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1
Deaths of Despair
Econ 43565
Bill Evans
Fall 2019
1
Introduction
• Long term secular decline in mortality
• Especially pronounced for minorities
• Starting in late 1990s, mortality rates started to climb for middle-aged whites – particularly low educated males
• Generated from particular deaths– Drug poisonings, suicides, alcohol liver disease
– Case and Deaton: “Deaths of despair”
2
This class
• Outline the basic trends– Trends are scary
– The declining economics prospects for low-skilled males is a part of the problem
• Two notes– Problem is concentrated in a particular group
– But economics is not the whole story
3
• Components of the trends
• Most of the deaths of despair is rising drug deaths
• Most of drug deaths are opioid/heroin
• Outline the origins of the opioid/heroin/fentanyl crisis
• Opioid crisis looks to be started by OxyContin
• Heroin crisis started by the reformulation of Oxy
• Fentanyl crisis piggy-back on the heroin crisis
4
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2
5 6
7
White 25‐29: 82% increaseBlack 25‐29: 8% decline
White 30‐34: 90% increaseBlack 30‐34: 12.5% decline
8
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3
9 10
11 12
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4
13
0
5
10
15
20
25
30
35
40
45
1999 2001 2003 2005 2007 2009 2011 2013 2015
Mo
rtal
ity
rate
Axis Title
Deaths of Despair and its Components
Deaths of despair
Drug poisonings
Alcohol-relatedliver mortality
Suicides
65% of the increasein the deaths if despair due to drugs
14
0
5
10
15
20
25
1999 2001 2003 2005 2007 2009 2011 2013 2015
Mo
rtal
ity
Year
Drug Poisonings, 1999-2016
All drugsAll drugsAll drugs
Heroin/opioids
Not heroin/opioids
77% of the increasein the drug poisoning rateis heroin/opioidpoisonings
15
0
10
20
30
40
50
60
80
90
100
110
120
130
140
1999 2001 2003 2005 2007 2009 2011 2013 2015
Mo
rtal
ity
rate
Mo
rta
lity
rate
Year
White, non-Hispanics, 25-34
All cause(left axis)
Heroin/opioid(right axis)
72% of the increasein the death rateis heroin/opioidpoisonings
0
10
20
30
40
170
180
190
200
210
1999 2001 2003 2005 2007 2009 2011 2013 2015
Mo
rtal
ity
rate
Mo
rta
lity
rate
Year
White, non-Hispanics, 35-44
All cause(left axis)
Heroin/opioid(right axis)
16
98% of the increasein the death rateis heroin/opioidpoisonings
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5
17
0
10
20
30
40
50
380
390
400
410
420
430
1999 2001 2003 2005 2007 2009 2011 2013 2015
Mo
rtal
ity
rate
Mo
rta
lity
rate
Year
White, non-Hispanics, 45-54
All cause(left axis)
Heroin/opioid(right axis)
56% of the increasein the death rateis heroin/opioidpoisonings
Case and Deaton
• Deaths of despair are a result of the breakdown in institutions: Jobs, earnings, family
• Time trends are easy to establish
• Correlation pronounced
• Correlation ≠ causation
18
19
0
0.1
0.2
0.3
0.4
0.5
0.6
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
Fra
cti
on
Year
Fraction Not Married by Education,White non-Hispanic Males 25-54, 1971-2017, March CPS
High school or less Some college College grad20
0.00
0.05
0.10
0.15
0.20
0.25
0.30
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
Fra
cti
on
Year
Fraction Not Living Independently by Education,White non-Hispanic Males 25-54, 1971-2017, March CPS
High school or less Some college College grad
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6
21
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
Fra
ctio
n
Year
Fraction Not in Labor Force by Education,White non-Hispanic Males 25-54, 1971-2017, March CPS
High school or less Some college College grad22
$0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
$80,000
$90,000
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
2017
$
Year
Real Earnings (2017$) of Full-Time/Full Year Workers by Education,White non-Hispanic Males 25-54, 1971-2017, March CPS
High school or less Some college College grad
23
-10
0
10
20
30
40
50
60
70
80
-0.1 -0.05 0 0.05 0.1 0.15 0.2
Ch
ang
e in
dru
g p
ois
on
ing
dea
th r
ate,
200
0/02
to
201
4/16
Change in condition, 2000/02 to 2014/16
