README.md

---
language:
- en
tags:
- endocrinology
- hormones
- estradiol
- progesterone
- testosterone
- insulin
- igf-1
- sub-saharan-africa
license: cc-by-nc-4.0
pretty_name: SSA Hormonal Profiles Dataset (Multi-ancestry)
task_categories:
- other
size_categories:
- 1K<n<10K
---

# SSA Hormonal Profiles Dataset (Multi-ancestry, Synthetic)

## Dataset summary

This dataset provides a **synthetic hormonal profile cohort** of 10,000 adults across multiple ancestry groups with a focus on **sub-Saharan Africa (SSA)**. It includes:

- **Estradiol (E2)** and **progesterone (P4)** in women and men (by menopausal status for women).
- **Testosterone (T)** in women and men (by age band).
- **Fasting insulin** levels (by population).
- **IGF-1** levels (by age band).

Values are informed by published **reference intervals and age/sex trends** for these hormones, but all individuals and measurements are fully synthetic.


## Cohort design

### Sample size and populations

- **Total N**: 10,000 synthetic adults.
- **Populations**:
  - `SSA_West`: 2,000
  - `SSA_East`: 2,000
  - `SSA_Central`: 1,500
  - `SSA_Southern`: 1,500
  - `AAW` (African American, admixed): 1,500
  - `EUR` (European reference): 1,000
  - `EAS` (East Asian reference): 500

- **Sex distribution**:
  - `Male`: ~45%
  - `Female`: ~55%

- **Age**: 18–80 years with population-specific means/SDs, loosely aligned with prior cardiovascular and reproductive-history datasets.


## Hormonal variables

### Menopausal status (women)

Variable:

- `menopausal_status` – for women:
  - `premenopausal`
  - `perimenopausal`
  - `postmenopausal`
- For men: `menopausal_status = "NA"`.

Status is assigned by **age band** (18–39, 40–49, 50–80) with probabilities reflecting typical menopause timing:

- 18–39: mostly premenopausal.
- 40–49: mix of pre-, peri-, and postmenopausal.
- 50–80: predominantly postmenopausal.


### Estradiol (E2)

Variable:

- `estradiol_pg_ml` – estradiol in **pg/mL**.

Design anchors:

- Premenopausal women have higher and more variable estradiol (mean ~80 pg/mL, SD ~40), capturing the broad range across the menstrual cycle.
- Perimenopausal women have intermediate values (mean ~50 pg/mL).
- Postmenopausal women have low values (mean ~15 pg/mL) with an approximate upper bound of 20–30 pg/mL.
- Men have low-to-moderate estradiol (mean ~35 pg/mL, SD ~15).

These values are informed qualitatively by **clinical reference intervals** and reviews of estradiol levels in pre- vs postmenopausal women and men.


### Progesterone (P4)

Variable:

- `progesterone_ng_ml` – progesterone in **ng/mL**.

Design anchors:

- Premenopausal women: mean ~3 ng/mL (large SD), representing random-cycle values with luteal peaks.
- Perimenopausal women: mean ~1.5 ng/mL.
- Postmenopausal women: mean ~0.5 ng/mL.
- Men: mean ~0.5 ng/mL.

These reflect the general pattern of high-cycle variation in premenopausal women and low steady values after menopause or in men.


### Testosterone (T)

Variable:

- `testosterone_ng_dl` – total testosterone in **ng/dL**.

Age bands:

- 18–29, 30–39, 40–49, 50–59, 60–80 years.

Design anchors (mid-range values from reference summaries):

- **Men**
  - 18–29: mean ~600 ng/dL.
  - 30–39: ~550 ng/dL.
  - 40–49: ~500 ng/dL.
  - 50–59: ~450 ng/dL.
  - 60–80: ~400 ng/dL.

- **Women**
  - 18–29: mean ~40 ng/dL.
  - 30–39: ~35 ng/dL.
  - 40–49: ~30 ng/dL.
  - 50–59: ~25 ng/dL.
  - 60–80: ~20 ng/dL.

