Accelerometer-Derived Sedentary and Physical Activity Time in Overweight/Obese Adults with Type 2 Diabetes: Cross-Sectional Associations with Cardiometabolic Biomarkers

Abstract

ObjectiveTo examine the associations of sedentary time and physical activity with biomarkers of cardiometabolic health, including the potential collective impact of shifting mean time use from less- to more-active behaviours (cross-sectionally, using isotemporal substitution), in adults with type 2 diabetes.MethodsParticipants with overweight/obese body mass index (BMI; ≥25 kg/m2) (n = 279; 158 men, mean [SD] age = 58.2 [8.6] years) wore Actigraph GT1M accelerometers (waking hours; seven days) to assess moderate- to vigorous-intensity physical activity (MVPA), light-intensity activity, and sedentary time (segregated into non-prolonged [accumulated in bouts <30min] and prolonged [accumulated in bouts ≥30 min]). Cross-sectional associations with waist circumference, BMI, fasting blood (HbA1c, glucose, triacylglycerols, high-density lipoprotein cholesterol), and blood pressure of these activity variables (30 min/day increments) were examined adjusted for confounders and wear then, if significant, examined using isotemporal substitution modelling.ResultsWaist circumference and BMI were significantly (p<0.05) associated with more prolonged sedentary time and less light-intensity activity. Light intensity activity was also significantly associated with lower fasting plasma glucose (relative rate: 0.98, 95% CI: 0.97, 1.00; p<0.05). No biomarker was significantly associated with non-prolonged sedentary time or MVPA. Lower mean prolonged sedentary time (−30 min/day) with higher mean light intensity time (+30 min/day) was significantly associated with lower waist circumference (β = −0.77, 95% CI: −1.33, −0.22 cm). Lower mean prolonged sedentary time (−30 min/day) with either 30 min/day higher mean non-prolonged sedentary time (β = −0.35, 95%CI: −0.70, −0.01 kg/m2) or light-intensity time (β = −0.36, −0.61, −0.11 kg/m2) was associated with significantly lower average BMI.ConclusionsSignificantly improved mean levels of waist circumference and BMI were observed when shifting time from prolonged sedentary to non-prolonged sedentary or light-intensity activity (cross-sectionally). Lifestyle interventions in overweight/obese adults with type 2 diabetes might consider targeting shifts in these non-MVPA activities to more rigorously evaluate their potential cardiometabolic benefit in this population.

Correlates of accelerometer-assessed physical activity and sedentary time among adults with type 2 diabetes

“…Our results are also consistent with those from Healy and colleagues, 17 who found that among a subsample of the AusDiab study that wore an accelerometer for 7 days (n = 169), 57% of their day was spent sedentary. More recently, Healy et al 30 31 Given that collectively our participants spent the majority (97%) of their time either sedentary or in LPA, we could suggest that adults with type 2 diabetes should redistribute their sedentary behaviours in favour of fewer prolonged bouts. In addition, we found significant associations between sedentary time/LPA and sex, increasing BMI, employment status, and income.…”

SCAPIS Pilot Study: Sitness, Fitness and Fatness— Is Sedentary Time Substitution by Physical Activity Equally Important for Everyone’s Markers of Glucose Regulation?

“…Running isotemporal substitution analyses, rather than regression modeling, has been put forward as a suitable analysis method to examine the theoretical effect of substituting one activity, for example, SED with another, for example LIPA, while keeping total time and time in other activities fixed 13 . Previous isotemporal substitution studies, including measurements of glucose regulation and/or insulin sensitivity, have found beneficial associations with SED substitution with standing 14 , LIPA [14][15][16][17] and MVPA 16,17 , respectively, in healthy individuals 14,16 and those at-risk of or with type 2 diabetes.…”

An Evaluation of Accelerometer-derived Metrics to Assess Daily Behavioral Patterns

“…Descriptive studies have used metrics that may reflect daily behavioral patterns, including time spent active or sedentary within various bout lengths (e.g., 1,5,10, 20 min) (3, 12, 20, 41). Other studies have identified associations between several accelerometer-derived metrics (e.g., number of breaks, Gini index and bouts of sedentary time >20minutes) in relation to obesity and metabolic health (5, 18, 19, 44), and differences in sedentary behavioral patterns have been noted in cross-sectional analysis comparing healthy and diseased populations (6, 36). Understanding whether there are links between daily behavioral patterns and health could lead to innovative opportunities for intervention and improve public health.…”