Moderate-intensity stepping in older adults: insights from treadmill walking and daily living.

BACKGROUND: A step cadence of 100 steps/minute is widely used to define moderate-intensity walking. However, the generalizability of this threshold to different populations needs further research. We investigate moderate-intensity step cadence values during treadmill walking and daily living in older adults. METHODS: Older adults (≥ 60 years) were recruited from urban community venues. Data collection included 7 days of physical activity measured by an activPAL3™ thigh worn device, followed by a laboratory visit involving a 60-min assessment of resting metabolic rate, then a treadmill assessment with expired gas measured using a breath-by-breath analyser and steps measured by an activPAL3™. Treadmill stages were undertaken in a random order and lasted 5 min each at speeds of 1, 2, 3, 4 and 5 km/h. Metabolic equivalent values were determined for each stage as standardised values (METSstandard) and as multiples of resting metabolic rate (METSrelative). A value of 3 METSstandard defined moderate-intensity stepping. Segmented generalised estimating equations modelled the association between step cadence and MET values. RESULTS: The study included 53 participants (median age = 75, years, BMI = 28.0 kg/m2, 45.3% women). At 2 km/h, the median METSstandard and METSrelative values were above 3 with a median cadence of 81.00 (IQR 72.00, 88.67) steps/minute. The predicted cadence at 3 METSstandard was 70.3 (95% CI 61.4, 75.8) steps/minute. During free-living, participants undertook median (IQR) of 6988 (5933, 9211) steps/day, of which 2554 (1297, 4456) steps/day were undertaken in continuous stepping bouts lasting ≥ 1 min. For bouted daily steps, 96.4% (90.7%, 98.9%) were undertaken at ≥ 70 steps/minute. CONCLUSION: A threshold as low as 70 steps/minute may be reflective of moderate-intensity stepping in older adults, with the vast majority of all bouted free-living stepping occurring above this threshold.

Self-reported walking pace, polygenic risk scores and risk of coronary artery disease in UK biobank.

BACKGROUND AND AIMS: Both polygenic risk scores (PGS) and self-reported walking pace have been shown to predict cardiovascular disease; whether combining both factors produces greater risk differentiation is, however, unknown. METHODS AND RESULTS: We estimated the 10-year absolute risk of coronary artery disease (CAD), adjusted for traditional risk factors, and the C-index across nine PGS and self-reported walking pace in UK Biobank study participants between Mar/2006-Feb/2021. In 380,693 individuals (54.8% women), over a median (5th, 95th percentile) of 11.9 (8.3, 13.4) years, 2,603 (1.2%) CAD events occurred in women and 8,259 (4.8%) in men. Both walking pace and genetic risk were strongly associated with CAD. The absolute 10-year risk of CAD was highest in slow walkers at high genetic risk (top 20% of PGS): 2.72% (95% CI: 2.30-3.13) in women; 9.60% (8.62-10.57) in men. The risk difference between slow and brisk walkers was greater at higher [1.26% (0.81-1.71) in women; 3.63% (2.58-4.67) in men] than lower [0.76% (0.59-0.93) and 2.37% (1.96-2.78), respectively] genetic risk. Brisk walkers at high genetic risk had equivalent (women) or higher (men) risk than slow walkers at moderate-to-low genetic risk (bottom 80% of PGS). When added to a model containing traditional risk factors, both factors separately improved risk discrimination; combining them resulted in the greatest discrimination: C-index of 0.801 (0.793-0.808) in women; 0.732 (0.728-0.737) in men. CONCLUSION: Self-reported slow walkers at high genetic risk had the greatest risk of CAD, identifying a potentially important population for intervention. Both PGS and walking pace contributed to risk discrimination.

Regular brief interruptions to sitting after a high-energy evening meal attenuate glycemic excursions in overweight/obese adults.

BACKGROUND AND AIMS: Modern Western lifestyles are characterized by consumption of approximately 45% of total daily energy intake at the evening meal, followed by prolonged sitting while watching television (TV), which may deleteriously impact glycemic control. After a high-energy evening meal (dinner), we examined whether regular, brief activity bouts during TV commercial breaks could acutely lower postprandial glucose and insulin responses in overweight/obese adults, compared to prolonged uninterrupted sitting. METHODS AND RESULTS: Nine overweight/obese adults (29.7 ± 4.06 kg m-2; aged 32 ± 3 years; 5 male) completed two laboratory-based conditions of three and a half hours: prolonged sitting during TV viewing (SIT); and, prolonged sitting interrupted every 20 min with 3 min of light-intensity body-weight resistance activities (active commercial breaks; ACBs). Venous postprandial glucose and insulin responses to dinner were calculated as positive incremental area under the curve (iAUC) from baseline. Interstitial glucose was measured using a continuous glucose monitor and quantified as total AUC (tAUC). Compared to SIT, plasma glucose iAUC was reduced by 33% [3.4 ± 1.0 vs 5.1 ± 1.0 (mean ± SEM) mmol h·L-1, p = 0.019] and plasma insulin iAUC by 41% (813 ± 224 vs 1373 ± 224, p = 0.033 pmol h·L-1) for the ACB condition. During the ACB condition there was a significant reduction in interstitial glucose tAUC (24.4 ± 5.2 vs 26.9 ± 5.2 mmol h·L-1, p < 0.001), but this did not persist beyond the laboratory observation period. CONCLUSIONS: Regular brief light-intensity activity bouts can attenuate glycemic responses during television viewing time following a high-energy evening meal in overweight/obese adults.

Health effects of reduced occupational sedentary behaviour in type 2 diabetes using a mobile health intervention: a study protocol for a 12-month randomized controlled trial-the ROSEBUD study.

BACKGROUND: Short-term trials conducted in adults with type 2 diabetes mellitus (T2DM) showed that reducing sedentary behaviour by performing regular short bouts of light-intensity physical activity enhances health. Moreover, support for reducing sedentary behaviour may be provided at a low cost via mobile health technology (mHealth). There are a wide range of mHealth solutions available including SMS text message reminders and activity trackers that monitor the physical activity level and notify the user of prolonged sitting periods. The aim of this study is to evaluate the effects of a mHealth intervention on sedentary behaviour and physical activity and the associated changes in health in adults with T2DM. METHODS: A dual-arm, 12-month, randomized controlled trial (RCT) will be conducted within a nationwide Swedish collaboration for diabetes research in primary health care. Individuals with T2DM (n = 142) and mainly sedentary work will be recruited across primary health care centres in five regions in Sweden. Participants will be randomized (1:1) into two groups. A mHealth intervention group who will receive an activity tracker wristband (Garmin Vivofit4), regular SMS text message reminders, and counselling with a diabetes specialist nurse, or a comparator group who will receive counselling with a diabetes specialist nurse only. The primary outcomes are device-measured total sitting time and total number of steps (activPAL3). The secondary outcomes are fatigue, health-related quality of life and musculoskeletal problems (self-reported questionnaires), number of sick leave days (diaries), diabetes medications (clinical record review) and cardiometabolic biomarkers including waist circumference, mean blood pressure, HbA1c, HDL-cholesterol and triglycerides. DISCUSSION: Successful interventions to increase physical activity among those with T2DM have been costly and long-term effectiveness remains uncertain. The use of mHealth technologies such as activity trackers and SMS text reminders may increase awareness of prolonged sedentary behaviour and encourage increase in regular physical activity. mHealth may, therefore, provide a valuable and novel tool to improve health outcomes and clinical management in those with T2DM. This 12-month RCT will evaluate longer-term effects of a mHealth intervention suitable for real-world primary health care settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT04219800 . Registered on 7 January 2020.