Using latent class analysis to develop a model of the relationship between socioeconomic position and ethnicity: cross-sectional analyses from a multi-ethnic birth cohort study
Date
2014
Type:
Artículo
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14
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ORCID:
Journal Title
Journal ISSN
Volume Title
Publisher
BioMed Central
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Abstract
Background: Almost all studies in health research control or investigate socioeconomic position (SEP) as exposure
or confounder. Different measures of SEP capture different aspects of the underlying construct, so efficient
methodologies to combine them are needed. SEP and ethnicity are strongly associated, however not all measures
of SEP may be appropriate for all ethnic groups.
Methods: We used latent class analysis (LCA) to define subgroups of women with similar SEP profiles using 19
measures of SEP. Data from 11,326 women were used, from eight different ethnic groups but with the majority
from White British (40%) or Pakistani (45%) backgrounds, who were recruited during pregnancy to the Born in
Bradford birth cohort study.
Results: Five distinct SEP subclasses were identified in the LCA: (i) “Least socioeconomically deprived and most
educated” (20%); (ii) “Employed and not materially deprived” (19%); (iii) “Employed and no access to money” (16%);
(iv) “Benefits and not materially deprived” (29%) and (v) “Most economically deprived” (16%). Based on the
magnitude of the point estimates, the strongest associations were that compared to White British women, Pakistani
and Bangladeshi women were more likely to belong to groups: (iv) “benefits and not materially deprived” (relative
risk ratio (95% CI): 5.24 (4.44, 6.19) and 3.44 (2.37, 5.00), respectively) or (v) most deprived group (2.36 (1.96, 2.84)
and 3.35 (2.21, 5.06) respectively) compared to the least deprived class. White Other women were more than twice
as likely to be in the (iv) “benefits and not materially deprived group” compared to White British women and all
ethnic groups, other than the Mixed group, were less likely to be in the (iii) “employed and not materially deprived”
group than White British women.
Conclusions: LCA allows different aspects of an individual’s SEP to be considered in one multidimensional
indicator, which can then be integrated in epidemiological analyses. Ethnicity is strongly associated with these
identified subgroups. Findings from this study suggest a careful use of SEP measures in health research, especially
when looking at different ethnic groups. Further replication of these findings is needed in other populations.
Description
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Citation
BMC Public Health 2014 14:835
Keywords
Socioeconomic position, Ethnicity, Latent class analysis, Born in Bradford