Simple step counting captures comparable health information to complex accelerometer measurements.

Area of Science:

• Exercise Physiology
• Biomedical Engineering
• Public Health

Background:

• Current physical activity guidelines are hard to interpret and monitor.
• Step-based metrics offer a simpler alternative to accelerometer data but need validation.
• Wearable device data requires comparison with established accelerometer measurements for health outcome correlation.

Purpose of the Study:

• To assess how well step-based metrics reflect health information from accelerometer data.
• To identify optimal step cadence and intensity thresholds for cardiometabolic health in middle-aged adults.

Main Methods:

• Analysis of cross-sectional data from 4172 participants (50-64 years) in the Swedish CArdioPulmonary bioImage Study (SCAPIS).
• Physical activity measured using ActiGraph accelerometers (step metrics and full data).
• Cardiorespiratory fitness and cardiometabolic health assessed via cycle ergometer tests and composite scores (waist circumference, blood pressure, lipids, HbA1c).

Main Results:

• Step counting metrics retained 88% of health-related information from full accelerometer data.
• Optimal accelerometer intensity for cardiometabolic health was approximately four metabolic equivalents of tasks (METs).
• A step cadence of 80 steps/min, not 100 steps/min, better captured moderate-intensity activity.

Conclusions:

• Step data effectively captures significant health-related information from accelerometer measurements in middle-aged adults.
• Findings support using step-based metrics for physical activity assessment and promotion.
• Recalibration of intensity thresholds for free-living conditions is suggested.