The Housing Choice Voucher Program (often referred to as Section 8) was the only intervention reviewed that had sufficient evidence for implementation or expansion. This federal government program assists very low-income families, older persons, and persons with disability in accessing safe and sanitary housing in the private market and reducing rent burdens.21,22 To have housing choice and mobility, participants can use the vouchers in any neighborhood with available housing units that meet the US Department of Housing and Urban Development's health and safety standards.21 The program currently assists approximately 2 million households22; however, only 1 of every 4 households eligible for the voucher program receives federal housing assistance because of funding limitations.22,23
State and local housing agencies have flexibility in determining the income eligibility limits for local voucher programs and may set the maximum income between 50% and 80% of local area median income.22 The amount that a voucher pays toward housing costs is based on (1) a payment standard set by the local housing agency that can range from 90% to 110% of the area's fair market rent; (2) the actual cost for rent and utilities for the particular housing unit; and (3) the household's annual adjusted income, which factors in information such as the number of children in a household, child care costs, and disability status.22 In general, the program aims for households to contribute 30% of their income toward housing costs; however, some households pay more than this because of actual housing costs and local payment standards.
The program aims to help families move from deprived, racially segregated neighborhoods where many public housing projects are located. Indeed, on average, public housing residents live in neighborhoods that are 59% minority, whereas households receiving vouchers live in neighborhoods that are 39% minority.24 Similarly, in the late 1990s, 14.8% of voucher recipients lived in high-poverty neighborhoods (poverty rate >30%) compared with 53.6% of public housing residents.25
Population-based data from New York City compare housing outcomes (eg, crowding, affordability, and maintenance deficiencies) in subsidized housing with those in unregulated rental housing. These data suggest that voucher holders experienced less crowding and faced lower rent burdens than low-income individuals living in unregulated housing.26 The mean number of persons per room for individuals with a Section 8 certificate or voucher was 0.63 compared with 0.69 in unregulated rental properties (P < .05). The mean rent as a percentage of income was 44 for individuals with a Section 8 certificate or voucher compared with 73 in unregulated rental housing (P < .05).
In addition, housing vouchers may mitigate some of the negative health consequences of food insecurity on children. Among food-insecure households, children whose families were not receiving a housing subsidy were 2.11 times (95% confidence interval [CI]: 1.34-3.32) likelier to have a weight (standardized for age) more than 2 SDs below the median weight.27 These data suggest that housing subsidies may help to protect the nutritional status of children living in low-income, food-insecure households.
Finally, neighborhood choice may be improved through voucher programs. Evidence shows that when families are provided with housing search assistance and counseling, they can find housing in better-quality neighborhoods. Housing search counseling may be specifically tailored to assist families in finding neighborhoods that offer better opportunities for healthy living, such as neighborhoods with low crime rates or healthy food options.28–30 Additional research is needed to examine the impact of voucher programs on other important outcome measures such as youth educational performance.
Interventions needing more field evaluation
Relocation to low-poverty neighborhoods
Two of the interventions reviewed—relocating families to low-poverty neighborhoods and demolishing distressed public housing and relocating its residents—need more field testing but are promising. The primary evidence supporting interventions that move families from high- to low-poverty neighborhoods comes from the Moving to Opportunity (MTO) program, which was sponsored by the US Department of Housing and Urban Development and began in 1994. A total of 4608 low-income families residing in central-city public housing in high-poverty neighborhoods (poverty rate ≥40%) in 5 metropolitan areas (Baltimore, Boston, Chicago, Los Angeles, and New York) that volunteered were randomly assigned to 1 of 3 groups as part of an experimental, longitudinal study design:30–35
- The experimental group was offered Section 8 housing vouchers that could be used only in a low-poverty neighborhood (poverty rate ≤10%).
- The comparison group was offered geographically unrestricted Section 8 housing vouchers.
- The control group did not receive vouchers but remained eligible for public housing.
