Neighborhood environment,physical activity,and quality of life in adults: Intermediary effects of personal and psychosocial factors

Eleni Theodoropoulou,Nektarios A.M.Stavrou,Konstantinos Karteroliotis

School of Physical Education and Sport Science,National and Kapodistrian University of Athens,Athens 17237,Greece

Neighborhood environment,physical activity,and quality of life in adults: Intermediary effects of personal and psychosocial factors

Eleni Theodoropoulou*,Nektarios A.M.Stavrou,Konstantinos Karteroliotis

School of Physical Education and Sport Science,National and Kapodistrian University of Athens,Athens 17237,Greece

Background:Studies have indicated that there is a positive and indirect relationship between physical activity(PA)and quality of life(QoL).The current study examined this relationship through a social cognitive model with consideration to the intermediary effects of exercise self-effica y, and physical(PCS,physical component summary)and psychological(MCS,mental component summary)health.Additionally,this model was widened to include concepts from the ecological theory,and any causal associations among neighborhood environment,PA,and QoL.

Methods:Six hundred and eighty-four physically active adults(39.16±13.52 years,mean±SD),living in Athens,Greece,completed a series of questionnaires measuring PA,QoL,exercise self-effica y,PCS,MCS,neighborhood environment,and family and friend support for PA.The examined models were analyzed using structural equation modeling.

Results:The social cognitive and ecological models proved to be of appropriate fit Within the social cognitive model,PA positively affected QoL through the mediating effects of exercise self-effica y,PCS,and MCS.With regards to the ecological model,neighborhood environment positively influence QoL through the intermediary effects of family support for PA,exercise self-effica y,PA,PCS,and MCS.

Conclusion:Results indicated that the most important mediators in the examined models were exercise self-effica y and health.Further,finding demonstrated the role of neighborhood environment in enhancing PA and QoL.Future studies should be carried out applying longitudinal data for a better understanding of these associations over time.

?2017 Production and hosting by Elsevier B.V.on behalf of Shanghai University of Sport.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Cognitive;Ecological;Health;Self-effica y;Structural equation modeling

1.Introduction

During the last20 yearsthere hasbeen an increasing research interest on the prediction of quality of life(QoL).1QoL consists a multidimensional concept incorporating factors such as personal health,social relationships,perceived happiness,family life,occupationalsatisfaction,and environmentalconnection.2–5In particular,social researchers have define QoL as a cognitive judgment of satisfaction with one’s life.2,6Lately,various scientists have replaced the term QoL with health-related QoL, focusing on the effects of illnesses or other variables on one’s perceived health status.2,3Despite the different definition of QoL,it is common that QoL has been associated with various factors,such as physical and psychological health,social function,well-being,and satisfaction with life.2–5Further, several studies have demonstrated that participation in physical activity(PA)is an effective intervention for increasing and maintaining QoL.2,3,7–10Specificaly,Sorensen et al.8indicated thatparticipation in a 4-month exercise program increased QoL. In line with this,Wolin et al.10have longitudinally examined 63,152 women aged 40–67 yearsold,and observed thatincreases in PA were associated with an improvement in QoL.

The well-established positive relationship between PA and QoL has led to an examination of possible mediators that may explain this association.11–15Specificaly,PA has been positively associated with QoL,which was define as satisfaction with one’s life,through the intermediary effects of exercise selfeffica y,physical(PCS,physical component summary)and psychological(MCS,mental component summary)health,and positive affect.11–15In particular,Elavsky et al.11observed that PA positively influence QoL through the mediating effects of exercise self-effica y,and positive affect.However,this causalmodel accounted for only 12%of the variance in QoL.Higher percentages of the variance in QoL have been found in other studies including health status as a mediator.12–14More specifi cally,McAuley et al.12,13have examined a social cognitive model,and demonstrated that PA positively affected exercise self-effica y,which positively influence PCS and MCS.In turn,PCS and MCS had positive effects on QoL.12,13For the development of these models both the social cognitive theory and the value that individuals place on PA were considered,as they play an important role in QoL outcomes.2,3,12–15

Apart from the aforementioned models,recently the associations among neighborhood environment,PA,PCS,and MCS have been examined.16Results have showed that neighborhood environment,which serves as an important concept in the ecological theory,was positively related to the PA,PCS,and MCS. Additionally,PA was supported to be a possible mediator in the relationship between neighborhood environment,PCS,and MCS.16This hypothesis could be supported by data that proved the positive associations between neighborhood environment and PA,17and also among PA,health status,and QoL.12,13In particular,Ishii et al.17have examined a model of the relationship between neighborhood environment and PA,in which they found:(a)direct positive effects of neighborhood environment on PA,(b)indirect positive effects of neighborhood environment on PA through the intermediary roles of social support for PA and exercise self-effica y,and(c)direct positive effect of exercise self-effica y on PA.In addition,positive associations among neighborhood environment,PCS,and MCS have been observed.9,16As far as the effects among PA,exercise selfeffica y,PCS,MCS,and QoL were concerned,these associations were well established.12,13Therefore,it could be hypothesized that neighborhood environment on the one hand is positively associated with PA through the intermediary roles of social support for PA and exercise self-effica y,and on the other hand is positively related to PCS and MCS.PA seems to enhance PCS and MCS,which in turn increase QoL.

