Datasets:

electricsheepafrica
/

ssa-risk-factor-prevalence

sample_id stringlengths 15 15	population stringclasses 7 values	region stringclasses 5 values	is_SSA bool 2 classes	is_reference_panel bool 2 classes	sex stringclasses 2 values	age int64 18 85	bmi_category stringclasses 4 values	physical_activity_level stringclasses 2 values	alcohol_use_pattern stringclasses 3 values	smoking_status stringclasses 3 values	dietary_pattern stringclasses 3 values
RF_SAMPLE_00001	SSA_West	West	true	false	Female	49	Obese	Sedentary	None	Never	Mixed
RF_SAMPLE_00002	SSA_West	West	true	false	Female	31	Underweight	Sedentary	None	Never	Traditional
RF_SAMPLE_00003	SSA_West	West	true	false	Female	55	Overweight	Active	None	Never	Traditional
RF_SAMPLE_00004	SSA_West	West	true	false	Female	57	Normal	Active	None	Never	Western
RF_SAMPLE_00005	SSA_West	West	true	false	Female	20	Obese	Sedentary	None	Never	Mixed
RF_SAMPLE_00006	SSA_West	West	true	false	Male	28	Obese	Sedentary	Low	Never	Traditional
RF_SAMPLE_00007	SSA_West	West	true	false	Female	47	Obese	Active	None	Never	Mixed
RF_SAMPLE_00008	SSA_West	West	true	false	Female	41	Normal	Active	None	Never	Mixed
RF_SAMPLE_00009	SSA_West	West	true	false	Male	45	Underweight	Active	Low	Never	Mixed
RF_SAMPLE_00010	SSA_West	West	true	false	Female	34	Normal	Active	Low	Never	Traditional
RF_SAMPLE_00011	SSA_West	West	true	false	Female	56	Obese	Active	None	Never	Traditional
RF_SAMPLE_00012	SSA_West	West	true	false	Male	55	Normal	Active	Harmful	Current	Traditional
RF_SAMPLE_00013	SSA_West	West	true	false	Female	46	Obese	Active	None	Former	Mixed
RF_SAMPLE_00014	SSA_West	West	true	false	Female	60	Overweight	Sedentary	None	Never	Traditional
RF_SAMPLE_00015	SSA_West	West	true	false	Female	51	Underweight	Sedentary	None	Never	Western
RF_SAMPLE_00016	SSA_West	West	true	false	Male	34	Normal	Active	Low	Never	Traditional
RF_SAMPLE_00017	SSA_West	West	true	false	Female	50	Normal	Active	Low	Never	Western
RF_SAMPLE_00018	SSA_West	West	true	false	Female	33	Obese	Sedentary	Low	Never	Mixed
RF_SAMPLE_00019	SSA_West	West	true	false	Female	56	Normal	Sedentary	None	Never	Traditional
RF_SAMPLE_00020	SSA_West	West	true	false	Female	44	Overweight	Active	None	Never	Traditional
RF_SAMPLE_00021	SSA_West	West	true	false	Male	43	Normal	Active	Harmful	Never	Western
RF_SAMPLE_00022	SSA_West	West	true	false	Female	36	Obese	Active	Harmful	Never	Traditional
RF_SAMPLE_00023	SSA_West	West	true	false	Male	61	Obese	Active	None	Never	Traditional
RF_SAMPLE_00024	SSA_West	West	true	false	Female	43	Normal	Sedentary	Harmful	Never	Mixed
RF_SAMPLE_00025	SSA_West	West	true	false	Female	39	Underweight	Active	Harmful	Never	Traditional
RF_SAMPLE_00026	SSA_West	West	true	false	Male	40	Overweight	Sedentary	None	Current	Traditional
RF_SAMPLE_00027	SSA_West	West	true	false	Female	52	Overweight	Sedentary	None	Never	Mixed
RF_SAMPLE_00028	SSA_West	West	true	false	Female	50	Normal	Active	Low	Never	Traditional
RF_SAMPLE_00029	SSA_West	West	true	false	Male	50	Overweight	Active	None	Current	Traditional
RF_SAMPLE_00030	SSA_West	West	true	false	Female	51	Obese	Active	None	Never	Mixed
RF_SAMPLE_00031	SSA_West	West	true	false	Female	73	Overweight	Active	None	Never	Western
RF_SAMPLE_00032	SSA_West	West	true	false	Male	40	Obese	Sedentary	Harmful	Never	Mixed
RF_SAMPLE_00033	SSA_West	West	true	false	Female	38	Normal	Active	None	Never	Traditional
RF_SAMPLE_00034	SSA_West	West	true	false	Female	34	Obese	Active	Low	Never	Traditional
RF_SAMPLE_00035	SSA_West	West	true	false	Female	53	Underweight	Sedentary	None	Former	Traditional
RF_SAMPLE_00036	SSA_West	West	true	false	Female	60	Overweight	Active	Harmful	Never	Western
RF_SAMPLE_00037	SSA_West	West	true	false	Female	44	Overweight	Active	Low	Never	Mixed
RF_SAMPLE_00038	SSA_West	West	true	false	Male	34	Overweight	Active	Harmful	Never	Traditional
RF_SAMPLE_00039	SSA_West	West	true	false	Female	34	Normal	Active	Low	Never	Traditional
RF_SAMPLE_00040	SSA_West	West	true	false	Male	53	Normal	Active	Low	Never	Traditional
RF_SAMPLE_00041	SSA_West	West	true	false	Female	55	Obese	Active	None	Never	Traditional
RF_SAMPLE_00042	SSA_West	West	true	false	Female	52	Normal	Sedentary	None	Never	Traditional
RF_SAMPLE_00043	SSA_West	West	true	false	Female	36	Obese	Active	None	Never	Traditional
RF_SAMPLE_00044	SSA_West	West	true	false	Male	48	Overweight	Active	Low	Former	Western
RF_SAMPLE_00045	SSA_West	West	true	false	Female	47	Obese	Active	Low	Never	Traditional
RF_SAMPLE_00046	SSA_West	West	true	false	Female	48	Overweight	Active	None	Former	Traditional
RF_SAMPLE_00047	SSA_West	West	true	false	Male	56	Overweight	Active	None	Current	Mixed
