The NFSI is a composite measure of reality...
ANALYTICAL FRAMEWORK
The four pillars of food security that manifest in people, markets, and policy.
30%
PURCHASING POWER DIVERGENCE
Measures household capacity to afford a nutritious diet across income levels, states, and seasons.
25%
PHANTOM HARVEST
Tracks food production, market reach, and whether supply actually reaches those who need it.
25%
SANITATION-MALNUTRITION LINK
Assesses dietary diversity, food safety standards, and the WASH conditions that determine nutritional outcomes.
20%
RISK-BUDGET MISMATCH
Evaluates climate resilience, institutional capacity, and long-term food system stability.
Primary statistical sources for macroeconomic and agricultural baselines.
Real-time and near-real-time data on commodity prices, trade flows, and fiscal allocation.
Event-driven data on conflict, climate shocks, and displacement affecting food access.
SCORING SYSTEM
All raw indicators are scaled to a 0–100 range, enabling cross-indicator and cross-state comparison on a unified axis.
Contextual factors assessed on a 0–2 ordinal system where 0 = severe constraint, 1 = moderate, 2 = minimal constraint.
Pillar scores are computed as weighted averages and combined into the NFSI Composite Score using pillar-specific weights.
GRANULARITY
The NFSI operates at two levels of geographic resolution — enabling both national strategy and local intervention planning.
36 States + FCT
State Level
Primary scoring unit. Full pillar breakdown with time-series tracking.
774 LGAs
LGA Level
Derived via proxy model from state-level data and available census indicators.
TRANSPARENCY
We document constraints openly. Rigour includes honesty about what the data cannot tell us.
Some official statistics carry 6–12 month collection delays, which can understate rapidly evolving conditions.
Nigeria's informal food markets are structurally under-reported, creating systematic blind spots in access metrics.
Active conflict in states like Borno and Zamfara restricts direct data collection requiring proxy and satellite estimation.
Sub-state LGA data is modelled rather than directly surveyed, introducing estimation error at granular levels.
Some official statistics carry 6–12 month collection delays, which can understate rapidly evolving conditions.
Nigeria's informal food markets are structurally under-reported, creating systematic blind spots in access metrics.
Active conflict in states like Borno and Zamfara restricts direct data collection requiring proxy and satellite estimation.
Sub-state LGA data is modelled rather than directly surveyed, introducing estimation error at granular levels.