Philip Morris
Self-Regulation and Mortality From Cancer, Coronary Heart Disease, and Other Causes: A Prospective Study
Fields
- Author
- Eysenck, H.J.
- Grossarthmaticek, R.
- Type
- PSCI, PUBLICATION SCIENTIFIC
- BIBL, BIBLIOGRAPHY
- Author (Organization)
- Elsevier Science
- Pergamon
- Person Individ Diff
- Un, United Nations
- Univ for Peace
- Univ of London
- Master ID
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DR. C.R.E. COGGINS
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SELF-REGULATION AND MORTALITY FROM CANCER,
CORONARY HEART DISEASE, AND OTHER CAUSES: A
PROSPECTIVE STUDY
R. Grossarth-MaticekI and H. J. Eysenck2
1University for Peace, United Nations and 2Department of Psychology, Institute of Psychiatry,
University of London, De Crespigny Park, Denmark Hill, London SE5 8A5, England
(Received 3 July 1995)
SummaryDThis article introduces a new personality inventory dealing with self-regulation. This is in
some
ways the opposite of neuroticism, and measures personal autonomy or independence, particularly as
far as
emotional dependence is concerned. Our concern was the relation between self-regulation and health,
and
large samples of healthy men and women were tested and followed up to demonstrate high
predictability
of mortality from cancer, coronary heart disease and other causes of death from scores on the
questionnaire.
It was also demonstrated that psychological risk factors were largely independent from physical risk
factors,
and could bc changed by behavioural--cognitive treatment, reducing mortality.
INTRODUCTION
The ancients had a motto for happiness: Mens sana in corpore sano. They believed, following
Hippocrates, that the sound mind was related to the sound body, and that there were cancer-prone
personalities predisposed to develop this disease more readily, and die of it more quickly, than
others
not so prone (Mettler & Mettler, 1947; Kowal, 1955; Greer, 1983; Rosch, 1979, 1980). In recent
years,
many studies have given support to the idea of a cancer-prone personality (Eysenck, 1991, 1994a;
Temoshok & Dreher, 1992), as well as a coronary heart disease-prone personality (Friedman, 1991;
.~ohnson, 1990; Turner, Sherwood & Light, 1992). The latter is often referred to as Type A,
contrasted
with the healthy Type B (Eysenck, 1990); the cancer-prone type is sometimes referred to as Type C.
Disease-prone types share certain similarities, but can be differentiated successfully both
experimentally (Kneier & Temoshok, 1984) and by interview/questionnaire (Eysenck, 1988).
While most interest has been directed towards Types A and C, there has also been some interest
in the study of the healthy type of person, Type B (Friedman & Rosenman, 1974) or Type 4
(Grossarth-Maticek, Eysenck & Vetter, 1988). This may be defined negatively in terms of the absence
of traits characteristic of cancer-prone and CHD-prone personalities, or positively in terms of
active
health-promoting traits. The difference is of course of little practical importance; a given trait
may
be formulated positively, or negatively, and scored in the health-giving or disease-prone direction.
Table 1 shows some of the concepts related to the disease-prone and the healthy personality
(Friedman
& Booth-Kewley, 1987), respectively. Obviously these varied conceptions have a great deal in
common, and the present study reports an attempt to bring this consensus to a focus, and demonstrate
its relevance to actual physical health. What seemed to us to be the defining feature of the healthy
personality was autonomy, emotional independence, and self-regulation, i.e. the ability to actively
regulate one' s own life, without a degree of emotional dependence on other people that acted in
such
a way as to thwart one's needs and aims. The concept of 'locus of control' has some similarity to
self-regulation, but is rather narrower in its meaning. Both are clearly related to low neuroticism
(Eysenck, 1994a).
The term 'self-regulation' has been used in the past with similar but somewhat differing meaning
(Schwartz, 1983; Leventhal, Nerenz & Strauss, 1980; Carver & Scheier, 1982) as an aspect of control
theory. These authors review self-regulation in terms of coping with symptoms or medical treatments
781

Self-regulation and mortality
Table 2. Personality and other correlate~ of the six Grossarth-Maticek types (Schmitz. 1992.
