Yael Benyamini

Community Studies Reporting Association between Self-Rated Health and Mortality Additional Studies, 1995 to 1998

The following table amends and updates the summary table of mortality studies published in 1997 (Idler and Benyamini 1997). To locate additional studies, we searched Medline using the terms self-rated health, self-rating/s of health, self-assessment/s of health, self-assessed health, self-evaluated health, perception/s of health, perceived health, self-evaluation/s of health, subjective assessment/s of health, subjective health, selfreported health, and self-reports of health and crossed these terms with mortality, survival, and deaths. Additional studies not reporting these terms in their abstracts were identified through careful monitoring of the literature. Articles identified with this process were eliminated if they were not in English, if the study population was not a representative community sample, or if the estimate of the effect of self-rated health on mortality was not adjusted for a set of health status covariates. With these restrictions, we identified 19 additional studies for the period 1995 to 1998. The studies in Table 1 are presented chronologically. They report secondary analyses of large data sets, use increasingly sophisticated statistical methods, and adjust for comprehensive sets of health status covariates. The association of poor self-ratings of health with higher risk of mortality is consistent; in just 2 of the 19 studies there were no effects of self-rated health for either men or women. In most of its content, the table presented here is like the 1997 table. The data sources are international, 15 of the 19 have elderly samples, and the health status covariates almost always include activities of daily living

Gender differences in processing information for making self-assessments of health.

Objective This study proposes that women’s greater inclusiveness of various sources of information when making self-assessed health (SAH) judgments accounts for the finding that SAH is a weaker predictor of mortality in women than in men. Methods Data from a sample of 830 elderly residents of a retirement community and a 5-year mortality follow-up study were used to examine the bases for women’s and men’s reports of negative affect (NA) and judgments of SAH. The degree to which each health-related measure accounts for the SAH-mortality association in each gender group was examined. Results The findings support two possible explanations for the lower accuracy of SAH as a predictor of mortality among women: 1) In both men and women, NA is associated with poorer SAH, but in men, NA is more closely linked to serious disease in conjunction with other negative life events, whereas in women, NA reflects a wider range of factors not specific to serious disease. 2) Men’s SAH judgments reflect mainly serious, life-threatening disease (eg, heart disease), whereas women’s SAH judgments reflect both life-threatening and non–life-threatening disease (eg, joint diseases). Conclusions Women’s SAH judgments and NAs are based on a wider range of health-related and non–health-related factors than are men’s. This difference can explain gender differences in the accuracy of SAH judgments and may be related to other documented differences in women’s physical and mental health and illness behavior. The findings emphasize the need to study the bases of NA and other self-evaluations separately for women and men.

Self-Assessments of Health: What Do People Know that Predicts their Mortality?

Factors reflecting current experience—for example, number of medications used, poor function, negative affects, and positive affect—had stronger associations with self-assessments of health (SAH) than factors related to prior events (medical history, prior smoking) in baseline data from 830 elderly retirement-community residents (mean age = 73). Participants appear to have implicit knowledge of the factors affecting their SAH: The rank order of the beta weights relating factors to SAH was correlated with the rank order of participant ratings of the attention given to each factor when making SAH judgments. Relationships of SAH and each of the factors to five year mortality showed that subjectively salient factors such as function and lack of energy predicted five-year mortality, reduced the relationship of SAH to mortality, and accounted for most of the relationship of medical factors to mortality. Affective variables, however, had no relationship to mortality despite their impact on SAH.

Elderly people's ratings of the importance of health-related factors to their self-assessments of health

Identifying the bases for self-assessed health (SAH) has interested researchers in their attempts to understand its validity as a predictor of future health outcomes. Quantitative approaches typically used statistical methods to identify correlates of SAH while qualitative approaches asked people to elaborate on the reasons underlying their rating of health. The current study used a quantitative methodology, asking 487 elderly people to rate the importance of 42 health-related factors as bases for their SAH judgment. Factors indicating overall functioning/vitality were rated highly by all participants. Factors indicating current disease were rated highly by people reporting poor/fair SAH while risk factors and positive indicators were rated highly by those reporting good, very good, or excellent health. Thus, there seems to be a clear distinction between poor and fair SAH that reflect levels of illness, and higher levels of SAH that reflect levels of health.