The aforementioned concepts have not been examined within the context of the same theoretical model so far.Similarly,neighborhood environment,social support,and ecological theory have not been used in tandem regarding an examination of the PA and QoL relationship.In particular,an ecological model of the association between neighborhood environment,PA,and QoLincluding the mediating effects of social factors,such as family and friend support for PA has not been examined so far in the literature.Therefore,the purpose of the current study is twofold.First, it aims to examine further the social cognitive model of PA and QoL proposed by McAuley et al.13testing its adequacy to fi in a different sample.The second purpose is to evaluate the usefulness of an ecological model of neighborhood environment,PA, and QoL.Specificaly,the model proposed by McAuley et al.13was widened including concepts from the ecological theory,17with the aim to examine a model including associations between neighborhood environment and QoL.In the ecological model, the intermediary effects of family and friend support for PA, exercise self-effica y,PA,PCS,and MCS were assessed.An original aspect of this study was the investigation of the model with the best fi of the collected data.

2.Materials and methods

2.1.Participants’recruitment and sample size calculation

The sample’s selection met the following criteria:(a)participation in PAbecausethe importancethatindividualsplaceon PA is a moderator of PA and QoL relationship,2and(b)18–65 years old to exclude older adults and adolescents.In particular,the sample that was not randomly selected consisted of 752 participants who agreed to complete the questionnaires.They participated in various exercise programs in the sport facilities of the Municipality ofAthens.Due to listwise deletion both ofmissing values and outliers,684 participants consisting of 206 men (30.12%)and 478 women(69.88%)aged 39.16±13.52 years (mean±SD)were used for the analyses.

The sample size was calculated using the criterion of 10 participants per item(10:1 ratio).18Further,a statistical algorithm calculating sample size in structural equation modeling was used(www.danielsoper.com).19The sample size definitio was calculated based on the following criteria:(a)a power of 0.8,(b)an effect size of 0.1,and(c)a significan level of 0.5.19

2.2.Assessments

2.2.1.PA

PA was measured using the International Physical Activity Questionnaire(IPAQ)short form.20The IPAQ-short form,having 7 days recall period,consists of 6 items assessing exercise frequency and duration and one item measuring sedentary behavior. The 6 items evaluated the following PA indexes:walking PA, moderate PA,vigorous PA,and total PA.The PA indexes are expressed in MET-minutes per week and are calculated as duration×frequency per week×MET intensity.The total PA index wascalculated by adding the walking PA,the moderate PA,and the vigorous PA indexes.20Validity and reliability of the IPAQ were well established,and verifie for its Greek version.20–22

2.2.2.QoL

The Satisfaction With Life Scale(SWLS)was used to assess QoL.6The SWLS consists of the following 5 items:“in most ways my life is close to my ideal”,“the conditions of my life are excellent”,“Iam satisfie with my life”,“so farIhave gotten the important things I want in my life”,and“if I could live my life over,I would change almost nothing”.Each item was rated on a 7-pointscale with highervaluesrepresenting betterlife satisfaction.All items constituted 1 factor.Pavot and Diener6have reported satisfactory factorial and construct validity as well as acceptable internal consistency(α=0.80–0.89),and test–retest reliability(r=0.64–0.84)of the SWLS.6In line with this,the psychometric properties examination of the Greek SWLS version indicated acceptable factorial validity,internal consistency(α=0.90–0.93),and test–retest reliability(ICC=0.77).23

2.2.3.Exercise self-efficac

Exercise self-effica y was estimated using a 5-item Self-Effica y Scale.24This scale was designed to estimate one’s belief in his/her ability to persist in exercising under the following adverse situations:tired,bad mood,not having time,on vacation,and raining or snowing.The validity as well asthe internal consistency(α=0.76),and test–retest reliability (r=0.90)of the scale are well established.24Recent research finding demonstrated that the Greek version of the Self-Effica y Scale had sufficien factorial validity and reliability (α=0.83–0.87,ICC=0.96).25

