Do psychosocial factors cause coronary heart disease or affect survival among patients with coronary heart disease? Here we use an explicit methodological quality filter to review systematically the prospective cohort studies testing specific psychosocial hypotheses. This review of the epidemiological literature identifies the psychosocial factors that have been most rigorously tested. Only four psychosocial factors met the quality filter: type A/hostility, depression and anxiety, work characteristics, and social supports. The importance of other study designs—for example, ecological1 or nested case-control2–4 studies—is acknowledged. The review should be seen as complementary to existing reviews5–8 on single psychosocial factors and as a challenge to investigators in the field to ensure that the systematic review is made unbiased, kept up to date, and used to guide future hypothesis testing.
Summary points
In healthy populations, prospective cohort studies show a possible aetiological role for type A/hostility (6/14 studies), depression and anxiety (11/11 studies), psychosocial work characteristics (6/10 studies), social support (5/8 studies)
In populations of patients with coronary heart disease, prospective studies show a prognostic role for depression and anxiety (6/6 studies), psychosocial work characteristics (1/2 studies), and social support (9/10 studies); none of five studies showed a prognostic role for type A/hostility
Although this review can not discount the possibility of publication bias, prospective cohort studies provide strong evidence that psychosocial factors, particularly depression and social support, are independent aetiological and prognostic factors for coronary heart disease
What is a psychosocial factor?
A psychosocial factor may be defined as a measurement that potentially relates psychological phenomena to the social environment and to pathophysiological changes. The validity and reliability (precision) of the questionnaire based instruments used to measure psychosocial factors has been improved through the use of psychometric techniques. By avoiding the unhelpful general term of “stress,” recent work has developed theoretical models—for example, the job control-demands-support model of psychosocial work characteristics—which generate specific hypotheses that can be tested.
How might psychosocial factors be linked to coronary heart disease?
Evidence of mechanisms linking psychosocial factors with coronary heart disease (reviewed elsewhere9,10) is important in making causal inferences and therefore in designing preventive interventions. Psychosocial factors may act alone or combine in clusters11 and may exert effects at different stages of the life course.12 Broadly, three interrelated pathways may be considered. Firstly, psychosocial factors may affect health related behaviours such as smoking, diet, alcohol consumption, or physical activity, which in turn may influence the risk of coronary heart disease.13 If such behaviours do lie on the causal pathway between psychosocial factors and coronary heart disease, then treating them as confounding variables, as some studies do, must be questioned. Secondly, psychosocial factors may cause direct acute or chronic pathophysiological changes. Thirdly, access to and content of medical care may plausibly be influenced by, for example, social supports (but there is little direct evidence for this). Although it is beyond the scope of this review to consider the determinants of adverse psychosocial factors, socioeconomic status is inversely associated with coronary heart disease14 and also with certain psychosocial factors, and it has been proposed that psychosocial pathways may play a mediating role.15,16
Method of systematic review
A methodological quality filter was used to select studies for inclusion in the systematic review, so that the strength of evidence could be compared across psychosocial factors. Prospective cohort studies are the best observational design for questions of aetiology and prognosis. The studies included had a prospective cohort design; a population based sample (aetiological studies in healthy populations); at least 500 participants (aetiological studies) or 100 participants (prognostic studies in populations of patients with coronary heart disease); measurements of a psychosocial factor used in at least two different study populations; outcomes of fatal coronary heart disease or non-fatal myocardial infarction or (prognostic studies only) all cause mortality.
Articles were identified by Medline search (1966-97), manual searching of the bibliographies ofretrieved articles, previous review articles, writing to researchersin the field, and an in-house bibliographic database. No register of published and unpublished studies with psychosocial exposures exists, and hand searching of journals was not performed, so there is a serious potential for publication bias. For this reason as well as the lack of standardised methods of measurement of psychosocial factors, we carried out a narrative, rather than quantitative, systematic review. Given that randomised controlled trials, at least for primary prevention, are rarely feasible, observational studies are likely to remain the main type of evidence on which to base preventive action.
Evidence for specific psychosocial factors
Largely on the basis of studies in middle aged men (table 1), four groups of psychosocial factors were identified by using the predefined quality filter: psychological traits (type A behaviour, hostility), psychological states (depression, anxiety), psychological interaction with the organisation of work (job control-demands-support), and social networks and social support. In simple terms this corresponds to a spectrum with mainly psychological components at one end and a stronger social component at the other. The box summarises the key results.
