1 Copenhagen Centre for Prospective Population Studies, Danish Epidemiology Science Centre at the Institute of Preventive Medicine, H:S Kommunehospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
2 Copenhagen Centre for Prospective Population Studies at the Institute of Public Health, Copenhagen University, Copenhagen, Denmark.
3 Centre for Alcohol Research, National Institute of Health, Svanemøllevej 25, DK-2100 Copenhagen, Denmark.
Correspondence:
Ingelise Andersen, Institute of Preventive Medicine, Danish Epidemiology Science Centre, H:S Kommunehospitalet, DK-1399 Copenhagen, Denmark. E-mail:
ia{at}ipm.hosp.dk
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Abstract |
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Methods We used data from two prospective population studies conducted in Copenhagen. A total of 22 782 subjects, 54% women, with initial examination between 1964 and 1992 were followed until 1996 for hospital admission or death from IHD. We performed survival analyses, taking traditional cardiovascular risk factors into account, and estimated IHD-free life expectancy by household income in men and women.
Results During follow-up, 1803 men and 1258 women experienced an event of IHD (21% fatal). The hazards by deciles of income showed a non-linear graded inverse effect of income, with a large group of middle-income in which income was not associated with risk of IHD. The hazard ratio for highest versus lowest deciles was 0.53 (95% CI: 0.440.65). The association was attenuated by adjustment for risk factors, but remained statistically significant. The associations were similar for both sexes. Median IHD-free life expectancy for low-income versus high-income groups was reduced by 9.4 and 7.0 years in men and women, respectively.
Conclusions The effect of household income on risk of IHD was graded and similar for men and women. The difference between high and low income, regarding IHD-free life expectancy, was considerable.
Accepted 15 July 2002
The inverse relation between socioeconomic position and ischaemic heart disease (IHD) is well documented among men in the Western world.13A few studies have suggested that, compared with men, women exposed to socioeconomic disadvantage have higher risks of developing IHD4 whereas others have found smaller5 or similar gradients.68 Thus, whether the impact of social position on IHD risk is similar for men and women has yet to be determined. In addition, it remains a matter of debate whether the relation between income and IHD is explained by differences in lifestyle factors.915
That most studies use education and/or occupation as a proxy for socioeconomic position could explain the divergence of study results. The substance and value of education may differ between men and women, and these measures might therefore not describe socioeconomic position equally well in the two sexes. Correspondingly, the same occupation may behave differently as a variable in men versus women.16
Fundamental changes have influenced family structures in the Western world since the middle of the 20th century. Most important has been the growing participation of women in paid employment, resulting in more equal opportunities for men and women. These changes occurred more rapidly in Denmark than in any other European country,17 and Danish and Finnish women have the highest rate of full-time employment in the EU.18,19
Most previous studies have taken place in the USA and GB: liberal welfare states characterized by modest social insurance schemes and less support for womens participation in the labour market and, hence, more dependence on male breadwinners. Whether men and women live in comparable conditions in these societies is debatable. Even in a Danish welfare society with relatively equal opportunities for education and labour, there are nevertheless gender differences associated with these variables.
Income is a quantitative measurement without the conceptual and qualitative problems associated with education and occupation. Purchasing power is, in principle, independent of how income is generated, and the social position associated with income is probably similar for men and women.
The aim of this prospective Danish study is to analyse the effect of gross household income (HHI) on incidence of IHD at the individual level, taking traditional cardiovascular risk factors into account, with special attention to the gender perspective. Since the study is conducted in a welfare state with high full-time employment status among women, it may be especially effective in demonstrating gender differences in the relationship between social position and IHD.20
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Material and Methods |
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The CCHS comprised 14 119 randomly selected men and women, aged 20+ years, from a defined area of central Copenhagen. The subjects were examined initially between 1976 and 1978. Between 1981 and 1983, the subjects were re-examined and 1560 new subjects were included. The CCHS thus consisted of 15 679 subjects.
