Mediators of socioeconomic inequalities in preterm birth: a systematic review

Philip McHale1, Gillian Maudsley2, Andy Pennington2

  • 1Department of Public Health, Policy and Systems, Institute of Population Health, University of Liverpool, Liverpool, England. hlpmchal@liverpool.ac.uk.

BMC Public Health
|June 6, 2022
PubMed
Abstract

Related Concept Videos

Regression Toward the Mean01:52

Regression Toward the Mean

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...
6.5K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

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:  
713
Environmental Influences on Intelligence01:29

Environmental Influences on Intelligence

Despite the strong genetic influence on traits like intelligence, environmental factors significantly shape outcomes. For example, while over 90% of height variation is due to genetic differences, environmental factors such as nutrition also have a notable impact. Similarly, for intelligence, changes in a child's surroundings can significantly alter their IQ. Research shows that enriched environments boost children's academic success and help them develop key cognitive skills. Children...
439
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

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...
280