Why does self-rated health predict mortality? An update on current knowledge and a research agenda for psychologists

‘How in general would you rate your health – poor, fair, good, very good or excellent?’ This simple question is typically labelled self-rated health (SRH) and is also known as self-assessed health, self-evaluated health, subjective health or perceived health. The large number of studies using this item is in stark contrast to its brevity and simplicity. Its value as a predictor of mortality and other health outcomes makes this paradox even more intriguing, especially since in most of the studies SRH retained an independent effect even after controlling for a wide variety of health-related measures that cover medical, physical, cognitive, emotional and social status (see reviews by Benyamini & Idler, 1999; Idler & Benyamini, 1997). Why does SRH predict future health outcomes? Many studies use the repeatedly documented findings of the predictive validity of SRH as sufficient justification to include it as their sole measure of health, i.e. as a ‘proxy’ for more extensive measurements of health. These studies usually lack more detailed health and psychological measurements and therefore do not get us any closer to answering this question. Moreover, though SRH is correlated with many measures of health that are considered to be more ‘objective’, research based on the Congruence Framework shows that the more interesting case is when subjective and objective health differ, as this in itself contributes to the prediction of mortality (Ruthig, Chipperfield, & Payne, 2011). Studies that can potentially shed light on the mechanisms underlying the unique predictive value of SRH include this item along with other measures. Most of these studies have been carried out by sociologists and epidemiologists. The SRH question is often used as an opening line in health surveys so many large-scale studies collected responses to this item along with many other characteristics of their participants. The advantages of these studies are the extensive measurement, based on large representative samples, often at multiple time points. Yet these studies often lack psychological measures and are therefore limited in their ability to provide new insights on the mechanisms underlying possible answers to the following questions: (1) Why is SRH a valid independent predictor of future health? (2) What are the limits to its validity? (Benyamini, Blumstein, Murad, & Lerner-Geva, 2011). The dearth of psychological research in this area is surprising: ‘Self’, ‘Rating’ or ‘Assessment’, and ‘Health’ are all concepts of great interest to psychologists in general and to health psychologists in particular. Yet, only in recent years, studies on the nature of SRH have slowly begun to appear in journals in the health psychology area. The purpose of this editorial is to briefly lay out four explanations for the predictive value of SRH along with a short update of the state-of-the-art of

Smoking status and long-term survival after first acute myocardial infarction a population-based cohort study.

OBJECTIVES We compared long-term survival after acute myocardial infarction (AMI) of never-smokers, pre-AMI quitters, post-AMI quitters, and persistent smokers and assessed whether cigarette reduction among persistent smokers is associated with lower mortality. BACKGROUND Quitting smoking has been shown to improve outcome after AMI. However, longitudinal cohort data with repeated assessments of smoking and information on multiple confounders are lacking. Moreover, little is known about the importance, if any, of reductions in the amount smoked. METHODS Consecutive patients < or = 65 years of age, discharged from 8 hospitals in central Israel after first AMI in 1992 to 1993, were followed through 2005. Extensive data, including self-reported smoking habits, were obtained at baseline and 4 times during follow-up. Cox proportional hazards regressions were used to assess the hazard ratios (HRs) for death associated with smoking categories modeled as time-dependent variables. RESULTS At baseline, smokers were younger, more likely to be male, and had a lower prevalence of hypertension and diabetes than nonsmokers. Over a median follow-up of 13.2 years, 427 deaths occurred in 1,521 patients. The multivariable-adjusted HRs for mortality were 0.57 (95% confidence interval [CI]: 0.43 to 0.76) for never-smokers, 0.50 (95% CI: 0.36 to 0.68) for pre-AMI quitters, and 0.63 (95% CI: 0.48 to 0.82) for post-AMI quitters, compared with persistent smokers. Among persistent smokers, upon multivariable adjustment including pre-AMI intensity, each reduction of 5 cigarettes smoked daily after AMI was associated with an 18% decline in mortality risk (p < 0.001). CONCLUSIONS Smoking cessation either before or after AMI is associated with improved survival. Among persistent smokers, reducing intensity after AMI appears to be beneficial.

