Neighborhood Social Environment and Cardiovascular Disease Risk
Purpose of Review
Limited physical activity (PA) and obesity are two primary risk factors for cardiovascular disease (CVD). Within a socio-ecological framework, neighborhood social environment may play a key role in influencing PA and obesity. However, the mechanisms underlying this relationship remain ambiguous. Our goals in this review are as follows: (1) to summarize findings from the recent studies on neighborhood social environment in relation to PA and obesity as CVD risk factors, and (2) to briefly describe several innovative approaches to assessing neighborhood social environment.
Almost all recent studies assessed neighborhood social environment around residential areas. There were consistent associations between neighborhood social environment and PA and obesity, with some exceptions (indicating null associations or paradoxical associations). However, a focus on residential social environment may limit results because these studies did not account for any exposures occurring away from individuals’ homes. Additionally, the majority of studies utilized a cross-sectional design, which limits our ability to make inferences regarding the causality of the association between neighborhood social environment and PA or obesity as CV risk factors.
The majority of the studies on neighborhood social environment characterized factors around residential areas and assessed participant activity via self-reported surveys. Future research should leverage tools to account for the spatial mismatch between environmental exposures and outcomes by using global positioning systems, ecological momentary assessments, virtual neighborhood audits, and simulation modeling. These approaches can overcome major limitations by tracking individuals’ daily activity and real-time perceptions of neighborhood social environments linked to CVD events.
KeywordsPhysical activity Obesity Social environment Health disparities Neighborhood socioeconomic position Cardiovascular disease risk
Body mass index
Ecological momentary assessment
Federal Bureau of Investigation
Geographic information systems
Global positioning system
Leisure-time physical activity
Moderate-to-vigorous physical activity
Neighborhood deprivation index
National Health and Nutrition Examination Survey
The views of the present review study are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute (NHLBI), the National Institute on Minority Health and Health Disparities (NIMHD), the National Institutes of Health (NIH), or the U.S. Department of Health and Human Services.
Funding for the Social Determinants of Obesity and Cardiovascular Risk Laboratory is provided through the Division of Intramural Research (DIR) of the NHLBI of the NIH, and through the Intramural Research Program of the NIMHD of the NIH. This research was made possible through the NIH Medical Research Scholars Program, a public-private partnership supported jointly by the NIH and generous contributions to the Foundation for the NIH from the Doris Duke Charitable Foundation, Genentech, the American Association for Dental Research, the Colgate-Palmolive Company, Elsevier, alumni of student research programs, and other individual supporters via contributions to the Foundation for the National Institutes of Health.
Compliance with Ethical Standards
Conflict of Interest
All the authors (Tamura, Langerman, Ceasar, Andrews, Agrawal, Powell-Wiley) declare that they have no conflict of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
- 3.Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity among adults and youth: United States, 2015-2016. NCHS Data Brief. 2017(288):1–8.Google Scholar
- 8.Kraus WE, Bittner V, Appel L, Blair SN, Church T, Despres JP, et al. The National Physical Activity Plan: a call to action from the American Heart Association: a science advisory from the American Heart Association. Circulation. 2015;131(21):1932–40. https://doi.org/10.1161/CIR.0000000000000203.CrossRefPubMedGoogle Scholar
- 9.Community Preventive Services Task Force. Physical activity: built environment approaches combining transportation system interventions with land use and environmental design. CDC. 2016. https://www.thecommunityguide.org/Accessed 6/20 2018.
