Contrasting compositions of sitting, standing, stepping, and sleeping time: associations with glycaemic outcome by diabetes risk

Associations of 24 h time-use compositions of sitting, standing, physical activity and sleeping with optimal cardiometabolic risk and glycaemic control: The Maastricht Study

AIMS/HYPOTHESIS

The associations of sitting, standing, physical activity and sleep with cardiometabolic health and glycaemic control markers are interrelated. We aimed to identify 24 h time-use compositions associated with optimal metabolic and glycaemic control and determine whether these varied by diabetes status.

METHODS

Thigh-worn activPAL data from 2388 participants aged 40-75 years (48.7% female; mean age 60.1 [SD = 8.1] years; n=684 with type 2 diabetes) in The Maastricht Study were examined. Compositional isometric log ratios were generated from mean 24 h time use (sitting, standing, light-intensity physical activity [LPA], moderate-to-vigorous physical activity [MVPA] and sleeping) and regressed with outcomes of waist circumference, fasting plasma glucose (FPG), 2 h plasma glucose, HbA1c, the Matsuda index expressed as z scores, and with a clustered cardiometabolic risk score. Overall analyses were adjusted for demographics, smoking, dietary intake and diabetes status, and interaction by diabetes status was examined separately. The estimated difference when substituting 30 min of one behaviour with another was determined with isotemporal substitution. To identify optimal time use, all combinations of 24 h compositions possible within the study footprint (1st-99th percentile of each behaviour) were investigated to determine those cross-sectionally associated with the most-optimal outcome (top 5%) for each outcome measure.

RESULTS

Compositions lower in sitting time and with greater standing time, physical activity and sleeping had the most beneficial associations with outcomes. Associations were stronger in participants with type 2 diabetes (p<0.05 for interactions), with larger estimated benefits for waist circumference, FPG and HbA1c when sitting was replaced by LPA or MVPA in those with type 2 diabetes vs the overall sample. The mean (range) optimal compositions of 24 h time use, considering all outcomes, were 6 h (range 5 h 40 min-7 h 10 min) for sitting, 5 h 10 min (4 h 10 min-6 h 10 min) for standing, 2 h 10 min (2 h-2 h 20 min) for LPA, 2 h 10 min (1 h 40 min-2 h 20 min) for MVPA and 8 h 20 min (7 h 30 min-9 h) for sleeping.

CONCLUSIONS/INTERPRETATION

Shorter sitting time and more time spent standing, undergoing physical activity and sleeping are associated with preferable cardiometabolic health. The substitutions of behavioural time use were significantly stronger in their associations with glycaemic control in those with type 2 diabetes compared with those with normoglycaemic metabolism, especially when sitting time was balanced with greater physical activity.

Relationship of device measured physical activity type and posture with cardiometabolic health markers: pooled dose-response associations from the Prospective Physical Activity, Sitting and Sleep Consortium

AIMS/HYPOTHESIS

The aim of this study was to examine the dose-response associations of device-measured physical activity types and postures (sitting and standing time) with cardiometabolic health.

METHODS

We conducted an individual participant harmonised meta-analysis of 12,095 adults (mean ± SD age 54.5±9.6 years; female participants 54.8%) from six cohorts with thigh-worn accelerometry data from the Prospective Physical Activity, Sitting and Sleep (ProPASS) Consortium. Associations of daily walking, stair climbing, running, standing and sitting time with a composite cardiometabolic health score (based on standardised z scores) and individual cardiometabolic markers (BMI, waist circumference, triglycerides, HDL-cholesterol, HbA1c and total cholesterol) were examined cross-sectionally using generalised linear modelling and cubic splines.

RESULTS

We observed more favourable composite cardiometabolic health (i.e. z score <0) with approximately 64 min/day walking (z score [95% CI] -0.14 [-0.25, -0.02]) and 5 min/day stair climbing (-0.14 [-0.24, -0.03]). We observed an equivalent magnitude of association at 2.6 h/day standing. Any amount of running was associated with better composite cardiometabolic health. We did not observe an upper limit to the magnitude of the dose-response associations for any activity type or standing. There was an inverse dose-response association between sitting time and composite cardiometabolic health that became markedly less favourable when daily durations exceeded 12.1 h/day. Associations for sitting time were no longer significant after excluding participants with prevalent CVD or medication use. The dose-response pattern was generally consistent between activity and posture types and individual cardiometabolic health markers.

CONCLUSIONS/INTERPRETATION

In this first activity type-specific analysis of device-based physical activity, ~64 min/day of walking and ~5.0 min/day of stair climbing were associated with a favourable cardiometabolic risk profile. The deleterious associations of sitting time were fully attenuated after exclusion of participants with prevalent CVD and medication use. Our findings on cardiometabolic health and durations of different activities of daily living and posture may guide future interventions involving lifestyle modification.

Prospective associations between changes in physical activity and sedentary time and subsequent lean muscle mass in older English adults: the EPIC-Norfolk cohort study

BACKGROUND

The longitudinal associations between physical behaviours and lean muscle mass indices need to be better understood to aid healthy ageing intervention development.