In general, MTO researchers found better health among members of the experimental group and, in some instances, the comparison group than among members of the control group. Health improvements included reducing adult obesity by 11% in the experimental group.36 In addition, MTO increased perceived safety, with 55% of individuals in the control group reporting feeling safe at night in their neighborhoods compared with 71% in the Section 8 group and 85% in the experimental group.36
Girls aged 12 to 19 years in the experimental group and, in some instances, girls in the Section 8 comparison group reported improved mental health, including reduced psychological distress, depression, and generalized anxiety disorder.36 When compared with their counterparts in public housing, girls aged 15 to 19 years in the experimental group also had better health behaviors, such as lower rates of smoking and marijuana use.36 Data from other mobility studies, such as the Yonkers Scattered-Site Public Housing Program, have corroborated the evidence linking improved mental health outcomes to housing mobility programs.35,37–39
Additional field evaluation is warranted to examine other health outcomes, such as asthma, blood pressure, and alcohol use, that showed no significant improvements at the latest MTO follow-up, all of which could be influenced by neighborhood conditions.30 For example, some evidence from the MTO study shows negative impacts for adolescent boys who participated in the program, with adolescent boys in the experimental group demonstrating higher rates of injuries and substance use than those in the control group.40
In addition, families in the experimental group faced challenges in successfully using their housing vouchers and had high rates of subsequent moves after the required 1-year lease in a low-poverty neighborhood. Just 48% of the 1820 families assigned to the experimental group found a willing landlord with a suitable rental unit and moved successfully. At the time of the interim evaluation, 66% of the families in the experimental groups had moved at least once after their initial lease expired. Those families that had moved were likelier to live in a higher poverty neighborhood than those who remained in the same census tract of their initial move with their MTO voucher. However, families in the MTO experimental group were still much likelier to be living in low-poverty areas (whether the original placement areas or other areas) than their Section 8 voucher or control family counterparts and also had lived for longer periods of time in such areas than families in the other 2 groups. These data highlight the need for housing mobility programs to help participants both move to and remain in low-poverty neighborhoods.41
To date, results from MTO evaluations also show inconsistent impacts on youth educational outcomes.36,42,43 The interim evaluation found significant impacts on only 2 of the 58 educational outcomes analyzed for the Section 8 group and no significant impacts for the experimental group.36 Impacts on education may be confounded by factors such as the size and quality of school districts and the presence of school choice programs.44 Although families moved to lower-poverty neighborhoods, nearly three-fourths of the children in the experimental group remained in schools within their baseline school district at the time of the interim evaluation.36 In addition, given that a high proportion of families in the experimental group had moved at least once at the time of the interim evaluation, educational impacts may be confounded by housing instability. These inconsistent findings highlight the need to provide ongoing support services for families who relocate to lower-poverty neighborhoods.44
Further study is needed to better understand the full impact of housing mobility programs on specific subgroups such as adolescent boys and to identify ways to improve mobility programs to ensure that households can successfully use their vouchers and promote long-term residence in low-poverty neighborhoods. The MTO Final Evaluation is expected to be completed in 2011 and will help to assess whether the effects demonstrated at the time of the interim evaluation are sustained over the long term.
Demolition of distressed public housing and relocation of residents: Housing Opportunities for People Everywhere
Housing and Urban Development's HOPE VI program funds the demolition and revitalization of housing units that are substantially physically deteriorated and located in high-poverty neighborhoods (>30% of residents living in poverty). HOPE VI aims to improve the living environment for residents of distressed public housing developments by improving housing quality, increasing supportive services, and avoiding or decreasing concentrated poverty.42 Residents are relocated during the demolition and revitalization of their original properties. Some residents will ultimately move back to the new community that replaced the development, whereas others receive vouchers or move to other public housing developments.
The Urban Institute evaluated the impact of the program on residents through “The HOPE VI Panel Study,” a longitudinal study that collected baseline and follow-up data at 5 sites. At the 2001 baseline survey, 38% of adults participating in HOPE VI were reported to be in “excellent” or “very good” physical health compared with the national average of 68% and the minority national average of 60% reported in the 2001 National Health Interview Survey.45 Thirty-three percent of residents reported peeling paint or plaster in their units, 25% reported cockroach infestation, 42% reported water leaks, 33% reported inadequate heat, and 16% reported rat and mice infestations.45 In addition, 90% of residents reported serious problems with drug trafficking, drug use, and gang activity in their neighborhoods, and 75% reported that violent crimes were “big problems” in their neighborhoods.45
Data from the 2005 follow-up survey suggest that housing quality improved for those people who relocated to the private housing market through the HOPE VI program. At the 2005 follow-up survey, 25% of residents living in private market units reported having 2 or more housing problems (eg, leaks, peeling paint, broken appliances) compared with more than 50% at the 2001 baseline survey.42 However, self-rated health was still significantly worse than national averages, with 41% of HOPE VI study participants reporting fair or poor health in the 2005 survey.46 In addition, mental health problems persisted, with 29% of respondents reporting poor mental health.
