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Cardiovascular Disease and Adiposity / Diabetes, Cardiovascular Risks, and Lipoproteins · Journal article
Medical Sciences · September 9, 2026
Reinforces what was already believed, rather than introducing something new.
This cross-sectional analysis of 166,008 Spanish workers with normal BMI (18.5–24.9 kg/m²) stratified participants into four adiposity–metabolic phenotypes and found that approximately 21% exhibited discordance or combined high-risk status. The findings confirm that BMI-based classification alone misses hidden metabolic dysfunction and cardiometabolic heterogeneity in the normal-weight population, supporting multidimensional assessment beyond weight.
Cross-sectional study (secondary analysis). Spanish occupational workers aged 18–69 years with normal body weight (BMI 18.5–24.9 kg/m²) undergoing routine occupational health examinations.. n = 166,008. Spain (occupational health screening program, 2019–2024)..
Concordant healthy phenotype was most prevalent at 78.9%; adiposity-only 9.8%, metabolic-only 9.2%, and concordant high-risk 2.0% Approximately 21% of normal-BMI participants exhibited adiposity–metabolic discordance or combined high-risk status Metabolic-only phenotype showed markedly adverse triglyceride, TG/HDL-c ratio, fasting glucose, and blood pressure despite preserved anthropometric parameters
Metabolic-only phenotype showed markedly adverse triglyceride, TG/HDL-c ratio, fasting glucose, and blood pressure despite preserved anthropometric parameters Sedentary lifestyle, unfavorable dietary adherence, smoking, older age, male sex, and higher BMI within normal-weight range independently associated with metabolically adverse phenotypes
Clinicians should recognize that normal BMI does not exclude cardiometabolic risk; a subset of normal-weight adults harbour adverse metabolic profiles. Integration of waist-to-height ratio, metabolic parameters (triglycerides, glucose, blood pressure, HDL cholesterol), and visceral adiposity markers may identify hidden-risk phenotypes missed by weight-based screening alone.
Cross-sectional analysis of a large occupational cohort confirming that BMI-normal adults exhibit metabolic heterogeneity and hidden cardiometabolic risk not detected by weight-based screening alone, replicating established knowledge that adiposity and metabolic dysfunction may diverge.
As stated by the source record.
Quoted from the source exactly as published.
Clinicians should recognize that normal BMI does not exclude cardiometabolic risk; a subset of normal-weight adults harbour adverse metabolic profiles. Integration of waist-to-height ratio, metabolic parameters (triglycerides, glucose, blood pressure, HDL cholesterol), and visceral adiposity markers may identify hidden-risk phenotypes missed by weight-based screening alone.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Background: Body mass index (BMI) is widely used to classify obesity and cardiometabolic risk, although it may fail to detect hidden metabolic impairment in individuals with normal body weight. Increasing evidence suggests that adiposity and metabolic dysfunction may not always coexist, giving rise to biologically discordant phenotypes associated with different cardiometabolic profiles. Methods: This cross-sectional study was a secondary analysis of a subset of normal-weight adults selected from a larger database of Spanish workers undergoing routine occupational health examinations between 2019 and 2024. The final analytical sample included 166,008 workers aged 18–69 years with BMI values between 18.5 and 24.9 kg/m2. Participants were classified into four adiposity–metabolic phenotypes according to the presence or absence of increased adiposity, operationally defined as a waist-to-height ratio (WtHR) ≥ 0.50, and metabolic dysfunction, defined as the presence of ≥2 of five adverse cardiometabolic criteria. METS-VF was additionally evaluated as a marker of visceral adiposity. Anthropometric, metabolic, vascular, and lifestyle-related variables were analyzed. Multivariable logistic regression models were used to evaluate factors associated with discordant phenotypes. Results: The concordant healthy phenotype was the most prevalent subgroup (78.9%), followed by adiposity-only (9.8%), metabolic-only (9.2%), and concordant high-risk phenotypes (2.0%). Despite normal BMI, approximately 21% of participants exhibited adiposity–metabolic discordance or combined high-risk status. The metabolic-only phenotype showed markedly adverse triglyceride, TG/HDL-c ratio, fasting glucose, and blood pressure values despite relatively preserved anthropometric parameters. Conversely, the adiposity-only phenotype exhibited increased central and visceral adiposity with comparatively preserved metabolic status. Sedentary lifestyle, unfavorable dietary adherence, smoking, older age, male sex, and higher BMI within the normal-weight range were independently associated with metabolically adverse phenotypes. The concordant high-risk phenotype demonstrated the greatest overall cardiometabolic burden. Conclusions: Adults with normal BMI are metabolically heterogeneous and may present clinically relevant hidden-risk phenotypes despite conventional normal-weight classification. Adiposity–metabolic discordance highlights the limitations of BMI-based screening alone and supports the incorporation of multidimensional anthropometric, metabolic, and lifestyle-related assessment strategies for earlier identification of cardiometabolic risk.
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