Deaths of Despair – Detailed Study Notes
Introduction
- Lecturer apologizes for raspy voice; promises a short lecture that frames the week’s independent content
- Central theme: “Deaths of Despair” (D.o.D.) and their outsized impact in Missouri and the U.S.
- Goal: define the term, explore data patterns, critique common mistakes, and connect sociological theories (anomie, inequality) to real-world trends
Definition & Core Components of “Deaths of Despair”
- Phrase coined by demographers/economists to explain unusual mid-2000s mortality spike among older, rural white men
- 3 mutually reinforcing death categories:
• Drug overdoses – prescription pain-killers (hydrocodone, oxycontin), heroin, (now) fentanyl, and methamphetamine
• Alcohol-related disease – chiefly cirrhosis and other liver pathologies
• Suicide – self-inflicted fatalities - Observed despite an overall \uparrow life expectancy trend in the U.S.
Historical Discovery & Alarm
- Mid-2000s data broke the usual pattern: white mortality generally lowest, yet this cohort spiked
- Demographers flagged an epidemiological “blip” → prompted Congressional, CDC, JAMA studies
- “Deaths of Despair” rose sharply after \text{2000} – coincident with wide opioid marketing/availability
Key Data Sources Mentioned
- U.S. Joint Economic Committee (Republican staff report) → concise research brief (14 sources; model for student projects)
- Missouri Foundation for Health infographic (contains math errors)
- CDC surveillance, JAMA 2019 geographic heat maps
- National surveys of happiness: General Social Survey (GSS), Pew, Gallup
Missouri: A Case Study
- State exhibits dramatic D.o.D. rates; useful microcosm for studying rural impact
- Infographic highlights steep rises in:
• Drug overdoses: claimed “585%” increase (statistically incorrect)
• Alcohol poisoning: “763%” increase (suspect)
• Suicide: minor rise - Lecturer’s critique: you cannot show “585%” (percentages cap at 100\%); proper statement is “5.85-fold increase”
- Rural counties show highest concentrations; pattern not limited to whites—recent data show minorities increasingly affected (likely earlier under-surveillance)
- Prescription drug monitoring enables precise user counts, revealing demographic spread
Trend Lines (1930s → 2010s)
- Composite D.o.D. curve rises gradually until \sim 2000, then steep \uparrow
- Individual components:
• Drug deaths accelerate fastest (opioid phase ➜ fentanyl/meth phase)
• Alcohol line remains elevated; suicide line steadily high - Post-COVID numbers feared worse (pending data) — authors adding methamphetamine as 4th pillar
Racial & Gender Disparities
- Alcohol-related death rates, ages 45-54:
• Non-Hispanic white men top, followed by non-Hispanic white women
• Hispanic men/women lower but rising - Drug-related death rates show identical racial hierarchy
- Medical bias: whites more likely to be believed re: pain, thus more likely to receive opioids; non-whites often labeled “drug-seeking”
- Gendered coping networks: women cultivate stronger social support, mitigating late-life despair; men fare worse
Geographic Hotspots (JAMA 2019 Heat Map)
- Pacific Northwest
- Upper Midwest / Upper Peninsula
- “Rust Belt” (de-industrialized factory corridor)
- Common denominator: employment loss, shrinking community infrastructure, limited healthcare access
Under-Counting & Survey Design Issues
- CDC pilot found many opioid users deny “opioid” use because they don’t recognize the term
- Questionnaire now lists each pain-killer by brand/generic
Sociological Explanations — Multi-Level Factors
- Economic
• Closure of manufacturing plants (GM, RCA, DuPont, etc.) → “Rust Belt effect”
• Stagnant real wages since the 1970s \Rightarrow declining material wellbeing
• Housing collapse (2006-08) & Great Recession (2008) worsen insecurities - Educational
• Shrinking Pell Grants & rising tuition limit upward mobility - Political/Cultural
• Polarization, policy gridlock, erosion of communal institutions (churches, unions)
• Thomas Frank’s books (“What’s the Matter with Kansas?” & “Listen, Liberal”) argue Americans feel the American Dream is unreachable - Psychological
• Increased reported unhappiness; GSS “very happy” responses lowest since 1970s
• Anomie (Durkheim): normlessness, feeling one’s world is “crumbling”
• Marx’s “false consciousness”/“opiate of the masses” metaphor → literal opioid epidemic - Technological/Social Media
• Double-edged: connectivity vs. isolation, misinformation, comparison effects
Quantifying Unhappiness
- Surveys chart % “not too happy” tracking economic shocks
- Key correlation: \text{Unhappiness} \uparrow when inequality or perceived unfairness \uparrow
International Comparison
- U.S. uniquely severe; peer nations avoid similar spikes due to:
• Universal healthcare
• Paid parental/sick leave
• Subsidized higher education & job-retraining pipelines - UK, other Western nations face issues, but smaller public-health crisis magnitude
Evolving Crisis
- Shift from Rx opioids → fentanyl & polysubstance mixes (fentanyl + meth)
- COVID-19 lockdowns likely exacerbated overdoses and suicides (data forthcoming)
Policy/Practice Considerations
- Universal healthcare, paid leave, affordable education, retraining identified as structural fixes in Missouri infographic
- Sociological community reluctant to prescribe one-size solutions; calls for systemic rethink
- Importance of accurate data collection, culturally sensitive outreach, and destigmatizing mental-health / SUD treatment
Ethical & Practical Implications
- Medical gatekeeping & racial bias -> unequal harm
- Economic restructuring vs. individual blame
- Urgency: Lecturer ranks D.o.D. crisis near—or on some days above—COVID-19 as a public-health priority
Connections to Course & Upcoming Material
- Builds on earlier lectures on anomie, inequality, drug policy
- Sets stage for forthcoming unit on pharmaceutical industry’s role
Key Terms & Concepts (Quick Reference)
- Deaths of Despair (D.o.D.)
- Anomie (Durkheim): normlessness, social disintegration
- False Consciousness (Marx)
- Rust Belt
- Prescription Opioids: hydrocodone, oxycontin, fentanyl
- Crude Death Rate (CDR)
- Relative Increase Formula: \text{Relative\ Increase} = \frac{\text{New\ Rate} - \text{Old\ Rate}}{\text{Old\ Rate}} (multiply by 100\% for percentage)
- Fold-Change (times increase): \text{Fold} = \frac{\text{New}}{\text{Old}}
Study Prompts / Questions
- How does anomie theory help explain geographic clustering of D.o.D.?
- In what ways does racial bias in prescribing intersect with broader health inequities?
- Compare U.S. structural factors to one peer nation; why different outcomes?
- Brainstorm multi-level interventions (individual, community, policy)