Exploring the difference between men and women in physical functioning: How do sociodemographic, lifestyle- and health-related determinants contribute?

BACKGROUND: To explore whether differences between men and women in the sensitivity to (strength of the association) and/or in the exposure to determinants (prevalence) contribute to the difference in physical functioning, with women reporting more limitations. METHODS: Data of the Doetinchem Cohort Study was used (n = 5856, initial ages 26-70 years), with follow-up measurements every 5 years (up to 20). Physical functioning (subscale SF-36, range:0-100), sex (men or women) and a number of socio-demographic, lifestyle- and health-related determinants were assessed. Mixed-model multivariable analysis was used to investigate differences between men and women in sensitivity (interaction term with sex) and in exposure (change of the sex difference when adjusting) to determinants of physical functioning. RESULTS: The physical functioning score among women was 6.55 (95%CI:5.48,7.61) points lower than among men. In general, men and women had similar determinants, but pain was more strongly associated with physical functioning (higher sensitivity), and also more prevalent among women (higher exposure). The higher exposure to low educational level and not having a paid job also contributed to the lower physical functioning score among women. In contrast, current smoking, mental health problems and a low educational level were more strongly associated with a lower physical functioning score among men and lower physical activity and higher BMI were more prevalent among men. CONCLUSIONS: Although important for physical functioning among both men and women, our findings provide no indications for reducing the difference in physical functioning by promoting a healthy lifestyle but stress the importance of differences in pain, work and education.

20-year individual physical activity patterns and related characteristics.

BACKGROUND: This study aims to describe individual leisure-time physical activity patterns among Dutch adults over a 20-year period, and to compare baseline characteristics of participants with different patterns. METHODS: The study population consisted of 2,518 adults (53% women) aged 26-65 years at baseline, measured every 5 years over a 20-year period. Self-reported physical activity measurements (from 1994 to 2017) were used to compose five (predefined) patterns: stable active, becoming active, becoming inactive, stable inactive, and varying physical activity. Multivariate logistic regression analyses were used to compare baseline socio-demographic, lifestyle, and health-related characteristics of these patterns. RESULTS: The total population shows a stable percentage being active in each round (between 55 and 58%). However over a period of 20 years, 32.6% of the participants were stable active, 19.9% were stable inactive, 15.2% became active, 11.6% became inactive, and 20.8% had varying physical activity behaviour. Compared to participants who were stable active, becoming active was associated with being 46-55 years old, having an intermediate level of education, and smoking, at baseline. Participants who became inactive were less likely to be 46-55 years old and more likely to be obese. Stable inactivity was associated with an intermediate level of education, low adherence to dietary guidelines, smoking, low levels of alcohol use and a moderate/poor perceived health. Participants with a varying physical activity level were more likely to have low adherence to dietary guidelines and to smoke. CONCLUSIONS: Almost half of the participants changed their physical activity behaviour over 20 years. Baseline age, level of education, smoking, alcohol consumption, adherence to dietary guidelines, weight status and perceived health were associated with different physical activity patterns.

Associations of self-reported physical activity and anxiety symptoms and status among 7,874 Irish adults across harmonised datasets: a DEDIPAC-study.

BACKGROUND: Anxiety is an adaptive response to an objective or perceived threat; however, when symptoms become severe and chronic it that can become a maladaptive anxiety disorder. Limited evidence suggests that physical activity may be associated with prevention against anxiety. This study uses data from The Irish Longitudinal Study on Ageing (TILDA) and The Mitchelstown Cohort Study to investigate cross-sectional associations between physical activity and anxiety symptoms and status among Irish adults. METHODS: Both datasets were harmonized (n = 7874). The short form International Physical Activity Questionnaire measured physical activity. Participants were classified as meeting World Health Organization physical activity guidelines (≥150 min weekly of moderate intensity physical activity, ≥75 min weekly of vigorous intensity physical activity, or ≥ 600 MET-minutes) or not. They were also divided into three groups based on weekly MET-minutes of moderate-to-vigorous physical activity (Low: 0-599; Moderate: 600-1199; High: ≥1200), and three groups based on weekly minutes of walking (Low: 0-209; Moderate: 210-419; High: 420+). Anxiety symptoms were measured by the Hospital Anxiety and Depression Scale with a score of ≥8 indicating anxiety. Binomial logistic regression, adjusted for relevant confounders examined physical activity-anxiety associations. RESULTS: Females had higher rates of anxiety than males (28.0% vs 20.0%; p < 0.001). Following adjustment for relevant covariates, meeting physical activity guidelines was associated with 13.5% (95% CI: 2.0-23.7; p = 0.023) lower odds of anxiety. Moderate and High physical activity were associated with 13.5% (- 11.0-32.6; p = 0.254) and 13.6% (1.4-4.2; p = 0.030) lower odds of anxiety compared to Low physical activity, respectively. Moderate and High walking were associated with 2.1% (- 14.5-16.3; p = 0.789) and 5.1% (- 9.3-17.6; p = 0.467) lower odds of anxiety compared to Low walking, respectively. CONCLUSION: Meeting physical activity guidelines is associated with lower odds of anxiety, but the strength of associations did not increase considerably with increased physical activity levels.

