Crime rates per capita are used virtually everywhere to rank and compare cities. However, they rely on a strong linear assumption that crime increases at the same pace as the number of people in a region. Here we show that using per capita rates to rank cities can produce substantially different rankings from rankings adjusted for population size. We analyze the population–crime relationship in cities across twelve countries and assess the impact of per capita measurements on crime analyses, depending on offense type. In most countries, we find that theft increases superlinearly with population size, whereas burglary increases linearly. Our results reveal that per capita rankings can differ from population-adjusted rankings in such a way that they disagree about half of the cities in the top ten most dangerous cities. We advise caution when using crime rates per capita to rank cities and recommend evaluating the linear plausibility before analyzing crime rates.
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