Presentation on theme: "Self-Rated Health in Epidemiological Surveys as a Predictor of Disability and Mortality Ellen Idler, PhD Institute for Health, Health Care Policy and Aging."— Presentation transcript:
1Self-Rated Health in Epidemiological Surveys as a Predictor of Disability and Mortality Ellen Idler, PhDInstitute for Health, Health Care Policy and Aging ResearchRutgers University, NJ, USAReadingsIdler EL, Russell LB, Davis D. Survival, functional limitations, and self-rated health in the NHANES I Epidemiologic Follow-up Study, American Journal of Epidemiology 2000;152:874-83Idler EL, Benyamini Y. Self-rated health and mortality: a review of twenty-seven community studies. Journal of Health and Social Behavior 1997; 38:21-37Benyamini Y, Idler EL. Community studies reporting associations between self-rated health and mortality: additional studies, 1995 to Research on Aging 1999;21:
2Ellen L. Idler, Ph.D.Ellen Idler is Professor and Chair of the Department of Sociology, Rutgers University, New Brunswick, NJ, US. She has been interested in self-rated health since graduate school when she read the original Mossey and Shapiro article (AJPH 1982). She has received multiple grants, including a 5-year FIRST Award, from the National Institute on Aging for studies of self-rated health, mortality, and disability. In 1999 she was a visiting professor at the University of Copenhagen, Denmark. Self-ratings of health are an appealing research topic because they support the importance of the lay person’s perspective in health.Links
3Learning objectivesTo understand that self-ratings of health (SRH) have been studied for decadesTo trace the history of the identification of SRH as a predictor of mortalityTo report new findings on SRH as a predictor of both mortality and ADL/IADL disabilityTo suggest new directions for research on the mechanisms through which SRH affects health outcomesThe first learning objective is to show that SRH has long been a focus of interdisciplinary research on social and psychological factors in health. The first study on self-rated health and mortality appeared in 1982, but there were decades of study before that, showing that individuals’ ratings did not always agree with other, more objective sources of information about their health. Since 1982, more than 50 studies from around the world have been published that tested the association between self-rated health and mortality. In the great majority of these studies a significant association emerged, even in multivariate analyses.The new study reported here uses US national data to test the association between self-rated health and two endpoints: mortality and ADL/IADL disability. The finding suggest new directions for future research.
4Self-Ratings of Health (SRH) All in all, would you say your health is…Excellent, Good, Fair, PoorHow would you rate your health at the present time? Excellent, Good, Fair, Poor, BadHow is your health, compared with others your age? Better, Same, WorseHere are only a few of the many ways health surveys ask respondents to rate their health with a single question. Single item global ratings are used in health surveys all over the world, in many languages, to serve as health indicators for the population and to track trends over time. Note that the question concerns the individual’s state of health, not disease or illness. The responses to any of these questions can be called self-ratings of health (SRH).
5Duke Longitudinal Study of Human Aging, 1962 - 1973 Consistent differences between SRH and physician (MD) ratingDifferences tend toward higher SRH than MD ratingHighest SRH (compared to MD rating) among the most elderlySRH appears to predict future MD ratings better than MD ratings predict future SRHThe first systematic studies of self-ratings of health (SRH) in the US were made at Duke University beginning in the 1950s. Healthy elderly volunteers were administered repeated medical examinations, and also rated their own health. Data from the 1960s and 1970s showed some association between SRH and physician’s ratings, but not a perfect correspondence. When there were differences between the ratings, SRH was more often in the direction of better health than the physician’s rating. The older the study subject was, the more likely they were to give an optimistic rating of their health, considering their higher levels of chronic illness and disability. Some of the last studies from this series showed that, over time, the self-ratings were very good predictors of future physicians’ ratings. In fact, they were better at predicting future physician ratings than physician ratings were at predicting future self-ratings.