Studies showing role of psychosocial factors
In healthy populations, prospective cohort studies suggest a possible aetiological role for:
Type A/hostility (6/14 studies)
Depression and anxiety (11/11 studies)
Psychosocial work characteristics (6/10 studies)
Social support (5/8 studies)
In coronary heart disease patient populations, prospective studies suggest a prognostic role for:
Type A/hostility (0/5 studies)
Depression and anxiety (6/6 studies)
Psychosocial work characteristics (1/2 studies)
Social support (9/10 studies)
Although this review cannot discount the possibility of publication bias, prospective cohort studies provide strong evidence that psychosocial factors, particularly depression and social support, are independent aetiological and prognostic factors for coronary heart disease.
Table 1.
Studies of type A behaviour, hostility, and coronary heart disease. References in this table are given on the BMJ website
| Author, year, country | Total sample (% women) | Age at entry | Exposure | Follow up (years) | No of events | Type of events | Adjustments | Relative risk* | Summary† |
|---|---|---|---|---|---|---|---|---|---|
| Prospective aetiological studies | |||||||||
| Jenkins 1974w1 USA | 2750 (0) | 39-59 | Type A | 4 | 120 | Non-fatal MI + angina | Age | 1.8* | + |
| Rosenman 1976w2 USA | 3154 (0) | 39-59 | Type A | 8.5 | 257 | Fatal CHD + non-fatal MI | Age, smoking, cholesterol, family history, corneal arcus, schooling, β:α lipoprotein ratio | 2.16* | ++ |
| Haynes 1980w3 USA | 1674 (57) | 45-77 | Type A (Framingham) | 8 | 170 | Fatal CHD + non-fatal MI + coronary insufficiency + angina | Age, smoking, blood pressure, cholesterol, glucose intolerance and other psychosocial factors | 1.8*; among men, the effect was confined to white collar workers | + |
| Shekelle 1983w4 USA | 1877 (0) | 40-55 | Hostility (MMPI) | 10 | 139 | Fatal CHD + non-fatal MI | Age, smoking, blood pressure, cholesterol, alcohol | 1.47*, but effect not linear | + |
| Cohen 1985w5 USA | 2187 (0) | 57.8 (mean) | Type A (JAS) | 8 | 190 | Fatal CHD + non-fatal MI + angina | Smoking, blood pressure, cholesterol, body mass index, alcohol, and other biological factors | 1.43, Type A associated with prevalence, not incidence or postmortem findings | 0 |
| Shekelle 1985w6 USA | 3110 (0) | 46 (mean) | Type A (JAS) | 7.1 | 554 | Fatal CHD + non-fatal MI | Age, smoking, blood pressure, cholesterol, alcohol, education | 0.87 | 0 |
| Johnston 1987w7 UK | 5936 (0) | 40-59 | Type A (Bortner) | 6.2 | 255 | Fatal CHD + non-fatal MI | Age, social class | 0.89 | 0 |
| Ragland 1988w8 USA | 3154 (0) | 39-59 | Type A (SI) | 22 | 214 | Fatal CHD | Age, smoking, blood pressure, cholesterol | 0.98 | 0 |
| Hearn 1989w9 USA | 1399 (0) | 19 | Hostility (MMPI) | 33 | 54 | Fatal CHD + non-fatal MI + angina + coronary surgery | Smoking, hypertension, family history | 1.1; no association in crude or risk factor adjusted analyses | 0 |
| Barefoot 1995w10 USA | 730 (44) | 50 | Hostility (Cook-Medley) | 27 | 122 | Non-fatal MI | Age, sex, smoking, blood pressure, triglycerides, exercise | 1.26 (men) 2.95* (women) | 0 (men) ++(women) |
| Bosma 1995w11 Lithuania and Netherlands | 5817 (0) | 45-60 | Type A (JAS) | 9.5 | 394 | Fatal CHD + non-fatal MI | Age | No association | 0 |
| Kawachi 1996w12 USA | 1305 (0) | 40-90 | MMPI-2 anger content scale | 7 | 110 | Fatal CHD + non-fatal MI + angina | Age, smoking, blood pressure, cholesterol, body mass index, family history, alcohol | 2.66* | ++ |
| Everson 1997w13 Finland | 1599 (0) | 42-60 | Cynical hostility (Cook-Medley) | 6 | 60 | First MI | Age, biological, socioeconomic, behavioural, social support, prevalent diseases | 1.43 (2.18* when adjusted for age only) | 0 |
| Tunstall-Pedoe 1997w14 Scotland | 11659 (50) | 40-59 | Type A (Bortner) | 7.6 | 581 | Fatal CHD + non-fatal MI + coronary surgery | Age | 0.82* in women, ie type A protective | 0 |
| Prognostic studies | |||||||||
| Case 1985w15 USA | 516 (18) patients <14 days post MI | <70 | Type A (JAS) | 2 | 53 | Fatal CHD and all cause mortality | Age, sex, education, rales, ejection fraction, New York Heart Assocation functional class, ventricular premature beats | 0.8 | 0 |
| Shekelle 1985w16 USA | 2314 (11) patients post MI | 30-69 | Type A (JAS) | 3 | 294 | Non-fatal MI and fatal CHD | Smoking, previous MI, angina, fasting glucose | No association | 0 |
