Do Divorce rate (UN) and Homicide rate go together across countries?

Across 90 countries the link before adjusting for anything is r = -0.26, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.02.

Does the link hold within countries over time, not just across countries?

Comparing each country only with itself across 2013-2024, and setting aside what happened worldwide in each year, the link is +0.102 (72 countries, 702 country-years). Using year-to-year changes, it is +0.024.

Does Divorce rate (UN) cause Homicide rate?

This analysis cannot answer that. It shows only that the two go together. A link between two country measures, adjusted or not, does not show that either one changes the other. Country figures also say nothing about individual people.

Divorce rate (UN) vs. Homicide rate

Holds up after adjusting for income

Across 90 countries, Divorce rate (UN) and Homicide rate rise and fall together at r = -0.26 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = -0.26, q = 0.013, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of homicide rate, 0.792 to 4.96 per 100,000 population, divorce rate (un) is 0.0659 divorces per 1,000 people lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0691 divorces per 1,000 people.

Link before adjusting (r)-0.259p = 0.014 · 90 countries

After adjusting for national income-0.261p = 0.013 · likely range [-0.45, -0.06]

p, allowing for regions0.329standard error 0.241 · 6 regions

Check for luck (q)0.013across 12,497 pairs

How to read these.r runs from −1 (one goes up as the other goes down) to +1 (they rise together), and 0 means no link. Adjusting for national income means comparing countries with the same GDP per person, so differences in wealth can’t explain the link. Income is used in percentage terms, since an extra $1,000 means more to a poor country than to a rich one. p is how likely a link this strong would be if there were really none. Below 0.05 means it is unlikely to be chance. Very small values are written in short form: 1.1e-32 means a decimal point followed by 31 zeros and then 11, so very close to zero. The likely range is where the true figure probably lies, and a range that crosses zero means the link could easily be chance. Countries in the same region tend to resemble each other, so the third figure allows for that, which gives a fairer p. The standard error is the typical size of the error in r. Finally, testing this many pairs means some will look strong by luck alone. A q below 0.05 means this link is unlikely to be one of those.

Divorce rate (UN) · divorces per 1,000 peoplelink with income +0.07 · independent

Homicide rate · per 100,000 populationlink with income -0.38 · moderate

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

best-fit line line after adjusting

Four ways to measure the link

Method	r	p	Countries
Standard (Pearson), not adjusted	-0.259	0.014	90
By rank (Spearman), not adjusted	+0.017	0.876	90
Standard (Pearson), adjusted for national income	-0.261	0.013	90
By rank (Spearman), adjusted for national income	+0.089	0.407	90

The rank version uses only each country’s place in line, from lowest to highest, so a few extreme countries count for less. The adjusted and unadjusted versions use the same 90 countries: those that report both measures and GDP per person. So the gap between them comes from the adjustment, not from a change in which countries are counted. Drop in the size of r after adjusting: -0.002 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.295 (without RUS) to -0.212 (without VCT). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: VCT (+0.049).

Fragile: this link may not hold up.

correlation moves sharply once outliers are trimmed
sign flips once outliers are trimmed
direction is not consistent across regions

Within each region

Countries are not separate, unrelated cases, and neighbors share a lot. A link that holds inside each region is far more believable than one that shows up only when comparing regions.

	n	r
Europe & Central Asia	49	+0.71
Latin America & Caribbean	19	-0.42

By income third

If the link shows up only in the richest third of countries, it is a feature of rich countries, not a general pattern.

	n	r
Poorest third	30	-0.43
Middle third	30	-0.19
Richest third	30	+0.26

By largest religious group

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

	n	r
Christians	57	-0.30
Muslims	15	+0.57

By last european coloniser

	n	r
United Kingdom	21	-0.60

Without outliers (countries far outside the middle half of countries on either measure, by more than one and a half times the width of that middle half): r = +0.103 after dropping 19 countries.

Two series, one country

Both measures over the years for one country you pick. The two charts are stacked so they share only the years along the bottom.

Loading…

Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 12years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = +0.102, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose divorce rate (un) moved did not tend to see their homicide rate move with it.

Across countries (adjusted)-0.261for comparison

Within countries+0.123each country vs itself

…and vs the same year elsewhere+0.102q = 0.289 · 72 countries

Year-on-year changes+0.024q = 0.842

Read with care.

Almost all of this indicator's variation is between countries, not within them, so the within-country estimate rests on a small part of the data.

702 country-years (one country in one year), 72 countries, 2013–2024, about 10 years each on average. Share of the variation that happens within countries over time: 6% for Divorce rate (UN), 10% for Homicide rate. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

Same year (lag 0): +0.102. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The largest value on this curve (+0.18 at lag +3) is higher than the same-year one by 0.08. That gap is not a finding. It is the largest of 17 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.

The data

	divorces per 1,000 people	per 100,000 population	Years
Russian Federation RUS	4.65	7.82	2013, 2024
Moldova MDA	3.92	2.54	2024, 2023
Belarus BLR	3.81	2.38	2024, 2019
Georgia GEO	3.66	2.03	2024, 2019
Aruba ABW	3.49	1.93	2023, 2014
Ukraine UKR	2.93	3.78	2021
Latvia LVA	2.85	2.5	2024, 2023
Mauritius MUS	2.51	2.27	2024, 2022
Egypt, Arab Rep. EGY	2.5	1.31	2022, 2017
Costa Rica CRI	2.48	17.7	2024, 2023
Andorra AND	2.48	2.58	2024, 2020
Lithuania LTU	2.47	2.63	2024, 2023
Dominican Republic DOM	2.43	10.9	2024, 2023
Iran, Islamic Rep. IRN	2.41	2.38	2022, 2014
Greenland GRL	2.39	5.35	2023, 2016

United Nations Statistics Division, Demographic Yearbook, 2017 to 2024 editions: tables of marriages and crude marriage rates, and of divorces and crude divorce rates, by urban/rural residence.
UN Office on Drugs and Crime, Intentional Homicide Victims

Sources

Divorce rate (UN)

Crude divorce rate, countries with complete registration

United Nations Statistics Division · UNdata terms of use · updated annual (each edition covers the latest five years)

Divorces granted in the year per 1,000 people, from the same UN Demographic Yearbook collection and with the same rule: only countries whose register the UN rates as at least 90% complete. It is a crude rate, counted against everyone, not just married people. So a country where few people marry can have few divorces without its marriages lasting any longer. Countries where divorce is rare by law or custom and countries where it is simply not recorded can look alike. The United States is left out: its divorce counts miss six states, but the rate is worked out over the whole population. No "better" direction is set.

Homicide rate

Intentional homicide rate (per 100,000 population)

United Nations Office on Drugs and Crime · via Our World in Data · CC BY 3.0 IGO · updated annual

Counts victims of intentional homicide (murder). Homicide is the crime least often left unreported. So it is the only crime figure similar enough across countries to use here. Rates of assault, theft and rape reflect how often people report crimes and how police record them, at least as much as how much crime there is, so they are left out on purpose. Even homicide figures shift when a country switches between police records and public-health records.

How this was computed

Data used: most recent value in 2010-2025; values come from 2011–2024. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 6 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Divorce rate (UN) and Homicide rate

This page shows that two measures go together. It does not show that Divorce rate (UN) changes Homicide rate, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.