Purpose: 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.
Materials And Methods: 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.
Results: 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.
Conclusions: 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.
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| http://dx.doi.org/10.3290/j.ohpd.b5816556 | DOI Listing |
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11619838 | PMC |
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