| Ragland 1988w17 USA | 257 (0) with MI or angina | 39-70 | Type A (SI) | 11.5 | 91 | Fatal CHD | Age at initial event, follow up time, type of initial coronary event, smoking, blood pressure, cholesterol | 0.58*; type A protective | 0 |
| Barefoot 1989w18 USA | 1467 (18) patients with angiographic disease | mean 52 (SD 9) | Type A (SI) | 5 | 315 | Fatal CVD + non-fatal MI | Stratified on clinical prognostic factors | No association with non-fatal MI | 0 |
| Jenkinson 1993w19 UK | 1376 (22) 7 days post-MI | 25-84 | Type A | 3 | 247 | All cause mortality | Age, previous MI,hospital complications, diabetes, hypertension, car ownership, sex | No association | 0 |
CHD=coronary heart disease; MI=myocardial infarction; SI=structured interview; JAS=Jenkins activity survey; MMPI=Minnesota multiphasic personality inventory.
P<0.05. †0=no association—that is, relative risk not significantly different from unity; +=moderate association (relative risk >1⩽2.0); ++=strong association (relative risk >2.0).
Hostility and type A behaviour
Type A behaviour pattern—the only personality trait which met the criteria of our review—is characterised by hard driving and competitive behaviour, a potential for hostility, pronounced impatience, and vigorous speech stylistics. The instruments for measurement of type A behaviour and hostility—the Jenkins activity scale, the structured interview, the Minnesota multiphasic personality inventory (MMPI), the Bortner hostility scale—have been subjected to psychometric testing and incorporated into many cardiovascular cohort studies, including some that have not reported results. Unlike other psychosocial factors, type A is distinguished by being the subject of numerous intervention trials.17 On the basis of early positive findings in the Framingham study18 and the Western Collaborative Group’s eight year follow up,19 among other evidence, the National Institutes of Health declared type A an independent risk factor for coronary heart disease. However, with the publication of negative findings20–22 it was proposed that a more specific component of type A, namely hostility, might be aetiological, although there are conflicting studies. None of the five studies that examined type A or hostility in relation to prognosis among patients with coronary heart disease showed an increased risk; indeed, one suggested a protective effect.
SUE SHARPLES
Depression and anxiety
The relation between depression and anxiety and coronary heart disease differs from those of other psychosocial factors for several reasons. Firstly, unlike other psychosocial factors, depression and anxiety represent well defined psychiatric disorders, with standardised instruments for measurement. Secondly, depression and anxiety are commonly the consequence of coronary heart disease, and the extent to which they are also the cause poses important methodological issues. Thirdly, the ability to diagnose and treat such disorders makes them attractive points for intervention. Finally, depression and coronary heart disease could share common antecedents—for example, environmental stressors and social supports.
Table 2 shows the results from the 11 prospective studies that investigated depression or anxiety in the aetiology of coronary heart disease, all of which were positive. All three of the prospective studies examining the effect of anxiety in the aetiology of coronary heart disease had positive results. Intriguingly, there is some evidence that this effect is strongest specifically for phobic anxiety and sudden cardiac death. Wassertheil-Smoller23 reported the effect of depression in relation to cardiovascular events among 4367 healthy older people. An increase in depression symptoms (but not the baseline scores) predicted events, even when multiple covariates were controlled for. Such findings are compatible with the hypothesis that premonitory signs of coronary heart disease such as angina or breathlessness may have led to the increase in depression. Studies with longer periods of follow up are less likely to be confounded by the possibility of early disease causing depression, but raise further questions about the time course of exposure. For example, it is possible that there is a common trigger (such as viral illness) that precipitates both symptoms of depression and atherothrombotic processes. By examination of subclinical manifestations of coronary heart disease (using non-invasive measures of arterial structure and function, for example) before the onset of symptoms, the temporal sequence of the relation might be better understood.
