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Journal of Public Health Advance Access originally published online on June 10, 2008
Journal of Public Health 2008 30(3):274-281; doi:10.1093/pubmed/fdn041
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© The Author 2008, Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved

Association of perceived environment with meeting public health recommendations for physical activity in seven European countries



Anchya Bamana, M.Sc., Masters Student

Sabrina Tessier, Ph.D., Research Assistant

Anne Vuillemin, Ph.D., Assistant Professor
EA 4003, Nancy-Université, Ecole de Santé Publique, Faculté de Médecine, 9 avenue de la Forêt de Haye, BP 184, 54500 Vandoeuvre-Les-Nancy, France

Address correspondence to Anne Vuillemin, E-mail: anne.vuillemin{at}staps.uhp-nancy.fr and anne.vuillemin{at}medecine.uhp-nancy.fr

Background This study investigates the association of perceived environment and meeting the current public health recommendations (PHRs) for physical activity (PA) and examines the role of body mass index (BMI) in this relation.

Methods A total of 4231 subjects (≥18 years), from seven European countries, were involved in a cross-sectional survey. PA was measured by the International PA Questionnaire, and specific questions about perceived environment for PA were added.

Results Adults with high personal motivation were more likely to meet PHRs for PA than those without motivation (odds ratio [OR] 1.79; 95% confidence interval [CI] 1.50–2.14). Participants perceiving high social support from work or school were more likely to meet PHRs for PA than those without this support (OR 1.60; 95% CI 1.30–2.00). Likewise, those with perceived opportunities for PA were more likely to meet PHRs than those without this perception (OR 1.23; 95% CI 1.02–1.50). BMI had no effect on meeting PHRs for PA.

Conclusion The study shows a relation between personal motivation and some aspects of social and physical environment in meeting current PHRs for PA. Future research involving an objective environment to meet PHRs for PA should be undertaken to validate these findings.

Keywords: body mass index, perceived environment, physical activity recommendations


   Introduction
TOP
 Introduction
Methods
 Results
 Factors associated with meeting...
 Discussion
 Funding
 Acknowledgments
 References
 
Physical activity (PA) determinants have received increasing attention in recent years.1 Indeed, regular PA is well known to be beneficial for health and well being.2,3 Thus, identifying the correlates of participation in PA is the first step in understanding the factors that influence meeting current public health recommendations (PHRs) for PA across populations.4 Among the main factors related to the overall PA levels are well-documented intrapersonal characteristics such as sex, age, socioeconomic status, educational level, attitudes and beliefs.1 Likewise, interpersonal resources such as social environment (family, friends, school and workplace) can provide sources of role models encouragement to practice PA.5 On the wider scale, the community and environmental resources may have a significant impact in creating a physical environment for promoting PA. In some studies, the built environment was shown to encourage active transportation such as walking and cycling and so increase adherence to PHRs for PA.6,7 Other studies showed that the environment can present important barriers to participation in PA, including a lack of bicycle trails and walking paths away from traffic, inclement weather and unsafe neighbourhoods.8,9 Finally, public policy that places an emphasis on PA of the whole population seems to be related to better opportunities for PA.10

Recently, environmental influences of PA have received considerable interest in Europe.11–13 The environment can be seen as the extent to which incentives or restrictions make health behaviour easier or less easy. Incentive environments provide the best access to facilities for PA; examples are sport fields, bicycle paths and swimming pools. Restricted environments constrain access or provide attractive sedentary environments, as in sedentary games rooms and many office-based workplaces.14 These environments can be objectively measured by the use of geographic information systems technology, as has been shown in several studies,15,16 or can be self-reported by subjects.11,12,17 Measuring the subject's perceived environment is important to ensure that subjects are aware of opportunities for PA in the area where they live.

Before implementing policies to promote PA across the population, the following question, which remains insufficiently explored in Europe, must be answered: is the perceived environment associated with meeting the current PHRs for PA? At present, several studies are interested in the relation between the perceived environment and PA, but a limited number have assessed the association of environmental factors and meeting the current PHRs for PA.18 To our knowledge, no studies have been conducted in several European countries. Moreover, body mass index (BMI) has emerged as a consistent negative influence on PA.19

In this context, we aimed to (i) investigate the association of perceived environment and meeting current PHRs for PA and (ii) examine the role of BMI in this relation.


