European Journal of Epidemiology

, Volume 29, Issue 5, pp 311–324 | Cite as

Adiposity has a greater impact on hypertension in lean than not-lean populations: a systematic review and meta-analysis

  • Simin Arabshahi
  • Doreen Busingye
  • Asvini K. Subasinghe
  • Roger G. Evans
  • Michaela A. Riddell
  • Amanda G. Thrift
REVIEW

Abstract

More than 75 % of people with hypertension live in low-to-middle income countries (LMICs). Based on the mismatch theory of developmental origins of disease, we hypothesised that the impact of adiposity on hypertension is augmented in lean compared with not-lean populations in rural areas of LMICs (RLMICs). We reviewed studies from RLMICs in which the association between body mass index (BMI) or waist circumference (WC) and hypertension was assessed using multivariable models. Applying random effect models, we conducted separate meta-analyses, depending on whether BMI/WC was assessed as a continuous or categorical variable. In each analysis, the studies were ranked by the mean BMI of the total population. Those populations with a mean BMI below the median were categorised as lean and those above the median as not-lean. We identified 46 studies of BMI and 12 of WC. The risk of hypertension was greater in lean than in not-lean populations. Obese males in lean populations were 45 % more likely to be hypertensive compared to obese males in not-lean populations, ratio of the two effect sizes: 1.45 (95 % CI 1.04, 2.03), p = 0.027. Also, individuals with WC above normal in lean populations were 52 % more likely to be hypertensive than their counterparts in not-lean populations, ratio of the two effect sizes: 1.52 (95 % CI 1.06, 2.17), p = 0.021. We conclude that the risk of hypertension associated with adiposity is greater in lean than in not-lean populations. This provides further evidence for the mismatch theory and highlights the need for strategies to improve nutrition in disadvantaged RLMICs.

Keywords

Hypertension Low-to-middle income countries Meta-analysis Body mass index Waist circumference Developmental origins of health and diseases 

Notes

Acknowledgments

We gratefully acknowledge Cielito C. Reyes-Gibby for providing access to their data, Hiram Beltran-Sanchez, Hao Wang, Hoang Van Minh, Arash Etemadi, Prabhdeep Kaur, Yan Li, B. Madhu, and JesusVioque Lopez for providing further details about their studies. This work was supported by a Project Grant from the National Health & Medical Research Council of Australia (NHMRC, 1005740). AGT was supported by a Senior Research Fellowship from the NHMRC (1042600).

Conflict of interest

None.

Supplementary material

10654_2014_9911_MOESM1_ESM.doc (124 kb)
Caption for ESM 1 Supplementary MOOSE and PRISMA checklists (DOC 124 kb)
10654_2014_9911_MOESM2_ESM.doc (62 kb)
Caption for ESM 2 Supplementary methods and results (DOC 62 kb)
10654_2014_9911_MOESM3_ESM.doc (468 kb)
Caption for ESM 3 Supplementary Figures and Tables (DOC 468 kb)

