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Associational mediation analysis has generally relied on the linearity of models to estimate the indirect effect as a product of regression coefficients. Very few examples of generalisations to nonlinear settings have been proposed, including a derivative-based method that, however, is far from being widely spread among scholars. In this paper, we clarify some aspects of such an approach to nonlinear mediation models, which have not been addressed by the previous literature. In addition, we run a simulation study to compare confidence intervals for the indirect effect obtained through different approaches.

This paper investigates the effect of socio-economic status on interregional mobility and mortality among cancer patients. The cohort under analysis comprises patients residing in Sicily (Italy), who were diagnosed with lung and colon cancer between 2010 and 2011. The data was collated from the hospital discharge records of the Sicilian Region and the Regional register of the causes of death, by considering all those patients for whom information relating to socio-economic status was available. First, graphical models were applied to highlight the multivariate structure of association among socio-economic status, interregional mobility and 3-year mortality. Secondly, mediation analysis quantified the direct and indirect effect of socio-economic status relating to mortality. The results revealed that socio-economic status is associated directly and indirectly with mortality due to lung cancer, mediated by interregional mobility. On the other hand, the association of socio-economic status with mortality from colon cancer is only indirect, and also mediated by interregional mobility. The authors of this research hold that the extent of patient mobility and its relation to mortality call for a reconsideration of health policy.

Ocean warming is a worldwide phenomenon. The mean temperature of the catch (MTC) is becoming one of the leading indicators to assess the impact of sea surface temperature on fish communities. In this study, we apply a semiparametric regression approach to the MTC of the catches from MEDITS bottom trawl program in the Strait of Sicily (Central Mediterranean Sea) for the period 1995 to 2018 to evaluate the effects of climate change on continental shelf fish community. All covariates included in the model have a significant impact on the MTC level. Notably, the sea surface temperature (SST) effect on the MTC depends on depth, being positive near the surface and negative at the bottom.