Meyer Frederic, Karch André, Schlinkmann Kristin Maria, Dreesman Johannes, Horn Johannes, Rübsamen Nicole, Sudradjat Henny, Schubert Rainer, Mikolajczyk Rafael
Microbial Communication, Helmholtz Centre for Infection Research, Braunschweig, Germany.
ESME - Epidemiological and Statistical Methods Research Group, Department of Epidemiology, Helmholtz Centre for Infection Research, Braunschweig, Germany.
Community Dent Oral Epidemiol. 2017 Oct;45(5):442-448. doi: 10.1111/cdoe.12308. Epub 2017 May 26.
To identify spatial disparities in dental caries experience (measured by dmft (decayed missing filled teeth) index) of children in the city of Braunschweig and to evaluate whether these disparities can be explained by sociodemographic characteristics.
We examined the dental health of children aged 3-6 years visiting a daycare centre (DCC) in the metropolitan area of Braunschweig between 2009 and 2014 by combining data on dental health from the annual visits of the local health service with aggregated data on sociodemographic factors for Braunschweig's city districts. We assessed longitudinal patterns of change in average dmft index at district level from 2009 to 2014 using a finite mixture model. We analysed spatial autocorrelation of the district's average dmft indices by Moran's I to identify spatial clusters. With a spatial lag model, we evaluated whether sociodemographic risk factors (data from 2012) were associated with high dmft scores (data from 2014) and whether spatial disparities remained after adjusting for these sociodemographic characteristics.
The average dmft index decreased slightly (β=-0.048; P<.03; CI 95% [-0.079; -0.017]) from 2009 to 2014. The finite mixture model resulted in four different groups of trajectories over time. While three groups showed a decrease in dmft score, one group showed an increase from 2009 to 2014. Moran's I test statistic showed strong evidence for spatial clustering (Moran's I 0.30, P=.002). A cluster of districts with high dmft values was identified in the centre of the city. The spatial lag model showed that both the proportion of unemployed persons (aged 16-65) and the proportion of persons with migration background were associated with the dmft values at district level. After adjusting for these, no further spatial heterogeneity was observed.
We identified regional clusters for poor dental health in a German city and showed that these clusters can be explained by sociodemographic characteristics. The findings support the need of targeted interventions and prevention measures in regions with less favourable sociodemographic characteristics.
确定不伦瑞克市儿童龋齿患病情况（以dmft（龋失补牙数）指数衡量）的空间差异，并评估这些差异是否可由社会人口学特征来解释。
我们通过将当地卫生服务机构年度访视的牙齿健康数据与不伦瑞克市各城区社会人口学因素的汇总数据相结合，对2009年至2014年间在不伦瑞克市区一家日托中心（DCC）就诊的3至6岁儿童的牙齿健康状况进行了检查。我们使用有限混合模型评估了2009年至2014年各城区平均dmft指数的纵向变化模式。我们通过莫兰指数分析各城区平均dmft指数的空间自相关性，以识别空间聚类。使用空间滞后模型，我们评估了社会人口学风险因素（2012年数据）是否与高dmft得分（2014年数据）相关，以及在调整这些社会人口学特征后空间差异是否仍然存在。
2009年至2014年，平均dmft指数略有下降（β=-0.048；P<.03；95%置信区间[-0.079；-0.017]）。有限混合模型得出了随时间变化的四种不同轨迹组。虽然三组显示dmft得分下降，但一组从2009年至2014年呈上升趋势。莫兰指数检验统计量显示出空间聚类的有力证据（莫兰指数0.30，P=.002）。在市中心发现了一个dmft值较高的城区集群。空间滞后模型显示，失业人员（16至65岁）比例和有移民背景人员比例均与城区层面的dmft值相关。调整这些因素后，未观察到进一步的空间异质性。
我们在德国一个城市中识别出了牙齿健康状况较差的区域集群，并表明这些集群可由社会人口学特征来解释。研究结果支持在社会人口学特征不太有利的地区采取有针对性的干预措施和预防措施的必要性。
