Perceived Neighbourhood
Environmental Attributes Associated
with Adults’ Recreational Walking
IPEN Adult Study in 12 Countries
Takemi Sugiyama PhD MArch
Spatial Epidemiology & Evaluation Research Group
University of South Australia, Adelaide, Australia
Sugiyama T, Cerin E, Owen N, Oyeyemi AL, Conway TL, Van Dyck D, Schipperijn J, Macfarlane DJ, Salvo D, Reis RS,
Mitáš J, Sarmiento OL, Davey R, Schofield G, Orzanco-Garralda R, Sallis JF. Perceived neighbourhood environmental
attributes associated with adults’ recreational walking: IPEN Adult study in 12 countries. Health & Place, 2014;28:22–30.
Acknowledgements
Co-Authors
Ester Cerin (Hong Kong)
Neville Owen (Australia)
Adewale L Oyeyemi (Nigeria)
Terry L Conway (USA)
Delfien Van Dyck (Belgium)
Jasper Schipperijn (Denmark)
Duncan J Macfarlane (Hong Kong)
Deborah Salvo (Mexico)
Rodrigo S Reis (Brazil)
Josef Mitáš (Czech Republic)
Olga L Sarmiento (Colombia)
Rachel Davey (UK)
Grant Schofield (New Zealand)
Rosario Orzanco-Garralda (Spain)
James F Sallis (USA)
IPEN Coordinating Centre
Nicole Bracy
Kelli Cain
Carrie Geremia
Lisa Husak
Marc Adams
IPEN Executive Committee
James F Sallis
Jacqueline Kerr
Ilse De Bourdeaudhuij
Neville Owen
Lawrence Frank
Terry Conway
Takemi Sugiyama
And all IPEN investigators
Background
An increasing number of studies have examined
associations of neighbourhood environmental attributes
with physical activity.
To date, most studies on this topic have examined data
collected in a single country.
Non-significant or weak associations reported in singlecountry studies may be due partly to limited variation in
environmental attributes.
Multi-country studies can fill this methodological gap by
provide larger variance in environmental attributes.
Aims
Q1. To examine the strength and shape of associations
of perceived neighbourhood environmental
attributes with adults’ recreational walking using
data obtained from 12 countries
Q2. To examine whether these associations differ
across countries
IPEN Adult Study
The International Physical Activity and Environment
Network (IPEN) Adult Study was an observational, crosssectional, multi-country study, involving 13,745 adults aged
18–66 years from 12 countries (17 study sites).
Countries included: Australia (AUS; Adelaide), Belgium
(BEL; Ghent), Brazil (BRA; Curitiba), Colombia (COL;
Bogota), the Czech Republic (CZ; Olomouc, Hradec
Kralove), Denmark (DEN; Aarhus), Hong Kong (HK),
Mexico (MEX; Cuernavaca), New Zealand (NZ; North
Shore, Waitakere, Wellington, Christchurch), Spain (ESP;
Pamplona), the United Kingdom (UK; Stoke-on-Trent), and
the United States of America (USA; Baltimore, Seattle).
Outcome: Recreational Walking
Self-reported frequency (days/week) and duration
(minutes/week) of walking for recreation in the last week,
obtained from the International Physical Activity
Questionnaire (IPAQ; long version), were used.
Exposure: Neighbourhood Environment
Perceived neighbourhood environmental attributes were
determined using the Neighborhood Environment
Walkability Scale (NEWS).
The following 10 items were used:
• residential density score
• land use mix–access
• street connectivity
• infrastructure and safety
• aesthetics
• safety from traffic
• safety from crime
• few cul-de-sacs
• no major barriers
• proximity to parks
Analysis
Generalized Additive Mixed Models (GAMMs) were used
to estimate the strength and shape of associations of
perceived environmental attributes with recreational
walking. All analyses were conducted in R.
Main effects of environmental attributes on the outcome
(linear and curvilinear components) were examined for
the whole sample, adjusting for study site, sociodemographic covariates, and area-level SES.
Interaction effects were probed by computing the sitespecific association of a perceived environmental
attributed with the outcome via linear functions. Analyses
stratified by sites were conducted when significant.
