occur in various settings, including for leisure purposes (eg, TV viewing) or occupation (eg, office-based jobs); however, such sitting behaviors are typically influenced by factors within homes and workplaces rather than in neighborhoods.34 On the other hand, sedentary travel (ie, car use)—which is likely to be influenced by the design of neighborhood built environment—should be considered more seriously as a CVD risk factor. To highlight this, an Australian cross-sectional study found that prolonged sitting in cars (≥1 hr/d) was associated with an adverse CVD risk profile, after adjusting for sociodemographic and behavioral confounders.35 A recent review has also found evidence for the detrimental effects of higher durations of car use on obesity risk.36 Among UK Biobank study participants, shifting from active travel modes (walking, cycling) to a sedentary travel mode (car use) has been shown to lead to increases in body mass index (BMI), whereas participants who shifted from sedentary to active modes decreased their BMI.37

As it is an emerging field of research, only a few reviews have summarized the evidence on associations between neighborhood built environments and SB, with the most compelling evidence related to effects on transport-related SB (eg, car use).38–40 Reviews have consistently reported that those who live in sprawling urban areas tend to spend more time sitting in cars.15,38–40 There has also been a recent call to conceptualize a neighborhood drivability index that not only consists of the traditional 3Ds, but also additional Ds related to car use (eg, demand management factors such as parking availability).41 A recent study found that those living in neighborhoods that are characterized as high in drivability were twice more likely to use cars for transportation, notably more strongly for short trips that could easily be replaced by walking or cycling.42

BUILT ENVIRONMENT AND CARDIOVASCULAR HEALTH

Obesity has been the most frequently studied CVD risk factor in relation to the built environment.43 Since the early 2000s, hundreds of empirical studies have been published examining the associations between built environment attributes and obesity-related measures (eg, weight, BMI, and waist circumference). Two umbrella reviews (ie, review of systematic reviews) on this topic have been published in 2021,21,43 summarizing findings of >30 individual reviews. These reviews consistently found higher walkability, greater land use mix, and access to more greenspaces in the neighborhoods to be associated with lower obesity risk.21,43 Another consistent finding across systematic reviews was living in a sprawling neighborhood may increase obesity risk.21,43

On the relationships between built environment attributes and T2DM, two reviews with meta-analyses were published in 2018.44,45 Both reported that higher walkability and access to more greenspaces were consistently associated with a lower risk of T2DM.

One of the above-mentioned umbrella reviews reported that the strength of this evidence base is generally low.43 A key methodological issue related to this is the lack of experimental studies. Since randomizing study participants into neighborhoods with different types of built environments is not feasible in general, the evidence base is derived from observational studies, with a dominance of cross-sectional studies. Such cross-sectional studies are limited by the “temporal ordering” issue (ie, whether exposure to the built environment precedes a CVD risk factor or vice versa). Residential self-selection issue (ie, healthy individuals choosing to live in PA-supportive environments) can lead to biased estimates. Several longitudinal studies have also been conducted in recent years.46 This includes both observational longitudinal studies examining associations between exposure to certain built environments at baseline and subsequent changes in health outcomes and quasi-experimental studies that track changes in built environments over time and resultant changes in health outcomes.46 Findings of such studies can provide better-quality evidence in the absence of experimental studies.

A 2019 review synthesized findings from 36 longitudinal studies on built environments and cardiovascular health outcomes.46 This review also quantified the strength of the evidence using a meta-analytic approach that accounted for methodological quality aspects of the studies reviewed. Table 2 shows a summary of findings of this review. The main conclusion is that there was strong evidence suggesting a protective effect of higher walkability against the risk of developing obesity, hypertension, and T2DM. In particular, very strong evidence (four out of six studies reporting significant associations in the hypothesized direction) was found for the potential long-term protective effect of higher walkability against hypertension risk. The review also found consistent associations of urban sprawl with risk of developing obesity. Moderate evidence suggested that access to recreational facilities in the neighborhood may reduce the obesity risk. It should also be noted that this review did not identify sufficient longitudinal studies to draw conclusions about the cardiovascular health effects of other built environment attributes (eg, residential density and land use mix).

