A glossary for social-to-biological research.

IF 1.2 4区 社会学 Q4 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Longitudinal and Life Course Studies Pub Date : 2024-11-01 DOI:10.1332/17579597Y2024D000000032
Tony Robertson, Michaela Benzeval, Martin Betzer, Cara Booker, Raphaële Castagné, Cyrille Delpierre, Iain Gallagher, Michelle Kelly-Irving, Cathal McCrory, Tim Morris, Ethan Narimatsu, Robert Paval
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Abstract

Research has shown that our socially structured experiences elicit a biological response, leading to the observation that numerous biomarkers (objective biological measures that are representative of various biological processes) are socially patterned. This 'social-to-biological' research is of interest to researchers across multiple disciplines and topics and especially to those with an interest in understanding the biological embodiment of the 'social environment'. Combining social and biomarker data is also of relevance to those examining the biological determinants of social behaviours (for example, the relationship between genetics and certain behaviours like smoking). However, as much of the research involving biomarkers and social data are multidisciplinary, researchers need to understand why and how to optimally use and combine such data. This article provides a resource for researchers by introducing a range of commonly available biomarkers across studies and countries. Because of the breadth of possible analyses, we do not aim to provide an exhaustive and detailed review of each. Instead, we have structured the glossary to include: an easy-to-understand definition; a description of how it is measured; key considerations when using; and an example of its use in a relevant social-to-biological study. We have limited this glossary to biomarkers that are available in large health and social surveys or population-based cohort studies and focused on biomarkers in adults. We have structured the glossary around the main physiological systems studied in research on social to biological transition and those that go across systems and highlight some basic terms and key theoretical concepts.

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CiteScore
2.50
自引率
11.10%
发文量
43
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