【摘要】 目的　测量北京市城区居民牙科服务就诊概率的影响因素 ,建立口腔保健就诊概率模型 ,为预测未来口腔保健需求量 ,建立合理有效的口腔保健服务体系提供依据。方法　分层、整群、随机抽取北京市区实际人口中所有年龄组 15 17人进行调查 ,用Logistic回归建立口腔保健需求的第一部模型———就诊概率模型。结果　认识是影响就诊概率的最主要因素 ,R值为 0 3 6,OR值为 4 8 79。医生教师、7～ 14岁儿童、出现明显疼痛症状或影响功能疾病及社会经济因素对就诊概率有较大影响。结论　口腔卫生服务领域存在与医疗服务需求有所不同的作用机制。人们的牙科服务利用主要取决于其对疾病的认识以及收入和保障制度的高低。更多还原

【Abstract】 Objective To develop probability model for dental visits based on analysis of the factors affecting people′s dental services utilization in urban area of Beijing, thus p roviding some evidence for forecasting further demanded denta l care and building the more efficient oral health care delivery system. Methods A cross-sectional survey was conducted among 1 517 subje cts of all age groups in Beijing selected by stratified, clustering, random samp ling. The first model of dental care demand--probability model for dental vi sits was established with logistic regression. Results Awareness of oral health showed the most important relationship. Different social background and economic facto rs also had great effects on demand. Higher demand for care were existed among those who suffered f rom a disease that was painful or resulted in poor oral function. Concl usions It is suggested that dental care has different characters from general health ser vice. Utilization of dental service is largely determined by people′s awarenes s, income and insurance system. So oral health education should be extended in or d er to promote the effective demands and reduce the potential demands. Rational o ral health insurance system should be set up to provide some priority to certain people, thus stimulating the supply of dental care and improving the utilization of dental service. Since raising price for care will restrain the low-income r′ s basic demand, and it will neither add the profit nor improve people′s oral he a lth, the price decision should be considered carefully. At last, oral health ca r e should be emphasized on children and adolescent as priority age groups based o n the conclusion from demand model.更多还原