摘要：Objectives. We examined how changes in demographic, geographic, and childbearing risk factors were related to changes in the Black–White infant mortality rate (IMR) gap over 2 decades. Methods. Using 1983–2004 Vital Statistics, we applied inverse probability weighting methods to examine the relationship between risk factors and 3 outcomes: the overall IMR gap, its birth weight component, and its conditional (on birth weight) IMR component. Results. The unexplained IMR gap (the part not related to observed risk factors) was stable, changing from 5.0 to 5.3 deaths per 1000 live births. By contrast, the explained gap declined from 4.6 to 1.9. The decline in the explained gap was driven by the changing relationship between risk factors and IMR. Further analysis revealed that most of the unexplained gap occurred among infants weighing less than 1000 grams at birth, whereas most of the explained gap occurred among infants weighing more than 1000 grams. Conclusions. The unexplained gap was stable over the last 2 decades, but the explained gap declined markedly. If the stability of the unexplained gap continues, even complete convergence of risk factors would reduce the Black–White IMR gap by only one quarter. One of the most dramatic health disparities in the United States is the infant mortality rate (IMR) gap between Blacks and Whites. The size and persistence of this gap are well-documented. 1,2 To shed light on why the gap exists, numerous studies examined how it is related to birth weight and gestational age. These studies found that the gap in numerous years could largely be accounted for by the much higher rates of low birth weight and preterm births among Blacks, particularly at the smallest and earliest ranges. 3–8 Other studies analyzed how the IMR gap (sometimes disaggregated by cause of death) is associated with differences in risk factors, such as maternal age and education. 9–13 To the extent that infant mortality varies by observed risk factors, some of the IMR gap can be explained by differences in these risk factors between the 2 groups. The unpredicted IMR gap (the part that is unrelated to differences in the observed risk factors) is then a measure of the overall IMR gap net of well-documented differences between Blacks and Whites in measured socioeconomic, geographic, and childbearing characteristics. Documenting the relationship between the explained and unexplained gaps and birth weight can provide important additional information about how the risk factors operate. Our study examined how changes in the absolute IMR gap and its components were related to changing risk factors over 2 decades, making 3 contributions to the literature. First, we used inverse probability weighting to distinguish between the explained and unexplained IMR gaps, allowing us to provide detailed results regarding how these gaps are related to birth weight. Second, we focused on the trends in the explained and unexplained gaps. Third, we included state of birth as a risk factor because many important inputs for the production of healthy infants vary by state and there are substantial differences between the geographic distributions of White and Black births. 14
