Takemi Sugiyama PhD MArch

Spatial Epidemiology & Evaluation Research Group

University of South Australia, Adelaide, Australia

Perceived Neighbourhood Environmental Attributes Associated

with Adults’ Recreational Walking

IPEN Adult Study in 12 Countries

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.

Co-AuthorsEster 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)

Acknowledgements

IPEN Coordinating CentreNicole BracyKelli CainCarrie GeremiaLisa HusakMarc Adams

IPEN Executive CommitteeJames F SallisJacqueline KerrIlse De BourdeaudhuijNeville OwenLawrence FrankTerry ConwayTakemi Sugiyama

And all IPEN investigators

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 single-country 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.

Background

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

Aims

The International Physical Activity and Environment Network (IPEN) Adult Study was an observational, cross-sectional, 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).

IPEN Adult Study

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, socio-demographic covariates, and area-level SES.

Interaction effects were probed by computing the site-specific 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

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

Descriptive Results

Walking 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]

%reporting no walking 43% 21% [DEN] 66% [MEX]

1 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

Environmental attributes Mean (SD) Lowest4 Highest4

Residential density score1 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]

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

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 2)

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

Linear Association (Model 3)

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.

Curvilinear Association (Model 1)

Residential density score

Odd

s of

wal

king

for

rec

reat

ion

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.

Curvilinear Association (Model 1)

Land use mix – access

Odd

s of

wal

king

for

rec

reat

ion

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.

Curvilinear Association (Model 3)

Aesthetics

Min

utes

of

wal

king

for

rec

reat

ion

Associations were not significant in Australia, Belgium, Brazil, Columbia, Czech Republic (Olomouc, Hradec Kralove), Denmark, Mexico, New Zealand (Christchurch), Spain, UK, USA (Seattle)

Site-Specific Associations (Aesthetics)

Country (study site) 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

Site-specific linear associations of aesthetics with duration of walking for recreation among walkers

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)

Q1. To examine the strength and shape of associations of perceived neighbourhood environmental attributes with adults’ recreational walking

Summary

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

Q1. To examine the strength and shape of associations of perceived neighbourhood environmental attributes with adults’ recreational walking

Summary

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.

Summary

Q2. To examine whether associations of environmental attributes with recreational walking differ across countries

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.

Conclusions

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.

Funding Sources