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Assessing the social climate of physical (in)activity in Canada Yun, Lira; Vanderloo, Leigh; Berry, Tanya R; Latimer-Cheung, Amy E; O’Reilly, Norman; Rhodes, Ryan E; Spence, John C; Tremblay, Mark S; Faulkner, Guy Nov 27, 2018

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RESEARCH ARTICLE Open AccessAssessing the social climate of physical(in)activity in CanadaLira Yun1, Leigh Vanderloo2, Tanya R. Berry3, Amy E. Latimer-Cheung4, Norman O’Reilly5, Ryan E. Rhodes6,John C. Spence3, Mark S. Tremblay7 and Guy Faulkner1*AbstractBackground: Ecological models suggest that a strategy for increasing physical activity participation within apopulation is to reconstruct the “social climate”. This can be accomplished through 1) changing norms and beliefs,2) providing direct support for modifying environments, and 3) implementing policies to encourage physical activity.Nevertheless, surveillance efforts have paid limited attention to empirical assessment of social climate. This studyresponds to this gap by assessing the social climate of physical activity in Canada.Methods: A representative sample of Canadian adults (n = 2519, male/female = 50.3%/49.7%, Mage = 49.1 ± 16.3 years)completed an online survey asking them to assess social climate dimensions including social norms of physical (in)activity, perceptions of who causes physical inactivity and who is responsible for solving physical inactivity, and supportfor physical activity-related policy. Descriptive statistics (frequencies) were calculated. Multinomial logistic regressionswere constructed to identify whether demographic variables and physical activity participation associated with socialclimate dimensions.Results: Physical inactivity was considered a serious public health concern by 55% of the respondents; similar tounhealthy diets (58%) and tobacco use (57%). Thirty-nine percent of the respondents reported that they often seeother people exercising. Twenty-eight percent of the sample believed that society disapproves of physical inactivity.The majority of respondents (63%) viewed the cause of physical inactivity as both an individual responsibility and otherfactors beyond an individuals’ control. Sixty-seven percent of respondents reported physical inactivity as being both aprivate matter and a public health matter. Strong support existed for environmental-, individual-, and economic-levelpolicies but much less for legislative approaches. The social climate indicators were associated with respondents’ levelof physical activity participation and demographic variables in expected directions.Conclusion: This study is the first known attempt to assess social climate at a national level, addressing an importantgap in knowledge related to advocating for, and implementing population-level physical activity interventions. Futuretracking will be needed to identify any temporal (in)stability of these constructs over time and to explore therelationship between physical activity participation and indicators of the national social climate of physical activity.Keywords: Social climate, Physical activity, Policy, Public opinion, Ecological model* Correspondence: guy.faulkner@ubc.ca1School of Kinesiology, University of British Columbia, Lower Mall ResearchStation 337, 2259 Lower Mall, Vancouver, British Columbia V6T 1Z4, CanadaFull list of author information is available at the end of the article© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Yun et al. BMC Public Health         (2018) 18:1301 https://doi.org/10.1186/s12889-018-6166-2BackgroundPhysical inactivity is an important cause of chronic diseaseand is a major public health concern in Canada. Neverthe-less, the prevalence of physical inactivity is growing [1].According to the Canadian Health Measures Survey(CHMS; [2]), objectively measured physical activity datademonstrated just over 2 in 10 adults and 1 in 10 childrenand youth met the Canadian physical activity guidelines(www.csep.ca/guidelines). A holistic approach targetingstructural and systemic change is recommended for re-versing declines in physical activity and to influence be-havior of an entire population [3]. Ecological modelsprovide a framework that can guide the development of acomprehensive intervention targeting systematic mecha-nisms of change at each level of determinants from indi-vidual, social, environmental, to policy levels [4, 5].Environments are multidimensional and can be describedas social or physical, built or natural, actual or perceived,and can include constructs such as social climate – apsychological term that refers to the general feelings, atti-tudes, beliefs and opinions on a subject within society [6].Thus, a means to achieve behavior change of whole popula-tions may be to de-normalize physical inactivity and re-normalize physical activity through changing norms andbeliefs and by providing direct support for modifying envi-ronments and policies to encourage physical activity [4].Further, individuals’ unhealthy behaviors and lifestyles maybe modified through the alteration of social climate [6, 7].For instance, de-normalizing smoking has been one of themost effective strategies in reducing smoking prevalencethrough policies aimed at restricting smoking in public incombination with health advocacy and media efforts to shiftthe social acceptability of smoking [8–11]. Programs andpolicy actions that reinforced the message that tobacco useis not a normal activity have changed public perceptions ofthe social acceptability of smoking [12]. In turn, this de-creased social acceptability of smoking has been shown toreduce tobacco use as well as build public support of to-bacco control regulations. However, whether there is acomparable role for the social climate regarding physical(in)activity to influence policy enactment and populationchanges in behavior remains to be seen.Based on a number of theoretical frameworks influencinghealth-related behaviors [13, 14] and a set of related studiesexploring aspects of social climate related to tobacco con-trol [15] and obesity [16, 17], a range of potential factorsreflecting social climate can be identified, including: 1) thesocial norms and acceptability of physical (in)activity, 2)perceptions of the causes of physical inactivity, 3) percep-tions of responsibility for preventing physical inactivity, and4) the social acceptability of different policies and regula-tions in addressing physical inactivity.As noted, social norms – a pattern of behaviors or be-liefs generally held by ‘society’ – are one salient constructwithin a broader conceptualization of social climate. Con-ceptually, how