The following is just one of many papers that condemns the use of dichotomization of continuous variables. Nothing good can come from it, as it loses large amounts of information in the best case, to ability to manipulate results at worst.
Dichotomization leads us to overlook the true nature of the relationship between X and Y. According to [6] , “simply dichotomizing continuous variables without previously referring to the original distributions by plotting them and checking consequences of dichotomization is a bad idea and should be discouraged” (p. 3). These two examples show how dichotomization can lead scholars to wrong inferences.
The Data Methods thread on Categoizing Continuous Variables is also worth study.