Association between a self-rated health question and mortality in young and old dialysis patients: a cohort study

BACKGROUND Self-rated health (SRH) has been shown to predict mortality in large community-based studies; however, large clinical-based studies of this topic are rare. We assessed whether an SRH item predicts mortality in a large sample of incident dialysis patients beyond sociodemographic, disease, and clinical measures and possible age interaction. STUDY DESIGN Prospective cohort study. SETTING & PARTICIPANTS 1,443 predominantly white patients from 38 dialysis centers in The Netherlands participating in the Netherlands Cooperative Study on the Adequacy of Dialysis-2 between 1997 and 2004. PREDICTOR SRH score completed at 3 months after the start of dialysis therapy (baseline). OUTCOMES & MEASUREMENTS Cox proportional hazards model estimated the association between SRH and all-cause mortality. Interaction of SRH with age (<65 and >/=65 years) was examined in an additive model. RESULTS Mean age of patients was 59.6 +/- 14.8 years, with 61% men and 69% married/living together. Mean follow-up was 2.7 +/- 1.8 years. Deaths per SRH group in the multivariate analyses sample: excellent/very good (9 of 63 patients; 14.3%), good (148 of 473 patients; 31.3%), fair (194 of 508 patients; 38.2%), and poor (45 of 71 patients; 63.4%). Patients with poor, fair, or good health ratings had a greater mortality risk than those with excellent/very good health ratings (adjusted hazard ratio [HR(adj)], 3.56; 95% confidence interval [CI], 1.71 to 7.42; HR(adj), 2.09; 95% CI, 1.06 to 4.12; HR(adj), 1.87; 95% CI, 0.95 to 3.70, respectively) independent of a range of risk factors. No age interaction with SRH was found. LIMITATIONS Although the SRH-mortality association remained strong despite extensive adjustments, unknown residual confounding could still exist. CONCLUSION SRH is an independent predictor of mortality in incident dialysis patients. Patients with poor SRH in both age strata had a significantly increased risk of mortality even after controlling for demographic and clinical confounders. Patient self-assessment of health can be an invaluable and economical complement to clinical measures in risk assessment.

Illness Causal Attributions: An Exploratory Study of Their Structure and Associations with Other Illness Cognitions and Perceptions of Control

Two studies were conducted to investigate the cognitive organization and psychological meaning of illness causes. Using a direct similarity judgment method (Study 1), illness causes were found cognitively organized in a hierarchical configuration that could meaningfully be represented as a tree with three main branches—environmental, behavioral, and hidden causes—that further divided into subcategories. This classification of illness causes was associated with other components of the illness schema, namely, the consequences and control/cure dimensions, but not with timeline perceptions (Study 2). Perceptions of control were significantly associated with the cognitive organization of illness causal attributions. Personal relevancy was found as a moderator of illness causal attributions, influencing the relationships between attributions and other illness cognitions.

Neighborhood Socioeconomic Context and Long-Term Survival After Myocardial Infarction

Background— Neighborhood of residence has been suggested to affect cardiovascular risk above and beyond personal socioeconomic status (SES). However, such data are currently lacking for patients with myocardial infarction (MI). We examined all-cause and cardiac mortality according to neighborhood SES in a cohort of MI patients. Methods and Results— Consecutive patients ≤65 years of age discharged from 8 hospitals in central Israel after incident MI in 1992 to 1993 were followed up through 2005. Individual data were obtained at study entry, including education, income, and employment. Neighborhood SES was estimated through a composite census-derived index developed by the Israel Central Bureau of Statistics. During follow-up, 326 deaths occurred in 1179 patients. Patients residing in disadvantaged neighborhoods had higher mortality rates, with 13-year survival estimates of 61%, 74%, and 82% in increasing tertiles (Ptrend<0.001). After adjustment for sociodemographic variables, traditional risk factors, MI severity indexes, and individual SES measures, the hazard ratios for death associated with neighborhood SES were 1.47 (95% confidence interval, 1.05 to 2.06) in the lower and 1.19 (95% confidence interval, 0.86 to 1.63) in the middle tertiles compared with the upper tertile (Ptrend=0.02). The respective hazard ratios were even stronger for cardiac death (1.63; 95% confidence interval, 1.09 to 2.25; and 1.41; 95% confidence interval, 0.96 to 2.07). In the final models, neighborhood context and several individual SES measures were concurrently associated with all-cause and cardiac mortality. Conclusions— Neighborhood SES is strongly associated with long-term survival after MI. The association is partly, but not entirely, attributable to individual SES and clinical characteristics. These data support a multidimensional relationship between SES and MI outcome.

The Relationship of Activity Restriction and Replacement With Depressive Symptoms Among Older Adults.

Activity restriction is known to mediate the disease-depression relationship. Data from 423 older Israeli adults showed that having to give up activities because of failing health was related to more depressive symptoms (DS), whereas satisfactorily replacing these activities was related to DS levels comparable to those of healthier older adults. Giving up and replacing activities mediated, in part, the effect of functional limitations on DS, after controlling for health status, demographics, and resources. Such questions about activities given up and replaced could contribute to the means of assessing the extent and impact of functional limitations on older adults.