Objective: To identify, in a group of 6-8-year-old schoolchildren, risk factors for dental caries increment in permanent dentition. Methods: Two hundred and six children from three different schools in Piracicaba, Brazil, were examined at baseline and after 7 years by the same two calibrated dentists. Data on dental caries (dmfs, DMFS, presence of initial lesions), fluorosis, oral hygiene and presence of sealant were collected at the clinical examination that was performed in an outdoor setting, under natural light, using a dental mirror and probe following the WHO recommendations. Information on socioeconomic level, fluoride usage, dental service utilization, dietary and oral hygiene habits was also obtained at baseline In a semi-structured questionnaire sent to the parents. The dependent variable was the 7-year DMFS increment. A univariate analysis was performed to test the association of independent variables in caries increment. Then a logistic regression model was used to estimate the adjusted Odds Ratio for caries increment. Results: Clinical (dmfs, DMFS) and non-clinical variables (daily toothbrushing, use of preventive topical methods, parents' educational level) were entered in the multiple logistic regression analysis. The prediction model included the clinical and socioeconomic variables, DMFS, dmfs and mother's educational level. The best caries predictor was the dmfs variable. Conclusion: Caries experience and mother's educational level were predictors of caries increment in permanent dentition.663169173Disney, J.A., Graves, R.C., Stamm, J.W., Bohannan, H.M., Abernathy, J.R., Zack, D.D., The University of North Carolina Caries Risk Assessment study: Further developments in caries risk prediction (1992) Community Dent Oral Epidemiol, 20, pp. 64-75Tinanoff, N., Critique of evolving methods for caries risk assessment (1995) J Dent Educ, 59, pp. 980-985Raitio, M., Pienihakkinen, K., Scheinin, A., Multifactorial modeling for prediction of caries increment in adolescents (1996) Acta Odontol Scand, 54, pp. 118-121Petti, S., Hausen, H.W., Caries prediction by multiple salivary mutans streptococcal counts in caries-free children with different levels of fluoride exposure, oral hygiene and sucrose intake (2000) Caries Res, 34, pp. 380-387Wandera, A., Bhakta, S., Barker, T., Caries prediction and indicators using a pediatric risk assessment teaching tool (2000) J Dent Child, 67, pp. 408-412Van Palenstein Helderman, W.H., Mulder, J., Van't Hof, M.A., Truin, G.J., Validation of a Swiss method of caries prediction in Dutch children (2001) Community Dent Oral Epidemiol, 29, pp. 341-345Vanobbergen, J., Martens, L., Lesaffre, E., Bogaerts, K., Declerck, D., The value of a baseline caries risk assessment model in the primary dentition for the prediction of caries incidence in the permanent dentition (2001) Caries Res, 35, pp. 442-450Pearce, E.I.F., Dong, Y.M., Yue, L., Gao, X.J., Purdie, G.L., Wang, J.D., Plaque minerals in the prediction of caries activity (2002) Community Dent Oral Epidemiol, 30, pp. 61-69Stenlund, H., Mejare, I., Kallestal, C., Caries rates related to approximal caries at ages 11-13: A 10-year follow-up study in Sweden (2002) J Dent Res, 81, pp. 455-458Bader, J.D., Perrin, N.A., Maupome, G., Rindal, B., Rush, W.A., Validation of a simple approach to caries risk assessment (2005) J Public Health Dent, 65, pp. 76-81Hausen, H., Caries prediction - State of the art (1997) Community Dent Oral Epidemiol, 25, pp. 87-96Demers, M., Brodeur, J.M., Mouton, C., Simard, P.L., Trahan, L., Veilleux, G., A multivariate model to predict caries increment in Montreal children aged 5 years (1992) Community Dent Health, 9, pp. 273-281Grindefjord, M., Dahllof, G., Nilsson, B., Modeer, T., Prediction of dental caries development in 1-year-old children (1995) Caries Res, 29, pp. 343-348Burt, B.A., Prevention policies in the light of the changed distribution of dental caries (1998) Acta Odontol Scand, 56, pp. 179-186Li, Y., Wang, W., Predicting caries in permanent teeth from caries in primary teeth: An eight-year cohort study (2002) J Dent Res, 81, pp. 561-566Landis, J.R., Koch, G.G., The measurement of observer agreement for categorical data (1977) Biometrics, 33, pp. 159-174(1987) Oral Health Surveys. Basic Methods. 3rd Ed., , World Health Organization. Geneva: WHORimmer, P.A., Pitts, N.B., Effects of diagnostic threshold and overlapped approximal surfaces on reported caries status (1991) Community Dent Oral Epidemiol, 19, pp. 205-212Greene, J.C., Vermillion, J.R., The simplified oral hygiene index (1964) J Am Dent Assoc, 68, pp. 7-13Dean, H.T., Classification of mottled enamel diagnosis (1934) J Am Dent Assoc, 21, pp. 1421-1426Russel, A.L., The differential diagnosis of fluoride and non-fluoride enamel opacities (1961) J Public Health Dent, 21, pp. 143-146Krasse, B., Biological factors as indicators of future caries (1988) Int Dent J, 38, pp. 219-225(2001) SAS/STAT 8.2. Guide for Personal Computers, , SAS Institute Inc. Cary: SAS Institute(2004) SB Brazil 2003 Project - Oral Health Conditions of the Brazilian Population 2002-2003, , http://portalweb02.saude.gov.br/portal/arquivos/pdf/ relatorio_brasil_sorridente.pdf, Brazil. Health Ministry of Brazil. Brasília, DF, (in Portuguese). Available at. Accessed June 2005Tagliaferro, E.P.S., Cypriano, S., Sousa, M.L.R., Wada, R.S., Caries experience among schoolchildren in relation to community fluoridation status and town size (2004) Acta Odontol Scand, 62, pp. 124-128Burt, B.A., Concepts of risk in dental public health (2005) Community Dent Oral Epidemiol, 33, pp. 240-247