6Self-Ratings Predict Mortality In 1982 a Canadian study of a large and representative sample of elderly residents of Manitoba found that SRH was among the strongest predictors of mortality over 7 years, second only to age.The analysis adjusted for individual health status obtained from medical records and self-report of conditions.Even after adjustment for covariates, respondents rating their health Poor were 2.9 times as likely to die as those rating their health Excellent.Mossey JM, Shapiro E. Self-rated health: a predictor of mortality among the elderly. American Journal of Public Health 1982;72:This initial study led to many more, with similar results.
7SRH - Mortality Studies since 1982 Over 50 prospective, population-based studies to dateFrom Canada, US, Poland, Israel, England, France, Hong Kong, Sweden, Wales, Netherlands, Australia, Japan, Lithuania, Finland, Denmark, Italy, China, KoreaThese reports are referenced and reviewed in the articles listed in the Readings in the first slide. Papers were selected for the reviews only if:they were in Englishthey were published in peer-reviewed journalsthe sample was a representative one from a population of community-dwelling adultsthe study included adequate measures of physical health status as covariates
8SRH - Mortality Studies since 1982 Sample sizes: N=421 to 7725Follow-up times: 2 to 18 yearsHealth status covariates: MD Exams, Chronic conditions, Symptoms, ADL disability, Medications, Weight, Blood pressureSignificant OR or HR for “Poor” vs. “Excellent” 1.4 to 93.5Early studies tended to use logistic regression methods for binary mortality status at the end of the follow-up period. These models report odds ratios (OR). Most recent studies use more sensitive Cox proportional hazards methods for analysis of time to death. These models report hazard ratios (HR). The method of analysis does not appear to affect the significance of the results.This has become an extremely well-replicated finding in a very short time, considering that the studies are prospective and have quite long follow-up periods. Most or all of the studies would be considered “secondary analysis” of data (the data were collected initially for another purpose). Because self-ratings of health are so commonly used in surveys, there were many available data files with the necessary elements for the analysis, and hence a large number of studies have appeared.
9Survival, Functional Limitations, and Self-Rated Health in the NHANES I Epidemiologic Follow-Up Study, 1992Ellen Idler, Louise Russell, Diane DavisInstitute for Health, Health Policy and Aging ResearchRutgers, The State University of New JerseyAmerican Journal of Epidemiology 2000; 152:874-83The most recent report from our research group advances on previous research by adding a second endpoint (ADL/IADL disability) to the mortality analysis. It also focuses on gender differences in the findings.
10NHANES-I Epidemiologic Follow-Up Study (NHEFS Data) General Medical History Supplement subsample N=6913Complex sample design, weightedAges at baselineFollow-up3.5% of subsample lost to follow-upThe NHEFS is a large sample that was representative of the US at the study’s initiation in Over 14,000 persons participated in different segments of the research. We studied only respondents who gave self-ratings of health at baseline, N= Initial response rates were very high and attrition during the follow-up period was very low. Respondents were re-interviewed in 1982, 1987, and Our analysis takes the sample design and weighting into account.For more reports on the NHANES and NHEFS, go to:
11NHEFS Data N=6641, complete data for mortality analysis Dependent variable: Time-to-death in daysN=4136, complete data for ADL/IADL limitations analysisDependent variable: Scale of 23 ADL/IADLsStanford Health Assessment QuestionnaireCronbach’s alpha = .96 (1982), .92 (1992)Assessed 1982 and 1992 onlyVirtually all known deaths were verified by death certificate. If a participant was lost to follow-up, their case was censored at the last known contact. If a respondent was alive at the 1992 follow-up, their case was censored at the date of interview.The study of ADL/IADL limitations was restricted to respondents interviewed (alive) in 1982 and The dependent variable is a summed scale of 23 Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) items taken from the Stanford Health Assessment Questionnaire. The items are scored from 0 (no difficulty with activity) to 3 (unable to do). The scale has excellent internal consistency at both time points.
