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Measures of Population Health

Measures of Population Health. CONTEMPORARY METHODS OF MORTALITY ANALYSIS. Lecture 5. Living longer but healthier?. Keeping the sick and frail alive expansion of morbidity (Kramer, 1980).   Delaying onset and progression compression of morbidity (Fries, 1980, 1989).

francis-alvarez
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Measures of Population Health

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  1. Measures of Population Health CONTEMPORARY METHODS OF MORTALITY ANALYSIS Lecture 5

  2. Living longer but healthier? • Keeping the sick and frail alive • expansion of morbidity (Kramer, 1980).   • Delaying onset and progression • compression of morbidity(Fries, 1980, 1989). • Somewhere in between: more disability but less severe • Dynamic equilibrium(Manton, 1982).

  3. WHO model of health transition (1984)

  4. Quality or quantity of life? Health expectancy • partitions years of life at a particular age into years healthy and unhealthy • adds information on quality • is used to: • monitor population health over time • compare countries (EU Healthy Life Years) • compare regions within countries • compare different social groups within a population (education, social class)

  5. What is the best measure? Health Expectancy Healthy LE Disability free LE Disease free LE (self rated health) DFLE DemFLE HLE Cog imp-free LE Active LE (ADL) Many measures of health = many health expectancies!

  6. What is the best measure? • Depends on the question • Need a range of severity • dynamic equilibrium • Performance versus self-report • cultural differences • Cross-national comparability • translation issues

  7. Estimation ofhealth expectancyby Sullivan’s method

  8. Life expectancy 1.0 0.9 0.8 0.7 0.6 0.5 Survival probability 0.4 Life expectancy 0.3 0.2 0.1 0.0 0 10 20 30 40 50 60 70 80 90 100 110 Age

  9. Calculation of health expectancy (Sullivan method) • Lxh = Lx x πx • Where πx - prevalence of healthy individuals at age x • Lxh - person-years of life in healthy state in age interval (x,x+1)

  10. Probability to be in good or excellent health Andreyev et al., Bull.WHO, 2003

  11. Probability to be in good or excellent health Andreyev et al., Bull.WHO, 2003

  12. Choice ofhealth expectancyindicators

  13. Self-rated health Interview question: “How do you rate your present state of health in general?” Answer categories: • Very good • Good • Fair • Poor • Very poor } Dichotomised }

  14. Long-standing illness Interview question: “Do you suffer from any long-standing illness, long-standing after-effect of injury, any handicap, or other long-standing condition?”

  15. Long-lasting restrictions (if “yes” to the following questions) First question: “Within the past 2 weeks, has illness, injury or ailment made it difficult or impossible for you to carry out your usual activities?” Second question: “Have these difficulties/restrictions been of a more chronic nature? By chronic is meant that the difficulties/restrictions have lasted or are expected to last 6 months or more”

  16. What is the best measure? • Depends on the question • Need a range of severity • dynamic equilibrium • Performance versus self-report • cultural differences • Cross-national comparability • translation issues

  17. 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

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

  19. 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

  20. 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

  21. 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?

  22. 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

  23. A 30-40 minute telephone survey A 114 page mail survey Number of respondents: 4,242 Number of respondents: 3,690

  24. 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

  25. 80% Currently Sexually Active With Partner 84% AGE 25-54 (n=1,436) 31% 56% 37% 60% AGE 55-64 (n=414) AGE 65-74 (n=237)

  26. IS SEX IMPORTANT? “How much thought and effort do you put into the sexual aspect of your life?”

  27. CONTROL OVER SEXUAL ASPECT OF LIFE “How would you rate the amount of control you have over the sexual aspect of your life?”

  28. Self-rated Healthby age and sexual activity

  29. Satisfaction with sexual aspect of lifeby age and self-rated health

  30. MIDUS: Sexuality and Lifecourse Health Events • 52.9% actively engaged in a sexual relationship, all with a male partner. • Sexually inactive women report lower sex life satisfaction (2.30 vs 5.70, p<0.0001) • Sexually active women more likely to report good physical health than sexually inactive women (57.3% vs. 42.7%, p<.05).

  31. 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

  32. Bidirectional Relationship ? Health Sexuality Biological / Physiological Mechanisms TIME

  33. 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)

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

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

  36. LE and SALE at Age 30 (MIDUS 1)

  37. Sexually Active Life Expectancy at Age 30 (MIDUS 1)

  38. Percent of Expected Life Without Sexual Activity at Age 30 (MIDUS 1)

  39. Comparison with other surveys • NSHAP - National Social Life, Health, and Aging Project, is an in-home survey of 3,000 persons aged 57 to 84 that collect biomarkers of health and physiological functioning to better characterize the health of survey participants. Rich source of data on sexuality at older ages. • MIDUS-2 – second wave of the MIDUS study conducted in 2004-2006

  40. Introduction to:

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

  42. 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

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

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