Simple Screening Instruments for Chronic Disease & Personalised Prevention at the Workplace

__Abstract__ Prevention refers to actions directed to preventing illness and promoting health. It includes the assessment of disease risk and early diagnosis. Preventive strategies are most commonly classified based on the level of selection being applied in the target group or the stage in the disease process where preventive measures are employed. The entire population is aimed at in universal prevention whereas other prevention strategies target specific groups in the general population. In selective prevention, individuals at high risk are identified through the presence of specific risk factors, such as smoking, age, and lack of physical activity. Ind

A six question screen to facilitate primary cardiovascular disease prevention

Background: European guidelines on primary prevention of cardiovascular disease (CVD) recommend the SCORE risk charts for determining CVD risk, which include blood pressure and serum cholesterol as risk parameters. To facilitate cost-effective large-scale screening, we aimed to construct a risk score with 'non-invasive' parameters as a first screening step to identify persons at increased CVD risk requiring further risk assessment. Methods: We used data of Dutch employees from 25 organisations participating in a health risk assessment between August 2007 and January 2013. Backward multivariate logistic regression analysis was employed to select non-invasive, independent predictors of high CVD risk, defined as the 10-year risk of fatal CVD of ≥5 % based on the SCORE formula. The total CVD risk score was calculated as the summed coefficients of the retained variables. Results: Data of 6189 male participants was used for the development and validation of the risk score. Age, tobacco use, history of hypertension, alcohol consumption, BMI, and waist circumference were independent predictors of high CVD risk. Ten-fold cross-validation resulted in an area under the curve of 0.95 (SE 0.01, 95 % confidence interval 0.94-0.96). A cut-off score ≥45 on the CVD risk score yielded a sensitivity of 0.93, and a specificity of 0.85. Conclusions: We developed a simple, non-invasive risk score that accurately identifies persons at increased CVD risk according to the SCORE formula in a population of working men. The risk score enables a stepwise approach in large screening programmes, strongly reducing the number of persons that require full risk estimation including blood pressure and cholesterol measures