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Effects of age on polycythemia, cardiometabolic risk and their associations in middle-aged men

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Abstract

Background

Polycythemia has been reported to be associated with cardiometabolic risk factors. However, it remains to be determined whether age affects their associations.

Methods

The subjects were 11,261 men at ages of 30 ~ 65 years who had received annual health checkup examinations. They were divided by age into four groups of 30 ~ 39, 40 ~ 49, 50 ~ 59 and 60 ~ 65 years. Variables related to polycythemia and cardiometabolic risk and their associations were compared in the different age groups.

Results

The prevalences of polycythemia and metabolic syndrome tended to be lower and higher, respectively, with an increase of age. Odds ratios (ORs) of subjects with vs. subjects without polycythemia for high LDL-C/HDL-C ratio and metabolic syndrome were significantly high in the age group of 30 ~ 39 years when compared with the reference level (OR with 95% confidence interval: 3.21 [2.35 ~ 4.37] [high LDL-C/HDL-C ratio] and 3.49 [2.38 ~ 5.12] [metabolic syndrome]) and tended to be lower with an increase of age (60 ~ 65 years, OR with 95% confidence interval: 1.36 [0.63 ~ 2.93] [high LDL-C/HDL-C ratio] and 1.88 [1.16 ~ 3.03] [metabolic syndrome]).

Conclusion

The prevalence of polycythemia was higher and its associations with cardiometabolic risk such as high LDL-C/HDL-C ratio and metabolic syndrome were stronger in the youngest group than in the older groups. The results suggest that early detection and correction of polycythemia are more effective than its later correction for prevention of cardiovascular disease in middle-aged men.

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Data Availability

The data that support the findings of this study are available from the corresponding author (IW) upon reasonable request.

Code Availability

Not applicable.

References

  1. Cinar Y, Demir G, Paç M, Cinar AB. Effect of hematocrit on blood pressure via hyperviscosity. Am J Hypertens. 1999;12:739–43.

    Article  CAS  PubMed  Google Scholar 

  2. Malek AM, Alper SL, Izumo S. Hemodynamic shear stress and its role in atherosclerosis. J Am Med Assoc. 1999;282:2035–42.

    Article  CAS  Google Scholar 

  3. Wakabayashi I. Associations between polycythemia and cardiometabolic risk factors in middle-aged men. Clin Chim Acta. 2022;531:248–53.

    Article  CAS  PubMed  Google Scholar 

  4. Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127:2391–405.

    Article  CAS  PubMed  Google Scholar 

  5. Moulard O, Mehta J, Fryzek J, Olivares R, Iqbal U, Mesa RA. Epidemiology of myelofibrosis, essential thrombocythemia, and polycythemia vera in the European Union. Eur J Haematol. 2014;92:289–97.

    Article  PubMed  Google Scholar 

  6. Mehta J, Wang H, Iqbal SU, Mesa R. Epidemiology of myeloproliferative neoplasms in the United States. Leuk Lymphoma. 2014;55:595–600.

    Article  PubMed  Google Scholar 

  7. Souresho H, Mgerian M, Havican S, Suniega E, Gambrill C. A practical approach to polycythemia in the outpatient setting and its importance. Cureus. 2021;13:e19368.

    PubMed  PubMed Central  Google Scholar 

  8. Lakatta EG, Levy D. Arterial and cardiac aging: major shareholders in cardiovascular disease enterprises: Part I: aging arteries: a “set up” for vascular disease. Circulation. 2003;107:139–46.

    Article  PubMed  Google Scholar 

  9. Sniderman AD, Furberg CD. Age as a modifiable risk factor for cardiovascular disease. Lancet. 2008;371(9623):1547–9.

    Article  PubMed  Google Scholar 

  10. Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, et al, American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics-2020 update: A report from the American Heart Association. Circulation. 2020;141:e139–596.

    Article  PubMed  Google Scholar 

  11. Cheng S, Xanthakis V, Sullivan LM, Vasan RS. Blood pressure tracking over the adult life course: patterns and correlates in the Framingham heart study. Hypertension. 2012;60:1393–9.

    Article  CAS  PubMed  Google Scholar 

  12. Jack L Jr, Boseman L, Vinicor F. Aging Americans and diabetes. A public health and clinical response. Geriatrics. 2004;59:14–7.

    PubMed  Google Scholar 

  13. Wang M, Liu M, Li F, Guo C, Liu Z, Pan Y, et al. Gender heterogeneity in dyslipidemia prevalence, trends with age and associated factors in middle age rural Chinese. Lipids Health Dis. 2020;19:135.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wakabayashi I. Age-related change in relationship between body-mass index, serum sialic acid, and atherogenic risk factors. J Atheroscler Thromb. 1998;5:60–5.

