发展中国家剖腹产率的社会经济差异:回顾性分析

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:

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,...

Culture shapes how people approach attraction, choose partners, and build long-term relationships. While some preferences in mate selection appear consistent across cultures, such as men valuing physical attractiveness and women emphasizing financial resources, cultural contexts influence how these preferences are expressed and prioritized. Marriage extends beyond romantic ideals in many societies and is deeply embedded in social, economic, and religious frameworks.The Role of Culture in Mate...

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...

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...

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 phenomenon...