Physical Activity Levels, Correlates, and All-Cause Mortality Risk in People Living With Different Health Conditions.

BACKGROUND: To better understand physical activity behavior and its health benefits in people living with health conditions, we studied people with and without 20 different self-reported health conditions with regard to (1) their physical activity levels, (2) factors correlated with these physical activity levels, and (3) the association between physical activity and all-cause mortality. METHODS: We used a subsample (n = 88,659) of the Lifelines cohort study from the Netherlands. For people living with and without 20 different self-reported health conditions, we studied the aforementioned factors in relation to physical activity. Physical activity was assessed with the Short Questionnaire to Assess Health-Enhancing Physical Activity Questionnaire, and mortality data were obtained from the Dutch death register. RESULTS: People with a reported health condition were less likely to meet physical activity guidelines than people without a reported health condition (odds ratios ranging from 0.55 to 0.89). Higher body mass index and sitting time, and lower self-rated health, physical functioning, and education levels were associated with lower odds of meeting physical activity guidelines across most health conditions. Finally, we found a protective association between physical activity and all-cause mortality in both people living with and without different health conditions. CONCLUSION: People living with different health conditions are generally less physically active compared with people living without a health condition. Both people living with and without self-reported health conditions share a number of key factors associated with physical activity levels. We also observed the expected protective association between physical activity and all-cause mortality.

Stability of clustering of lifestyle risk factors in the Dutch adult population and the association with mental health.

BACKGROUND: Lifestyle factors often co-occur in clusters. This study examines whether clusters of lifestyle risk factors, such as smoking, alcohol use, physical inactivity, poor diet, sexual risk behaviour, cannabis and other drug use, change over time in a representative sample of Dutch adults. Additionally, the association between mental health and self-reported depression of lifestyle clusters was examined. METHODS: Each year cross-sectional data of approximately 7500 individuals of 18 years and older from the annual Dutch Health Survey of 2014-2019 were used. Clusters were determined by a two-step cluster analysis. Furthermore, regression analyses determined the association between clusters of lifestyle risk factors and mental health. RESULTS: Results show six clusters composed of one, multiple or no lifestyle risk factors. The clusters remained relatively stable over time: in some clusters, the number of people slightly changed between 2014 and 2019. More specifically, clusters that increased in size were the cluster with no lifestyle risk factors and the cluster with multiple lifestyle risk factors. Furthermore, results show that clusters with none to a few lifestyle risk factors were associated with better mental health and a lower prevalence of self-reported depression compared with clusters with multiple lifestyle risk factors. CONCLUSIONS: The clustering of lifestyle risk factors remained stable over time. People with multiple lifestyle risk factors had poorer mental health than those without risk factors. These findings may emphasize the need for intervention strategies targeting this subgroup with multiple lifestyle risk factors.

[The Lifestyle Monitor: prevalence rates for health policy]. / De Leefstijlmonitor: Cijfers voor gezondheidsbeleid.

The Lifestyle Monitor (LSM) was launched in 2013 on behalf of the Ministry of Health, Welfare and Sports to reorganize the multiple data collections in the field of lifestyle and health in the Netherlands. The reorganization should enhance the efficiency and coherence of the lifestyle and health data collections and should provide unambiguous figures for policymakers. This article describes the background and content (including the lifestyle-themes) of the LSM and the tasks and roles of the collaborating parties involved. The measurement methods used and requirements for data requests are described as well. Finally, some examples of figures and trends over the period 2014-2020 to underpin the health policy are described.

An inventory of national surveillance systems assessing physical activity, sedentary behaviour and sport participation of adults in the European Union.

