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

J M Molenaar; L van der Meer; L C M Bertens; E F de Vries; A J M Waelput; M Knight; E A P Steegers; J C Kiefte-de Jong; J N Struijs

doi:10.1093/eurpub/ckac170

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

Eur J Public Health. 2023 Feb 3;33(1):25-34. doi: 10.1093/eurpub/ckac170.

Authors

J M Molenaar^{1

2}, L van der Meer³, L C M Bertens³, E F de Vries^{1

2}, A J M Waelput³, M Knight^{2

4}, E A P Steegers³, J C Kiefte-de Jong², J N Struijs^{1

2}

Affiliations

¹ Department of Quality of Care and Health Economics, National Institute for Public Health and the Environment (RIVM), Centre for Nutrition, Prevention and Health Services, Bilthoven, the Netherlands.
² Department of Public Health and Primary Care/Health Campus The Hague, Leiden University Medical Centre, the Hague, the Netherlands.
³ Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands.
⁴ National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Abstract

Background: Early detection of vulnerability during or before pregnancy can contribute to optimizing the first 1000 days, a crucial period for children's development and health. We aimed to identify classes of vulnerability among pregnant women in the Netherlands using pre-pregnancy data on a wide range of social risk and protective factors, and validate these classes against the risk of adverse outcomes.

Methods: We conducted a latent class analysis based on 42 variables derived from nationwide observational data sources and self-reported data. Variables included individual, socioeconomic, lifestyle, psychosocial and household characteristics, self-reported health, healthcare utilization, life-events and living conditions. We compared classes in relation to adverse outcomes using logistic regression analyses.

Results: In the study population of 4172 women, we identified five latent classes. The largest 'healthy and socioeconomically stable'-class [n = 2040 (48.9%)] mostly shared protective factors, such as paid work and positively perceived health. The classes 'high care utilization' [n = 485 (11.6%)], 'socioeconomic vulnerability' [n = 395 (9.5%)] and 'psychosocial vulnerability' [n = 1005 (24.0%)] were characterized by risk factors limited to one specific domain and protective factors in others. Women classified into the 'multidimensional vulnerability'-class [n = 250 (6.0%)] shared multiple risk factors in different domains (psychosocial, medical and socioeconomic risk factors). Multidimensional vulnerability was associated with adverse outcomes, such as premature birth and caesarean section.

Conclusions: Co-existence of multiple risk factors in various domains is associated with adverse outcomes for mother and child. Early detection of vulnerability and strategies to improve parental health and well-being might benefit from focussing on different domains and combining medical and social care and support.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Cesarean Section*
Child
Female
Humans
Latent Class Analysis
Pregnancy
Pregnant People*
Risk Factors
Socioeconomic Factors