Related Experiment Video
Updated: May 21, 2025

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
Published on: February 21, 2025
Nontraditional Factors Influencing Cardiovascular Disease Risk: Correlation Among Framingham Risk Score, Body
Libo Zhao1, Xin Xue2, Yinghui Gao3
1Cardiology Department of the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
Abstract:
To examine the correlation among body composition, sleep-breathing indicators, and Framingham risk score (FRS) to identify and amplify nontraditional factors that influence the risk of CVD in males, A total of 195 male participants underwent examinations for body composition and sleep-breathing monitoring. We compared the differences in individual factors across various FRS groups. We further conducted multiple linear regression analysis. A cutoff value of FRS ≥ 14 was utilized, and potential influencing factors were examined by logistic regression analysis. Statistical differences were observed in the levels of fasting blood glucose (FBG), CO2, serum ferritin, hemoglobin (HB), and ECT/TBW among the FRS tripartite groups. However, no significant differences were found in AHI and MSpO2. The multiple linear regression analysis revealed positive correlations between ECW/TBW and FBG with FRS (β = 0.324 and 0.324, p < 0.001), while HB and muscle/fat mass exhibited negative correlations with the score (β = -0.185 and - 0.169, p < 0.01). These five factors-ECW/TBW, FBG, HB, serum ferritin, and muscle/fat mass-collectively accounted for 28.6% of the variation in FRS. A higher ECW/TBW was significantly associated with FRS ≥ 14 (OR = 2.208, 95% CI: 1.503-3.244). Conversely, reduced levels of muscle/fat mass, HB, and basal metabolic rate (BMR) were significantly linked to moderate-to-high CVD risk (ORratio = 0.532, 95% CI: 0.284-0.996; ORHB = 0.961, 95% CI: 0.932-0.991; ORBMR = 0.997, 95% CI: 0.995-1.000). This study revealed correlations among ECW/TBW, HB, FBG, and muscle-to-fat mass ratio with the risk of CVD predicted using FRSs.
Related Concept Videos
Assessment of the Cardiovascular System I: Subjective Data
Initial Enquiry
Ask the patient about their primary concern and thoroughly explore all reported symptoms.
Medical History
Investigate past illnesses affecting the cardiovascular system, such as angina, anemia, rheumatic fever, congenital heart disease, stroke, thrombophlebitis, dysrhythmias, varicosities
Inquire about symptoms...
Correlations
Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
Insufficient Sleep and Sleep Deprivation
Sleep deprivation is a more severe form of sleep loss...
Sleep Apnea
The condition is more prevalent among...
Assessment of blood pressure in brachial artery(two-step method)

