BackgroundAmong blue-collar workers, high physical work demands are generally considered to be the main cause of musculoskeletal pain and work disability. However, current available research on this topic has been criticised for using self-reported data, cross-sectional design, insufficient adjustment for potential confounders, and inadequate follow-up on the recurrent and fluctuating pattern of musculoskeletal pain. Recent technological advances have provided possibilities for objective diurnal field measurements of physical activities and frequent follow-up on musculoskeletal pain.The main aim of this paper is to describe the background, design, methods, limitations and perspectives of the Danish Physical Activity cohort with Objective measurements (DPhacto) investigating the association between objectively measured physical activities capturing work and leisure time and frequent measurements of musculoskeletal pain among blue-collar workers.Methods/designApproximately 2000 blue-collar workers are invited for the study and asked to respond to a baseline questionnaire, participate in physical tests (i.e. muscle strength, aerobic fitness, back muscle endurance and flexibility), to wear accelerometers and a heart rate monitor for four consecutive days, and finally respond to monthly text messages regarding musculoskeletal pain and quarterly questionnaires regarding the consequences of musculoskeletal pain on work activities, social activities and work ability for a one-year follow-up period.DiscussionThis study will provide novel information on the association between physical activities at work and musculoskeletal pain. The study will provide valid and precise documentation about the relation between physical work activities and musculoskeletal pain and its consequences among blue-collar workers.

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Until recently, methods for objective quantification of sitting time have been lacking. The aim of this study was to validate self-reported measures against objectively measured total sitting time and longest continuous time with uninterrupted sitting during working hours, leisure time on workdays and leisuredays. Objective diurnal measurement of sitting time was obtained among 26 office workers with 2 accelerometers (ActiGraph GT3X+) for a 7-day period. Customized software (Acti4) was used to identify sitting time separated from other sedentary behaviours. Self-reported sitting time was obtained from a retrospective 7-day questionnaire. A generalized linear model showed the difference between the methods. No significant correlations were found between objective and self-reported sitting time (r<0.315). Total sitting time was significantly underestimated (2.4 h) on a leisureday (p<0.001) and uninterrupted sitting time was in all 3 time settings significantly overestimated (0.4-0.5 h) (p<0.045). Poor agreement (mean difference between 0.5 to -2.4 h) between objectively measured and self-reported sitting time was shown in Bland-Altman plots with wide (3.3-10.8 h) limits of agreement. This study showed a great individual variation and a general lack of agreement between self-reported vs. objectively measured total and uninterrupted sitting time. Objective measures are recommended for determining sitting time.

Sitting at work is suggested to increase risk for low-back pain (LBP). Thus, an association between temporal patterns of sitting and time course of LBP, across 12 months, among 665 participants from the DPhacto cohort was conducted. We found that longer durations of total and temporal sitting periods at work were significantly associated with a favorable time course of LBP.Affiliation:

This study is the first to investigate the association between objectively measured duration of forward bending and the prospective development and aggravation of low-back pain among blue-collar workers. This study shows no significant association. Future studies in the cohort will investigate the contribution of possible effect modifiers such as psychosocial work factors and physical capacity.Affiliation:

BackgroundLow back pain (LBP) occurrence and intensity are considered to fluctuate over time, requiring frequent repetitive assessments to capture its true time pattern. Text messages makes frequent reporting of LBP feasible, which enables investigation of 1) the time pattern of LBP, and 2) predictors for having a continued high (chronic) level of LBP over longer periods of time. However, this has not previously been investigated in a larger working population.The aim of this study was to examine these two aspects in a working population of 842 workers with repetitive measurements of LBP over one year.MethodsThere were 842 workers from 15 companies in the DPhacto study participating in this study. Demographic, work- and health-related factors, and back endurance were measured at baseline, while 14 monthly repeated text message assessments of LBP intensity were prospectively collected. A factor analysis was used to cluster different time-patterns of LBP, and defining the group of participants with chronic LBP. A multi-adjusted logistic regression analysis was performed to investigate baseline predictors for chronic LBP.ResultsThe factor analysis revealed two dimensions of the time pattern of LBP, defined as the LBP intensity and LBP variation, respectively. A Visual Pain Mapping was formed based on the combination of the two pain dimensions, classifying the time-patterns of LBP into four categories: (1) low intensity and low variation, (2) low intensity and high variation, (3) high intensity and high variation, (4) high intensity and low variation (defined as chronic LBP). Significant baseline predictors for chronic LBP in the fully adjusted model were high baseline LBP (p < 0.01), low workability (p < 0.01), low BMI (p < 0.05), and being a blue-collar worker (vs. white-collar worker) (p < 0.05).ConclusionThis study presents a novel classification of the course of LBP based on repetitive measurements over a year, and revealed the predicting factors for chronic LBP based on repetitive measurements in a working population.