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Updated: Jun 17, 2026

Oral Health Assessment by Lay Personnel for Older Adults
Published on: February 2, 2020
Assessment of factors associated with dental caries in rural communities in Rakai District, Uganda
Charles Mugisha Rwenyonyi1, Louis Mugambe Muwazi, William Buwembo
1Department of Dentistry, College of Health Sciences, Makerere University, P. O. Box 7072, Kampala, Uganda. mrwenyonyi@chs.mak.ac.ug
Abstract:
To assess factors associated with dental caries in rural communities in Rakai District, Uganda. This was a cross-sectional survey in 18-62 year olds, randomly selected from three sub-counties: Kyalurangira (n = 121), Kabira (n = 133), and Kacheera (n = 67). The participants were clinically examined for caries using Decayed Missing Filled Teeth (DMFT) index and were administered to a structured questionnaire. In the whole material, caries prevalence (DMFT score > 0) was 57.3% and the mean DMFT score was 2.3. The M-component contributed 61% of the DMFT scores. Using bivariate analyses, age, consumption of sugared snacks and tobacco smoking were directly and significantly associated with development of dental caries. Tooth cleaning and previous dental visits were indirectly and significantly associated with dental caries. In binary logistic regression analyses, the participants who were older were four times and those who consumed sugared snacks were 11 times more likely to develop dental caries as compared to their counterparts. The participants who cleaned their teeth or who had visited the dentists were less likely to develop dental caries as compared to their counterparts. The odds ratios were 0.6 and 0.5, respectively. Based on stepwise multiple linear regression analyses, age, previous dental treatment, consumption of sugared snacks, tooth cleaning and tobacco smoking explained a total of 46% of the variations in DMFT scores. Caries prevalence and severity were relatively low in this population. Although a number of independent variables were significantly associated with caries they gave a modest overall multivariate model.
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