Models
The following three models were examined:
Model 1: likelihood of any walking for recreation versus
no walking for recreation;
Model 2: frequency (days/week) of walking for recreation
among those reporting walking during the past week;
Model 3: duration (minutes/week) of walking for
recreation among those reporting walking during the past
week
Descriptive Results
Sample Characteristics (N=13,745)
Mean age 42 years; 57% women; 44% with a college/university
degree; 75% working; 60% married or living with a partner
Mean (SD)
Lowest2
Highest2
Frequency (days/wk)
1.9 (2.3)
1.0 [BEL]
3.6 [ESP]
Non-zero frequency (days/wk)1
3.4 (2.2)
2.1 [BEL]
4.6 [ESP]
Duration (min/wk)
115 (226)
54 [BRA]
234 [ESP]
Non-zero duration (min/wk)1
204 (249)
146 [BRA]
316 [CZ]
Walking
%reporting no walking
1
43%
21% [DEN] 66% [MEX]
among those who reported walking, 2 site-level lowest/highest [country]
BEL: Belgium; BRA: Brazil; CZ: Czech Republic (Olomouc); DEN: Denmark;
ESP: Spain; MEX: Mexico
Descriptive Results
Mean (SD)
Lowest4
Highest4
77 (114)
18 [NZ]
440 [HK]
Land use mix–access2
3.4 (0.66)
3.0 [US1]
3.7 [ESP]
Connectivity2
3.0 (0.73)
2.7 [NZ]
3.3 [BRA]
Infrastructure and safety2
3.0 (0.57)
2.6 [MEX]
3.3 [ESP]
Aesthetics2
2.8 (0.70)
2.2 [UK]
3.1 [US2]
Safety from traffic2
2.6 (0.67)
2.4 [BRA]
3.1 [CZ]
Safety from crime2
3.0 (0.80)
2.1 [COL]
3.5 [ESP]
Few cul-de-sacs2
2.8 (1.00)
2.3 [NZ]
3.5 [ESP]
No major barriers2
3.3 (0.84)
2.2 [HK]
3.7 [US1]
Proximity to parks3
4.1 (1.21)
3.1 [BEL]
4.8 [ESP]
Environmental attributes
Residential density score1
1
range: 0–1024, 2 range: 1–4, 3 range: 1–5, 4 site-level lowest/highest [country]
BEL: Belgium; BRA: Brazil; COL: Colombia; CZ: Czech Republic (Hradec
Kralove); ESP: Spain; HK: Hong Kong; NZ: New Zealand (North Shore); US1:
USA (Baltimore); US2: USA (Seattle)
Linear Association (Model 1)
Odds of walking for recreation1
OR
95%CI
p
Residential density score
1.08
0.88, 1.32
0.482
Land use mix–access
1.02
0.90, 1.17
0.726
Connectivity
1.01
0.96, 1.07
0.745
Infrastructure and safety
1.01
0.94, 1.09
0.826
Aesthetics
1.26
1.18, 1.35
<0.001
Safety from traffic
1.05
0.99, 1.11
0.128
Safety from crime
1.07
1.00, 1.14
0.036
Few cul-de-sacs
0.94
0.90, 0.98
0.024
No major barriers
1.00
0.95, 1.05
0.886
Proximity to parks
1.07
1.03, 1.11
0.031
1
Analysis for the whole sample (n=13,745), GAMMs with binomial variance and
logit link functions
Linear Association (Model 2)
Non-zero walking frequency1 (days/wk)
exp(b)
95%CI
p
Residential density score
1.001
0.999, 1.003
0.138
Land use mix–access
1.02
0.99, 1.05
0.062
Connectivity
1.02
1.00, 1.05
0.025
Infrastructure and safety
0.97
0.94, 1.00
0.053
Aesthetics
1.05
1.03, 1.08
<0.001
Safety from traffic
0.99
0.96, 1.01
0.313
Safety from crime
1.00
0.97, 1.02
0.737
Few cul-de-sacs
0.99
0.98, 1.01
0.274
No major barriers
1.00
0.98, 1.02
0.898
Proximity to parks
1.01
0.99, 1.02
0.213
1
Analysis for those who reported walking (n=7,838), GAMMs with negative
binomial and logarithmic link functions
Linear Association (Model 3)
Non-zero walking duration1 (minutes/wk)
exp(b)
95%CI
p
Residential density score
1.001
1.000, 1.001
0.005
Land use mix–access
1.07
1.02, 1.11
0.003
Connectivity
1.02
0.98, 1.05
0.298
Infrastructure and safety
0.98
0.92, 1.04
0.519
Aesthetics
1.02
0.95, 1.10
0.569
Safety from traffic
0.97
0.93, 1.01
0.101
Safety from crime
0.98
0.94, 1.02
0.334
Few cul-de-sacs
0.98
0.95, 1.00
0.059
No major barriers
1.00
0.97, 1.04
0.795
Proximity to parks
1.01
0.99, 1.04
0.344
1
Analysis for those who reported walking (n=7,838), GAMMs with negative
binomial and logarithmic link functions
Odds of walking for recreation
Curvilinear Association (Model 1)
Residential density score
The solid line represents point estimates (and black dashed lines their 95% confidence intervals) of the
odds of walking at various levels of perceived environmental attribute for the imputed dataset producing
median values of odds of walking (relative to other imputed models). The black dots and grey dashed
lines represent the same estimates produced by the other nine imputed datasets.
