The Importance of Research on Occupational Sedentary Behaviour and Activity Right Now.

The workplace has been identified as a key setting for public health interventions to 'promote and maintain the highest degree of physical, mental and social well-being of workers in all occupations' by the World Health Organisation [...].

Physical activity and sitting time in occupational groups from Papua New Guinea.

PURPOSE: To assess physical activity and sitting time in workers from varied occupations in a regional urban population of Papua New Guinea (PNG), to identify priorities for worker health in a country experiencing rapid industrial development. METHODS: PNG workers from a variety of settings (office [n = 213], blue-collar [n = 131], and retail [n = 52]) completed an interviewer-administered demographic questionnaire, the International Physical Activity Questionnaire-short form (IPAQ) and the Occupational Sitting and Physical Activity Questionnaire (OSPAQ); and had height and weight measured. Comparison of activity and sitting time between occupational groups was undertaken using generalised linear equations, with models including demographic variables and sitting time/physical activity as appropriate. RESULTS: Participants reported median total physical activity (walking, moderate and vigorous PA) of 5025 MET-min/week (80% constituting walking) and over 97% of participants met physical activity guidelines (> 600 MET-min/week). Total sitting time was 7 hours/day (IPAQ) and workers sat for 50% of working hours (OSPAQ). There was no difference between groups total physical activity. Office workers reported more total sitting time and a greater proportion of their work time spent sitting than blue-collar and retail workers reported significantly less total sitting time both p < 0.001) and retail workers reported a greater proportion of their work hours standing than office workers and blue-collar workers. CONCLUSIONS: Sitting time in PNG office workers was high, similar to findings from high-income countries, but total physical activity was also high in all groups. As the PNG economy develops and office-based work becomes more prevalent, the challenge will be to minimise sitting time at work whilst maintaining high total physical activity.

Alternatives for Measuring Sitting Accumulation in Workplace Surveys.

OBJECTIVES: To develop and assess the measurement properties of self-report measures of accumulation of sitting time. METHODS: Seven candidate measures were collected in 51 workers from three office environments (79% women) via online questionnaire administered immediately before and after 7-day monitoring periods (activPAL3 24-hour protocol with diary recorded work hours). RESULTS: Three measures had some validity (P < 0.05 vs activPAL): % of sitting in long bouts more than or equal to 30 minutes, sitting strategy frequency (0 to 100), and interruption rate (n/h sitting). Agreement was limited. Some reliability (intraclass correlation or kappa P < 0.05) was seen for these measures, strategy variety (0 to 100), typical day (five categories), and making a conscious effort to sit less (yes/no). CONCLUSIONS: Two brief and one longer option may suit workplace studies requiring self-report measures of sitting accumulation. Validity was weaker for sitting accumulation than sitting time.

Sitting at work & waist circumference-A cross-sectional study of Australian workers.

Studies examining associations of sitting time at work with obesity measures have produced inconsistent findings. Different sample characteristics across studies, e.g., the composition of different occupational groups, may be one explanation for the mixed findings. We examined cross-sectional associations of workplace sitting time with waist circumference in workers engaged in desk-based work and those engaged in other work settings using a population-based sample of Australian workers. Participants (5878 full-time workers in the 2014-15 Australian National Health Survey) were categorized into desk-based (N = 3006) or non-desk-based (N = 2872) workers, based on self-reported predominant behavior at work (sitting, standing, walking, and physical labor) and occupational group. Linear regression analyses examined associations of measured waist circumference with self-reported sitting time at work for each group, which was further stratified by gender and leisure-time physical activity level. Longer sitting time at work was associated with greater waist circumference in desk-based workers (b = 0.45 [95%CI: 0.09, 0.80] cm for a 1 h/day increment of sitting) but not in non-desk-based workers (b = 0.25 [95%CI: -0.12, 0.63]). For desk-based workers, stratified analyses found significant associations in men and those who were insufficiently physically active during leisure time. Our findings support interventions to decrease occupational sitting time for desk-based workers to reduce their cardio-metabolic risk. Differential associations observed between desk-based and non-desk-based workers and between genders may be attributable to the ways in which sitting time is accumulated. Future research is needed to examine the impact of behavior patterns at work (sitting breaks, occupational physical activity) on adiposity in working adults.

