Assessing SB as a sum of behaviours and using a previous day recall were the most promising features of existing tools .
Accuracy was poor for all existing tools , with underestimation and overestimation of SB .
There was a lack of evidence about sensitivity to change .
OBJECTIVE Sedentary behaviour ( SB ) has distinct deleterious health outcomes , yet there is no consensus on best practice for measurement .
This study aim ed to identify the optimal self-report tool for population surveillance of SB , using a systematic framework .
Objective vs. Self-Reported Physical Activity and Sedentary Time: Effects of Measurement Method on Relationships with Risk Biomarkers
Purpose Imprecise measurement of physical activity variables might attenuate estimates of the beneficial effects of activity on health-related outcomes . We aim ed to compare the cardiometabolic risk factor dose-response relationships for physical activity and sedentary behaviour between accelerometer- and question naire-based activity measures . Methods  Physical activity and sedentary behaviour  were assessed in 317 adults by 7-day accelerometry and International Physical Activity Question naire ( IPAQ ) . Fasting blood was taken to determine insulin , glucose , triglyceride and total , LDL and HDL cholesterol concentrations and homeostasis model-estimated insulin resistance ( HOMAIR ) . Waist circumference , BMI , body fat percentage and blood pressure were also measured . Results For both accelerometer-derived sedentary time ( < 100 counts.min−1 ) and IPAQ-reported sitting time significant positive ( negative for HDL cholesterol ) relationships were observed with all measured risk factors – i.e. increased sedentary behaviour was associated with increased risk ( all p≤0.01 ) . However , for HOMAIR and insulin the regression coefficients were > 50 % lower for the IPAQ-reported compared to the accelerometer-derived measure ( p<0.0001 for both interactions ) . The relationships for moderate-to-vigorous physical activity ( MVPA ) and risk factors were less strong than those observed for sedentary behaviours , but significant negative relationships were observed for both accelerometer and IPAQ MVPA measures with glucose , and insulin and HOMAIR values ( all p<0.05 ) . For accelerometer-derived MVPA only , additional negative relationships were seen with triglyceride , total cholesterol and LDL cholesterol concentrations , BMI , waist circumference and percentage body fat , and a positive relationship was evident with HDL cholesterol ( p = 0.0002 ) . Regression coefficients for HOMAIR , insulin and triglyceride were 43–50 % lower for the IPAQ-reported compared to the accelerometer-derived MVPA measure ( all p≤0.01 ) . Conclusion Using the IPAQ to determine sitting time and MVPA reveals some , but not all , relationships between these activity measures and metabolic and vascular disease risk factors . Using this self-report method to quantify activity can therefore underestimate the strength of some relationships with risk factors
Assessing SB as a sum of behaviours and using a previous day recall were the most promising features of existing tools .
Accuracy was poor for all existing tools , with underestimation and overestimation of SB .
There was a lack of evidence about sensitivity to change .
OBJECTIVE Sedentary behaviour ( SB ) has distinct deleterious health outcomes , yet there is no consensus on best practice for measurement .
This study aim ed to identify the optimal self-report tool for population surveillance of SB , using a systematic framework .