Associations between occupational indicators and total, work-based and leisure-time sitting: a cross-sectional study

Prolonged sitting time is increasingly recognised as a distinct health risk behaviour associated with increased cardiovascular disease, diabetes, obesity and mortality independent from physical activity levels [1–4]. Therefore, even though adults may meet physical activity recommendations for good health, they may still sit for extended periods each day with detrimental effects on their physical and mental health [5, 6]. High levels of sitting time have been reported, with generally over 50% of waking time spent sitting in adults [7, 8]. Hence, there is a need to develop effective health behaviour change interventions to reduce sitting time. To succeed in this task the correlates that drive sitting behaviour need to be well understood [9].

A group of seldom studied sitting time correlates include occupational indicators, such as working full or part-time, working normal or shift-work hours, working in a white- or blue-collar job or having a low or highly physically demanding job [10]. It is important to examine whether occupational indicators influence different domains of sitting time and what effect they have on total sitting time, as working adults spend up to half of their workday sitting [11, 12], and additionally spend many hours of sitting in their leisure-time (e.g. TV viewing) [13, 14]. For example, employees with white-collar jobs and those that are desk-bound are more likely to have high occupational sitting [10, 11], and sit up to 75% of their working time [15, 16]. However, occupational sitting has been shown to vary according to different occupations, and no studies have simultaneously evaluated the influence of a wide range of different occupational indicators on different domains of sitting (total, occupational and leisure-time). Most studies have focused on a single occupational indicator and a single domain of sitting time; hence more research in this area is needed.

The relationship between occupational sitting and leisure-time sitting is also unclear. Some studies indicate that there is no relationship between the amount of time spent sitting at work and the amount of time spent sitting during leisure-time [11, 17], whereas others reported that sedentary workers are more likely to have high leisure-time sitting [18]. Similarly, some studies indicate no relationship between the level of physical demand at work and leisure-time sitting [17], whereas others find that high physically demanding jobs lead to more sitting during leisure-time [19, 20]. Accordingly, these latter studies argue that there are ‘compensation effects’ whereby little occupational sitting is compensated with more leisure-time sitting. The inconsistency of these findings suggest the need for further research.

Given that most adults in Western nations spend the most of their lives employed [21], it is important to clarify the influence and interactions that occupational indicators have on different domains of sitting time [10]. This information can then be utilised to direct the development of public health interventions [22]. Therefore, the aim of this study was to examine the associations between several occupational indicators and total, occupational and leisure-time sitting.

The occupational indicators with the strongest influence on both total and occupational sitting time were having a physically demanding job and having a blue-collar job, although neither had a significant impact on leisure-time sitting. With the exception of having a part-time job (lower total sitting) and working more than eight hours a day (lower leisure-time sitting), no significant differences were observed for any of the other occupational indicators. Overall, the differences in sitting time between the occupational indicators were smaller than one might expect based on stereotypical notions of differences between occupations [30]. In fact, total sitting time was high across all occupational indicators, as was leisure-time sitting. Compared to this study, several studies report lower minutes of total sitting time a day [11, 31, 32], although Chau et al. [18], who used the same sitting time measure, reported higher total sitting a day. It is difficult to explain these differences, although the use of different measures and study populations (the sample of Chau et al. [18] was characterised by lower proportions of women, educated participants, full-time and white-collar workers compared to the sample in this study) is likely to have contributed. The total time spent sitting was predominantly made up of time spent in leisure-time sitting (approximately 60%), irrespective of occupational indicators. Few studies have reported on both occupational and leisure-time sitting: a study by Jans et al. reported similar outcomes to our study [11], whereas Chau et al., who’s study predominantly included office workers, reported more occupational than leisure-time sitting [18].

The outcomes for total and occupational sitting time in relation to physically demanding and blue-collar jobs are as one would expect and in line with previous research. In a study by Mummery et al. white-collar employees sat significantly more than blue-collar employees [12]. Similar outcomes regarding blue/withe collar workers were reported in other studies [11, 32], and a study by Van Dyck et al. was able to demonstrate the same observation using objective measures (accelerometry) [31]. In relation to physical demand Tigbe et al. demonstrated, in line with the present study, that those in a physically demanding job had lower total and occupational sitting time [17]. There is, however, limited evidence in relation to sitting time and physical demand and therefore a review by Rhodes et al. indicated that sustained research is needed before conclusions can be drawn in this area [28]. The same applies in relation to shift-work, where no studies were found to compare the unexpected outcomes of this study: there were no significant differences in total and occupational sitting time between shift-workers and non shift-workers. A closer look at job-types undertaken by shift- and non shift-workers (not reported) in this study might explain this outcome, as both groups engaged to a large extent in occupations that could be typified by low (e.g. shift-worker: health services; non shift-worker: construction) and high (e.g. shift-worker: transport; non shift-worker: education) sitting time.

The average differences in leisure-time sitting were minimal across occupational indicators; as such, on a group level, this study did not find evidence for ‘compensation effects’: those with blue-collar, shift-work or physically demanding jobs did not sit significantly more in their leisure-time and vice-versa. This is in line with some studies [11, 17], but in contrast with studies that indicate that people with blue-collar [33], shift-work [19], and physically demanding jobs [20] sit more in their leisure-time. However, one significant difference was observed for leisure-time sitting: those working more than eight hours per day sat less in their leisure-time. This is not unexpected, as it is likely due to having less leisure-time when performing longer working hours which results in having less opportunity to sit, and this finding is in line with several other studies that report lower leisure-time sitting when working more hours [14, 32]. This study illustrates that there is a need to reduce leisure-time sitting irrespective of occupational background, given the high sitting time reported across categories. In this context, the promotion of a positive balance between time spend in light intensity physical activity and sitting time (i.e. spending more time in light intensity physical activity than time spent sitting) is recommended [8, 34], as several studies have demonstrated poorer health when the balance between sitting time and light intensity physical activity is negative [35].

Consistent with the current study, previous studies have indicated that those working full-time have higher total sitting when compared to those working part-time [32]. Interestingly, other studies have reported that those who are unemployed sit more than those who have a job [27, 31, 36]. As such, there seems to be a U-shaped relationship with high sitting in those who work either very little or very much and lower sitting in those who work moderate amounts of time. However, further investigation is needed to determine whether this relationship only applies for those with white-collar employment, but perhaps not for those with blue-collar and/or physically demanding jobs, as the current study seems to suggest. In any case the current study illustrates, in line with previous research [10, 11, 15], that workplace initiatives to reduce occupational sitting are especially needed for those in white-collar or sedentary occupations, but to a lesser extent for those with blue-collar or physically demanding jobs. Reducing sitting time at work will require innovative approaches that don’t adversely impact on worker productivity.

The main limitation in this study is the use of a cross-sectional design that does not allow inferences about causality; longitudinal data is needed to further study this area of interest. Secondly, all data was obtained through self-report questionnaires. However, the instrument used to measure sitting time has shown good reliability and validity [23], and the total sitting time reported in other studies using this measure was similar to what is reported in this study. Furthermore, the data was obtained through well-trained CATI interviewers, which has shown to produce reliable data [37]. The response rate of 51.9% is acceptable for this type of survey although the potential for non-response bias is acknowledged. Response rates in CATI surveys are declining due to aggressive tele-marketing and increased efforts of people to protect their privacy [38, 39]. A strength of the study was the sampling design applied to randomly select a population to participate in this study, however as this study was part of the Healthy Shift Workers Study data were only collected in cities known to have high proportions of shift workers, as such the sample obtained in this study may not be representative for the wider Australian population. Nevertheless, the greater variability in working conditions obtained in the study sample should be considered as a strength. To our knowledge this study is also the first that evaluated a broad range of occupational indicators simultaneously in terms of how they influence different domains of sitting time. Most studies focus on a single occupational indicator and a single domain of sitting, making it more difficult to get an overview and see patterns.

In conclusion, this study adds some important findings. Firstly, total and leisure-time sitting were high irrespective of occupational indicators, and behaviour change interventions are needed to reduce sitting time and prevent chronic disease. Secondly, white-collar and low physically demanding jobs were significantly associated with high occupational sitting time, and need targeting by workplace initiatives to reduce sitting time. Thirdly, no evidence for ‘compensation’ effects was found; where lower sitting at work is compensated with higher sitting in leisure. Fourth, working full-time is associated with higher total sitting; although working long hours is associated with lower leisure-time sitting. While causal relations can not be inferred from this cross-sectional study, the outcomes suggest it may be beneficial to limit total working hours and avoid working over-time as a way to reduce total sitting. Further, it is recommended to couple this with efforts to increase light intensity physical activity during leisure-time to generate a positive balance with sitting time. Future research should consider the use of experimental and time-series designs to assess whether changes in the different domains of sitting time can be brought about using workplace interventions.