Table 2.

Summary of studies included in the systematic review.

Study basics	Walking or PA variable	Built environment measure	Indicator of disadvantage	Evidence of weaker built environment effect for disadvantaged groups	Description of difference in built environment effect on walking and PA
Arvidsson et al. (2013) Discipline: Public health Geography: Stockholm (Sweden) Population: Adults Sample size: 2,252	PA (continuous)	Index: residential density, street connectivity, land use mix	Incomea	Yes	“Living in a high walkability neighborhood was associated with more MVPA compared with living in a low walkability neighborhood…However, for those participants with low incomes, the P values were >0.05, although a tendency was seen with a possible association between neighborhood walkability and MVPA” (p. 698).
Forsyth et al. (2009) Discipline: Planning Geography: Minneapolis (MN) Population: Adults Sample size: 716	Walking for transport, leisure walking, total miles walked	Residential density, median block size	Race/ethnicity, educationa	Mixed	“A number of other findings were close to significance with several groups walking more in high density areas including whites, those without a college degree, the employed, those with cars, and the obese” (p. 45).
Frank et al. (2004) Discipline: Public health Geography: Atlanta (GA) Population: Adults Sample size: 10,878	Time spent in car, distance walked, BMI	Connectivity, residential density, land use mix	Racea	Yes	“The strongest association between urban form and BMI was for white males.” “Walk distance was positively associated with all three urban form variables for whites, while land use mix and intersection distance were positively associated with walk distance for black females. No linear relationships were found between urban form and walk distance for black males” (p. 93).
Frank et al. (2008) Discipline: Public health Geography: Atlanta (GA) Population: Adults Sample size: 13,065	Any walking trips over 2-day period (dichotomous), obesity	Residential density, street connectivity, land use mix	Income, race/ethnicity,a educationa	Yes	“Men without a degree, unemployed, and non-white were more likely to be obese if they lived in highly connected neighborhoods as were white women without a degree who lived in more dense neighborhoods. These two results may be due to crime and other social factors in the most urban settings in Atlanta” (p. 177).
Freeman et al. (2012) Discipline: Public health Geography: New York City (NY) Population: Adults Sample size: 8,064	Zero episodes of active travel (binary), number of episodes of active travel (continuous)	Index: residential density, intersection density, subway station density, land use mix, ratio of retail building floor area to retail land area	Income,a race/ethnicitya	Yes	“Associations between lower walkability and reporting zero episodes of active travel were significantly stronger for non-Hispanic Whites as compared to non-Hispanic Blacks and to Hispanics and for those living in higher income zip codes” (p. 575).
Hooker et al. (2005) Discipline: Public health Geography: Rural South Carolina Population: Older adults Sample size: 1,165	At least 150 min PA (binary)	Perceived environmental supports	Race/ethnicitya	Yes	“These data indicate that perceptions of certain social and safety-related environmental supports were strongly associated with meeting the recommendations for PA and walking among white but not African American adults” (p. 1).
Ivory et al. (2015) Discipline: Public health Geography: Auckland, Wellington, and Christchurch (New Zealand) Population: Adults Sample size: 2,033	PA (average accelerometer counts per hour)	Streetscape, neighborhood destinations, street connectivity	Income	No (opposite effect)	“For example, our findings showed that the built environment-physical activity gradients were steeper across income and car access groups compared to gender and working status” (p. 238).
Kerr et al. (2007) Discipline: Planning Geography: Atlanta (GA) Population: Youth Sample size: 3,161	At least one walking trip over 2-day period (binary)	Intersection density, residential density, mixed land use (binary), at least one commercial land use (binary), at least one recreation space	Race/ethnicity,a incomea	Yes	“In summary, urban form was not as significantly related to walking for non-whites, low-income groups and those with no car in the household” (p. 181).
