Document Detail


What statistical method should be used to evaluate risk factors associated with dmfs index? Evidence from the National Pathfinder Survey of 4-year-old Italian children.
MedLine Citation:
PMID:  19845715     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND: Traditional approaches to the analysis of dmfs/DMFS count data pose analytical challenges, considering the increasing proportion of zeroes in the distribution. The aim of this paper was to predict the probability of 'caries-free' subjects and the dependence of dmfs index on the influence of childhood sociodemographic factors, through the application of regression models. METHODS: Data were gathered as part of the National Pathfinder Survey of 4-year-old Italian children. Clinical data on caries disease (dmfs) and childhood sociodemographic factors were collected. The predicted probability for Poisson, negative binomial and zero-inflated models (Poisson and negative binomial) were estimated using STATA commands for count outcomes. The outcome variable in the regression models was the severity of the disease (dmfs index), while statistically significant variables on bivariate analysis were considered as covariates. RESULTS: Out of 5538 children, 4344 (78.44%) had a dmfs = 0. The mean dmfs index was 1.36 (range: 0-104). The statistical significance of the dispersion parameter (O = 141.6, P < 0.0001) showed the inappropriateness of the Poisson model when compared with the negative binomial model. Vuong's test indicated that the zero-inflated models (ZIP and ZINB) fitted the data significantly better than the others (P < 0.001). A significative likelihood ratio statistic indicates that the ZINB regression model fitted better than ZIP model (P < 0.0001). The father's educational level was significant in both parts of the ZINB regression model (P < 0.05), implying that the degree of caries experience increases in children whose fathers have a low level of education, while the excess of caries-free children decreases. Moreover, the increase of coefficients in the zero-inflated part of ZINB regression model implies that the excess of caries-free subjects increases with the later age of tooth eruption. The observed underestimation of the frequencies of zero dmfs counts by the Poisson model is a common result when a dual-group process is not taken into account. CONCLUSIONS: These regression models provide a useful approach to handling count outcomes as dmfs/DMFS index in caries epidemiology.
Authors:
Giuliana Solinas; Guglielmo Campus; Carmelo Maida; Giovanni Sotgiu; Maria Grazia Cagetti; Emmanuel Lesaffre; Paolo Castiglia
Related Documents :
20728975 - The impact of downsizing on remaining workers' sickness absence.
18310095 - Biological behavior of cin lesions is predictable by multiple parameter logistic regres...
9465995 - Adjustment for regression dilution in epidemiological regression analyses.
10399205 - Testing proportionality in the proportional odds model fitted with gee.
16527285 - Biomechanics of side impact: injury criteria, aging occupants, and airbag technology.
19162665 - Estimation of muscle strength during motion recognition using multichannel surface emg ...
Publication Detail:
Type:  Journal Article     Date:  2009-10-21
Journal Detail:
Title:  Community dentistry and oral epidemiology     Volume:  37     ISSN:  1600-0528     ISO Abbreviation:  Community Dent Oral Epidemiol     Publication Date:  2009 Dec 
Date Detail:
Created Date:  2009-11-17     Completed Date:  2010-02-01     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0410263     Medline TA:  Community Dent Oral Epidemiol     Country:  Denmark    
Other Details:
Languages:  eng     Pagination:  539-46     Citation Subset:  D; IM    
Affiliation:
Institute of Hygiene and Preventive Medicine, Unit of Biostatistics, Sassari, Italy. giuliana.solinas@uniss.it
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Child, Preschool
Cross-Sectional Studies
DMF Index*
Dental Caries / epidemiology
Health Surveys
Humans
Italy / epidemiology
Poisson Distribution
Prevalence
Regression Analysis*
Risk Factors

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Quantification of betel quid chewing and cigarette smoking in oral cancer patients.
Next Document:  Topical antibiotics: therapeutic value or ecologic mischief?