Paths to Subjective Poverty Among Midlife and Older Russian‐Speaking Migrants: A Data Mining Approach Using the General Unary Hypotheses Automaton

ABSTRACT In the Nordic countries, older migrants experience higher poverty rates compared with the majority population. Research on this issue highlights a gap in understanding the complex interplay of ageing, migration and poverty risks. Using the General Unary Hypotheses Automaton (GUHA) data mining approach, we identified various factor combinations that contribute to subjective poverty experiences. We analysed data from the 2019 Care, Health, and Ageing of the Russian‐Speaking Minority (CHARM) study in Finland ( N = 1082, 57% men), which covers migration‐related, socio‐demographic, health and behavioural domains. Our findings reveal 37 distinct paths to subjective poverty involving 13 factors, including health limitations, multi‐morbidity, receipt of housing benefit, religious affiliation, poor self‐rated health, immigration age of 36–55, discrimination and living alone. While health‐related factors predominated, our results highlight the intersection of multiple disadvantages in shaping subjective poverty, providing new insights on the dynamics of migrant poverty.

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Publication Details

Journal
International Migration
Published
2025-06-24
DOI
https://doi.org/10.1111/imig.70053
Primary Topic
Migration and Labor Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Paths to Subjective Poverty Among Midlife and Older Russian‐Speaking Migrants: A Data Mining Approach Using the General Unary Hypotheses Automaton

Erja Turunen, Anne M. Kouvonen, Sirpa Wrede, Lily Nosraty
International Migration
Migration and Labor Dynamics
article

Paths to Subjective Poverty Among Midlife and Older Russian‐Speaking Migrants: A Data Mining Approach Using the General Unary Hypotheses Automaton

Erja Turunen, Anne M. Kouvonen, Sirpa Wrede, Lily Nosraty
article en

Abstract

ABSTRACT In the Nordic countries, older migrants experience higher poverty rates compared with the majority population. Research on this issue highlights a gap in understanding the complex interplay of ageing, migration and poverty risks. Using the General Unary Hypotheses Automaton (GUHA) data mining approach, we identified various factor combinations that contribute to subjective poverty experiences. We analysed data from the 2019 Care, Health, and Ageing of the Russian‐Speaking Minority (CHARM) study in Finland ( N = 1082, 57% men), which covers migration‐related, socio‐demographic, health and behavioural domains. Our findings reveal 37 distinct paths to subjective poverty involving 13 factors, including health limitations, multi‐morbidity, receipt of housing benefit, religious affiliation, poor self‐rated health, immigration age of 36–55, discrimination and living alone. While health‐related factors predominated, our results highlight the intersection of multiple disadvantages in shaping subjective poverty, providing new insights on the dynamics of migrant poverty.

International MigrationVol. 63(4)
Queen's University Belfast (GB), University of Helsinki (FI), Tampere University of Applied Sciences (FI), Tampere University (FI), Tampere University (FI)
Strategic Research Council
Openalex Percentile: Top 80%
Migration and Labor Dynamics
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Paths to Subjective Poverty Among Midlife and Older Russian‐Speaking Migrants: A Data Mining Approach Using the General Unary Hypotheses Automaton — Erja Turunen, Anne M. Kouvonen, et al. · International Migration (2025) | TGRS Research Map | TGRS