placestats

Female labor participation vs. Tuberculosis incidence

Holds up after adjusting for income

Across 176 countries, Female labor participation and Tuberculosis incidence rise and fall together at r = +0.09 (on a scale from −1 to +1, where 0 means no link). There is almost no link to explain.

Comparing countries across the middle half of female labor participation, 43.8% to 60.8% of women 15+, tuberculosis incidence is worse by 12.9 per 100,000 people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 17.9 per 100,000 people.

Link before adjusting (r)+0.087p = 0.252 · 176 countries
After adjusting for national income+0.140p = 0.065 · likely range [-0.01, +0.28]
p, allowing for regions0.003standard error 0.029 · 7 regions
Check for luck (q)0.038across 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.

Female labor participation · % of women 15+link with income +0.07 · independent
Tuberculosis incidence · per 100,000 peoplelink with income -0.67 · high

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

Every country as a dot

Female labor participation · % of women 15+ →Tuberculosis incidence · per 100,000 people →5.09%82.9%0.29664Afghanistan: 5.09% of women 15+, 203 per 100,000 peopleAngola: 72.2% of women 15+, 373 per 100,000 peopleAlbania: 58.6% of women 15+, 15 per 100,000 peopleUnited Arab Emirates: 53% of women 15+, 0.63 per 100,000 peopleArgentina: 52.5% of women 15+, 44 per 100,000 peopleArmenia: 51.1% of women 15+, 19 per 100,000 peopleAustralia: 62.5% of women 15+, 6.9 per 100,000 peopleAustria: 55.1% of women 15+, 4.9 per 100,000 peopleAzerbaijan: 60.8% of women 15+, 64 per 100,000 peopleBurundi: 79.5% of women 15+, 83 per 100,000 peopleBelgium: 49.8% of women 15+, 2.7 per 100,000 peopleBenin: 75.2% of women 15+, 40 per 100,000 peopleBurkina Faso: 64.1% of women 15+, 57 per 100,000 peopleBangladesh: 38.6% of women 15+, 221 per 100,000 peopleBulgaria: 50.4% of women 15+, 12 per 100,000 peopleBahrain: 42.3% of women 15+, 12 per 100,000 peopleBahamas, The: 70.7% of women 15+, 18 per 100,000 peopleBosnia and Herzegovina: 39.2% of women 15+, 21 per 100,000 peopleBelarus: 56.8% of women 15+, 17 per 100,000 peopleBelize: 46.5% of women 15+, 34 per 100,000 peopleBolivia: 72.9% of women 15+, 114 per 100,000 peopleBrazil: 53.4% of women 15+, 49 per 100,000 peopleBarbados: 61% of women 15+, 1 per 100,000 peopleBrunei Darussalam: 54.4% of women 15+, 65 per 100,000 peopleBhutan: 56.7% of women 15+, 191 per 100,000 peopleBotswana: 63.7% of women 15+, 143 per 100,000 peopleCentral African Republic: 65.5% of women 15+, 419 per 100,000 peopleCanada: 60.2% of women 15+, 6.2 per 100,000 peopleSwitzerland: 62.2% of women 15+, 5.4 per 100,000 peopleChile: 52.9% of women 15+, 19 per 100,000 peopleChina: 59.1% of women 15+, 49 per 100,000 peopleCote d'Ivoire: 59.5% of women 15+, 99 per 100,000 peopleCameroon: 56.6% of women 15+, 132 per 100,000 peopleCongo, Dem. Rep.: 61.8% of women 15+, 377 per 100,000 peopleCongo, Rep.: 65.6% of women 15+, 302 per 100,000 peopleColombia: 51.6% of women 15+, 49 per 100,000 peopleComoros: 47.6% of women 15+, 22 per 100,000 peopleCabo Verde: 50.5% of women 15+, 47 per 100,000 peopleCosta Rica: 46% of women 15+, 9.3 per 100,000 peopleCyprus: 61.2% of women 15+, 5.5 per 100,000 peopleCzechia: 53.5% of women 15+, 4.9 per 100,000 peopleGermany: 55.3% of women 15+, 5.4 per 100,000 peopleDjibouti: 19.4% of women 15+, 495 per 100,000 peopleDenmark: 60.8% of women 15+, 3.2 per 