The GPS have, since 1964, followed different birth cohorts in the populations of selected Western suburbs of Copenhagen, which, during the study period, have changed from partly rural to almost exclusively suburban residential areas. Three of these cohorts are part of the MONICA (MONItoring Trends and Determinants in CArdiovascular Diseases) investigations. All cohorts had a similar distribution of men and women. For this study we used data from different cohorts born between 1897 and 1962 and examined between 1964 and 1992. The GPS population consisted of 10 092 subjects.
Data collection
In 2000, the study population was linked to those Registers in Statistics Denmark containing socioeconomic information, using the personal identification number as a key. Information on housing, income, occupation, and education were obtained for study participants and cohabitating adults for the years 1980, 1985, and 1990. The present study used data from the year prior to the baseline examination.
Measures of individual income
Information on gross annual income was obtained from the Register of Income Statistics for each study participant and his or her cohabitant. Household income (HHI) comprises all income types subject to income taxation (wages and salaries, all types of benefits and pensions, net surplus or deficit, interest received and share dividends). Information on cohabitation status was derived from Registers with socioeconomic information in Statistics Denmark.
We calculated HHI as the sum of participants and cohabitants gross income. Income was corrected for inflation since 1980 using the apposite components from the Statistics Denmark price index. Income is expressed in 1995 prices. Denmarks mean HHI in 1995 was 247 700 DKr.21 The rate of exchange that year was 10 Danish crowns (DKr.) for 1.8 USD.21
Other covariates
Standard risk factors were assessed for each participant at the baseline survey by a self-administered questionnaire covering well-known lifestyle risk factors, as well as a large number of health-related items. Although phrasing of questions differed in various sub-cohorts it has been possible to maintain sufficient consistency in the covariates used for this investigation.
Smoking behaviour was determined using questions to categorize smokers according to present tobacco consumption. Current smoking status was categorized into five groups according to rate of tobacco consumption, but regardless of inhalation and type of tobacco (never, ex, 114, 1524, 25 g/day). Alcohol intake was categorized into six groups (<1, 16, 713, 1427, 2841, >41 drinks/week). Physical activity in leisure time was divided into three groups, measured in hours per week (none/little, moderate 24 h, moderate >4 h/hard work 24 h/ competition >4 h).
The participants were also given a health examination with anthropometric measurements and various laboratory tests. Body mass index (BMI) was calculated as weight (kg)/height (m)2, based on data collected by trained nurses. In the present study, BMI was categorized into five groups (<22, 2224, 2527, 2832, >32). Systolic blood pressure (SBP) and blood lipids measured as total cholesterol were divided into quintiles within cohorts, in order to avoid systematic errors in measurement between cohorts. Self-reported diabetes mellitus (DM) was categorized as yes/no.
Information on risk factors was given at the first examination. No control for changes in income-level or risk factors during follow-up was attempted in the main analysis. In order to account for misclassification from changes in covariates over time, however, we conducted a sensitivity analysis with only 5 years follow-up.
Follow-up
The subjects were examined during 19641992, and were followed-up on morbidity and mortality until 31 December 1996. The first linkage between study population and information on socioeconomic factors was 1980. Consequently, the follow-up started in 1980 or at study entry, whichever was latest, and subjects who died prior to this date were excluded. Information regarding HHI was only available for selected years beginning in 1980. Subjects included before 1980 could thus have a gap of up to 16 years between first examination and register information on income. Figure 1 illustrates the time-gap between first examination and register information for the different sub-cohorts. As shown in Figure 1
, there were only 894 subjects included before 1967. For the rest of the study population the time-gap was minor and consequently resulted in no significant limitations to the study design.
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The combined study population study comprised 25 771 subjects, with 7846 non-participants (participation rate 77%). A total of 2989 subjects were excluded due to lack of information of the following key variables: death before 31 December 1980 (1080 subjects); emigration before 31 December 1980 (22 subjects); IHD before 31 December 1980 (523 subjects); and missing information on blood pressure, cholesterol, BMI, tobacco, physical activity, income, education, (in total 1364). This resulted in a study population of 22 782 subjects, 12 210 women and 10 572 men, equal to 88% of the investigated population and 68% of the invited population.