Manaugh & El-Geneidy (2011) Discipline: Planning Geography: Montreal (Canada) Population: Adults Sample size: 17,395	Share of home-based trips by walking	Walkability index, Walk Score™, walk opportunities index	Incomea	Yes	“Wealthy, car owning households are much more sensitive to elements of walkability than retired or low-income households” (p. 315).
McCormack et al. (2014) Discipline: Public health Geography: Calgary (Canada) Population: Adults Sample size: 2,006	PA within neighborhood	Cluster analysis based on street connectivity, density of businesses and services, density of bus stops, sidewalk length, mix of park types, mix of recreational facilities, population density, pathway/cycleway length, proportion of green space	Income, educational attainment	No (no difference observed)	“…this relationship between walkability and PA appears to exist regardless of the participants’ sociodemographic and self-rated health characteristics” (p. 112).
Owen et al. (2007) Discipline: Public health Geography: Adelaide (Australia) Population: Adults Sample size: 2,650	Weekly frequency of walking for transport	Walkability index composed of housing unit density, street connectivity, land use mix, and net retail area	Educational attainmenta	Yes	“Educational attainment moderated the relationship between weekly frequency of walking for transport and neighborhood walkability. There was no significant effect of neighborhood walkability on frequency of walking for transport in respondents with 10 or less years of education. In contrast, a positive significant association was found between walkability and frequency of walking for transport in respondents with 12 or more years of education” (pp. 391–392).
Pan et al. (2009) Discipline: Public health Geography: Canada (national sample) Population: Adults Sample size: 5,167	PA (continuous), metabolic equivalent	Facility availability	Educational attainmenta	Yes	“Facility availability was more strongly associated with PA among people with a university degree than among people with lower education level” (p. 1).
Sallis et al. (2009) Discipline: Public health Geography: Seattle (WA) and Baltimore (MD) Population: Adults Sample size: 2,197	PA	Index: intersection density, residential density, retail floor area ratio, land use mix	Incomea	Yes	“Walking for transportation was significantly higher in high-walkability neighborhoods compared to low-walkability neighborhoods; however, the differential was larger in high-income neighborhoods (5.1 min) vs. low-income neighborhoods (2.3)” (p. 1288).
Steinmetz-Wood & Kestens (2015) Discipline: Public health Geography: Montreal (Canada) Population: Adults Sample size: 156,700	Walking trip (binary)	Connectivity, land use mix, density of businesses and services	Incomea	Yes	“Trips in the highest quartiles of connectivity and density of businesses and services were found to have a weaker association with active transportation if the individual undergoing the trip was from a low SES neighborhood” (p. 262).
Sundquist et al. (2011) Discipline: Public health Geography: Stockholm (Sweden) Population: Adults Sample size: 2,269	PA	Index: residential density, street connectivity, land use mix	Incomea	Yes	“The logistic part shows that the odds for walking for active transportation were 92% higher among individuals who lived in highly walkable neighborhoods than among those living in less walkable neighborhoods. After including neighborhood-level SES and the individual-level variables, the odds decreased to 1.77 (i.e. 77% higher odds) but remained significant” (p. 1271).
Van Dyck et al. (2010) Discipline: Public health Geography: Ghent (Belgium) Population: Adults Sample size: 1,166	PA	Index: residential density, street connectivity, land use mix	Income	No (no difference observed)	“For the moderating effects of neighborhood SES on the relationship between walkability and the physical activity behaviors, no significant results were found” (p. S77).
Van Holle et al. (2014) Discipline: Public health Geography: Belgium Population: Older adults Sample size: 438	PA (binary)	Index: residential density, street connectivity, land use mix	Income	No (opposite effect)	“A walkability × income interaction was found for accelerometer-derived MVPA (B = −1.826 ± 1.03; p = 0.075), showing only a positive association between walkability and MVPA in low-income neighborhood residents” (p. 1).

Note: PA = physical activity; MVPA = moderate to vigorous physical activity; BMI = body mass index; SES = socioeconomic status.

^a.Indicates differences.