Effects of the built environment on physical activity: a ...... · Antonina Tcymbal1*, Yolanda...

REVIEW ARTICLE Open Access

Effects of the built environment on physicalactivity: a systematic review of longitudinalstudies taking sex/gender into accountAntonina Tcymbal1* , Yolanda Demetriou2, Anne Kelso2, Laura Wolbring3, Kathrin Wunsch3, Hagen Wäsche3,Alexander Woll3 and Anne K. Reimers1

Abstract

Background: Individual health behavior is related to environmental and social structures. To promote physicalactivity (PA) effectively, it is necessary to consider structural influences. Previous research has shown the relevanceof the built environment. However, sex/gender differences have yet not been considered. The aim of thissystematic review was to identify built environmental determinants of PA by taking sex/gender into account.

Methods: A systematic literature search was carried out using six electronic databases (PubMed, CINAHL,SportDiscus, PsycInfo, Scopus, Web of Knowledge) to identify studies analyzing the effect of changes in the builtenvironment on PA, taking sex/gender into account. To be included, studies had to be based on quantitative dataand a longitudinal study design. Changes in the built environment had to be objectively assessed. Themethodological quality of the studies was examined using the QualSyst tool for examining risk of bias.

Results: In total, 36 studies published since 2000 were included in this review. The data synthesis revealed that themajority of reviewed studies found the built environment to be a determinant of PA behavior for both, males andfemales, in a similar way. Creating a new infrastructure for walking, cycling, and public transportation showed apositive effect on PA behavior. Findings were most consistent for the availability of public transport, which waspositively associated with overall PA and walking. The improvement of walking and cycling infrastructure had noeffect on the overall level of PA, but it attracted more users and had a positive effect on active transportation. Inwomen, the availability of public transport, safe cycling lanes, housing density, and the distance to dailydestinations proved to be more relevant with regard to their PA behavior. In men, street network characteristicsand road environment, such as intersection connectivity, local road density, and the presence of dead-end roads,were more important determinants of PA.

Conclusion: This review sheds light on the relevance of the built environment on PA. By focusing on sex/genderdifferences, a new aspect was addressed that should be further analyzed in future research and considered byurban planners and other practitioners.

Keywords: Health equity, Active transport, Active commuting, Men, Women, Built environment, Physical activity,Gender

© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate ifchanges were made. The images or other third party material in this article are included in the article's Creative Commonslicence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commonslicence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtainpermission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to thedata made available in this article, unless otherwise stated in a credit line to the data.

* Correspondence: [email protected] of Sport Science and Sport, Friedrich-Alexander-UniversityUniversity Erlangen-Nuremberg, Gebbertstraße 123b, 91058 Erlangen,GermanyFull list of author information is available at the end of the article

Environmental Health andPreventive Medicine

Tcymbal et al. Environmental Health and Preventive Medicine (2020) 25:75 https://doi.org/10.1186/s12199-020-00915-z

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IntroductionCurrently, there is convincing evidence that physical ac-tivity (PA) plays an important role in maintaining phys-ical and mental health [1]. Insufficient PA is one of themain risk factors for developing non-communicable dis-eases [2]. Moreover, insufficient PA poses a large burdenon national economies [3]. Besides personal characteris-tics, PA of individuals is also related to contextual fac-tors, such as environmental and social structures [4]. Arecent study on the worldwide epidemiology of insuffi-cient PA, which included data from 168 countries, esti-mated that 27.5% of the pooled sample did not meet theWHO recommendations on PA for health. Additionally,in 159 of 168 countries, the level of PA was lower inwomen than in men [5]. In this regard, it is necessary todevelop and implement new interventions aiming at PApromotion that target both, males and females. By tar-geting males and females equally, intervention-generatedinequalities in health behaviors, such as PA and resultinghealth benefits, can be avoided [6].The differences in PA behavior between males and fe-

males can on the one hand be explained by sex-linkedbiology and on the other hand by gender socializationand social norms. Based on Johnson et al. [7], gender re-fers to “the socially constructed roles, behaviors, expres-sions and identities of girls, women, boys, men andgender diverse people.” In acknowledging the theoreticalentanglement of biological factors and gendered socialfactors, we use the term sex/gender in the present article[8].Besides sex/gender differences, various studies have in-

dicated that the built environment is a relevant pre-requisite for PA [9–13]. Built environments can bedefined as any human-made environments that generateneeds and provide opportunities for active travel and PAincluding transportation infrastructure, land use pat-terns, and urban design characteristics [14, 15]. Salliset al. in their ecological model of four domains of PA[16] described that built environment features may alsobe referred to the transportation, recreation, occupation,or household domain.In recent years, there has been a large number of stud-

ies examining which built environmental characteristicshave an impact on PA behavior, with the majority ofstudies being cross-sectional. The longitudinal relation-ships should be taken into account to identify causal ef-fects of built environmental determinants on PA. Gebelet al. [17] emphasize that controlled prospective evalua-tions of environmental interventions and relocationstudies in which the same individuals are exposed todifferent environments provide the highest level ofevidence in this research area. For planning built envir-onmental interventions, it can be recommended to takeinto account data from studies that measured built

environmental characteristics objectively. Objective mea-sures are more appropriate as starting points for inter-vention programs than subjective perceptions of theenvironment because objective measures can be directlyaddressed when applying changes in the built environ-ment. Additionally, objective measures seem to be moreappropriate starting points for stopping the decliningrates of PA on the population level whose underlyingcauses cannot be primarily ascribed to individuals andtheir perceptions [18]. Furthermore, objective measureshave been shown to have a stronger association withwalking than subjective measures [19].In addition, the needs of diverse target groups should

be taken into account when planning built environmentinterventions, because diverse groups live in the sameneighborhoods and should benefit equally from such in-terventions. With regard to sex/gender, it has beenshown, for example, that crime safety may be more rele-vant for women, while men are more sensitive to pedes-trian and traffic safety [20, 21]. Taking into account thesex/gender differences in PA and its built environmentaldeterminants as well as PA-related gender health in-equalities, it is especially important to address both,males and females concomitantly when planning inter-vention studies. Despite the fact that the influence ofbuilt environment on PA behavior is currently of interestin many studies and reviews [9–13], a systematic analysisof whether the influence of the built environment isequal for/differs between males and females is notavailable.Thus, the objective of the present systematic literature

review is to identify built environmental determinants ofPA by taking sex/gender into account. This is an import-ant precondition to identify starting points of built envir-onmental interventions and to create effectiveapproaches aiming at PA promotion in both, males andfemales.

MethodsThe review follows the guidelines of the PRISMA (Pre-ferred Reporting Items for Systematic reviews and Meta-Analyses) statement [22]. The protocol was registered tothe international prospective register of systematic re-views PROSPERO (www.crd.york.ac.uk) on July 14, 2020with registration number CRD42020169923.

Eligibility criteriaArticles were included if they reported a quantitativeempirical study with a longitudinal pre-post-design (i.e.,prospective longitudinal cohort studies or natural experi-ments with at least two data collection points, includingrepeated cross-sectional surveys) investigating the rela-tionship between built environmental features and PAtaking sex/gender in statistical analyses and/or

Tcymbal et al. Environmental Health and Preventive Medicine (2020) 25:75 of 25

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presentation of results into account. Qualitative studies,cross-sectional studies, or those that did not considersex/gender were excluded. Additionally, studies examin-ing populations with specific health impairments such asoverweight and obesity or cognitive and psychologicaldisorders were also excluded. Only healthy participantsrepresenting the general population without any age re-striction were eligible.For the purpose of this review, “built environment”

was broadly defined as any human-made environmentthat generates needs and provides opportunities for ac-tive travel and PA [14, 15]. A change in the built envir-onment had to be objectively assessed usinggeographical information systems (GIS), desktop map-ping, or other audit tools. Natural experiments shouldbe focused on changes in the built environment in termsof moving from one kind of environment into anotheror changes in infrastructure (creating new walking orcycling trails, park improvements, etc.). This inclusioncriterion is based on the aim to identify starting pointsfor built environmental interventions to improve PA.Hence, studies including perceived measures of the builtenvironment were excluded. In addition, studies that fo-cused solely on neighborhood socioeconomic status orsocio-environmental aspects (including population dens-ity) were also excluded.Changes in PA behavior were used as the primary out-

come. All possible types of PA outcome were eligible in-cluding overall PA, moderate to vigorous physicalactivity (MVPA), exercise, walking, steps per day, cyc-ling, jogging, active transport, number of cyclists, andnumber of visitors of PA facilities. Studies with both ob-jective and subjective (self-reported) assessments of PAwere also included.All included articles had to be written in English lan-

guage and published in scientific journals. In order totrack the most current trends, it was decided to limit thesearch to articles that were published from January 2000onwards and listed in the databases up to March 122020.

