Relationship between Pulse Pressure and Handgrip Strength in the Korean Population: A Nationwide Cross-Sectional Study.
Ryuk Jun KwonYoung Hye ChoEun Ju ParkYoungin LeeSang Yeoup LeeJung-In ChoiSae Rom LeeSoo Min SonPublished in: Journal of clinical medicine (2024)
Background: Sarcopenia is defined as the loss of muscle mass and strength and low physical performance, and it is closely related to the risk of cardiovascular disease and mortality. Pulse pressure (PP) is a biomarker of arterial stiffness and compliance. Elevated PP levels increase the risk of cardiovascular diseases and all-cause mortality. Nevertheless, the association between PP and sarcopenia has not yet been clearly established. Methods: Participant data were extracted from the Korea National Health and Nutrition Examination Survey conducted from 2014 to 2020. The study population was classified into three groups (PP < 40 mmHg, 40 mmHg ≤ PP < 60 mmHg, and PP ≥ 60 mmHg). PP was calculated by deducting the diastolic blood pressure from the systolic blood pressure. For handgrip strength, the maximum value measured with a grip dynamometer was adopted (weak handgrip strength: <28 kg for men, <18 kg for woman; normal handgrip strength: ≥28 kg for men, ≥18 kg for women). To determine the relationship between PP and the prevalence of weak handgrip strength, multiple logistic regression analysis was performed after adjusting for possible confounding factors. Results: The higher PP group had a higher age, body mass index; systolic blood pressure, prevalence of hypertension, diabetes, hyperlipidemia, and metabolic syndrome, and maximum handgrip strength. In all models, the prevalence of weak handgrip strength was significantly higher in the group with PP ≥ 60 mmHg compared to the control group (PP < 40 mmHg). Conclusions: Elevated PP was significantly associated with a higher prevalence of weak muscle strength. Thus, PP monitoring may be used to identify individuals at risk of sarcopenia and is helpful in improving health outcomes.
Keyphrases
- blood pressure
- cardiovascular disease
- hypertensive patients
- metabolic syndrome
- body mass index
- heart rate
- type diabetes
- left ventricular
- skeletal muscle
- physical activity
- pregnant women
- electronic health record
- insulin resistance
- artificial intelligence
- middle aged
- cardiovascular events
- adipose tissue
- high fat diet
- cross sectional
- deep learning
- coronary artery disease
- data analysis
- ejection fraction