Goals of CCBAR: Foster interdisciplinary research community

1. Goals of CCBAR: • Foster interdisciplinary research community • Establish means of exchanging rapidly evolving ideas related to biomarker collection in population-based health research • Translation to clinical, remote, understudied areas

2. Population surveys • Provide more detailed information on specific topics compared to censuses • Cover relatively small proportion of population (usually several thousand) • Population-based survey – random sample of the total population; represents existing groups of population

3. New trends in health surveys • Harmonization of surveys at world scale • Biomarker collection

4. Large-scale study of health and retirement of older americans • Survey of more that 22000 americans older than 55 years every 2 years. Started in 1992

5. HRS-harmonizing studies • UK English Longitudinal Study of Ageing (ELSA) • Study on Health, Ageing and Retirement in Europe (SHARE) • WHO Study on global AGEing and adult health (SAGE) including Russia • Отдельные исследования в Мексике, Китае, Индии, Японии, Корее, Ирландии

6. Introduction to:

7. Public Dataset http://www.icpsr.umich.edu/NACDA/

8. NSHAP Collaborators • Co-Investigators • Linda Waite, PI • Ed Laumann • Wendy Levinson • Martha McClintock • Stacy Tessler Lindau • Colm O’Muircheartaigh • Phil Schumm • NORC Team • Stephen Smith and many others • Collaborators • David Friedman • Thomas Hummel • Jeanne Jordan • Johan Lundstrom • Thomas McDade • Ethics Consultant • John Lantos • Outstanding Research Associates and Staff

9. Affiliated Investigators and Labs

10. Corporate Contributions and Grants

11. Study Timeline • Funding: NIH / October, 2003 • Pretest: September – December, 2004 • Wave I Field Period: June 2005 – March 2006 • Wave I Analysis: Began October, 2006

12. He, W., Sengupta, M., Velkoff, V. A., DeBarros, K. A. (2005). 65+ In the United States: 2005. Current Population Reports: Special Studies, U. S. Census Bureau.

13. NSHAP Design Overview • Interview 3,005 community-residing adults ages 57-85 • Population-based sample, minority over-sampling • 75.5% weighted response rate • 120-minute in-home interview • Questionnaire • Biomarker collection • Leave-behind questionnaire

14. Est. Pop. Distributions (%)

15. Domains of Inquiry • Medical • Physical Health • Medications, vitamins, nutritional supplements • Mental Health • Caregiving • HIV • Women’s Health • Ob/gyn history, care • Hysterectomy, oophorectomy • Vaginitis, STDs • Incontinence • Demographics • Basic Background Information • Marriage • Employment and Finances • Religion • Social • Networks • Social Support • Activities, Engagement • Intimate relationships, sexual partnerships • Physical Contact

16. Self-Report Measures • Demographic Variables: • Age • Race/Ethnicity • Education • Insurance Status

17. Self-Report Measures • Social/Sexuality Variables: • Spousal/other intimate partner status • Cohabitation • Lifetime sex partners • Sex partners in last 12 months • Frequency of sex in last 12 months • Frequency of vaginal intercourse • Condom use

18. Self-Report Measures • Health Measures: • Obstetric/Gynecologic history • Number of pregnancies • Duration since last menstrual period • Hysterectomy • Physical health • Overall health • Co-morbidities • Health behaviors • Tobacco use • Pap smear, pelvic exam history • Cancer

19. NSHAP Biomeasures • Blood: hgb, HgbA1c, CRP, EBV • Saliva: estradiol, testosterone, progesterone, DHEA, cotinine • Vaginal Swabs: BV, yeast, HPV, cytology • Anthropometrics: ht, wt, waist • Physiological: BP, HR and regularity • Sensory: olfaction, taste, vision, touch • Physical: gait, balance

20. NSHAP Biomeasures Cooperation

21. Principles of Minimal Invasiveness • Compelling rationale: high value to individual health, population health or scientific discovery • In-home collection is feasible • Cognitively simple • Can be self-administered or implemented by single data collector during a single visit • Affordable • Low risk to participant and data collector • Low physical and psychological burden • Minimal interference with participant’s daily routine • Logistically simple process for transport from home to laboratory • Validity with acceptable reliability, precision and accuracy Lindau ST and McDade TW. 2006. Minimally-Invasive and Innovative Methods for Biomeasure Collection in Population-Based Research. National Academies and Committee on Population Workshop. Under Review.