- 10.Boone-Heinonen J, Roux AVD, Kiefe CI, Lewis CE, Guilkey DK, Gordon-Larsen P. Neighborhood socioeconomic status predictors of physical activity through young to middle adulthood: the CARDIA study. Soc Sci Med. 2011;72(5):641–9. https://doi.org/10.1016/j.socscimed.2010.12.013.CrossRefPubMedPubMedCentralGoogle Scholar
- 11.• Powell-Wiley TM, Ayers C, Agyemang P, Leonard T, Berrigan D, Ballard-Barbash R, et al. Neighborhood-level socioeconomic deprivation predicts weight gain in a multi-ethnic population: longitudinal data from the Dallas Heart Study. Prev Med. 2014;66:22–7. https://doi.org/10.1016/j.ypmed.2014.05.011 This study demonstrated that individuals residing in the highest-deprivation neighborhoods gained 6.0 kg compared to those living in the lowest ones, suggesting that individuals living in deprived neighborhoods for a longer period of time experienced an increase in their weight.CrossRefPubMedPubMedCentralGoogle Scholar
- 12.Sallis JF, Cervero RB, Ascher W, Henderson KA, Kraft MK, Kerr J. An ecological approach to creating active living communities. Annu Rev Public Health. 2006;27:297–322. https://doi.org/10.1146/annurev.publhealth.27.021405.102100.CrossRefGoogle Scholar
- 13.Sallis J, Owen N. Ecological models of health behavior In: Glanz K, Rimer BK, Viswanath K, editors. Health behavior and health education: theory, research, and practice. 5 ed.: Jossey-Bass; 2015.Google Scholar
- 15.Carroll-Scott A, Gilstad-Hayden K, Rosenthal L, Peters SM, McCaslin C, Joyce R, et al. Disentangling neighborhood contextual associations with child body mass index, diet, and physical activity: the role of built, socioeconomic, and social environments. Soc Sci Med. 2013;95:106–14. https://doi.org/10.1016/j.socscimed.2013.04.003.CrossRefPubMedPubMedCentralGoogle Scholar
- 16.Barnett DW, Barnett A, Nathan A, Van Cauwenberg J, Cerin E, Council on E, et al. 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. https://doi.org/10.1186/s12966-017-0558-z.CrossRefPubMedPubMedCentralGoogle Scholar
- 20.Yi SS, Trinh-Shevrin C, Yen IH, Kwon SC. Racial/ethnic differences in associations between neighborhood social cohesion and meeting physical activity guidelines, United States, 2013–2014. Prev Chronic Dis. 2016;13:160261. https://doi.org/10.5888/pcd13.160261.
- 21.James P, Hart JE, Arcaya MC, Feskanich D, Laden F, Subramanian SV. Neighborhood self-selection: the role of pre-move health factors on the built and socioeconomic environment. Int J Environ Res Public Health. 2015;12(10):12489–504. https://doi.org/10.3390/ijerph121012489.CrossRefPubMedPubMedCentralGoogle Scholar
- 23.• Kakinami L, Wissa R, Khan R, Paradis G, Barnett TA, Gauvin L. The association between income and leisure-time physical activity is moderated by utilitarian lifestyles: a nationally representative US population (NHANES 1999-2014). Prev Med. 2018;113:147–52. https://doi.org/10.1016/j.ypmed.2018.05.013 This study indicated that individuals having the lowest poverty-income ratio had fewer minutes of moderate, vigorous, and moderate-vigorous PA than those with the highest poverty-income ratio. This study also found that individuals with the lowest poverty-income ratio were 31-55% less likely to meet national PA recommendations.CrossRefPubMedGoogle Scholar
- 24.• Armstrong-Brown J, Eng E, Hammond WP, Zimmer C, Bowling JM. Redefining racial residential segregation and its association with physical activity among African Americans 50 years and older: a mixed methods approach. J Aging Phys Act. 2015;23(2):237–46. https://doi.org/10.1123/japa.2013-0069 This study demonstrated that racial residential segregation was positively associated with minutes of PA and odds of meeting PA guidelines.CrossRefPubMedGoogle Scholar
- 26.• Kerr Z, Evenson KR, Moore K, Block R, Diez Roux AV. Changes in walking associated with perceived neighborhood safety and police-recorded crime: the multi-ethnic study of atherosclerosis. Prev Med. 2015;73:88–93. https://doi.org/10.1016/j.ypmed.2015.01.017 The authors found that there were no relationships between changes in perceived safety and changes in walking for transportation or recreation. In contrast, individuals living in neighborhoods with increases in murder rates had decreases in transportation walking.
- 27.Perez LG, Slymen DJ, Sallis JF, Ayala GX, Elder JP, Arredondo EM. Interactions between individual and perceived environmental factors on Latinas’ physical activity. J Public Health. 2017;39(2):E10–E8. https://doi.org/10.1093/pubmed/fdw061.
- 28.Tamayo A, Karter AJ, Mujahid MS, Warton EM, Moffet HH, Adler N, et al. Associations of perceived neighborhood safety and crime with cardiometabolic risk factors among a population with type 2 diabetes. Health Place. 2016;39:116–21. https://doi.org/10.1016/j.healthplace.2016.03.007.CrossRefPubMedPubMedCentralGoogle Scholar
- 29.Richardson AS, Troxel WM, Ghosh-Dastidar MB, Beckman R, Hunter GP, DeSantis AS et al. One size doesn’t fit all: cross-sectional associations between neighborhood walkability, crime and physical activity depends on age and sex of residents. BMC Public Health. 2017;17. https://doi.org/10.1186/s12889-016-3959-z.
