Evidence map›Paper›PMID 38307987›Full record

ArticleScientific reports2024

Joint effect of BMI and metabolic status on mortality among adults: a population-based longitudinal study in United States.

Feilong Chen, Yunping Shi, Miao Yu, Yuehua Hu, Tao Li, Yijing Cheng, Tao Xu, Junting Liu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Precision or Paradox? AI-Driven Adiposity Imaging in Women With Overweight and Obesity: A Systematic Review and Meta-Analysis.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
    Pooled it
  2. DietaryCurrent issues in molecular biology · 2026
    Article
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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

8 authors.

Feilong Chen *Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, No.5, Dong dan san tiao, Beijing, 100005, China.
Yunping Shi *Department of Information and Statistics, Beijing Center for Disease Prevention and Control, No. 16 Heping Li Middle Street, Dongcheng District, Beijing, 100013, China.
Miao YuDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, No.5, Dong dan san tiao, Beijing, 100005, China.
Yuehua HuOffice of Epidemiology, Chinese Center for Disease Control and Prevention, No. 155 Changbai Road Changping District, Beijing, 102206, China.
Tao LiChild Health Big Data Research Center, Capital Institute of Pediatrics, No. 2 Yabao Road, Beijing, 100020, China.
Yijing ChengChild Health Big Data Research Center, Capital Institute of Pediatrics, No. 2 Yabao Road, Beijing, 100020, China.
Tao XuDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, No.5, Dong dan san tiao, Beijing, 100005, China. xutaosd@126.com.
Junting LiuChild Health Big Data Research Center, Capital Institute of Pediatrics, No. 2 Yabao Road, Beijing, 100020, China. junting_liu@163.com.

Funding

National High Level Hospital Clinical Research Funding 2022-PUMCH-C-058Research Foundation of Capital Institute of Pediatrics ERB-2023-01
6 · The paper itself

Abstract

We explored the joint effects of different metabolic obesity phenotypes on all-cause and disease-specific mortality risk among the American population. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Mortality outcome data were from mortality files linked to National Death Index record and follow-up information was up to December 31, 2019. 50,013 participants were finally included. Four metabolic obesity phenotypes were defined based on obesity and metabolic status: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy non-obese (MHNO), and metabolically unhealthy non-obese (MUNO). Population-weighted Cox proportional hazards models were used to explore the all-cause and disease-specific mortality risk of metabolic obesity phenotypes. The all-cause mortality risk of MUO and MUNO was significantly higher than MHNO. MUNO was associated with a significantly increased risk of death from heart disease (HR: 1.40, 95% CI 1.16-1.70), hypertension (HR: 1.68, 95% CI 1.34-2.12), diabetes (HR: 2.29, 95% CI 1.67-3.15), and malignant neoplasms (HR:1.29, 95% CI 1.09-1.53). Metabolic unhealth significantly increased the risk of all-cause mortality, regardless of obesity status. Among individuals with metabolic unhealthy status, obesity significantly reduced the risk of all-cause mortality (HR: 0.91, 95% CI 0.85-0.98). Our study highlights the importance of identifying and characterizing metabolic obesity phenotypes in obese and metabolically abnormal patients, as well as healthy adults. Comprehensive evaluation of obesity and metabolic status is necessary to adopt appropriate interventions and treatment measures and maximize patient benefit.

Indexed as

Metabolic SyndromeObesityAdultBody Mass IndexHumansLongitudinal StudiesNutrition SurveysPhenotypeRisk FactorsUnited States

Identifiers

PMID38307987
PMCPMC10837108

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Registered trials

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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.