1993)
Types 1 2 3
4 5 6
N +++ +++ ++
+ +++
E .... ++ - +
P ~ + =, -- _-- ++
L = = -, = + -
Autonomic anxiety + + + =* - +
:=
Cognitive anxiety + + + + + - - +
+ +
State anxiety + + + + -- - - + +
Dogmatism + + + + + + + - - + + +
Alienation + + + + + +'+ - + + +
Can't describe feelings + + + + + + ,,~ - - =
+
Can't communicate feelings + + + + + - +
+ +
Alexithymia + + = = - + =
Task-oriented ,= - = + + + -
Emotion-oriented + + + + + + + + - - =
+ +
Coping
Avoidance-oriented + + + + +
= = =
Distraction + + + + + + = = =
Social diversion = = + = =
=
Psychosomatic complaints
Physical exhaustion + + + + 4- - -
+ +
Insom~tia + + + - - + + + + +
Cardiovascular problems + + + + + - + +
+ +
Depressive tendencies + + + + + + + -- - + +
+ + +
Impulsiveness + + + + + + - - = +
+ +
Abuse of drugs
Psychopath. +. + + =
- = +
Alcohol + + + + = - + + + + +
Drugs + + + + ffi -- -- = +
Smoking + + + - -- = + +
783
interviewer-administration involving the establishment of trust, and the explanation of obscure or
complex questions, has the greatest validity. The second problem is that response may depend on the
circumstances leading to the establishment of a given sample; a sample consisting of people coming
for psychotherapy is more likely to give truthful answers than a random sample uncertain about the
relevance of the questions asked. These problems are closely linked to the hypothesis that a major
aspect of the cancer-prone personality, for instance, is the suppression of feelings and emotional
responses; such denial may lead to differential responding in different conditions of test
Table 3. Personality of other correlates of the six Grossarth-Maticek types (Sandin et al.,
1993a, b)
Types 1 2 3 4
5 6
Immunological,
Cardiovascular '
Respiratory
Gastrointestinal
Neurology: sensorial
Skin
Musculoskeletal
Genito-urinary
N
p
Alexithymia
Coping
Task-oriented
Emotion-oriented
Avoidance-oriented
Social support
Anger-state
Anger-strait
Angevin
Anger-out
Anger-control
AnSer.~-x

~ett-regulat~on ant1 mortality
Table 2, Personality and other correlates of the six Orossarth-Maticek types (Schmitz, 1992,
1993)
Types ! 2 3 4
5 6
N +++ +++ ++
+ +++
E .... ++
- +
p = + = -
__ ++
I. = -- =, =
4- -
Autonomic anxiety + + +
Cognitive anxiety + + + + +
+ + +
State anxiety + + + + = - -
+ +
Dogmatism + + + + + + + - -
+ + +
Alienation + + + + + + + -
+ + +
Can't describe feelings + + + + + + ....
+
Can't communicate feelings + + + + + -
+ + +
Alexithymia + + =
Task-oriented ffi - ffi + +
+ -
Emotion-oriented + + + + + + + + - -
= + +
Coping
Avoidance-oriented + + + + +
Distraction + + + + + + --
Social diversion = = + =
=
Psychosomatic complaints
Physical exhaustion + + + + ÷ - -
+ +
Insomnia + + + - -
+ + + + +
Cardiovascular problems + + + + + -
+ + + +
Depressive tendencies + + + + + + + - -
+ + + + +
Impulsiveness + + + + + + - -
= + + +
Abuse of drugs
Psychopath. + + + = -
= +
Alcohol + + + + ffi -
+ + + + +
Drugs + + + + ....
+
Smoking + + + - -
= + +
783
interviewer-administration involving the establishment of trust, and the explanation of obscure or
complex questions, has the greatest validity. The second problem is that response may depend on the
circumstances leading to the establishment of a given sample; a sample consisting of people coming
for psychotherapy is more likely to give truthful answers than a random sample uncertain about the
relevance of the questions asked. These problems are closely linked to the hypothesis that a major
aspect of the cancer-prone personality, for instance, is the suppression of feelings and emotional
responses; such denial may lead to differential responding in different conditions of test
Table 3. Personality of other correlates of the six Grossarth-Maticek types (Sandin et al.,
1993a, b)
Types 1 2 3 4 5 6
Immunological + + + - = +
Cardiovascular + + + + + - = +
Respiratory + + + + =~ - = +
Gastrointestinal + + + + - = +
Neurology: sensorial + + + + + + + - - + +
Skin + + + + = = +
Musculoskeletal . + + + + + + - = + .