Supporting Workers to Sit Less and Move More Through the Web-Based BeUpstanding Program: Protocol for a Single-Arm, Repeated Measures Implementation Study.

BACKGROUND: The web-based BeUpstanding Champion Toolkit was developed to support work teams in addressing the emergent work health and safety issue of excessive sitting. It provides a step-by-step guide and associated resources that equip a workplace representative-the champion-to adopt and deliver the 8-week intervention program (BeUpstanding) to their work team. The evidence-informed program is designed to raise awareness of the benefits of sitting less and moving more, build a supportive culture for change, and encourage staff to take action to achieve this change. Work teams collectively choose the strategies they want to implement and promote to stand up, sit less, and move more, with this bespoke and participative approach ensuring the strategies are aligned with the team's needs and existing culture. BeUpstanding has been iteratively developed and optimized through a multiphase process to ensure that it is fit for purpose for wide-scale implementation. OBJECTIVE: The study aimed to describe the current version of BeUpstanding, and the methods and protocol for a national implementation trial. METHODS: The trial will be conducted in collaboration with five Australian workplace health and safety policy and practice partners. Desk-based work teams from a variety of industries will be recruited from across Australia via partner-led referral pathways. Recruitment will target sectors (small business, rural or regional, call center, blue collar, and government) that are of priority to the policy and practice partners. A minimum of 50 work teams will be recruited per priority sector with a minimum of 10,000 employees exposed to the program. A single-arm, repeated-measures design will assess the short-term (end of program) and long-term (9 months postprogram) impacts. Data will be collected on the web via surveys and toolkit analytics and by the research team via telephone calls with champions. The Reach, Effectiveness, Adoption, Implementation, and Maintenance Framework will guide the evaluation, with assessment of the adoption/reach of the program (the number and characteristics of work teams and participating staff), program implementation (completion by the champion of core program components), effectiveness (on workplace sitting, standing, and moving), and maintenance (sustainability of changes). There will be an economic evaluation of the costs and outcomes of scaling up to national implementation, including intervention affordability and sustainability. RESULTS: The study received funding in June 2018 and the original protocol was approved by institutional review board on January 9, 2017, with national implementation trial consent and protocol amendment approved March 12, 2019. The trial started on June 12, 2019, with 48 teams recruited as of December 2019. CONCLUSIONS: The implementation and multimethod evaluation of BeUpstanding will provide the practice-based evidence needed for informing the potential broader dissemination of the program. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12617000682347; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372843&isReview=true. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15756.

Sedentary Behavior and Public Health: Integrating the Evidence and Identifying Potential Solutions.

In developed and developing countries, social, economic, and environmental transitions have led to physical inactivity and large amounts of time spent sitting. Research is now unraveling the adverse public health consequences of too much sitting. We describe improvements in device-based measurement that are providing new insights into sedentary behavior and health. We consider the implications of research linking evidence from epidemiology and behavioral science with mechanistic insights into the underlying biology of sitting time. Such evidence has led to new sedentary behavior guidelines and initiatives. We highlight ways that this emerging knowledge base can inform public health strategy: First, we consider epidemiologic and experimental evidence on the health consequences of sedentary behavior; second, we describe solutions-focused research from initiatives in workplaces and schools. To inform a broad public health strategy, researchers need to pursue evidence-informed collaborations with occupational health, education, and other sectors.

Temporal features of sitting, standing and stepping changes in a cluster-randomised controlled trial of a workplace sitting-reduction intervention.