Families that relocated to the private market derived the most benefit from relocation, and adults experienced significantly reduced anxiety. Those people who were relocated to other public housing saw decreased violence and drug activity in their neighborhoods but saw no change in their housing quality.42 The data also show that residents were still living in racially segregated neighborhoods and that the program did not influence employment rates regardless of where an individual relocated.42 Finally, although a major goal of the HOPE VI program is rehabilitating or rebuilding the original distressed public housing units into a mixed-income community, only 5% of residents in the study sample had been able to move back to a rehabilitated HOPE VI site as of 2005. To date, the HOPE VI research does not provide insight into the potential benefits of mixed-income housing.
Interventions needing more formative research
The panel identified 7 interventions needing more formative research. Given the limited research identified by the panel examining connections between these interventions and health outcomes, this section only briefly reviews the interventions and any existing literature.
Universal design criteria promote access to the home for all persons regardless of age or physical ability. The criteria include accessibility features at new construction to avoid the need for later home modifications. These standards can include providing at least 1 entrance without stairs, a bathroom on the ground-floor level, door widths that accommodate wheelchairs, and open work counters in kitchens and other areas that allow their use in wheelchairs or while seated. These designs can help people remain connected with their communities. Although a number of cities and jurisdictions are including universal design standards in local code or city accessibility plans,47 the panel was unable to locate any data linking the implementation of universal design standards to improved health outcomes.
Crime prevention through environmental design
Crime prevention through environmental design (CPTED) interventions use various design principles, previously described in the literature, to discourage crime.48 CPTED principles have been applied to different settings, including workplaces, jails, universities, nightclubs, subway systems, and residential areas.49
An evaluation of CPTED in Sarasota, Florida, suggests that implementing various CPTED interventions resulted in some benefits regarding police service needs, rates of prostitution, and rates of narcotic crimes.50 However, this evaluation did not control for potential neighborhood-level confounders and did not allow the evaluation of individual CPTED components. Additional evidence suggests that CPTED can reduce workplace robberies and robbery-related workplace injuries and homicides.51,52 However, these evaluations suffer from study design limitations and are specific to businesses, although some businesses may colocate with residences. Additional formative research is needed to evaluate the effectiveness of CPTED in residential areas, to control for confounding factors, and to identify specific elements of CPTED that are most applicable to residential areas.
Smart growth and connectivity designs
The design strategies of new urbanism, smart growth, and connectivity promote the design of housing in communities to allow easy access to services and community resources without driving. Smart growth and connectivity strategies are supported by research linking land use and design patterns with physical activity levels and by evidence that sprawl negatively affects health outcomes.53 Sprawl has been linked to increased risks of obesity and hypertension and lower rates of physical activity.54,55 Adults living in walkable neighborhoods—defined as neighborhoods where residents can walk to essential services such as grocery stores and other common destinations—are likelier to meet national physical activity guidelines than those adults living in the least walkable neighborhoods.56 In addition, individuals living in mixed-use neighborhoods with easy walking access to shops and other services have a 35% lower risk of obesity,57 and children are likelier to be physically active when sidewalks are present and destinations are easily accessible.58 Individuals living in walkable neighborhoods also show higher levels of social capital as indicated by political participation, social involvement, trust, and knowing one's neighbors.59 Despite this evidence, additional research is needed to examine the effects of individual smart growth components to determine the combinations of smart growth features that most impact health and to better understand potential confounding factors.
Residential siting away from highways
Individuals living within 30 m from highways are exposed to higher levels of air pollutants than individuals living at least 200 m away from highways.19 Children living within 75 m of a highway or arterial road are 1.5 times more likely to suffer from asthma (95% CI: 1.16–1.95) and 1.40 times likelier to experience wheezing (95% CI: 1.09–1.78).60 The current research on cardiac health and lung cancer development suggests that exposure to elevated levels of particulate matter is associated with cardiac mortality and lung cancer rates.19,61 The existing literature supports policies that place a buffer zone between freeways and new residences, schools, day cares, and other areas where children spend much time. These strategies are particularly critical regarding low-income communities and communities of color that are disproportionately exposed to air pollutants.62–64 The research identified by the panel examines only the association between residential siting near highways and risk of negative health outcomes rather than associations between interventions to mitigate these impacts and subsequent health outcomes.
