The global impact of income inequality on health by age: an observational study
BMJ 2007; 335 doi: https://doi.org/10.1136/bmj.39349.507315.DE (Published 25 October 2007) Cite this as: BMJ 2007;335:873
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The Italian public healthcare service is rapidly evolving from a
state centric model to one based upon the equilibrium of central
governance of demand and regional funding. The state has exclusive power
to define the basic level of coverage, which must be uniformly provided
across the country, while each Regional Health Authority (ASSR) is
responsible for funding its cost. Equity of access based upon clinical
need alone remains the central principle of the national healthcare
system, raising the issue of an equitable distribution of resources in
proportion to the population needs.
Large differences in disposable income per capita can be observed
among Italian Regions: the families living below the threshold of poverty
varies from 3.9% in Emilia-Romagna to 28.9% in Sicily (1). An efficient
distribution of healthcare resources, based on weighted capitation models,
would account for a number of determinants of patients demand for health,
ignoring the long-term impact of income inequalities on the Regional
supply of healthcare services. Underprivileged patients would have access
to the basic level of coverage, but the total amount of healthcare
available to them would be largely dependent on the Region where they
live. Regions with higher income from local taxes would necessarily supply
a higher amount of better quality healthcare service.
The principle of social solidarity recognises large historical
inequalities, allowing Regions with lower per-capita income to spend more
on welfare. As an example, in 2006 the annual average per-capita public
pharmaceutical spending in Emilia-Romagna was €188, while in Sicily was
€302, showing a 61% difference in favour of the Region with the higher
poverty rate (2). Patients with severe chronic conditions are allowed to
migrate to centres of excellence located in a different Region. The
migration rate of cancer patients from Emilia-Romagna to other Regions was
only 6%, compared to 16% from Sicily (3).
The social solidarity principle is pushing the public cost of
healthcare to exceed the 10% threshold of the Italian Gross Domestic
Product, and it is possibly economically inefficient. In return, a
socially responsible allocation of public healthcare funding can minimise
the negative impact of income inequalities on mortality rates. This
valuable outcome has been achieved by the Italian health service, since
poverty and mortality at Regional level show an extremely weak correlation
(r-square = 0.094).
Life expectancy at birth is almost identical for Emilia-Romagna and
Sicily, respectively 77.5 and 76.7 years, in spite of the large difference
in per-capita disposable income, supporting the relevance of solidarity in
public healthcare funding.
References.
(1) ISTAT, Italian National Institute of Statistics (2007), Consumi e
poverta’, Anno 2005. Available online at: http://www.istat.it/
(2) AIFA, Agenzia Italiana del Farmaco (2007), L’uso dei farmaci in
Italia. Rapporto OSMED 2006. Available online at:
http://www.agenziafarmaco.it/wscs_render_attachment_by_id/111.272708.118...
(3) Balzi D, Geddes M, Lispi L (2002), La “migrazione sanitaria” per
tumore della mammella fra le regioni italiane. Available online at:
www.ministerosalute.it/programmazione/resources/documenti/migrazionesani...
(4) ISS, Istituto Superiore di Sanita’ (2007), La mortalita’ per causa in
Italia: 1980-2002. Available online at: http://www.iss.it/site/mortalita/
Competing interests:
None declared
Competing interests: No competing interests
One thing is true from all the above references. The rich have better
access to health care system, whereas at the same time the poor struggle
to find basic health care to stay alive.
The rich can seek health care in hospitals and also have the luxury of
visiting their physician in private opd's where definitely the doctor
devotes more time on one patient examining him/her. Rich can also have
the luxury of calling the doctor at home at the dial of a ph call. So the
doctor is a ph call away for them. Whereas for the poor, even if they need
basic health care they have to travel relatively longer distances, maybe
they will have to wait a longer time in queue’s for getting a simple
medical care, maybe the best doctor available won’t be seeing them in the
first instance.
Because of financial constraints, the poor can’t afford the best of the
medicines, hence there is a compromise when medication is prescribed to
them. Eg a poor patient may be prescribed a cheaper trimethoprim-
sulphamethoxazole combination for fever where as the rich would be
prescribed a costly 3rd or 4th generation cephalosporin, that would act
faster and cover a broader spectrum of organisms. So the chances of
recovery increase with better antibiotic selection.
