The importance of healthy lifestyle behaviors in the prevention of cardiovascular disease

Kaminsky, Leonard A.; German, Charles; Imboden, Mary T.; Ozemek, Cemal; Peterman, James E.; Brubaker, Peter H.

doi:10.1016/j.pcad.2021.12.001

Cited by 92 publications

(65 citation statements)

References 67 publications

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“…To date, the obese population has exceeded 650 million all over the world and is still increasing with a younger trend [ 1 ]. Obesity is a chronic disease resulting from an abnormal metabolism, characterized by an excessive fat accumulation and may further cause type Ⅱ diabetes [ 2 , 3 ], cardiovascular diseases [ 4 , 5 , 6 ], non-alcoholic fatty liver disease [ 7 ], chronic kidney disease [ 8 ], hypertension, hyperlipidemia [ 9 ], sleep apnea, and tumors [ 10 ]. Accompanied by physical ailments, obese patients can also experience issues with mental health from receiving different visions.…”

Section: Introductionmentioning

confidence: 99%

Application of Caenorhabditis elegans in Lipid Metabolism Research

Chen

et al. 2023

IJMS

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Over the last decade, the development and prevalence of obesity have posed a serious public health risk, which has prompted studies on the regulation of adiposity. With the ease of genetic manipulation, the diversity of the methods for characterizing body fat levels, and the observability of feeding behavior, Caenorhabditis elegans (C. elegans) is considered an excellent model for exploring energy homeostasis and the regulation of the cellular fat storage. In addition, the homology with mammals in the genes related to the lipid metabolism allows many aspects of lipid modulation by the regulators of the central nervous system to be conserved in this ideal model organism. In recent years, as the complex network of genes that maintain an energy balance has been gradually expanded and refined, the regulatory mechanisms of lipid storage have become clearer. Furthermore, the development of methods and devices to assess the lipid levels has become a powerful tool for studies in lipid droplet biology and the regulation of the nematode lipid metabolism. Herein, based on the rapid progress of C. elegans lipid metabolism-related studies, this review outlined the lipid metabolic processes, the major signaling pathways of fat storage regulation, and the primary experimental methods to assess the lipid content in nematodes. Therefore, this model system holds great promise for facilitating the understanding, management, and therapies of human obesity and other metabolism-related diseases.

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Section: Introductionmentioning

confidence: 99%

Application of Caenorhabditis elegans in Lipid Metabolism Research

Chen

et al. 2023

IJMS

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“…However, there are several risk factors such as lifestyle and health profile promoting the disease manifestation. Given that people at risk for cardiovascular disease are more likely to have a heart attack, the prevention of its occurrence is mainly based on these factors’ modification in the population to reduce the likelihood of cardiovascular disease occurrence [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Efficient Data-Driven Machine Learning Models for Cardiovascular Diseases Risk Prediction

Δρίτσας

Trigka

2023

Sensors

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Cardiovascular diseases (CVDs) are now the leading cause of death, as the quality of life and human habits have changed significantly. CVDs are accompanied by various complications, including all pathological changes involving the heart and/or blood vessels. The list of pathological changes includes hypertension, coronary heart disease, heart failure, angina, myocardial infarction and stroke. Hence, prevention and early diagnosis could limit the onset or progression of the disease. Nowadays, machine learning (ML) techniques have gained a significant role in disease prediction and are an essential tool in medicine. In this study, a supervised ML-based methodology is presented through which we aim to design efficient prediction models for CVD manifestation, highlighting the SMOTE technique’s superiority. Detailed analysis and understanding of risk factors are shown to explore their importance and contribution to CVD prediction. These factors are fed as input features to a plethora of ML models, which are trained and tested to identify the most appropriate for our objective under a binary classification problem with a uniform class probability distribution. Various ML models were evaluated after the use or non-use of Synthetic Minority Oversampling Technique (SMOTE), and comparing them in terms of Accuracy, Recall, Precision and an Area Under the Curve (AUC). The experiment results showed that the Stacking ensemble model after SMOTE with 10-fold cross-validation prevailed over the other ones achieving an Accuracy of 87.8%, Recall of 88.3%, Precision of 88% and an AUC equal to 98.2%.

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“…Both lifestyle factors and genetics jointly affect the occurrence and development of CVD [ 10 , 11 ]. Previous studies demonstrated that adherence to healthy lifestyle factors could effectively reduce the risk of CVD [ 12 , 13 ]. Traditional modifiable healthy lifestyle factors, including avoiding overweight or obesity, no smoking, moderate alcohol consumption, regular physical activity, and keeping a healthy dietary pattern, are shown to be the best strategies to prevent the risk of CVD [ 14 , 15 , 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Lifestyle Factors, Genetic Risk, and Cardiovascular Disease Risk among Breast Cancer Survivors: A Prospective Cohort Study in UK Biobank

Peng

Wang

et al. 2023

Nutrients

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Background: Evidence is limited regarding the association between lifestyles and cardiovascular disease (CVD), and the extent to which healthy lifestyles could offset the genetic risk of CVD in females with breast cancer (BC). Methods: Females diagnosed as BC, who were free of CVD at baseline, from UK Biobank were included. Five modifiable lifestyle factors were considered to calculate the healthy lifestyle score, namely body mass index (BMI), smoking, alcohol drinking, dietary habits, and physical activity. The polygenetic risk score (PRS) was derived for coronary heart disease (CHD), ischemic stroke (IS), and heart failure (HF). Results: In 13,348 female BC survivors, there were 986 CVD events (736 CHD, 165 IS, and 353 HF) over a median of 8.01 years of follow-up. Participants with 4–5 healthy lifestyle components were associated with a decreased risk of incident CVD (HR: 0.50; 95%CI: 0.37, 0.66), CHD (HR: 0.49; 95%CI: 0.35, 0.69), IS (HR: 0.35; 95%CI: 0.19, 0.65), and HF (HR: 0.59; 95%CI: 0.36, 0.97), compared with those with 0–1 lifestyle components. Evidence for the genetic–lifestyle interaction was observed for CHD (p = 0.034) and HF (p = 0.044). Among participants at high genetic risk, a healthy lifestyle was associated with a lower risk of CHD (HR: 0.37; 95%CI: 0.24, 0.56), IS (HR: 0.37; 95%CI: 0.15, 0.93) and HF (HR: 0.39; 95%CI: 0.21, 0.73). Conclusions: Our findings suggest that BC survivors with a high genetic risk could benefit more from adherence to a healthy lifestyle in reducing CVD risk.

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The importance of healthy lifestyle behaviors in the prevention of cardiovascular disease

Cited by 92 publications

References 67 publications

Application of Caenorhabditis elegans in Lipid Metabolism Research

Application of Caenorhabditis elegans in Lipid Metabolism Research

Efficient Data-Driven Machine Learning Models for Cardiovascular Diseases Risk Prediction

Lifestyle Factors, Genetic Risk, and Cardiovascular Disease Risk among Breast Cancer Survivors: A Prospective Cohort Study in UK Biobank

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