placestats

Anaemia in women vs. Liberal democracy

Holds up after adjusting for income

Across 165 countries, Anaemia in women and Liberal democracy rise and fall together at r = -0.56 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.32 (q = 0.014, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak negative link remains.

Comparing countries across the middle half of liberal democracy, 0.127 to 0.621 points, anaemia in women is better by 11.7% of women aged 15-49 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 5.88% of women aged 15-49.

Link before adjusting (r)-0.561p = 4.5e-15 · 165 countries
After adjusting for national income-0.322p = 2.6e-5 · likely range [-0.45, -0.18]
p, allowing for regions0.066standard error 0.143 · 7 regions
Check for luck (q)0.014across 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.

Anaemia in women · % of women aged 15-49link with income -0.67 · high
Liberal democracy · index (0-1)link with income +0.52 · moderate

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

Every country as a dot

Anaemia in women · % of women aged 15-49 →Liberal democracy · index (0-1) →10.5%59.9%0.0150.884Afghanistan: 45.4% of women aged 15-49, 0.018 index (0-1)Angola: 43.8% of women aged 15-49, 0.163 index (0-1)Albania: 24.7% of women aged 15-49, 0.382 index (0-1)United Arab Emirates: 28.2% of women aged 15-49, 0.077 index (0-1)Argentina: 23.5% of women aged 15-49, 0.524 index (0-1)Armenia: 18.7% of women aged 15-49, 0.371 index (0-1)Australia: 11.1% of women aged 15-49, 0.793 index (0-1)Austria: 16.7% of women aged 15-49, 0.757 index (0-1)Azerbaijan: 35.6% of women aged 15-49, 0.053 index (0-1)Burundi: 39% of women aged 15-49, 0.06 index (0-1)Belgium: 15% of women aged 15-49, 0.794 index (0-1)Benin: 50% of women aged 15-49, 0.323 index (0-1)Burkina Faso: 44.3% of women aged 15-49, 0.103 index (0-1)Bangladesh: 37.6% of women aged 15-49, 0.116 index (0-1)Bulgaria: 25.8% of women aged 15-49, 0.499 index (0-1)Bahrain: 38.4% of women aged 15-49, 0.062 index (0-1)Bosnia and Herzegovina: 26% of women aged 15-49, 0.339 index (0-1)Belarus: 22.1% of women aged 15-49, 0.038 index (0-1)Bolivia: 24.9% of women aged 15-49, 0.352 index (0-1)Brazil: 21.3% of women aged 15-49, 0.704 index (0-1)Barbados: 20.1% of women aged 15-49, 0.679 index (0-1)Bhutan: 33.8% of women aged 15-49, 0.457 index (0-1)Botswana: 30.9% of women aged 15-49, 0.52 index (0-1)Central African Republic: 43.4% of women aged 15-49, 0.102 index (0-1)Canada: 14% of women aged 15-49, 0.736 index (0-1)Switzerland: 16.6% of women aged 15-49, 0.843 index (0-1)Chile: 15.7% of women aged 15-49, 0.781 index (0-1)China: 15.6% of women aged 15-49, 0.039 index (0-1)Cote d'Ivoire: 51.4% of women aged 15-49, 0.228 index (0-1)Cameroon: 38.9% of women aged 15-49, 0.114 index (0-1)Congo, Dem. Rep.: 40% of women aged 15-49, 0.115 index (0-1)Congo, Rep.: 46.7% of women aged 15-49, 0.115 index (0-1)Colombia: 22.4% of women aged 15-49, 0.555 index (0-1)Comoros: 29.9% of women aged 15-49, 0.132 index (0-1)Cabo Verde: 40.6% of women aged 15-49, 0.631 index (0-1)Costa Rica: 13.7% of women aged 15-49, 0.809 index (0-1)Cyprus: 16.4% of women aged 15-49, 0.664 index (0-1)Czechia: 24.6% of women aged 15-49, 0.794 index (0-1)Germany: 14% of women aged 15-49, 0.782 index (0-1)Djibouti: 31.8% of women aged 15-49, 0.118 index (0-1)Denmark: 17% of women aged 15-49, 0.884 