2134/10059266.v1 Alex V. Rowlands Alex V. Rowlands Stuart J. Fairclough Stuart J. Fairclough Tom Yates Tom Yates Charlotte L. Edwardson Charlotte L. Edwardson Melanie Davies Melanie Davies Fehmidah Munir Fehmidah Munir Kamlesh Khunti Kamlesh Khunti Vicky H. Stiles Vicky H. Stiles Activity intensity, volume, and norms: Utility and interpretation of accelerometer metrics Loughborough University 2019 GENEActiv ActiGraph Axivity Wrist-worn GGIR Intensity gradient 2019-10-29 09:21:45 Journal contribution https://repository.lboro.ac.uk/articles/journal_contribution/Activity_intensity_volume_and_norms_Utility_and_interpretation_of_accelerometer_metrics/10059266 PURPOSE: The physical activity profile can be described from accelerometer data using two population-independent metrics: average acceleration (ACC, volume) and intensity gradient (IG, intensity). This article aims 1) to demonstrate how these metrics can be used to investigate the relative contributions of volume and intensity of physical activity for a range of health markers across data sets and 2) to illustrate the future potential of the metrics for generation of age and sex-specific percentile norms. METHODS: Secondary data analyses were conducted on five diverse data sets using wrist-worn accelerometers (ActiGraph/GENEActiv/Axivity): children (n = 145), adolescent girls (n = 1669), office workers (n = 114), premenopausal (n = 1218) and postmenopausal (n = 1316) women, and adults with type 2 diabetes (n = 475). Open-source software (GGIR) was used to generate ACC and IG. Health markers were (a) zBMI (children), (b) út (adolescent girls and adults), (c) bone health (pre- and postmenopausal women), and (d) physical function (adults with type 2 diabetes). RESULTS: Multiple regression analyses showed that IG, but not ACC, was independently associated with zBMI/út in children and adolescents. In adults, associations were stronger and the effects of ACC and IG were additive. For bone health and physical function, interactions showed associations were strongest if IG was high, largely irrespective of ACC. Exemplar illustrative percentile "norms" showed the expected age-related decline in physical activity, with greater drops in IG across age than ACC. CONCLUSION: The ACC and the IG accelerometer metrics facilitate the investigation of whether volume and intensity of physical activity have independent, additive, or interactive effects on health markers. In future studies, the adoption of data-driven metrics would facilitate the generation of age- and sex-specific norms that would be beneficial to researchers.