A life course approach to explore the biological embedding of socioeconomic position and social mobility through circulating inflammatory markers

Scientific Reports

Volumn 6, Issue , 2016, Pages

  Castagné, Raphaële ^a,b   Delpierre, Cyrille ^b   Kelly Irving, Michelle ^b   Campanella, Gianluca ^a   Guida, Florence ^a   Krogh, Vittorio ^c   Palli, Domenico ^d   Panico, Salvatore ^e   Sacerdote, Carlotta ^f   Tumino, Rosario ^g   Kyrtopoulos, Soterios ^h   Hosnijeh, Fatemeh Saberi ⁱ   Lang, Thierry ^b   Vermeulen, Roel ^a,i   Vineis, Paolo ^a,j   Stringhini, Silvia ^k   Chadeau Hyam, Marc ^a,i  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b UNIVERSITÉ PAUL SABATIER   (France)

^c NATIONAL CANCER INSTITUTE   (Italy)

^d Istituto per Lo Studio e la Prevenzione Oncologica (ISPO Toscana)   (Italy)

^e UNIVERSITY OF NAPLES FEDERICO II   (Italy)

^f Piedmont Reference Centre for Epidemiology and Cancer Prevention (CPO Piemonte)   (Italy)

^g CIVILE M P AREZZO HOSPITAL   (Italy)

^h INSTITUTE OF BIOLOGY   (Greece)

ⁱ UTRECHT UNIVERSITY   (Netherlands)

^j Human Genetics Foundation   (Italy)

^k UNIVERSITY OF LAUSANNE   (Switzerland)

more..

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER; GRANULOCYTE COLONY STIMULATING FACTOR;

ADULT; BLOOD; EUROPE; FEMALE; HUMAN; INFLAMMATION; MALE; MIDDLE AGED; PROSPECTIVE STUDY; RISK FACTOR; SOCIAL CLASS;

ADULT; BIOMARKERS; EUROPE; FEMALE; GRANULOCYTE COLONY-STIMULATING FACTOR; HUMANS; INFLAMMATION; MALE; MIDDLE AGED; PROSPECTIVE STUDIES; RISK FACTORS; SOCIAL MOBILITY;

EID: 84964621908     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep25170     Document Type: Article

References (37)