Genito-urinary + + + + - = +
N ++ ++ ++ - = +
E .... 4- = =
p = ++ - ffi = +
Alexithymia + + .....
Coping
Task-oriented - - - + + = ffi
Emotion-oriented + + + - = + +
Avoidance-oriented + + + + - = +
Social support - - ffi + + ffi =
STAXI
Anger-state = + =, m = +
Anger-strait + + + + + -' = + +
Anger-in + + + + + + = + +
Anger-out =, + + + + = = + +
Anger-control = - - + = --
Anger..ex + + + + + + = ffi +

1~. ~JrossarLil-~la~lcoK an~ t~. J. l~ysencK
administration. Intelligence, too, may play a part; complex questions embodying complicated theories
may not be easily understood by persons with below-average IQs.
If we may take the results of the studies summarized in Tables 2 and 3 as suggesting the nature
of the 'healthy' (Type 4) and 'unhealthy' (Types I and 2) personality, we see that the 'healthy
personality' is low in psychopathology (neuroticism and psychoticism), extraverted, task-oriented
rather than emotion-oriented, and controlled in his anger. We may compare these characteristics with
those noted in an early but still valuable study that played a pioneering role in this field (Hinkle
&
Wolff, 1957). They studied three rather homogeneous groups, composed of over 4000 men and
women, looking at their history of major and minor illnesses, as well as their circumstances,
personalities, and stresses and stress reactions. Their first finding was that the distribution of
illnesses
was not Gaussian, but negative binomial, a sort of distribution that occurs in groups when the
members
of the group have different 'risks' of becoming ill. In other words, people differ in their
predisposition
to become ill. In addition, those so predisposed showed an increased susceptibility to illness in
general;
they developed many different types of minor or major illness, not just one or two. (Number of major
illnesses correlated 0.40 with number of minor illnesses.) There was a clear correlation between
number of illnesses and stress experienced, in terms of objective events like divorces, separations,
conflicts with family members, uncongenial living and working arrangements, etc. Further, clusters
of illness often occurred during periods of significant stress. Constitutional differences
predisposing
to disease have not been found to differentiate the 'healthy' from the 'diseased'. The subjectivity
of
the 'stresses' involved becomes apparent in the conclusion drawn by the authors "that illness often
occurs when a person perceives his life situation as peculiarly threatening to him, even though this
life situation may not appear to be threatening to an outside observer, and that people who maintain
good health in a setting of what are 'objectively' difficult life situations do not usually perceive
these
situations as difficult."
The study closely targeted psychological factors similar to those found in Tables 2 and 3 as
related
to illness predisposition. "Those people who had the greater number of bodily illnesses, regardless
of their nature and regardless of their etiology, were the ones who experienced the greater number
of disturbances of mood, thought, and behaviour. For example, not uncommonly, persons were seen
with recurrent episodes of anxiety, depression, chronic obsessive and compulsive symptoms, or
character disturbances; symptoms of this type, with exacerbations and remissions, might predominate
in their illness pattern throughout life. But such people, as a group, also had more bodily
illnesses
of all types than were found among those who had few or no disturbances of mood, thought, or
behaviour. This can be put in other terms by saying that ... there was a parallelism between the
occurrence of psychoneuroses and psychoses and the occurrence of bodily illness." (p. 446; italics
not in original).
