In the present research, models based on multivariate adaptive regression splines (MARS) are proposed to study the influence of gender in the factors affecting the development of shoulders, neck and upper limb MSD. Two different MARS models, corresponding to men and women, are constructed to identify variables with the strongest effect on the target MSD. Both models are capable to predict successfully the occurrence of the studied disorders. Men seem to be more vulnerable to physical risk factors and some other working conditions, whereas women appear to be more affected by psychosocial risk factors and activities carried out outside their working hours. According to the results, gender needs to be considered to ensure the success and effectiveness of ergonomic interventions on the whole working population.

中文翻译：

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通过多元自适应回归样条（MARS）识别影响肩膀，颈部和上肢MSD的因素中的性别差异。

在本研究中，提出了基于多元自适应回归样条（MARS）的模型，以研究性别对影响肩膀，颈部和上肢MSD发育的因素的影响。构建了两种不同的MARS模型，分别对应于男性和女性，以识别对目标MSD影响最大的变量。两种模型都能够成功预测所研究疾病的发生。男性似乎更容易受到身体风险因素和其他一些工作条件的影响，而女性似乎更受心理社会风险因素和在工作时间以外进行的活动的影响。根据结果​​，需要考虑性别，以确保对整个劳动人口的人体工程学干预措施的成功和有效性。