Zoning is the use of local ordinances to specify permitted and prohibited land uses within certain areas (zones) within a jurisdiction. Zoning ordinances specify what types of development can occur in what areas (eg, residential, industrial), maximum building height, building setback requirements, and other features intended to ensure that development occurs in a manner that will provide neighborhood consistency and protect resident health. Zoning tools have been used to limit the proximity of alcohol outlets to schools and playgrounds,65 to limit the concentration of fast-food restaurants within neighborhoods,65 and to create environmental health buffer zones to ensure that housing units, schools, and other sensitive land uses are located away from freeways.66 Researchers have also hypothesized that altering zoning ordinances to incorporate nursing homes and assisted living facilities directly into communities could improve health for older persons through an increase in social capital.67 Despite the potential for zoning tools to improve health outcomes and decrease health disparities, the panel did not identify specific literature linking zoning with improved health outcomes and therefore recommends more formative research in this area.
Density bonuses are land use planning tools that enable developers to build at higher densities (the average number of people per unit of land) than normally permitted in an area. These bonuses are often provided in exchange for the developers' contribution to desired public features, such as affordable housing or the preservation of open space or resource lands. No literature was located that specifically linked density bonuses as an urban planning tool to any health outcomes; however, studies have examined connections between residential densities and physical activity and between residential densities and air quality.68,69 The results of these studies are mixed and are likely confounded by many other neighborhood- and individual-level factors that make disentangling the direct and indirect impacts of density on health difficult.
Green space around housing
Various studies of residents living in Chicago's public housing developments have provided evidence that trees and other vegetation surrounding public housing buildings and within public spaces can positively affect residents. The researchers demonstrated that trees in public spaces resulted in higher use of the space by both children and adults and that children's level of play and supervision by adults were twice that observed in barren public spaces without trees and grass.70,71 Another study of public housing residents in Chicago revealed that residents' sense of safety was positively correlated with the density of trees and maintenance of grass in the residents' neighborhood.72 Finally, in another study, 145 women living in a Chicago public housing development were randomly assigned to buildings with high or low amounts of surrounding vegetation. The study revealed that residents living in barren buildings surrounded by little to no vegetation reported higher levels of aggression and violence than residents in buildings surrounded by more vegetation.73
The majority of studies examining housing proximity to greenery have been conducted with a specific population of public housing residents in Chicago and with methodological limitations.70,71 Additional research is needed to examine whether these effects can be generalized to other populations and to examine whether the planting of trees and vegetation as an intervention would result in improved physical or mental health outcomes for residents.
This review supports the expansion of the Housing Choice Voucher Program on the basis of evidence that voucher holders are less likely to suffer from overcrowding, malnutrition due to food insecurity, and concentrated poverty than nonvoucher holders. A number of neighborhood-level interventions show potential for improving the health and well-being of individuals, even though the majority of these interventions were not explicitly designed to improve health. The evidence of associations between specific neighborhood-level interventions and improved health suggests strong potential for spillover health effects from a number of these policies. Furthermore, many of the interventions have positively affected other areas of social, economic, and environmental well-being. Tools and strategies exist to ensure that health impacts are considered at the forefront of neighborhood-level housing policies and programs. For example, a health impact assessment can be used to ensure adequate housing conditions, stability, and affordability during residential redevelopment and construction.74
Efforts to improve neighborhood environments are critical to ensuring safe, healthy, and affordable housing for all people in the United States. The intent of this review panel was not to discourage the implementation of the policies presented in this document but, rather, to highlight the need for improved research designs that specifically identify direct and indirect health improvements related to these policies. Moving forward, the panel recommends that key leaders and researchers in housing, health, economic, and environmental fields collaborate to identify key neighborhood-level policies that can be supported and evaluated for their impacts on individual and neighborhood well-being. Many of these policies may have positive co-benefits to health, social justice, and other areas.
1. US Department of Health and Human Services. The Surgeon General's Call to Action to Promote Healthy Homes. Washington, DC: US Department of Health and Human Services, Office of the Surgeon General; 2009.
2. Northridge ME, Sclar ED, Biswas P. Sorting out the connections between the built environment and health: a conceptual framework for navigating pathways and planning healthy cities. J Urban Health. 2003; 80(4):556–568.
