Department of Clinical Sciences Lund, Obstetrics and Gynaecology, Lund University, Lund, BMC C14. Lund, 22185, Sweden.
Department of Obstetrics and Gynaecology, Ystad Hospital, Ystad, Sweden.
Eur J Public Health. 2024 Feb 5;34(1):22-28. doi: 10.1093/eurpub/ckad184.
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.
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).
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).
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.
小胎龄儿(SGA)的风险与单维社会人口因素之间存在明确关联。我们研究了 SGA 风险中的社会不平等,并采用了交叉方法,同时考虑了不同的社会类别。这样,我们可以评估单维社会人口类别中 SGA 风险的异质性。
我们纳入了 2010 年至 2016 年期间瑞典所有 679694 例活产单胎妊娠。结局为 SGA,暴露因素为年龄、母亲教育程度、二元化移民状况和婚姻状况。这些因素的 36 种可能组合构成了交叉模型中的暴露因素。我们报告比值比(OR)及其 95%置信区间(95%CI)和接收者操作特征曲线下面积(AUC)-衡量区分准确性的指标(即区分 SGA 出生婴儿和非 SGA 出生婴儿的能力)。
在单维分析中,教育程度低的女性和出生在瑞典以外的女性的 OR 分别为 1.46(95%CI 1.38-1.54)和 1.50(95%CI 1.43-1.56)。在年龄在 25 岁以下、教育程度低且出生在瑞典以外且未婚的女性中,最高的 OR 为 3.06(2.59-3.63)。对于包含所有社会人口因素的单维模型(AUC 0.563)和交叉模型(AUC 0.571),区分准确性均较低。
交叉方法揭示了 SGA 风险的复杂社会人口模式。社会人口因素在个体水平上识别 SGA 的准确性较低,即使在量化其多维交叉时也是如此。这提醒人们不要针对属于社会定义群体的个体进行干预,以减少 SGA 风险中的社会不平等。