How to use sequence analysis for life course epidemiology? An example on HIV-positive Sub-Saharan migrants in France

Abstract

Background: Life course epidemiology is now an established field in social epidemiology; in sociodemography, the quantitative analysis of biographies recently experienced significant trend from event history analysis to sequence analysis. The purpose of this article is to introduce and adapt this methodology to a social epidemiology question, taking the example of the impact of HIV diagnosis on Sub-Saharan migrants' residential trajectories in the Paris region.

Methods: The sample consists of 640 migrants born in Sub-Saharan Africa receiving HIV care. They were interviewed in healthcare facilities in the Paris region within the PARCOURS project, conducted from 2012 to 2013, using life event history calendars, which recorded year by year their health, family and residential histories. We introduce a two-step methodological approach consisting of (1) sequence analysis by optimal matching to build a typology of migrants' residential pathways before and after diagnosis, and (2) a Cox model of the probability to experience changes in the residential situation.

Results: The seven-clusters typology shows that for a majority, the HIV diagnosis did not entail changes in residential situation. However 30% of the migrants experienced a change in their residential situation at time of diagnosis. The Cox model analysis reveals that this residential change was in fact moving in with one's partner (HR 2.99, P<0.000) rather than network rejection.

Conclusion: This original combination of sequence analysis and Cox models is a powerful process that could be applied to other themes and constitutes a new approach in the life course epidemiology toolbox.

Trial registration number: NCT02566148.

Keywords: communicable diseases; demography; epidemiological methods; life course epidemiology; longitudinal studies.