Skip to content
naulon
Get started

No retraction, correction or concern found when last checked on Oct 17, 2026.

Socioeconomic inequalities in occupational, leisure-time, and transport related physical activity among European adults: A systematic review

Marielle A Beenackers, Carlijn BM Kamphuis, Katrina Giskes and 4 more

International Journal of Behavioral Nutrition and Physical Activity · 2012 · Systematic review

doi:10.1186/1479-5868-9-116

Abstract

Background. This study systematically reviewed the evidence pertaining to socioeconomic inequalities in different domains of physical activity (PA) by European region.

Methods. Studies conducted between January 2000 and December 2010 were identified by a systematic search in Pubmed, Embase, Web of Science, Psychinfo, Sportdiscus, Sociological Abstracts, and Social Service Abstracts. English-language peer-reviewed studies undertaken in the general population of adults (18–65 years) were classified by domain of PA (total, leisure-time including sport, occupational, active transport), indicator of socioeconomic position (education, income, occupation), and European region. Distributions of reported positive, negative, and null associations were evaluated.

Results. A total of 131 studies met the inclusion criteria. Most studies were conducted in Scandinavia (n = 47). Leisure-time PA was the most frequently studied PA outcome (n = 112). Considerable differences in the direction of inequalities were seen for the different domains of PA. Most studies reported that those with high socioeconomic position were more physically active during leisure-time compared to those with low socioeconomic position (68% positive associations for total leisure-time PA, 76% for vigorous leisure-time PA). Occupational PA was more prevalent among the lower socioeconomic groups (63% negative associations). Socioeconomic differences in total PA and active transport PA did not show a consistent pattern (40% and 38% positive associations respectively). Some inequalities differed by European region or socioeconomic indicator, however these differences were not very pronounced.

Conclusions. The direction of socioeconomic inequalities in PA in Europe differed considerably by domain of PA. The contradictory results for total PA may partly be explained by contrasting socioeconomic patterns for leisure-time PA and occupational PA.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 17, 2026. Paragraph numbers are ours, so an answer can point at one.

Introduction

Socioeconomic inequalities in morbidity and mortality are well-documented. Differences in health behaviours play an important role in these inequalities. Next to the higher prevalence of smoking in lower socio-economic groups, evidence suggests that the higher obesity rates are of major importance to health inequalities.

Obesity levels in Europe are rising rapidly; the prevalence of obesity has tripled since the 1980s. This high prevalence of obesity is estimated to account for 1 million deaths and 12 million life years of ill health in Europe each year. European regions are thought to be in a different stage of the obesity epidemic; when the level of economic development increases, the proportion of positive associations between socioeconomic position (SEP) and overweight and obesity decreases and the proportion of negative association increases. Because overweight and obesity are the result of an excessive energy intake or limited energy expenditure, differences in dietary intake or physical activity (PA) are expected to contribute to the socioeconomic inequalities in overweight and obesity. A recent review of socioeconomic inequalities in nutrition in Europe reported that consistent socioeconomic inequalities in diet were seen for fruit and vegetable consumption and, to a lesser degree, for fibre consumption but not in amounts of energy intake. PA is a health behaviour of major importance as it is strongly associated with obesity and a number of diseases such as metabolic disease and certain cancers. However, no systematic review of the evidence of socio-economic differences in PA in Europe has been published to date.

PA is often categorized as low intensity PA (<3 Metabolic Equivalent (MET)) versus moderate (3–6 METs) to vigorous PA (>6 METs). The latter two categories are regarded as especially important for health. Furthermore, leisure-time, work-related, and transport-related PA are often distinguished from each other. Empirical evidence suggests that socioeconomic patterns may differ for different domains of PA. Patterns may also differ by gender, as exemplified by the finding that inequalities in overweight and obesity are larger in women, and by European region, as illustrated by the North to South gradient in obesity inequalities. Finally, traditional indicators of SEP, such as income, occupation, and education, may reflect different aspects of one’s position in the social stratification, and may therefore be more strongly or weakly related to specific outcomes.

The purpose of this review is to describe socioeconomic inequalities in different domains of physical activity, across different SEP indicators, in men and women, and across different regions in Europe.

Databases and search terms

Major databases (PubMed, EMbase, Web of Science, PsychINFO, SportDiscus, and Sociological Abstracts and Social Services Abstracts) were searched to locate relevant studies published between the first of January 2000 and the 31st of December 2010. Broad search terms, including synonyms, were used to ensure that all potentially relevant articles were included in the search results. When possible, database specific search terms were used to optimize the results. The search strategy and syntax for each database are available from the authors (MAB) upon request.

Inclusion and exclusion criteria

Publications were included if they were published in English-written peer-reviewed journals. Studies had to be conducted among the general population, which therefore excluded studies utilizing patient groups. Given the interest in occupational physical activity, study participants had to be of working age (18–65 years of age). Studies quantitatively assessed the association between at least one SEP indicator and one domain of physical activity (measured, either in terms of frequency (e.g. times/week), duration (e.g. hours or minutes), and/or intensity (e.g. vigorous)). Indicators of SEP included education, social class (based on occupation), income (either individual or household level), household wealth (e.g. car ownership, housing tenure) or area-based indicators (e.g. area deprivation). Outcomes included were total physical activity, leisure-time physical activity including but not limited to sports and exercise (both organized and unorganized), active transport (walking, cycling), and occupational physical activity. Manuscripts that elicited concerns about the study quality were excluded. These quality concerns were inconsistencies between the results in the text and the results in the tables, missing information on how the outcome or SEP indicator was measured, or missing information on the basic description of the sample, such as sample size.

Title scanning and selection

As a first step in identifying relevant studies, titles and abstracts were read by the lead author (MAB). Second, the full text was read if studies met the inclusion criteria and when it was clear from the title and/or abstract that the association between SEP and PA was studied. A second researcher (CBMK) executed an independent parallel selection process with a random subsample of 200 titles and abstracts which resulted in a similar selection.

Data synthesis

The following information was extracted into data extraction tables from each included study: country, year (or years) the data were collected, sample size and sample characteristics (in case a subpopulation was studied), age range, percentage males, percentage response, SEP indicator and PA outcomes (Table 1).

Classification of the outcome measures

The following guidelines were used to classify the studies into the different domains of PA:

A PA outcome was categorized as ‘total physical activity’ (TPA) if it concerned a general PA question (not defined whether they mean occupational PA or leisure-time PA) or if the measure included leisure-time PA as well as occupational PA. Total physical activity was often described as ‘usual’ or ‘daily’ physical activity.

A PA outcome was categorized as ‘occupational physical activity’ (OPA) if it was specifically identified as occupational PA in the methods with words such as ‘occupational’ or ‘during work’.

A PA outcome was categorized as ‘total leisure-time physical activity’ (TLTPA) if it was specifically identified as leisure-time PA in the methods with words such as ‘in free time’ or ‘during leisure time’. Exception: leisure-time physical activity that can be defined as vigorous physical activity (see classification criteria below).

A PA outcome was categorized as ‘vigorous leisure-time physical activity’ (VLTPA) if the methods specifically reported that it is about high intensity physical activity, vigorous physical activity, conditioning physical activity, or sports participation. Only vigorous physical activity at leisure time was considered for this category.

A PA outcome was categorized as ‘active transport’ (AT) if the outcome measure was defined as walking or cycling to work, school or other destinations such as shops or friends.

For some studies, PA outcomes could not be clearly classified in either of these groups (e.g. heavy manual leisure (like chopping wood) or walking or cycling of which the purpose (leisure or transport) was not clear). Therefore, these outcomes were excluded from the current review.

Classification of the socioeconomic position indicators

The following guidelines were used to classify the SEP indicators in this study.

Income refers to (net or gross) individual income or household income. When area-level income was used as an indicator, it was classified as ‘other’ and specified further in the footnotes of the tables.

Education refers to the highest attained level of education (e.g. university education) or as the total years of education.

Social class refers to occupation-based social class, such as blue collar or white collar workers, or the British Registrar General classification.

Other SEP indicators that were included were neighbourhood SEP, such as mean/median income of a neighbourhood, material circumstances, such as home ownership, or other individual SEP measures, such as an individual composite SEP score that was constructed from several SEP indicators.

Parental SEP, childhood SEP, or the SEP of the spouse were excluded as a SEP indicator in this review.

Classification of European regions

The results were grouped by European region, based on geographical location and type of welfare regime. The regions that were distinguished are:

Anglo-Saxon region, including Great-Britain and Ireland

Western European region, including Belgium, France, Germany, Luxembourg, Netherlands, and Switzerland

Scandinavian region, including Denmark, Finland, Norway, and Sweden

Southern European region, including Greece, Italy, Portugal, and Spain

Eastern European region, including Albania, Croatia (Hrvatska), Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, and Slovenia

As many studies included more than one PA domain and/or more than one SEP indicator, the results were analysed on the level of the separate associations rather than the level of complete studies. This is in concordance with methods form McLaren and Ball and Crawford. The advantage is that we could distinguish between the domains of PA behaviour and the SEP indicators. Disadvantages of this method are that all associations are weighted equally and that studies with more associations have more influence than those with only one reported association.

