Confounding bias is a validity problem and cannot be solved by hypothesis testing as p-values are precision measures. Adjustment for confounding factors needs to be based on assumptions regarding cause-effect relationships. For example, while including a confounder in the statistical model will reduce confounding bias, the inclusion of a mediator or collider will induce adjustment bias, see e.g. Shrier I, Platt RW. Reducing bias through directed acyclic graphs. BMC Med Res Methodol 2008;8:70. Please provide a rationale for the adjustment variables in terms of cause and effect.