index (0-1)Dominican Republic: 22.4% of women aged 15-49, 0.505 index (0-1)Algeria: 31.6% of women aged 15-49, 0.126 index (0-1)Ecuador: 20.2% of women aged 15-49, 0.386 index (0-1)Egypt, Arab Rep.: 32.7% of women aged 15-49, 0.115 index (0-1)Spain: 15.6% of women aged 15-49, 0.741 index (0-1)Estonia: 24.7% of women aged 15-49, 0.837 index (0-1)Ethiopia: 23.1% of women aged 15-49, 0.1 index (0-1)Finland: 13.6% of women aged 15-49, 0.808 index (0-1)Fiji: 29.9% of women aged 15-49, 0.398 index (0-1)France: 13.1% of women aged 15-49, 0.8 index (0-1)Gabon: 59.9% of women aged 15-49, 0.178 index (0-1)United Kingdom: 13.6% of women aged 15-49, 0.689 index (0-1)Georgia: 30.2% of women aged 15-49, 0.275 index (0-1)Ghana: 36% of women aged 15-49, 0.606 index (0-1)Guinea: 45.7% of women aged 15-49, 0.095 index (0-1)Gambia, The: 46.1% of women aged 15-49, 0.522 index (0-1)Guinea-Bissau: 45.7% of women aged 15-49, 0.095 index (0-1)Equatorial Guinea: 41.3% of women aged 15-49, 0.047 index (0-1)Greece: 15.6% of women aged 15-49, 0.568 index (0-1)Guatemala: 10.5% of women aged 15-49, 0.523 index (0-1)Guyana: 37.5% of women aged 15-49, 0.328 index (0-1)Honduras: 18.8% of women aged 15-49, 0.38 index (0-1)Croatia: 23.3% of women aged 15-49, 0.593 index (0-1)Haiti: 45.9% of women aged 15-49, 0.098 index (0-1)Hungary: 24.1% of women aged 15-49, 0.315 index (0-1)Indonesia: 26.7% of women aged 15-49, 0.296 index (0-1)India: 53.7% of women aged 15-49, 0.26 index (0-1)Ireland: 14% of women aged 15-49, 0.822 index (0-1)Iran, Islamic Rep.: 25.5% of women aged 15-49, 0.103 index (0-1)Iraq: 27.1% of women aged 15-49, 0.22 index (0-1)Iceland: 14.7% of women aged 15-49, 0.72 index (0-1)Israel: 14.6% of women aged 15-49, 0.588 index (0-1)Italy: 16.4% of women aged 15-49, 0.642 index (0-1)Jamaica: 21.5% of women aged 15-49, 0.679 index (0-1)Jordan: 33% of women aged 15-49, 0.274 index (0-1)Japan: 18.7% of women aged 15-49, 0.734 index (0-1)Kazakhstan: 30.5% of women aged 15-49, 0.131 index (0-1)Kenya: 32.2% of women aged 15-49, 0.446 index (0-1)Kyrgyz Republic: 32.9% of women aged 15-49, 0.178 index (0-1)Cambodia: 38% of women aged 15-49, 0.051 index (0-1)Korea, Rep.: 15.7% of women aged 15-49, 0.739 index (0-1)Kuwait: 27.7% of women aged 15-49, 0.127 index (0-1)Lao PDR: 28.6% of women aged 15-49, 0.11 index (0-1)Lebanon: 34% of women aged 15-49, 0.267 index (0-1)Liberia: 42.5% of women aged 15-49, 0.417 index (0-1)Libya: 29.3% of women aged 15-49, 0.098 index (0-1)Sri Lanka: 20.9% of women aged 15-49, 0.613 index (0-1)Lesotho: 34.2% of women aged 15-49, 0.512 index (0-1)Lithuania: 23.7% of women aged 15-49, 0.712 index (0-1)Luxembourg: 15.4% of women aged 15-49, 0.777 index (0-1)Latvia: 21.4% of women aged 15-49, 0.751 index (0-1)Morocco: 29.5% of women aged 15-49, 0.251 index (0-1)Moldova: 28.5% of women aged 15-49, 0.449 index (0-1)Madagascar: 37.2% of women aged 15-49, 0.187 index (0-1)Maldives: 43.4% of women aged 15-49, 0.416 index (0-1)Mexico: 13.2% of women aged 15-49, 0.221 index (0-1)North Macedonia: 21.5% of women aged 15-49, 0.374 index (0-1)Mali: 56.5% of women aged 15-49, 0.15 index (0-1)Malta: 15.7% of women aged 15-49, 0.621 index (0-1)Myanmar: 39.7% of women aged 15-49, 0.015 index (0-1)Montenegro: 25.8% of women aged 15-49, 0.5 index (0-1)Mongolia: 19.1% of women aged 15-49, 0.424 index (0-1)Mozambique: 47% of women aged 15-49, 0.175 