In India a daily wage worker with a family of 10 to support, earning 40-50
rupees a day won’t be able to afford costlier forms of treatment for
certain medical conditions, like thrombolytic therapy in acute myocardial
infarction, or he won’t go for laproscopic surgery for acute appendicitis,
or he would decide against seeking treatment for cancer, or he may not be
able to afford to vaccinate his children against preventable diseases.
At the same time incidence of illiteracy, overcrowding, poor hygiene, poor
diet are seen more amongst the poor population. These again predispose the
poor to more illnesses and hence increased mortality. I think more stress
needs to be laid for government health organizations and other non profit
organizations to look into this problem more deeply to narrow this gap
between treatment of rich and poor.
Competing interests:
None declared
Competing interests: No competing interests
Dorling at al confirm that income inequalities seem to be most
damaging to health during working adult ages.(1) There could be one more
hypothesis why this is happening. Inequality means a gap between rich and
poor people in a given society. Rich and poor are not independent
variables, on the contrary. The rich become richer, because the poor
becomes poorer. They become richer because there is a transfer of value of
the poor to the rich. That means for the poor harder work, in worse
working circumstances and lower remunerations or in other words: increased
exploitation. That exploitation takes place at the working adult ages.
Exploitation means more then increasing subjective psychosocial stress.
Increased exploitation is associated with objective worsening of the
working conditions and decreasing of income and affluence, which have both
a bad influence on health.
(1) Dorling D at al. The global impact of income inequality on health
by age: an observational study. BMJ 2007;335:873
Competing interests:
None declared
Competing interests: No competing interests
The problem of aggregated analysis: the need for a multilevel methodology in evaluating the relative income hypothesis
Wilkinson’s relative income hypothesis has generated considerable
debate and many papers support, develop or criticise his work.1 2 3 4 5
Much of this interest derives from there being a great deal at stake in
policy terms, between the competing demands for policies aimed at material
disadvantage and those aimed at social cohesion. However, empirical
evidence for the income inequality hypothesis is largely based on the
results of aggregated data analyses in developed countries. Dorling et
al.6 have similarly used ecological data in their study of associations
between countries’ age-sex mortality rates and both GDP (as a measure of
wealth) and income inequality.
There are two problems with the study by Dorling et al.6 First its
design is sub-optimal. Their data set has a multilevel structure in which
age-sex specific mortality is nested within countries. Within a country,
people are more similar to each other than they are between countries. To
ignore this is to violate the assumption of standard regression that all
observations are independent. Therefore, their results may be biased. A
multilevel binomial model should be able to handle this dataset by
treating the mortality outcome as a function of age/sex cells nested
within countries, with the absolute and relative income measures at the
country level. Second, in pursuing an ecological study design, Dorling et
al.6 neglect the possibility that the effect of country level relative
(and absolute) inequality is confounded by individual income. We have
pursued an alternative approach to testing Wilkinson’s hypothesis using
individual data from the World Values Survey (170k respondents nested
within 4 waves and within 69 countries)7. Morbidity (self-rated health)
was related to age, sex, individual absolute income and national income
inequalities in a multilevel framework to take account of within-country
autocorrelation. We found no evidence supporting a Wilkinson hypothesis
for self-rated health once individual income was taken into account. Even
when interactions were allowed between individual income and inequality,
poor people in the most unequal counties do not appear to experience the
worsened poor health predicted by Wilkinson.
References
1.Gravelle H. How much of the relation between population mortality and
unequal distribution of income is a statistical artefact? British Medical
Journal 1998;316: 382-5.
2.Kawachi I, Kennedy B.P. Income inequality and health: pathways and
mechanisms. Health service research 1999; 34: 215-217.
3.Wagstaff A, van Doorslaer E. Income inequality and health: what
does the literature tell us? Annual review of public health 2000; 21: 543-
67.
4.Macinko J, Shi L, Starfield B, Wulu J. Income inequality and
health: a critical review of the literature. Medical Care Research and
Review 2003; 60: 407-52.
5.Lynch J, Davy-Smith G, Harper S, Hillemeier M, Ross N, Kaplan G,
Wolfson M. Is income inequality a determinant of population health? Part
1: a systematic review. The Milbank Quarterly 2004; 82: 5-99.
6.Dorling D, Mitchell R, Pearce J. The global impact of income
inequality on health by age: an observational study. British Medical
Journal 2007; 335: 873-7.
7.Jen M. Health outcomes and income inequality: a multilevel analysis
of the Wilkinson hypothesis. 2006; PhD thesis. University of Bristol, UK.
Competing interests:
None declared
Competing interests: No competing interests