METHODS

We assessed physical behaviours (total physical activity, moderate-to-vigorous physical activity (MVPA), light physical activity, total sedentary time and prolonged sedentary bout time) for 7 days using hip-worn accelerometers. We also assessed domain-specific physical behaviours (walking, cycling, gardening and housework time) with self-report questionnaires at baseline (2006-2011) and follow-up (2012-2016) in the European Prospective Investigation into Cancer (EPIC)-Norfolk study. We assessed body composition using dual-energy X-ray absorptiometry (DEXA) at follow-up in 1535 participants (≥ 60 years at baseline). From this, we derived appendicular lean muscle mass (ALM) indices (% relative ALM = (ALM/total body weight)*100), body mass index (BMI)-scaled ALM (ALM/BMI, kg/kg/m2) and height-scaled ALM (ALM/height2, kg/m2)). We evaluated the prospective associations of both baseline and change in physical behaviours with follow-up muscle mass indices using multivariable linear regression.

RESULTS

Over 5.5 years (SD 14.8) follow-up, higher baseline accelerometer-measured physical activity and lower sedentary time were associated with higher subsequent relative ALM and BMI-scaled ALM, but not height-scaled ALM (e.g. 0.02% higher subsequent relative ALM per minute/day of baseline MVPA for men). Greater increases in physical activity and greater declines in sedentary time variables were associated with higher subsequent relative ALM and BMI-scaled ALM, but not height-scaled ALM (e.g. 0.001 kg/kg/m2 subsequent BMI-scaled ALM and 0.04% subsequent relative ALM per min/day/year increases in LPA over follow-up; 0.001 kg/kg/m2 subsequent BMI-scaled ALM and -0.03% subsequent relative ALM per min/day/year less of total sedentary time over follow-up). Greater increases in women's cycling and gardening over follow-up were associated with greater subsequent relative ALM (cycling 0.9% per hour/week/year; gardening 0.2% per hour/week/year) and BMI-scaled ALM (cycling 0.03 kg/kg/m2 per hour/week/year; gardening 0.004 kg/kg/m2 per hour/week/year).

CONCLUSION

Physical behaviours across all intensities, and in women more specifically cycling and gardening, may help prevent age-related declines in muscle mass.

Reallocating desk workers' sitting time to standing or stepping: associations with work performance

BACKGROUND

Studies have suggested that sitting time at work may lead to underperformance but they may underestimate the benefits to desk workers' performance of reducing occupational sitting time without considering the relative effects of the specific activities replaced.

AIMS

To estimate differences in work performance (presenteeism, absenteeism and engagement) when occupational sitting time is reallocated to standing/stepping in desk workers.

METHODS

Data for middle-aged desk workers were from a Japan-wide online survey (n = 2228). Self-report proportion of occupational sitting and standing/stepping, work hours and work performance indicators, including absolute (ratings relating only to self) and relative (ratings of self, compared to others) presenteeism and absenteeism, and dimensions of work engagement, were collected. Partition and isotemporal substitution models were used to investigate the associations of occupational sitting and standing/stepping time with work performance, including their reallocation effects.

RESULTS

In partition models, longer occupational sitting time was associated with a lower absolute presenteeism score (i.e. less productivity), lower absolute absenteeism (i.e. longer-than-expected work hours), and lower engagement. Longer occupational standing/stepping time was associated with lower absolute absenteeism and more engagement. Isotemporal substitution models showed that each hour of occupational sitting reallocated to standing/stepping was favourably associated with overall work engagement (B = 0.087; 95% confidence interval 0.051, 0.122) and its dimensions (B ranged from 0.078 to 0.092), but was not associated with presenteeism or absenteeism.

CONCLUSIONS

These findings suggest that management support and practical initiatives to encourage desk workers to replace portions of their sitting time with standing/stepping may contribute to enhanced work engagement.

Effect of night-time data on sedentary and upright time and energy expenditure measured with the Fibion accelerometer in Emirati women

BACKGROUND AND AIMS

Wearing an accelerometer during night-time could conflate sedentary behavior time and sleep hours. It is important to assess the impact of including night-time data on sedentary and upright behavior in a sedentary population. Therefore, we investigated differences in sitting and upright time and associated energy expenditure (EE), recorded by a Fibion accelerometer, with and without night-time data in Emirati women working in desk-based jobs.

METHODS

Thirty-one healthy Emirati women working in the government offices used the Fibion accelerometer for a week. Fibion data were included if the participants wore the device for ≥600 min per day for a minimum of three weekdays and one weekend day. Sedentary (sitting) and upright time and associated energy expenditure (EE) were recorded using the Fibion. Variables were compared with and without night-time data using the paired t tests or Wilcoxon signed-rank tests. Effect sizes were determined using Cohen's d.

RESULTS

Statistically significant differences for 15 out of 18 variables were observed when the night-time data were included. Except for cycling time, cycling EE, and vigorous activity time, nearly all other outcome measures showed a significant increase (moderate to large effect sizes) with night-time data compared to those without night-time data.

CONCLUSIONS

Cycling time/EE and vigorous activity time did not change with standard night-time data. Therefore, studies examining only cycling and/or vigorous activity time with the Fibion accelerometer do not require night-time data removal. An analysis of other variables relating to sedentary and upright time will require night-time data exclusion.