BACKGROUND: There is now a body of evidence on the effectiveness of interventions to reduce workplace sitting time. However, there has been limited reporting of how such interventions may impact behaviour both during and outside of work. Sitting, standing and stepping changes following a workplace intervention were examined across five timeframes (work time on work days; non-work time on work days; work days; non-work days; overall (i.e. work and non-work time on all days)), and the relationships between changes during and outside of work was assessed. METHODS: The cluster-randomised controlled trial, 'Stand Up Victoria', delivered a multi-component workplace-delivered intervention that successfully reduced workplace and overall sitting time (relative to controls). Separately, over the five timeframes, changes in device (activPAL3)-assessed outcomes - sitting; prolonged sitting (≥30 min bouts); standing; and, stepping - were compared between intervention (n = 114) and controls (n = 84), along with the time-course of sitting changes during work hours, using mixed models. The potential relationships of changes during work with changes outside of work were examined using compositional data analysis. RESULTS: On workdays, intervention participants significantly (p < 0.05) improved their activity profile relative to controls, with reduced sitting (- 117 min/8-h workday, 95% CI: - 141, - 93) and prolonged sitting (- 77 min/8 h workday, 95% CI: - 101, - 52); increased standing (114 min/8 h workday, 95% CI: 92, 136) and maintenance of stepping (3 min/8 h workday, 95% CI: - 7, 11, p = 0.576). Effects were nearly identical for time at work; similar but slightly weaker for overall; and, small and non-significant outside of work on workdays and non-work days. Improvements occurred at all times, but not equally, during work hours (p < 0.001). Correlations between changes during and outside of work on workdays were very weak in both the intervention group (r = - 0.07) and controls (r = - 0.09). CONCLUSIONS: Sitting time was reduced almost exclusively during work hours (via replacement with standing), with reductions evident during all working hours, to varying degrees. There was no evidence of compensation, with minimal change in activity outside of work, in response to changes in activity at work. Future interventions may benefit from exploring how best to elicit change throughout the whole day, and across work and non-work domains. TRIAL REGISTRATION: This trial was prospectively registered with the Australian New Zealand Clinical Trials register (ACTRN12611000742976) on 15 July 2011.

Associations of context-specific sitting time with markers of cardiometabolic risk in Australian adults.

BACKGROUND: High volumes of sitting time are associated with an elevated risk of type 2 diabetes and cardiovascular disease, and with adverse cardiometabolic risk profiles. However, previous studies have predominately evaluated only total sitting or television (TV) viewing time, limiting inferences about the specific cardiometabolic health impacts of sitting accumulated in different contexts. We examined associations of sitting time in four contexts with cardiometabolic risk biomarkers in Australian adults. METHODS: Participants (n = 3429; mean ± SD age 58 ± 10 years) were adults without clinically diagnosed diabetes or cardiovascular disease from the 2011-2012 Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Multiple linear regressions examined associations of self-reported context-specific sitting time (occupational, transportation, TV-viewing and leisure-time computer use) with a clustered cardiometabolic risk score (CMR) and with individual cardiometabolic risk biomarkers (waist circumference, BMI, resting blood pressure, triglycerides, HDL- and LDL-cholesterol, and fasting and 2-h post-load plasma glucose). RESULTS: Higher CMR was significantly associated with greater TV-viewing and computer sitting time (b [95%CI] = 0.07 [0.04, 0.09] and 0.06 [0.03, 0.09]), and tended to be associated with higher occupational and transport sitting time (0.01 [- 0.01, 0.03] and 0.03 [- 0.00, 0.06]), after adjustment for potential confounders. Furthermore, keeping total sitting time constant, accruing sitting via TV-viewing and computer use was associated with significantly higher CMR (0.05 [0.02, 0.08] and 0.04 [0.01, 0.06]), accruing sitting in an occupational context was associated with significantly lower CMR (- 0.03 [- 0.05, - 0.01]), while no significant association was seen for transport sitting (0.00 [- 0.03, 0.04]). Results varied somewhat between the respective biomarkers; however, higher sitting time in each domain tended to be associated detrimentally with individual biomarkers except for fasting glucose (non-significant associations) and systolic blood pressure (a beneficial association was observed). Overall, associations were stronger for TV-viewing and computer use, and weaker for occupational sitting. CONCLUSIONS: Higher context-specific sitting times tended to be detrimentally associated, albeit modestly, with CMR and several cardiometabolic risk biomarkers. There was some evidence suggesting that the context in which people sit is relevant above and beyond total sitting time. Methodological issues notwithstanding, these findings may assist in identifying priorities for sitting-reduction initiatives, in order to achieve optimal cardiometabolic health benefits.

