An article in the Guardian today reports an actimetry study that links patterns of activity during the day to disease: https://www.theguardian.com/society...ening-activity-could-reduce-bowel-cancer-risk I would be quite sceptical about the interpretation here since activity patterns may correlate with other things but I thought it was a simple example of how altimeters can provide patterns for activity, not just amounts.
Smoking, shift work and “other variables”. Perhaps I am missing something but considering the type of cancer, might diet not have had an influence? I do not understand how because they have found a correlation between two things they can suggest a causal link.
Published in BMC Medicine, 18th September 2024 Diurnal timing of physical activity and risk of colorectal cancer in the UK Biobank Michael J. Stein, Hansjörg Baurecht, Patricia Bohmann, Béatrice Fervers, Emma Fontvieille, Heinz Freisling, Christine M. Friedenreich, Julian Konzok, Laia Peruchet-Noray, Anja M. Sedlmeier, Michael F. Leitzmann & Andrea Weber 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. ........... Strengths and limitations The primary strength of our study lies in its novel exploration of diurnal activity timing in relation to colorectal cancer using fPCA. This method is free from pre-set assumptions about data structure, and it efficiently reduces data complexity and captures essential variation while maintaining the continuous nature of the data, rendering it ideal for understanding nuanced trends in time-series of raw accelerometry data. Capturing the entire range of acceleration signals provided us with a detailed perspective on overall activity timing. Another significant asset of our study is its large sample size, allowing us to perform a wide range of informative sub-analyses, confirming the robustness of our findings. A limitation is our focus on hourly acceleration averages without distinguishing activity types or intensities, potentially masking certain aspects affecting colorectal cancer risk, such as the benefits of short bursts of vigorous activity [55]. The accelerometry data lacked contextual details, limiting insights into how different environments in which activity occurred could influence the impact of physical activity on colorectal cancer. Additionally, we did not examine whether chronotype or sleep patterns modified the association between activity timing and colorectal cancer. Case numbers were relatively low, especially in subgroup analyses, potentially masking true effects. UK Biobank is susceptible to selection bias [56] and the accelerometer subpopulation studied may exhibit healthy volunteer bias given the relatively high levels of activity [57, 58]. Finally, translating the fPCA findings into public health messages is challenging given the complexity of these analytic approaches. However, our results support physical activity recommendations that “every move counts.”
They did include a lot of covariates, including diet: And they don't say they found a causal link, but suggest it's a possibility.
I don’t understand and never will how medicine thinks it can get away from the fact that physical activity is indicating some feeling healthier not ‘making themselves healthier’ … in the general ie isn’t it more likely the people who recovered excercise more than those who died because they weren’t dying rather than them being less likely to die because of their step aerobics. How can you separate those two options therefore?
This seems a classic 'correlation equals causation' misstep but I agree it's interesting that there is technology to reveal patterns of activity. Would showing a diurnal pattern of activity for PwME move anything forward in terms of ruling mechanisms in or out, or generating biomedical research hypotheses?
It might do. Even for sleep disturbance we have a consensus that it is part of ME/CFS but do we have any data on how altered sleep patterns differ from other disorders?
I don't know that we have any data on sleep patterns for PwME at all. If studies like this would be useful, are there some billionaires we could be putting research proposals to? Or would the studies be cheap enough for our charities to fund, or for PwME to crowdfund for? We just raised $70,000 for David Tuller (worth every penny). Is this another project that could be made relatively easily possible by inviting a random selection of DecodeME participants to use wearables?
There have been sleep studies, but I can't recall seeing much comparing it directly with other disorders. There appear to be several distinct patterns anyway, and the same people may experience all of them. The most consistent factor seems to be feeling like death dug up on waking, specially for the first few hours. Almost as if sleep is an activity in ME/CFS, and we need a rest afterwards.
I have been waking consistently too early for some weeks at around 5am and have caught this 'like death' symptom coming on not long thereafter and continuing to build as I approach my normal wake-time. I wish I knew what this symptom was, and what it means. So weird to always go to bed feeling reasonably OK and to know I'll always wake up feeling awful. Is it sleep that's hurting us? Or immobility? That symptom does shift somewhat once I'm able to get up and move around, but it feels so awful that it stops me moving for a long time.
It's hard to know whether something is happening that shouldn't, or something isn't happening that should.
My guess is it might be the opposite. The body is okay with using maximum energy at night for healing, and this leads to feeling like crud for some reason, but during the day, when you need to be alert for activities, the healing gets toned down and energy gets rerouted to activities of being awake. And it takes some time to change to the more alert mode. Kind of like a longer, milder form of the "adrenaline" feeling that can mask a crash. </wild speculation> Edit: Or maybe forget the "energy rerouting" part. Maybe just an adrenaline feeling from being awake masking what ME/CFS feels like at baseline.
My wife and I have tracked activity with a FitBit watch and Garmin watch since 2018. It counts arm movements in addition to steps which I find very helpful what with having severe ME. Also, both watches don't rely on meeting a minimum number of steps before starting to count like most pedometers do. We found that ME vs HC (N=1+1) is NOT a good marker for health comparison. Total values are pretty meaningless for comparison purposes. For myself it is perfect for recording patterns over time in an unbiased way. Step and stair counts track very well with status of health and that is how I found for certain that I have seasonal variations in my disease that happen like clockwork. The most surprising fact is that stair count is the best indicator of health in my case.
I think you’d have to look very carefully at how to reassure subjects that they will be safe giving over these patterns. And I think given the risk to some it would need to be an incredibly high level to actually get the properly full gamut to sign up Eg those who get strong sleep reversal, including PEM-induced just can’t risk the very very serious danger unless they can’t massively trust the person in charge (maybe Bateman but not certain others - because the whole sleep hygiene thing is so not understood gif girls dangerous it is. I think it’s affects are faster and more serious than get eg 3times faster deterioration, imagine being deprived of any rest by someone deluded ) Until studies start covering and acknowledging the massive safety issue - and how awful it then is if we end up in hospital, so it’s not even like another illness and getting harm but a feeling if a forever decline to hell potentially- we will be being coerced and silenced into only the ‘most normal’ subject can risk taking part, which then leads to misrepresentation of what the illness is we need to start being honest about the protections and risks we need and have been through and responding to safety measures being flagged (not the awful dismissal like Tyson - who doesn’t know what she’s talking about to the extent it will lead to bullying harm to some and harm by her misleading others into doing too much that they will never recover from and that’s outrageous she will never be held accountable or made to see how detrimental what she does /believes there is)