BACKGROUND: Physical inactivity has been recognised as a global public health problem that requires concerted action. This calls for systematic physical activity (PA) surveillance as a mechanism for assessing the problem and evaluating the effectiveness of related policies. Because countries tend to design their policy measures based on national surveillance data, here we present an inventory of existing national surveillance systems on PA, sedentary behaviour (SB) and sport participation (SP) among adult population in all European Union (EU) Member States. METHODS: As a part of the European Physical Activity and Sports Monitoring System (EUPASMOS) project, a questionnaire was constructed in the form of an on-line survey to collect detailed information on existing national surveillance systems on either PA, SB, or SP. National HEPA focal points from all 27 EU Member States were invited to answer the on-line questionnaire and data collection took part in the period May 2018-September 2019. RESULTS: National monitoring of PA or SB or SP for adults has been established in 16/27 EU Member States, that host 33 different PA/SB/SP monitoring systems. Apart from 3 countries that are using accelerometers (Finland, Ireland and Portugal), surveillance is typically based on questionnaires. In most Member States these questionnaires have not been validated in the particular language and cultural setting. Next, specific domains and dimensions of PA, SB and SP assessed vary a lot across countries. Only 3 countries (the Netherlands, Portugal and Slovenia) are monitoring all three behaviours while covering most of the domains and dimensions of PA/SB/SP. Lastly, as half of the existing surveillance systems set an upper age limit, in 9/16 countries that are monitoring PA/SB/SP, no data for people older than 80 years are available. CONCLUSIONS: Systematic surveillance of PA is lacking among 11/27 EU countries, with even few monitoring SB and SP. Besides, existing surveillance systems typically fail to assess all dimensions and domains of PA/SB/SP with only three countries maintaining monitoring systems that encompass all three behaviours while covering most of the domains and dimensions of PA/SB/SP. Hence, additional efforts in advocacy of systematic PA surveillance in the EU are called for.

Development of national physical activity recommendations in 18 EU member states: a comparison of methodologies and the use of evidence.

OBJECTIVES: The aim of the study is to compare how member states of the European Union (EU) develop their national physical activity (PA) recommendations and to provide an overview of the methodologies they apply in doing so. Information was collected directly from the physical activity focal points of EU member states in 2018. Five countries were chosen for detailed case study analysis of development processes. DESIGN: Cross-sectional survey. PARTICIPANTS: The representatives of the 28 EU member state governments to the EU physical activity Focal Point Network. OUTCOME MEASURES: From national documents we extracted data on (1) the participants of the development process, (2) the different methods used during development, and (3) on which sources national PA recommendations were based. An additional survey for case study countries provided details on (1) anonymised information on the participants of development process, (2) methods employed and rationale for choosing them, (3) development process and timeline, and (4) main source documents used for recommendation development. RESULTS: Eighteen national documents on PA recommendations contained information about development process. The results showed that countries used different approaches to develop national recommendations. The main strategies were (1) adoption of WHO 2010 recommendations or (2) a combination of analysis and adoption of other national and international recommendations and literature review. All of the five case study countries relied on review processes rather than directly adopting WHO recommendations. CONCLUSIONS: While there are arguments for the use of particular strategies for PA recommendation development, there is currently no evidence for the general superiority of a specific approach. Instead, our findings highlight the broad spectrum of potential development methods, resources utilisation and final recommendations design currently available to national governments. These results may be a source of inspiration for other countries currently planning the development or update of national PA recommendations.

The added value of using the HEPA PAT for physical activity policy monitoring: a four-country comparison.

BACKGROUND: Public policy is increasingly recognized as an important component of physical activity promotion. This paper reports on the current status of physical activity policy development and implementation in four European countries based on the Health-Enhancing Physical Activity Policy Audit Tool (HEPA PAT) developed by WHO. It compares the findings to previous studies and discusses the general utility of this tool and its unique features in relation to other instruments. METHODS: The study was conducted as part of the Policy Evaluation Network ( www.jpi-pen.eu ) in Germany, Ireland, the Netherlands and Poland. Data collection built upon information obtained via the EU Physical Activity Monitoring Framework survey, additional desk research and expert opinion. Data analysis employed Howlett's policy cycle framework to map and compare national physical activity policies in the four countries. RESULTS: In all countries under study, policy agenda-setting is influenced by prevalence data from national health monitoring systems, and the sport and/or health sector takes the lead in policy formulation. Key policy documents were located mainly in the health sector but also in sport, urban design and transport. Physical activity programmes implemented to meet policy objectives usually cover a broad range of target groups, but currently only a small selection of major policies are evaluated for effectiveness. National experts made several suggestions to other countries wishing to establish physical activity policies, e.g. regarding cross-sectoral support and coordination, comprehensive national action plans, and monitoring/surveillance. CONCLUSIONS: This study provides a detailed overview of physical activity policies in the four countries. Results show that national governments are already very active in the field but that there is room for improvement in a number of areas, e.g. regarding the contribution of sectors beyond sport and health. Using the HEPA PAT simultaneously in four countries also showed that procedures and timelines have to be adapted to national contexts. Overall, the instrument can make an important contribution to understanding and informing physical activity policy, especially when used as an add-on to regular monitoring tools like the EU HEPA Monitoring Framework.

