Evidence map›Paper›PMID 42859919›Full record

ArticleInternational journal of epidemiology2026

Sicker at all ages? Two decades of changing disease histories and mortality in the United States.

Marcus Ebeling, Neil K Mehta, Leah Abrams, Mikko Myrskylä

Abstract read
In one paragraph

Article in International journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Marcus EbelingMax Planck Institute for Demographic Research, Rostock, Germany.ORCID 0000-0002-6531-8525
Neil K MehtaDepartment of Epidemiology, University of Texas Medical Branch, Galveston (TX), United States.ORCID 0000-0001-6671-8435
Leah AbramsDepartment of Community Health, Tufts University, Medford (MA), United States.ORCID 0000-0002-8766-0903
Mikko MyrskyläMax Planck Institute for Demographic Research, Rostock, Germany.

Funding

UTMB OAIC Research Education Component (REC)P30AG024832 · NIA · UNIVERSITY OF TEXAS MEDICAL BR GALVESTON · PI JAMES S. GOODWIN, MD, MELISSA M. MORROW · 2005 to 2026
$26.7M
Disparities in the burden and progression of multi-morbidity across adulthoodR01AG074019 · NIA · EMORY UNIVERSITY · PI ARGESEANU CUNNINGHAM, SOLVEIG · 2022 to 2025
$1.5M
Identifying the Causes of the Stagnation in National U.S. Cardiovascular Disease MortalityR01AG075208 · NIA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI NEIL MEHTA · 2023 to 2026
$1.5M
NIA NIH HHS P30 AG024832NIA NIH HHS P30AG024832NIA NIH HHS R01 AG074019NIA NIH HHS R01AG074019NIA NIH HHS R01 AG075208NIA NIH HHS R01AG075208
6 · The paper itself

Abstract

backgroundStagnating cardiovascular disease mortality and rising drug- and suicide-related deaths are key drivers of stalled US mortality improvements. However, prior research has largely overlooked disease histories preceding death, despite increasing multimorbidity. We examined changes in disease-history profiles in the US population and assessed how shifts in profile composition and within-profile mortality shaped mortality trends.

methodsWe analysed adults aged ≥30 years (N = 510 372) from the IPUMS-NHIS (National Health Interview Survey) 1997-2018 linked mortality files (follow-up through 2019). Latent class analysis on the pooled sample across all ages and years identified disease-history profiles based on self-reported cancer, diabetes, cardiovascular disease, mental health, internal diseases, obesity, and physical limitations. Logistic regression was used to estimate profile-specific 5-year mortality over time, and counterfactual decomposition was used to quantify the contributions of compositional change and within-profile mortality improvement to overall mortality trends.

resultsFive disease-history profiles were identified. Prevalence and 5-year death probability ranged from disease-free (62.4%; men 3.7% [95% confidence interval (CI) 3.5-3.8], women 2.4% [95% CI 2.3-2.5]) to high-burden multimorbidity (5.9%; men 17.8% [95% CI 16.8-18.8], women 12.6% [95% CI 11.9-13.3]), with substantial gradients across intermediate profiles. Profile composition varied substantially by gender, education, and race/ethnicity. The disease-free population declined by nearly 1% annually, replaced primarily by cardiometabolic and high-burden multimorbidity profiles. Most profiles experienced stagnating or increasing mortality after the mid-2000s. The decomposition shows that within-profile mortality improvement was the dominant driver of declining mortality; compositional shifts, mostly driven by the declining disease-free share, partially offset these gains.

conclusionStagnating US mortality reflects both the growing prevalence of high-morbidity profiles and worsening or stagnating survival within them, highlighting the limited reach of prevention and disease-management efforts.

Indexed as

MortalityAdultAgedAged, 80 and overCardiovascular DiseasesCause of DeathChronic DiseaseFemaleHumansMaleMiddle AgedMultimorbidityNeoplasmsPrevalenceUnited Statesdisease historydisparitiesmortalitypopulation compositionprevalence

Identifiers

PMID42859919
PMCPMC13654198

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.