Information sources and search strategyA systematic search in the databases PubMed (Ovid),CINAHL (EBSCO), SportDiscus (EBSCO), PsycInfo(EBSCO), Scopus (Elsevier), and Web of Knowledge wasconducted on March 12, 2020. Additionally, referencelists from previous reviews on associations between builtenvironment and PA and other relevant publicationswere screened to identify other potentially eligible stud-ies. A comprehensive search strategy was developedusing the SPIDER approach [23] with a combination ofkeywords in the categories study sample, phenomenonof interest, design, and evaluation. The search formulawas as follows: (child* OR youth* OR adolescen* OR

boy* OR girl* OR wom*n OR m*n OR adult* OR elderlyOR aged OR student) AND (“built environment*” ORneighborhood* OR neighbourhood* OR “city planning*”OR “urban planning” OR “residence characteristic*” ORwalkabil* OR bikeabil*) AND (longitud* OR follow-upOR intervention* OR experiment*) AND (“physicalactiv*” OR exercise OR sport* OR bicycl* OR cycl* OR“active transport*” OR “active commut*” OR “activetravel” OR walk*).

Study selectionTwo reviewers (AT and SF) independently screened andselected the relevant articles. First, all articles werescreened based on titles and abstracts. In a second step,full texts of potentially relevant articles were reviewed. Ifnecessary, supplementary files were also reviewed foradditional information. Disagreements between the re-viewers were discussed until a consensus was reached.Records were managed in Covidence systematic review

software (Veritas Health Innovation, Melbourne,Australia; www.covidence.org) and EndNote x9 (Clari-vate Analytics, Philadelphia, PA, USA).

Data extractionData of included studies were extracted and summarizedby one researcher, with verification by another reviewer,in order to reduce bias and error. Extraction includedthe following items: general study information (authors,year of publication, country), description of study sample(age, gender, number of participants), study design,follow-up time, objective built environment variables,PA variables, statistical analysis, and overall and genderspecific results on associations between changes in builtenvironment and PA (see Table 1).

Risk of bias assessmentThe QualSyst tool developed by the Alberta HeritageFoundation for Medical Research was used to assess themethodological quality of each study [24]. The tool wasselected as it allows to evaluate and compare studieswith different designs. Studies were evaluated accordingto 14 criteria, including objective, study design, methodof subject/comparison group selection, subject charac-teristics, intervention allocation, blinding, outcomemeasure definition, exposure measure definition, samplesize, analytic methods, estimate of variance, control forconfounding, reporting results, and conclusions. De-pending on the degree to which the specific criteria weremet, each item was scored as “yes” = 2, “partial” = 1,“no” = 0, and the total sum was calculated as (number of“yes” * 2) + (number of “partials” * 1). If an item was notapplicable to the study, it was marked “N/A” and ex-cluded from the total possible sum, which was calculatedas 28—(number of “N/A” * 2). The summary score was


http://www.covidence.org

Table 1 Study characteristics

Studydetails

Participantcharacteristics(% female)

Follow-uptime

Types of builtenvironment,measurementinstrument/description ofintervention

PA outcome,(S—subjectivemeasurement;O—objectivemeasurement)

Statisticalanalysis

Results on associations betweenchanges in BE and PA

Qualityscore

Overall By gender

Prospective longitudinal cohort studies

Boone-Heinonenet al. 2010,USA

Adolescentsand youngadultsN = 12,701(50.9%)

6 years Pay and public PAfacilities availability(count per 10,000population)Street connectivity(Alpha index)Landscapediversity(Simpson’sdiversity index)

Leisure timeMVPA (S)

Fixed effectsPoissonregression

In the wholesample landscapediversity, publicfacility availability,and alpha indexwere unrelated toMVPA.

Leisure-time MVPAbouts associatedwith increasedpublic facilityavailability amongfemale movers(0.053, 95% CI:0.008, 0.097) andwith pay facilityavailability amongmen (0.024, 95%CI: 0.006, 0.042, p< 0.05)No significantgender specificeffects oflandscape diversityand streetconnectivity onleisure-time MVPAbouts.

1

Buck et al2019,Germany,Italy, andSweden

Children andadolescents 3–15 years oldN = 2488(48.1%)

6 years Movability index(land use mix,street connectivity,availability ofpublic transportand public openspaces)

LPA and MVPA(O)

Linear mixedmodel

Results presentedseparately forgenders.

In girls, themovability indexshowed aconsistentsignificantlypositive effect onMVPA (β = 2.14,95% CI: (0.11; 4.16))for all ages, and inboys, on LPA withage for each year(β = 2.68, 95% CI:(0.46; 4.90)).Availability ofpublic openspaces was morerelevant for MVPAin girls (β = 2.38,95% CI: (0.43; 4.34))and LPA in boys (β= 10.6, 95% CI:(4.78; 16.3)) duringchildhood,whereas inadolescence,intersectiondensity (β = 3.36,95% CI: (1.14; 5.57))became moreimportant for boysLPA.

0.86

Carver et al.2010,Australia

Children 8–9years oldN = 170 (49%)Adolescents13–15 years oldN = 276 (57%)

2 years Road environment;GIS

MVPA (O)Activetransport(walkingcycling) (S)

Linearregression


ChildrenBoys: Change inMVPA waspositivelyassociated withthe number ofslow points(chicanes) in theneighborhood (β

0.82


Table 1 Study characteristics (Continued)

Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

= 1.55, 95% CI =0.25 to 2.86)(before school),the total length oflocals roads (B =3.81, 95% CI = 0.95to 6.67)(weekends) andintersectiondensity (B = 0.49,95% CI = 0.14 to0.84) (weekends).Girls: Change inMVPA wasnegativelyassociated withthe intersectiondensity (B = − 0.05,95% CI = − 0.09 to− 0.003) and thenumber of traffic/pedestrian lights (B= − 0.88, 95% CI =− 1.41 to − 0.35)(evenings).Adolescents.Boys: The numberof speed humps inthe neighborhoodwas positivelyassociated withchange in MVPAafter school (p <0.05), and the localroad index wasnegativelyassociated withchange in MVPAon weekend days(p < 0.05).Girls: Total lengthof local roads (p <0.01), intersectiondensity (p < 0.01),and the number oftraffic/pedestrianlights (p < 0.05)were eachpositivelyassociated withchange in MVPAbefore school. Thelocal road indexwas negativelyassociated withchange in MVPAafter school (p <0.01). The numbersof speed humps (p< 0.05) and gates/barriers (p < 0.01)were positivelyassociated with



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

change in MVPAduring evenings.The total length oflocal roads (p <0.01), intersectiondensity (p < 0.05),and the number ofspeed humps (p <0.05) werepositivelyassociated withchange in MVPAduring non-schoolhours, while thelocal road indexwas negatively as-sociated withMVPA (p < 0.01).The number ofspeed humps waspositively associ-ated with changein MVPA on week-end days (p <0.05).