2.2.4.PCS and MCS

The ShortForm 36(SF-36)Health Survey26,27isa questionnaire consisting of 36 items that evaluate 8 first-orde factors:physical functioning,role disability due to physicalproblems(physicalrole), bodily pain,general health perceptions(general health),vitality, socialfunctioning,role disability due to emotionalproblems(emotional role),and mental health.These first-orde factors can be grouped under2 second-orderfactorsthatwere used in the current statistical analyses:PCS and MCS.In the current study,the 8 first-orde factors’scores were transformed into 8 factors’scores using the equations proposed by Ware et al.27PCS and MCS second-order factors were calculated through confi matory factor analytic procedure using the first-orde factors’scores.27,28Finally, recent studies proposed the existence of a valid and reliable Greek version of the SF-36 Health Survey.29,30

2.2.5.Neighborhood environment

Regarding Ishii et al.’s17theoretical work,the neighborhood environment was evaluated based on 5 items:“I possess home fitnes equipment”,“my neighborhood provides facilities(e.g., walking trail,park,fitnes club)for PA”,“my neighborhood provides a safe and well-maintained environment(e.g., adequate lighting and sidewalks)for PA”,“I have access to enjoyable scenery when engaging in PA”,and“I frequently observe other people exercising”.A recent study demonstrated that the Greek version of the Neighborhood Environment Scale was valid and reliable(α=0.84–0.86,ICC=0.87).31

2.2.6.Family support for PA

The Family Support for Exercise Behaviour Scale(FaSEBS) was administered for the assessment of family support for PA.32The FaSEBS consisted of 15 items(e.g.,“my family exercised with me”,“gave me encouragement to stick with my exercise program”,“changed their schedule so we could exercise together”).Satisfactory construct validity,internal consistency (α=0.91),and test–retest reliability(r=0.77)were established forFaSEBS.32In linewith this,arecentstudy indicated acceptable constructvalidity,internalconsistency(α=0.85–0.91),and test–retest reliability(ICC=0.89–0.93)for the FaSEBS Greek version.33Particularly,the Greek version contained 12 items that constituted 2 factors named the“family supportforexercise”and“family participation in exercise”.33

2.2.7.Friend support for PA

Friend support for PA was estimated using the Friend Support for Exercise Behaviour Scale(FrSEBS).32The FrSEBS consists of 5 items,asking participants if their friends exercised with them, offered to exercise with them,gave them helpful reminders to exercise,gave them encouragement to stick with their exercise program,and changed their schedule so they could exercise together.The FrSEBS construct validity,internal consistency (α=0.84),and test–retest reliability(r=0.79)were satisfactory.32Recent study demonstrated acceptable validity,internal consistency(α=0.86–0.91),and test–retest reliability(ICC=0.90)for the Greek version of FrSEBS.33

2.3.Ethical approval,study design,and procedure

This cross-sectional study was approved by the National and Kapodistrian University ofAthens’Ethical Committee,and was carried out from February to May in 2012.An experienced research group visited the sport facilities and informed individuals about the purpose and the procedure of the study.Participants who agreed to participate in the study signed the consent form and fille in the questionnaires.

2.4.Statistical analyses

Means,medians,standard deviations,frequencies,sums,skew, kurtosis,and normality tests were conducted using the SPSS Version 17.0 statistical software(SPSS Inc.,Chicago,IL,USA).

2.4.1.Model testing

The hypothesized models were examined following 2 steps: (a)confi matory factor analysis(CFA)for assessing the fi of the measurement models,and(b)structural equation modeling (SEM)for testing the fi of the structural models.18,34Analyses were performed using the AMOS Version 16.0 statistical software(AMOS Development Corp.,Chicago,IL,USA).

2.4.2.CFA

Separate CFA employing maximum likelihood estimation were conducted in order to examine the factorial validity of the SWLS,Exercise Self-Effica y Scale,SF-36 Health Survey, Neighborhood Environment Scale,and Family and Friend SupportforPhysicalActivity Scales.Appropriatenessoftheitems was based on the criteria of skewness(±2),kurtosis(±2.5), Mardia’scoefficien(0.40),and correlation matrix(<0.90).18,35In addition,internalconsistency wasestimated using the Cronbach’sαcoefficient18

2.4.3.SEM

SEM utilizing maximum likelihood estimation and bootstrapping procedures was conducted to assess the fi of the 2 structural models.18,34In particular,the social cognitive model (Fig.1)proposed by McAuley et al.13specifie a direct effect of PA on exercise self-effica y,which directly affected PCS and MCS.In turn,PCS and MCS had direct paths on QoL(SWLS).

Further,as Fig.2 proposes,the ecological model specifie direct paths of neighborhood environment on family and friend support,PA,PCS,and MCS.Family and friend support for PA directly affected exercise self-effica y,which had direct paths on PA,PCS,and MCS.PA directly influence exercise self-effica y, PCS,and MCS.Therefore,the relationship between exercise self-effica y and PA was bidirectional,based on studies showing that both PA affected exercise self-effica y,13and the latter influ enced PA.17In turn,directpathsofPCSand MCS on QoL(SWLS) were specified Regarding the development of this model,neighborhood environment as well as family and friend support for PA constituting concepts of the ecological theory were added in the model proposed by McAuley et al.,13in accordance with recentstudies.9,16,17Therefore,the aforementioned structural models were considered as hierarchical.

