Predicting population-level vulnerability among pregnant women using routinely collected data and the added relevance of self-reported data.

ABSTRACT: Recognizing and addressing vulnerability during the first thousand days of life can prevent health inequities. It is necessary to determine the best data for predicting multidimensional vulnerability (i.e. risk factors to vulnerability across different domains and a lack of protective factors) at population level to understand national prevalence and trends. This study aimed to (1) assess the feasibility of predicting multidimensional vulnerability during pregnancy using routinely collected data, (2) explore potential improvement of these predictions by adding self-reported data on health, well-being, and lifestyle, and (3) identify the most relevant predictors. The study was conducted using Dutch nationwide routinely collected data and self-reported Public Health Monitor data. First, to p

SUBMITTER: Molenaar JM 

PROVIDER: S-EPMC11631480 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature