Laloux Pierre, Gisle Lydia, D'hoore William, Charafeddine Rana, Van der Heyden Johan
Institute of Health and Society (IRSS), Université catholique de Louvain, Clos Chapelle-aux-champs 30, Brussels, 1200, Belgium.
Department of Epidemiology and Public Health, Rue Juliette Wytsman 14, Sciensano, Brussels, 1050, Belgium.
BMC Public Health. 2024 Dec 18;24(1):3465. doi: 10.1186/s12889-024-21028-0.
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.
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.
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.
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.
多重疾病是一个日益受到关注的公共卫生问题。用于处理这些复杂健康状况的指标往往只专注于身体疾病。由于精神健康障碍疾病负担较重,也应予以考虑。本文旨在衡量在基于人群的多重疾病指标中纳入精神健康维度的附加价值,并确定哪些精神健康测量方法最为合适。
对2018年比利时健康访谈调查的数据进行二次分析。我们比较了不同多重疾病指标(MI)与健康影响测量指标(如生活质量(EQ-5D评分)和活动受限(GALI))的患病率。这些MI在涉及的健康状况方面存在差异:一个仅基于身体状况;另外三个包括通过自我报告或量表(广泛性焦虑障碍量表-7(GAD-7)、患者健康问卷-9(PHQ-9)和一般健康问卷-12(GHQ-12))评估的精神健康维度。我们进行了线性和逻辑回归,以评估MI与健康相关因素之间的关联,并比较不同模型的拟合优度。
与仅考虑身体状况(35.0%)相比,当纳入通过GHQ-12评估的精神健康维度(42.0%)以及通过GAD-7或PHQ-9评估的精神健康维度(39.4%)时,MI患病率更高。如果MI包含精神健康维度,MI与健康相关因素之间的关联始终更强。包含GAD-7和PHQ-9的MI回归模型显示MI与健康相关因素之间的关联最强,并且拟合优度测量指标也最佳。
仅考虑身体状况的MI低估了它们对个人生活的影响。在MI中纳入精神健康不佳是将其与健康相关因素联系起来的关键。