BACKGROUND: Multimorbidity is a rising public health concern. Indicators that address these complex health conditions are often exclusively devoted to physical diseases. Because of their high disease burden, mental health disorders ought to be considered as well. This paper aims to measure the added value of including a mental health dimension in a population-based multimorbidity indicator and identify which mental health measures are most appropriate.

METHODS: Secondary analyses were conducted on data from the Belgian Health Interview Survey 2018. We compared the prevalence of different multimorbidity indicators (MIs) in relation to health impact measures, such as quality of life (EQ-5D score) and activity limitation (GALI). The MIs differed as to the health conditions involved: one was based on physical conditions only; the other three included mental health dimensions that were either self-reported or assessed by a scale (GAD-7, PHQ-9, and GHQ-12). We performed linear and logistic regressions to assess the association between the MIs and the health correlates and compared the goodness of fit of the different models.

RESULTS: MI prevalence was higher when including a mental health dimension assessed with the GHQ-12 (42.0%) and with the GAD-7 or the PHQ-9 (39.4%) as compared to physical conditions only (35.0%). Associations between the MI and health correlates were consistently stronger if the MI included a mental health dimension. The regression models with MI including the GAD-7 and PHQ-9 showed the strongest association between MI and the health correlates and also had the best goodness-of-fit measures.

CONCLUSIONS: MIs that only take physical conditions into account underestimate their impact on individuals' lives. Including mental ill-health in an MI is key to linking it to health correlates.