vida: extract claims from 2025-xx-penn-ldi-obbba-snap-cuts-93000-premature-deaths

- Source: inbox/queue/2025-xx-penn-ldi-obbba-snap-cuts-93000-premature-deaths.md
- Domain: health
- Claims: 1, Entities: 0
- Enrichments: 2
- Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5)

Pentagon-Agent: Vida <PIPELINE>

domains/health/snap-benefit-loss-causes-measurable-mortality-through-food-insecurity-pathway.md

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+---
+type: claim
+domain: health
+description: Penn LDI projects 93,000 premature deaths from OBBBA SNAP cuts by applying empirically-derived mortality rates to CBO's 3.2 million coverage loss estimate
+confidence: experimental
+source: Penn LDI, CBO headcount projection, peer-reviewed SNAP mortality research
+created: 2026-04-01
+title: SNAP benefit loss causes measurable mortality increases in under-65 populations through food insecurity pathways with peer-reviewed rate estimates of 2.9 percent excess deaths over 14 years
+agent: vida
+scope: causal
+sourcer: Penn LDI (Leonard Davis Institute of Health Economics)
+related_claims: ["[[SDOH interventions show strong ROI but adoption stalls because Z-code documentation remains below 3 percent and no operational infrastructure connects screening to action]]", "[[medical care explains only 10-20 percent of health outcomes because behavioral social and genetic factors dominate as four independent methodologies confirm]]"]
+---
+
+# SNAP benefit loss causes measurable mortality increases in under-65 populations through food insecurity pathways with peer-reviewed rate estimates of 2.9 percent excess deaths over 14 years
+
+Penn Leonard Davis Institute researchers project 93,000 premature deaths between 2025-2039 from SNAP provisions in the One Big Beautiful Bill Act using a transparent methodology: CBO projects 3.2 million people under 65 will lose SNAP benefits; peer-reviewed research quantifies mortality rates comparing similar populations WITH vs. WITHOUT SNAP over 14 years; applying these rates to the CBO headcount yields the 93,000 estimate (approximately 2.9% excess mortality rate over 14 years, or ~6,600 additional deaths annually). The methodology's strength is its transparency and grounding in empirical research rather than black-box modeling. Prior LDI research establishes SNAP's protective mechanisms: lower diabetes prevalence and reduced heart disease deaths. The 14-year projection window matches the observation period in the underlying mortality research, providing methodological consistency. This translates abstract SNAP-health evidence into concrete policy mortality stakes at scale comparable to doubling annual US road fatalities. Uncertainty sources include: long projection window allows policy changes, mortality rates may differ from base research population, and modeling assumptions about benefit loss duration and intensity.