Cooganet al. 2009,USA

Adult womenN = 20,354(100%)

6 years Housing density,land use, streetconnectivity,traffic, publictransit availability,presence ofsidewalks, distanceto parks; GIS

Utilitarian andexercisewalking (S)

Multinomiallogisticregressiongeneralizedestimatingequationmodel

(Only females) Increases inutilitarian walkingwere associatedwith increasedhousing density(OR = 2.72, 95% CI2.22, 3.31) and busavailability (OR =1.44, 95% CI: 1.21,1.72).Increased housingdensity led toincreased exercisewalking (OR =1.28, 95% CI: 1.07,1.52)Land use, streetconnectivity, traffic,presence ofsidewalks, anddistance to parkswere notassociated withutilitarian orexercise walking.

0.91

Coombeset al. 2014,UK

Children 10–11years oldN = 518 (55.8%)

1 year Availability ofgreenerenvironments anddestinations,density of theroad network,school-homedistance;GIS

Overall PA (O).Travel mode(S)

Multipleregressionmodels

No significantassociationsbetween changein schoolcommuteenvironment orhomeneighborhoodsupportivenessand overall PA.

No gender specificeffects.

0.82

Crawfordet al. 2010,

ChildrenN = 301 (57.5%)

5 years Destinations (PArelated and

MVPA (O) Generalizedestimating

Results presentedseparately for

No significantassociations

0.86



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

Australia school), roadconnectivity, trafficexposure; GIS.

equation genders. between BE andMVPA, only thepresence of dead-end roads waspositively associ-ated with MVPA inboys (b = 0.007,95% CI: 0.01, 0.13;p < 0.05).

Dowdaet al. 2020,USA

ChildrenN = 555 (56%)

3 years Outdoor PAequipment

Number of PAdays and PAlocation (S)

LongitudinalPoissonregression

Outside PAequipment werepositive significantpredictors of streetPA in total sample(p < 0.05).


0.82

Evensonet al. 2018,USA

AdolescentsgirlsN = 265

1 year Parks availability;GIS

Park visits;MVPA in parks(O)

Wilcoxonsign rank testfor twodependentsamples,Pearsoncorrelationcoefficients

(Only females) Parks were anunder-used re-source for adoles-cent girls,particularly forMVPA.Only one-fifth ofthe sample (20%at baseline, 19% atfollow-up) visited apark at least oncein six days of ob-servation. Theaverage durationof park visits washigher at baseline(63.9 min) com-pared to follow-up(38.4 min). On dayswhen a park wasvisited, MVPA washigher than ondays when a parkwas not visited.However, only1.9% (baseline)and 2.8% (follow-up) of MVPA oc-curred in parks.

0.77

Hou et al.2010, USA

AdultsN = 5115(54.5%)

15 years Street connectivity(intersectiondensity, link-noderatio) , characteris-tic of local roads(density, propor-tion local relativeto total road);StreetMap data,TIGER/line roadclassification

Overallwalking,cycling, andjogging (S)

Two-partmarginaleffect model(probitmodel andan ordinaryleast squaresregressionmodel)


Intersectiondensity waspositivelyassociated withwalking, bicyclingand joggingfrequencies in lowurbanicity areas forboth genders(men: β = 1.0; 95%CI: 0.04, 1.9, p =0.04; women: β =1.3; 95% CI: 0.6, 2.0,p = 0.001). Densityof local roads waspositivelyassociated onlyamong men in

0.86



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

low urbanicityareas (β = 1.0; 95%CI: 0.1, 2.0, p =0.03).In high urbanicityareas walking,cycling andjoggingfrequencies inwomen werenegativelyassociated withlocal road density(β = − 1.3; 95% CI:− 2.2, − 0.3, p =0.007) andproportion of localroads (β = − 1.4;95% CI: − 2.3, − 0.6,p = 0.001).No significantassociationsbetween link-noteratio and PA forboth genders.

Michaelet al. 2010,USA

Adult men (>65 years old)N = 513

Average 3.6years

Availability ofproximate PAresources: parks,trails, andrecreationalfacilities; GIS

Walking (S) Log-binomialregression

(Only males) Proximity torecreationalfacilities was notassociated withwalking.Distances to a parkand a trail werepositivelyassociated withmaintaining orincreasing walkingbetween baselineand follow-up, butwas not significantfor the whole sam-ple. Proximity toparks and proxim-ity to trails, re-spectively, wereassociated with a22% (95% CI: 1.01,1.47) and 34%(95% CI: 1.16, 1.55)higher likelihoodof maintaining orincreasing walkingtime in high-SESneighborhoods,but there was noassociation in low-SESneighborhoods.

0.77

Sanderset al. 2015,Australia

ChildrenN = 4983(49.1%)

8 years Availability ofgreen areas

Overall PA (S) Multilevellinearregressionandmultilevel


Boys living in areaswith 10 % moreneighbourhoodgreen space had a7 % (95% CI =

0.91



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

logisticmodels

1.02, 1.13) greaterodd of choosingphysically activepastimes; and 7%(95% CI = 1.02;1.12) and 9% (95%CI = 1.03; 1.15)greater odds ofmeeting PAguidelines onweekdays andweekends,respectively. A10% difference ingreen space wasassociated with amean of 1.9 mingreater time spentphysically activeon a weekday (β =1.88, 95% CI =0.22, 3.53; p =0.026), and 3.0 minmore weekend PA(β = 3.01, 95% CI= 0.37, 5.66; p =0.026) afteradjusting forconfounders, butonly at youngerages.No statisticallysignificant resultswere observed forgirls.

Schipperijnet al. 2015,Denmark

Young adults,N = 177 (57%)

6 years Movability index,recreationalfacilities, density ofdaily destinations,street connectivity;GIS

Overall PA (O) Multivariableanalysis ofvariance

No significantassociationsbetween changesin movabilityindex, availabilityin recreationalfacilities, density ofdaily destinations,street connectivityand PA for thewhole sample.

Increases in meandaily total PAassociated withincreases inmovability index(β = 10.15, 95% CI:2.08, 18.21, p =0.014) and dailydestinations (β =31.24, 95% CI:10.64, 51.84, p =0.003) in females.Increasedintersectiondensity (streetconnectivity) wasnegativelyassociated withmean daily totalPA in males (β =− 35.47, 95% CI: −67.10, − 3.83, p =0.03)

0.91

Intervention studies

Andersenet al. 2017,Denmark

AdolescentsNbaseline = 354(53%)

1 year New urban greenspaces andplaygrounds were

PA within therenovated area(O).

Linear mixedmodel

Post-interventionsample spent 7.8min per day in


0.77



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

Npost-renewal =319 (59.6%)

created LPA (p = 0.012)and 4.5 min perday in MPVA (p <0.001).

Brown andWerner2007, USA

AdultsN = 51 (47%)

1 year New rail stop Moderate PAbouts (O).

Ordinaryleast squaresregression

Rail ridership waspositivelyassociated withmoderate activitybouts, β = 0.39 (SE= 0.01), p = 0.01.


0.77

Burbidgeand Goulias2009, USA

Children andadults from 5years oldN = 82 (54.9%)

1 and 5months

New trail Overall PA,walking andbiking trips (S)

A fixed-effects panelanalysisregression

The new trail wasassociated withsignificantdecrease in totalPA (-0.245, t value= − 2.13, R-square= 0.045, p = 0.036)and in the numberof walking trips (−0.265, t value = −2.71, R-square =0.070, p = 0.008).


0.77

Changet al. 2017,Mexico

AdultsNpre-intervention =1067 (52%)Npost-intervention

= 1420 (51%)

3 years Bus rapid transitand streetscaperedesign (widenedsidewalks, roaddiets, recovery ofgreen and publicspace)

Walking fortransport,walking forrecreation, andcycling fortransport (S)

Propensityscorematching,clusteranalysis

The averagetreatment effect ofliving in post-intervention neigh-bourhood onwalking for trans-port was 24.37min per week, onwalking for trans-port and recre-ation—31.72 min,on cycling fortransport—4.81min.

