New models for large prospective studies: Is there a risk of throwing out the baby with the bathwater?

American Journal of Epidemiology

Volumn 177, Issue 4, 2013, Pages 285-289

  Bracken, Michael B ^a   Baker, Dean ^a   Cauley, Jane A ^a   Chambers, Christina ^a   Culhane, Jennifer ^a   Dabelea, Dana ^a   Dearborn, Dorr ^a   Drews Botsch, Carolyn D ^a   Dudley, Donald J ^a   Durkin, Maureen ^a   Entwisle, Barbara ^a   Flick, Louise ^a   Hale, Daniel ^a   Holl, Jane ^a   Hovell, Melbourne ^a   Hudak, Mark ^a   Paneth, Nigel ^a   Specker, Bonny ^a   Wilhelm, Mari ^a   Wyatt, Sharon ^a  

^a YALE UNIVERSITY   (United States)

Author keywords

cohort studies; epidemiology; prospective studies; research design

Indexed keywords

SEROTONIN TRANSPORTER;

ASSESSMENT METHOD; COHORT ANALYSIS; DATA PROCESSING; DATABASE; EPIDEMIOLOGY; HEALTH CARE; RESEARCH WORK; SAMPLING BIAS; SUBPOPULATION;

BLOOD SAMPLING; COHORT ANALYSIS; COST EFFECTIVENESS ANALYSIS; DEPRESSION; ENVIRONMENTAL EXPOSURE; ENVIRONMENTAL FACTOR; GENOTYPE ENVIRONMENT INTERACTION; HEALTH CARE PERSONNEL; HEALTH CARE SYSTEM; HEREDITY; HUMAN; MEDICAL RESEARCH; PROSPECTIVE STUDY; REVIEW;

UNITED STATES;

EID: 84873633913     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kws408     Document Type: Review

References (36)

