Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Public Health
Published in: BMC Public Health 1/2019

Open Access 01-12-2019 | Obesity | Research article

Abdominal obesity increases metabolic risk factors in non-obese adults: a Hungarian cross-sectional study

Authors: Anita Lukács, Edina Horváth, Zsuzsanna Máté, Andrea Szabó, Katalin Virág, Magor Papp, János Sándor, Róza Ádány, Edit Paulik

Published in: BMC Public Health | Issue 1/2019

Login to get access

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.
Appendix
Available only for authorised users
Literature
1.
Blüher M. Obesity: global epidemiology and pathogenesis. Nat Rev Endocrinol. 2019;15(5):288–98.CrossRef
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.
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.CrossRef
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.CrossRef
6.
Erdei G, Kovács VA, Bakacs M, Martos É. Hungarian Diet and Nutritional Status Survey 2014. I. Nutritional status of the Hungarian adult population. Orv Hetil. 2017;158(14):533–40.CrossRef
7.
Domján BA, Ferencz V, Tänczer T, Szili-Janicsek Z, Barkai L, Hidvégi T, et al. Large increase in the prevalence of self-reported diabetes based on a nationally representative survey in Hungary. Prim Care Diabetes. 2017;11(2):107–11.CrossRef
8.
9.
Hsieh SD, Yoshinaga H, Muto T. Waist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women. Int J Obes Relat Metab Disord. 2003;27(5):610–6.CrossRef
10.
Park J, Lee ES, Lee DY, Kim J, Park SE, Park CY, et al. Waist circumference as a marker of obesity is more predictive of coronary artery calcification than body mass index in apparently healthy Korean adults: The Kangbuk Samsung Health Study. Endocrinol Metab. 2016;31:559–66.CrossRef
11.
Lee SC, Hairi NN, Moy FM. Metabolic syndrome among non-obese adults in the teaching profession in Melaka. Malaysia. J Epidemiol. 2017;27(3):130–4.CrossRef
12.
Thaikruea L, Thammasarot J. Prevalence of normal weight central obesity among Thai healthcare providers and their association with CVD risk: a cross-sectional study. Sci Rep. 2016;6:37100.CrossRef
13.
Czernichow S, Kengne AP, Stamatakis E, Hamer M, Batty GD. Body mass index, waist circumference and waist-hip ratio: which is the better discriminator of cardiovascular disease mortality risk? Evidence from an individual-participant meta-analysis of 82 864 participants from nine cohort studies. Obes Rev. 2011;12(9):680–7.PubMedPubMedCentral
14.
Sándor J, Kósa K, Fürjes G, Papp M, Csordás Á, Rurik I, et al. Public health services provided in the framework of general practitioners’ clusters. Eur J Public Health. 2013;23(4):530–2.CrossRef
15.
Sándor J, Kósa K, Papp M, Fürjes G, Kőrösi L, Jakovljevic M, et al. Capitation-Based Financing hampers the Provision of Preventive services in Primary health care. Front Public Health. 2016;4:200.CrossRef
16.
Ádány R, Kósa K, Sándor J, Papp M, Fürjes G. General practitioners’ cluster: a model to reorient primary health care to public health services. Eur J Public Health. 2013;23(4):529–30.CrossRef
17.
18.
19.
20.
21.
22.
23.
Hu L, Huang X, You C, Li J, Hong K, Li P, Wu Y, Wu Q, Wang Z, Gao R, Bao H, Cheng X. Prevalence of overweight, obesity, abdominal obesity and obesity-related risk factors in southern China. PLoS One. 2017;12(9):e0183934.CrossRef
24.
Chinedu SN, Ogunlana OO, Azuh DE, Iweala EE, Afolabi IS, Uhuegbu CC, Idachaba ME, Osamor VC. Correlation between body mass index and waist circumference in Nigerian adults: implication as indicators of health status. J Public Health Res. 2013;2(2):e16.CrossRef
25.
Atlantis E, Martin SA, Haren MT, Taylor AW, Wittert GA. Lifestyle factors associated with age-related differences in body composition: the Florey Adelaide Male Aging Study. Am J Clin Nutr. 2008;88:95–104.CrossRef
26.
Okosun IS, Liao Y, Rotimi CN, Prewitt TE, Cooper RS. Abdominal adiposity and clustering of multiple metabolic syndrome in white, black and hispanic Americans. Ann Epidemiol. 2000;10(5):263–70.CrossRef
27.
Cerhan JR, Moore SC, Jacobs EJ, Kitahara CM, Rosenberg PS, Adami HO, et al. A pooled analysis of waist circumference and mortality in 650,000 adults. Mayo Clin Proc. 2014;89(3):335–45.CrossRef
28.
Huang L-H, Liao Y-L, Hsu C-H. Waist circumference is a better predictor than body mass index of insulin resistance in type 2 diabetes. Obes Res Clin Pract. 2012;6(4):314–20.CrossRef
29.
Pi-Sunyer X. The Medical Risks of Obesity. Postgrad Med. 2009;121(6):21–33. Orces CH, Montalvanb M, Tettamantic D: Prevalence of abdominal obesity and its association with cardio metabolic risk factors among older adults in Ecuador. Diabetes Metab Syndr. 2017;11(2):727–33.
30.
Kaur J. Assessment and screening of the risk factors in metabolic syndrome. Med Sc. 2014;2:140–52.
31.
32.
33.
Virginia A. Moyer: Screening for and Management of Obesity in Adults: U.S. Preventive Services Task Force Recommendation Statement. Ann Intern Med. 2012;157:373–8.
34.
35.
36.
Sándor J, Nagy A, Földvári A, Szabó E, Csenteri O, Vincze F, Sipos V, Kovács N, Pálinkás A, Papp M, Fürjes G, Ádány R. Delivery of cardio-metabolic preventive services to Hungarian Roma of different socio-economic strata. Fam Pract. 2017;34(1):83–9.CrossRef
37.
Orces CH, Montalvanb M, Tettamantic D. Prevalence of abdominal obesity and its association with cardio metabolic risk factors among older adults in Ecuador. Diabetes Metab Syndr. 2017;11(2):727–33.CrossRef
Metadata
Title
Abdominal obesity increases metabolic risk factors in non-obese adults: a Hungarian cross-sectional study
Authors
Anita Lukács
Edina Horváth
Zsuzsanna Máté
Andrea Szabó
Katalin Virág
Magor Papp
János Sándor
Róza Ádány
Edit Paulik
Publication date
01-12-2019
Publisher
BioMed Central
Keywords
Obesity
Obesity
Published in
BMC Public Health / Issue 1/2019
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-019-7839-1

Other articles of this Issue 1/2019

BMC Public Health 1/2019 Go to the issue

Research article

Spontaneous and repeat spontaneous abortion risk in relation to occupational characteristics among working Korean women: a cross-sectional analysis of nationally representative data from Korea

Research article

Determinants of neonatal mortality in the largest international border of Brazil: a case-control study

Research article

Inequitable coverage of vitamin A supplementation in Nigeria and implications for childhood blindness

Research article

Is the goal of 12,000 steps per day sufficient for improving body composition and metabolic syndrome? The necessity of combining exercise intensity: a randomized controlled trial

Research article

Air pollution dispersion from biomass stoves to neighboring homes in Mirpur, Dhaka, Bangladesh

Research article

Prevalence of tobacco related chronic diseases and its role in smoking cessation among smokers in a rural area of Shanghai, China: a cross sectional study