Psychology
2011. Vol.2, No.9, 987-991
Copyright © 2011 SciRes. DOI:10.4236/psych.2011.29148
Self-Rated Health and Survival: A Seven-Years Follow-up
Ofra Anson, Jenny Shteingrad, Ester Paran
Faculty of Health Sciences Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Email: ofra@bgu.ac.il
Received July 8th, 2011; revised September 2nd, 2011; accepted October 14th, 2011.
The association between self-rated health and mortality has been well documented, but not completely under-
stood. The purpose of this study was to search for the components of self-rated health among the elderly, draw-
ing on the framework recently proposed by Jylhä (2009) and the degree to which these predict survival. 535
seniors were interviewed, of whom 121 passed away during the seven years that followed. Self-rated health was
significantly related to a variety of health and social indicators, which appeared to be represented by five health
and three social characteristics: chronic conditions, physical functioning, the ability to perform daily activity,
mental health, body pain, economic state, expected future health, and peers’ health. Contrary to Jylhä’s (2009)
suggestion, formal signs of illness and diagnosed life threatening conditions were not related to self-rated health.
Self-rated health was related to mortality along with age, sex, physical and cognitive functioning, and systolic
blood pressure. Only physical functioning predicted both mortality and self-rated health. It appears that self-
rated health is comprised of health information that is not directly related to mortality.
Keywords: Self-Rated Health, Components of Self-Rated Health, Survival, Health Measures
Introduction
Over the past three decades, evidence of the importance of
self-rated health in predicting mortality has been accumulating
(Mossey & Shapiro, 1982; Idler & Benyamini, 1997; Ben-
yamini & Idler, 1999; Jylhä, 2009). In some studies subjective
health evaluation was found as a predictor of mortality even
after clinical, “objective”, medical characteristics were con-
trolled for. Such observations were reported in community
samples (e.g. Farkas, Nabb, Zaletel-Krageli et al., 2009; af
Sillèn, Nilsson, Månsson et al., 2005), as well as among pa-
tients in specific health conditions (e.g. Thong, Kaptein, Ben-
yamini et al., 2008), and, although with differential predictive
value—among men and women (Deeg & Kriegsman, 2003;
Dowd & Zajacova, 2007; Huisman, Van Lenthe, & Macken-
bach, 2007), younger as well as among older individuals (Ben-
yamini, Blumstein, Lusky et al., 2003), persons of advantaged
and disadvantaged social position (Franks, Gold, & Fiscella,
2003; Redigor, Guallar-Castillón, Gutiérez-Fisac et al., 2010).
While the self-rated health—mortality association has been
quite consistently documented in different cultures and social
groops, it is not yet fully understood (Bailis, Segall, & Chipper-
field, 2004; Benjamins, Hummer, Eberstein, & Nam, 2004;
Jylhä, Volpato, & Guralnik, 2006; Jylhä, 2009). Recently, Jylhä
(2009) suggested that in order to understand self-rated health,
the cognitive process by which individuals come to evaluate
their own health has to be understood. She proposed that this
process involves the collection of information, that is, selecting
what is culturally perceived as relevant data, then summarizing,
interpreting and weighing it.
According to Jylhä (2009), the information considered rele-
vant to the evaluation of health includes medical diagnosis,
formal signs of health conditions such as prescribed medica-
tions, experienced bodily sensations, health risks such as health
behaviour. These data are evaluated on the bases of past health
and future health expectations, one’s age and the perceived
health of peers.
Past research largely supported the notion that individuals
apply the above information when evaluating their health. Thus,
self-rated health was found to be associated with haemoglobin
levels and white blood cells count (Jilhä, Volpato, & Guralnik,
2006), health problems and limitations of daily functioning
(Murata, Kondo, Tamakosh et al., 2006; Bath, 2003). Health
behaviour, and the possibility of changing current health be-
haviour, were related to self-rated health in a Canadian sample
(Bailis, Seppal, & Chipperfield, 2003). Empirical support to the
role of past health, health expectations and health of peers in
evaluation one’s health can be found in an eight-year follow-up
study in California (Wang & Satariano, 2007).