What strategies do desk-based workers choose to reduce sitting time and how well do they work? Findings from a cluster randomised controlled trial.

BACKGROUND: Large amounts of sitting at work have been identified as an emerging occupational health risk, and findings from intervention trials have been reported. However, few such reports have examined participant-selected strategies and their relationships with behaviour change. METHODS: The Stand Up Victoria cluster-randomised controlled trial was a workplace-delivered intervention comprising organisational, environmental and individual level behaviour change strategies aimed at reducing sitting time in desk-based workers. Sit-stand workstations were provided, and participants (n = 134; intervention group only) were guided by health coaches to identify strategies for the 'Stand Up', 'Sit Less', and 'Move More' intervention targets, including how long they would stand using the workstation. Three-month workplace sitting and activity changes (activPAL3-assessed total sitting, prolonged sitting (i.e., sitting ≥30 min continuously) and purposeful walking) were evaluated in relation to the number (regression analysis) and types of strategies (decision-tree analysis). RESULTS: Over 80 different strategies were nominated by participants. Each additional strategy nominated for the 'Stand Up' intervention target (i.e. number of strategies) was associated with a reduction in prolonged sitting of 27.6 min/8-h workday (95% CI: -53.1, - 2.1, p = 0.034). Types of strategies were categorised into 13 distinct categories. Strategies that were task-based and phone-based were common across all three targets. The decision tree models did not select any specific strategy category as predicting changes in prolonged sitting ('Stand Up'), however four strategy categories were identified as important for total sitting time ('Sit Less') and three strategy categories for purposeful walking ('Moving More'). The uppermost nodes (foremost predictors) were nominating > 3 h/day of workstation standing (reducing total workplace sitting) and choosing a 'Move More' task-based strategy (purposeful walking). CONCLUSIONS: Workers chose a wide range of strategies, with both strategy choice and strategy quantity appearing relevant to behavioural improvement. Findings support a tailored and pragmatic approach to encourage a change in sitting and activity in the workplace. Evaluating participant-selected strategies in the context of a successful intervention serves to highlight options that may prove feasible and effective in other desk-based workplace environments. TRIAL REGISTRATION: This trial was prospectively registered with the Australian New Zealand Clinical Trials register ( ACTRN12611000742976 ) on 15 July 2011.

Evaluating Short-Term Musculoskeletal Pain Changes in Desk-Based Workers Receiving a Workplace Sitting-Reduction Intervention.

This paper explores changes in musculoskeletal pain among desk-based workers over three months of a workplace-delivered, sitting-reduction intervention. Participants (n = 153, 46% female; mean ± SD aged 38.9 ± 8.0 years) were cluster-randomized (n = 18 work teams) to receive an organizational change intervention, with or without an activity tracker. A modified Nordic Musculoskeletal Questionnaire assessed pain intensity (0⁻9; none⁻worst possible) in the neck, upper and lower back, upper and lower extremities, and in total. The activPAL3 (7 days, 24 h/day protocol) measured sitting and prolonged sitting in ≥30 min bouts at work. Mixed models adjusting for cluster and intervention arm examined changes in pain (n = 104), and their associations with reductions in sitting and prolonged sitting (h/10 h at work) (n = 90). Changes in pain were nonsignificant (p ≥ 0.05) and small for total pain (-0.06 [95% CI: -0.27, 0.16]) and for each body area (-0.26 [-0.66, 0.15] for upper back to 0.09 [-0.39, 0.56] for lower back). Sitting reduction was associated with reduced lower back pain (-0.84 [-1.44, -0.25] per hour, p = 0.005); other effects were small and non-significant. No substantial average changes in pain were seen; some improvement in lower back pain might be expected with larger sitting reductions. Larger samples and diverse interventions are required for more definitive evidence.

