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Clinical Research

Association between BMI-based metabolic phenotypes and prevalence of intracranial atherosclerotic stenosis: a cross-sectional study

International Journal of Obesity (2024)Cite this article

Subjects

Abstract

Background

Obesity and metabolic syndrome (MetS) have been acknowledged to commonly co-exist and lead to increased risks of stroke, whereas the association between various BMI-based metabolic phenotypes and development of intracranial atherosclerotic stenosis (ICAS) remained controversial.

Methods

A total of 5355 participants were included from the Asymptomatic Polyvascular Abnormalities Community (APAC) study. Participants were categorized into six groups according to their body mass index (BMI) and MetS status. ICAS was assessed using transcranial Doppler (TCD) Ultrasonography. Logistic regression was employed to evaluate the association between BMI-based metabolic phenotypes and ICAS.

Results

704 participants were diagnosed with ICAS. Compared to the metabolic healthy normal weight (MH-NW) group, the metabolic unhealthy normal weight (MUH-NW) group demonstrated a higher risk of ICAS (full-adjusted odds ratio [OR], 1.91; 95% confidence interval [CI], 1.42–2.57), while no significant association was observed in the metabolic unhealthy obesity (MUO) group (full-adjusted OR, 1.07; 95% CI, 0.70–1.65) and other metabolic healthy groups regardless of BMI. The results were consistent across gender, age, smoking, alcohol intake, and physical activity subgroups.

Conclusion

The present study suggested that MUH-NW individuals had a significant association with increased risk of ICAS compared with MH-NW individuals.

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Fig. 1: The flowchart of the study.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Aune D, Sen A, Norat T, Janszky I, Romundstad P, Tonstad S, et al. Body Mass Index, Abdominal Fatness, and Heart Failure Incidence and Mortality: A Systematic Review and Dose-Response Meta-Analysis of Prospective Studies. Circulation. 2016;133:639–49.

    Article  PubMed  Google Scholar 

  2. Collaboration NCDRF. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants. Lancet. 2016;387:1377–96.

    Article  Google Scholar 

  3. Mongraw-Chaffin M, Foster MC, Kalyani RR, Vaidya D, Burke GL, Woodward M, et al. Obesity Severity and Duration Are Associated With Incident Metabolic Syndrome: Evidence Against Metabolically Healthy Obesity From the Multi-Ethnic Study of Atherosclerosis. J Clin Endocrinol Metab. 2016;101:4117–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, et al. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol. 2010;56:1113–32.

    Article  PubMed  Google Scholar 

  5. Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX, et al. Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss: an update of the 1997 American Heart Association Scientific Statement on Obesity and Heart Disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation. 2006;113:898–918.

    Article  PubMed  Google Scholar 

  6. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants. Lancet. 2011;377:557–67.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet. 2005;365:1415–28.

    Article  CAS  PubMed  Google Scholar 

  8. Ma YH, Leng XY, Dong Y, Xu W, Cao XP, Ji X, et al. Risk factors for intracranial atherosclerosis: A systematic review and meta-analysis. Atherosclerosis. 2019;281:71–7.

    Article  CAS  PubMed  Google Scholar 

  9. Liu L, Shi Z, Ji X, Zhang W, Luan J, Zahr T, et al. Adipokines, adiposity, and atherosclerosis. Cell Mol Life Sci. 2022;79:272.

    Article  CAS  PubMed  Google Scholar 

  10. White H, Boden-Albala B, Wang C, Elkind MS, Rundek T, Wright CB, et al. Ischemic stroke subtype incidence among whites, blacks, and Hispanics: the Northern Manhattan Study. Circulation. 2005;111:1327–31.

    Article  PubMed  Google Scholar 

  11. Wong LK. Global burden of intracranial atherosclerosis. Int J Stroke. 2006;1:158–9.

    Article  PubMed  Google Scholar 

  12. Wang Y, Zhao X, Liu L, Soo YO, Pu Y, Pan Y, et al. Prevalence and outcomes of symptomatic intracranial large artery stenoses and occlusions in China: the Chinese Intracranial Atherosclerosis (CICAS) Study. Stroke. 2014;45:663–9.