Statistical methods
The association between risk factors and incidence of IHD was analysed using Coxs proportional hazards regression models with age as underlying time scale. A basic Cox model was developed which included the two variables HHI and cohort of investigation. The HHI was main variable of interest. A second series of models included the risk factors tobacco, alcohol, physical activity in leisure time, SBP, cholesterol, BMI and DM. Risk factors were entered as categorical covariates as described above. In the initial analyses each confounder was controlled for separately before performing multivariable adjustments as reported. The proportional hazards assumption was evaluated for all variables by comparing estimated log-log survivor curves over the different categories of variables being investigated, and by tests based on the generalization of Grambsch and Therneau.23 All covariates were tested for interaction with HHI by means of the likelihood ratio test. Initially, all survival analyses were carried out separately for women and men. If the associations were similar, analyses were in some cases repeated on the pooled data, stratified by sex.
We also applied standard life-table techniques. Subjects were included in the life-table at age 35. The survival time was defined as time until first IHD, whether fatal or non-fatal. Subjects were censored at the time of their death, if not from IHD, or at the end of follow-up. Statistical analysis was performed using STATA for Windows version 7.24
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Results |
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In order to test any influence of the changing role of gender, the effect of birth cohort was examined by performing separate analyses on subjects born before and after 1930 (Table 3). In both men and women, hazard ratios were higher for subjects born after 1930, but the difference was not statistically significant. (Likelihood-ratio test for interaction between HHI and birth cohort, 3 d.f., P = 0.75 in men and P = 0.17 in women.) Analysis of pooled data of men and women showed no gender difference in associations for subjects born before 1930 versus after 1930. (Likelihood-ratio test for interaction between HHI and sex, 3 d.f., P = 0.94 in subjects born before 1930 and P = 0.94 in subjects born after 1930.)
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Since both income and other cardiovascular risk factors may change during follow-up, and hence disturb the results due to misclassifications in covariates over time, analyses were repeated including only the first 5 years of follow-up. During 5 years follow-up, 1045 people experienced an IHD event: 674 men and 371 women. The multivariate HR for low-income was 1.21 (95% CI: 0.751.21) for women and 1.51 (95% CI: 1.072.12) for men. Comparing these figures to Table 2 demonstrates that differential changes in covariates over time do not explain the income gradient.
The difference in the probability of IHD-free survival is shown for high-income (>400 000 DKr.) and low-income (<75 000 DKr.) for both sexes (Figure 3). Of women alive at age 35, an estimated 64% (95% CI: 6067) of high-income women would be alive and free of IHD causing hospitalization and/or death at age 75, compared with 44% (95% CI: 3949) of low-income women. Corresponding prospects for men would be 43% (95% CI: 4046) and 18% (95% CI: 1422), respectively. The difference in the median IHD-free survival between high- and low-income was 9.4 years in men and 7.0 years in women. In addition to the difference in median survival, the figures also give the difference in IHD-free life span for 25th and 75th percentiles. The difference in survival between high- and low-income groups remained stable at approximately 9 years among men, whereas among women the difference seemed to decrease from 10.7 years to 4.3 years between 25th and 75th percentile.
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Discussion |
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There are, however, limitations to the study. During the study period, women became increasingly economically independent of their husbandsalthough womens mean income is still lower than that of men. In order to see if these changes influenced the results, we carefully examined associations for gender, birth cohort, age, and cohabitation, but the results were very stable.
Another limitation is the possibility of residual confounding. We corrected for inflation, but any changes in individual income levels during follow-up were not accounted for. Hence, we failed fully to capture health effects of sustained exposure to low income, or to account for transitions into and out of low-income groups. Further, our study does not include early factors in life, such as low birthweight, which have been associated with socioeconomic position and IHD later in life. Nor did we account for changes in cardiovascular risk factors. Although smoking is a major risk factor for development of IHD, and, since smokers in a higher social position are more inclined to quit smoking,25,26 not controlling for cessation during follow-up would result in overestimation of the social differences in IHD risk. On the other hand, using a Poisson regression with 5-year age bandswhich gives results comparable with the Cox regression presentedwe found that the difference in hazard ratios between highest and lowest income groups would be levelled out if at least 50% of the person years among high-income, female heavy smokers without IHD were due to quitting misclassification. For men, the misclassification proportion was 33%.27 In other words: if differentials in smoking cessation were to explain the gradient found, then all female heavy smokers in the high-income group would have to quit for half of the follow-up, versus none of the female heavy smokers in low-income groups. Since smoking represents one of the major risk factors for IHD, we argue that any change in another of the traditional risk factors would not be able to explain the income differences in IHD in the present study either. Nor did analyses with only 5 years follow-up show that differential changes in covariates over time would explain the income gradient. Some residual confounding due to increased social differences in traditional risk factors during follow-up, however, cannot be ruled out.
