PainSci summary of Gupta 2015?This page is one of thousands in the PainScience.com bibliography. It is not a general article: it is focused on a single scientific paper, and it may provide only just enough context for the summary to make sense. Links to other papers and more general information are provided at the bottom of the page, as often as possible. ★★★★☆4-star ratings are for bigger/better studies and reviews published in more prestigious journals, with only quibbles. Ratings are a highly subjective opinion, and subject to revision at any time. If you think this paper has been incorrectly rated, please let me know.
This appears to be the first-ever study of the relationship between back pain severity and objectively measured total sitting time — not just sitting at work, and measured by accelerometers instead of self-report. On its face, it is a good trial with results that contradict my modern bias against sitting being a cause of back pain (based on the evidence), but supports by original once-upon-a-time belief (based on “common sense”) that sitting was a risk factor for back pain.
There’s some heavy duty number crunching in this one, which makes it harder to evaluate. There’s plenty of room for flaws to hide in all that number crunching, but there’s nothing obviously wrong with it. Seems like good methodology to me, likely to produce more reliable results. Unfortunately, it also still appears to be the only study using objective measure of total sitting time, so it still really needs to be replicated — all the more so because it is reporting results that are at odds with many other studies.
Maybe it’s actually a (rare) case of new, improved methodology finally producing a clearer, better answer than previous research could. Or maybe it’s just more noise. That’s why we need some replication.
I think it’s weird that the risk of back pain from occupational-sitting time alone was not statistically significant. Not sure what to make of it, but it seems like confirmation that the signal is hard to separate from the noise. Every dataset has weird subsets, but why would that subset be anomalous like that? If sitting a lot increases the risk of back pain, then any large segment of sitting time should show about the same association, and pretty clearly.
Not saying it’s a deal-breaker, just a bit of a head-scratcher, and another reason replication is needed.
But overall it’s fairly compelling.
original abstract†Abstracts here may not perfectly match originals, for a variety of technical and practical reasons. Some abstacts are truncated for my purposes here, if they are particularly long-winded and unhelpful. I occasionally add clarifying notes. And I make some minor corrections.
BACKGROUND: Studies on the association between sitting time and low back pain (LBP) have found contrasting results. This may be due to the lack of objectively measured sitting time or because socioeconomic confounders were not considered in the analysis.
OBJECTIVES: To investigate the association between objectively measured sitting time (daily total, and occupational and leisure-time periods) and LBP among blue-collar workers.
METHODS: Two-hundred-and-one blue-collar workers wore two accelerometers (GT3X+ Actigraph) for up to four consecutive working days to obtain objective measures of sitting time, estimated via Acti4 software. Workers reported their LBP intensity the past month on a scale from 0 (no pain) to 9 (worst imaginable pain) and were categorized into either low (≤ 5) or high > 5) LBP intensity groups. In the multivariate-adjusted binary logistic regression analysis, total sitting time, and occupational and leisure-time sitting were both modeled as continuous (hours/day) and categorical variables (i.e. low, moderate and high sitting time).
RESULTS: The multivariate logistic regression analysis showed a significant positive association between total sitting time (per hour) and high LBP intensity (odds ratio; OR = 1.43, 95%CI = 1.15-1.77, P = 0.01). Similar results were obtained for leisure-time sitting (OR = 1.45, 95%CI = 1.10-1.91, P = 0.01), and a similar but non-significant trend was obtained for occupational sitting time (OR = 1.34, 95%CI 0.99-1.82, P = 0.06). In the analysis on categorized sitting time, high sitting time was positively associated with high LBP for total (OR = 3.31, 95%CI = 1.18-9.28, P = 0.03), leisure (OR = 5.31, 95%CI = 1.57-17.90, P = 0.01), and occupational (OR = 3.26, 95%CI = 0.89-11.98, P = 0.08) periods, referencing those with low sitting time.
CONCLUSION: Sitting time is positively associated with LBP intensity among blue-collar workers. Future studies using a prospective design with objective measures of sitting time are recommended.
- “Association between objectively measured sitting time and neck-shoulder pain among blue-collar workers,” David M Hallman, Nidhi Gupta, Svend Erik Mathiassen, and Andreas Holtermann, Int Arch Occup Environ Health, 2015.
This page is part of the PainScience BIBLIOGRAPHY, which contains plain language summaries of thousands of scientific papers & others sources. It’s like a highly specialized blog. A few highlights:
- Effectiveness of customised foot orthoses for Achilles tendinopathy: a randomised controlled trial. Munteanu 2015 Br J Sports Med.
- A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: the case of felt power. Gronau 2017 Comprehensive Results in Social Psychology.
- The neck and headaches. Bogduk 2014 Neurol Clin.
- Agreement of self-reported items and clinically assessed nerve root involvement (or sciatica) in a primary care setting. Konstantinou 2012 Eur Spine J.
- Effect of NSAIDs on Recovery From Acute Skeletal Muscle Injury: A Systematic Review and Meta-analysis. Morelli 2017 Am J Sports Med.