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Guinea

GIN

Western Africa · Africa · 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?”.

72 metrics for this country

Education

  • 100 = highest adult literacy in the dataset, 0 = lowest

    Ranks 150th of 155 · native score 17.48 · reference year 2018

    4percentile
    How is this calculated?
    Metric
    Adult literacy rate
    Scale
    100 = highest adult literacy in the dataset, 0 = lowest
    Raw value
    39.62 % of adults
    Native score
    17.48 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    4th percentile — ranks 150th of 155. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (39.62 − 26.83) / (100 − 26.83) = 17.48

    Min and max are this dataset's lowest (26.83) and highest (100) 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.
  • 100 = highest education spending (% GDP) in the dataset, 0 = lowest

    Ranks 190th of 200 · native score 10.52 · reference year 2023

    5percentile
    How is this calculated?
    Metric
    Government education spending
    Scale
    100 = highest education spending (% GDP) in the dataset, 0 = lowest
    Raw value
    1.72471 % of GDP
    Native score
    10.52 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    5th percentile — ranks 190th of 200. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (1.72 − 0) / (16.39 − 0) = 10.52

    Min 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 187th of 197 · native score 47.41 · reference year 2016

    5percentile
    How is this calculated?
    Metric
    Pupil–teacher ratio (primary)
    Scale
    100 = lowest pupil–teacher ratio (best), 0 = highest
    Raw value
    47.1486 pupils per teacher
    Native score
    47.41 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    5th percentile — ranks 187th of 197. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (47.15 − 6.93) / (83.41 − 6.93) ] = 47.41

    Min 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 177th of 192 · native score 18.37 · reference year 2020

    8percentile
    How is this calculated?
    Metric
    Lower-secondary completion rate
    Scale
    100 = highest completion in the dataset, 0 = lowest
    Raw value
    34.4574 % of relevant age group
    Native score
    18.37 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    8th percentile — ranks 177th of 192. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (34.46 − 8.89) / (148.09 − 8.89) = 18.37

    Min 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
    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 tertiary enrollment in the dataset, 0 = lowest

    Ranks 157th of 195 · native score 5.52 · reference year 2014

    19percentile
    How is this calculated?
    Metric
    Tertiary enrollment ratio
    Scale
    100 = highest tertiary enrollment in the dataset, 0 = lowest
    Raw value
    10.8547 % gross enrollment
    Native score
    5.52 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    19th percentile — ranks 157th of 195. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (10.85 − 1.84) / (165.11 − 1.84) = 5.52

    Min 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
    2014
    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.

Society & culture

  • Adult male heightTier ADescriptive

    100 = tallest mean male height, 0 = shortest — descriptive, not better or worse

    Ranks 145th of 200 · native score 34.09 · reference year 1996

    28percentile
    How is this calculated?
    Metric
    Adult male height
    Scale
    100 = tallest mean male height, 0 = shortest — descriptive, not better or worse
    Raw value
    167.545 cm
    Native score
    34.09 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    28th percentile — ranks 145th of 200. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (167.54 − 159.79) / (182.54 − 159.79) = 34.09

    Min 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 = lowest child labour (best), 0 = highest

    Ranks 84th of 97 · native score 41.18 · reference year 2012

    14percentile
    How is this calculated?
    Metric
    Child labour
    Scale
    100 = lowest child labour (best), 0 = highest
    Raw value
    38.1 % of children 7–14
    Native score
    41.18 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    14th percentile — ranks 84th of 97. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (38.1 − 1.23) / (63.92 − 1.23) ] = 41.18

    Min and max are this dataset's lowest (1.23) and highest (63.92) 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
    2012
    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 = highest cocoa supply per person in the dataset, 0 = lowest

    Ranks 157th of 191 · native score 0.57 · reference year 2023

    18percentile

    Low 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
    0.08 kg cocoa per person / year
    Native score
    0.57 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    18th percentile — ranks 157th of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.08 − 0) / (14.07 − 0) = 0.57

    Min 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 female participation in the dataset, 0 = lowest

    Ranks 141st of 186 · native score 48.54 · reference year 2025

    24percentile
    How is this calculated?
    Metric
    Female labour force participation
    Scale
    100 = highest female participation in the dataset, 0 = lowest
    Raw value
    42.646 % of women 15+
    Native score
    48.54 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    24th percentile — ranks 141st of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (42.65 − 4.66) / (82.91 − 4.66) = 48.54

    Min and max are this dataset's lowest (4.66) and highest (82.91) 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 fish & seafood supply per person, 0 = lowest — descriptive, not better or worse

    Ranks 118th of 191 · native score 12.31 · reference year 2023

    38percentile
    How 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
    10.65 kg per person per year
    Native score
    12.31 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    38th percentile — ranks 118th of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (10.65 − 0.38) / (83.81 − 0.38) = 12.31