References

  1. 1.
    Lim SS, Vos T, Flaxman AD, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2224–60. doi: 10.1016/S0140-6736(12)61766-8.PubMedCrossRefGoogle Scholar
  2. 2.
    World Health Organizsation. The world health report 2002: reducing risks, promoting healthy life. Geneva: World Health Organization; 2002.Google Scholar
  3. 3.
    World Health Organizsation. WHO Global Report. Preventing chronic disease: a vital investment. World Health Organization, Geneva. 2005.Google Scholar
  4. 4.
    Barker DJ, editor. Mothers, babies and health in later life. Edinburgh, United Kingdom: Churchill Livingstone; 1998.Google Scholar
  5. 5.
    Luyckx VA, Bertram JF, Brenner BM, et al. Effect of fetal and child health on kidney development and long-term risk of hypertension and kidney disease. Lancet. 2013;382(9888):273–83. doi: 10.1016/S0140-6736(13)60311-6.PubMedCrossRefGoogle Scholar
  6. 6.
    Hales CN, Barker DJ. The thrifty phenotype hypothesis. Br Med Bull. 2001;60:5–20.PubMedCrossRefGoogle Scholar
  7. 7.
    White SL, Perkovic V, Cass A, et al. Is low birth weight an antecedent of CKD in later life? A systematic review of observational studies. Am J Kidney Dis. 2009;54(2):248–61. doi: 10.1053/j.ajkd.2008.12.042.PubMedCrossRefGoogle Scholar
  8. 8.
    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
  9. 9.
    Stroup DF, Berlin JA, Morton SC, 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(15):2008–12.PubMedCrossRefGoogle Scholar
  10. 10.
    Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151(4):264–9, W64.Google Scholar
  11. 11.
    World Bank. World development indicators. World Bank, Washington, DC. 2012. http://data.worldbank.org/about/country-classifications/country-and-lending-groups.
  12. 12.
    Hedges LV, Olkin I. Statistical methods for meta-analysis. San Diego: Academic Press; 1985.Google Scholar
  13. 13.
    DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177–88.PubMedCrossRefGoogle Scholar
  14. 14.
    Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58. doi: 10.1002/sim.1186.PubMedCrossRefGoogle Scholar
  15. 15.
    Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50(4):1088–101.PubMedCrossRefGoogle Scholar
  16. 16.
    Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    He J, Klag MJ, Whelton PK, Chen JY, Qian MC, He GQ. Body mass and blood pressure in a lean population in Southwestern China. Am J Epidemiol. 1994;139(4):380–9.PubMedGoogle Scholar
  18. 18.
    Perez LH, Gutierrez LA, Vioque J, Torres Y. Relation between overweight, diabetes, stress and hypertension: a case-control study in Yarumal-Antioquia, Colombia. Eur J Epidemiol. 2001;17(3):275–80.PubMedCrossRefGoogle Scholar
  19. 19.
    Gupta R, Sharma AK. Prevalence of hypertension and subtypes in an Indian rural population: clinical and electrocardiographic correlates. J Hum Hypertens. 1994;8(11):823–9.PubMedGoogle Scholar
  20. 20.
    Malhotra P, Kumari S, Kumar R, Jain S, Sharma BK. Prevalence and determinants of hypertension in an un-industrialised rural population of North India. J Hum Hypertens. 1999;13(7):467–72.PubMedCrossRefGoogle Scholar
  21. 21.
    Fezeu L, Kengne AP, Balkau B, Awah PK, Mbanya JC. Ten-year change in blood pressure levels and prevalence of hypertension in urban and rural Cameroon. J Epidemiol Commun Health. 2010;64(4):360–5. doi: 10.1136/jech.2008.086355.CrossRefGoogle Scholar
  22. 22.
    Shah SM, Luby S, Rahbar M, Khan AW, McCormick JB. Hypertension and its determinants among adults in high mountain villages of the Northern Areas of Pakistan. J Hum Hypertens. 2001;15(2):107–12. doi: 10.1038/sj.jhh.1001131.PubMedCrossRefGoogle Scholar
  23. 23.
    Goel NK, Kaur P. Dr. P.C. Sen Memorial Award–1994. Role of various risk factors in the epidemiology of hypertension in a rural community of Varanasi district. Indian J Public Health. 1996;40(3):71–6.PubMedGoogle Scholar
  24. 24.
