Ranking the effect of chronodisruption-based biomarkers in reproductive health

Abstract

Chronodisruption alters circadian rhythms, which has negative consequences on different pathologies and mental disorders. This work studies whether factors related to chronodisruption of circadian rhythms motivated by shift works influence on reproductive health or not. In particular, this influence is studied on four particular aspects related to reproductive health: reproductive health disease, first pregnancy attempt, problems during pregnancy and gestation period. Some explainable machine learning models based on trees have been employed. These methods provided information about the importance of each predictor. The most important variables provided by each method were aggregated using a ranking aggregation function in order to reach a consensus ranking of variables that made possible to understand whether the chronodisruption factors had an effect on each of the aspects studied. The data have been obtained from 697 health professionals. Information about classical biomarkers, sleep quality indices and also other new variables related to eating jet lag, sleep hygiene and how the sleep is affected by shift works were considered as input data. Experiments have shown how some of these novel biomarkers are ranked in the top positions of the issues studied in relation to reproductive health. In particular, the light level and the use of electronic devices, which are features related to chronodisruption, are highlighted as biomarkers.