Introduction: Although previous public health efforts have focused on redressing health disparities associated with insufficient gestational weight gain, examination of the impact of excessive gestational weight gain is warranted currently given the 2009 revision of the Institute of Medicine (IOM) gestational weight gain guidelines for obese women coupled with rising rates of obesity, particularly among African American women. Materials and Methods: In the years [2004][2005][2006][2007][2008] 4619 African American and Caucasian women gave birth to a single, live, and full-term infant, completed Arkansas Pregnancy Risk Assessment Monitoring System questions about gestational weight gain and prepregnancy weight status, and gained within or in excess of the guidelines. Logistic regression was used to identify sociodemographic and health variables associated with the odds of exceeding the 2009 IOM guidelines overall and by race. Results: Regardless of race, overweight (odds ratio [OR] = 3.21; 95% confidence interval [CI]: 2.64-3.91) and obese (OR = 4.37; 95% CI: 3.50-5.46) women had significantly higher odds of gaining excessively, as compared with normal weight women. In the multivariate model, women who were overweight or obese prepregnancy and who were married had higher odds of exceeding the IOM guidelines, while lower odds of exceeding the guidelines were seen among African American women, those who had Medicaid at any point in their pregnancy, who were multiparous, and those of Hispanic ethnicity. Discussion: These findings can inform efforts to promote appropriate gestational weight gain among those at highest risk (i.e., overweight/obese women) and facilitate targeting to produce greatest improvement in the health of mothers and children.

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The diversification of the rural population of the United States provides substantial challenges to the current and to future health care systems in rural areas. Because of a variety of historical, discriminatory, and other factors, minority populations have had lower levels of access to health care in rural as well as urban areas and higher rates of both mortality and morbidity than nonminority populations. Although minority health issues have often been seen as primarily urban issues, this article demonstrates that minority population growth has become a major component of total population growth in rural areas in the past several decades (accounting for nearly 62% of the net growth in the nonmetropolitan population of the United States in the 1980s and for nearly 42% in the 1990s), that future US population growth is likely to be largely a product of minority population growth (nearly 89% of US net population growth from 2000 to 2100 is projected to be due to minority population growth), and that the incidence of diseases and disorders in the US population will come to increasingly involve minority populations (by 2050 roughly 43% of all disease/disorder incidences would involve minority population members). The growth of younger minority populations with disproportionately impoverished socioeconomic characteristics will pose challenges for rural areas and health care systems, which also are likely to face health issues created by disproportionately older populations.

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The United States has embarked upon an initiative to eliminate health disparities between advantaged and disadvantaged populations in this country (DHHS 1992(DHHS , 2000. Being able to measure our progress in eliminating these disparities, as well as knowing exactly where and why they exist, requires having reliable data or information to track and monitor changes in health indicators or outcomes. The research done by Stockwell et al. (2005; in this issue) on the relationship between infant mortality and socioeconomic status for whites and nonwhites covering five time periods and four decades for Ohio is an important step towards making that type of information available. Their research is also important for a number of other reasons.Eliminating health disparities requires that we understand how these disparities may vary based on a combination of factors that include race/ethnicity, gender, age, cause of death or incidence of disease, and geography. A dilemma faced by researchers is how to develop stable rates for these types of disaggregations which may result in no cases or a small number of cases, particularly for substate areas. The research by Stockwell and his colleagues provides an example of a simple methodology that can be used by other researchers interested in developing stable rates for small areas (e.g., substate areas), with small numbers of cases. Developing or having methodologies to conduct this type of health research for small areas will become more important as the interest developed on the national level to improve the health of the population shifts to state and substate agencies.While this research focused on metropolitan Ohio, the methodology used would be especially helpful in examining the relationship between socioeconomic status and infant mortality or other health outcomes in rural or nonmetropolitan areas for at least two reasons. The first is to examine the differences or similarities in the observed trends for metropolitan and nonmetropolitan areas.

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