在Kheramah PERSION队列人群中心血管疾病风险因素的模式,使用隐性类分析
Hadis Salimi1, Mohebat Vali2, Abbas Rezaianzadeh3
1Student Research Committee, Shiraz University of Medical Science, Shiraz, Iran.
Scientific reports
|July 8, 2025
概括
这项研究在40-70岁的伊朗成年人中确定了三种不同的心血管疾病风险因素模式. 女性性别和法尔斯族裔等人口因素与更高的临床和生活方式风险有关.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 心脏病学 心脏病学
背景情况:
- 心血管疾病 (CVD) 是一个主要的全球健康问题,在伊朗产生重大影响.
- 伊朗对可修改的心血管疾病风险因素模式的研究是有限的.
- 了解这些模式对于有针对性的预防策略至关重要.
研究的目的:
- 在40岁及以上的伊朗成年人中识别可修改的心血管疾病风险因素的独特模式.
- 探索人口特征与这些已识别的风险因素模式之间的关联.
主要方法:
- 利用了Kherameh队列研究的数据,包括9,422名年龄在40-70岁之间的参与者,没有先前存在的心血管疾病.
- 使用隐性类分析 (LCA) 来识别风险因素模式.
- 使用多项逻辑回归来分析人口变量和潜在类之间的关系.
主要成果:
- 确定了三个不同的潜在类别:低风险 (42%),临床风险 (52%) 和生活方式风险 (6%).
- 女性性别,年龄较大和农村居住与属于临床风险类别的风险增加有关.
- 在临床风险和生活方式风险类别中,Fars族裔的风险显著更高.
结论:
- 在伊朗成年人中存在可修改的心血管疾病风险因素的独特模式.
- 人口因素在这些风险模式的分布中起着重要作用.
- 研究结果可以为制定针对心血管疾病风险降低的量身定制的预防策略和健康协议提供信息.
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