serious a health issue is recognized in one’ssociety (c.f., Health Belief Model [18], Protection Motiv-ation Theory [19]) is theorized to guide one’s behavior.Perceived seriousness of physical inactivity, compared toother public health issues, may reflect the degree andmagnitude of social beliefs regarding physical activity as apublic health concern [20]. Perceptions of how common itis to see people exercising in their environment (descrip-tive norms) and perceptions of whether others approve ordisapprove of physical (in)activity (subjective or injunctivenorms) are also proposed to reflect the social climate ofphysical (in)activity [21, 22]. Previous research applyingsocial cognitive theories have posited that individuals aremore likely to be physically active if they perceive that thesocial expectations are to be active [23]. However, it is im-portant to note that social norms are commonly found tobe weak predictors of physical activity behavior comparedto risk behaviors such as drinking, smoking, and drug use[24–26]. Although speculative, this may be due to the po-tential harm to others of engaging in risky behaviors (e.g.,drinking and driving, secondhand smoking) whereas phys-ical (in)activity may not directly affect others’ health.The social ecological approach further acknowledgesthat collective norms reflect one’s perceptions of politicalactors, social institutions, and causes of social issues [7].Internal or external attributions of a public health issue(in this case, physical inactivity) and perceptions of indi-vidual or societal responsibility for solutions are linkedto expectations of societal actions and acceptance ofpolicies to address the issue [27]. Previous studies haveproposed that societal solution attributions are positivelyassociated with support for public policies [28]. Peoplewho hold internal causal attributions for health aremore likely to perceive themselves responsible whereasthose who hold external causal attributions of healthproblems are more likely to support societal actionsincluding policy, legislation, and regulation [29, 30].Public beliefs about what causes physical inactivity aswell as who is responsible for addressing physical in-activity likely reflect the physical activity social cli-mate at a population level.A final component of social climate measured in thecurrent study is public support for different policy solu-tions for physical inactivity. Here, policy interventionsvary in their level of intrusiveness [31]. Policies targetingindividual responsibility for behaviors (e.g., media cam-paigns promoting the benefits of physical activity and/orharms of physical inactivity) are less intrusive and lessforceful while modifying community environments (e.g.,quantity and quality of green spaces, safe areas for phys-ical activity, and the design of neighborhoods to encour-age informal physical activity) or economic levelsupports (e.g., providing incentives, subsidies and taxYun et al. BMC Public Health         (2018) 18:1301 Page 2 of 13credits around physical activity) are more intrusive. Pub-lic resistance to policy may cause problems with imple-mentation and adherence, and ultimately result in itswithdrawal from consideration [32]. Conversely, publicsupport for different policy interventions may be a pre-requisite for policy makers in developing and imple-menting those policies. Social climate may thereforeindirectly influence population level physical activitythrough the implementation of more effective policy ap-proaches that have public support.In other health domains, research has included moni-toring beliefs about smoking, perceived harm, social in-fluences, and attitudes to regulations (e.g., InternationalTobacco Control Policy Evaluation Project [33]). Thiswork provided guidance in the development and imple-mentation of policies to reduce tobacco use. Similarly,the body of research assessing aspects of social climatewith regard to obesity has grown in the last decade. Forexample, Raine et al. [17] examined perceptions amongCanadian ‘policy influencers’ of the causes of, responsi-bility for, and levels of support for different policies ad-dressing obesity. They found that most policyinfluencers viewed all risk behaviors as personal respon-sibilities (47.0% for alcohol, 55.5% for obesity, 59.3% fortobacco, 69.1% for physical activity, and 63.1% forhealthy eating), while one-fifth (for healthy eating andphysical activity) to one-third (for obesity, alcohol, andtobacco) viewed the responsibility to be both personaland societal. Most policy influencers indicated theirorganization has at least some responsibility for obesityprevention programs and policies (i.e., approximately70% for encouraging healthy eating and 90% for physicalactivity). Policies with very strong overall support werethose aimed at individual responsibility for behaviors, suchas providing programs to educate the general public andimplementing programs aimed at changing school envi-ronments. However, policies to change the design of work-places and communities to encourage informal physicalactivity and those that affect economic measures and leg-islations received weak overall support [17].Similar results have also been reported among the gen-eral public in the UK, USA, and Germany such that beingoverweight or obese was mainly perceived to be an indi-vidual’s own fault [34–36]. Furthermore, less intrusive pol-icies targeting individuals through school-based programsand campaigns are generally more supported than moreintrusive actions such as restricting unhealthy foods atrestaurants and increasing taxes on the sale of unhealthyfoods. Most recently, both public (38.7%) and health pro-fessionals (32.2%) in Canada viewed obesity as a commu-nity problem of bad food and inactivity followed by apersonal problem stemming from bad choices (31.7% forpublic and 28.7% for health-care professionals [37]). Bha-wra et al. [38] reported that Canadian youth and youngadults strongly supported menu labelling in restaurantsand schools, and food package symbols whereas taxation,zoning restrictions, and bans on marketing to children re-ceived relatively lower levels of support.Past empirical measurement and analysis of social cli-mate has paid less attention to the context of physical(in)activity. We are not aware of studies directly asses-sing the social climate of physical (in)activity beyond thecontext of obesity. Rather, previous research has largelyapplied social cognitive models focused on normativebeliefs and not a broader conceptualization of socialnorms. This study seeks to address this gap. As socialclimate change is often central to public health