placestats

Anaemia in women vs. Life satisfaction

Fades after adjusting for income

Across 156 countries, Anaemia in women and Life satisfaction rise and fall together at r = -0.67 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.30, which could easily be chance (q = 0.40, allowing for the many pairs tested, and allowing for countries in the same region being alike). So the first figure mostly shows richer countries differing from poorer ones, not a link between these two things. Caution: direction is not consistent across regions.

Comparing countries across the middle half of anaemia in women, 19% to 34.5% of women aged 15-49, life satisfaction is worse by 1.1 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.378 points.

Link before adjusting (r)-0.673p = 6.1e-22 · 156 countries
After adjusting for national income-0.295p = 0.000 · likely range [-0.43, -0.14]
p, allowing for regions0.196standard error 0.203 · 7 regions
Check for luck (q)0.398across 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
Life satisfaction · score (0-10)link with income +0.81 · proxy

Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.

“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 →Life satisfaction · score (0-10) →10.5%59.9%1.457.76Afghanistan: 45.4% of women aged 15-49, 1.45 score (0-10)Angola: 43.8% of women aged 15-49, 3.79 score (0-10)Albania: 24.7% of women aged 15-49, 5.66 score (0-10)United Arab Emirates: 28.2% of women aged 15-49, 6.82 score (0-10)Argentina: 23.5% of women aged 15-49, 6.43 score (0-10)Armenia: 18.7% of women aged 15-49, 5.58 score (0-10)Australia: 11.1% of women aged 15-49, 6.92 score (0-10)Austria: 16.7% of women aged 15-49, 6.84 score (0-10)Azerbaijan: 35.6% of women aged 15-49, 4.99 score (0-10)Burundi: 39% of women aged 15-49, 3.77 score (0-10)Belgium: 15% of women aged 15-49, 6.93 score (0-10)Benin: 50% of women aged 15-49, 4.39 score (0-10)Burkina Faso: 44.3% of women aged 15-49, 4.46 score (0-10)Bangladesh: 37.6% of women aged 15-49, 4.32 score (0-10)Bulgaria: 25.8% of women aged 15-49, 5.7 score (0-10)Bahrain: 38.4% of women aged 15-49, 6.25 score (0-10)Bosnia and Herzegovina: 26% of women aged 15-49, 6.38 score (0-10)Belarus: 22.1% of women aged 15-49, 5.82 score (0-10)Belize: 21.3% of women aged 15-49, 6.71 score (0-10)Bolivia: 24.9% of women aged 15-49, 5.83 score (0-10)Brazil: 21.3% of women aged 15-49, 6.63 score (0-10)Bhutan: 33.8% of women aged 15-49, 5.08 score (0-10)Botswana: 30.9% of women aged 15-49, 3.46 score (0-10)Central African Republic: 43.4% of women aged 15-49, 3.48 score (0-10)Canada: 14% of women aged 15-49, 6.74 score (0-10)Switzerland: 16.6% of women aged 15-49, 7.02 score (0-10)Chile: 15.7% of women aged 15-49, 6.3 score (0-10)China: 15.6% of women aged 15-49, 6.07 score (0-10)Cote d'Ivoire: 51.4% of women aged 15-49, 5.15 score (0-10)Cameroon: 38.9% of women aged 15-49, 5.08 score (0-10)Congo, Dem. Rep.: 40% of women aged 15-49, 3.76 score (0-10)Congo, Rep.: 46.7% of women aged 15-49, 4.46 score (0-10)Colombia: 22.4% of women aged 15-49, 6.04 score (0-10)Comoros: 29.9% of women aged 15-49, 3.92 score (0-10)Costa Rica: 13.7% of women aged 15-49, 7.44 score (0-10)Cyprus: 16.4% of women aged 15-49, 6.13 score (0-10)Czechia: 24.6% of women aged 15-49, 6.82 score (0-10)Germany: 14% of women aged 15-49, 6.88 