100,000 peopleDominican Republic: 53.7% of women 15+, 51 per 100,000 peopleAlgeria: 14.1% of women 15+, 54 per 100,000 peopleEcuador: 52.4% of women 15+, 66 per 100,000 peopleEgypt, Arab Rep.: 18.5% of women 15+, 10 per 100,000 peopleSpain: 52.8% of women 15+, 7.9 per 100,000 peopleEstonia: 61% of women 15+, 8.2 per 100,000 peopleEthiopia: 58.5% of women 15+, 141 per 100,000 peopleFinland: 56.5% of women 15+, 3.7 per 100,000 peopleFiji: 38.5% of women 15+, 104 per 100,000 peopleFrance: 51.5% of women 15+, 7.8 per 100,000 peopleGabon: 41.6% of women 15+, 371 per 100,000 peopleUnited Kingdom: 57.3% of women 15+, 9.7 per 100,000 peopleGeorgia: 56.7% of women 15+, 45 per 100,000 peopleGhana: 55.3% of women 15+, 126 per 100,000 peopleGuinea: 42.6% of women 15+, 178 per 100,000 peopleGambia, The: 45.5% of women 15+, 138 per 100,000 peopleGuinea-Bissau: 60.3% of women 15+, 176 per 100,000 peopleEquatorial Guinea: 52.6% of women 15+, 199 per 100,000 peopleGreece: 44.7% of women 15+, 3.6 per 100,000 peopleGuatemala: 38.3% of women 15+, 28 per 100,000 peopleGuyana: 47.4% of women 15+, 67 per 100,000 peopleHong Kong SAR, China: 51.8% of women 15+, 66 per 100,000 peopleHonduras: 39.6% of women 15+, 38 per 100,000 peopleCroatia: 47.4% of women 15+, 6.6 per 100,000 peopleHaiti: 58.3% of women 15+, 175 per 100,000 peopleHungary: 54.3% of women 15+, 5.6 per 100,000 peopleIndonesia: 53.7% of women 15+, 382 per 100,000 peopleIndia: 32.4% of women 15+, 187 per 100,000 peopleIreland: 59.8% of women 15+, 6.2 per 100,000 peopleIran, Islamic Rep.: 14% of women 15+, 10 per 100,000 peopleIraq: 10.9% of women 15+, 21 per 100,000 peopleIceland: 70% of women 15+, 3 per 100,000 peopleIsrael: 62.3% of women 15+, 2.4 per 100,000 peopleItaly: 40.8% of women 15+, 5 per 100,000 peopleJamaica: 63% of women 15+, 2.3 per 100,000 peopleJordan: 16% of women 15+, 3.5 per 100,000 peopleJapan: 55.9% of women 15+, 9.8 per 100,000 peopleKazakhstan: 62.6% of women 15+, 45 per 100,000 peopleKenya: 63% of women 15+, 207 per 100,000 peopleKyrgyz Republic: 44.1% of women 15+, 128 per 100,000 peopleCambodia: 77.4% of women 15+, 272 per 100,000 peopleKorea, Rep.: 56.8% of women 15+, 35 per 100,000 peopleKuwait: 47.2% of women 15+, 10 per 100,000 peopleLao PDR: 61.6% of women 15+, 127 per 100,000 peopleLebanon: 22.2% of women 15+, 13 per 100,000 peopleLiberia: 72% of women 15+, 207 per 100,000 peopleLibya: 33% of women 15+, 63 per 100,000 peopleSt. Lucia: 62% of women 15+, 0.56 per 100,000 peopleSri Lanka: 31% of women 15+, 59 per 100,000 peopleLesotho: 48.1% of women 15+, 548 per 100,000 peopleLithuania: 57.7% of women 15+, 31 per 100,000 peopleLuxembourg: 57.5% of women 15+, 7.5 per 100,000 peopleLatvia: 55.2% of women 15+, 21 per 100,000 peopleMacao SAR, China: 63.1% of women 15+, 59 per 100,000 peopleMorocco: 19.7% of women 15+, 98 per 100,000 peopleMoldova: 72.3% of women 15+, 64 per 100,000 peopleMadagascar: 82.9% of women 15+, 224 per 100,000 peopleMaldives: 40.7% of women 15+, 40 per 100,000 peopleMexico: 47.5% of women 15+, 28 per 100,000 peopleNorth Macedonia: 42.7% of women 15+, 11 per 100,000 peopleMali: 52.8% of women 15+, 51 per 100,000 peopleMalta: 55.8% of women 15+, 15 per 100,000 peopleMyanmar: 40.9% of women 15+, 482 per 100,000 peopleMontenegro: 51.2% of women 15+, 16 per 100,000 peopleMongolia: 51.5% of women 15+, 446 per 100,000 peopleMozambique: 77.1% of women 15+, 361 per 100,000 peopleMauritania: 26.2% of women 15+, 65 per 100,000 