Table 2.
Studies of depression and anxiety and coronary heart disease. References in the table are given on the BMJ website
| Author, year, country | Total sample (% women) | Age at entry | Exposure | Follow up (years) | No of events | Type of events | Adjustments | Relative risk* | Summary† |
|---|---|---|---|---|---|---|---|---|---|
| Prospective aetiological studies | |||||||||
| Hallstrom 1986w20 Sweden | 795 (100) | 38-54 | Depression (Hamilton and psychiatric interview) | 12 | 75 | Non-fatal MI + angina + ischaemic changes on electrocardiograph | Age, social class, marital status, conventional risk factors | 5.4* severity of depression predicted angina but not other outcomes | ++ |
| Hagman 1987w21 Sweden | 5735 (0) | 55 (mean) | Anxiety (“stress”) | 2-7 | 162 | Angina with or without MI | Age, smoking, blood pressure, cholesterol, relative weight | Strong predictor for angina alone | + |
| Haines 1987w22 UK | 1457 (0) | 40-64 | Phobic anxiety (Crown-Crisp) | 10 | 113 | Fatal CHD + non-fatal MI | fibrinogen, cholesterol, factor VII, systolic blood pressure | 3.77* for fatal CHD | ++ |
| Appels 1990w23 Netherlands | 3877 (0) | 39-65 | Depression | 4.2 | 59 | Non-fatal MI + unstable angina + angina | Age, smoking, blood pressure, cholesterol | 1.86* for unstable angina for combination of low mood, low energy, hopelessness, poor sleep (termed “vital exhaustion”) | + |
| Anda 1993w24 USA | 2832 (52) | 45-77 | Depression (General Well Being) | 12 | 394 | Fatal CHD + non-fatal CHD hospitalisations | Age, sex, race, education, marital status, smoking, blood pressure, cholesterol, body mass index, alcohol, exercise | 1.6* | + |
| Aromaa 1994w25 Finland | 5355 (55) | 40-64 | Depression (GHQ and PSE) | 6.6 | 91 | Fatal CHD | Age, pre-existing cardiovascular disease | 3.36* (5.52 in those with pre-existing cardiovascular disease) | ++ |
| Kawachi 1994w26 USA | 33999 (0) | 42-77 | Phobic anxiety (Crown Crisp) | 2 | 168 | Fatal CHD + non-fatal MI | Age, smoking, blood pressure, cholesterol, body mass index, diabetes, parental history of MI, alcohol, exercise | 3.01* (6.08 when sudden cardiac death examined) | ++ |
| Everson 1996w27 Finland | 2428 (0) | 42-60 | Hopelessness | 6 | 95 | Non-fatal MI | Age, smoking, blood pressure, cholesterol education, income, exercise, alcohol, lipids, social supports, depression | 2.05* | ++ |
| Wassertheil-Smoller 1996w28 USA | 4367 (53) | 72 (mean) | Depression (CES-D) | 4.5 | 321 | Non-fatal MI + non-fatal strokes | Age, smoking, baseline depression, sex, race, randomisation group, education, history of stroke, MI, diabetes, and baseline ADL | 1.18* per 5 unit increase in depression score (baseline scores alone did not predict events) | + |
| Barefoot 1996w29 Denmark | 730 (44) | 50 or 60 | Depression (MMPI-obvious depression scale) | 27 | 122 | Non-fatal MI | Age, conventional CHD risk factors, baseline CHD | 1.7* for 2 SD difference in depression score | + |
| Kubzansky 1997w30 USA | 1759 (0) | 21-80 | Social conditions worry scale | 20 | 323 | Fatal CHD + non-fatal MI + angina | Age, smoking, blood pressure, cholesterol, body mass index, family history, alcohol | 1.23* per 1 point increase in social conditions worry scale | + |
| Prognostic studies | |||||||||
| Ahern 199031 USA | 353 | Depression (Beck), anxiety (Spielberger) | 12 | Fatal CHD | Age, left ventricular dysfunction and previous MI | 1.3* for depression | + | ||
| Kop 199432 Netherlands | 127 (17) patients 2 weeks after coronary angioplasty | 56 (SD 9) | Maastricht questionnaire for vital exhaustion | 1.5 | 29 | Fatal CHD + non-fatal MI + further revascularisation + increase in coronary atherosclerosis + new angina | Age, sex, smoking, blood pressure, cholesterol, severity of coronary artery disease, clinical presentation | 2.34 (P=0.06) | + |
