Comparisons among countries can help to identify opportunities for the reduction of inequalities in cardiometabolic health. The present cross-sectional analysis and meta-analysis aim to address to what extent obesity traits, socioeconomic, and behavioral factors determine poor metabolic health across body mass index (BMI) categories in two urban population-based samples from Central Europe. Data from the CoLaus (~6,000 participants; Lausanne, Switzerland) and the Kardiovize Brno 2030 (~2,000 participants; Brno, Czech Republic) cohorts. For each cohort, logistic regression analyses were performed to identify the main determinants of poor metabolic health overall and stratified by body mass index (BMI) categories. The results of each cohort were then combined in a meta-analysis. We first observed that waist circumference and body fat mass were associated with metabolic health, especially in non-obese individuals. Moreover, increasing age, being male, having low-medium educational level, abdominal obesity, and high body fat mass were the main determinants of the metabolically unhealthy profile in both cohorts. Meta-analysis stratified by BMI categories confirmed the previous results with slight differences across BMI categories. In fact, increasing age and being male were the main determinants of poor metabolic health independent of obesity status. In contrast, low educational level and current smoking were associated with poor metabolic health only in non-obese individuals. In line, public health strategies against obesity and related comorbidities should aim to improve social conditions and to promote healthy lifestyles before the progression of metabolic disorders.

Department of Medical and Surgical Sciences and Advanced Technologies GF Ingrassia University of Catania Catania Italy

Department of Medicine Internal Medicine Lausanne University Hospital Lausanne Switzerland

Division of Preventive Cardiology Department of Cardiovascular Medicine Mayo Clinic Rochester MN United States

International Clinical Research Center St Anne's University Hospital Brno Czechia

Zobrazit více v PubMed

Haslam DW, James W. Obesity. Lancet. (2005) 366:1197–209. 10.1016/S0140-6736(05)67483-1 PubMed DOI

Stefan N, Schick F, Haring H. Causes, characteristics, and consequences of metabolically unhealthy normal weight in humans. Cell Metab. (2017) 26:292–300. 10.1016/j.cmet.2017.07.008 PubMed DOI

Iacobini C, Pugliese G, Blasetti Fantauzzi C, Federici M, Menini S. Metabolically healthy versus metabolically unhealthy obesity. Metab Clin Exp. (2018) 92:51–60. 10.1016/j.metabol.2018.11.009 PubMed DOI

Kramer CK, Zinman B, Retnakaran R. Are metabolically healthy overweight and obesity benign conditions? A systematic review and meta-analysis. Ann Int Med. (2013) 159:758–69. 10.7326/0003-4819-159-11-201312030-00008 PubMed DOI

Mackenbach JP, Cavelaars AE, Kunst AE, Groenhof F. Socioeconomic inequalities in cardiovascular disease mortality; an international study. Eur Heart J. (2000) 21:1141–51. 10.1053/euhj.1999.1990 PubMed DOI

Firmann M, Mayor V, Vidal PM, Bochud M, Pecoud A, Hayoz D, et al. . The CoLaus study: a population-based study to investigate the epidemiology and genetic determinants of cardiovascular risk factors and metabolic syndrome. BMC Cardiovasc Disord. (2008) 8:6. 10.1186/1471-2261-8-6 PubMed DOI PMC

Movsisyan NK, Vinciguerra M, Lopez-Jimenez F, Kunzova S, Homolka M, Jaresova J, et al. . Kardiovize Brno 2030, a prospective cardiovascular health study in Central Europe: methods, baseline findings and future directions. Eur J Prev Cardiol. (2018) 25:54–64. 10.1177/2047487317726623 PubMed DOI

IMF (2018). Available online at: https://www.imf.org/

Agodi A, Maugeri A, Kunzova S, Sochor O, Bauerova H, Kiacova N, et al. . Association of dietary patterns with metabolic syndrome: results from the Kardiovize Brno 2030 Study. Nutrients. (2018) 10:E898. 10.3390/nu10070898 PubMed DOI PMC

Hruskova J, Maugeri A, Podrouzkova H, Stipalova T, Jakubik J, Barchitta M, et al. . Association of cardiovascular health with epicardial adipose tissue and intima media thickness: the kardiovize study. J Clin Med. (2018) 7:113. 10.3390/jcm7050113 PubMed DOI PMC

Lo Re O, Maugeri A, Hruskova J, Jakubik J, Kucera J, Bienertova-Vasku J, et al. . Obesity-induced nucleosome release predicts poor cardio-metabolic health. Clin Epigenetics. (2019) 12:2. 10.1186/s13148-019-0797-8 PubMed DOI PMC

Maugeri A, Kunzova S, Medina-Inojosa JR, Agodi A, Barchitta M, Homolka M, et al. . Association between eating time interval and frequency with ideal cardiovascular health: results from a random sample Czech urban population. Nutr Metab Cardiovasc Dis. (2018) 28:847–55. 10.1016/j.numecd.2018.04.002 PubMed DOI

Maugeri A, Medina-Inojosa JR, Kunzova S, Agodi A, Barchitta M, Sochor O, et al. . Sleep duration and excessive daytime sleepiness are associated with obesity independent of diet and physical activity. Nutrients. (2018) 10:E1219. 10.3390/nu10091219 PubMed DOI PMC

Maugeri A, Medina-Inojosa JR, Kunzova S, Barchitta M, Agodi A, Vinciguerra M, et al. . Dog ownership and cardiovascular health: results from the Kardiovize 2030 Project. Mayo Clin Proc Innov Qual Outcomes. (2019) 3:268–75. 10.1016/j.mayocpiqo.2019.07.007 PubMed DOI PMC

Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. . Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. (2009) 120:1640–5. 10.1161/CIRCULATIONAHA.109.192644 PubMed DOI

Higgins JP, Thompson S. Quantifying heterogeneity in a meta-analysis. Stat Med. (2002) 21:1539–58. 10.1002/sim.1186 PubMed DOI

Forum TW. The World Economic Forum's Human Capital Report 2016. (2016). Available online at: https://www.weforum.org/reports/the-human-capital-report-2016

Irala-Estevez JD, Groth M, Johansson L, Oltersdorf U, Prattala R, Martinez-Gonzalez M. A systematic review of socio-economic differences in food habits in Europe: consumption of fruit and vegetables. Eur J Clin Nutr. (2000) 54:706–14. 10.1038/sj.ejcn.1601080 PubMed DOI

Dallongeville J, Marecaux N, Cottel D, Bingham A, Amouyel P. Association between nutrition knowledge and nutritional intake in middle-aged men from Northern France. Public Health Nutr. (2001) 4:27–33. 10.1079/PHN200052 PubMed DOI

Traill WB, Chambers SA, Butler L. Attitudinal and demographic determinants of diet quality and implications for policy targeting. J Human Nutr Dietetics. (2012) 25:87–94. 10.1111/j.1365-277X.2011.01218.x PubMed DOI

Gallus S, Schiaffino A, La Vecchia C, Townsend J, Fernandez E. Price and cigarette consumption in Europe. Tobacco Control. (2006) 15:114–9. 10.1136/tc.2005.012468 PubMed DOI PMC

Tuovinen EL, Saarni SE, Mannisto S, Borodulin K, Patja K, Kinnunen TH, et al. . Smoking status and abdominal obesity among normal- and overweight/obese adults: population-based FINRISK study. Prev Med Rep. (2016) 4:324–30. 10.1016/j.pmedr.2016.07.003 PubMed DOI PMC

Yun JE, Kimm H, Choi YJ, Jee SH, Huh K. Smoking is associated with abdominal obesity, not overall obesity, in men with type 2 diabetes. J Prev Med Public Health. (2012) 45:316–22. 10.3961/jpmph.2012.45.5.316 PubMed DOI PMC

Canoy D, Wareham N, Luben R, Welch A, Bingham S, Day N, et al. . Cigarette smoking and fat distribution in 21,828 British men and women: a population-based study. Obesity Res. (2005) 13:1466–75. 10.1038/oby.2005.177 PubMed DOI

Anti-oestrogenic effect of cigarette smoking Lancet. (1986) 2:1433 10.1016/S0140-6736(86)92742-X PubMed DOI

Kim SH, Reaven G. Insulin resistance and hyperinsulinemia: you can't have one without the other. Diabetes Care. (2008) 31:1433–8. 10.2337/dc08-0045 PubMed DOI PMC

Pharmacogenomic profile of a central European urban random population-Czech population

Lipidomic Profiling Identifies Signatures of Poor Cardiovascular Health