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.

  • Review Article
  • Published:

Body mass index, abdominal fatness, and hypertension incidence: a dose-response meta-analysis of prospective studies

Abstract

Despite the established relationship of obesity to hypertension, the question as to whether there is a linear association between these two morbidities is unanswered. To quantitatively evaluate the relationship between obesity and hypertension, we carried out a dose–response meta-analysis of studies that looked at the relationship of different adiposity measures to hypertension. We searched PubMed, Embase, and Web of Science databases for articles published before 27 June 2017. A random-effects model was used to pool relative risks and 95% confidence intervals. Restricted cubic spline analysis was used to model the relationship. A total of 59 studies were included. Fifty-seven cohort studies with 125,071 incident cases among 830,685 participants were included in the analysis of body mass index and hypertension with the summary relative risk for per 5-unit increment in body mass index of 1.50 (95% confidence interval: 1.40–1.59). We found that the risk of hypertension in the body mass index analysis was greater in populations where the baseline body mass index was <25 kg/m2. The summary relative risk for a 10-cm increase in waist circumference was 1.25 (95% confidence interval: 1.19–1.32) and per 0.1-unit increase in waist-to-hip ratio was 1.27 (95% confidence interval: 1.18–1.37). This meta-analysis suggests that in normal range of obesity indexes, as lean as possible may be the best suggestion to prevent hypertension incidence.

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

Access options

Buy this article

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:766–81.

    Article  Google Scholar 

  2. Whitlock G, Lewington S, Sherliker P, Clarke R, Emberson J, Halsey J, et al. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009;373:1083–96.

    Article  Google Scholar 

  3. 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  Google Scholar 

  4. Vazquez G, Duval S, Jacobs DR Jr, Silventoinen K. Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis. Epidemiol Rev. 2007;29:115–28.

    Article  Google Scholar 

  5. Grootveld LR, Van Valkengoed IG, Peters RJ, Ujcic-Voortman JK, Brewster LM, Stronks K, et al. The role of body weight, fat distribution and weight change in ethnic differences in the 9-year incidence of hypertension. J Hypertens. 2014;32:990–6.

    Article  CAS  Google Scholar 

  6. GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1545–602.

    Article  Google Scholar 

  7. GBD 2015 Mortality and Causes of Death Collaborators. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1459–544.

    Article  Google Scholar 

  8. Fuchs FD, Gus M, Moreira LB, Moraes RS, Wiehe M, Pereira GM, et al. Anthropometric indices and the incidence of hypertension: a comparative analysis. Obes Res. 2005;13:1515–7.

    Article  Google Scholar 

  9. Moliner-Urdiales D, Artero EG, Sui X, Espana-Romero V, Lee D, Blair SN. Body adiposity index and incident hypertension: the Aerobics Center Longitudinal Study. Nutr Metab Cardiovasc Dis. 2014;24:969–75.

    Article  CAS  Google Scholar 

  10. Chei CL, Iso H, Yamagishi K, Tanigawa T, Cui R, Imano H, et al. Body fat distribution and the risk of hypertension and diabetes among Japanese men and women. Hypertens Res. 2008;31:851–7.

    Article  Google Scholar 

  11. Williams PT, Hoffman K, La I. Weight-related increases in hypertension, hypercholesterolemia, and diabetes risk in normal weight male and female runners. Arterioscler Thromb Vasc Biol. 2007;27:1811–9.

    Article  CAS  Google Scholar 

  12. Arabshahi S, Busingye D, Subasinghe AK, Evans RG, Riddell MA, Thrift AG. Adiposity has a greater impact on hypertension in lean than not-lean populations: a systematic review and meta-analysis. Eur J Epidemiol. 2014;29:311–24.

    Article  Google Scholar 

  13. Seo DC, Choe S, Torabi MR. Is waist circumference ≥102/88cm better than body mass index ≥30 to predict hypertension and diabetes development regardless of gender, age group, and race/ethnicity? Meta-analysis. Prev Med. 2017;97:100–8.