Table 2 - The Level of Evidence for the Effects of Built Environments on Cardiovascular Health Outcomesa Built Environment Category Cardiovascular Health Outcome Obesity Hypertension T2DM CVD Walkability Strong Very strong Strong Recreational facility access Moderate Urban sprawl Strong Destinations Limited Design Limited Density and diversity

Abbreviations: CVD, cardiovascular disease; T2DM, type 2 diabetes mellitus.

aBased on a review of longitudinal studies conducted by Chandrabose et al (2019).46 The level of evidence was assessed statistically using a meta-analytic approach in the review. A blank indicates that the effect was examined in insufficient number of studies (

Although quasi-experimental research on built environments and cardiovascular health is limited,46 it is worth highlighting a few such studies, as they provide the highest level of evidence for potential causal relationships. One US study examined BMI changes among those who were assigned to different types of neighborhoods after Hurricane Katrina (with little to no control over their residential location assignment).47 This study found that those who were relocated to more sprawling areas increased their BMI, providing robust evidence for an adverse effect of urban sprawl on obesity risk. Such an effect is unlikely to be influenced by residential self-selection bias. Similarly, a recent study conducted in China examined the change in BMI following a large-scale greenway intervention (ie, converting a motorized-vehicle road into a traffic-free road with greenspaces).48 This study reported that residents living closer to the newly built greenway (treatment group) experienced a BMI reduction, while those who lived away from it (control group) increased their BMI over a 3-yr follow-up period. This finding strengthens the rationale for a causal link between exposure to greenspaces and a lower obesity risk.

Fewer studies have examined associations between built environmental attributes and CVD events, limiting the ability to systematically review the findings.46 However, several studies published in the past few years found that certain built environmental attributes were associated with a lower risk of CVD events. A study using the Women's Health Initiative data found that those living in more sprawling areas had significantly higher CVD incidence rates over a 7.5-yr follow-up period.49 Among a cohort of older adults in the Cardiovascular Health Study, higher density of destinations (eg, retail and service outlets, recreational facilities) in the local area was associated with lower risk of CVD events over 11 yr.50 A study conducted in Lithuania reported that those living near larger parks (>1 hectare) had lower CVD incidence rates over 4 yr compared with those living further away from the parks.51

DISCUSSION

In this review, we aimed to provide an overview of the state of evidence for potential cardiovascular health impacts of the neighborhood built environment—a key social determinant of health. We presented findings of recently published systematic reviews on this topic and highlighted some key empirical studies. A significant body of work has now investigated the associations of built environment attributes with PA, SB, and cardiovascular health outcomes. There exists convincing evidence to suggest that living in a place where the built environment is supportive of engaging in PA for transportation (eg, higher walkability) and recreation (eg, better access to parks) can be protective against CVD risk. On the other hand, the literature also suggests that living in sprawling areas (ie, low-density neighborhoods located further away from city centers) can be conducive to higher levels of sedentary travel and may adversely affect cardiovascular health.

We postulated that the key mechanisms through which neighborhood built environments affect the cardiovascular health of residents are through influencing PA and SB. Since the cardiovascular health benefits of PA are well established, there is a justification to argue that built environments that facilitate PA can be beneficial for cardiovascular health. Supporting this, a recent longitudinal study found that overall PA (a combination of walking, and other moderate-to-vigorous intensity exercises) was a partial mediator of the relationship between high walkability and low risk of obesity.52 Findings of such mediation studies are informative to enhance our understanding of the causal pathways between built environment attributes and cardiovascular health outcomes.

Many cities around the world were intentionally built to accommodate private motor vehicles as the main mode of transport.53 It should be acknowledged that not every car trip can be replaced by walking/cycling. This holds implications for promoting more viable public transportation options, which often involve some form of active travel (ie, users generally walk or cycle to/from transportation stops). While little research exists on this topic, a review found modest evidence that public transportation use was also associated with lower obesity risk.54

It is important to note that built environmental attributes can interact with other features of neighborhood environments, such as air pollution and food environments, which also affect cardiovascular health.55 For instance, high-walkability neighborhoods may have greater exposure to air pollution since they may attract more car traffic due to the presence of commercial destinations. Similarly, high-walkability neighborhoods can have a wider range of food outlets, including those providing unhealthy food options.56 Integrating these diverse environmental exposure measures is needed to assess the overall effect of the environment on cardiovascular health. For disease prevention purposes, it should be considered that built environments can have a complex interplay with other environmental features that should also be targeted in parallel.

