TY - JOUR
T1 - Validation of continuous clinical indices of cardiometabolic risk in a cohort of Australian adults
AU - CARROLL, Suzanne
AU - Paquet, Catherine
AU - Howard, Natasha
AU - Adams, Robert
AU - Taylor, Anne
AU - DANIEL, Mark
N1 - Funding Information:
The Spatial Epidemiology and Evaluation Research Group at the University of South Australia in collaboration with the South Australian Department for Health and Aging conducted this research under National Health and Medical Research Council (NHMRC) projects (#570150 and #631917) investigating associations between Place and Metabolic Syndrome (PAMS). Dr Catherine Paquet was funded by a NHMRC Post-doctoral Training Research Fellowship (#570139). This manuscript has been reviewed for scientific content and consistency of data interpretation by Chief Investigators of the NWAHS. We are grateful for the interest and commitment of cohort participants. We appreciate the contributions of research support staff involved in recruitment and clinical follow up.
PY - 2014
Y1 - 2014
N2 - Background: Indicators of cardiometabolic risk typically include non-clinical factors (e.g., smoking). While the incorporation of non-clinical factors can improve absolute risk prediction, it is impossible to study the contribution of non-clinical factors when they are both predictors and part of the outcome measure. Metabolic syndrome, incorporating only clinical measures, seems a solution yet provides no information on risk severity. The aims of this study were: 1) to construct two continuous clinical indices of cardiometabolic risk (cCICRs), and assess their accuracy in predicting 10-year incident cardiovascular disease and/or type 2 diabetes; and 2) to compare the predictive accuracies of these cCICRs with existing risk indicators that incorporate non-clinical factors (Framingham Risk Scores).Methods: Data from a population-based biomedical cohort (n = 4056) were used to construct two cCICRs from waist circumference, mean arteriole pressure, fasting glucose, triglycerides and high density lipoprotein: 1) the mean of standardised risk factors (cCICR-Z); and 2) the weighted mean of the two first principal components from principal component analysis (cCICR-PCA). The predictive accuracies of the two cCICRs and the Framingham Risk Scores were assessed and compared using ROC curves.Results: Both cCICRs demonstrated moderate accuracy (AUCs 0.72 – 0.76) in predicting incident cardiovascular disease and/or type 2 diabetes, among men and women. There were no significant differences between the predictive accuracies of the cCICRs and the Framingham Risk Scores.Conclusions: cCICRs may be useful in research investigating associations between non-clinical factors and health by providing suitable alternatives to current risk indicators which include non-clinical factors.
AB - Background: Indicators of cardiometabolic risk typically include non-clinical factors (e.g., smoking). While the incorporation of non-clinical factors can improve absolute risk prediction, it is impossible to study the contribution of non-clinical factors when they are both predictors and part of the outcome measure. Metabolic syndrome, incorporating only clinical measures, seems a solution yet provides no information on risk severity. The aims of this study were: 1) to construct two continuous clinical indices of cardiometabolic risk (cCICRs), and assess their accuracy in predicting 10-year incident cardiovascular disease and/or type 2 diabetes; and 2) to compare the predictive accuracies of these cCICRs with existing risk indicators that incorporate non-clinical factors (Framingham Risk Scores).Methods: Data from a population-based biomedical cohort (n = 4056) were used to construct two cCICRs from waist circumference, mean arteriole pressure, fasting glucose, triglycerides and high density lipoprotein: 1) the mean of standardised risk factors (cCICR-Z); and 2) the weighted mean of the two first principal components from principal component analysis (cCICR-PCA). The predictive accuracies of the two cCICRs and the Framingham Risk Scores were assessed and compared using ROC curves.Results: Both cCICRs demonstrated moderate accuracy (AUCs 0.72 – 0.76) in predicting incident cardiovascular disease and/or type 2 diabetes, among men and women. There were no significant differences between the predictive accuracies of the cCICRs and the Framingham Risk Scores.Conclusions: cCICRs may be useful in research investigating associations between non-clinical factors and health by providing suitable alternatives to current risk indicators which include non-clinical factors.
KW - AUC
KW - Cardiometabolic
KW - Cardiovascular disease
KW - ROC
KW - Risk scores
KW - Type 2 diabetes
KW - Validation
UR - http://www.scopus.com/inward/record.url?scp=84897574879&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/validation-continuous-clinical-indices-cardiometabolic-risk-cohort-australian-adults
U2 - 10.1186/1471-2261-14-27
DO - 10.1186/1471-2261-14-27
M3 - Article
SN - 1471-2261
VL - 14
SP - 1
EP - 9
JO - BMC Cardiovascular Disorders
JF - BMC Cardiovascular Disorders
IS - 27
M1 - 27
ER -