Detailed tables in which all the associations reported in the included studies were synthesized are described in the additional tables ( Additional file 1, tables A1-A5, one for each domain of PA). A ‘+’ indicates a positive and significant association between the SEP indicator and the PA outcome of interest, a ‘-’ indicates a negative and significant association between the SEP indicator and the PA outcome of interest. A ‘0’ means that there was no significant (linear) association found. Significance was judged with α = 0.05. When there were more than two categories, the overall test of significance, or trend test was used (when available). If not available, significance was judged by looking at the significance level of the difference between the two most extreme groups. When there was no trend, or a curvilinear trend, for example when only the middle group was significantly different (but not the extremes), the association was classified as being non significant. When the symbol is between brackets, no test of significance was reported and difference was judged solely on descriptive measures such as percentages.

When both adjusted and unadjusted results were presented in the manuscripts, the adjusted results were recorded into the table, including a notification of the variables that were used for adjustment. Duplicate articles on the same study population were only included in the tables if they contributed unique associations not previously reported. Distributions of reported positive, negative, and null associations were evaluated by gender, SEP indicator, and European region for each PA outcome (Tables 2 and 3).

Quality assessment

Since only observational studies were included in this study, methods for quality assessment were limited. Only a few basic quality guidelines were used as exclusion criteria. All included studies were treated equally in the results. To check if quality issues affected the results, sensitivity analyses were conducted for three common quality markers; response, adjustment, and sample size. In these analyses, the results were synthesized again after excluding the articles that did not report a response or studies with a response of less than 50%. In separate analysis, associations that were not adjusted for at least age and gender were excluded from the results. Finally, the results were synthesized for those studies with at least 2000 participants. The results that were found in the subsets of associations were compared with the results obtained when all publications were included.

Results

The search strategy retrieved 7420 unique and potentially relevant titles (Figure 1). After scanning titles and abstracts a total of 193 articles were identified for inclusion. Sixty-two articles were excluded, primarily because no association between SEP and PA was reported (n = 18), because of quality concerns (n = 11), because the population was older than 65 (n = 8), or because the study was conducted outside of Europe (n = 6). As a result, 131 studies were included in the current review.

These 131 studies reported on 105 study populations and 447 unique associations between a SEP indicator and PA outcome (Table 1). Most studies were conducted in Scandinavian countries and Great Britain. The majority of the sample sizes were large (e.g. including over 4000 participants) with a range from 224 to 60 938 participants. In most studies the response was higher than 60% (range 20-96%) but approximately one quarter of the studies did not report any response percentage. Apart from the study by Van Dyck and colleagues who used accelerometer data in addition to self-reported data, all studies relied on self-reported PA. The majority of the studies did not report the validity of the PA measure. The most frequently used validated PA questionnaire was the International PA Questionnaire (IPAQ), other validated measures that were used were the Minnesota Leisure Time PA Questionnaire, the MONICA Optional Study of PA Questionnaire (MOSPA-Q), the Short Questionnaire to Assess Health-Enhancing PA (SQUASH), and the Modifiable Activity Questionnaire (MAQ).

Total physical activity

There were 30 studies, with a total of 70 unique associations, which reported on the association between SEP IMDStril’ total PA ( Additional file 1, Table A1). Approximately equal amounts of positive (n = 28), null (n = 19) associations, and negative (n = 23) associations were found (Table). This pattern did not differ between men and women. While most associations were not statistically significant with income as indicator of SEP, both positive and negative associations were found with education as indicator of SEP (Table 2). In Southern Europe, nine out of 12 assessed associations (75%) indicated decreasing levels of physical activity by increasing levels of SEP, while in the Anglo-Saxon countries most (50%) associations showed the opposite pattern (Table 3).

Occupational physical activity

There were 10 studies, with a total of 19 unique associations, which reported on the association between SEP and occupational PA ( Additional file 1, Table A2). The majority of the associations (68%) were negative, indicating that persons in lower socioeconomic groups did more occupational PA (Table 2). Patterns were similar for men and women. Almost all associations based on social class showed a negative relationship, while mixed patterns were found for education and income (Table 2). In studies in Eastern Europe, four out of six associations were non significant, while mainly negative associations were found in other regions of Europe (Table 3).

Leisure-time physical activity

Leisure-time PA was the most frequent domain of PA assessed in relation to SEP. A total of 112 studies reported 310 unique associations. The results are presented for total leisure-time PA and vigorous leisure-time PA separately.

Total leisure-time physical activity

A total of 75 studies reported 200 unique associations ( Additional file 1, Table A3) on the association between TLTPA and SEP. Most studies (68% of associations) showed that people with a higher SEP were more likely to be physically active in their leisure-time, whereas one study reported that a higher SEP was associated with less TLTPA (Table 2). The association between education and TLTPA was reported most frequently and most studies found a positive association (74%) (Table 2). Men and women differed slightly by the SEP indicator used. For women, the associations between education and TLTPA were mostly positive (78% in women versus 68% in men), and for men the associations between social class and TLTPA were mostly positive (79% in men versus 68% in women). Income showed a more consistent positive association with TLTPA among men (71% positive) compared to women (47% positive). There were also geographical differences (Table 3). In Scandinavia and the Western European countries, predominantly positive associations were observed (84% and 81% respectively). In Eastern Europe and in the Anglo-Saxon region, only half of the associations were positive (46% and 48% respectively), with the remaining being null associations.

Vigorous leisure-time physical activity

The results from the 37 included studies reporting about VLTPA and SEP showed clear socioeconomic inequalities in VLTPA ( Additional file 1, Table A4). A total of 84 out of the 110 associations (76%) were positive, indicating that higher socioeconomic groups were more vigorously physically active during leisure-time than lower socioeconomic groups (Table 2). No studies found a significant inverse association. Income was found to be positively associated with VLTPA more frequently among men (83%) than among women (67%) (Table 2). Regarding the other SEP indicators, the results were slightly more pronounced in women. Nearly all studies (96%) conducted in the Western European region reported that VLTPA was more prevalent among people with a higher SEP (Table 3). In both Scandinavia and in the Anglo-Saxon countries, the positive associations also dominated (both 88% positive), whereas in Southern Europe about a third of the associations were positive (37%), the other 63% being non significant.

Active transport

There were 11 studies that examined socioeconomic differences in active transport ( Additional file 1, Table A5). Two studies distinguished between engaging in active transport (yes/no) and the amount of active transport in a week. This resulted in a total of 48 associations of which 18 (38%) were positive, 14 (29%) were neutral, and 16 (33%) were negative (Table 2). There were no clear differences by gender, SEP indicator, or geographic region (Tables 2 and 3).

Quality sensitivity analyses

After excluding all studies that did not report a percentage of response or that did not have a response of at least 50% (n = 40), a total of 91 studies remained in the sensitivity analysis. The number of associations decreased from 447 to 313, though patterns remained similar ( Additional file 1, Table A6 and Table A7). The main difference was that now all associations between OPA and SEP were negative, compared with 63% in the main analysis.

Excluding associations that were not at least adjusted for age and gender from the analysis resulted in a total of 342 unique associations ( Additional file 1, Table A6 and Table A7). In this restricted set of studies, all associations between OPA and SEP were negative thus accentuating the negative pattern found in the main analysis. All other patterns remained similar.

Finally, excluding the studies with less than 2000 participants (n = 31) resulted in an analysis with the remaining 100 studies ( Additional file 1, Table A6 and Table A7). The patterns became somewhat more pronounced, since larger studies in general produce more significant associations. In this restricted set of studies, half of the associations for TPA were positive, compared with 40% in the main analysis. Also the associations in TLTPA and VLTPA were more often positive (77% and 82% relatively compared with 68% and 76%). The associations between OPA and SEP were more often negative (77% compared with 63%). The pattern for active transport remained similar.

Discussion

Patterns of socioeconomic inequalities in PA are perhaps more complex than often thought. The direction of socioeconomic inequalities in PA in Europe differs considerably by domain of PA and to some degree by European region and socioeconomic indicator. Since only few studies reported men and women separately, no conclusions about gender differences are warranted.

Domains of physical activity

Different domains of PA demonstrated different socioeconomic patterns. The most consistent socioeconomic inequalities were found for vigorous leisure-time PA, with the lower SEP groups participating less in vigorous activities like sports than higher SEP groups. For overall leisure-time PA a similar pattern was observed although less articulated. In contrast to PA during leisure time, occupational PA was more frequently reported by lower SEP groups. For total PA and active transport, many studies found a significant association, but they differed considerably in direction.