There are also important equity considerations in considering the optimal neighborhood built environments for cardiovascular health. Relocating to higher-walkability neighborhoods, which are often located closer to city centers where housing can be more expensive,57 is not feasible for many people. The challenge is then to consider how established low-walkability neighborhoods can be modified to support active living. It is not an easy endeavor to modify walkability components (residential density, land use mix, and street connectivity) as they are fundamental structural elements of built environments. The provision of recreational facilities such as parks and walking/cycling infrastructures can be more feasible options.58 It has been reported that deprived neighborhoods (ie, areas with a higher percentage of residents with lower socioeconomic status) tend to lack high-quality parks and walking infrastructures.59–61 Advocating for improving parks and walking/cycling infrastructures in deprived neighborhoods may be an effective way to reduce socioeconomic inequalities in cardiovascular health.18

Global and local public health organizations have now recognized the importance of built environments that support active living. The World Health Organization,62 the Centers for Disease Control and Prevention in the United States,63 Public Health England,64 and the National Heart Foundation of Australia65 are advocating for city planning that prioritizes chronic disease prevention through promoting PA across the lifespan.

The information from this review can provide additional knowledge to physicians and allied health professionals who seek to recommend their patients to sit less and move more.33,66 A 2020 commentary in this journal recommended several research-based lifestyle behavior change strategies to clinical professionals, which include emphasizing the benefits of utilizing health-promoting resources in the immediate environments of patients.67 Increasing patient awareness of such local resources would be the first step in the transition to active lifestyles. Specifically, building on the evidence presented in the current review, clinical professionals can consider the environmental opportunities and constraints of the communities in which their patients live. For example, they can ask patients whether or not they have shops, good-quality parks, public transport stops, and walking or biking opportunities within walking distance from their home. This can help them to understand the relevant opportunities and barriers to active living that their patients encounter and to propose a suitable behavioral change strategy. The use of neighborhood PA resources would also benefit those with CVD, who may have additional difficulties in undertaking moderate-vigorous PA due to reduced functional mobility or fatigue. For them, a “staircase approach” can be proposed, whereby clinical professionals could suggest they start by reducing time spent sitting and then progress from light to moderate-intensity exercises to improve health.68 This transition would be facilitated by locally available resources, such as neighborhood parks with supportive features (eg, walking paths, benches, and shade), where it is possible for them to gradually increase the amount that they walk.

There is also scope for clinical professionals to be involved in research and advocacy work related to the built environment and cardiovascular health. For instance, through collaborations between built environment/public health researchers and clinical professionals, there are potential opportunities to examine the role of built environments in prevention of CVD through data linkages (ie, linking built environmental variables to patient registries). Such initiatives will provide further research opportunities that would enhance this evidence base. In addition, by engaging with cardiovascular health peak bodies and public health organizations, clinical professionals can be involved in advocacy work for creating “heart-healthy” built environments.

SUMMARY

Increasing evidence suggests that the neighborhood built environment is a key determinant of cardiovascular health. It is important for clinical professionals to understand the context in which their patients live, as it can serve either as a resource for or a barrier to engaging in active living. The COVID-19 pandemic has demonstrated that certain changes to neighborhood built environments can be implemented fairly rapidly if there is a will for change. For example, a number of cities around the world have installed new cycling infrastructure since the first year of the pandemic to reduce the demand for crowded public transport.69 Such initiatives can, and should, be continued with the goal of better preventing and managing CVD. This can only be attained with strong support from clinical professionals involved in CVD prevention practices.

ACKNOWLEDGMENTS

N.O. is supported by the Victorian Government's Operational Infrastructure Support Program (Australia).