| Ladwig 199433 Germany | 377 (0) 17-21 days after acute MI | 29-65 | Depression (interview) | 0.5 | Angina, not returning to work, continuing to smoke | Age, social class, recurrent infarction, rehabilitation, cardiac events and helplessness | 2.31* for the effect on angina; depression predicted all outcomes | ++ | |
| Frasure-Smith 1995w34 USA | 222 (21) patients 5-15 days after acute MI | 24-88 | Depression (diagnostic interview schedule) | 1.5 | 21 | All cause mortality and fatal CHD | Age, Killip class, premature ventricular contractions and previous MI | 6.64* effect of depression higher in those with (10 premature contractions per hour | ++ |
| Barefoot 1996w35 USA | 1250 (18) patients with angiographic disease | 52 (mean) | Depression (Zung) | 19.4 | 604 | All cause mortality and fatal CHD | Disease severity, initial treatment | 1.66*, 1.84* and 1.72* in three follow up periods (year 1, 5-10 and >10 respectively) | + |
| Denollet 1996w36 Belgium | 303 (12) patients with angiographic disease | 31-79 | Type D personality (suppression of emotional distress), depression, social alienation | 7.9 | 38 | All cause mortality and fatal CHD | Left ventricular function, number of diseased vessels, low exercise tolerance, lack of thrombolytic therapy | 4.1* for type D and 2.7* for depression | ++ |
CHD=coronary heart disease; MI=myocardial infarction; CES-D=Center for Epidemiological Studies-Depression scale; GHQ=general health questionnaire; PSE=present state examination; MMPI=Minnesota multiphasic personality inventory.
P<0.05. †0=no association—that is, relative risk not significantly different from unity; +=moderate association (relative risk >1⩽2.0); ++=strong association (relative risk >2.0) association.
Depression in patients after myocardial infarction seems to be of prognostic importance beyond the severity of coronary artery disease. Although discrete major depressive episodes are not uncommon after a myocardial infarction, depressive symptoms are more prevalent. Given the graded relation between depression scores and risk, the long lasting nature of the effect, and the stability of the depression measured across time, it has been proposed that depression is a continuously distributed chronic psychological characteristic.
Psychosocial work characteristics
The longstanding observation that rates of coronary heart disease vary markedly among occupations—more than can be accounted for by conventional risk factors for coronary heart disease—has generated a quest for specific components of work that might be of aetiological importance. The dominant “job strain” model of psychosocial work characteristics, as proposed by Karasek and Theorell, grew out of secondary analyses of existing survey data on the labour force. This model proposes that people in jobs characterised by low control over work and high conflicting demands might be high strain. A subsequent addition to the model was that social support might buffer this effect. The advantage of the model is that it generates specific hypotheses for testing.
Table 3 shows prospective cohort studies that have examined the relation between job strain and coronary heart disease. Both self reports and ecological measurements (assigning a score on the basis of job title) of job strain have been made. Self reports may be biased by early manifestations of disease, and ecological measurements may lack precision. The finding that these methods tend to give reasonably consistent results suggests that they are complementary. Six of the 10 studies were had positive results. There is growing emphasis on the importance of low job control rather than on conflicting demands,24 and it seems likely that these empirical results will lead to a reformulation of the model. Alternative models of psychosocial work characteristics involve an imbalance between the effort at work and rewards received.25,26
Table 3.
Studies of psychosocial work characteristics and coronary heart disease. References in table are given on BMJ website
| Author, year, country | Total sample (% women) | Age at entry | Exposure | Follow up (years) | No of events | Type of events | Adjustments | Relative risk* | Summary† |
|---|---|---|---|---|---|---|---|---|---|
| Prospective aetiological studies | |||||||||
| LaCroix 1984w37 USA | 876 (37) | 45-64 | Job control and demands (individual and ecological) | 10 | Not stated | Fatal CHD + non-fatal MI + coronary insufficiency + angina | Age, smoking, blood pressure, cholesterol | 2.9* all women (clerical women RR=5.2) no association in men. Ecological exposure was associated with risk in men and women | + |
| Alfredsson 1985w38 Sweden | 958 096 (51) | 20-64 | Hectic work and few possibilities for learning (ecological) | 1 | 1201 | Non-fatal MI (hospitalisation) | Age, 10 sociodemographic factors, smoking, heavy lifting | 1.5* | + |
| Haan 1988w39 Finland | 902 (33) factory workers | 20-62 | Job control, physical strain, variety (individual) | 10 | 60 | Fatal CHD + and non-fatal CHD | Age, smoking, blood pressure, cholesterol, alcohol, relative weight | 4.95* for low control, low variety, high physical strain | ++ |
| Reed 1989w40 Hawaii (Japanese ancestry) | 4737 (0) | 45-65 | Job control, demands and their interaction (ecological) | 18 | 359 | Fatal CHD and non-fatal MI | Age | No effect of control, demands or their interaction (ns trend for lower strain men to have higher CHD) | 0 |
| Netterstrom 1993w41 Denmark | 2045 (0) bus drivers | 21-64 | Job variety, satisfaction | 10 | 59 | Fatal CHD | Age | 2.1*—high job variety and satisfaction associated with CHD risk | 0 |
| Suadicani 1993w42 Denmark | 1752 (0) | 59 (mean) | Job influence, monotony, pace, satisfaction, ability to relax | 3 | 46 | Fatal CHD + non-fatal MI | None | Only inability to relax after work associated with CHD | 0 |
| Alterman 1994w43 USA | 1683 (0) | 38-56 | Job control, demands and their interaction (ecological) | 25 | 283 | Fatal CHD | Age | 1.4 for job strain | 0 |
| Bosma 1997w44 UK | 10 308 (33) civil servants | 35-55 | Job control, demands (individual, assessed twice 3 years apart, and ecological) | 5 | 654 | Angina + doctor diagnosed ischaemia | Age, smoking, blood pressure, cholesterol, body mass index, employment grade | 1.93* self reported or externally assessed low job control predicted CHD | + |
| Lynch 1997w45 Finland | 1727 (0) | 42-60 | Job demands, resources, income | 8.1 | 89 | Fatal CHD + non-fatal MI | Age, behavioural, biological and psychosocial covariates | 1.57* for the effect of high demands, low resources and low income; 2.59 when adjustment made for age only | + |
| Steenland 1997w46 USA | 3575 (0) | 25-74 | Job control and demands (ecological) | 14 | 519 | Fatal CHD + non-fatal MI | Age, smoking, blood pressure, cholesterol, education, body mass index, self reported diabetes | 1.41* for low control | + |
| Prognostic studies | |||||||||
| Hlatky 1995w47 USA | 1489 (24) employed patients undergoing coronary angiography | 41-59 | Job control, demands (individual) | 5 | 112 | Fatal CHD + non-fatal MI prevalence of coronary artery disease | Ejection fraction, extent of coronary atherosclerosis, myocardial ischaemia | 0.96 for effect of job strain on events. Job strain was associated with normal coronary arteries | - |
| Hoffmann 1995w48 Switzerland | 222 (0) after first MI | 30-60 | Job work load, locus of control, social supports | 1 | 19 | All cause mortality, reinfarction, severe symptoms, or poor exercise capacity | Age, severity of MI, exercise | High workload and low external locus of control associated with outcome | + |
CHD=coronary heart disease; MI=myocardial infarction.
P<0.05. †0=no association—that is, relative risk not significantly different from unity; +=moderate association (relative risk >1⩽2.0); ++=strong association (relative risk >2.0) association.
Social network structure and quality of social support
Social supports and networks relate to both the number of a person’s social contacts and their quality (including emotional support and confiding support). Marital status—information routinely sought in clinical practice—is a simple measure of social support, and the ability of low social support to predict all cause mortality has long been recognised. It has been proposed that social supports may act to buffer the effect of various environmental stressors and hence increase susceptibility to disease,27 but most of the evidence supports a direct role.
Five of the eight prospective cohort studies that investigated aspects of social support in relation to the incidence of coronary heart disease were positive (table 4). Nine of the 10 prognostic studies were positive, and the relative risks for three of these studies exceeded 3. Despite the strength and consistency of these findings, the relative effect of structural and functional aspects of social supports has yet to be delineated.
Table 4.
Studies of social networks and social supports and coronary heart disease. References in table are given on BMJ website
| Author, year, country | Total sample (% women) | Age at entry | Exposure | Follow up (years) | No of events | Type of events | Adjustments | Relative risk* | Summary† |
|---|---|---|---|---|---|---|---|---|---|
| Prospective aetiological studies | |||||||||
| Medalie 1976w49 Israel | 10 000 (0) | >40 | Perceived love and support from spouse | 5 | 300 | Angina | Age, blood pressure, cholesterol, diabetes, ECG abnormalities | 1.8* | + |
| House 1982w50 USA | 2754 (52) | 35-69 | Social relationships and activities | 11 | 114 | Fatal CHD | Age, baseline CHD, smoking, forced expiratory volume at 1 second | Not stated | + |
| Berkman 1983w51 USA | 4725 (53) | 30-69 | Social network index | 9 | 120 | Fatal CHD | Age | 2.13* | ++ |
| Reed 1983w52 USA | 4653 (0) | 52-71 | Social network score | 6 | 218 | Fatal CHD + non-fatal | Age, blood pressure, cholesterol, glucose, uric acid, forced vital capacity, body mass index, exercise, alcohol, complex carbohydrate | Social network associated with CHD prevalence, but not incidence | 0 |
| Kaplan 1988w53 Finland | 13301 | 39-59 | Social network index | 5 | 223 | Fatal CHD | Age, smoking, blood pressure, cholesterol, prevalent illness, urban/ rural residence | 1.34 for men but not women | 0 |
| Vogt 1992w54 USA | 2603 (54) | 18-75+ | Network scope, network frequency, and network size | 15 | not stated | Fatal CHD + non-fatal CHD | Age, sex, SES, smoking and subjective health status at baseline | 1.5* for effect of network scope on CHD incidence; all 3 measures predicted survival in those with CHD | + |
| Orth-Gomer 1993w55 Sweden | 736 (0) | 50 | Emotional support from close people and support from extended network (social integration) | 6 | 25 | Fatal CHD + non-fatal CHD | Age, cholesterol treatment of hypertension, diabetes, body mass index< smoking, physical activity | 3.8* for social integration 3.1 for emotional support | ++ |
| Kawachi 1996w56 USA | 36 624 (0) | 42-77 | Social network index | 4 | 403 | Fatal CHD + non-fatal MI | Age, time period, smoking, blood pressure, cholesterol, diabetes, angina, body mass index, family history, alcohol, exercise | 1.14. Some evidence for association with fatal CHD (particularly non-sudden cardiac death) rather than non-fatal MI | 0 |
| Prognostic studies | |||||||||
| Chandra 1983w57 USA | 1401 | Not stated | Marital status | 10 | Not stated | All cause mortality | Age, race, smoking, severity of MI, medical care factors | Married men and women had better in hospital and 10 year survival | + |
| Ruberman 1984w58 USA | 2320 (0) patients with MI | 30-69 | Social support, life stress | 3 | 128 | All cause mortality, sudden cardiac death | Age, myocardial function, ventricular arrhythmia, smoking | 4.5* for the effect of social isolation + high life stress on all cause mortality; 5.62 for sudden cardiac death | ++ |
| Wiklund 1988w59 Sweden | 201(0) patients with first MI | 32-60 | Social support, depression and other psychosocial factors | 8.3 | 85 | All cause mortality + recurrent non-fatal MI | Hypertension, smoking, angina | Being single increased risk of death | + |
| Case 1992w60 USA | 1234 (38) participants in diltiazem post-MI trial | 25-75 | Living alone, disrupted marriage | 2 | 226 | Fatal CHD + recurrent non-fatal MI | New York Heart Assocation functional class, ejection fraction, education, no β blockers, ventricular premature complexes, prior infarction | 1.54* for effect of living alone. No effect of marital disruption | + |
| Hedblad 199261 Sweden | 98 (0) men with ischaemic 24 hour ECG | 68 | Social support and social network | 5 | 17 | Fatal CHD + non-fatal MI | Age, smoking, blood pressure, cholesterol, alcohol, exercise, body mass index, triglycerides | 5.6* and 4.1* for low informational support and low emotional support respectively | ++ |
| Williams 1992w62 USA | 1368 (18) patients with angiographicdis ease | 52 (median) | Structural social support (marital status) and function social support | 9 | 249 | All cause mortality | Age, ejection fraction, non-invasive myocardial damage index, conduction disturbance, pain/ ischaemic index, mitral regurgitation, number of diseased vessels, % stenosis of left main stem and left anterior descending artery | 3.34* for effect of unmarried patients without confidant | ++ |
| Berkman 1992w63 USA | 194 (48) patients with acute MI | 65-85+ | Emotional support | 0.5 | 76 | All cause mortality | Age, sex, Killip class, ejection fraction, reinfarction, comorbidity, functional disability, previous MI, ventricular tachycardia | 2.9* for lack of emotional support | + |
| Gorkin 1993w64 USA | 1322 (17) patients with previous MI + ventricular premature complexes | 60.8 (SD 9.9) | Social support | 0.8 | Not stated | All cause mortality | Ejection fraction, arrhythmia rates, CHD risk factors, | 1.46* for 1 point decrease in social support | + |
| Jenkinson 1993w19 UK | 1376 (22) 7 days after MI | 25-84 | Social isolation, life stress, depression, type A | 3 | 247 | All cause mortality | Age, previous MI, hospital complications, diabetes, hypertension, car ownership, sex | 1.33 for social support; no effect of type A or depression | 0 |
| Friedman 1995w65 USA | 369 (15) patients after acute MI with ventricular arrhythmias in the CAST | 63 (SD 9) | Social support, life events, depression, anxiety, type A, anger | 1 | 20 | All cause mortality | Physiological severity, demographic and other psychosocial factors | Not stated | + |
CHD=coronary heart disease; MI=myocardial infarction; CAST=cardiac arrhythmia suppression trial.
