Literature DB >> 24838697

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

Simin Arabshahi1, Doreen Busingye, Asvini K Subasinghe, Roger G Evans, Michaela A Riddell, Amanda G Thrift.   

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.

Entities:  

Mesh:

Year:  2014        PMID: 24838697     DOI: 10.1007/s10654-014-9911-6

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  64 in total

1.  Quantifying heterogeneity in a meta-analysis.

Authors:  Julian P T Higgins; Simon G Thompson
Journal:  Stat Med       Date:  2002-06-15       Impact factor: 2.373

Review 2.  The thrifty phenotype hypothesis.

Authors:  C N Hales; D J Barker
Journal:  Br Med Bull       Date:  2001       Impact factor: 4.291

3.  Prevalence and correlates of hypertension: a cross-sectional study among rural populations in sub-Saharan Africa.

Authors:  S Stewart de Ramirez; D A Enquobahrie; G Nyadzi; D Mjungu; F Magombo; M Ramirez; S Ehrlich Sachs; W Willett
Journal:  J Hum Hypertens       Date:  2010-03-11       Impact factor: 3.012

4.  The changing patterns of hypertension in Ghana: a study of four rural communities in the Ga District.

Authors:  Juliet Addo; Albert G B Amoah; Kwadwo A Koram
Journal:  Ethn Dis       Date:  2006       Impact factor: 1.847

5.  Operating characteristics of a rank correlation test for publication bias.

Authors:  C B Begg; M Mazumdar
Journal:  Biometrics       Date:  1994-12       Impact factor: 2.571

6.  Hypertension in the native rural population of Assam.

Authors:  N C Hazarika; K Narain; D Biswas; H C Kalita; J Mahanta
Journal:  Natl Med J India       Date:  2004 Nov-Dec       Impact factor: 0.537

7.  Prevalence of and risk factors for hypertension in a rural area of the Philippines.

Authors:  C C Reyes-Gibby; L A Aday
Journal:  J Community Health       Date:  2000-10

8.  Dr. P.C. Sen Memorial Award--1994. Role of various risk factors in the epidemiology of hypertension in a rural community of Varanasi district.

Authors:  N K Goel; P Kaur
Journal:  Indian J Public Health       Date:  1996 Jul-Sep

9.  Prevalence of and risk factors for isolated systolic hypertension in the rural adult population of Liaoning Province, China.

Authors:  C Xu; Z Sun; L Zheng; D Zhang; J Li; X Zhang; S Liu; J Li; F Zhao; D Hu; Y Sun
Journal:  J Int Med Res       Date:  2008 Mar-Apr       Impact factor: 1.671

10.  Poverty and access to health care in developing countries.

Authors:  David H Peters; Anu Garg; Gerry Bloom; Damian G Walker; William R Brieger; M Hafizur Rahman
Journal:  Ann N Y Acad Sci       Date:  2007-10-22       Impact factor: 5.691

View more
  8 in total

1.  The Rotterdam Study: 2016 objectives and design update.

Authors:  Albert Hofman; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; M Arfan Ikram; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Ch Stricker; Henning W Tiemeier; André G Uitterlinden; Meike W Vernooij
Journal:  Eur J Epidemiol       Date:  2015-09-19       Impact factor: 8.082

Review 2.  Body mass index, abdominal fatness, and hypertension incidence: a dose-response meta-analysis of prospective studies.

Authors:  Wen Zhou; Yuanyuan Shi; Yu-Qian Li; Zhiguang Ping; Chongjian Wang; Xuejiao Liu; Jie Lu; Zhen-Xing Mao; Jingzhi Zhao; Lei Yin; Dongdong Zhang; Zhongyan Tian; Lulu Zhang; Linlin Li
Journal:  J Hum Hypertens       Date:  2018-03-27       Impact factor: 3.012

Review 3.  Metabolic (dysfunction)-associated fatty liver disease in individuals of normal weight.

Authors:  Mohammed Eslam; Hashem B El-Serag; Sven Francque; Shiv K Sarin; Lai Wei; Elisabetta Bugianesi; Jacob George
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2022-06-16       Impact factor: 73.082

4.  Childhood Fat and Lean Mass: Differing Relations to Vascular Structure and Function at Age 8 to 9 Years

Authors:  Line Sletner; Pamela Mahon; Sarah R Crozier; Hazel M Inskip; Keith M Godfrey; Scott Chiesa; Devina J Bhowruth; Marietta Charakida; John Deanfield; Cyrus Cooper; Mark Hanson
Journal:  Arterioscler Thromb Vasc Biol       Date:  2018-10       Impact factor: 8.311

5.  Association of triglyceride glucose index and its combination of obesity indices with prehypertension in lean individuals: A cross-sectional study of Chinese adults.

Authors:  Zhen Yu Zeng; Su Xuan Liu; Hao Xu; Xia Xu; Xing Zhen Liu; Xian Xian Zhao
Journal:  J Clin Hypertens (Greenwich)       Date:  2020-05-22       Impact factor: 3.738

6.  Consumption of fried foods and risk of heart failure in the physicians' health study.

Authors:  Luc Djoussé; Andrew B Petrone; J Michael Gaziano
Journal:  J Am Heart Assoc       Date:  2015-04-23       Impact factor: 5.501

7.  Body mass index and the risk of incident functional disability in elderly Japanese: The OHSAKI Cohort 2006 Study.

Authors:  Shu Zhang; Yasutake Tomata; Kemmyo Sugiyama; Yu Kaiho; Kenji Honkura; Takashi Watanabe; Fumiya Tanji; Yumi Sugawara; Ichiro Tsuji
Journal:  Medicine (Baltimore)       Date:  2016-08       Impact factor: 1.889

8.  Association and Interaction Analysis of Body Mass Index and Triglycerides Level with Blood Pressure in Elderly Individuals in China.

Authors:  Lin Zhang; Jin-Long Li; Li-Li Zhang; Lei-Lei Guo; Hong Li; Dan Li
Journal:  Biomed Res Int       Date:  2018-11-22       Impact factor: 3.411

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.