Validity of continuous metabolic syndrome score for predicting metabolic syndrome; a systematic review and meta-analysis

Journal of Diabetes & Metabolic Disorders (2021)Cite this article

Abstract

Background

Nowadays, use of continuous metabolic syndrome (cMetS) score has been suggested to improve recognition of metabolic syndrome (MetS). The aim of this study was to evaluate the validity of cMetS scores for predicting MetS.

Methods

We searched the electronic databases included MEDLINE/PubMed, Embase, ISI Web of Science, and Scopus from 1 January 1980 to 30 September 2020. Observational studies on participants with different cMetS scores were included in this meta-analysis. The sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR) and diagnostic odds ratio (DOR) with 95% CI were calculated.

Results

Ten studies involving a total of 25,073 participants were included. All studies had cross-sectional design. The pooled sensitivity and specificity of cMetS scores for predicting MetS were 0.90 (95% CI: 0.83 to 0.95) and 0.86 (95% CI: 0.83 to 0.89), respectively. Moreover, cMetS scores had the pooled LR+ of 6.5 (95% CI: 5.0 to 8.6), and a pooled (LR-) of 0.11 (95% CI: 0.063 to 0.21). The pooled DOR of cMetS scores to predict MetS were 57 (95% CI: 26 to 127).

Conclusions

The high sensitivity and specificity of cMetS scores indicates that it has a high accuracy to predict the risk of MetS. Furthermore, the cMetS scores has a good ability to rule out healthy people.

Study registration

This study was registered as PROSPERO CRD42020157273.

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Acknowledgements

The authors are thankful of Emam Ali clinical research development unit for their assistance.

Availability of data and materials

Please contact corresponding author for data requests.

Funding

This study was funded and designed by Alborz University of Medical Sciences.

Author information

Affiliations

  1. Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran

    Maryam Khazdouz & Motahareh Hasani

  2. Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran

    Sanaz Mehranfar

  3. Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

    Hanieh-Sadat Ejtahed

  4. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

    Hanieh-Sadat Ejtahed

  5. Non-communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

    Shirin Djalalinia

  6. Deputy of Research and Technology, Ministry of Health and Medical Education, Tehran, Iran

    Shirin Djalalinia

  7. Probiotic Research Center, Alborz University of Medical Sciences, Karaj, Iran

    Armita Mahdavi Gorabi

  8. Social Determinants of Health Research Center, Alborz University of Medical Sciences, Karaj, Iran

    Mohammad Esmaeili-Abdar

  9. Department of Cardiology, School of Medicine, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran

    Shahrokh Karbalahi Saleh

  10. Elderly Health Research Center, Endocrinology and Metabolism Population Science Institute, Tehran University of Medical Sciences, Tehran, Iran

    Seyed Masoud Arzaghi

  11. Hematopoietic Stem Cell Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Hoda Zahedi

  12. Hematology, Oncology and Stem Cell Transplantation Research Center, Research Institute for Oncology, Hematology and Cell Therapy, Tehran University of Medical Sciences, Tehran, Iran

    Amir Kasaeian

  13. Digestive Diseases Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran

    Amir Kasaeian

  14. Inflammation Research Center, Tehran University of Medical Sciences, Tehran, Iran

    Amir Kasaeian

  15. Non-communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran

    Mostafa Qorbani

  16. Chronic Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

    Mostafa Qorbani

Authors
  1. Maryam Khazdouz
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  2. Motahareh Hasani
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  4. Hanieh-Sadat Ejtahed
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Contributions

MK, MH, SM, HSE, SD, SKS, AMG, MQ, AK design and data gathering, MQ, SD, MEA, SKS, AK design and revision, MQ, AK data analysis. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Amir Kasaeian or Mostafa Qorbani.

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Ethics approval and consent to participate

The Research and Ethics council of Alborz University of Medical Sciences approved the study.

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Not applicable.

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The authors declare that they have no competing interests.

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Appendices

Appendix 1

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figure6

Graph quality assessment subgroup

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Fig. 7
figure7

Graph population subgroup

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Fig. 8
figure8

Graph cMetS subsets

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Appendix 2

Fig. 9
figure9

Graph population subgroup

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Khazdouz, M., Hasani, M., Mehranfar, S. et al. Validity of continuous metabolic syndrome score for predicting metabolic syndrome; a systematic review and meta-analysis. J Diabetes Metab Disord (2021). https://doi.org/10.1007/s40200-021-00771-w

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Keywords

  • Continuous metabolic syndrome score (cMetS)
  • Metabolic syndrome
  • Sensitivity