Jane A. Weintraub, DDS, MPH, Lee Hysan Professor of Oral Epidemiology and Dental Public Health, will assume additional duties as director of the new Center to Address Disparities in Children's Oral Health, based in San Francisco. The Center will collaborate in a seven-year program with the San Francisco Department of Public Health and the San Ysidro Community Center, located at the Mexican border south of San Diego. An additional 12 institutions located along the West Coast will participate in the work of CAN-DO, the acronym for the center.
"This is the first time that the NIDCR (part of the National Institutes of Health) has funded a project so closely networked with community organizations," Weintraub said.
A California survey of children showed that 33 of every 100 children in Headstart programs had cavities, with even higher rates among children of Asian heritage (44 of every 100) and Latino children (39 of every 100).
"The prevalence of early childhood caries (tooth decay) is particularly high among some racial and ethnic minorities and low socioeconomic groups," Weintraub said. "The primary goals of the Center are to understand, prevent and reduce oral health disparities among young children, with a primary focus on preventing early childhood caries."
A secondary focus of the Center is to understand the interactions between the oral health and medical delivery systems that can affect children’s oral health, Weintraub explained.
The goals will be pursued from two directions:
1. retrospective data-based projects to increase understanding of the causes of oral health disparities and to identify children most susceptible and
2. intervention projects to prevent disease.
More than 25 UCSF faculty members are involved in the multidisciplinary projects, including faculty from the UCSF Schools of Dentistry, Medicine, Nursing and Pharmacy, the Comprehensive Oral Health Research Center of Discovery, the Centers for Health and Community, Health Professions, Workplace Studies, Cochrane Collaboration, Health Improvement and Prevention Studies, Oral AIDS, Medical Effectiveness Research, Institute for Health Policy Studies, and the Departments of Epidemiology and Biostatistics, Pediatrics, Medical Anthropology, History and Social Medicine, Family and Community Medicine, Family Health Care Nursing, Medicine and Psychiatry.
The Center has four main projects:
- Prevention and Treatment Options for Early Childhood Caries (ECC) previously called Baby Bottle Tooth Decay and Nursing Caries. This randomized clinical trial which tests the efficacy of fluoride varnish to prevent ECC has already been funded by NIDCR as part of the UCSF Comprehensive Oral Health Research Center of Discovery. UCSF is partnering with the San Francisco Department of Public Health, the Chinatown Public Health Center and San Francisco General Hospital to conduct this study.
- Prevention Management Model for Early Childhood Caries. The goal of this project, led by Francisco Ramos-Gomez, DDS, MS, MPH, is to increase understanding and to assess the effectiveness of a dental disease prevention management model based on an infant oral care program. This project is partnered with the San Ysidro Community Health Center. High-risk children include those with early signs of ECC, poor hygiene, limited exposure to fluorides, and frequent exposure to high dietary sugars. The children and their caretakers will be targeted with a professional preventive program that includes anticipatory guidance counseling, the use of chlorhexidine for postpartum women and the application of fluoride varnish for their infants.
- Understanding Ethnic/Racial Cultural Differences Related to Oral Health. This project is partnered with the San Francisco Department of Public Health with Patricia Evans, MD, MPH, as the lead investigator. The goal of this project is to identify barriers (racial, ethnic and cultural) to accessing preventive oral health care among African American, Chinese, Filipino and Hispanic caregivers of children between one and five years of age. This study will address assessment of barriers to preventive oral health care and may impact policy development and assurance to improve the oral health of the affected population.
- Assessing Risk for Early Childhood Caries. This study, led by Stuart Gansky, DrPH, will utilize statewide and local cross-sectional data sources to develop, test and refine an ECC risk association model to be tested with longitudinal data from the NIDCR funded UCSF fluoride varnish trial. The partner for this project is the San FranciscoDepartment of Public Health and collaborators include the Alameda County Health Care Services and California Department of Health Services. This is the first study to simultaneously examine individual, family and community level characteristics related to ECC with data mining techniques.* This study coordinates with three existing studies (California Department of Health Services/CDC, the Center for Medicare and Medicaid Services and NIDCR) as well as the other projects and the cores of this proposed center. The project will provide input to the San Ysidro intervention study, the San Francisco focus group project and provide risk assessment models that can be tested and refined with their study data.
"Findings from the Center research will identify cultural, environmental, workforce, behavioral and biologic factors associated with health disparities among ethnic/racial groups in the very diverse California environment," Weintraub said.
"We also hope to enhance our ability to target children likely to be at risk for dental caries, provide successful interdisciplinary interventions to prevent disease and reduce oral health disparities. The Center will also provide an enriched environment for training future health-care professionals and scientists, especially those from underrepresented groups. This award provides a tremendous opportunity to improve the oral health of children," Weintraub explained.
*Data mining is the process of selecting, exploring and modeling large data bases using a variety of tools. These models can then be used for prediction in new data bases.