Testosterone decreases with age in both sexes, roughly consistent with published age-specific reference data.


### Fasting insulin

Variable:

- `insulin_fasting_uIU_ml` – fasting serum insulin in **uIU/mL**.

Design anchors:

- Healthy adult reference intervals suggest **2–12 uIU/mL** as typical.
- Population-specific means reflect metabolic differences:
  - SSA and AAW have slightly higher means (~8.5–10 uIU/mL).
  - EUR/EAS have somewhat lower means (~7–7.5 uIU/mL).

Values are truncated between 1 and 40 uIU/mL.


### IGF-1

Variable:

- `igf1_ng_ml` – insulin-like growth factor 1 in **ng/mL**.

Age bands and means reflect **age-related decline** (≈15% per decade) from young adulthood:

- 18–29: mean ~250 ng/mL.
- 30–39: ~210 ng/mL.
- 40–49: ~180 ng/mL.
- 50–59: ~150 ng/mL.
- 60–80: ~130 ng/mL.

Values are truncated between 40 and 500 ng/mL.


## File and schema

### `hormonal_profiles_data.parquet` / `hormonal_profiles_data.csv`

One row per synthetic individual with:

- `sample_id`
- `population`, `region`, `is_SSA`, `is_reference_panel`
- `sex` (`Male`, `Female`)
- `age` (18–80 years)
- `menopausal_status` (for women; `NA` for men)
- `estradiol_pg_ml`
- `progesterone_ng_ml`
- `testosterone_ng_dl`
- `insulin_fasting_uIU_ml`
- `igf1_ng_ml`


## Generation

The dataset is generated with:

- `hormonal_profiles/scripts/generate_hormonal_profiles.py`

using configuration in:

- `hormonal_profiles/configs/hormonal_profiles_config.yaml`

and literature curated in:

- `hormonal_profiles/docs/LITERATURE_INVENTORY.csv`

Key modeling steps:

1. **Sample generation** – multi-ancestry sample with age/sex distribution.
2. **Menopausal status assignment** – by age band in women.
3. **Hormone sampling** – for each hormone, sample from normal distributions with age/sex/status-specific means and SDs and truncate to plausible ranges.


## Validation

Validation is implemented in:

- `hormonal_profiles/scripts/validate_hormonal_profiles.py`

Checks include:

- **C01–C02 – Sample size and population counts** vs config.
- **C03 – Estradiol means by sex and menopausal status** vs config.
- **C04 – Progesterone means by sex and menopausal status** vs config.
- **C05 – Testosterone means by sex and age band** vs config.
- **C06 – Insulin means by population** vs config.
- **C07 – IGF-1 means by age band** vs config.
- **C08 – Missingness in key variables**.

The validator writes:

- `hormonal_profiles/output/validation_report.md`

For the released version, the validator reports **overall status `PASS`** (with some checks at `WARN` level where sampling noise produces minor deviations from target means).


## Intended use

This dataset is intended for:

- **Methods development** in endocrine modeling and multi-modal risk prediction.
- Exploring how **age, sex, and menopausal status** relate to key hormonal axes.
- Serving as a **companion** to the reproductive history, body composition, and cardiovascular metrics datasets.

It is **not suitable** for:

- Clinical decision-making or hormone therapy dosing.
- Deriving exact clinical reference intervals.
- Individual-level risk prediction.

All hormone levels are synthetic.


## Ethical considerations

- No real patient data are used.
- Population labels are for simulation and methodological realism only.
- Analyses should be interpreted as methodological demonstrations rather than statements about specific groups.


## License

- License: **CC BY-NC 4.0**.
- Free to use for non-commercial research, education, and methods development with attribution.


## Citation

If you use this dataset, please cite:

> Electric Sheep Africa. "SSA Hormonal Profiles Dataset (Multi-ancestry, Synthetic)." Hugging Face Datasets.

and consider citing relevant endocrine reference works that informed the design (estradiol/progesterone reference intervals, age-related testosterone and IGF-1 studies, and fasting insulin reference interval papers).