1. Mackenbach, J. P. et al. Socioeconomic Inequalities in Health in 22 European Countries. N. Engl. J. Med. 358, 2468-2481 (2008).
2. Mackenbach, J. P. Health inequalities: Europe in profile (Produced by COI for the Department of Health, 2006).
3. Marmot, M. et al. Closing the gap in a generation: health equity through action on the social determinants of health. The Lancet 372, 1661-1669 (2008).
4. Stringhini, S. et al. Health Behaviours, Socioeconomic Status, and Mortality: Further Analyses of the British Whitehall II and the French GAZEL Prospective Cohorts. PLos Med. 8, e1000419 (2011).
5. Gallo, V. et al. Social Inequalities and Mortality in Europe-Results from a Large Multi-National Cohort. PLos One 7, e39013 (2012).
6. Blane, D., Kelly-Irving, M., d'Errico, A., Bartley, M., Montgomery, S. Social-biological transitions: how does the social become biological? Longitud. Life Course Stud. 4, 136-146 (2013).
7. McEwen, B. S. Physiology and Neurobiology of Stress and Adaptation: Central Role of the Brain. Physiol. Rev. 87, 873-904 (2007).
8. Yang, E. V., Glaser, R. Stress-induced immunomodulation and the implications for health. Int. Immunopharmacol. 2, 315-324 (2002).
9. Scrivo, R., Vasile, M., Bartosiewicz, I., Valesini, G. Inflammation as "common soil" of the multifactorial diseases. Autoimmun. Rev. 10, 369-374 (2011).
10. Ranjit, N. et al. Socioeconomic position, race/ethnicity, and inflammation in the multi-ethnic study of atherosclerosis. Circulation 116, 2383-2390 (2007).
11. Koster, A. et al. Association of inflammatory markers with socioeconomic status. J. Gerontol. A. Biol. Sci. Med. Sci. 61, 284-290 (2006).
12. Gruenewald, T. L., Cohen, S., Matthews, K. A., Tracy, R., Seeman, T. E. Association of socioeconomic status with inflammation markers in black and white men and women in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Soc. Sci. Med. 69, 451-459 (2009).
13. Fraga, S. et al. Association of socioeconomic status with inflammatory markers: a two cohort comparison. Prev. Med. 71, 12-19 (2015).
14. Panagiotakos, D. B. et al. The association between educational status and risk factors related to cardiovascular disease in healthy individuals: The ATTICA study. Ann. Epidemiol. 14, 188-194 (2004).
15. Steinvil, A. et al. Relation of educational level to inflammation-sensitive biomarker level. Am. J. Cardiol. 102, 1034-1039 (2008).
16. Kelly-Irving, M., Mabile, L., Grosclaude, P., Lang, T., Delpierre, C. The embodiment of adverse childhood experiences and cancer development: potential biological mechanisms and pathways across the life course. Int. J. Public Health 58, 3-11 (2013).
17. Ben-Shlomo, Y., Kuh, D. A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. Int. J. Epidemiol. 31, 285-293 (2002).
18. Loucks, E. B. et al. Life course socioeconomic position is associated with inflammatory markers: the Framingham Offspring Study. Soc. Sci. Med. 71, 187-195 (2010).
19. Stringhini, S. et al. Association of lifecourse socioeconomic status with chronic inflammation and type 2 diabetes risk: the Whitehall II prospective cohort study. PLos Med. 10, e1001479 (2013).
20. Ansar, W., Ghosh, S. C-reactive protein and the biology of disease. Immunol. Res. 56, 131-142 (2013).
21. Leng, S. X. et al. ELISA and multiplex technologies for cytokine measurement in inflammation and aging research. J. Gerontol. A. Biol. Sci. Med. Sci. 63, 879-884 (2008).
22. Moncunill, G., Aponte, J. J., Nhabomba, A. J., Dobanõ, C. Performance of multiplex commercial kits to quantify cytokine and chemokine responses in culture supernatants from Plasmodium falciparum stimulations. PLos One 8, e52587 (2013).
23. Hebels, D. G. A. J. et al. Performance in omics analyses of blood samples in long-term storage: opportunities for the exploitation of existing biobanks in environmental health research. Environ. Health Perspect. 121, 480-487 (2013).
24. Chaturvedi, A. K. et al. Evaluation of multiplexed cytokine and inflammation marker measurements: a methodologic study. Cancer Epidemiol. Biomark. Prev. Publ. Am. Assoc. Cancer Res. Cosponsored Am. Soc. Prev. Oncol. 20, 1902-1911 (2011).
25. Klassen, A. C., Smith, K. C. The enduring and evolving relationship between social class and breast cancer burden: a review of the literature. Cancer Epidemiol. 35, 217-234 (2011).
26. Lawlor, D. A., Smith, G. D., Rumley, A., Lowe, G. D. O., Ebrahim, S. Associations of fibrinogen and C-reactive protein with prevalent and incident coronary heart disease are attenuated by adjustment for confounding factors. British Women's Heart and Health Study. Thromb. Haemost. 93, 955-963 (2005).
27. Pollitt, R. A. et al. Early-life and adult socioeconomic status and inflammatory risk markers in adulthood. Eur. J. Epidemiol. 22, 55-66 (2007).
28. Mendall, M. A. et al. Relation of serum cytokine concentrations to cardiovascular risk factors and coronary heart disease. Heart 78, 273-277 (1997).
29. Ben-Shlomo, Y., Kuh, D. A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. Int. J. Epidemiol. 31, 285-293 (2002).
30. Krieger, N. Embodiment: a conceptual glossary for epidemiology. J. Epidemiol. Community Health 59, 350-355 (2005).
31. Palli, D. et al. A molecular epidemiology project on diet and cancer: the EPIC-Italy Prospective Study. Design and baseline characteristics of participants. Tumori 89, 586-593 (2003).
32. Fraga, S. et al. Association of socioeconomic status with inflammatory markers: a two cohort comparison. Prev. Med. 71, 12-19 (2015).
33. Seeman, T. E., Singer, B. H., Rowe, J. W., Horwitz, R. I., McEwen, B. S. Price of adaptation-allostatic load and its health consequences. MacArthur studies of successful aging. Arch. Intern. Med. 157, 2259-2268 (1997).
34. Juster, R.-P., McEwen, B. S., Lupien, S. J. Allostatic load biomarkers of chronic stress and impact on health and cognition. Neurosci. Biobehav. Rev. 35, 2-16 (2010).
35. Development Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0 (2005).
36. Lubin, J. H. et al. Epidemiologic evaluation of measurement data in the presence of detection limits. Environ. Health Perspect. 112, 1691-1696 (2004).
37. Chadeau-Hyam, M. et al. Prediagnostic transcriptomic markers of Chronic lymphocytic leukemia reveal perturbations 10 years before diagnosis. Ann. Oncol. 25, 1065-1072 (2014).