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Using Latent Class Analysis to Model Socioeconomic Position: Results from Three UK Birth Cohorts

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Abstract

Background: Socioeconomic position (SEP) is a multi-dimensional construct which changes over time as societal norms and behaviours change. Exploring how SEP differs between cohorts requires access to equivalent SEP indicators from the same socio-cultural context, which are often unavailable. However, consistent measures can be derived using retrospective harmonization, allowing researchers to conduct cross-cohort comparisons in relationships between equivalent variables. This study aimed to model SEP and then identify associated characteristics using harmonized data from three UK birth cohorts: the BCS70 (1970s), ALSPAC (1990s), and MCS (2000s).

Method: Latent class analysis (LCA) was conducted in each cohort using harmonized SEP data. The validity of the latent class models was evaluated with a subjective measure of financial stress. Finally, sociodemographic characteristics were tested as covariates of the latent classes to explore cross-cohort differences in the profile of the people within each class.

Results: Although different latent class models emerged in each cohort, the most disadvantaged class within in each cohort experienced the highest subjective financial difficulties. Additionally, certain characteristics were consistently associated with the most disadvantaged class across cohorts including single or cohabiting parents, parents that smoked, larger family sizes, and greater maternal mental distress.

Discussion: Despite using equivalent SEP indicators, the findings suggest that the nature and composition of SEP differs between cohorts. Nonetheless, the most disadvantaged in each cohort consistently experienced greater financial strain and were distinguished by specific sociodemographic characteristics; however, the risks associated with those characteristics fluctuate over time.
Original languageEnglish
Pages (from-to)1717-1746
Number of pages30
JournalSocial Indicators Research
Volume180
Early online date13 Oct 2025
DOIs
Publication statusPublished (in print/issue) - 30 Dec 2025

Bibliographical note

© The Author(s) 2025

Data Availability Statement

Data for the BCS70 are available through the UK Data Service repository for free, https://doi.org/10.5255/UKDA-Series-200001. Data for the MCS are available through the UK Data service repository for free, https://doi.org/10.5255/UKDA-Series-2000031. Data for the ALSPAC cohort are available from the University of Bristol for a fee following a research proposal, see https://www.bristol.ac.uk/als pac/researchers/access/.

Funding

This work was supported by a Vice-Chancellor’s Research Scholarship at Ulster University for the first author’s PhD studentship. The BCS70 and MCS are core funded by the Economic and Social Research Council (ESRC) and are hosted by the Centre for Longitudinal Studies at University College London. Additionally, the MCS is also funded by a consortium of governmental departments. The UK Medical Research Council and Wellcome (Grant ref: 217,065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and C. Rawers, O. McBride, J. Murphy, and E. McElroy will serve as guarantors for the contents of this paper. A comprehensive list of grants funding is available on the ALSPAC website

FundersFunder number
University of Bristol
Medical Research Council
Economic and Social Research Council
217,065/Z/19/Z

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • harmonization
    • Socioeconomic inequalities
    • Time trends
    • ALSPAC
    • Harmonization

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