Evidence map›Paper›PMID 39497471›Full record

ArticleDiabetes, obesity & metabolism2025

The impact of metabolic heterogeneity of obesity and transitions on cardiovascular disease incidence in Chinese middle-aged and elderly population: A nationwide prospective cohort study.

Qiang He, Rujie Zheng, Wenjuan Song, Xiaotong Sun, Chengzhi Lu

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Article in Diabetes, obesity & metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
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17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Qiang HeDepartment of Cardiology, Tianjin First Central Hospital, Tianjin, P.R. China.
Rujie ZhengDepartment of Cardiology, Tianjin First Central Hospital, Tianjin, P.R. China.ORCID 0000-0003-0608-0817
Wenjuan SongDepartment of Cardiology, Tianjin First Central Hospital, Tianjin, P.R. China.
Xiaotong SunDepartment of Cardiology, Tianjin First Central Hospital, Tianjin, P.R. China.
Chengzhi LuDepartment of Cardiology, Tianjin First Central Hospital, Tianjin, P.R. China.ORCID 0000-0002-4546-6395

Funding

National Natural Science Foundation of China 81970303Tianjin Key Municipality Medical Discipline (Specialty) Construction Project TJYXZDXK-054B
6 · The paper itself

Abstract

backgroundPrevious studies indicated that metabolic heterogeneity of obesity would affect the risk of cardiovascular disease (CVD). However, the alterations in CVD risk associated with transitions between various metabolic health statuses influenced by obesity status remain unclear.

methodsWe utilized data from the China Health and Retirement Longitudinal Study (CHARLS), a longitudinal cohort study involving Chinese residents aged 45 years and older. Baseline data were collected in 2011-2012, with follow-up surveys conducted up to 2020. Participants in the study were categorized into four body mass index-metabolic phenotypes: metabolically healthy normal weight (MHNW), metabolically healthy overweight/obesity (MHOO), metabolically unhealthy normal weight (MUNW) and metabolically unhealthy overweight/obesity (MUOO). Transitions in these phenotypes over 4 years were analysed. Cox regression models were used to assess the associations of these phenotypes and their transitions with CVD incidence.

resultsAmong 7721 participants, 1353 (17.5%) developed CVD during the follow-up period. Both overweight/obese and metabolically unhealthy statuses were associated with increased CVD risk. The highest risk was observed in the MUOO group (hazard ratio [HR]: 1.74, 95% confidence interval [CI]: 1.50-2.09, p < 0.0001), followed by the MUNW (HR 1.35, 95% CI: 1.13-1.66, p < 0.001) and MHOO (HR: 1.29, 95% CI: 1.08-1.56, p = 0.002) groups compared to the MHNW group. The deteriorations of obesity and metabolic health status elevated the incidence of CVD, whereas improvements in these statuses reduced the risk of CVD. Additionally, alterations in metabolic health status conferred greater benefits in overweight/obese individuals compared to those with normal weight.

conclusionThe study highlights the importance of maintaining and promoting metabolic health, particularly in overweight/obese individuals, to reduce CVD risk. Metabolic health status plays a more crucial role than obesity status in predicting CVD incidence.

Indexed as

Cardiovascular DiseasesObesityAgedBody Mass IndexChinaCohort StudiesEast Asian PeopleFemaleHumansIncidenceLongitudinal StudiesMaleMiddle AgedObesity, Metabolically BenignOverweightProspective Studiescardiovascular diseasedatabase researchobesity careprimary careweight management

Identifiers

PMID39497471
PMCPMC11701191

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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.