Smooth and shape-constrained quantile distributed lag models.

ABSTRACT: Exposure to environmental pollutants during the gestational period can significantly impact infant health outcomes, such as birth weight and neurological development. Identifying critical windows of susceptibility, which are specific periods during pregnancy when exposure has the most profound effects, is essential for developing targeted interventions. Distributed lag models (DLMs) are widely used in environmental epidemiology to analyze the temporal patterns of exposure and their impact on health outcomes. However, traditional DLMs focus on modeling the conditional mean, which may fail to capture heterogeneity in the relationship between predictors and the outcome. Moreover, when modeling the distribution of health outcomes like gestational birth weight, it is the extreme quantiles that

SUBMITTER: Jin Y 

PROVIDER: S-EPMC12381565 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature