Saint Kitts and Nevis
KNACaribbean · Americas · UN member
The circle shows each metric's percentile rank (position among countries with data), which is comparable across metrics. Each metric's native score uses its own scale and is not comparable between metrics — see it (and the full formula) in “How is this calculated?”.
57 metrics for this country
Society & culture
100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
Ranks 116th of 200 · native score 43.23 · reference year 1996
42percentileHow is this calculated?
- Metric
- Adult male height
- Scale
- 100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
- Raw value
- 169.623 cm
- Native score
- 43.23 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 42th percentile — ranks 116th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (169.62 − 159.79) / (182.54 − 159.79) = 43.23Min and max are this dataset's lowest (159.79) and highest (182.54) values, so the score is relative to the current country set.
- Source
- NCD Risk Factor Collaboration (via Our World in Data) · NCD Risk Factor Collaboration (NCD-RisC)
- License
- CC BY 4.0
- Reference year
- 1996
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Pooled analysis of population-based measured-height studies, retrieved via the Our World in Data mirror. Indexed by year of birth.
100 = highest cocoa supply per person in the dataset, 0 = lowest
Ranks 139th of 191 · native score 1.56 · reference year 2023
27percentileLow reliability (Tier C — Survey / proxy). Survey-based, patchy, or proxy metric. Indicative only — coverage gaps and methodology limits are significant. Not a definitive ranking.
How is this calculated?
- Metric
- Chocolate supply per person (proxy)
- Scale
- 100 = highest cocoa supply per person in the dataset, 0 = lowest
- Raw value
- 0.219892 kg cocoa per person / year
- Native score
- 1.56 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 27th percentile — ranks 139th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.22 − 0) / (14.07 − 0) = 1.56Min and max are this dataset's lowest (0) and highest (14.07) values, so the score is relative to the current country set.
- Source
- FAO (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier C — Survey / proxy
- Source notes
- Cocoa 'food available for consumption' per capita from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. A supply proxy, not measured consumption — Tier C.
100 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse
Ranks 26th of 191 · native score 43.18 · reference year 2023
87percentileHow is this calculated?
- Metric
- Fish & seafood supply per capita
- Scale
- 100 = highest fish & seafood supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 36.4021 kg per person per year
- Native score
- 43.18 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 87th percentile — ranks 26th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (36.4 − 0.38) / (83.81 − 0.38) = 43.18Min and max are this dataset's lowest (0.38) and highest (83.81) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
Ranks 8th of 191 · native score 36.95 · reference year 2023
96percentileHow is this calculated?
- Metric
- Fruit supply per capita
- Scale
- 100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 198.173 kg per person per year
- Native score
- 36.95 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 96th percentile — ranks 8th of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (198.17 − 4.27) / (529.06 − 4.27) = 36.95Min and max are this dataset's lowest (4.27) and highest (529.06) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
Ranks 31st of 191 · native score 55.62 · reference year 2023
84percentileHow is this calculated?
- Metric
- Meat supply per capita
- Scale
- 100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 88.8363 kg per person per year
- Native score
- 55.62 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 84th percentile — ranks 31st of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (88.84 − 3.49) / (156.93 − 3.49) = 55.62Min and max are this dataset's lowest (3.49) and highest (156.93) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
100 = universal social protection coverage, 0 = none
Ranks 44th of 214 · native score 90.2 · reference year 2020
80percentileHow is this calculated?
- Metric
- Social protection coverage
- Scale
- 100 = universal social protection coverage, 0 = none
- Raw value
- 90.2 % of population
- Native score
- 90.2 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 80th percentile — ranks 44th of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (90.2 − 0) / (100 − 0) = 90.2The index is kept on its own published scale.
- Source
- ILOSTAT (International Labour Organization) · International Labour Organization
- License
- CC BY 4.0
- Reference year
- 2020
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- ILOSTAT via the ILO rplumber API (rplumber.ilo.org). CC BY 4.0 for databases published since 3 May 2023.
100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
Ranks 152nd of 174 · native score 34.42 · reference year 2019
13percentileHow is this calculated?