Cluster analysesshowed thatfemales with loweducationexperienced thegreatest increasesin PA. All of thefemale clustersexperiencedsignificant growthin recreationalwalking andtransport walkingexcept femalehomemakers withhigh education.Male clustersexperienced eitherminimalimprovements inrecreationalwalking ordecreases, butsignificantimprovement inwalking fortransport (thegreatest increasein male studentswith mid-leveleducation).

0.82

Cohenet al. 2015,USA

Nbaseline = 922Npost-renewal =1043

3 years Parkimprovements

Park use andPA (O)

Mixed effectmodel andlogit models

Use of the tworenovated parksand PA level ofusers increasedcompared withbaseline.%-change in totalpark use (β =


0.86



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

233.1, SE = 55.9, p= 0.001); %-changein MET-hoursexpended in park(β = 254.8, SE =70.1, p = 0.001).The total park useand MET-hoursexpended in unre-novated parks sig-nificantlydecreased.

Cohen et al2014, USA

N/A 2 years Creation of pocketparks

Park use andPA (O)Self-reportedpark use

Generalizedestimatingequation

The new pocketparks hadsignificantly moreusers thancomparison parkplaygrounds (β =− 1.21, SE = 0.28, p= 0.001).

More females wereobserved at thepocket parksduring follow-upthan at compari-son park play-grounds (63% vs.56%, p = 0.0068).Females weresomewhat lessactive than malesin the pocketparks, with 22%engaged in MVPAvs. 29% of males(p = 0.08).

0.68

Cranneyet al. 2016,Australia

Children andadultsNbaseline = 8560(46%)Npost-installation =7097 (46%)Nfollow-up =8248 (46%)

1 year Park improvement(outdoor gym)

Park use andPA (O)

Two samplez-test

The proportion ofall park usersengaged in MVPAincreasedsignificantly (p <0.001) frombaseline (9.4%) topost-installation(12.8), then de-creased towardthe baseline pro-portion at follow-up.The proportion ofoutdoor area usersfrom all park usersincreased from2.4% to 6% (p <0.001) anddecreased back to3.3% at follow-up,which is still a sig-nificant increase incomparison withbaseline (p <0.001).

The proportion ofmale park usersengaged in MVPAduring follow-upmeasurement in-creased on 1.9% incomparison withbaseline (p < 0.01),for female users in-crease was notsignificant.The proportion ofmale outdoor areausers from all parkusers duringfollow-up meas-urement increasedon 1.1% in com-parison with base-line (p < 0.01), forfemale users in-crease was notsignificant.

0.77

Dill et al.2014, USA

AdultsN = 353

2 years New bicycleboulevard

MVPA (O).Walking andcycling trips (S)

Binomiallogitregression,negativebinomialregressionand linearregression

No significantassociationsbetweeninstallation ofbicycle boulevardsand increases inPA and activetransportation.

Women engagedin less MVPA (ß =− 4.46, p = 0.02)and minutes ofbicycling (ß = −0.311, p = 0.01),were less likely tocycle more than

0.85



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

models 10 min (ß = −0.475, p = 0.04)and make biketrips (ß = − 0.58, p= 0.01), but weremore likely to walkmore than 20 min(ß = 0.616, p <0.001).

Goodmanet al. 2013,UK

AdultsN = 1510 (57%)

2 years New local walkingand cycling routes

Walking andcycling at newrouts (S)

LongitudinalPoissonregression

After one year 32%of sample startedto use new routes(29% walking, 13%cycling), after twoyears theproportion ofusers increased to38% (35% walking,16% cycling).

Men were morelikely to useConnect2 (rateratio 1.14 for menvs. women, p <0.05). However,results weresignificant only inone of three cities.

0.91

Heien et al.2015, UK

AdultsN = 470 (66,6%)

3 years New transportinfrastructure(busway with pathfor walking andcycling)

Commutemode share(active travel)(S)

Multivariablemultinomiallogisticregressionmodels

Commuters living4 km from thebusway werealmost twice aslikely to report asubstantialincrease (> 30%) intheir active travelmode share(relative risk ratio[RRR] 1.80, 95%confidence interval[95% CI] 1.27 to2.55), and half aslikely to report asmall decrease RRR0.47, 95 % CI 0.28to 0.81), thanthose living 9 kmaway.Proximity to thebusway alsopredicted a largedecrease in theshare of tripsmade entirely bycar (RRR 2.09, 95 %CI 1.35, 3.21).


0.86

Heinenet al. 2018,Australia

AdultsN = 4637(57.7%)

4 years New publicbicycle-sharingscheme

Time spentcycling (S)

Multinomiallogisticregression

On average, therespondentsdecreased thetotal time spentcycling by 1.98minutes a week.Time spent cyclingfor transportdecreased by 2.34min per week,whereas theaverage timespent cycling orrecreationincreased by 0.35

Women, whencompared to men,were less likely toincrease ordecrease the timespent cycling.

0.82



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

min.No significantassociationsbetween proximityto a bicycle-sharing stationand changes intime spent cycling.

King et al.2015, USA

Children andadultsNbaseline = 2888(42.2%)Npost-intervention

= 4525 (46.4%)

2 years New park Park use andPA (O)

T-test The total numberof peopleobserved usingthe park post-construction sig-nificantly increased(p = 0.004). Three-fold increase in en-ergy expendedwithin the parkafter construction(p = 0.002). In-crease in the pro-portion of parkusers who wereengaged in mod-erate (p = 0.007)or vigorous activity(p = 0.04).

The number ofvisitors increasedfor both genders.Proportion ofvisitors engagedonly in sedentaryactivitiesdecreased both infemales (from 59to 42%) and inmales (from 44 to26%).Proportion offemales observedengaging invigorous PA insideof the parkboundariesincreased from 0to 20% (mostlychildren).Adolescentfemales were veryunder-representedwithin the park. Ofthe adolescent fe-males counted,few were engagedin vigorous PA. Onthe other hand,there was a signifi-cant increase inthe proportion ofadolescent malesobserved en-gaging in vigorousPA (P < 0.001), es-pecially inplayfields.

0.77

Ng et al.2020,Australia

Preschoolers 2-5 years old

Nbaseline = 223Nfollow-up = 116

6–12months

Upgrade odchildcare outdoorspaces (installationof outdoor PAequipment)

Overall PA,MVPA (O)

Multivariablelinearregression

Interventionpreschoolers weremore active thancontrol at follow-up (58.09 vs. 42.13min/day increasein total PA; 30.46vs. 19.16 min/dayincrease in MVPA(all p < 0.001)).

Boys weresignificantly moreactive than girls (p< 0.01).

0.86

Panteret al. 2017,UK

AdultsN = 1257

2 years New walking andcyclinginfrastructure

Walking fortransport andrecreation (S)

Latent classanalysis andmultinomialregression

Short-lived andsustained increaseas well as uptakein walking fortransport and

Increase anduptake in walkingfor transport orrecreation werenot associated

0.82



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

recreation wereassociated withuse of newwalking andcyclinginfrastructure.Proximity to theintervention wasassociated withboth uptake ofand short-lived in-creases in walkingfor transport.

with gender.

Parker et al.2011, USA

AdultsN/A

1 year New bike lane Number ofcyclists (O)

Negativebinomialregression

The mean numberof cyclistsobserved per dayincreased by 57%(p < 0.001).

The increaseamong adultfemale riders(133%, p < 0.001)was greater thanamong adult maleriders (44%, p <0.001).

0.6

Parker et al.2013, USA

Youth andadultsN/A

1 year New bike lane Number ofcyclists (O)

Negativebinomialregression

There was anincrease in cyclistson all three streetsafter theinstallation of thebike lanes [62.5 (±28.8) vs. 110 (±109); Z = 8.97, p <0.000], with thelargest increase onthe street with thenew lane [pre 79.2(± 30.5), post 257.1(± 50.9); Z = 10.79,p < 0.000].