peopleMauritius: 47.5% of women 15+, 13 per 100,000 peopleMalawi: 58.2% of women 15+, 113 per 100,000 peopleMalaysia: 51.6% of women 15+, 96 per 100,000 peopleNamibia: 54.9% of women 15+, 422 per 100,000 peopleNiger: 72.8% of women 15+, 86 per 100,000 peopleNigeria: 80.7% of women 15+, 219 per 100,000 peopleNicaragua: 51.3% of women 15+, 43 per 100,000 peopleNetherlands: 62.7% of women 15+, 4.7 per 100,000 peopleNorway: 62.1% of women 15+, 3.3 per 100,000 peopleNepal: 27.5% of women 15+, 227 per 100,000 peopleNew Zealand: 66.1% of women 15+, 7.9 per 100,000 peopleOman: 30% of women 15+, 11 per 100,000 peoplePakistan: 24% of women 15+, 266 per 100,000 peoplePanama: 54.9% of women 15+, 63 per 100,000 peoplePeru: 65% of women 15+, 139 per 100,000 peoplePhilippines: 50.5% of women 15+, 625 per 100,000 peoplePapua New Guinea: 50.8% of women 15+, 664 per 100,000 peoplePoland: 51.6% of women 15+, 11 per 100,000 peoplePuerto Rico (US): 36.9% of women 15+, 0.55 per 100,000 peoplePortugal: 54.6% of women 15+, 15 per 100,000 peopleParaguay: 59% of women 15+, 81 per 100,000 peopleWest Bank and Gaza: 18.9% of women 15+, 0.29 per 100,000 peopleQatar: 61.9% of women 15+, 37 per 100,000 peopleRomania: 41.8% of women 15+, 60 per 100,000 peopleRussian Federation: 54.5% of women 15+, 34 per 100,000 peopleRwanda: 57.3% of women 15+, 62 per 100,000 peopleSaudi Arabia: 33.6% of women 15+, 8.4 per 100,000 peopleSudan: 14.5% of women 15+, 47 per 100,000 peopleSenegal: 38.2% of women 15+, 132 per 100,000 peopleSingapore: 63.6% of women 15+, 43 per 100,000 peopleSolomon Islands: 82.3% of women 15+, 123 per 100,000 peopleSierra Leone: 51.6% of women 15+, 372 per 100,000 peopleEl Salvador: 49.1% of women 15+, 116 per 100,000 peopleSomalia, Fed. Rep.: 20.7% of women 15+, 151 per 100,000 peopleSerbia: 52.6% of women 15+, 8.7 per 100,000 peopleSao Tome and Principe: 22.7% of women 15+, 87 per 100,000 peopleSuriname: 44.9% of women 15+, 34 per 100,000 peopleSlovak Republic: 55.1% of women 15+, 3.3 per 100,000 peopleSlovenia: 52.3% of women 15+, 2.6 per 100,000 peopleSweden: 61.5% of women 15+, 3.3 per 100,000 peopleEswatini: 48.5% of women 15+, 319 per 100,000 peopleSyrian Arab Republic: 12.7% of women 15+, 23 per 100,000 peopleChad: 47.3% of women 15+, 118 per 100,000 peopleTogo: 56.6% of women 15+, 48 per 100,000 peopleThailand: 59% of women 15+, 146 per 100,000 peopleTajikistan: 21.9% of women 15+, 75 per 100,000 peopleTurkmenistan: 38.2% of women 15+, 40 per 100,000 peopleTimor-Leste: 61.7% of women 15+, 496 per 100,000 peopleTonga: 42.3% of women 15+, 1.9 per 100,000 peopleTrinidad and Tobago: 47.8% of women 15+, 27 per 100,000 peopleTunisia: 26.5% of women 15+, 39 per 100,000 peopleTurkiye: 37.1% of women 15+, 13 per 100,000 peopleTanzania: 80.3% of women 15+, 172 per 100,000 peopleUganda: 75.6% of women 15+, 197 per 100,000 peopleUkraine: 47.7% of women 15+, 86 per 100,000 peopleUruguay: 57.3% of women 15+, 47 per 100,000 peopleUnited States: 56.3% of women 15+, 3.2 per 100,000 peopleUzbekistan: 41.2% of women 15+, 51 per 100,000 peopleSt. Vincent and the Grenadines: 59.2% of women 15+, 4.6 per 100,000 peopleViet Nam: 68.6% of women 15+, 182 per 100,000 peopleVanuatu: 53.3% of women 15+, 44 per 100,000 peopleSamoa: 30.7% of women 15+, 5.5 per 100,000 peopleSouth Africa: 49.9% of women 15+, 389 per 100,000 peopleZambia: 56.4% of women 15+, 272 per 100,000 peopleZimbabwe: 62.2% of women 15+, 203 per 100,000 peopleBDIBENDJIIRNIRQISLPHLPNGSYRTLS