- Metric
- International tourist arrivals
- Scale
- 100 = most arrivals (2019), 0 = fewest — descriptive, not better or worse
- Raw value
- 120,000 arrivals per year
- Native score
- 34.42 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 13th percentile — ranks 152nd of 174. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 120,000 − ln 3,700) / (ln 90,914,000 − ln 3,700) = 34.42Log scale (values are heavily skewed). 0 and 100 are the dataset's min (3,700) and max (90,914,000) — relative, not absolute or year-over-year comparable.
- Source
- UN Tourism (via Our World in Data) · UN Tourism (UNWTO)
- License
- CC BY 4.0
- Reference year
- 2019
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- International tourist arrivals — overnight visitors — from UN Tourism (UNWTO), retrieved via the Our World in Data mirror (OWID's processing layer is CC BY; underlying values are UN Tourism).
100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
Ranks 163rd of 191 · native score 7.53 · reference year 2023
15percentileHow is this calculated?
- Metric
- Vegetable supply per capita
- Scale
- 100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
- Raw value
- 36.0323 kg per person per year
- Native score
- 7.53 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 15th percentile — ranks 163rd of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (36.03 − 5.34) / (412.72 − 5.34) = 7.53Min and max are this dataset's lowest (5.34) and highest (412.72) values, so the score is relative to the current country set.
- Source
- FAO Food Balance Sheets (via Our World in Data) · Food and Agriculture Organization of the UN (FAO)
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita food available for consumption from the FAO Food Balance Sheets, retrieved via the Our World in Data mirror. This is national food SUPPLY per person, not measured intake.
Demographics & migration
100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
Ranks 191st of 215 · native score 27.44 · reference year 2025
11percentileHow is this calculated?
- Metric
- Age dependency ratio
- Scale
- 100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 42.9751 dependents per 100 working-age
- Native score
- 27.44 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 11th percentile — ranks 191st of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (42.98 − 20.05) / (103.59 − 20.05) = 27.44Min and max are this dataset's lowest (20.05) and highest (103.59) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest fertility, 0 = lowest — descriptive, not better or worse
Ranks 146th of 215 · native score 17.33 · reference year 2024
32percentileHow is this calculated?
- Metric
- Fertility rate
- Scale
- 100 = highest fertility, 0 = lowest — descriptive, not better or worse
- Raw value
- 1.526 births per woman
- Native score
- 17.33 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 32th percentile — ranks 146th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.53 − 0.58) / (6.03 − 0.58) = 17.33Min and max are this dataset's lowest (0.58) and highest (6.03) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
Ranks 25th of 215 · native score 68.98 · reference year 2024
88percentileHow is this calculated?
- Metric
- Life expectancy gap (female − male)
- Scale
- 100 = largest female−male gap, 0 = smallest (or male-favouring) — descriptive, not better or worse
- Raw value
- 7.467 years (female − male)
- Native score
- 68.98 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 88th percentile — ranks 25th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (7.47 − 0.46) / (10.62 − 0.46) = 68.98Min and max are this dataset's lowest (0.46) and highest (10.62) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = oldest median age, 0 = youngest — descriptive, not better or worse
Ranks 97th of 237 · native score 46.42 · reference year 2023
59percentileHow is this calculated?
- Metric
- Median age
- Scale
- 100 = oldest median age, 0 = youngest — descriptive, not better or worse
- Raw value
- 35.349 years
- Native score
- 46.42 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 59th percentile — ranks 97th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (35.35 − 14.32) / (59.63 − 14.32) = 46.42Min and max are this dataset's lowest (14.32) and highest (59.63) values, so the score is relative to the current country set.
- Source
- UN World Population Prospects (via Our World in Data) · UN DESA, Population Division
- License
- CC BY 3.0 IGO
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- UN World Population Prospects (median age; medium-variant projections), retrieved via the Our World in Data mirror.
100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
Ranks 51st of 214 · native score 17 · reference year 2024
76percentileHow is this calculated?
- Metric
- Foreign-born population
- Scale
- 100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
- Raw value
- 17 % foreign-born
- Native score
- 17 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 76th percentile — ranks 51st of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (17 − 0) / (100 − 0) = 17The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse
Ranks 74th of 215 · native score 52.21 · reference year 2025
66percentileHow is this calculated?
- Metric
- Net migration rate
- Scale
- 100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse
- Raw value
- 0.384 per 1,000 people
- Native score
- 52.21 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 66th percentile — ranks 74th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (0.38 − -46.91) / (43.67 − -46.91) = 52.21Min and max are this dataset's lowest (-46.91) and highest (43.67) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most populous, 0 = least populous — descriptive, not better or worse
Ranks 201st of 215 · native score 13.38 · reference year 2025
7percentileHow is this calculated?
- Metric
- Total population
- Scale
- 100 = most populous, 0 = least populous — descriptive, not better or worse
- Raw value
- 46,922 people
- Native score
- 13.38 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 7th percentile — ranks 201st of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 46,922 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 13.38Log scale (values are heavily skewed). 0 and 100 are the dataset's min (9,492) and max (1,463,865,525) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most dense, 0 = least dense — descriptive, not better or worse
Ranks 67th of 215 · native score 60.2 · reference year 2023
69percentileHow is this calculated?
- Metric
- Population density
- Scale
- 100 = most dense, 0 = least dense — descriptive, not better or worse
- Raw value
- 179.838 people per km²
- Native score
- 60.2 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 69th percentile — ranks 67th of 215. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 179.84 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 60.2Log scale (values are heavily skewed). 0 and 100 are the dataset's min (0.14) and max (20,569.7) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
Ranks 179th of 237 · native score 20.66 · reference year 2050
25percentileHow is this calculated?
- Metric
- Population change (projection)
- Scale
- 100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
- Raw value
- -5.5 % change 2024→2050
- Native score
- 20.66 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 25th percentile — ranks 179th of 237. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (-5.5 − -32.9) / (99.7 − -32.9) = 20.66Min and max are this dataset's lowest (-32.9) and highest (99.7) values, so the score is relative to the current country set.
- Source
- UN World Population Prospects (via Our World in Data) · UN DESA, Population Division
- License
- CC BY 3.0 IGO
- Reference year
- 2050
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- UN World Population Prospects (median age; medium-variant projections), retrieved via the Our World in Data mirror.
100 = most refugees produced, 0 = fewest — descriptive, not better or worse
Ranks 169th of 211 · native score 20.14 · reference year 2024
20percentileHow is this calculated?
- Metric
- Refugees (by origin)
- Scale
- 100 = most refugees produced, 0 = fewest — descriptive, not better or worse
- Raw value
- 27 refugees
- Native score
- 20.14 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 20th percentile — ranks 169th of 211. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 27 among 211 countries = 20.14The score is the country's position in the distribution.
- Source
- UNHCR (via Our World in Data) · UN High Commissioner for Refugees (UNHCR)
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Refugee population by country of origin, retrieved via the Our World in Data mirror.
100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 76th of 193 · native score 7.29 · reference year 2024
61percentileHow is this calculated?
- Metric
- Remittances received
- Scale
- 100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 3.45138 % of GDP
- Native score
- 7.29 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 61th percentile — ranks 76th of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.45 − 0.01) / (47.15 − 0.01) = 7.29Min and max are this dataset's lowest (0.01) and highest (47.15) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fully rural, 0 = fully urban — descriptive, not better or worse
Ranks 25th of 215 · native score 68.1 · reference year 2025
89percentileHow is this calculated?
- Metric
- Rural population share
- Scale
- 100 = fully rural, 0 = fully urban — descriptive, not better or worse
- Raw value
- 68.1012 % rural
- Native score
- 68.1 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 89th percentile — ranks 25th of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (68.1 − 0) / (100 − 0) = 68.1The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse
Ranks 170th of 215 · native score 17.11 · reference year 2024
21percentileHow is this calculated?
- Metric
- Sex ratio at birth
- Scale
- 100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse
- Raw value
- 1.037 male births per female birth
- Native score
- 17.11 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 21th percentile — ranks 170th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (1.04 − 1.01) / (1.16 − 1.01) = 17.11Min and max are this dataset's lowest (1.01) and highest (1.16) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = fully urban, 0 = fully rural — descriptive, not better or worse
Ranks 191st of 215 · native score 31.9 · reference year 2025
11percentileHow is this calculated?
- Metric
- Urbanization
- Scale
- 100 = fully urban, 0 = fully rural — descriptive, not better or worse
- Raw value
- 31.8988 % urban
- Native score
- 31.9 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 11th percentile — ranks 191st of 215. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (31.9 − 0) / (100 − 0) = 31.9The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Economy
- New business densityTier A
100 = highest new-business density in the dataset, 0 = lowest
Ranks 10th of 182 · native score 9.3 · reference year 2024
95percentileHow is this calculated?
- Metric
- New business density
- Scale
- 100 = highest new-business density in the dataset, 0 = lowest
- Raw value
- 18.7213 new firms per 1,000 aged 15–64
- Native score
- 9.3 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 10th of 182. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (18.72 − 0.02) / (201.01 − 0.02) = 9.3Min and max are this dataset's lowest (0.02) and highest (201.01) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 65th of 201 · native score 88.71 · reference year 2024
67percentileHow is this calculated?
- Metric
- Foreign direct investment
- Scale
- 100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 3.74958 % of GDP (net inflows)
- Native score
- 88.71 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 67th percentile — ranks 65th of 201. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.75 − -1,303.11) / (170.05 − -1,303.11) = 88.71Min and max are this dataset's lowest (-1,303.11) and highest (170.05) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- GDP growth (projection)Tier B
100 = highest projected growth, 0 = lowest
Ranks 122nd of 189 · native score 13.52 · reference year 2031
36percentileHow is this calculated?
- Metric
- GDP growth (projection)
- Scale
- 100 = highest projected growth, 0 = lowest
- Raw value
- 2.48 % per year (avg 2026–2031)
- Native score
- 13.52 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 36th percentile — ranks 122nd of 189. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (2.48 − 0.62) / (14.38 − 0.62) = 13.52Min and max are this dataset's lowest (0.62) and highest (14.38) values, so the score is relative to the current country set.
- Source
- IMF (World Economic Outlook) · International Monetary Fund
- License
- IMF terms (reuse with attribution)
- Reference year
- 2031
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- IMF World Economic Outlook via the IMF DataMapper API (imf.org/external/datamapper).
- GDP per capita (PPP)Tier A
100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
Ranks 70th of 202 · native score 69.45 · reference year 2024
66percentileHow is this calculated?
- Metric
- GDP per capita (PPP)
- Scale
- 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
- Raw value
- 34,846.6 international $ (PPP, current)
- Native score
- 69.45 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 66th percentile — ranks 70th of 202. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 34,846.6 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 69.45Log scale (values are heavily skewed). 0 and 100 are the dataset's min (1,154.89) and max (155,941.29) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
Ranks 59th of 155 · native score 22.6 · reference year 2020
62percentileHow is this calculated?
- Metric
- Government revenue
- Scale
- 100 = largest government revenue (% GDP), 0 = lowest — descriptive, not better or worse
- Raw value
- 28.459 % of GDP
- Native score
- 22.6 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 62th percentile — ranks 59th of 155. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (28.46 − 3.03) / (115.55 − 3.03) = 22.6Min and max are this dataset's lowest (3.03) and highest (115.55) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2020
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
Ranks 78th of 192 · native score 59.64 · reference year 2023
60percentileHow is this calculated?
- Metric
- Inflation rate
- Scale
- 100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
- Raw value
- 3.55711 % annual change (CPI)
- Native score
- 59.64 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 60th percentile — ranks 78th of 192. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = percentile rank of 3.56 among 192 countries = 59.64The score is the country's position in the distribution.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
Ranks 83rd of 193 · native score 18.92 · reference year 2025
57percentileHow is this calculated?
- Metric
- Government debt
- Scale
- 100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
- Raw value
- 58.4 % of GDP
- Native score
- 18.92 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 57th percentile — ranks 83rd of 193. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (58.4 − 0) / (308.7 − 0) = 18.92Min and max are this dataset's lowest (0) and highest (308.7) values, so the score is relative to the current country set.
- Source
- IMF (World Economic Outlook) · International Monetary Fund
- License
- IMF terms (reuse with attribution)
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- IMF World Economic Outlook via the IMF DataMapper API (imf.org/external/datamapper).