The absence of a consistent direction in the socioeconomic inequalities in total PA might be caused by the contrasting socioeconomic patterns found for leisure-time PA and occupational PA, that both may make up a large part of total PA. This was nicely illustrated by a study by Lissner and colleagues. They studied leisure-time PA, occupational PA, and PA index (total PA) which was a combined measure of occupational and leisure-time PA. Their results showed that education was positively associated with leisure-time PA and inversely associated with occupational PA. Education and the PA index were not associated since the association between leisure-time PA and occupational PA evened each other out. This mechanism may partly explain the contradictory results with as much negative as positive associations between SEP and total PA, since the association will be determined by the relative influence of leisure-time PA and occupational PA on total PA.

Another question that rises is whether occupational physical activity compensates for not being active during leisure time. A few included studies examined socio-economic differences in leisure-time PA while correcting for occupational PA. In the multivariable models, both income and education, and occupational PA were significantly associated with leisure-time PA. These studies indicated that although respondents who were more occupationally active were less active in leisure time, people from lower socio-economic backgrounds were still less physically active compared to high socio-economic people, even after correcting for occupational PA.

Also, by including occupational PA as an indicator of healthy PA, it is assumed that occupational PA is beneficial to health, however this may not be the case. The few studies that look at associations between occupational PA and mortality or morbidity show no clear pattern. There are studies that report a beneficial effect, no effect, or a detrimental effect of occupational PA on cardiovascular diseases and mortality. The health benefits of leisure-time PA and sports are more consistent. The different types of activity carried out at work might partly explain these inconsistent findings. For example, Fransson et al. found that walking and standing at work, both aerobic activities, decreases the risk of myocardial infarction, while lifting or carrying at work increases the risk of myocardial infarction. The relation between all aspects of occupational PA and health should be investigated further.

Active transport was studied considerably less often than the other domains of PA and no clear pattern was detected. There were almost equal amounts of studies showing a positive, a null, or a negative association between SEP and active transport. It could be that whether or not one engages in active transport and time spent doing so have different determinants. The two studies that distinguished between participation and time spent in active transport showed for example that participation was not or inversely associated with education while, among the participators, the higher educated spent more time in active transport. The contradictory results may also be explained by factors that influence the association between SEP and active transport. A Dutch and a Belgium study both looked at neighbourhood SEP as an indicator of active transport and found negative associations. This could either be an indication that people with a lower SEP are more likely to engage in transport PA or for example, that neighbourhoods with a low SEP are more likely to make people engage in transport PA for example because of a higher density or more connectivity. External factors such as connectivity, density and the availability of public transport might be especially important for active transport PA and more research should be conducted to get a better insight into determinants of active transport.

Types of SEP indicator

Income, education and occupation reflect different aspects of SEP. Occupational class appears to be the SEP indicator most sensitive for studying SEP differences in occupational PA. However, the consistent associations found for this indicator may also be due to the definitions used to describe social classes. Because manual jobs are in general considered to be of lower social class, the social class definition is often partly based on having a manual or a non-manual job. This already implies a difference in activities at work.

Inequalities in leisure-time PA and vigorous activity are often thought to be caused by either an educational effect on knowledge about the positive health consequences of PA, or financial possibilities to engage in leisure-time PA, for example to buy PA equipment or to afford memberships or admission rates for sports and PA facilities. The fact that the patterns in inequalities in PA were roughly similar for the different indicators of SEP, including education and income, suggest that it is not one or the other but both may indeed be important. Other factors related to chance and choice of lifestyle, such as SEP differences in social or cultural capital or differences in physical environmental opportunities for PA, may be additional determinants of SEP inequalities in PA. Also, some factors, such as intrapersonal factors, may act as intermediary in the process between SES and PA. In a previous review, Gidlow and colleagues reported that education was stronger associated with PA than income. Although in the present review education was the most frequent studied SEP indicator we could not confirm that the associations of education with PA were also stronger than the associations with the other SEP indicators.

European regions

A recent study showed that the largest inequalities in obesity prevalence were found in Southern Europe, especially among women, and the smallest in Eastern Europe. In concordance with these findings, we found that the socioeconomic inequalities in PA were less consistent in Eastern Europe for both occupational PA and leisure-time PA. Opposite to what would be expected from the inequalities found in obesity, the inequalities in vigorous leisure-time PA were least pronounced in Southern Europe. This was also found in the few pan-European studies that were included in this review and by a recent pan-European study by Mäkinen et al.. A possible explanation could be that general levels of PA are low in these countries which would make it harder to detect SEP differences in PA.

Strengths & limitations

The main strength of this review is the systematic exploration of different domains of physical activity, different SEP indicators, and geographic regions of Europe. Also, the inclusion of a quality sensitivity analyses strengthens the results. There are, however, also some limitations to be taken into account when interpreting the results.

Like any review of the published literature, the present review may suffer from publication bias. The fact that a substantial numbers of null findings were reported in the reviewed studies may indicate that publication bias may not be severe. Also, some relevant studies may have been missed because only English-language studies that were available in electronic databases and that were published in peer-reviewed journals were included. Moreover, by analyzing the data on the level of the associations instead of the level of studies, more weight was given to studies that reported more than one association. Although this may have influenced conclusions based on all reported associations, this influence was expected to be smaller when subgroups of associations, such as by PA domain and SEP indicator, are considered.

Methodological differences between the included studies, such as the assessment of PA, the selection of participants, and the adjustment for confounders, could have influenced the reported associations. Although this probably introduced some noise, the sensitivity analysis showed that the overall patterns seem to be quite stable.

Conclusion

This review showed that leisure-time PA, and specifically vigorous leisure-time PA, is less prevalent while occupational PA is more prevalent among people with lower SEP. Although there were some regional differences, these inequalities were visible throughout Europe. The contradictory inequalities for total PA may partly be explained by the contrasting socioeconomic patterns found for leisure-time PA and occupational PA. These inconsistent results in total PA indicate that total PA may not be a suitable summary measure when investigating inequalities in PA and their effects on morbidity and mortality.

The found inequalities indicate that leisure-time PA should be an important focus in improving physical activity levels and reducing inequalities. However, interventions aimed at improving leisure-time PA in lower socioeconomic groups needs to acknowledge their potential higher levels of occupational PA.

Abbreviations

PA: Physical Activity; MET: Metabolic Equivalent; SEP: Socioeconomic Position; TPA: Total physical Activity; OPA: Occupational Physical Activity; TLTPA: Total Leisure Time Physical Activity; VLTPA: Vigorous Leisure Time Physical Activity; AT: Active Transport.

Competing interest

The author(s) declare that they have no competing interests'.

Authors’ contributions

MAB carried out the systematic literature search, the title scanning and selection, the data synthesis, and the drafting of the manuscript. CBMK assisted in the title selection and the data synthesis. She also helped to interpret the results and critically reviewed and improved the manuscript. KG, FJvL, and AEK designed the study, helped to interpret the results, and critically reviewed and improved the manuscript. JB and AB helped to interpret the results and critically reviewed and improved the manuscript. All authors read and approved the final manuscript.

References 173

  1. 1.

    Mackenbach JP Stirbu I Roskam AJ Schaap MM Menvielle G Leinsalu M Kunst AE Socioeconomic inequalities in health in 22 European countriesN Engl J Med2008 35824682481

    Not in our library10.1056/nejmsa0707519

  2. 2.

    Stirbu I Kunst AE Bopp M Leinsalu M Regidor E Esnaola S Costa G Martikainen P Borrell C Deboosere P Educational inequalities in avoidable mortality in EuropeJ Epidemiol Community Health2010 64913920

    Not in our library10.1136/jech.2008.081737

  3. 3.

    Stringhini S Sabia S Shipley M Brunner E Nabi H Kivimaki M Singh-Manoux A Association of socioeconomic position with health behaviors and mortalityJAMA2010 30311591166

    Not in our library10.1001/jama.2010.297

  4. 4.

    Menvielle G Boshuizen H Kunst AE Dalton SO Vineis P Bergmann MM Hermann S Ferrari P Raaschou-Nielsen O Tjønneland A The role of smoking and diet in explaining educational inequalities in lung cancer incidenceJ Natl Cancer Inst2009 101321330

    Not in our library10.1093/jnci/djn513

  5. 5.

    Huisman M Kunst AE Mackenbach JP Educational inequalities in smoking among men and women aged 16 years and older in 11 European countriesTob Control2005 14106113

    Not in our library10.1136/tc.2004.008573

  6. 6.

    McLaren L Socioeconomic status and obesity. Epidemiol Rev2007 292948

    Not in our library10.1093/epirev/mxm001

  7. 7.

