Preventive cardiologyCentral Obesity and Multivariable Cardiovascular Risk as Assessed by the Framingham Prediction Scores
Section snippets
Methods
Baseline data of 4,175 men from an age- and gender-stratified sample of adults in Australian capital cities (Australian Risk Factor Prevalence Survey, 1989) with no previous diabetes, heart attack, or stroke were linked with the National Death Index to determine the causes of death for the 346 subjects who had died by December 31, 2004. The sample of voters 42.3 ± 13.1 years of age had their fasting serum lipid levels, blood pressure, smoking, and obesity measured. Registration for voting is
Results
Baseline characteristics for the 4,175 subjects who had no history of angina, heart attack, stroke, or diabetes are presented in Table 1. Framingham predicted risks of 15-year CHD and CVD deaths are also presented. During 15 years of follow-up (1989 to 2004) there were 346 deaths due to all causes, 88 deaths due to CVD, and 64 deaths due to CHD.
Actual CHD and CVD deaths were compared with Framingham predicted risk for CHD and CVD deaths, respectively, in 10% class intervals of increasing risk (
Discussion
This study shows that measurements of central obesity predict CVD and CHD risk independently from the multivariable Framingham score in a representative sample of men of European descent free of previous CHD, stroke, and diabetes. The Framingham risk score is the most common way to predict cardiovascular risk and is recommended for providing a reliable simple tool for stratifying a patient's risk status.7, 8 It was developed from a U.S. population cohort with a high prevalence of CVD, and it
References (18)
- et al.
Obesity and the risk of myocardial infarction in 2700 participants from 52 countries: a case–control study
Lancet
(2005) - et al.
The association of differing measures of overweight and obesity with prevalent atherosclerosisThe Dallas Heart Study
J Am Coll Cardiol
(2007) - et al.
Waist and hip circumferences have independent and opposite effects on cardiovascular disease risk factors: the Quebec family study
Am J Clin Nutr
(2001) Obesity: Preventing and Managing the Global EpidemicReport of a WHO Consultation on Obesity
(1998)- et al.
Body mass index and mortality in a prospective cohort of US adults
N Engl J Med
(1999) - et al.
Preferred clinical measure of central obesity for predicting mortality
Eur J Clin Nutr
(2007) - et al.
Waist–hip ratio is the dominant risk factor predicting cardiovascular death in Australia
Med J Aust
(2003) - et al.
Waist-to-hip ratios in Australia: a different picture of obesity
Aust J Nutr Diet
(1993) - et al.
Which waist–hip ratio?
Med J Aust
(1990)
Cited by (78)
Adipokines: Deciphering the cardiovascular signature of adipose tissue
2022, Biochemical PharmacologyCitation Excerpt :This systems biology approach, described as a “Mosaic” by Dr. Irvine Page more than 60 years ago, has helped to inform our understanding of HTN as a multi-organ disease with many potential contributions.[6,7]. As one of the many contributors to HTN, obesity is one of the most highly correlated pathophysiological conditions with HTN, and the Framingham Heart study suggests that nearly 80 % of male patients with HTN and 65 % of female patients with HTN cases were attributable directly to obesity. [8,9] Obesity-related medical care costs constitute somewhere between $120–170 billion in annual direct and indirect costs.[10–14],
DXA-Derived vs Standard Anthropometric Measures for Predicting Cardiometabolic Risk in Middle-Aged Australian Men and Women
2022, Journal of Clinical DensitometryCitation Excerpt :There have been suggestions of using fat mass index (FMI, fat mass [kg]/height [m2]) to estimate if an individual has excess body fat (2), but a recent study showed that the prevalence of metabolic syndrome (MetS) and its components was not significantly different between obesity classified using BMI and FMI (3). Central obesity measures such as waist circumference (WC) and waist-to-hip ratio (WHR) are superior to BMI in predicting cardiovascular disease risk (4), probably due to the adverse impact of the visceral adipose tissue (VAT) component on CM profile (5), whereas subcutaneous fat, especially that of lower limbs, is thought to be protective against CM diseases (6–9). Computed tomography (CT) and magnetic resonance imaging (MRI) are the gold standard methods for quantifying regional fat compartments such as VAT and subcutaneous adipose tissue (SAT), but their high-cost limits wide clinical application.
The health impact of obesity
2020, Obesity: Global Impact and EpidemiologyVisceral adipose tissue volume is associated with premature atherosclerosis in early type 2 diabetes mellitus independent of traditional risk factors
2019, AtherosclerosisCitation Excerpt :Abdominal adipose tissue can be divided into visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Both are key contributors to abdominal obesity but their associated atherosclerotic risk profiles differ significantly [3,4]. VAT secretes pro-inflammatory (i.e. C-reactive protein, leptin) and anti-inflammatory (i.e. adiponectin) adipokines.
This work was supported by a grant-in-aid from Merck, Sharp and Dohme (Australia) Pty. Ltd., South Granville, NSW 2142, Australia.