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Quintessence Publishing: Journals: OHPD


Oral Health & Preventive Dentistry

Edited by Anton Sculean, Poul Erik Petersen, Avijit Banerjee

ISSN (print) 1602-1622 • ISSN (online) 1757-9996


Winter 2013
Volume 11 , Issue 4

Pages: 349-358
PMID: 23957046
DOI: 10.3290/j.ohpd.a30480
Share Abstract:

A Cohort Study of Caries Incidence and Baseline Socioeconomic, Clinical and Demographic Variables: A Kaplan-Meier Survival Analysis

Cortellazzi, Karine Laura / Tagliaferro, Elaine Pereira da Silva / Pereira, Stela Márcia / Ambrosano, Gláucia Maria Bovi / Guerra, Luciane Miranda / Vazquez, Fabiana de Lima / Meneghim, Marcelo de Castro / Pereira, Antonio Carlos

Purpose: To determine the incidence of dental caries and evaluate the influence of socioeconomic, clinical and demographic variables on the time for disease to appear in the permanent teeth after 3 years of follow-up.
Materials and Methods: The random sample of this cohort study consisted of 427 5-year-old preschool children attending 22 public preschools in Piracicaba, SP, Brazil. Dental caries was measured using the dmf/DMF indices. The Kaplan- Meier survival analysis method was used to study the isolated effect of socioeconomic, clinical and demographic variables on caries incidence after 3 years. A Cox proportional hazards regression model was built to test the influence of the variables collected at baseline on time to develop DMFT increment.
Results: Survival analysis showed that children without past caries experience in primary teeth at baseline remained caries free in permanent teeth for a longer period than children with past caries experience at baseline. The variables monthly family income, parents’ educational level, number of people living in the household, home ownership and car ownership were not significant.
Conclusion: Children who presented past caries experience in primary teeth at baseline are at greater risk of developing DMFT increment than children who have no past caries experience at baseline.

Keywords: dental caries, risk assessment, risk predictor, survival analysis

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