1. Manolio TA, Weis BK, Cowie CC, et al. New models for large prospective studies: is there a better way? Am J Epidemiol. 2012;175(9):859-866.
2. Hamilton CM, Strader LC, Pratt JG, et al. The PhenX Toolkit: get the most from your measures. Am J Epidemiol. 2011;174(3):253-260.
3. Fortier I, Doiron D, Burton P, et al. Invited commentary: consolidating data harmonization-how to obtain quality and applicability? Am J Epidemiol. 2011;174(3):261-264.
4. Klein RJ, Zeiss C, Chew EY, et al. Complement factor H polymorphism in age-related macular degeneration. Science. 2005;308(5720):385-389.
5. Dewan A, Liu M, Hartman S, et al. HTRA1 promoter polymorphism in wet age-related macular degeneration. Science. 2006;314(5801):989-992.
6. Botto L, Lin AE, Riehle-Colarusso T, et al. Seeking causes: classifying and evaluating congenital heart defects in etiologic studies. Birth Defects Res A Clin Mol Teratol. 2007;79(10):714-727.
7. Havill LM, Mahaney MC, Binkley TL, et al. Effects of genes, sex, age and activity on BMC, bone size, and areal and volumetric BMD. J Bone Mineral Res. 2007;22(5):737-746.
8. Yang YJ, Dvornyk V, Jian WX, et al. Genetic and environmental correlations between bone phenotypes and anthropometric indices in Chinese. Osteoporos Int. 2005; 16(9):1134-1140.
9. Kimmel CA, Collman GW, Fields N, et al. Lessons learned for the National Children's Study from the National Institute of Environmental Health Sciences/U.S. Environmental Protection Agency Centers for Children's Environmental Health and Disease Prevention Research. Environ Health Perspect. 2005;113(10):1414-1418.
10. Fenske RA, Bradman A, Whyatt RM, et al. Lessons learned for the assessment of children's pesticide exposure: critical sampling and analytical issues for future studies. Environ Health Perpect. 2005;113(10):1455-1462.
11. Gilliland F, Avol E, Kinney P, et al. Air pollution exposure assessment for epidemiologic studies of pregnant women and children: lessons learned from the Centers for Children's Environmental Health and Disease Prevention Research. Environ Health Perspect. 2005;113(10):1447-1454.
12. Needham LL, Ozkaynak H, Whyatt RM, et al. Exposure assessment in the National Children's Study: introduction. Environ Health Perspect. 2005;113(10):1076-1082.
13. Cohen Hubal EA, Moya J, Selevan SG. A lifestage approach to assessing children's exposure. Birth Defects Res B Dev Reprod Toxicol. 2008;83(6):522-529.
14. Michael RT, O'Muircheartaigh CA. Design priorities and disciplinary perspectives: the case of the US National Children's Study. J Royal Stat Soc. 2008;A171(part 2): 465-480.
15. Mitchell C, Notterman D, Brooks-Gunn J, et al. Role of mother's genes and environment in postpartum depression. Proc Natl Acad Sci USA. 2011;108(20):8189-8193.
16. Clayton D, McKeigue PM. Epidemiological methods for studying genes and environmental factors in complex diseases. Lancet. 2001;358(9290):1356-1360.
17. Kotelchuk M. Pregnancy Risk Assessment Monitoring System (PRAMS): possible new roles for a national MCH data system. Public Health Rep. 2006;121(1):6-10.
18. Nicholson JM, Rempel LA. Australian and New Zealand birth cohort studies: breadth, quality and contributions. J Paediatr Child Health. 2004;40(3):87-95.
19. Nechuta S, Mudd LM, Biery L, et al. Attitudes of pregnant women towards participation in perinatal epidemiological research. Paediatr Perinat Epidemiol. 2009;23(5):424-430.
20. Belanger KB, Buka S, Cherry DC, et al. Implementing provider-based sampling for the National Children's Study: opportunities and challenges. Paediatr Perinat Epidemiol. In press.
21. UK Biobank. Protocol for a Large-Scale Prospective Epidemiological Resource. Stockport, UK; March 2007. (http://www.ukbiobank.ac.uk/wp-content/ uploads/2011/11/UK-Biobank-Protocol.pdf?phpMyAdmin=trmKQlYdjjnQIgJ %2CfAzikMhEnx6). (Accessed March 21, 2012).
22. Israel BA, Parker EA, Rowe Z, et al. Community-based participatory research: lessons learned from the Centers for Children's Environmental Health and Disease Prevention Research. Environ Health Perspect. 2005;113(10): 1463-1471.
23. Eskenazi B, Gladstone EA, Berkowitz GS, et al. Methodologic and logistic issues in conducting longitudinal birth cohort studies: lessons learned from the Centers for Children's Environmental Health and Disease Prevention Research. Environ Health Perspect. 2005;113(10): 1419-1429.
24. RTI International. Final Report and White Paper: Assessment of Existing Linkages with Local Communities among Potential Research Sites for the National Children's Study. Rockville, MD: RTI International; 2004.
25. Brugge D, Missaghian M. Protecting the Navajo people through tribal regulation of research. Sci Eng Ethics. 2006;12(3):491-507.
26. McCally M, Cassel C, Kimball DG. U.S. governmentsponsored radiation research on humans 1945-1975. Med Glob Surviv. 1994;1(1):4-16.
27. Shavers-Hornaday VL, Lynch CF, Burmeister LF, et al. Why are African Americans under-represented in medical research studies? Impediments to participation. Ethn Health. 1997;2(1-2):31-45.
28. Freimuth VS, Quinn SC, Thomas SB, et al. African Americans' views on research and the Tuskegee Syphylis Study. Soc Sci Med. 2001;52(5):797-808.
29. Petersen A. Securing our genetic health: engendering trust in UK Biobank. Sociol Health Illn. 2005;27(2):271-292.
30. Watts G. UK Biobank gets 10% response rate as it starts recruiting volunteers. BMJ. 2007;334(7595):659.
31. Ravdin PM, Cronin KA, Howlader N, et al. The decrease in breast-cancer incidence in 2003 in the United States. N Engl J Med. 2007;356(16):1670-1674.
32. Chlebowski RT, Kuller LH, Prentice RL, et al. Breast cancer after use of estrogen plus progestin in postmenopausal women. N Engl J Med. 2009;360(6):573-587.
33. Taylor HS, Manson JE. Update in hormone therapy use in menopause. J Clin Endocrinol Metab. 2011;96(2): 255-264.
34. Dawber TR, Meadors GF, Moore FE. Epidemiological approaches to heart disease: the Framingham Study. Am J Pub Health. 1951;41(3):279-281.
35. Barbour V. UK Biobank: a project in search of a protocol? Lancet. 2003;361(9370):1734-1738.
36. Watts G. Will UK Biobank pay off? BMJ. 2006;332(7549): 1052.