Quantifying Cardiometabolic Risk Using Modifiable Non–Self-Reported Risk Factors

Details

• Alternative Title:
  Am J Prev Med
• Personal Author:
  Marino, Miguel ; Li, Yi ; Pencina, Michael J. ; D’Agostino, Ralph B. ; Berkman, Lisa F. ; Buxton, Orfeu M.
• Description:
  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 χ2=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 based on modifiable risk factors that can motivate an individual’s commitment to prevention and intervention.
  
  
• Keywords:
  Adult Algorithms Cardiovascular Diseases Cohort Studies Female Follow-Up Studies Glycated Hemoglobin Humans Male Metabolic Diseases Middle Aged Predictive Value Of Tests Primary Prevention Proportional Hazards Models Prospective Studies Risk Assessment Risk Factors Sensitivity And Specificity Sex Factors

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• Source:
  Am J Prev Med. 2014; 47(2):131-140
• Pubmed ID:
  24951039
• Pubmed Central ID:
  PMC4107093
• Document Type:
  Journal Article
• Funding:
  N01-HC-25195/HC/NHLBI NIH HHSUnited States/ ; U01OH008788/OH/NIOSH CDC HHSUnited States/ ; R01HL107240/HL/NHLBI NIH HHSUnited States/ ; N01 HC025195/HC/NHLBI NIH HHSUnited States/ ; U01 HD051217/HD/NICHD NIH HHSUnited States/ ; U01 HD051256/HD/NICHD NIH HHSUnited States/ ; U01HD059773/HD/NICHD NIH HHSUnited States/ ; U01HD051276/HD/NICHD NIH HHSUnited States/ ; U01 OH008788/OH/NIOSH CDC HHSUnited States/ ; U01HD051256/HD/NICHD NIH HHSUnited States/ ; U01HD051218/HD/NICHD NIH HHSUnited States/ ; U01AG027669/AG/NIA NIH HHSUnited States/ ; N01HC25195/HL/NHLBI NIH HHSUnited States/ ; R01 AG040248/AG/NIA NIH HHSUnited States/ ; U01HD051217/HD/NICHD NIH HHSUnited States/ ; U01 AG027669/AG/NIA NIH HHSUnited States/ ; R01 HL107240/HL/NHLBI NIH HHSUnited States/ ; U01 HD059773/HD/NICHD NIH HHSUnited States/ ; U01 HD051276/HD/NICHD NIH HHSUnited States/ ; U01 HD051218/HD/NICHD NIH HHSUnited States/
• Volume:
  47
• Issue:
  2
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:949736bf9c47ff1ca6dcef1d11dbc100aadd3192bc76ccc16b53da893b9b6bfc
• Download URL:
  https://stacks.cdc.gov/view/cdc/30042/cdc_30042_DS1.pdf
• File Type:
  [PDF - 562.73 KB ]