    Roskam AJ Kunst AE Van Oyen H Demarest S Klumbiene J Regidor E Helmert U Jusot F Dzurova D Mackenbach JP Comparative appraisal of educational inequalities in overweight and obesity among adults in 19 European countriesInt J Epidemiol2010 39392404

    Not in our library10.1093/ije/dyp329

  8. 8.

    Seidell JC Epidemiology of obesitySemin Vasc Med2005 5314

    Not in our library10.1055/s-2005-871737

  9. 9.

    Molarius A Seidell JC Sans S Tuomilehto J Kuulasmaa K Educational level, relative body weight, and changes in their association over 10 years: an international perspective from the WHO MONICA ProjectAm J Public Health2000 9012601268

    Not in our library10.2105/ajph.90.8.1260

  10. 10.

    Branca F Nikogosian H Lobstein T Challenge of Obesity in the WHO European Region and the Strategies for Response2007 Denmark: World Health Organization

    Not in our library

  11. 11.

    Giskes K Avendaňo M Brug J Kunst AE A systematic review of studies on socioeconomic inequalities in dietary intakes associated with weight gain and overweight/obesity conducted among European adultsObes Rev2010 11413429

    Not in our library10.1111/j.1467-789x.2009.00658.x

  12. 12.

    Centers for Disease Control and PreventionPhysical activity and health: a report of the Surgeon General1996 Washington DC: U.S. Department of Health and Human services

    Not in our library

  13. 13.

    Warburton DE Nicol CW Bredin SS Health benefits of physical activity: the evidenceCan Med Assoc J2006 174801809

    Not in our library10.1503/cmaj.051351

  14. 14.

    Pate RR Pratt M Blair SN Haskell WL Macera CA Bouchard C Buchner D Ettinger W Heath GW King AC Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports MedicineJAMA1995 273402407

    Not in our library10.1001/jama.1995.03520290054029

  15. 15.

    Allender S Foster C Boxer A Occupational and nonoccupational physical activity and the social determinants of physical activity: results from the Health Survey for EnglandJ Phys Act Health2008 5104116

    Not in our library10.1123/jpah.5.1.104

  16. 16.

    Popham F Mitchell R Relation of employment status to socioeconomic position and physical activity typesPrev Med2007 45182188

    Not in our library10.1016/j.ypmed.2007.06.012

  17. 17.

    Geyer S Hemström Ö Peter R Vågerö D Education, income, and occupational class cannot be used interchangeably in social epidemiology. Empirical evidence against a common practice.J Epidemiol Community Health2006 60804810

    Not in our library10.1136/jech.2005.041319

  18. 18.

    Galobardes B Lynch J Smith GD Measuring socioeconomic position in health researchBr Med Bull2007 81-822137

    Not in our library10.1093/bmb/ldm001

  19. 19.

    Rose D Official Social Classifications in the UKSocial Research Update1995 91

    Not in our library

  20. 20.

    Eikemo TA Huisman M Bambra C Kunst AE Health inequalities according to educational level in different welfare regimes: a comparison of 23 European countriesSociol Health Illn2008 30565582

    Not in our library10.1111/j.1467-9566.2007.01073.x

  21. 21.

    Ferrera M The 'Southern Model' of Welfare in Social EuropeJournal of European Social Policy1996 61737

    Not in our library10.1177/095892879600600102

  22. 22.

    Ball K Crawford D Socioeconomic status and weight change in adults: a reviewSoc Sci Med2005 6019872010

    Not in our library10.1016/j.socscimed.2004.08.056

  23. 23.

    Van Dyck D Cardon G Deforche B Sallis JF Owen N De Bourdeaudhuij I Neighborhood SES and walkability are related to physical activity behavior in Belgian adultsPrev Med2010 50S74S79

    Not in our library10.1016/j.ypmed.2009.07.027

  24. 24.

    Craig CL Marshall AL Sjöström M Bauman AE Booth ML Ainsworth BE Pratt M Ekelund U Yngve A Sallis JF Oja P International physical activity questionnaire: 12-country reliability and validityMed Sci Sports Exerc2003 3513811395

    Not in our library10.1249/01.mss.0000078924.61453.fb

  25. 25.

    Taylor HL Jacobs DR Jr Schucker B Knudsen J Leon AS Debacker G A questionnaire for the assessment of leisure time physical activitiesJ Chronic Dis1978 31741755

    Not in our library10.1016/0021-9681(78)90058-9

  26. 26.

    Pereira MA FitzerGerald SJ Gregg EW Joswiak ML Ryan WJ Suminski RR Utter AC Zmuda JM A collection of Physical Activity Questionnaires for health-related researchMed Sci Sports Exerc1997 29S1S205

    Not in our library

  27. 27.

    Wendel-Vos GCW Schuit AJ Saris WHM Kromhout D Reproducibility and relative validity of the short questionnaire to assess health-enhancing physical activityJ Clin Epidemiol2003 5611631169

    Not in our library10.1016/s0895-4356(03)00220-8

  28. 28.

    Kwaśniewska M Kaczmarczyk-Chałas K Pikala M Broda Kozakiewicz K Pajak A Tykarski A Zdrojewski T Drygas W Socio-demographic and lifestyle correlates of commuting activity in PolandPrev Med2010 50257261

    Not in our library10.1016/j.ypmed.2010.02.011

  29. 29.

    Adams J Prevalence and socio-demographic correlates of "active transport" in the UK: analysis of the UK time use survey 2005Prev Med2010 50199203

    Not in our library10.1016/j.ypmed.2010.01.006

  30. 30.

    Lissner L Bengtsson C Björkelund C Wedel H Physical activity levels and changes in relation to longevityA prospective study of Swedish women. Am J Epidemiol1996 1435462

    Not in our library10.1093/oxfordjournals.aje.a008657

  31. 31.

    Drygas W Kwaśniewska M Kaleta D Pikala M Bielecki W Głuszek J Zdrojewski T Pajak A Kozakiewicz K Broda G Epidemiology of physical inactivity in Poland: prevalence and determinants in a former communist country in socioeconomic transitionPublic Health2009 123592597

    Not in our library10.1016/j.puhe.2009.08.004

  32. 32.

    Kaleta D Jegier A Occupational energy expenditure and leisure-time physical activityInt J Occup Med Environ Health2005 18351356

    Not in our library

  33. 33.

    Holtermann A Hansen JV Burr H Søgaard K Sjøgaard G The health paradox of occupational and leisure-time physical activityBr J Sports Med2012 69485492

    Not in our library10.1136/bjsm.2010.079582

  34. 34.

    Wang Y Tuomilehto J Jousilahti P Antikainen R Mähönen M Katzmarzyk PT Hu G Occupational, commuting, and leisure-time physical activity in relation to heart failure among finnish men and womenJ Am Coll Cardiol2010 5611401148

    Not in our library10.1016/j.jacc.2010.05.035

  35. 35.

    Salonen JT Puska P Tuomilehto J Physical activity and risk of myocardial infarction, cerebral stroke and death: a longitudinal study in Eastern FinlandAm J Epidemiol1982 115526537

    Not in our library10.1093/oxfordjournals.aje.a113334

  36. 36.

    Hu G Jousilahti P Borodulin K Barengo NC Lakka TA Nissinen A Tuomilehto J Occupational, commuting and leisure-time physical activity in relation to coronary heart disease among middle-aged Finnish men and womenAtherosclerosis2007 194490497

    Not in our library10.1016/j.atherosclerosis.2006.08.051

  37. 37.

    Hu G Qiao Q Silventoinen K Eriksson JG Jousilahti P Lindström J Valle TT Nissinen A Tuomilehto J Occupational, commuting, and leisure-time physical activity in relation to risk for Type 2 diabetes in middle-aged Finnish men and womenDiabetologia2003 46322329

    Not in our library10.1007/s00125-003-1031-x

  38. 38.

    Steeves JA Bassett DR Jr Thompson DL Fitzhugh EC Relationships of occupational and non-occupational physical activity to abdominal obesityInt J Obes2012 36100106

    Not in our library10.1038/ijo.2011.50

  39. 39.

    Sisson SB Camhi SM Church TS Martin CK Tudor-Locke C Bouchard C Earnest CP Smith SR Newton RL Jr Rankinen T Katzmarzyk PT Leisure time sedentary behavior, occupational/domestic physical activity, and metabolic syndrome in U.S. men and womenMetab Syndr Relat Disord2009 7529536

    Not in our library10.1089/met.2009.0023

  40. 40.

    Stender M Hense HW Döring A Keil U Physical activity at work and cardiovascular disease risk: results from the MONICA Augsburg studyInt J Epidemiol1993 22644650

    Not in our library10.1093/ije/22.4.644

  41. 41.

    Kristal-Boneh E Harari G Melamed S Froom P Association of physical activity at work with mortality in Israeli industrial employees: the CORDIS studyJ Occup Environ Med2000 42127135

    Not in our library10.1097/00043764-200002000-00005

  42. 42.