Environment & infrastructure
- Climate vulnerabilityTier B
100 = least climate-vulnerable (best), 0 = most vulnerable
Ranks 116th of 190 · native score 46.54 · reference year 2024
39percentileHow is this calculated?
- Metric
- Climate vulnerability
- Scale
- 100 = least climate-vulnerable (best), 0 = most vulnerable
- Raw value
- 0.472847 index (0–1, higher = more vulnerable)
- Native score
- 46.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 39th percentile — ranks 116th of 190. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (0.47 − 0.26) / (0.66 − 0.26) ] = 46.54Min and max are this dataset's lowest (0.26) and highest (0.66) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- ND-GAIN Country Index (University of Notre Dame) · University of Notre Dame Global Adaptation Initiative
- License
- CC BY 3.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier B — Reputable / modeled
- Source notes
- ND-GAIN vulnerability score. The source ZIP is version-stamped (no stable 'latest' URL), so the snapshot is pinned to a specific release; refreshes are a manual, documented step.
- CO₂ emissions per capitaTier A
100 = lowest emissions per capita (best), 0 = highest
Ranks 157th of 214 · native score 26.87 · reference year 2024
27percentileHow is this calculated?
- Metric
- CO₂ emissions per capita
- Scale
- 100 = lowest emissions per capita (best), 0 = highest
- Raw value
- 5.54243 tonnes CO₂ per capita
- Native score
- 26.87 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 27th percentile — ranks 157th of 214. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 5.54 among 214 countries ] = 26.87The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- Global Carbon Project (via Our World in Data) · Global Carbon Project
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Per-capita CO₂ emissions from the Global Carbon Project's Global Carbon Budget, retrieved via the Our World in Data mirror.
- Access to electricityTier A
100 = universal electricity access, 0 = none
Ranks 1st of 214 · native score 100 · reference year 2023
70percentileHow is this calculated?
- Metric
- Access to electricity
- Scale
- 100 = universal electricity access, 0 = none
- Raw value
- 100 % of population
- Native score
- 100 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 1st of 214. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (100 − 0) / (100 − 0) = 100The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
Ranks 66th of 177 · native score 70.12 · reference year 2007
63percentileHow is this calculated?
- Metric
- Energy use per capita
- Scale
- 100 = highest energy use per capita, 0 = lowest — descriptive, not better or worse
- Raw value
- 1,777.07 kg oil-equivalent per capita
- Native score
- 70.12 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 63th percentile — ranks 66th of 177. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 1,777.07 − ln 9.73) / (ln 16,343.04 − ln 9.73) = 70.12Log scale (values are heavily skewed). 0 and 100 are the dataset's min (9.73) and max (16,343.04) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2007
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most fixed-broadband subscriptions per capita, 0 = fewest
Ranks 11th of 208 · native score 76.66 · reference year 2022
95percentileHow is this calculated?
- Metric
- Fixed broadband subscriptions
- Scale
- 100 = most fixed-broadband subscriptions per capita, 0 = fewest
- Raw value
- 46.7447 per 100 people
- Native score
- 76.66 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 95th percentile — ranks 11th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (46.74 − 0) / (60.97 − 0) = 76.66Min and max are this dataset's lowest (0) and highest (60.97) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = most forested, 0 = least — descriptive, not better or worse
Ranks 71st of 213 · native score 42.31 · reference year 2023
67percentileHow is this calculated?
- Metric
- Forest area
- Scale
- 100 = most forested, 0 = least — descriptive, not better or worse
- Raw value
- 42.3077 % of land area
- Native score
- 42.31 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 67th percentile — ranks 71st of 213. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (42.31 − 0) / (100 − 0) = 42.31The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Internet usersTier A
100 = whole population online, 0 = none
Ranks 117th of 209 · native score 76.88 · reference year 2024
44percentileHow is this calculated?
- Metric
- Internet users
- Scale
- 100 = whole population online, 0 = none
- Raw value
- 76.884 % of population
- Native score
- 76.88 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 44th percentile — ranks 117th of 209. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (76.88 − 0) / (100 − 0) = 76.88The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- PM2.5 air pollutionTier A
100 = cleanest air (lowest PM2.5), 0 = most polluted
Ranks 39th of 200 · native score 80.75 · reference year 2023
81percentileHow is this calculated?
