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A comparison of ordinal regression models in an analysis of factors associated with periodontal disease

机译：序贯回归模型在牙周疾病相关因素分析中的比较

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Aim:The study aimed to determine the factors associated with periodontal disease (different levels of severity) by using different regression models for ordinal data.Design:A cross-sectional design was employed using clinical examination and ‘questionnaire with interview’ method.Materials and Methods:The study was conducted during June 2008 to October 2008 in Dharwad, Karnataka, India. It involved a systematic random sample of 1760 individuals aged 18-40 years. The periodontal disease examination was conducted by using Community Periodontal Index for Treatment Needs (CPITN).Statistical Analysis Used:Regression models for ordinal data with different built-in link functions were used in determination of factors associated with periodontal disease.Results:The study findings indicated that, the ordinal regression models with four built-in link functions (logit, probit, Clog-log and nlog-log) displayed similar results with negligible differences in significant factors associated with periodontal disease. The factors such as religion, caste, sources of drinking water, Timings for sweet consumption, Timings for cleaning or brushing the teeth and materials used for brushing teeth were significantly associated with periodontal disease in all ordinal models.Conclusions:The ordinal regression model with Clog-log is a better fit in determination of significant factors associated with periodontal disease as compared to models with logit, probit and nlog-log built-in link functions. The factors such as caste and time for sweet consumption are negatively associated with periodontal disease. But religion, sources of drinking water, Timings for cleaning or brushing the teeth and materials used for brushing teeth are significantly and positively associated with periodontal disease.
机译：目的：本研究旨在通过使用不同的序贯数据回归模型来确定与牙周疾病相关的因素（严重程度不同）。设计：采用临床检查和``访谈问卷''的方法进行横断面设计。方法：该研究于2008年6月至2008年10月在印度卡纳塔克邦达瓦德进行。它涉及1760名18-40岁的个体的系统随机样本。使用社区牙周治疗需要指数（CPITN）进行牙周疾病检查。统计分析使用：使用具有不同内置链接功能的序数数据回归模型确定与牙周疾病相关的因素。结果：研究结果指出，具有四个内置链接功能（logit，probit，Clog-log和nlog-log）的有序回归模型显示出相似的结果，与牙周疾病相关的重要因素差异可忽略不计。在所有序数模型中，诸如宗教，种姓，饮用水来源，甜食的时间，牙齿清洁或刷牙的时间以及刷牙的材料等因素均与牙周疾病密切相关。结论：采用Clog的序数回归模型与具有logit，probit和nlog-log内置链接功能的模型相比，-log更适合确定与牙周疾病相关的重要因素。种姓和甜食时间等因素与牙周疾病负相关。但是宗教，饮用水来源，清洁或刷牙的时间以及刷牙的材料与牙周疾病有显着正相关。

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