    Article  Google Scholar 

  14. World Health Organization. Obesity: preventing and managing the global epidemic of obesity, report of a WHO consultation. Geneva: World Health Organisation; 2000 (Report No: 894).

    Google Scholar 

  15. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE) Group. JAMA. 2000;283:2008–12.

    Article  CAS  Google Scholar 

  16. Ohnishi H, Saitoh S, Akasaka H, Mitsumata K, Chiba M, Furugen M, et al. Incidence of hypertension in individuals with abdominal obesity in a rural Japanese population: the Tanno and Sobetsu study. Hypertens Res. 2008;31:1385–90.

    Article  Google Scholar 

  17. Heianza Y, Kodama S, Arase Y, Hsieh SD, Yoshizawa S, Tsuji H, et al. Role of body mass index history in predicting risk of the development of hypertension in Japanese individuals: Toranomon Hospital Health Management Center Study 18 (TOPICS 18). Hypertension. 2014;64:247–52.

    Article  CAS  Google Scholar 

  18. Wells GSB, O’Connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. http://www.ohrica/programs/clinical_epidemiology/oxford.asp. 2014.

  19. Niu J, Seo DC. Central obesity and hypertension in Chinese adults: a 12-year longitudinal examination. Prev Med. 2014;62:113–8.

    Article  Google Scholar 

  20. Feng BY, Chen JC, Li Y, Huang JF, Li JX, Zhao LC, et al. Relationship between overweight/obesity and hypertension among adults in China: a prospective study. Zhonghua Liu Xing Bing Xue Za Zhi. 2016;37:606–11.

    CAS  PubMed  Google Scholar 

  21. Zheng L, Zhang Z, Sun Z, Li J, Zhang X, Xu C, et al. The association between body mass index and incident hypertension in rural women in China. Eur J Clin Nutr. 2010;64:769–75.

    Article  CAS  Google Scholar 

  22. Banda JA, Clouston K, Sui X, Hooker SP, Lee CD, Blair SN. Protective health factors and incident hypertension in men. Am J Hypertens. 2010;23:599–605.

    Article  Google Scholar 

  23. Zhao D, Wang W, Liu J, Cheng J, Liu J, Qin LP. Association between body mass index and ten-year-accumulative-risk of hypertension. Zhonghua Liu Xing Bing Xue Za Zhi. 2009;30:435–8.

    PubMed  Google Scholar 

  24. Shuger SL, Sui X, Church TS, Meriwether RA, Blair SN. Body mass index as a predictor of hypertension incidence among initially healthy normotensive women. Am J Hypertens. 2008;21:613–9.

    Article  Google Scholar 

  25. Parikh NI, Pencina MJ, Wang TJ, Benjamin EJ, Lanier KJ, Levy D, et al. A risk score for predicting near-term incidence of hypertension: the Framingham Heart Study. Ann Intern Med. 2008;148:102–10.

    Article  Google Scholar 

  26. Luo W, Guo Z, Hao C, Yao X, Zhou Z, Wu M, et al. Interaction of current alcohol consumption and abdominal obesity on hypertension risk. Physiol Behav. 2013;122:182–6.

    Article  CAS  Google Scholar 

  27. Orsini N, Li R, Wolk A, Khudyakov P, Spiegelman D. Meta-analysis for linear and non-linear dose–response relations: examples, an evaluation of approximations, and software. Am J Epidemiol. 2012;175:66–73.

    Article  Google Scholar 

  28. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177–88.

    Article  CAS  Google Scholar 

  29. Bekkering GE, Harris RJ, Thomas S, Mayer AM, Beynon R, Ness AR, et al. How much of the data published in observational studies of the association between diet and prostate or bladder cancer is usable for meta-analysis? Am J Epidemiol. 2008;167:1017–26.

    Article  Google Scholar 

  30. Orsini N, Bellocco R, Greenland S. Generalized least squares for trend estimation of summarized dose–response data. Stata J. 2006;6:40–57.

