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Michael Wolfson a Institutions and Social Statistics Branch,
Statistics Canada, Ottawa, Canada K1A 0T6, b Department of Epidemiology, School
of Public Health, University of Michigan, Ann Arbor, MI 48109-2029, USA, c Social and
Economic Studies Division, Statistics Canada, d Federal Building #3, US Bureau of the
Census, Washington, DC 20233-8700, USA
Correspondence
to: M Wolfson wolfson{at}statcan.ca
Objective:
To assess the extent to which observed
associations at population level between income inequality and
mortality are statistical artefacts.
Design:
Indirect "what if" simulation by using
observed risks of mortality at individual level as a function of income to construct hypothetical state level mortality specific for age and
sex as if the statistical artefact argument were 100% correct.
Setting:
Data from the 1990 census for the 50 US
states plus Washington, DC, were used for population distributions by age, sex, state, and income range; data disaggregated by age, sex, and
state from the Centers for Disease Control and Prevention were used for
mortality; and regressions from the national longitudinal mortality
study were used for the individual level relation between income and
risk of mortality.
Results:
Hypothetical mortality, while correlated with inequality (as implied by the logic of the statistical artefact argument), showed a weaker association with states' levels of income
inequality than the observed mortality.
Conclusions:
The observed associations in the United
States at the state level between income inequality and mortality
cannot be entirely or substantially explained as statistical artefacts of an underlying individual level relation between income and mortality. There remains an important association between income inequality and mortality at state level over and above anything that
could be accounted for by any statistical artefact. This result
reinforces the need to consider a broad range of factors, including the
social milieu, as fundamental determinants of health.
Key messages
What can you learn from this BMJ paper? Read Leanne Tite's Paper+