policyagendas, the purpose of this study was to assess the so-cial climate of physical (in)activity in Canada and toexamine whether the social climate dimensions were re-lated to individuals’ behavior. Such an improved under-standing will allow for the identification of a benchmarkthat can be reassessed over time to determine if socialclimate changes in response to broader policy and pro-grammatic initiatives, or whether changes in the socialclimate precede consideration and implementation ofgreater policy and legislative innovation to facilitate amore active Canada.MethodsSample and recruitmentA total of 2519 participants were recruited from a repre-sentative sample of panelists (Canadian adults ≥18 years)drawn from the Angus Reid Forum. This forum includes100,000 Canadians who have already consented to partici-pating in survey research before joining the panel. Thepanel is comparable with the Canadian census in terms ofage, sex, region, income, employment, and languagespoken. Panelists generally receive a small cash reward($0.50–$3 CAD), after completing a survey. By enrollingas a panelist in the Angus Reid Forum, recruited individ-uals consented to their participation in invited surveys orpanel discussions. Ethical approval was not needed ac-cording to article 2.4 and 5.5 of the Tri-Council policystatement (TCPS2) regarding ethical conduct of humanresearch reporting on secondary analyses of minimal riskand anonymous data [39]. The survey was conducted byPArticipACTION, a Canadian non-profit organizationpromoting physical activity (www.participaction.com) aspart of its ongoing public relations and advocacy work.MeasuresSurvey development procedureThe survey instrument was initially generated drawingon similar questions that have been used to assess thesocial climate regarding obesity and tobacco control [17,40], including the International Tobacco Control Survey(http://www.itcproject.org). The questionnaire aimed toYun et al. BMC Public Health         (2018) 18:1301 Page 3 of 13solicit information regarding the social climate of phys-ical activity in Canada including the perceived serious-ness of physical (in)activity as a public health issue,social norms of physical (in)activity, attributions ofcauses and responsibility in solving physical inactivity,and level of support for physical activity related policies,regulations and programs. Demographics and physicalactivity participation were also assessed. Once drafted,the questionnaire was distributed to members of two ad-visory groups of ParticipACTION to solicit feedback andhelp enhance face and content validity [41]. The ques-tionnaire was piloted online (n = 35) to ensure the ques-tions and language were clear and comprehensible.Test-retest reliability was examined by performing intra-class correlations (ICC) using a two-way random effectsmodel, absolute agreement with a sample of 100 partici-pants. Moderate reliability [42] across all (ICC scores ≥ .70)except for one item (society disapproves of physical inactiv-ity, ICC = .33, 95% CI: 0.02, 0.38) was demonstrated. Thefinal survey is available upon request to the first author.Seriousness of public health issuesThe first section of the survey covered perceived ser-iousness of different health risk behaviors based on asimilar question examining public opinion of obesity[16]. Health issues included physical inactivity, sittingtoo much (sedentary behavior), tobacco use, alcohol mis-use, cannabis use, unhealthy diets, and lack of sleep. Re-spondents were asked to rate perceived seriousness on a7-point scale ranging from “not at all serious (1)” to“very serious (7).”Social normsModified from a previous study [43], three descriptivenorm items were used as follows: “I often see otherpeople walking in my neighborhood”, “I often see otherpeople exercising (e.g., jogging, bicycling, playing sports)in my neighborhood”, and “I often see kids playing ac-tively outdoors (e.g., playing games like tag, sports, rid-ing their bikes) in my neighborhood”. Response optionsfor each item were on a 7-point scale ranging from“strongly disagree (1)” to “strongly agree (7)”. Addition-ally, respondents were asked to estimate the proportionof Canadians their age meeting physical activity guidelineson a scale ranging from “0%” to “100%” within a ten-per-centage interval. One item measured injunctive norms ofphysical activity: “How many people who are important toyou (e.g., friends or family) would you say engage in 150minutes of moderate-to-vigorous physical activity perweek?” This item was rated on a 5-point scale rangingfrom “all of them” to “none of them.” The acceptability ofphysical inactivity was also measured using one item: “So-ciety disapproves of physical inactivity.” Responses on theitem were made on a 7-point scale ranging from “stronglydisagree (1)” to “strongly agree (7)”. All items had the fol-lowing instruction: “Please indicate how much you agreeor disagree with the following statements. In consideringthese questions, think about where you live during thespring or fall seasons.”Perceptions of the causes and responsibility in solvingphysical inactivityItems were based on questions used to assess percep-tions of obesity [17, 36]. Perceptions of the causes of in-activity were assessed on one of the following options ofphysical inactivity as “an individual’s fault”, “caused byother factors beyond an individual’s control”, “both anindividual’s fault and caused by other factors beyond anindividual’s control”, “neither an individual’s fault norcaused by other factors beyond an individual’s control”,and “don’t know”. Responsibility to solve the issue ofphysical inactivity was measured on one of the followingoptions of physical inactivity as “a private matter thatpeople need to deal with on their own”, “a public healthmatter that society needs to solve”, “both a private mat-ter and a public health matter”, “neither a private matternor a public health matter”, and “don’t know.”Support for physical activity-related policySupport for physical activity-related policies, regulationsand programs was assessed to address the following: 1)individual responsibility for behaviors (e.g., providingprograms to educate or motivate the general publicabout the importance of regular physical activity), 2)modifying community environments (e.g., the quantityand quality of green spaces, safe areas for physical activ-ity, and the design of neighborhoods to encourage infor-mal physical activity), 3) targeting legislative changes tomodify the environment (e.g., banning all traffic inhigh-use pedestrian areas during peak hours to supportactive or public transportation and restricting the use ofelevators