Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Box 630, Rochester, NY 14642, United States; Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY, United States.
Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Box 630, Rochester, NY 14642, United States.
Neurotoxicology. 2022 Sep;92:49-60. doi: 10.1016/j.neuro.2022.07.003. Epub 2022 Jul 19.
In many studies of the health effects of toxicants, exposure is measured once even though exposure may be continuous. However, some studies collect repeated measurements on participants over an extended time with the goal of determining a long-term metric that captures the average or cumulative exposure. This can be challenging, especially when exposure is measured at irregular intervals and has some missing values. Here we describe a method for determining a measure of long-term exposure using data on postnatal mercury (Hg) from the Seychelles Child Development Study (SCDS) Main Cohort as a model. In this cohort (n = 779), we incorporate postnatal Hg values that were measured on most study participants at seven ages, three between 6 months and 5.5 years ("childhood"), and an additional four between 17 and 24 years ("early adulthood"). We develop time-weighted measures of average exposure during the childhood and the early adulthood periods and compare the strengths and weaknesses of our metric to two standard measures: overall average and cumulative exposure. We account for missing values through an imputation method that uses information about age- and sex-specific Hg means and the participant's Hg values at similar ages to estimate subject-specific missing Hg values. We compare our method to the implicit imputation assumed by these two standard methods, and to Fully Conditional Specification (FCS), an alternative method of imputing missing data. To determine the accuracy of our imputation method we use data from participants with no missing Hg values in the relevant time window. The imputed values from our proposed method are substantially closer to the observed values on average than the average or cumulative exposure, while also performing slightly better than FCS. In conclusion, time-weighted long-term exposure appears to offer advantages over cumulative exposure in longitudinal studies with repeated measures where the follow-up period for a toxicant is similar for all participants. Additionally, our method to impute missing values maximizes the number of participants for whom the overall exposure metric can be calculated and should provide a more accurate long-term exposure metric than standard methods when exposure has missing values. Our method is applicable to any study of long-term toxicant effects when longitudinal exposure measurements are available but have missing values.
在许多关于有毒物质对健康影响的研究中，即使暴露是连续的，也只是一次性测量暴露情况。然而，一些研究在较长时间内对参与者进行了重复测量，目的是确定一个长期指标，以捕捉平均或累积暴露情况。这可能具有挑战性，尤其是当暴露是在不规律的时间间隔内测量的，并且存在一些缺失值时。这里我们描述了一种使用塞舌尔儿童发展研究（SCDS）主要队列的产后汞（Hg）数据来确定长期暴露量的方法，作为模型。在这个队列中（n=779），我们纳入了在 7 个年龄阶段测量的大多数研究参与者的产后 Hg 值，其中 3 个在 6 个月至 5.5 岁之间（“儿童期”），另外 4 个在 17 至 24 岁之间（“青年期”）。我们制定了儿童期和青年期期间平均暴露的时间加权指标，并比较了我们的指标与两种标准指标的优缺点：总体平均值和累积暴露。我们通过一种插补方法来处理缺失值，该方法使用了年龄和性别特异性 Hg 平均值以及参与者在相似年龄时的 Hg 值的信息，以估计特定于个体的缺失 Hg 值。我们将我们的方法与这两种标准方法所假设的隐含插补方法进行比较，并与替代缺失数据插补方法——完全条件说明（FCS）进行比较。为了确定我们的插补方法的准确性，我们使用在相关时间窗口内没有缺失 Hg 值的参与者的数据。与平均或累积暴露相比，我们提出的方法的插补值平均更接近观察值，而性能略优于 FCS。总之，在具有重复测量的纵向研究中，当所有参与者的毒物随访期相似时，时间加权的长期暴露似乎优于累积暴露。此外，我们的缺失值插补方法最大限度地增加了可以计算总体暴露指标的参与者数量，并且当暴露值缺失时，应该比标准方法提供更准确的长期暴露指标。当有纵向暴露测量值但存在缺失值时，我们的方法适用于任何长期毒物效应的研究。
