Child marriage prevalence by country (UNICEF Data Warehouse)

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Latest nationally-representative child-marriage estimates for ~140+ countries (keyless UNICEF Data Warehouse SDMX, Child Marriage dataflow): share of women 20-24 married before 18 (SDG 5.3.1) and before 15, plus share of girls 15-19 currently married/in union — each with estimate year, survey coverage window, source survey and within-indicator prevalence rank. The gender/child-protection layer for development, human-rights and country-risk models; joins on country_code with the catalog's other global panels. Survey-based point estimates, not an annual panel.

Source: UNICEF child-marriage intelligence
Rows: 425
Columns: 11
Source cadence: Yearly
Last refreshed: Oct 4, 2026
Theme: social

Column	Type	Description
country_code	string	ISO 3166-1 alpha-3 country code (UNICEF Data Warehouse field REF_AREA; regional aggregates dropped; XKX kept for Kosovo).
country	string	Country name from the catalog's canonical ISO3 mapper (+Kosovo override).
indicator	string	Canonical indicator slug: u18 (SDG 5.3.1), u15, or current_15_19.
indicator_label	string	Human-readable indicator definition.
value_pct	float	Latest nationally-representative estimate of the indicator, percent. (unit: %)
estimate_year	integer	Reference year of the estimate (TIME_PERIOD).
survey_coverage	string	Underlying survey window (COVERAGE_TIME, e.g. 2019-21).
data_source	string	Source survey/programme (MICS, DHS, NFHS, ...).
obs_status	string	UNICEF observation status (RP/RA).
prevalence_rank	integer	Within-indicator rank by prevalence, 1 = highest prevalence.
row_hash	string	Deterministic 12-hex row identity hash (country_code\|indicator).

First 10 sample rows — a preview, not the complete dataset.

country_code	country	indicator	indicator_label	value_pct	estimate_year	survey_coverage	data_source	obs_status	prevalence_rank	row_hash
AFG	Afghanistan	current_15_19	Girls 15-19 currently married/in union (%)	16.4	2,023	2022-23	MICS 2022-23	RA	37	6e3a5d6ecae7
AGO	Angola	current_15_19	Girls 15-19 currently married/in union (%)	11.9	2,024	2023-24	DHS 2023-24	RP	59	04222faba393
ALB	Albania	current_15_19	Girls 15-19 currently married/in union (%)	6.7	2,018	2017-18	DHS 2017-18	RP	100	1f888a7b0f42
ARG	Argentina	current_15_19	Girls 15-19 currently married/in union (%)	7.7	2,020	2019-20	MICS 2019-20	RP	86	094fd95d01c0
ARM	Armenia	current_15_19	Girls 15-19 currently married/in union (%)	3	2,022	2022	Population Census 2022	RP	127	f4011402b65f
AZE	Azerbaijan	current_15_19	Girls 15-19 currently married/in union (%)	9.6	2,023	2023	MICS 2023	RP	74	54a36d0643bf
BDI	Burundi	current_15_19	Girls 15-19 currently married/in union (%)	5.9	2,017	2016-17	DHS 2016-17	RP	105	ebf9f4e4a61e
BEN	Benin	current_15_19	Girls 15-19 currently married/in union (%)	12.6	2,022	2021-22	MICS 2021-22	RP	52	98b3e42f7410
BFA	Burkina Faso	current_15_19	Girls 15-19 currently married/in union (%)	23.1	2,015	2015	EMDS 2015	RP	14	29b4fc16496b
BGD	Bangladesh	current_15_19	Girls 15-19 currently married/in union (%)	38.9	2,025	2025	MICS 2025	RP	3	32617a66f3ff

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

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

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/unicef_child_marriage_intel/unicef_child_marriage_prevalence").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/unicef_child_marriage_intel/unicef_child_marriage_prevalence

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

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Pinned to snapshot 20261004T182020Z-4476dcde1a28 and its content hash, so readers get exactly the data you used.

APA

UNICEF child-marriage intelligence. (2026). Child marriage prevalence by country (UNICEF Data Warehouse) [Data set, snapshot 20261004T182020Z-4476dcde1a28, sha256 4476dcde1a28]. Datazimuts. Retrieved 2026-10-05, from https://datazimuts.com/en/datasets/unicef_child_marriage_intel/unicef_child_marriage_prevalence?snapshot=20261004T182020Z-4476dcde1a28

BibTeX

@misc{dz_unicef_child_marriage_intel_unicef_child_4476dcde,
  title        = {{Child marriage prevalence by country (UNICEF Data Warehouse)}},
  author       = {{UNICEF child-marriage intelligence}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/unicef_child_marriage_intel/unicef_child_marriage_prevalence?snapshot=20261004T182020Z-4476dcde1a28}},
  note         = {Snapshot 20261004T182020Z-4476dcde1a28, sha256 4476dcde1a287075f422c4982baf3a872a5e6f327841745bf3d34cd8a1bb428e; accessed 2026-10-05}
}

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Child marriage prevalence by country (UNICEF Data Warehouse)

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