ArticleGeroScience2025
Association of longitudinal body mass index trajectories with phenotypic age acceleration: a cross-sectional study based on growth mixture modeling.
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.
What it found
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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.
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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.
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Who cites it
5 citing papers in PubMed.
- Mortality associated biological age improves independently of weight loss after bariatric surgery.npj aging · 2026Article
- Phenotypic age acceleration and all-cause and cardiovascular mortality among U.S. adults at risk for heart failure.American heart journal plus : cardiology research and practice · 2026Article
- Postoperative Oropharyngeal Muscle Training Compliance in Obstructive Sleep Apnea: Growth Mixture Model.Patient preference and adherence · 2026Article
- Vitamin D metabolites and the gut microbiota dietary index are associated with reduced all-cause mortality in US adults: a prospective cohort study.BMC nutrition · 2025Article
- Association between BMI trajectories and metabolic syndrome in postmenopausal women: a cross-sectional study from NHANES 1999-2018.BMC public health · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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.
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Registered trials
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.