List all available Pathways segmentations (country-level studies).

Each segmentation represents a population segmentation study for a specific country, based on survey data (e.g., DHS). Use this to discover which countries and studies are available. Only returns active, published segmentations.

Get full details of a segmentation including all its segments.

Returns segmentation metadata (country, source, methodology) plus a list of all population segments with their vulnerability levels and prevalence.

List population segments for a segmentation, with optional filters.

Each segment represents a distinct group of women identified through cluster analysis, with a vulnerability level (least/less/more/most) and stratum (urban/rural).

Get a comprehensive profile for a specific population segment.

This is the "who are these women?" view — returns the segment's vulnerability level, prevalence, and key metrics organized into:

• health_outcomes: metrics linked to Themes (measurable health results such as maternal health, nutrition, sexual and reproductive health).

• vulnerability_factors: metrics linked to Domains (structural and social determinants such as household economics, social support).

To compare a segment against the sample total, call get_segment_metrics without a segment_code to retrieve the weighted sample-aggregate baseline.

Use this to understand the characteristics, health outcomes, and vulnerability profile of a specific segment.

Get quantitative metrics (indicators, prevalence) for a segment or the sample total.

Sample-total metrics: metrics with no segment represent the weighted aggregate across all sample respondents (not a census). Omit segment_code to retrieve them. Use these as a baseline to compare individual segments.

Segment-level metrics: pass a segment_code to retrieve metrics for a specific population group.

Metrics fall into two categories:

• Health Outcomes: linked to Themes (e.g., maternal_health, nutrition). Filter with theme_code.

• Vulnerability Factors: linked to Domains (e.g., household_economics, social_support). Filter with domain_code.

Use list_themes_and_domains to discover available theme and domain codes.

Search and filter variables (indicators) for a segmentation.

Variables are quantitative indicators measured in a segmentation study. They can be health outcomes (e.g., "No current modern FP use") or vulnerability factors (e.g., "Education level").

List all health themes (Health Outcomes) and vulnerability domains (Vulnerability Factors).

• Themes relate to Health Outcomes: measurable health results such as Maternal Health, Nutrition, or Sexual and Reproductive Health.

• Domains describe sets of Vulnerability Factors: structural and social determinants that explain why a segment is vulnerable, such as Household Economics or Social Support.

Use theme codes to filter health outcome metrics and domain codes to filter vulnerability factor metrics in get_segment_metrics.

List sub-national regions for a segmentation's country.

Regions are administrative areas within a country. The geometry (GeoJSON) is excluded to keep the response small.

Get the geographic distribution of population segments across regions.

Each record shows what percentage of a region's population belongs to a given segment. Use this to answer questions like:

• "Which regions have the highest concentration of the most vulnerable segment?"

• "How are the segments distributed across Dakar?"

• "Where is segment R2 most prevalent?"

Supply only segmentation_code to get the full distribution matrix. Filter by segment_code to rank regions for a specific segment. Filter by region_code to see the segment breakdown within one region. Both filters can be combined.

Results are sorted by percentage descending (highest concentration first).