Using Bluetooth proximity sensing to determine where office workers spend time at work.

BACKGROUND: Most wearable devices that measure movement in workplaces cannot determine the context in which people spend time. This study examined the accuracy of Bluetooth sensing (10-second intervals) via the ActiGraph GT9X Link monitor to determine location in an office setting, using two simple, bespoke algorithms. METHODS: For one work day (mean±SD 6.2±1.1 hours), 30 office workers (30% men, aged 38±11 years) simultaneously wore chest-mounted cameras (video recording) and Bluetooth-enabled monitors (initialised as receivers) on the wrist and thigh. Additional monitors (initialised as beacons) were placed in the entry, kitchen, photocopy room, corridors, and the wearer's office. Firstly, participant presence/absence at each location was predicted from the presence/absence of signals at that location (ignoring all other signals). Secondly, using the information gathered at multiple locations simultaneously, a simple heuristic model was used to predict at which location the participant was present. The Bluetooth-determined location for each algorithm was tested against the camera in terms of F-scores. RESULTS: When considering locations individually, the accuracy obtained was excellent in the office (F-score = 0.98 and 0.97 for thigh and wrist positions) but poor in other locations (F-score = 0.04 to 0.36), stemming primarily from a high false positive rate. The multi-location algorithm exhibited high accuracy for the office location (F-score = 0.97 for both wear positions). It also improved the F-scores obtained in the remaining locations, but not always to levels indicating good accuracy (e.g., F-score for photocopy room ≈0.1 in both wear positions). CONCLUSIONS: The Bluetooth signalling function shows promise for determining where workers spend most of their time (i.e., their office). Placing beacons in multiple locations and using a rule-based decision model improved classification accuracy; however, for workplace locations visited infrequently or with considerable movement, accuracy was below desirable levels. Further development of algorithms is warranted.

Sitting Time, Physical Activity and Sleep by Work Type and Pattern-The Australian Longitudinal Study on Women's Health.

Data from the Australian Longitudinal Study on Women's Health were used to examine how work was associated with time spent sleeping, sitting and in physical activity (PA), in working women. Young (31-36 years; 2009) and mid-aged (59-64 years; 2010) women reported sleep (categorised as shorter ≤6 h/day and longer ≥8 h/day) and sitting time (work, transport, television, non-work computer, and other; summed for total sitting time) on the most recent work and non-work day; and moderate and vigorous PA (categorised as meeting/not meeting guidelines) in the previous week. Participants reported occupation (manager/professional; clerical/sales; trades/transport/labourer), work hours (part-time; full-time) and work pattern (shift/night; not shift/night). The odds of shorter sleep on work days was higher in both cohorts for women who worked shift or night hours. Longer sitting time on work days, made up primarily of sitting for work, was found for managers/professionals, clerical/sales and full-time workers. In the young cohort, clerical/sales workers and in the mid-aged cohort, full-time workers were less likely to meet PA guidelines. These results suggest multiple behaviour interventions tailored to work patterns and occupational category may be useful to improve the sleep, sitting and activity of working women.

Maintaining a Healthy BMI: Data From a 16-Year Study of Young Australian Women.