for trips to lower floors), 4) focusing on eco-nomic levers (e.g., incentives, subsidies, and tax credits).Each of the items was measured on a 7-point scale ran-ging from “strongly oppose (1)” to “strongly support(7)”. Items were initially generated using those reportedby Raine et al. [17] and supplemented with five itemsgenerated through feedback from the consultations withthe advisory groups.Physical activity participationThe Physical Activity for Adults Questionnaire (PAAQ)was administered to measure respondents’ physical ac-tivity participation [44]. The PAAQ captures total timespent doing moderate to vigorous-intensity physical ac-tivity (MVPA) in three domains: transportation, leisuretime, and ‘other’ including work, home and volunteering.Respondents were asked to report activities that lastedYun et al. BMC Public Health         (2018) 18:1301 Page 4 of 13at least 10 consecutive minutes. Once completed, a totalamount of MVPA in the last 7 days was calculated. Pre-vious research has supported the validity of the PAAQ[44]).DemographicsRespondents reported sex, age, dwelling (urban,semi-urban, rural), and household income level (in in-crements from <$35,000 to > $125,000, don’t want toreport).Data collection proceduresThe survey was deployed online in French and Englishon January 15, 2018 and remained open for 7 days. Par-ticipants were sent an email with a link to the survey,with a follow-up reminder email being re-sent 2 days be-fore the survey closed. The survey required approxi-mately 15–20 min to complete. Once closed, all datawere cleaned, de-identified, and tabulated into an SPSS(IBM, New York, USA).Data analyses proceduresDescriptive statistics are reported as frequencies and per-centages. Multinomial logistic regressions were constructedto assess the associations of sociodemographic factors withsocial climate dimensions. Sex (female, male), age, house-hold income level (< $35,000, ≤$35,000 to <$75,000,≤$75,000 to <$125,000, and $125,000 ≤), dwelling (urban,semi-urban, rural), and meeting the Canadian physical ac-tivity guidelines (achieving 150mins/week MVPA or not)served as predictors. For ease of interpretation, responsesto the Likert scales for the seriousness of physical inactiv-ity, response of social norms of physical activity and policysupport questions were collapsed and recoded tothree-level outcome variables (e.g., “strongly and moder-ately disagree” vs. “slightly disagree, neutral, and slightlyagree” vs. “moderately and strongly agree”). This codingmethod was modified from a previous study [45]. Percep-tions of the causes of physical inactivity were recoded to“individual cause”, “societal cause”, and “both individualand societal cause”. Perceptions of responsibility for solv-ing physical inactivity were recoded to “private matter”,“public health matter”, and “both private and public healthmatter”. A linear regression was conducted to assess therelationship between socio-demographic factors and theperception of the proportion of Canadians their age meet-ing the guidelines. Statistical analyses were conductedusing SPSS version 24 and all statistical inferences werebased on an alpha of p < 0.01.ResultsThe sociodemographic characteristics of the respondentsare described in Table 1. The sample was well distributedin terms of sex (male = 50.3%), age (mean = 49.06 ±16.28 years, range 18–92), income (< $35,000 = 16.2%, ≤$35,000 to <$75,000 = 28.5%, ≤ $75,000 to < $125,000 =25%, > $125,000 = 13.1%, no response = 17.1%), and dwell-ing setting (urban = 54.1%, semi-urban = 26.5%, rural =19.4%). Among the total sample of the respondents, only404 (16.0%) reported engaging in a minimum of 150 minof MVPA per week and were categorized as the ‘active’group.The respondents rated “not enough physical activity”(55.1% reported very or moderately serious) as serious as“unhealthy diets” (57.7%) and “tobacco use” (56.8%). “Al-cohol misuse” (50.3%) was also rated fairly seriousfollowed by “lack of sleep” (41.4%) and “sitting toomuch” (38.7%). “Cannabis use” was rated the least ser-ious issue (33.3%).Sex, income, and active group membership were asso-ciated with perceived seriousness of physical inactivity(see Table 2). Specifically, respondents who were femalewere more likely to report greater seriousness (vs. notserious) and individuals of higher income and who werephysically active were more likely to report greaterTable 1 Sociodemographic characteristics of participants (N= 2519)Frequency PercentageSexFemale 1253 49.7Male 1266 50.3Age group (years)18–29 356 14.130–39 468 18.640–49 432 17.150–59 516 20.560–69 425 16.970 and above 322 12.8Income level (Canadian dollars)< $35,000 407 16.2$35,000 to <$75,000 719 28.5$75,000 to <$125,000 630 25.0$125,000< 331 13.1Don’t want to report 432 17.1Dwelling settingUrban 1363 54.1Semi urban 668 26.5Rural 488 19.4Active groupInactive 1822 72.3Active 404 16.0Total 2226 88.4Missing 293 11.6Yun et al. BMC Public Health         (2018) 18:1301 Page 5 of 13seriousness (vs. neutral) of physical inactivity comparedto their counterparts.The majority of the sample agreed that they often seeother people walking in the neighborhood (N = 1406,55.8%), while less than half of the respondents agreedthat they often see other people exercising in the neigh-borhood (N = 989, 39.3%). Only a quarter of the sampleagreed that they often see children playing actively out-doors in the neighborhood (N = 647, 25.6%). In general,older adults, those living in urban or semi-urban set-tings, and individuals meeting physical activity guidelineshad higher odds of reporting seeing people walking orexercising, or kids playing actively outdoors in theirneighborhood (see Table 3).A minority (N = 706, 28%) of the respondents be-lieved that society disapproves of physical inactivity.Older respondents and those living in semi-urban set-tings were more likely to agree with the statement thatsociety disapproves of physical inactivity (see Table 3).Overall, participants perceived that 35% of Canadianstheir age met physical activity guidelines. Participantswho were younger (β = − 0.19, p < .001, η2 = 0.07), hadlower income (β = − 0.08, p < .01, η2 = 0.04), or were ac-tive (β = 0.07, p < .01, η2 = 0.02) reported a higher per-centage of Canadians their age to be meeting theguidelines.In terms of injunctive norms, 2.5% of the respondentsreported all, and 10.8% of the respondents (total 13.3%)reported most, people important to them engage in150 min of MVPA per week (i.e., meet the guidelines).Physical activity participation was the only predictor ofinjunctive norms such that active participants had higherodds of reporting more people important to them en-gaging