Huisman & Deeg (2010), however, argued that the cognitive
process of selecting and evaluating health-related information is
unlikely to be a rational, conscious, action of decision making.
Rather, health evaluation is an ongoing process, affected, dis-
torted, and modified by internal and external factors. Indeed,
several studies provided evidence suggesting that mental health,
such as depressive symptoms, moral, and life satisfaction, were
important for the way persons rated their health status (Nunley,
Hall, & Rowles, 2000; Bath, 2003; Murata et al., 2006).
Moreover, perceived social isolation and lack of social sup-
port seemed to lead to poor self-rated health (Bailis et al., 2003;
Murata et al., 2006). Franks et al. (2010) reported that socio-
economic position have also been found to influence the way
individuals rate their own health status, yet with a differential
relationships with survival: self-rated health was a stronger
predictor of mortality among whites and better educated re-
spondents. Similarly, self-rated health differentially predicted
mortality in different age-sex groups (Benyamini et al., 2003;
Franks et al., 2010).
At the same time, all these physical, psychological, social
support, and demographic characteristics were found to be re-
lated to mortality risk in past research (Berkman & Syme, 1979;
Cambois, Robine, & Brouard, 1998; Grémy & Cambois, 2000;
Boyle, Barnes, Buchman et al., 2009). The present study seeks
to add to this body of knowledge by first, test for Jylhä’s (2009)
suggesting regarding the variables related to one’s self-rated
health and second, by exploring which of the variables that
construct self-rated health are independently related to survival.
O. ANSON ET AL.
988
Finally, we shall examine weather self-rated health contributes
to the explanation of seven-years survival among a sample of
elderly men and women after controlling for the variables with
which it is directly related.
Method
The Sample
A sample of 750 elderly, aged 70 to 85 was drawn from three
sources, to cover, as much as possible, the diverse population of
the Beer-Sheva area, a city of about 200,000 in the South of
Israel: members of the General Sick Fund, which covers 81%
of the aged in the region; public sheltered housing (whose two
important admission criteria are independent daily functioning
and the absence of privately owned residence); and day clubs
for the aged. Criteria for inclusion in the study were age and
willingness to participate. Criteria for exclusion were dementia
(known or indicated by preliminary Mini-Mental State Exam
(18, 19) and a severe systemic disease such as actively treated
malignancy, past stroke, cardiovascular conditions (unstable
ischemic heart disease, arrhythmia, clinically significant valvu-
lar disease), liver and renal diseases, and Parkinson’s. These
criteria were used to enable us to explore the research question
net of life threatening conditions.
Of the 750 sampled seniors, 535 (157 men and 378 women)
completed the interview. The major reasons for exclusion were
death, younger or older than the age indicated in the records,
incorrect address, major disease, and inability to complete the
interview. The age and sex distribution of respondents and non-
respondents was similar.
Six years later, a follow-up study was conducted. Using the
ministry of interior population register, 330 survivors were
identified and date of death was recorded for 121 deceased.
Twenty four subjects were lost to follow-up.
The Instrument
A structured questionnaire was constructed, including the
following measures:
1) Socio-demographic characteristics: age, sex, educational
level, subjective measure of economic state, marital status,
country of birth, and age at immigration;
2) Health status: self reported chronic conditions; cardio-
vascular risks; the SF-36 (McHorney, Ware, & Raczek, 1993)
which measures four dimensions of physical health: physical
functioning (PF), limited role performance as a result of physi-
cal health (RP), body pain (BP), general health attitudes (GH);
three dimensions of psychological well being: limited role per-
formance as a result of emotional difficulties (RE), mental
health (MH), vitality (VT), and social functioning (SF). In the
current study, Chronbach’s alpha = 0.94 was observed at base-
line for the whole scale after using standardized items.
3) Health behaviour: respondents were asked whether or not
they kept a certain diet, performed physical activity, and con-
sumed tobacco or alcohol.
4) Cognitive functioning: the Mini-Mental State Examination
was administered (Folstein, Folstein, & McHugh, 1975; Fol-
stein, Antony, & Parhad, 1985).
5) Cardio-vascular risk: blood pressure, overweight, and the
presence of diabetes were used as objective health risk factors.