The increase incyclists wasgreater amongfemales (4.69) thanmales (3.12).

0.75

Rissel et al.2015,Australia

AdultsN = 512 (62.5%)

1 year New cyclinginfrastructure

Number ofcyclist (O).Cyclingbehavior (S)

Mixed-effectslogisticregressionmodels

Bike counts at twosites on the newbicycle pathreported anincrease of 23 %and 97 %respectively at 12months. Weeklyfrequency ofcycling remainedhigher in theintervention (29.2–25.8% at follow-up) area than thecomparison area(22.4–23.2% atfollow-up) (p =0.04).Among theparticipants in thecohort, there wasno change in theself-reportedweekly frequencyof cycling. Only 15% participants


0.91



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

reported using thenew bicycle path,with most users(76 %) living in theintervention area.

Schultzet al. 2017,USA

Children andadultsNbaseline = 2080(46%)N1 year = 2275(45%)N2 years = 2276(46%)

2 years Improved accessto the park

Park use andPA (S)

One-wayANCOVAmodel andSidak post-hoccomparisons

Total park useincreased from2012 (n = 2080) to2013 (n = 2275)and remainedconstant in 2014(n = 2276).However, despiteincreases in safeaccess and overallpark use, therewas a significantdecrease in totalenergyexpenditurefollowing theinstallation of thecrosswalk that wassustained in 2014.

Male park useincreased from2012 to 2013 (6.95to 10.49) butsignificantlydecreased from2013 to 2014(10.49 to 7.82);however, therewas still asignificant increasefrom 2012 to 2014(6.95 to 7.82).Females alsoshowed asignificant increaseof park use from2012 to 2013 (7.45to 9.78); however,unlike males, theincreased use wasmaintained in2014 (9.63).The total energyexpenditure bothfor males andfemales in 2014was significantlylower than in2012.

0.91

Smith et al.2019,Australia

AdultsN = 389 (58.4%)

1 year New recreationalinfrastructurePeninsula Aquaticand RecreationCentre (PARC)

Use of PARC,MVPA (S)

Multivariablelogisticregression

After 12 months17,5% of samplereportedoccasional use ofPARC and 8.7%used it on regularbasis.PARC users werenot significantlymore likely thannon-users to showimprovements intheir level ofleisure-time PAover 12 months.

Females usedPARC more often(odds ratio 2.30,95% CI: 1.37–3.87)than males.

0.82

Sun et al.2014, China

Young adults,N = 169 (56%)

10 months(3 afterintervention)

Increase in landuse, streetconnectivity, andbus accessibility

Walkingbehavior (S)

Multivariablelinearregressionmodel

Intervention hadpositive effect onwalking distanceand walking ratio.An increase inpedestriannetworkconnectivity (roadintersections)positivelypredicted walkingdistance (p <


0.82



Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

0.001) and walkingratio (p < 0.001).An increasedexposure to lifearea buildings andan increase inpopulation densitywere associatedwith longer walks(p < 0.001). At thelower campuslevel, an increasein the number ofwork areabuildings wasassociated with adecrease insubjects’ altituderanges (p < 0.001),while theincreased busservice resulted inmore peoplefrequenting higherelevation levels (p= 0.01), and achange in middle-class bus servicewas inversely asso-ciated with sub-jects’ predictedmovement acrosshilly terrain (p =0.02).

Tanniset al. 2019,USA

AdultsN = 88 (78.4%)

1 year Move into houseswith active design(more attractivestairwells, outdoorcommunitygarden area,outdoor fitnessarea, communitygym)

PA (S)Steps per day(O)

T-tests andMann–Whitney Utest

The greater dailysteps increase hadAD residents whomoved from anelevator building(p = 0.051).Difference inMVPA betweenAD and non-ADresidents was notsignificant.

AD buildingwomen reportedmore work-relatedMVPA overall (p =0.01).AD men engagedin more moderaterecreational PA (p= 0.044).

0.91

Tester andBaker 2009,USA

Children andadultsN/A

1 year Parkimprovements(playfields)

Park use andPA (O)

T test Results presentedseparately forgenders.

There weresignificantincreases of theamount ofplayfield usersamong childrenand adults of bothgenders at theintervention parks(p < 0.05), but notin the control park.There werestatisticallysignificantincreases amongmales and femaleswho were

0.75


calculated as a total sum divided by total possible sum.The summary score (range 0–1) indicated the risk ofbias, with a higher score indicating higher quality.

Data synthesis and analysesThe association between changes in the built environ-ment and changes in PA was used as the primary meas-ure effect. The data was summarized narratively due tothe heterogeneity of studies and the variety of exposureand outcome measures, which prevented a quantitativemeta-analysis. Built environment characteristics wereclassified according to the ecological model of four do-mains of PA [16] as related to the transportation, recre-ation, occupation, or household domain. Type of PAbehavior outcomes were grouped in (1) PA measured in

minutes or days per week, or METs; (2) walking orcycling measured in minutes or days per week, num-ber of trips or steps per day; and (3) visitation or useof PA settings measured in count of users or timespent in location. Table 2 presents the results accord-ing to the number of associations coded as positivelysignificant (“+”), negatively significant (“−”), or havingno association (“0”). Associations with p value ≤ .05were considered statistically significant. If the studyindicated that built environmental characteristicsaffect PA in both sexes in a similar way, the mark(“+”) or (“−”) was placed in the column “All.” In casethe effect was observed in only one of the sexes, themark (“+”) or (“−”) was placed in the column “Fe-male” or “Male,” respectively.


Studydetails


Follow-uptime



Statisticalanalysis


Qualityscore

Overall By gender

observed at eachrespective PA level(sedentary,moderate,vigorous) in theintervention parks(p<0.05).On the controlplayfield, onlymoderately activemales increased.

Wells andYang 2008,USA

Adult womenN = 32 (100%)

4 years Moving to neo-traditionalneighbourhood

Overall walking(O)

Mixedmodeling

(only females) Women whomoved to placeswith fewer cul-de-sac, on average,walked more (5303more steps perweek, or 757 moresteps per day, p =0.025).Increases in land-use mix were asso-ciated with lesswalking (31,820fewer steps perweek, or 4545fewer steps perday), p = 0.013.

0.86

West andShores2015, US

AdultsN = 273 (41.1%)

1 year New greenway Walking, MVPA(S)

Ordinaryleast squaresregressions

No significantdifferencesbetween theexperimental andcontrol groups indays of walking,moderate activity,or vigorous activitybefore and afterthe greenway wasconstructed.


0.88

N number of participants, PA physical activity, LPA light physical activity, MVPA moderate to vigorous physical activity, AD active design


Table 2 Key findings for impact of built environment on PA behaviorDomain BE characteristics Physical activity (minutes,

days per week, METs)Walking, cycling(minutes, days perweek, number of trips,steps per day)

Visitation or use ofsettings (count of users,time spent in locations)

All Female Male All Female Male All Female Male

Transport New walking/cycling infrastructure 0(1)0(2)−-3)

+, f<m(4)+,f>m(5)+(6)+(7)+(8)0(1)0(2)0(9)−-3)

+(9)+,f>m(10)+,f>m(11)

Street network characteristics, (street connectivity, roadenvironment)

+(12)+(13)0(14)0(15)0(16)

0(17) +(18)+(16)−-17)

+(19) 0(20)

Local road density −-12) −-13) +(13)

Land use mix 0(20)−-21)

House density +(20)

Availability of public transport +(22) +,f>m(5)+(6)+(8)+(19)

+(20)

Landscape diversity 0(14)

Movability index +(18) +(17) 0(17)

Distance to school and daily destinations 0(15)0(16)

+(17) 0(17)

Recreation Park/ green space improvement +(23)+(24)−-25)

+(26) +(23)+(25)+(24)

+(26)