    Min 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.
  • Fruit supply per capitaTier ADescriptive

    100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse

    Ranks 63rd of 191 · native score 18.9 · reference year 2023

    67percentile
    How is this calculated?
    Metric
    Fruit supply per capita
    Scale
    100 = highest fruit supply per person, 0 = lowest — descriptive, not better or worse
    Raw value
    103.44 kg per person per year
    Native score
    18.9 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    67th percentile — ranks 63rd of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (103.44 − 4.27) / (529.06 − 4.27) = 18.9

    Min 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 = most gender-equal (GII 0), 0 = most unequal (GII 1)

    Ranks 163rd of 172 · native score 39.1 · reference year 2023

    6percentile
    How is this calculated?
    Metric
    Gender equality (inverted GII)
    Scale
    100 = most gender-equal (GII 0), 0 = most unequal (GII 1)
    Raw value
    0.609 index (0–1, lower = more equal)
    Native score
    39.1 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    6th percentile — ranks 163rd of 172. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 − [ 100 · (0.61 − 0) / (1 − 0) ] = 39.1

    The index is kept on its own published scale. Direction is inverted (higher raw value = worse), so the position is subtracted from 100.

    Source
    UNDP Human Development Report (via Our World in Data) · UNDP, Human Development Report Office
    License
    CC BY 3.0 IGO
    Reference year
    2023
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Gender Inequality Index from the UNDP Human Development Report, retrieved via the Our World in Data mirror.
  • Meat supply per capitaTier ADescriptive

    100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse

    Ranks 163rd of 191 · native score 7.62 · reference year 2023

    15percentile
    How is this calculated?
    Metric
    Meat supply per capita
    Scale
    100 = highest meat supply per person, 0 = lowest — descriptive, not better or worse
    Raw value
    15.18 kg per person per year
    Native score
    7.62 — 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 · (15.18 − 3.49) / (156.93 − 3.49) = 7.62

    Min 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 207th of 214 · native score 3.7 · reference year 2021

    4percentile
    How is this calculated?
    Metric
    Social protection coverage
    Scale
    100 = universal social protection coverage, 0 = none
    Raw value
    3.7 % of population
    Native score
    3.7 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    4th percentile — ranks 207th of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (3.7 − 0) / (100 − 0) = 3.7

    The index is kept on its own published scale.

    Source
    ILOSTAT (International Labour Organization) · International Labour Organization
    License
    CC BY 4.0
    Reference year
    2021
    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 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse

    Ranks 154th of 191 · native score 9.22 · reference year 2023

    20percentile
    How is this calculated?
    Metric
    Vegetable supply per capita
    Scale
    100 = highest vegetables supply per person, 0 = lowest — descriptive, not better or worse
    Raw value
    42.91 kg per person per year
    Native score
    9.22 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    20th percentile — ranks 154th of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (42.91 − 5.34) / (412.72 − 5.34) = 9.22

    Min 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

  • Age dependency ratioTier ADescriptive

    100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse

    Ranks 17th of 215 · native score 70.14 · reference year 2025

    92percentile
    How is this calculated?
    Metric
    Age dependency ratio
    Scale
    100 = highest dependency ratio, 0 = lowest — descriptive, not better or worse
    Raw value
    78.6397 dependents per 100 working-age
    Native score
    70.14 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    92th percentile — ranks 17th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (78.64 − 20.05) / (103.59 − 20.05) = 70.14

    Min 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.
  • Fertility rateTier ADescriptive

    100 = highest fertility, 0 = lowest — descriptive, not better or worse

    Ranks 20th of 215 · native score 65.17 · reference year 2024

    91percentile
    How is this calculated?
    Metric
    Fertility rate
    Scale
    100 = highest fertility, 0 = lowest — descriptive, not better or worse
    Raw value
    4.131 births per woman
    Native score
    65.17 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    91th percentile — ranks 20th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (4.13 − 0.58) / (6.03 − 0.58) = 65.17

    Min 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 208th of 215 · native score 19.39 · reference year 2024

    3percentile
    How 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
    2.426 years (female − male)
    Native score
    19.39 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    3th percentile — ranks 208th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (2.43 − 0.46) / (10.62 − 0.46) = 19.39

    Min 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.
  • Median ageTier ADescriptive

    100 = oldest median age, 0 = youngest — descriptive, not better or worse

    Ranks 215th of 237 · native score 8.09 · reference year 2023

    9percentile
    How is this calculated?
    Metric
    Median age
    Scale
    100 = oldest median age, 0 = youngest — descriptive, not better or worse
    Raw value
    17.984 years
    Native score
    8.09 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    9th percentile — ranks 215th of 237. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (17.98 − 14.32) / (59.63 − 14.32) = 8.09