Procedure
The first contact with the respondent was a short telephone
conversation, performed by trained interviewers. Interviewers
insisted on speaking with the potential participant, and subjects
who were not able to speak on the phone because of chronic
health problem or cognitive status, were excluded from the
study. The purpose and the procedure of the study were then
explained, and respondents were invited to participate. Subjects
willing to participate were briefly interviewed to assess exclu-
sion criteria, and if eligible a time for a home visit was set.
On the average, each interview lasted for 40 minutes. Nurses
and paramedics were specially trained for the study. Interview-
ers presented the purpose of the study and asked the subject to
sign the informed consent form. At both times the study was
approved by the ethics committee.
Data Analysis
Self-rated health was categorized into a dichotomy of “ex-
cellent or good” and “fair or poor”. Bivariate statistics was used
to assess the association between self-rated health and demo-
graphic characteristics, health, cognitive functioning, and health
behaviour. Cox proportional hazards regression was employed
to explore the relationships between these variables and length
of survival.
Results
The mean age at baseline was 76.4 ± 3.6 years (Table 1).
Less than one third of the participants were men, half were
married. Some half had less than high school, and, on the aver-
age, respondents evaluated their economic state as intermediate.
About a half of the sample evaluated their health as excellent
or good. The mean cognitive functioning score was somewhat
below the accepted cut-off point for mild impairment (24). The
distribution of the variables suggested by Jylhä (2009) is pre-
sented in Table 1.
We now turn to explore what are the variables which predict
self rated health. Following the model suggested by Jylhä
(2009), we started by analysing the relevant components of
health (Table 2). With few exceptions, all the variables pro-
posed were related to self-rated health in the expected direction.
Persons evaluating their health more favourably, on the average,
reported fewer chronic conditions, fewer limitation on daily
activity, fewer formal signs of ill-health better cognitive abili-
ties and somewhat better health behaviour. Yet, the exceptions
should be noted. Diagnosed diabetes did not affect self-rated
health, and those with higher blood-pressure perceive their
health to be better. Accepted preferred health behaviour, that is,
watching one’s diet and exercising, were associated with better
self-rated health. However, risky behaviour—being overweight,
the consumption of tobacco and alcohol—did not affect
self-rated health.
In the next stage of the analysis we set out to examine which
of the health variables independently contributes to favourable
self-rated health. The results of logistic regression analysis
showed that just five health variables play a statistically sig-
nificant role in defining one’s health as excellent or good: the
reported number of chronic conditions (ExpB = 0.56, p < 0.001);
physical functioning or disability (ExpB = 0.91, p < 0.001); the
ability to perform daily activity (role performance, ExpB = 1.16,
p < 0.05); good mental health (ExpB = 1.09, p < 0.01); and body
pain (ExpB = 0.87, p < 0.01). Note that none of the formal signs
of illness and risks and strengths had statistically significant
contribution to self-rated health after controlling for these five
variables.
O. ANSON ET AL. 989
Table 1.
Baseline characteristics (percent, means and standard deviatio ns).
Variable Sample Range
Socio-demographic
Age 76.4 (3.6) 70 - 85
Sex (men) 29.2%
Education (highschool or higher) 53.3%
Marital status (married) 46.2%
Economic state 5.5 (1.4) 2 = poor; 8 = good
Health
Self rated heath (good, excellent) 52.1%
compared to others your age (good,
excellent) 59.8%
Number of chronic conditions 1.5 (1.4)
Of these: % with condition
Respiratory 9.4%
Heart 27.0%
CVA 1.9%
Cancer 1.5%
Physical functioning 20.0
(6.1)
2 = disabled;
30 = not disabled
Mental health 21.3 (5.2) 6 = poor; 30 = good
Role performance 9.9 (2.1) 6 = poor; 12 = good
Energy 4.8 (2.6) 2 = low; 12 = high
Pain 7.3 (2.8) 2 = severe; 12 = none
Vitality 7.6 (2.4) 2 = low; 12 = high
Social activity 7.8 (2.3) 2 = low; 10 = active
Health attitudes 17.2 (3.3) 4 = negative;
28 = positive
Medicines taken regularly (% none) 44.5%
Hospitalization past year (% none) 78.0%
Cognitive functioning
MMSE 22.4 (4.3) 0 = poor; 30 = good
Health Behavior
Diet (keeping) 57.4%
Smoking 25.7%
Alcohol (consuming) 7.5%
Physical activity (yes) 31.2%
Cardiovascul ar risk
Diabetes 12.5%
Systolic blood pressure 141.9 (20.6)
Overweight 2.9%
Examining the social characteristics, we observed that the
probability of an excellent or good self-rated health was greater
for men than for women; for the better than for the lesser edu-
cated; for married than for unmarried persons; and for those
who experienced fewer economic strains (Table 3). Moreover,
the ability to be socially active also increased the tendency to
feel healthy. As may have been expected, respondents evalu-
ated their health relative the health of peers and their expecta-
Table 2.