Fig.1.Social cognitive structural model of PA and QoL(SWLS).Measurement models were not included to improve the clarity of the figure Solid lines with standardized directeffectsrepresentsignifican effects(***p<0.01).The valuesin italics present the variance of the measurement errors.ESE=exercise self-effi cacy;MCS=mental component summary;PA=physical activity;PCS=physical component summary;QoL=quality of life;SWLS=Satisfaction With Life Scale.

2.4.4.Model fi

Fig.2.Ecological structural model of neighborhood environment and QoL (SWLS).Measurementmodelswerenotincluded to improvetheclarity ofthefigure Solid lineswith standardized directeffectsrepresentsignif canteffects(*p<0.05,***p<0.01),whereasdashed linesrepresentnon-signifcanteffects.Thevaluesin italics present the variance of the measurement errors.The relationship between exercise self-effica y and PA was reciprocal.ESE=exercise self-effica y;MCS=mental component summary;NE=neighborhood environment;PA=physical activity; PCS=physical component summary;QoL=quality of life;SS=social support; SWLS=Satisfaction With Life Scale.

Assessment of models fi was based on the chi-square test (χ2),the Satorra–Bentlerχ2/dfratio,and the root mean square error of approximation(RMSEA).18,36Non-significan values ofχ2and values ofχ2/dfratio smaller than 3.0 indicate acceptable fitRMSEAvalues lower than 0.05 represent close fit between 0.05 and 0.08 indicate acceptable fit whereasRMSEAvalues greater than 0.08 represent poor fit Further,assessment of models fi was based on the following indexes:(a)Comparative Fit Index(CFI),(b)Goodness-of-Fit Index(GFI),(c)Incremental Fit Index(IFI),and(d)Tucker and Lewis Index (TLI).18,37CFI,GFI,IFI,andTLIvalues approximating 1.0 indicate perfect fit whereas values above 0.90 represent acceptable fit Finally,differences(D)between the structural models in theχ2/dfratio(χ2D/dfD)and inCFI(CFID)were examined to fin the model with the best fit18Significan differences between them in theχ2/dfratio,and differences higher than the value of?0.01 between the models inCFIindicated significan differences.For findin the differences between the models in theχ2/dfratio,the statistical software SBDIFF.EXE(University of Aberdeen,Aberdeen,UK)was used.

3.Results

3.1.Descriptive statistics and sample size calculation

In total,2.20%of sample participated in light intensity PA,72.95%participated in moderate PA,while 24.85%participated in vigorous PA.The mean value of sedentary life was 5.57±3.02 h/day(mean±SD).Additionally,initial analysis indicated non-normal distributions for the total PA index and the scores of the 8 first-orde factors of the SF-36 Health Survey.Therefore,the values were transformed using square root and logarithmic functions to solve the problem of nonnormal distributions.18

Regarding the sample size,the ratio of participants’number to observed variables was higher than the 10:1 ratio,as it was 42.75:1 for the social cognitive model,and 20.73:1 for the ecological model.In line with the above,the number of participants was higher than the recommended sample size for both models’structure(Nsoc/cognitive=100,Necological=90),and signifi cant effects’identificatio (Nsoc/cognitive=387,Necological=579).

3.2.CFA results

3.2.1.SWLS(QoL)

The SWLS Mardia’s coefficien(2.65)supported the multivariate normality.The measurement model provided a good fi(χ2=43.282,df=5,p=0.000,χ2/df=8.656,CFI=0.978,GFI=0.974,IFI=0.978,TLI=0.956)apart fromRMSEAvalue(0.106).Therefore,an alternative model was examined setting a pair of correlated errors between items 2 and 3 based on their conceptual similarity.The alternative model represented a better fi to the data(χ2=21.320,df=4,p=0.000,χ2/df=5.330,CFI=0.990,GFI=0.987,IFI=0.990,TLI= 0.975,RMSEA=0.070).Further,the better fi of the alternative model was confi med by the differences between the models inCFI(CFID=?0.01),andχ2/dfratio(χ2D=4.14,dfD=1,p<0.05).The Cronbach’sαof the SWLS was 0.88.

3.2.2.Exercise Self-Efficac Scale

The Mardia’s coefficien(2.87)of the scale indicated multivariate normality.The measurement model demonstrated anadequate factorial validity(χ2=16.668,df=5,p=0.005,χ2/df=3.334,CFI=0.993,GFI=0.990,IFI=0.993,TLI=0.987,RMSEA=0.058).The Cronbach’sαof this scale was 0.88.