Exploring mechanisms underlying the relationship between the natural outdoor environment and health and well-being - Results from the PHENOTYPE project.

BACKGROUND: Despite the large number of studies on beneficial effects of the natural outdoor environment (NOE) on health, the underlying mechanisms are not fully understood. OBJECTIVE: This study explored the relations between amount, quality, use and experience of the NOE; and physical activity, social contacts and mental well-being. METHODS: In this cross-sectional study, data on GIS-derived measures of residential surrounding greenness (NDVI), NOE within 300 m, and audit data on quality of the streetscape were combined with questionnaire data from 3947 adults in four European cities. These included time spent in NOE (use); and perceived greenness, and satisfaction with and importance given to the NOE (experience). Physical activity, social contacts and mental health were selected as key outcome indicators. Descriptive and multilevel analyses were conducted both on pooled data and for individual cities. RESULTS: More minutes spent in the NOE were associated with more minutes of physical activity, a higher frequency of social contacts with neighbors, and better mental well-being. Perceived greenness, satisfaction with and importance of the NOE, were other strong predictors of the outcomes, while GIS measures of NOE and streetscape quality were not. We found clear differences between the four cities. CONCLUSIONS: Use and experience of the natural outdoor environment are important predictors for beneficial effects of the natural outdoor environment and health. Future research should focus more on these aspects to further increase our understanding of these mechanisms, and needs to take the local context into account.

Chronically ill patients' preferences for a financial incentive in a lifestyle intervention. Results of a discrete choice experiment.

BACKGROUND: The preferences of diabetes type 2 patients and cardiovascular disease patients for a financial incentive added to a specified combined lifestyle intervention were investigated. METHODS: A discrete choice experiment questionnaire was filled out by 290 diabetes type 2 patients (response rate 29.9%). Panel-mixed-logit models were used to estimate the preferences for a financial incentive. Potential uptake rates of different financial incentives and relative importance scores of the included attributes were estimated. Included attributes and levels were: form of the incentive (cash money and different types of vouchers), value of the incentive (ranging from 15 to 100 euros), moment the incentive is received (start, halfway, after finishing the intervention) and prerequisite for receiving the incentive (registration, attendance or results at group or individual level). RESULTS: Prerequisites for receiving the financial incentive were the most important attribute, according to the respondents. Potential uptake rates for different financial incentives ranged between 37.9% and 58.8%. The latter uptake rate was associated with a financial incentive consisting of cash money with a value of €100 that is handed out after completing the lifestyle program with the prerequisite that the participant attended at least 75% of the scheduled meetings. CONCLUSIONS: The potential uptake of the different financial incentives varied between 37.9% and 58.8%. The value of the incentive does not significantly influence the potential uptake. However, the potential uptake and associated potential effect of the financial incentive is influenced by the type of financial incentive. The preferred type of incentive is €100 in cash money, awarded after completing the lifestyle program if the participant attended at least 75% of the scheduled meetings.

Dog ownership, the natural outdoor environment and health: a cross-sectional study.

