Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Association of childhood anthropometric measurements and laboratory parameters with high blood pressure in young adults

Hypertension Research volume 44, pages 711–719 (2021)Cite this article

Abstract

Early intervention to manage high blood pressure (BP) in young adulthood is a promising approach for the prevention of future cardiovascular diseases. We aimed to examine the ability of childhood health information to predict the incidence of young adults with high BP. This cohort study included baseline clinical data of Japanese individuals aged 12–13 years. A total of 1129 participants were followed up for an average of 8.6 years. We examined the association of childhood variables consisting of body weight, body mass index, systolic BP, white blood cell count, red blood cell count, hemoglobin, hematocrit, platelet count, uric acid, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the development of high BP defined as ≥120/80 mmHg at 18–22 years old. At follow-up, the prevalence of high BP was 42.2% in men and 7.7% in women. Young men with high BP had childhood baseline characteristics that included higher body weight, body mass index, systolic BP, red blood cell count, hemoglobin, hematocrit, and uric acid than normotensive men. Young women with high BP had higher body weight, systolic BP, and uric acid at baseline. Multivariable logistic regression analysis revealed that a model including body weight, systolic BP, hematocrit, and uric acid had the highest predictive power (AUC 0.65 [95% CI, 0.62–0.69]) for men, and a model including body weight, systolic BP, and uric acid had the highest predictive power (AUC 0.70 [95% CI, 0.58–0.81]) for women. Comprehensive childhood health information contributes to the prediction of high BP in young adults.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390:1345–422.

    Article  Google Scholar 

  2. Rapsomaniki E, Timmis A, George J, Pujades-Rodriguez M, Shah AD, Denaxas S, et al. Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1.25 million people. Lancet. 2014;383:1899–911.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Whelton PK, Carey RM, Aronow WS, Casey DE Jr., Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2018;138:e484–594.

    PubMed  Google Scholar 

  4. Qi Y, Han X, Zhao D, Wang W, Wang M, Sun J, et al. Long-term cardiovascular risk associated with stage 1 hypertension defined by the 2017 ACC/AHA Hypertension Guideline. J Am Coll Cardiol. 2018;72:1201–10.

    Article  PubMed  Google Scholar 

  5. Yano Y, Reis JP, Colangelo LA, Shimbo D, Viera AJ, Allen NB, et al. Association of blood pressure classification in young adults using the 2017 American College of Cardiology/American Heart Association Blood Pressure Guideline with cardiovascular events later in life. JAMA. 2018;320:1774–82.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Vos LE, Oren A, Bots ML, Gorissen WH, Grobbee DE, Uiterwaal CS. Does a routinely measured blood pressure in young adolescence accurately predict hypertension and total cardiovascular risk in young adulthood? J Hypertens. 2003;21:2027–34.

    Article  CAS  PubMed  Google Scholar 

  7. Juhola J, Oikonen M, Magnussen CG, Mikkila V, Siitonen N, Jokinen E, et al. Childhood physical, environmental, and genetic predictors of adult hypertension: the cardiovascular risk in young Finns study. Circulation. 2012;126:402–9.

    Article  PubMed  Google Scholar 

  8. Theodore RF, Broadbent J, Nagin D, Ambler A, Hogan S, Ramrakha S, et al. Childhood to early-midlife systolic blood pressure trajectories: early-life predictors, effect modifiers, and adult cardiovascular outcomes. Hypertension. 2015;66:1108–15.

    Article  CAS  PubMed  Google Scholar 

  9. Urbina EM, Khoury PR, Bazzano L, Burns TL, Daniels S, Dwyer T, et al. Relation of blood pressure in childhood to self-reported hypertension in adulthood. Hypertension. 2019;73:1224–30.

    Article  CAS  PubMed  Google Scholar 

  10. Flynn JT, Kaelber DC, Baker-Smith CM, Blowey D, Carroll AE, Daniels SR, et al. Clinical practice guideline for screening and management of high blood pressure in children and adolescents. Pediatrics. 2017;140:e20171904.

    Article  PubMed  Google Scholar 

  11. Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, et al. 2000 CDC growth charts for the United States: methods and development. Vital Health Stat. 2002;11:1–190.

    Google Scholar 

  12. Barlow SE, Expert C. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(Suppl 4):S164–92.

    Article  PubMed  Google Scholar 

  13. Kato N, Sato K, Takimoto H, Sudo N. BMI for age references for Japanese children–based on the 2000 growth survey. Asia Pac J Public Health. 2008;20(Suppl):118–27.

    PubMed  Google Scholar 

  14. Kato N, Takimoto H, Sudo N. The cubic functions for spline smoothed L, S and M values for BMI reference data of Japanese children. Clin Pediatr Endocrinol. 2011;20:47–9.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Gray L, Lee IM, Sesso HD, Batty GD. Blood pressure in early adulthood, hypertension in middle age, and future cardiovascular disease mortality: HAHS (Harvard Alumni Health Study). J Am Coll Cardiol. 2011;58:2396–403.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Alper AB Jr., Chen W, Yau L, Srinivasan SR, Berenson GS, Hamm LL. Childhood uric acid predicts adult blood pressure: the Bogalusa Heart Study. Hypertension. 2005;45:34–8.

    Article  CAS  PubMed  Google Scholar 

  17. Srinivasan SR, Myers L, Berenson GS. Changes in metabolic syndrome variables since childhood in prehypertensive and hypertensive subjects: the Bogalusa Heart Study. Hypertension. 2006;48:33–9.

