PROXIMATE DETERMINANTS OF LBW AND INFANT MORTALITY

消除持续存在的黑人/白色婴儿死亡率差异是一个很高的目标， 国家优先目标。 我们假设这是 社会不平等如何对黑人母亲的健康产生负面影响， 限制她们获得产前和围产期保健服务。 我们的理论 框架将社会经济特征与婴儿结局联系起来， 基于生物学的直接决定因素 我们提出了一个“风化” 假设社会不平等对健康的影响 人口随着年龄增长而增加。 我们正在进行的项目证实， 女性的健康和行为特征患病率较高， 比白色更容易使怀孕复杂化，这些差异 随着年龄增长。 黑人/白色人在不良生育结果方面的差异也 随着母亲年龄的增长。 女性健康的差异可能是 造成黑人/白色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年出生队列，当出生证明得到改善时， 第一次验证这些假设。 我们将分析 加州、纽约、密歇根和北卡罗来纳州1989年的录音带 队列。 这些州提供大量的新生儿（包括黑人和 西班牙裔），代表该国的每个地区，并在婴儿 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的测量。 我们将补充和验证链接 将孕产妇健康数据与卫生保健和人口普查数据相结合，并对人口普查数据采取同样的做法 使用来自PSID的数据。 我们将估计多变量logit模型， 孕产妇健康、行为、产前保健和医院水平的影响 出生结果;以及母亲年龄，种族，状态， 和其他特征对产妇健康的影响。 我们将深入建设 国家概况，作为分析的定性背景， 解释。 由一个多学科的研究小组实施， 研究超越了高风险的人口统计学识别， 人口，并超越生物医学对疾病过程的关注， 在个人层面，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.