Suchergebnisse

AbstractThis study examines the co-development of cognitive and physical function in older Americans using an age-heterogeneous sample drawn from the Health and Retirement Study (1998–2008). We used multiple-group parallel process latent growth models to estimate the association between trajectories of cognitive function as measured by immediate word recall scores, and limitations in physical function as measured as an index of functional mobility limitations. Nested model fit testing was used to assess model fit for the separate trajectories followed by estimation of an unconditional parallel process model. Controls for demographic characteristics, socioeconomic status, and chronic health conditions were added to the best-fitting parallel process model. Pattern mixture models were used to assess the sensitivity of the parameter estimates to the effect of selective attrition. Results indicated that favorable cognitive health and mobility at initial measurement were associated with faster decline in the alternate functional domain. The cross-process associations remained significant when we adjusted estimates for the influence of covariates and selective attrition. Demographic and socioeconomic characteristics were consistently associated with initial cognitive and physical health but had few relations with change in these measures.

Abstract

Background
The rapidly growing field of multimorbidity research demonstrates that changes in multimorbidity in mid- and late-life have far reaching effects on important person-centered outcomes, such as health-related quality of life. However, there are few organizing frameworks and comparatively little work weighing the merits and limitations of various quantitative methods applied to the longitudinal study of multimorbidity.


Methods
We identify and discuss methods aligned to specific research objectives with the goals of (i) establishing a common language for assessing longitudinal changes in multimorbidity, (ii) illuminating gaps in our knowledge regarding multimorbidity progression and critical periods of change, and (iii) informing research to identify groups that experience different rates and divergent etiological pathways of disease progression linked to deterioration in important health-related outcomes.


Results
We review practical issues in the measurement of multimorbidity, longitudinal analysis of health-related data, operationalizing change over time, and discuss methods that align with 4 general typologies for research objectives in the longitudinal study of multimorbidity: (i) examine individual change in multimorbidity, (ii) identify subgroups that follow similar trajectories of multimorbidity progression, (iii) understand when, how, and why individuals or groups shift to more advanced stages of multimorbidity, and (iv) examine the coprogression of multimorbidity with key health domains.


Conclusions
This work encourages a systematic approach to the quantitative study of change in multimorbidity and provides a valuable resource for researchers working to measure and minimize the deleterious effects of multimorbidity on aging populations.