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. 2024 Sep 18;22(1):399.
doi: 10.1186/s12916-024-03632-4.

Diurnal timing of physical activity and risk of colorectal cancer in the UK Biobank

Affiliations

Diurnal timing of physical activity and risk of colorectal cancer in the UK Biobank

Michael J Stein et al. BMC Med. .

Abstract

Background: Physical activity reduces colorectal cancer risk, yet the diurnal timing of physical activity in colorectal cancer etiology remains unclear.

Methods: This study used 24-h accelerometry time series from UK Biobank participants aged 42 to 79 years to derive circadian physical activity patterns using functional principal component analysis. Multivariable Cox proportional hazard models were used to examine associations with colorectal cancer risk.

Results: Among 86,252 participants (56% women), 529 colorectal cancer cases occurred during a median 5.3-year follow-up. We identified four physical activity patterns that explained almost 100% of the data variability during the day. A pattern of continuous day-long activity was inversely associated with colorectal cancer risk (hazard ratio (HR) = 0.94, 95% confidence interval (CI) = 0.89-0.99). A second pattern of late-day activity was suggestively inversely related to risk (HR = 0.93, 95% CI = 0.85-1.02). A third pattern of early- plus late-day activity was associated with decreased risk (HR = 0.89, 95% CI = 0.80-0.99). A fourth pattern of mid-day plus night-time activity showed no relation (HR = 1.02, 95% CI = 0.88-1.19). Our results were consistent across various sensitivity analyses, including the restriction to never smokers, the exclusion of the first 2 years of follow-up, and the adjustment for shift work.

Conclusions: A pattern of early- plus late-day activity is related to reduced colorectal cancer risk, beyond the benefits of overall activity. Further research is needed to confirm the role of activity timing in colorectal cancer prevention.

Keywords: Colorectal cancer; Physical activity patterns; Raw accelerometry; UK Biobank.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
A Four distinct previously derived physical activity patterns from functional principal component analysis. B Average hourly physical activity (PA) for positive scores (dashed line; > 1 standard deviation above the mean score), negative scores (dotted line; < 1 standard deviation below the mean score), and population average (solid gray line), for each functional principal component

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