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Using zero inflated models to analyze dental caries with many zeroes
Shivalingappa B Javali1, Parameshwar V Pandit
1Department of Public Health Dentistry, SDM College of Dental Sciences & Hospital, Dharwad, Karnataka, India. javalimanju@rediffmail.com
Summary
This study used zero-inflated models to analyze dental caries (DMFT) data. Factors like family size and brushing frequency were linked to caries, while sweet consumption showed a negative association.
Area of Science:
- Dental Public Health
- Biostatistics
- Epidemiology
Background:
- Dental caries (DMFT) data often exhibit excess zeros, posing challenges for standard statistical analysis.
- Zero-inflated models offer a potential solution for analyzing count data with a high prevalence of zero values.
Purpose of the Study:
- To analyze factors associated with dental caries experience using zero-inflated models.
- To compare the performance of Zero Inflated Poisson (ZIP) and Zero Inflated Negative Binomial (ZINB) models for DMFT data.
Main Methods:
- Cross-sectional study involving 1760 individuals aged 18-40 years in Dharwad, India.
- DMFT index used for dental caries assessment.
- Zero Inflated Poisson (ZIP) and Zero Inflated Negative Binomial (ZINB) models applied to analyze DMFT data.
Main Results:
- Family size, brushing frequency, and toothbrush replacement duration were positively associated with dental caries.
- Frequency of sweet consumption showed a negative association with dental caries experience.
- Both ZIP and ZINB models provided better fit than standard Poisson and Negative Binomial models, respectively.
Conclusions:
- The Zero Inflated Negative Binomial (ZINB) model demonstrated a superior statistical fit for modeling DMFT count data compared to the Zero Inflated Poisson (ZIP) model.
- Zero-inflated models are effective for analyzing dental caries data with excess zeros.
