A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance.

Area of Science:

• Biomedical Engineering
• Public Health
• Sports Science

Background:

• Current physical activity guidelines often rely on self-report or simplistic accelerometer cut-points.
• These methods can be population-dependent and lack comparability across different studies and demographics.
• There is a need for objective, population-independent metrics to assess physical activity levels globally.

Purpose of the Study:

• To introduce and validate a novel accelerometer metric (M_ACC) for quantifying physical activity.
• To demonstrate its utility in assessing the prevalence of meeting current physical activity guidelines for global surveillance.
• To explore its potential for informing future accelerometer-driven physical activity guidelines.

Main Methods:

• Secondary analysis of five diverse accelerometer datasets (children, adolescents, adults, specific populations).
• Utilized open-source GGIR software to calculate acceleration thresholds for accumulated active minutes (M60_ACC, M30_ACC, M2_ACC).
• Cross-sectional data analysis to determine metric prevalence across different age and health groups.

Main Results:

• Prevalence of meeting moderate-to-vigorous physical activity guidelines varied significantly (17-68% in children, 15-81% in adults) based on M_ACC metrics.
• A smaller proportion of women (6-13%) met bone health thresholds indicated by M2_ACC.
• Metric values generally declined with increasing age.

Conclusions:

• The developed M_ACC metrics are suitable for global physical activity surveillance and assessing guideline adherence.
• Future accumulation of accelerometer and health data will enable age- and sex-specific interpretations.
• These metrics hold potential for deriving evidence-based physical activity guidelines directly from accelerometer data.