Prevalence and correlates of domain-specific sedentary time of adults in the Netherlands: findings from the 2006 Dutch time use survey.

BACKGROUND: Relatively little is known about how total sedentary time is accumulated in different domains and if correlates of sedentary time differ across domains. Time use surveys present a unique opportunity to study sedentary time in more detail. This study aimed to use the 2006 Dutch time use survey to 1) describe the (sedentary) time use of Dutch adults, and 2) explore socio-demographic and health-related correlates of total (non-occupational) and domain-specific sedentary time. METHODS: The Dutch time use survey randomly selected participants from a population-representative research sample of Dutch households. Participants reported daily activities on seven consecutive days using a time use diary and socio-demographic and health-related characteristics during telephone interviews. All reported activities were coded for activity domain (i.e. education; household; leisure; occupation; sleep; transport; voluntary work) and activity intensity (i.e. sedentary; light intensity physical activity; moderate-to-vigorous intensity physical activity). As occupational activities were not specified in sufficient detail, the intensity of these activities was unknown. We described the time spent in different domains and intensities, and assessed the socio-demographic and health-related correlates of high levels of total (non-occupational), household, leisure, and transport sedentary time using logistic regression analyses. RESULTS: The final dataset consisted of 1614 adult (18+) participants. On average, participants spent 8.0 h (61.1%) of their daily waking non-occupational time on sedentary activities. More than 87% of leisure time was spent sedentary. Men, participants aged 18-34 and 65+ years, full-time employed participants and obese participants had higher levels of total non-occupational sedentary time. The correlates of household, leisure and transport sedentary time differed by domain. CONCLUSIONS: This study reports high levels of total non-occupational sitting time of Dutch adults. The large proportion of sedentary leisure activities might indicate the potential of strategies aiming to reduce leisure sedentary time. The difference in correlates across sedentary behaviour domains demonstrates the importance of targeting these domains differently in interventions and policies.

The Dynamic Work study: study protocol of a cluster randomized controlled trial of an occupational health intervention aimed at reducing sitting time in office workers.

BACKGROUND: Large volumes of sitting time have been associated with multiple health risks. To reduce sitting time of office workers working for a Dutch insurance company, the Dynamic Work intervention was developed. The primary objective of this paper is to describe the study protocol of the Dynamic Work study, which aims to evaluate if this multicomponent intervention is (cost-)effective in reducing total sitting time on the short-term (≈3 months) and longer-term (≈12 months) compared to usual practice. METHODS/DESIGN: This two-arm cluster randomized controlled trial will recruit 250 desk-based office workers working at different locations of an insurance company in the Netherlands. After baseline measurements, departments will be matched in pairs and each pair will be randomly assigned to the control or intervention condition. The multicomponent intervention contains organizational (i.e. face to face session with the head of the department), work environmental (i.e. the introduction of sit-stand desks and cycling workstations), and individual elements (i.e. counselling and activity/sitting tracker with a self-help program booklet). The counselling involves two group intervention sessions and four on-site department consultations with an occupational physiotherapist. Sitting time (primary outcome), upright time and step counts will be assessed objectively using the activPAL activity monitor at baseline, short-term (approximately 3 months) and longer-term (12 months). Other outcomes will include: self-reported lifestyle behaviours, anthropometrics, work-related outcomes (i.e. absenteeism, presenteeism, work performance, work-related stress), health-related outcomes (i.e. vitality, musculoskeletal symptoms, need for recovery, quality of life), and costs from both company and societal perspective. The study will include economic and process evaluations. DISCUSSION: This study will assess the longer-term (cost-) effectiveness of a multicomponent workplace intervention aimed at reducing sitting time in comparison with usual practice. Furthermore, the process evaluation will provide insights in factors associated with successful implementation of this intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT03115645 ; Registered 13 April 2017. Retrospectively registered.

Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study.

BACKGROUND: Depression is a prevalent, debilitating, and often recurrent mood disorder for which successful first-line treatments remains limited. The purpose of this study was to investigate the cross-sectional associations between self-reported physical activity (PA) and depressive symptoms and status among Irish adults, using two existing datasets, The Irish Longitudinal Study on Ageing (TILDA) and The Mitchelstown Cohort Study. METHODS: The two selected databases were pooled (n = 10,122), and relevant variables were harmonized. PA was measured using the short form International Physical Activity Questionnaire. Depressive symptoms were measured by the Center for Epidemiologic Studies Depression (CES-D) questionnaire. Participants were classified as meeting World Health Organization moderate-to-vigorous PA (MVPA) guidelines or not, and divided into tertiles based on weekly minutes of MVPA. A CES-D score of ≥16 indicated elevated depressive symptoms. Data collection were conducted in 2010-2011. RESULTS: Significantly higher depressive symptoms were reported by females (7.11 ± 7.87) than males (5.74 ± 6.86; p < 0.001). Following adjustment for age, sex, BMI, and dataset, meeting the PA guidelines was associated with 44.7% (95%CI: 35.0 to 52.9; p < 0.001) lower odds of elevated depressive symptoms. Compared to the low PA tertile, the middle and high PA tertiles were associated with 25.2% (95%CI: 8.7 to 38.6; p < 0.01) and 50.8% (95%CI: 40.7 to 59.2; p < 0.001) lower odds of elevated depressive symptoms, respectively. CONCLUSION: Meeting the PA guidelines is associated with lower odds of elevated depressive symptoms, and increased volumes of MVPA are associated with lower odds of elevated depressive symptoms.

Determinants of diet and physical activity (DEDIPAC): a summary of findings.

The establishment of the Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub, 2013-2016, was the first action taken by the 'Healthy Diet for a Healthy Life' European Joint Programming Initiative. DEDIPAC aimed to provide better insight into the determinants of diet, physical activity and sedentary behaviour across the life course, i.e. insight into the causes of the causes of important, non-communicable diseases across Europe and beyond. DEDIPAC was launched in late 2013, and delivered its final report in late 2016. In this paper we give an overview of what was achieved in terms of furthering measurement and monitoring, providing overviews of the state-of-the-art in the field, and building toolboxes for further research and practice. Additionally, we propose some of the next steps that are now required to move forward in this field, arguing in favour of 1) sustaining the Knowledge Hub and developing it into a European virtual research institute and knowledge centre for determinants of behavioural nutrition and physical activity with close links to other parts of the world; 2) establishing a cohort study of families across all regions of Europe focusing specifically on the individual and contextual determinants of major, non-communicable disease; and 3) furthering DEDIPAC's work on nutrition, physical activity, and sedentary behaviour policy evaluation and benchmarking across Europe by aligning with other international initiatives and by supporting harmonisation of pan-European surveillance.

Sitting too much: A hierarchy of socio-demographic correlates.

Too much sitting (extended sedentary time) is recognized as a public health concern in Europe and beyond. Time spent sedentary is influenced and conditioned by clusters of individual-level and contextual (upstream) factors. Identifying population subgroups that sit too much could help to develop targeted interventions to reduce sedentary time. We explored the relative importance of socio-demographic correlates of sedentary time in adults across Europe. We used data from 26,617 adults who participated in the 2013 Special Eurobarometer 412 "Sport and physical activity". Participants from all 28 EU Member States were randomly selected and interviewed face-to-face. Self-reported sedentary time was dichotomized into sitting less or >7.5h/day. A Chi-squared Automatic Interaction Detection (CHAID) algorithm was used to create a tree that hierarchically partitions the data on the basis of the independent variables (i.e., socio-demographic factors) into homogeneous (sub)groups with regard to sedentary time. This allows for the tentative identification of population segments at risk for unhealthy sedentary behaviour. Overall, 18.5% of the respondents reported sitting >7.5h/day. Occupation was the primary discriminator. The subgroup most likely to engage in extensive sitting were higher educated, had white-collar jobs, reported no difficulties with paying bills, and used the internet frequently. Clear socio-demographic profiles were identified for adults across Europe who engage in extended sedentary time. Furthermore, physically active participants were consistently less likely to engage in longer daily sitting times. In general, those with more indicators of higher wealth were more likely to spend more time sitting.

