Multilevel analyses of oral health conditions among older adults in the All of Us Research Program

摘要 美国人口正在迅速老龄化。美国人的寿命更长，慢性病更多，而且 更多的牙齿。由于口腔和全身疾病之间的关系，有必要进行牙科护理 与初级保健更好地结合在一起。口腔健康在获得牙科保健方面的不平等现象很普遍 在老年人中。常规牙科护理不包括在联邦医疗保险中，而且存在较大的州级差异 牙科医疗补助福利。由于几乎没有全国性的大型口腔健康项目，美国老年人的口腔健康研究不足。 包括医疗牙科、个人和社区层面数据在内的纵向组成部分的规模研究。 有了这个补充，来自全国NIH All of US(AOU)研究项目的次要数据分析将 扩展有关51岁成年人的信息，可从纵向的、具有全国代表性的美国健康 和目前正在分析的退休研究(HRS)(NIDCR R03 DE030161-02)。我们的R03目标是 研究老年人口腔健康的纵向变化与认知、退休、 医疗、背景、心理社会、行为和牙科使用数据。HRS和AOU数据集都提供 将口腔健康状况与医疗条件、人口统计、生活方式、心理社会因素联系起来的信息 整体健康状况。HRS和AOU都包括自我报告调查数据。此外，AOU包括临床上的- 从参与者在医疗保健设置中获得的电子健康记录(EHR)中确定信息。AoU 寻求招收不同的、传统上代表性不足的群体。AOU控制的层级数据包括3- 数字邮政编码，提供对地理背景信息的访问，以探索 使用多水平分析的健康。老年人口腔健康状况不佳、部分牙齿脱落和无牙 对他们的生活质量和功能状态产生负面影响。AOU分析控制层数据集将是 根据EHR数据，由3组不同口腔条件的人组成比较：1)完全 无牙，2)部分无牙，3)有齿的证据(例如，龋齿，牙周炎)。这个 具体目标是：目标1a)列出社会人口因素的平均数(SD)和频率分布 在受控的AOU数据以及来自调查和EHR的医疗、认知和社交/生活方式风险指标中 与这3个牙齿状态组相关的数据(上图)。目标1b)使用这些工具开发多变量模型 3个牙齿状况组和牙齿使用情况，以确定他们对自我评估的健康、认知和 其他疾病(如糖尿病、心血管疾病、中风)。目标1c)开发多层次模型 包括使用邮政编码数据来表示参与者居住的地理区域的上下文变量 检查结果中的个体和地区差异。目标2：将AOU调查结果与2018年HRS数据和 评估人群在自我评估的健康、认知和医疗结果方面的差异。HRS和AOU都是 具有不同关键特征的大规模、具有里程碑意义的研究。通过分析这两个数据集，我们将能够 利用每一个的最佳功能，以进一步了解老年人的口腔健康。

Abstract The U.S. population is rapidly aging. Americans are living longer, with more chronic conditions, and retaining more teeth. Because of the relationships between oral and systemic conditions, there is a need for dental care to become better integrated with primary care. Oral health inequalities in access to dental care are prevalent among older adults. Routine dental care is not included in Medicare and large state-level variations exist in dental Medicaid benefits. The oral health of older adults in the US is understudied due to few national large- scale studies with longitudinal components that include medical dental, individual and community level data. With this supplement, secondary data analysis from the national NIH All of US (AoU) Research Project will expand information about adults age 51+ available from the longitudinal, nationally representative US Health and Retirement Study (HRS) currently being analyzed (NIDCR R03 DE030161-02). Our R03 goals are to study longitudinal changes in the oral health of older adults in relationship to changes in cognition, retirement, medical, contextual, psychosocial, behavioral and dental utilization data. Both HRS and AoU datasets provide information to link oral health status to medical conditions, demographics, lifestyle, psychosocial factors, and overall health. The HRS and AoU both include self-report survey data. Additionally, the AoU includes clinically- determined information from participants' electronic health records (EHR) obtained in healthcare settings. AoU seeks to enroll diverse, traditionally under-represented groups. The AoU Controlled Tier level data includes 3- digit ZIP code that provides access to geographical contextual information to explore social determinants of health using multilevel analyses. Poor oral health, partial tooth loss, and edentulism among older adults negatively affect their quality of life and functional status. An AoU analytical Controlled Tier dataset will be constructed with 3 groups having different oral conditions based on EHR data for comparison: 1) completely edentulous, 2) partially edentulous, and 3) evidence of being dentate (e.g., dental caries, periodontitis). The specific aims are: AIM 1a) Tabulate the means (SD) and frequency distribution of socio-demographic factors in Controlled Tier AoU data and medical, cognition, and social/lifestyle risk indicators from survey and EHR data associated with these 3 dental status groups (above). Aim 1b) Develop multivariable models using these 3 dental status groups and dental utilization to determine their influence on self-rated health, cognition, and other medical conditions (e.g., diabetes, cardiovascular disease, stroke). Aim 1c) Develop multilevel models including contextual variables using zip code data to represent geographic regions where participants reside to examine individual and area variations in outcomes. AIM 2: Compare AoU findings with 2018 HRS data and assess population differences in self-rated health, cognition, and medical outcomes. HRS and AoU are both large-scale, landmark studies with different key features. By analyzing both datasets, we will be able to take advantage of the best features of each one to further our understanding of the oral health of older adults.