    Min 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.
  • Foreign-born populationTier ADescriptive

    100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse

    Ranks 178th of 214 · native score 0.8 · reference year 2024

    16percentile
    How is this calculated?
    Metric
    Foreign-born population
    Scale
    100 = highest foreign-born share, 0 = lowest — descriptive, not better or worse
    Raw value
    0.8 % foreign-born
    Native score
    0.8 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    16th percentile — ranks 178th of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.8 − 0) / (100 − 0) = 0.8

    The 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.
  • Net migration rateTier BDescriptive

    100 = highest net inflow per capita, 0 = highest net outflow — descriptive, not better or worse

    Ranks 134th of 215 · native score 50.6 · reference year 2025

    38percentile
    How 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
    -1.078 per 1,000 people
    Native score
    50.6 — 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 · (-1.08 − -46.91) / (43.67 − -46.91) = 50.6

    Min 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.
  • Total populationTier ADescriptive

    100 = most populous, 0 = least populous — descriptive, not better or worse

    Ranks 74th of 215 · native score 61.71 · reference year 2025

    66percentile
    How is this calculated?
    Metric
    Total population
    Scale
    100 = most populous, 0 = least populous — descriptive, not better or worse
    Raw value
    15,099,727 people
    Native score
    61.71 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    66th percentile — ranks 74th of 215. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 15,099,727 − ln 9,492) / (ln 1,463,865,525 − ln 9,492) = 61.71

    Log 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.
  • Population densityTier ADescriptive

    100 = most dense, 0 = least dense — descriptive, not better or worse

    Ranks 145th of 215 · native score 50.79 · reference year 2023

    33percentile
    How is this calculated?
    Metric
    Population density
    Scale
    100 = most dense, 0 = least dense — descriptive, not better or worse
    Raw value
    58.6255 people per km²
    Native score
    50.79 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    33th percentile — ranks 145th of 215. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 58.63 − ln 0.14) / (ln 20,569.7 − ln 0.14) = 50.79

    Log 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 34th of 237 · native score 69 · reference year 2050

    86percentile
    How is this calculated?
    Metric
    Population change (projection)
    Scale
    100 = fastest projected growth, 0 = fastest projected decline — descriptive, not better or worse
    Raw value
    58.6 % change 2024→2050
    Native score
    69 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    86th percentile — ranks 34th of 237. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (58.6 − -32.9) / (99.7 − -32.9) = 69

    Min 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.
  • Refugees (by origin)Tier ADescriptive

    100 = most refugees produced, 0 = fewest — descriptive, not better or worse

    Ranks 35th of 211 · native score 83.65 · reference year 2024

    84percentile
    How is this calculated?
    Metric
    Refugees (by origin)
    Scale
    100 = most refugees produced, 0 = fewest — descriptive, not better or worse
    Raw value
    42,096 refugees
    Native score
    83.65 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    84th percentile — ranks 35th of 211. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = percentile rank of 42,096 among 211 countries = 83.65

    The 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.
  • Remittances receivedTier ADescriptive

    100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse

    Ranks 95th of 193 · native score 5.2 · reference year 2024

    51percentile
    How is this calculated?
    Metric
    Remittances received
    Scale
    100 = highest remittance inflow (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    2.46482 % of GDP
    Native score
    5.2 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    51th percentile — ranks 95th of 193. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (2.46 − 0.01) / (47.15 − 0.01) = 5.2

    Min 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.
  • Rural population shareTier ADescriptive

    100 = fully rural, 0 = fully urban — descriptive, not better or worse

    Ranks 40th of 215 · native score 61.48 · reference year 2025

    82percentile
    How is this calculated?
    Metric
    Rural population share
    Scale
    100 = fully rural, 0 = fully urban — descriptive, not better or worse
    Raw value
    61.4835 % rural
    Native score
    61.48 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    82th percentile — ranks 40th of 215. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (61.48 − 0) / (100 − 0) = 61.48

    The 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.
  • Sex ratio at birthTier ADescriptive

    100 = highest male-to-female birth ratio, 0 = lowest — descriptive, not better or worse

    Ranks 135th of 215 · native score 22.37 · reference year 2024

    37percentile
    How 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
    1.045 male births per female birth
    Native score
    22.37 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    37th percentile — ranks 135th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (1.05 − 1.01) / (1.16 − 1.01) = 22.37

    Min 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.
  • UrbanizationTier ADescriptive

    100 = fully urban, 0 = fully rural — descriptive, not better or worse

    Ranks 176th of 215 · native score 38.52 · reference year 2025

    18percentile
    How is this calculated?
    Metric
    Urbanization
    Scale
    100 = fully urban, 0 = fully rural — descriptive, not better or worse
    Raw value
    38.5165 % urban
    Native score
    38.52 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    18th percentile — ranks 176th of 215. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (38.52 − 0) / (100 − 0) = 38.52