    van der Sande MA, Milligan PJ, Nyan OA, et al. Blood pressure patterns and cardiovascular risk factors in rural and urban gambian communities. J Hum Hypertens. 2000;14(8):489–96.PubMedCrossRefGoogle Scholar
  25. 25.
    Singh RB, Rastogi SS, Rastogi V, et al. Blood pressure trends, plasma insulin levels and risk factors in rural and urban elderly populations of north India. Coron Artery Dis. 1997;8(7):463–8.PubMedCrossRefGoogle Scholar
  26. 26.
    Reyes-Gibby CC, Aday LA. Prevalence of and risk factors for hypertension in a rural area of the Philippines. J Commun Health. 2000;25(5):389–99.CrossRefGoogle Scholar
  27. 27.
    Li Y, Wang JG, Gao PJ, et al. Interaction between body mass index and alcohol intake in relation to blood pressure in HAN and SHE Chinese. Am J Hypertens. 2006;19(5):448–53. doi: 10.1016/j.amjhyper.2005.08.014.PubMedCrossRefGoogle Scholar
  28. 28.
    Beltran-Sanchez H, Crimmins EM, Teruel GM, Thomas D. Links between childhood and adult social circumstances and obesity and hypertension in the Mexican population. J Aging Health. 2011;23(7):1141–65. doi: 10.1177/0898264311422255.PubMedCentralPubMedCrossRefGoogle Scholar
  29. 29.
    Zhang M, Batu B, Tong W, Liu Y, Zhang Y. Clustering of hyperlipidemia, hyperglycemia, alcohol drinking, overweight and central obesity and hypertension in Mongolian people, China. CVD Prev Control. 2009;4(3):163–9. doi: 10.1016/j.cvdpc.2009.06.001.CrossRefGoogle Scholar
  30. 30.
    Howteerakul N, Suwannapong N, Sittilerd R, Rawdaree P. Health risk behaviours, awareness, treatment and control of hypertension among rural community people in Thailand. Asia Pac J Public Health. 2006;18(1):3–9.PubMedCrossRefGoogle Scholar
  31. 31.
    Midha T, Idris MZ, Saran RK, Srivastav AK, Singh SK. Prevalence and determinants of hypertension in the urban and rural population of a north Indian district. East Afr J Public Health. 2009;6(3):268–73.PubMedGoogle Scholar
  32. 32.
    Tesfaye F, Nawi NG, Van Minh H, et al. Association between body mass index and blood pressure across three populations in Africa and Asia. J Hum Hypertens. 2007;21(1):28–37. doi: 10.1038/sj.jhh.1002104.PubMedCrossRefGoogle Scholar
  33. 33.
    Hazarika NC, Narain K, Biswas D, Kalita HC, Mahanta J. Hypertension in the native rural population of Assam. Natl Med J India. 2004;17(6):300–4.PubMedGoogle Scholar
  34. 34.
    Pang W, Sun Z, Zheng L, et al. Body mass index and the prevalence of prehypertension and hypertension in a Chinese rural population. Intern Med. 2008;47(10):893–7.PubMedCrossRefGoogle Scholar
  35. 35.
    Xu C, Sun Z, Zheng L, et al. Prevalence of and risk factors for isolated systolic hypertension in the rural adult population of Liaoning Province, China. J Int Med Res. 2008;36(2):353–6.PubMedCrossRefGoogle Scholar
  36. 36.
    Malekzadeh MM, Etemadi A, Kamangar F, et al. Prevalence, awareness and risk factors of hypertension in a large cohort of Iranian adult population. J Hypertens. 2013;. doi: 10.1097/HJH.0b013e3283613053.PubMedCentralPubMedGoogle Scholar
  37. 37.
    Van Minh H, Soonthornthada K, Ng N, et al. Blood pressure in adult rural INDEPTH population in Asia. Glob Health Action. 2009;2. doi:  10.3402/gha.v2i0.2010.
  38. 38.
    Kaur P, Rao SR, Radhakrishnan E, Rajasekar D, Gupte MD. Prevalence, awareness, treatment, control and risk factors for hypertension in a rural population in South India. Int J Public Health. 2011;. doi: 10.1007/s00038-011-0303-3.PubMedGoogle Scholar
  39. 39.
    Addo J, Amoah AG, Koram KA. The changing patterns of hypertension in Ghana: a study of four rural communities in the Ga District. Ethn Dis. 2006;16(4):894–9.PubMedGoogle Scholar
  40. 40.
    Thrift AG, Evans RG, Kalyanram K, Kartik K, Fitzgerald SM, Srikanth V. Gender-specific effects of caste and salt on hypertension in poverty: a population-based study. J Hypertens. 2011;29(3):443–50. doi: 10.1097/HJH.0b013e328341888c.PubMedCrossRefGoogle Scholar
  41. 41.
