10 July 2023

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Vitamin D and periodontal disease

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Objective

There are conflicting reports on the relationship between vitamin D and periodontal disease. This research aimed to further analyze the association between serum 25(OH)D3, a vitamin D precursor and periodontal disease based on a large national survey sample in Japan.

Methods

The research team downloaded the 2009–2018 National Health and Nutrition Examination Survey (NHANES), which included a total of 23,324 samples. Logistic regression of factors influencing perioral disease including periodontal disease, and subgroup logistic regression were performed to analyze the relationship between serum vitamin D and perioral disease, using WTMEC2YR as weights for regression analysis. Then the team used a machine learning model–based prediction of perioral disease onset. The machine learning algorithms used included boost tree, artificial neural network, AdaBoost and random forest.

Results

Researchers evaluated the vitamin D, age, sex, race, education, marriage, body mass index, ratio of family income to poverty (PIR), smoking, alcohol consumption, diabetes and hypertension as variables in the included samples. Vitamin D was negatively associated with perioral disease; compared with Q1, the odds ratios and 95% CI were 0.8 (0.67–0.96) for Q2, 0.84 (0.71–1.00) for Q3, and 0.74 (0.6–0.92) for Q4 (P for trend <.05), respectively.

The results of the subgroup analysis showed that the effect of 25(OH)D3 on periodontal disease was more pronounced in women younger than 60 years of age. Based on the accuracy and receiver operating characteristic curve, researchers concluded that a boost tree was a relatively good model to predict periodontal disease.

Conclusions

Vitamin D might be a protective factor for periodontal disease, and boost tree analysis employed in the study was a relatively good model to predict perioral disease.

Ying Li, Jinjuan Wang, Yunxian Cai, Haokun Chen, "Association of Serum Vitamin D With Periodontal Disease," International Dental Journal, 2023, ISSN 0020-6539, https://doi.org/10.1016/j.identj.2023.06.004.