Odds of walking for recreation
Curvilinear Association (Model 1)
Land use mix – access
The solid line represents point estimates (and black dashed lines their 95% confidence intervals) of the odds of walking at
various levels of perceived environmental attribute for the imputed dataset producing median values of odds of walking
(relative to other imputed models). The black dots and grey dashed lines represent the same estimates produced by the
other nine imputed datasets.
Minutes of walking for recreation
Curvilinear Association (Model 3)
Aesthetics
The solid line represents point estimates (and black dashed lines their 95% confidence intervals) of the odds of walking at
various levels of perceived environmental attribute for the imputed dataset producing median values of odds of walking
(relative to other imputed models). The black dots and grey dashed lines represent the same estimates produced by the
other nine imputed datasets.
Site-Specific Associations (Aesthetics)
Site-specific linear associations of aesthetics with duration of walking
for recreation among walkers
exp(b)
exp(95%CI)
p
Hong Kong
1.26
1.01, 1.56
0.037
New Zealand (North Shore)
1.36
1.06, 1.73
0.014
New Zealand (Waitakere)
1.35
1.00, 1.82
0.048
New Zealand (Wellington)
1.22
0.97, 1.54
0.089
USA (Baltimore)
1.19
1.01, 1.41
0.039
Country (study site)
Associations were not significant in Australia, Belgium, Brazil, Columbia,
Czech Republic (Olomouc, Hradec Kralove), Denmark, Mexico, New Zealand
(Christchurch), Spain, UK, USA (Seattle)
Summary
Q1. To examine the strength and shape of associations
of perceived neighbourhood environmental
attributes with adults’ recreational walking
Of the 10 perceived environmental attributes examined,
seven were (either linearly or curvilinearly) positively
associated with at least one walking outcome.
Stronger evidence was obtained for Aesthetics, which was
associated with all three walking measures, with a larger
effect size (26% higher odds of walking for a unit increase).
Summary
Q1. To examine the strength and shape of associations
of perceived neighbourhood environmental
attributes with adults’ recreational walking
Results show some support for the importance of:
• Safety from crime (linear association)
• Proximity to parks (linear association)
• Residential density (curvilinear association)
• Land use mix (curvilinear association)
Summary
Q1. To examine the strength and shape of associations
of perceived neighbourhood environmental
attributes with adults’ recreational walking
Mixed findings were obtained for:
• Connectivity and Few cul-de-sacs (higher street
connectivity and many cul-de-sacs were both positively
associated with walking)
No linear/curvilinear associations were found for:
• Infrastructure and safety
• Safety from traffic
• No major barriers
Summary
Q2. To examine whether associations of environmental
attributes with recreational walking differ across
countries
Effect modification by study sites was found for aesthetics,
which was associated linearly with walking in 4 sites.
The associations observed were mostly consistent across
countries, suggesting the generalisability of the findings.
Conclusions
Associations of perceived neighbourhood environmental
attributes with adults’ walking for recreation may be
similar in environmentally, culturally diverse countries.
Aesthetics appears to be an important factor in whether
and how often adults walk for recreation.
Higher population density (but not excessively high) and
higher land use diversity seem to contribute to longer
duration of recreational walking.
Safe neighbourhoods (from crime) with parks may
facilitate recreational walking.
Funding Sources
Australian data collection was supported by National Health and Medical
Research Council (NHMRC) of Australia Project Grant #213114. The
contributions of Neville Owen were supported by NHMRC Grant #569940,
NHMRC Senior Principal Research Fellowship#1003960, and by the
Victorian Government‫׳‬s Operational Infrastructure Support Program. Data
collection in Hong Kong was supported by the HK Research Grants Council
GRF Grants (#HKU740907H and #747807H) and HKU URC Strategic
Research Theme (Public Health). US data collection and Coordinating Center
processing was supported by the NIH Grants R01 HL67350 (NHLBI) and R01
CA127296 (NCI). The Danish study was partly funded by the Municipality of
Aarhus. Data collection in the Czech Republic was supported by the Ministry
of Education Youth and Sports Grant #MSM6198959221. The study
conducted in Colombia was funded by Colciencias Grant 519_2010, Fogarty
and CeiBA. Data collection in New Zealand was supported by the Health
Research Council of New Zealand Grant #07/356. Data collection in Mexico
was supported by the CDC Foundation (project #550), which received an
unrestricted training grant from the Coca-Cola Company. The UK study was
funded by the Medical Research Council Grant number G0501287 under the
National Preventive Research Initiative.