    The 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

  • 100 = highest new-business density in the dataset, 0 = lowest

    Ranks 141st of 182 · native score 0.33 · reference year 2024

    22percentile
    How is this calculated?
    Metric
    New business density
    Scale
    100 = highest new-business density in the dataset, 0 = lowest
    Raw value
    0.685253 new firms per 1,000 aged 15–64
    Native score
    0.33 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    22th percentile — ranks 141st of 182. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.69 − 0.02) / (201.01 − 0.02) = 0.33

    Min 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 = highest employment ratio in the dataset, 0 = lowest

    Ranks 141st of 186 · native score 43.67 · reference year 2025

    24percentile
    How is this calculated?
    Metric
    Employment-to-population ratio
    Scale
    100 = highest employment ratio in the dataset, 0 = lowest
    Raw value
    49.894 % of population 15+
    Native score
    43.67 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    24th percentile — ranks 141st of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (49.89 − 21.21) / (86.9 − 21.21) = 43.67

    Min and max are this dataset's lowest (21.21) and highest (86.9) 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 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse

    Ranks 80th of 192 · native score 20.29 · reference year 2025

    59percentile
    How is this calculated?
    Metric
    Exports of goods & services
    Scale
    100 = most export-oriented (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    41.4119 % of GDP
    Native score
    20.29 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    59th percentile — ranks 80th of 192. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (41.41 − 1.1) / (199.76 − 1.1) = 20.29

    Min and max are this dataset's lowest (1.1) and highest (199.76) 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.
  • Foreign direct investmentTier ADescriptive

    100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse

    Ranks 43rd of 201 · native score 88.84 · reference year 2024

    79percentile
    How is this calculated?
    Metric
    Foreign direct investment
    Scale
    100 = largest net FDI inflow (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    5.60537 % of GDP (net inflows)
    Native score
    88.84 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    79th percentile — ranks 43rd of 201. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (5.61 − -1,303.11) / (170.05 − -1,303.11) = 88.84

    Min 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.
  • 100 = highest projected growth, 0 = lowest

    Ranks 3rd of 189 · native score 60.54 · reference year 2031

    99percentile
    How is this calculated?
    Metric
    GDP growth (projection)
    Scale
    100 = highest projected growth, 0 = lowest
    Raw value
    8.95 % per year (avg 2026–2031)
    Native score
    60.54 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    99th percentile — ranks 3rd of 189. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (8.95 − 0.62) / (14.38 − 0.62) = 60.54

    Min 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).
  • 100 = highest GDP per capita in the dataset, 0 = lowest (log scale)

    Ranks 166th of 202 · native score 28.02 · reference year 2024

    18percentile
    How is this calculated?
    Metric
    GDP per capita (PPP)
    Scale
    100 = highest GDP per capita in the dataset, 0 = lowest (log scale)
    Raw value
    4,565.3 international $ (PPP, current)
    Native score
    28.02 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    18th percentile — ranks 166th of 202. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 4,565.3 − ln 1,154.89) / (ln 155,941.29 − ln 1,154.89) = 28.02

    Log 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.
  • Gross savingsTier ADescriptive

    100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse

    Ranks 158th of 177 · native score 39.11 · reference year 2024

    11percentile
    How is this calculated?
    Metric
    Gross savings
    Scale
    100 = highest gross savings (% GDP), 0 = lowest — descriptive, not better or worse
    Raw value
    9.59342 % of GDP
    Native score
    39.11 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    11th percentile — ranks 158th of 177. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (9.59 − -21.13) / (57.42 − -21.13) = 39.11

    Min and max are this dataset's lowest (-21.13) and highest (57.42) 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 = most equal (lowest Gini in the dataset), 0 = most unequal

    Ranks 30th of 167 · native score 83.57 · reference year 2018

    82percentile
    How is this calculated?
    Metric
    Income inequality (Gini)
    Scale
    100 = most equal (lowest Gini in the dataset), 0 = most unequal
    Raw value
    29.6 Gini index (0–100)
    Native score
    83.57 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    82th percentile — ranks 30th of 167. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (29.6 − 23.8) / (59.1 − 23.8) ] = 83.57

    Min and max are this dataset's lowest (23.8) and highest (59.1) 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
    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.
  • Inflation rateTier ADescriptive

    100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse

    Ranks 80th of 192 · native score 58.59 · reference year 2025

    59percentile
    How is this calculated?
    Metric
    Inflation rate
    Scale
    100 = highest inflation in the dataset, 0 = lowest/most negative — descriptive, not better or worse
    Raw value
    3.5463 % annual change (CPI)
    Native score
    58.59 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    59th percentile — ranks 80th of 192. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = percentile rank of 3.55 among 192 countries = 58.59

    The score is the country's position in the distribution.