    Suadicani P Hein HO Gyntelberg F Socioeconomic status and ischaemic heart disease mortality in middle-aged men: importance of the duration of follow-up. The Copenhagen Male StudyInt J Epidemiol2001 30248255

    Not in our library10.1093/ije/30.2.248

  43. 43.

    Krause N Brand RJ Kaplan GA Kauhanen J Malla S Tuomainen TP Salonen JT Occupational physical activity, energy expenditure and 11-year progression of carotid atherosclerosisScand J Work Environ Health2007 33405424

    Not in our library10.5271/sjweh.1171

  44. 44.

    Behre CJ Bergström G Schmidt CB Increasing leisure time physical activity is associated with less prevalence of the metabolic syndrome in healthy middle-aged menAngiology2011 62509512

    Not in our library10.1177/0003319711398863

  45. 45.

    Savela S Koistinen P Tilvis RS Strandberg AY Pitkälä KH Salomaa VV Miettinen TA Strandberg TE Leisure-time physical activity, cardiovascular risk factors and mortality during a 34-year follow-up in menEur J Epidemiol2010 25619625

    Not in our library10.1007/s10654-010-9483-z

  46. 46.

    Fransson E De Faire U Ahlbom A Reuterwall C Hallqvist J Alfredsson L The risk of acute myocardial infarction: interactions of types of physical activityEpidemiology2004 15573582

    Not in our library10.1097/01.ede.0000134865.74261.fe

  47. 47.

    van Lenthe FJ Brug J Mackenbach JP Neighbourhood inequalities in physical inactivity: the role of neighbourhood attractiveness, proximity to local facilities and safety in the NetherlandsSoc Sci Med2005 60763775

    Not in our library10.1016/j.socscimed.2004.06.013

  48. 48.

    Rundle A Roux AV Free LM Miller D Neckerman KM Weiss CC The urban built environment and obesity in New York City: a multilevel analysisAm J Health Promot2007 21326334

    Not in our library10.4278/0890-1171-21.4s.326

  49. 49.

    Cockerham WC Rütten A Abel T Conceptualizing contemporary health lifestylesSociological Quarterly1997 38321342

    Not in our library10.1111/j.1533-8525.1997.tb00480.x

  50. 50.

    Abel T Cultural capital and social inequality in healthJ Epidemiol Community Health2008 62e13

    Not in our library10.1136/jech.2007.066159

  51. 51.

    Kamphuis CB van Lenthe FJ Giskes K Huisman M Brug J Mackenbach JP Socioeconomic differences in lack of recreational walking among older adults: the role of neighbourhood and individual factorsInt J Behav Nutr Phys Act2009 61

    Not in our library10.1186/1479-5868-6-1

  52. 52.

    Kamphuis CB Van Lenthe FJ Giskes K Huisman M Brug J Mackenbach JP Socioeconomic status, environmental and individual factors, and sports participationMed Sci Sports Exerc2008 407181

    Not in our library10.1249/mss.0b013e318158e467

  53. 53.

    Gidlow C Johnston LH Crone D Ellis N James D A systematic review of the relationship between socio-economic position and physical activityHealth Educ J2006 65338367

    Not in our library10.1177/0017896906069378

  54. 54.

    Martinez-Gonzalez MA Varo JJ Santos JL De Irala J Gibney M Kearney J Martinez JA Prevalence of physical activity during leisure time in the European UnionMed Sci Sports Exerc2001 3311421146

    Not in our library10.1097/00005768-200107000-00011

  55. 55.

    Van Tuyckom C Scheerder J Sport for All? Insight into stratification and compensation mechanisms of sporting activity in the 27 European Union member statesSport, Education and Society2010 15495512

    Not in our library10.1080/13573322.2010.514746

  56. 56.

    Varo JJ Martínez-González MA De Irala-Estévez J Kearney J Gibney M Martínez JA Distribution and determinants of sedentary lifestyles in the European UnionInt J Epidemiol2003 32138146

    Not in our library10.1093/ije/dyg116

  57. 57.

    Mäkinen TE Sippola R Borodulin K Rahkonen O Kunst A Klumbiene J Regidor E Ekholm O Mackenbach J Prättälä R Explaining educational differences in leisure-time physical activity in Europe: the contribution of work-related factorsScand J Med Sci Sports2012 22439447

    Not in our library10.1111/j.1600-0838.2010.01234.x

  58. 58.

    Dickersin K Min Y-I Meinert CL Factors Influencing Publication of Research Results: Follow-up of Applications Submitted to Two Institutional Review BoardsJAMA1992 267374378

    Not in our library10.1001/jama.1992.03480030052036

  59. 59.

    van Poppel MN Chinapaw MJ Mokkink LB van Mechelen W Terwee CB Physical activity questionnaires for adults: a systematic review of measurement propertiesSports Med2010 40565600

    Not in our library10.2165/11531930-000000000-00000

  60. 60.

    Ståhl T Rütten A Nutbeam D Bauman A Kannas L Abel T Lüschen G Rodriquez DJ Vinck J van der Zee J The importance of the social environment for physically active lifestyle–results from an international studySoc Sci Med2001 52110

    Not in our library10.1016/s0277-9536(00)00116-7

  61. 61.

    Van Tuyckom C Scheerder J Sport for all? Social stratification of recreational sport activities in the EU-27Kinesiologia Slovenica2008 145463

    Not in our library

  62. 62.

    Van Tuyckom C Scheerder J A multilevel analysis of social stratification patterns of leisure-time physical activity among EuropeansScience & Sports2010 25304311

    Not in our library

  63. 63.

    Addor V Wietlisbach V Narring F Michaud PA Cardiovascular risk factor profiles and their social gradient from adolescence to age 74 in a Swiss regionPrev Med2003 36217228

    Not in our library10.1016/s0091-7435(02)00016-6

  64. 64.

    Bertrais S Preziosi P Mennen L Galan P Hercberg S Oppert JM Sociodemographic and geographic correlates of meeting current recommendations for physical activity in middle-aged French adults: the Supplementation en Vitamines et Mineraux Antioxydants (SUVIMAX) StudyAm J Public Health2004 9415601566

    Not in our library10.2105/ajph.94.9.1560

  65. 65.

    Chaix B Chauvin P Tobacco and alcohol consumption, sedentary lifestyle and overweightness in France: A multilevel analysis of individual and area-level determinantsEur J Epidemiol2003 18531538

    Not in our library10.1023/a:1024642301343

  66. 66.

    Dragano N Bobak M Wege N Peasey A Verde PE Kubinova R Weyers S Moebus S Möhlenkamp S Stang A Neighbourhood socioeconomic status and cardiovascular risk factors: a multilevel analysis of nine cities in the Czech Republic and GermanyBMC Public Health2007 7255

    Not in our library10.1186/1471-2458-7-255

  67. 67.

    Drieskens S Van Oyen H Demarest S Van der Heyden J Gisle L Tafforeau J Multiple risk behaviour: increasing socio-economic gap over time?Eur J Public Health2010 20634639

    Not in our library10.1093/eurpub/ckp185

  68. 68.

    Galobardes B Costanza MC Bernstein MS Delhumeau C Morabia A Trends in risk factors for lifestyle-related diseases by socioeconomic position in Geneva, Switzerland, 1993–2000: health inequalities persistAm J Public Health2003 9313021309

    Not in our library10.2105/ajph.93.8.1302

  69. 69.

    Meyer K Rezny L Breuer C Lamprecht M Stamm HP Physical activity of adults aged 50 years and older in SwitzerlandSoz Praventivmed2005 50218229

    Not in our library10.1007/s00038-005-4093-3

  70. 70.

    Nocon M Keil T Willich SN Education, income, occupational status and health risk behaviourJ Public Health2008 15401405

    Not in our library

  71. 71.

    van Oort FV van Lenthe FJ Mackenbach JP Cooccurrence of lifestyle risk factors and the explanation of education inequalities in mortality: results from the GLOBE studyPrev Med2004 3911261134

    Not in our library10.1016/j.ypmed.2004.04.025

  72. 72.

    Rathmann W Haastert B Icks A Giani G Holle R Meisinger C Mielck A Group KS Sex differences in the associations of socioeconomic status with undiagnosed diabetes mellitus and impaired glucose tolerance in the elderly population: the KORA Survey 2000Eur J Public Health2005 15627633

    Not in our library10.1093/eurpub/cki037

  73. 73.

    Ribet C Lang T Zins M Bingham A Ferrières J Arveiler D Amouyel P Bonenfant S Chastang JF Goldberg M Ducimetière P Do cardiovascular risk factors in men depend on their spouses' occupational category?Eur J Epidemiol2001 17347356

    Not in our library10.1023/a:1012709700189

  74. 74.