Self-rated health and health characteristics (percents, means, and
standard deviations).
Variable Excellent-good Faire-poor Statistics
Current Health
Number of chronic conditions0.9 (1.0) 2.0 (1.5) t = 10.0***
Physical functioning1 23.3 (5.2) 17.4 (5.5) t = 12.5***
Mental health1 23.4 (4.7) 18.9 (5.1) t = 10.2***
Role performance1 10.9 (1.7) 9.0 (2.2) t = 10.8***
Body sensations
Energy1 5.8 (2.6) 3.9 (2.3) t = 8.7***
Pain1 8.6 (2.5) 6.1 (2.6) t = 10.8***
Vitality1 8.5 (2.0) 6.9 (2.4) t = 8.3***
Formal signs of illness
Medications taken regularly
(1 or more) 46.0% 71.3% χ2 = 33.3***
Hospitalized past year
(1 or more) 16.9% 27.9% χ2 = 8.7**
Respiratory disease (yes) 4.2% 14.3% χ2 = 14.8***
Heart condition (yes) 15.6% 37.4% χ2 = 29.9***
CVA 0.4% 3.4% χ2 = 5.7*
Diabetes (yes) 14.7% 9.7% χ2 = 3.0
Systolic blood pressure 143.8 (21.2) 139.4 (19.7) t = 2.5*
Cognitive functioning
MMSE1 23.3 (4.0) 21.6 (4.4) t = 4.5***
Risks and strengths
Diet (keeping) 64.2% 50.2% χ2 = 10.4**
Smoking (yes) 25.6% 21.7% χ2 = 0.1
Alcohol (consuming) 8.5% 6.5% χ2 = 0.7
Physical activity (yes) 43.3% 20.1% χ2 = 33.1***
Overweight (yes) 3.2% 2.4% χ2 = 0.3
1Higher score indicates better economic state and better health. *p < 0.05; **p <
0.01; ***p < 0.001.
tions for future health.
Nevertheless, the results of logistic regression analysis
showed that only three variables independently contribute to
positive self-rated health: better economic state (ExpB = 1.37, p
< 0.01; positive perception of future health (ExpB = 1.59, p <
0.001); and rating one’s health positively compared to peer1
(ExpB = 12.98, p < 0.001).
To assess the degree to which self-rated health independently
predicted the length of survival during the follow-up period,
stepwise Cox proportional hazard regression was performed.
Variables were entered to the equation in blocks: first health
variables, second than cognitive functioning, risks and strengths,
and last social characteristics. At each stage the variables which
had no statistically significant contribution to the explanation of
survival since baseline were excluded from the equation.
Self-rated health was added to the equation after this procedure.
The final model is presented at Table 4.
Of the health variables, only disability decreased the odds of
1It should be noted that the correlation between self-rated health and com-
paring one’s health with that of peers was r = 0.64.
O. ANSON ET AL.
990
Table 3.
Self-rated health and social characteristics (percents, means, and
standard deviations).