    Article  Google Scholar 

  31. Bagnardi V. Flexible meta-regression functions for modeling aggregate dose–response data, with an application to alcohol and mortality. Am J Epidemiol. 2004;159:1077–86.

    Article  Google Scholar 

  32. Hartemink N, Boshuizen HC, Nagelkerke NJ, Jacobs MA, van Houwelingen HC. Combining risk estimates from observational studies with different exposure cutpoints: a meta-analysis on body mass index and diabetes type 2. Am J Epidemiol. 2006;163:1042–52.

    Article  Google Scholar 

  33. Hamling J, Lee P, Weitkunat R, Ambuhl M. Facilitating meta-analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category. Stat Med. 2008;27:954–70.

    Article  Google Scholar 

  34. Greenland S. Dose–response and trend analysis in epidemiology: alternatives to categorical analysis. Epidemiology. 1995;6:356–65.

    Article  CAS  Google Scholar 

  35. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. Br Med J. 2003;327:557–60.

    Article  Google Scholar 

  36. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. Bmj. 1997;315:629–34.

    Article  CAS  Google Scholar 

  37. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50:1088–101.

    Article  CAS  Google Scholar 

  38. Park CS, Ha KH, Kim HC, Park S, Ihm SH, Lee H-Y. The association between parameters of socioeconomic status and hypertension in Korea: The Korean Genome and Epidemiology Study. J Korean Med Sci. 2016;31:1922.

    Article  Google Scholar 

  39. Fujita M, Hata A. Sex and age differences in the effect of obesity on incidence of hypertension in the Japanese population: A Large Historical Cohort Study. J Am Soc Hypertens. 2014;8:64–70.

    Article  Google Scholar 

  40. Talaei M, Sadeghi M, Mohammadifard N, Shokouh P, Oveisgharan S, Sarrafzadegan N. Incident hypertension and its predictors: the Isfahan Cohort Study. J Hypertens. 2014;32:30–8.

    Article  CAS  Google Scholar 

  41. Schmiegelow MD, Andersson C, Kober L, Andersen SS, Norgaard ML, Jensen TB, et al. Associations between body mass index and development of metabolic disorders in fertile women—a nationwide cohort study. J Am Heart Assoc. 2014;3:e000672.

    Article  Google Scholar 

  42. Sun Jiayi ZD, Wei Wang, Jing Liu, Jun Cheng, Lanping Qin. Association between body mass index and ten-year-accumulative-risk of hypertension. Chin J Epidemiol. 2009;30:435–8.

    Google Scholar 

  43. Jackson C, Herber-Gast G-C, Brown W. Joint effects of physical activity and BMI on risk of hypertension in women: A Longitudinal Study. J Obes. 2014;2014:1–7.

    Article  Google Scholar 

  44. Thawornchaisit P, de Looze F, Reid CM, Seubsman SA, Sleigh AC, Thai Cohort Study T. Health risk factors and the incidence of hypertension: 4-year prospective findings from a national cohort of 60 569 Thai Open University students. BMJ Open. 2013;3:e002826.

    Article  Google Scholar 

  45. Tsujimoto T, Sairenchi T, Iso H, Irie F, Yamagishi K, Tanaka K, et al. Impact of obesity on incident hypertension independent of weight gain among nonhypertensive Japanese: the Ibaraki Prefectural Health Study (IPHS). J Hypertens. 2012;30:1122–8.

    Article  CAS  Google Scholar 

  46. Chien KL, Hsu HC, Su TC, Chang WT, Sung FC, Chen MF, et al. Prediction models for the risk of new-onset hypertension in ethnic Chinese in Taiwan. J Hum Hypertens. 2011;25:294–303.

    Article  Google Scholar 

  47. Tirosh A, Afek A, Rudich A, Percik R, Gordon B, Ayalon N, et al. Progression of normotensive adolescents to hypertensive adults: a study of 26,980 teenagers. Hypertension. 2010;56:203–9.