OBJECTIVES: Dog owners walking their dog in natural outdoor environments (NOE) may benefit from the physical activity facilitated by dog walking and from time spent in nature. However, it is unclear whether dog owners receive additional health benefits associated with having access to NOE above the physical activity benefit of walking with their dog. We investigated associations between dog ownership, walking, time spent in NOE and health and whether these associations differed among those with good and poor access to NOE and those living in green and less green areas. DESIGN: Cross-sectional study. SETTING: The Positive Health Effects of the Natural Outdoor Environment in Typical Populations in Different Regions in Europe project. PARTICIPANTS: n=3586 adults from Barcelona (Spain), Doetinchem (the Netherlands), Kaunas (Lithuania) and Stoke-on-Trent (UK). DATA COLLECTION AND ANALYSIS: We calculated access to NOE with land maps and residential surrounding greenness with satellite data. Leisure time walking, time spent in NOE and general and mental health status were measured using validated questionnaires. Associations were estimated using multilevel analysis with a random intercept defined at the neighbourhood level. RESULTS: Dog ownership was associated with higher rates of leisure time walking and time spending in NOE (OR 2.17, 95% CI 1.86 to 2.54 and 2.37, 95% CI 2.02 to 2.79, respectively). These associations were stronger in those living within 300 m of a NOE and in greener areas. No consistent associations were found between dog ownership and perceived general or mental health status. CONCLUSIONS: Compared with non-dog owners, dog owners walked more and spent more time in NOE, especially those living within 300 m of a NOE and in greener areas. The health implications of these relationships should be further investigated. In a largely physically inactive society, dog walking in NOE may be a simple way of promoting physical activity and health.

Living Close to Natural Outdoor Environments in Four European Cities: Adults' Contact with the Environments and Physical Activity.

This study investigated whether residential availability of natural outdoor environments (NOE) was associated with contact with NOE, overall physical activity and physical activity in NOE, in four different European cities using objective measures. A nested cross-sectional study was conducted in Barcelona (Spain); Stoke-on-Trent (United Kingdom); Doetinchem (The Netherlands); and Kaunas (Lithuania). Smartphones were used to collect information on the location and physical activity (overall and NOE) of around 100 residents of each city over seven days. We used Geographic Information Systems (GIS) to determine residential NOE availability (presence/absence of NOE within 300 m buffer from residence), contact with NOE (time spent in NOE), overall PA (total physical activity), NOE PA (total physical activity in NOE). Potential effect modifiers were investigated. Participants spent around 40 min in NOE and 80 min doing overall PA daily, of which 11% was in NOE. Having residential NOE availability was consistently linked with higher NOE contact during weekdays, but not to overall PA. Having residential NOE availability was related to NOE PA, especially for our Barcelona participants, people that lived in a city with low NOE availability.

Greener living environment healthier people?: Exploring green space, physical activity and health in the Doetinchem Cohort Study.

BACKGROUND: Evidence is emerging that more green space in the living environment is associated with better health, partly via the pathway of physical activity. OBJECTIVES: We explored the cross-sectional and longitudinal associations between green space and physical activity and several health indicators in the Doetinchem Cohort Study. METHODS: A random sample of men and women aged 20-59years at baseline was measured max 5 times with 5year-intervals in the period 1987-2012. Data of round 3-5 were used. Measurements were based on examinations (height, weight, blood pressure) or questionnaires (physical activity, perceived health, depressive symptoms, chronic conditions). The percentage of green space (mainly urban and agricultural green) around the home address (125m and 1km) was calculated using satellite data. RESULTS: More agricultural green was associated with less time spent on bicycling (ß1km=-0.15, 95%CL -0.13; -0.04) and sports (ß1km=-0.04, 95%CL -0.07; -0.01) and more time spent on gardening (ß1km=0.16, 95%CL 0.12; 0.19) and odd jobs (ß1km=0.10, 95%CL 0.05; 0.15), and this was in the other direction for urban green. For only a few of the many health indicators a positive association with green was found, and mainly for total green within 1km radius. Longstanding green or a transition to more green did not show more pronounced associations with health. CONCLUSIONS: For the green space range of the Doetinchem area the findings do not strongly support the hypothesis that the percentage of green in the living environment affects health positively. The distinction by type of green may, however, be relevant for physical activity.