    Scheerder J Vanreusel B Taks M Renson R Social Sports Stratification in Flanders 1969–1999: Intergenerational Reproduction of Social Inequalities?International Review for the Sociology of Sport2002 37219245

    Not in our library10.1177/1012690202037002006

  75. 75.

    Scheerder J Vanreusel B Taks M Stratification patterns of active sport involvement among adults: Social change and persistenceInternational Review for the Sociology of Sport2005 40139162

    Not in our library10.1177/1012690205057191

  76. 76.

    Schneider S Becker S Prevalence of physical activity among the working population and correlation with work-related factors: results from the first German National Health SurveyJ Occup Health2005 47414423

    Not in our library10.1539/joh.47.414

  77. 77.

    Verdaet D Dendale P De Bacquer D Delanghe J Block P De Backer G Association between leisure time physical activity and markers of chronic inflammation related to coronary heart diseaseAtherosclerosis2004 176303310

    Not in our library10.1016/j.atherosclerosis.2004.05.007

  78. 78.

    De Vries H Vant Riet J Spigt M Metsemakers J Van den Akker M Vermunt JK Kremers S Clusters of lifestyle behaviors: results from the Dutch SMILE studyPrev Med2008 46203208

    Not in our library10.1016/j.ypmed.2007.08.005

  79. 79.

    Wagner A Simon C Evans A Ducimetière P Bongard V Montaye M Arveiler D Group PSPhysical activity patterns in 50–59 year men in France and Northern Ireland. Associations with socio-economic status and health behaviourEur J Epidemiol2003 18321329

    Not in our library10.1023/a:1023625110856

  80. 80.

    Frömel K Mitáš J Kerr J The associations between active lifestyle, the size of a community and SES of the adult population in the Czech RepublicHealth Place2009 15447454

    Not in our library10.1016/j.healthplace.2008.08.003

  81. 81.

    Jurakić D Pedišić Z Andrijašević M Physical activity of Croatian population: cross-sectional study using International Physical Activity QuestionnaireCroat Med J2009 50165173

    Not in our library10.3325/cmj.2009.50.165

  82. 82.

    Kaleta D Jegier A Predictors of inactivity in the working-age populationInt J Occup Med Environ Health2007 20175182

    Not in our library10.2478/v10001-007-0019-z

  83. 83.

    Leskošek B Doupona M Moćnik R Jošt B Sport participation in the Republic of Slovenia and its relation to selected socio-demographic variables./Beteiligung an Sport in der Republik Slowenien und deren Zusammenhang mit den Ausgewaehlten sozio-demographischen Variablen./Relacije sudjelovanja u sportskim aktivnostima u Repbulici Slovenijis izabranim socio-demografskim varijablamaKinesiology2002 344149

    Not in our library

  84. 84.

    Mišigoj-Durakoviæ M Heimer S Matkoviæ BR Ružiæ L Prskalo I Physical activity of urban adult population: questionnaire studyCroat Med J2000 41428432

    Not in our library

  85. 85.

    Nowak MA Relationships between the perception of the influence of physical activity on health and women's engagement in exercise or their physical passivityPolish Journal of Sport & Tourism2010 17179184

    Not in our library

  86. 86.

    Paulik E Bóka F Kertész A Balogh S Nagymajtényi L Determinants of health-promoting lifestyle behaviour in the rural areas of HungaryHealth Promot Int2010 25277288

    Not in our library10.1093/heapro/daq025

  87. 87.

    Pomerleau J McKee M Robertson A Vaasc S Kadziauskiene K Abaravicius A Bartkeviciute R Pudule I Grinberga D Physical inactivity in the Baltic countriesPrev Med2000 31665672

    Not in our library10.1006/pmed.2000.0761

  88. 88.

    Puska P Helasoja V Prättälä R Kasmel A Klumbiene J Health behaviour in Estonia, Finland and Lithuania 1994–1998. Standardized comparisonEur J Public Health2003 131117

    Not in our library10.1093/eurpub/13.1.11

  89. 89.

    Shapo L Pomerleau J McKee M Physical inactivity in a country in transition: a population-based survey in Tirana City, AlbaniaScand J Public Health2004 326067

    Not in our library10.1080/14034940310011801

  90. 90.

    Stelmach W Kaczmarczyk-Chałas K Bielecki W Drygas W The impact of income, education and health on lifestyle in a large urban population of Poland (Cindi programme)Int J Occup Med Environ Health2004 17393401

    Not in our library

  91. 91.

    Zaletel-Kragelj L Fras Z Zakotnik JM Results of CINDI health monitor surveys in Slovenia as a tool for development of effective healthy nutrition and physical activity intervention programmesJ Public Health2007 14110118

    Not in our library

  92. 92.

    Artazcoz L Borrell C Benach J Cortès I Rohlfs I Women, family demands and health: the importance of employment status and socio-economic positionSoc Sci Med2004 59263274

    Not in our library10.1016/j.socscimed.2003.10.029

  93. 93.

    Bolívar J Daponte A Rodríguez M Sánchez JJ The Influence of Individual, Social and Physical Environment Factors on Physical Activity in the Adult Population in Andalusia, SpainInt J Environ Res Public Health2010 76077

    Not in our library10.3390/ijerph7010060

  94. 94.

    Borrell C Domínguez-Berjón F Pasarín MI Ferrando J Rohlfs I Nebot M Social inequalities in health related behaviours in BarcelonaJ Epidemiol Community Health2000 542430

    Not in our library10.1136/jech.54.1.24

  95. 95.

    Borrell C Rue M Pasarín MI Rohlfs I Ferrando J Fernandez E Trends in social class inequalities in health status, health-related behaviors, and health services utilization in a Southern European urban area (1983–1994)Prev Med2000 31691701

    Not in our library10.1006/pmed.2000.0751

  96. 96.

    De Vogli R Gnesotto R Goldstein M Andersen R Cornia GA The lack of social gradient of health behaviors and psychosocial factors in Northern ItalySoz Praventivmed2005 50197205

    Not in our library10.1007/s00038-005-4025-2

  97. 97.

    Gal DL Santos AC Barros H Leisure-time versus full-day energy expenditure: a cross-sectional study of sedentarism in a Portuguese urban populationBMC Public Health2005 516

    Not in our library10.1186/1471-2458-5-16

  98. 98.

    Lera-López F Rapún-Gárate M Sports Participation versus Consumer Expenditure on Sport: Different Determinants and Strategies in Sports ManagementEuropean Sport Management Quarterly2005 5167186

    Not in our library10.1080/16184740500188656

  99. 99.

    Meseguer CM Galán I Herruzo R Zorrilla B Rodríguez-Artalejo F Leisure-time physical activity in a southern European mediterranean country: adherence to recommendations and determining factorsRev Esp Cardiol2009 6211251133

    Not in our library10.1016/s0300-8932(09)72381-4

  100. 100.

    Panagiotakos DB Pitsavos C Chrysohoou C Vlismas K Skoumas Y Palliou K Stefanadis C Dietary habits mediate the relationship between socio-economic status and CVD factors among healthy adults: the ATTICA studyPublic Health Nutr2008 1113421349

    Not in our library10.1017/s1368980008002978

  101. 101.

    Panagiotakos DB Pitsavos C Chrysohoou C Vlismas K Skoumas Y Palliou K Stefanadis C The effect of clinical characteristics and dietary habits on the relationship between education status and 5-year incidence of cardiovascular disease: the ATTICA studyEur J Nutr2008 47258265

    Not in our library10.1007/s00394-008-0720-0

  102. 102.

    Pascual C Regidor E Astasio P Ortega P Navarro P Domínguez V The association of current and sustained area-based adverse socioeconomic environment with physical inactivitySoc Sci Med2007 65454466

    Not in our library10.1016/j.socscimed.2007.03.023

  103. 103.

    Pascual C Regidor E Martínez D Elisa Calle M Domínguez V Socioeconomic environment, availability of sports facilities, and jogging, swimming and gym useHealth Place2009 15553561

    Not in our library10.1016/j.healthplace.2008.08.007

  104. 104.

    Pitsavos C Panagiotakos DB Lentzas Y Stefanadis C Epidemiology of leisure-time physical activity in socio-demographic, lifestyle and psychological characteristics of men and women in Greece: the ATTICA StudyBMC Public Health2005 537

    Not in our library10.1186/1471-2458-5-37

  105. 105.

    Santos R Santos MP Ribeiro JC Mota J Physical Activity and Other Lifestyle Behaviors in a Portuguese Sample of Adults: Results From the Azorean Physical Activity and Health StudyJ Phys Act Health2009 6750759

    Not in our library10.1123/jpah.6.6.750

  106. 106.

    Schröder H Rohlfs I Schmelz EM Marrugat J for the REGIDOR investigatorsRelationship of socioeconomic status with cardiovascular risk factors and lifestyle in a Mediterranean populationEur J Nutr2004 437785

    Not in our library10.1007/s00394-004-0443-9

  107. 107.