- 31.• Yuma-Guerrero PJ, Cubbin C, von Sternberg K. Neighborhood social cohesion as a mediator of neighborhood conditions on mothers’ engagement in physical activity: results from the geographic research on wellbeing study. Health Educ Behav. 2017;44(6):845–56. https://doi.org/10.1177/1090198116687537. This study showed that social cohesion mediated the association between neighborhood safety and mother’s PA, suggesting that future PA interventions could incorporate social cohesion, which in turn may increase mother’s PA level in the community perceived as unsafe.
- 36.Kwarteng JL, Schulz AJ, Mentz GB, Israel BA, Shanks TR, Perkins DW. Neighbourhood poverty, perceived discrimination and central adiposity in the USA: independent associations in a repeated measures analysis. J Biosoc Sci. 2016;48(6):709–22. https://doi.org/10.1017/S0021932016000225.CrossRefPubMedPubMedCentralGoogle Scholar
- 39.Lippert AM, Evans CR, Razak F, Subramanian SV. Associations of continuity and change in early neighborhood poverty with adult cardiometabolic biomarkers in the United States: results from the national longitudinal study of adolescent to adult health, 1995-2008. Am J Epidemiol. 2017;185(9):765–76. https://doi.org/10.1093/aje/kww206.CrossRefPubMedPubMedCentralGoogle Scholar
- 40.• Bower KM, Thorpe RJ, Yenokyan G, McGinty EEE, Dubay L, Gaskin DJ. Racial residential segregation and disparities in obesity among women. J Urban Health. 2015;92(5):843–52. https://doi.org/10.1007/s11524-015-9974-z The authors showed that, within each metropolitan statistical area, living in a neighborhood with a higher black isolation index was associated with higher odds of obesity, especially among black women.CrossRefPubMedPubMedCentralGoogle Scholar
- 41.Cozier YC, Yu J, Coogan PF, Bethea TN, Rosenberg L, Palmer JR. Racism, segregation, and risk of obesity in the Black Women's Health Study. Am J Epidemiol. 2014;179(7):875–83. https://doi.org/10.1093/aje/kwu004.
- 43.• Wong MS, Chan KS, Jones-Smith JC, Colantuoni E, Thorpe RJ Jr, Bleich SN. The neighborhood environment and obesity: understanding variation by race/ethnicity. Prev Med. 2018;111:371–7. https://doi.org/10.1016/j.ypmed.2017.11.029 The authors found that neighborhood social cohesion was negatively associated with BMI among whites and Hispanics, as well as obesity among whites. No associations between them were found for African Americans and Asians.CrossRefPubMedGoogle Scholar
- 44.• Powell-Wiley TM, Moore K, Allen N, Block R, Evenson KR, Mujahid M, et al. Associations of neighborhood crime and safety and with changes in body mass index and waist circumference: The Multi-Ethnic Study of Atherosclerosis. Am J Epidemiol. 2017;186(3):280–8. https://doi.org/10.1093/aje/kwx082 This study indicated that individual- and neighborhood-level safety over time were related to lower BMI over 10 years. In contrast, they found that objectively assessed neighborhood crime based on police records was not associated with adiposity.
- 46.Richardson AS, Troxel WM, Ghosh-Dastidar M, Hunter GP, Beckman R, Colabianchi N et al. Pathways through which higher neighborhood crime is longitudinally associated with greater body mass index. Int J Behav Nutr Phys Act 2017;14. https://doi.org/10.1186/s12966-017-0611-y.
- 48.Tung EL, Wroblewski KE, Boyd K, Makelarski JA, Peek ME, Lindau ST. Police-recorded crime and disparities in obesity and blood pressure status in Chicago. J Am Heart Assoc. 2018;7(7). https://doi.org/10.1161/JAHA.117.008030.
- 50.Mayne SL, Jose A, Mo A, Vo L, Rachapalli S, Ali H et al. Neighborhood disorder and obesity-related outcomes among women in Chicago. Int J Environ Res Public Health. 2018;15(7). https://doi.org/10.3390/ijerph15071395.
