Science topic

Physical Activity Epidemiology - Science topic

Physical activity epidemiology is a topic area concerned with understanding the public health benefits of physical activity.
Questions related to Physical Activity Epidemiology
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Prolonged sitting has been increasingly recognized as a serious issue in public health. However, the cut-off point above which health is impaired in general population is still equivocal. Are there any quantitative guidelines on sitting? Especially it provides suggestions about a cut-off or threshold of daily sedentary time for adults or older people?
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The latest evidence suggests that all adults (including 65+) should engage in less sedentary behaviors (< 9 h a day). These are derived from different studies based on accelerometer-measured sedentary time conducted by different research teams and using different analytical methods.
2. J. Clin. Med. 2019, 8(4), 564;
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Disabled people are considered under WHO recommandations for daily physical activity, but standard measures used for healthy people could them really be used at the same for disabled ?
In other way, for example, for a femoral amputee, walking at 4m/s speed is it under 3 MET (very low level activity) or over (low activity)?
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Emmanuelle Cugy Firstly, physical activity guidelines expressed using Metabolic Equivalent Tasks (METs) are not useful for the general public. The concept of METs is difficult to understand and few people are familiar with it. It is really challenging for the public to know the MET values for any/all the activities they do.
Secondly, The energy consumption in people with limb amputation would be certainly much higher for amputees. To my knowledge METs values and disability have not been worked on very much. See systematic review
Metabolic costs of activities of daily living in persons with a lower limb amputation: A systematic review and meta-analysis. https://www.ncbi.nlm.nih.gov/pubmed/30893346
Thirdly, there has been some work on METs and paraplegia which may help guide you.
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I have run an analysis with melogit in STATA, but I´m having troubles interpretating the output.
The multilevel multivariate logistic regression gives me the following output:
region OR STD ER 95% CI
var(_cons)| .012162 .0134205 .0013987 .1057516
LR test vs. logistic regression: chibar2(01) = 1.52 Prob>=chibar2 = 0.1087
Thanks!
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According to the results above, there is very little impact from random effects, and they should likely be dropped. Given that you have properly identified the covariance matrix, you should not need this random coefficient and can use fixed effects/standard log.reg. As mentioned above, make sure to try each possible cov(), f.ex. unstructured, identity, etc, and run estat ic after each: pick the one with the lower BIC. This is the _first_ step, before doing an LR test. If the _properly identified_ covariance matrix of a random effect is no better than fixed, according to LR test, I think that is quite strong justification for not including them. I guess, if a reviewer really wants you to adjust for invididual difference according to some group by random coffiecient, because it is established that you should do it (it probably isn't), you could include it as a "theoretical confounder". If you need more details, I will need more details on the problem, the covariates, the justification for the random effect, etc. Best of luck!
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Ideally looking for a 7-day recall or usual self-report.  
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Dear Patrick,
However, as far as I am aware, validity of the previously mentioned questionnaires (GPAQ, IPAQ) has only been demonstrated for physical activity and not (extensively) for sedentary behaviour. For example, the IPAQ has only two questions addressing sitting time (none for overall sedentary behaviour), with one item asking for time spent sitting during the last seven days on a weekday and another asking for sitting time on a weekend day (each in hours and minutes). From my point of view, data from those questions are, at best, questionable.
Hence, I strongly agree with Dieter on the objective measurement of sedentary behaviour to take the risk of recall bias (and social desirability to a certain degree) out of the assessment. The papers attached might be of help in your decision which method may yield the appropriate data to answer your research question.
Bests,
Carsten
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Do you know what type of intervention is best to promote physical activity in different population? Does anyone use a particular theory?
Thanks!!
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Although this one is little dated now, it was systematic review that was done in 2002. I have found it very useful for determining which PA actually work.
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They suggest that journals formally define sedentary behaviour as "any waking behaviour characterized by an energy expenditure ≤1.5 METs while in a sitting or reclining posture.". They also suggest that journals should use the term "inactive" to describe those who are performing insufficient amounts of moderate to vigorous intensity physical activity (i.e., not meeting specified physical activity guidelines).
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This definition of sedentary behaviour has been widely accepted. Such standardization of terms should be encouraged, as it is essential for cross-study comparability.
Cheers,
Zeljko
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If I have a RCT where I have a control group (receiving funny data messages) and an intervention group (diet, physical activity tips reinforced with self-efficacy) with the aim of improving glycemic control.
I measured physical activity (PA) with an accelerometer. And I want to know the pros and cons of using my PA data as continuous and as a categorical variable.
Thank you for your help and time.
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Hi Alejandra,
In general, if you have a continuous variable (such as PA measured by accelerometry), it is much better to use it as it is, continuous. From a statistical point of view, categotizing continuous variables will lead to lost of information.However, depending on what you need to study, sometimes it is practical/necessary to categorize.
In your case, as I understand, you want to examine the relationship between receiving self-efficacy messages (or not) and glycemic control, after controling for diet and PA. I would then use physical activity as a continuous variable. You could use total PA, MVPA, or whatever literature suggests.
You can review this article for further information:
Altman DG, Royston P. The cost of dichotomising continuous variables. British Medical Journal. 2006;332:1080.
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There are well documented examples in medicine such as the use of steroids in premature deliveries, prescription of streptokinase and more recently statins and tamiflu have had significant shifts in perceived benefits due to systematic reviews. The use of pre-exercise static stretching comes to mind, although this is also an example of how long applied practice can take to change. Any other areas would be more than welcome.
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Not sure if this relates to what you are looking for. Several systematic review articles published in British J of Sports Med (2011; vol45) reported evidence about school-, home-, and/or community-based interventions as well as their effect on youth physical activity promotion.