Role of anthropometric indices as a screening tool for predicting metabolic syndrome among apparently healthy individuals of Karachi, Pakistan

Syed Omair Adil*, Kamarul Imran Musa, Fareed Uddin, Kashif Shafique, Asima Khan, Md Asiful Islam*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Introduction: Anthropometric indices are affordable and non-invasive methods for screening metabolic syndrome (MetS). However, determining the most effective index for screening can be challenging.

Objective: To investigate the accuracy of anthropometric indices as a screening tool for predicting MetS among apparently healthy individuals in Karachi, Pakistan.

Methods: A community-based cross-sectional survey was conducted in Karachi, Pakistan, from February 2022 to August 2022. A total of 1,065 apparently healthy individuals aged 25 years and above were included. MetS was diagnosed using International Diabetes Federation guidelines. Anthropometric indices were defined based on body mass index (BMI), neck circumference (NC), mid-upper arm circumference (MUAC), waist circumference (WC), waist to height ratio (WHtR), conicity index, reciprocal ponderal index (RPI), body shape index (BSI), and visceral adiposity index (VAI). The analysis involved the utilization of Pearson’s correlation test and independent t-test to examine inferential statistics. The receiver operating characteristic (ROC) analysis was also applied to evaluate the predictive capacities of various anthropometric indices regarding metabolic risk factors. Moreover, the area under the curve (AUC) was computed, and the chosen anthropometric indices’ optimal cutoff values were determined.

Results: All anthropometric indices, except for RPI in males and BSI in females, were significantly higher in MetS than those without MetS. VAI [AUC 0.820 (95% CI 0.78–0.86)], WC [AUC 0.751 (95% CI 0.72–0.79)], WHtR [AUC 0.732 (95% CI 0.69–0.77)], and BMI [AUC 0.708 (95% CI 0.66–0.75)] had significantly higher AUC for predicting MetS in males, whereas VAI [AUC 0.693 (95% CI 0.64–0.75)], WHtR [AUC 0.649 (95% CI 0.59–0.70)], WC [AUC 0.646 (95% CI 0.59–0.61)], BMI [AUC 0.641 (95% CI 0.59–0.69)], and MUAC [AUC 0.626 (95% CI 0.57–0.68)] had significantly higher AUC for predicting MetS in females. The AUC of NC for males was 0.656 (95% CI 0.61–0.70), while that for females was 0.580 (95% CI 0.52–0.64). The optimal cutoff points for all anthropometric indices exhibited a high degree of sensitivity and specificity in predicting the onset of MetS.

Conclusion: BMI, WC, WHtR, and VAI were the most important anthropometric predictors for MetS in apparently healthy individuals of Pakistan, while BSI was found to be the weakest indicator.
Original languageEnglish
Article number1223424
Number of pages11
JournalFrontiers in Endocrinology
Volume14
DOIs
Publication statusPublished - 9 Oct 2023

Bibliographical note

Funding Information:
The study received support from the Sindh Higher Education Commission of Pakistan (Project code: 299), which contributed to the provision of essential consumables, supplies, facilitation of fieldwork, and the printing of necessary materials. Acknowledgments

Publisher Copyright:
Copyright © 2023 Adil, Musa, Uddin, Shafique, Khan and Islam.

Keywords

  • metabolic syndrome
  • anthropometry
  • predictive value of tests
  • mass screening
  • Pakistan anthropometric indices
  • Pakistan

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism

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