Workers' physical activity data contribute to estimating maximal oxygen consumption: a questionnaire study to concurrently assess workers' sedentary behavior and cardiorespiratory fitness
Workers' physical activity data contribute to estimating maximal oxygen consumption: a questionnaire study to concurrently assess workers' sedentary behavior and cardiorespiratory fitness
复制标题
DOI：
10.1186/s12889-019-8067-4
复制
发表时间：
2020-01-08
影响因子：
4.5
通讯作者：
Takahashi, Masaya
中科院分区：
文献类型：
--
作者：
Matsuo, Tomoaki;So, Rina;Takahashi, Masaya
背景久坐行为（SB）和心肺健康（CRF）是职业健康的重要问题。制定一份同时评估工人SB和CRF的问卷可以从根本上改善流行病学研究。工人生活活动时间问卷（WLAQ）是以前开发的，以评估工人的坐着时间。如果收集到额外的体力活动（PA）数据，如PA频率、持续时间和强度，则可以修改WLAQ以评估工人的CRF。方法198名工作成年人（女性93人，男性105人，年龄30-60岁）完成了人体测量、跑步机运动测试（测量最大耗氧量（VO2max））和修改的WLAQ （m-WLAQ，在原问题的基础上增加了PA数据的问题）。通过多元回归分析建立VO2max预测方程。利用预测残差平方和法对生成的模型进行交叉验证。其中，97名每隔一周完成两次m-WLAQ的参与者的数据用于计算类内相关系数（ICC）进行重测信度分析。结果年龄（r = - 0.29）、性别（r = 0.48）、体重指数（BMI, r = - 0.20）、总坐位时间（r = - 0.15）、PA评分（PA数据总分，r = 0.47）与VO2max显著相关。包含年龄、性别和BMI的模型占测量VO2max方差的43%[估计的标准误差(SEE) = 5.04 ml中心点kg（- 1）中心点min(- 1)]。当PA评分纳入模型时，这一比例增加到59% （SEE = 4.29 ml中心点kg（- 1）中心点min(- 1)）。交叉验证分析表明，VO2max预测模型具有较好的稳定性，但在高、低适应度个体中存在系统性的VO2max低估和高估现象。PA评分的ICC为0.87(0.82-0.91)，信度极佳。结论使用m-WLAQ获得的PA评分与测量的VO2max相关性较好，而不是静坐时间。包含PA评分、年龄、性别和BMI的方程模型对估计VO2max有良好的效度。因此，m-WLAQ可以作为一份有用的问卷，同时评估工人的SB和CRF，使其成为未来职业健康流行病学调查的合理资源。
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 (VO2max), 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 VO2max. 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 VO2max. The models that included age, sex, and BMI accounted for 43% of the variance in measured VO2max [standard error of the estimate (SEE) = 5.04 ml center dot kg(- 1)center dot min(- 1)]. These percentages increased to 59% when the PA score was included in the models (SEE = 4.29 ml center dot kg(- 1)center dot min(- 1)). Cross-validation analyses demonstrated good stability of the VO2max prediction models, while systematic underestimation and overestimation of VO2max 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 VO2max. The equation model that included the PA score as well as age, sex, and BMI had a favorable validity for estimating VO2max. 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.