    Article  CAS  Google Scholar 

  48. Forman JP, Stampfer MJ, Curhan GC. Diet and lifestyle risk factors associated with incident hypertension in women. JAMA. 2009;302:401–11.

    Article  CAS  Google Scholar 

  49. Hi Choy-LyeChei, Yamagishi Kazumasa, Tanigawa Takeshi, Cui Renzhe, Imano Hironori, Kiyama Masahiko, Kitamura Akihiko, Sato Shinichi, Shimamoto Takashi. Body fat distribution and the risk of hypertension and diabetes among Japanese men and women. Hypertens Res. 2008;31:851–7.

    Article  Google Scholar 

  50. Nemesure B, Wu SY, Hennis A, Leske MC, BESS Group. The relationship of body mass index and waist-hip ratio on the 9-year incidence of diabetes and hypertension in a predominantly African-origin population. Ann Epidemiol. 2008;18:657–63.

    Article  Google Scholar 

  51. Takase H, Dohi Y, Toriyama T, Okado T, Tanaka S, Sato K, Kimura G. Metabolic disorders predict development of hypertension in normotensive Japanese subjects. Hypertens Res. 2008;31:665–71.

    Article  Google Scholar 

  52. Li Y, Zhai F, Wang H, Wang Z. A four-year prospective study of the relationship between body mass index and waist cirumstances and hypertension in Chinese adults. J Hyg Res. 2007;36:478–80.

    CAS  Google Scholar 

  53. Gu D, Wildman RP, Wu X, Reynolds K, Huang J, Chen CS, et al. Incidence and predictors of hypertension over 8 years among Chinese men and women. J Hypertens. 2007;25:517–23.

    Article  CAS  Google Scholar 

  54. Gelber RP, Gaziano JM, Manson JE, Buring JE, Sesso HD. A prospective study of body mass index and the risk of developing hypertension in men. Am J Hypertens. 2007;20:370–7.

    Article  Google Scholar 

  55. Lee SH, Kim YS, Sunwoo S, Huh BY. A retrospective cohort study on obesity and hypertension risk among Korean adults. J Korean Med Sci. 2005;20:188–95.

    Article  Google Scholar 

  56. Radi S, Lang T, Lauwers-Cances V, Chatellier G, Fauvel JP, Larabi L, et al. One-year hypertension incidence and its predictors in a working population: the IHPAF study. J Hum Hypertens. 2004;18:487–94.

    Article  CAS  Google Scholar 

  57. Hu G, Barengo NC, Tuomilehto J, Lakka TA, Nissinen A, Jousilahti P. Relationship of physical activity and body mass index to the risk of hypertension: a prospective study in Finland. Hypertension. 2004;43:25–30.

    Article  CAS  Google Scholar 

  58. Folsom AR, Kushi LH, Anderson KE, Mink PJ, Olson JE, Hong CP, et al. Associations of general and abdominal obesity with multiple health outcomes in older women: the Iowa Women’s Health Study. Arch Intern Med. 2000;160:2117–28.

    Article  CAS  Google Scholar 

  59. He J, Klag MJ, Appel LJ, Charleston J, Whelton PK. Seven-year incidence of hypertension in a cohort of middle-aged African Americans and whites. Hypertension. 1998;31:1130–5.

    Article  CAS  Google Scholar 

  60. Huang Z, Willett WC, Manson JE, Rosner B, Stampfer MJ, Speizer FE, et al. Body weight, weight change, and risk for hypertension in women. Ann Intern Med. 1998;128:81–8.

    Article  CAS  Google Scholar 

  61. Hunt SC, Stephenson SH, Hopkins PN, Williams RR. Predictors of an increased risk of future hypertension in Utah. A screening analysis. Hypertension. 1991;17(6 Pt 2):969–76.

