Preconception health risk profiles among women planning pregnancy in northern Ethiopia: a latent class analysis

Although the WHO and the Centers for Disease Control and Prevention (CDC) classify preconception health risks (PCHRs) into biomedical, behavioural and social categories, this classification remains theoretical, mainly inconsistent and lacks a scientifically robust framework. Data-driven clustering techniques may help clarify this complexity for policymakers and healthcare providers. This study aimed to assess the status of PCHRs and identify latent classes of these risks among women preparing for pregnancy.

This community-based cross-sectional study was conducted from 31 July to 16 August 2024 in Tigray, Ethiopia, among 865 married women planning to conceive within the next 6 months. Data were gathered through face-to-face interviews using a structured questionnaire. Risk factor indicators covering lifestyle behaviours, substance use, nutritional risks and related factors were developed based on guidelines from the WHO, the CDC and national recommendations. Latent class analysis (LCA) was employed to identify distinct classes of PCHRs, with the optimal number of classes determined using statistical fit indices, adequacy criteria and interpretability. The study also evaluated the overall distribution of PCHRs among participants.

The study took place in Tigray, Ethiopia, among married women intending to become pregnant within 6 months.

Burden of PCHRs and identified distinct latent classes of these risks within the participants.

All participants were exposed to at least four PCHRs, with 84.2% experiencing between 6 and 12 risk factors. The optimal LCA model identified four distinct classes of PCHRs: lifestyle behavioural risks (n=458, 52.9%), reproductive health risks and chronic medical conditions (n=106, 12.25%), nutritional risks and environmental exposure (n=149, 17.23%) and social determinants of health (n=152, 17.57%).

Our study reveals a high baseline level of PCHRs, with all participants exhibiting multiple risk factors for adverse pregnancy outcomes. The identification of four distinct risk profiles underscores the need for tailored risk-specific interventions, particularly in conflict-affected settings. Our findings point out the need for targeted preconception care and risk stratification in national health strategies to improve maternal and child health outcomes.