    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 output per worker, 0 = lowest

    Ranks 144th of 177 · native score 36.61 · reference year 2024

    19percentile
    How is this calculated?
    Metric
    Labour productivity
    Scale
    100 = highest output per worker, 0 = lowest
    Raw value
    13,569.4 constant PPP$ per worker
    Native score
    36.61 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    19th percentile — ranks 144th of 177. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 13,569.42 − ln 2,444.23) / (ln 263,863.91 − ln 2,444.23) = 36.61

    Log scale (values are heavily skewed). 0 and 100 are the dataset's min (2,444.23) and max (263,863.91) — 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.
  • Government debtTier BDescriptive

    100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse

    Ranks 111th of 193 · native score 15.58 · reference year 2025

    42percentile
    How is this calculated?
    Metric
    Government debt
    Scale
    100 = highest debt (% GDP) in the dataset, 0 = lowest — descriptive, not better or worse
    Raw value
    48.1 % of GDP
    Native score
    15.58 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    42th percentile — ranks 111th of 193. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (48.1 − 0) / (308.7 − 0) = 15.58

    Min 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).
  • 100 = lowest unemployment in the dataset, 0 = highest

    Ranks 94th of 186 · native score 85.23 · reference year 2025

    50percentile
    How is this calculated?
    Metric
    Unemployment rate
    Scale
    100 = lowest unemployment in the dataset, 0 = highest
    Raw value
    5.163 % of labour force
    Native score
    85.23 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    50th percentile — ranks 94th of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (5.16 − 0.13) / (34.2 − 0.13) ] = 85.23

    Min and max are this dataset's lowest (0.13) and highest (34.2) 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
    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 = lowest youth unemployment (best), 0 = highest

    Ranks 44th of 186 · native score 91.4 · reference year 2025

    77percentile
    How is this calculated?
    Metric
    Youth unemployment rate
    Scale
    100 = lowest youth unemployment (best), 0 = highest
    Raw value
    7.017 % of labour force 15–24
    Native score
    91.4 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    77th percentile — ranks 44th of 186. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (7.02 − 0.46) / (76.77 − 0.46) ] = 91.4

    Min and max are this dataset's lowest (0.46) and highest (76.77) 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
    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.

Environment & infrastructure

  • 100 = least climate-vulnerable (best), 0 = most vulnerable

    Ranks 117th of 190 · native score 46.35 · reference year 2024

    39percentile
    How is this calculated?
    Metric
    Climate vulnerability
    Scale
    100 = least climate-vulnerable (best), 0 = most vulnerable
    Raw value
    0.473598 index (0–1, higher = more vulnerable)
    Native score
    46.35 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    39th percentile — ranks 117th of 190. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (0.47 − 0.26) / (0.66 − 0.26) ] = 46.35

    Min 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.
  • 100 = lowest emissions per capita (best), 0 = highest

    Ranks 21st of 214 · native score 90.42 · reference year 2024

    90percentile
    How is this calculated?
    Metric
    CO₂ emissions per capita
    Scale
    100 = lowest emissions per capita (best), 0 = highest
    Raw value
    0.272873 tonnes CO₂ per capita
    Native score
    90.42 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    90th percentile — ranks 21st of 214. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 0.27 among 214 countries ] = 90.42

    The 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.
  • 100 = universal electricity access, 0 = none

    Ranks 195th of 214 · native score 51.1 · reference year 2023

    9percentile
    How is this calculated?
    Metric
    Access to electricity
    Scale
    100 = universal electricity access, 0 = none
    Raw value
    51.1 % of population
    Native score
    51.1 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    9th percentile — ranks 195th of 214. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (51.1 − 0) / (100 − 0) = 51.1

    The 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 = most fixed-broadband subscriptions per capita, 0 = fewest

    Ranks 204th of 208 · native score 0.01 · reference year 2022

    2percentile
    How is this calculated?
    Metric
    Fixed broadband subscriptions
    Scale
    100 = most fixed-broadband subscriptions per capita, 0 = fewest
    Raw value
    0.00627529 per 100 people
    Native score
    0.01 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    2th percentile — ranks 204th of 208. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.01 − 0) / (60.97 − 0) = 0.01

    Min 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.
  • Forest areaTier ADescriptive

    100 = most forested, 0 = least — descriptive, not better or worse

    Ranks 119th of 213 · native score 24.7 · reference year 2023

    44percentile
    How is this calculated?
    Metric
    Forest area
    Scale
    100 = most forested, 0 = least — descriptive, not better or worse
    Raw value
    24.6988 % of land area
    Native score
    24.7 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    44th percentile — ranks 119th of 213. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (24.7 − 0) / (100 − 0) = 24.7

