Correction to: Examining Racial and Ethnic Disparities in Low-Risk Cesarean Section Deliveries in the Colorado...

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:

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 researchers try to extrapolate results...

The establishment of the oral microbiome begins before birth, challenging the long-held belief that the fetal oral cavity is sterile. The presence of oral microbes such as Streptococcus and Fusobacterium in amniotic fluid suggests that microbial exposure may occur in utero, potentially through translocation from the maternal oral or gastrointestinal tract. This early colonization primes the neonatal immune system and sets the stage for subsequent microbial succession. Maternal health,...

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...