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. 2024 Feb 5;34(1):22-28.
doi: 10.1093/eurpub/ckad184.

Social inequalities in the risk of giving birth to a small for gestational age child in Sweden 2010-16: a cross-sectional study adopting an intersectional approach

Sten Axelsson Fisk  1   2 , Jesper Alex-Petersen  2 , Mikael Rostila  3   4   5 , Can Liu  3   4   6 , Sol Pia Juárez  3   4
Affiliations

Social inequalities in the risk of giving birth to a small for gestational age child in Sweden 2010-16: a cross-sectional study adopting an intersectional approach

Sten Axelsson Fisk et al. Eur J Public Health. .

Abstract

Background: Well-established associations exist between the risk of small for gestational age (SGA) and unidimensional sociodemographic factors. We investigated social inequalities in SGA risk and adopted an intersectional approach that simultaneously considers different social categories. By doing so, we could assess heterogeneities in SGA risk within unidimensional sociodemographic categories.

Methods: We included all live 679 694 singleton births in Sweden between 2010 and 2016. The outcome was SGA, and the exposures were age, maternal educational level, dichotomous migration status and civil status. Thirty-six possible combinations of these factors constituted the exposure in an intersectional model. We present odds ratios (ORs) with 95% confidence intervals (95% CIs) and the area under the receiver operating characteristic curve (AUC)-a measurement of discriminatory accuracy (i.e. the ability to discriminate the babies born SGA from those who are not).

Results: Women with low education and women born outside Sweden had ORs of 1.46 (95% CI 1.38-1.54) and 1.50 (95% CI 1.43-1.56) in unidimensional analyses, respectively. Among women aged under 25 with low education who were born outside Sweden and unmarried, the highest OR was 3.06 (2.59-3.63). The discriminatory accuracy was low for both the unidimensional model that included all sociodemographic factors (AUC 0. 563) and the intersectional model (AUC 0.571).

Conclusions: The intersectional approach revealed a complex sociodemographic pattern of SGA risk. Sociodemographic factors have a low accuracy in identifying SGA at the individual level, even when quantifying their multi-dimensional intersections. This cautions against interventions targeted to individuals belonging to socially defined groups to reduce social inequalities in SGA risk.

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Figures

Figure 1
Figure 1
Flow chart showing the selection of the study population
See this image and copyright information in PMC

References

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