Introduction

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The idea that income inequality may be associated with health and mortality has attracted considerable research interest.^1-3 Several ecological studies using different income distribution measures have shown that higher levels of inequality in income among states^4-7 or cities ^{8 9} in the United States are associated with higher all cause mortality, whereas in Canadian states and cities income inequalities are smaller and not associated with mortality.⁹ In a few cross sectional studies, income inequality at state or county level in the United States has also been associated with coronary risk factors¹⁰ and poor self rated health after adjustment for individual socioeconomic status and income. ^{11 12} It has therefore been suggested that areas with an unequal income distribution are less likely to invest in health and more likely to have a psychosocial climate that is damaging to health.¹³

Only a few prospective studies, all from the United States, have examined whether area income inequality is related to individual health outcomes. Fiscella and Franks found that income inequality at community level did not predict all cause mortality after control for individual income,¹⁴ whereas other studies have suggested an effect in different subpopulations.^15-17 These relations are likely to differ among other Western countries too, but to our knowledge no studies have examined whether area based measures of income inequality predict all cause mortality after adjustment for individual income and other risk factors in a society outside the United States.

We analysed whether income inequality at the parish level predicted increased mortality after adjustment for individual income and standard risk factors in a society built on the Nordic welfare model.

	Methods

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Participants
The study is based on data from two longitudinal population studies conducted in Copenhagen. The Copenhagen city heart study comprised 14 223 randomly selected men and women aged 20 years or more from a defined area of central Copenhagen in 1976-8¹⁸; in 1981-3 and 1993-4 the participants were re-examined and 3816 new participants were included. The Glostrup population study examined and followed, between 1964 and 1992, 10 092 participants from different birth cohorts (born during 1897-1962) in selected western suburbs of Copenhagen.¹⁹ Of 35 977 adults originally invited to join these two studies, 7846 had not taken part (response rate 78%). Our study is therefore based on a combined population of 28 131 adults (14 723 women).

We obtained information on housing, income, occupation, and education from Danish registers (see below) for 25 728 participants (13 710 women), and our analyses are based on these individuals.

Measures of individual income
Every inhabitant in Denmark aged more than 15 years is classified annually according to income and wealth in the register of income statistics held by the organisation Statistics Denmark.²⁰ For each participant and cohabiting partner we obtained information on gross income and calculated the household income as the sum of the individual's and his or her cohabitant's gross income. The gross income comprises all income types subject to income taxation.²¹ We corrected income for inflation since 1985 using the price index in the Statistics Denmark register. They are expressed in 1995 prices, and a conversion rate of Kr10 to £1 was used.

Measures of income inequality in area of residence
In each of the 149 parishes analysed we used the median share of income estimated as the proportion of total household gross income earned by the poorer 50% of the households in the area, ^{8 14} calculated for the total population. The mean median share of income within the parishes was 22.7% (median 22.8%; range 13.9-30.3%).

Other covariates
Standard risk factors were assessed for each participant at baseline by a self administered questionnaire and a health examination. We calculated body mass index as weight(kg)/(height(m)²). We categorised participants as non-smokers (never or former smokers) and smokers and classified alcohol consumption according to average daily intake (<1 drink, 1-2.9 drinks, 3-5.9 drinks, 6-10.9 drinks, 11 drinks); one drink contained 9-13 g alcohol. We categorised physical activity in leisure time as sedentary (<4 hours of activity a week) or active (>4 hours a week). We categorised educational level according to years of schooling (<8 years (completed primary school); 8-11 years; and >11 years).

Follow up
Participants were followed from 1980 until 31 October 1999 for total mortality in the national central person register (mean follow up 12.8 years).

	Results

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Compared with participants living in parishes with a more unequal income distribution, those in parishes with the most homogeneous income distributionnamely, the highest quarterhad higher income levels both at individual and area level; were younger; had a higher proportion of men and of cohabiting partners with children (both at individual and area level); and had lower proportions of smokers, people with sedentary leisure time, and people with less education (table 1).

In total, 3460 women and 4107 men died during follow up, and age standardised mortality was highest in the parishes with the least homogeneous income distribution. Mortality among the participants in the lowest quarter of household income was significantly higher than among those in the highest income quarter. This ratio was not modified by the level of income inequality of the area (table 2). In the Cox regression analyses, area income inequality was not associated with mortality in women before or after adjustment for other risk factors (table 3). Men in the areas with most equality had lower mortality than those from areas with least equality, but the relation vanished when individual income or other risk factors were included in the model. In both men and women those with highest level of income had lowest mortality. Area income inequality did not predict mortality in any quarter of individual income.

	Discussion

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This study showed no association between income inequality at parish level and all cause mortality either in women or (after adjustment for individual income or other risk factors) in men, but it confirmed the well established inverse relation between individual income and mortality.

To compare our findings with previous studies we used gross income (including pensions and benefits)that is, income before taxation. As the Danish taxation system aims at levelling out extreme incomes, gross income indicates a wider income disparity than actually exists, but since the ranking of areas is not influenced this is unlikely to affect the risk estimates. The rates of inequality in the parishes in Copenhagen city were similar to those reported from US communities¹⁴ and cities,⁸ and in accordance with most ecological studies we found that areas with least equality had highest mortality at the aggregate level. Our study also supports Fiscella and Franks's finding that area income inequality is not in itself associated with all cause mortality,¹⁴ as adjustment for individual income made the apparent effect disappear. Contrary to three other prospective studies, ^{15 16 17} we found no relation between area income inequality and mortality in any subgroups defined by sex, age, or income. One of the concerns about Fiscella and Franks's finding is that they used a level of aggregation that was too small to allow income distribution to exert an effect independent of individual income.¹² It has been suggested that the level of geographical aggregation influences the pathways through which income inequality affects individual morbidity risk.¹¹ At higher levels of aggregation there are independent effects of income inequality, whereas at lower levels of aggregation income inequality is mediated by neighbourhood consequences of income inequality and individual process.¹¹ Our level of aggregation was low, but it was higher than the local area level used in the study by Soobader and LeClere, which showed an independent effect of income inequality on self rated health.¹¹ This supports the suggestion that the level of geographic aggregation needs further investigation.¹

Three main interpretations have been proposed to explain the mechanisms behind the effects of income inequality on health: the individual income interpretation, the psychosocial environment interpretation, and the "neomaterial" interpretation.¹³ The latter comprises a combination of negative exposures and lack of resources by individuals, along with systematic under-investment across a wide range of societal infrastructures. Lynch et al stated that "an aggregate relation between income inequality and health is not necessaryassociations are contingent on the level and distribution of other aspects of social resources."¹³ One explanation of our findings is that the Danish welfare system evens out the effects of many of the infrastructural components that are included in the complex mechanism linking area based inequality and health. For example, Danish housing policy ensures that even those relying on social welfare payments have access to housing in affluent as well as poorer areas. This contributes to greater economic variation in areas that would otherwise have had high average incomes and more equal income distributions. Consequently, we see what seem to be areas of high inequality of income that in fact have many features in common with high income areassuch as parks, playgrounds, and low crime rates. It is therefore debatable whether measures of such income inequality are adequate in the Nordic welfare states because income distribution is not linked to many other aspects of social infrastructure that are important for public health. The three main interpretations of the mechanisms at stake need further investigation; comparative studies would be valuable but should involve only countries that are comparable.

	Acknowledgments

We thank John Lynch for valuable comments on the interpretation of the results.

	Footnotes

Funding: Danish Heart Association and Danish Research Council.

Competing interests: None declared.

The full version of this article appears on bmj.com

	References

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(Accepted 4 June 2001)