    Ali SM Lindström M Psychosocial work conditions, unemployment, and leisure-time physical activity: A population-based studyScand J Public Health2006 34209216

    Not in our library10.1080/14034940500307515

  108. 108.

    Andersen LB Schnohr P Schroll M Hein HO All-cause mortality associated with physical activity during leisure time, work, sports, and cycling to workArch Intern Med2000 16016211628

    Not in our library10.1001/archinte.160.11.1621

  109. 109.

    Barengo NC Nissinen A Pekkarinen H Halonen P Tuomilehto J Twenty-five-year trends in lifestyle and socioeconomic characteristics in Eastern FinlandScand J Public Health2006 34437444

    Not in our library10.1080/14034940500489818

  110. 110.

    Bergman P Grjibovski AM Hagströmer M Bauman A Sjöstrom M Adherence to physical activity recommendations and the influence of socio-demographic correlates - a population-based cross-sectional studyBMC Public Health2008 8367

    Not in our library10.1186/1471-2458-8-367

  111. 111.

    Borodulin K Laatikainen T Lahti-Koski M Jousilahti P Lakka TA Association of age and education with different types of leisure-time physical activity among 4437 Finnish adultsJ Phys Act Health2008 5242251

    Not in our library10.1123/jpah.5.2.242

  112. 112.

    Cubbin C Sundquist K Ahlén H Johansson SE Winkleby MA Sundquist J Neighborhood deprivation and cardiovascular disease risk factors: protective and harmful effectsScand J Public Health2006 34228237

    Not in our library10.1080/14034940500327935

  113. 113.

    Engström L-M Who is physically active? Cultural capital and sports participation from adolescence to middle age—a 38-year follow-up studyPhysical Education & Sport Pedagogy2008 13319343

    Not in our library10.1080/17408980802400510

  114. 114.

    Häkkinen U Järvelin MR Rosenqvist G Laitinen J Health, schooling and lifestyle among young adults in FinlandHealth Econ2006 1512011216

    Not in our library10.1002/hec.1123

  115. 115.

    Henriksson KM Lindblad U Ågren B Nilsson-Ehle P Råstam L Associations between unemployment and cardiovascular risk factors varies with the unemployment rate: the Cardiovascular Risk Factor Study in Southern Sweden (CRISS)Scand J Public Health2003 31305311

    Not in our library10.1080/14034940210164948

  116. 116.

    Kivimäki M Lawlor DA Davey Smith G Kouvonen A Virtanen M Elovainio M Vahtera J Socioeconomic position, co-occurrence of behavior-related risk factors, and coronary heart disease: the Finnish Public Sector studyAm J Public Health2007 97874879

    Not in our library10.2105/ajph.2005.078691

  117. 117.

    Korniloff K Häkkinen A Kautiainen H Koponen H Peltonen M Mäntyselkä P Oksa H Kampman O Vanhala M Leisure-time physical activity and metabolic syndrome plus depressive symptoms in the FIN-D2D surveyPrev Med2010 51466470

    Not in our library10.1016/j.ypmed.2010.09.007

  118. 118.

    Laaksonen M Lahelma E Prättälä R Associations among health-related behaviours: sociodemographic variation in FinlandSoz Praventivmed2002 47225232

    Not in our library10.1007/bf01326403

  119. 119.

    Laaksonen M Talala K Martelin T Rahkonen O Roos E Helakorpi S Laatikainen T Prättälä R Health behaviours as explanations for educational level differences in cardiovascular and all-cause mortality: a follow-up of 60 000 men and women over 23 yearsEur J Public Health2008 183843

    Not in our library10.1093/eurpub/ckm051

  120. 120.

    Lagerros YT Bellocco R Adami HO Nyrén O Measures of physical activity and their correlates: the Swedish National March CohortEur J Epidemiol2009 24161169

    Not in our library10.1007/s10654-009-9327-x

  121. 121.
    Is there a demand for physical activity interventions provided by the health care sector? Findings from a population survey · 2010
    Not checked
  122. 122.

    Lindström M Hanson BS Östergren PO Socioeconomic differences in leisure-time physical activity: the role of social participation and social capital in shaping health related behaviourSoc Sci Med2001 52441451

    Not in our library10.1016/s0277-9536(00)00153-2

  123. 123.

    Lindström M Isacsson SO Merlo J Increasing prevalence of overweight, obesity and physical inactivity: two population-based studies 1986 and 1994Eur J Public Health2003 13306312

    Not in our library10.1093/eurpub/13.4.306

  124. 124.

    Lindström M Moghaddassi M Merlo J Social capital and leisure time physical activity: a population based multilevel analysis in Malmo, SwedenJ Epidemiol Community Health2003 572328

    Not in our library10.1136/jech.57.1.23

  125. 125.

    Mäkinen T Borodulin K Laatikainen T Fogelholm M Prättälä R Twenty-five year socioeconomic trends in leisure-time and commuting physical activity among employed FinnsScand J Med Sci Sports2009 19188197

    Not in our library10.1111/j.1600-0838.2007.00739.x

  126. 126.

    Mäkinen T Kestilä L Borodulin K Martelin T Rahkonen O Leino-Arjas P Prättälä R Occupational class differences in leisure-time physical inactivity - contribution of past and current physical workload and other working conditionsScand J Work Environ Health2010 366270

    Not in our library10.5271/sjweh.2879

  127. 127.

    Mäkinen T Kestilä L Borodulin K Martelin T Rahkonen O Prättälä R Effects of childhood socio-economic conditions on educational differences in leisure-time physical activityEur J Public Health2010 20346353

    Not in our library10.1093/eurpub/ckp187

  128. 128.

    Mäkinen TE Borodulin K Tammelin TH Rahkonen O Laatikainen T Prättälä R The effects of adolescence sports and exercise on adulthood leisure-time physical activity in educational groupsInt J Behav Nutr Phys Act2010 727

    Not in our library10.1186/1479-5868-7-27

  129. 129.

    Molarius A The contribution of lifestyle factors to socioeconomic differences in obesity in men and women - A population-based study in SwedenEur J Epidemiol2003 18227234

    Not in our library10.1023/a:1023376012627

  130. 130.

    Nielsen TL Wraae K Brixen K Hermann AP Andersen M Hagen C Prevalence of overweight, obesity and physical inactivity in 20- to 29-year-old, Danish men. Relation to sociodemography, physical dysfunction and low socioeconomic status: the Odense Androgen StudyInt J Obes2006 30805815

    Not in our library10.1038/sj.ijo.0803197

  131. 131.

    Norman A Bellocco R Vaida F Wolk A Total physical activity in relation to age, body mass, health and other factors in a cohort of Swedish menInt J Obes Relat Metab Disord2002 26670675

    Not in our library10.1038/sj.ijo.0801955

  132. 132.

    Novak M Ahlgren C Hammarström A A life-course approach in explaining social inequity in obesity among young adult men and womenInt J Obes2006 30191200

    Not in our library10.1038/sj.ijo.0803104

  133. 133.

    Orsini N Bellocco R Bottai M Pagano M Wolk A Correlates of total physical activity among middle-aged and elderly womenInt J Behav Nutr Phys Act2007 416

    Not in our library10.1186/1479-5868-4-16

  134. 134.

    Osler M Gerdes LU Davidsen M Brønnum-Hansen H Madsen M Jørgensen T Schroll M Socioeconomic status and trends in risk factors for cardiovascular diseases in the Danish MONICA population, 1982–1992J Epidemiol Community Health2000 54108113

    Not in our library10.1136/jech.54.2.108

  135. 135.

    Osler M Clausen JO Ibsen KK Jensen GB Social influences and low leisure-time physical activity in young Danish adultsEur J Public Health2001 11130134

    Not in our library10.1093/eurpub/11.2.130

  136. 136.

    Osler M Godtfredsen NS Prescott E Childhood social circumstances and health behaviour in midlife: the Metropolit 1953 Danish male birth cohortInt J Epidemiol2008 3713671374

    Not in our library10.1093/ije/dyn115

  137. 137.

    Petersen CB Thygesen LC Helge JW Grønbæk M Tolstrup JS Time trends in physical activity in leisure time in the Danish population from 1987 to 2005Scand J Public Health2010 38121128

    Not in our library10.1177/1403494809357098

  138. 138.

    Piro FN Næss O Claussen B Area deprivation and its association with health in a cross-sectional study: Are the results biased by recent migration?Int J Equity Health2007 610

    Not in our library10.1186/1475-9276-6-10

  139. 139.

    Pudaric S Sundquist J Johansson SE Major risk factors for cardiovascular disease in elderly migrants in SwedenEthn Health2000 5137150

    Not in our library10.1080/713667448

  140. 140.