INTRODUCTION: The aims of this prospective cohort study were to examine 16-year trajectories of weight and BMI in young adult women who had a healthy BMI in 1996 and determinants of remaining in the healthy BMI category. METHODS: A total of 4,881 women with healthy BMI at baseline and either healthy, overweight, or obese BMI at 16-year follow-up reported their weight, height, health, and health behaviors in six surveys of the Australian Longitudinal Study on Women's Health between 1996 (aged 18-23 years) and 2012 (aged 34-39 years). Determinants of BMI maintenance were estimated using binary logistic regression and generalized estimating equations in 2015. RESULTS: Almost 60% remained in the healthy BMI category from 1996 to 2012, (mean weight gain, 0.19 kg/year), 29% transitioned to overweight BMI (0.83 kg/year), and 11.6% transitioned to obese (1.73 kg/year). The mean rates of annual weight gain in each group were consistent over time. Only three factors (low alcohol, moderate/high physical activity, having a university degree) were positively associated with maintaining a healthy BMI. Additional behavioral factors (smoking, high sitting time, energy intake, dieting, takeaway food, and use of oral contraceptives), as well as blue collar occupation, separation/divorce/widowhood, and major illness were negatively associated with BMI maintenance. CONCLUSIONS: To prevent the transition from healthy to overweight/obese BMI, weight gain must be limited to <0.5 kg/year. Women with healthy BMI, but with higher rates of weight gain in their early 20s, could be identified by health professionals for assistance with prevention of becoming overweight/obese.

Past-day recall of sedentary time: Validity of a self-reported measure of sedentary time in a university population.

OBJECTIVES: To assess the validity of the Past-day Adults' Sedentary Time-University (PAST-U) questionnaire, modified for a university population, compared with activPAL. DESIGN: Participants (n=57, age=18-55 years, 47% female, 65% students) were recruited from the University of Queensland (students and staff). METHODS: Participants answered the PAST-U questionnaire, which asked about time spent sitting or lying down for work, study, travel, television viewing, leisure-time computer use, reading, eating, socialising and other purposes, during the previous day. Times reported for these questions were summed to provide a measure of total sedentary time. Participants also wore an activPAL device for the full day prior to completing the questionnaire and recorded their wake and sleep times in an activity log. Total waking sedentary time derived from the activPAL was used as the criterion measure. Correlation (intraclass correlation coefficient, ICC) and agreement (Bland-Altman plots) between PAST-U and activPAL sedentary time were examined. RESULTS: Participants were sedentary (activPAL-determined) for 66% of waking hours. The correlation between PAST-U and activPAL sedentary time for the whole sample was ICC=0.64 [95% confidence interval (CI)=0.45, 0.77]; and higher for non-students (ICC=0.78, 95%CI 0.52, 0.91) than students (ICC=0.59, 95%CI 0.33, 0.77). Bland-Altman plots revealed that the mean difference between the two measures was 5min although limits of agreement were wide (95% limits of agreement: -3.9 to 4.1h). CONCLUSIONS: The PAST-U provides an acceptable measure of sedentary time in this population, which included students and adults with high workplace sitting time.

The validity of the GENEActiv wrist-worn accelerometer for measuring adult sedentary time in free living.

OBJECTIVES: Based on self-reported measures, sedentary time has been associated with chronic disease and mortality. This study examined the validity of the wrist-worn GENEactiv accelerometer for measuring sedentary time (i.e. sitting and lying) by posture classification, during waking hours in free living adults. DESIGN: Fifty-seven participants (age=18-55 years 52% male) were recruited using convenience sampling from a large metropolitan Australian university. METHODS: Participants wore a GENEActiv accelerometer on their non-dominant wrist and an activPAL device attached to their right thigh for 24-h (00:00 to 23:59:59). Pearson's Correlation Coefficient was used to examine the convergent validity of the GENEActiv and the activPAL for estimating total sedentary time during waking hours. Agreement was illustrated using Bland and Altman plots, and intra-individual agreement for posture was assessed with the Kappa statistic. RESULTS: Estimates of average total sedentary time over 24-h were 623 (SD 103) min/day from the GENEActiv, and 626 (SD 123) min/day from the activPAL, with an Intraclass Correlation Coefficient of 0.80 (95% confidence intervals 0.68-0.88). Bland and Altman plots showed slight underestimation of mean total sedentary time for GENEActiv relative to activPAL (mean difference: -3.44min/day), with moderate limits of agreement (-144 to 137min/day). Mean Kappa for posture was 0.53 (SD 0.12), indicating moderate agreement for this sample at the individual level. CONCLUSIONS: The estimation of sedentary time by posture classification of the wrist-worn GENEActiv accelerometer was comparable to the activPAL. The GENEActiv may provide an alternative, easy to wear device based measure for descriptive estimates of sedentary time in population samples.