REFERENCES 1. Roth GA, Mensah GA, Johnson CO, et al. Global burden of cardiovascular diseases and risk factors, 1990-2019: update from the GBD 2019 Study. J Am Coll Cardiol. 2020;76(25):2982–3021. 2. Wilkinson RG, Marmot M. Social Determinants of Health: The Solid Facts. Geneva, Switzerland: World Health Organization; 2003. 3. US Department of Health and Human Services. Social Determinants of Health in “Healthy People 2030”. US Department of Health and Human Services, Office of Disease Prevention and Health Promotion. https://health.gov/healthypeople/objectives-and-data/social-determinants-health. Accessed July 18, 2022. 4. Braveman P, Gottlieb L. The social determinants of health: it's time to consider the causes of the causes. Public Health Rep. 2014;129(suppl 2):19–31. 5. Saelens BE, Handy SL. Built environment correlates of walking: a review. Med Sci Sports Exerc. 2008;40(7 suppl):S550–S566. 6. Lear SA, Hu W, Rangarajan S, et al. The effect of physical activity on mortality and cardiovascular disease in 130 000 people from 17 high-income, middle-income, and low-income countries: the PURE study. Lancet. 2017;390(10113):2643–2654. 7. Young DR, Hivert MF, Alhassan S, et al. Sedentary behavior and cardiovascular morbidity and mortality: a science advisory from the American Heart Association. Circulation. 2016;134(13):e262–e279. 8. Pedersen BK, Saltin B. Exercise as medicine—evidence for prescribing exercise as therapy in 26 different chronic diseases. Scand J Med Sci Sports. 2015;25(suppl 3):1–72. 9. Franklin BA, Brubaker PH, Harber MP, Lavie CJ, Myers J, Kaminsky LA. The Journal of Cardiopulmonary Rehabilitation and Prevention at 40 years and its role in promoting lifestyle medicine for prevention of cardiovascular diseases: part 1. J Cardiopulm Rehab Prev. 2020;40(3):131–137. 10. Marcus BH, Williams DM, Dubbert PM, et al. Physical activity intervention studies: what we know and what we need to know: a scientific statement from the American Heart Association Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity); Council on Cardiovascular Disease in the Young; and the Interdisciplinary Working Group on Quality of Care and Outcomes Research. Circulation. 2006;114(24):2739–2752. 11. Marteau TM, Hollands GJ, Fletcher PC. Changing human behavior to prevent disease: the importance of targeting automatic processes. Science. 2012;337(6101):1492–1495. 12. Sallis JF, Owen N. Ecological models of health behavior. In: Glanz K, Rimer BK, Viswanath K, eds. Health Behavior: Theory, Research, and Practice. San Francisco, CA: Jossey-Bass; 2015:43–64. 13. Cervero R, Kockelman K. Travel demand and the 3Ds: density, diversity, and design. Transp Res D Transp Environ. 1997;2(3):199–219. 14. Giles-Corti B, Vernez-Moudon A, Reis R, et al. City planning and population health: a global challenge. Lancet. 2016;388(10062):2912–2924. 15. Ewing R, Cervero R. Travel and the built environment. J Am Plan Assoc. 2010;76(3):265–294. 16. Frank LD, Sallis JF, Saelens BE, et al. The development of a walkability index: application to the Neighborhood Quality of Life Study. Br J Sports Med. 2010;44(13):924–933. 17. Ewing R, Hamidi S. Costs of Sprawl. New York, NY: Routledge; 2017. 18. Smith M, Hosking J, Woodward A, et al. Systematic literature review of built environment effects on physical activity and active transport—an update and new findings on health equity. Int J Behav Nutr Phys Act. 2017;14(1):158. 19. Kärmeniemi M, Lankila T, Ikäheimo T, Koivumaa-Honkanen H, Korpelainen R. The built environment as a determinant of physical activity: a systematic review of longitudinal studies and natural experiments. Ann Behav Med. 2018;52(3):239–251. 20. Elshahat S, O'Rorke M, Adlakha D. Built environment correlates of physical activity in low- and middle-income countries: a systematic review. PLoS One. 2020;15(3):e0230454. doi:10.1371/journal.pone.0230454. 