P<0.05. †0=no association—that is, relative risk not significantly different from unity; +=moderate association (relative risk >1⩽2.0); ++=strong association (relative risk >2.0).
Modification of psychosocial factors
The main implications of these findings for clinical practice are summarised in the box. A recent meta-analysis found that psychosocial interventions are associated with improved survival after myocardial infarction.28 However, two recent large randomised controlled trials of psychological rehabilitation after myocardial infarction found no difference in anxiety and depression, and this may in part explain the lack of effect on mortality.29,30 Randomised controlled trials of modification of social supports after myocardial infarction show a decrease in cardiac death or reinfarction rates.31 A patient’s social circumstances should be elicited as part of the history, and the doctor may have a role in mobilising social support. A multicentre trial of 3000 patients after myocardial infarction (ENRICHD—enhancing recovery in coronary heart disease) is currently under way in the United States. It will target patients at high psychosocial risk (those who are depressed or socially isolated) and enrol large numbers of women and ethnic minorities.
Psychosocial components of secondary prevention
Clinicians should consider:
Detecting and treating depression
Mobilising social support
Using socioeconomic status and psychosocial factors to risk stratify patients
The potential for primary prevention in relation to psychosocial factors lies largely outside the remit of clinicians. Psychosocial factors themselves are determined largely by social, political, and economic factors and it is therefore policy makers who influence the structure and function of communities—in the public and private domains—who may have scope for primary prevention.
Conclusion
Of the large number of psychosocial factors that have been studied, only four met the quality filter: type A/hostility, depression and anxiety, work characteristics, and social supports. While this review cannot discount the possibility of publication bias, the prospective observational studies show aetiological roles for social supports, depression and anxiety, and work characteristics and prognostic roles for social supports and depression. Further evidence of a causal role is provided by human and other primate evidence of biological and behavioural pathways mediating these effects. However, conflicting data exist on whether psychosocial interventions reduce mortality after myocardial infarction. This systematic review should be updated and expanded to include other observational study designs and other endpoints (for example, all cause mortality) in order to focus future research and, ultimately, policy. In this expanding area, future primary research might investigate the:
Interrelationships between different psychosocial factors
Effect of change in and cumulative exposure to psychosocial factors
Short and long term effects thoughout the life course
Differences by sex, ethnic group, and country
Behavioural and biological mechanisms involved
Effect of psychosocial factors on different clinical and subclinical outcomes
Appropriate primary and secondary preventive measures.
Supplementary Material
Acknowledgments
The comments of Lisa Berkman, Ichiro Kawachi, Redford Williams, and Mandy Feeney are gratefully acknowledged. To keep this review complete and up to date, we would be grateful to be informed of studies which we may have missed.
Footnotes
This is the third of four articles
Funding: MM is supported by an MRC research professorship; his group investigating pyschosocial factors and health has been supported by the Agency for Health Care Policy and Research (5 RO1 HS06516); the New England Medical Centre-Division of Health Improvement; the National Heart Lung and Blood Institute (2RO1 HL36310); National Institute on Aging (RO1 AG13196-02); the John D and Catherine T MacArthur Foundation Research Network on Successful Midlife Development; the Institute for Work and Health, Ontario, Canada; the Volvo Research Foundation, Sweden; Medical Research Council; Health and Safety Executive; and British Heart Foundation (RG/28).
website extra: References in the tables are given on the BMJ website www.bmj.com
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