KOLESTEROL TOTAL DAN TEKANAN DARAH SISTOLIK: ANALISIS HUBUNGAN PADA POPULASI DEWASA - Megawati; Riki Ristanto (Jurnal Keperawatan Malang, 2026)
that frequently coexist in adult populations. However, most previous studies have been largely associative and have relied on categorical classifications of hypertension, resulting in limited quantitative evidence regarding the effects of total cholesterol on systolic and diastolic blood pressure components Purpose: This study aimed to assess the predictive value of total cholesterol on changes in blood pressure among adults Methods: This study employed a cross-sectional design. The study population included all patients attending the Internal Medicine Outpatient Clinic at Jailolo Regional Hospital, with 50 respondents recruited through consecutive sampling according to the inclusion criteria. Total cholesterol level was defined as the independent variable, while blood pressure was the dependent variable. Total cholesterol was measured using a digital cholesterol meter (Nesco), and blood pressure was assessed using a digital sphygmomanometer (Omron). Data were analyzed using simple linear regression with SPSS version 22, with a significance level set at p < 0.05. Result: The majority of respondents were female (58%), with a mean age of 58.1 years. The mean total cholesterol level was within the hypercholesterolemia range (>200 mg/dL), while the mean systolic and diastolic blood pressures were 168 mmHg and 94 mmHg, respectively. Regression analysis demonstrated that total cholesterol had a significant effect on systolic blood pressure (R = 0.394; R² = 0.156; p = 0.005), with each 1 mg/dL increase in total cholesterol associated with a 0.439 mmHg increase in systolic blood pressure. In contrast, no significant association was observed between total cholesterol and diastolic blood pressure (p = 0.196). Implication: These findings underscore the importance of lipid profile screening as part of comprehensive cardiovascular risk assessment. Future studies are recommended to employ longitudinal designs with larger sample sizes and multivariable analyses to control for major confounding factors