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加利福尼亚州的邻里投资不足与严重孕产妇发病率。

Neighborhood disinvestment and severe maternal morbidity in the state of California.

机构信息

Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA (Dr Mujahid, Mses Hailu, Gao, and Morris, and Dr Abrams).

Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University (Drs Wall-Wieler and Carmichael); Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada (Dr Wall-Wieler).

出版信息

Am J Obstet Gynecol MFM. 2023 Jun;5(6):100916. doi: 10.1016/j.ajogmf.2023.100916. Epub 2023 Mar 10.

Abstract

BACKGROUND

Social determinants of health, including neighborhood context, may be a key driver of severe maternal morbidity and its related racial and ethnic inequities; however, investigations remain limited.

OBJECTIVE

This study aimed to examine the associations between neighborhood socioeconomic characteristics and severe maternal morbidity, as well as whether the associations between neighborhood socioeconomic characteristics and severe maternal morbidity were modified by race and ethnicity.

STUDY DESIGN

This study leveraged a California statewide data resource on all hospital births at ≥20 weeks of gestation (1997-2018). Severe maternal morbidity was defined as having at least 1 of 21 diagnoses and procedures (eg, blood transfusion or hysterectomy) as outlined by the Centers for Disease Control and Prevention. Neighborhoods were defined as residential census tracts (n=8022; an average of 1295 births per neighborhood), and the neighborhood deprivation index was a summary measure of 8 census indicators (eg, percentage of poverty, unemployment, and public assistance). Mixed-effects logistic regression models (individuals nested within neighborhoods) were used to compare odds of severe maternal morbidity across quartiles (quartile 1 [the least deprived] to quartile 4 [the most deprived]) of the neighborhood deprivation index before and after adjustments for maternal sociodemographic and pregnancy-related factors and comorbidities. Moreover, cross-product terms were created to determine whether associations were modified by race and ethnicity.

RESULTS

Of 10,384,976 births, the prevalence of severe maternal morbidity was 1.2% (N=120,487). In fully adjusted mixed-effects models, the odds of severe maternal morbidity increased with increasing neighborhood deprivation index (odds ratios: quartile 1, reference; quartile 4, 1.23 [95% confidence interval, 1.20-1.26]; quartile 3, 1.13 [95% confidence interval, 1.10-1.16]; quartile 2, 1.06 [95% confidence interval, 1.03-1.08]). The associations were modified by race and ethnicity such that associations (quartile 4 vs quartile 1) were the strongest among individuals in the "other" racial and ethnic category (1.39; 95% confidence interval, 1.03-1.86) and the weakest among Black individuals (1.07; 95% confidence interval, 0.98-1.16).

CONCLUSION

Study findings suggest that neighborhood deprivation contributes to an increased risk of severe maternal morbidity. Future research should examine which aspects of neighborhood environments matter most across racial and ethnic groups.

摘要

背景

健康的社会决定因素,包括邻里环境,可能是严重产妇发病率及其相关的种族和民族不平等的关键驱动因素;然而,调查仍然有限。

目的

本研究旨在检验邻里社会经济特征与严重产妇发病率之间的关联,以及邻里社会经济特征与严重产妇发病率之间的关联是否因种族和民族而异。

研究设计

本研究利用了加利福尼亚州全州范围内的所有 20 周以上妊娠(1997-2018 年)的医院分娩数据资源。严重产妇发病率定义为至少有一种 21 种诊断和程序(如输血或子宫切除术),这些诊断和程序是由疾病控制和预防中心规定的。邻里关系被定义为居住的人口普查区(n=8022;每个邻里平均有 1295 例分娩),而邻里剥夺指数是 8 个人口普查指标的综合衡量标准(如贫困、失业和公共援助的百分比)。采用个体嵌套在邻里关系中的混合效应逻辑回归模型,比较了邻里剥夺指数的四个四分位数(四分位 1[最不贫困]到四分位 4[最贫困])之间的严重产妇发病率的比值比(OR),并在调整了产妇社会人口学和妊娠相关因素以及合并症后。此外,创建了交叉乘积项来确定关联是否因种族和民族而异。

结果

在 10384976 例分娩中,严重产妇发病率为 1.2%(N=120487)。在完全调整的混合效应模型中,严重产妇发病率随着邻里剥夺指数的增加而增加(比值比:四分位 1,参考;四分位 4,1.23[95%置信区间,1.20-1.26];四分位 3,1.13[95%置信区间,1.10-1.16];四分位 2,1.06[95%置信区间,1.03-1.08])。种族和民族的关联存在差异,在“其他”种族和民族类别的个体中,关联(四分位 4 与四分位 1)最强(1.39;95%置信区间,1.03-1.86),而在黑人个体中最弱(1.07;95%置信区间,0.98-1.16)。

结论

研究结果表明,邻里贫困导致严重产妇发病率增加。未来的研究应该检验邻里环境的哪些方面在不同种族和民族群体中最重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4084/10959123/7bbaa8a235ba/nihms-1973419-f0001.jpg

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