   Methods
TOP
 Introduction
 Methods
Results
 Factors associated with meeting...
 Discussion
 Funding
 Acknowledgments
 References
 
Procedure and sample
This study involved the use of data from the European PA Surveillance System (EUPASS) survey conducted in 2000 in eight countries: Belgium, Finland, France, Germany, Italy, Netherlands, Spain and England.20 The general aims of EUPASS were to develop and to test a surveillance system for PA as a major behavioural determinant of health.21 Inclusion criteria were being a resident of a private household within the country and age 18 years or older. Telecommunications company records constituted the basis of sampling for this study. Interviewers used the ‘last-birthday’ method for respondent selection.

The EUPASS design involved three different surveys conducted in each country. Our study is based on one of the surveys: the random-digit-dialled telephone time series survey. This survey was carried out over 6 consecutive months (June–November 2000) with 100 interviews per month and per country. In total, 4976 people participated in this study: 611 Belgian, 603 Finnish, 597 French, 654 German, 600 Italian, 632 Dutch, 600 Spanish and 679 English. For our analysis, all Belgian participants were excluded because they were not asked to answer one question.

Measures
Physical activity
PA was measured by the use of the International PA Questionnaire (IPAQ) short-form telephone version. Shown as being reliable and valid across cultures in developed and developing countries,22,23 the IPAQ assesses total PA during the previous 7 days. Questions measure the frequency (days week–1) and duration (min) of various levels of intensity (vigorous, moderate, walking or sitting) of PA. Respondents are asked to include all PA at work, during transportation, at home and during leisure time. PA levels are classified into three categories by the use of algorithms provided in the short-form scoring protocol version of November 2005, developed by the IPAQ group (www.ipaq.ki.se). The three categories were defined as follows:

  1. Low
    1. No activity reported or
    2. Some activity is reported but not enough to meet categories (ii) or (iii) following

  2. Moderate (any of the following three criteria)
    1. 3 or more days of vigorous activity of at least 20 min day–1, or
    2. 5 or more days of moderate-intensity activity and/or walking of at least 30 min day–1, or
    3. 5 or more days of any combination of walking, moderate- or vigorous-intensity activities achieving a minimum of at least 600 Metabolic Equivalent Task (MET)-min week–1.

  3. High (either of the following two criteria)
    1. Vigorous-intensity activity on at least 3 days and accumulating at least 1500 MET-min week–1 or
    2. 7 or more days of any combination of walking, moderate- or vigorous-intensity activities, accumulating at least 3000 MET-min week–1.

In this study, subjects in the ‘High’ category were considered to meet the current PHRs for PA (Health-Enhancing PA threshold).24 The recommendations are 5 x 30 min of moderate or 3 x 20 min of vigorous activity per week, in addition to a basal 60 min of moderate activity per day. Indeed, for a Health-Enhancing PA threshold, we need to consider an additional PA above the basal levels, to approximately summate amounts consistent with ≥10 000 steps days–1.

Perceived environment
The independent variables of primary interest were environmental perceptions of opportunities for practicing PA, determinants considered in earlier European studies of PA and health.11–13 Items were divided into three dimensions of perceived environment for PA: (i) a personal motivation scale (three items), (ii) a social scale (five items) and (iii) a physical and policy environment scale (three items). The Cronbach alpha reliability coefficients for the three scales were 0.80, 0.60 and 0.74, respectively.

Other variables
Some information was self reported by subjects (sex, age, professional status, self-reported health, weight and height), and other information was collected (country, month of the survey). Self-reported health was assessed on a five-point Lickert scale (1, very good to 5, bad). Weight and height were used to calculate the BMI.

Statistical analysis
Data on participant's characteristics are described by country, means and standard deviation for continuous variables, and percentages for categorical variables. Chi-square test for categorical data and Student's t-test for continuous data were used to compare the characteristics of subjects by country. Each item of the perceived environment was recoded into three categories instead of five.

