Relationship between two indicators of coronary risk estimated by the Framingham Risk Score and the number of metabolic syndrome components in Japanese male manufacturing workers.
BACKGROUND
The Framingham Risk Score (FRS) has frequently been used in the United States to predict the 10-year risk of coronary heart disease (CHD). Components of the metabolic syndrome and several lifestyle factors have also been evaluated to estimate the risk of CHD.


METHODS
To determine the relationship between the FRS and components of metabolic syndrome as coronary risk indicators, the authors conducted a cross-sectional study of 2,619 Japanese male workers, ranging in age from 40 to 64 years, at a single workplace. Although the estimation by the FRS and metabolic syndrome involved some different factors, significant association of the risk estimated by the 2 methods was observed.


RESULTS
When logistic regression analysis was conducted with adjustment for several lifestyle factors, the FRS and serum insulin were found to be significantly associated with the risk of likelihood of metabolic syndrome. The odds ratios and 95% confidence intervals of FRS by per standard deviation increment and serum insulin by increasing 1 microIU/mL for the prediction of metabolic syndrome were 2.50 (2.17-2.88) and 1.24 (1.20-1.27), respectively. A preventive effect of abstaining from drinking every day and eating breakfast almost daily against the likelihood of metabolic syndrome was also observed.


CONCLUSIONS
In conclusion, the FRS and insulin were found to be significantly associated with the risk of likelihood of metabolic syndrome, even after controlling for weight change.
Kawada
Tomoyuki
T
Department of Hygiene and Public Health, Nippon Medical School, Tokyo 113-8602, Japan. kawada@nms.ac.jp
Otsuka
Toshiaki
T
Inagaki
Hirofumi
H
Wakayama
Yoko
Y
Li
Qing
Q
Katsumata
Masao
M
D000328:Adult; D044466:Asian People / Q000706:statistics & numerical data; D015415:Biomarkers / Q000097:blood; D003327:Coronary Disease / Q000097:blood / Q000208:ethnology / Q000209:etiology* / Q000503:physiopathology; D003430:Cross-Sectional Studies; D006801:Humans; D007221:Industry / Q000706:statistics & numerical data; D007328:Insulin / Q000097:blood; D007564:Japan / Q000453:epidemiology; D008019:Life Style; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000150:complications* / Q000208:ethnology / Q000503:physiopathology; D008875:Middle Aged; D016017:Odds Ratio; D018570:Risk Assessment; D012307:Risk Factors
D015415:Biomarkers; D007328:Insulin