Original reportsMaterial and Behavioral Factors in the Explanation of Educational Differences in Incidence of Acute Myocardial Infarction: The Globe Study
Introduction
There is substantial evidence of socio-economic inequalities in incidence and mortality from coronary heart diseases (CHD) in general 1, 2, 3, 4, 5 and acute myocardial infarction (AMI) in particular 6, 7, with higher rates in lower compared to higher socio-economic groups. The intriguing question how these inequalities can be explained has been subject of a number of studies. Higher prevalence of biological and behavioral risk factors of AMI in lower compared to higher socio-economic groups was found to contribute substantially to the inequalities, but cannot explain them entirely (2). Other identified explanatory factors include material living circumstances, psychosocial factors, factors early in life, access to health care, and environmental factors 8, 9.
To fully understand the mechanism underlying inequalities in AMI, these factors should preferably all be included in explanatory research. However, they are not mutually exclusive: there is a complex interrelationship between the factors. Currently, only a limited number of studies included several groups of explanatory factors, while taking into account their interrelationship.
As mentioned above, unhealthy behavior is more prevalent in lower compared to higher socio-economic groups. Differences in health-related behavior between socio-economic groups however, may at least partly be the result of differences in material living circumstances. Several studies have shown an association between unemployment, financial problems and feelings of deprivation on the one hand and smoking and excessive alcohol consumption on the other hand 10, 11, 12, 13, 14. These findings suggest that these forms of behavior may be a strategy to cope with living in worse material circumstances. Further, limited sports participation in lower compared to higher socio-economic groups may perhaps be partly caused by financial restraints in the prior group (15). Hence, there may be an overlap between the two groups, consisting of the contribution of differences in behavioral factors, which are the result of differences in material factors (Figure 1, Group B).
On the one hand, quantifying this overlap provides important information on the mechanism through which material factors contribute to inequalities in incidence of AMI. On the other hand, it provides valuable information for the development of behavioral interventions aimed at reducing inequalities in the incidence of AMI. Worse material living circumstances may increase the incidence risk of AMI through other than behavioral pathways. The “direct contribution of material factors” (Figure 1, Group C) includes these non-behavioral pathways through which material factors are related to the incidence of AMI. For example, worse material living circumstances may be associated with unfavorable psychosocial factors and these latter factors may increase the risk of AMI in the absence of an association with unhealthy behavior (16). Finally, unhealthy behavior will not exclusively be the result of living in unfavorable material factors. According to the psychosocial theory of health-related behavior, attitudes, social norms and self-efficacy predict the behavioral intention, and these three aspects may be determined by other factors than material deprivation (17). The “independent contribution of behavioral factors” (Figure 1, group A) reflects predictors of health-related behavior, as far as they are not the result of dealing with the consequences of material living circumstances.
In the present study, we aimed to quantify the contribution of: a) worse material living circumstances; and b) more unhealthy behavior in lower compared to higher educational groups to inequalities in the incidence of AMI. In addition, we aimed to quantify the contribution of behavioral factors to these educational inequalities, which are the result of differences in material living circumstances.
Section snippets
Study Design
Data are used from the Dutch GLOBE-study, a prospective cohort study carried out in the Netherlands since 1991. The study aims at explaining socio-economic inequalities in health. The rationale for and design of the study have been presented elsewhere (18). Briefly, a sample of 27,070 non-institutionalized subjects, aged 15–74 years, was randomly drawn from 18 population registers in the southeastern part of the Netherlands and asked to participate in the study. The response rate was 70.1% and
Results
A total number of 235 first AMI were identified. Table 1 presents the association between educational level and the incidence of AMI. The hazard ratio was significantly higher in subjects in the lowest compared to those in the highest educational group (HR = 1.85; 95% CI = 1.19; 2.88).
All four behavioral factors contributed significantly to a model containing the confounding variables (Table 2). An increased hazard ratio of AMI was found for total abstainers (HR = 2.08, 95% CI = 1.36; 3.17) and
Discussion
We found that the effect of living in worse material circumstances contributed more than the effect of unhealthy behavior to the explanation of educational differences in the incidence of AMI. We also showed that a substantial part of the contribution of unhealthy behavior to the educational inequalities was due to differences in material living circumstances between higher and lower educational groups.
Several methodological problems need to be taken into account in interpreting our findings.
Acknowledgements
The GLOBE study is carried out by the Department of Public Health of the Erasmus University Rotterdam, in collaboration with the Public Health Services of the city of Eindhoven and region SouthEast Brabant. The authors are indebted to Michel Provoost, Ilse Oonk, and Roel Faber for constructing the database and the participants for their willingness to participate in the study ever since 1991.
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