Variation in population levels of sedentary time in European children and adolescents according to cross-European studies: a systematic literature review within DEDIPAC.

BACKGROUND: A high amount of sedentary time has been proposed as a risk factor for various health outcomes in adults. While the evidence is less clear in children and adolescents, monitoring sedentary time is important to understand the prevalence rates and how this behaviour varies over time and by place. This systematic literature review aims to provide an overview of existing cross-European studies on sedentary time in children (0-12y) and adolescents (13-18y), to describe the variation in population levels of sedentary time, and to discuss the impact of assessment methods. METHODS: Six literature databases were searched (PubMed, EMBASE, CINAHL, PsycINFO, SportDiscus and OpenGrey), followed by backward- and forward tracking and searching authors' and experts' literature databases. Included articles were observational studies reporting on levels of sedentary time in the general population of children and/or adolescents in at least two European countries. Population levels were reported separately for children and adolescents. Data were reviewed, extracted and assessed by two researchers, with disagreements being resolved by a third researcher. The review protocol is published under registration number CRD42014013379 in the PROSPERO database. RESULTS: Forty-two eligible articles were identified, most were cross-sectional (n = 38). The number of included European countries per article ranged from 2 to 36. Levels of sedentary time were observed to be higher in East-European countries compared to the rest of Europe. There was a large variation in assessment methods and reported outcome variables. The majority of articles used a child-specific questionnaire (60%). Other methods included accelerometers, parental questionnaires or interviews and ecological momentary assessment tools. Television time was reported as outcome variable in 57% of included articles (ranging from a mean value of 1 h to 2.7 h in children and 1.3 h to 4.4 h in adolescents), total sedentary time in 24 % (ranging from a mean value of 192 min to 552 min in children and from 268 min to 506 min in adolescents). CONCLUSION: A substantial number of published studies report on levels of sedentary time in children and adolescents across European countries, but there was a large variation in assessment methods. Questionnaires (child specific) were used most often, but they mostly measured specific screen-based activities and did not assess total sedentary time. There is a need for harmonisation and standardisation of objective and subjective methods to assess sedentary time in children and adolescents to enable comparison across countries.

Variation in population levels of physical activity in European children and adolescents according to cross-European studies: a systematic literature review within DEDIPAC.

BACKGROUND: Regular physical activity is associated with physical, social and mental health benefits, whilst insufficient physical activity is associated with several negative health outcomes (e.g. metabolic problems). Population monitoring of physical activity is important to gain insight into prevalence of compliance to physical activity recommendations, groups at risk and changes in physical activity patterns. This review aims to provide an overview of all existing studies that measure physical activity in youth, in cross-European studies, to describe the variation in population levels of physical activity and to describe and define challenges regarding assessment methods that are used. METHODS: A systematic search was performed on six databases (PubMed, EMBASE, CINAHL, PsycINFO, SportDiscus and OpenGrey), supplemental forward- and backward tracking was done and authors' and experts' literature databases were searched to identify relevant articles. Journal articles or reports that reported levels of physical activity in the general population of youth from cross-European studies were included. Data were reviewed, extracted and assessed by two researchers, with disagreements being resolved by a third researcher. The review protocol of this review is published under registration number CRD42014010684 in the PROSPERO database. RESULTS: The search resulted in 9756 identified records of which 30 articles were included in the current review. This review revealed large differences between countries in prevalence of compliance to physical activity recommendations (i.e. 60 min of daily moderate- to vigorous-intensity physical activity (MVPA)) measured subjectively (5-47%) and accelerometer measured minutes of MVPA (23-200 min). Overall boys and children were more active than girls and adolescents. Different measurement methods (subjective n = 12, objective n = 18) and reported outcome variables (n = 17) were used in the included articles. Different accelerometer intensity thresholds used to define MVPA resulted in substantial differences in MVPA between studies conducted in the same countries when assessed objectively. CONCLUSIONS: Reported levels of physical activity and prevalence of compliance to physical activity recommendations in youth showed large variation across European countries. This may reflect true variation in physical activity as well as variation in assessment methods and reported outcome variables. Standardization across Europe, of methods to assess physical activity in youth and reported outcome variables is warranted, preferably moving towards a pan-European surveillance system combining objective and self-report methods.