in physical activity compared to those in the in-active group (see Table 3).The majority of respondents endorsed physical inactiv-ity as both an individual and societal responsibility (N =1578, 62.5%), followed by only an individual’s fault (N =711, 28.2%), only societal responsibility (N = 129, 5.1%),don’t know (N = 52, 2.1%), and neither an individual norsocietal responsibility (N = 49, 1.9%). Similarly, most re-spondents (N = 1678, 66.6%) viewed physical inactivity asboth a private and public health matter, while 20.5% (N= 517) of the respondents responded that physical in-activity is a private matter that people need to deal withon their own. Only a small number of respondentsviewed physical inactivity as a public health matter (N =237, 9.4%), neither a private nor a public health matter(N = 29, 1.2%), and don’t know (N = 58, 2.3%). Respon-dents who were older, had higher income, or were active,showed higher odds of attributing physical inactivity toindividual than to societal causes and endorsed physicalinactivity more as a private matter than as a publichealth matter or both a private and a public health mat-ter (see Table 4).Table 5 describes the response rates of strong andmoderate support for different policy approaches. The find-ings indicate overall strong support for individual-level pol-icies, such as providing programs to educators (65.4%) andthe general public (55.6%), and creating and sharing phys-ical activity guidelines (52.6%). However, fewer respondentsindicated strong or moderate support for funding mediacampaigns to educate the public (39.1% of total support).Policies to change community environments [i.e., improveuniversal accessibility (67.3%), providing more green spaces(67.1%), implementing transportation policies designed topromote physical activity through safe routes (55.8%), andchanging the design of neighborhoods (55%)], as well aspolicies focusing on economic levers [i.e., providing incen-tives (63.9%), subsidies (57.7%), tax credits (56%) for phys-ical activity participation and removing sales taxes on allphysical activity equipment (56.7%)] were both well sup-ported across all policy actions. However, legislative policiesTable 2 Likelihood of support for perceptions of seriousnessand social norms of physical (in)activitySeriousness of physical (in)activityB (SE) OR (95% CI)Not seriousbIntercept −1.16(0.83)Age −0.02 (.01) 0.98 (0.96–1.00)Income −0.36 (0.17) 0.70 (0.50–0.99)Sex (female) −1.39 (0.39) 0.25 (0.12–0.54)**Sex (male) ReferenceDwelling (urban) − 0.43 (0.47) 0.65 (0.26–1.63)Dwelling (semi-urban) 0.45 (0.47) 1.57(0.63–3.92)Dwelling (rural) ReferencePAa (inactive) 0.49 (0.46) 1.63 (0.66–3.98)PAa (active) ReferenceNeutralbIntercept 0.09 (0.25)Age −0.001 (0.003) 1.00 (0.99–1.00)Income −0.18 (0.05) 0.83 (0.75–0.92)**Sex (female) −0.22 (0.10) 0.80 (0.66–0.97)Sex (male) ReferenceDwelling (urban) −0.08 (0.13) 0.93 (0.72–1.19)Dwelling (semi-urban) −0.12 (0.14) 0.89 (0.67–1.18)Dwelling (rural) ReferencePAa (inactive) 0.42 (0.13) 1.53 (1.19–1.96)*PAa (active) ReferenceR2 (Nagelkerke) .035* p < .01, ** p < .001aThose who do (vs. do not) achieve 150 min of moderate-to-vigorous physicalactivity a weekbThe reference category is: seriousYun et al. BMC Public Health         (2018) 18:1301 Page 6 of 13Table3Likelihoodofsupportforsocialnormsofphysical(in)activityDescriptivenormsSocietydisapprovesofinactivityInjunctivenormsofphysicalactivityWalkingExercisingKidsactiveB(SE)OR(CI)B(SE)OR(CI)B(SE)OR(CI)B(SE)OR(CI)B(SE)OR(CI)DisagreebNonecIntercept0.11(0.47)0.22(0.40)0.12(0.34)−0.00(0.37)−1.11(0.57)Age−0.02(0.01)0.99(0.97–1.00)−0.01(0.01)0.99(0.98–1.00)0.003(0.004)1.00(1.00–1.01)−0.001(0.00)0.10(0.99–1.01)0.002(0.01)1.00(0.99–1.02)Income−0.16(0.10)0.19(0.70–1.04)−0.16(0.08)0.85(0.72–1.00)−0.03(0.07)0.97(0.85–1.11)0.08(0.07)1.08(0.93–1.25)−0.17(0.11)0.84(0.68–1.06)Sex(female)−0.41(0.19)0.66(0.45–0.97)−0.18(0.16)0.84(0.61–1.15)−0.05(0.13)0.95(0.74–1.23)−0.37(0.15)0.69(0.52–0.91)0.09(0.22)1.09(0.71–1.68)Sex(male)ReferenceReferenceReferenceReferenceReferenceDwelling(urban)−1.21(0.23)0.30(0.19–0.47)**−0.85(0.20)0.43(0.29–0.63)**−0.42(0.17)0.66(0.47–0.92)−0.43(0.18)0.65(0.46–0.92)−0.24(0.28)0.78(0.45–1.36)Dwelling(semi-urban)−0.76(0.25)0.47(0.29–0.76)*−0.70(0.23)0.50(0.32–0.78)*−0.59(0.20)0.55(0.38–0.82)*−0.84(0.23)0.43(0.28–0.67)**0.29(0.32)1.34(0.72–2.51)Dwelling(rural)ReferenceReferenceReferenceReferenceReferencePAa(inactive)−0.18(0.23)0.84(0.53–1.31)0.03(0.20)1.03(0.70–1.51)0.14(0.16)1.15(0.84–1.58)0.07(0.18)1.08(0.76–1.53)1.03(0.30)2.79(1.54–5.05)*PAa(active)ReferenceReferenceReferenceReferenceReferenceNeutralbAfew/somecIntercept0.53(0.27)0.81(0.27)0.95(0.30)1.31(0.29)1.04(0.35)Age−0.02(0.003)0.98(0.98–0.99)**−0.01(0.003)0.99(0.98–0.99)**−0.01(0.004)0.99(0.98–1.00)−0.01(0.00)0.99(0.98–0.99)**0.00(0.00)1.00(0.99–1.01)Income−0.01(0.05)0.99(0.89–1.10)−0.04(0.05)0.97(0.87–1.07)−0.01(0.06)0.99(0.88–1.11)0.02(0.06)1.02(0.91–1.14)0.05(0.07)1.05(0.92–1.21)Sex(female)−0.24(0.10)0.79(0.64–0.96)−0.22(0.10)0.80(0.66–0.98)−0.11(0.12)0.90(0.72–1.12)−0.20(0.11)0.82(0.66–1.02)0.14(0.14)1.15(0.87–1.51)Sex(male)ReferenceReferenceReferenceReferenceReferenceDwelling(urban)−0.30(0.14)0.74(0.57–0.96)−0.30(0.14)0.74(0.57–0.97)−0.30(0.16)0.74(0.54–1.00)−0.26(0.15)0.77(0.58–1.04)−0.08(0.18)0.93(0.65–1.32)Dwelling(semi-urban)−0.21(0.15)0.81(0.60–1.09)−0.17(0.15)0.84(0.62–1.14)−0.30(0.18)0.75(0.53–1.05)0.10(0.17)1.10(0.79–1.54)0.24(0.22)1.27(0.83–1.94)Dwelling(rural)ReferenceReferenceReferenceReferenceReferencePAa(inactive)0.18(0.13)1.20(0.92–1.56)0.43(0.13)1.54(1.19–1.99)*0.43(0.14)1.54(1.16–2.05)*0.22(0.14)1.24(0.94–1.64)0.64(0.16)1.90(1.39–2.58)**PAa(active)ReferenceReferenceReferenceReferenceReferenceR2(Nagelkerke).