Bivariate and multivariate analysis produced multiple binary logistic models to examine the association of the independent variables and meeting current PHRs for PA. ORs with 95% CI adjusted for sex, age, self-reported health, country and month of the survey were calculated. Models were created by the dimension on a global basis, not by country. Interaction terms were included in the models. All analyses were adjusted on the variables ‘country’ and ‘month’. The Hosmer–Lemeshow test was used to valid the logistic models. Statistical analyses involved use of SAS, version 9.1. A P < 0.05 was considered significant.


   Results
TOP
 Introduction
 Methods
 Results
Factors associated with meeting...
 Discussion
 Funding
 Acknowledgments
 References
 
Subject characteristics
Analyses involved 4231 participants aged 18 and older. Characteristics of the subjects are shown in Tables 1 and 2. Globally, the distribution of sociodemographic characteristics, except for sex, differed among countries.


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  		Table 1 Subject characteristics

 


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  		Table 2 Description of perceived environment (%)

 
One-fifth of the participants (20.3%) exhibited a low level of PA, 33.0% a moderate level and 46.7% a high level corresponding to the Health-Enhancing PA threshold. For the high level of PA, the highest percentage was found in Germany and the lowest in Italy (66.0 versus 24.6%, P < 0.0001) (Fig. 1). A survey month effect was noted (P = 0.04). Characteristics of excluded subjects differed from included subjects.


Figure 1
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  		Fig. 1 Levels of PA level by country.

 

   Factors associated with meeting current PHRs for PA
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 Introduction
 Methods
 Results
 Factors associated with meeting...
Discussion
 Funding
 Acknowledgments
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Bivariate analysis results are shown in Table 3. Subjects with high personal motivation were more likely to meet PHRs for PA than those with no motivation. Subjects who perceived that they were very motivated by their social environment and who observed opportunities for PA in the area where they lived were more likely to meet PHRs for PA than those who were not motivated or observed no opportunities, respectively. Inversely, low perceived motivation from health-care personnel or insurance company was associated with meeting current PHRs.


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  		Table 3 Factors associated with meeting physical activity recommendations for physical activity on bivariate analysis

 
We found no association of motivation from local authorities and/or politicians, local clubs or other neighbourhood providers or policies of municipalities and meeting PHRs for PA. Men, younger people, professionals, those who reported better self-reported health and those with low BMI were more likely to meet the current PHRs for PA.

Multivariate analysis results are shown in Table 4. After adjustment for covariates, adults with high personal motivation were more likely to meet PHRs for PA than those without motivation. Participants perceiving a high social support environment were more likely to meet PHRs than those without social support. Likewise, those who perceived opportunities for PA where they lived were more likely to meet PHRs for PA than those not perceiving opportunities. We found no effect of BMI on meeting PHRs for PA.


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  		Table 4 Factors associated with meeting physical activity recommendations for physical activity on multivariate analysis

 

   Discussion
TOP
 Introduction
 Methods
 Results
 Factors associated with meeting...
 Discussion
Funding
 Acknowledgments
 References
 
Main finding of this study
Across populations, people with high personal motivation and a high social or physical support environment were likely to meet the current PHRs for PA. Motivation from local authorities/politicians, local sport clubs/other neighbourhood providers or the local policy environment had no effect on meeting PHRs. Finally, BMI did not influence meeting PHRs for PA.

We found no association of motivation from local authorities/politicians and meeting PHRs for PA, which was strongly anticipate, from results of previous European studies.11,12 Surprisingly, subjects from all countries perceived low levels of policy support for PA, whereas other studies found that policies emphasizing PA for the whole population seemed to be related to better opportunities for PA.10,14 These differences might help to explain the observed north–south gradient in PA in Europe.25

What is already known on this topic
Level of PA
The proportion of adults meeting PHRs or PA in this sample may appear high (46.7%) compared with that from other PA surveillance surveys, such as the 2002 Eurobarometer (29.0%) (European Commission, Eurobarometer http://europa.eu.int/comm/public_opinion/index_en.htm).24 The IPAQ was used in this latter survey, but the differing rates might be interpreted with caution because our study concerned seven countries, whereas the Eurobarometer investigated 15 countries. As well, our rates are not comparable with those from 2001 Behavioural Risk Factor Surveillance System (BRFSS) (45%) because of different PA measures:26 our study did not use the same threshold of health-enhancing PA as in the BRFSS study. This latter study considered a basal level of recommended PA of at least 30 min for 5 or more days per week in moderate-intensity activities, whereas in our study, the cut-off PA values for ‘sufficient for health’ were above this level.24 Other differences concerned the activity constructs used between the two studies. The BRFSS used the recommended PA levels during non-working hours, whereas the IPAQ is based on the total PA. The IPAQ describes the total PA as not only leisure-time exercise or occupational PA but also all moderate- and vigorous-intensity activity in multiple domains: leisure time, work, transport and home. Finally, differences in PA rates have been associated with differences in the level of infrastructure for PA, as was shown in a study comparing two countries.10 This result appears to be in line with our finding that people with a favourable perception of opportunities in the area where they lived were more likely to meet the current PHRs for PA.