Variation in population levels of sedentary time in European adults according to cross-European studies: a systematic literature review within DEDIPAC.

BACKGROUND: Sedentary behaviour is increasingly recognized as a public health risk that needs to be monitored at the population level. Across Europe, there is increasing interest in assessing population levels of sedentary time. This systematic literature review aims to provide an overview of all existing cross-European studies that measure sedentary time in adults, to describe the variation in population levels across these studies and to discuss the impact of assessment methods. METHODS: Six literature databases (PubMed, EMBASE, CINAHL, PsycINFO, SportDiscus and OpenGrey) were searched, supplemented with backward- and forward tracking and searching authors' and experts' literature databases. Articles were included if they reported on observational studies measuring any form of sedentary time in the general population in two or more European countries. Each record was reviewed, extracted and assessed by two independent researchers, and disagreements were resolved by a third researcher. The review protocol of this review is registered in the PROSPERO database under registration number CRD42014010335. RESULTS: Of the 9,756 unique articles that were identified in the search, twelve articles were eligible for inclusion in this review, reporting on six individual studies and three Eurobarometer surveys. These studies represented 2 to 29 countries, and 321 to 65,790 participants. Eleven studies focused on total sedentary time, while one studied screen time. The majority of studies used questionnaires to assess sedentary time, while two studies used accelerometers. Total sedentary time was reported most frequently and varied from 150 (median) to 620 (mean) minutes per day across studies and countries. CONCLUSIONS: One third of European countries were not included in any of the studies. Objective measures of European adults are currently limited, and most studies used single-item self-reported questions without assessing sedentary behaviour types or domains. Findings varied substantially between studies, meaning that population levels of sedentary time in European adults are currently unknown. In general, people living in northern Europe countries appear to report more sedentary time than southern Europeans. The findings of this review highlight the need for standardisation of the measurement methods and the added value of cross-European surveillance of sedentary behaviour.

Variation in population levels of physical activity in European adults according to cross-European studies: a systematic literature review within DEDIPAC.

BACKGROUND: Physical inactivity is a well-known public health risk that should be monitored at the population level. Physical activity levels are often surveyed across Europe. This systematic literature review aims to provide an overview of all existing cross-European studies that assess physical activity in European adults, describe the variation in population levels according to these studies, and discuss the impact of the assessment methods. METHODS: Six literature databases (PubMed, EMBASE, CINAHL, PsycINFO, SportDiscus and OpenGrey) were searched, supplemented with backward- and forward tracking and searching authors' and experts' literature databases. Articles were included if they reported on observational studies measuring total physical activity and/or physical activity in leisure time in the general population in two or more European countries. Each record was reviewed, extracted and assessed by two independent researchers and disagreements were resolved by a third researcher. The review protocol of this review is registered in the PROSPERO database under registration number CRD42014010334. RESULTS: Of the 9,756 unique identified articles, twenty-five were included in this review, reporting on sixteen different studies, including 2 to 35 countries and 321 to 274,740 participants. All but two of the studies used questionnaires to assess physical activity, with the majority of studies using the IPAQ-short questionnaire. The remaining studies used accelerometers. The percentage of participants who either were or were not meeting the physical activity recommendations was the most commonly reported outcome variable, with the percentage of participants meeting the recommendations ranging from 7% to 96% across studies and countries. CONCLUSIONS: The included studies showed substantial variation in the assessment methods, reported outcome variables and, consequently, the presented physical activity levels. Because of this, absolute population levels of physical activity in European adults are currently unknown. However, when ranking countries, Ireland, Italy, Malta, Portugal, and Spain generally appear to be among the less active countries. Objective data of adults across Europe is currently limited. These findings highlight the need for standardisation of the measurement methods, as well as cross-European monitoring of physical activity levels.