Independent and combined effects of physical activity and body mass index on the development of Type 2 Diabetes - a meta-analysis of 9 prospective cohort studies.

BACKGROUND: The aim of this harmonized meta-analysis was to examine the independent and combined effects of physical activity and BMI on the incidence of type 2 diabetes. METHODS: Our systematic literature review in 2011 identified 127 potentially relevant prospective studies of which 9 fulfilled the inclusion criteria (total N = 117,878, 56.2 % female, mean age = 50.0 years, range = 25-65 years). Measures of baseline physical activity (low, intermediate, high), BMI-category [BMI < 18.4 (underweight), 18.5-24.9 (normal weight), 25.0-29.9 (overweight), 30+ (obese)] and incident type 2 diabetes were harmonized across studies. The associations between physical activity, BMI and incident type 2 diabetes were analyzed using Cox regression with a standardized analysis protocol including adjustments for age, gender, educational level, and smoking. Hazard ratios from individual studies were combined in a random-effects meta-analysis. RESULTS: Mean follow-up time was 9.1 years. A total of 11,237 incident type 2 diabetes cases were recorded. In mutually adjusted models, being overweight or obese (compared with normal weight) and having low physical activity (compared with high physical activity) were associated with an increased risk of incident type 2 diabetes (hazard ratios 2.33, 95 % CI 1.95-2.78; 6.10, 95 % CI: 4.63-8.04, and 1.23, 95 % CI: 1.09-1.39, respectively). Individuals who were both obese and had low physical activity had 7.4-fold (95 % CI 3.47-15.89) increased risk of type 2 diabetes compared with normal weight, high physically active participants. CONCLUSIONS: This harmonized meta-analysis shows the importance of maintaining a healthy weight and being physically active in diabetes prevention.

Health in All Policies? The case of policies to promote bicycle use in the Netherlands.

To gather insight on how Health in All Policies (HiAP) is applied in practice, we carried out a case study on transport policies intended to stimulate a shift from car use to bicycling. We reviewed 3 years (2010, 2011, and 2012) of national budgets and policy documents in the Netherlands, followed by two focus group sessions and a second round of document analysis. We found to our surprise, given the country's history of bicycle promotion, that no HiAP approaches for bicycle promotion remain in place in national transport policies. The Netherlands may face serious challenges in the near future for facilitating bicycle use. Inclusion of health goals requires that the health sector work towards acquiring a better understanding of core values in other sector's policies.

Transport choice when travelling to a sports facility: the role of perceived route features - Results from a cross-sectional study in the Netherlands.

BACKGROUND: Physical activity and sedentary behaviour are independently associated with health outcomes, where physical activity (PA) is associated with health benefits and sedentary behaviour is associated with health risks. One possible strategy to counteract sedentary behaviour is to stimulate active transport use. As monitoring studies in the Netherlands have shown that among sedentary people the proportion of adults who engage in sports (hereafter: sports practitioners) is 62.3%, sports practitioners seem a feasible target group for this strategy. Previous studies have generally reported associations between neighbourhood characteristics and active transport use. However, the neighbourhood covers only part of the route to a certain destination. Therefore, we examined the association between perceived route features and transport choice when travelling up to 7.5 kilometres to a sports facility among sports practitioners. METHODS: For 1118 Dutch sports practitioners - who indicated that they practice a sport and travel to a sports facility - age 18 and older, data on transport choice and perceived features of the route to a sports facility were gathered. Participants were classified into one of three transport groups based on their transport choice: car users, cyclists and walkers. Participants were asked whether perceived route features influenced their transport choice. Logistic regression was used to model the odds of cycling versus car use and walking versus car use in the association with perceived route features, adjusted for potential confounders. RESULTS: Perceived traffic safety was associated with lower odds of cycling (OR: 0.36, 95% CI: 0.15-0.86). Perceived route duration was associated with lower odds of both cycling (OR: 0.54, 95%CI: 0.39-0.75) and walking (OR: 0.60, 95%CI: 0.36-1.00). Perceived distance to a sports facility and having to make a detour when using other transport modes than the chosen transport mode were associated with higher odds of both cycling and walking (ORrange: 1.82-5.21). What and who people encountered during their trip (i.e. visual aspects) was associated with higher odds of both cycling and walking (ORrange: 2.40-3.69). CONCLUSIONS: Perceived traffic safety, duration, distance, detour, and visual aspects, when travelling to a sports facility were associated with transport choice. Therefore, the perception of route features should be considered when stimulating active transport use among sports practitioners.

