Bioindicators in the MIDUS national study: Protocol, measures, sample, and comparative context

Journal of Aging and Health

Volumn 22, Issue 8, 2010, Pages 1059-1080

  Dienberg Love, Gayle ^a   Seeman, Teresa E ^b   Weinstein, Maxine ^c   Ryff, Carol D ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c GEORGETOWN UNIVERSITY   (United States)

Author keywords

Bioindicators; Comparative studies; Cross project participation; Response rates

Indexed keywords

BIOLOGICAL MARKER;

ADULT; AGED; AGING; ARTICLE; BLOOD PRESSURE; BONE DENSITY; CHEMISTRY; CLINICAL PROTOCOL; COMPARATIVE STUDY; DIET RESTRICTION; FEMALE; HEALTH CARE QUALITY; HEALTH STATUS; HEALTH SURVEY; HEART RATE; HUMAN; INFORMATION PROCESSING; LONGITUDINAL STUDY; MALE; MIDDLE AGED; PATIENT PARTICIPATION; PHYSIOLOGY; QUESTIONNAIRE; SALIVA; UNITED STATES;

ADULT; AGED; AGED, 80 AND OVER; AGING; BIOLOGICAL MARKERS; BLOOD PRESSURE; BONE DENSITY; CLINICAL PROTOCOLS; DATA COLLECTION; FASTING; FEMALE; HEALTH STATUS; HEALTH SURVEYS; HEART RATE; HUMANS; LONGITUDINAL STUDIES; MALE; MIDDLE AGED; PATIENT PARTICIPATION; PROGRAM EVALUATION; QUESTIONNAIRES; SALIVA; UNITED STATES;

EID: 78649241756     PISSN: 08982643     EISSN: 15526887     Source Type: Journal    
DOI: 10.1177/0898264310374355     Document Type: Article

References (20)

1. Almeida, D.M., McGonagle, K., & King, H. (2009). Assessing daily stress processes in social surveys by combining stressor exposure and salivary cortisol. Biodemography and Social Biology, 55, 220-238.
2. Brim, O.G., Ryff, C.D., & Kessler, R.C. (2004). The MIDUS National Survey: An overview. In O. G. Brim, C. D. Ryff, & R. C. Kessler (Eds.), How healthy are we? A national study of well-being at midlife (pp. 1-36). Chicago: University of Chicago Press.
3. Chang, M., Glei, D., Goldman, N., & Weinstein, M. (2008). The Taiwan biomarker project. In M. Weinstein, J. W. Vaupel, & K. W. Wachter (Eds.), Biosocial surveys (pp. 60-77). Washington, DC: National Academies Press (Committee on Population, Division of Behavioral and Social Sciences and Education).
4. Chicago Core on Biomarkers in Population-Based Aging Research. (n.d. Studies collecting biomarkers in population settings. Retrieved May 30, 2010, from http://biomarkers.uchicago.edu/studiescollectingbiomarkers.htm
5. Christensen, K., Bathum, L., & Christiansen, L. (2008). Biological indicators and genetic information in Danish Twin and Oldest-Old Survey. In M. Weinstein, J. W. Vaupel, & K. W. Wachter (Eds.), Biosocial surveys (pp. 42-59). Washington, DC: National Academies Press (Committee on Population, Division of Behavioral and Social Sciences and Education).
6. Cushman, M., Cornell, E.S., Howard, P.R., Bovill, E.G., & Tracy, R.P. (1995). Laboratory methods and quality assurance in the Cardiovascular Health Study. Clinical Chemistry, 41, 264-270.
7. Harris, J.R., Gruenewald, T.L., & Seeman, T. (2008). An overview of biomarker research from community and population-based studies on aging. In M. Weinstein, J. W. Vaupel, & K. W. Wachter (Eds.), Biosocial surveys (pp. 96-135). Washington, DC: National Academies Press (Committee on Population, Division of Behavioral and Social Sciences and Education).
8. Fried, L.P., Kronmal. R. A., Newman, A.B., Bild, D.E., Mittelmark, M.B., Polak, J.F., Robbins, J.A., and Gardin, J.M. (1998). Risk Factors for 5-Year Mortality in Older Adults: The Cardiovascular Health Study. JAMA, 279, 585-592.
9. Harris, T.B., Launer, L.J., Eiriksdottir, G., Kjartansson, O., Jonsson, P.V., Sigurdsson, G., et al. (2007). Age, Gene/Environment, Susceptibility- Reykjavik Study: Multidisciplinary applied phenomics. American Journal of Epidemiology, 165, 1076-1087.
10. Hofman, A., Grobbee, D.E., De Jong, P.T.V. M., & VanDenOuweland, F.A. (1991). Determinants of disease and disability in the elderly: The Rotterdam Elderly Study. European Journal of Epidemiology, 7, 403-422.
11. Inter-University Consortium for Political and Social Research. (n.d. The National Archive of Computerized Data on Aging. Retrieved May 30, 2010, from http://www.icpsr.umich.edu/icpsrweb/NACDA/
12. Kasper, J.D., Shapiro, S., Guralnik, J.M., Bandeen-Roche, K.J., & Fried, L.P. (1999). Designing a community study of moderately to severely disabled older women: The Womeng's Health and Aging Study. Annals of Epidemiology, 9, 498-507.
13. Marmot, M., & Steptoe, A. (2008). Whitehall II and ELSA: Integrating epidemiological and psychobiological approaches to the assessments of biological indicators. In M. Weinstein, J. W. Vaupel, & K. W. Wachter (Eds.), Biosocial surveys (pp. 15-41). Washington, DC: National Academies Press (Committee on Population, Division of Behavioral and Social Sciences and Education).
14. Midlife in the United States. Retrieved June 28, 2010 from http://www.midus.wisc.edu
15. National Institute on Aging. (n.d. Database of longitudinal studies. Retrieved May 30, 2010, from http://www.nia.nih.gov/ResearchInformation/ ScientificResources/LongitudinalStudies.htm
16. Radler, B.T., & Ryff, C.D. (2010). Who participates? Accounting for longitudinal retention in the MIDUS National Study of Well-being. Journal of Aging and Health, 22, 307-331.
17. Ryff, C.D., & Singer, B. (1998). The contours of positive human health. Psychological Inquiry, 9, 1-28.
18. Singer, B., & Ryff, C.D. (2001). New horizons in health: An integrative approach. Washington, DC: National Academy Press.
19. Tun, P.A., & Lachman, M.E. (2008). Age differences in reaction time and attention in a national telephone sample of adults: Education, sex, and task complexity matter. Developmental Psychology, 44, 1421-1429.
20. Weinstein, M., Vaupel, J. W., & Wachter, K. W. (Eds. (2008). Biosocial surveys. Washington, DC: National Academies Press (Committee on Population, Division of Behavioral and Social Sciences and Education).