Literature DB >> 25953813

Long-Term BMI Trajectories and Health in Older Adults: Hierarchical Clustering of Functional Curves.

Anna Zajacova1, Snehalata Huzurbazar2, Mark Greenwood3, Huong Nguyen4.   

Abstract

OBJECTIVE: This project contributes to the emerging research that aims to identify distinct body mass index (BMI) trajectory types in the population. We identify clusters of long-term BMI curves among older adults and determine how the clusters differ with respect to initial health.
METHOD: Health and Retirement Study cohort (N = 9,893) with BMI information collected in up to 10 waves (1992-2010) is analyzed using a powerful cutting-edge approach: hierarchical clustering of BMI functions estimated via the Principal Analysis by Conditional Expectations (PACE) algorithm.
RESULTS: Three BMI trajectory clusters emerged for each gender: stable, gaining, and losing. The initial health of the gaining and stable groups in both genders was comparable; the losing cluster experienced significantly poorer health at baseline. DISCUSSION: BMI trajectories among older adults cluster into distinct types in both genders, and the clusters vary substantially in initial health. Weight loss but not gain is associated with poor initial health in this age group.
© The Author(s) 2015.

Entities:  

Keywords:  BMI trajectories; BMI trajectory clusters; functional data analysis; health; older adults

Mesh:

Year:  2015        PMID: 25953813      PMCID: PMC5436799          DOI: 10.1177/0898264315584329

Source DB:  PubMed          Journal:  J Aging Health        ISSN: 0898-2643


  32 in total

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