New parks/ green spaces +(27)+, f<m(28)+(29)

+,f>m(28)+(29)

New PA facilities 0(30) +,f>m(30)

Availability of PA and recreation facilities and public open spaces +(14)+(18)0(15)0(17)

0(parks)(31)0(parks)(32)

+(parks)(32) +(33)

Outdoor PA equipment +(34)+, f<m(35)

Household Houses with active design +(36) +(36)

+ positive association− negative association0 no significant associationsf>m effect for females was greater than for malesf<m effect for females was smaller than for males1. Dill J, McNeil N, Broach J, Ma L. Bicycle boulevards and changes in physical activity and active transportation: Findings from a natural experiment. PreventiveMedicine. 2014;69:S74-S8.2. West ST, Shores KA. Does building a greenway promote physical activity among proximate residents? Journal of Physical Activity & Health. 2015;12(1):52-7.3. Burbidge SK, Goulias KG. Evaluating the impact of neighborhood trail development on active travel behavior and overall physical activity of suburban residents.2009. p. 78-86.4. Goodman A, Sahlqvist S, Ogilvie D, iConnect c. Who uses new walking and cycling infrastructure and how? Longitudinal results from the UK iConnect study.Preventive medicine. 2013;57(5):518-24.5. Chang A, Miranda-Moreno L, Cao J, Welle B. The effect of BRT implementation and streetscape redesign on physical activity: a case study of Mexico City.Transportation Research Part a-Policy and Practice. 2017;100:337-47.6. Heinen E, Kamruzzaman M, Turrell G. The public bicycle-sharing scheme in Brisbane, Australia: evaluating the influence of its introduction on changes in timespent cycling amongst a middle- and older-age population. Journal of Transport & Health. 2018;10:56-73.7. Panter J, Ogilvie D, iConnect C. Can environmental improvement change the population distribution of walking? Journal of Epidemiology and CommunityHealth. 2017;71(6):528-35.


ResultsStudy selection processThe search across the six databases resulted in 6836 publi-cations (see Fig. 1). In addition, 24 articles were identifiedby screening reference lists from previous reviews and otherrelevant publications. Then, 3864 duplicates were removedresulting in 3176 records that were screened. In the firststep, 3018 articles were excluded based on titles and ab-stracts. This left 158 potentially eligible studies for the full-text screening. In total, 36 studies were included for dataextraction and methodological quality assessment.

Characteristics of included studiesFrom the 36 included studies, more than half were con-ducted in the USA (n = 19), the others took place in

Australia (n = 8), European countries (n = 7), Mexico (n= 1), and China (n = 1). Eleven of the included studieshad prospective longitudinal cohort designs; others wereintervention studies with pre-post-measurements (nat-ural and quasi-experiments). Half of the studies onlyfocused on adults, ten focused on children and adoles-cents, and eight studies on all age groups. Most samplesincluded both men and women except for three studiesthat included women only and one that included menonly. Fourteen studies measured follow-up effects during1 year or less, and only seven studies followed partici-pants for up to 5 years or longer.Exposure and outcome measurement varied widely.

Sixteen studies used objective methods for measuringPA (accelerometers or observation), fourteen studies

8. Heinen E, Panter J, Mackett R, Ogilvie D. Changes in mode of travel to work: a natural experimental study of new transport infrastructure. International Journalof Behavioral Nutrition and Physical Activity. 2015;12.9. Rissel C, Greaves S, Li Ming W, Crane M, Standen C. Use of and short-term impacts of new cycling infrastructure in inner-Sydney, Australia: a quasi-experimentaldesign. International Journal of Behavioral Nutrition & Physical Activity. 2015;12:1-8.10. Parker KM, Gustat J, Rice JC. Installation of bicycle lanes and increased ridership in an urban, mixed-income setting in New Orleans, Louisiana. J Phys ActHealth. 2011;8 Suppl 1:S98-S102.11. Parker KM, Rice J, Gustat J, Ruley J, Spriggs A, Johnson C. Effect of bike lane infrastructure improvements on ridership in one New Orleans neighborhood. AnnBehav Med. 2013;45(SUPPL.1):S101-S7.12. Carver A, Timperio A, Hesketh K, Crawford D. Are safety-related features of the road environment associated with smaller declines in physical activity amongyouth? Journal of urban health : bulletin of the New York Academy of Medicine. 2010;87(1):29-43.13. Hou N, Popkin BM, Jacobs DR, Jr., Song Y, Guilkey D, Lewis CE, et al. Longitudinal associations between neighborhood-level street network with walking,bicycling, and jogging: the CARDIA study. Health & place. 2010;16(6):1206-15.14. Boone-Heinonen J, Guilkey DK, Evenson KR, Gordon-Larsen P. Residential self-selection bias in the estimation of built environment effects on physical activitybetween adolescence and young adulthood. The international journal of behavioral nutrition and physical activity. 2010;7:70-.15. Coombes E, Jones A, Page A, Cooper AR. Is change in environmental supportiveness between primary and secondary school associated with a decline inchildren's physical activity levels? Health Place. 2014;29:171-8.16. Crawford D, Cleland V, Timperio A, Salmon J, Andrianopoulos N, Roberts R, et al. The longitudinal influence of home and neighbourhood environments onchildren's body mass index and physical activity over 5 years: the CLAN study. International journal of obesity (2005). 2010;34(7):1177-87.17. Schipperijn J, Ried-Larsen M, Nielsen MS, Holdt AF, Grøntved A, Ersbøll AK, et al. A longitudinal study of objectively measured built environment asdeterminant of physical activity in young adults: The European Youth Heart Study. Journal of physical activity & health. 2015;12(7):909-14.18. Buck C, Eiben G, Lauria F, Konstabel K, Page A, Ahrens W, et al. Urban Moveability and physical activity in children: longitudinal results from the IDEFICS andI.Family cohort. The international journal of behavioral nutrition and physical activity. 2019;16(1):128-.19. Sun G, Oreskovic NM, Lin H. How do changes to the built environment influence walking behaviors? A longitudinal study within a university campus in HongKong. Int J Health Geogr. 2014;13.20. Coogan PF, White LF, Adler TJ, Hathaway KM, Palmer JR, Rosenberg L. Prospective study of urban form and physical activity in the Black Women's HealthStudy. American journal of epidemiology. 2009;170(9):1105-17.21. Wells NM, Yang Y. Neighborhood design and walking. A quasi-experimental longitudinal study. American journal of preventive medicine. 2008;34(4):313-9.22. Brown BB, Werner CM. A New Rail Stop. Tracking Moderate Physical Activity Bouts and Ridership. Am J Prev Med. 2007;33(4):306-9.23. Cohen DA, Han B, Isacoff J, Shulaker B, Williamson S, Marsh T, et al. Impact of park renovations on park use and park-based physical activity. Journal ofPhysical Activity & Health. 2015;12(2):289-95.24. Tester J, Baker R. Making the playfields even: evaluating the impact of an environmental intervention on park use and physical activity. Preventivemedicine. 2009;48(4):316-20.25. Schultz CL, Stanis SAW, Sayers SP, Thombs LA, Thomas IM. A longitudinal examination of improved access on park use and physical activity in a low-incomeand majority African American neighborhood park. Preventive Medicine. 2017;95:S95-S100.26. Cranney L, Phongsavan P, Kariuki M, Stride V, Scott A, Hua M, et al. Impact of an outdoor gym on park users' physical activity: A natural experiment. Health &Place. 2016;37:26-34.27. Andersen HB, Christiansen LB, Klinker CD, Ersbøll AK, Troelsen J, Kerr J, et al. Increases in use and activity due to urban renewal: effect of a natural experiment.American journal of preventive medicine. 2017;53(3):e81-e7.28. Cohen DA, Marsh T, Williamson S, Han B, Derose KP, Golinelli D, et al. The potential for pocket parks to increase physical activity. American journal of healthpromotion : AJHP. 2014;28(3 Suppl):S19-S26.29. King DK, Litt J, Hale J, Burniece KM, Ross C. 'The park a tree built': Evaluating how a park development project impacted where people play. Urban Forestry &Urban Greening. 2015;14(2):293-9.30. Smith BJ, MacKenzie-Stewart R, Newton FJ, Haregu TN, Bauman A, Donovan RJ, et al. A longitudinal study examining uptake of new recreation infrastructureby inactive adults. The international journal of behavioral nutrition and physical activity. 2019;16(1):59-.31. Evenson KR, Cho G-H, Rodríguez DA, Cohen DA. Park use and physical activity among adolescent girls at two time points. Journal of sportssciences. 2018;36(22):2544-50.32. Sanders T, Feng X, Fahey PP, Lonsdale C, Astell-Burt T. The influence of neighbourhood green space on children's physical activity and screen time: findingsfrom the longitudinal study of Australian children. The international journal of behavioral nutrition and physical activity. 2015;12:126-.33. Michael YL, Perdue LA, Orwoll ES, Stefanick ML, Marshall LM, Osteoporotic Fractures in Men Study G. Physical activity resources and changes in walking in acohort of older men. American journal of public health. 2010;100(4):654-60.34. Dowda M, Saunders RP, Colabianchi N, Dishman RK, McIver KL, Pate RR. Longitudinal associations between psychosocial, home, and neighborhood factors andchildren's physical activity. Journal of physical activity & health. 2020:1-7.35. Ng M, Rosenberg M, Thornton A, Lester L, Trost SG, Bai P, et al. The effect of upgrades to childcare outdoor spaces on preschoolers' physical activity: findingsfrom a natural experiment. International journal of environmental research and public health. 2020;17(2):E468.36. Tannis C, Senerat A, Garg M, Peters D, Rajupet S, Garland E. Improving physical activity among residents of affordable housing: is active design enough?International journal of environmental research and public health. 2019;16(1):151.


