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Vous devriez être flexible et vous devriez être fort.
L'entraînement en force est un moyen très efficace d'améliorer votre flexibilité, et j'ai créé un graphique pour rendre cela compréhensible :

Ceci provient d'une méta-analyse des essais d'entraînement en force.
Ce qui rend cela si utile, c'est qu'il y a un biais de publication majeur pour les résultats de force (illustré).
Mais, comme les auteurs ne l'ont pas examiné, il n'y a pas de biais de publication pour les résultats de flexibilité.

Les études ont été incluses dans cette méta-analyse parce qu'elles avaient un résultat de flexibilité, mais elles ont été intégrées à la littérature parce qu'elles ont montré des résultats positifs en termes de force.
Cela pourrait indirectement biaiser les résultats de flexibilité en raison d'une sélection sur un résultat corrélé.
S'il y a un biais de publication évident pour le résultat principal et aucun pour un résultat secondaire, s'ils sont corrélés à, disons, 0,5, alors si la force de l'effet est gonflée de 0,10 (0,40), la flexibilité est gonflée de 0,05 (0,20)
Dans l'ensemble, la flexibilité pourrait donc être de 0,48 à 0,53—20 % de moins
Le problème plus important est de généraliser à partir de ces études.
Les études portaient toutes sur des adultes en bonne santé, et les modérateurs avaient tendance à être marginaux.
L'intensité de l'exercice était un modérateur (p = 0,02) et le sexe l'était à peine (p = 0,04). Rien d'autre n'avait d'importance, y compris l'âge, malgré une plage allant de 18,2 à 83,5 !
Dans l'ensemble, j'ai une impression très encourageante de cette étude car ses résultats semblent assez ouverts à la généralisation parmi les gens normaux.
Faites de la musculation et vous deviendrez probablement beaucoup plus flexible ! De plus, vous vivrez avec moins de douleur !

19 août 2025
I'm curious what proportion of issues like chronic lower back pain can be treated with strength training.
To answer this question, we need to know a few quantities. The first of those is: what's the effect of strength training on chronic lower back pain?
If we consult some meta-analytic data, we get to a pretty sizable effect that looks like it might have some publication bias, but it's not major.
To account for potential publication bias, let's assume the effect lies somewhere in the range of 0.85 to 0.15. We'll say the midpoint is still 0.50 and we'll just sample throughout. We'll also have to convert from an SMD to an odds ratio.
The conversion is approximately exp{d*\frac{\pi}{\sqrt{3}}}, which turns 0.50 into an OR of ~2.477. We would use an OR of 2.477 for the interpretation of odds of a good outcome, but for an adverse event, we would invert it, so 1/2.477 ~= 0.404. This conversion is approximate and assumes equal standard deviations and a logistic link, but I think those are reasonable enough.
Given a baseline risk P_0 of "still in clinically-significant pain" at follow-up, the treated risk is P_1 = \frac{OR_{pain}P_0}{1-P_0+OR_{pain}P_0}. We'll sample among a range of values for P_0, assuming that between 10 and 20% of chronic lower back pain cases resolve on their own.
So, what's the prevalence of chronic lower back pain? To figure this quantity out, I consulted a systematic review. The review estimated a chronic lower back pain prevalence of 4.2% for people aged 24-39 and 19.6% for those aged 20-59, so let's just simplify and say 10-20%, based on a systematic review I found.
I'm not sure how realistic this value is, because I assume some amount of people who achieve resolution are actively doing something, and this draws them apart from the estimand we see in trials. Moreover, if the baseline to talk about is people who do nothing, then maybe the trials aren't so great, since they tend to have active controls instead of passive ones, thus underselling the population benefits of exercise.
Now we have what we need and we can compute the "PIF", the "Potential Impact Fraction". This effect size is used to estimate the change in risk after a change in an exposure with a given size of effect. It's very similar to the PAF (Population Attributable Fraction) that you might've seen me use before. Be warned, the use of this for categorical things has been criticized. I'll link a study on that.
My seed for this is 12345. I'm taking 100,000 draws, and the other details will be in the picture. TL;DR: It looks like given these assumptions, you could eliminate about 20% of chronic lower back pain if people committed to strength training.
At a 5% prevalence, 0.85% or so of the population is no longer in significant pain due to exercise; at a 20% prevalence, 3.4% of the population is no longer in significant pain. That's huge!
Two final remarks.
First, if you want changes to the simulation, tell me. I'll gladly output runs with different parameters.
Second, I think this really undersells it. I've known so many people who fixed their backs with strength training, and I think the strength training and commitment to it in RCTs is not all that great. If people were on more effective exercise plans and gained more muscle, I think they'd probably do even better. Plus, I think there's even more room to get strong prevention going on here, if more people go into midlife with strong backs.
Thoughts? Questions? If you're wondering what the take-home message is, it's get out there and lift. That's always a good message.
Sources:
(see also:


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