3.2.3.SF-36 Health Survey

The Mardia’s coefficien of the SF-36 Health Survey showed multivariate non-normality,and CFA was conducted applying bootstrapping with the Bollen–Stine approach.18Three hypothesized hierarchical models were examined.26–29In the firs model,physical functioning,physical role,bodily pain,and general health subscales constitute the PCS factor,whereas vitality,social functioning,emotional role,and mental health subscales comprised the MCS factor.27This model provided a poor fi(χ2=46.517,df=19,p=0.005,χ2/df=2.448,CFI=0.847,GFI=0.913,IFI=0.848,TLI=0.775,RMSEA= 0.132).In the second model,the PCS factor consisted of the physical functioning,physical role,and bodily pain subscales, the MCS factor was composed of the social functioning, emotional role,and mental health subscales,whereas the wellbeing factor consisted of the general health and vitality subscales.26This model also represented a poor fi(χ2=33.516,df=17,p=0.005,χ2/df=1.972,CFI=0.871,GFI=0.924,IFI=0.872,TLI=0.788,RMSEA=0.128).Finally,a 2-factor model was tested,in which the physical functioning,physical role,and bodily pain subscales constitute the PCS factor, whereas the emotional role,and mental health subscales constitute the MCS factor.28This model demonstrated the best fi(χ2=2.521,df=2,p=0.075,χ2/df=1.261,CFI=0.991,GFI=0.996,IFI=0.991,TLI=0.955,RMSEA=0.063).In line with this,the differences between the latter and the firs 2 models inCFI(CFID≥?0.02)indicated significan differences.

3.2.4.Neighborhood Environment Scale

The Mardia’s coefficien(3.04)of the scale demonstrated multivariate normality.The measurement model provided a good fi(χ2=13.948,df=4,p=0.007,χ2/df=3.487,CFI=0.988,GFI=0.992,IFI=0.988,TLI=0.970,RMSEA=0.060).The Cronbach’sαwas 0.76.

3.2.5.Family and Friend Support for Physical Actvity Scales

The Mardia’s coefficien(29.75)of the family support for PA scale indicated multivariate non-normality,and CFA was conducted performing bootstrapping with the Bollen–Stine approach.18Results showed that the measurement model represented a good fi(χ2=67.434,df=53,p=0.005,χ2/df=1.272,CFI=0.970,GFI=0.949,IFI=0.970,TLI=0.963,RMSEA= 0.065).The Cronbach’sαwas 0.92 for the“family support for exercise”factor,and 0.91 for the“family participation in exercise”factor.In the current study,only the“family support for exercise”factor was used in the structural model,due to the ecological theory’s focus on social support for PA.

With regard to the friend support for PA scale,the Mardia’s coefficien (1.29)indicated multivariate normality.Results supported the factorial validity of the scale(χ2=84.837,df=5,p=0.000,χ2/df=16.967,CFI=0.964,GFI=0.949,IFI=0.964,TLI=0.929).However,theRMSEAvalue(0.153) was high.An alternative model was examined setting a pair of correlated errors between Items 3 and 4,based on their conceptual similarity.The alternative model provided a better fi (χ2=12.738,df=4,p=0.013,χ2/df=3.185,CFI=0.996,GFI=0.992,IFI=0.996,TLI=0.990,RMSEA=0.057).This findin was confi med by the differences between the models inCFI(CFID=?0.03),andχ2/dfratio(χ2D=8.01,dfD=1,p<0.05).The Cronbach’sαwas 0.88.

3.3.Structural models’fi

The Mardia’s coefficient for both the social cognitive and the ecological models indicated multivariate non-normality. Therefore,SEM was conducted utilizing bootstrapping with the Bollen–Stine approach to assess model fi under non normal conditions.18

In particular,the social cognitive model provided an appropriate fi (χ2=103.029,df=96,p=0.001,χ2/df=1.073,CFI=0.965,GFI=0.957,IFI=0.965,TLI=0.956,RMSEA= 0.048).The model accounted for 14%of the QoL variance.As Fig.1 shows,PA positively affected exercise self-effica y(0.35,p<0.01),which had positive paths on PCS(0.17,p<0.01)and MCS(0.22,p<0.01).In turn,PCS(0.18,p<0.01)and MCS (0.48,p<0.01)positively affected QoL.The total standardized effect of PA on QoL was 0.03,indicating that an increase of 1 SD on PA predicts an increase of 0.03 SD on QoL.