2063633598
THE SELF-REGULATION INVENTORY(SRI)
To investigate the hypothetical relationship between personality and illness, a self-regulation
inventory wasconstructed using questions based on those that had in past research proved useful in
predicting good health or poor health respectively, reversing the scoring for the latter so that a
high
score indicated good health, a low score poor health. Likert-scale scoring on a six-point scale was
used. Scores can vary between 105 and 630. The Cronbach ~ reliability for various groups centred
on 0.80. For purposes of presentation scores were grouped into six groups, from 1 (low
self-regulation)
to 6 (high self-regulation). The six steps are coded in multiples of 105. Thus a score of 1 is
obtained
when the total point score is between 105 and 209; a score of 2 is obtained when the total point
score
is between 210 and 314, etc. The number of men and women with each score is given in Table 4.
A detailed statistical analysis of the questionnaire will be given in a later publication; here we
shall
be concerned with the validity of the questionnaire as regards predictive accuracy of mortality. Ss
were
tested by trained interviewers in 1973, and mortality established in 1988; thus the study reports a
15-year follow-up. Data were collected by 116 trained students in all. Ss were randomly selected on
the basis of lists of inhabitants in Heidelberg, Germany, at the time. (Copies of the questionnaire
can
be obtained from H. J. Eysenck.)
Table 4 shows the degree of self-regulation for the men and women who took part in the study.

Selt~regulauon an~l ~0rtality
Tabl~ 4. Degre~ of self-regulation and mortality in women and men
Group 1 2 3 4 5 6
Total
Women 150 316 535 912 502 193
2608
5.7% 12.1% 20.5% 34.9% 19.2% 7.4%
Men 154 509 1221 813 308 I03 3108
4.9% 16.3% 39.2% 26.1% 9.9% 3.3%
Total 304 825 1756 1725 810 296
5716
5.3% 14.4% 30.7% 30.1% 30.1% 5.1%
785
Table 5. Degree of self-regulation and mortality in women
Group
Score Score Score Score Score Score
1 2 3 4 5 6
150 316 535 912 502 193
N 5.7% 12.1% 20.5% 34.9% 19.2% 7.4%
Cancer 25 43 58 35 15 4
16.6% 13.6% 10.9% 3.8% 2.9% 2.0%
CHD 45 60 96 51 14 5
30.0% 18.9% 17.9% 5.5% 2.7% 2.5%
Other causes 52 79 147 130 37 7
of death 34.6% 25.0% 27.4% 14.2% 7.3% 3.6%
Still alive 28 134 234 696 436 177
18.6% 42.4% 43.7% 76.3% 86.8% 91.7%
Total 122 182 301 216 66 18
mortality 8 ! .3% 57.5% 56.2% 23.6% 13.1% 8.2%
Average age
(1973) 55.7 56.1 57.8 58.3 56.9 58.8
Table 6. Degree of self-regulation and mortality in men
Group
Score Score Score Score Score Score
I 2 3 4 5 6
154 509 1221 813 308 103
N 4.9% 16.3% 39.2% 26.1% " 9.9% 3.3%
Cancer 22 63 126 29 8 2
14.2% 12.3% 10.3% 3.5% 2.5% 1.9%
49 121 251 48 10 2
31.15% 23.7% 20.5% 5.9% 3.5% 1.9%
51 128 349 92 15 5
33.1% 25.1% 28.5% 11.3% 4.8% 4.8%
32 197 495 644 275 94
20.7% 38.7% 40.5% 79.2% 89.3% 91.2%
122 312 726 169 33 9
79.2% 61.2% 59.4% 20.7% 10.7% 8.7%
CHD
O~her causes
of death
Still alive
Total
mortality
Average age
(1973)
57.8 56.5 55.9 57.2 58.9 58.4
It is clear that women are significantly higher on the S-R scale (P < 0.001 by Mann-Whitney U-test).
This agrees well with the universal tendency of women to live longer than men.
Tables 5 and 6 show, separately for women (Table 5) and men (Table 6) the interaction between
degree of self-regulation and mortality from Cancer, CHD, and other causes of death. Also given are
number still living and total mortality, g2 values were calculated for total mortality vs still
living, cancer
vs still living, CHD vs still living, and other causes of death vs still living; all were
significant at
P < 0001 for the sexes separately. Also given are the average ages of the S-R groups. (Ages ranged
from 45 to 68 yr in 1973.) Thus for all causes of death (cancer, CHD, other) there is a very
significant
correlation between S-R and mortality. Figures 1 and 2 show the results diagramatically.
Table 7 shows the relationship between S-R scores and a number of risk factors in a small group
of 571 persons where more detailed investigation was possible. Clearly those low on self-regulation
have higher blood pressure, suffer more from diabetes, are more overweight and lacking in exercise,

786 R. Grossarth-Maticek and H. J. Eysenck
Prospective 1973 - 1988 study: females (N -- 2608)
35 -
• Cancer " /
/
30- . CHD
25- " Other
o 20 --
o 15 -- / /
5 4 3 2 1
High Self regulation Low
Fig. 1. Mo~lity and de~ee of self-~gulafion; 2608 women.
smoke more, drink more, have more accidents, have a poorer diet, are more often ill, spend more time
in hospital, and report more symptoms leading to medical treatment. All these are at high levels of
significance, with P < 0.001.
Table 8 lists smokers in relation to self-regulation for men only. There are two groups, those
still
alive, and those who had died. (There were too few women smokers in 1973 to make results
meaningful.) Among the former, smoking is positively related to higher degrees in self-regulation.
In those who died, smoking was more frequent in those with low self-regulation, and they smoked
Pros ~ective 1973 - 1988 study: males (N = 3108)
35
30
"" 25
o 20
O
0
6
High
5 4 .3 2 I
Self regulation Low
0
O~
o~
O~
O
O
• . Fig. 2. Mortality and degree of self-regulation; 3108 men.

S~lf-regulation and mortality 787
Table 7. Self-regulation as related to various physical risk factors
Type Type Type T);pe Type Type
1 2 3 4 5 6
304 825 175 172 810 296
Blood pressure 168/93 155/90 144/86 135/75 123/71
121/70
Diabetes 39 68 69 11 2 1
12.6% 8.2% 3.9% 0.6% 0.2%
0.3%
Overweight 183 478 80 I" 159 40 13
60.0% 57.9% 45.6% 9.2% 4.9%
4.3%
Lack of exercise 194 536 961 201 62 10
63.8% 64.9% 54.7% 11.6% 7.6%
3.3%
Number of cigarettes smoked
per day
Alcohol consumed daily (g)
Number of accidents per
year treated individ.
(1970-1973)
Poor nutrition
Days ill per year
(1970-1973)
Days in hospital per year
(1970-1973)
Needing medicare care
over 1 yr
Number of symptoms leading
to medical treatment
(1970-1973)
40.2 35.1 30.6 15.1 11.2 7.7
83.6 80.2 64.9 19.8 I 1.6 I0
84 155 167 90 I0 I
27.5% 18.7% 9.5% 5.2% 1.2% 0.3%
265 557 718 401 89 19
87.1% 67.5% 40.9% 23.2% I0.9% 6.4%
64.7 57.2 31.5 16 18 15
22.8 20.6 10.6 4.3 2.5 1.1
71 125 216 99 36 8
23.3% 15.1% 12.3% 5.7% 4.4% 2.7%
14.3 12.8 11.4 4.7 2.3 1.2
more per day. These results for the relation between smoking and self-regulation may at first seem
contradictory, but both are highly significant by X2 (P < 0.001). The results are in good agreement
with previous studies (e.g. Friedman, Firman, Petitti, Siegelaub, Ury & Klatsky, 1983; Howard,
Curmingham & Rechnitzer, 1985) which demonstrated that personality acts as a moderator of the
effects of cigarette smoking on coronary risk, in the sense that smoking was having deleterious
effects
on heal.th only for people with CHD-prone personality, but not on those with psychologically healthy
personalities. Eysenck (1994b) has shown that this effect occurs equally for cancer, and the results
in Table 8 are clearly in line with this general rule.
Data for alcohol consumption are given in Table 9. Among those alive in 1988, the relation
between
drinking and degree of self-regulation is reasonably linear, with low S-R scorers drinking less than
Table 8. Self-regulation ahd smoking--in live and dead pmbands
Type Type Type Type Type Type
I 2 3 4 5 6 Total
154 509 1221 813 308 103 3108
Group 1"
32 197 495 644. 275 94 1737
55.9%
9 57 164 303 108 49 690
28.1% 28.9% 33.1% 47.0% 39.3% 52.1% 39.7%
15.3 15.6 14.7 24.6 21.7 22.0
122 312 726 169 33 8 1370
44.1%
N
Still alive
Smokers (n;%)
Cigarettes per day
Total mortality
No longer living
Smokers (n;%)
Cigarettes per day
Total smokers
Group
122 312 726 169 33 8
91 224 415 89 7 1
74.5% 71.7% 57.1% 40.8% 21.2% 12.5%
26.9% 25.6% 24.3% 23.9% 21.3% 21.3%
100 281 579 372 115 50
64.9% 55.2% 47.4% 45.7% 37.3% 48.5%
*~. (linear) ffi 20.63, d.f. = I, P = 0.0000.
~'~ (linear) = 70.59, d.f. = I, P ffi 0.0000.
1370
44.1%
807
59.0%
1497
48.2;c
0

788
R. Grossarth-Maticck and H. J. Eysenck
Table 9. Self-regulation and drinking---in live and dead probands
Type Type Type Type Type
Type
1 2 3 4 5
6 Total
N 154 509 1221 813 308
• 103 3108
Group !*
Still alive32 197 495 644 275 94 1737
55.9%
Alcohol consumed
(n;%) 4 48 51 353 210
50 718
12.5% 24.3% 10.3% 54.8% 76.3%
53.1% 23.1%
Daily intake (g) 21.6 23.6 39.8 48.7 42.6 44.6
Group llt
No longer living 122 312 726 169 33 8.0
1370
44.1%
Alcohol consumed
(n;%) 85 197 617 17 6
+ I 923
69.6% 63.1% 84.9% 10.0% 18.1%
12.5% 67.3%
Daily intake (g) 75.8 79.4 69.6 28.3 24.2 25.3
Total alcohol
consumed (n;%) 89 245 668 370 216
51 1639
57.7% 48.1% 54.7% 45.5% 70.1%
49.5% 52.7%
0
O~
O~
C.O
0
*.~ (Iinear)= 216.44, d.f. = 1, P = 0.0000.
~.Ztk-~ = 160.29, d.f. = 1, P = 0.0000.
high scorers. For those who died, low S-R scores clearly drank more than high S-R scorers. We again
see a paradox, and again this finds an explanation in previous research that showed clearly that the
effects of alcohol are dependent on personality factors; Grossarth-Maticek & Eysenck (1991 a) found
that alcohol consumption had a negative valence for health if drunk to drown one's sorrows, but not
if drunk for pleasure, celebration, etc. This is an interesting feature common to smoking and
drinking,
showing that leaving out of account psychological factors may lead to serious misinterpretations of
epidemiological data concerning the effects of cigarette and alcohol consumption. (The X2 results
for
our conclusions show P < 0.001 levels.)
SELF-REGULATION AND GROSSARTH-MATICEK TYPOLOGY
It is of interest to see to what extent the Grossarth-Maticek Typology (Grossarth-Maticek &
Eysenck, 1990), with its six types, interacts with the self-regulation typology. It has often been
objected that the Grossarth-Maticek methodology of assigning a person to one or other of the six
types
is faulty because: (1) it uses only a small portion of the available data, (2) it does not correct
scores
on one type by drawing on information regarding another type. Thus a Type 1 person with a high score
on Type 4 might be expected to do better health-wise than a Type 1 person with a low Type 4 score.
Profile scoring might be a better method of analysis ~han simply assigning a person to a given type
just because he happened to score highest for that type, but from the beginning Grossarth-Maticek
has used the simple typology concept, rather like Friedman and Rosenman used the Type A concept
because to a medical audience this method of analysis might seem more natural and easier to follow.
The fact that this simple typological approach has been very successful (Eysenck, 1991) does not
mean
that better methods should not be tried; it might be hoped that their use would improve predictive
accuracy.
