Project 1.2

What do the family networks of older migrants in the Netherlands look like, and how do they relate to strengthening or weakening social cohesion? This project uses microdata from Statistics Netherlands (CBS) to analyse differences in the size, structure and spatial distribution of kinship networks among older migrants and non-migrants. This PhD project will compare patterns across diverse migrant groups and explore how these relate to key outcomes such as health, well-being, and loneliness in later life. This position offers the opportunity to work with rich population-level data and contribute to timely debates on ageing, migration and social inequalities.

The aim of this project is to examine the size, structure and diversity of kinship networks among older migrants in the Netherlands. Using Statistics Netherlands (CBS) microdata, the project will assess how network characteristics and family configurations are associated with older migrants’ health, well-being and loneliness. The project will identify differences across migrant groups and between migrants and non-migrants, and analyse how kinship networks change over time and across institutional contexts. Where the expertise and interests of the candidate allow, the project will be complemented by a qualitative component aimed at understanding how older migrants themselves interpret, navigate and experience their family networks and social ties.

This project employs a mixed-methods, cross-level research design that integrates quantitative and qualitative approaches to investigate the family networks of older migrants in the Netherlands and their relationship to loneliness. The study combines the use of CBS microdata, including information on kinship networks and health, geospatial mapping and – if feasible – qualitative interviews to provide a multidimensional understanding of how family configurations evolve and operate in later life.

The core of the quantitative analysis will draw on linked CBS microdata, which offers detailed demographic, household and migration-related information at the individual and household levels. Using this data, the project will construct family network typologies that capture both the structure (e.g., size, proximity, intergenerational ties) and spatial distribution (e.g., geographic dispersion or co-residence) of networks among older migrants and their non-migrant counterparts. Geospatial mapping will further enrich the analysis by highlighting regional or urban–rural variations in network configurations and their correlation with health and well-being outcomes, such as loneliness indicators.

To deepen the analysis and validate the patterns observed in the quantitative data, a small number of qualitative interviews may be conducted, focusing on the lived experiences of older migrants in navigating family ties, emotional support and social embeddedness.

A key innovation of the project lies in its historical and comparative lens. By comparing across migrant groups with different arrival cohorts and legal pathways, the project explores how varied migration histories have shaped family networks over time. This approach allows for a better understanding of how structural factors – such as integration regimes, housing policies and welfare access – interact with personal and cultural norms to influence later-life loneliness.