Erango Markos Abiso, Fiseha Tademe, Nura Galgalo Jaba
Department of Statistics, Arba Minch University, Arba Minch, Ethiopia.
Department of Statistics, Borana University, Borena, Oromia Region, Ethiopia.
BMC Public Health. 2025 Jan 3;25(1):23. doi: 10.1186/s12889-024-21176-3.
Hypertension is among the most significant non-communicable public health issues worldwide. High blood pressure, or hypertension, has been associated with severe health consequences, including death, aneurysms, stroke, chronic renal disease, eye damage, heart attack, heart failure, peripheral artery disease, and vascular dementia. Consequently, this study aimed to investigate the predictors linked to survival time and the progression of blood pressure measurements in hypertensive patients.
This study on retrospective cohort analysis was conducted among hypertensive patients receiving follow-up treatment. A total of 200 hypertensive patients were screened during their follow-up at Sawula General Hospital. Multivariate joint models typically combine a multivariate linear mixed-effects model for repeated measurements with a Cox model for time-to-event outcomes.
The baseline characteristics of patients indicated that, out of 200 hypertensive patients, the majority were male, totaling 116 (58%). Regarding alcohol consumption, 72 (36%) of the hypertensive patients reported using alcohol, while 128 (64%) did not. The multivariate joint model emerged as the most effective model in this study. The analysis revealed that observation time, economic status, sex, place of residence, baseline FBS, and age significantly influenced log FBS, while visiting time, age, sex, pulse rate, place of residence, and baseline DBP were identified as significant factors for log diastolic blood pressure.
The multivariate joint model exhibited superior performance. Hypertension continues to be a non-communicable disease and a public health issue in Sawula and Ethiopia, deserving greater attention.
高血压是全球最重要的非传染性公共卫生问题之一。高血压已与严重的健康后果相关联，包括死亡、动脉瘤、中风、慢性肾病、眼部损伤、心脏病发作、心力衰竭、外周动脉疾病和血管性痴呆。因此，本研究旨在调查高血压患者生存时间和血压测量进展的相关预测因素。
本回顾性队列分析研究在接受随访治疗的高血压患者中进行。在萨武拉综合医院对200名高血压患者进行了随访筛查。多变量联合模型通常将用于重复测量的多变量线性混合效应模型与用于事件发生时间结局的Cox模型相结合。
患者的基线特征表明，在200名高血压患者中，大多数为男性，共计116名（58%）。关于饮酒情况，72名（36%）高血压患者报告饮酒，而128名（64%）不饮酒。多变量联合模型是本研究中最有效的模型。分析显示，观察时间、经济状况、性别、居住地点、基线空腹血糖和年龄对空腹血糖对数有显著影响，而就诊时间、年龄、性别、脉搏率、居住地点和基线舒张压被确定为舒张压对数的显著影响因素。
多变量联合模型表现出卓越的性能。高血压在萨武拉和埃塞俄比亚仍然是一种非传染性疾病和公共卫生问题，值得更多关注。