How combined trip purposes are associated with transport choice for short distance trips. Results from a cross-sectional study in the Netherlands.

BACKGROUND: One way to increase physical activity is to stimulate a shift from car use to walking or cycling. In single-purpose trips, purpose was found to be an important predictor of transport choice. However, as far as known, no studies have been conducted to see how trips with combined purposes affect this decision. This study was designed to provide insight into associations between combined purposes and transport choice. METHODS: An online questionnaire (N = 3,663) was used to collect data concerning transport choice for four primary purposes: shopping, going to public natural spaces, sports, and commuting. Per combination of primary trip purpose and transport choice, participants were asked to give examples of secondary purposes that they combine with the primary purpose. Logistic regression analyses were used to model the odds of both cycling and walking versus car use. RESULTS: Primary trip purposes combined with commuting, shopping, visiting private contacts or medical care were more likely to be made by car than by cycling or walking. Combinations with visiting catering facilities, trips to social infrastructure facilities, recreational outings, trips to facilities for the provision of daily requirements or private contacts during the trip were more likely to be made by walking and/or cycling than by car. CONCLUSION: Combined trip purposes were found to be associated with transport choice. When stimulating active transport focus should be on the combined-trip purposes which were more likely to be made by car, namely trips combined with commuting, other shopping, visiting private contacts or medical care.

Positive health effects of the natural outdoor environment in typical populations in different regions in Europe (PHENOTYPE): a study programme protocol.

INTRODUCTION: Growing evidence suggests that close contact with nature brings benefits to human health and well-being, but the proposed mechanisms are still not well understood and the associations with health remain uncertain. The Positive Health Effects of the Natural Outdoor environment in Typical Populations in different regions in Europe (PHENOTYPE) project investigates the interconnections between natural outdoor environments and better human health and well-being. AIMS AND METHODS: The PHENOTYPE project explores the proposed underlying mechanisms at work (stress reduction/restorative function, physical activity, social interaction, exposure to environmental hazards) and examines the associations with health outcomes for different population groups. It implements conventional and new innovative high-tech methods to characterise the natural environment in terms of quality and quantity. Preventive as well as therapeutic effects of contact with the natural environment are being covered. PHENOTYPE further addresses implications for land-use planning and green space management. The main innovative part of the study is the evaluation of possible short-term and long-term associations of green space and health and the possible underlying mechanisms in four different countries (each with quite a different type of green space and a different use), using the same methodology, in one research programme. This type of holistic approach has not been undertaken before. Furthermore there are technological innovations such as the use of remote sensing and smartphones in the assessment of green space. CONCLUSIONS: The project will produce a more robust evidence base on links between exposure to natural outdoor environment and human health and well-being, in addition to a better integration of human health needs into land-use planning and green space management in rural as well as urban areas.

Cross-sectional associations of objectively measured physical activity, cardiorespiratory fitness and anthropometry in European adults.

OBJECTIVE: To quantify the independent associations between objectively measured physical activity (PA), cardiorespiratory fitness (CRF), and anthropometry in European men and women. METHODS: 2,056 volunteers from 12 centers across Europe were fitted with a heart rate and movement sensor at 2 visits 4 months apart for a total of 8 days. CRF (ml/kg/min) was estimated from an 8 minute ramped step test. A cross-sectional analysis of the independent associations between objectively measured PA (m/s(2)/d), moderate and vigorous physical activity (MVPA) (%time/d), sedentary time (%time/d), CRF, and anthropometry using sex stratified multiple linear regression was performed. RESULTS: In mutually adjusted models, CRF, PA, and MVPA were inversely associated with all anthropometric markers in women. In men, CRF, PA, and MVPA were inversely associated with BMI, whereas only CRF was significantly associated with the other anthropometric markers. Sedentary time was positively associated with all anthropometric markers, however, after adjustment for CRF significant in women only. CONCLUSION: CRF, PA, MVPA, and sedentary time are differently associated with anthropometric markers in men and women. CRF appears to attenuate associations between PA, MVPA, and sedentary time. These observations may have implications for prevention of obesity.

