Statistical Methods For Studying Human Fertility

在以下几个领域的工作取得了进展：（1）开发了改进的统计方法，用于分析与妇女和月经周期特征有关的整个月经周期的激素数据;（2）开发了改进的方法，用于评估激素轨迹与妊娠结果之间的关系;（3）利用月经周期和阴道分泌物的时间数据，开发寻找最佳性交时间规则以实现受孕的方法;以及（4）将这些方法应用于意大利多中心生育力研究的数据，该研究收集了自然计划生育中心妇女的详细记录。 我们发现，排卵后孕酮水平的数据高度预测早期妊娠丢失，并且轨迹的形状可用于预测植入后不久的早期丢失风险。 我们还发现，基于在具有特定类型分泌物的周期中间窗口的日子性交时间的简单规则可以大大减少受孕时间，减少对辅助生殖干预的需求以及相关的成本和健康风险。

Work has progressed in several areas: (1) the development of improved statistical methods for analyzing hormone data across the menstrual cycle in relation to characteristics of the woman and menstrual cycle; (2) the development of improved methods for assessing the relationship between hormone trajectories and pregnancy outcomes; (3) the development of methods for searching for optimal rules for timing intercourse to achieve conception using data on timing in the cycle and vaginal secretions; and (4) application of these methods to data from an Italian multi-center fecundability study collecting detailed records for women in natural family planning centers. We found that data on progesterone levels following ovulation are highly predictive of early pregnancy loss and that the shape of the trajectory can be used to predict risk of early loss soon after implantation. We have also found that simple rules based on timing of intercourse on days in a mid-cycle window having particular types of secretions can substantially reduce time to conception, reducing need for assisted reproductive intervention with associated costs and health risks.