Variable Excellent-good Faire-poor Statistics
Socio-demographic
Age 76.7 (3.7) 76.0 (3.5) t = –2.1
Sex
men 59.0% 41.0%
women 41.7% 58.3%
χ2 = 13.1***
Education
less than highschool 37.7% 62.3%
highschool or higher 53.3% 44.7%
χ2 = 15.7***
Marital status
married 54.1% 45.9%
not married 40.8% 59.2%
χ2 = 9.3**
Economic state1 6.0 (1.3) 5.0 (1.3) t = –9.1***
Social activity1 8.8 (1.7) 6.9 (2.4) t = 10.0***
Future health
Health attitudes1,2 19.8 (2.8) 14.8 (3.1) t = 18.7***
Own health compared
with others
(excellent, good)
73.8% 8.3% χ2 = 208.4***
1Higher score indicates better economic state, social activity, and positive health
attitudes; 2Taken from the SF-36; *p < 0.05; **P < 0.01; ***P < 0.001.
survival. Of the formal signs of illness, blood pressure alone
was associated with shorter survival. Of the social characteris-
tics—older age and being a man increased the risk of dying
during follow-up. Self-rated health had statistically significant
addition to the explanation of mortality. Note that none of the
variables that predicted self-rated health predicted the likeli-
hood to die during the seven years follow-up.
Discussion
In this study we explored part of Marija Jylhä’s (2009) pro-
posed process of health evaluation. Namely, our research ques-
tion focussed on the data which is relevant to self-rated health.
We sought for the health and social variables a sample of eld-
erly individuals took into account when coming to rate their
own health as excellent-good or faire-poor. Second, we exam-
ined which of these information items predicted seven-years
survival among seniors. For this purpose, 535 men and women
70 to 85 years of age were interviewed in 1999-2000, of whom
121 passed away during the seven year follow-up period. Date
of death was taken from the national vital statistics records.
As suggested by Jylhä’s (2009) and documented in previous
reports, a plethora of health indicators were related to self-rated
health: medically diagnosed conditions and formal signs of
illness along with chronic health problems, disability and men-
tal health, cognitive functioning, social involvement and
watching over what one eats. Yet, only few of these had a
unique, independent, contribution to self-rated health. It ap-
peared that all “relevant health information” in Jylhä’s (2009)
terminology, were compressed into five components: the num-
ber of chronic conditions, disability and difficulties in perform-
ing daily roles and tasks, mental health and body pain. Note
Table 4.
Proportional hazzard ratios for seven-year mortality (Cox regressions
coefficients).
Variable B Hazard ratio 95% CI Wald
Health
Physical functioning1 –0.51 0.95 0.92 - 0.9810.54***
Formal signs of disease
Systolic blood pressure 0.01 1.01 1.00 - 1.027.83**
Body sensations ns
Cognitive functioning
MMSE1 –0.040.96 0.93 - 0.996.68**
Risks and strengths ns
Social characteristic
Age 0.08 1.08 1.04 - 1.1313.27***
Sex (men) 0.83 2.23 1.65 - 3.1625.0***
Self evaluation of health
(excellent/good) –0.490.62 0.44 - 0.867.92**
1Higher score indicates better health; *p < 0.05; **p < 0.01; ***p < 0.001.
that none of the formal signs of illness or diagnosed health
conditions were included in the final model. Not only the num-
ber of medications taken regularly and diagnosed health risks,
such as diabetes and hypertension, factors were excluded, but
also what is often considered as life threatening conditions such
as cardio-vascular disease.
We would like to propose that these findings can be ex-
plained in light of Huisman and Deeg’s (2010) criticism on
Jylhä’s model. As mention in the introduction, they argued that
health evaluation is not necessarily a rational, deductive and/or
inductive, cognitive process of collecting and weighing data.
According to them, people rate their health, modify and refine
their evaluation, continuously throughout life, as a result of
internal as well as external experiences. Thus, diagnosed health
problems and other formal signs of ill-health, healthy or risky
behaviour, seem to be less important than the accumulation of
chronic conditions, even if minor and not life threatening, nega-
tive bodily or mental sensations, and the ability or increasing
difficulties in being active according to one’s expectations and
desire.
In accordance with this approach and shown by past research,
social roles and positions, social life and experiences are also
taken into account when evaluating health. Thus, one’s age and
sex, marital status and economic state appeared as relevant to
health evaluation along with social activity, health attitudes and
perceived health of peers. However, multi-variate analysis
showed that of these just three independently construct self-
rated health: economic state, expected future health, and the
perception of the health of peers. Note that age and gender were
not related to self-rated health in the multivariate analysis in
this sample, probably because of the limited age range. More-
over, gender differences, almost universally observed in past
research, fell below the level statistical significance once these
three variables were taken into account. This finding can be the
result of gender gradient mortality which is reflected in the
large proportion of women at this age.