index (0-1)Mauritania: 54.5% of women aged 15-49, 0.127 index (0-1)Mauritius: 32.8% of women aged 15-49, 0.639 index (0-1)Malawi: 32.4% of women aged 15-49, 0.462 index (0-1)Malaysia: 31.3% of women aged 15-49, 0.355 index (0-1)Namibia: 24.9% of women aged 15-49, 0.519 index (0-1)Niger: 47.1% of women aged 15-49, 0.177 index (0-1)Nigeria: 37.9% of women aged 15-49, 0.311 index (0-1)Netherlands: 16.5% of women aged 15-49, 0.774 index (0-1)Norway: 16.3% of women aged 15-49, 0.847 index (0-1)Nepal: 33.2% of women aged 15-49, 0.505 index (0-1)New Zealand: 12.4% of women aged 15-49, 0.787 index (0-1)Oman: 34.4% of women aged 15-49, 0.14 index (0-1)Pakistan: 46.5% of women aged 15-49, 0.176 index (0-1)Panama: 25.5% of women aged 15-49, 0.575 index (0-1)Peru: 21% of women aged 15-49, 0.506 index (0-1)Philippines: 12% of women aged 15-49, 0.291 index (0-1)Papua New Guinea: 28.8% of women aged 15-49, 0.384 index (0-1)Poland: 23.4% of women aged 15-49, 0.645 index (0-1)Portugal: 15% of women aged 15-49, 0.717 index (0-1)Paraguay: 23.2% of women aged 15-49, 0.376 index (0-1)Qatar: 23.6% of women aged 15-49, 0.091 index (0-1)Romania: 24.3% of women aged 15-49, 0.464 index (0-1)Russian Federation: 24.1% of women aged 15-49, 0.056 index (0-1)Rwanda: 16.1% of women aged 15-49, 0.09 index (0-1)Saudi Arabia: 17.6% of women aged 15-49, 0.047 index (0-1)Sudan: 34% of women aged 15-49, 0.034 index (0-1)Senegal: 43.1% of women aged 15-49, 0.484 index (0-1)Singapore: 16.6% of women aged 15-49, 0.36 index (0-1)Solomon Islands: 32.6% of women aged 15-49, 0.539 index (0-1)Sierra Leone: 44.6% of women aged 15-49, 0.348 index (0-1)El Salvador: 14.4% of women aged 15-49, 0.09 index (0-1)Somalia, Fed. Rep.: 46.2% of women aged 15-49, 0.128 index (0-1)Serbia: 24.9% of women aged 15-49, 0.208 index (0-1)Sao Tome and Principe: 39.7% of women aged 15-49, 0.519 index (0-1)Suriname: 22.2% of women aged 15-49, 0.626 index (0-1)Slovak Republic: 25.3% of women aged 15-49, 0.573 index (0-1)Slovenia: 25.7% of women aged 15-49, 0.589 index (0-1)Sweden: 16.8% of women aged 15-49, 0.853 index (0-1)Eswatini: 28.3% of women aged 15-49, 0.097 index (0-1)Seychelles: 25.8% of women aged 15-49, 0.68 index (0-1)Syrian Arab Republic: 31% of women aged 15-49, 0.054 index (0-1)Chad: 46.5% of women aged 15-49, 0.062 index (0-1)Togo: 41.5% of women aged 15-49, 0.157 index (0-1)Thailand: 20.7% of women aged 15-49, 0.314 index (0-1)Tajikistan: 37.3% of women aged 15-49, 0.043 index (0-1)Turkmenistan: 34.8% of women aged 15-49, 0.034 index (0-1)Timor-Leste: 29.7% of women aged 15-49, 0.549 index (0-1)Trinidad and Tobago: 22.1% of women aged 15-49, 0.668 index (0-1)Tunisia: 27.7% of women aged 15-49, 0.265 index (0-1)Turkiye: 29.3% of women aged 15-49, 0.11 index (0-1)Tanzania: 38.8% of women aged 15-49, 0.297 index (0-1)Uganda: 27.2% of women aged 15-49, 0.165 index (0-1)Ukraine: 19.4% of women aged 15-49, 0.24 index (0-1)Uruguay: 24.5% of women aged 15-49, 0.79 index (0-1)United States: 15% of women aged 15-49, 0.571 index (0-1)Uzbekistan: 30.4% of women aged 15-49, 0.079 index (0-1)Viet Nam: 20.5% of women aged 15-49, 0.102 index (0-1)Vanuatu: 30.4% of women aged 15-49, 0.623 index (0-1)South Africa: 31.2% of women aged 15-49, 0.633 index (0-1)Zambia: 27.1% of women aged 15-49, 0.375 index (0-1)Zimbabwe: 27.5% of women aged 15-49, 0.147 index (0-1)AUSCHNCPVGABGMBIRLMLIMRTNZLSAUSLV

