placestats

Female labor participation vs. Tobacco use

Holds up after adjusting for income

Across 157 countries, Female labor participation and Tobacco use rise and fall together at r = -0.21 (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 = -0.21, q = 0.016, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of female labor participation, 45.5% to 60.8% of women 15+, tobacco use is better by 2.18% of adults at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.16% of adults.

Link before adjusting (r)-0.211p = 0.008 · 157 countries
After adjusting for national income-0.214p = 0.007 · likely range [-0.36, -0.06]
p, allowing for regions0.001standard error 0.033 · 7 regions
Check for luck (q)0.016across 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
Tobacco use · % of adultslink with income +0.24 · independent

Neither of these is closely tied to national income, so adjusting for income is a real test here, not a formality.

“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+ →Tobacco use · % of adults →5.09%82.9%3.1%48.8%Afghanistan: 5.09% of women 15+, 22.1% of adultsAlbania: 58.6% of women 15+, 21.4% of adultsUnited Arab Emirates: 53% of women 15+, 9% of adultsArgentina: 52.5% of women 15+, 23.5% of adultsArmenia: 51.1% of women 15+, 26.2% of adultsAustralia: 62.5% of women 15+, 11.6% of adultsAustria: 55.1% of women 15+, 23.8% of adultsAzerbaijan: 60.8% of women 15+, 18.7% of adultsBurundi: 79.5% of women 15+, 10.1% of adultsBelgium: 49.8% of women 15+, 23.5% of adultsBenin: 75.2% of women 15+, 7.4% of adultsBurkina Faso: 64.1% of women 15+, 11.6% of adultsBangladesh: 38.6% of women 15+, 32% of adultsBulgaria: 50.4% of women 15+, 38.7% of adultsBahrain: 42.3% of women 15+, 15.4% of adultsBahamas, The: 70.7% of women 15+, 17.3% of adultsBosnia and Herzegovina: 39.2% of women 15+, 37.1% of adultsBelarus: 56.8% of women 15+, 29.2% of adultsBelize: 46.5% of women 15+, 8.5% of adultsBolivia: 72.9% of women 15+, 12.3% of adultsBrazil: 53.4% of women 15+, 11.9% of adultsBrunei Darussalam: 54.4% of women 15+, 14.5% of adultsBhutan: 56.7% of women 15+, 19.6% of adultsBotswana: 63.7% of women 15+, 18% of adultsCanada: 60.2% of women 15+, 11.2% of adultsSwitzerland: 62.2% of women 15+, 23.1% of adultsChile: 52.9% of women 15+, 26.7% of adultsChina: 59.1% of women 15+, 22.8% of adultsCote d'Ivoire: 59.5% of women 15+, 7.3% of adultsCameroon: 56.6% of women 15+, 5.7% of adultsCongo, Dem. Rep.: 61.8% of women 15+, 12.3% of adultsCongo, Rep.: 65.6% of women 15+, 16.2% of adultsColombia: 51.6% of women 15+, 8% of adultsComoros: 47.6% of women 15+, 8.9% of adultsCabo Verde: 50.5% of women 15+, 10.4% of adultsCosta Rica: 46% of women 15+, 7.9% of adultsCyprus: 61.2% of women 15+, 32.5% of adultsCzechia: 53.5% of women 15+, 28.4% of adultsGermany: 55.3% of women 15+, 22% of adultsDenmark: 60.8% of women 15+, 15.7% of adultsAlgeria: 14.1% of women 15+, 22.4% of adultsEcuador: 52.4% of women 15+, 10.1% of adultsEgypt, Arab Rep.: 18.5% of women 15+, 25% of adultsSpain: 52.8% of women 15+, 27.6% of adultsEstonia: 61% of women 15+, 26.1% of adultsEthiopia: 58.5% of women 15+, 5.2% of adultsFinland: 56.5% of women 15+, 21.4% of adultsFiji: 38.5% of women 15+, 25.8% of adultsFrance: 51.5% of women 15+, 33.6% of adultsGabon: 41.6% of women 15+, 13.3% of adultsUnited Kingdom: 57.3% of women 15+, 12.8% of adultsGeorgia: 56.7% of women 15+, 33% of adultsGhana: 55.3% of women 15+, 3.3% of adultsGambia, The: 45.5% of women 15+, 11.1% of adultsGuinea-Bissau: 60.3% of women 15+, 8.2% of adultsGreece: 44.7% of women 15+, 30.2% of adultsGuatemala: 38.3% of women 15+, 11.2% of adultsGuyana: 47.4% of women 15+, 11.7% of adultsHonduras: 39.6% of women 15+, 12.1% of adultsCroatia: 47.4% of women 15+, 34.4% of adultsHaiti: 58.3% of women 15+, 8% of adultsHungary: 54.3% of women 15+, 30.8% of adultsIndonesia: 53.7% of women 15+, 31% of adultsIndia: 32.4% of women 15+, 22.6% of adultsIreland: 59.8% of women 15+, 18.2% of adultsIran, Islamic Rep.: 14% of women 15+, 11.9% of adultsIraq: 10.9% of women 15+, 20.1% of adultsIceland: 70% of women 15+, 9.2% of adultsIsrael: 62.3% of women 15+, 21.2% of adultsItaly: 40.8% of women 15+, 22.4% of adultsJamaica: 63% of women 15+, 11.5% of adultsJordan: 16% of women 15+, 34.1% of adultsJapan: 55.9% of women 15+, 17.5% of adultsKazakhstan: 62.6% of women 15+, 21.1% of adultsKenya: 63% of women 15+, 9.6% of adultsKyrgyz Republic: 44.1% of women 15+, 22.2% of adultsCambodia: 77.4% of women 15+, 18.6% of adultsKorea, Rep.: 56.8% of women 15+, 18.6% of adultsKuwait: 47.2% of women 15+, 19.4% of adultsLao PDR: 61.6% of women 15+, 25.4% of adultsLebanon: 22.2% of women 15+, 46.9% of adultsLiberia: 72% of women 15+, 5.2% of adultsLibya: 33% of women 15+, 24.2% of adultsSt. Lucia: 62% of women 15+, 13.9% of adultsSri Lanka: 31% of women 15+, 20.7% of adultsLesotho: 48.1% of women 15+, 28% of adultsLithuania: 57.7% of women 15+, 31.4% of adultsLuxembourg: 57.5% of women 15+, 24.5% of adultsLatvia: 55.2% of women 15+, 34.6% of adultsMorocco: 19.7% of women 15+, 12.5% of adultsMoldova: 72.3% of women 15+, 28.8% of adultsMadagascar: 82.9% of women 15+, 25.6% of adultsMaldives: 40.7% of women 15+, 25.5% of adultsMexico: 47.5% of women 15+, 15.7% of adultsNorth Macedonia: 42.7% of women 15+, 39.6% of adultsMali: 52.8% of women 15+, 7.4% of adultsMalta: 55.8% of women 15+, 24.6% of adultsMyanmar: 40.9% of women 15+, 43.4% of adultsMontenegro: 51.2% of women 15+, 37.2% of adultsMongolia: 51.5% of women 15+, 29.5% of adultsMozambique: 77.1% of women 15+, 10.5% of adultsMauritania: 26.2% of women 15+, 9.9% of adultsMauritius: 47.5% of women 15+, 17.7% of adultsMalawi: 58.2% of women 15+, 8.9% of adultsMalaysia: 51.6% of women 15+, 16.9% of adultsNiger: 72.8% of women 15+, 7.4% of adultsNigeria: 80.7% of women 15+, 3.1% of adultsNetherlands: 62.7% of women 15+, 20.5% of adultsNorway: 62.1% of women 15+, 12.9% of adultsNepal: 27.5% of women 15+, 28.7% of adultsNew Zealand: 66.1% of women 15+, 9.3% of adultsOman: 30% of women 15+, 8.5% of adultsPakistan: 24% of women 15+, 17.9% of adultsPanama: 54.9% of women 15+, 4.8% of adultsPeru: 65% of women 15+, 12.4% of adultsPhilippines: 50.5% of women 15+, 19.9% of adultsPapua New Guinea: 50.8% of women 15+, 39.3% of adultsPoland: 51.6% of women 15+, 21.7% of adultsPortugal: 54.6% of women 15+, 28.6% of adultsParaguay: 59% of women 15+, 6.4% of adultsWest Bank and Gaza: 18.9% of women 15+, 35.5% of adultsQatar: 61.9% of women 15+, 12.5% of adultsRomania: 41.8% of women 15+, 29.7% of adultsRussian Federation: 54.5% of women 15+, 27% of adultsRwanda: 57.3% of women 15+, 10.1% of adultsSaudi Arabia: 33.6% of women 15+, 14.7% of adultsSenegal: 38.2% of women 15+, 5.4% of adultsSingapore: 63.6% of women 15+, 13.8% of adultsSolomon Islands: 82.3% of women 15+, 38.4% of adultsSierra Leone: 51.6% of women 15+, 11.3% of adultsEl Salvador: 49.1% of women 15+, 8.2% of adultsSerbia: 52.6% of women 15+, 39.7% of adultsSao Tome and Principe: 22.7% of women 15+, 8.3% of adultsSlovak Republic: 55.1% of women 15+, 29.5% of adultsSlovenia: 52.3% of women 15+, 20.9% of adultsSweden: 61.5% of women 15+, 20.3% of adultsEswatini: 48.5% of women 15+, 11.5% of adultsChad: 47.3% of women 15+, 7.4% of adultsTogo: 56.6% of women 15+, 5.8% of adultsThailand: 59% of women 15+, 17.8% of adultsTurkmenistan: 38.2% of women 15+, 5.4% of adultsTimor-Leste: 61.7% of women 15+, 48.8% of adultsTonga: 42.3% of women 15+, 32.1% of adultsTunisia: 26.5% of women 15+, 24.4% of adultsTurkiye: 37.1% of women 15+, 31.1% of adultsTanzania: 80.3% of women 15+, 7.7% of adultsUganda: 75.6% of women 15+, 7.5% of adultsUkraine: 47.7% of women 15+, 23.7% of adultsUruguay: 57.3% of women 15+, 19.3% of adultsUnited States: 56.3% of women 15+, 15.8% of adultsUzbekistan: 41.2% of women 15+, 16.3% of adultsViet Nam: 68.6% of women 15+, 21.1% of adultsVanuatu: 53.3% of women 15+, 24.9% of adultsSamoa: 30.7% of women 15+, 23.1% of adultsSouth Africa: 49.9% of women 15+, 23.7% of adultsZambia: 56.4% of women 15+, 14.3% of adultsZimbabwe: 62.2% of women 15+, 11% of adultsAFGBDIIRNJORLBNMDGNGAPSESLBSTPTLSTZA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.2110.008157
By rank (Spearman), not adjusted-0.2420.002157
Standard (Pearson), adjusted for national income-0.2140.007157
By rank (Spearman), adjusted for national income-0.2610.001157

