Cureus | Assessing the Association between Oral Hygiene and Preterm Birth by Quantitative Light-Induced Fluorescence
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Research Article

Assessing the Association between Oral Hygiene and Preterm Birth by Quantitative Light-Induced Fluorescence

Christopher K. Hope, Qian Wang, Girvan Burnside, Adejumoke A. Adeyemi, Siobhan Quenby, Philip W. Smith, Susan M. Higham, Melissa Whitworth

Published:

DOI: 10.1155/2014/374694

License: Copyright © 2014 Christopher K. Hope et al. 2014 This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The aim of this study was to investigate the purported link between oral hygiene and preterm birth by using image analysis tools to quantify dental plaque biofilm. Volunteers (n = 91) attending an antenatal clinic were identified as those considered to be “at high risk” of preterm delivery (i.e., a previous history of idiopathic preterm delivery, case group) or those who were not considered to be at risk (control group). The women had images of their anterior teeth captured using quantitative light-induced fluorescence (QLF). These images were analysed to calculate the amount of red fluorescent plaque (ΔR%) and percentage of plaque coverage. QLF showed little difference in ΔR% between the two groups, 65.00% case versus 68.70% control, whereas there was 19.29% difference with regard to the mean plaque coverage, 25.50% case versus 20.58% control. A logistic regression model showed a significant association between plaque coverage and case/control status (P = 0.031), controlling for other potential predictor variables, namely, smoking status, maternal age, and body mass index (BMI).


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Scholarly Impact Quotient™ (SIQ™)

Scholarly Impact Quotient™ (SIQ™) is our unique post-publication peer review rating process. SIQ™ assesses article importance and quality by embracing the collective intelligence of the Cureus community-at-large. All registered users are invited to contribute to the SIQ™ of any published article. (Authors cannot rate their own articles.)

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