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      Racial variations of adverse perinatal outcomes: A population-based retrospective cohort study in Ontario, Canada

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          Abstract

          Introduction

          Racial differences in adverse maternal and birth outcomes have been studied in other countries, however, there are few studies specific to the Canadian population. In this study, we sought to examine the inequities in adverse perinatal outcomes between Black and White pregnant people in Ontario, Canada.

          Methods

          We conducted a population-based retrospective cohort study that included all Black and White pregnant people who attended prenatal screening and had a singleton birth in any Ontario hospital (April 1 st, 2012-March 31 st, 2019). Poisson regression with robust error variance models were used to estimate the adjusted relative risks of adverse perinatal outcomes for Black people compared with White people while adjusting for covariates.

          Results

          Among 412,120 eligible pregnant people, 10.1% were Black people and 89.9% were White people. Black people were at an increased risk of gestational diabetes mellitus, preeclampsia, placental abruption, preterm birth (<37, <34, <32 weeks), spontaneous preterm birth, all caesarean sections, emergency caesarean section, low birth weight (<2500g, <1500g), small-for-gestational-age (<10th percentile, <3 rd percentile) neonates, 5-minute Apgar score <4 and <7, neonatal intensive care unit admission, and hyperbilirubinemia requiring treatment but had lower risks of elective caesarean section, assisted vaginal delivery, episiotomy, 3rd and 4th degree perineal tears, macrosomia, large-for-gestational-age neonates, and arterial cord pH≤7.1, as compared with White people. No difference in risks of gestational hypertension and placenta previa were observed between Black and White people.

          Conclusion

          There are differences in several adverse perinatal outcomes between Black and White people within the Ontario health care system. Findings might have potential clinical and health policy implications, although more studies are needed to further understand the mechanisms.

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          Most cited references82

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          A modified poisson regression approach to prospective studies with binary data.

          G Zou (2004)
          Relative risk is usually the parameter of interest in epidemiologic and medical studies. In this paper, the author proposes a modified Poisson regression approach (i.e., Poisson regression with a robust error variance) to estimate this effect measure directly. A simple 2-by-2 table is used to justify the validity of this approach. Results from a limited simulation study indicate that this approach is very reliable even with total sample sizes as small as 100. The method is illustrated with two data sets.
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            Multiple imputation of discrete and continuous data by fully conditional specification.

            The goal of multiple imputation is to provide valid inferences for statistical estimates from incomplete data. To achieve that goal, imputed values should preserve the structure in the data, as well as the uncertainty about this structure, and include any knowledge about the process that generated the missing data. Two approaches for imputing multivariate data exist: joint modeling (JM) and fully conditional specification (FCS). JM is based on parametric statistical theory, and leads to imputation procedures whose statistical properties are known. JM is theoretically sound, but the joint model may lack flexibility needed to represent typical data features, potentially leading to bias. FCS is a semi-parametric and flexible alternative that specifies the multivariate model by a series of conditional models, one for each incomplete variable. FCS provides tremendous flexibility and is easy to apply, but its statistical properties are difficult to establish. Simulation work shows that FCS behaves very well in the cases studied. The present paper reviews and compares the approaches. JM and FCS were applied to pubertal development data of 3801 Dutch girls that had missing data on menarche (two categories), breast development (five categories) and pubic hair development (six stages). Imputations for these data were created under two models: a multivariate normal model with rounding and a conditionally specified discrete model. The JM approach introduced biases in the reference curves, whereas FCS did not. The paper concludes that FCS is a useful and easily applied flexible alternative to JM when no convenient and realistic joint distribution can be specified.
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              Implicit Racial/Ethnic Bias Among Health Care Professionals and Its Influence on Health Care Outcomes: A Systematic Review.

              In the United States, people of color face disparities in access to health care, the quality of care received, and health outcomes. The attitudes and behaviors of health care providers have been identified as one of many factors that contribute to health disparities. Implicit attitudes are thoughts and feelings that often exist outside of conscious awareness, and thus are difficult to consciously acknowledge and control. These attitudes are often automatically activated and can influence human behavior without conscious volition.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                30 June 2022
                2022
                : 17
                : 6
                : e0269158
                Affiliations
                [1 ] Better Outcomes Registry & Network Ontario, Ottawa, Ontario, Canada
                [2 ] School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
                [3 ] Children’s Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
                [4 ] OMNI Research Group, Ottawa Hospital Research Institute, Ottawa, ON, Canada
                [5 ] Department of Obstetrics and Gynecology, University of Ottawa, Faculty of Medicine, Ottawa, Ontario, Canada
                Tulane University School of Public Health and Tropical Medicine, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-4903-8491
                Article
                PONE-D-21-34290
                10.1371/journal.pone.0269158
                9246499
                35772371
                9dff1fa2-6442-47d1-aea6-9140288f2332
                © 2022 Miao et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 October 2021
                : 16 May 2022
                Page count
                Figures: 1, Tables: 3, Pages: 17
                Funding
                Qun Miao is currently holding a Canadian Institutes of Health Research (CIHR) Early Career Investigator Award in Maternal, Reproductive, Child and Youth Health (CIHR Institute of Circulatory and Respiratory Health) in Canada. The funding partner is BORN Ontario. The funders had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Pregnancy
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Pregnancy
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Biology and Life Sciences
                Developmental Biology
                Neonates
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Birth
                Preterm Birth
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Birth
                Preterm Birth
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Pregnancy
                Pregnancy Complications
                Preterm Birth
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Pregnancy
                Pregnancy Complications
                Preterm Birth
                People and places
                Geographical locations
                North America
                Canada
                Ontario
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Birth
                Labor and Delivery
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Birth
                Labor and Delivery
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Birth Weight
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Neonatal Care
                Medicine and Health Sciences
                Pediatrics
                Neonatology
                Neonatal Care
                Medicine and Health Sciences
                Health Care
                Neonatal Care
                Custom metadata
                We are not able to share data to the public due to the Personal Health Information Protection Act in Ontario, Canada. The data analyzed during this study is held securely at the prescribed registry BORN Ontario. Data sharing regulations prevent this data from being made available publicly due to the personal health information in the datasets. Enquiries regarding BORN data must be directed to BORN Ontario ( Science@ 123456BORNOntario.ca ).

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