    The 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 = whole population online, 0 = none

    Ranks 179th of 209 · native score 33.3 · reference year 2024

    15percentile
    How is this calculated?
    Metric
    Internet users
    Scale
    100 = whole population online, 0 = none
    Raw value
    33.3047 % of population
    Native score
    33.3 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    15th percentile — ranks 179th of 209. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (33.3 − 0) / (100 − 0) = 33.3

    The 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 = best logistics performance (index 5), 0 = worst (1)

    Ranks 113th of 169 · native score 37.5 · reference year 2022

    28percentile
    How is this calculated?
    Metric
    Logistics Performance Index
    Scale
    100 = best logistics performance (index 5), 0 = worst (1)
    Raw value
    2.5 index (1–5)
    Native score
    37.5 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    28th percentile — ranks 113th of 169. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (2.5 − 1) / (5 − 1) = 37.5

    The 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.
  • 100 = cleanest air (lowest PM2.5), 0 = most polluted

    Ranks 145th of 200 · native score 27.75 · reference year 2023

    28percentile
    How is this calculated?
    Metric
    PM2.5 air pollution
    Scale
    100 = cleanest air (lowest PM2.5), 0 = most polluted
    Raw value
    27.264 µg/m³
    Native score
    27.75 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    28th percentile — ranks 145th of 200. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 27.26 among 200 countries ] = 27.75

    The 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.
  • 100 = most land protected, 0 = least

    Ranks 8th of 212 · native score 42.6 · reference year 2025

    96percentile
    How is this calculated?
    Metric
    Protected land area
    Scale
    100 = most land protected, 0 = least
    Raw value
    42.6 % of land area
    Native score
    42.6 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    96th percentile — ranks 8th of 212. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (42.6 − 0) / (100 − 0) = 42.6

    The 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 = all energy renewable, 0 = none

    Ranks 31st of 212 · native score 66.6 · reference year 2022

    86percentile
    How is this calculated?
    Metric
    Renewable energy share
    Scale
    100 = all energy renewable, 0 = none
    Raw value
    66.6 % of final energy
    Native score
    66.6 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    86th percentile — ranks 31st of 212. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (66.6 − 0) / (100 − 0) = 66.6

    The 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

    64percentile
    How 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 ] = 63.71

    The 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.
  • 100 = lowest road-death rate (best), 0 = highest

    Ranks 164th of 190 · native score 54.02 · reference year 2019

    14percentile
    How is this calculated?
    Metric
    Road-traffic deaths
    Scale
    100 = lowest road-death rate (best), 0 = highest
    Raw value
    29.7 deaths per 100,000
    Native score
    54.02 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    14th percentile — ranks 164th of 190. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (29.7 − 0) / (64.6 − 0) ] = 54.02

    Min and max are this dataset's lowest (0) and highest (64.6) 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
    2019
    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.

Governance & institutions

  • 100 = cleanest (least corrupt), 0 = most corrupt

    Ranks 133rd of 180 · native score 28 · reference year 2024

    26percentile
    How is this calculated?
    Metric
    Corruption Perceptions Index
    Scale
    100 = cleanest (least corrupt), 0 = most corrupt
    Raw value
    28 CPI score (0–100)
    Native score
    28 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    26th percentile — ranks 133rd of 180. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (28 − 0) / (100 − 0) = 28

    The index is kept on its own published scale.

    Source
    Transparency International · Transparency International
    License
    CC BY-ND 4.0
    Reference year
    2024
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    CPI retrieved via the Our World in Data mirror (ourworldindata.org/grapher/ti-corruption-perception-index), which republishes the official TI CPI series verbatim. Snapshot verified against Transparency International's official CPI 2024 figures and matches exactly (spot-checked: DNK 90, FIN 88, SGP 84, DEU 75, USA 65, ESP 56, SSD 8). We were unable to fetch TI's primary file directly (their CDN returns an access-denied stub for the CPI xlsx and no clean CSV is offered), so the OWID mirror is the machine-readable source; primary source and methodology owner is Transparency International.
  • 100 = most democratic (index 1.0), 0 = least democratic

    Ranks 140th of 175 · native score 18.7 · reference year 2025

    20percentile
    How is this calculated?
    Metric
    Electoral democracy index
    Scale
    100 = most democratic (index 1.0), 0 = least democratic
    Raw value
    0.187 index (0–1)
    Native score
    18.7 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    20th percentile — ranks 140th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.19 − 0) / (1 − 0) = 18.7

    The index is kept on its own published scale.

