Conception Failure and Pregnancy Loss in the U.S.

美国受孕和流产的新证据 摘要 受孕失败和怀孕失败阻碍了数百万美国夫妇成为父母的道路 年尽管流产是可以改变的和常见的，但流产的发生率是婴儿死亡率的50倍， 流产是人口健康或人口动态研究得最少的方面之一。我们知道 很少有人知道是什么原因造成这些损失，从研究小的估计产生的普遍性， 招募的样本，包括流产的风险如何在不同的时间，地点或亚群。 这些巨大的差距是由于研究人类活产的途径是多么困难，需要 一个足够大的、多样化的“先入为主的群体”。到目前为止，小的，不具代表性的队列贡献 我们所知道的关于早孕的大部分知识。但是有限的样本量、变异和覆盖范围排除了 社会和生态因素的研究-贫困，伴侣健康，环境破坏-现在广泛 被理解为在以后的年龄形成死亡率：例如，死产、婴儿和儿童死亡率。这种遗漏是 后果严重受孕失败和流产会带来巨大的情感和经济代价。虽然 怀孕失败可能在人群中分布不均匀，这种不同负担的大小是 未知我们没有证据表明政策对预防这些结果的潜在影响。 我们的研究结合了数据科学和社会科学的工具，将前概念设计扩展到 在美国的一个庞大的、多样化的群体。在数字设备上进行经期和怀孕“跟踪”现在很常见， 育龄妇女我们使用了400万妇女每天记录的月经周期数据， 排卵和怀孕，以及报告的社会和经济特征。这些数据使我们能够 衡量报告和检测到的受孕和流产情况。我们联合收割机将数据与地理参考相结合 关于妇女及其伴侣所处的物质、社会、经济和政策环境的信息; live.样本是多样化的：用户来自超过99%的美国县;超过100万用户在医疗补助。 我们使用这些非凡的数据来提供大规模人口变异的第一次估计， 活产的途径，并记录影响这一途径的因素。目标1提出新的估计数 受孕和流产，包括与教育、收入、种族认同、 邻里贫困。目标2估计男性伴侣特征对受孕的贡献， 根据报告的关于伴侣的详细数据，Aim 3使用准实验设计， 提供对来自多个环境、社会和经济领域的未充分研究的暴露的第一次估计 怀孕和流产的风险这项研究揭示了一个普遍存在且大量研究不足的问题， 公共卫生问题，对改善早孕结果有直接影响。在这样做时， 研究还产生了非常需要的估计数， 在社会，健康和生物医学科学的研究连接领域。

NEW EVIDENCE ON CONCEPTION AND PREGNANCY LOSS IN THE U.S. ABSTRACT Conception failure and pregnancy loss impede the pathway to parenthood for millions of US couples each year. Despite being modifiable and common—pregnancy loss occurs fifty times as often as infant mortality— miscarriage is among the least well-studied aspects of population health or population dynamics. We know little about what causes these losses, the generalizability of estimates generated from the study of small recruited samples, including how the risk of miscarriage differs across time, place, or subpopulation. These enormous gaps are driven by how difficult it is to study the pathway to live birth in humans, requiring a sufficiently large and diverse “preconception cohort.” To date small, nonrepresentative cohorts contribute most of what we know about early pregnancy. But limited sample size, variation, and coverage preclude the study of social and ecological factors—poverty, partner health, environmental exposures—that are now widely understood to shape mortality at later ages: e.g., stillbirth, infant, and child mortality. Such omissions are consequential. Conception failures and pregnancy loss have significant emotional and economic costs. Though pregnancy failures are likely distributed unevenly across populations, the size of this disparate burden is unknown. We do not have evidence about the potential impact of policies on the prevention of these outcomes. Our research combines the tools of data science and social science to scale the preconception design to a large, diverse cohort in the US. Period and pregnancy “tracking” on digital devices is now common among reproductive-age women. We use data on 4 million women’s day-to-day recording of menstrual cycles, ovulation, and pregnancy, as well as reported social and economic characteristics. The data allow us to measure both reported and detected conception and pregnancy loss. We combine the data with georeferenced information about the physical, social, economic, and policy environments in which women and their partners live. The sample is diverse: users come from over 99% of U.S. counties; over 1 million users are on Medicaid. We use these extraordinary data to provide the first estimates of large-scale population variability in the pathway to live birth and to document factors that affect this pathway. Aim 1 develops new estimates of conception and pregnancy loss, including disparities associated with education, income, racial identification, and neighborhood poverty. Aim 2 estimates the contribution of male partner characteristics to conception and pregnancy loss, drawing on detailed data reported about partners. Aim 3 uses quasi-experimental designs to provide the first estimates of understudied exposures from multiple environmental, social, economic domains on conception and pregnancy loss. The research sheds new light on a pervasive and massively understudied public health concern, with direct implications for the improvement of early pregnancy outcomes. In so doing, the research also generates estimates that are much-needed inputs to support advancement in multiple, connected fields of study in the social, health, and biomedical sciences.