Alobaidi F, Heidari E, Sabbah W
Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, UK.
J Dent Res. 2025 May 4;104(10):220345251329337. doi: 10.1177/00220345251329337.
The aims of this study were to evaluate how behaviors cluster together and to investigate the relationship among cluster of behaviors, social support and network, socioeconomic factors, and edentulism in older English adults. Data on social factors (Wave 3, 2006/07), behaviors (Wave 5, 2010/11), and edentulism (Wave 7, 2014/15) were extracted from the English Longitudinal Study of Ageing (ELSA). Baseline demographic factors (gender, ethnicity, and age) were included. Latent class analysis (LCA) was conducted on 4 behaviors (smoking, alcohol intake, fruit and vegetable consumption, physical activity). Confirmatory factor analysis (CFA) was used to create 2 latent variables, social support and network (positive support, negative support, network), and socioeconomic factors (education, wealth, self-rated social status). Two models of structural equation modeling (SEM) were constructed to assess the direct and indirect effect of latent variables on edentulism. A total of 3,087 participants were included. In the LCA, a 2-class model was chosen: class 1 (risky) and class 2 (healthy). The first SEM model showed that social support and network was not linked directly to edentulism, but higher levels of social support and network predicted being dentate indirectly through cluster of behaviors. The second model additionally accounting for socioeconomic position showed that social support and network was not associated with edentulism directly or indirectly, but higher socioeconomic position predicted directly and indirectly being dentate. In both models, cluster of behaviors was associated with edentulism. The result of this study clearly shows that cluster of behaviors mediate the relationship between each of social support and socioeconomic position and edentulism. Actions to improve socioeconomic conditions might have strong effects on changing behaviors and improved oral health.
本研究的目的是评估行为如何聚集在一起，并调查英国老年成年人的行为集群、社会支持与网络、社会经济因素和无牙状态之间的关系。社会因素数据（2006/07年第3波）、行为数据（2010/11年第5波）和无牙状态数据（2014/15年第7波）取自英国老龄化纵向研究（ELSA）。纳入了基线人口统计学因素（性别、种族和年龄）。对4种行为（吸烟、饮酒、水果和蔬菜消费、体育活动）进行了潜在类别分析（LCA）。使用验证性因素分析（CFA）创建了2个潜在变量，即社会支持与网络（积极支持、消极支持、网络）和社会经济因素（教育、财富、自评社会地位）。构建了两个结构方程模型（SEM）来评估潜在变量对无牙状态的直接和间接影响。共纳入3087名参与者。在LCA中，选择了一个2类别模型：第1类（有风险）和第2类（健康）。第一个SEM模型表明，社会支持与网络与无牙状态没有直接联系，但较高水平的社会支持与网络通过行为集群间接预测有牙状态。第二个额外考虑社会经济地位的模型表明，社会支持与网络与无牙状态没有直接或间接关联，但较高的社会经济地位直接和间接预测有牙状态。在两个模型中，行为集群都与无牙状态相关。本研究结果清楚地表明，行为集群介导了社会支持和社会经济地位与无牙状态之间的关系。改善社会经济状况的行动可能对改变行为和改善口腔健康有很大影响。