*p<.01,**p<.001a Thosewhodo(vs.donot)achieve150minofmoderate-to-vigorousphysicalactivityaweekbThereferencecategoryis:agreec Thereferencecategory:mostpeopleYun et al. BMC Public Health         (2018) 18:1301 Page 7 of 13targeting community infrastructure and facilities re-ceived the weakest support such that only 14% of therespondents “strongly supported” banning all traffic inhigh-use pedestrian areas during peak hours andrestricting the use of elevators for trips three floorsor less (14%).Female respondents demonstrated higher likelihood ofsupporting individual, community environment, andeconomic level policy although no difference was foundin legislative policy support by sex (see Table 6). The as-sociations between respondents’ age and the level of sup-port varied by different policy domains such that olderrespondents were more likely to support individual levelpolicy approaches, while younger respondents weremore likely to support economic approaches. Incomealso predicted different policy actions: the lower incomegroup was more likely to support legislative policy thanthe higher income group; however, no differences wereseen in all other policy categories. Finally, active respon-dents were more likely to support individual andlegislative policy, but not economic and community en-vironment policy support.DiscussionThe current study assessed the social climate of physical(in)activity in Canada and to the best of our knowledge,represents the first focused evaluation of a range of indi-cators that potentially reflect this construct. As an initialbenchmark, interpreting the findings remains speculativeuntil longitudinal tracking is completed to identifywhether social climate changes over time. One positivefinding is that Canadians perceive physical inactivity as aserious public health issue comparable to tobacco useand unhealthy diets. Perhaps reflecting the impendinglegalization of cannabis in Canada and fewer campaignshighlighting potential health risks [46, 47], cannabis usewas rated as the least serious public health issue. In con-trast, descriptive norms regarding physical activity couldbe considered low. This identifies room for improve-ment over time that may be tracked concurrent withTable 4 Likelihood of support for perceptions of causes and solutions of physical inactivityCause of inactivity Solution of inactivityB (SE) OR (95% CI) B (SE) OR (95% CI)DisagreebIntercept −0.16 (0.58) −0.16 (0.58)Age −0.02 (0.01) 0.98 (0.97–1.00) −0.02 (0.01) 0.98 (0.97–1.00)Income −0.48 (0.12) 0.62 (0.49–0.79)** −0.48 (0.12) 0.62 (0.49–0.79)**Sex (female) −0.20 (0.24) 0.82 (0.51–1.32) −0.20 (0.24) 0.82 (0.51–1.32)Sex (male) Reference ReferenceDwelling (urban) 0.32 (0.30) 1.38 (0.76–2.48) 0.32 (0.30) 1.38 (0.76–2.48)Dwelling (semi-urban) −0.30 (0.39) 0.74 (0.34–1.60) − 0.30 (0.39) 0.74 (0.34–1.60)Dwelling (rural) Reference ReferencePAa (inactive) 0.40 (0.31) 1.49 (0.82–2.71) 0.40 (0.31) 1.49 (0.82–2.71)PAa (active) Reference ReferenceNeutralbIntercept 0.76 (0.28) 0.76 (0.28)Age −0.01 (0.00) 0.99 (0.99–1.00) −0.01 (0.00) 0.99 (0.99–1.00)Income −0.17 (0.06) 0.85 (0.76–0.94)* −0.17 (0.06) 0.85 (0.76–0.94)*Sex (female) 0.39 (0.11) 1.48 (1.19–1.83)** 0.39 (0.11) 1.48 (1.19–1.83)**Sex (male) Reference ReferenceDwelling (urban) 0.27 (0.14) 1.31 (1.00–1.71) 0.27 (0.14) 1.31 (1.00–1.71)Dwelling (semi-urban) 0.41 (0.16) 1.50 (1.10–2.05) 0.41 (0.16) 1.50 (1.10–2.05)Dwelling (rural) Reference ReferencePAa (inactive) 0.36 (0.13) 1.44 (1.11–1.86)* 0.36 (0.13) 1.44 (1.11–1.86)*PAa (active) Reference ReferenceR2 (Nagelkerke) .047 .047* p < .01, ** p < .001aThose who do (vs. do not) achieve 150 min of moderate-to-vigorous physical activity a weekbThe reference category is: agreeYun et al. BMC Public Health         (2018) 18:1301 Page 8 of 13changes in physical activity at a population level result-ing from the implementation of new policies, programsor broader geopolitical events including climate change.Complementary to using social climate as an indicatorof changes at the population-level, is the future consid-eration of interventions targeting these social climate in-dicators. From the social norms perspective [21, 22],individuals may be more likely to participate in physicalactivity when they believe society or people important tothem expect them to do so [23, 48]. There has been on-going efforts to change social norms regarding physicalactivity through community-wide media campaigns (e.g.,ParticipACTION’s campaigns in Canada [49], VERB inthe USA [50], ACTIVE for LIFE in England [51]). Mediacampaigns have been proposed as a potential influencerof physical activity of the whole population by reframingthe salience of social norms around the behavior intocampaign messages [52]. Yet, the effectiveness of suchTable 5 Level of support for policy approaches to promote physical activityCategory Policy support StronglysupportModeratelysupportTotal level ofsupportIndividual Increase training of educators and school support staff to deliverquality physical activity programming867 781 164834.4% 31% 65.4%Provide programs to educate, inspire, support, or motivate thegeneral public about the importance of regular physical activity677 723 140026.9% 28.7% 55.6%Create and share guidelines for adults that provide guidance onphysical activity, sedentary behavior and sleep569 756 132522.6% 30% 52.6%Fund media campaigns to educate the public about increasingphysical activity and reducing screen time410 574 98416.3% 22.8% 39.1%Environment (school/community)Provide mandatory daily physical education or physical activityrequirements in all schools1332 568 190052.9% 22.5% 75.4%Improve universal accessibility (e.g., wheelchair access) of recreationfacilities to enable participation among all ability groups1066 630 169642.3% 25% 67.3%Enhance the quantity and quality of green spaces in allneighbourhoods1011 680 169140.1% 27% 67.1%Implement transportation policies designed to promote physicalactivity through safe routes, cycle facilities, adequate lighting, etc.758 647 140530.1% 25.7% 55.8%Change the design of our neighbourhoods and communities toencourage informal physical activity in daily life713 672 138528.3% 26.7% 55%Provide support to guarantee safe and supported play areas inurban environments (e.g., security/chaperone at an urbanbasketball court).656 700 135626% 27.8% 53.8%Environment (legislative) Redirect government funding for high performance sport (e.g.,Olympians) to recreational sport371 516 88714.7% 20.5% 35.2%Ban all traffic in high-use pedestrian areas during peak hours tosupport active (walking, cycling) or public transportation347 424 77113.8% 16.8% 30.6%Restrict the use of elevators for trips three floors or less (e.g.exceptions include use by individuals with disabilities, personswith baby strollers)351 414 76513.9% 16.4% 30.4%Economics Provide incentives for workplaces to develop physical activitypolicies and access to physical activity facilities for workers892 717 160935.4% 28.5% 63.9%Subsidize programs that encourage people to be physically active 762 691 145330.3% 27.4% 57.7%Remove sales taxes on all physical activity equipment 854 575 142933.9% 22.8% 56.7%Provide tax credits or monetary incentives for people who areinvolved in physical activity839 571 141033.3% 22.7% 56%Yun et al. BMC Public Health         (2018) 18:1301 Page 9 of 