Academic journal article Scandinavian Journal of Work, Environment & Health

Prediction of Objectively Measured Physical Activity and Sedentariness among Blue-Collar Workers Using Survey Questionnaires

Academic journal article Scandinavian Journal of Work, Environment & Health

Prediction of Objectively Measured Physical Activity and Sedentariness among Blue-Collar Workers Using Survey Questionnaires

Article excerpt

Even in modern information societies, a considerable proportion of the working population is exposed to physical activity at work (1, 2). In a national survey in 2012, 39% of the Danish workforce reported to have a job where >75% of the time required some physical activity, such as standing and walking (3). More selfreported time spent in physical activity during work has been associated with increased risk of long-term sickness absence (2, 4), premature drop-out from the workforce (5), and cardiovascular and all-cause mortality (1, 6, 7). On the other hand, other workers spend a large proportion of the time at work being sedentary (8-10), which has been suggested to be associated with increased all-cause mortality (11), musculoskeletal pain (12), and obesity (13).

Occupational time spent sedentary and in physical activity have so far mainly been determined using questionnaires that are feasible to administer in a large population, such as in national surveys (14-16). However, questionnaires have been criticized for giving biased and imprecise results compared to objective measurements (17). Systematic and random measurement errors may lead to misleading results, both when documenting time spent sedentary and in physical activity and when determining associations with relevant outcomes such as health and well-being. As an alternative, objective measurements using accelerometers offer accurate information of time spent sedentary and in physical activity (18, 19). Thus, accelerometer recordings have been used as the gold standard for validating questionnaire-based data on time spent sedentary and in physical activity (20, 21). However, accelerometers demanding more resources to use than questionnaires (22), disqualifing them from most large-scale studies.

An attractive compromise would be to predict objectively measured occupational time spent sedentary and in physical activity from self-reported information that would generally be available in most large epidemiological studies and surveys. Explicit prediction models have been proposed before to predict time spent sedentary and in physical activity (23-25), but these studies have not developed models for exposures at work, which may show associations with self-reported predictors other than leisure time exposures. A few previous studies have, indeed, developed prediction models for time spent sedentary and in physical activity specifically at work (26-30). However, they have mainly focused on predicting answers to some self-reported variables by another type of self-reported information. This approach increases the risk of correlated error or common-method bias (31).

Another limitation of previous prediction models addressing time spent sedentary and in physical activity at work is that the predictors included in the models, such as cognitive (32) and psychosocial variables - including social norms, self-efficacy and advantages of sitting less (26) - are not normally available in large epidemiological studies and surveys. Developing models based on predictors that typically appear in large epidemiological studies and surveys would increase the utility of the models in the context of, for instance, public health surveys and cohort studies of occupational health.

As a general endeavor in exposure modelling, examination of simple models based on few predictors is of interest, since parsimonious models may be easier to use and more stable than models based on many predictors. In the present context, this would call for assessments of the performance of models based only on selected questionnaire variables that can be expected to be particularly predictive of sedentary behavior and physical activity at work. Thus, this study aimed at developing and evaluating statistical models predicting objectively measured time spent sedentary and in physical activity at work from self-reported variables which would generally be available in large epidemiological studies and surveys. …

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