1. NORC at The University of Chicago
Sex, health, and years of sexually active life gained due to good health
Natalia S. Gavrilova
NORC at The University of Chicago
Chicago, USA
Although scientific discovery has had a major impact on disease, illness, and disability at older ages, much less is known about health in later life. Women outnumber men in the older population, yet broad scale gerontological survey research is heavily male-centered. The National Social Life Health and Aging Project was designed by an interdisciplinary team of biomedical and social science researchers to understand the mechanisms through which social life and relationships influence health, in addition to illness, at older ages. Because the study was designed to explore sexuality at older ages, and in reflection of the diverse disciplinary orientations of the researchers, data on many previously untouched issues pertinent to older women's health have been collected. 1

2. 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?
SEX HEALTH

3. Introduction to:
NSHAP

4. NSHAP Design Overview
Wave 1: In interview 3,005 community-residing adults ages
Population-based sample, minority over-sampling
75.5% weighted response rate
120-minute in-home interview
Questionnaire
Biomarker collection
Leave-behind questionnaire
The NSHAP study interviewed 3005 community-residing adults ages between July 2005 and March This involved a population-based sample with oversampling of Black and Hispanic individuals. The study included a 120 minute in- home face-to-face questionnaire conducted in English and Spanish and collection of 17 different biological measures.
In addition, a s questionnaire was left behind for self-completion. 4

5. Domains of Inquiry Demographics Social Medical Women’s Health
Basic Background Information
Marriage
Employment and Finances
Religion
Social
Networks
Social Support
Activities, Engagement
Intimate relationships, sexual partnerships
Physical Contact
Medical
Physical Health
Medications, vitamins, nutritional supplements
Mental Health
Caregiving
HIV
Women’s Health
Ob/gyn history, care
Hysterectomy, oophorectomy
Vaginitis, STDs
Incontinence
Because this data set will become available for public use in 2008, and many of you share my interest in studying issues of aging, let me briefly tell you about the spectrum of data we collected. Here, you see listed all of the interview domains. 5

6. NSHAP Biomeasures Cooperation
This slide summarizes the measures we collected. As you can see, cooperation rates were excellent, exceeding 90% for almost all. Among the more demanding measures, including saliva collection, HIV testing, fingerstick blood samples, and vaginal self- swabs, cooperation rates were also very high. 6

7. NSHAP Biomeasures Salimetrics McClintock Laboratory (Saliva) Analysis)
“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)

8. Salivary Biomeasures Sex hormone assays Cotinine Estradiol
Progesterone
DHEA
Testosterone
Cotinine
Saliva collection involved production of approximately 2 milliliters of saliva into a small, code-labeled polystyrene collection vial via a 5-centimeter section of a household plastic straw. The salivary specimens were stored on ice and transported on cold packs to Salimetrics, LLC (State College, PA). After transport, specimens were stored at -40°C, thawed for testing, and centrifuged. An appropriate volume of clear sample was pipetted and quantitatively analyzed for the presence of cotinine using the High Sensitivity Salivary Cotinine Enzyme Immunoassay Kit according to manufacturer’s instructions. 8

9. 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

10. 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
Because this data set will become available for public use in 2008, I list here all of the domains of inquiry.

11. MIDUS study

12. 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 and 2003 (from Human Mortality Database)

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

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

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

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

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

18. Is Sex an Important Predictor of Mortality?
Wave 2 of NSHAP is able to answer this question.
In 2010 and 2011, nearly 3,400 interviews were completed for Wave 2 with Wave 1 Respondents, Wave 1 Non-Interviewed Respondents, and their spouses or cohabiting romantic partners.
NSHAP study collected information on the number of deaths between two waves.

19. Sexual inactivity and 5-year mortality NSHAP data. Men
Multivariate logistic regression, N=2672
Variable
Odds ratio
95% CI
P-value
No sexual activity past 12 months
2.41
<0.001
Age
1.07
Living with partner
0.64
0.062
Smoking
1.49
0.090
Poor/Fair SRH
1.80
0.011
College or higher education
0.79
0.248 19

20. Sexual inactivity and 5-year mortality NSHAP data. Women
Multivariate logistic regression, N=2498
Variable
Odds ratio
95% CI
P-value
No sexual activity past 12 months
0.97
0.933
Age
1.10
<0.001
Living with partner
0.84
0.535
Smoking
4.57
Poor/Fair SRH
2.45
0.001
College or higher education
0.60
0.051 20

21. Results were not changed if we used “interest in sex” variable (thinking about sex once a week or more often) instead of sexual inactivity

22. Biomarkers tested as mortality predictors
C-reactive protein (CRP)
DHEA
Testosterone (T)
Estradiol (E2)
Glycated hemoglobin (HbA1C)
Note: HbA1C turned out to be non-significant predictor of mortality

23. Selected biomarkers and 5-year mortality NSHAP data. Men
Multivariate logistic regression, N=2287
Variable
Odds ratio
95% CI
P-value
CRP (log)
1.51
0.003
DHEA (log)
0.85
0.294
Testosterone (log)
1.64
0.069
Estradiol (log)
1.00
0.976
Sexual inactivity
2.14
0.004
Controlled for age and smoking status 23

24. Selected biomarkers and 5-year mortality NSHAP data. Women
Multivariate logistic regression, N=2117
Variable
Odds ratio
95% CI
P-value
CRP (log)
0.93
0.688
DHEA (log)
0.70
0.057
Testosterone (log)
0.71
0.430
Estradiol (log)
1.58
0.006
Sexual inactivity
1.63
0.333
Controlled for age and smoking status 24

25. More Information on Biomarkers is Available at the CCBAR website
Acknowledgements
This study was supported by NIH grants.
Study on SALE has been jointly conducted with Dr. Stacy Lindau, MD, MAPP at the ObGyn Dept., University of Chicago