Further,the ecological model represented an adequate fi (χ2=517.029,df=479,p=0.001,χ2/df=1.079,CFI=0.958,GFI=0.924,IFI=0.958,TLI=0.953,RMSEA=0.037).The model accounted for 16%of the variance in QoL.As Fig.2 shows,neighborhood environment had positive effects on family(0.12,p<0.05)and friend(0.16,p<0.01)support for PA,PA(0.11,p<0.05),and MCS(0.11,p<0.05),but did not significanty affect PCS(p=0.30).Family support for PA positively influence exercise self-effica y(0.08,p<0.05). However,friend support for PA did not significanty affect exercise self-effica y(p=0.29).The relationship between exercise self-effica y and PA was reciprocal(0.34,p<0.01).In addition,exercise self-effica y had positive paths on PCS(0.13,p<0.05)and MCS(0.19,p<0.01).In turn,PA positively influ enced PCS(0.12,p<0.05),but not MCS(p=0.19).Finally, positive paths from PCS(0.23,p<0.01)and MCS(0.52,p<0.01)to QoL were found.The total standardized effects of neighborhood environment on exercise self-effica y was 0.02 and on QoL was 0.07,indicating that when neighborhood environment increases by 1 SD exercise self-effica y increases by 0.02 SD,whereas QoL increases by 0.07 SD.

Regarding comparisons between the aforementioned models in fit analyses demonstrated that there were not significan differences between them,based on bothCFI(CFID=?0.007), andχ2/dfratio(p>0.05).

4.Discussion

This study examined the causal relationships between PA and QoL as well as among neighborhood environment,PA,and QoL within the context of theoretical frameworks.Particularly, the selection of the models’variables was based on the social cognitive and ecological theories strengthening the researchpurpose for identifying effects and interactions among them.In addition,an original aspect of the current study was the investigation of the ecological model regarding the relationship between neighborhood environment and QoL through the intermediary effects of family and friend support for PA,exercise self-effica y,PA,PCS,and MCS.Such associations have not been reported so far in the literature,because concepts from the ecological approach have not been used until now to enlighten the relationship between PA and QoL.

The currentstudy demonstrated thatadultswho participate in PA feel confiden enough with regard to their ability to persist in exercising under adverse situations,providing also better PCS, MCS,and QoL.Therefore,the important mediating effects of exercise self-effica y,as a basic social cognitive theory concept, and perceived health status to the PA and QoL relationship were supported.These finding indicated thatto improve health status and QoL,specialists should focus on increasing exercise selfeffica y.One of the ways to enhance self-effica y is to create successful experiences and positive feelings during PA.The aforementioned resultsare in accordance with previousresearch findings12,13However,PA accounted for a small amount of variance in QoL.A possible explanation is that QoL was assessed as satisfaction with one’s life,which represents a multidimensional concept that is not indispensably associated with either PA or perceived health.2,3In other words,the relationship between PA and QoL may be moderated by personal valuesystemsnotincluding PAorhealth perceptionsin cognitive judgment of QoL.2,3Further,satisfaction with one’s life may serve asa more salientfactorofQoL.2,3Finally,itwasfound that MCS had a higher positive effect on satisfaction with one’s life than PCS.This could be explained by the fact that satisfaction with one’s life reflect subjective well-being which is highly associated with psychological health status.2,3

Regarding the ecological model,the current finding suggest that environmental factors,such as access to facilities for PA, may improve MCS and family’s efforts to increase PA.In turn, social support from family could enhance self-effica y beliefs for PA and participation in PA.The direct effect of neighborhood environment on PA was low.Therefore,social ecological models should be used in promoting PA as it seems that social ecological variables modulate PA.The above finding are in line with previous research findings in which environmental factors positively affected PA through the intermediary effects of social support for PA,and exercise self-effica y.17In addition,the current study indicated that both high PA levels were associated with greater beliefs in one’s ability to persist in exercising,and the latter was related to high PA levels,indicating that selfeffica y is closely linked to PA.Finally,the present results demonstrated that greater levels of exercise self-effica y were associated with better PCS,MCS,and QoL,confi ming the finding of previous research in the area.12,13The aforementioned finding provided further support to the importance of the ecological and social cognitive theories,PA levels,and perceived health status for explaining the relationship between neighborhood environment and QoL.However,the ecological model accounted for a small amount of variance in QoL.A possible explanation is that satisfaction with one’s life is related to a diverse variety of concepts,such as self-confidence emotional affect,and enjoyment.2,3Future research needs to examine these factors.In line with this,the small amount of variance could be partly explained from the fact that only 5 items’scales were used for both the satisfaction with one’s life and neighborhood environment assessment.

