Harmonizing measurement tools: examining the concurrent validity of the Daily Activity Behaviors Questionnaire compared to the ActiGraph to assess 24-hour movement behaviors among adults - Iris Willems; Vera Verbestel; Dorothea Dumuid; Patrick Calders; Bruno Lapauw; Marieke De Craemer (BMC Public Health)
Abstract Purpose An accurate assessment of time spent in 24-hour movement behaviors (24 h-MBs) is crucial in exploring health related associations. This study aims to evaluate the concurrent validity of the Daily Activity Behavior Questionnaire (DABQ) compared to the ActiGraph using absolute and relative indicators of validity. Methods This cross-sectional observational study included 105 adults (45 ± 13 y/o, 54% female). Participants wore an ActiGraph during seven consecutive days followed by filling in the DABQ recalling the past seven days. Intraclass correlations (95% confidence intervals), Bland-Altman plots, Spearman’s correlations and the magnitude of error were calculated to estimate the absolute agreement and validity. Interaction effects between sociodemographic variables and the measurement methods were explored in mixed models. All analyses were compared by four commonly used data processing methods for ActiGraph data (cut-points and data reduction method-specific). Results Moderate absolute agreement (ICC = 0.56) and validity (rhosleep=0.58) was found for sleep comparing the DABQ with the ActiGraph. Time spent in sedentary behavior (SB), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) showed poor absolute agreement (ICCSB: 0.01–0.38, ICCLPA: 0.00-0.31; ICCMVPA: 0.23–0.30) and validity (rhoSB: 0.01–0.43, rhoLPA: 0.10–0.46; rhoMVPA: 0.38–0.44) comparing the DABQ with the ActiGraph. The Ranges in ICC and Spearmans’ rho include the comparison between the four data processing methods. A significant interaction was found between the measurement method and educational level (p < 0.001), in specific for sleep, SB and LPA. Conclusion Compared to the ActiGraph, the DABQ showed accurate time-use estimates for sleep but presented poor to moderate evidence of validity regarding SB, LPA and MVPA. This was shown in underestimations regarding SB and MVPA, and overestimations regarding LPA. However, educational level and data processing methods contributed to these variations.