ArticleAesthetic plastic surgery2024
Obesity, Glycemic Traits, Lifestyle Factors, and Risk of Facial Aging: A Mendelian Randomization Study in 423,999 Participants.
Article in Aesthetic plastic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Body Mass Index and Facial Aging: Mendelian Randomization and Exploratory Target Prioritization.Clinical, cosmetic and investigational dermatology · 2026Article
- Letter on Obesity, Glycemic Traits, Lifestyle Factors, and Risk of Facial Aging: A Mendelian Randomization Study in 423,999 Participants.Aesthetic plastic surgery · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundSeveral recent observational studies have associated obesity, lifestyle factors (smoking, sleep duration, and alcohol drinking), and glycemic traits with facial aging. However, whether this relationship is causal due to confounding and reverse causation is yet to be substantiated.
aimsWe aimed to assess these relationships using Mendelian randomization (MR).
methodsFor the instrumental variables, this paper selected independent single nucleotide polymorphisms (SNPs) linked to the exposures at a genome-wide state (P < 5 × 10-8) in equivalent genome-wide association studies (GWAS). Using the UK Biobank, we obtained summary-level data for facial aging on 423,999 individuals. The primary assessments were performed through the combination of complementing techniques (simple method approaches, weighted model, MR-Egger, and weighted median) and the inverse-variance-weighted method. Along with that, we examined the heterogeneity and horizontal pleiotropy through different types of sensitivity analyses.
resultsThe correlations were (a) facial aging for body mass index (BMI, OR = 1.054, 95% CI 1.044-1.64), (b) waist/hip ratio (OR = 1.056, 95% CI 1.023-1.091), and (c) smoking (OR = 1.023, 95% CI 1.007-1.039). Equally important, the correlations for waist/hip ratio remained robust after adjusting for the genetically predicted BMI (OR = 1.028, 95% CI 1.003-1.054). However, no causal effects of alcoholic drinking, glycemic traits, and sleep duration on facial aging were observed.
conclusionsThe outcomes shed light on the potential correlation of obesity and cigarette smoking with facial aging while putting forward a more comprehensive and credible foundation for the optimization of facial aging strategies. NO LEVEL ASSIGNED: This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.