Finally,this study had several limitations that need to be reported.First,due to the cross-sectional nature of the study, such data are not optimal for assuming causality over time,and testing intermediary effects.18In particular,single source-bias may account for some of the associations,and the proportion of the total effect mediated by mediators is often misleading. However,the hypothesized models were based on a sufficien theoretical background,and they could be examined within a cross-sectional framework for identifying relationships among the examined factors.Second,measures were self-reported and problems associated with common method variance should be considered.Third,multidimensional measures of QoL and objective measures of environment through geographical information systems technology were not used.Despite the apparent limitations,this study had some advantages that should be considered.In particular,a key feature of this study was the ecological theoretical model of the associations among neighborhood environment,PA,and QoL that has not been examined until now.Further,no such study has been carried out in physically active adults,aged 18–65 years old.

5.Conclusion

In this study,associations between PA and QoL as well as between neighborhood environment and QoL were examined. The most important mediators in these relationships appeared to be exercise self-effica y and health status indicating the role of beliefs in one’s ability to persist in exercising and perceptions of one’s health.In addition,the current study proposed that an effective neighborhood environment for PA promotion could be used for enhancing both PA and QoL.Considering the limitations of the study,future studies should be carried out to examine the structural models using longitudinal data for better understanding the interactions and relations over time.Finally, similar studies using multidimensional measures of QoL,and objective assessments of neighborhood environment and PA would be of considerable value.

Acknowledgments

This research has been co-finance by the European Union (European Social Fund—ESF)and Greek national funds through the Operational Program “Education and Lifelong Learning”of the National Strategic Reference Framework (NSRF)—Research Funding Program:Heracleitus II.Invest in knowledge society through the European Social Fund.

Authors’contributions

All authors were involved in formulating the paper.ET conceived of,designed and carried outthe study,analyzed the models, drafted and revised the manuscript;NAMS contributed to the study’sdesign and statisticalanalyses,and helped to draftand revisethe manuscript;KK participated in designing and carrying out the study,and contributed to the manuscript’s statistical analyses and revision.Allauthorshaveread and approved the fina version ofthe manuscript,and agree with the orderofpresentation oftheauthors.

Competing interests

None of the authors declare competing financia interests.

1.Eime R,Harvey J,Payne W.Dose-response of women’s Health-Related Quality of Life(HRQoL)and life satisfaction to physical activity.J Phys Act Health 2014;11:330–8.

2.McAuley E,Morris KS.Advances in physical activity and mental health: quality of life.Am J Lifestyle Med 2007;1:389–96.

3.Rejeski WJ,Mihalko SL.Physical activity and quality of life in older adults.J Gerontol 2001;56(Suppl.2):23–35.

4.World Health Organization.Health promotion glossary.Available at: http://www.who.int/healthpromotion/about/HPRGlossary1998.pdf; [accessed 16.10.2009].

5.World Health Organization.Concepts and methods of community-based initiatives.Available at:http://www.who.int/iris/handle/10665/116357; [accessed 24.10.2009].

6.Pavot W,Diener E.Review of the satisfaction with life scale.Psychol Assess 1993;5:164–72.

7.Bize R,Johnson JA,Plotnikoff RC.Physical activity level and health-related quality of life in the general adult population:a systematic review.Prev Med 2007;45:401–15.

8.Sorensen J,Sorensen JB,Skovgaard T,Bredahl T,Puggaard L.Exercise on prescription:changes in physical activity and health-related quality of life in fi e Danish programmes.Eur J Public Health 2010;21:56–62.

9.Sarmiento OL,Schmid TL,Parra DC,Diaz-del-Castillo A,Gomez LF, Pratt M,et al.Quality of life,physical activity and built environment characteristics among Colombian adults.JPAH 2010;7(Suppl.2):S181–95.

10.Wolin KY,Glynn RJ,Colditz GA,Lee IM,Kawachi I.Long-term physical activity patterns and health-related quality of life in U.S.women.Am J Prev Med 2007;32:490–9.

11.Elavsky S,McAuley E,Motl RW,Konopack JF,Marquez DX,Hu L,et al. Physical activity enhances long-term quality of life in older adults:effica y, esteem and affective influences Ann Behav Med 2005;30:138–45.

12.McAuley E,Konopack JE,Motl RW,Morris KS,Doerksen SE,Rosengren KR.Physical activity and quality of life in older adults:influenc of health status and self-effica y.Ann Behav Med 2006;31:99–103.

13.McAuley E,Doerksen SE,Morris KS,Motl RW,Hu L,Wojcicki TR,et al. Pathways from physical activity to quality of life in older women.Ann Behav Med 2008;36:13–20.

14.Konopack JF,McAuley E.Effica y-mediated effects of spirituality and physical activity on quality of life:a path analysis.Health Qual Life Outcomes 2012;10:57.doi:10.1186/1477-7525-10-57

15.Paxton RJ,Motl RW,Aylward A,Nigg CR.Physical activity and quality of life—the complementary influenc of self-effica y for physical activity and mental health difficulties Int J Behav Med 2010;17:255–63.

