The fallacy of global comparisons based on per capita measures

Media, social scientists and public health researchers often present comparisons across countries, and policy makers use such comparisons to take evidence-based action. For a meaningful comparison among countries, one often needs to normalize the measure for differences in population size. To addres...

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Bibliographic Details
Published in:Royal Society open science 2024-03, Vol.11 (3), p.230832-9
Main Authors: Kratochvíl, Lukáš, Havlíček, Jan
Format: Article
Language:English
Subjects:
Carbon dioxide
Coronaviruses
COVID-19
Data interpretation
GDP
global comparisons
Gross Domestic Product
Mortality
Normal distribution
Per capita
per capita measures
Population number
Populations
Public health
Ratios
Science, Society and Policy
Statistical analysis
Trends
Citations: Items that this one cites
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Summary:Media, social scientists and public health researchers often present comparisons across countries, and policy makers use such comparisons to take evidence-based action. For a meaningful comparison among countries, one often needs to normalize the measure for differences in population size. To address this issue, the first choice is usually to calculate ratios. Such ratios, however, normalize the measure for differences in population size directly only under the highly restrictive assumption of a proportional increase of the measure with population size. Violation of this assumption frequently leads to misleading conclusions. We compare ratios with an approach based on regression, a widely used statistical procedure that eliminates many of the problems with ratios and allows for straightforward data interpretation. It turns out that the measures in three global datasets (gross domestic product, COVID-19-related mortality and CO production) systematically overestimate values in countries with small populations, while countries with large populations tend to have misleadingly low ratios owing to the large denominators. Unfortunately, despite their biases, comparisons based on ratios are still ubiquitous, and they are used for influential recommendations by various global institutions. Their continued use can cause significant damage when employed as evidence for policy actions and should therefore be replaced by a more scientifically substantiated and informative method, such as a regression-based approach.
ISSN:2054-5703
2054-5703
DOI:10.1098/rsos.230832