Database fields can combine in subtle ways. For example, nationality is not usually enough to identify anyone. Neither is religion. But the *combination* of nationality and religion can be surprisingly informative.

## Information content of nationality

How much information is contained in nationality? That depends on exactly how you define nations versus territories etc., but for this blog post I’ll take this Wikipedia table for my raw data. You can calculate that nationality has entropy of 5.26 bits. That is, on average, nationality is slightly more informative than asking five independent yes/no questions. (See this post for how to calculate information content.)

Entropy measures expected information content. Knowing that someone is from India (population 1.3 billion) carries only 2.50 bits of information. Knowing that someone is from Vatican City (population 800) carries 23.16 bits of information.

One way to reduce the re-identification risk of **PII** (personally identifiable information) such as nationality is to combine small categories. Suppose we lump all countries with a population under one million into “other.” Then we go from 240 categories down to 160. This hardly makes any difference to the entropy: it drops from 5.26 bits to 5.25 bits. But the information content for the smallest country on the list is now 8.80 bits rather than 23.16.

## Information content of religion

What about religion? This is also subtle to define, but again I’ll use Wikipedia for my data. Using these numbers, we get an entropy of 2.65 bits. The largest religion, Christianity, has an information content 1.67 bits. The smallest religion on the list, Rastafari, has an information content of 13.29 bits.

## Joint information content

So if nationality carries 5.25 bits of information and religion 2.65 bits, how much information does the combination of nationality and religion carry? At least 5.25 bits, but no more than 5.25 + 2.65 = 7.9 bits on average. For two random variables *X* and *Y*, the **joint entropy** *H*(*X*, *Y*) satisfies

max( *H*(X), *H*(Y) ) ≤ *H*(*X*, *Y*) ≤ *H*(X) + *H*(Y)

where *H*(*X*) and *H*(*Y*) are the entropy of *X* and *Y* respectively.

Computing the joint entropy exactly would require getting into the joint distribution of nationality and religion. I’d rather not get into this calculation in detail, except to discuss possible **toxic pairs**. On *average*, the information content of the combination of nationality and religion is no more than the sum of the information content of each separately. But *particular combinations* can be highly informative.

For example, there are not a lot of Jews living in predominantly Muslim countries. According to one source, there are at least five Jews living in Iraq. Other sources put the estimate as “less than 10.” (There are zero Jews living in Libya.)

Knowing that someone is a Christian living in Mexico, for example, would not be highly informative. But knowing someone is a Jew living in Iraq would be extremely informative.