Evidence map›Paper›PMID 40307654›Full record

ArticleGeroScience2025

Association of longitudinal body mass index trajectories with phenotypic age acceleration: a cross-sectional study based on growth mixture modeling.

Yalan Liu, Li Zhang, Zhaofeng Jin, Lin Zhang, Yan Song, Li He

Abstract read
In one paragraph

Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
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

6 authors.

Yalan LiuNanan District Center for Disease Control and Prevention, Chongqing, 401336, China.ORCID 0009-0000-2006-777X
Li ZhangQianxi People's Hospital, Guizhou, 551500, Qianxi, China.
Zhaofeng JinKweichow Moutai Hospital, RenhuaiGuizhou, 564500, China.
Lin ZhangQianxi People's Hospital, Guizhou, 551500, Qianxi, China.
Yan SongQianxi People's Hospital, Guizhou, 551500, Qianxi, China. Songyan202407@163.com.
Li HeQianxi People's Hospital, Guizhou, 551500, Qianxi, China. heli897212530@163.com.ORCID 0009-0007-0821-4002

Funding

the Science and Technology Program of BiJie Bikehe Support (2023)21
6 · The paper itself

Abstract

To examine the association between body mass index (BMI) trajectories, early and recent BMI changes, and phenotypic age acceleration (PhenoAgeAccel), addressing inconsistent findings in previous studies on weight change and aging. Data from the National Health and Nutrition Examination Survey from 2005 to 2018 were used, selecting participants aged 50 years and older. A growth mixture model was employed to identify BMI trajectories. The association between different BMI trajectories and PhenoAgeAccel was assessed using linear and multinomial logistic regression models. The nonlinear effects of BMI changes were identified through threshold effect analysis. Among 5404 participants, the four BMI trajectories identified were as follows: stable weight (29.07%), midlife weight gain (24.31%), late-life weight gain (32.22%), and chronic obesity (14.41%). The chronic obesity group exhibited the most significant elevations in PhenoAgeAccel, indicating they were phenotypically older compared to other groups (β = 4.34, 95% confidence interval 3.67-5.02). Early BMI changes of less than 6% were associated with being phenotypically younger (β =  - 5.06, P = 0.029), whereas increases exceeding 6% were linked to being phenotypically older (β = 2.83, P < 0.001). The key threshold for recent BMI changes was 2%; changes below this level were associated with being phenotypically younger, while those exceeding this threshold were linked to being phenotypically older (P < 0.001). This cross-sectional study suggests that individuals with long-term chronic obesity tend to be phenotypically older, whereas those with stable body weight are more likely to be phenotypically younger.

Indexed as

AgingBody Mass IndexObesityAgedBody-Weight TrajectoryCross-Sectional StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedNutrition SurveysPhenotypeWeight GainBMIGrowth mixture modelPhenotypic age accelerationThreshold effectTrajectory

Identifiers

PMID40307654
PMCPMC12397099

What Socratic 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 Socratic graph.