In this sample, as in many others, self-rated health was asso-
ciated with survival net of health and social characteristics.
Advanced age, being a men, higher blood pressure, and poorer
cognitive capability predicted shorter survival, though none of
O. ANSON ET AL. 991
these predicted self-rated health. The only variable which was
independently associated with both self-rated health and the
risk of death physical functioning, or the level of disability.
It is plausible that self-rated health predicts mortality above
and beyond physical (age, sex) and medical statuses (cognitive
functioning and blood pressure) precisely because it is com-
prised of information generally not considered by scientific
medicine. It may reflect one’s feeling if life is worth living,
given one’s ability to conduct the way and the quality of life
he/she would like to have. Looking at one’s social environment
and at peers may bring about the feeling that the time has come
similar to the effect of special days in one’s own life or holi-
days (see for example, Anson & Anson, 2000, 2001). Health
professionals should be aware of the importance of self-rated
health and take it into considerations when making medical
evaluation and treatment plans.
References
Anson, J., & Anson, O. (2000) Thank god it’s Friday: The weekly cycle
of mortality in Israel. Population Research & Policy Review, 19,
143-154. doi:10.1023/A:1006483623664
Anson, J., & Anson, O. (2001) Death rests for a while: Holy-day and
Sabbath effects on Jewish mortality in Israel. Social Science &
Medicine, 52, 83-97. doi:10.1016/S0277-9536(00)00125-8
Bailis, D. S., Segall, A., & Chipperfield, J. G. (2003) Two views on
self-rated general health status. Social Science & Medicine, 56,
203-217. doi:10.1016/S0277-9536(02)00020-5
Bath, P. A. (2003). Differences between men and women in the self-
rated health—M ortality relationships. The Gerontologist, 43, 387-
395. doi:10.1093/geront/43.3.387
Benjamins, M. R., Hummer, R. A., Eberstein, I. M., & Nam, C. B.
(2004) Self-reported health and mortality risk. An analysis of
cause-specific mortality. Social Science & Medicine, 5 9 , 1297-1306.
doi:10.1016/j.socscimed.2003.01.001
Benyamini, Y., Blumstein, T., Lusky, A., & Modan, B. (2003). Gender
differences in the self-rated health—Mortality differences. Is it poor
self-rated health that predicts mortality or excellent self-rated health
that predicts survival. The Gerontologist, 43, 396-405.
doi:10.1093/geront/43.3.396
Benyamini, Y., & Idler, E. L. (1999). Community studies reporting
association between self-rated health and mortality: Additional stud-
ies 1995-1998. Research on Aging, 21, 392-401.
doi:10.1177/0164027599213002
Berkman, L. F., & Syme, S. L. (1979) Social networks, host resistance
and mortality. A nine-year follow-up study. American Journal of
Epidemiology, 109, 186-204.
Boyle, P. A., Barnes, L. L., Buchman, A. S., & Bennett, D. A. (2009).
Purpose in life is associated with mortality among commu-
nity-dwelling old persons. Psychosomatic Medicine , 71, 574-579.
doi:10.1097/PSY.0b013e3181a5a7c0
Cambois, E., Robine, J. M., & Brouard, N. (1999) Life-expectancies
applied to specific statuses. Population, 11, 7-34.
Deeg, D. J. H., & Kriegsman, D. M. W. (2003). Concepts of self-rated
health: Specifyingthe gender difference in mortality risk. Gerontolo-
gist, 43, 376-386. doi:10.1093/geront/43.3.376
Dowd, J. B., & Zajacova, A. (2007). Does the predictive power of
self-rated health forsubsequent mortality risk vary by socioeconomic
status in the US? International Journal of Epidemiology, 36, 1214-
1221. doi:10.1093/ije/dym214
Farkas, J., Nabb, S., Zaletel-Krageli, L., Cleland, J. G., & Lainscak, M.