16.Chan AKC.How the built environment affects physical activity and health. Hong Kong:University of Hong Kong;2010.[Dissertation].

17.Ishii K,Shibata A,Oka K.Environmental,psychological and social influ ences on physical activity among Japanese adults:structural equation modeling analysis.Int J Behav Nutr Phys Act 2010;7:61.doi:10.1186/1479-5868-7-61

18.Kline RB.Principles and practice of structural equation modeling.2nd ed. New York,NY:Guilford;2005.

19.Westland JC.Erratum to“Lower bounds on sample size in structural equation modeling”.Electron Commerce Res Appl 2010;9:476–87.

20.Craig CL,Marshall AL,Sjostrom M,Bauman AE,Booth ML,Ainsworth BE,et al.International physical activity questionnaire:12-country reliability and validity.Med Sci Sports Exerc 2003;35:1381–95.

21.Papathanasiou G,Georgoudis G,Georgakopoulos D,Katsouras C, Kalfakakou V,Evangelou A.Criterion-related validity of the short international physical activity questionnaire against exercise capacity in young adults.Eur J Cardiovasc Prev Rehabil 2010;17:380–6.

22.Papathanasiou G,Georgoudis G,Papandreou M,Spyropoulos P, Georgakopoulos D,Kalfakakou V,et al.Reliability measures of the short international physical activity questionnaire(IPAQ)in Greek young adults. Hellenic J Cardiol 2009;50:283–94.

23.Theodoropoulou E,Karteroliotis K.Validity and reliability of the Greek version of the Satisfaction with Life Scale(SWLS):evidence from physically active college students.In:18th annual conference of the European College of Sport Science.Barcelona,Spain.June 26–29,2013.

24.Marcus BH,Selby VC,Niaura RS,Rossi JS.Self-effica y and the stages of exercise behavior change.Res Q Exerc Sport 1992;63:60–6.

25.Theodoropoulou E,Karteroliotis K.Validation of the Greek version of the Exercise Self-Effica y Scale.In:17th annual conference of the European College of Sport Science.Bruges,Belgium.July 4–7,2012.

26.Keller SD,Ware JE,Bentler PM,Aaronson NK,Alonso J,Apolone G, et al.Use of structural equation modelling to test the construct validity of the SF-36 Health Survey in ten countries:results from the IQOLA project. J Clin Epidemiol 1998;51:1179–88.

27.Ware JE,Kosinski MA,Dewey JE.How to score version 2 of the SF-36 health survey.Lincoln,RI:QualityMetric Incorporated;2000.

28.Hann M,Reeves D.The SF-36 scales are not accurately summarized by independent physical and mental component scores.Qual Life Res 2008;17:413–23.

29.Anagnostopoulos F,Niakas D,Pappa E.Construct validation of the Greek SF-36 Health Survey.Qual Life Res 2005;14:1959–65.

30.Pappa E,Kontodimopoulos N,Niakas D.Validating and norming of the Greek SF-36 Health Survey.Qual Life Res 2005;14:1433–8.

31.Theodoropoulou E, Karteroliotis K. Validation of a fi e-item neighbourhood environment scale:evidence from Greece.In:17th annual conference of the European College of Sport Science.Bruges,Belgium. July 4–7,2012.

32.Sallis JF,Grossman RM,Pinski RB,Patterson TL,Nader PR.The development of scales to measure social support for diet and exercise behaviors.Prev Med 1987;16:825–36.

33.Theodoropoulou E,Karteroliotis K,Stavrou N.Validity and reliability of Greek versions of two scales assessing family and friend support for exercise behaviour.Percept Mot Skills 2014;118:26–40.

34.Pedhazur EJ.Structural equation models with observed variables:path analysis—structural equation models with latent variables.In:Klein CP, editor.Multiple regression in behavioural research:explanation and prediction.3rd ed.Orlando,FL:Harcourt College publishers;1997. p.765–893.

35.Russell DW.The search of underlying dimensions:the use(and abuse)of factor analysis in personality and social psychology bulletin.Pers Soc Psychol Bull 2002;28:1629–46.

36.Steiger JH.Structural model evaluation and modification an interval estimation approach.Multivar Behav Res 1990;25:173–80.

37.Bentler PM.Comparative fi indices in structural equation models.Psychol Bull 1990;107:238–46.

Received 8 July 2015;revised 8 September 2015;accepted 19 October 2015 Available online 25 January 2016

Peer review under responsibility of Shanghai University of Sport.

*Corresponding author.

E-mail addresses:theodorelen@gmail.com(E.Theodoropoulou).

http://dx.doi.org/10.1016/j.jshs.2016.01.021

2095-2546/?2017 Production and hosting by Elsevier B.V.on behalf of Shanghai University of Sport.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).