Oral Health Prev Dent. 2024 Nov 7;22:573-582. doi: 10.3290/j.ohpd.b5816556.
Periodontal diseases, commonly linked to dental biofilm and affecting adults, were studied using Geographic Information Systems (GIS) and Kernel Analyses with epidemiological data. This paper presents a hybrid method for use in epidemiological studies by evaluating the spatiotemporal distribution of disease prevalence.
This study analy ed 47,757 patients from the Department of Periodontology out of 662,351 visitors to University Faculty of Dentistry (2012 to July 2023). The central districts of Kayseri in Turkey were selected as the study areas. Periodontitis prevalence was assessed through radiographic evidence and clinical examination. Point-based location data, including gender, age, and disease type, matched household data, creating building-based spatial data. Kernel Density (KD) and Average Nearest Neighbor (ANN) analyses examined patient concentration and disease types in specific regions. Accordingly, standard deviation ellipses were prepared by year to assess the spatial changes in the regions where patients resided.
The study found higher periodontitis prevalence in males, increasing with age, while gingivitis decreased. After 2017, periodontitis prevalence notably declined. Location-based data exhibited clustering in patient distribution. KD maps showed similar patient distributions over the years, with more applications from areas closer to the Faculty of Dentistry. The spatial distribution of the patients applying has remained consistent over the last 5 years.
Through GIS, KD maps reveal the spatial-temporal distribution of periodontitis patients. This aids in identifying high-prevalence regions and guiding strategic healthcare facility placement. Implementing preventive programs in high-demand areas, particularly in family health centers (local health facilities), can reduce community-wide periodontal disease prevalence.
牙周病通常与牙菌斑有关，影响成年人，本研究使用地理信息系统（GIS）和核密度分析方法结合流行病学数据进行研究。本文提出了一种混合方法，用于评估疾病流行率的时空分布，以进行流行病学研究。
本研究分析了土耳其开塞利市中心地区的 47757 名患者，这些患者来自于大学牙科学院的 662351 名就诊者（2012 年至 2023 年 7 月）。通过放射影像学证据和临床检查评估牙周炎的流行率。基于点的位置数据，包括性别、年龄和疾病类型，与家庭数据相匹配，创建基于建筑物的空间数据。核密度（KD）和平均最近邻（ANN）分析检查了特定区域的患者集中程度和疾病类型。相应地，按年份准备标准偏差椭圆，以评估患者居住区域的空间变化。
研究发现男性的牙周炎患病率较高，且随着年龄的增长而增加，而牙龈炎的患病率则下降。2017 年后，牙周炎的患病率显著下降。基于位置的数据显示患者分布存在聚类现象。KD 图显示了多年来患者分布的相似性，靠近牙科学院的地区有更多的应用。过去 5 年来，患者申请的空间分布保持一致。
通过 GIS，KD 图揭示了牙周病患者的时空分布。这有助于确定高患病率区域，并指导战略性医疗设施的设置。在高需求地区（特别是在家庭健康中心）实施预防计划可以降低社区范围内牙周病的患病率。