Level of PA and perceived environment
The interpretation of our results raises the question of the relation between perceived environmental opportunities and reality in terms of PA. On this question, findings are divergent. A study assessing perceived and objective measures of PA facilities found a significant positive association with objective but not perceived measures.27 Results of another study suggested that perceived environment measures seem to be related more with PA than objective environment measures.28 Finally, evaluation of the concordance between perceived and objective environment measures revealed no association of an individual's perceived opportunities and density of facilities in the area where people lived.28,29 The objective data for a neighbourhood and perceptions of a neighbourhood do not match, because subjects judge the environment according to their own desires and expectations.28 To illustrate, the message used by providers or politicians may be not clear enough or not adapted even if sport facilities are available in a locality.

What this study adds
This study is among the first to investigate the relation between perceived environment and meeting the current PHRs for PA in a random sample of European adults aged 18 years and older. An interesting finding of our study is that subjects who met the current PHRs for PA reported a high perceived personal motivation. This result supports general assumptions about the need to contextualize individual health behaviour.30 As well, self-efficacy theory proposes that confidence in personal ability to carry out behaviour influences the direction, intensity and persistence of behaviour.31 Personal motivation to meet PHRs for PA may be an important factor to consider in individual policies of PA promotion. Regarding the social environment, our findings strengthen previous European study results showing a positive association of the social environment and PA.11,13,32 Motivation from the sources at work or school was particularly explanatory to meet the PHRs for PA. Strategies to promote greater participation in PA will require multilevel and multisectoral approaches that build individual capability and organizational capacity for behaviour change.30

The association of PA level and sex, age, professional status and self-reported health in this sample was consistent with the literature in which men, younger people and those who reported better self-reported health were likely to meet the current PHRs for PA.1,33 The present survey confirms previously reported associations such as the inverse relation between BMI and PA.34 Indeed, low OR in meeting the current PHRs for PA were associated with a high proportion of overweight and obesity.34 After adjusting for covariates, we found the effects of environmental variables in meeting the current PHRs for PA not influenced by BMI, which does not agree with other results: an English study showed that social ecological correlates of PA (social support, self-efficacy, access to facilities) varied by BMI level.35 This study also confirmed the complex relation between environmental factors and BMI, as was shown in a French study.36

Limitations of this study
Our study has some limitations. First, because this was a cross-sectional survey, we could not draw conclusions regarding causality. Second, the validity and the reliability of the self-reported perceptions of environmental factors have not been established, although such efforts are in progress.28 However, Cronbach alpha reliability coefficients calculated in our study were in the same order of those from other studies.12,13 Third, the factors assessed in this study do not represent the entire domain of potential environmental influences on PA. This study focused on the perceived environment, which does not necessarily reflect objective aspects of where people live.15 We were only interested in what the subjects, not observers, report about their environment and consequences on their PA behaviour. Finally, data analysed in this study were not representative of the entire sample of the EUPASS random-digit-dialled survey selected for this study. Moreover, the proportion of obese subjects was not enough for BMI parameter to be significant. Our study suffered from the fact that the average BMI was lower than 25, the overweight threshold. In addition, weight and height, used to calculate BMI, were self-reported.

In conclusion, our results confirm that those found in other studies of some relation between aspects of physical and social environment and meeting the current PHRs for PA. As well, we identified that the personal motivation influences a person's will to achieve these recommendations. Thus, future public policies for PA promotion should consider the personal motivation aspect. However, future research should investigate the relation between the objective environmental measures and meeting the current PHRs for PA to confirm our findings.


