European Heart Journal Advance Access published online on December 21, 2006
European Heart Journal, doi:10.1093/eurheartj/ehl435
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Heart failure in different occupational classes in Sweden
Department of Medicine, Sahlgrenska University Hospital/Östra, SE-416 85 Göteborg, Sweden
Received 18 August 2006; revised 19 November 2006; accepted 23 November 2006.
* Corresponding author. Tel: +46 31 3434100; fax: +46 31 259 254. E-mail address: annika.rosengren{at}hjl.gu.se
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Abstract |
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Aims The link between low socioeconomic status (SES) and coronary heart disease (CHD) is well established, but there is a paucity of data whether a similar relation exists for heart failure (HF).
Methods and results A total of 6999 men 47–55 years old, without a prior stroke or myocardial infarction, from a population sample of 9998 men, were investigated during 1970–73. Over a 28-year follow-up, 1004 men (14.3%) were discharged from hospital or died with a diagnosis of HF. There was an inverse relationship between SES, measured as an occupational class, and future risk of HF. Compared with men in the highest occupational class, men with intermediate non-manual occupations had a multiple-adjusted hazard ratio (HR) of 1.28, 95% confidence interval (CI) 0.98–1.67, lower officials and foremen had an HR of 1.57 (1.22–2.03), semiskilled and skilled workers 1.48 (1.15–1.89), and unskilled workers 1.72 (1.34–2.20). Results were similar if only men with a principal diagnosis of HF (n=516) were considered, irrespective of whether a diagnosis of acute myocardial infarction or coronary revascularization had been recorded at any time.
Conclusion Low SES is an independent risk factor for long-term risk of HF in men.
Key Words: Heart failure • Coronary disease • Socioeconomic status
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Background |
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Although new treatment modalities have improved survival in heart failure (HF), mortality is still high,1 and accordingly, it is important to identify risk factors that can be translated into primary prevention. Prior research has identified hypertension, coronary heart disease (CHD), diabetes, smoking, and obesity as important causes.2–7 Because CHD is a major cause of HF, CHD and HF have several risk factors in common. Low socioeconomic status (SES) is associated with an increased risk of CHD,8–10 but whether low SES is also a predictor of HF has not been well investigated. In Scotland, incident HF and deprivation were found to be related on a group level in a primary care population.11 A recent publication, also from Scotland, demonstrated a link between social deprivation, as defined from post-code area, and the risk of developing HF, irrespective of baseline cardio-respiratory status and cardiovascular risk factors.12 In a prospective study from the USA, men and women with HF had less education,5 but this was not significant in multivariable analyses. Thus, there is some evidence that socioeconomic status has an effect on HF, but there is still a lack of data focusing on the specific influence of individual SES on the risk of future HF. The aim of the present study is, therefore, to examine the longitudinal relationship between SES, defined by occupation, and risk of hospital discharge or death with a diagnosis of HF.
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Methods |
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Data were derived from participant men from the intervention group in the multifactor Primary Prevention Study which began in Göteborg, Sweden in 1970.13 All men in the city born between 1915 and 1925 (n=30 000), except those born in 1923 (because they were part of another study) were randomized into three groups of 10 000 men each. The men in one of the groups (intervention group; n=9998) were offered a medical examination to identify and treat risk factors. The intervention was essentially a high-risk strategy directed towards men with pronounced hypercholesterolaemia, severe hypertension, or heavy smoking habits, according to pre-defined criteria, with treatment offered at specialist clinics. The first screening examination included 7495 men (participation rate 75%) in the intervention group and took place between January 1970 and March 1973. During the first 12-year follow-up, there were no significant differences in risk factors or outcome with respect to cardiovascular disease, cancer, or all-cause mortality between the intervention and control groups.13 Thus, despite the fact that the men took part in an intervention study, we consider the study group to be representative of the general Göteborg male population. All participants gave their informed consent to participate in the study. The study was approved by the Ethics Committee for Medical Research at Göteborg University.
Information on occupation, smoking, physical activity during leisure time, hypertension, and diabetes mellitus was collected via a questionnaire mailed to all men in the intervention group. Occupation was used to classify men into five occupational classes and was coded according to the Swedish socio-economic classification system, Socio-Economic Index (SEI): (1) unskilled and semiskilled workers, (2) skilled workers, (3) foremen in industrial production and assistant non-manual employees, (4) intermediate non-manual employees, and (5) employed and self-employed professionals, higher civil servants, and executives.8 Of the 7495 men, 7404 men had no prior history of myocardial infarction or stroke, and of these, 6999 men could be classified into the SEI classification, forming the basis for the present study. The main reason for the absence of an SEI code was early retirement.