4. Ellen IG, Turner MA. Do neighborhoods matter and why? In:Goering J, Feins JD, eds. Choosing a Better Life? Evaluating the Moving to Opportunity Social Experiment. Washington, DC: The Urban Institute Press; 2003:313–338.
5. Ellen IG, Mijanovich T, Dillman KN. Neighborhood effects on health: exploring the links and assessing the evidence. J Urban Aff. 2001; 23(3-4):391–408.
6. Kawachi I, Berkman LF, eds. Neighborhoods and Health. New York, NY: Oxford University Press; 2003.
7. Macintyre S, Ellaway A. Ecological approaches: rediscovering the role of the physical and social environment. In:Berkman LF, Kawachi I, eds. Social Epidemiology. New York, NY: Oxford University Press; 2000:332-348.
8. Macintyre S, Ellaway A, Cummins S. Place effects on health: how can we conceptualise, operationalise and measure them? Soc Sci Med. 2002; 55(1):125–139.
9. Macintyre S, Ellaway A. Neighborhoods and health: an overview. In:Kawachi I, Berkman LF, eds. Neighborhoods and Health. New York, NY: Oxford University Press; 2003:20-42.
10. Pickett KE, Pearl M. Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. J Epidemiol Community Health. 2001; 55(2):111–122.
11. Diez Roux AV, Nieto FJ, Muntaner C, et al. Neighborhood environments and coronary heart disease: a multilevel analysis. Am J Epidemiol. 1997; 146(1):48–63.
12. Waitzman NJ, Smith KR. Phantom of the area: poverty-area residence and mortality in the United States. Am J Public Health. 1998; 88(6):973–976.
13. Buckner JC. Understanding the impact of homelessness on children: challenges and future research directions. Am Behav Sci. 2008; 51(6):721–736.
14. Weinreb L, Goldberg R, Perloff J. Health characteristics and medical service use patterns of sheltered homeless and low-income housed mothers. J Gen Intern Med. 1998; 13(6):389–397.
15. Marsh A, Gordon D, Heslop P, Pantazis C. Housing deprivation and health: a longitudinal analysis. Housing Stud. 2000; 15(3):411–428.
16. Centers for Disease Control and Prevention. Neighborhood safety and prevalence of physical inactivity-selected states. MMWR Morb Mortal Wkly Rep. 1996; 48:143–146.
17. Sallis JF, McKenzie TL, Elder JP, Broyles SL, Nader PR. Factors parents use in selecting play spaces for young children. Arch Pediatr Adolesc Med. 1997; 151(4):414–417.
18. Morland K, Wing S, Roux AD, Poole C. Neighborhood characteristics associated with the location of food stores and food service places. Am J Prev Med. 2002; 22(1):23–29.
19. Brugge D, Durant JL, Rioux C. Near-highway pollutants in motor vehicle exhaust: a review of epidemiologic evidence of cardiac and pulmonary health risks. Environ Health. 2007; 6:23.
20. Jacobs DE, Brown MJ, Baeder A, et al. A systematic review of housing interventions and health: introduction and methods. J Public Health Manag Pract. 2010; 16(5S):S5–S10.
22. Center on Budget and Policy Priorities. Introduction to the Housing Voucher Program. Washington, DC: Center on Budget and Policy Priorities; 2009. http://www.cbpp.org/files/5-15-09hous.pdf
. Accessed November 12, 2009.
23. Center on Budget and Policy Priorities. Policy Basics: The Housing Choice Voucher Program. Washington, DC: Center on Budget and Policy Priorities; 2007. http://www.centeronbudget.org/5-15-03hous.htm
. Accessed November 14, 2008.
25. Turner MA. Moving out of poverty: expanding mobility and choice through tenant-based housing assistance. Housing Pol Debate. 1998; 9(2):373–394.
26. Van Ryzin GG, Kamber T. Subtenures and housing outcomes for low income renters in New York City. J Urban Aff. 2002; 24(2):197–218.
27. Meyers A, Cutts D, Frank DA, et al. Subsidized housing and children's nutritional status: data from a multisite surveillance study. Arch Pediatr Adolesc Med. 2005; 159(6):551–556.
28. Acevedo-Garcia D, Osypuk TL. Impacts of housing and neighborhoods on health: pathways, racial/ethnic disparities, and policy directions. In:Carr J, Kutty N, eds. Segregation: The Rising Costs for America. New York, NY: Routledge; 2008;197–235.
