---
description: Schroeder 2007 attributes 10 percent of premature deaths to healthcare while Braveman-Egerter 2019 reviews four methods converging on the same estimate -- the 90 percent non-clinical claim is directionally correct but rhetorically imprecise
type: claim
domain: health
created: 2026-02-20
source: "Braveman & Egerter 2019, Schroeder 2007, County Health Rankings, Dever 1976"
confidence: proven
---

# medical care explains only 10-20 percent of health outcomes because behavioral social and genetic factors dominate as four independent methodologies confirm

The claim that "90% of health outcomes are determined by non-clinical factors" has become a cornerstone of the value-based care and social determinants of health movements. The intellectual lineage traces through five decades of converging evidence:

**Dever (1976)** published the first formal epidemiological model for health policy analysis, identifying four determinant categories: healthcare system, lifestyle, environment, and human biology. This established the framework that subsequent researchers refined.

**McGinnis & Foege (1993)** identified "actual causes of death" in the US in JAMA, finding approximately 40% of all deaths attributable to preventable behavioral factors (tobacco, diet/activity, alcohol, firearms, sexual behavior).

**Schroeder (2007)** synthesized this work in the New England Journal of Medicine, attributing premature deaths: behavioral patterns (40%), genetic predispositions (30%), social circumstances (15%), health care shortfalls (10%), environmental exposures (5%).

**County Health Rankings (Booske et al. 2010)** derived operational weights: social/economic factors (40%), health behaviors (30%), clinical care (20%), physical environment (10%). The 2025 model revision substantially restructured this framework, introducing climate and structural racism as explicit factors.

**Braveman & Egerter (2019)** published the most rigorous synthesis in Annals of Family Medicine, reviewing four independent methodologies that converge on medical care accounting for roughly 10% of premature mortality. Estimates of behavioral factors ranged from 16% to 65% depending on methodology.

**Why the 90% claim is imprecise:** It conflates several distinct claims: (a) medical care explains ~10-20% of population-level health variation, (b) behavioral and social factors are larger drivers of premature mortality than clinical care, therefore (c) 80-90% of health is "non-clinical." The leap from (a)+(b) to (c) elides the difference between explaining variation and determining outcomes, and between modifiable and total factors. The word "modifiable" is critical -- genetics (20-30%) is excluded from the denominator to get from "medical care is 10-20% of total determinants" to "80-90% of modifiable factors are non-clinical."

**The Manhattan Institute critique** (Chris Pope) argues the claim confuses variation with causation -- County Health Rankings measures what explains differences between counties, not what determines absolute outcomes. Clinical care shows low variation because it's relatively standardized, not because it's unimportant. Additionally, RCT evidence for SDOH expenditure impact on health outcomes is weaker than the observational data suggests.

**The defensible version:** "Most of what determines whether a population is healthy or unhealthy lies outside the doctor's office." The least defensible version: "Medical care barely matters."

This has structural implications for how healthcare should be organized. Since [[value-based care transitions stall at the payment boundary because 60 percent of payments touch value metrics but only 14 percent bear full risk]], the 90% finding argues that the 86% of payments still not at full risk are systematically ignoring the factors that matter most. Fee-for-service reimburses procedures, not outcomes, creating no incentive to address food insecurity, social isolation, or housing instability -- even though these may matter more than the procedure itself.


### Additional Evidence (confirm)
*Source: [[2024-09-19-commonwealth-fund-mirror-mirror-2024]] | Added: 2026-03-12 | Extractor: anthropic/claude-sonnet-4.5*

The Commonwealth Fund's 2024 Mirror Mirror international comparison provides the strongest real-world proof of this claim. The US ranks **second in care process quality** (clinical excellence when care is accessed) but **last in health outcomes** (life expectancy, avoidable deaths) among 10 peer nations. This paradox proves that clinical quality alone cannot produce population health — the US has near-best clinical care AND worst outcomes, demonstrating that non-clinical factors (access, equity, social determinants) dominate outcome determination. The care process vs. outcomes decoupling across 70 measures and nearly 75% patient/physician-reported data is the international benchmark showing medical care's limited contribution to population health outcomes.