13Table6Oddsofsupport(95%confidenceinterval)forperceptionsofcausesandsolutionsofphysicalinactivityIndividualCommunityEconomicLegislativeB(SE)OR(CI)B(SE)OR(CI)B(SE)OR(CI)B(SE)OR(CI)Disagree6Intercept−1.41(0.71−4.72(1.20)−4.80(0.81)−1.16(0.42)Age−0.02(0.01)0.98(0.96–1.00)−0.003(0.01)1.00(0.97–1.02)0.03(0.01)1.03(1.01–1.05)*0.004(0.01)1.00(0.99–1.01)Income0.02(0.14)1.02(0.77–1.34)0.49(0.22)1.63(1.07–2.48)0.37(0.15)1.44(1.07–1.94)0.24(0.08)1.27(1.07–1.49)*Sex(female)−0.51(0.28)0.60(0.35–1.04)−1.23(0.47)0.29(0.12–0.74)*−0.64(0.30)0.53(0.30–0.95)0.14(0.17)1.15(0.83–1.59)Sex(male)ReferenceReferenceReferenceReferenceDwelling(urban)−0.53(0.35)0.59(0.30–1.16)0.77(0.76)2.17(−.49–9.58)−0.40(0.34)0.67(0.34–1.32)0.19(0.22)1.21(0.78–1.86)Dwelling(semi-urban)−0.32(0.39)0.73(0.34–1.55)1.08(0.79)2.94(0.62–13.87)−0.24(0.40)0.79(0.36–1.71)0.18(0.25)1.20(0.74–1.95)Dwelling(rural)ReferenceReferenceReferenceReferencePAa(inactive)0.61(0.39)1.84(0.85–3.98)−0.32(0.45)0.73(0.30–1.77)0.26(0.38)1.30(0.62–2.72)0.29(0.20)1.33(0.90–1.96)PAa(active)ReferenceReferenceReferenceReferenceNeutralbIntercept0.85(0.26)0.32(0.25)−0.24(0.25)0.68Age−0.01(0.00)0.99(0.98–1.00)**0.00(0.45)1.00(0.99–1.00)0.01(0.00)1.01(1.00–1.01)*−0.001(0.00)1.00(0.99–1.01)Income0.04(0.05)1.04(0.94–1.15)0.05(0.05)1.00(0.91–1.10)−0.06(0.05)0.94(0.85–1.04)0.17(0.07)1.18(1.04–1.35)Sex(female)−0.31(0.10)0.73(0.60–0.89)*−0.40(0.10)0.62(0.52–0.75)**−0.39(0.10)0.68(0.56–0.82)**0.08(0.13)1.09(0.84–1.41)Sex(male)ReferenceReferenceReferenceReferenceDwelling(urban)−0.22(0.13)0.80(0.62–1.03)−0.42(0.13)0.75(0.59–0.96)−0.05(0.13)0.95(0.74–1.22)−0.08(0.17)0.92(0.66–1.29)Dwelling(semi-urban)−0.21(0.15)0.81(0.61–1.09)−0.25(0.14)0.81(0.61–1.07)0.05(0.15)1.05(0.79–1.39)−0.10(0.20)0.91(0.62–1.33)Dwelling(rural)ReferenceReferenceReferenceReferencePAa(inactive)0.36(0.13)1.44(1.12–1.83)*0.15(0.12)1.17(0.92–1.50)0.29(0.13)1.34(1.05–1.71)0.50(0.16)1.64(1.21–2.23)*PAa(active)ReferenceReferenceReferenceReferenceR2(Nagelkerke).*p<.01,**p<.001a Thosewhodo(vs.donot)achieve150minofmoderate-to-vigorousphysicalactivityaweekbThereferencecategoryis:agreeYun et al. BMC Public Health         (2018) 18:1301 Page 10 of 13campaigns is likely to be modest without increases in ac-cess and opportunities to be physically active. Ironically,support for media campaigns in our study was relativelyweaker compared to other policy options and this mayreflect broader acknowledgement of the limits of educa-tion only approaches to physical activity promotion.The majority of participants viewed physical inactivityas a result of both personal and societal factors and thatboth private and public health approaches are needed tosolve the inactivity problem. This indicates the importanceof emerging social ecological approaches for interventionsto concurrently tackle individual- as well as societal-levelinfluencers of physical activity. This contrasts with aprevious finding that the majority of Canadian policyinfluencers perceived physical activity to be a personal re-sponsibility [17]. It may be that the differences are due tothe target behavior – physical inactivity in the presentstudy and physical activity in the previous study [17]. Pub-lic health policy support depends on public attribution onthe problem [9, 30]. Decreases in internal attributions andincreases in external attributions of physical inactivity re-vealed in the present study may reflect a shift in Cana-dians’ views on accepting societal support and policyinterventions for addressing physical inactivity.Though most policy actions to promote physical activ-ity were well supported by the respondents, the level ofsupport varied by the type of policy actions. Policiestargeting individual responsibility for behaviors, modify-ing the environment including the built environmentand school settings, and targeting economic levers werehighly supported whereas legislative actions were muchless supported. This is consistent with the previous re-search that public support for policy interventions gen-erally tends to decrease as their level of “intrusiveness”or “force” increases [31]. However, such tendency canalso be different by the target behavior (e.g., intrusive in-terventions for tobacco control being more supportedthan those for addressing unhealthy diet and physical in-activity) [31].A normative approach to reducing tobacco use was asuccessful example of changes in public perception thattobacco use is neither mainstream nor socially acceptable,helping to reduce smoking prevalence [12]. Compared tounhealthy diet and physical inactivity, a high level ofawareness exists regarding the harm from tobacco and theeffects of second- and third-hand smoke; this likely led togreater public acceptance of intrusive regulations restrict-ing tobacco use. Or, it could be that public acceptability ofrestrictions on smoking is increased once these restrictivepolicies are introduced [53, 54]. A longitudinal assessmentof changes in the social climate of physical activity includ-ing different policy approaches will be needed to guidepopulation-level physical activity interventions. However,without a similar side-effect and public health concern asenvironmental tobacco smoke, there may be limits to howmuch the social climate for physical (in)activity can bemodified.The present research is the first attempt to assess socialclimate using a large representative sample of Canadiansand it addresses an important gap in knowledge neededfor advocating for, and implementing population-levelphysical activity interventions. The measures utilized inthe present study generally demonstrated strongtest-retest reliability. One measure assessing social accept-ability of physical inactivity did not. It may be speculatedthat the double negative nature of the statement may havecaused confusion in its interpretation. In addition, it maynot measure social climate but another construct –stigmatization [55] – whether people who are physicallyinactive are socially devalued and negatively appraised ifthey do not meet society’s normative expectations.Suggesting some evidence of construct validity, the so-cial climate indicators were associated with other demo-graphic variables in directions that could be hypothesized.The associations of sex and age with social climate areconsistent with previous research in that being female andolder age were positively associated with higher supportfor all alcohol policy approaches [32] and obesity preven-tion policies [36, 56, 57]. Where people live was also dif-ferentially associated with social norms: urban andsemi-urban residents were more likely to report seeingpeople walking, exercising, and kids being active outdoorsin their neighborhood compared to those living in ruralsettings. Importantly, respondents’ level of physical activ-ity participation predicted most of the social climate di-mensions. People who met the Canadian physical activityguidelines perceived physical inactivity more seriously as ahealth problem