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.

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.

Barriers and facilitators influencing the implementation of the occupational health intervention 'Dynamic Work': a qualitative study.

BACKGROUND: Sedentary behavior is associated with an increased risk of morbidity and mortality. To reduce occupational sitting time of office workers, the multi-component intervention 'Dynamic Work' was implemented in a Dutch insurance company. Although the results showed no significant reductions in sitting time, associations were found between higher levels of implementation and reductions in sitting time. Building upon these findings, this qualitative study aimed to identify barriers and facilitators from an organizational perspective for the implementation of Dynamic Work. In addition, we explored differences in barriers and facilitators between departments with a low, middle and high level of implementation. METHODS: In total, eighteen semi-structured interviews were conducted with two Dynamic Work coordinators, three occupational physiotherapists who delivered the intervention, and thirteen department managers. All participants were purposively sampled. The data was coded in Atlas.ti and a thematic analysis was performed guided by The Integrated Checklist of Determinants (TICD). RESULTS: Implementation factors were related to the organization; working culture and financial support facilitated implementation. Factors related to the implementing department mainly hindered implementation, i.e. lack of information at start of the project, late delivery of Dynamic Work equipment, large group sizes, employee's workload and work tasks, and an ongoing reorganization. The facilitating role of managers was experienced as both enabling and hindering. The pre-existing familiarity of the occupational physiotherapists with the departments and alignment amongst the three implementers facilitated implementation. Yet, the non-obligatory nature of the intervention as well as limited availability and technical problems of equipment did not support implementation. CONCLUSIONS: Various barriers and facilitators influenced the implementation of the Dynamic Work intervention, where the key role of the department manager, late delivery of dynamic work equipment and groups sizes varied between low and high implementing departments. These results can contribute to developing and improving implementation strategies in order to increase the effectiveness of future occupational health interventions. TRIAL REGISTRATION: The study protocol was registered on April 14, 2017 in the ClinicalTrials.gov Protocol Registration and Results System under registration number NCT03115645 .

Child and Parent Perceived Determinants of Children's Inadequate Sleep Health. A Concept Mapping Study.

Many children do not meet the recommendations for healthy sleep, which is concerning given the potential negative effects on children's health. To promote healthy sleep, it is crucial to understand its determinants. This concept mapping study therefore explores perspectives of children and parents on potential determinants of children's inadequate sleep. The focus lies on 9-12 year old children (n = 45), and their parents (n = 33), from low socioeconomic neighbourhoods, as these children run a higher risk of living in a sleep-disturbing environment (e.g., worries, noise). All participants generated potential reasons (i.e., ideas) for children's inadequate sleep. Next, participants sorted all ideas by relatedness and rated their importance. Subsequently, multidimensional scaling and hierarchical cluster analyses were performed to create clusters of ideas for children and parents separately. Children and parents both identified psychological (i.e., fear, affective state, stressful situation), social environmental (i.e., sleep schedule, family sleep habits), behavioural (i.e., screen behaviour, physical activity, diet), physical environmental (i.e., sleep environment such as temperature, noise, light), and physiological (i.e., physical well-being) determinants. These insights may be valuable for the development of future healthy sleep interventions.

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.