score (0-10)Djibouti: 31.8% of women aged 15-49, 4.37 score (0-10)Denmark: 17% of women aged 15-49, 7.54 score (0-10)Dominican Republic: 22.4% of women aged 15-49, 6.09 score (0-10)Algeria: 31.6% of women aged 15-49, 5.71 score (0-10)Ecuador: 20.2% of women aged 15-49, 6.14 score (0-10)Egypt, Arab Rep.: 32.7% of women aged 15-49, 3.86 score (0-10)Spain: 15.6% of women aged 15-49, 6.54 score (0-10)Estonia: 24.7% of women aged 15-49, 6.41 score (0-10)Ethiopia: 23.1% of women aged 15-49, 3.98 score (0-10)Finland: 13.6% of women aged 15-49, 7.76 score (0-10)France: 13.1% of women aged 15-49, 6.59 score (0-10)Gabon: 59.9% of women aged 15-49, 5.17 score (0-10)United Kingdom: 13.6% of women aged 15-49, 6.69 score (0-10)Georgia: 30.2% of women aged 15-49, 5.52 score (0-10)Ghana: 36% of women aged 15-49, 4.55 score (0-10)Guinea: 45.7% of women aged 15-49, 4.61 score (0-10)Gambia, The: 46.1% of women aged 15-49, 4.31 score (0-10)Greece: 15.6% of women aged 15-49, 5.7 score (0-10)Guatemala: 10.5% of women aged 15-49, 6.53 score (0-10)Guyana: 37.5% of women aged 15-49, 5.99 score (0-10)Honduras: 18.8% of women aged 15-49, 6.1 score (0-10)Croatia: 23.3% of women aged 15-49, 6.01 score (0-10)Haiti: 45.9% of women aged 15-49, 3.62 score (0-10)Hungary: 24.1% of women aged 15-49, 5.94 score (0-10)Indonesia: 26.7% of women aged 15-49, 5.62 score (0-10)India: 53.7% of women aged 15-49, 4.54 score (0-10)Ireland: 14% of women aged 15-49, 6.93 score (0-10)Iran, Islamic Rep.: 25.5% of women aged 15-49, 5.15 score (0-10)Iraq: 27.1% of women aged 15-49, 5.21 score (0-10)Iceland: 14.7% of women aged 15-49, 7.54 score (0-10)Israel: 14.6% of women aged 15-49, 7.19 score (0-10)Italy: 16.4% of women aged 15-49, 6.57 score (0-10)Jamaica: 21.5% of women aged 15-49, 6.3 score (0-10)Jordan: 33% of women aged 15-49, 4.48 score (0-10)Japan: 18.7% of women aged 15-49, 6.13 score (0-10)Kazakhstan: 30.5% of women aged 15-49, 6.63 score (0-10)Kenya: 32.2% of women aged 15-49, 4.67 score (0-10)Kyrgyz Republic: 32.9% of women aged 15-49, 6.05 score (0-10)Cambodia: 38% of women aged 15-49, 4.46 score (0-10)Korea, Rep.: 15.7% of women aged 15-49, 6.04 score (0-10)Kuwait: 27.7% of women aged 15-49, 6.54 score (0-10)Lao PDR: 28.6% of women aged 15-49, 5.51 score (0-10)Lebanon: 34% of women aged 15-49, 3.72 score (0-10)Liberia: 42.5% of women aged 15-49, 4.28 score (0-10)Libya: 29.3% of women aged 15-49, 5.73 score (0-10)Sri Lanka: 20.9% of women aged 15-49, 4.01 score (0-10)Lesotho: 34.2% of women aged 15-49, 4.38 score (0-10)Lithuania: 23.7% of women aged 15-49, 6.7 score (0-10)Luxembourg: 15.4% of women aged 15-49, 7.06 score (0-10)Latvia: 21.4% of women aged 15-49, 6.37 score (0-10)Morocco: 29.5% of women aged 15-49, 4.65 score (0-10)Moldova: 28.5% of women aged 15-49, 5.85 score (0-10)Madagascar: 37.2% of women aged 15-49, 4.17 score (0-10)Maldives: 43.4% of women aged 15-49, 5.2 score (0-10)Mexico: 13.2% of women aged 15-49, 6.97 score (0-10)North Macedonia: 21.5% of women aged 15-49, 5.72 score (0-10)Mali: 56.5% of women aged 15-49, 4.59 score (0-10)Malta: 15.7% of women aged 15-49, 6.44 score (0-10)Myanmar: 39.7% of women aged 15-49, 4.29 score (0-10)Montenegro: 25.8% of women aged 15-49, 6.14 score (0-10)Mongolia: 19.1% of women aged 15-49, 5.94 score (0-10)Mozambique: 47% of women aged 15-49, 5.34 score (0-10)Mauritania: 54.5% of women aged 15-49, 4.47 score (0-10)Mauritius: 32.8% of women aged 15-49, 5.94 score (0-10)Malawi: 32.4% of women aged 15-49, 3.28 score (0-10)Malaysia: 31.3% of women aged 15-49, 6 score (0-10)Namibia: 24.9% of women aged 15-49, 4.78 score (0-10)Niger: 47.1% of women aged 15-49, 4.94 score (0-10)Nigeria: 37.9% of women aged 15-49, 4.79 score (0-10)Netherlands: 16.5% of women aged 15-49, 7.22 score (0-10)Norway: 16.3% of women aged 15-49, 7.24 score (0-10)Nepal: 33.2% of women aged 15-49, 5.15 score (0-10)New Zealand: 12.4% of women aged 15-49, 7 score (0-10)Oman: 34.4% of women aged 15-49, 6.2 score (0-10)Pakistan: 46.5% of women aged 15-49, 4.87 score (0-10)Panama: 25.5% of women aged 15-49, 6.55 score (0-10)Peru: 21% of women aged 15-49, 5.97 score (0-10)Philippines: 12% of women aged 15-49, 6.21 score (0-10)Poland: 23.4% of women aged 15-49, 6.77 score (0-10)Portugal: 15% of women aged 15-49, 6.03 score (0-10)Paraguay: 23.2% of women aged 15-49, 6.2 score (0-10)West Bank and Gaza: 24.8% of women aged 15-49, 4.69 score (0-10)Qatar: 23.6% of women aged 15-49, 6.37 score (0-10)Romania: 24.3% of women aged 15-49, 6.63 score (0-10)Russian Federation: 24.1% of women aged 15-49, 5.83 score (0-10)Rwanda: 16.1% of women aged 15-49, 3.27 score (0-10)Saudi Arabia: 17.6% of women aged 15-49, 6.82 score (0-10)Sudan: 34% of women aged 15-49, 4.14 score (0-10)Senegal: 43.1% of women aged 15-49, 4.79 score (0-10)Singapore: 16.6% of women aged 15-49, 6.58 score (0-10)Sierra Leone: 44.6% of women aged 15-49, 3.25 score (0-10)El Salvador: 14.4% of women aged 15-49, 6.58 score (0-10)Somalia, Fed. Rep.: 46.2% of women aged 15-49, 4.51 score (0-10)Serbia: 24.9% of women aged 15-49, 6.69 score (0-10)Suriname: 22.2% of women aged 15-49, 6.27 score (0-10)Slovak Republic: 25.3% of women aged 15-49, 6.25 score (0-10)Slovenia: 25.7% of women aged 15-49, 6.87 score (0-10)Sweden: 16.8% of women aged 15-49, 7.25 score (0-10)Eswatini: 28.3% of women aged 15-49, 3.91 score (0-10)Syrian Arab Republic: 31% of women aged 15-49, 3.46 score (0-10)Chad: 46.5% of women aged 15-49, 4.38 score (0-10)Togo: 41.5% of women aged 15-49, 4.28 score (0-10)Thailand: 20.7% of women aged 15-49, 6.3 score (0-10)Tajikistan: 37.3% of women aged 15-49, 5.59 score (0-10)Turkmenistan: 34.8% of women aged 15-49, 5.47 score (0-10)Trinidad and Tobago: 22.1% of women aged 15-49, 5.91 score (0-10)Tunisia: 27.7% of women aged 15-49, 4.8 score (0-10)Turkiye: 29.3% of women aged 15-49, 5.3 score (0-10)Tanzania: 38.8% of women aged 15-49, 3.9 score (0-10)Uganda: 27.2% of women aged 15-49, 4.49 score (0-10)Ukraine: 19.4% of women aged 15-49, 4.66 score (0-10)Uruguay: 24.5% of women aged 15-49, 6.63 score (0-10)United States: 15% of women aged 15-49, 6.82 score (0-10)Uzbekistan: 30.4% of women aged 15-49, 6.28 score (0-10)Viet Nam: 20.5% of women aged 15-49, 6.43 score (0-10)South Africa: 31.2% of women aged 15-49, 5.01 score (0-10)Zambia: 27.1% of women aged 15-49, 4.11 score (0-10)Zimbabwe: 27.5% of women aged 15-49, 3.35 score (0-10)AFGCIVCRIFINGABISLLKAMLIRWASLE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6736.1e-22156
By rank (Spearman), not adjusted-0.7231.5e-26156
Standard (Pearson), adjusted for national income-0.2950.000156
By rank (Spearman), adjusted for national income-0.3905.1e-7156