Personal and environmental characteristics associated with choice of active transport modes versus car use for different trip purposes of trips up to 7.5 kilometers in The Netherlands.

INTRODUCTION: This explorative study examines personal and neighbourhood characteristics associated with short-distance trips made by car, bicycle or walking in order to identify target groups for future interventions. METHODS: Data were derived from 'Mobility Research Netherlands (2004-2009; MON)', a dataset including information regarding trips made by household members (n = ±53,000 respondents annually). Using postal codes of household addresses, MON data were enriched with data on neighbourhood typologies. Multilevel logistic modelling was used to calculate odds ratio (OR) of active transport versus car use associated with four different trip purposes (shopping (reference), commuting, taking or bringing persons or sports). A total of 277,292 short distance trips made by 102,885 persons were included in analyses. RESULTS: Compared to women shopping, women less often take active transport to sports clubs (OR = 0.88) and men less often take active transport for shopping (OR = 0.92), or for bringing or taking persons (OR = 0.76). Those aged 25-34 years (OR = 0.83) and 35-44 years (OR = 0.96) were more likely to use active transport for taking or bringing persons than persons belonging to the other age groups (relative to trips made for shopping by those 65 years or over). A higher use of active transport modes by persons with an university or college degree was found and particularly persons living in urban-centre neighbourhoods were likely to use active transport modes. CONCLUSION: IN DEVELOPING POLICIES PROMOTING A MODE SHIFT SPECIAL ATTENTION SHOULD BE GIVEN TO THE FOLLOWING GROUPS: a) men making short distance trips for taking or bringing persons, b) women making short distance trips to sport facilities, c) persons belonging to the age groups of 25-44 years of age, d) Persons with a primary school or lower general secondary education degree and persons with a high school or secondary school degree and e) persons living in rural or urban-green neighbourhoods.

Validity of a short questionnaire to assess physical activity in 10 European countries.

To accurately examine associations of physical activity (PA) with disease outcomes, a valid method of assessing free-living activity is required. We examined the validity of a brief PA questionnaire (PAQ) used in the European Prospective Investigation into Cancer and Nutrition (EPIC). PA energy expenditure (PAEE) and time spent in moderate and vigorous physical activity (MVPA) was measured in 1,941 healthy individuals from 10 European countries using individually-calibrated combined heart-rate and movement sensing. Participants also completed the short EPIC-PAQ, which refers to past year's activity. Pearson (r) and Spearman (σ) correlation coefficients were calculated for each country, and random effects meta-analysis was used to calculate the combined correlation across countries to estimate the validity of two previously- and one newly-derived ordered, categorical PA indices ("Cambridge index", "total PA index", and "recreational index") that categorized individuals as inactive, moderately inactive, moderately active, or active. The strongest associations with PAEE and MVPA were observed for the Cambridge index (r = 0.33 and r = 0.25, respectively). No significant heterogeneity by country was observed for this index (I(2) = 36.3%, P = 0.12; I(2) = 0.0%, P = 0.85), whereas heterogeneity was suggested for other indices (I(2) > 48%, P < 0.05, I(2) > 47%, P < 0.05). PAEE increased linearly across self-reported PA categories (P for trend <0.001), with an average difference of approximately 460 kJ/d for men and 365 kJ/d for women, between categories of the Cambridge index. The EPIC-PAQ is suitable for categorizing European men and women into four distinct categories of overall physical activity. The difference in PAEE between categories may be useful when estimating effect sizes from observational research.