58 CHAPTER 3 whether this can be assessed using solely routinely collected observational data and what the added value of self-reported data is. Moreover, we lack an understanding of the strongest predictors for population-level vulnerability. Mapping out the percentage of multidimensional vulnerability among pregnant women in the Netherlands and its predictors is relevant for risk stratification. In population health management, this is an essential initial step to tailor (preventive) actions to the needs of specific risk-groups to enhance population health (13, 14). Such stratification commonly relies on routinely collected data (15), offering advantages such as widespread availability, reduced practitioner burden, time and costs (16, 17). Moreover, the longitudinal and systematic approach facilitates comparisons over time (16, 17). However, it is important to empirically evaluate whether routinely collected data is sufficient for risk-stratification for high-risk groups. In addition, there is a potential for improvement in predicting multidimensional vulnerability at population-level by incorporating self-reported health, well-being and lifestyle data. For example, studies indicate that self-reported health and vulnerability correspond to or complement clinical measures in predicting adverse health outcomes (18-22). Yet, the impact of adding self-reported data next to routinely collected data in predicting vulnerability remains unexplored. This study has three objectives. First, to assess the feasibility of accurately predicting multidimensional vulnerability during pregnancy at population-level using solely routinely collected observational data. We use the predictions to report on the prevalence and spatial variation of multidimensional vulnerability during pregnancy at population-level in the Netherlands. Second, to identify whether self-reported data on health, wellbeing, and lifestyle could improve those predictions with routinely collected data. Third, to identify the predictors that have the most significant impact on the classification of multidimensional vulnerability. METHODS Data sources This study employed data from DIAPER (Data-InfrAstructure for ParEnts and childRen) (17). DIAPER integrates individual-level, routinely collected observational data from various nationwide data sources in the Netherlands, including Perined and Statistics Netherlands. Perined collects routine care data on pregnancy, birth, and the first 28 days after birth from midwives, gynaecologists, and paediatricians (23). Statistics Netherlands collects data about social issues, including health, welfare, income, education, and labour (24, 25). To enrich DIAPER, self-reported data on health, well-being, and lifestyle of the PHM-2016 were included (26). The PHM is a health survey conducted every 4 years among a varying sample of Dutch adults aged 19 years and older (about 450.000 in 2016).
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