    Source
    V-Dem Institute (via Our World in Data) · V-Dem Institute, University of Gothenburg
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Varieties of Democracy (V-Dem) expert-coded indices (electoral democracy, rule of law, freedom of expression), retrieved via the Our World in Data mirror. Expert-coded estimates; see V-Dem for uncertainty intervals.
  • 100 = most free expression (index 1.0), 0 = least

    Ranks 113th of 175 · native score 56 · reference year 2025

    36percentile
    How is this calculated?
    Metric
    Freedom of expression index
    Scale
    100 = most free expression (index 1.0), 0 = least
    Raw value
    0.56 index (0–1)
    Native score
    56 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    36th percentile — ranks 113th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.56 − 0) / (1 − 0) = 56

    The index is kept on its own published scale.

    Source
    V-Dem Institute (via Our World in Data) · V-Dem Institute, University of Gothenburg
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Varieties of Democracy (V-Dem) expert-coded indices (electoral democracy, rule of law, freedom of expression), retrieved via the Our World in Data mirror. Expert-coded estimates; see V-Dem for uncertainty intervals.
  • 100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)

    Ranks 170th of 204 · native score 32.24 · reference year 2024

    17percentile
    How is this calculated?
    Metric
    Government effectiveness
    Scale
    100 = strongest government effectiveness (index +2.5), 0 = weakest (−2.5)
    Raw value
    -0.888163 index (−2.5 to +2.5)
    Native score
    32.24 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    17th percentile — ranks 170th of 204. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (-0.89 − -2.5) / (2.5 − -2.5) = 32.24

    The 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 = strongest rule of law (index 1.0), 0 = weakest

    Ranks 158th of 175 · native score 10.6 · reference year 2025

    10percentile
    How is this calculated?
    Metric
    Rule of law index
    Scale
    100 = strongest rule of law (index 1.0), 0 = weakest
    Raw value
    0.106 index (0–1)
    Native score
    10.6 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    10th percentile — ranks 158th of 175. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.11 − 0) / (1 − 0) = 10.6

    The index is kept on its own published scale.

    Source
    V-Dem Institute (via Our World in Data) · V-Dem Institute, University of Gothenburg
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier A — Official / robust
    Source notes
    Varieties of Democracy (V-Dem) expert-coded indices (electoral democracy, rule of law, freedom of expression), retrieved via the Our World in Data mirror. Expert-coded estimates; see V-Dem for uncertainty intervals.
  • 100 = all seats held by women, 0 = none (≈50 = parity)

    Ranks 80th of 193 · native score 29.63 · reference year 2025

    59percentile
    How is this calculated?
    Metric
    Women in parliament
    Scale
    100 = all seats held by women, 0 = none (≈50 = parity)
    Raw value
    29.6296 % of seats
    Native score
    29.63 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    59th percentile — ranks 80th of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (29.63 − 0) / (100 − 0) = 29.63

    The 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.

Health

  • 100 = lowest diabetes prevalence (best), 0 = highest

    Ranks 19th of 208 · native score 89.63 · reference year 2024

    90percentile
    How is this calculated?
    Metric
    Diabetes prevalence
    Scale
    100 = lowest diabetes prevalence (best), 0 = highest
    Raw value
    4.6 % of adults 20–79
    Native score
    89.63 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    90th percentile — ranks 19th of 208. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (4.6 − 1.5) / (31.4 − 1.5) ] = 89.63

    Min 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 166th of 193 · native score 18.41 · reference year 2023

    14percentile
    How is this calculated?
    Metric
    Health expenditure per capita
    Scale
    100 = highest health spending per capita, 0 = lowest
    Raw value
    59.3301 current US$ per capita
    Native score
    18.41 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    14th percentile — ranks 166th of 193. Comparable across metrics.
    Normalization
    Log + min–max (log scale, for skewed data)
    score = 100 · (ln 59.33 − ln 17.44) / (ln 13,473.19 − ln 17.44) = 18.41

    Log 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.
  • 100 = most hospital beds per capita in the dataset, 0 = fewest

    Ranks 187th of 191 · native score 0.69 · reference year 2011

    2percentile
    How is this calculated?
    Metric
    Hospital beds per 1,000
    Scale
    100 = most hospital beds per capita in the dataset, 0 = fewest
    Raw value
    0.3 per 1,000 people
    Native score
    0.69 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    2th percentile — ranks 187th of 191. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.3 − 0.15) / (21.99 − 0.15) = 0.69

    Min 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
    2011
    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 180th of 193 · native score 63 · reference year 2024

    7percentile
    How is this calculated?
    Metric
    Immunization coverage (DTP3)
    Scale
    100 = full DTP3 coverage, 0 = none
    Raw value
    63 % of children aged 12–23 months
    Native score
    63 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    7th percentile — ranks 180th of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (63 − 0) / (100 − 0) = 63

    The 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 = lowest infant mortality in the dataset, 0 = highest