    de Ramirez SS, Enquobahrie DA, Nyadzi G, et al. Prevalence and correlates of hypertension: a cross-sectional study among rural populations in sub-Saharan Africa. J Hum Hypertens. 2010;24(12):786–95. doi: 10.1038/jhh.2010.14.PubMedCrossRefGoogle Scholar
  42. 42.
    Yang J, Lu F, Zhang C, et al. Prevalence of prehypertension and hypertension in a Chinese rural area from 1991 to 2007. Hypertens Res. 2010;33(4):331–7. doi: 10.1038/hr.2009.235.PubMedCrossRefGoogle Scholar
  43. 43.
    Yip W, Wong TY, Jonas JB, et al. Prevalence, awareness, and control of hypertension among Asian Indians living in urban Singapore and rural India. J Hypertens. 2013;. doi: 10.1097/HJH.0b013e328361d52b.PubMedGoogle Scholar
  44. 44.
    Madhu B, Srinath KM, Ashok NC. Hypertension: prevalence and its associated factors in a rural south Indian population. Indian J Public Health Res Develop. 2012;3(4):105–9.Google Scholar
  45. 45.
    Dutta A, Ray MR. Prevalence of hypertension and pre-hypertension in rural women: a report from the villages of West Bengal, a state in the eastern part of India. Aust J Rural Health. 2012;20(4):219–25. doi: 10.1111/j.1440-1584.2012.01287.x.PubMedCrossRefGoogle Scholar
  46. 46.
    Ruixing Y, Weixiong L, Hanjun Y, et al. Diet, lifestyle, and blood pressure of the middle-aged and elderly in the Guangxi Bai Ku Yao and Han populations. Am J Hypertens. 2008;21(4):382–7. doi: 10.1038/ajh.2008.1.PubMedCrossRefGoogle Scholar
  47. 47.
    Cai L, He J, Song Y, Zhao K, Cui W. Association of obesity with socio-economic factors and obesity-related chronic diseases in rural southwest China. Public Health. 2012;127(3):247–51. doi: 10.1016/j.puhe.2012.12.027.CrossRefGoogle Scholar
  48. 48.
    Maher D, Waswa L, Baisley K, Karabarinde A, Unwin N. Epidemiology of hypertension in low-income countries: a cross-sectional population-based survey in rural Uganda. J Hypertens. 2011;29(6):1061–8. doi: 10.1097/HJH.0b013e3283466e90.PubMedCrossRefGoogle Scholar
  49. 49.
    Huang S, Xu Y, Yue L, et al. Evaluating the risk of hypertension using an artificial neural network method in rural residents over the age of 35 years in a Chinese area. Hypertens Res. 2010;33(7):722–6. doi: 10.1038/hr.2010.73.PubMedCrossRefGoogle Scholar
  50. 50.
    Lwin-Mm-Khin Tassanee S, Oranut P, Chaweewon B. Risk factors for hypertension among rural Thais. Southeast Asian J Trop Med Public Health. 2011;42(1):208–17.PubMedGoogle Scholar
  51. 51.
    Wang H, Zhang X, Zhang J, et al. Factors associated with prevalence, awareness, treatment and control of hypertension among adults in Southern China: A community-based, cross-sectional survey. PLoS ONE. 2013;8(5):e62469. doi: 10.1371/journal.pone.0062469.PubMedCentralPubMedCrossRefGoogle Scholar
  52. 52.
    Pimenta AM, Kac G, Gazzinelli A, Correa-Oliveira R, Velasquez-Melendez G. Association between central obesity, triglycerides and hypertension in a rural area in Brazil. Arq Bras Cardiol. 2008;90(6):386–92.PubMedCrossRefGoogle Scholar
  53. 53.
    Sun Z, Zheng L, Xu C, et al. Prevalence of prehypertension, hypertension and, associated risk factors in Mongolian and Han Chinese populations in Northeast China. Int J Cardiol. 2008;128(2):250–4. doi: 10.1016/j.ijcard.2007.08.127.PubMedCrossRefGoogle Scholar
  54. 54.
    Zhang X, Yao S, Sun G, et al. Total and abdominal obesity among rural Chinese women and the association with hypertension. Nutrition. 2012;28(1):46–52. doi: 10.1016/j.nut.2011.02.004.PubMedCrossRefGoogle Scholar
  55. 55.
    Sathish T, Kannan S, Sarma PS, Razum O, Thankappan KR. Incidence of hypertension and its risk factors in rural Kerala, India: a community-based cohort study. Public Health. 2012;126(1):25–32. doi: 10.1016/j.puhe.2011.11.002.PubMedCrossRefGoogle Scholar
  56. 56.
    Consultation WHOE. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157–63. doi: 10.1016/S0140-6736(03)15268-3.CrossRefGoogle Scholar
  57. 57.
    UNICEF. Low birthwieght: country, regional and global estimates. New York 2004.Google Scholar
  58. 58.
