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. Author manuscript; available in PMC: 2017 Dec 1.
Published in final edited form as: J Transp Health. 2016 Mar 22;3(4):467–478. doi: 10.1016/j.jth.2016.02.010

Table 4.

Associations of built environment attributes with days of walking for transportation (n=8,462)

Built environment variable (unit) Buffer size Model Days/week of walking Interactions by study site Curvilinear (MEV Model)
exp(b) (95% CI) p
Net residential density (1000 dwellings/km2) 1km SEV 1.01# (1.01, 1.01) <0.001 NS. graphic file with name nihms772109t4.jpg
MEV 1.09# (1.00, 1.18) 0.045 NS.
500m SEV 1.01# (1.01, 1.01) <0.001 NS.
MEV 1.10# (1.00, 1.20) 0.049 NS.
Land use mix - 3 uses 1km SEV 1.10 (1.04, 1.17) 0.002 NS. NONE
MEV - -
500m SEV 1.09 (1.03, 1.15) 0.001 NS.
MEV - -
Intersection density (100 intersections/km2) 1km SEV 1.08 (1.04, 1.12) <0.001 Adelaide
Ghent
Aarhus
Wellington
Seattle		 graphic file with name nihms772109t5.jpg
MEV - -
500m SEV 1.04# (1.02, 1.07) 0.002 NS.
MEV 1.01# (0.96, 1.06) 0.746 NS.
No. parks contained or intersected by buffer (1 park/km2) 1km SEV 1.00# (1.00, 1.01) 0.018 Ghent
Aarhus
North Shore
Waitakere
Seattle		 graphic file with name nihms772109t6.jpg
MEV 1.00# (1.00, 1.01) 0.956 Ghent
Aarhus
North Shore
Waitakere
Seattle
500m SEV 1.01 (1.00, 1.01) 0.018 NS.
MEV - -

Notes. SEV = single-environment-variable model; MEV = multi-environment-variable model; exp(b) = antilogarithm of regression coefficient to be interpreted as the proportional increase in the outcome associated with a unit increase in the predictor; exp(95% CI) = antilogarithm of confidence intervals; - = excluded from the model as not a significant independent correlate of the outcome; All regression coefficients are adjusted for respondents’ age, sex, marital status, educational attainment, employment status, administrative-unit socio-economic status, and city.