   Funding
TOP
 Introduction
 Methods
 Results
 Factors associated with meeting...
 Discussion
 Funding
Acknowledgments
 References
 
Health monitoring, DG SANCO F/3, agreement: VS/1999/5133 (99CVF3–502).


   Acknowledgments
TOP
 Introduction
 Methods
 Results
 Factors associated with meeting...
 Discussion
 Funding
 Acknowledgments
References
 
We thank the EUPASS group and the participants in the EUPASS study who gave their time and without whom this study would not have been possible.


   References
TOP
 Introduction
 Methods
 Results
 Factors associated with meeting...
 Discussion
 Funding
 Acknowledgments
 References
 

  1. Trost SG, Owen N, Bauman AE, et al. Correlates of adults' participation in physical activity: review and update. Med Sci Sports Exerc (2002) 34(12):1996–2001.[Web of Science][Medline]
  2. Brown DW, Brown DR, Heath GW, et al. Associations between physical activity dose and health-related quality of life. Med Sci Sports Exerc (2004) 36(5):890–6.[Web of Science][Medline]
  3. Erlichman J, Kerbey AL, James WP. Physical activity and its impact on health outcomes. Paper 1: The impact of physical activity on cardiovascular disease and all-cause mortality: an historical perspective. Obes Rev (2002) 3(4):257–71.[CrossRef][Medline]
  4. Pate RR, Pratt M, Blair SN, et al. Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA (1995) 273(5):402–7.[Abstract/Free Full Text]
  5. Fleury J, Lee SM. The social ecological model and physical activity in African American women. Am J Community Psychol (2006) 37(1–2):129–40.[CrossRef][Web of Science][Medline]
  6. Berrigan D, Troiano RP, McNeel T, et al. Active transportation increases adherence to activity recommendations. Am J Prev Med (2006) 31(3):210–6.[CrossRef][Web of Science][Medline]
  7. Handy SL, Boarnet MG, Ewing R, et al. How the built environment affects physical activity: views from urban planning. Am J Prev Med (2002) 23((2 Suppl)):64–73.[CrossRef][Web of Science][Medline]
  8. Poortinga W. Perceptions of the environment, physical activity, and obesity. Soc Sci Med (2006) 63(11):2835–46.[CrossRef][Web of Science][Medline]
  9. Royce SW, Sharpe PA, Ainsworth BE, et al. Conceptualising barriers and supports for physical activity: a qualitative assessment. Int J Health Promot Educ (2003) 41(2):49–56.
  10. Stahl T, Rutten A, Nutbeam D, et al. The importance of policy orientation and environment on physical activity participation—a comparative analysis between Eastern Germany, Western Germany and Finland. Health Promot Int (2002) 17(3):235–46.[Abstract/Free Full Text]
  11. Rutten A, Abel T, Kannas L, et al. Self reported physical activity, public health, and perceived environment: results from a comparative European study. J Epidemiol Community Health (2001) 55(2):139–46.[Abstract/Free Full Text]
  12. Rutten A, Abu-Omar K. Perceptions of environmental opportunities for physical activity in the European Union. Soz Praventivmed (2004) 49(5):310–7.[Web of Science][Medline]
  13. Stahl T, Rutten A, Nutbeam D, et al. The importance of the social environment for physically active lifestyle—results from an international study. Soc Sci Med (2001) 52(1):1–10.[CrossRef][Web of Science][Medline]
  14. Sallis JF, Bauman A, Pratt M. Environmental and policy interventions to promote physical activity. Am J Prev Med (1998) 15(4):379–97.[CrossRef][Web of Science][Medline]
  15. King WC, Belle SH, Brach JS, et al. Objective measures of neighborhood environment and physical activity in older women. Am J Prev Med (2005) 28(5):461–9.[CrossRef][Web of Science][Medline]
  16. Porter DE, Kirtland KA, Neet MJ, et al. Considerations for using a geographic information system to assess environmental supports for physical activity. Prev Chronic Dis (2004) 1(4).
  17. Hoehner CM, Brennan Ramirez LK, Elliott MB, et al. Perceived and objective environmental measures and physical activity among urban adults. Am J Prev Med (2005) 28((2 Suppl)):105–16.[CrossRef][Web of Science][Medline]