measured PA outcomes using self-report questionnaires,and six studies combined subjective and objective mea-surements. The built environment was measured object-ively (with GIS, similar mapping tools or audited byresearchers) in 11 studies, improvements or construc-tions of new infrastructures were used as a measure ofthe built environment in 25 studies. According to theecological model of four domains of PA [16], 22 studieswere focused on the built environment related to thetransportation domain, 17 studies on the built environ-ment related to the recreation domain, and one study onthe built environment related to the household domain.We did not find studies that investigated effects of thebuilt environment on occupational PA taking sex/genderinto account.

Risk of bias assessmentThe average quality score of included studies was 0.83with a range between 0.6 and 0.96. In most of the stud-ies, the research question, the objective, the analysis, andthe results were sufficiently described and the study de-sign was appropriate. The main sources of bias wererelated to confounding, measurement, and subject

selection. In prospective longitudinal cohort studies,there were high rates of loss to follow-up. Interventionstudies suffered from poor sample representativeness orlack of a control group. Quality scores of the individualstudies are reported in Table 1.

Effects of built environmental changes on PA outcomesMost of the studies (n = 27) reported a statistically sig-nificant beneficial relationship between at least one builtenvironmental characteristic and PA behavior.

Effects of the built environment on males and femalesMost of the selected studies showed that built environ-ment characteristics have a similar effect on the PA be-havior of males and females.Fourteen intervention studies and eight longitudinal

studies investigated how different characteristics of roadsand transport infrastructure influence the residents’ PA.Eleven of these studies assessed the impact of newroutes for walking and cycling and showed that all ef-fects were similar for both sexes/genders. There was nopositive effect of changes in built environment on overallPA [25, 26]. In one study, the level of PA even decreased

Fig. 1 PRISMA flow-diagram of the study selection process


after installation of a new trail [27]. However, five stud-ies [28–32] reported that the level of walking and/orcycling increased after built environment interventionsand three studies [33–35] reported an increasing num-ber of users of new facilities. The availability of publictransport had a significantly positive effect on PA [36]and walking [28, 30, 31, 37]. The movability index (cal-culated based on residential density, land use mix, streetconnectivity, availability of public transport, and publicopen spaces) was associated with higher levels of PA inboys and girls [38]. Landscape diversity [39], distance toschool, and daily destinations [40, 41] had no effect onPA. Local road density was negatively associated withPA level [42]. The studies that focused on street networkcharacteristics showed diverse results: three longitudinalstudies reported no effect of street connectivity and roadenvironments on PA [39–41], two studies [42, 43] re-ported positive associations of intersection density withPA levels, and one study [37] with walking for bothmales and females.The studies that investigated effects of built environ-

ment on recreational PA behavior largely showed a posi-tive effect in both, males and females. Park and greenspace improvements [44, 45], the creation of new parks[46–48], and the installation of outdoor PA equipment[49, 50] were associated with increased PA and use of fa-cilities. One study [51] reported that after park accessimprovement, the number of users increased, but overallPA decreased. The construction of a new aquatic and re-creation center did not affect overall PA of residents, butthe number of users increased 1 year after the construc-tion [52]. In two studies [1, 2], the availability of PA fa-cilities and public open spaces was associated withincreased PA and two studies [40, 53] reported no effect.One study had a specific focus on changes in PA after

moving into houses with active design (more attractivestairwells, outdoor community garden area, etc.) [54]. Itshowed that female and male residents which used tolive in houses with an elevator increased their number ofsteps per day and MVPA after moving in the newenvironment.

Effects of the built environment on femalesThe review of selected studies also identified a numberof built environment characteristics that had a larger/stronger effect on PA behavior in females. Some studiesreported that building of new bike lanes [33, 34], avail-ability of public transport [28, 55], and house density[55] increased active transportation and using of PA fa-cilities more in women than in men. The movabilityindex and the distance to daily destinations had a posi-tive effect on the overall PA level in females [53]. Streetnetwork characteristics had no effect on the PA level orwalking [53, 55]. It was shown that local road density

and land use mix were even negatively associated withoverall PA and active transportation in females [43, 56]New recreation facilities such as pocket parks [47] and

new aquatic and recreation centers [52] attracted morefemale users; however, it did not affect their overall levelof PA. Moving into houses with active design increasedwork-related MVPA in women [54].

Effects of the built environment determinants on malesThe studies that investigated the effects of transport-related built environment on PA have shown that thepresence of dead-end roads [41] and intersection con-nectivity [38] had stronger positive associations withoverall PA in boys. In three studies that investigated theeffect of building new bike lanes on active travel, onefound increases in using facilities in favor of men [29].Local road density and proportion of local roads waspositively associated with PA among men in low urbani-city areas [43]. All other transportation-related built en-vironment characteristics had no positive effect on PAbehavior in men and street connectivity was even nega-tively associated with mean of daily PA in men [53].The availability of parks and green zones [57, 58], the

creation of new pocket parks [47], the installation ofoutdoor gyms in parks [59], and outdoor PA equipment[50] increased PA levels significantly more in men thanin women. Michael et al. [60] reported that in a malesample, the proximity to recreation facilities was associ-ated with a higher likelihood of maintaining or increas-ing walking time in high-socioeconomic statusneighborhoods. After moving into houses with an activedesign, men had higher levels of moderate recreationalPA [54].

