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Updated: Jul 2, 2025

A Novel Approach to Monitoring Graft Neovascularization in the Human Gingiva
Published on: January 12, 2019
Explaining the colour of natural healthy gingiva
Cristina Gómez-Polo1, Javier Montero2, Ana Maria Martín Casado3
1Department of Surgery, School of Medicine, University of Salamanca, Campus Miguel de Unamuno s/n, 37007, Salamanca, Spain. crisgodent@usal.es.
Abstract:
To examine the differences between natural gingival colour in men and women. To determine the degree of predictability of changes in the gingival colour coordinates recorded for healthy gingiva, according to age, long-term medication, frequency of toothbrushing, and smoking habits. The CIELAB colour coordinates were recorded using a spectrophotometer for 360 Caucasian adult participants (aged 18-92 years), in three zones of the healthy attached gingiva of the maxillary central incisor. Regression models were created for each zone and each sex, taking the L*, a* and b* coordinates as dependent variables and age, frequency of toothbrushing, smoking habits (0-non-smoker; 1-smoker) and whether participants were taking long-term medication (0-no; 1-yes) as independent variables. The statistical analysis was conducted with SPSS version 26.0, using multiple regression models. Statistically significant differences between men and women were found only for colour coordinate b*, in all three zones. The only colour coordinate on which the predictor variables had a significant effect was the L* coordinate. In men, age and long-term medication had the greatest effect as predictors (maximum R2 = 0.149). In women, frequency of toothbrushing was the strongest predictor in the predictive models (maximum R2 = 0.099). The colour of gingiva in men contained a larger amount of blue, given that significantly lower values for colour coordinate b* were recorded in men than women, although this difference lacked clinical implications. For both sexes, the regression models produced had a modest predictive capacity. The L* coordinate was the dependent variable that showed the greatest predictability.
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