A sub-group of 3240 men and women was selected on a random basis and administered the
Personality Stress Inventory (Grossarth-Maticek & Eysenck, 1990), in order to cross-validate the two
inventories. Table 10 shows the major findings. Results are given separately for bad and for good
self-regulation (scores of 1, 2 or 3 vs 4, 5 or 6), subdivided by subjects according to Type (1, 2,
3,
4, 5 or 6). For each of the 12 sub-divisions (2 × 6) are given the number and percentage of deaths
from cancer, CHD (infarct) and other causes. Clearly SR is vitally important, as the percentage of
mortality figures for the High and low S-R scores show. This of course merely mirrors the data in
Figs 1 and 2. Within the low S-R group, clearly Type 1 has the highest cancer mortality, Type 4 the
least, while for Type 2 CHD has the highest mortality, with all the other types roughly on a par.
For

Self-regulation and mortality
Table 10. Degree of stir-regulation and six Grossarth-Maticek types as related to mortality
Type Type Type Type Type Type
1 2 3 4 5 6 Total
N 392
Cancer 117
29.8%
Infarct 51
13.0%
Other causes
of death 101
25.7%
Average age (yr) 57.6
Mean S-R score 2.4
N 26O
Cancer 4
1.5%
lnfaret 4
1.5%
Other causes
of death 21
8.0%
Average age (yr) 56.2
Mean S-R score 3.8
N 652
Cancer 121
18.5%
Infarct 55
8%4%
Other causes 122
of death 18.7%
Poor Self-regulation (1, 2 or 3 points)
403 102 52 507 64 1520
50 17 10 81 12 287
12.4% 16.6% 19.2% 15.9% 18.7% 18.8%
119 19 10 69 10 278
29.5% 18.6% 19.2% 13.6% 15.8% 18.3%
99 24 13 105 17 359
24.5% 23.5% 25.0% 20.7% 26.5% 23.6%
57.4 57.3 58.2 58.4 58.1
2.3 2.5 3.0 2.1 2.4
Good Self-regulatlon (4, 5 or 6 points)
204 351 477 358 70 1720
4 3 2 3 + I 17
1.9% 0.8% 0.4% 0.8% 1.4% 1.0%
5 7 2 2 1 21
2.4% 1.9% 0.4% 0.5% 1.4% 1,2%
27 29 34 38 15 164
13.2% 8.2% 7.2% 10.6% 21.4% 9.5%
56.9 57.1 56.2 56.4 55.7
3.9 4.1 4.7 3.8 3.9
Total Degree of Self-regulation
607 453 529 865 134 3240
54 20 12 84 13 304
8.9% 4.4% 2.2% 9.7% 9.7% 9.4%
204 26 12 71 11 379
33.6% 5.7% 2.3% 8.2% 8.2% 11.7%
126 53 47 143 32 523
20.8% 11.7% 8.9% 16.5% 23.9% 16.1%
789
'Other causes', there is little to choose between Types. For the good S-R scores, Type 4 does best
overall, but the other Types have mortality too low to produce marked differences.
It is interesting to look at the ratios of good/bad SRI scores for each of the typologies. Going
from
1 to 6, these are: 0.66; 0.51; 3.34; 9.17; 0.71; 1.09. Not unexpectedly, the 'healthy' Type 4 has
much
the highest ratio, followed by the fairly healthy Type 3; while the cancer-prone and CHD-prone Types
1 and 2 have much the lowest. It is apparent that the SRI measures much the same traits as does the
Grossarth-Maticek Typology Type 4.
Analyses by generalized linear model shows the main effects (Typology and Self-regulation) as
well as their interaction are all significant at the P < 0.001 level. One important consequence of
these
findings would seem to be that questionnaires using a positive wording are as useful, if not better,
at
indicating psychological disposition to good health, as questionnaires using a negative wording are
in indicating psychological disposition to bad health. Most people are apparently more likely to
respond truthfully to positive than to negative questions, although this point would have to be
established by a specially designed experiment.
Physical risk factors for disease
To study the relationship of physical risk factors to mortality, a score was based on a
specially
designed questionnaire, based on known risk factors which could be obtained relatively easily. Table
11 gives the items involved and the points given for the various items. The scale has a minimum of
0 points (no positive factors, high risk), and a maximum of 24 points (many positive factors, low
risk).