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5614.5e-15165
By rank (Spearman), not adjusted-0.5587.2e-15165
Standard (Pearson), adjusted for national income-0.3222.6e-5165
By rank (Spearman), adjusted for national income-0.3144.2e-5165

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 165 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: +0.239 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.342 (without SLV) to -0.299 (without BHR). 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: BHR (+0.022).

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.

nr
East Asia & Pacific20-0.31
Europe & Central Asia48-0.46
Latin America & Caribbean22-0.28
Middle East, North Africa, Afghanistan & Pakistan21-0.52
Sub-Saharan Africa46-0.20

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.

nr
Poorest third55-0.18
Middle third55-0.20
Richest third55-0.68

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.

nr
Christians98-0.24
Muslims47+0.08

By last european coloniser

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.

nr
France25+0.17
Never a European colony21-0.35
Spain18-0.36
United Kingdom49-0.46

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 = -0.312 after dropping 1 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 24years. 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 = -0.093, 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 anaemia in women moved did not tend to see their liberal democracy move with it.

Across countries (adjusted)-0.322for comparison
Within countries-0.153each country vs itself
…and vs the same year elsewhere-0.093q = 0.235 · 171 countries
Year-on-year changes-0.029q = 0.374
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.

4,102 country-years (one country in one year), 171 countries, 2000–2023, about 24 years each on average. Share of the variation that happens within countries over time: 5% for Anaemia in women, 3% for Liberal democracy. 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

0.10−0.1-100+10years Liberal democracy trails Anaemia in women →lag -10: r = -0.083 (n = 4,072)lag -9: r = -0.074 (n = 4,078)lag -8: r = -0.073 (n = 4,081)lag -7: r = -0.075 (n = 4,084)lag -6: r = -0.082 (n = 4,087)lag -5: r = -0.087 (n = 4,090)lag -4: r = -0.090 (n = 4,093)lag -3: r = -0.094 (n = 4,096)lag -2: r = -0.096 (n = 4,099)lag -1: r = -0.096 (n = 4,101)lag +0: r = -0.093 (n = 4,102)lag +1: r = -0.093 (n = 4,103)lag +2: r = -0.093 (n = 4,104)lag +3: r = -0.091 (n = 3,933)lag +4: r = -0.087 (n = 3,762)lag +5: r = -0.081 (n = 3,591)lag +6: r = -0.075 (n = 3,420)lag +7: r = -0.075 (n = 3,249)lag +8: r = -0.077 (n = 3,078)lag +9: r = -0.073 (n = 2,907)lag +10: r = -0.064 (n = 2,736)

Same year (lag 0): -0.093. 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 women aged 15-49

index (0-1)
Years
Gabon GAB59.9%0.1782023, 2025
Mali MLI56.5%0.152023, 2025
Mauritania MRT54.5%0.1272023, 2025
India IND53.7%0.262023, 2025
Cote d'Ivoire CIV51.4%0.2282023, 2025
Benin BEN50%0.3232023, 2025
Niger NER47.1%0.1772023, 2025
Mozambique MOZ47%0.1752023, 2025
Congo, Rep. COG46.7%0.1152023, 2025
Chad TCD46.5%0.0622023, 2025
Pakistan PAK46.5%0.1762023, 2025
Somalia, Fed. Rep. SOM46.2%0.1282023, 2025
Gambia, The GMB46.1%0.5222023, 2025
Haiti HTI45.9%0.0982023, 2025
Guinea-Bissau GNB45.7%0.0952023, 2025

World Bank, World Development Indicators
Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project

Sources

Anaemia in women

Prevalence of anaemia among women of reproductive age (% of women ages 15-49)

World Health Organization · CC BY 4.0 · updated quarterly

Liberal democracy

Liberal democracy index

V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual

Electoral democracy plus limits on the head of government, independent courts and protected personal freedoms. It contains the electoral democracy index as a part, so the two are built from the same numbers and bound to match.

How this was computed

Data used: most recent value in 2010-2025; values come from 2023–2025. 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 Anaemia in women and Liberal democracy

This page shows that two measures go together. It does not show that Anaemia in women changes Liberal democracy, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Anaemia in women or Liberal democracy