Are Self-report Measures Able to Define Individuals as Physically Active or Inactive?

    loading  Checking for direct PDF access through Ovid

Abstract

Purpose

Assess the agreement between commonly used self-report methods compared with objectively measured physical activity (PA) in defining the prevalence of individuals compliant with PA recommendations.

Methods

Time spent in moderate and vigorous PA (MVPA) was measured at two time points in 1713 healthy individuals from nine European countries using individually calibrated combined heart rate and movement sensing. Participants also completed the Recent Physical Activity Questionnaire (RPAQ), short form of the International Physical Activity Questionnaire (IPAQ), and short European Prospective Investigation into Cancer and Nutrition Physical Activity Questionnaire (EPIC-PAQ). Individuals were categorized as active (e.g., reporting ≥150 min of MVPA per week) or inactive, based on the information derived from the different measures. Sensitivity and specificity analyses and Kappa statistics were performed to evaluate the ability of the three PA questionnaires to correctly categorize individuals as active or inactive.

Results

Prevalence estimates of being sufficiently active varied significantly (P for all <0.001) between self-report measures (IPAQ 84.2% [95% confidence interval {CI}, 82.5–85.9], RPAQ 87.6% [95% CI, 85.9–89.1], EPIC-PAQ 39.9% [95% CI, 37.5–42.1] and objective measure 48.5% [95% CI, 41.6–50.9]. All self-report methods showed low or moderate sensitivity (IPAQ 20.0%, RPAQ 18.7%, and EPIC-PAQ 69.8%) to correctly classify inactive people and the agreement between objective and self-reported PA was low (ĸ = 0.07 [95% CI, 0.02–0.12], 0.12 [95% CI, 0.06–0.18], and 0.19 [95% CI, 0.13–0.24] for IPAQ, RPAQ, and EPIC-PAQ, respectively).

Conclusions

The modest agreement between self-reported and objectively measured PA suggests that population levels of PA derived from self-report should be interpreted cautiously. Implementation of objective measures in large-scale cohort studies and surveillance systems is recommended.

Related Topics

    loading  Loading Related Articles