The scale takes into account genetic factors, exercise, nutrition, alcohol, smoking and direct
estimates
of poor fitness---overweight, high blood pressure, high cholesterol, etc. Different numbers of
points
can be obtained for different items, thus blood pressure is more important than smoking or drinking.
The various items were of course specified in considerable detail for the interviewers.
Table 12 shows the relationship between physical risk factor scores and (a) mortality and (b)
SRI
Scores.
There is clearly a close relation between physical risk factors and mortality; the greater the
number
of positive factors, the greater the chance of survival, and the lower the risk of mortality.
Conversely,

790
R. Grossarth-Maticek and H.. J. Eysenck
Table I I. Point scale for physical risk factors
Points
1. A close member of fl~e family (parents, grandparents)
has reached an age of 75 yr. Add one point for each
such family member. Points 0-6, respectively 0-6
2. Regular exercise 2
3. Dally activity in fresh air, irrespective of the weather 1
4. Healthy nourishment 2
5. Sufficient amount of fluid intake 1
6. Normal body weight 1
7. Little alcohol 1
8. Non-smoker I
9. Normal blood pressure 2
10. Normal blood sugar 2
l I. Normal total cholesterol 2
12. Low consumption of coffee, black tea and Coca-Cola® 1
13. No stimulant or depressant psychopharmaca. I
14. Normal sensitivity for pain (not overly sensitive) 1
the smaller the number of positive factors, the greater the risk of mortality. Those with the most
positive
factors, i.e. 24 points, show a survival rate seven times greater than those with a score of 0
points.
For those who died, probands with a score of 0 died 15 times more frequently than those with a score
of 24. The relationship is significant by Mann-Whitney U-test, with P<0.00001. SRI also
independently predicted mortality, with P < 0.00001 by Mann-Whitney U-test. The regression of S-R
on physical risk factors appears linear for the dead group but curvilinear for the living; only a
replication can show whether this is an accidental finding, of no importance. But clearly the S-R
scale
measures causes of death largely independent of physical causes.
It will be obvious from Table 12 that physical risk factors, as expected, correlate separately
with
mortality, r (bis) between total mortality and physical risk factors is 0.36, P< 0.001. Using a
Kruskal-Wallis ANOVA by ranks for the relationship between S-R and mortality, we obtain
H= 3520.83, which with d.f. = 2 gives P < 0.00001. Carrying out the same type of analysis for
physical risk factors, H = 1118.26, which with d.f. = 2 gives P < 0.00001. There is little
correlation
Table 12. Mortality as related to physical risk factors and
self-regulation
Still living Mortality
Positive
physical S-R S-R
factors n % (%) n % (%)
0 20 0.6 4.8 315 13.9 3.1
1 21 0.6 4.9 206 9.1 3.0
2 34 1.0 4.7 170 7.5 2.8
3 47 1.4 4.6 ~ 153 6.7 3.9
4 96 2.8 4.3 104 4.6 3.1
5 78 2.3 3.9 107 4.7 3.3
6 103 3.0 3.6 I01 4.4 3.3
7 124 3.6 3.7 162 7.1 3.4
8 113 3.3 3.5 103 4.5 3.5
9 272 7.9 3.8 102 4.4 3.3
10 271 7.9 3.6 100 4.4 3.4
11 294 8.5 3.7 84 3.7 3.4
12 231 6.7 3.8 75 3.3 3.3
13 186 5.4 3.6 62 2.7 3.5
14 144 4.2 3.9 51 2.2 3.6
15 169 4.9 3.7 45 1.9 3.4
16 124 3.6 3.6 37 1.6 3.3
17 116 3.4 3.8 40 1.6 3.1
18 127 3.7 3.9 35 1.5 2.9
19 131 3.8 3.4 49 2.2 2.7
20 155 4.5 3.9 51 2.2 2.5
21 163 4.7 4.0 42 1.8 2.6
22 143 4.2 4.1 31 1.4 2.1
23 136 4.0 4.5 28 1.2 2.3
24 144 4.1 4.9 21 0.9 2.4
Total 3422 2274
0
0
