Joint modelling of individual trajectories, within-individual variability and a later outcome: systolic blood pressure through childhood and left ventricular mass in early adulthood
Joint modelling of individual trajectories, within-individual variability and a later outcome: systolic blood pressure through childhood and left ventricular mass in early adulthood
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个体轨迹、个体内变异性和后期结果的联合建模：儿童时期的收缩压和成年早期的左心室质量
DOI：
10.1101/19008474
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Parker R
中科院分区：
文献类型：
--
作者：
Parker R
重复测量暴露的个体内变异性可能预测后期结果（例如，血压（BP）变异性（BPV）是一个独立的心血管风险因素，高于和超过平均血压）。由于2阶段方法通常用于研究此类相关性，因此我们引入了联合建模方法，使用来自英国雅芳父母和儿童队列纵向研究的数据（1990-2011年收集），检查儿童期平均BP和BPV与成年早期左心室质量（以身高为指数; LVMI）的相关性。使用多水平模型，我们允许BPV在个体之间变化（“随机效应”）以及依赖于协变量（允许异方差）。我们进一步区分了诊所内变异性（“测量误差”）与访视间BPV。在年龄较大、体重较高和女性受试者中，预测BPV较大，并且与平均BP呈正相关。BPV与LVMI呈弱正相关（个体内BP方差增加10%，预测LVMI增加0.21%，95%可信区间：-0.23，0.69），但一旦调整平均BP对LVMI的影响，这种相关性变为负相关（-0.78%，95%可信区间：-2.54，0.22）。这种联合建模方法提供了一种灵活的方法，将重复测量的暴露与后来的结果联系起来。
Within-individual variability of repeatedly measured exposures might predict later outcomes (e.g., blood pressure (BP) variability (BPV) is an independent cardiovascular risk factor above and beyond mean BP). Because 2-stage methods, known to introduce bias, are typically used to investigate such associations, we introduce a joint modeling approach, examining associations of mean BP and BPV across childhood with left ventricular mass (indexed to height; LVMI) in early adulthood with data (collected 1990–2011) from the UK Avon Longitudinal Study of Parents and Children cohort. Using multilevel models, we allowed BPV to vary between individuals (a “random effect”) as well as to depend on covariates (allowing for heteroskedasticity). We further distinguished within-clinic variability (“measurement error”) from visit-to-visit BPV. BPV was predicted to be greater at older ages, at higher body weights, and in female participants and was positively correlated with mean BP. BPV had a weak positive association with LVMI (10% increase in within-individual BP variance was predicted to increase LVMI by 0.21%, 95% credible interval: −0.23, 0.69), but this association became negative (−0.78%, 95% credible interval: −2.54, 0.22) once the effect of mean BP on LVMI was adjusted for. This joint modeling approach offers a flexible method of relating repeatedly measured exposures to later outcomes.