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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

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 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.

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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