Re: "Need for more individual-level meta-analyses in social epidemiology: Example of job strain and coronary heart disease"

American Journal of Epidemiology

Volumn 178, Issue 1, 2013, Pages 153-154

  Davey Smith, George ^a   Egger, Matthias ^b   Ebrahim, Shah ^c  

^a UNIVERSITY OF BRISTOL   (United Kingdom)

^b UNIVERSITY OF BERN   (Switzerland)

^c PUBLIC HEALTH FOUNDATION OF INDIA   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ALCOHOL CONSUMPTION; GENETIC EPIDEMIOLOGY; HUMAN; ISCHEMIC HEART DISEASE; LETTER; META ANALYSIS (TOPIC); SMOKING; SOCIAL STATUS;

CORONARY DISEASE; FEMALE; HUMANS; MALE; META-ANALYSIS AS TOPIC; OCCUPATIONAL DISEASES; SOCIOLOGY, MEDICAL; STRESS, PSYCHOLOGICAL;

EID: 84880194460     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwt104     Document Type: Letter

References (16)

1. Kivimäki M, Kawachi I. Need for more individual-level metaanalyses in social epidemiology: Example of job strain and coronary heart disease. Am J Epidemiol. 2012;177(1):1-2
2. Kivimäki M, Nyberg ST, Batty GD, et al. Job strain as a risk factor for coronary heart disease: A collaborative meta-Analysis of individual participant data. Lancet. 2012;380(9852): 1491-1497
3. Colhoun HM, McKeigue PM, Davey Smith G. Problems of reporting genetic associations with complex outcomes. Lancet. 2003;361(9360):865-872
4. Davey Smith G, Lawlor DA, Harbord R, et al. Clustered environments and randomized genes: A fundamental distinction between conventional and genetic epidemiology. PLoS Med. 2008;4(12):1985-1992
5. Davey Smith G, Ebrahim S. 'Mendelian randomization': Can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32(1):1-22
6. Egger M, Schneider M, Davey Smith G. Spurious precision? Meta-Analysis of observational studies. BMJ. 1998; 316:140-144
7. Brion MJ, Lawlor DA, Matijasevich A, et al. What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income and middleincome cohorts. Int J Epidemiol. 2011;40(3):670-680
8. Davey Smith G. Assessing intrauterine influences on offspring health outcomes: Can epidemiological findings yield robust results? Basic Clin Pharmacol Toxicol. 2008;102(2):245-256
9. Lipsitch M, Tchetgen Tchetgen E, Cohen T. Negative controls: A tool for detecting confounding and bias in observational studies. Epidemiology. 2010;21(3):383-388
10. Davey Smith G. Negative control exposures in epidemiologic studies [letter]. Epidemiology. 2012;23(2):350-351
11. Davey Smith G. Use of genetic markers and gene-Diet interactions for interrogating population-level causal influences of diet on health. Genes Nutr. 2011;6(1):27-43
12. Heijmans BT, Mill J. The seven plagues of epigenetic epidemiology. Int J Epidemiol. 2012;41(1):74-78
13. Relton CL, Davey Smith G. Is epidemiology ready for epigenetics? Int J Epidemiol. 2012;41(1):5-9
14. Lewington S, Whitlock G, Clarke R, et al. Blood cholesterol and vascular mortality by age, sex, and blood pressure: A metaanalysis of individual data from 61 prospective studies with 55,000 vascular deaths. Prospective Studies Collaboration. Lancet. 2007;370(9620):1829-1839
15. Kaptoge S, Di Angelantonio E, Lowe G, et al. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: An individual participant meta-Analysis. Emerging Risk Factors Collaboration. Lancet. 2010; 375(9709):132-140
16. Wensley F, Gao P, Burgess S, et al. Association between C reactive protein and coronary heart disease: Mendelian randomisation analysis based on individual participant data. C Reactive Protein Coronary Heart Disease Genetics Collaboration (CCGC). BMJ. 2011;342:d548