    Article  CAS  PubMed  Google Scholar 

  18. Field AE, Cook NR, Gillman MW. Weight status in childhood as a predictor of becoming overweight or hypertensive in early adulthood. Obes Res. 2005;13:163–9.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Rademacher ER, Jacobs DR Jr., Moran A, Steinberger J, Prineas RJ, Sinaiko A. Relation of blood pressure and body mass index during childhood to cardiovascular risk factor levels in young adults. J Hypertens. 2009;27:1766–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kouda K, Ohara K, Fujita Y, Nakamura H, Iki M. Trunk-to-peripheral fat ratio predicts subsequent blood pressure levels in pubertal children with relatively low body fat- three-year follow-up study. Circ J. 2016;80:1838–45.

    Article  PubMed  Google Scholar 

  21. Cnop M, Havel PJ, Utzschneider KM, Carr DB, Sinha MK, Boyko EJ, et al. Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex. Diabetologia. 2003;46:459–69.

    Article  CAS  PubMed  Google Scholar 

  22. Kim DH, Kim C, Ding EL, Townsend MK, Lipsitz LA. Adiponectin levels and the risk of hypertension: a systematic review and meta-analysis. Hypertension. 2013;62:27–32.

    Article  CAS  PubMed  Google Scholar 

  23. Cook NR, Gillman MW, Rosner BA, Taylor JO, Hennekens CH. Prediction of young adult blood pressure from childhood blood pressure, height, and weight. J Clin Epidemiol. 1997;50:571–9.

    Article  CAS  PubMed  Google Scholar 

  24. Feig DI, Johnson RJ. Hyperuricemia in childhood primary hypertension. Hypertension. 2003;42:247–52.

    Article  CAS  PubMed  Google Scholar 

  25. Tatsumi Y, Asayama K, Morimoto A, Satoh M, Sonoda N, Miyamatsu N, et al. Hyperuricemia predicts the risk for developing hypertension independent of alcohol drinking status in men and women: the Saku study. Hypertens Res. 2020;43:442–9.

    Article  CAS  PubMed  Google Scholar 

  26. Lee SW, Kim HC, Nam C, Lee HY, Ahn SV, Oh YA, et al. Age-differential association between serum uric acid and incident hypertension. Hypertens Res. 2019;42:428–37.

    Article  CAS  PubMed  Google Scholar 

  27. Feig DI, Soletsky B, Johnson RJ. Effect of allopurinol on blood pressure of adolescents with newly diagnosed essential hypertension: a randomized trial. JAMA. 2008;300:924–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Sun HL, Pei D, Lue KH, Chen YL. Uric acid levels can predict metabolic syndrome and hypertension in adolescents: a 10-year longitudinal study. PLoS ONE. 2015;10:e0143786.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Mazzali M, Hughes J, Kim YG, Jefferson JA, Kang DH, Gordon KL, et al. Elevated uric acid increases blood pressure in the rat by a novel crystal-independent mechanism. Hypertension. 2001;38:1101–6.

    Article  CAS  PubMed  Google Scholar 

  30. Khosla UM, Zharikov S, Finch JL, Nakagawa T, Roncal C, Mu W, et al. Hyperuricemia induces endothelial dysfunction. Kidney Int. 2005;67:1739–42.

    Article  PubMed  Google Scholar 

  31. Sanchez-Lozada LG, Tapia E, Santamaria J, Avila-Casado C, Soto V, Nepomuceno T, et al. Mild hyperuricemia induces vasoconstriction and maintains glomerular hypertension in normal and remnant kidney rats. Kidney Int. 2005;67:237–47.

    Article  PubMed  Google Scholar 

  32. Sakata S, Hata J, Honda T, Hirakawa Y, Oishi E, Shibata M, et al. Serum uric acid levels and cardiovascular mortality in a general Japanese population: the Hisayama Study. Hypertens Res. 2020;43:560–8.

    Article  CAS  PubMed  Google Scholar 

  33. Cirillo M, Laurenzi M, Trevisan M, Stamler J. Hematocrit, blood pressure, and hypertension. The Gubbio Population Study. Hypertension. 1992;20:319–26.

    Article  CAS  PubMed  Google Scholar 

  34. Jae SY, Kurl S, Laukkanen JA, Heffernan KS, Choo J, Choi YH, et al. Higher blood hematocrit predicts hypertension in men. J Hypertens. 2014;32:245–50.

    Article  CAS  PubMed  Google Scholar 

  35. Strand A, Gudmundsdottir H, Hoieggen A, Fossum E, Bjornerheim R, Os I, et al. Increased hematocrit before blood pressure in men who develop hypertension over 20 years. J Am Soc Hypertens. 2007;1:400–6.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the Keio University Academic Development Funds for Joint Research (TA).

Author information

Authors and Affiliations

  1. Keio University Health Center, 4-1-1 Hiyoshi, Kohoku-ku, Yokohama-shi, Kanagawa, 223-8521, Japan

    Tatsuhiko Azegami, Keiko Uchida, Fujiyo Arima, Mikako Inokuchi, Ayano Murai-Takeda, Mitsuaki Tokumura & Masaaki Mori

  2. Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan

    Tatsuhiko Azegami & Hiroshi Itoh

  3. Department of Preventive Medicine and Public Health, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan

    Yasunori Sato

  4. Department of Pediatrics, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan

    Midori Awazu

Authors
  1. Tatsuhiko Azegami
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Keiko Uchida
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fujiyo Arima
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yasunori Sato
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Midori Awazu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mikako Inokuchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ayano Murai-Takeda
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Hiroshi Itoh
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Mitsuaki Tokumura
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Masaaki Mori
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tatsuhiko Azegami.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Azegami, T., Uchida, K., Arima, F. et al. Association of childhood anthropometric measurements and laboratory parameters with high blood pressure in young adults. Hypertens Res 44, 711–719 (2021). https://doi.org/10.1038/s41440-021-00615-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41440-021-00615-3

Keywords

This article is cited by

Search

Advanced search

Quick links