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What are the most accurate predictors of caries in children aged 5 years in the UK?

机译:在英国5岁的儿童中,龋齿最准确的预测因素是什么?

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Objective: To find the most accurate indicators of the distribution of dental caries in 5-year-olds in the city of Sheffield, UK, using a conceptual framework based on the social determinants of health. Method: A list of structural and intermediary indicators was compiled based on the Commission on the Social Determinants of Health's (CSDH) conceptual framework. To quantify these indicators, existing data on dental caries were obtained from the NHS Dental Epidemiology Programme, while data on social position, education, employment, income, material circumstances, social cohesion, psychosocial factors and individual behaviours were obtained from the Public Health Intelligence Team at Sheffield City Council. These data were mapped onto a simplified framework of the social determinants of dental caries. Regression analysis was conducted on this simplified framework to determine the amount of variance each indicator contributed to the distribution of dental caries at neighbourhood level. Results: The total score for the 2010 Index of Multiple Deprivation contributed a significant amount of variance (60.4%) compared to the combined variance of the other 13 indicators (70.5%). Conclusion: The total IMD score has the potential to be used as an indicator for the targeting of oral health improvement programmes where survey data are not available. A large prospective study is required in the UK to investigate the full range of factors in the CSDH model to develop a new index which might better predict dental caries experience than IMD.
机译:目的:使用基于健康社会决定因素的概念框架,找出英国谢菲尔德市5岁儿童龋齿分布的最准确指标。方法:根据卫生社会决定因素委员会(CSDH)概念框架编制了结构和中介指标清单。为了量化这些指标,从NHS牙科流行病学计划获得了龋齿的现有数据,而社会地位,教育,就业,收入,物质环境,社会凝聚力,社会心理因素和个人行为的数据则从公共卫生情报团队获得在谢菲尔德市议会。这些数据被映射到龋齿社会决定因素的简化框架。在此简化的框架上进行了回归分析,以确定每个指标对邻域龋齿分布的贡献程度。结果:与其他13个指标的总和方差(70.5%)相比,2010年多重剥夺指数的总分贡献了显着的方差(60.4%)。结论:IMD总分有可能用作无法获得调查数据的口腔健康改善计划的指标。英国需要进行大规模的前瞻性研究,以调查CSDH模型中的所有因素,以开发出一个新的指数,该指数可能比IMD更好地预测龋齿的发生。

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