Prediction of objectively measured physical activity and sedentariness among blue-collar workers using survey questionnaires
2016 (English)In: Scandinavian Journal of Work, Environment and Health, ISSN 0355-3140, E-ISSN 1795-990X, Vol. 42, no 3, 237-245 p.Article in journal (Refereed) Published
Objectives We aimed at developing and evaluating statistical models predicting objectively measured occupational time spent sedentary or in physical activity from self-reported information available in large epidemiological studies and surveys.
Methods Two-hundred-and-fourteen blue-collar workers responded to a questionnaire containing information about personal and work related variables, available in most large epidemiological studies and surveys. Workers also wore accelerometers for 1-4 days measuring time spent sedentary and in physical activity, defined as non-sedentary time.Least-squares linear regression models were developed, predicting objectively measured exposures from selected predictors in the questionnaire.
Results A full prediction model based on age, gender, BMI, job group, self-reported occupational physical activity, and self-reported occupational sedentary time explained 63% (R2 adjusted) of the variance of both objectively measured occupational sedentary time and physical activity time since these two exposures were complementary. Single-predictor models based only on self-reported information about either occupational physical activity or occupational sedentary time explained21% and 38%, respectively, of the variance of the objectively measured exposures. Internal validation using bootstrapping suggested that the full and single-predictor models would show almost the same performance in new data sets as in that used for modelling.
Conclusions Both full and single-predictor models based on self-reported information typically available in most large epidemiological studies and surveys were able to predict objectively measured occupational time spent sedentary or in physical activity, with explained variances ranging from 21% to 63%.
Place, publisher, year, edition, pages
2016. Vol. 42, no 3, 237-245 p.
accelerometry, actigraph, blue-collar worker, objective measure, physical activity, prediction, prediction model, questionnaire, sedentariness, sedentary time
Environmental Health and Occupational Health
IdentifiersURN: urn:nbn:se:hig:diva-20113DOI: 10.5271/sjweh.3561ISI: 000376055500008ScopusID: 2-s2.0-84964968193OAI: oai:DiVA.org:hig-20113DiVA: diva2:846603
Funding agency: Danish Work Environment Research Fund Grant number: 20130069161/92015-08-172015-08-172016-06-15Bibliographically approved