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Bias in Epidemiological Studies

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Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
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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...
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Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
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Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
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Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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加快认知衰退中的不平等:使用嵌套非线性回归解决观察窗口偏差.

Sean A P Clouston1,2, Douglas W Hanes1, Dylan M Smith1,2

  • 1Program in Public Health, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York, USA.

Alzheimer's & dementia : the journal of the Alzheimer's Association
|July 13, 2024
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概括

解决阿尔茨海默病和相关痴呆症 (ADRD) 研究中的观察窗口偏差揭示了显著的社会不平等. 教育差异和种族影响加速认知衰退的开始,突出了ADRD风险的不平等.

关键词:
阿尔茨海默病和相关疾病.认知病理学的认知病理学纵向认知衰退 纵向认知衰退参数细分建模参数细分建模

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科学领域:

  • 神经科学是一个神经科学.
  • 公共卫生 公共卫生
  • 社会学 社会学 社会学

背景情况:

  • 观察窗口偏差使对阿尔茨海默病和相关痴呆症 (ADRD) 风险的教育差异的研究复杂化.
  • 之前的研究已经产生了相互矛盾的结果,因为在观察加速认知衰退之前的时期有局限性.

研究的目的:

  • 在ADRD研究中引入一种解决观察窗口偏差的新型模型.
  • 调查ADRD的加速认知衰退中的差异存在和起源.

主要方法:

  • 利用了来自32,441名健康与退休研究参与者的167,314个认知评估的大数据集.
  • 实现了一个参数非线性嵌套纵向回归模型.
  • 报告的多变量调整的节点发病率 (aNIR) 以量化风险.

主要成果:

  • 大学学位与加速认知衰退的发病率降低了74.7% (aNIR = 0.253,p < 0.001).
  • 黑人参与者表现出99.5%更高的加速认知衰退发病率 (aNIR = 1.995,p < 0.001),即使经过对共变量进行调整.
  • 性别分层分析显示,女性受教育收益减少,少数群体女性的发病率增加.

结论:

  • 这种新的方法有效地减轻了观察窗口的偏差,揭示了ADRD发病的重大社会不平等.
  • 结果表明,在ADRD临床前阶段,教育和种族/种族差异显著.
  • 这项研究强调了性/性别与种族和教育在ADRD差异中的交叉性.