Our results indicate that the pathways between income and health are similar for both genders. Similar patterns for coronary heart disease in relation to social class for men and women have also been demonstrated in other Nordic studies.7 Dissimilarities between genders in studies from other Western countries could be due to the income indicator chosen.4,5 When gender is taken into account, womens employment grade influences the choice of income indicator used. One study recommended the use of household equivalent income if most of the women were employed part time.20 Since most of Danish women are employed full-time, we have chosen gross household income (HHI), which gives a comparable picture of the basic economic and social situation of the household.
The only gender difference we find is among retired people, where the social difference among women almost disappears. One possible explanations for this difference could be that income among older (women) is a less-sensitive measure of their socioeconomic position28 as they have often been dependent on male breadwinners. Another possible explanation is that retired high- and low-income women, who mostly have not had full-time employment, may still have had social relations that remain stable after age 67, and which counteract the effect of social position.
The main question is whether low income in itself represents a risk factor for IHD. Income relates directly to the material conditions that may influence health. Material factors are biologically plausible as causes of IHD, because low-income groups have fewer possibilities for success in terms of quality of housing, variety in diet and group-based physical activity.29 Moreover, early life circumstances, such as slow growth in uteri and low birthweight, which according to the Barker hypothesis influence risk of IHD, are more common among low-income groups.30 The increased risk of IHD in low-income groups could be due to accumulation, over the life course, of negative exposures and lack of individual resources such as economic surplus and the means for social participationwhich results in stress and poor health.31 These shortcomings may, in turn, be explained by insufficient material conditions.32
Many of the negative exposures have been related to lifestyle factors, and some studies have shown that the association between low socioeconomic position and increased risk of IHD could be explained by well-known cardiovascular risk factors.9,10,12,14 In the present study, however, adjustment for risk factors had only moderate impact on the magnitude of the inverse association between income and IHDsimilar to other studies.11,13 Other negative exposures could be related to the tendency among low-income individuals to earn their living by hazardous occupations or in jobs characterized by negative organizational, physical, psychological, and social aspects. These factors are also associated with an increased risk of IHD.15
Studies have shown that even in countries in which basic material needs are met, each step up the income ladder seems to improve individual states of health.28 The lack of decreased risk in the large middle-income group in our study could be due to the fact that the study is conducted in a welfare society with rather fair distribution of public resources that influence health. Other considerations must also be taken into account. It might be questioned whether income is a proxy in itself or if the association between income and IHD merely reflects the possibilities linked to education and occupation. Our preliminary analyses showed that education, occupation, and HHI all explain some of the social gradients, but they were not mutually exclusive: a result in accordance with other studies.33 Social position measured by education and occupation might reveal a gradient in health in the large middle-income grouppossibly dissimilar for the two genders.
Another way of illustrating the relation between socioeconomic position and health is by looking at lost years of expected life. This is done in studies on tobacco use showing that heavy smokers, compared with non-smokers, lost more than 9 years of median life-expectancy.34,35 These studies examined all-cause mortality. In the present study we looked at lost years of expected IHD-free life and found that the risk of IHD affected the survival prospects for both sexes; even the difference in survival between high- and low-income among men was independent of age, whereas it diminished with age among women. This finding is concordant with the lack of association between HHI and IHD in older women in the survival analyses. The survival curves illustrate that the impact of social inequality, measured by life-years lost, was considerable even in a welfare society. To our knowledge, no other study has measured the consequence of low income in life-years free of IHD.
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Conclusion |
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KEY MESSAGES
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Acknowledgments |
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References |
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