Workers’ physical activity data contribute to estimating maximal oxygen consumption: a questionnaire study to concurrently assess workers’ sedentary behavior and cardiorespiratory fitness

Abstract

Background: Sedentary behavior (SB) and cardiorespiratory fitness (CRF) are important issues in occupational health. Developing a questionnaire to concurrently assess workers' SB and CRF could fundamentally improve epidemiological research. The Worker's Living Activity-time Questionnaire (WLAQ) was developed previously to assess workers' sitting time. WLAQ can be modified to evaluate workers' CRF if additional physical activity (PA) data such as PA frequency, duration, and intensity are collected. Methods: A total of 198 working adults (93 women and 105 men; age, 30-60 years) completed anthropometric measurements, a treadmill exercise test for measuring maximal oxygen consumption (VO 2max), and modified WLAQ (m-WLAQ, which included questions about PA data additional to the original questions). Multiple regression analyses were performed to develop prediction equations for VO 2max. The generated models were cross-validated using the predicted residual error sum of squares method. Among the participants, the data of 97 participants who completed m-WLAQ twice after a 1-week interval were used to calculate intraclass correlation coefficient (ICC) for the test-retest reliability analyses. Results: Age (r = − 0.29), sex (r = 0.48), body mass index (BMI, r = − 0.20), total sitting time (r = − 0.15), and PA score (total points for PA data, r = 0.47) were significantly correlated with VO 2max. The models that included age, sex, and BMI accounted for 43% of the variance in measured VO 2max [standard error of the estimate (SEE) = 5.04 ml•kg − 1 •min − 1 ]. These percentages increased to 59% when the PA score was included in the models (SEE = 4.29 ml•kg − 1 •min − 1). Cross-validation analyses demonstrated good stability of the VO 2max prediction models, while systematic underestimation and overestimation of VO 2max were observed in individuals with high and low fitness, respectively. The ICC of the PA score was 0.87 (0.82-0.91), indicating excellent reliability. Conclusions: The PA score obtained using m-WLAQ, rather than sitting time, correlated well with measured VO 2max. The equation model that included the PA score as well as age, sex, and BMI had a favorable validity for estimating VO 2max. Thus, m-WLAQ can be a useful questionnaire to concurrently assess workers' SB and CRF, which makes it a reasonable resource for future epidemiological surveys on occupational health.

Development and Validation of 3 Min Incremental Step-In-Place Test for Predicting Maximal Oxygen Uptake in Home Settings: A Submaximal Exercise Study to Assess Cardiorespiratory Fitness

“…Many previous studies of . VO 2max prediction have also found that PBF is a better predictor than BMI [2,40,41]. Therefore, when financial conditions permit, people can consider adopting the PBF models to evaluate their .…”

Accuracy of Non-Exercise Estimated Cardiorespiratory Fitness in Japanese Adults

“…The authors found strong correlations, R = 0.85 (SEE 3.11) and R = 0.84 (SEE 4.15), compared to maximal cycle ergometer testing [ 23 , 24 ]. More recently, Matsuo et al developed an eCRF PAS-based equation compared to maximal treadmill test in working Japanese adults ( n = 198) and found a strong correlation ( r = 0.77) [ 25 ]. As expected, the PAS model correlations are higher than our eCRF model without PAS; beyond genetics, PAS is an essential variable for modifying CRF [ 2 , 4 , 11 ].…”

“…As expected, the PAS model correlations are higher than our eCRF model without PAS; beyond genetics, PAS is an essential variable for modifying CRF [ 2 , 4 , 11 ]. Though these eCRF PAS-based correlations are higher, access to specific PAS data from existing EMR datasets is not likely to have been recorded in EMRs [ 7 , 25 ].…”

What Intervention Techniques Are Effective in Changing Positive Affective Variables and Physical Activity? A Systematic Review and Meta-Analysis

“…Studies in which the first author was unsure whether to be included were discussed and determined with the last author. A study was eligible for our meta-analysis if it met the following criteria: (1) experimental studies assessing PAV as a dependent variable; (2) PAV was a target of the intervention; (3) studies whose goal was to increase lifestyle or recreational PA, not for competitive sports (Caspersen et al, 1985 ; Vanhees et al, 2005 ); (4) sufficient data to calculate the effect sizes (Hedges' g) of PAVs and PA; (5) participants were healthy individuals (not a clinically defined population and not pregnant). Furthermore, we intentionally chose a minimum duration of PA of 10 min, given that 10 min is the recommended minimum duration of exercise to elicit health benefits (Edwards and Loprinzi, 2019 ).…”