    Gluckman PD, Hanson MA, Bateson P, et al. Towards a new developmental synthesis: adaptive developmental plasticity and human disease. Lancet. 2009;373(9675):1654–7. doi: 10.1016/S0140-6736(09)60234-8.PubMedCrossRefGoogle Scholar
  59. 59.
    Gluckman PD, Hanson MA, Pinal C. The developmental origins of adult disease. Matern Child Nutr. 2005;1(3):130–41. doi: 10.1111/j.1740-8709.2005.00020.x.PubMedCrossRefGoogle Scholar
  60. 60.
    Bhargava SK, Sachdev HS, Fall CH, et al. Relation of serial changes in childhood body-mass index to impaired glucose tolerance in young adulthood. N Engl J Med. 2004;350(9):865–75. doi: 10.1056/NEJMoa035698.PubMedCentralPubMedCrossRefGoogle Scholar
  61. 61.
    Corvalan C, Gregory CO, Ramirez-Zea M, Martorell R, Stein AD. Size at birth, infant, early and later childhood growth and adult body composition: a prospective study in a stunted population. Int J Epidemiol. 2007;36(3):550–7. doi: 10.1093/ije/dym010.PubMedCrossRefGoogle Scholar
  62. 62.
    Uauy R, Kain J, Corvalan C. How can the Developmental Origins of Health and Disease (DOHaD) hypothesis contribute to improving health in developing countries? Am J Clin Nutr. 2011;94(6):1759S–64S. doi: 10.3945/ajcn.110.000562.PubMedCrossRefGoogle Scholar
  63. 63.
    Brenner BM, Garcia DL, Anderson S. Glomeruli and blood pressure. Less of one, more the other? Am J Hypertens. 1988;1(4 Pt 1):335–47.PubMedCrossRefGoogle Scholar
  64. 64.
    Collins JW, Rankin KM, David RJ. Low birth weight across generations: the effect of economic environment. Matern Child Health J. 2011;15(4):438–45. doi: 10.1007/s10995-010-0603-x.PubMedCrossRefGoogle Scholar
  65. 65.
    Bryce J, Coitinho D, Darnton-Hill I, et al. Maternal and child undernutrition: effective action at national level. Lancet. 2008;371(9611):510–26. doi: 10.1016/S0140-6736(07)61694-8.PubMedCrossRefGoogle Scholar
  66. 66.
    World Health Organization. Global burden of disease: 2004 update. Geneva World Health Organization 2008.Google Scholar
  67. 67.
    Nevis IF, Reitsma A, Dominic A, et al. Pregnancy outcomes in women with chronic kidney disease: a systematic review. Clin J Am Soc Nephrol. 2011;6(11):2587–98. doi: 10.2215/CJN.10841210.PubMedCentralPubMedCrossRefGoogle Scholar
  68. 68.
    Zetterstrom K, Lindeberg S, Haglund B, Magnuson A, Hanson U. Being born small for gestational age increases the risk of severe pre-eclampsia. BJOG. 2007;114(3):319–24. doi: 10.1111/j.1471-0528.2006.01231.x.PubMedCrossRefGoogle Scholar
  69. 69.
    Boivin A, Luo ZC, Audibert F, et al. Pregnancy complications among women born preterm. CMAJ. 2012;184(16):1777–84. doi: 10.1503/cmaj.120143.PubMedCentralPubMedCrossRefGoogle Scholar
  70. 70.
    Godfrey KM, Gluckman PD, Hanson MA. Developmental origins of metabolic disease: life course and intergenerational perspectives. Trends Endocrinol Metab. 2010;21(4):199–205. doi: 10.1016/j.tem.2009.12.008.PubMedCrossRefGoogle Scholar
  71. 71.
    Gluckman PD, Hanson MA, Buklijas T, Low FM, Beedle AS. Epigenetic mechanisms that underpin metabolic and cardiovascular diseases. Nat Rev Endocrinol. 2009;5(7):401–8.PubMedCrossRefGoogle Scholar
  72. 72.
    Ibrahim MM, Damasceno A. Hypertension in developing countries. Lancet. 2012;380(9841):611–9. doi: 10.1016/S0140-6736(12)60861-7.PubMedCrossRefGoogle Scholar
  73. 73.
    Peters DH, Garg A, Bloom G, Walker DG, Brieger WR, Rahman MH. Poverty and access to health care in developing countries. Ann N Y Acad Sci. 2008;1136:161–71. doi: 10.1196/annals.1425.011.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Simin Arabshahi
    • 1
  • Doreen Busingye
    • 1
  • Asvini K. Subasinghe
    • 1
  • Roger G. Evans
    • 2
  • Michaela A. Riddell
    • 1
  • Amanda G. Thrift
    • 1
    • 3
  1. 1.Epidemiology and Prevention Unit, Stroke and Ageing Research, Department of Medicine, Southern Clinical SchoolMonash UniversityMelbourneAustralia
  2. 2.Department of PhysiologyMonash UniversityMelbourneAustralia
  3. 3.Florey Neuroscience InstitutesHeidelbergAustralia

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