估计假设干预对结构性种族主义模式资源影响的挑战:北卡罗来纳州农村医疗补助人口中的一个例子
Mekhala V Dissanayake1,2,3, John W Jackson4, Chantel L Martin1,2
1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States.
American journal of epidemiology
|April 9, 2025
概括
结构性种族主义影响农村医疗保健和严重孕产妇发病率 (SMM). 假设的资源均等干预措施并没有减少中小企业的差异,这可能是由于边缘化群体的资源获取有限.
科学领域:
- 公共卫生 公共卫生
- 健康差距 研究 研究 研究 研究
- 农村卫生 农村卫生
背景情况:
- 结构性种族主义影响农村地区的资源分配,影响边缘化种族/民族群体.
- 在医疗保健资源分配和严重孕产妇发病率方面存在显著差异.
- 了解这些差异对于开发有效的干预措施至关重要.
研究的目的:
- 量化北卡罗来纳州农村地区的SMM和医疗保健资源分配的种族差异.
- 评估假设的资源均等干预措施是否可以减少中小企业的种族差异.
主要方法:
- 在北卡罗来纳州农村地区 (2014-2019年) 使用链接出生证明和医疗补助申请.
- 假设干预的调解者概率权重的使用比率.
- 专注于在种族群体和县组成中等同妊娠护理提供者比例和产科单位.
主要成果:
- 根据种族和县的种族组成观察到资源分配和SMM率的差异.
- 旨在平衡资源的假设干预措施没有证明中小企业差异的减少.
- 缺乏共同支持可能解释了这些发现,因为边缘化群体没有经历最佳的资源分配.
结论:
- 如果边缘化群体无法获得最佳的资源水平,对医疗保健资源分配的假设干预可能不会减少中小企业的差异.
- 针对健康差异的因果推断方法需要仔细考虑不同群体所经历的资源分配.
- 调查结果强调了解决健康差异的局限性,当干预情景超出了对边缘化人口的观察数据的范围时.
相关概念视频
Strategies for Assessing and Addressing Confounding
70
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
70
Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Study Designs in Epidemiology
144
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
144
Community Based Intervention
26
Community-based interventions in mental health represent a paradigm shift from institution-centered care to treatments embedded within the fabric of local communities. By prioritizing inclusion and leveraging existing societal structures, this approach fosters a supportive environment conducive to addressing mental health challenges while promoting individual dignity and agency.
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
26
Longitudinal Research
11.8K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
11.8K
Confounding in Epidemiological Studies
113
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
113