    Pulkki L Kivimäki M Elovainio M Viikari J Keltikangas-Järvinen L Contribution of socioeconomic status to the association between hostility and cardiovascular risk behaviors: a prospective cohort studyAm J Epidemiol2003 158736742

    Not in our library10.1093/aje/kwg204

  141. 141.

    Pulkki L Kivimäki M Keltikangas-Järvinen L Elovainio M Leino M Viikari J Contribution of adolescent and early adult personality to the inverse association between education and cardiovascular risk behaviours: prospective population-based cohort studyInt J Epidemiol2003 32968975

    Not in our library10.1093/ije/dyg097

  142. 142.

    Salonen MK Kajantie E Osmond C Forsén T Ylihärsilä H Paile-Hyvärinen M Barker DJ Eriksson JG Prenatal and childhood growth and leisure time physical activity in adult lifeEur J Public Health2010 21719724

    Not in our library10.1093/eurpub/ckq176

  143. 143.

    Schnohr C Højbjerre L Riegels M Ledet L Larsen T Schultz-Larsen K Petersen L Prescott E Grønæk M Does educational level influence the effects of smoking, alcohol, physical activity, and obesity on mortality? A prospective population studyScand J Public Health2004 32250256

    Not in our library10.1080/14034940310019489

  144. 144.

    Simonen RL Videman T Kaprio J Levälahti E Battié MC Factors associated with exercise lifestyle - A study of monozygotic twinsInt J Sports Med2003 24499505

    Not in our library10.1055/s-2003-42013

  145. 145.

    Sjögren K Stjernberg L A gender perspective on factors that influence outdoor recreational physical activity among the elderlyBMC Geriatr2010 1034

    Not in our library10.1186/1471-2318-10-34

  146. 146.

    Strand BH Tverdal A Can cardiovascular risk factors and lifestyle explain the educational inequalities in mortality from ischaemic heart disease and from other heart diseases? 26 year follow up of 50,000 Norwegian men and womenJ Epidemiol Community Health2004 58705709

    Not in our library10.1136/jech.2003.014563

  147. 147.

    Strandhagen E Berg C Lissner L Nunez L Rosengren A Torén K Thelle DS Selection bias in a population survey with registry linkage: potential effect on socioeconomic gradient in cardiovascular riskEur J Epidemiol2010 25163172

    Not in our library10.1007/s10654-010-9427-7

  148. 148.

    Suadicani P OleHein H Gyntelberg F Lifestyle, social class, and obesity-the Copenhagen Male StudyEur J Cardiovasc Prev Rehabil2005 12236242

    Not in our library10.1097/00149831-200506000-00009

  149. 149.

    Tammelin T Näyhä S Laitinen J Rintamäki H Järvelin MR Physical activity and social status in adolescence as predictors of physical inactivity in adulthoodPrev Med2003 37375381

    Not in our library10.1016/s0091-7435(03)00162-2

  150. 150.

    Wemme KM Rosvall M Work related and non-work related stress in relation to low leisure time physical activity in a Swedish populationJ Epidemiol Community Health2005 59377379

    Not in our library10.1136/jech.2004.031526

  151. 151.

    Adams J The mediating role of time perspective in socio-economic inequalities in smoking and physical activity in older English adultsJ Health Psychol2009 14794799

    Not in our library10.1177/1359105309338979

  152. 152.

    Amuzu A Carson C Watt HC Lawlor DA Ebrahim S Influence of area and individual lifecourse deprivation on health behaviours: findings from the British Women's Heart and Health StudyEur J Cardiovasc Prev Rehabil2009 16169173

    Not in our library10.1097/hjr.0b013e328325d64d

  153. 153.

    Bartley M Fitzpatrick R Firth D Marmot M Social distribution of cardiovascular disease risk factors: change among men in England 1984–1993J Epidemiol Community Health2000 54806814

    Not in our library10.1136/jech.54.11.806

  154. 154.

    Bartley M Martikainen P Shipley M Marmot M Gender differences in the relationship of partner's social class to behavioural risk factors and social support in the Whitehall II studySoc Sci Med2004 5919251936

    Not in our library10.1016/j.socscimed.2004.03.002

  155. 155.

    Chaudhury M Shelton N Physical activity among 60-69-year-olds in England: knowledge, perception, behaviour and risk factorsAgeing & Society2010 3013431355

    Not in our library10.1017/s0144686x10000486

  156. 156.

    Ecob R Macintyre S Small area variations in health related behaviours; do these depend on the behaviour itself, its measurement, or on personal characteristics?Health Place2000 6261274

    Not in our library10.1016/s1353-8292(00)00008-3

  157. 157.

    Harrison RA McElduff P Edwards R Planning to win: Health and lifestyles associated with physical activity amongst 15,423 adultsPublic Health2006 120206212

    Not in our library10.1016/j.puhe.2005.08.021

  158. 158.

    Heslop P Smith GD Macleod J Hart C The socioeconomic position of employed women, risk factors and mortalitySoc Sci Med2001 53477485

    Not in our library10.1016/s0277-9536(00)00350-6

  159. 159.

    Hillsdon M Lawlor DA Ebrahim S Morris JN Physical activity in older women: associations with area deprivation and with socioeconomic position over the life course: observations in the British Women's Heart and Health StudyJ Epidemiol Community Health2008 62344350

    Not in our library10.1136/jech.2006.058610

  160. 160.

    Lahelma E Lallukka T Laaksonen M Martikainen P Rahkonen O Chandola T Head J Marmot M Kagamimori S Tatsuse T Sekine M Social class differences in health behaviours among employees from Britain, Finland and Japan: The influence of psychosocial factorsHealth Place2010 166170

    Not in our library10.1016/j.healthplace.2009.08.004

  161. 161.

    Livingstone MB Robson PJ McCarthy S Kiely M Harrington K Browne P Galvin M Wareham NJ Rennie KL Physical activity patterns in a nationally representative sample of adults in IrelandPublic Health Nutr2001 411071116

    Not in our library10.1079/phn2001192

  162. 162.

    Lunn PD The sports and exercise life-course: a survival analysis of recall data from IrelandSoc Sci Med2010 70711719

    Not in our library10.1016/j.socscimed.2009.11.006

  163. 163.

    Mein GK Shipley MJ Hillsdon M Ellison GT Marmot MG Work, retirement and physical activity: cross-sectional analyses from the Whitehall II studyEur J Public Health2005 15317322

    Not in our library10.1093/eurpub/cki087

  164. 164.

    Mullineaux DR Barnes CA Barnes EF Factors affecting the likelihood to engage in adequate physical activity to promote healthJ Sports Sci2001 19279288

    Not in our library10.1080/026404101750158376

  165. 165.

    Mutrie N Hannah MK Some work hard while others play hard: The achievement of current recommendations for physical activity levels at work, at home, and in leisure time in the West of ScotlandInt J Health Promot Edu2004 42109117

    Not in our library

  166. 166.

    Myint PK Luben RN Welch AA Bingham SA Wareham NJ Khaw KT Effect of age on the relationship of occupational social class with prevalence of modifiable cardiovascular risk factors and cardiovascular diseases. A population-based cross-sectional study from European Prospective Investigation into Cancer - Norfolk (EPIC-Norfolk)Gerontology2006 525158

    Not in our library10.1159/000089826

  167. 167.

    Poortinga W Associations of physical activity with smoking and alcohol consumption: a sport or occupation effect?Prev Med2007 456670

    Not in our library10.1016/j.ypmed.2007.04.013

  168. 168.

    Popham F Mitchell R Leisure time exercise and personal circumstances in the working age population: longitudinal analysis of the British household panel surveyJ Epidemiol Community Health2006 60270274

    Not in our library10.1136/jech.2005.041194

  169. 169.

    Popham F Intergenerational social class stability and mobility are associated with large absolute differences in adult participation in sport and exerciseBr J Sports Med2010 4411841185

    Not in our library10.1136/bjsm.2009.059626

  170. 170.

    Stamatakis E Chaudhury M Temporal trends in adults' sports participation patterns in England between 1997 and 2006: the Health Survey for EnglandBr J Sports Med2008 42601608

    Not in our library10.1136/bjsm.2008.048082

  171. 171.

    Wardle J Griffith J Socioeconomic status and weight control practices in British adultsJ Epidemiol Community Health2001 55185190

    Not in our library10.1136/jech.55.3.185

  172. 172.

    Wardle J Steptoe A Socioeconomic differences in attitudes and beliefs about healthy lifestylesJ Epidemiol Community Health2003 57440443

    Not in our library10.1136/jech.57.6.440

  173. 173.

    Watt HC Carson C Lawlor DA Patel R Ebrahim S Influence of life course socioeconomic position on older women's health behaviors: findings from the British Women's Heart and Health StudyAm J Public Health2009 99320327

    Not in our library10.2105/ajph.2007.129288

Cited by papers we hold 10

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.