Towards the integration and development of a cross-European research network and infrastructure: the DEterminants of DIet and Physical ACtivity (DEDIPAC) Knowledge Hub.

To address major societal challenges and enhance cooperation in research across Europe, the European Commission has initiated and facilitated 'joint programming'. Joint programming is a process by which Member States engage in defining, developing and implementing a common strategic research agenda, based on a shared vision of how to address major societal challenges that no Member State is capable of resolving independently. Setting up a Joint Programming Initiative (JPI) should also contribute to avoiding unnecessary overlap and repetition of research, and enable and enhance the development and use of standardised research methods, procedures and data management. The Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub (KH) is the first act of the European JPI 'A Healthy Diet for a Healthy Life'. The objective of DEDIPAC is to contribute to improving understanding of the determinants of dietary, physical activity and sedentary behaviours. DEDIPAC KH is a multi-disciplinary consortium of 46 consortia and organisations supported by joint programming grants from 12 countries across Europe. The work is divided into three thematic areas: (I) assessment and harmonisation of methods for future research, surveillance and monitoring, and for evaluation of interventions and policies; (II) determinants of dietary, physical activity and sedentary behaviours across the life course and in vulnerable groups; and (III) evaluation and benchmarking of public health and policy interventions aimed at improving dietary, physical activity and sedentary behaviours. In the first three years, DEDIPAC KH will organise, develop, share and harmonise expertise, methods, measures, data and other infrastructure. This should further European research and improve the broad multi-disciplinary approach needed to study the interactions between multilevel determinants in influencing dietary, physical activity and sedentary behaviours. Insights will be translated into more effective interventions and policies for the promotion of healthier behaviours and more effective monitoring and evaluation of the impacts of such interventions.

Mixed-methods process evaluation of the Dynamic Work study: A multicomponent intervention for office workers to reduce sitting time.

Previously, we observed no significant reductions in sitting time of the multicomponent Dynamic Work (DW) intervention among office workers. In this study we used mixed-method data to understand context, implementation (i.e. recruitment and delivery) and mechanism of impact (i.e. experiences) of the DW intervention and to explore whether an higher implementation index score led to larger changes in participants' outcomes. We found considerable variation across departments regarding context (i.e. different size and work tasks) and implementation (i.e. delivery varied). Satisfaction with the DW intervention was high. An higher implementation index score was associated with lower overall sitting time, lower occupational sitting time, higher number of steps/day and steps/day at work at 4-months, which was maintained at 8-month for occupational sitting time. These findings provide an understanding that implementation was affected by a lack of availability of intervention components, department policy, work tasks, positioning and work location. TRIAL REGISTRATION: Clinicaltrials.gov, registration number:NCT03115645. Registered February 17, 2017 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03115645.

Effectiveness of the multi-component dynamic work intervention to reduce sitting time in office workers - Results from a pragmatic cluster randomised controlled trial.

OBJECTIVE: Prolonged sitting, which is highly prevalent in office workers, has been associated with several health risks. The aim of this study was to evaluate the Dynamic Work intervention by determining its effect on total sitting time at the 8-month follow-up in comparison to the control. METHODS: This two-arm pragmatic cluster randomised controlled trial included 244 office workers from 14 different departments of a large, Dutch insurance company. The Dynamic Work intervention was a real-life, worksite intervention that included environmental components (i.e. sit-stand workstations), organisational components (i.e. group sessions), and individual components (e.g. activity/sitting trackers). Outcomes were assessed at baseline, 4-month follow-up, and 8-month follow-up. The primary outcome was total sitting time per day, objectively assessed using the activPAL activity monitor at 8-month follow-up. Secondary outcomes included other total and occupational movement behaviour outcomes, health-related outcomes, and work-related outcomes. Data analyses were performed using linear and logistic mixed models. RESULTS: Total sitting time did not differ between the intervention and control group at the 8-month follow-up. Secondary outcomes also showed no difference between the intervention and control group at either the 4-month or at 8-month follow-up, with the exception of number of occupational steps, which showed a statistically significant effect at 4-month follow-up (but not at 8-month follow-up) of 913 (95% CI = 381-1445) steps/8-h working day. CONCLUSIONS: This study evaluated the effectiveness of a real-life worksite intervention to reduce sitting time and showed little to no effect. This may be due to the relatively low intensity of the intervention, i.e. that it only involved the replacement of 25% of sitting workstations with sit-stand workstations. Future research should focus on the evaluation of more intensive real-life worksite interventions that are still feasible for implementation in daily practice. CLINICALTRIALS. GOV, REGISTRATION NUMBER: NCT03115645.

