Quantifying cardiometabolic risk using modifiable non-self-reported risk factors.

Pubmed ID: 24951039

Pubmed Central ID: PMC4107093

Journal: American journal of preventive medicine

Publication Date: Aug. 1, 2014

Affiliation: Department of Medicine, Brigham and Women's Hospital, Department of Social and Behavioral Sciences, Harvard School of Public Health, Division of Sleep Medicine, Harvard Medical School Boston; Department of Biobehavioral Health, Pennsylvania State University, University Park, Pennsylvania.

MeSH Terms: Humans, Male, Adult, Female, Cardiovascular Diseases, Risk Factors, Cohort Studies, Algorithms, Middle Aged, Risk Assessment, Proportional Hazards Models, Sex Factors, Prospective Studies, Follow-Up Studies, Sensitivity and Specificity, Predictive Value of Tests, Primary Prevention, Metabolic Diseases, Glycated Hemoglobin

Grants: N01 HC025195, N01-HC-25195, R01 HL107240, R01HL107240, U01 AG027669, U01 HD051217, U01 HD051218, U01 HD051256, U01 HD051276, U01 HD059773, U01AG027669, U01HD051217, U01HD051218, U01HD051256, U01HD051276, U01HD059773, U01OH008788, R01 AG040248

Authors: Pencina MJ, D'Agostino RB, Li Y, Marino M, Berkman LF, Buxton OM

Cite As: Marino M, Li Y, Pencina MJ, D'Agostino RB Sr, Berkman LF, Buxton OM. Quantifying cardiometabolic risk using modifiable non-self-reported risk factors. Am J Prev Med 2014 Aug;47(2):131-40. Epub 2014 Jun 17.

Studies:

Abstract

BACKGROUND: Sensitive general cardiometabolic risk assessment tools of modifiable risk factors would be helpful and practical in a range of primary prevention interventions or for preventive health maintenance. PURPOSE: To develop and validate a cumulative general cardiometabolic risk score that focuses on non-self-reported modifiable risk factors such as glycosylated hemoglobin (HbA1c) and BMI so as to be sensitive to small changes across a span of major modifiable risk factors, which may not individually cross clinical cut-off points for risk categories. METHODS: We prospectively followed 2,359 cardiovascular disease (CVD)-free subjects from the Framingham offspring cohort over a 14-year follow-up. Baseline (fifth offspring examination cycle) included HbA1c and cholesterol measurements. Gender-specific Cox proportional hazards models were considered to evaluate the effects of non-self-reported modifiable risk factors (blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking, BMI, and HbA1c) on general CVD risk. We constructed 10-year general cardiometabolic risk score functions and evaluated its predictive performance in 2012-2013. RESULTS: HbA1c was significantly related to general CVD risk. The proposed cardiometabolic general CVD risk model showed good predictive performance as determined by cross-validated discrimination (male C-index=0.703, 95% CI=0.668, 0.734; female C-index=0.762, 95% CI=0.726, 0.801) and calibration (lack-of-fit chi-square=9.05 [p=0.338] and 12.54 [p=0.128] for men and women, respectively). CONCLUSIONS: This study presents a risk factor algorithm that provides a convenient and informative way to quantify cardiometabolic risk on the basis of modifiable risk factors that can motivate an individual's commitment to prevention and intervention.