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 157 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: -0.003 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.253 (without SLB) to -0.184 (without LBN). 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: SLB (-0.039).

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 & Pacific23-0.19
Europe & Central Asia47-0.19
Latin America & Caribbean21+0.13
Middle East, North Africa, Afghanistan & Pakistan20+0.17
Sub-Saharan Africa38+0.02

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 third53-0.22
Middle third52-0.21
Richest third52-0.07

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
Christians94-0.09
Muslims43-0.44

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
France21-0.04
Never a European colony20-0.07
Spain16-0.03
United Kingdom49-0.40

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 = -0.164 after dropping 10 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 = -0.010, 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 tobacco use move with it.

Across countries (adjusted)-0.214for comparison
Within countries-0.131each country vs itself
…and vs the same year elsewhere-0.010q = 0.940 · 159 countries
Year-on-year changes-0.001q = 0.992
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.

1,425 country-years (one country in one year), 159 countries, 2000–2024, about 9 years each on average. Share of the variation that happens within countries over time: 5% for Female labor participation, 19% for Tobacco use. 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 Tobacco use trails Female labor participation →lag -10: r = -0.047 (n = 780)lag -9: r = -0.024 (n = 780)lag -8: r = -0.023 (n = 785)lag -7: r = -0.000 (n = 790)lag -6: r = 0.015 (n = 795)lag -5: r = 0.003 (n = 951)lag -4: r = 0.019 (n = 951)lag -3: r = -0.009 (n = 1,108)lag -2: r = -0.001 (n = 1,265)lag -1: r = -0.005 (n = 1,423)lag +0: r = -0.010 (n = 1,425)lag +1: r = -0.008 (n = 1,428)lag +2: r = -0.018 (n = 1,430)lag +3: r = -0.009 (n = 1,431)lag +4: r = -0.009 (n = 1,431)lag +5: r = 0.003 (n = 1,431)lag +6: r = 0.000 (n = 1,431)lag +7: r = 0.005 (n = 1,431)lag +8: r = 0.007 (n = 1,431)lag +9: r = -0.004 (n = 1,431)lag +10: r = -0.012 (n = 1,431)

Same year (lag 0): -0.010. 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.

This curve peaks at the edge of the window (lag -10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data


% of women 15+
% of adults		Years
Madagascar MDG82.9%25.6%2025, 2024
Solomon Islands SLB82.3%38.4%2025, 2024
Nigeria NGA80.7%3.1%2025, 2024
Tanzania TZA80.3%7.7%2025, 2024
Burundi BDI79.5%10.1%2025, 2024
Cambodia KHM77.4%18.6%2025, 2024
Mozambique MOZ77.1%10.5%2025, 2024
Uganda UGA75.6%7.5%2025, 2024
Benin BEN75.2%7.4%2025, 2024
Bolivia BOL72.9%12.3%2025, 2024
Niger NER72.8%7.4%2025, 2024
Moldova MDA72.3%28.8%2025, 2024
Liberia LBR72%5.2%2025, 2024
Bahamas, The BHS70.7%17.3%2025, 2024
Iceland ISL70%9.2%2025, 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

Tobacco use

Prevalence of current tobacco use (% of adults, age-standardised)

World Health Organization · CC BY 4.0 · updated quarterly

Published every other year.

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 Tobacco use

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

More links with Female labor participation or Tobacco use