Time trends between 2002 and 2017 in correlates of self-reported sitting time in European adults.

BACKGROUND: This study explores trends in the prevalence of high sitting time and its correlates among "high sitting" and "high sitting-least active" European adults from 2002 to 2017. Both groups have merit for future public health interventions to prevent development of a range of prevalent non-communicable diseases. METHODS: Data collected in the 2002 (15 countries), 2005 (30 countries), 2013 (28 countries) and 2017 (28 countries) Eurobarometer surveys were used, including around 15,000 respondents in 2002 and >26,000 respondents in the other years. Sitting time and moderate to vigorous intensity physical activity were measured with the validated International Physical Activity Questionnaire-short. High sitting was defined as >7.5 hours per day. Respondents in the lowest quartile of total reported days of physical activity (i.e. days walking, days in moderate activity, and days in vigorous activity) were defined as least active. Multivariate odds ratios of high sitting, and high sitting-least active were assessed by country and socio-demographic characteristics for each survey year using binary logistic regression analyses. RESULTS: Trends in sitting time were relatively stable over a 15-year period, although this time trend was limited by a change in the sitting question between 2005 and 2013. Men, higher educated people, students, retired people, white collar workers, people living in urban areas, people with lower physical activity levels, and people living in the Czech Republic, Denmark or the Netherlands were consistently more likely to be in the high sitting group across all four survey years. Similarly, men, students, retired people, unemployed people, white collar workers, and people living in the Czech Republic or Denmark were consistently more likely to be in the high sitting-least active group across all four surveys. CONCLUSION: This study identified population sub-groups that need special attention in public health interventions to lower total sitting time.

Factors influencing sedentary behaviour: A system based analysis using Bayesian networks within DEDIPAC.

BACKGROUND: Decreasing sedentary behaviour (SB) has emerged as a public health priority since prolonged sitting increases the risk of non-communicable diseases. Mostly, the independent association of factors with SB has been investigated, although lifestyle behaviours are conditioned by interdependent factors. Within the DEDIPAC Knowledge Hub, a system of sedentary behaviours (SOS)-framework was created to take interdependency among multiple factors into account. The SOS framework is based on a system approach and was developed by combining evidence synthesis and expert consensus. The present study conducted a Bayesian network analysis to investigate and map the interdependencies between factors associated with SB through the life-course from large scale empirical data. METHODS: Data from the Eurobarometer survey (80.2, 2013) that included the International physical activity questionnaire (IPAQ) short as well as socio-demographic information and questions on perceived environment, health, and psychosocial information were enriched with macro-level data from the Eurostat database. Overall, 33 factors were identified aligned to the SOS-framework to represent six clusters on the individual or regional level: 1) physical health and wellbeing, 2) social and cultural context, 3) built and natural environment, 4) psychology and behaviour, 5) institutional and home settings, 6) policy and economics. A Bayesian network analysis was conducted to investigate conditional associations among all factors and to determine their importance within these networks. Bayesian networks were estimated for the complete (23,865 EU-citizens with complete data) sample and for sex- and four age-specific subgroups. Distance and centrality were calculated to determine importance of factors within each network around SB. RESULTS: In the young (15-25), adult (26-44), and middle-aged (45-64) groups occupational level was directly associated with SB for both, men and women. Consistently, social class and educational level were indirectly associated within male adult groups, while in women factors of the family context were indirectly associated with SB. Only in older adults, factors of the built environment were relevant with regard to SB, while factors of the home and institutional settings were less important compared to younger age groups. CONCLUSION: Factors of the home and institutional settings as well as the social and cultural context were found to be important in the network of associations around SB supporting the priority for future research in these clusters. Particularly, occupational status was found to be the main driver of SB through the life-course. Investigating conditional associations by Bayesian networks gave a better understanding of the complex interplay of factors being associated with SB. This may provide detailed insights in the mechanisms behind the burden of SB to effectively inform policy makers for detailed intervention planning. However, considering the complexity of the issue, there is need for a more comprehensive system of data collection including objective measures of sedentary time.

