Cardiometabolic index: a new tool for screening the metabolically obese normal weight phenotype

doi:10.1007/s40618-020-01417-z

. 2021 Jun;44(6):1253-1261.

doi: 10.1007/s40618-020-01417-z. Epub 2020 Sep 9.

Cardiometabolic index: a new tool for screening the metabolically obese normal weight phenotype

X Liu^#¹, Q Wu^#¹, G Yan¹, J Duan¹, Z Chen², P Yang², N L Bragazzi³, Y Lu^{4

5

6}, H Yuan^{7

8

9}

Affiliations

¹ Center of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, 138 Tong-Zi-Po Road, Changsha, 410013, Hunan, China.
² Department of Health Examination Center, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
³ Centre for Disease Modelling, York University, Toronto, ON, Canada.
⁴ Center of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, 138 Tong-Zi-Po Road, Changsha, 410013, Hunan, China. luyao0719@163.com.
⁵ Key Laboratory of Medical Information Research, Central South University, Changsha, Hunan, China. luyao0719@163.com.
⁶ National-Local Joint Engineering Laboratory of Drug Clinical Evaluation Technology, Changsha, Hunan, China. luyao0719@163.com.
⁷ Center of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, 138 Tong-Zi-Po Road, Changsha, 410013, Hunan, China. yuanhong01@csu.edu.cn.
⁸ Key Laboratory of Medical Information Research, Central South University, Changsha, Hunan, China. yuanhong01@csu.edu.cn.
⁹ National-Local Joint Engineering Laboratory of Drug Clinical Evaluation Technology, Changsha, Hunan, China. yuanhong01@csu.edu.cn.

^# Contributed equally.

PMID: 32909175
DOI: 10.1007/s40618-020-01417-z

Cardiometabolic index: a new tool for screening the metabolically obese normal weight phenotype

X Liu et al. J Endocrinol Invest. 2021 Jun.

. 2021 Jun;44(6):1253-1261.

doi: 10.1007/s40618-020-01417-z. Epub 2020 Sep 9.

Authors

X Liu^#¹, Q Wu^#¹, G Yan¹, J Duan¹, Z Chen², P Yang², N L Bragazzi³, Y Lu^{4

5

6}, H Yuan^{7

8

9}

Affiliations

¹ Center of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, 138 Tong-Zi-Po Road, Changsha, 410013, Hunan, China.
² Department of Health Examination Center, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
³ Centre for Disease Modelling, York University, Toronto, ON, Canada.
⁴ Center of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, 138 Tong-Zi-Po Road, Changsha, 410013, Hunan, China. luyao0719@163.com.
⁵ Key Laboratory of Medical Information Research, Central South University, Changsha, Hunan, China. luyao0719@163.com.
⁶ National-Local Joint Engineering Laboratory of Drug Clinical Evaluation Technology, Changsha, Hunan, China. luyao0719@163.com.
⁷ Center of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, 138 Tong-Zi-Po Road, Changsha, 410013, Hunan, China. yuanhong01@csu.edu.cn.
⁸ Key Laboratory of Medical Information Research, Central South University, Changsha, Hunan, China. yuanhong01@csu.edu.cn.
⁹ National-Local Joint Engineering Laboratory of Drug Clinical Evaluation Technology, Changsha, Hunan, China. yuanhong01@csu.edu.cn.

^# Contributed equally.

PMID: 32909175
DOI: 10.1007/s40618-020-01417-z

Abstract

Purpose: People with the metabolically obese normal weight (MONW) phenotype are considered as an extremely high-risk group for unfavorable health consequences, but they are frequently undetected due to deceptive body mass index (BMI) and complex assessment. This study aimed to explore the clinical usefulness of cardiometabolic index (CMI) in identifying MONW individuals.

Methods: This cross-sectional study involved a total of 47,683 normal-weight subjects aged ≥ 18 years. Participants underwent anthropometrics, routine biochemical tests, and questionnaires for a full evaluation of the metabolic profile. The odds ratio (OR) of CMI and MONW phenotype was determined by the Logistic regression models and the diagnostic accuracy of CMI was evaluated by the receiver operating characteristic (ROC) curve analysis.

Results: The prevalence of MONW phenotype was 11.0%. After multivariate adjustment, the ORs for MONW in the highest compared with the lowest quartile of CMI was 71.20 (95% CI 55.19-91.86), and 1-SD increment of CMI brought a 54% additional risk. In ROC analysis, compared with BMI and waist circumference, CMI showed superior performance for identifying MONW individuals with an AUC of 0.853 (95% CI 0.847-0.860) in men and 0.912 (95% CI 0.906-0.918) in women, respectively. Moreover, CMI exhibited the highest diagnostic accuracy in younger age groups (aged 18-34 for men; aged 18-34 and 35-44 for women), in which AUCs surpassed 0.9 in both sexes.

Conclusions: CMI could be served as a valuable indicator to identify MONW phenotype of Chinese adults, particularly for young people.

Keywords: Cardiometabolic index; Metabolically healthy normal weight; Metabolically obese normal weight.