### Additional Evidence (extend)
*Source: [[2025-00-00-nhs-england-waiting-times-underfunding]] | Added: 2026-03-15*

The NHS paradox—ranking 3rd overall while having catastrophic specialty access—provides supporting evidence that medical care's contribution to health outcomes is limited. A system can have multi-year waits for specialty procedures yet still rank highly in overall health system performance because primary care, equity, and universal coverage (which address behavioral and social factors) matter more than specialty delivery speed for population health outcomes.


### Additional Evidence (confirm)
*Source: [[2025-12-01-who-glp1-global-guidelines-obesity]] | Added: 2026-03-16*

WHO's three-pillar framework for GLP-1 obesity treatment explicitly positions medication as one component within a comprehensive approach requiring healthy diets, physical activity, professional support, and population-level policies. WHO states obesity is a 'societal challenge requiring multisectoral action — not just individual medical treatment.' This institutional positioning from the global health authority confirms that pharmaceutical intervention alone cannot address health outcomes driven by behavioral and social factors.


### Additional Evidence (extend)
*Source: [[2025-04-07-tufts-health-affairs-medically-tailored-meals-50-states]] | Added: 2026-03-18*

While social determinants predict health outcomes in observational studies, RCT evidence from food-as-medicine interventions shows that directly addressing social determinants (food insecurity) does not automatically improve clinical outcomes. The AHA 2025 systematic review of 14 US RCTs found Food Is Medicine programs improve diet quality and food security but "impact on clinical outcomes was inconsistent and often failed to reach statistical significance." This suggests the causal pathway from social determinants to health is more complex than simple resource provision.


### Additional Evidence (extend)
*Source: [[2025-01-01-produce-prescriptions-diabetes-care-critique]] | Added: 2026-03-18*

The Diabetes Care perspective provides a specific mechanism example: produce prescription programs may improve food security (a social determinant) without improving clinical outcomes (HbA1c, diabetes control) because the causal pathway from social disadvantage to disease is not reversible through single-factor interventions. This demonstrates the 10-20% medical care contribution in practice—addressing one SDOH factor (food access) doesn't overcome the compound effects of poverty, stress, and social disadvantage.


### Additional Evidence (confirm)
*Source: [[2026-03-19-vida-ai-biology-acceleration-healthspan-constraint]] | Added: 2026-03-19*

Amodei's complementary factors framework explicitly identifies 'human constraints' (behavior change, social systems, meaning-making) as a factor that bounds AI returns even in biological science. This provides theoretical grounding for why the 80-90% non-clinical determinants remain unaddressed by AI-accelerated biology—they fall into the 'human constraints' category that AI cannot optimize.

---

Relevant Notes:
- [[social isolation costs Medicare 7 billion annually and carries mortality risk equivalent to smoking 15 cigarettes per day making loneliness a clinical condition not a personal problem]] -- loneliness is one of the most actionable SDOH factors with clear cost signature and robust evidence
- [[SDOH interventions show strong ROI but adoption stalls because Z-code documentation remains below 3 percent and no operational infrastructure connects screening to action]] -- the 90% finding motivates SDOH intervention but the implementation gap persists
- [[value-based care transitions stall at the payment boundary because 60 percent of payments touch value metrics but only 14 percent bear full risk]] -- VBC is the payment model aligned with addressing non-clinical determinants but remains minority practice
- US healthcare incentives are fundamentally misaligned because every participant profits from sickness not health -- the misalignment is even deeper than clinical vs preventive -- it ignores the 80-90% of determinants that clinical care does not touch
- [[healthcare is a complex adaptive system requiring simple enabling rules not complicated management because standardized processes erode the clinical autonomy needed for value creation]] -- addressing the full spectrum of determinants requires enabling rules, not standardized SDOH checklists
- [[human needs are finite universal and stable across millennia making them the invariant constraints from which industry attractor states can be derived]] -- health needs are a subset of universal needs, and the attractor state must address the full spectrum not just clinical encounters

Topics:
- health and wellness