22. NSHAP Biomeasures “Laboratory Without Walls” Salimetrics (Saliva Analysis) McClintock Laboratory (Cytology) Jordan Clinical Lab Magee Women’s Hospital (Bacterial, HPV Analysis) McDade Lab Northwestern (Blood Spot Analysis) UC Cytopathology (Cytology)

23. Salivary Biomeasures • Sex hormone assays • Estradiol • Progesterone • DHEA • Testosterone • Cotinine

24. Salivary Sex Hormones (preliminary analysis) Frequency Frequency Frequency log(estradiol) log(testosterone) log(progesterone) Units: pg/ml

25. Salivary Cotinine • Nicotine metabolite • Objective marker of tobacco exposure, including second-hand • Non-invasive collection method (vs. serum cotinine)

26. Distribution of Salivary Cotinine Classification of Smoking Status by Cotinine Level in Females Cut-points based on distribution among smokers .2 Occasional .15 Nonsmoker Passive Regular .1 Fraction 10 ng 15 ng 34 ng 103 ng 344 ng 10% M 30% M M .05 0 -5 0 5 10 log(Cotinine) M = mean cotinine among female who report current smoking Bar on left corresponds to cotinine below level of detection

27. Dried Blood Spots • C-Reactive Protein (CRP) • Epstein-Barr Virus (EBV) Antibody Titers Thanks, Thom and McDade Lab Staff!

28. Challenges for Predicting Mortality

29. Accuracy • Measurement errors (e.g., sex hormones) • Individual variability (e.g., CRP)

30. Different risk factors at different ages Examples: • Cholesterol • Blood pressure

31. Blood Pressure, Lipids and Mortality Risk among older Costa Ricans Source: Rosero-Bixby, Dow, Pop. Health Metrics, 2012

32. More Information on Biomarkers is Available at the CCBAR website http://biomarkers.uchicago.edu/

33. SEX HEALTH Is sex an “integral part” of health at older ages? What is health? Subjective measures Functional measures Biomeasures What aspects of health are most highly associated with sexual function at older ages?

34. National survey conducted in 1994/95 7,189 Americans aged 25-74 core national sample (N=3,485) city oversamples (N=957) Strata: age, self-reported health status Control variables: partner status, partner health, race, education

35. Domains of Inquiry • Social Networks • Physical Health • Sexuality • Personal beliefs • Work and Finances • Children • Marriage • Religion Childhood family background Psychological turning Community involvement Neighborhood Life overall

36. MIDUS study

37. SEXUALITY AND HEALTH Self-rated physical health is higher among sexually active women Women with very good and excellent health are more sexually active at all ages Satisfaction with sexual aspect of life is higher among women with very good and excellent health compared to women with poor health

38. How to Compare Sexual Activity Across Populations? We suggest to use a new measure – Sexually Active Life Expectancy (SALE) Calculated using the Sullivan method Based on self-reported prevalence of having sex over the last 6 months (MIDUS and NSHAP studies) Life tables for the U.S. population in 1995 and 2003 (from Human Mortality Database)

39. Prevalence of Sexual Activity by Age and Gender (MIDUS 1)

40. Prevalence of Sexual Activity by Age and Gender (MIDUS 1)Men and women having intimate partner

41. Publication on sexuality Lindau, Gavrilova, British Medical Journal, 2010, 340, c810

42. Life expectancy and sexually active life expectancy (SALE) Based on the MIDUS study

43. Sexually active life expectancy and self-rated health Based on the MIDUS study