This conceptual model represents a starting point for thinking about children's oral health. The model incorporates many of the important breakthroughs by social epidemiologists over the past 25 years by including a broad range of genetic, social, and environmental risk factors; multiple pathways by which they operate; a time dimension; the notion of differential susceptibility and resilience; and a multilevel approach. The study of children's oral health from a global perspective remains largely in its infancy and is poised for additional development. This work can help inform how best to approach and improve children's oral health.

Objective Assess the extent apparent racial/ethnic disparities in children’s oral health and oral health care are explained by factors other than race/ethnicity. Data Source 2007 National Survey of Children’s Health, for children 2–17 years (N=82,020). Outcomes included parental reports of child’s oral health status, receipt of preventive dental care, and delayed dental care/unmet need. Model-based survey data analysis examined racial/ethnic disparities, controlling for other child, family, and community/state (contextual) factors. Results Unadjusted results show large oral health disparities by race/ethnicity. Compared to non-Hispanic Whites, Hispanics and non-Hispanic Blacks were markedly more likely to be reported in only fair/poor oral health (odds ratios (ORs) [95% confidence intervals] 4.3 [4.0–4.6], 2.2 [2.0–2.4], respectively), lack preventive care (ORs 1.9 [1.8–2.0], 1.4 [1.3–1.5]), and experience delayed care/unmet need (ORs 1.5 [1.3–1.7], 1.4 [1.3–1.5]). Adjusting for child, family, and community/state factors reduced or eliminated racial/ethnic disparities. Adjusted ORs (AORs) for Hispanics and non-Hispanic Blacks attenuated for fair/poor oral health, to 1.6 [1.5–1.8] and 1.2 [1.1–1.4], respectively. Adjustment eliminated disparities in each group for lacking preventive care (AORs 1.0 [0.9–1.1], 1.1 [1.1–1.2]), and in Hispanics for delayed care/unmet need (AOR 1.0). Among non-Hispanic Blacks, adjustment reversed the disparity for delayed care/unmet need (AOR 0.6 [0.6–0.7]). Conclusions Racial/ethnic disparities in children’s oral health status and access were found to be attributable largely to determinants such as socioeconomic and health insurance factors. Efforts to decrease disparities may be more efficacious if targeted at the social, economic, and other factors associated with minority racial/ethnic status, and may also have collateral positive effects on sectors of the majority population who share similar social, economic and cultural characteristics.

Aims To determine whether menthol is related to initiation, quantity or quitting, we examined differences in smoking behaviors among menthol and non-menthol smokers, stratified by gender and race/ethnicity, and adjusting for age, income and educational attainment. Design Cross-sectional, using data from the 2005 National Health Interview Survey and Cancer Control Supplement. Setting United States. Participants Black, Hispanic and white women and men aged 25-64 years. Measurements For each group, we examined (i) proportion of menthol smokers (comparing current and former smokers); (ii) age of initiation, cigarettes smoked per day and quit attempt in the past year (comparing menthol and non-menthol current smokers); and (iii) time since quitting (comparing menthol and nonmenthol former smokers). We calculated predicted values for each demographic group, adjusting for age, income and educational attainment. Findings After adjusting for age, income and education, black (compared with Hispanic and white) and female (compared with male) smokers were more likely to choose menthol cigarettes. There was only one statistically significant difference in age of initiation, cigarettes smoked per day, quit attempts or time since quitting between menthol and non-menthol smokers: white women who smoked menthol cigarettes reported longer cessation compared with those who smoked non-menthol cigarettes. Conclusions The results do not support the hypothesis that menthol smokers initiate earlier, smoke more or have a harder time quitting compared with non-menthol smokers. A menthol additive and the marketing of it, given the clear demographic preferences demonstrated here, however, may be responsible for enticing the groups least likely to smoke into this addictive behavior.

Objectives-To empirically test a multilevel conceptual model of children's oral health incorporating 22 domains of children's oral health across four levels: child, family, neighborhood and state. Study design-We examined child-, family-, neighborhood-, and state-level factors influencing parent's report of children's oral health using a multilevel logistic regression model, estimated for 26 736 children ages 1-5 years.Principal findings-Factors operating at all four levels were associated with the likelihood that parents rated their children's oral health as fair or poor, although most significant correlates are represented at the child or family level. Of 22 domains identified in our conceptual model, 15 domains contained factors significantly associated with young children's oral health. At the state level, access to fluoridated water was significantly associated with favorable oral health for children.Conclusions-Our results suggest that efforts to understand or improve children's oral health should consider a multilevel approach that goes beyond solely child-level factors. NIH Public Access Author ManuscriptCommunity Dent Oral Epidemiol. Author manuscript; available in PMC 2011 August 1. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptDespite reductions in dental caries rates over the past 25 years resulting from water fluoridation, fluoride toothpaste use, and improvements in oral hygiene and nutrition, dental caries remains the most common chronic childhood disease, overall (1), and the cause of the vast predominance of oral health problems in children. Nationally, 42% of children 2-11 years old have caries experience in their primary teeth, with 23% having untreated caries; among 12-19-year-olds, 59% have caries experience in their permanent teeth with 20% having untreated caries (2). Dental caries accounted for 117 lost school-hours per 100 school-age children in 1989 (3). As overall caries rates decrease, diminishing returns can be expected from applying current individual-based approaches to fight disease.Population health research has looked beyond the biomedical model to explain disease states, but with the exceptions of water fluoridation and school-based dental sealant programs, population-based approaches have not been implemented extensively in oral health. Health conditions (e.g., diabetes and HIV), health behaviors (e.g., use of alcohol, tobacco, sugary diet, certain drugs, and lack of preventive care), socioeconomic factors (e.g., lower education and income), and minority race/ethnicity are related to poor oral health (4-6). However, few models explain the relationships between the larger contextual, environmental and societal factors and oral health. An individual is exposed to multiple factors at a time and over a lifetime, so focusing primarily on traditional biomedical factors limits our understanding of how these different complex factors operate.Population health models generally classify health determinants into five broad categories: genetic endowmen...

Objectives To ascertain differences across states in children's oral health care access and oral health status and the factors that contribute to those differences Study Design Observational study using cross-sectional surveys Methods Using the 2007 National Survey of Children's Health, we examined state variation in parent's report of children's oral health care access (absence of a preventive dental visit) and oral health status. We assessed the unadjusted prevalences of these outcomes, then adjusted with child-, family-, and neighborhood-level variables using logistic regression; these results are presented directly and graphically. Using multilevel analysis, we then calculated the degree to which child-, family-, and community-level variables explained state variation. Finally, we quantified the influence of state-level variables on state variation. Results Unadjusted rates of no preventive dental care ranged 9.0-26.8% (mean 17.5%), with little impact of adjusting (10.3-26.7%). Almost 9% of population had fair/poor oral health; unadjusted range 4.1-14.5%. Adjusting analyses affected fair/poor oral health more than access (5.7-10.7%). Child, family and community factors explained ~¼ of the state variation in no preventive visit and ~½ of fair/poor oral health. State-level factors further contributed to explaining up to a third of residual state variation. Conclusion Geography matters: where a child lives has a large impact on his or her access to oral health care and oral health status, even after adjusting for child, family, community, and state variables. As state-level variation persists, other factors and richer data are needed to clarify the variation and drive changes for more egalitarian and overall improved oral health.