Income inequality and mortality in England. Debbie Stanistreet, Alex Scott-Samuel and Mark A. Bellis. Abstract. Background Despite the increasing evidence that ...
Journal of Public Health Medicine
Vol. 21, No. 2, pp. 205–207 Printed in Great Britain
Income inequality and mortality in England Debbie Stanistreet, Alex Scott-Samuel and Mark A. Bellis
Abstract Background Despite the increasing evidence that income inequality causes reductions in life expectancy in developed countries, this relationship has not been explored in the United Kingdom, where local income data are not routinely available. We have surmounted this problem by employing an ecological design which applies national income data to local mortality and occupational data. Methods This ecological, cross-sectional study used 1991 mortality and Census data on the 366 English local government districts, and 1991 New Earnings Survey data for England, to determine the independent effect of income inequalities within English local authorities on the variation in all cause mortality between them. The subjects were all men and women recorded as economically active in the 1991 Census. We carried out linear regression analyses between all cause, all ages standardized mortality ratios, income inequality indexes and mean income levels of the local government districts. Results Both income inequality and mean income were independently associated with mortality. Conclusions It is likely that income inequality makes an independent contribution to life expectancy in English local authorities. This finding adds further to the international evidence supporting the potentially positive health impact of increasing the scale of redistributive fiscal policies. Keywords: income, inequality, mortality
Introduction Recent research on the causal association between poverty and ill-health has focused on the role of income distribution, and in particular on the extent of income inequality, in causing reductions in overall life expectancy in developed societies. There is increasing evidence to support the view that income inequality is an important determinant of variations in average life expectancy at birth between developed regions or countries.1–4 The Independent Inquiry into Inequalities in Health5 concluded that ‘available evidence is insufficient to confirm or deny a causal relationship between changes in income distribution and the parallel deterioration in inequalities in some areas of ill-health. Nevertheless, we take the view that these changes are likely to be related.’ On this basis the Inquiry included in its three chief recommendations the adoption of ‘policies which will further reduce income inequalities’.
Although previous work has demonstrated associations between mortality in English local authorities and variations in deprivation between their constituent electoral wards,6 the unavailability of routine income data has restricted the opportunities for directly examining the relationship between income inequality and mortality in the United Kingdom. We have analysed the variance in mortality in English local authorities to determine the independent effects of mean income and of income inequality.
Methods Reliable mean income and within-district income inequality levels have been calculated for the 366 English local authorities by Gordon and Forrest.7 Mean income was calculated by multiplying the number of men and women in each of the 77 occupation categories used in the 1991 Census by the national average weekly full-time earnings of that occupation as recorded in the 1991 New Earnings Survey. Adjustments were made for those in part-time work, on government schemes or unemployed. The total figure was then divided by the economically active population to give the mean estimated income from earnings. The income inequality index was calculated as the squared coefficient of variation, employing Gordon and Forrest’s adjusted formula j2/ 2m2, where j is the standard deviation of estimated income from earnings and m is the mean estimated income from earnings.7 It has been assumed that the generally consistent nature of regional variation in earnings between occupations means that this factor does not substantively affect the scale of local income inequality. All cause, all ages standardized mortality ratios (SMRs) for each local authority were obtained for 19918 and a multivariate general linear model9 was used to distinguish the independent effects of mean weekly income and income inequality index on SMR.
Department of Public Health, University of Liverpool, Whelan Building, Quadrangle, Liverpool L69 3GB. Debbie Stanistreet, Lecturer in Public Health Alex Scott-Samuel, Director, EQUAL (Equity in Health Research and Development Unit) Liverpool John Moores University, 79 Tithebarn Street, Liverpool L2 2ER. Mark A. Bellis, Professor of Public Health Address correspondence to Dr Scott-Samuel.
䉷 Faculty of Public Health Medicine 1999
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JOURNAL OF PUBL IC HEALTH MEDIC I NE
Table 1 Non-parametric descriptive statistics for English local authorities
Variable
SMR
Income inequality index (units*)
Mean income (£)
Median Lower quartile Upper quartile Minimum Maximum
96 91 105 76 123
0.15 0.14 0.16 0.12 0.23
226 214 238 175 300
correlating with each other (r(Spearman) = – 0.67, p < 0.001). To avoid the problems associated with inter-correlated variables and examine in more detail the relationship between III and SMR, III was categorized (in categories of 0.1 III units) and a multivariate general linear model applied to logged SMR values (see Table 2). We found that both income and III were independently associated with SMR (F = 59.087, df = 1, p < 0.001; F = 3.477, df = 10, p < 0.001, respectively). Using this model, estimates of SMR, independent of income, can be calculated for each III category (see Fig. 1). Overall, the model explains 40.3% of the variance in SMR. Table 3 gives illustrative examples of the relationship between income inequality and SMR, at differing levels of mean weekly income.
*See text.
Results Although the distribution of mean income does not differ significantly from normal (Kolmogorov–Smirnov Z = 0.667, p = 0.766), both SMR and income inequality index (III) differ significantly from a normal distribution ( p < 0.005 and p < 0.001, respectively). Therefore, where possible, either nonparametric statistics (see Table 1) or transformed data have been used. Mean income and income inequality index each correlated significantly with SMR (r(Spearman) = – 0.59, p < 0.001; r(Spearman) = 0.48, p < 0.001, respectively). However, these relationships were confounded by both variables also
Discussion Our findings demonstrate an independent association between income inequality and mortality within English local authorities, which is present in both affluent and deprived areas. Although this ecological study cannot establish causality, our findings are consistent with those cited above1–4 and those reviewed by the Independent Inquiry,5 which increasingly point in this direction. A major policy implication – which we would support – is that increasing the redistributive effects
Table 2 Analysis of variance table for log SMR Model component
Variable name
df
Mean square
F
p
Covariate Main effect Model Residual Total
Income Income Inequality Index
1 10 11 354 365
0.0628 0.0037 0.0231 0.0011 0.0017
59.087 3.477 21.746
