Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study

Abstract

BackgroundThis study sought to identify multimorbidity patterns and determine the association between these latent classes with several outcomes, including health, functioning, disability, quality of life and use of services, at baseline and after 3 years of follow-up.MethodsWe analyzed data from a representative Spanish cohort of 3541 non-institutionalized people aged 50 years old and over. Measures were taken at baseline and after 3 years of follow-up. Latent Class Analysis (LCA) was conducted using eleven common chronic conditions. Generalized linear models were conducted to determine the adjusted association of multimorbidity latent classes with several outcomes.Results63.8% of participants were assigned to the “healthy” class, with minimum disease, 30% were classified under the “metabolic/stroke” class and 6% were assigned to the “cardiorespiratory/mental/arthritis” class. Significant cross-sectional associations were found between membership of both multimorbidity classes and poorer memory, quality of life, greater burden and more use of services. After 3 years of follow-up, the “metabolic/stroke” class was a significant predictor of lower levels of verbal fluency while the two multimorbidity classes predicted poor quality of life, problems in independent living, higher risk of hospitalization and greater use of health services.ConclusionsCommon chronic conditions in older people cluster together in broad categories. These broad clusters are qualitatively distinct and are important predictors of several health and functioning outcomes. Future studies are needed to understand underlying mechanisms and common risk factors for patterns of multimorbidity and to propose more effective treatments.Electronic supplementary materialThe online version of this article (doi:10.1186/s12877-017-0586-1) contains supplementary material, which is available to authorized users.

Identifying obesity‐related multimorbidity combinations in the United States

“…Guisando‐Clavero et al use cluster analysis to identify six patterns of comorbidities in a study of 190 108 patients with multimorbidities. Several other researchers perform either cluster analysis or Latent Class Analysis (LCA, or exploratory factor analysis [EFA]) to identify patterns of multimorbidity . EFA and LCA are dimensionality reduction methods that collapse combinations of observed variables into unobserved factors.…”

“…Class Analysis (LCA, or exploratory factor analysis [EFA]) to identify patterns of multimorbidity. [21][22][23][24][25] EFA and LCA are dimensionality reduction methods that collapse combinations of observed variables into unobserved factors. These factors can then be used to represent subgroups.…”

<p>Patterns of Multimorbidity and Differences in Healthcare Utilization and Complexity Among Acutely Hospitalized Medical Patients (≥65 Years) – A Latent Class Approach</p>

“…A handful of studies have investigated multimorbidity patterns and their relationship with healthcare outcomes. [21][22][23][24] Olaya et al (2017) found two multimorbid patternsthe cardiovascular/mental/arthritis and the metabolic/strokethat were significantly associated with more use of health services. 21 Another study found four multimorbid patterns: Heart impairment, Metabolic-ischemic, Cardio-respiratory, and Cancer were associated with hospitalization.…”

Condiciones sociodemográficas y perfil de salud de los adultos mayores indígenas del departamento de Nariño

“…En este sentido, Nariño ocupa el segundo lugar en cuanto a víctimas de conflicto armado en Colombia(27). En relación con el desempeño funcional de los adultos mayores indígenas, se pudo evidenciar que la gran mayoría son funcionales en las actividades básicas e instrumentales de la vida diaria, lo anterior posiblemente alude a la particularidad de su contexto, en el que se hacen prácticas de trabajo comunitario y siempre existirá la actividad física que, de alguna manera, refuerza su potencial o capacidad de desempeño para la autonomía y la independencia(28).De manera similar, a partir los hallazgos del perfil de salud derivado del acl, se pudieron establecer tres grandes grupos. En primer lugar, las clases 1 y 3, compuestas por individuos con una alta presencia de comorbilidad, riesgo de desnutrición, deterioro cognitivo y sintomatología depresiva.…”

“…Por otro lado, en menos del 5 % de los adultos mayores que pertenecen a la clase 3 se presentó baja comorbilidad y mayor presencia de riesgo de desnutrición. La clase 2 muestra un perfil de salud más favorable, aunque los individuos de esta clase presentan riesgos de desnutrición.Un estudio reciente realizado en adultos mayores de población general no indígena muestra hallazgos similares, aunque menos desfavorables(28).En este estudio al que aludimos se encontraron tres clases. Dos terceras partes de los adultos mayores fueron clasificados en la clase "saludable", una tercera parte en la clase…”