Literature DB >> 22748425

Age-dependent influence of gender on the association between obesity and a cluster of cardiometabolic risk factors.

Ichiro Wakabayashi1.   

Abstract

BACKGROUND: Obesity is a main risk factor in metabolic syndrome. Gender is known to influence the risk of obesity and other cardiovascular risk factors. However, it remains to be determined whether there is a gender-specific difference in the relationship between obesity and accumulation of other cardiometabolic risk factors such as hypertension, dyslipidemia, and diabetes.
OBJECTIVE: The aim of this study was to determine whether the association between obesity and a cluster of other cardiometabolic risk factors is modified by gender.
METHODS: The subjects were 17,791 Japanese men and women who were divided into younger (35-40 years) and older (60-70 years) age groups. The relationships between obesity (body mass index [BMI] ≥25 kg/m(2) or waist-to-height ratio [WHtR] ≥0.5) and multiple cardiometabolic risk factors (≥2 of the risk factors of high blood pressure, dyslipidema, and hyperglycemia) were compared between men and women in each age group.
RESULTS: In the younger group, the crude odds ratios (ORs) for multiple cardiometabolic risk factors in obese versus nonobese subjects were significantly higher in women than in men (BMI: 6.23 [range, 5.53-7.02] in men vs 16.63 [range, 12.37-22.37] in women, P < 0.01; WHtR: 6.04 [range, 5.36-6.81] in men vs 9.77 [range, 7.14-13.37] in women, P < 0.01), whereas this difference was not found in the older group (BMI: 3.03 [range, 2.69-3.42] in men vs 2.92 [range, 2.33-3.67] in women P = 0.076; WHtR: 3.11 [range, 2.78-3.47] in men vs 2.50 [range, 2.02-3.09] in women, P < 0.05). On multivariate logistic regression analysis, the ORs for multiple cardiometabolic risk factors after adjusting for age, smoking, alcohol consumption, and regular exercise in subjects with versus subjects without a large waist circumference tended to be higher in women than in men in the younger group but not in the older group. The ORs of the interaction term consisting of gender and each adiposity index for multiple cardiometabolic risk factors were significantly higher than a reference level of 1.00 in the younger group (BMI: 2.68 [range, 1.95-3.69], P < 0.01; WHtR: 1.62 [range, 1.16-2.27], P < 0.01) but not in the older group (BMI: 0.95 [range, 0.74-1.23], P = 0.712; WHtR: 0.80 [range, 0.63-1.02], P = 0.066).
CONCLUSION: The results suggest that the association between obesity and a cluster of cardiometabolic risk factors is stronger in women than in men, and this gender-specific difference exists in younger (35-40 years) but not in older (60-70 years) individuals.
Copyright © 2012 Elsevier HS Journals, Inc. All rights reserved.

Entities:  

Mesh:

Year:  2012        PMID: 22748425     DOI: 10.1016/j.genm.2012.05.004

Source DB:  PubMed          Journal:  Gend Med        ISSN: 1550-8579


  11 in total

1.  Association of PGC-1α gene with type 2 diabetes in three unrelated endogamous groups of North-West India (Punjab): a case-control and meta-analysis study.

Authors:  Rubina Sharma; Kawaljit Matharoo; Rohit Kapoor; A J S Bhanwer
Journal:  Mol Genet Genomics       Date:  2017-10-24       Impact factor: 3.291

2.  Comparison of adiposity indices in relation to prehypertension by age and gender: A community-based survey in Henan, China.

Authors:  Shuaibing Wang; Rui Peng; Shuying Liang; Kaiyan Dong; Wei Nie; Qian Yang; Nan Ma; Jianying Zhang; Kaijuan Wang; Chunhua Song
Journal:  Clin Cardiol       Date:  2018-12-05       Impact factor: 2.882

Review 3.  Clinical characteristics in Taiwanese women with polycystic ovary syndrome.

Authors:  Ming-I Hsu
Journal:  Clin Exp Reprod Med       Date:  2015-09-30

4.  Obesity and its relationship with hypertension among adults 50 years and older in Jinan, China.

Authors:  Shu-Kang Wang; Wei Ma; Shumei Wang; Xiang-Ren Yi; Hong-Ying Jia; Fuzhong Xue
Journal:  PLoS One       Date:  2014-12-17       Impact factor: 3.240

5.  Hyperglycemia and blood pressure treatment goal: a cross sectional survey of 18350 patients with type 2 diabetes in 77 tertiary hospitals in China.

Authors:  Linong Ji; Xinyue Zhi; Juming Lu; Xiaohui Guo; Wenying Yang; Weiping Jia; Dajin Zou; Zhiguang Zhou; Qiuhe Ji; Dalong Zhu; Lixin Shi; Jianping Weng
Journal:  PLoS One       Date:  2014-08-14       Impact factor: 3.240

6.  Prevalence and factors associated with hypertension and obesity among civil servants in Kaduna, Kaduna State, June 2012.

Authors:  Abisola Monisola Oladimeji; Olufunmilayo Fawole; Patrick Nguku; Peter Nsubuga
Journal:  Pan Afr Med J       Date:  2014-07-21

7.  Prevalence of Obesity among Rehabilitated Urban Slum Dwellers and Altered Body Image Perception in India (PRESUME).

Authors:  Jeffrey Pradeep Raj; Shervin Ploriya
Journal:  Indian J Endocrinol Metab       Date:  2018 Jan-Feb

8.  Self-reported hypertension in Northern China: a cross-sectional study of a risk prediction model and age trends.

Authors:  Maolin Du; Shaohua Yin; Peiyu Wang; Xuemei Wang; Jing Wu; Mingming Xue; Huiqiu Zheng; Yajun Zhang; Danyan Liang; Ruiqi Wang; Dan Liu; Wei Shu; Xiaoqian Xu; Ruiqi Hao; Shiyuan Li
Journal:  BMC Health Serv Res       Date:  2018-06-19       Impact factor: 2.655

9.  Prevalence and risk factors of obesity and hypertension among students at a central university in the West Bank.

Authors:  Yasin I Tayem; Nagham A Yaseen; Wiam T Khader; Lama O Abu Rajab; Ahmad B Ramahi; Mohammad H Saleh
Journal:  Libyan J Med       Date:  2012-10-15       Impact factor: 1.657

10.  Age-dependent decline of association between obesity and coronary heart disease: a cohort study in a remote Australian Aboriginal community.

Authors:  Zhiqiang Wang; Wendy E Hoy
Journal:  BMJ Open       Date:  2013-11-25       Impact factor: 2.692

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.