Abstract
Abstract
Background
The prevalence of abdominal obesity is increasing worldwide. Adults with abdominal obesity have been reported to have increased risk of cardiometabolic disorders.
The aim of this study was to examine whether non-obese subjects (body mass index (BMI) < 25 kg/m2) with abdominal obesity examined in the framework of the Swiss–Hungarian Cooperation Programme had increased metabolic risk compared to participants without abdominal obesity.
Methods
A cross-sectional study was carried out in 5228 non-obese individuals. Data were collected between July 2012 and February 2016. Descriptive statistics, Pearson’s correlation analysis and multiple logistic regression models were applied, odds ratios (OR) with 95% confidence interval (CI) being the outcomes.
Results
607 (11.6%) out of the 5228 non-obese individuals had abdominal obesity. The correlation analysis indicated that the correlation coefficients between BMI and waist circumference (WC) were 0.610 in males and 0.526 in females. In this subgroup, the prevalence of high systolic blood pressure, high fasting blood glucose, and high total cholesterol and triglyceride levels were significantly higher. The logistic regression model based on these data showed significantly higher risk for developing high systolic blood pressure (OR = 1.53; 95% CI = 1.20–1.94), low HDL cholesterol (OR = 2.06; 95% CI = 1.09–3.89), and high trygliceride level (OR = 1.65; 95% CI = 1.27–2.16).
Conclusions
There was a very high, significant, positive correlation between WC and BMI. Abdominal obesity was found to be strongly related to certain metabolic risk factors among non-obese subjects. Hence, measuring waist circumference could be recommended as a simple and efficient tool for screening abdominal obesity and related metabolic risk even in non-obese individuals.
Funder
Swiss Contribution Programme
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health
Reference37 articles.
1. Blüher M. Obesity: global epidemiology and pathogenesis. Nat Rev Endocrinol. 2019;15(5):288–98.
2. N. C. D. Risk Factor Collaboration: Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet. 2017;390(10113):2627-42.
3. Organisation for Economic Co-operation and Development. Obesity update 2017. OECD https://www.oecd.org/els/health-systems/Obesity-Update-2017.pdf. Accessed 20 May 2018.
4. Rurik I, Ungvári T, Szidor J, Torzsa P. Móczár Cs, Jancsó Z, Sándor J. Obese Hungary. Trend and prevalence of overweight and obesity in Hungary, 2015. Orv. Hetil. 2016;157(31):1248–55.
5. Li W, Wang D, Wang X, Gong Y, Cao S, Yin X, Zhuang X, Shi W, Wang Z, Lu Z. The association of metabolic syndrome components and diabetes mellitus: evidence from China National Stroke Screening and Prevention Project. BMC Public Health. 2019;19(1):192.
Cited by
35 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献