DiscussionThis systematic review included 36 studies that exam-ined the determinants of built environmental features as-sociated with PA, taking sex/gender into account. To thebest of our knowledge, this is the first study that aims toidentify built environmental determinants that are rele-vant for both males and females, and that could be start-ing points for intervention programs addressing theneeds of both populations. The review summarized re-sults from studies with longitudinal and intervention de-signs that currently provide the highest level of evidencein this field of research [17]. A variety of built environ-mental features were identified and allocated to thetransport, recreational, or household environment.The majority of the reviewed studies reported that the

built environment determined PA behavior in a similarway in males and females. Creating new infrastructurefor walking, cycling, and public transportation showed apositive effect on PA behavior. The findings were mostconsistent for the availability of public transport, which


was positively associated with overall PA and walking.The improvement of walking and cycling infrastructurehad no effect on the overall level of PA, but it attractedmore users and had a positive effect on active transpor-tation in more than half of the studies. These findingsare in line with previous reviews [9, 11, 32]. These typesof interventions seem to be promising for promoting ac-tive travel. In women, the availability of public transport,specially organized safe cycling lanes, house density, andthe distance to daily destinations, showed to be morerelevant for PA behavior. In men, street network charac-teristics and road environment, such as intersection con-nectivity, local road density, and the presence of dead-end roads, were identified as important determinants ofPA. Some of the built environmental determinants ofPA identified in women are more related to safety as-pects. Similar results were found in previous studiesshowing that safety concerns were barriers of PA inwomen [61, 62]. These findings should be taken intoaccount when planning future environmentalinterventions.Based on the results of the current review, improve-

ments in recreation facilities can be considered a usefulstrategy to enhance overall PA, especially in males. Thecreation of new parks as well as the renovation of exist-ing parks and green areas can make them more attract-ive for visitors and increase overall PA levels of usersindependent of sex/gender. Outdoor equipment, play-grounds, and green areas/spaces rather attract maleusers. No specific characteristics of the built environ-ment related to recreation were found to increase overallPA in females only.Houses with active design seem to be promising for

increasing the daily number of steps and the level of PA.In the reviewed studies, an increase in steps was ob-served for both sexes/genders: males increased moderaterecreational PA and females increased work-relatedMVPA. However, only one study with a small sampleanalyzed this type of the built environment [54]; hence,results must be interpreted with caution.The comparison of the effects of different features of

the built environment on PA behavior in males and fe-males shows that environmental interventions should becomplex and include improvements both in transport-related and recreational environments to address PA be-havior of both genders. Urban planners, policy makersand other practitioners should take into account thateasy access to public transport and safety when usingcycling lanes is more important for females than formales. For males, it is more important to have play-grounds and outdoor PA equipment in parks.The methodology, measures, and analytical approaches

used to evaluate built environmental determinants of PAbehavior are characterized by substantial variability. This

finding is in line with previous reviews on similar topics[9, 13] and hampers comparisons between studies andinterventions. Even studies that examined similar builtenvironmental characteristics had significant differencesin research design and evaluation approaches that re-sulted in a diverse quality of research. In most studies,the methodological quality of the studies was limiteddue to a lack of appropriate control conditions, consid-eration of cofounders, and poor sample representatives(small number of participants, high loss to follow-up).Blinding was not described in the majority of studies

and hardly implemented in the reviewed studies. Thislimitation can affect results especially in studies thatused subjective tools for assessing PA behavior. We ex-cluded questions on blinding during the quality assess-ment for all studies where it was not applicable, whichdid not affect the final quality score. However, it is rec-ommended that future studies find a way to prevent biasassociated with participants’ self-reports and investiga-tors’ partiality when blinding is not possible.The timing and number of follow-up measures were

inconsistent and varied from 6 months to 15 years. Thislimits comparison of results and a clear understandingof the impact of the built environment on PA. In almost40% of the studies, the follow-up period was 1 year orless. In their review of experimental studies, Mayne et al.[63] found that studies with longer follow-up times re-ported stronger impacts of changes in the built environ-ment on PA. The short follow-up periods in builtenvironmental interventions were usually caused bypragmatic and economic factors. However, longer pe-riods are recommended.Moreover, it has to be taken into account that almost

all of the studies were conducted in the USA, Australia,and Europe, where gender roles for PA behaviors areless pronounced and opportunities for an active lifestylemight be more similar for males and females [64]. Thiscould be one of the explanations why most of the builtenvironmental determinants of PA behavior were similarfor males and females in the included studies. The con-duction of further studies in developing countries and inAsian countries is necessary to investigate whether sex/gender differences in built environmental determinantsof PA are related to culture and socio-economic factors.Although the number of studies focused on built en-

vironmental determinants of PA behavior is growing,most of them do not take sex/gender into account or donot present sex/gender-related results in the articles.Adding such information to the articles could contributeto a better understanding of the issue and confirm ordisprove the results of this review. The review showedthat the included studies are predominantly related totransportation and recreation environments. This doesnot allow us to draw conclusions about whether there is


a difference in the influence of occupational and house-hold environment on PA in males and females. Thiscould be recommended as one of the topics for futureresearch in this field.

Strengths and limitationsThe strengths of this review lie in the systematic searchof relevant studies in six electronic databases and in theevaluation of methodological quality (risk of bias) of allincluded studies. The analysis of longitudinal and inter-vention studies allows to identify associations betweenbuilt environment characteristics and PA, which mayprove useful for planning future interventions by focus-ing on sex/gender differences in effects of the built en-vironment on PA; future interventions can be informedso that they are effective for both males and females. Inthis manner, inequalities caused by the intervention canbe prevented by including different parameters thatmake it effective both for males and females.The review also has some limitations. Publication bias

cannot be ruled out as only published journal articles inEnglish language were eligible for inclusion and all othertypes of publications and gray literature as well as arti-cles in other languages were excluded. Differences in theapproaches used to examine and report PA outcomeshinder a comprehensive comparison of the reviewedstudies. For this reason, a quantitative synthesis of re-sults with meta-analytic procedures could not be con-ducted. Furthermore, age stratification was not possibledue to high heterogeneity of included studies. This limitsthe interpretation of the results since the effects of thebuilt environment on PA by gender may be different forchildren and adults. More than half of the studies mea-sured PA behavior of participants with self-reported in-struments and, in this case, people may under- oroverestimate their level of PA. This, combined with thefact that built environmental intervention studies arerarely blind for participants, can affect the results andmake them less reliable.

ConclusionsThis review sheds light on the relevance of the built en-vironment on PA. The findings from this review supportthe hypothesis that designing an activity-friendly envir-onment can have a positive effect on PA. In general, im-provements are beneficial for both genders. However, itshows that in order to address both genders equally,urban planning should focus on built environmentalcharacteristics related to different PA domains as someof them are more effective PA in females and some inmales. The focus on sex/gender differences introduces anew aspect that should be further analyzed in future re-search and considered by urban planners and otherpractitioners.

AbbreviationsGIS: Geographical information systems; MVPA: Moderate to vigorous physicalactivity; PA: Physical activity; WHO: World health organisation

AcknowledgementsThe authors would like to thank Susan Faizy for the participation as a secondreviewer in screening and selection of the relevant studies, data extraction,and quality assessment.

Availability of data and materialNot applicable.

Authors’ contributionsAll authors contributed to conceptualization of the study and theinterpretation of the results. AT conducted the literature search, dataextraction, and analysis. KW participated in the quality assessment. AT withsupport from AKR and HW prepared a first draft of the manuscript. AKRsupervised this work. All authors critically reviewed the draft and approvedthe final manuscript.

FundingThe present systematic review is part of the KOMM-Project “Systematic datacollection, analysis and communication of places and motivations for phys-ical activity and needs of change agents for physical activity promotion”funded by Federal Ministry of Health, Germany (BMG) (Grant Number: ZMVI1-2519FSB105), which had no influence on the content of this manuscript.Open Access funding enabled and organized by Projekt DEAL.

Ethics approval and consent to participateNot applicable.

Consent for publicationNot applicable.

Competing interestsThe authors declare that they have no competing interests.

Author details1Department of Sport Science and Sport, Friedrich-Alexander-UniversityUniversity Erlangen-Nuremberg, Gebbertstraße 123b, 91058 Erlangen,Germany. 2Department of Sport and Health Sciences, Technical University ofMunich, Munich, Germany. 3Institute of Sports and Sports Science, KarlsruheInstitute of Technology (KIT), Karlsruhe, Germany.

Received: 2 September 2020 Accepted: 9 November 2020

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