  18. Sharpe PA, Granner ML, Hutto B, et al. Association of environmental factors to meeting physical activity recommendations in two South Carolina counties. Am J Health Promot (2004) 18(3):251–7.[Web of Science][Medline]
  19. Martinez-Gonzalez MA, Martinez JA, Hu FB, et al. Physical inactivity, sedentary lifestyle and obesity in the European Union. Int J Obes Relat Metab Disord (1999) 23(11):1192–201.[CrossRef][Web of Science][Medline]
  20. Rutten A, Rzewnicki R, Ziemainz HR, et al. Towards a European health monitoring system. Results of a pilot study on physical activity. 2003. In: Global Behavioral Risk Factor Surveillance—McQueen D, Puska P, eds. (2003) New York: Kluwer Academic: Plenum Publishers. 73–93.
  21. Rutten A, Vuillemin A, Ooijendijk WT, et al. Physical activity monitoring in Europe. The European Physical Activity Surveillance System (EUPASS) approach and indicator testing. Public Health Nutr (2003) 6(4):377–84.[Web of Science][Medline]
  22. Craig CL, Marshall AL, Sjostrom M, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc (2003) 35(8):1381–95.[CrossRef][Web of Science][Medline]
  23. Rutten A, Abu-Omar K. Prevalence of physical activity in the European Union. Soz Praventivmed (2004) 49(4):281–9.[Web of Science][Medline]
  24. Sjostrom M, Oja P, Hagstromer M, et al. Health-enhancing physical activity across European Union countries: the Eurobarometer study. J Public Health (2006) 14(5):291–300.[CrossRef]
  25. Martinez-Gonzalez MA, Varo JJ, Santos JL, et al. Prevalence of physical activity during leisure time in the European Union. Med Sci Sports Exerc (2001) 33(7):1142–6.[CrossRef][Web of Science][Medline]
  26. Macera CA, Ham SA, Yore MM, et al. Prevalence of physical activity in the United States. Prev Chronic Dis (2005) 2(2). Behavioral Risk Factor Surveillance System, 2001.
  27. Sallis JF, Hovell MF, Hofstetter CR, et al. Distance between homes and exercise facilities related to frequency of exercise among San Diego residents. Public Health Rep (1990) 105(2):179–85.[Web of Science][Medline]
  28. Kirtland KA, Porter DE, Addy CL, et al. Environmental measures of physical activity supports: perception versus reality. Am J Prev Med (2003) 24(4):323–31.[CrossRef][Web of Science][Medline]
  29. Troped PJ, Saunders RP, Pate RR, et al. Associations between self-reported and objective physical environmental factors and use of a community rail-trail. Prev Med (2001) 32(2):191–200.[CrossRef][Web of Science][Medline]
  30. Yancey AK, Fielding JE, Flores GR, et al. Creating a robust public health infrastructure for physical activity promotion. Am J Prev Med (2007) 32(1):68–78.[CrossRef][Web of Science][Medline]
  31. Dishman RK, Motl RW, Sallis JF, et al. Self-management strategies mediate self-efficacy and physical activity. Am J Prev Med (2005) 29(1):10–18.[CrossRef][Web of Science][Medline]
  32. Booth ML, Owen N, Bauman A, et al. Social-cognitive and perceived environment influences associated with physical activity in older Australians. Prev Med (2000) 31(1):15–22.[CrossRef][Web of Science][Medline]
  33. Abu-Omar K, Rutten A, Robine JM. Self-rated health and physical activity in the European Union. Soz Praventivmed (2004) 49(4):235–42.[Web of Science][Medline]
  34. Sharpe PA, Granner ML, Hutto B, et al. Association of body mass index to meeting physical activity recommendations. Am J Health Behav (2004) 28(6):522–30.[Web of Science][Medline]
  35. Blanchard CM, McGannon KR, Spence JC, et al. Social ecological correlates of physical activity in normal weight, overweight, and obese individuals. Int J Obes (Lond) (2005) 29(6):720–6.[CrossRef][Medline]
  36. Cournot M, Ruidavets JB, Marquie JC, et al. Environmental factors associated with body mass index in a population of Southern France. Eur J Cardiovasc Prev Rehabil (2004) 11(4):291–7.[CrossRef][Web of Science][Medline]

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