- Metric
- PM2.5 air pollution
- Scale
- 100 = cleanest air (lowest PM2.5), 0 = most polluted
- Raw value
- 8.87073 µg/m³
- Native score
- 80.75 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 81th percentile — ranks 39th of 200. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 8.87 among 200 countries ] = 80.75The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Protected land areaTier A
100 = most land protected, 0 = least
Ranks 108th of 212 · native score 16.9 · reference year 2025
49percentileHow is this calculated?
- Metric
- Protected land area
- Scale
- 100 = most land protected, 0 = least
- Raw value
- 16.9 % of land area
- Native score
- 16.9 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 49th percentile — ranks 108th of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (16.9 − 0) / (100 − 0) = 16.9The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Renewable energy shareTier A
100 = all energy renewable, 0 = none
Ranks 183rd of 212 · native score 1.5 · reference year 2022
14percentileHow is this calculated?
- Metric
- Renewable energy share
- Scale
- 100 = all energy renewable, 0 = none
- Raw value
- 1.5 % of final energy
- Native score
- 1.5 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 14th percentile — ranks 183rd of 212. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (1.5 − 0) / (100 − 0) = 1.5The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2022
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Safety & crime
100 = fewest conflict deaths (most at peace), 0 = most
Ranks 1st of 197 · native score 63.71 · reference year 2025
64percentileHow is this calculated?
- Metric
- Deaths in armed conflicts
- Scale
- 100 = fewest conflict deaths (most at peace), 0 = most
- Raw value
- 0 deaths per year
- Native score
- 63.71 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 1st of 197. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 0 among 197 countries ] = 63.71The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- Uppsala Conflict Data Program (via Our World in Data) · Uppsala Conflict Data Program (UCDP)
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Deaths in armed conflicts, best estimate, retrieved via the Our World in Data mirror.
- Homicide rateTier A
100 = safest (fewest homicides), 0 = most homicides
Ranks 192nd of 193 · native score 0.78 · reference year 2023
1percentileHow is this calculated?
- Metric
- Homicide rate
- Scale
- 100 = safest (fewest homicides), 0 = most homicides
- Raw value
- 64.1601 per 100,000 population
- Native score
- 0.78 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 1th percentile — ranks 192nd of 193. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 64.16 among 193 countries ] = 0.78The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- UNODC (via World Bank) · UN Office on Drugs and Crime / World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Intentional homicide victims per 100,000, indicator VC.IHR.PSRC.P5, retrieved via the World Bank API. Primary source is UNODC; the World Bank redistributes the series under CC BY 4.0.
Health
- Diabetes prevalenceTier A
100 = lowest diabetes prevalence (best), 0 = highest
Ranks 170th of 208 · native score 58.86 · reference year 2024
18percentileHow is this calculated?
- Metric
- Diabetes prevalence
- Scale
- 100 = lowest diabetes prevalence (best), 0 = highest
- Raw value
- 13.8 % of adults 20–79
- Native score
- 58.86 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 18th percentile — ranks 170th of 208. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (13.8 − 1.5) / (31.4 − 1.5) ] = 58.86Min and max are this dataset's lowest (1.5) and highest (31.4) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest health spending per capita, 0 = lowest
Ranks 54th of 193 · native score 64.78 · reference year 2023
72percentileHow is this calculated?
- Metric
- Health expenditure per capita
- Scale
- 100 = highest health spending per capita, 0 = lowest
- Raw value
- 1,294.88 current US$ per capita
- Native score
- 64.78 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 72th percentile — ranks 54th of 193. Comparable across metrics.
- Normalization
- Log + min–max (log scale, for skewed data)
score = 100 · (ln 1,294.88 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 64.78Log scale (values are heavily skewed). 0 and 100 are the dataset's min (17.44) and max (13,473.19) — relative, not absolute or year-over-year comparable.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Hospital beds per 1,000Tier A
100 = most hospital beds per capita in the dataset, 0 = fewest
Ranks 43rd of 191 · native score 17.54 · reference year 2023
78percentileHow is this calculated?
