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Objectives: To describe upper arm postures and movements among female hairdressers, including the variability between hairdressers, between days within hairdresser, and between tasks, as a basis for understanding the characteristics of exposures in the job, considering possible sources of variation and recovery, and discussing appropriate exposure assessment strategies.

Methods: Data on upper arm postures were collected using inclinometers during four working days the same week from 28 female hairdressers working in 13 salons. Twenty of the hairdressers noted customer on and off times in a diary, to allow separate analyses of customer tasks (CT) and auxiliary non-customer tasks (AT), including breaks. For a number of posture and movement variables, mean values and variance components between subjects (BS) and within subjects between days (BD) were estimated using restricted maximum likelihood algorithms in one-way random effect models.

Results: For the 20 hairdressers with diaries, CT accounted for 279 min (58%) (SD_BS = 39 min and SD_BD = 85 min) of the working day and AT and breaks for 207 min (42%) (SD_BS = 46 min and SD_BD = 88 min). The hairdressers worked with the right arm elevated >60° for 6.8% of the whole job (SD_BS = 2.8% and SD_BD = 2.0%). On average, the hairdressers worked with the right arm elevated >60° for 9.0% of the time during CT, compared to 3.7% during AT, resulting in a contrast between tasks of 0.35.

Conclusions: Hairdressers may be at risk for developing musculoskeletal disorders in the neck and shoulders due to a considerable occurrence of highly elevated arms, especially during CT. On the other hand, we do not find reasons to classify hairdressing as a job with too little variation. Posture variability between days within hairdressers was in the same order of magnitude as that between hairdressers, suggesting that ‘typical’ workdays do not exist. The exposure contrast between CT and AT for variables describing elevated arm postures indicates that for these variables a simple task-based approach for estimating job exposure could be successful.