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Background <p>Traditional anthropometric measures such as body mass index (BMI) have limitations in accurately assessing cardiometabolic risk and body fat distribution. Consequently, advanced anthropometric indices have emerged as more specific tools for assessing metabolic health and predicting cardiovascular complications.</p> Objectives <p>To assess the prevalence of metabolic syndrome (MetS) in the study population and evaluate its relationships with advanced anthropometric indices and selected cardiometabolic marker. </p> &#xa0;Methods <p>The study comprised of 2354 participants from the tertiary care setting and screened for metabolic syndrome using IDF and revised NCEP ATP III criteria. The demographic, anthropometric and biochemical data were recorded. BMI and advanced anthropometric indices and cardiometabolic marker, viz., body roundness index (BRI), conicity index (CI), waist-to-height ratio (WHtR), relative fat mass (RFM) and triglyceride-glucose index (TyG index), were computed.</p> Results <p>Advanced anthropometric indices and cardiometabolic marker showed significant associations with age, gender, BMI and BMI classification stages (<i>p</i> &lt; 0.000). The prevalence of MetS was 40.2% according to IDF and 33.7% as per revised NCEP ATP III criteria. RFM showed the strongest associations (chi-square = 547.4 IDF, 349.6 revised NCEP ATP III). WHtR demonstrated a significant increase in MetS prevalence when elevated. BRI exhibited highest specificity (82% IDF, 71% revised NCEP ATP III). CI showed weakest associations. TyG index performed exceptionally with revised NCEP ATP III criteria (73.2% prevalence). IDF criteria identified more cases than revised NCEP ATP III.</p> Conclusion <p>IDF criteria identified more cases than revised NCEP ATP III. These indices effectively screen for MetS at population level. Multi-index approaches offer comprehensive risk assessment for identifying individuals at high risk of poor metabolic health.</p>

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Advanced anthropometric indices and metabolic syndrome (AIMS):   A comparative analysis

  • 期刊论文

  • 发表日期：

    2026年5月12日

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  • Sachdev Meenakshi,
  • Renuka Mainde,
  • Rekha Sharma,
  • Sabiha Vali,
  • N. Prabhavathy Devi,
  • Pritham Kapil D,
  • Ishika Jain R

摘要

Background

Traditional anthropometric measures such as body mass index (BMI) have limitations in accurately assessing cardiometabolic risk and body fat distribution. Consequently, advanced anthropometric indices have emerged as more specific tools for assessing metabolic health and predicting cardiovascular complications.

Objectives

To assess the prevalence of metabolic syndrome (MetS) in the study population and evaluate its relationships with advanced anthropometric indices and selected cardiometabolic marker.

 Methods

The study comprised of 2354 participants from the tertiary care setting and screened for metabolic syndrome using IDF and revised NCEP ATP III criteria. The demographic, anthropometric and biochemical data were recorded. BMI and advanced anthropometric indices and cardiometabolic marker, viz., body roundness index (BRI), conicity index (CI), waist-to-height ratio (WHtR), relative fat mass (RFM) and triglyceride-glucose index (TyG index), were computed.

Results

Advanced anthropometric indices and cardiometabolic marker showed significant associations with age, gender, BMI and BMI classification stages (p < 0.000). The prevalence of MetS was 40.2% according to IDF and 33.7% as per revised NCEP ATP III criteria. RFM showed the strongest associations (chi-square = 547.4 IDF, 349.6 revised NCEP ATP III). WHtR demonstrated a significant increase in MetS prevalence when elevated. BRI exhibited highest specificity (82% IDF, 71% revised NCEP ATP III). CI showed weakest associations. TyG index performed exceptionally with revised NCEP ATP III criteria (73.2% prevalence). IDF criteria identified more cases than revised NCEP ATP III.

Conclusion

IDF criteria identified more cases than revised NCEP ATP III. These indices effectively screen for MetS at population level. Multi-index approaches offer comprehensive risk assessment for identifying individuals at high risk of poor metabolic health.