Validity of a multi-context sitting questionnaire across demographically diverse population groups: AusDiab3.

BACKGROUND: Sitting time questionnaires have largely been validated in small convenience samples. The validity of this multi-context sitting questionnaire against an accurate measure of sitting time is reported in a large demographically diverse sample allowing assessment of validity in varied demographic subgroups. METHODS: A subgroup of participants of the third wave of the Australian Diabetes, Obesity, and Lifestyle (AusDiab3) study wore activPAL3™ monitors (7 days, 24 hours/day protocol) and reported their sitting time for work, travel, television viewing, leisure computer use and "other" purposes, on weekdays and weekend days (n = 700, age 36-89 years, 45% men). Correlations (Pearson's r; Spearman's ρ) of the self-report measures (the composite total, contextual measures and items) with monitor-assessed sitting time were assessed in the whole sample and separately in socio-demographic subgroups. Agreement was assessed using Bland-Altman plots. RESULTS: The composite total had a correlation with monitor-assessed sitting time of r = 0.46 (95% confidence interval [CI]: 0.40, 0.52); this correlation did not vary significantly between demographic subgroups (all >0.4). The contextual measure most strongly correlated with monitor-assessed sitting time was work (ρ = 0.25, 95 % CI: 0.17, 0.31), followed by television viewing (ρ = 0.16, 95 % CI: 0.09, 0.24). Agreement of the composite total with monitored sitting time was poor, with a positive bias (B = 0.53, SE 0.04, p < 0.001) and wide limits of agreement (±4.32 h). CONCLUSIONS: This multi-context questionnaire provides a total sitting time measure that ranks participants well for the purposes of assessing health associations but has limited accuracy relative to activPAL-assessed sitting time. Findings did not differ in demographic subgroups.

Excessive sitting at work and at home: Correlates of occupational sitting and TV viewing time in working adults.

BACKGROUND: Recent evidence links sedentary behaviour (or too much sitting) with poorer health outcomes; many adults accumulate the majority of their daily sitting time through occupational sitting and TV viewing. To further the development and targeting of evidence-based strategies there is a need for identification of the factors associated with higher levels of these behaviours. This study examined socio-demographic and health-related correlates of occupational sitting and of combined high levels of occupational sitting/TV viewing time amongst working adults. METHODS: Participants were attendees of the third wave (2011/12) of the Australian Diabetes, Obesity and Lifestyle (AusDiab) study who worked full-time (≥35 h/week; n = 1,235; 38 % women; mean ± SD age 53 ± 7 years). Logistic and multinomial logistic regression analyses were conducted (separately for women and men) to assess cross-sectional associations of self-reported occupational sitting time (categorised as high/low based on the median) and also the combination of occupational sitting time/TV viewing time (high/low for each outcome), with a number of potential socio-demographic and health-related correlates. RESULTS: Higher levels of occupational sitting (>6 h/day) were associated with higher household income for both genders. Lower levels of occupational sitting were associated with being older (women only); and, for men only, having a blue collar occupation, having a technical/vocational educational attainment, and undertaking more leisure-time physical activity (LTPA). Attributes associated with high levels of both occupational sitting and TV viewing time included white collar occupation (men only), lower levels of LTPA (both genders), higher BMI (men), and higher energy consumption (women). CONCLUSIONS: Higher household income (both genders) and professional/managerial occupations (men only) were correlates of high occupational sitting time, relative to low occupational sitting time, while health-related factors (lower LTPA, higher BMI - men, and higher energy consumption - women) were associated with high levels of both occupational sitting and TV viewing time, relative to low occupational sitting and low TV viewing time. These findings suggest possible high-risk groups that may benefit from targeted interventions. Further research is needed on potentially modifiable environmental and social correlates of occupational sitting time, in order to inform workplace initiatives.

