Observational studyInternational journal of obesity (2005)2023
Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic.
Observational study in International journal of obesity (2005), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A Reporting Guideline for Observational Studies in Metabolomic Epidemiology: Explanation and Elaboration of the Strobe-MetEpi Checklist.Research square · 2026Article
- Mortality associated biological age improves independently of weight loss after bariatric surgery.npj aging · 2026Article
- Epidemiological associations between obesity, metabolism and disease risk: are body mass index and waist-hip ratio all you need?International journal of obesity (2005) · 2025Article
- Manifold fitting reveals metabolomic heterogeneity and disease associations in UK Biobank populations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Bayesian semiparametric inference in longitudinal metabolomics data.Scientific reports · 2024Article
- Mendelian randomization reveals that abnormal lipid metabolism mediates the causal relationship between body mass index and keratoconus.Scientific reports · 2024Article
- Metabolic liability for weight gain in early adulthood.Cell reports. Medicine · 2024Article
- Influence of age and sex on longitudinal metabolic profiles and body weight trajectories in the UK Biobank.International journal of epidemiology · 2024Article
- Clinical and biochemical associations of urinary metabolites: quantitative epidemiological approach on renal-cardiometabolic biomarkers.International journal of epidemiology · 2024Article
- Novel subgroups of obesity and their association with outcomes: a data-driven cluster analysis.BMC public health · 2024Article
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Authors and funding
10 authors.
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Abstract
BACKGROUND/
objectiveThis observational study dissects the complex temporal associations between body-mass index (BMI), waist-hip ratio (WHR) and circulating metabolomics using a combination of longitudinal and cross-sectional population-based datasets and new systems epidemiology tools. SUBJECTS/
methodsFirstly, a data-driven subgrouping algorithm was employed to simplify high-dimensional metabolic profiling data into a single categorical variable: a self-organizing map (SOM) was created from 174 metabolic measures from cross-sectional surveys (FINRISK, n = 9708, ages 25-74) and a birth cohort (NFBC1966, n = 3117, age 31 at baseline, age 46 at follow-up) and an expert committee defined four subgroups of individuals based on visual inspection of the SOM. Secondly, the subgroups were compared regarding BMI and WHR trajectories in an independent longitudinal dataset: participants of the Young Finns Study (YFS, n = 1286, ages 24-39 at baseline, 10 years follow-up, three visits) were categorized into the four subgroups and subgroup-specific age-dependent trajectories of BMI, WHR and metabolic measures were modelled by linear regression.
resultsThe four subgroups were characterised at age 39 by high BMI, WHR and dyslipidemia (designated TG-rich); low BMI, WHR and favourable lipids (TG-poor); low lipids in general (Low lipid) and high low-density-lipoprotein cholesterol (High LDL-C). Trajectory modelling of the YFS dataset revealed a dynamic BMI divergence pattern: despite overlapping starting points at age 24, the subgroups diverged in BMI, fasting insulin (three-fold difference at age 49 between TG-rich and TG-poor) and insulin-associated measures such as triglyceride-cholesterol ratio. Trajectories also revealed a WHR progression pattern: despite different starting points at the age of 24 in WHR, LDL-C and cholesterol-associated measures, all subgroups exhibited similar rates of change in these measures, i.e. WHR progression was uniform regardless of the cross-sectional metabolic profile.
conclusionsAge-associated weight variation in adults between 24 and 49 manifests as temporal divergence in BMI and uniform progression of WHR across metabolic health strata.
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