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References

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[1] Di Angelantonio E, Bhupathiraju ShN, Wormser D, Gao P, Kaptoge S, Berrington de Gonzalez A, Cairns BJ, Huxley R, Jackson ChL, Joshy G, Lewington S, Manson JE, Murphy N, Patel AV, Samet JM, Woodward M, Zheng W, Zhou M, Bansal N, Barricarte A, Carter B, Cerhan JR, Smith GD, Fang X, Franco OH, Green J, Halsey J, Hildebrand JS, Jung KJ, Korda RJ, McLerran DF, Moore SC, O'Keeffe LM, Paige E, Ramond A, Reeves GK, Rolland B, Sacerdote C, Sattar N, Sofianopoulou E, Stevens J, Thun M, Ueshima H, Yang L, Yun YD, Willeit P, Banks E, Beral V, Chen Z, Gapstur SM, Gunter MJ, Hartge P, Jee SH, Lam TH, Peto R, Potter JD, Willett WC, Thompson SG, Danesh J, Hu FB (2016) Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet (Lond, Engl) 388(10046):776–786. https://doi.org/10.1016/s0140-6736(16)30175-1 - DOI

[2] Di Angelantonio E, Bhupathiraju ShN, Wormser D, Gao P, Kaptoge S, Berrington de Gonzalez A, Cairns BJ, Huxley R, Jackson ChL, Joshy G, Lewington S, Manson JE, Murphy N, Patel AV, Samet JM, Woodward M, Zheng W, Zhou M, Bansal N, Barricarte A, Carter B, Cerhan JR, Smith GD, Fang X, Franco OH, Green J, Halsey J, Hildebrand JS, Jung KJ, Korda RJ, McLerran DF, Moore SC, O'Keeffe LM, Paige E, Ramond A, Reeves GK, Rolland B, Sacerdote C, Sattar N, Sofianopoulou E, Stevens J, Thun M, Ueshima H, Yang L, Yun YD, Willeit P, Banks E, Beral V, Chen Z, Gapstur SM, Gunter MJ, Hartge P, Jee SH, Lam TH, Peto R, Potter JD, Willett WC, Thompson SG, Danesh J, Hu FB (2016) Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet (Lond, Engl) 388(10046):776–786. https://doi.org/10.1016/s0140-6736(16)30175-1 - DOI

[3] Wang B, Zhuang R, Luo X, Yin L, Pang C, Feng T, You H, Zhai Y, Ren Y, Zhang L, Li L, Zhao J, Hu D (2015) Prevalence of metabolically healthy obese and metabolically obese but normal weight in adults worldwide: a meta-analysis. Horm Metab Res 47(11):839–845. https://doi.org/10.1055/s-0035-1559767 - DOI - PubMed

[4] Wang B, Zhuang R, Luo X, Yin L, Pang C, Feng T, You H, Zhai Y, Ren Y, Zhang L, Li L, Zhao J, Hu D (2015) Prevalence of metabolically healthy obese and metabolically obese but normal weight in adults worldwide: a meta-analysis. Horm Metab Res 47(11):839–845. https://doi.org/10.1055/s-0035-1559767 - DOI - PubMed

[5] Stefan N, Schick F, Haring HU (2017) Causes, characteristics, and consequences of metabolically unhealthy normal weight in humans. Cell Metab 26(2):292–300. https://doi.org/10.1016/j.cmet.2017.07.008 - DOI - PubMed

[6] Stefan N, Schick F, Haring HU (2017) Causes, characteristics, and consequences of metabolically unhealthy normal weight in humans. Cell Metab 26(2):292–300. https://doi.org/10.1016/j.cmet.2017.07.008 - DOI - PubMed

[7] Lee SH, Ha HS, Park YJ, Lee JH, Yim HW, Yoon KH, Kang MI, Lee WC, Son HY, Park YM, Kwon HS (2011) Identifying metabolically obese but normal-weight (MONW) individuals in a nondiabetic Korean population: the Chungju Metabolic disease Cohort (CMC) study. Clin Endocrinol 75(4):475–481. https://doi.org/10.1111/j.1365-2265.2011.04085.x - DOI

[8] Lee SH, Ha HS, Park YJ, Lee JH, Yim HW, Yoon KH, Kang MI, Lee WC, Son HY, Park YM, Kwon HS (2011) Identifying metabolically obese but normal-weight (MONW) individuals in a nondiabetic Korean population: the Chungju Metabolic disease Cohort (CMC) study. Clin Endocrinol 75(4):475–481. https://doi.org/10.1111/j.1365-2265.2011.04085.x - DOI

[9] Kramer CK, Zinman B, Retnakaran R (2013) Are metabolically healthy overweight and obesity benign conditions?: a systematic review and meta-analysis. Ann Intern Med 159(11):758–769. https://doi.org/10.7326/0003-4819-159-11-201312030-00008 - DOI - PubMed

[10] Kramer CK, Zinman B, Retnakaran R (2013) Are metabolically healthy overweight and obesity benign conditions?: a systematic review and meta-analysis. Ann Intern Med 159(11):758–769. https://doi.org/10.7326/0003-4819-159-11-201312030-00008 - DOI - PubMed

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Cardiometabolic index: a new tool for screening the metabolically obese normal weight phenotype

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Cardiometabolic index: a new tool for screening the metabolically obese normal weight phenotype

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