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Obesity among adults, BMI ≥ 30 kg/m2 (age-standardized estimate) (%)

Obesity among adults, BMI ≥ 30 kg/m2 (age-standardized estimate) (%) Source: WHO Global Health Observatory (indicator NCD_BMI_30A). Rows are country x year; sex-disaggregated rows carry a sex label.

Source: WHO Global Health Observatory26,865 lignesMis à jour: 21/09/2026
obesityncdwho

Qualité

97

Attribution

World Health Organization (WHO)

Schéma

ColonneTypeDescription
country_codestringCountry code (WHO GHO API field SpatialDim, country-level rows only).
country_namestringCountry name from the WHO GHO COUNTRY dimension labels.
yearintegerYear of observation (WHO GHO API field TimeDim).
sexstringSex disaggregation label (WHO GHO API dimension Dim1). Only present when the indicator is published sex-disaggregated.
valuefloatEstimate value for the country, year (and sex where present), as defined by the WHO GHO indicator (see the dataset description; WHO GHO API field NumericValue).
lowfloatLower bound of the published uncertainty interval (WHO GHO API field Low). Only present when the indicator publishes uncertainty intervals.
highfloatUpper bound of the published uncertainty interval (WHO GHO API field High). Only present when the indicator publishes uncertainty intervals.

Exemple de lignes

country_codecountry_nameyearsexvaluelowhigh
AFGAFG1980SEX_BTSX0.974845510.435055611.9094944
AFGAFG1980SEX_FMLE1.06701240.359696622.4551133
AFGAFG1980SEX_MLE0.891441670.264516332.1715384
AFGAFG1981SEX_BTSX1.04391840.486255341.9854777
AFGAFG1981SEX_FMLE1.14808820.409065792.5457801

Utiliser avec un LLM

Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/who_gho/obesity_adults" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/who_gho/obesity_adults").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

Point d’accès API: https://datazimuts.com/v1/datasets/who_gho/obesity_adults

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.