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This study examined the prevalence, socio-demographic correlates, and clinical predictors of traumatic dental injuries (TDIs) in the primary dentition among a community-based sample of preschool-age children. The sample comprised 1,546 preschool-age children (mean age 49 [range: 24-71] months) in North Carolina public preschools, enrolled in a population-based investigation among young children and their parents in North Carolina. Information on socio-demographic, extraoral, and intraoral characteristics was collected and analyzed with bivariate and multivariate methods, including logistic regression modeling and marginal effects estimation. The prevalence of dental trauma was 47% and 8% of TDI cases were "severe" (pulp exposure, tooth displacement, discolored or necrotic tooth, or tooth loss). In bivariate analyses, overjet and lip incompetence were significantly associated with TDI. Overjet remained positively associated with severe trauma in multivariate analysis, OR  = 1.4, 95% confidence interval (CI) [1.2, 1.6], corresponding to an absolute 1.3%, 95% CI [0.7, 1.8], increase in the likelihood of severe trauma, per millimeter of overjet. Children with increased overjet (>3 mm) were 3.8, 95% CI [2.0, 7.4], times as likely to have experienced severe TDI compared with those with ≤3 mm. Overjet is a strong risk factor for TDIs in the primary dentition. Incorporating and operationalizing this information may help TDI prevention and related anticipatory guidance for families of preschool-age children., Competing Interests: None declared.

Background: Indicators of poor oral health, including smoking, have been associated with increased risk of head and neck squamous cell carcinoma, especially oropharyngeal squamous cell carcinoma (OPSCC), yet few studies have examined whether this association is modified by human papillomavirus (HPV) status., Methods: Data from interviews and tumor HPV status from a large population-based case-control study, the Carolina Head and Neck Cancer Study (CHANCE), were used to estimate the association between oral health indicators and smoking among 102 HPV-positive patients and 145 HPV-negative patients with OPSCC and 1396 controls. HPV status was determined by p16INK4a (p16) immunohistochemistry. Unconditional, multinomial logistic regression was used to estimate odds ratios (ORs) for all oral health indictors adjusting for important covariates., Results: Routine dental examinations were associated with a decreased risk of both HPV-negative OPSCC (OR, 0.52; 95% confidence interval [CI], 0.35-0.76) and HPV-positive OPSCC (OR, 0.55; 95% CI, 0.36-.86). Tooth mobility (a proxy for periodontal disease) increased the risk of HPV-negative disease (OR, 1.70; 95% CI, 1.18-2.43) slightly more than the risk for HPV-positive disease (OR, 1.45; 95% CI, 0.95-2.20). Ten or more pack-years of cigarette smoking were strongly associated with an increased risk of HPV-negative OPSCC (OR, 4.26; 95% CI, 2.85-6.37) and were associated less with an increased risk of HPV-positive OPSCC (OR, 1.62; 95% CI, 1.10-2.38)., Conclusions: Although HPV-positive and HPV-negative HNSCC differ significantly with respect to etiology and tumorigenesis, the current findings suggest a similar pattern of association between poor oral health, frequency of dental examinations, and both HPV-positive and HPV-negative OPSCC. Future research is required to elucidate interactions between poor oral health, tobacco use, and HPV in the development of OPSCC. Cancer 2017;71-80. © 2016 American Cancer Society., Competing Interests: There are no conflicts of interest to disclose., (© 2016 American Cancer Society.)

The zero-inflated negative binomial regression model (ZINB) is often employed in diverse fields such as dentistry, health care utilization, highway safety, and medicine to examine relationships between exposures of interest and overdispersed count outcomes exhibiting many zeros. The regression coefficients of ZINB have latent class interpretations for a susceptible subpopulation at risk for the disease/condition under study with counts generated from a negative binomial distribution and for a non-susceptible subpopulation that provides only zero counts. The ZINB parameters, however, are not well-suited for estimating overall exposure effects, specifically, in quantifying the effect of an explanatory variable in the overall mixture population. In this paper, a marginalized zero-inflated negative binomial regression (MZINB) model for independent responses is proposed to model the population marginal mean count directly, providing straightforward inference for overall exposure effects based on maximum likelihood estimation. Through simulation studies, the finite sample performance of MZINB is compared with marginalized zero-inflated Poisson, Poisson, and negative binomial regression. The MZINB model is applied in the evaluation of a school-based fluoride mouthrinse program on dental caries in 677 children., (Copyright © 2015 John Wiley & Sons, Ltd.)