Rapaka Ravindra, Kaushik Richa
University of Connecticut, Storrs, CT, USA.
School of Family Medicine and Public Health Sciences, Wayne State University, Detroit, USA.
J Racial Ethn Health Disparities. 2025 Mar 13. doi: 10.1007/s40615-025-02378-w.
This study investigates the prevalence of tooth loss among the US geriatric population (≥ 65 years) in relation to socioeconomic and demographic characteristics at the local level, specifically identified by ZIP code tabulation areas (ZCTAs).
Data obtained from the American Community Survey (ACS) and PLACES in collaboration with the Centers for Disease Control and Prevention (CDC) were evaluated. Geographical autocorrelation was examined using Moran's I, while geographically weighted regression (GWR) and geographical lag models were employed to analyze spatial patterns and relationships, accounting for spatial dependence. K-means clustering established several ZCTA typologies based on socioeconomic variables.
A notable spatial autocorrelation was seen in the rates of total tooth loss (Moran's I = 0.64, p < 0.001). GWR demonstrated superior accuracy when compared with ordinary least squares (OLS) regression, accounting for 81.1% of the variance and indicating significant spatial heterogeneities in the associations between tooth loss and variables such as education, income, and poverty. Spatial lag models corroborated the impact of adjacent ZCTAs on the prevalence of tooth loss. Ethnic and racial discrepancies suggested that Black majority ZCTAs exhibited greater incidences of severe tooth loss. K-means clustering discovered distinct ZCTA typologies, one of which is a high-risk group marked by extreme poverty and lack of education, resulting in a higher rate of tooth loss.
The findings emphasize the critical role of geographic context in understanding disparities in oral health care and underscore the necessity for localized primary preventive strategies targeted to the elderly, particularly those living in economically disadvantaged regions, to attain oral equality.
本研究调查美国老年人群(≥65岁)牙齿缺失的患病率与当地社会经济和人口特征的关系,具体通过邮政编码分区(ZCTA)来确定。
对从美国社区调查(ACS)和与疾病控制与预防中心(CDC)合作的“地方卫生评估与社区健康统计项目(PLACES)”获得的数据进行评估。使用莫兰指数(Moran's I)检验地理自相关性,同时采用地理加权回归(GWR)和地理滞后模型分析空间模式和关系,并考虑空间依赖性。基于社会经济变量,通过K均值聚类建立了几种ZCTA类型。
全口牙齿缺失率存在显著的空间自相关性(莫兰指数I = 0.64,p < 0.001)。与普通最小二乘法(OLS)回归相比,GWR显示出更高的准确性,解释了81.1%的方差,并表明牙齿缺失与教育、收入和贫困等变量之间的关联存在显著的空间异质性。空间滞后模型证实了相邻ZCTA对牙齿缺失患病率的影响。种族差异表明,黑人占多数的ZCTA严重牙齿缺失的发生率更高。K均值聚类发现了不同的ZCTA类型,其中一类是高风险组,其特征是极端贫困和缺乏教育,导致更高的牙齿缺失率。
研究结果强调了地理背景在理解口腔卫生保健差异方面的关键作用,并强调有必要针对老年人制定本地化的初级预防策略,特别是针对生活在经济弱势地区的老年人,以实现口腔健康平等。