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Risk factors for development of chronic periodontitis in Bulgarian patients (pilot research)
The aim of this work was to assess the risks and analyse the risk factors for development of chronic periodontitis in Bulgarian patients. The quality of life was investigated in a cohort of 228 patients with chronic periodontitis. Within the frame of this study, pilot research (a case-control study)...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4433785/ https://www.ncbi.nlm.nih.gov/pubmed/26019602 http://dx.doi.org/10.1080/13102818.2014.974328 |
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author | Stoykova, Maria Musurlieva, Nina Boyadzhiev, Doychin |
author_facet | Stoykova, Maria Musurlieva, Nina Boyadzhiev, Doychin |
author_sort | Stoykova, Maria |
collection | PubMed |
description | The aim of this work was to assess the risks and analyse the risk factors for development of chronic periodontitis in Bulgarian patients. The quality of life was investigated in a cohort of 228 patients with chronic periodontitis. Within the frame of this study, pilot research (a case-control study) was conducted among 80 patients (20 cases and 60 control patients without periodontitis) to evaluate the risk for development of chronic periodontitis. The minimum sample size of patients was determined based on power analysis for sample-size calculation. The mean age of participants in the control group was 31.33 ± 9.38 years and in the case group, 33.00 ± 11.52. Data were accumulated by clinical and sociological methods. Descriptive statistics and multi-factor logistic regression analysis (Backward Conditional procedure) were used. One-factor dispersion analysis showed that, of the 12 studied risk factors, the following variables were significant: stress, diabetes, presence of calculus, overlapping and misaligned teeth (P < 0.05). Multiple logistic regressions were applied to evaluate the association between the variables. Three predictors were selected in the final logistic regression equation: diabetes (B = 4.195; P = 0.001), crooked and overlapping teeth (B = 3.022; P = 0.010) and stress (B = 2.882; P = 0.014). The logistic risk assessment model for development of periodontitis has a predictive value of 93.80% (χ(2) = 63.91; P = 0.000). Our results confirmed some proven risk factors for periodontal disease. In the studied population, diabetes was the single, most important predictor for development of periodontitis. |
format | Online Article Text |
id | pubmed-4433785 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-44337852015-05-25 Risk factors for development of chronic periodontitis in Bulgarian patients (pilot research) Stoykova, Maria Musurlieva, Nina Boyadzhiev, Doychin Biotechnol Biotechnol Equip Article; Medical Biotechnology The aim of this work was to assess the risks and analyse the risk factors for development of chronic periodontitis in Bulgarian patients. The quality of life was investigated in a cohort of 228 patients with chronic periodontitis. Within the frame of this study, pilot research (a case-control study) was conducted among 80 patients (20 cases and 60 control patients without periodontitis) to evaluate the risk for development of chronic periodontitis. The minimum sample size of patients was determined based on power analysis for sample-size calculation. The mean age of participants in the control group was 31.33 ± 9.38 years and in the case group, 33.00 ± 11.52. Data were accumulated by clinical and sociological methods. Descriptive statistics and multi-factor logistic regression analysis (Backward Conditional procedure) were used. One-factor dispersion analysis showed that, of the 12 studied risk factors, the following variables were significant: stress, diabetes, presence of calculus, overlapping and misaligned teeth (P < 0.05). Multiple logistic regressions were applied to evaluate the association between the variables. Three predictors were selected in the final logistic regression equation: diabetes (B = 4.195; P = 0.001), crooked and overlapping teeth (B = 3.022; P = 0.010) and stress (B = 2.882; P = 0.014). The logistic risk assessment model for development of periodontitis has a predictive value of 93.80% (χ(2) = 63.91; P = 0.000). Our results confirmed some proven risk factors for periodontal disease. In the studied population, diabetes was the single, most important predictor for development of periodontitis. Taylor & Francis 2014-11-02 2014-11-12 /pmc/articles/PMC4433785/ /pubmed/26019602 http://dx.doi.org/10.1080/13102818.2014.974328 Text en © 2014 The Author(s). Published by Taylor & Francis. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted. |
spellingShingle | Article; Medical Biotechnology Stoykova, Maria Musurlieva, Nina Boyadzhiev, Doychin Risk factors for development of chronic periodontitis in Bulgarian patients (pilot research) |
title | Risk factors for development of chronic periodontitis in Bulgarian patients (pilot research) |
title_full | Risk factors for development of chronic periodontitis in Bulgarian patients (pilot research) |
title_fullStr | Risk factors for development of chronic periodontitis in Bulgarian patients (pilot research) |
title_full_unstemmed | Risk factors for development of chronic periodontitis in Bulgarian patients (pilot research) |
title_short | Risk factors for development of chronic periodontitis in Bulgarian patients (pilot research) |
title_sort | risk factors for development of chronic periodontitis in bulgarian patients (pilot research) |
topic | Article; Medical Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4433785/ https://www.ncbi.nlm.nih.gov/pubmed/26019602 http://dx.doi.org/10.1080/13102818.2014.974328 |
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