12NHEFS data Self-reported data Chronic conditions Symptoms 42 itemsSymptoms22 itemsHealth practices6 itemsObserved dataMD examination17 ICD-8 categoriesClinical measurements4 blood, urine testsblood pressureheight, weightThe NHEFS sets a very high standard for health status measurement in SRH - mortality studies, because it combines standardized MD-administered physical examinations and standard laboratory screening tests for cholesterol, potassium, albumin, hematocrit, blood pressure, and measured height and weight (objective, external indicators of health/disease) with very detailed interviews on medical history, dietary practices and health risk behaviors (self-reports). The primary purpose of the original NHANES was to detect undiagnosed disease in the population, particularly cardiovascular or nutrition-related disease. Self-ratings of health (SRH) were collected as part of the medical history interview -- it was the opening question.
13Mortality Hazard Ratios (p<.05) MalesFemalesAgeOverweightSBP >=160 mmHgHeart attackStrokeProtein, sugar in urineShortness of breathCurrent smokerNo exerciseSelf-rated health (SRH)Excellent .52Very good .56Good .68AgeMD: Circulatory diseaseUnderweightHematocrit >43%SBP = mmHgSBP >= 160 mmHgProtein, sugar in urineCurrent smokerNo exerciseThe above lists show variables significant in Cox regression models after all variables in the previous slide were tested in stages. Analyses accounted for the complex sample design.Nine factors were associated with increased hazard of mortality for women, but self-ratings of health were not included. The factors that predict mortality for women were primarily obtained by physical examination, not self-report.SRH is associated with greater mortality hazard for men. Men with “excellent” health had a hazard of mortality that was 48% less than those who reported “poor” health. Men with “very good” health had a 44% reduced risk, and men with “good” health had a 32% reduced risk compared with “poor”. Other risk factors included both measured and self-reported variables.
14ADL/IADL limitations analysis (p<.05) AgeMD: Circulatory diseaseMD: Musculoskeletal diseaseOverweightArthritisDiabetesHeart attackCoughPain in legsWheezy chestDrinks weekly (-)Self-rated health (SRH)Excellent -8.1***Very good -7.1***Good -8.1***Fair -3.9*AgeBronchitisHeart attackHernia (-)Hives (-)CoughChest painPain in legsSelf-rated health (SRH)Excellent -5.8***Very good -5.7***Good -5.4**Fair -4.1*FemalesMalesWith the second endpoint, 1992 ADL/IADL limitations, we see a different result. “Excellent”, “very good”, “good”, and even “fair” self-ratings of health are associated with fewer ADL/IADL limitations than “poor” ratings, for both men and women. Other factors in the models are associated with greater limitations, unless they have a negative (-) sign. ADL/IADL limitations were not measured at baseline, so we cannot adjust for limitations at the beginning of the study. However, this scale was administered in 1982, midway through the follow-up period. When we add 1982 ADL/IADL limitations as a covariate, the effect of SRH on 1992 ALD/IADL limitations remains significant for men, but is eliminated for women.
15Conclusions Data quality Multiple endpoints for analysis includes both self-report and MD examunlikely to be surpassed in US studies in futureMultiple endpoints for analysisMortality - includes entire sampleADL/IADL limitations - discriminates among survivorsGender differencesimplications for future researchThis study extends the findings on SRH in the NHEFS and other studies in several ways. In a previous report, we found SRH associated with mortality to 1982 among men, but not among women, after health status was adjusted.Idler EL, Angel RJ. Self-rated health and mortality in the NHANES-I Epidemiologic Follow-Up Study. American Journal of Public Health 1990;80:This study extends the follow-up period by 10 years, adds a large number of additional health status covariates including results from a physician’s examination, and analyzes an additional endpoint, ADL/IADL limitations. The use of an endpoint prior to death suggests that SRH has an impact, not only on life expectancy, but also on functional limitations in the period prior to death. The use of additional endpoints is important because it could help us understand the process by which SRH affects health.The findings were weaker for women than they were for men. This pattern has been seen in a number of other studies. We might speculate that women’s excess chronic disease morbidity may lead to higher levels of knowledge and better health status reporting. A new focus on gender differences could also help explain the process by which SRH predicts both mortality and functional limitations.