    Article  CAS  PubMed  Google Scholar 

  15. Wakabayashi I, Daimon T. Age-dependent decline of association between obesity and hyperglycemia in men and women. Diabetes Care. 2012;35:175–7.

    Article  PubMed  Google Scholar 

  16. Wakabayashi I. Influence of age and gender on triglycerides-to-HDL-cholesterol ratio (TG/HDL ratio) and its association with adiposity index. Arch Gerontol Geriatr. 2012;55:729–34.

    Article  CAS  PubMed  Google Scholar 

  17. Wakabayashi I. Relationships of body mass index with blood pressure and serum cholesterol concentrations at different ages. Aging Clin Exp Res. 2004;16:461–6.

    Article  PubMed  Google Scholar 

  18. Kannel WB. Lipids, diabetes, and coronary heart disease: insights from the Framingham Study. Am Heart J. 1985;110:1100–7.

    Article  CAS  PubMed  Google Scholar 

  19. Wakabayashi I, Daimon T. The “cardiometabolic index” as a new marker determined by adiposity and blood lipids for discrimination of diabetes mellitus. Clin Chim Acta. 2015;438:274–8.

    Article  CAS  PubMed  Google Scholar 

  20. Anonymous. Metabolic Syndrome-Definition and Diagnostic Criteria in Japan. J Jpn Soc Intern Med. 2005;94:794–809. (in Japanese).

    Google Scholar 

  21. Kashiwagi A, Kasuga M, Araki E, Oka Y, Hanafusa T, Ito H, et al, Committee on the Standardization of Diabetes Mellitus - Related Laboratory Testing of Japan Diabetes Society. International clinical harmonization of glycated hemoglobin in Japan: From Japan Diabetes Society to National Glycohemoglobin Standardization Program values. J Diabetes Investig. 2012;3:39–40.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al.; International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity. 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: 1640–45.

  23. Hsieh SD, Muto T. Metabolic syndrome in Japanese men and women with special reference to the anthropometric criteria for the assessment of obesity: Proposal to use the waist-to-height ratio. Prev Med. 2006;42:135–9.

    Article  PubMed  Google Scholar 

  24. Flack JM, Adekola B. Blood pressure and the new ACC/AHA hypertension guidelines. Trends Cardiovasc Med. 2020;30:160–4.

    Article  PubMed  Google Scholar 

  25. Teramoto T, Sasaki J, Ishibashi S, Birou S, Daida H, Dohi S, et al. Japan Atherosclerosis Society. Executive summary of the Japan Atherosclerosis Society (JAS) guidelines for the diagnosis and prevention of atherosclerotic cardiovascular diseases in Japan – 2012 version. J Atheroscler Thromb. 2013;20:517–23.

    Article  PubMed  Google Scholar 

  26. Anonimous, American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33(Suppl 1):62–9.

    Google Scholar 

  27. Wouters HJCM, Mulder R, van Zeventer IA, Schuringa JJ, van der Klauw MM, van der Harst P, et al. Erythrocytosis in the general population: clinical characteristics and association with clonal hematopoiesis. Blood Adv. 2020;4:6353–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Craig WY, Palomaki GE, Haddow JE. Cigarette smoking and serum lipid and lipoprotein concentrations: an analysis of published data. BMJ. 1989;298:784–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Drager LF, Togeiro SM, Polotsky VY, Lorenzi-Filho G. Obstructive sleep apnea: a cardiometabolic risk in obesity and the metabolic syndrome. J Am Coll Cardiol. 2013;62:569–76.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Sasaki Y, Ikeda Y, Miyauchi T, Uchikado Y, Akasaki Y, Ohishi M. Estrogen-SIRT1 axis plays a pivotal role in protecting arteries against menopause-induced senescence and atherosclerosis. J Atheroscler Thromb. 2020;27:47–59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

This work was supported by the Grant-in-Aid for Scientific Research (No. 21H03386) from the Japan Society for the Promotion of Science.

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Contributions

Conceptualization, analysis, writing, and visualization, IW.

Corresponding author

Correspondence to Ichiro Wakabayashi.

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Conflict of interest

The author declares no conflict of interest.

Ethical approval

The database used in this study was supplied from a local health checkup system without individual identification, and no informed consent was obtained from each subject. This study was approved by the Ethics Committee of Yamagata University School of Medicine (No. 112 from April 2005 to March 2006, approved on March 13, 2006) and the Hyogo College of Medicine Ethics Committee (No. 3003 in 2020).

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Wakabayashi, I. Effects of age on polycythemia, cardiometabolic risk and their associations in middle-aged men. J Diabetes Metab Disord 22, 287–295 (2023). https://doi.org/10.1007/s40200-022-01130-z

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  • DOI: https://doi.org/10.1007/s40200-022-01130-z

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