Northridge Mary E, Yu Chenchen, Chakraborty Bibhas, Port Greenblatt Ariel, Mark Janet, Golembeski Cynthia, Cheng Bin, Kunzel Carol, Metcalf Sara S, Marshall Stephen E, Lamster Ira B
At the time this article was written, Mary E. Northridge, Ariel Port Greenblatt, Janet Mark, and Cynthia Golembeski were with the New York University College of Dentistry, New York, NY. Chenchen Yu, Bibhas Chakraborty, Bin Cheng, and Ira B. Lamster were with the Mailman School of Public Health, Columbia University, New York. Carol Kunzel and Stephen E. Marshall were with the College of Dental Medicine, Columbia University. Sara S. Metcalf was with the University at Buffalo, The State University of New York, Buffalo.
Am J Public Health. 2015 Jul;105 Suppl 3(Suppl 3):S459-65. doi: 10.2105/AJPH.2015.302562. Epub 2015 Apr 23.
We explored the interrelationships among diabetes, hypertension, and missing teeth among underserved racial/ethnic minority elders.
Self-reported sociodemographic characteristics and information about health and health care were provided by community-dwelling ElderSmile participants, aged 50 years and older, who took part in community-based oral health education and completed a screening questionnaire at senior centers in Manhattan, New York, from 2010 to 2012.
Multivariable models (both binary and ordinal logistic regression) were consistent, in that both older age and Medicaid coverage were important covariates when self-reported diabetes and self-reported hypertension were included, along with an interaction term between self-reported diabetes and self-reported hypertension.
An oral public health approach conceptualized as the intersection of 3 domains-dentistry, medicine, and public health-might prove useful in place-based assessment and delivery of services to underserved older adults. Further, an ordinal logit model that considers levels of missing teeth might allow for more informative and interpretable results than a binary logit model.
我们探讨了在医疗服务不足的种族/族裔少数族裔老年人中,糖尿病、高血压和缺牙之间的相互关系。
年龄在50岁及以上的社区居住的老年微笑项目参与者提供了自我报告的社会人口学特征以及健康和医疗保健信息,这些参与者于2010年至2012年在纽约曼哈顿的老年中心参加了社区口腔健康教育并完成了一份筛查问卷。
多变量模型(二元和有序逻辑回归)结果一致,即当纳入自我报告的糖尿病和自我报告的高血压,以及自我报告的糖尿病和自我报告的高血压之间的交互项时,年龄较大和医疗补助覆盖是重要的协变量。
一种被概念化为牙科、医学和公共卫生这三个领域交叉的口腔公共卫生方法,可能在针对医疗服务不足的老年人进行基于地点的评估和服务提供方面证明是有用的。此外,一个考虑缺牙水平的有序逻辑模型可能比二元逻辑模型产生更具信息性和可解释性的结果。