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 156 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: +0.378 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.333 (without RWA) to -0.278 (without GTM). 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: RWA (-0.037).

Fragile: this link may not hold up.
  • 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.

nr
East Asia & Pacific15-0.80
Europe & Central Asia48-0.11
Latin America & Caribbean22-0.86
Middle East, North Africa, Afghanistan & Pakistan22-0.31
Sub-Saharan Africa41+0.41

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 third52+0.04
Middle third52-0.53
Richest third52-0.38

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
Christians89-0.35
Muslims47-0.01

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
France25-0.00
Never a European colony21-0.19
Spain17-0.79
United Kingdom45-0.29

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 = -0.290 after dropping 2 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 13years. 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 = -0.165, 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 life satisfaction move with it.

Across countries (adjusted)-0.295for comparison
Within countries-0.066each country vs itself
…and vs the same year elsewhere-0.165q = 0.071 · 152 countries
Year-on-year changes-0.095q = 0.024
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.

1,739 country-years (one country in one year), 152 countries, 2011–2023, about 11 years each on average. Share of the variation that happens within countries over time: 1% for Anaemia in women, 9% for Life satisfaction. 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

0.20−0.2-70+10years Life satisfaction trails Anaemia in women →lag -7: r = -0.138 (n = 700)lag -6: r = -0.153 (n = 865)lag -5: r = -0.177 (n = 1,028)lag -4: r = -0.179 (n = 1,177)lag -3: r = -0.182 (n = 1,323)lag -2: r = -0.175 (n = 1,463)lag -1: r = -0.167 (n = 1,600)lag +0: r = -0.165 (n = 1,739)lag +1: r = -0.154 (n = 1,889)lag +2: r = -0.137 (n = 2,031)lag +3: r = -0.127 (n = 2,031)lag +4: r = -0.112 (n = 2,031)lag +5: r = -0.095 (n = 2,031)lag +6: r = -0.075 (n = 2,031)lag +7: r = -0.056 (n = 2,031)lag +8: r = -0.039 (n = 2,031)lag +9: r = -0.024 (n = 2,031)lag +10: r = -0.009 (n = 2,031)

Same year (lag 0): -0.165. 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

score (0-10)
Years
Gabon GAB59.9%5.172023, 2025
Mali MLI56.5%4.592023, 2025
Mauritania MRT54.5%4.472023, 2025
India IND53.7%4.542023, 2025
Cote d'Ivoire CIV51.4%5.152023, 2025
Benin BEN50%4.392023, 2025
Niger NER47.1%4.942023, 2025
Mozambique MOZ47%5.342023, 2025
Congo, Rep. COG46.7%4.462023, 2025
Chad TCD46.5%4.382023, 2025
Pakistan PAK46.5%4.872023, 2025
Somalia, Fed. Rep. SOM46.2%4.512023, 2025
Gambia, The GMB46.1%4.312023, 2025
Haiti HTI45.9%3.622023, 2020
Guinea GIN45.7%4.612023, 2025

World Bank, World Development Indicators
Helliwell, J. et al., World Happiness Report; underlying data Gallup World Poll

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

Life satisfaction

Life satisfaction (Cantril ladder score)

Gallup / World Happiness Report · via Our World in Data · CC BY 4.0 · updated annual

The national average answer to the "Cantril ladder" question: "Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top...". It is a direct survey measure, not a combined index. The six factors the World Happiness Report uses to explain the ladder are not part of it. Values are usually three-year rolling averages of the Gallup World Poll. So each year's value overlaps with the next, and they are not separate readings.

How this was computed

Data used: most recent value in 2010-2025; values come from 2011–2025. 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 Life satisfaction

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

More links with Anaemia in women or Life satisfaction