Risk prediction model of dyslipidaemia over a 5-year period based on the Taiwan MJ health check-up longitudinal database

Abstract

Abstract Objective This study aimed to provide an epidemiological model to evaluate the risk of developing dyslipidaemia within 5 years in the Taiwanese population. Methods A cohort of 11,345 subjects aged 35–74 years and was non-dyslipidaemia in the initial year 1996 and followed in 1997–2006 to derive a risk score that could predict the occurrence of dyslipidaemia. Multivariate logistic regression was used to derive the risk functions using the check-up centre of the overall cohort. Rules based on these risk functions were evaluated in the remaining three centres as the testing cohort. We evaluated the predictability of the model using the area under the receiver operating characteristic (ROC) curve (AUC) to confirm its diagnostic property on the testing sample. We also established the degrees of risk based on the cut-off points of these probabilities after transforming them into a normal distribution by log transformation. Results The incidence of dyslipidaemia over the 5-year period was 19.1%. The final multivariable logistic regression model includes the following six risk factors: gender, history of diabetes, triglyceride level, HDL-C (high-density lipoprotein cholesterol), LDL-C (low-density lipoprotein cholesterol) and BMI (body mass index). The ROC AUC was 0.709 (95% CI: 0.693–0.725), which could predict the development of dyslipidaemia within 5 years. Conclusion This model can help individuals assess the risk of dyslipidaemia and guide group surveillance in the community.

Keywords

• Dyslipidaemia
• Risk predictive model
• MJ longitudinal data