RF_SAMPLE_00048	SSA_West	West	true	false	Male	48	Overweight	Active	Low	Never	Mixed
RF_SAMPLE_00049	SSA_West	West	true	false	Female	54	Normal	Active	None	Never	Mixed
RF_SAMPLE_00050	SSA_West	West	true	false	Male	46	Obese	Active	None	Never	Mixed
RF_SAMPLE_00051	SSA_West	West	true	false	Female	49	Normal	Active	None	Former	Traditional
RF_SAMPLE_00052	SSA_West	West	true	false	Female	53	Obese	Active	Low	Never	Traditional
RF_SAMPLE_00053	SSA_West	West	true	false	Female	26	Obese	Sedentary	None	Current	Mixed
RF_SAMPLE_00054	SSA_West	West	true	false	Female	41	Obese	Sedentary	None	Never	Traditional
RF_SAMPLE_00055	SSA_West	West	true	false	Female	39	Normal	Sedentary	Low	Never	Western
RF_SAMPLE_00056	SSA_West	West	true	false	Male	37	Normal	Sedentary	Harmful	Current	Mixed
RF_SAMPLE_00057	SSA_West	West	true	false	Female	41	Obese	Sedentary	None	Never	Traditional
RF_SAMPLE_00058	SSA_West	West	true	false	Male	64	Overweight	Active	None	Never	Western
RF_SAMPLE_00059	SSA_West	West	true	false	Male	34	Overweight	Active	Low	Never	Traditional
RF_SAMPLE_00060	SSA_West	West	true	false	Male	58	Normal	Active	Low	Never	Traditional
RF_SAMPLE_00061	SSA_West	West	true	false	Male	23	Underweight	Active	Harmful	Current	Traditional
RF_SAMPLE_00062	SSA_West	West	true	false	Male	41	Normal	Active	Low	Never	Western
RF_SAMPLE_00063	SSA_West	West	true	false	Male	47	Normal	Active	Low	Never	Traditional
RF_SAMPLE_00064	SSA_West	West	true	false	Female	53	Overweight	Sedentary	Low	Never	Traditional
RF_SAMPLE_00065	SSA_West	West	true	false	Female	54	Obese	Active	None	Current	Mixed
RF_SAMPLE_00066	SSA_West	West	true	false	Female	55	Normal	Active	Low	Never	Western
RF_SAMPLE_00067	SSA_West	West	true	false	Female	40	Overweight	Sedentary	None	Never	Traditional
RF_SAMPLE_00068	SSA_West	West	true	false	Female	39	Underweight	Active	Low	Never	Traditional
RF_SAMPLE_00069	SSA_West	West	true	false	Male	56	Normal	Active	None	Never	Mixed
RF_SAMPLE_00070	SSA_West	West	true	false	Female	43	Normal	Sedentary	Low	Never	Traditional
RF_SAMPLE_00071	SSA_West	West	true	false	Male	28	Normal	Active	Low	Current	Traditional
RF_SAMPLE_00072	SSA_West	West	true	false	Female	30	Overweight	Active	None	Never	Mixed
RF_SAMPLE_00073	SSA_West	West	true	false	Female	33	Overweight	Active	None	Never	Traditional
RF_SAMPLE_00074	SSA_West	West	true	false	Female	51	Overweight	Active	None	Never	Western
RF_SAMPLE_00075	SSA_West	West	true	false	Female	47	Overweight	Active	None	Never	Traditional
RF_SAMPLE_00076	SSA_West	West	true	false	Female	54	Normal	Active	Harmful	Never	Traditional
RF_SAMPLE_00077	SSA_West	West	true	false	Female	39	Normal	Active	Low	Never	Mixed
RF_SAMPLE_00078	SSA_West	West	true	false	Female	47	Underweight	Sedentary	Harmful	Never	Western
RF_SAMPLE_00079	SSA_West	West	true	false	Female	53	Normal	Active	None	Never	Traditional
RF_SAMPLE_00080	SSA_West	West	true	false	Female	41	Overweight	Sedentary	None	Never	Mixed
RF_SAMPLE_00081	SSA_West	West	true	false	Female	51	Obese	Active	Low	Never	Mixed
RF_SAMPLE_00082	SSA_West	West	true	false	Female	36	Normal	Active	Low	Never	Traditional
RF_SAMPLE_00083	SSA_West	West	true	false	Female	40	Normal	Active	Harmful	Never	Mixed
RF_SAMPLE_00084	SSA_West	West	true	false	Female	40	Overweight	Active	None	Never	Mixed
RF_SAMPLE_00085	SSA_West	West	true	false	Female	29	Normal	Active	None	Never	Western
RF_SAMPLE_00086	SSA_West	West	true	false	Female	51	Obese	Active	Harmful	Never	Traditional
RF_SAMPLE_00087	SSA_West	West	true	false	Male	39	Overweight	Sedentary	Harmful	Never	Mixed
RF_SAMPLE_00088	SSA_West	West	true	false	Male	45	Overweight	Active	Low	Never	Traditional
RF_SAMPLE_00089	SSA_West	West	true	false	Male	51	Overweight	Active	Low	Former	Traditional
RF_SAMPLE_00090	SSA_West	West	true	false	Female	51	Normal	Active	None	Never	Mixed
RF_SAMPLE_00091	SSA_West	West	true	false	Female	54	Obese	Sedentary	None	Never	Mixed
RF_SAMPLE_00092	SSA_West	West	true	false	Female	44	Overweight	Active	None	Never	Mixed
RF_SAMPLE_00093	SSA_West	West	true	false	Male	39	Obese	Active	Low	Never	Mixed
RF_SAMPLE_00094	SSA_West	West	true	false	Male	44	Obese	Active	None	Current	Mixed
RF_SAMPLE_00095	SSA_West	West	true	false	Male	23	Obese	Active	Low	Never	Mixed
RF_SAMPLE_00096	SSA_West	West	true	false	Male	26	Underweight	Active	Low	Current	Traditional
RF_SAMPLE_00097	SSA_West	West	true	false	Female	28	Normal	Active	None	Never	Mixed
RF_SAMPLE_00098	SSA_West	West	true	false	Male	32	Overweight	Active	Low	Current	Traditional
RF_SAMPLE_00099	SSA_West	West	true	false	Male	50	Overweight	Active	Harmful	Current	Traditional
RF_SAMPLE_00100	SSA_West	West	true	false	Female	33	Overweight	Active	None	Never	Traditional

