ArticleScientific reports2023
Different correlation of body mass index with body fatness and obesity-related biomarker according to age, sex and race-ethnicity.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers, 4 of them syntheses that pooled it.
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Who cites it
92 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Optimal BMI cut-offs associated with cardiometabolic risks in Arab and Middle Eastern populations: a systematic review and meta-analysis.International journal of obesity (2005) · 2026Pooled it
- Molecular Pathways Linking High-Fat Diet and PMBiomolecules · 2024Pooled it
- A literature review of biomarkers used for diagnosis of relative energy deficiency in sport.Frontiers in sports and active living · 2024Pooled it
- Pooled it
- Association Between Changes in Body Composition and Physical Function After Intensive Behavioral Weight-loss Intervention: A Look AHEAD Trial Subgroup Analysis.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Trial
- Protein-enriched intermittent meal replacement combined with moderate-intensity training for weight loss and body composition in overweight women.Scientific reports · 2025Trial
- Bioimpedance: From Body Composition Assessment to Emerging Technologies in Clinical Nutrition.Nutrients · 2026Review
- Diagnostic BMI and Induction Therapy Weight Change Associated With Hepatotoxicity in Pediatric Patients With Acute Lymphoblastic Leukemia.Cancer medicine · 2026Article
- Adiposity and risk of breast cancer in 280 000 Chinese women: a prospective cohort study.International journal of epidemiology · 2026Observational
- Duplicate-Aware Internal Validation of Machine-Learning Models for Classifying a Tanita BIA-Derived High-Adiposity Phenotype Using Simple Anthropometric Predictors.Journal of clinical medicine · 2026Article
- Age- and sex-specific predictive performance of obesity indices for hypertension in the Persian (Shahedieh) cohort study.Archives of public health = Archives belges de sante publique · 2026Article
- Multivariable Associations of Anthropometric and Psychosocial Markers with an Elevated Abdominal Volume Index Among University Students: A Sex- and Academic Program-Stratified Analysis.Healthcare (Basel, Switzerland) · 2026Article
- Unpacking adiposity: a narrative critical appraisal of diverse obesity definitions.Diabetology & metabolic syndrome · 2026Review
- Targeting the activin/myostatin - actrii pathway to preserve skeletal muscle mass in obesity: mechanistic insights and therapeutic perspectives.Reviews in endocrine & metabolic disorders · 2026Review
- A Systems Perspective on Lifestyle Behaviors, Excess Weight, and Healthy Longevity in the European Union.Nutrients · 2026Observational
- Obesity and Health Risk Factors in Czech Artillery Soldiers.Military medicine · 2026Article
- Role of systemic and epicardial adipose tissue in cardiometabolic disease.Nature reviews. Cardiology · 2026Review
- Defining Obesity Under the Lancet Commission Criteria: Metabolic Syndrome-Anchored Body Fat Percentage Thresholds in Korean Adults.Diabetes, obesity & metabolism · 2026Article
- Adiposity-based obesity classification and cardiometabolic and kidney outcomes: a longitudinal UK Biobank analysis.EBioMedicine · 2026Article
- Comparing multiple definitions of obesity in a large nationwide health program.Scientific reports · 2026Article
32 more citing papers are in PubMed but not listed here.
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Abstract
The relationship between body mass index (BMI) and body fatness could differ according to age, sex, and race-ethnicity. We aimed to evaluate in which contexts BMI could be a good measure for body fatness compared to dual-energy X-ray absorptiometry (DXA) derived measures. The study population included 18,061 participants (9141 men and 8920 women) aged 18 and older who tested DXA from the National Health and Nutrition Examination Survey (NHANES) database from 1999 to 2006, and 8107 men and 10,754 women with DXA data from Korea NHANES from 2008 to 2011 to represent the Asian population. We calculated Pearson correlation coefficients between BMI and DXA derived fat mass index (FMI) and percentage body fat (PBF) depending on age, sex, and race-ethnicity. The correlation between BMI, FMI and PBF and obesity-related biomarkers was also estimated among the subgroup with both DXA and information on each biomarker. BMI was strongly correlated with FMI (r = 0.944 in men and 0.976 in women), PBF (r = 0.735 in men and 0.799 in women), and truncal fat mass (r = 0.914 in men and 0.941 in women) with correlations stronger in women than in men except for with waist-height ratio (r = 0.921 in men and 0.911 in women). The correlation between BMI and DXA derived adiposity weakened with age in both sexes. BMI was less correlated with FMI (r = 0.840 in men and 0.912 in women), PBF (r = 0.645 in men and 0.681 in women), and truncal fat mass (r = 0.836 in men and 0.884 in women) in Korean compared to other race-ethnicities. Among obesity-related biomarkers, insulin was the most strongly correlated to body adiposity indices in both sexes and strength of these correlations generally decreased with age. BMI predicted obesity-related biomarkers as well as FMI and truncal fat mass and superior to PBF. BMI could be a good measure for body fatness, particularly among young age groups, women, the US population, but less so in Korean populations. The lower correlation between BMI and body fatness in older compared to younger age groups could be related to increasing PBF and decreasing lean body mass.
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