29. Acevedo-Garcia D, Osypuk TL, McArdle N, Williams DR. Towards a policy relevant analysis of geographic and racial/ethnic disparities in child health. Health Aff (Millwood). 2008; 27(2):321–333.
30. Acevedo-Garcia D, Osypuk TL, Werbel RE, et al. Does housing mobility policy improve health? Housing Pol Debate. 2004; 15(1):49–98.
31. Goering J. The impacts of new neighborhoods on poor families: evaluating the policy implications of the Moving to Opportunity demonstration. Federal Reserve Bank N Y Econ Policy Rev. 2003; 9(2):113–140.
32. Goering J, Feins JD, Richardson TM. A cross-site analysis of initial Moving to Opportunity demonstration results. J Housing Res. 2002; 13(1):1–30.
33. Goering J, Feins JD, eds. Choosing a Better Life? Evaluating the Moving to Opportunity Social Experiment. Washington, DC: The Urban Institute Press; 2003.
34. Leventhal T, Brooks-Gunn J. Moving to Better Neighborhoods Improves Health and Family Life Among New York Families. New York, NY: Joint Center for Poverty Research; 2001.
35. Leventhal T, Brooks-Gunn J. Moving to Opportunity: an experimental study of neighborhood effects on mental health. Am J Public Health. 2003; 93(9):1576–1582.
36. Orr L, Feins JD, Jacob R, et al. Moving to Opportunity Interim Impacts Evaluation. Final Report. Washington, DC: US Department of Housing and Urban Development, Office of Policy Development and Research (PD& R); 2003. http://www.abtassociates.com/reports/2003302754569_71451.pdf
. Accessed November 12, 2009.
37. Katz LF, Kling JR, Liebman JB. Moving to Opportunity in Boston: early results of a randomized mobility experiment. Quart J Econ. 2001; 116(2):607–654.
38. Briggs XD, Darden JT, Aidala A. In the wake of desegregation: early impacts of scattered-site public housing on neighborhoods in Yonkers, New York,. J Am Plann Assoc. 1999; 65(1):27–49.
39. Briggs XD, Yonkers Family and Community Projects. Yonkers Revisited: The Early Impacts of Scattered-Site Public Housing on Families and Neighborhoods. A Report to the Ford Foundation. New York, NY: Columbia University Teachers College, Harvard University, and Michigan State University; 1997.
40. Kling JR, Liebman JB, Katz LF. Experimental analysis of neighborhood effects. Econometrica. 2007; 75(1):83–119.
41. Popkin SJ, Leventhal T, Weismann G. Girls in the ‘Hood: The Importance of Feeling Safe. Washington, DC.: Urban Institute; 2008.
42. Popkin SJ, Levy D, Buron L. Has HOPE VI transformed residents' lives? Evidence from the HOPE VI panel study. Housing Stud. 2009; 24(4):477–502.
43. Briggs XD, Ferryman KS, Popkin SJ, Rendon M. Why didn't the Moving to Opportunity experiment get children to better schools? Housing Pol Debate. 2008; 19(1):53–91.
44. Leventhal T, Fauth RC, Brooks-Gunn J. Neighborhood poverty and public policy: a 5-year follow-up of children's educational outcomes in the New York City Moving to Opportunity demonstration. Dev Psychol. 2005; 41(6):933–952.
46. Manjarrez CA, Popkin SJ, Guernsey E. Poor Health: Adding Insult to Injury for HOPE VI Families. Washington, DC: Urban Institute; 2007.
47. Nishita CM, Liebig PS, Pynoos J, Perelman L, Spegal K. Promoting basic accessibility in the home: analyzing patterns in the diffusion of visitability legislation. J Disabil Pol Stud. 2007; 18(1):2–13.
48. Katyal NK. Architecture as crime control. Yale Law J. 2002;2002(5):1039–1139.
49. Mair JS, Mair M. Violence prevention and control through environmental modifications. Annu Rev Public Health. 2003; 24:209–225.
50. Carter SP, Carter SL, Dannenberg AL. Zoning out crime and improving community health in Sarasota, Florida: “crime prevention through environmental design.” Am J Public Health. 2003; 93(9):1442–1445.
