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. 2022 Apr 30;10:100119. doi: 10.1016/j.xnsj.2022.100119

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© 2022 The Author(s)

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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Fig 3 — Multivariable logistic regression analysis to evaluate the potential association between the injury mechanism (bicyclists versus non-bicyclists) and the risk of either OC-Fx (A) or OFx (B). The forest plots (the upper part of figures) visualize the coefficients obtained from the Bayesian multivariable logistic regression models. The marginal effect plots (lower part of the figures) of increasing age on the probability of fracture stratified via the HISS demonstrate the different effects of age and HISS score on fracture probability for OC-Fx and OFx. Bicyclists had a significantly increased risk of OC-Fx compared to non-bicyclists, while older age was the main factor associated with an increased risk of OFx.

Fig 3 — Multivariable logistic regression analysis to evaluate the potential association between the injury mechanism (bicyclists versus non-bicyclists) and the risk of either OC-Fx (A) or OFx (B). The forest plots (the upper part of figures) visualize the coefficients obtained from the Bayesian multivariable logistic regression models. The marginal effect plots (lower part of the figures) of increasing age on the probability of fracture stratified via the HISS demonstrate the different effects of age and HISS score on fracture probability for OC-Fx and OFx. Bicyclists had a significantly increased risk of OC-Fx compared to non-bicyclists, while older age was the main factor associated with an increased risk of OFx.