(2009). Self-rated health and mortality in patients with chronic heart
failure. European Journal of He art Failure, 11, 518-524.
doi:10.1093/eurjhf/hfp038
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-Mental
State: A practical method for grading the cognitive state of patients
for the clinician. Journal of Psychiatric Resea rch, 12, 189-98.
doi:10.1016/0022-3956(75)90026-6
Folstein, M. F., Antony, J. C., Parhad, I. et al. (1985). The meaning of
cognitive impairment in the elderly. Journal of the American Geriat-
ric Society, 33, 228-35.
Franks, P., Gold, M. R., & Fiscella, K. (2003). Sociodemographics,
self-rated health, and mortality in the U.S. Social Science & Medi-
cine, 56, 2505-2014. doi:10.1016/S0277-9536(02)00281-2
Grémy, F., & Cambois, E. (2000) Life expectancy in health: Major
indicators of health in a population. Bulletin de l’Academie Nationale
de Médecine, 184, 621-632.
Huisman, M., & Deeg, D. J. (2010). A commentary on Marija Jylhä’s
“What is self-rated health and why does it predict mortality? Toward
a unified conceptual model.” Social Science & Medicine, 70, 652-
654. doi:10.1016/j.socscimed.2009.11.003
Huisman, M., Van Lenthe, F., & Mackenbach, J. (2007). The predictive
ability of selfassessed health for mortality in different educational
groups. International. Journal of Epidemiology, 36, 1207-1213.
doi:10.1093/ije/dym095
Idler, E., & Benyamini, Y. (1997). Self-rated health and mortality: A
review of twenty-seven community studies. Journal of Health and
Social Behaviour, 38, 21-37. doi:10.2307/2955359
Jylhä, M., Volpato, S., & Guralnik, J. M. (2006) Self-rated health
showed a graded association with frequently used biomarkers in a
large population sample. Journal of Clinical Epidemiology, 59, 465-
471. doi:10.1016/j.jclinepi.2005.12.004
Jylhä, M. (2009). What is self-rated health and why does it predict
mortality? Toward a unified conceptual model. Social Science &
Medicine, 69, 307-316. doi:10.1016/j.socscimed.2009.05.013
Murata, C., Kondo, T., Tamakosh, K., Yastuya, H., & Toyoshima, H.
(2006). Determinants of self-rated health: Could health status explain
the association between self-rated health and mortality? Archives of
Gerontology and Geriatrics, 43, 369-380.
doi:10.1016/j.archger.2006.01.002
McHorney, C. A., Ware, J. E. Jr., & Raczek, A. E. (1993) The MOS
36-Item Short-Form Health Survey (SF-36): II. Psychometric and
clinical tests of validity in measuring physical and mental health
constructs. Medical Ca re , 31, 247-63.
doi:10.1097/00005650-199303000-00006
Mossey, J. M., & Shapiro, E. (1982) Self-rated health: A predictor of
mortality among the elderly. American Journal of Public Health, 72,
800-808. doi:10.2105/AJPH.72.8.800
Nunley, B. L., Hall, L. A., & Rowles, G. D. (2000) Effects of the qual-
ity of dyadic relationships on the psychological well-being of elderly
care-recipients. Journal of Gerontological Nursing, 26, 23-31.
Redigor, E., Guallar-Castillón, P., Gutiérez-Fisac, J. L., Banegas, J. R.,
& Rodrigues-Artalejo, F. (2010). Socioeconomic variation in the
magnitude of the association between self-rated health and mortality.
Annals of Epidemiology, 20, 395-400.
doi:10.1016/j.annepidem.2010.01.007
Thong, M. S., Kaptein, A. A., Benyamini, Y., Krediet, R. T., Boescho-
ten, E. W., & Dekker, F. W. (2008) Association between a self-rated
health question and mortality in young and old dialysis patients: A
cohort study. American Journ a l o f K idney Disease, 52, 1112-117.
doi:10.1053/j.ajkd.2008.04.001
Sillèn, U., Nilsson, J. A., Månsson, N. O., & Nilsson, P. M. (2005)
Self-rated health in relation to age and gender: Influence on mortality
risk in the Malmö Preventive Project. Scandinavian Journal of Pub-
lic Health, 33, 183-189.