Related Experiment Video
Updated: Jul 14, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Optimal risk factors in the population: prognosis, prevalence, and secular trends; data from Göteborg population
A Rosengren1, A Dotevall, H Eriksson
1Section of Preventive Cardiology, Sahlgrenska University Hospital/Ostra, Göteborg, Sweden.
Aims:
To assess the prognosis and prevalence of optimal risk factors in the population.
Methods And Results:
Data from several Göteborg population studies were used. Optimal risk factors were defined as serum cholesterol <5 mmol x l(-1), blood pressure <140/90 without treatment and being a non-smoker. In a 20-year follow-up of 7130 men aged 47 to 55 at baseline a group of 117 men who were optimal with respect to cholesterol, blood pressure and smoking were identified. In this group there was only one death from coronary disease, corresponding to 0.4 deaths per 1000 years, whereas the overall risk of coronary death in the study was 4.8 per 1000 years. Among men and women aged 25 to 34 in the Göteborg MONICA study 1995, less than half were optimal on all three scores, and in men and women aged 55 to 64, only 7% and 6%, respectively, were optimal. If body mass index below 25 was included only 34% and 37%, respectively, of men and women aged 25 to 34 were optimal, and 11% and 22% among men and women aged 35 to 44. In an analysis of secular trends over 30 years in four successive cohorts of men aged 50 the prevalence of optimal risk factors with respect to cholesterol, blood pressure and smoking increased from 1963 to 1993 but was still only 11% in 1993.
Conclusions:
As expected, optimal risk factors with respect to serum cholesterol, blood pressure and smoking confers a very low risk of coronary death. However, the prevalence of optimal risk factor status in the Swedish population is still low.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Introduction to Epidemiology
Prevalence and Incidence
Prevalence indicates the proportion of individuals in a population who have a specific disease or health condition at a...
Bias in Epidemiological Studies
Statistical Methods for Analyzing Epidemiological Data
Cancer Survival Analysis