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.0870.252176
By rank (Spearman), not adjusted+0.0680.369176
Standard (Pearson), adjusted for national income+0.1400.065176
By rank (Spearman), adjusted for national income+0.1560.040176

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 176 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: -0.053 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.122 (without SDN) to +0.182 (without DJI). 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: DJI (+0.042).

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 & Pacific25-0.06
Europe & Central Asia48+0.21
Latin America & Caribbean28+0.26
Middle East, North Africa, Afghanistan & Pakistan22+0.21
Sub-Saharan Africa45+0.18

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 third59+0.15
Middle third58+0.31
Richest third59-0.01

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
Christians105-0.02
Muslims49+0.16

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+0.18
Spain19+0.18
United Kingdom55+0.15

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 = +0.212 after dropping 24 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 25years. 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 = +0.097, 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 female labor participation moved did not tend to see their tuberculosis incidence move with it.

Across countries (adjusted)+0.140for comparison
Within countries+0.041each country vs itself
…and vs the same year elsewhere+0.097q = 0.065 · 184 countries
Year-on-year changes+0.016q = 0.152
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.

4,568 country-years (one country in one year), 184 countries, 2000–2024, about 25 years each on average. Share of the variation that happens within countries over time: 4% for Female labor participation, 17% for Tuberculosis incidence. 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

0.20−0.2-100+10years Tuberculosis incidence trails Female labor participation →lag -10: r = 0.020 (n = 2,904)lag -9: r = 0.033 (n = 3,087)lag -8: r = 0.039 (n = 3,275)lag -7: r = 0.047 (n = 3,459)lag -6: r = 0.055 (n = 3,643)lag -5: r = 0.065 (n = 3,827)lag -4: r = 0.074 (n = 4,011)lag -3: r = 0.080 (n = 4,195)lag -2: r = 0.087 (n = 4,379)lag -1: r = 0.093 (n = 4,563)lag +0: r = 0.097 (n = 4,568)lag +1: r = 0.100 (n = 4,573)lag +2: r = 0.103 (n = 4,576)lag +3: r = 0.106 (n = 4,577)lag +4: r = 0.108 (n = 4,577)lag +5: r = 0.109 (n = 4,577)lag +6: r = 0.107 (n = 4,577)lag +7: r = 0.104 (n = 4,577)lag +8: r = 0.100 (n = 4,577)lag +9: r = 0.096 (n = 4,577)lag +10: r = 0.093 (n = 4,577)

Same year (lag 0): +0.097. 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 15+
per 100,000 people		Years
Madagascar MDG82.9%2242025, 2024
Solomon Islands SLB82.3%1232025, 2024
Nigeria NGA80.7%2192025, 2024
Tanzania TZA80.3%1722025, 2024
Burundi BDI79.5%832025, 2024
Cambodia KHM77.4%2722025, 2024
Mozambique MOZ77.1%3612025, 2024
Uganda UGA75.6%1972025, 2024
Benin BEN75.2%402025, 2024
Bolivia BOL72.9%1142025, 2024
Niger NER72.8%862025, 2024
Moldova MDA72.3%642025, 2024
Angola AGO72.2%3732025, 2024
Liberia LBR72%2072025, 2024
Bahamas, The BHS70.7%182025, 2024

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

Female labor participation

Labor force participation rate, female (% of female population 15+)

International Labour Organization · CC BY 4.0 · updated quarterly

Tuberculosis incidence

Incidence of tuberculosis (per 100,000 people)

World Health Organization · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2025. 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 Female labor participation and Tuberculosis incidence

This page shows that two measures go together. It does not show that Female labor participation changes Tuberculosis incidence, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Female labor participation or Tuberculosis incidence