than those who did not meet the guide-lines. Active respondents perceived higher social norms ofphysical activity and their level of policy support washigher than inactive respondents. Our findings are con-sistent with other research such that public support forpolicies addressing health issues is associated with behav-ior. For example, those who exercised regularly are morelikely to support obesity policy [16] and heavy drinkerswere less likely than non-drinkers and ex-drinkers to besupportive of all alcohol policies, especially restrictive ac-tions that limited their own access to alcohol [32]. Overall,the social climate of physical activity was predicted by re-spondents’ demographics and behavioral factors includingphysical activity participation.Despite the noted strengths of the present study, it isnot without limitations. Due to the cross-sectional de-sign of the research, causal relationships cannot be in-ferred, and generalizability cannot be assumed. Giventhe self-report nature of the study, there is also the pos-sibility of social-desirability bias. For example, given thechoices of the cause of the solutions for physicalYun et al. BMC Public Health         (2018) 18:1301 Page 11 of 13inactivity, the most socially desirable choice is one whereeveryone is partly to blame (i.e., both individual and so-ciety), which was the most common response. In the fu-ture, using a forced choice without hybrid choices or atleast a measure that presents a continuum score for re-spondents is recommended to attenuate social desirabil-ity bias. The physical activity assessment itself is likely asource of bias, although in comparison to otherself-report tools, there is evidence of satisfactory criter-ion validity [44]. As the survey was administered in win-ter there is a possibility that the responses reflectseasonal effects even though respondents were asked toconsider their answers based on spring or fall seasons.Finally, although our focus was on physical (in)activity,understanding the social climate of physical (in)activityis less clear without the simultaneous and comparativemeasurement of social climate for other health behaviorssuch as alcohol use or healthy diets. Such comparisonswould be beneficial and suggest a possible need for fur-ther measurement development in comparing and con-trasting the social climate of different chronic diseaserisk factors.ConclusionThe outcome of the current assessment provides a base-line for tracking the impact of future system-level inter-ventions on social climate in Canada as it pertains tophysical (in)activity. When “being active needs to be theCanadian norm, not the exception” [58] then surveil-lance mechanisms are needed to track progress towardthis goal. Our study addresses this measurement gapand provides a snapshot of the social climate in Canadain 2018. There are some promising findings in the ac-knowledgement of physical inactivity as a serious publichealth issue and attributions for physical inactivity thatgo beyond individual blame. This in turn forecasts pub-lic acceptability for innovative policy intervention to ad-dress the problem. In contrast, descriptive andinjunctive norms for exercise and physical activity werelow. Future tracking is needed to identify any temporal(in)stability of these constructs over time and explorethe likely bidirectional relationship between physical ac-tivity participation and its related social climate.AbbreviationsMVPA: Moderate to vigorous-intensity physical activity; PA: Physical activity;PAAQ: Physical activity for adults questionnaireAcknowledgementsData collection, tabulation, and cleaning was provided in-kind by Maru/Matchbox.FundingGF receives support through a Canadian Institutes of Health Research-PublicHealth Agency of Canada (CIHR-PHAC) Chair in Applied Public Health. ALCand TB receive support from the Canada Research Chairs Program. LV holdsa CIHR Research Fellowship. LY is supported by a MITACS Accelerate award.These funding bodies had no role in the design of the study and collection,analysis, and interpretation of data, and in writing the manuscript.Availability of data and materialsThe datasets used and/or analyzed during the current study are availablefrom the corresponding author on reasonable request.Authors’ contributionsGF oversaw the whole research process as the supervisory author. LYperformed data analysis and prepared the original manuscript. TRB, AEL-C,MST, JCS, RER, NOR provided input for the development of the survey, com-mented on the research method and contributed to manuscript edits. LVmanaged the data collection process and contributed to manuscript edits.All authors read and approved final manuscript.Ethics approval and consent to participateParticipants of this study were recruited from a representative sample ofpanelists drawn from the Angus Reid Forum. By enrolling as a panelist in theAngus Reid Forum, recruited individuals consented to their participation ininvited surveys or panel discussions. Ethical approval was not needed accordingto article 2.4 and 5.5 of the Tri-Council policy statement regarding ethical con-duct of human research reporting on secondary analyses of minimal risk andanonymous data. The survey was conducted by ParticipACTION, a Canadiannon-profit organization promoting physical activity (www.participaction.com),as part of its ongoing public relations and advocacy work.Consent for publicationNot applicable.Competing interestsGF, TB, AL, MT, JS, RR, and NO are members of ParticipACTION’s volunteer-based Research Advisory Group, and LV works as ParticipACTION’s Know-ledge Translation Manager. No financial or promotional advantages weregained from conducting this study. The authors have no other conflict ofinterest to declare.Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.Author details1School of Kinesiology, University of British Columbia, Lower Mall ResearchStation 337, 2259 Lower Mall, Vancouver, British Columbia V6T 1Z4, Canada.2ParticipACTION, Toronto, ON, Canada. 3Faculty of Kinesiology, Sport, andRecreation, University of Alberta, Edmonton, AB, Canada. 4School ofKinesiology and Health Studies, Queens University, Kingston, ON, Canada.5College of Business and Economics, University of Guelph, Guelph, ON,Canada. 6School of Exercise Science, University of Victoria, Victoria, BC,Canada. 7Healthy Active Living and Obesity Research Group, Children’sHospital of Eastern Ontario Research Institute, Ottawa, ON, Canada.Received: 30 May 2018 Accepted: 30 October 2018References1. Ng SW, Popkin BM. Time use and physical activity: a shift away frommovement across the globe. 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