Validity of a Self-Report Recall Tool for Estimating Sedentary Behavior in Adults.

BACKGROUND: Sedentary behavior is continuing to emerge as an important target for health promotion. The purpose of this study was to determine the validity of a self-report use of time recall tool, the Multimedia Activity Recall for Children and Adults (MARCA) in estimating time spent sitting/lying, compared with a device-based measure. METHODS: Fifty-eight participants (48% female, [mean ± standard deviation] 28 ± 7.4 years of age, 23.9 ± 3.05 kg/m(2)) wore an activPAL device for 24-h and the following day completed the MARCA. Pearson correlation coefficients (r) were used to analyze convergent validity of the adult MARCA compared with activPAL estimates of total sitting/lying time. Agreement was examined using Bland-Altman plots. RESULTS: According to activPAL estimates, participants spent 10.4 hr/day [standard deviation (SD) = 2.06] sitting or lying down while awake. The correlation between MARCA and activPAL estimates of total sit/lie time was r = .77 (95% confidence interval = 0.64-0.86; P < .001). Bland-Altman analyses revealed a mean bias of +0.59 hr/day with moderately wide limits of agreement (-2.35 hr to +3.53 hr/day). CONCLUSIONS: This study found a moderate to strong agreement between the adult MARCA and the activPAL, suggesting that the MARCA is an appropriate tool for the measurement of time spent sitting or lying down in an adult population.

Adults' past-day recall of sedentary time: reliability, validity, and responsiveness.

PURPOSE: Past-day recall rather than recall of past week or a usual/typical day may improve the validity of self-reported sedentary time measures. This study examined the test-retest reliability, criterion validity, and responsiveness of the seven-item questionnaire, Past-day Adults' Sedentary Time (PAST). METHODS: Participants (breast cancer survivors, n = 90, age = 33-75 yr, body mass index = 25-40 kg·m) in a 6-month randomized controlled trial of a lifestyle-based weight loss intervention completed the interviewer-administered PAST questionnaire about time spent sitting/lying on the previous day for work, transport, television viewing, nonwork computer use, reading, hobbies, and other purposes (summed for total sedentary time). The instrument was administered at baseline, 7 d later for test-retest reliability (n = 86), and at follow-up. ActivPAL3-assessed sit/lie time in bouts of ≥5 min during waking hours on the recall day was used as the validity criterion measure at both baseline (n = 72) and follow-up (n = 68). Analyses included intraclass correlation coefficients, Pearson's correlations (r), and Bland-Altman plots and responsiveness index. RESULTS: The PAST had fair to good test-retest reliability (intraclass correlation coefficient = 0.50, 95% confidence interval [CI] = 0.32-0.64). At baseline, the correlation between PAST and activPAL sit/lie time was r = 0.57 (95% CI = 0.39-0.71). The mean difference between PAST at baseline and retest was -25 min (5.2%), 95% limits of agreement = -5.9 to 5.0 h, and the activPAL sit/lie time was -9 min (1.8%), 95% limits of agreement = -4.9 to 4.6 h. The PAST showed small but significant responsiveness (-0.44, 95% CI = -0.92 to -0.04); responsiveness of activPAL sit/lie time was not significant. CONCLUSION: The PAST questionnaire provided an easy-to-administer measure of sedentary time in this sample. Validity and reliability findings compare favorably with other sedentary time questionnaires. Past-day recall of sedentary time shows promise for use in future health behavior, epidemiological, and population surveillance studies.