Defining vulnerability subgroups among pregnant women using pre-pregnancy information: a latent class analysis

Area of Science:

• Maternal and Child Health
• Public Health
• Sociology

Background:

• Early detection of maternal vulnerability optimizes the critical first 1000 days of child development.
• Pre-pregnancy identification of risk and protective factors is essential for maternal and child well-being.

Purpose of the Study:

• To identify distinct classes of vulnerability among pregnant women in the Netherlands.
• To validate these vulnerability classes against the risk of adverse pregnancy and birth outcomes.

Main Methods:

• Latent class analysis of 42 pre-pregnancy variables (individual, socioeconomic, lifestyle, psychosocial, health, household).
• Logistic regression analysis to compare identified classes against adverse outcomes.

Main Results:

• Five latent classes of maternal vulnerability were identified in 4172 women.
• The 'multidimensional vulnerability' class (6.0%) exhibited multiple risk factors and was associated with premature birth and caesarean sections.
• Other classes included 'healthy and socioeconomically stable', 'high care utilization', 'socioeconomic vulnerability', and 'psychosocial vulnerability'.

Conclusions:

• The co-existence of multiple risk factors across different domains significantly increases the risk of adverse maternal and child outcomes.
• Targeted interventions focusing on diverse domains and integrated medical and social support are crucial for improving parental health and well-being.