Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Sep 21:4:502-506.
doi: 10.1016/j.pmedr.2016.09.007. eCollection 2016 Dec.

Identifying metabolic syndrome in a clinical cohort: Implications for prevention of chronic disease

Allison Martin  1 , Elizabeth P Neale  1 , Marjka Batterham  2 , Linda C Tapsell  1
Affiliations

Identifying metabolic syndrome in a clinical cohort: Implications for prevention of chronic disease

Allison Martin et al. Prev Med Rep. .

Abstract

In the clinical setting, calculating cardiovascular disease (CVD) risk is commonplace but the utility of the harmonised equation for metabolic syndrome (MetS) (Alberti et al., 2009) is less well established. The aims of this study were to apply this equation to an overweight clinical cohort to identify risk factors for being metabolically unhealthy and explore associations with chronic disease. Baseline data were analysed from a lifestyle intervention trial of Illawarra residents recruited in 2014/2015. Participants were aged 25-54 years with a BMI 25-40 kg/m2. Data included MetS, CVD risk, insulin sensitivity, weight, body fat, diet, peripheral artery disease (PAD), physical activity, socio-economic position and psychological profile. Backward stepwise regression tested the association of covariates with MetS status and linear or logistic regression tested associations between MetS and risk of CVD, coronary heart disease, PAD and insulin resistance. 374 participants were included in the analysis with 127 (34.0%) categorised with MetS. Covariates significantly and positively associated with MetS were higher BMI (odds 1.26, p < 0.01) and older age (odds 1.08, p < 0.01). MetS participants (n = 351) had a 4.50% increase in CVD risk and were 8.1 and 12.7 times (respectively) more likely to be at risk of CHD and insulin resistance, compared to participants without MetS. The utility of the harmonised equation in the clinical setting was confirmed in this overweight clinical cohort. Those classified as having MetS were more likely to be older, overweight/obese individuals and they had a substantially higher risk of developing CVD and insulin resistance than those without MetS.

Keywords: Cardiovascular disease risk; Insulin resistance; Lifestyle factors; Metabolic syndrome; Metabolically unhealthy; Obesity.

PubMed Disclaimer

References

    1. Alberti K.G., Eckel R.H., Grundy S.M. 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(16):1640–1645. - PubMed
    1. Alexander C.M., Landsman P.B., Grundy S.M. The influence of age and body mass index on the metabolic syndrome and its components. Diabetes Obes. Metab. 2008;10(3):246–250. - PubMed
    1. Ärnlöv J., Ingelsson E., Sundström J., Lind L. Impact of body mass index and the metabolic syndrome on the risk of cardiovascular disease and death in middle-aged men. Circulation. 2010;121(2):230–236. - PubMed
    1. AUSNUT 2007. http://www.foodstandards.gov.au/consumerinformation/ausnut2007/
    1. Brunner E.J., Marmot M.G., Nanchahal K. Social inequality in coronary risk: central obesity and the metabolic syndrome. Evidence from the Whitehall II study. Diabetologia. 1997;40(11):1341–1349. - PubMed

LinkOut - more resources