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Related Experiment Video

Updated: Oct 15, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Risk Patterns and Mortality in Postmenopausal Women Using Latent Class Analysis.

Juhua Luo1, Paul Dinh1, Michael Hendryx2

  • 1Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, Bloomington, Indiana.

American Journal of Preventive Medicine
|October 23, 2021
PubMed
Summary

Identifying distinct risk patterns in postmenopausal women reveals that combined lifestyle and psychosocial risks significantly increase mortality. Health interventions should address these factors concurrently for better outcomes.

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Area of Science:

  • Public Health
  • Epidemiology
  • Behavioral Science

Background:

  • Previous research often examined lifestyle or psychosocial factors individually.
  • Risk factors frequently co-occur, necessitating a pattern-based approach.

Purpose of the Study:

  • To identify subgroups of postmenopausal women based on distinct lifestyle and psychosocial risk patterns.
  • To investigate the association between these risk patterns and mortality.

Main Methods:

  • Latent class analysis was used to identify risk patterns in 64,812 postmenopausal women.
  • Follow-up occurred over a mean of 14.6 years, with mortality as the outcome.
  • Analyses were stratified by race/ethnicity.

Main Results:

  • Four latent classes were identified for Hispanic, Black, and White women; two for American Indian and Asian women.
  • The 'Risky Lifestyle and Risky Psychosocial' group exhibited the highest mortality risk across all race/ethnicity groups.
  • A 'Risky Psychosocial' class was linked to increased overall and cardiovascular mortality risk specifically in Black women.

Conclusions:

  • Concurrent risky lifestyle and psychosocial factors present the greatest mortality risk.
  • Health promotion strategies should simultaneously address behavioral and psychosocial risks.