- Metric
- Hospital beds per 1,000
- Scale
- 100 = most hospital beds per capita in the dataset, 0 = fewest
- Raw value
- 3.98 per 1,000 people
- Native score
- 17.54 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 78th percentile — ranks 43rd of 191. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.98 − 0.15) / (21.99 − 0.15) = 17.54Min and max are this dataset's lowest (0.15) and highest (21.99) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = full DTP3 coverage, 0 = none
Ranks 29th of 193 · native score 97 · reference year 2024
81percentileHow is this calculated?
- Metric
- Immunization coverage (DTP3)
- Scale
- 100 = full DTP3 coverage, 0 = none
- Raw value
- 97 % of children aged 12–23 months
- Native score
- 97 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 81th percentile — ranks 29th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (97 − 0) / (100 − 0) = 97The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Infant mortality rateTier A
100 = lowest infant mortality in the dataset, 0 = highest
Ranks 105th of 195 · native score 82.04 · reference year 2024
46percentileHow is this calculated?
- Metric
- Infant mortality rate
- Scale
- 100 = lowest infant mortality in the dataset, 0 = highest
- Raw value
- 13.9 per 1,000 live births
- Native score
- 82.04 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 46th percentile — ranks 105th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (13.9 − 1.2) / (71.9 − 1.2) ] = 82.04Min and max are this dataset's lowest (1.2) and highest (71.9) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Life expectancy at birthTier A
100 = longest life expectancy in the dataset, 0 = shortest
Ranks 134th of 215 · native score 55.38 · reference year 2024
38percentileHow is this calculated?
- Metric
- Life expectancy at birth
- Scale
- 100 = longest life expectancy in the dataset, 0 = shortest
- Raw value
- 72.281 years
- Native score
- 55.38 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 38th percentile — ranks 134th of 215. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (72.28 − 54.64) / (86.5 − 54.64) = 55.38Min and max are this dataset's lowest (54.64) and highest (86.5) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Maternal mortality ratioTier A
100 = lowest maternal mortality (best), 0 = highest
Ranks 117th of 194 · native score 39.95 · reference year 2023
40percentileHow is this calculated?
- Metric
- Maternal mortality ratio
- Scale
- 100 = lowest maternal mortality (best), 0 = highest
- Raw value
- 74 deaths per 100,000 live births
- Native score
- 39.95 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 40th percentile — ranks 117th of 194. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 74 among 194 countries ] = 39.95The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Physicians per 1,000Tier A
100 = most physicians per capita in the dataset, 0 = fewest
Ranks 59th of 195 · native score 32.06 · reference year 2018
70percentileHow is this calculated?
- Metric
- Physicians per 1,000
- Scale
- 100 = most physicians per capita in the dataset, 0 = fewest
- Raw value
- 3.085 per 1,000 people
- Native score
- 32.06 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 59th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.09 − 0.04) / (9.54 − 0.04) = 32.06Min and max are this dataset's lowest (0.04) and highest (9.54) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2018
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Under-5 mortality rateTier A
100 = lowest under-5 mortality (best), 0 = highest
Ranks 104th of 195 · native score 46.92 · reference year 2024
47percentileHow is this calculated?
- Metric
- Under-5 mortality rate
- Scale
- 100 = lowest under-5 mortality (best), 0 = highest
- Raw value
- 15.9 deaths per 1,000 live births
- Native score
- 46.92 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 47th percentile — ranks 104th of 195. Comparable across metrics.
- Normalization
- Percentile rank across countries
score = 100 − [ percentile rank of 15.9 among 195 countries ] = 46.92The score is the country's position in the distribution. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Education
100 = highest education spending (% GDP) in the dataset, 0 = lowest
Ranks 130th of 200 · native score 21.34 · reference year 2023
35percentileHow is this calculated?
- Metric
- Government education spending
- Scale
- 100 = highest education spending (% GDP) in the dataset, 0 = lowest
- Raw value
- 3.49726 % of GDP
- Native score
- 21.34 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 35th percentile — ranks 130th of 200. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (3.5 − 0) / (16.39 − 0) = 21.34Min and max are this dataset's lowest (0) and highest (16.39) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = lowest pupil–teacher ratio (best), 0 = highest
Ranks 53rd of 197 · native score 90.92 · reference year 2016
73percentileHow is this calculated?
- Metric
- Pupil–teacher ratio (primary)
- Scale
- 100 = lowest pupil–teacher ratio (best), 0 = highest
- Raw value
- 13.8728 pupils per teacher
- Native score
- 90.92 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 73th percentile — ranks 53rd of 197. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 − [ 100 · (13.87 − 6.93) / (83.41 − 6.93) ] = 90.92Min and max are this dataset's lowest (6.93) and highest (83.41) values, so the score is relative to the current country set. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2016
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest completion in the dataset, 0 = lowest
Ranks 3rd of 192 · native score 79.64 · reference year 2023
99percentileHow is this calculated?
- Metric
- Lower-secondary completion rate
- Scale
- 100 = highest completion in the dataset, 0 = lowest
- Raw value
- 119.749 % of relevant age group
- Native score
- 79.64 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 99th percentile — ranks 3rd of 192. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (119.75 − 8.89) / (148.09 − 8.89) = 79.64Min and max are this dataset's lowest (8.89) and highest (148.09) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
100 = highest tertiary enrollment in the dataset, 0 = lowest
Ranks 14th of 195 · native score 56.4 · reference year 2015
93percentileHow is this calculated?
- Metric
- Tertiary enrollment ratio
- Scale
- 100 = highest tertiary enrollment in the dataset, 0 = lowest
- Raw value
- 93.9224 % gross enrollment
- Native score
- 56.4 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 93th percentile — ranks 14th of 195. Comparable across metrics.
- Normalization
- Min–max (rescaled against the dataset)
score = 100 · (93.92 − 1.84) / (165.11 − 1.84) = 56.4Min and max are this dataset's lowest (1.84) and highest (165.11) values, so the score is relative to the current country set.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2015
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Governance & institutions
- Government effectivenessTier A
100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
Ranks 53rd of 204 · native score 63.83 · reference year 2024
74percentileHow is this calculated?
- Metric
- Government effectiveness
- Scale
- 100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
- Raw value
- 0.691385 index (−2.5 to +2.5)
- Native score
- 63.83 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 74th percentile — ranks 53rd of 204. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.69 − -2.5) / (2.5 − -2.5) = 63.83The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2024
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
- Women in parliamentTier A
100 = all seats held by women, 0 = none (≈50 = parity)
Ranks 70th of 193 · native score 31.25 · reference year 2025
64percentileHow is this calculated?
- Metric
- Women in parliament
- Scale
- 100 = all seats held by women, 0 = none (≈50 = parity)
- Raw value
- 31.25 % of seats
- Native score
- 31.25 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 64th percentile — ranks 70th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (31.25 − 0) / (100 − 0) = 31.25The index is kept on its own published scale.
- Source
- World Bank · World Bank
- License
- CC BY 4.0
- Reference year
- 2025
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- World Development Indicators and related databases, retrieved via the World Bank API (api.worldbank.org), most recent value per country. Each metric's indicator code and primary compiler (e.g. UN, WHO, ITU, UN IGME) are given in its methodology.
Quality of life & wellbeing
- Human Development IndexTier A
100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
Ranks 58th of 193 · native score 84 · reference year 2023
70percentileHow is this calculated?
- Metric
- Human Development Index
- Scale
- 100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
- Raw value
- 0.84 HDI (0–1)
- Native score
- 84 — this metric's own 0–100 scale; not comparable to other metrics.
- Percentile rank
- 70th percentile — ranks 58th of 193. Comparable across metrics.
- Normalization
- Native rescale (index kept on its own scale)
score = 100 · (0.84 − 0) / (1 − 0) = 84The index is kept on its own published scale.
- Source
- UNDP — Human Development Report · United Nations Development Programme
- License
- CC BY 3.0 IGO
- Reference year
- 2023
- Retrieved
- 2026-07-12
- Confidence
- Tier A — Official / robust
- Source notes
- Human Development Index, retrieved via the Our World in Data mirror (ourworldindata.org/grapher/human-development-index), which republishes the UNDP HDR series. Primary source and methodology owner is UNDP.