    Article  PubMed  Google Scholar 

  13. Wang A, Wu J, Zhou Y, Guo X, Luo Y, Wu S, et al. Measures of adiposity and risk of stroke in China: a result from the Kailuan study. PLoS One. 2013;8:e61665.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Zhou Y, Li Y, Xu L, Xu J, Wang A, Gao X, et al. Asymptomatic polyvascular abnormalities in community (APAC) study in China: objectives, design and baseline characteristics. PLoS One. 2013;8:e84685.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Fan C, Zhang Q, Zhang S, Wang A, Bi X, Chen S, et al. Association of Newly Found Asymptomatic Intracranial Artery Stenosis and Ideal Cardiovascular Health Metrics in Chinese Community Population. Sci Rep. 2020;10:7200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. WHO Consultation on Obesity (1999: Geneva, Switzerland) & WorldHealth Organization. Obesity: preventing and managing the global epidemic: report of a WHO consultation. World Health Organization; 2000. https://iris.who.int/handle/10665/42330.

  17. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–5.

    Article  CAS  PubMed  Google Scholar 

  18. Chen C, Lu FC. The guidelines for prevention and control of overweight and obesity in Chinese adults. Biomed Environ Sci. 2004;17:1–36.

    PubMed  Google Scholar 

  19. Hinnouho GM, Czernichow S, Dugravot A, Batty GD, Kivimaki M, Singh-Manoux A. Metabolically healthy obesity and risk of mortality: does the definition of metabolic health matter? Diabetes Care. 2013;36:2294–300.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Carmelli D, Swan GE, Bliwise DL. Relationship of 30-year changes in obesity to sleep-disordered breathing in the Western Collaborative Group Study. Obes Res. 2000;8:632–7.

    Article  CAS  PubMed  Google Scholar 

  21. Kramer H, Gutierrez OM, Judd SE, Muntner P, Warnock DG, Tanner RM, et al. Waist Circumference, Body Mass Index, and ESRD in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study. Am J Kidney Dis. 2016;67:62–9.

    Article  PubMed  Google Scholar 

  22. Fan J, Song Y, Chen Y, Hui R, Zhang W. Combined effect of obesity and cardio-metabolic abnormality on the risk of cardiovascular disease: a meta-analysis of prospective cohort studies. Int J Cardiol. 2013;168:4761–8.

    Article  PubMed  Google Scholar 

  23. Putra ICS, Kamarullah W, Prameswari HS, Pramudyo M, Iqbal M, Achmad C, et al. Metabolically unhealthy phenotype in normal weight population and risk of mortality and major adverse cardiac events: A meta-analysis of 41 prospective cohort studies. Diabetes Metab Syndr. 2022;16:102635.

    Article  CAS  PubMed  Google Scholar 

  24. Forlivesi S, Cappellari M, Bonetti B. Obesity paradox and stroke: a narrative review. Eat Weight Disord. 2021;26:417–23.

    Article  PubMed  Google Scholar 

  25. Zhao L, Du W, Zhao X, Liu L, Wang C, Wang Y, et al. Favorable functional recovery in overweight ischemic stroke survivors: findings from the China National Stroke Registry. J Stroke Cerebrovasc Dis. 2014;23:e201–6.

    Article  PubMed  Google Scholar 

  26. Andersen KK, Olsen TS. The obesity paradox in stroke: lower mortality and lower risk of readmission for recurrent stroke in obese stroke patients. Int J Stroke. 2015;10:99–104.

    Article  PubMed  Google Scholar 

  27. Xu J, Wang A, Meng X, Jing J, Wang Y, Wang Y, et al. Obesity-Stroke Paradox Exists in Insulin-Resistant Patients But Not Insulin Sensitive Patients. Stroke. 2019;50:1423–9.

    Article  CAS  PubMed  Google Scholar 

  28. Vemmos K, Ntaios G, Spengos K, Savvari P, Vemmou A, Pappa T, et al. Association between obesity and mortality after acute first-ever stroke: the obesity-stroke paradox. Stroke. 2011;42:30–6.

    Article  PubMed  Google Scholar 

  29. Wang Y, Li J, Johnston SC, Hankey GJ, Easton JD, Meng X, et al. Colchicine in High-risk Patients with Acute Minor-to-moderate Ischemic Stroke or Transient Ischemic Attack (CHANCE-3): Rationale and design of a multicenter randomized placebo-controlled trial. Int J Stroke. 2023;18:873–8.

