在纵向数据中识别虫活性个体,使用国家注册表进行方法研究
Håkan Flink1, Anders Hedenbjörk-Lager2, Simon Liljeström3
1Region Vastmanland, Uppsala University, Centre for Clinical Research, Vastmanland Hospital Vasteras, Vasteras, Sweden; Faculty of Odontology, Malmö University, Malmö, Sweden. Hakan.Flink@regionvastmanland.se.
一个轨迹模型在成年人中确定了明显的虫活动水平. 这种方法有助于精确确定有高牙经验的个体,以制定有针对性的预防策略.
科学领域:
- 牙科流行病学 牙科流行病学
- 纵向数据分析的数据分析.
背景情况:
- 在成年人中,脏活动有很大差异.
- 识别患有高脏病风险的个体对于有效预防至关重要.
研究的目的:
- 用轨迹模型来识别脏活跃的成年人.
- 为了比较来自瑞典 (SKaPa) 和尼丁队伍的纵向脏病数据.
主要方法:
- 在SKaPa (10年随访) 中分析了30岁和40岁的长度数据.
- 一个轨迹模型将受试者分为高 (15%),中等 (45%) 和低 (40%) 虫发育组.
- 数据与杜内丁研究中公布的纵向出生队列数据进行了比较.
主要成果:
- 在三种轨迹中观察到平均腐烂,缺失和填充表面 (DMFS) 指数的显著差异.
- 虫发育的模式反映了尼丁队列的发现.
- 高腐烂轨迹组显示,在10年内,DMFS的平均增长幅度显著增加.
结论:
- 一个三轨道模型有效地呈现了随着时间的推移而发生的经验.
- 这种方法可以识别具有不同疾病活动水平的个体.
- 识别高虫病轨迹的个体有助于有针对性的预防研究.
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