21. Dixon BN, Ugwoaba UA, Brockmann AN, Ross KM. Associations between the built environment and dietary intake, physical activity, and obesity: a scoping review of reviews. Obes Rev. 2021;22(4):e13171. doi:10.1111/obr.13171. 22. McCormack GR, Shiell A. In search of causality: a systematic review of the relationship between the built environment and physical activity among adults. Int J Behav Nutr Phys Act. 2011;8(1):125. doi:10.1186/1479-5868-8-125. 23. Sugiyama T, Neuhaus M, Cole R, Giles-Corti B, Owen N. Destination and route attributes associated with adults' walking: a review. Med Sci Sports Exerc. 2012;44(7):1275–1286. 24. Yang Y, Wu X, Zhou P, Gou Z, Lu Y. Towards a cycling-friendly city: an updated review of the associations between built environment and cycling behaviors (2007-2017). J Transp Health. 2019;14:100613. doi:10.1016/j.jth.2019.100613. 25. Sallis JF, Cerin E, Kerr J, et al. Built environment, physical activity, and obesity: findings from the International Physical Activity and Environment Network (IPEN) Adult Study. Annu Rev Public Health. 2020;41:119–139. 26. Rodgers JL, Jones J, Bolleddu SI, et al. Cardiovascular risks associated with gender and aging. J Cardiovasc Dev Dis. 2019;6(2):19. doi:10.3390/jcdd6020019. 27. Cerin E, Nathan A, van Cauwenberg J, Barnett DW, Barnett A; Council on Environment and Physical Activity (CEPA)—Older Adults Working Group. The neighbourhood physical environment and active travel in older adults: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):15. doi:10.1186/s12966-017-0471-5. 28. Barnett DW, Barnett A, Nathan A, Van Cauwenberg J, Cerin E; Council on Environment and Physical Activity (CEPA)—Older Adults Working Group. Built environmental correlates of older adults' total physical activity and walking: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):103. doi:10.1186/s12966-017-0558-z. 29. Van Cauwenberg J, Nathan A, Barnett A, Barnett DW, Cerin E; Council on Environment and Physical Activity (CEPA)—Older Adults Working Group. Relationships between neighbourhood physical environmental attributes and older adults' leisure-time physical activity: a systematic review and meta-analysis. Sports Med. 2018;48(7):1635–1660. 30. Bonaccorsi G, Manzi F, Del Riccio M, et al. Impact of the built environment and the neighborhood in promoting the physical activity and the healthy aging in older people: an umbrella review. Int J Environ Res Public Health. 2020;17(17):6127. 31. Kanai M, Izawa KP, Kubo H, et al. Association of perceived built environment attributes with objectively measured physical activity in community-dwelling ambulatory patients with stroke. Int J Environ Res Public Health. 2019;16(20):3908. doi:10.3390/ijerph16203908. 32. Sadeh M, Brauer M, Chudnovsky A, Ziv A, Dankner R. Residential greenness and increased physical activity in patients after coronary artery bypass graft surgery. Eur J Prev Cardiol. 2021;28(11):1184–1191. 33. Dunstan DW, Dogra S, Carter SE, Owen N. Sit less and move more for cardiovascular health: emerging insights and opportunities. Nat Rev Cardiol. 2021;18(9):637–648. 34. Hadgraft NT, Dunstan DW, Owen N. Models for understanding sedentary behaviour. In: Leitzmann M, Jochem C, Schmid D, eds. Sedentary Behaviour Epidemiology. Cham, Switzerland: Springer; 2018:381–403. 35. Sugiyama T, Wijndaele K, Koohsari MJ, Tanamas SK, Dunstan DW, Owen N. Adverse associations of car time with markers of cardio-metabolic risk. Prev Med. 2016;83:26–30. 36. Sugiyama T, Chandrabose M, Homer AR, Sugiyama M, Dunstan DW, Owen N. Car use and cardiovascular disease risk: systematic review and implications for transport research. J Transp Health. 2020;19:100930. doi:10.1016/j.jth.2020.100930. 