社会人口因素对印尼布利塔县急性冠脉综合征早期检测能力的影响

N. Anggraini, Faridah Moh Said, Nur Syazana Umar, Rahmania Ambarika, Reni Nurhidayah
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引用次数: 0

摘要

背景:印度尼西亚的ACS患病率很高,印度尼西亚至少有200万人被诊断为ACS。它是世界上许多国家成年人死亡的主要原因之一,包括印度尼西亚,印度尼西亚的心脏病患病率估计为200万ACS病例。导致ACS高死亡率的原因之一是院前延误。决策时间延迟是指患者需要的时间长度,以早期发现或作出决定寻求帮助。本研究将关注社会人口因素对ACS早期发现能力的影响。目的:本研究的目的是解释求诊行为、交通与社会人口因素(年龄、性别、社会经济、教育程度、医疗保险)之间的关系。方法:采用前瞻性横断面研究。样本将在布列塔省22个公共卫生中心分区获得,抽样126名答复者。采用卡方(?2)分析各变量之间的相关性,采用多元逻辑回归法确定主导因素。p值<0.05被认为是显著的。结果:研究发现患者的年龄、医疗保险状况、文化程度和就业状况是早期发现的重要因素。早期发现的延迟随着患者年龄的增加而增加,尽管逻辑回归不显着。结论:本研究揭示了影响早期检测能力的社会人口因素包括教育程度、就业状况和健康保险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social Demographic Factor on Early Detection Ability of Acute Coronary Syndrome in Blitar Regency Indonesia
Background: The prevalence of ACS in Indonesia is high, at least 2 million people in Indonesia are diagnosed with ACS. It is one of the main causes of death among adults in many countries around the world, including Indonesia with prevalence of heart disease in Indonesia is estimated at 2 million ACS cases. One of the causes of the high ACS mortality rate is a prehospital delay. Decision time delay refers to the length of time the patient takes for early detection or to make a decision to seek help. This study will focus on the influence of social demographic factors on the ability of early detection of ACS. Purpose: This study aims to explain the relationship between treatment-seeking behavior, transportation, and socio-demographic factors (age, gender, socio-economic, educational status, health insurance). Methods: A prospective cross-sectional study was conducted in this study. The samples will be obtained in Blitar regency with 22 public health center sub-districts with sample 126 respondents. The correlation among variables was analyzed using chi-squared (?2), and for determining the dominant factors, multiple logistic regression with the enter method was used. A p value <0.05 was considered significant. Results: The study found that the age, health insurance status, education level, and employment status of the patients were significant factors for early detection. Delay to early detection increased with the increase in age of the patients, although it was not significant by logistic regression. Conclusions:  This study reveals that several sociodemographic factors that can affect early detection abilities are education, employment status, and health insurance.
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