牙周炎和代谢综合征:全国性研究的统计和机器学习分析
Asaf Wilensky1, Noa Frank1, Gabriel Mizraji1
1Department of Periodontology, Hadassah Medical Center, Faculty of Dental Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel.
Bioengineering (Basel, Switzerland)
|December 23, 2023
概括
牙周炎与代谢综合征 (MetS) 组成部分有关,如肥胖和阻塞性睡眠呼吸暂停 (OSA). 识别有风险的个体需要采用整体方法,考虑饮食,吸烟和口腔卫生以及全身疾病.
科学领域:
- 口腔健康和全身疾病流行病学.
- 医疗信息学和数据分析
背景情况:
- 牙周炎是一种普遍的口腔疾病,已知与代谢综合征 (MetS) 有关.
- 了解牙周炎和特定的 MetS 组件之间的相互作用对于公共卫生至关重要.
- 之前的研究还没有充分探讨与较少研究的MetS相关疾病的关联.
研究的目的:
- 分析牙周炎和MetS组件/相关疾病之间的关联.
- 确定年轻和中年成人牙周炎的风险和保护因素.
- 制定易受牙周炎影响的个人的个人资料.
主要方法:
- 对57496名军事人员进行的国家代表性横截面研究 (牙科,口腔和医疗流行病学 - DOME) 的分析.
- 多变量逻辑回归用于评估牙周炎与各种因素之间的关联.
- 机器学习 eXtreme渐变增强 (XGBoost) 用于特征重要性分析.
主要成果:
- 与牙周炎的显著积极关联包括刷牙,阻塞性睡眠呼吸暂停 (OSA),空性饮食,非酒精性脂肪肝疾病 (NAFLD),吸烟和年龄.
- 预防牙周炎的保护因素包括更多的牙,出生在北美的国家,以及城市居民 (非犹太人和犹太人).
- XGBoost认为肥胖,OSA和NAFLD是牙周炎的关键系统预测因素.
结论:
- 牙周炎的脆弱性概况包括年龄较大,农村居住,吸烟,饮食不良以及肥胖,OSA和NAFLD等并发性疾病.
- 综合口腔健康,生活方式和全身状况的整体评估对于有效的牙周炎预防和管理至关重要.
- 调查结果强调了在牙周炎风险评估中考虑MetS相关条件的重要性.
相关概念视频
Teeth
433
The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...
433
Statistical Methods for Analyzing Epidemiological Data
371
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
371