- 51.Karmeniemi M, Lankila T, Ikaheimo 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):239–51. https://doi.org/10.1093/abm/kax043.CrossRefPubMedGoogle Scholar
- 52.Smith M, Hosking J, Woodward A, Witten K, MacMillan A, Field 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. https://doi.org/10.1186/s12966-017-0613-9.CrossRefPubMedPubMedCentralGoogle Scholar
- 58.•• Powell-Wiley TM, Wong MS, Adu-Brimpong J, Brown ST, Hertenstein DL, Zenkov E, et al. Simulating the impact of crime on African American women’s physical activity and obesity. Obesity (Silver Spring). 2017;25(12):2149–55. https://doi.org/10.1002/oby.22040 This study demonstrated that neighborhood crime could play a role as a barrier for leisure-time physical activity, suggesting that crime reduction with multilevel intervention strategies and programs could lower obesity prevalence, which in turn contributes to promote physical activity.CrossRefGoogle Scholar
- 59.•• Tamura K, Wilson JS, Puett RC, Klenosky DB, Harper WA, Troped PJ. Accelerometer and GPS analysis of trail use and associations with physical activity. J Phys Act Health. 2018;15(7):523–30. https://doi.org/10.1123/jpah.2016-0667 The authors demonstrated that concurrent use of accelerometers and GPS data has indicated that more trail use days were related to higher moderate physical activity.CrossRefPubMedGoogle Scholar
- 60.Tamura K, Elbel B, Athens JK, Rummo PE, Chaix B, Regan SD, et al. Assessments of residential and global positioning system activity space for food environments, body mass index and blood pressure among low-income housing residents in New York City. Geospat Health. 2018;13(2):298–307. https://doi.org/10.4081/gh.2018.712.CrossRefGoogle Scholar
- 61.•• Chaix B, Kestens Y, Duncan DT, Brondeel R, Meline J, El Aarbaoui T, et al. A GPS-based methodology to analyze environment-health associations at the trip level: case-crossover analyses of built environments and walking. Am J Epidemiol. 2016;184(8):570–8. https://doi.org/10.1093/aje/kww071 The authors used GPS and web-based surveys to better understand physical activity throughout the day, which allows researchers to investigate life-segment assessments of environment exposures in relation to walking.CrossRefPubMedGoogle Scholar
- 63.Dunton GF, Dzubur E, Intille S. Feasibility and performance test of a real-time sensor-informed context-sensitive ecological momentary assessment to capture physical activity. J Med Internet Res. 2016;18(6). https://doi.org/10.2196/jmir.5398.
- 64.Dunton GF, Dzubur E, Kawabata K, Bo B, Intille S. Development of a smartphone application to measure physical activity using sensor-driven context-sensitive ecological momentary assessment. Ann Behav Med. 2014;47:S52-S.Google Scholar
- 65.Zenk SN, Horoi I, Jones KK, Finnegan L, Corte C, Riley B, et al. Environmental and personal correlates of physical activity and sedentary behavior in African American women: an ecological momentary assessment study. Women Health. 2017;57(4):446–62. https://doi.org/10.1080/03630242.2016.1170093.CrossRefPubMedGoogle Scholar
- 66.Adu-Brimpong J, Coffey N, Ayers C, Berrigan D, Yingling LR, Thomas S et al. Optimizing scoring and sampling methods for assessing built neighborhood environment quality in residential areas. Int J Environ Res Public Health. 2017;14(3). https://doi.org/10.3390/ijerph14030273.
- 71.Kershaw KN, Albrecht SS. Racial/ethnic residential segregation and cardiovascular disease risk. Curr Cardiovasc Risk Rep. 2015;9(3).Google Scholar
- 72.Lê-Scherban F, Albrecht SS, Osypuk TL, Sanchez BN, Roux AVD. Neighborhood ethnic composition, spatial assimilation, and change in body mass index over time among Hispanic and Chinese immigrants: Multi-Ethnic Study of Atherosclerosis. Am J Public Health. 2014;104(11):2138–46. https://doi.org/10.2105/Ajph.2014.302154.
- 77.Sawyer ADM, Jones R, Ucci M, Smith L, Kearns A, Fisher A. Cross-sectional interactions between quality of the physical and social environment and self-reported physical activity in adults living in income-deprived communities. Plos One. 2017;12(12). doi:ARTN e0188962. https://doi.org/10.1371/journal.pone.0188962.
- 79.Chaix B. Mobile sensing in environmental health and neighborhood research. Annu Rev Public Health. 2018;39:367–84. https://doi.org/10.1146/annurev-publhealth-040617-013731.CrossRefPubMedGoogle Scholar
- 80.Drewnowski A, Aggarwal A, Tang W, Hurvitz PM, Scully J, Stewart O, et al. Obesity, diet quality, physical activity, and the built environment: the need for behavioral pathways. BMC Public Health. 2016;16:1153. https://doi.org/10.1186/s12889-016-3798-y.