Multimorbidity Patterns and Mortality Risk in a National Sample of US Adults Identified Using Latent Class Analysis
Emmanuel U. Azu, Gulzar H. Shah, Toktam Naderimoghaddam, Lili Yu · 2026
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Description
Emmanuel U. Azu, Gulzar H. Shah, Toktam Naderimoghaddam, and Lili Yu sort United States adults into patterns of multiple chronic conditions and test how each pattern relates to death risk, in 2026 work. The data joined a 2004 national health survey with death records through 2019, covering 28,598 adults. A statistical grouping method built classes from how diagnosed conditions cluster together in the same person.
Six patterns emerged, reflecting heart-metabolic, breathing, cardiovascular, and inflammatory profiles. Every pattern beyond the low-burden group carried higher death risk after full adjustment. A severe heart-lung-metabolic class and an advanced cardiovascular class sat at the top of the risk range, with a heart-metabolic plus arthritis class next. Effects looked stronger among younger adults and women in the worst classes. The authors say pattern-based care could target the riskiest combinations earlier.
Catalog record
| CREATOR | Emmanuel U. Azu, Gulzar H. Shah, Toktam Naderimoghaddam, Lili Yu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 41 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |