摘要：Objectives. We examined the associations between socioeconomic position, co-occurrence of behavior-related risk factors, and the effect of these factors on the relative and absolute socioeconomic gradients in coronary heart disease. Methods. We obtained the socioeconomic position of 9337 men and 39 255 women who were local government employees aged 17–65 years from employers’ records (the Public Sector Study, Finland). A questionnaire survey in 2000–2002 was used to collect data about smoking, heavy alcohol consumption, physical inactivity, obesity, and prevalence of coronary heart disease (myocardial infarction or angina diagnosed by a doctor). Results. The age-adjusted odds of coronary heart disease were 2.1–2.2 times higher for low-income groups than high-income groups for both men and women, and adjustment for risk factors attenuated these associations by 13%–29%. There was no further attenuation with additional adjustment for the number of co-occurring risk factors, although socioeconomic disadvantage was associated with the co-occurrence of multiple risk factors. The absolute difference in coronary heart disease risk between socioeconomic groups could not be attributed to the measured risk factors. Conclusions. Interventions to reduce adult behavior-related risk factors may not completely remove socioeconomic differences in relative or absolute coronary heart disease risk, although they would lessen these effects. Coronary heart disease (CHD), a leading cause of morbidity and mortality in all Western countries, is more prevalent among lower socioeconomic position (SEP) groups than among groups that have higher SEP. 1 – 7 Although the evidence of such a socioeconomic gradient in CHD is robust, the extent to which this gradient is the result of different distributions of coronary risk factors between SEP groups remains controversial. Several epidemiological studies suggested that most (60%–95%) of the CHD burden can be attributed to established risk factors: smoking, hypertension, diabetes, unfavorable cholesterol profile, and physical inactivity; appropriately, public health interventions target these risk factors to reduce the CHD epidemic. 8 – 13 However, several studies that compare the magnitude of the socioeconomic gradient before and after adjustment for these risk factors suggest that they explain only 15%–40% of the association between SEP and CHD. 7 – 14 Thus, the contradiction: most of the population burden of CHD can be attributed to established risk factors, but these same risk factors only explain a small part of the association between SEP and CHD. We raise the possibility that multivariable adjustment for risk factors may not have correctly estimated the contribution of these risk factors to SEP differences in the occurrence of CHD. 12 , 15 , 16 In the most commonly used approaches, such as logistic regression and proportional hazards regression, risk factors are entered into the model to examine how they change the effects of SEP indicators on CHD. 14 Any change in the effect estimate of SEP’s effects on CHD after adjustment for these risk factors is then used as an indication of the extent to which the risk factors “explain” the relative socioeconomic gradient in CHD. Underestimation might result from the failure of such models to fully account for clustering of individual risk factors. The overall effect of the risk factors would be underestimated if they were clustered (i.e., there was a greater than expected number of persons with either no risk factors or many risk factors), and this clustering was substantially more common in low- than high-SEP groups. 17 Underestimation can also occur if the risk factors have synergistic effects (i.e., the effect of combined risk factors exceeds the predicted effects from separate risk factors, which assumes independence within the particular multivariable model). 18 In most studies, the effect of synergism is examined by including interaction terms, but then removing them from the final model if the associated P value is large (conventionally >.05). However, most studies have a limited ability to detect multiple statistical interactions, and very large data sets are required to examine this possibility. Multivariable adjustment may underestimate the effect of established risk factors when explaining most of the “excess” cases among the lower SEP groups (i.e., the effect of established risk factors on the absolute risk difference between SEP groups). A recent study of 2682 Finnish men in the Kuopio Ischemic Heart Disease Risk Factor Study found that although adjustment for smoking, hypertension, dyslipidemia, and diabetes resulted in a modest (24%) attenuation of the relative socioeconomic gradient of CHD risk, these same risk factors accounted for most (72%) of the absolute socioeconomic gradient, that is, the excess risk among those from the lowest SEP compared with those in the highest. 19 The role of behavior-related risk factors in CHD, particularly those that might be modified through health promotion, is likely to lead to important policy implications. We used a large employee sample of people who were participating in the Finnish Public Sector Study 20 , 21 to examine the associations between SEP, co-occurrence of behavior-related risk factors (smoking, physical inactivity, obesity, and heavy alcohol consumption), 8 , 11 , 22 – 25 and the effect of these factors on the relative and absolute socioeconomic gradients in CHD.
