Do Adult obesity and Corporate tax rate go together across countries?

Across 81 countries the link before adjusting for anything is r = -0.34, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.23.

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

Comparing each country only with itself across 2000-2018, and setting aside what happened worldwide in each year, the link is +0.044 (81 countries, 1,539 country-years). Using year-to-year changes, it is +0.019.

Does Adult obesity cause Corporate tax 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.

Adult obesity vs. Corporate tax rate

Holds up after adjusting for income

Across 81 countries, Adult obesity and Corporate tax rate rise and fall together at r = -0.34 (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 = -0.28, q = 0.043, allowing for the many pairs tested). Caution: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of corporate tax rate, 19% to 29% of profit, adult obesity is better by 3.96% of adults at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 3.35% of adults.

Link before adjusting (r)-0.340p = 0.002 · 81 countries

After adjusting for national income-0.277p = 0.013 · likely range [-0.47, -0.06]

p, allowing for regions0.072standard error 0.127 · 7 regions

Check for luck (q)0.043across 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.

Adult obesity · % of adultslink with income +0.34 · moderate

Corporate tax rate · % of profitlink with income -0.36 · 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	-0.340	0.002	81
By rank (Spearman), not adjusted	-0.234	0.035	81
Standard (Pearson), adjusted for national income	-0.277	0.013	81
By rank (Spearman), adjusted for national income	-0.216	0.055	81

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 81 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: +0.063 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.300 (without VNM) to -0.211 (without BHS). 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: BHS (+0.066).

Fragile: this link may not hold up.

correlation moves sharply 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	33	-0.42
Latin America & Caribbean	12	-0.68
Sub-Saharan Africa	13	+0.10

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	27	-0.02
Middle third	27	-0.29
Richest third	27	-0.48

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	52	-0.21
Muslims	14	-0.11

By last european coloniser

	n	r
United Kingdom	23	-0.29

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 = -0.033 after dropping 6 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.

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Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 19years. 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 = +0.044, 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 adult obesity moved did not tend to see their corporate tax rate move with it.

Across countries (adjusted)-0.277for comparison

Within countries-0.465each country vs itself

…and vs the same year elsewhere+0.044q = 0.756 · 81 countries

Year-on-year changes+0.019q = 0.676

Read with care.

Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.
Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

1,539 country-years (one country in one year), 81 countries, 2000–2018, about 19 years each on average. Share of the variation that happens within countries over time: 13% for Adult obesity, 8% for Corporate tax 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): +0.044. 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 data

	% of adults	% of profit	Years
Bahamas, The BHS	48.3%	0%	2024, 2018
Egypt, Arab Rep. EGY	43.9%	22.5%	2024, 2018
United States USA	41%	25.8%	2024, 2018
Chile CHL	40.5%	25%	2024, 2018
Saudi Arabia SAU	40.1%	0%	2024, 2018
Barbados BRB	39.4%	25%	2024, 2018
Panama PAN	37.7%	25%	2024, 2018
Mexico MEX	37.4%	30%	2024, 2018
Argentina ARG	37.2%	30%	2024, 2018
Brunei Darussalam BRN	37.1%	18.5%	2024, 2018
Jamaica JAM	35.2%	25%	2024, 2018
Uruguay URY	34.9%	25%	2024, 2018
Bahrain BHR	34.9%	0%	2024, 2018
Paraguay PRY	34.7%	10%	2024, 2018
St. Vincent and the Grenadines VCT	34.6%	30%	2024, 2018

World Health Organization, Global Health Observatory
OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics

Sources

Adult obesity

Prevalence of obesity among adults, age-standardised

World Health Organization · via Our World in Data · CC BY-NC-SA 4.0 · updated annual

Adults with a body mass index (weight compared with height) over 30. Adjusted to one age mix, so an older country and a younger one can be compared fairly. Estimated with a statistical model from surveys. It rises with income across the poorer half of the world, then stops rising across the richer half. Adjusting for GDP assumes a straight-line link, so it cannot capture that bend.

Corporate tax rate

Combined statutory corporate income tax rate

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator

The headline tax rate on company profits, national and local combined, for over ninety countries and territories. That is the widest coverage of any OECD series here. It is the rate written in law, not the rate firms actually pay after allowances and tax avoidance. From a 2019 release kept as a snapshot, so the series ends in 2018. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2018–2024. 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 7 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 Adult obesity and Corporate tax rate

This page shows that two measures go together. It does not show that Adult obesity changes Corporate tax rate, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.