Longitudinal trajectories of intrinsic capacity and their association with quality of life and disability.

OBJECTIVES: Intrinsic capacity (IC) is a key concept within the World Health Organization's (WHO) healthy aging model. The systematic assessment of IC could provide a better understanding of the functional trajectories of individuals. Our aims were to identify the longitudinal trajectories of IC and estimate their association with quality of life and disability. STUDY DESIGN: The study data comes from the three waves of the WHO Study on global AGEing and adult health (SAGE) in Mexico (2009, 2014, 2017). In total, 2735 adults aged 50 years or more were included. An IC score was constructed using item response theory. We used growth mixture modeling (GMM) to investigate the longitudinal trajectories of IC. Three-level linear mixed effect models were used to estimate the associations of IC with quality of life and disability. MAIN OUTCOME MEASURES: Disability was measured using the WHO Disability Assessment Schedule (WHODAS 2.0) and quality of life using the WHOQOL (WHO Quality of Life) instrument. RESULTS: Three classes were identified: low baseline IC with a steeply decreasing trajectory, medium baseline IC with a slightly decreasing trajectory, and high baseline IC with a moderately increasing trajectory. The class with the better trajectory (higher baseline IC score and a moderately increasing pattern) exhibited higher quality-of-life scores and lower disability scores. CONCLUSIONS: The findings show that older Mexican adults exhibit different IC trajectories, and that these may be associated with quality of life and disability. Results highlight the need for health policies and strategies to maintain intrinsic capacity and to promote primary prevention.

Extracting Spurious Latent Classes in Growth Mixture Modeling With Nonnormal Errors.

Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This can lead to the overextraction of latent classes and the attribution of substantive meaning to these spurious classes. The goals of this study are (1) to explore the performance of the Bayesian information criterion, sample-adjusted BIC, and bootstrap likelihood ratio test in growth mixture modeling analysis with nonnormal distributed outcome variables and (2) to examine the effects of nonnormal time invariant covariates in the estimation of the number of latent classes when outcome variables are normally distributed. For both of these goals, we will include nonnormal conditions not considered previously in the literature. Two simulation studies were conducted. Results show that spurious classes may be selected and optimal solutions obtained in the data analysis when the population departs from normality even when the nonnormality is only present in time invariant covariates.

Parental and individual predictors of trajectories of depressive symptoms in Chilean adolescents.

Depressive symptoms are prevalent in adolescence, but not all adolescents experience the same level or evolution of symptoms, suggesting the need to identify differences in trajectories of symptoms. We used Growth Mixture Modeling to analyze different trajectories of depressive symptoms in a sample of 1,072 Chilean adolescents (12-15 years old, 54% female). First, a baseline model was selected and then adolescent irritability, maternal warmth, demandingness and disrespect were introduced to the model as predictors of class membership. Four latent class trajectories of depressive symptoms were identified: high persistent (12%), low stable (56%), high decreasing (15%) and low increasing (17%). Low stable was the most prevalent class, and was characterized by higher maternal warmth and lower maternal disrespect and adolescent irritability while high persistent was characterized by the opposite maternal characteristics. Significant gender differences in class membership were observed. The results highlight the importance of identifying different trajectories of depressive symptoms and specific predictors of each trajectory. The association of parenting dimensions with trajectories of persistent depressive symptoms provides evidence that parenting can serve as both a protective and risk factor for adolescent adjustment.

La sintomatología depresiva es prevalente durante la adolescencia, pero no todos los adolescentes experimentan el mismo nivel y evolución de esta sintomatología, lo que sugiere la necesidad de identificar diferencias en las trayectorias de los síntomas. Usando Growth Mixture Modeling analizamos diferentes trayectorias de síntomas depresivos en 1.072 adolescentes chilenos (12-15 años, 54% mujeres). Primero, se seleccionó un modelo basal y luego se utilizó la irritabilidad del adolescente, la calidez, demanda y falta de respeto de la madre como predictores de la pertenencia a las clases. Se seleccionó un modelo con 4 clases latentes de síntomas depresivos: alta persistente (12%), baja estable (56%), alta decreciente (15%) y baja creciente (17%). La clase baja estable fue la más prevalente y se caracterizó por alto nivel de calidez maternal y bajo nivel de falta de respeto materna e irritabilidad del adolescente, en tanto que la clase alta persistente presentó características opuestas (baja calidez y alta demanda materna e irritabilidad del adolescente). Se observaron diferencias en la prevalencia de clases por sexo. Estos resultados resaltan la importancia de identificar diferentes trayectorias de síntomas depresivos y sus predictores. La asociación entre las dimensiones parentales y las trayectorias de síntomas depresivos persistentes provee evidencia de que los comportamientos parentales pueden servir, tanto como factores protectores como de riesgo.