51. Casteel C, Peek-Asa C. Effectiveness of crime prevention through environmental design (CPTED) in reducing robberies. Am J Prev Med. 2000; 18(4)(suppl):99–115.
52. Loomis D, Marshall SW, Wolf SH, Runyan CW, Butts JD. Effectiveness of safety measures recommended for prevention of workplace homicide. JAMA. 2002; 287(8):1011–1017.
53. Frumkin H, Frank L, Jackson RJ. Urban Sprawl and Public Health: Designing, Planning, and Building for Healthy Communities. Washington, DC: Island Press; 2004.
54. Ewing R, Schmid T, Killingsworth R, Zlot A, Raudenbush S. Relationship between urban sprawl and physical activity, obesity, and morbidity. Am J Health Promot. 2003; 18(1):47–57.
55. Lopez R. Urban sprawl and risk for being overweight or obese. Am J Public Health. 2004; 94(9):1574–1579.
56. Frank LD, Schmid TL, Sallis JF, Chapman J, Saelens BE. Linking objectively measured physical activity with objectively measured urban form—findings from SMARTRAQ. Am J Prev Med. 2005; 28(2):117–125.
57. Frank LD, Andresen MA, Schmid TL. Obesity relationships with community design, physical activity, and time spent in cars. Am J Prev Med. 2004; 27(2):87–96.
58. Davidson KK, Lawson CT. Do attributes in the physical environment influence children's physical activity? A review of the literature. Int J Behav Nutr Phys Act. 2006; 3:19–35.
59. Leyden KM. Social capital and the built environment: the importance of walkable neighborhoods. Am J Public Health 2003; 93(9):1546–1551.
60. McConnell R, Berhane K, Yao L, et al. Traffic, susceptibility, and childhood asthma. Environ Health Perspect. 2006; 114(5):766–772.
61. Holguin F, Tellez-Rojo MM, Hernandez M, et al. Air pollution and heart rate variability among the elderly in Mexico City. Epidemiology. 2003; 14(5):521–527.
62. Morello-Frosch R, Pastor M, Porras C, Sadd J. Environmental justice and regional inequality in southern California: implications for future research. Environ Health Perspect. 2002; 110:149–154.
63. Brooks N, Sethi R. The distribution of pollution: community characteristics and exposure to air toxics. J Environ Econ Manage. 1997; 32(2):233–250.
64. Rauh VA, Landrigan PJ, Claudio L. Housing and health: intersection of poverty and environmental exposures. Ann N Y Acad Sci. 2008; 1136:276–288.
65. Ashe M, Jernigan D, Kline R, Galaz R. Land use planning and the control of alcohol, tobacco, firearms, and fast food restaurants. Am J Public Health. 2003; 93(9):1404–1408.
66. Coburn J. Urban planning and health disparities: implications for research and practice. Plann Pract Res. 2005; 20(2):111–126.
67. Cannuscio C, Block J, Kawachi I. Social capital and successful aging: the role of senior housing. Ann Intern Med. 2003; 139(5, pt 2): 395–399
68. Rodriguez DA, Khattak AJ, Evenson KR. Can new urbanism encourage physical activity? Comparing a new urbanist neighborhood with conventional suburbs. J Am Plann Assoc. 2006; 72(1):43–54.
69. Forsyth A, Oakes JM, Schmitz KH, Hearst M. Does residential density increase walking and other physical activity? Urban Stud. 2007; 44(4):679–697.
70. Taylor AF, Wiley A, Kuo FE, Sullivan WC. Growing up in the inner city: green spaces as places to grow. Environ Behav. 1998; 30(1):3–27.
71. Coley RL, Kuo FE, Sullivan WC. Where does community grow? The social context created by nature in urban public housing. Environ Behav. 1997; 29(4):468–494.
72. Kuo FE, Bacaicoa M, Sullivan WC. Transforming inner-city landscapes: trees, sense of safety, and preference. Environ Behav. 1998; 30(1):28–59.
73. Kuo FE, Sullivan WC. Aggression and violence in the inner city: effects of environment via mental fatigue. Environ Behav. 2001; 33(4):543–571.
74. Dannenberg AL, Bhatia R, Cole BL, et al. Use of health impact assessment in the U.S.: 27 case studies, 1999-2007. Am J Prev Med. 2008; 34(3):241–256.
Keywords:© 2010 Lippincott Williams & Wilkins, Inc.
environmental justice; law; prevention; public policy; universal design