PROXIMATE DETERMINANTS OF LBW AND INFANT MORTALITY

缩小持续的黑人/白人婴儿死亡率差异是一个很高的 优先实现国家目标。我们假设这是一种表现 社会不平等如何对黑人母亲的健康产生负面影响 限制他们获得产前和围产期保健服务。我们的理论 框架通过以下方式将社会经济特征与婴儿结局联系起来 基于生物的最接近的决定因素。我们建议进行“风化”。 假设社会不平等对健康的影响 种群随着年龄的增长而复合。我们正在进行的项目证实了布莱克 女性的健康和行为特征患病率较高 比白人更容易使怀孕复杂化，而且这些差异 随着年龄增长。不良出生结局中的黑人/白人差异也是如此 随着产妇年龄的增长而增加。女性健康方面的差异可能是 推动黑人/白人婴儿死亡率差异的重要机制。 发布与国家有关的出生和婴儿死亡证明磁带 1989年的出生队列，当出生证明被改进时， 首次验证这些假说是可能的。我们将分析 1989年加州、纽约、密歇根和北卡罗来纳州的录像带 一群人。这些州提供大量的出生人口(包括黑人和 西班牙人)，代表国家的每个地区，婴儿的情况各不相同 死亡率和贫困率。我们将用人口普查数据来补充这些数据 提供SES的衡量标准。我们将补充和验证链接的 使用Hanes数据的孕产妇健康数据，并对人口普查数据进行同样的处理 使用PSID中的数据。我们将估计多元Logit模型 产妇健康、行为、产前护理和医院水平的影响 关于分娩结果；以及产妇年龄、种族、状态、 以及其他特征对产妇健康的影响。我们将深入建设 各州概况，作为援助分析的定性背景 释义。这是由一个多学科研究团队实施的 研究超越了对高危人群的人口统计识别 人群，以及超越生物医学对疾病过程的关注 个人层面，将疾病过程与人群联系起来。

Closing the persistent black/white infant mortality differential is a high priority national objective. We hypothesize it to be a manifestation of how social inequality negatively affects the health of black mothers, and limits their access to pre- and perinatal health services. Our theoretical framework connects socioeconomic characteristics to infant outcomes through biologically-based proximate determinants. We propose a "weathering" hypothesis that the effects of social inequality on the health of populations compound with age. Our ongoing project confirms that black women have higher prevalence rates of health and behavioral characteristics that can complicate pregnancy than white, and that these differences increase with age. Black/white differentials in poor birth outcomes also increase with maternal age. The differences in women's health may be important mechanisms driving the black/white infant mortality differential. The release of state linked birth and infant death certificate tapes for the 1989 birth cohort, when the birth certificates were improved, makes testing these hypotheses possible for the first time. We will analyze tapes for California, New York, Michigan and North Carolina for the 1989 cohort. These states offer large numbers of births (including black and Hispanic), represent each region of the country, and vary in infant mortality and poverty rates. We will augment these with census data to provide measures of SES. We will supplement and validate the linked maternal health data with HANES data and do the same for the census data using data from the PSID. We will estimate multivariate logit models of the impact of maternal health, behaviors, prenatal care, and hospital level on birth outcomes; and of the relationship of maternal age, race, state, and other characteristics to maternal health. We will construct in-depth profiles of the states, as qualitative backdrops to the analyses to aid interpretation. Implemented by a multidisciplinary research team, this research goes beyond the demographic identification of high-risk populations, and beyond the biomedical focus on disease processes at the individual level, to connect disease processes to populations.