PROXIMATE DETERMINANTS OF LBW AND INFANT MORTALITY

降低低出生体重（LBW）和婴儿死亡率（IM） 美国公共卫生服务的主要目标。 拟议的研究将提供新的信息， LBW和IM的参数和原因。 本研究是 莫斯利-陈分析框架。 它侧重于 确定LBW和IM的最接近决定因素， 母亲的年龄和他们的种族，民族和经济 相关的生物社会和生物行为根源。 的数据 1976-1980年全国健康和营养检查调查， 西班牙裔健康和营养调查，1982-1984年 将进行分析，以估计吸烟和其他 不良妊娠结局的特定生物行为危险因素 在育龄妇女中。 这些流行率将是 根据年龄、产次、种族、西班牙裔和 社会经济因素。 吸烟的几率和 特定疾病将被建模为社会和 使用对数线性建模技术的人口因素。 的 假设生殖健康状况恶化， 黑人、白色和西班牙裔妇女的差别税率将是 以及生育模式（母亲年龄、出生 间隔，奇偶性）对这些恶化率进行评估。 按胎次和母亲年龄分列的低出生体重和肠内营养率将按 种族、西班牙裔和社会经济群体的估计 使用链接的出生和婴儿死亡证明数据磁带 1985年出生于加州、纽约、南卡罗来纳州和密苏里州 同伙 将LBW和IM的几率建模为以下函数： 产妇年龄、种族、民族、社会经济因素、产次、 产前护理、医疗条件、吸烟和获得 新生儿重症监护技术，并估计相对 层内和层间LBW和IM的风险，对数线性建模 技术也将应用于这些数据。 在莫斯利-陈模型下，拟议的研究将继续进行， 除了高风险人群的人口统计学识别之外， 并超越生物医学对LBW和IM病因的关注 通过个体层面上的疾病过程。 相反，疾病 过程将与人口相联系。 因果建模将 用于确定疾病的社会和行为相关性 过程并确定其对出生体重的影响 婴儿死亡率和死亡率 大.

Reducing low birth weight (LBW) and infant mortality (IM) are prominent objectives of the United States Public Health Service. The proposed research will contribute new information outlining the parameters and causes of LBW and IM. This research is guided by the Mosley-Chen analytic framework. It focuses on identifying the proximate determinants of LBW and IM by maternal age and their racially, ethnically, and economically associated biosocial and biobehavioral roots. Data from the National Health and Nutrition Examination Survey, 1976-1980 and the Hispanic Health and Nutrition Examination Survey, 1982-1984 will be analyzed to estimate prevalences of smoking and other specific biobehavioral risk factors for poor pregnancy outcomes among women of childbearing age. These prevalence rates will be estimated by age, parity, race, Hispanic ethnicity, and socioeconomic factors. The odds of smoking and of having specific diseases will be modeled as functions of social and demographic factors using log-linear modeling techniques. The hypothesis that reproductive health status deteriorates at differential rates for black, white, and Hispanic women will be tested, and the influence of fertility patterns (maternal age, birth spacing, parity) on these deterioration rates assessed. Rates of LBW and IM by parity and maternal age will be estimated for racial, Hispanic ethnic, and socio-economic groups using linked birth and infant death certificate data tapes for the 1985 California, New York, South Carolina, and Missouri birth cohorts. To model the odds of LBW and IM as functions of maternal age, race, ethnicity, socioeconomic factors, parity, prenatal care, medical conditions, smoking, and access to neonatal intensive care technology, and to estimate the relative risk of LBW and IM within and between strata, log-linear modeling techniques will also be applied to these data. Under the Mosley-Chen model, the proposed research will go beyond the demographic identification of high risk populations, and beyond the biomedical focus on the etiology of LBW and IM through disease processes on the individual level. Rather, disease processes will be connected to populations. Causal modeling will be used to locate the social and behavioral correlates of disease processes and identify their consequences for birthweight distributions and infant mortality rates among populations at large.