Explaining the colour of natural healthy gingiva

Author:

Gómez-Polo CristinaORCID,Montero Javier,Martín Casado Ana Maria

Abstract

AbstractTo 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.

Funder

Universidad de Salamanca

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3