Matthew D. Bramlett

Influences on Children's Oral Health: A Conceptual Model

OBJECTIVES. Despite marked improvements over the past century, oral health in America is a significant problem: caries is the most common chronic disease of childhood. Much oral health research examines influences primarily in the oral cavity or focuses on a limited number of individual-level factors. The purpose of this article was to present a more encompassing conceptual model of the influences on childrens oral health. METHODS. The conceptual model presented here was derived from the population health and social epidemiology fields, which have moved toward multilevel, holistic approaches to analyze the complex and interactive causes of childrens health problems. It is based on a comprehensive review of major population and oral health literatures. RESULTS. A multilevel conceptual model is described, with the individual, family, and community levels of influence on oral health outcomes. This model incorporates the 5 key domains of determinants of health as identified in the population health literature: genetic and biological factors, the social environment, the physical environment, health behaviors, and dental and medical care. The model recognizes the presence of a complex interplay of causal factors. Last, the model incorporates the aspect of time, recognizing the evolution of oral health diseases (eg, caries) and influences on the child-host over time. CONCLUSIONS. This conceptual model represents a starting point for thinking about childrens 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 childrens 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 childrens oral health.

Differentiating Subgroups of Children with Special Health Care Needs by Health Status and Complexity of Health Care Needs

Objectives Our objective is to use the Children with Special Health Care Needs (CSHCN) Screener to identify subgroups of CSHCN differentiated by health status and complexity of need. Methods Data are from the National Survey of Children with Special Health Care Needs, 2001 and the National Survey of Children’s Health, 2003 (conducted by the Maternal and Child Health Bureau and the National Center for Health Statistics); and the 2001 and 2002 Medical Expenditure Panel Survey, conducted by the Agency for Healthcare Research and Quality. A broad array of variables measuring health status, complexity of need, and related issues are examined by subgroupings of CSHCN. Results Relative to other CSHCN, CSHCN with functional limitations or who qualify on more CSHCN Screener items have poorer health status and more complex health care needs. They more often experience a variety of health issues; their insurance is more often inadequate; the impact of their conditions on their families is higher; and their medical costs are higher. Conclusion In the absence of information on specific conditions, health status, or complexity of need, the CSHCN Screener alone can be used to create useful analytic subgroups that differ on these dimensions. The proposed subgroups, based on the type or number of CSHCN screening criteria, differentiate CSHCN by health status and complexity of health care needs, and also show differences in the impact of their conditions on their families, costs of their medical care, and prevalence of various health problems.

Assessing a multilevel model of young children's oral health with national survey data.

OBJECTIVES To empirically test a multilevel conceptual model of childrens oral health incorporating 22 domains of childrens oral health across four levels: child, family, neighborhood and state. DATA SOURCE The 2003 National Survey of Childrens Health, a module of the State and Local Area Integrated Telephone Survey conducted by the Centers for Disease Control and Preventions National Center for Health Statistics, is a nationally representative telephone survey of caregivers of children. STUDY DESIGN We examined child-, family-, neighborhood-, and state-level factors influencing parents report of childrens 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 childrens 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 childrens 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 childrens oral health should consider a multilevel approach that goes beyond solely child-level factors.

Legal and Informal Adoption by Relatives in the U.S.: Comparative Characteristics and Well-Being from a Nationally Representative Sample

A large, nationally representative sample of households is used to compare children legally adopted by relatives with those living with relatives in households that that did not include the childs biological parents (i.e., children in informal adoptions). As context, children legally and informally adopted by kin are also compared with adopted children generally and with the broader population of all U.S. children. Demographically, there were virtually no differences between children legally and informally adopted by kin, though these groups are distinct from U.S. children overall and from other adopted children. Children legally adopted by kin fared better than those adopted informally on several measures of health and well-being.

The National Survey of Adoptive Parents: An Introduction to the Special Issue of Adoption Quarterly

This article describes the background, design, and operation of the first-ever large-scale nationally representative population survey regarding adopted children across adoption types. The National Survey of Adoptive Parents (NSAP) was administered to 2,089 adoptive parents between April 2007 and July 2008, including parents of 545 children adopted internationally, 763 children adopted from the U.S. foster care system, and 781 children adopted from private domestic sources. The survey includes information on the characteristics, well-being, and service utilization of adopted children and their families. These data can be used by researchers to explore a broad range of topics related to adoption.

Comparing states on outcomes for children with special health care needs.

Objectives: To develop two alternative methods for comparing and ranking states on the health, health care, and well-being of children with special health care needs (CSHCN). Methods: Fifteen key indicators of CSHCN’s functional abilities, health insurance coverage, access to care, and the impact of their conditions on their families were identified from the 2001 National Survey of Children with Special Health Care Needs. An initial composite score for each state was created by averaging the state’s standardized scores for each of these indicators. Using linear regression analyses and standardized residuals, an adjusted composite score for each state was then created that accounted for demographic variables that differed by state and were related to the initial composite score. States were ranked based on the initial and adjusted composite scores. Results: The initial composite scores were related to population differences by poverty status, African-American race, and the prevalence of special health care needs. Compared to ranks based on the initial scores, ranks based on the adjusted scores shifted by 10 or more positions for half the states. Hawaii, Rhode Island, Arizona, Iowa, and North Dakota had the highest (“best”) adjusted scores. Conclusion: Adjustment to the initial composite scores permits states with different demographic compositions to be compared. The adjusted scores may also help raise awareness of CSHCN’s concerns in states where demographic compositions favorable to health outcomes mask the fact that these outcomes are only average (or worse) given the states’ demographic compositions.

Commentary: Research Possibilities Using the National Survey of Adoptive Parents

The analyses presented in this special issue of Adoption Quarterly represent merely the beginning in terms of the research possibilities inherent in the National Survey of Adoptive Parents (NSAP), and much remains to be examined. This commentary summarizes the strengths and weaknesses of the data and suggests research possibilities that remain to be addressed. Information is provided about possibilities for linking NSAP data to data from the National Survey of Childrens Health, from which respondents were recruited, as well as on accessing restricted data through the National Center for Health Statistics’ Research Data Center.

When Stepparents Adopt: Demographic, Health and Health Care Characteristics of Adopted Children, Stepchildren, and Adopted Stepchildren

This article compares adopted stepchildren to both stepchildren and adopted children to determine which group adopted stepchildren more closely resemble. Adopted stepchildren more closely resemble stepchildren in terms of the childs demographic characteristics, but more closely resemble adopted children in terms of household socioeconomic characteristics. Stepchildren tend to have better health than adopted children, and adopted children tend to have better health care than stepchildren. Adopted stepchildren are more like stepchildren with respect to health and more like adopted children with respect to health care although this last finding is diluted once estimates are adjusted for demographic and socioeconomic characteristics.