# Longitudinal pattern of multimorbidity in older adult population: latent transition analysis in 34 countries

## TL;DR

This study explores how health conditions in older adults change over time across 34 countries, identifying patterns of mild, moderate, and severe multimorbidity.

## Contribution

The study introduces a cross-national longitudinal analysis of multimorbidity patterns using latent transition analysis in older adults.

## Key findings

- Severe multimorbidity is marked by high prevalence of diabetes and hypertension.
- Mild multimorbidity is associated with lower prevalence of health conditions.
- Men and low-educated individuals are more likely to experience severe multimorbidity.

## Abstract

Multimorbidity has become a global public health concern, yet cross-national comparisons remain limited, especially in longitudinal settings. This study investigates the longitudinal patterns and transitions of multimorbidity status of people over age 50 in 34 countries. Utilizing comparable health indicators across countries, we examine chronic health conditions (hypertension and diabetes), cognitive function, physical ability, and self-report of general health. Using latent transition analysis, we identify a pattern of multimorbidity and classify it into three classes: mild, moderate, and severe multimorbidity. Mild multimorbidity is characterized by a lower prevalence of 3 morbidities out of 5, while severe multimorbidity is characterized by a higher prevalence across all health conditions. Moderate multimorbidity falls between these 2 extremes. Our findings reveal substantial variation in these classes across countries, with diabetes and hypertension emerging as the predominant condition among older adults with severe and moderate multimorbidity, respectively. Over time, both severe and moderate multimorbidity tend to increase, with similar transition probabilities from mild to more severe categories across countries. Covariate analysis indicates that men and low-educated individuals are more likely to experience severe multimorbidity. These results underscore the importance of understanding multimorbidity patterns and dynamics for effective public health planning and healthcare services.

This article is part of a Special Collection on Cross-National Gerontology.