Changes in children's television and computer time according to parental education, parental income and ethnicity: A 6-year longitudinal EYHS study.

OBJECTIVES: To investigate changes in children's television and computer time according to three socio-economic status (SES) indicators. DESIGN: Prospective cohort study. METHODS: Data were drawn from the European Youth Heart Study and included longitudinal data collected in 1997 and 2003 in Denmark. Television and computer time were self-reported by children. Parental education, income and ethnicity were parent-reported. Baseline data were available for 549 children (47.0% boys, 9.6 years). Generalized linear mixed models analyzed whether changes in television and computer time from baseline to follow-up differed according to the SES-indicators. RESULT: TV viewing time increased with 25% over time (ExpB = 1.25, 95% CI = 1.04-1.50). At both time points, children with two higher educated parents viewed 25% less hours of television than children with no higher educated parents (ExpB = 0.75, 95% CI = 0.60-0.94) and one higher educated parent (ExpB = 0.75, 95%CI = 0.59-0.97). Among children with no higher educated parents the odds of being in a higher category of computer time increased with 80% over time (OR = 1.80, 95% CI = 1.24-2.60). Among children with two higher educated parents the odds of being in a higher category of computer time decreased with 45% over time (OR = 0.55, 95% CI = 0.32-0.94). The association with ethnicity showed that white children had 42% lower odds (OR = 0.58; 95% CI = 0.34-1.00) of being in a higher category of computer time than non-white children. No significant associations were found for parental income. CONCLUSIONS: The most important SES measure of screen-based behaviors in children was parental education. Ethnicity was only associated with computer time. Financial resources were less relevant for changes in television viewing and computer use.

Recent trends in population levels and correlates of occupational and leisure sitting time in full-time employed Australian adults.

This study aimed to explore the trend in population levels, as well as the correlates, of occupational and leisure sitting time in full-time employed Australian adults between 2007 and 2015. We used data from the 2007/08, 2011/12 and 2014/15 Australian Health Surveys, in which nationally representative samples of the Australian population were interviewed. Full-time (≥35 hours/week) employed respondents reported sitting time at work and during leisure on a usual workday. Trends over time and associations between socio-demographic and health-related characteristics and sitting time were analysed in the combined dataset using multivariable logistic regression models. Over 21,000 observations were included in the analyses. Across the three surveys, approximately 51% of the respondents reported ≥4 hours/workday occupational sitting time, 40% reported ≥4 hours/workday leisure sitting time, and 55% reported ≥7 hours/workday combined occupational and leisure sitting time. There were no clear trends over time. All potential correlates were associated with occupational sitting time and all but educational level were associated with leisure sitting time. The directions of the associations with gender, age and leisure-time physical activity were reversed for occupational sitting time and leisure sitting time. These findings show that the average levels of occupational and leisure sitting time on workdays were high but stable over the past decade. The observed differences in correlates of occupational and leisure sitting time demonstrate the need to assess and address sedentary behaviour domains separately in research and policy.

Data on Determinants Are Needed to Curb the Sedentary Epidemic in Europe. Lessons Learnt from the DEDIPAC European Knowledge Hub.

Societal and technological changes have resulted in sitting being the dominant posture during most activities of daily living, such as learning, working, travelling and leisure time. Too much time spent in seated activities, referred to as sedentary behaviour, is a novel concern for public health as it is one of the key lifestyle causes of poor health. The European DEDIPAC (Determinants of Diet and Physical Activity) Knowledge Hub coordinated the work of 35 institutions across 12 European member states to investigate the determinants of sedentary behaviour. DEDIPAC reviewed current evidence, set a theoretical framework and harmonised the available epidemiological data. The main results are summarised. The conclusion is that there is a dire lack of data that is exploitable across Europe to inform policy and intervention. There is an urgent need to develop international data collection compliant with FAIR (Findable, Accessible, Interoperable, Re-usable) and standardised surveillance systems for sedentary behaviour.