Screening examinations were done in the afternoon. Weight was measured in kilograms to the nearest 0.10 kg and height in meters to the nearest 0.01 m. Body mass index (BMI) was calculated as weight/(height)2. Blood pressure (BP) was measured to the nearest 2 mmHg after 5 min of rest, with the participant seated. Serum cholesterol concentration (from a sample taken after fasting for 
2 h) was determined according to standard laboratory procedures.
Smoking habits were defined using five categories: never smokers, former smoker of more than 1 month's duration, and current daily smoking of 1–14, 15–24, and 25 g or more of tobacco. One cigarette was considered to contain 1 g of tobacco; one cigarillo, 2 g; and one cigar, 5 g. Physical activity during leisure time was categorized into three levels: sedentary, moderate activity, and regular, strenuous activity for at least 2–3 h per week. Treatment for hypertension was defined as pharmacological treatment. Alcohol abuse was defined as registration with the Swedish Board of Social Welfare for medical or legal problems attributed to alcohol (for instance, drunken driving).14
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Follow-up |
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All participants in the multifactor Primary Prevention Study were followed from the date of their baseline examination until 31 December, 1998, using their unique personal identification number. A computer file of the men in the study was run against the Swedish National Register on Cause of Death and the Swedish Hospital Discharge Register. The hospital discharge register has operated on a nationwide basis since 1987, but all discharges from Göteborg hospitals have been entered in the national register since 1970 (except 1976, owing to a legislative change for that single year).6
HF and AMI diagnoses in Sweden according to the hospital discharge register have been validated. HF as the principal diagnosis was shown to have a validity of 95%, whereas HF in any position had a validity of 82%.15 Similarly, validation of CHD discharge diagnoses in Sweden demonstrated high sensitivity (94%) and a high positive predictive value (86%) with respect to definite AMI.16 For the purpose of these analyses, HF was defined as a discharge or death with a primary or secondary diagnosis code of 427,00 or 427,10 [International Classification of Diseases, eighth revision (ICD 8)], 428A, 428B, or 428X [International Classification of Diseases, ninth revision (ICD 9)], or I50 [International Classification of Diseases, 10th revision (ICD 10)]. Altogether, 1004 cases of HF were identified. In five cases, the HF diagnosis was based on a death certificate diagnosis only; all other cases had a hospital discharge diagnosis of HF.
For the purpose of identifying HF cases due to CHD, we categorized all cases with a discharge diagnosis of non-fatal AMI (surviving at least 28 days) or coronary revascularization, either before or at any time after a diagnosis of HF, as due to CHD. Non-fatal myocardial infarction was defined as discharge codes of 410 (ICD 8 and 9) or I21 (ICD 10). Coronary revascularization was defined as any discharge with operation codes of 3066, 3080, 3067, 3127, 3091, 3029, FNA, FNC, or FNG. Of the 1004 cases of HF, 460 had a CHD diagnosis; of these, 405 were diagnosed with CHD concomitant with or before being hospitalized with HF. HF cases dying with a death certificate diagnosis of CHD were not included into this category because we considered the diagnostic validity in cases dying with long-standing HF to be uncertain.
CHD as an outcome variable was defined in two ways: (i) all cases of either non-fatal AMI or revascularization (similar to the categorization used to define HF due to CHD); (ii) all cases of AMI or CHD death. CHD death was defined as any death with a diagnosis of 410–414 (ICD 8 and 9) or I20–I25 (ICD 10). Altogether, 1251 cases of non-fatal AMI or coronary revascularization were identified, according to the first definition, and 1663 cases of AMI or CHD death, according to the second.
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Statistics |
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All analyses were done using the SAS software version 8e. Baseline characteristics of the men in the study are summarized in terms of frequencies and percentages for the categorical variables, and differences in distribution across occupational class categories were examined by the use of Mantel–Haenzsel tests or trend tests, as appropriate. For continuous variables, Pearson's correlation tests were used. Of the 6999 men, 5995 men remained free of diagnosed HF, either as hospitalization or death, and all comparisons with respect to the development of HF are with this group. Prospective analyses were accomplished using Cox proportional hazards regression models to identify factors related to a hospital discharge or death with a diagnosis of HF. We considered, in separate analyses, (i) all men with HF; (ii) all men with a principal diagnosis only of HF; (iii) men with a diagnosis of HF, who at any time before or after their diagnosis had either had a non-fatal AMI or undergone a revascularization procedure; (iv) men with HF, who had not at any time had an AMI or undergone a revascularization procedure. Time at risk was calculated to first hospitalization with an HF diagnosis, to death, or to December 31, 1998. To measure the relationship between occupational class and HF, occupational class was entered in regression models as categorical variables, with the highest SES class as reference.
Univariate regression analyses were used to evaluate potential confounders of the occupational class—HF relationship. For comparison, univariate and multivariable analyses for CHD in relation to occupational class are also shown. Potential confounders for both HF and CHD included BMI, height, systolic BP, serum cholesterol level, smoking, sedentary leisure time, diabetes at baseline, and occupational class. Variables were included in final multivariable regression models if they met the criteria of P<0.15. Thus, the final regression models for HF, as well as for coronary disease, included age, smoking, physical activity, occupational class, diabetes mellitus, alcohol abuse, treatment for hypertension, BMI, height, systolic BP, and serum cholesterol level. In the multivariable analyses, age, BMI, systolic BP, and serum cholesterol were entered as continuous variables and all others as categorical variables. We checked the assumption of proportional hazards by entering in the Cox regression model time-dependent variables related to the factors we studied. The impact of these variables was not significant on the model fit, which indicates that the assumption holds.
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Results |
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Table 1 shows risk factors at baseline by the occupational class. Manual workers had a generally worse risk factor profile than non-manual working men, but the absolute differences were not large. Specifically, there were overall no differences in smoking (P=0.86). Unskilled workers had slightly higher mean BMI, systolic BP, and serum cholesterol and were on average 3 cm shorter in stature when compared with men who were high officials or professionals. Only 2% among the latter had been registered for alcohol problems, compared with 12% among unskilled workers.
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In longitudinal analyses, standard risk factors for coronary artery disease (CAD) also predicted HF (Table 2). Obese men (BMI
30 kg/m2), men in the highest quartile of systolic BP distribution, men with treated hypertension, and moderate-to-heavy smokers (15–24 g/d) all had approximately doubled hazard ratios (HR), compared with the reference for each of these variables. More moderate effects were seen for serum cholesterol and alcohol abuse. Being tall was associated with lower risk. The strongest risks were registered for heavy smoking [25 g/day or more; HR 2.81 (2.11–3.75)] and diabetes [HR 4.26 (3.13–5.81)].
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Compared with the highest occupational class, unskilled workers had an age-adjusted HR of 1.92 (1.50–2.45) of developing HF (Table 3). Semiskilled and skilled workers [HR 1.59 (1.25–2.03)] and lower officials and foremen [HR 1.62 (1.26–2.10)] had intermediate risks. Adjustment for other risk factors affected HR only moderately, with an adjusted HR of 1.72 for unskilled workers (1.34–2.20). If only cases with a principal diagnosis of HF were considered, results were essentially similar. Associations between HF and occupational class were slightly stronger among the men who at any time had been diagnosed with an AMI or had a revascularization procedure. The adjusted HR for unskilled workers was 2.06 (1.40–3.04) relative to high officials and professionals. The corresponding HR for HF without AMI or revascularization was 1.58 (1.14–2.18). The relation between occupational class and CHD was weaker, with multivariable HR of 1.25 (1.01–1.56) for non-fatal AMI and revascularization in unskilled workers, compared with that in high officials and professionals: 1.42 (1.17–1.72) for AMI, including CHD death.
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Discussion |
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The main finding of this study was the relationship between occupational class and a diagnosis of HF with a 72% increased risk in unskilled workers compared with high officials. This relation was independent of other risk factors and irrespective of concomitant coronary disease or whether HF was the principal diagnosis or not.
The strong similarity between risk factors for the development of HF and CHD is not unexpected because of the dominant role of CHD in the aetiology of HF in Western populations. Paradoxically, in patients with established HF, obesity, high BP, and elevated serum cholesterol are reported to be positive prognostic markers,17–18 probably because low levels are likely to herald the final stages of the disease.
Unskilled workers had an almost doubled risk of HF, compared with men in the highest occupational class. In the Cardiovascular Health Study, which investigated elderly US citizens, low education was associated with HF,5 but this association was not significant after adjusting for a number of covariates. However, they used a comparatively crude measure of education (high school graduate or not). In Scotland, sex- and age-standardized incidence of HF increased with greater deprivation on a group level in a population study including 307 741 men and women registered with general practitioners.11 Deprivation, as defined from area of residence, was found to be associated with an adjusted risk of admission for HF of 39% greater in the most vs. least deprived subjects in the Renfrew and Paisley study, whereas individually assigned SES, based on occupation, was a weaker predictor.12
Increased need for rehospitalization and worse symptomatology at admission has been found in patients with HF with low educational levels.19 Low income,20 deprivation,21 and lack of occupation22 were also associated with increased re-admissions for HF, whereas living alone was not related to risk for re-admission.22 However, marital status is associated with socioeconomic status and was found to be independently related to severity of illness.19
Because CHD is a condition with insidious onset, often with a long period without symptoms, CHD cases diagnosed after HF were also defined as being due to CHD. The relation between occupational class and HF was evident also in cases without CHD. However, with our definition, less than half, or 46%, had evidence of CHD. In the Euroheart Heart Failure Survey of hospitalized patients,23 which included angina among their criteria, 59% of the Swedish patients in the survey had evidence for CHD, similar to the proportion in the Framingham study,24 which means that the proportion of men with HF and concomitant CHD in the present study probably was underestimated. Accordingly, the increased risk of HF in men with low SES might reflect their increased risk of CHD. This issue is difficult to resolve because extensive coronary lesions may exist without chest pain. In order to exclude a diagnosis of CHD, a coronary arteriography would have been necessary. In an angiographic study, CHD was found to be the cause of 52% of incident HF, with a quarter of cases not recognized prior to the angiography.25 Even so, the fact that the inverse association between occupational class and CHD seemed to be less strong than for HF might indicate that the link between low SES and HF is not solely through CHD, but still, unrecognized CHD will have been present in a number of the HF patients of the present study. Our definition of CHD in HF did not include coronary deaths without prior AMI or revascularization because we were unsure of the validity of a CHD death certificate diagnosis in a patient with known HF. However, if these patients were excluded from the non-CHD group, results remained essentially unchanged, with a significant increase in risk for the two lowest occupational groups.
Men with low occupational status had higher BMI and systolic BP compared with men with higher SES, but absolute differences were comparatively minor, and the risk for HF associated with low SES was independent of potential confounders. Therefore, factors other than standard risk factors for CAD likely influence the risk for development of HF in low occupational classes, for instance dietary factors. Men in occupational class 1 were taller than men in occupational class 5, which may reflect nutritional status both during childhood and during the gestational period. Height was, however, only weakly related to HF in the present study and did not influence HR associated with low occupational class. Other potential explanations include differences in environmental factors (noise, chemical pollution) at work or in housing, sleep disturbances due to irregular hours or shift work, or psychological factors.
Limitations
Although our study points to a strong relationship between low occupational class and HF, there are potential limitations. First, our case ascertainment depended entirely on hospital diagnoses and, in rare cases, on HF as a cause of death. Milder cases not leading to hospitalization were not identified. The Framingham study, which used clinical criteria to define HF,7 found age-adjusted 10-year incidence rates of between 5 and 10%, which is comparable in absolute terms to what is found in the present study. Because their subjects were younger at the end of their follow-up than our subjects, however, the incidence in the present study is probably lower than might have been expected, if clinical criteria had been used.
Secondly, the HF cases in the present study could not be validated, or classified further, by examining the medical records. Echocardiographic or clinical data were not available. Even so, a recent validation study of the Swedish Hospital Discharge Data for HF showed excellent validity, particularly if HF was the primary diagnosis.15
Thirdly, only men who took part in the study, and who had an occupation, could be studied, or ~70% of the sample. The non-participants of the study had higher mortality and more alcohol problems.26 The occupation among non-participants could not be established, but it is unlikely that their inclusion in the study would have resulted in a weaker relation between HF and low occupational class.
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Conclusion |
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The central finding of the present study is that low occupational class was associated with increased risk for HF. Among the strengths of this study are the extended follow-up that was virtually complete for the endpoint under study, the large number of endpoints, and the high participation rate. The methods that we used will have underestimated the true prevalence of HF to an unknown degree, although it is probable that most cases were identified. Bearing these limitations in mind, the results of the present study indicate that additional efforts should be made to identify the factors associated with low occupational class, which cause CHD and HF.
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Acknowledgements |
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The statistical help and expertise of Mr George Lappas (BA), Sahlgrenska University Hospital/Östra, Göteborg, Sweden, is gratefully acknowledged. The study was funded by the Swedish Research Council and the Swedish Heart and Lung Foundation, both Stockholm, Sweden.
Conflict of interest: none declared.
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