37. Flint E, Webb E, Cummins S. Change in commute mode and body-mass index: prospective, longitudinal evidence from UK Biobank. Lancet Public Health. 2016;1(2):e46–e55. 38. Koohsari MJ, Sugiyama T, Sahlqvist S, Mavoa S, Hadgraft N, Owen N. Neighborhood environmental attributes and adults' sedentary behaviors: review and research agenda. Prev Med. 2015;77:141–149. 39. Yu YC, Lai TF, Lin CY, et al. Associations of the audited residential neighborhood built-environment attributes with objectively-measured sedentary time among adults: a systematic review. Int J Environ Health Res. 2022:1–15. doi:10.1080/09603123.2022.2048803. 40. Lin CY, Koohsari MJ, Liao Y, et al. Workplace neighbourhood built environment and workers' physically-active and sedentary behaviour: a systematic review of observational studies. Int J Behav Nutr Phys Act. 2020;17(1):148. 41. den Braver NR, Kok JG, Mackenbach JD, et al. Neighbourhood drivability: environmental and individual characteristics associated with car use across Europe. Int J Behav Nutr Phys Act. 2020;17(1):8. doi:10.1186/s12966-019-0906-2. 42. den Braver NR, Lakerveld J, Gozdyra P, et al. Development of a neighborhood drivability index and its association with transportation behavior in Toronto. Environ Int. 2022;163:107182. doi:10.1016/j.envint.2022.107182. 43. Lam TM, Vaartjes I, Grobbee DE, Karssenberg D, Lakerveld J. Associations between the built environment and obesity: an umbrella review. Int J Health Geogr. 2021;20(1):7. doi:10.1186/s12942-021-00260-6. 44. den Braver NR, Lakerveld J, Rutters F, Schoonmade LJ, Brug J, Beulens JWJ. Built environmental characteristics and diabetes: a systematic review and meta-analysis. BMC Med. 2018;16(1):12. doi:10.1186/s12916-017-0997-z. 45. Dendup T, Feng X, Clingan S, Astell-Burt T. Environmental risk factors for developing type 2 diabetes mellitus: a systematic review. Int J Environ Res Public Health. 2018;15(1):78. doi:10.3390/ijerph15010078. 46. Chandrabose M, Rachele JN, Gunn L, et al. Built environment and cardio-metabolic health: systematic review and meta-analysis of longitudinal studies. Obes Rev. 2019;20(1):41–54. 47. Arcaya M, James P, Rhodes JE, Waters MC, Subramanian SV. Urban sprawl and body mass index among displaced Hurricane Katrina survivors. Prev Med. 2014;65:40–46. 48. He D, Lu Y, Xie B, Helbich M. How greenway exposure reduces body weight: a natural experiment in China. Landsc Urban Plan. 2022;226:104502. doi:10.1016/j.landurbplan.2022.104502. 49. Griffin BA, Eibner C, Bird CE, et al. The relationship between urban sprawl and coronary heart disease in women. Health Place. 2013;20:51–61. 50. Garg PK, Platt JM, Hirsch JA, et al. Association of neighborhood physical activity opportunities with incident cardiovascular disease in the Cardiovascular Health Study. Health Place. 2021;70:102596. doi:10.1016/j.healthplace.2021.102596. 51. Tamosiunas A, Grazuleviciene R, Luksiene D, et al. Accessibility and use of urban green spaces, and cardiovascular health: findings from a Kaunas cohort study. Environ Health. 2014;13(1):20. doi:10.1186/1476-069X-13-20. 52. Chandrabose M, Cerin E, Mavoa S, et al. Neighborhood walkability and 12-year changes in cardio-metabolic risk: the mediating role of physical activity. Int J Behav Nutr Phys Act. 2019;16(1):86. doi:10.1186/s12966-019-0849-7. 53. Gössling S. Why cities need to take road space from cars—and how this could be done. J Urban Des. 2020;25(4):443–448. 54. Patterson R, Webb E, Hone T, Millett C, Laverty AA. Associations of public transportation use with cardiometabolic health: a systematic review and meta-analysis. Am J Epidemiol. 2019;188(4):785–795. 55. Frank LD, Iroz-Elardo N, MacLeod KE, Hong A. Pathways from built environment to health: a conceptual framework linking behavior and exposure-based impacts. J Transp Health. 2019;12:319–335.

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