Effectiveness of Lifestyle Modification vs. Therapeutic, Preventative Strategies for Reducing Cardiovascular Risk in Primary Prevention-A Cohort Study.

Paweł Sowa,Małgorzata Chlabicz,Jacek Jamiołkowski,Andrzej Raczkowski,Magdalena Zalewska,Anna Szpakowicz,Marlena Dubatówka,Natalia Zieleniewska,Magda Łapińska,Wojciech Łaguna,Karol A. Kamiński

doi:10.3390/jcm11030688

Abstract

Background: Cardiovascular diseases (CVD) are still the leading cause of death in developed countries. The aim of this study was to calculate the potential for CV risk reduction when using three different prevention strategies to evaluate the effect of primary prevention. Methods: A total of 931 individuals aged 20–79 years old from the Bialystok PLUS Study were analyzed. The study population was divided into CV risk classes. The Systematic Coronary Risk Estimation (SCORE), Framingham Risk Score (FRS), and LIFE-CVD were used to assess CV risk. The optimal prevention strategy assumed the attainment of therapeutic goals according to the European guidelines. The moderate strategy assumed therapeutic goals in participants with increased risk factors: a reduction in systolic blood pressure by 10 mmHg when it was above 140 mmHg, a reduction in total cholesterol by 25% when it was above 190 mg/dL, and a reduction in body mass index below 30. The minimal prevention strategy assumed that CV risk would be lowered by lifestyle modifications. The greatest CV risk reduction was achieved in the optimal model and then in the minimal model, and the lowest risk reduction was achieved in the moderate model, e.g., using the optimal model of prevention (Model 1). In the total population, we achieved a reduction of −1.74% in the 10-year risk of CVD death (SCORE) in relation to the baseline model, a −0.85% reduction when using the moderate prevention model (Model 2), and a −1.11% reduction when using the minimal prevention model (Model 3). However, in the low CV risk class, the best model was the minimal one (risk reduction of −0.72%), which showed even better results than the optimal one (reduction of −0.69%) using the FRS. Conclusion: A strategy based on lifestyle modifications in a population without established CVD could be more effective than the moderate strategy used in the present study. Moreover, applying a minimal strategy to the low CV risk class population may even be beneficial for an optimal model.

Highlights

This article is an open access articleCardiovascular diseases (CVD) are still the leading diseases in the European population [1] despite the fact that we have guidelines for CVD prevention, lifestyle, and the management of risk factors [2,3]
Multiple European reports of secondary prevention have revealed that a large number of patients with CVD maintain unhealthy lifestyles in terms of their diet, smoking, and sedentary behavior and that they did not achieve their low-density lipoprotein cholesterol (LDL-C), blood pressure (BP), and glucose targets [5,6]
The Systematic Coronary Risk Estimation—Polish version (Pol-SCORE) was used to assess the 10-year risk of fatal CV based on the following risk factors: age, gender, smoking, systolic blood pressure (BPs), and total cholesterol (TC) for individuals aged 40–70 [9,10]

Summary

Introduction

This article is an open access articleCardiovascular diseases (CVD) are still the leading diseases in the European population [1] despite the fact that we have guidelines for CVD prevention, lifestyle, and the management of risk factors [2,3]. The latest European primary prevention survey showed that a large number of individuals with high CVD risk have inadequate control of lipids, blood pressure (BP), and diabetes and maintain unhealthy lifestyles [4]. Multiple European reports of secondary prevention have revealed that a large number of patients with CVD maintain unhealthy lifestyles in terms of their diet, smoking, and sedentary behavior and that they did not achieve their low-density lipoprotein cholesterol (LDL-C), BP, and glucose targets [5,6]. Many studies show that a healthy lifestyle and the control of disorders such as hypertension (AH), hypercholesterolemia, and excess body weight prevent CVD events. Many of these disorders may go undiagnosed and untreated. The Framingham Risk Score (FRS) was used to predict the

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