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

Name: Obesity among adults, BMI ≥ 30 kg/m2 (age-standardized estimate) (%)
Creator: WHO Global Health Observatory
License: https://www.who.int/about/policies/terms-of-use
Keywords: obesity, ncd, who

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 rowsUpdated: 9/21/2026

obesityncdwho

Quality

Attribution

World Health Organization (WHO)

Schema

Column	Type	Description
country_code	string	Country code (WHO GHO API field SpatialDim, country-level rows only).
country_name	string	Country name from the WHO GHO COUNTRY dimension labels.
year	integer	Year of observation (WHO GHO API field TimeDim).
sex	string	Sex disaggregation label (WHO GHO API dimension Dim1). Only present when the indicator is published sex-disaggregated.
value	float	Estimate 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).
low	float	Lower bound of the published uncertainty interval (WHO GHO API field Low). Only present when the indicator publishes uncertainty intervals.
high	float	Upper bound of the published uncertainty interval (WHO GHO API field High). Only present when the indicator publishes uncertainty intervals.

Sample rows

country_code	country_name	year	sex	value	low	high
AFG	AFG	1980	SEX_BTSX	0.97484551	0.43505561	1.9094944
AFG	AFG	1980	SEX_FMLE	1.0670124	0.35969662	2.4551133
AFG	AFG	1980	SEX_MLE	0.89144167	0.26451633	2.1715384
AFG	AFG	1981	SEX_BTSX	1.0439184	0.48625534	1.9854777
AFG	AFG	1981	SEX_FMLE	1.1480882	0.40906579	2.5457801

Use with an LLM

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (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)

API endpoint: https://datazimuts.com/v1/datasets/who_gho/obesity_adults

Tip: fetch /llms.txt for the full machine-readable catalog.