Determinants of Health Trajectories in England and the United States: An Approach to Identify Different Patterns of Healthy Aging.

TitleDeterminants of Health Trajectories in England and the United States: An Approach to Identify Different Patterns of Healthy Aging.
Publication TypeJournal Article
Year of Publication2018
Authorsde la Fuente, J, Caballero, FFélix, Sánchez-Niubó, A, Panagiotakos, DB, A Prina, M, Arndt, H, Haro, JMaria, Chatterji, S, Ayuso-Mateos, JLuis
JournalJ Gerontol A Biol Sci Med Sci
Date Published2018 10 08
ISSN Number1758-535X
KeywordsAged, Aged, 80 and over, Chronic disease, Educational Status, England, Female, Health Surveys, healthy aging, Humans, Income, Kaplan-Meier Estimate, Longitudinal Studies, Male, Middle Aged, Models, Statistical, Mortality, United States

Background: Aging is a multidimensional process with a remarkable interindividual variability. This study is focused on identifying groups of population with similar aging patterns, and to define the health trajectories of these groups. Sociodemographic and health determinants of these trajectories are also identified.

Methods: Data from the English Longitudinal Study of Aging (ELSA) and the Health and Retirement Study (HRS) were used. A set of self-reported health items and measured tests were used to generate a latent health metric by means of a Bayesian multilevel IRT model, assessing the ability of the metric to predict mortality. Then, a Growth Mixture Model (GMM) was conducted in each study to identify latent classes and assess health trajectories. Kaplan-Meier survival curves were obtained for each class and a multinomial logistic regression was used to identify determinants of these trajectories.

Results: The health score generated showed an adequate ability to predict mortality over 10 years in ELSA (AUC = 0.74; 95% CI: 0.72, 0.75) and HRS (AUC = 0.74; 95% CI: 0.73, 0.75). By means of GMM, four latent classes were identified in ELSA and five in HRS. Chronic conditions, no qualification and low level of household wealth were associated to the classes which showed a higher mortality in both studies.

Conclusion: The method based on the creation of a common metric of health and the use of GMM to identify similar patterns of aging, allows for the comparison of trajectories of health across longitudinal surveys. Multimorbidity, educational level, and household wealth could be considered as determinants associated to these trajectories.

User Guide Notes

Alternate JournalJ. Gerontol. A Biol. Sci. Med. Sci.
Citation Key9475
PubMed ID29346518
PubMed Central IDPMC6175023
Grant List001 / / World Health Organization / International
U01 AG009740 / AG / NIA NIH HHS / United States