Accelerometry is increasingly being used to assess sedentary time in epidemiological studies, yet the most appropriate means of processing these data remains uncertain. This cross-sectional study examined the influence of selected accelerometer cut points and nonwear criteria on associations of sedentary time with adiposity and clustered metabolic risk.
Data were from the European Youth Heart Study, which included assessment of sedentary time by accelerometer. Sixteen sedentary time variables were constructed based on combinations of frequently used cut points (100, 500, 800, and 1100 counts per minute) and nonwear criteria (10-, 20-, 60-, and 100-min consecutive zeros). Adiposity was assessed by sum of four skinfold thickness measures. A clustered metabolic risk score was calculated as the mean of standardized metabolic syndrome components, including blood pressure, insulin resistance, and inverted fasting HDL-cholesterol. Analyses were conducted using multilevel cross-sectional time series regression, adjusted for overall physical activity (accelerometer counts per minute). Meta-analysis was used to obtain pooled estimates of the exposure–outcome association over all processing protocols; meta-regression was used to determine the influence of nonwear and cut point protocol on observed associations.
Sedentary time follows a power law with cut point (exponent = 0.27) and zero string (exponent = 0.03), and it was positively associated with clustered metabolic risk (β = 0.0051; 95% confidence interval = 0.0018–0.0085). The association was moderated by cut point, with higher cut points typically producing stronger associations. No significant association between sedentary time and adiposity was observed.
The choice of accelerometer cut point may moderate the association between sedentary time and clustered metabolic risk, suggesting that direct comparisons of associations between studies using different cut points must be made with caution.
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1UKCRC Centre for Diet and Activity Research (CEDAR), Cambridge, UNITED KINGDOM; 2Medical Research Council, Epidemiology Unit, Cambridge, UNITED KINGDOM; 3Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, NORWAY; 4Institute of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, DENMARK; and 5Faculty of Human Kinetics, CIPER, Technical University of Lisbon, Lisbon, PORTUGAL
Address for correspondence: Ulf Ekelund, Ph.D., Department of Sport Medicine, Norwegian School of Sport Sciences, PO Box 4014 – Ulleval Stadion, 0806 Oslo, Norway; E-mail: Ulf.Ekelund@nih.no.
Submitted for publication September 2012.
Accepted for publication November 2012.
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