Fatemi Yasin, Ali Haneen, Zheng Jingyi
Department of Industrial and Systems Engineering, Auburn University, Auburn, AL, USA.
Health Services Administration Program, Auburn University, 351 W Thach Concourse, 7080 Haley Center, Auburn, AL, 36849, USA.
J Racial Ethn Health Disparities. 2025 Apr 29. doi: 10.1007/s40615-025-02440-7.
The study employed a robust network analysis methodology to assess the effects of race and comorbidities on birth outcomes, using a dataset of 443,902 mothers in Alabama from 2014 to 2021.
Four multimorbidity networks corresponding to White, Black, Asian, and American Indian and Alaska Native groups were constructed to explore distinct comorbidity patterns. The nodes in these networks represented various diseases, while the edges, quantified by the Salton Cosine Index, depicted the associations between these conditions. Additionally, two separate networks were analyzed for low birth weight (LBW) and normal birth weight (NBW) to identify the differential impacts of specific diseases. Feature selection methods including random forest and logistic regression were applied to pinpoint crucial intersections between the LBW and NBW networks, enhancing the granularity of the analysis.
The findings indicated significant racial disparities in the density of comorbidity networks, with more complex disease interactions observed among Black, American Indian and Alaska Native, and Asian groups compared to Whites. Preexisting hypertension and eclampsia emerged as significant risk factors for LBW in White and Black groups, while gestational hypertension was prevalent across multiple racial groups. The LBW network displayed greater density than the NBW network, highlighting the intricate connections between comorbidities leading to adverse birth outcomes.
These insights underline the necessity for healthcare interventions tailored to the distinct health profiles of each racial group to effectively address and reduce maternal health disparities.
该研究采用了强大的网络分析方法,利用2014年至2021年阿拉巴马州443,902名母亲的数据集,评估种族和合并症对出生结局的影响。
构建了分别对应白人、黑人、亚洲人、美洲印第安人和阿拉斯加原住民群体的四个多重合并症网络,以探索不同的合并症模式。这些网络中的节点代表各种疾病,而通过索尔顿余弦指数量化的边则描绘了这些病症之间的关联。此外,还对低出生体重(LBW)和正常出生体重(NBW)分别进行了两个单独的网络分析,以确定特定疾病的不同影响。应用包括随机森林和逻辑回归在内的特征选择方法,以确定LBW和NBW网络之间的关键交叉点,提高分析的粒度。
研究结果表明,合并症网络的密度存在显著的种族差异,与白人相比,黑人、美洲印第安人和阿拉斯加原住民以及亚洲人群体中观察到更复杂的疾病相互作用。既往高血压和子痫在白人和黑人组中是LBW的重要危险因素,而妊娠期高血压在多个种族群体中普遍存在。LBW网络的密度高于NBW网络,突出了导致不良出生结局的合并症之间的复杂联系。
这些见解强调了针对每个种族群体独特的健康状况量身定制医疗保健干预措施的必要性,以有效解决和减少孕产妇健康差异。