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SSA Risk Factor Prevalence Dataset (Adults, Multi-ancestry) | Africa (World Health Organization)

Size category: 10K<n<100K - Formats: parquet - Sector: health - Engineered by Electric Sheep Africa

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Health datasets help researchers examine disease burden, service delivery, risk factors, outcomes, and public-health program performance.

Dataset context from the existing Hugging Face card: SSA Risk Factor Prevalence Dataset (Adults, Multi-ancestry, Synthetic) Dataset summary This dataset provides a synthetic adult cohort (age 18–85 years) with key modifiable non-communicable disease (NCD) risk factors, designed around sub-Saharan African (SSA) populations with comparative reference groups. Included risk factors: Obesity prevalence using WHO BMI categories. Physical activity: sedentary vs active. Alcohol use patterns: none, low, harmful. Smoking status:… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/ssa-risk-factor-prevalence.

Dataset Profile

Field	Value
Hugging Face repo	`electricsheepafrica/ssa-risk-factor-prevalence`
Sector	health
Topic tags	risk-factors, obesity, physical-activity, alcohol, smoking, diet, sub-saharan-africa
Modalities	`text`
Formats	`parquet`
Size category	`10K<n<100K`
Countries	Africa-wide or source-defined African coverage
ISO3 coverage	`not declared`
Last modified on HF	`2025-11-24 10:58:13+00:00`
Inventory snapshot	`2026-07-16T16:00:34Z`

How To Read This Dataset

Start from the repository files and the dataset viewer when available.
Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
Preserve missing values until you have a defensible imputation rule.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/ssa-risk-factor-prevalence")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
Exact schema, row counts, and source files should be inspected in the repository data files.
Metadata gaps from the inventory: country, upstream_publisher.
Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Source context: World Health Organization
Publisher/source attribution: WHO public data
License: cc-by-nc-4.0
Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/ssa-risk-factor-prevalence
Inventory retrieved at: 2026-07-16T16:00:34Z

Suggested Analyses

Inspect schema and missingness before modeling.
Profile variables by geography, time, and subgroup columns where present.
Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

@misc{electric_sheep_africa_ssa_risk_factor_prevalence_2026,
  title        = {SSA Risk Factor Prevalence Dataset (Adults, Multi-ancestry) | Africa (World Health Organization)},
  author       = {WHO public data},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/ssa-risk-factor-prevalence},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/ssa-risk-factor-prevalence}}
}

License

Released under cc-by-nc-4.0.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.

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