Glossary
Ecological study
An investigation in which populations or groups of people, rather than individuals
are looked at. Most of the studies referred to in this web page are such. An
individual does not have a life expectancy, nor an income distribution, but
a population, a city, state or country, does. Ecologic studies do not allow
statements to be made about individuals, just about the population. See ecologic
fallacy in the Overview and Making Causal Inferences
Epidemiology
The core discipline from which most of the studies cited below emanate. It can
be considered the study of the distribution and determinants of health-related
states or events in specified populations
Equity
Equity has various meanings, and here income equity
is used to connote a fair or just distribution of income resources.
Gini coefficient
A measure of inequality, usually applied to income. It is derived
from a Lorentz Curve which plots the cumulative percent of income
against the cumulative percent of income recipients. It is twice
the area of the curve between what would be perfect equality and
the existing distribution is the Gini coefficient. A coefficient
of 0 means perfect equality, while that of 1 means one unit of the
population has everything and there is none for the rest. It is more
sensitive to differences in the middle of the distribution, than
to the ends.
Health
Mortality measures are used as a proxy for population health,
since they are easily measured, allowing comparisons among populations,
common ones include:
- life expectancy namely, born today, on average, how long can
you expect to live, given the age specific mortality rates present
today
- infant mortality rate, namely, out of 1000 infants born alive,
how many die before living one year
Health inequalities (or inequalities in health) This is the term commonly used in Europe to indicate the virtually
universal phenomenon of variation of health by socioeconomic status,
that is poorer people have poorer health. In the US, there is no
single such term, and instead it is referred to as the socioeconomic
status and health relationship.
Income inequality
Income inequality is some measure of the extent of differences
in income received by individuals in the population, from the lowest,
to the highest.
Many studies have looked at the proportion of the total population
income received by the bottom 70% of the population.
On one studied data set, where there are several commonly used measures
of income istribution, the different measures of income inequality
have shown the same relationship between income distribution and
health (see Kawachi, and Kennedy 1997 below).
Infant mortality rate (IMR)
The IMR is the number of deaths occurring in a population per year
among infants in their first year of life.
Life expectancy (also termed the expectation of life)
This number, for a population , is the average number of years an
individual, born today, would be expected to life if current mortality
rates continued to apply. To calculate it, you need to know the
mortality pattern of the population, that is the death rates in
different age
intervals.
Median income
The median of a measure in a population is the number which divides
the population into two equal groups, those above, and those below.
Median income would then be the income value that separates the
population as above.
Social capital or social cohesion
Terms, that relate to the features of social organization and community
life, such as civic participation, norms of reciprocity and trust
in others that facilitate cooperation for mutual benefit.
Socioeconomic status
A descriptive term for a person’s position in society, usually
expressed in terms of income, education, occupation, but it could
also be represented by net worth, ownership of assets such as a
home, automobile,
yacht, etc.
Casual Inferences
What is being presented here
is a an argument regarding a factor (income inequality) that has been
shown
to be epidemiologically
related to health as measured by life expectancy or infant mortality.
Is this causal, that is does increased income inequality in some
sense, cause poorer health? The subject of epidemiology considers
criteria that should be met to judge an association to be causal. The
commonly accepted criteria are:
Strength of the Association
How much of the variability of health among different
populations can be explained by differences in income between
the populations?
Studies cited below (in b and c) suggest more than half of the variability
in health among populations can be attributed to income inequality.
Dose- response relationship
Increased income inequality associated with worse health, or vice-versa? This
correlation was first observed (namely that countries where income inequality
increased more than in other countries, did
not have such marked improvements in health as the other countries),
and led to further studies to validate the concept. See Wilkinson
1989 in e below.
Consistency of the relationship
Is it found in many different study populations, or was
it just found in one particular population, and not found in others?
The papers below (in b and c) address this question looking among
countries, and within countries. All the published material critical
of the studies are presented as well for the reader to judge.
Temporally Correct Relationship
Does the exposure precede the effect? Does poor health
lead to decreased income within a population, and so suggest that
increased income inequality is a result, rather than a cause? This
has been studied within populations, and the effect is not the reason
for the association (see Wilkinson's Unhealthy Societies in a).
Consideration of Alternative Explanations
In epidemiologic terms, are there confounders? Is there
another factor, mixed in with the one under question, that has
been overlooked yet explains the relationship? Consider the reviews
presented here (in a), as well as the published criticisms (in
f) to evaluate this.
Biologic Plausibility
Does the relationship make sense, given what we know about
biology and the mechanisms of health and disease?
For the details on biology, we have to look at indirect evidence,
since trying to do experiments on human populations to understand
this concept is unethical and immoral. Relative hierarchies within
other primate populations have been studied for the mechanisms
for the observed effects of poorer health among the relatively
deprived animals. Recent research presented below (in h) provides
considerable evidence for plausibility.
Ecologic Fallacy
In epidemiology, ecologic studies are those that deal with
groups rather than individuals. Ecologic fallacy is the concept
that an association is present in relation to populations rather
than individuals, and hence may not apply to individuals. From this
perspective, the studies presented here are controversial to some
(see papers critical of this), but there is considerable individual
data within populations looking at socioeconomic determinants of
health, and biological reasoning to support their being taken seriously.
As well, the conclusions drawn relate to populations, rather than
individuals, and suggest how population health may be determined
by factors conceptually affecting populations, not individuals.
This concept is outside the scope of the ecologic fallacy argument.
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