    Article  PubMed  Google Scholar 

  30. Rodriguez-Castro E, Rodriguez-Yanez M, Arias-Rivas S, Santamaria-Cadavid M, Lopez-Dequidt I, Hervella P, et al. Obesity Paradox in Ischemic Stroke: Clinical and Molecular Insights. Transl Stroke Res. 2019;10:639–49.

    Article  CAS  PubMed  Google Scholar 

  31. Quinones-Ossa GA, Lobo C, Garcia-Ballestas E, Florez WA, Moscote-Salazar LR, Agrawal A. Obesity and Stroke: Does the Paradox Apply for Stroke? Neurointervention. 2021;16:9–19.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Shu MJ, Zhai FF, Zhang DD, Han F, Zhou L, Ni J, et al. Metabolic syndrome, intracranial arterial stenosis and cerebral small vessel disease in community-dwelling populations. Stroke Vasc Neurol. 2021;6:589–94.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Choi KM, Cho HJ, Choi HY, Yang SJ, Yoo HJ, Seo JA, et al. Higher mortality in metabolically obese normal-weight people than in metabolically healthy obese subjects in elderly Koreans. Clin Endocrinol. 2013;79:364–70.

    Article  Google Scholar 

  34. Despres JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature. 2006;444:881–7.

    Article  CAS  PubMed  Google Scholar 

  35. Stefan N, Fritsche A, Schick F, Häring H-U. Phenotypes of prediabetes and stratification of cardiometabolic risk. The Lancet. Diabetes Endocrinol. 2016;4:789–98.

    Google Scholar 

  36. Stefan N, Kantartzis K, Machann J, Schick F, Thamer C, Rittig K, et al. Identification and Characterization of Metabolically Benign Obesity in Humans. Arch Intern Med. 2008;168:1609–16.

    Article  PubMed  Google Scholar 

  37. Fabbrini E, Magkos F, Mohammed BS, Pietka T, Abumrad NA, Patterson BW, et al. Intrahepatic fat, not visceral fat, is linked with metabolic complications of obesity. Proc Natl Acad Sci USA. 2009;106:15430–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank all the participants of the APAC study for their invaluable contributions.

Funding

This work was supported by National Key Research and Development Program of China (2022YFC3600600), Training Fund for Open Projects at Clinical Institutes and Departments of Capital Medical University (CCMU2022ZKYXZ009), Beijing Natural Science Foundation Haidian original innovation joint fund (L222123), Fund for Young Talents of Beijing Medical Management Center (QML20230505), and the high-level public health talents (xuekegugan-02-47).

Author information

Author notes

  1. These authors contributed equally: Xue Xia, Xinsheng Han, Guangxin Xia.

Authors and Affiliations

  1. Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China

    Xue Xia & Anxin Wang

  2. Department of Clinical Epidemiology and Clinical Trial, Capital Medical University, 100070, Beijing, China

    Xue Xia & Anxin Wang

  3. Beijing Municipal Key Laboratory of Clinical Epidemiology, 100070, Beijing, China

    Xue Xia & Anxin Wang

  4. Department of Neurology, Kaifeng Central Hospital, Xinxiang Medical University, Kaifeng, 475000, China

    Xinsheng Han & Guangxin Xia

  5. Henan Key Laboratory of Neuromuscular Pathology, Kaifeng Central Hospital, Kaifeng, 475000, China

    Xinsheng Han

  6. Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China

    Xingquan Zhao

  7. China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China

    Xingquan Zhao

  8. Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, 100070, Beijing, China

    Xingquan Zhao

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Contributions

Xinsheng Han, Guangxin Xia, Xingquan Zhao, and Anxin Wang designed the study. Xingquan Zhao and Anxin Wang recruited participants and conducted the study. Xue Xia and Anxin Wang conducted the statistical analysis. Xue Xia and Guangxin Xia wrote the first draft of the manuscript.

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Correspondence to Xingquan Zhao or Anxin Wang.

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Xia, X., Han, X., Xia, G. et al. Association between BMI-based metabolic phenotypes and prevalence of intracranial atherosclerotic stenosis: a cross-sectional study. Int J Obes (2024). https://doi.org/10.1038/s41366-024-01521-7

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