验证一个小区域模型,以估计在次国家一级的吸烟率
Carla Guerra-Tort1, Esther López-Vizcaíno2, María I Santiago-Pérez3
1Área de Medicina Preventiva e Saúde Pública, Universidade de Santiago de Compostela, Santiago de Compostela, Spain.
Tobacco induced diseases
|September 4, 2023
概括
小面积估计模型为西班牙各地区提供了有效的吸烟率估计. 这种方法允许使用国家调查数据进行地方风险因子表征,即使没有保证区域代表性.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 公共卫生 公共卫生
背景情况:
- 小面积估计方法提供了直接调查估计的替代方案,当样本大小不足以实现区域代表性时.
- 对小面积估计方法的验证对于可靠的数据至关重要.
- 这项研究旨在验证一个小面积模型,用于亚国家级健康特征估计.
研究的目的:
- 验证一个小区域模型,以估计西班牙自治区 (AR) 按性别和年龄组的吸烟率.
- 将小面积模型的估计与直接调查估计进行比较.
- 评估小面积模型估计的一致性和精度.
主要方法:
- 在两个AR中按性别和年龄组计算吸烟率 (吸烟者,前吸烟者,从未吸烟者),使用来自代表性调查的直接估计.
- 将一个小面积模型应用于西班牙国家健康调查的数据,该调查缺乏保证的区域代表性.
- 使用类内相关系数 (ICC) 和差异的95%置信区间评估估计一致性;使用变化系数评估精度.
主要成果:
- ICC为≥0.87,表明直接和小面积模型估计之间的一致性很好.
- 超过80%的95%置信区间的估计差异包括零.
- 小面积模型的变化系数始终为<30%,表明高精度.
结论:
- 应用于国家调查数据的小面积模型可以在AR层面产生有效的吸烟率估计.
- 这种方法可以使用国家调查数据在地方层面对人口风险因素进行表征.
- 当区域代表性在国家调查中受到限制时,小面积模型是公共卫生研究的宝贵工具.
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