Evidence map›Paper›PMID 42369058›Full record

ArticleFrontiers in endocrinology2026

Mortality trends in diabetes with proxy-defined steatotic liver disease in the United States, 1999-2023.

Hongzhou Liu, Ru Wang, Liqin Cui, Linlin Wang, Jia Liu, Yangfan Du, Song Dong, Kaide Xia

Abstract read
In one paragraph

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

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Hongzhou Liu *Department of Endocrinology, Aerospace Center Hospital, Beijing, China.
Ru Wang *Department of Endocrinology, Beijing Jishuitan Hospital, Beijing, China.
Liqin CuiDepartment of Endocrinology, Aerospace Center Hospital, Beijing, China.
Linlin WangDepartment of Endocrinology, Aerospace Center Hospital, Beijing, China.
Jia LiuDepartment of Endocrinology, Aerospace Center Hospital, Beijing, China.
Yangfan DuDepartment of Endocrinology, Aerospace Center Hospital, Beijing, China.
Song DongDepartment of Endocrinology, Aerospace Center Hospital, Beijing, China.
Kaide XiaGuiyang Maternal and Child Health Care Hospital, Guiyang Children's Hospital, Guiyang, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To characterize U.S. mortality trends for diabetes mellitus (DM), proxy-defined metabolic dysfunction-associated steatotic liver disease (MASLD), and deaths listing both conditions, and to present exploratory conditional overlap extrapolations through 2040. Methods: We analyzed CDC WONDER multiple-cause-of-death data from 1999-2023 among adults aged ≥25 years. DM was identified by ICD-10 codes E10-E14 and steatotic liver disease by K75.8 or K76.0. Because clinical MASLD cannot be directly ascertained in CDC WONDER, MASLD was defined using a death-certificate proxy combining steatotic liver disease codes with recorded cardiometabolic conditions. Age-adjusted mortality rates were assessed using Joinpoint regression. Prophet models generated conditional extrapolations through 2040. Sensitivity analyses used K76.0-only coding, K75.8-only coding, restriction to 1999-2019, and an underlying-cause-of-death-only analysis requiring K76.0 to be listed as the underlying cause of death. Results: DM-involved mortality changed little from 1999 to 2023 (118.47 to 122.61 per 100,000; average annual percent change [AAPC], -0.03%). In contrast, overlap mortality increased from 0.08 to 0.84 per 100,000 (AAPC, 11.20%), and proxy-defined MASLD mortality increased from 0.13 to 1.29 per 100,000 (AAPC, 9.83%), although absolute rates remained low. Sensitivity analyses using K76.0-only coding, restriction to 1999-2019, and an underlying-cause-of-death-only definition showed directionally consistent increases, whereas K75.8-only overlap deaths were sparse, zero, or suppressed. The underlying-cause-only analysis also showed a directionally consistent increase from 2000 to 2023 (AAPC, 14.46%; 95% CI, 13.46 to 21.51). Conditional extrapolations suggested continued growth through 2040 but were inherently uncertain. Conclusions: Proxy-based mortality involving co-recorded DM and steatotic liver disease increased substantially in U.S. death-certificate data. These findings were directionally consistent across alternative coding, period-restricted, and underlying-cause-only sensitivity analyses but remain limited by under-ascertainment, misclassification, and evolving death-certificate documentation. They should be interpreted as descriptive surveillance patterns rather than evidence of biological expansion or causal mechanisms.

Indexed as

Diabetes MellitusFatty LiverAdultAgedCause of DeathFemaleHumansMaleMiddle AgedMortalityUnited Statesdeath certificatesdiabetes mellitusmetabolic dysfunction–associated steatotic liver diseasemortalitysteatotic liver disease

Identifiers

PMID42369058
PMCPMC13303214

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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.