    Ranks 189th of 195 · native score 17.11 · reference year 2024

    3percentile
    How is this calculated?
    Metric
    Infant mortality rate
    Scale
    100 = lowest infant mortality in the dataset, 0 = highest
    Raw value
    59.8 per 1,000 live births
    Native score
    17.11 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    3th percentile — ranks 189th of 195. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (59.8 − 1.2) / (71.9 − 1.2) ] = 17.11

    Min 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.
  • 100 = longest life expectancy in the dataset, 0 = shortest

    Ranks 208th of 215 · native score 19.68 · reference year 2024

    3percentile
    How is this calculated?
    Metric
    Life expectancy at birth
    Scale
    100 = longest life expectancy in the dataset, 0 = shortest
    Raw value
    60.904 years
    Native score
    19.68 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    3th percentile — ranks 208th of 215. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (60.9 − 54.64) / (86.5 − 54.64) = 19.68

    Min 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.
  • 100 = lowest maternal mortality (best), 0 = highest

    Ranks 185th of 194 · native score 4.9 · reference year 2023

    5percentile
    How is this calculated?
    Metric
    Maternal mortality ratio
    Scale
    100 = lowest maternal mortality (best), 0 = highest
    Raw value
    494 deaths per 100,000 live births
    Native score
    4.9 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    5th percentile — ranks 185th of 194. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 494 among 194 countries ] = 4.9

    The 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.
  • 100 = most physicians per capita in the dataset, 0 = fewest

    Ranks 164th of 195 · native score 1.81 · reference year 2022

    16percentile
    How is this calculated?
    Metric
    Physicians per 1,000
    Scale
    100 = most physicians per capita in the dataset, 0 = fewest
    Raw value
    0.21 per 1,000 people
    Native score
    1.81 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    16th percentile — ranks 164th of 195. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 · (0.21 − 0.04) / (9.54 − 0.04) = 1.81

    Min 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
    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 = lowest under-5 mortality (best), 0 = highest

    Ranks 190th of 195 · native score 2.82 · reference year 2024

    3percentile
    How is this calculated?
    Metric
    Under-5 mortality rate
    Scale
    100 = lowest under-5 mortality (best), 0 = highest
    Raw value
    92.1 deaths per 1,000 live births
    Native score
    2.82 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    3th percentile — ranks 190th of 195. Comparable across metrics.
    Normalization
    Percentile rank across countries
    score = 100 − [ percentile rank of 92.1 among 195 countries ] = 2.82

    The 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.
  • 100 = lowest undernourishment (best), 0 = highest

    Ranks 118th of 169 · native score 82.79 · reference year 2023

    30percentile
    How is this calculated?
    Metric
    Undernourishment
    Scale
    100 = lowest undernourishment (best), 0 = highest
    Raw value
    11.4 % of population
    Native score
    82.79 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    30th percentile — ranks 118th of 169. Comparable across metrics.
    Normalization
    Min–max (rescaled against the dataset)
    score = 100 − [ 100 · (11.4 − 2.5) / (54.2 − 2.5) ] = 82.79

    Min and max are this dataset's lowest (2.5) and highest (54.2) 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
    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.

Quality of life & wellbeing

  • 100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)

    Ranks 179th of 193 · native score 50 · reference year 2023

    8percentile
    How is this calculated?
    Metric
    Human Development Index
    Scale
    100 = highest human development (HDI 1.0), 0 = lowest (HDI 0)
    Raw value
    0.5 HDI (0–1)
    Native score
    50 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    8th percentile — ranks 179th of 193. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (0.5 − 0) / (1 − 0) = 50

    The 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.
  • 100 = highest average life evaluation (ladder 10), 0 = lowest (ladder 0)

    Ranks 122nd of 165 · native score 46.09 · reference year 2025

    26percentile
    How is this calculated?
    Metric
    Life satisfaction (happiness)
    Scale
    100 = highest average life evaluation (ladder 10), 0 = lowest (ladder 0)
    Raw value
    4.609 Cantril ladder (0–10)
    Native score
    46.09 — this metric's own 0–100 scale; not comparable to other metrics.
    Percentile rank
    26th percentile — ranks 122nd of 165. Comparable across metrics.
    Normalization
    Native rescale (index kept on its own scale)
    score = 100 · (4.61 − 0) / (10 − 0) = 46.09

    The index is kept on its own published scale.

    Source
    World Happiness Report (via Our World in Data) · World Happiness Report / Gallup
    License
    CC BY 4.0
    Reference year
    2025
    Retrieved
    2026-07-12
    Confidence
    Tier B — Reputable / modeled
    Source notes
    Self-reported life evaluation (Cantril ladder, 0–10) from the Gallup World Poll, published in the World Happiness Report, retrieved via the Our World in Data mirror. Survey-based (Tier B).
Guinea — country scores · WorldScore