    Article  CAS  Google Scholar 

  62. Ukawa S, Tamakoshi A, Wakai K, Ando M, Kawamura T. Body mass index is associated with hypertension in Japanese young elderly individuals: findings of the new integrated suburban seniority investigation. Intern Med. 2015;54:3121–5.

    Article  Google Scholar 

  63. Kubo T, Fujino Y, Nakamura T, Kunimoto M, Tabata H, Tsuchiya T, et al. An industry-based cohort study of the association between weight gain and hypertension risk among rotating shift workers. J Occup Environ Med. 2013;55:1041–5.

    Article  Google Scholar 

  64. Bombelli M, Facchetti R, Sega R, Carugo S, Fodri D, Brambilla G, et al. Impact of body mass index and waist circumference on the long-term risk of diabetes mellitus, hypertension, and cardiac organ damage. Hypertension. 2011;58:1029–35.

    Article  CAS  Google Scholar 

  65. Matsuo T, Sairenchi T, Suzuki K, Tanaka K, Muto T. Long-term stable obesity increases risk of hypertension. Int J Obes. 2011;35:1056–62.

    Article  CAS  Google Scholar 

  66. Panagiotakos DB, Chrysohoou C, Pitsavos C, Skoumas J, Lentzas Y, Katinioti A, et al. Hierarchical analysis of anthropometric indices in the prediction of 5-year incidence of hypertension in apparently healthy adults: The ATTICA Study. Atherosclerosis. 2009;206:314–20.

    Article  CAS  Google Scholar 

  67. Chuang SY, Chou P, Hsu PF, Cheng HM, Tsai ST, Lin IF, et al. Presence and progression of abdominal obesity are predictors of future high blood pressure and hypertension. Am J Hypertens. 2006;19:788–95.

    Article  Google Scholar 

  68. Hayashi T, Boyko EJ, Leonetti DL, McNeely MJ, Newell-Morris L, Kahn SE, et al. Visceral adiposity is an independent predictor of incident hypertension in Japanese Americans. Ann Intern Med. 2004;140:992–1000.

    Article  Google Scholar 

  69. Ishikawa-Takata K, Ohta T, Moritaki K, Gotou T, Inoue S. Obesity, weight change and risks for hypertension, diabetes and hypercholesterolemia in Japanese men. Eur J Clin Nutr. 2002;56:601–7.

    Article  CAS  Google Scholar 

  70. Nyamdorj R, Qiao Q, Soderberg S, Pitkaniemi J, Zimmet P, Shaw J, et al. Comparison of body mass index with waist circumference, waist-to-hip ratio, and waist-to-stature ratio as a predictor of hypertension incidence in Mauritius. J Hypertens. 2008;26:866–70.

    Article  CAS  Google Scholar 

  71. Li M, McDermott R. Obesity, albuminuria, and gamma-glutamyl transferase predict incidence of hypertension in indigenous Australians in rural and remote communities in northern Australia. J Hypertens. 2015;33:704–9.

    Article  CAS  Google Scholar 

  72. DeMarco VG, Aroor AR, Sowers JR. The pathophysiology of hypertension in patients with obesity. Nat Rev Endocrinol. 2014;10:364–76.

    Article  CAS  Google Scholar 

  73. Zhou L, Li Y, Guo M, Wu Y, Zhao L. 61-Relations of body weight status in early adulthood and weight changes until middle age with hypertension in the Chinese population. Hypertens Res. 2016;39:913–8.

    Article  Google Scholar 

  74. Power C, Kuh D, Morton S. From developmental origins of adult disease to life course research on adult disease and aging: insights from birth cohort studies. Annu Rev Public Health. 2013;34:7–28.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Linlin Li.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, W., Shi, Y., Li, Yq. et al. Body mass index, abdominal fatness, and hypertension incidence: a dose-response meta-analysis of prospective studies. J Hum Hypertens 32, 321–333 (2018). https://doi.org/10.1038/s41371-018-0046-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41371-018-0046-1

Search

Quick links