Scatter Plot: ∆ in Marriage Rates vs. ∆ in Drug Poisoning Rate,White non-Hispanic Males, 25-54
ρ=0.28
24
-10
0
10
20
30
40
50
60
70
80
-0.1 -0.05 0 0.05 0.1 0.15
Ch
an
ge
in d
rug
po
iso
nin
g d
eat
h r
ate
, 20
00/0
2 t
o 2
014/
16
Change in condition, 2000/02 to 2014/16
Scatter Plot: ∆ in % Workers w/ Low Earningsvs. ∆ in Drug Poisoning Rate, White non-Hispanic Males, 25-54
ρ=0.25
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7
25
-10
0
10
20
30
40
50
60
70
80
-0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08
Ch
an
ge
in d
rug
po
iso
nin
g d
eat
h r
ate
, 20
00/0
2 t
o 2
014/
16
Change in condition, 2000/02 to 2014/16
Scatter Plot: ∆ in % Workers not in Labor Force,vs. ∆ in Drug Poisoning Rate, White non-Hispanic Males, 25-54
ρ=0.07
26
-10
0
10
20
30
40
50
60
70
80
-0.1 -0.05 0 0.05 0.1 0.15 0.2
Ch
an
ge
in d
rug
po
iso
nin
g d
eat
h r
ate
, 20
00/0
2 t
o 2
014/
16
Change in condition, 2000/02 to 2014/16
Scatter Plot: ∆ in % W/ at least one Negative Event,vs. ∆ in Drug Poisoning Rate, White non-Hispanic Males, 25-54
ρ=0.32
Problem for Case and Deaton
• Institutional outcomes have been declining for Blacks as well
• Poorer levels and same trends in outcomes
• Why has the drug crisis not impacted this group?
27 28
0
10
20
30
40
50
60
70
1999 2001 2003 2005 2007 2009 2011 2013 2015
Mo
rtal
ity
rate
Year
Drug Poisonings for Males, 24-54, by Race
White,non-Hispanic
Black,non-Hispanic
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8
29
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
Fra
cti
on
Year
Fraction Not Married by Race,Males 25-54, 1971-2017, March CPS
White non-Hispanic Black, non-Hispanic30
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
Fra
cti
on
Year
Fraction Not Living Independently by Race,Males 25-54, 1971-2017, March CPS
White non-Hispanic Black, non-Hispanic
31
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
Fra
cti
on
Year
Fraction Not in Labor Force by Race,Males 25-54, 1971-2017, March CPS
White non-Hispanic Black, non-Hispanic32
$0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
201
7$
Year
Real Earnings (2017$) of Full-Time/Full-Year Workers by Race,Males 25-54, 1971-2017, March CPS
White non-Hispanic Black, non-Hispanic
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The drug crisis
33 34
0
5
10
15
20
25
1989 1992 1995 1998 2001 2004 2007 2010 2013 2016
Dea
ths/
100,
000
Year
Drug Poisoning Death Rate, 1989-2017
All drugs
Opioids
non-opioids
Opioids 2/3rds of deaths in 201775% of the ↑ drug deaths
Some facts
• Drug deaths now 72,000/year– MV fatalities: 40,100– Gun deaths: 40,000– Homicides: 19,500– Suicides: 47,173
• Between 1989 – 2017– 704,000 drug poisoning deaths– About the same number of US soldiers that have died in
armed conflicts from Spanish American War through Operation Enduring Freedom
35
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10
37
0
5
10
15
20
25
30
35
40
45
50
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
De
ath
s/1
00,
000
Year
States with Lower Changes in Opioid Death Rates
CA OR TX AR38
0
5
10
15
20
25
30
35
40
45
50
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
De
ath
s/1
00,
000
Year
States with the Highest Changes in Opioid Death Rates
KY OH WV RI
39
0
2
4
6
8
10
12
14
16
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Dea
th R
ate
Year
Opioid Death Rate, 1999-2017All opioids
40
0
1
2
3
4
5
6
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Dea
th R
ate
Year
Opioid Death Rates, 1999-2017
Opioids only
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41
0
1
2
3
4
5
6
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Dea
th R
ate
Year
Opioid Death Rates, 1999-2017
Opioids only
Heroin only, orwith opioids
42
0
1
2
3
4
5
6
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Dea
th R
ate
Year
Opioid Death Rates, 1999-2017
Opioids only
Heroin only, orwith opioids
Fentanyl aloneor with heroinand/or opioids
43
0
1
2
3
4
5
6
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Dea
th R
ate
Year
Opioid Death Rates, 1999-2017
Opioids only
Heroin only, orwith opioids
Fentanyl aloneor with heroinand/or opioids
How did the opioid crisis come about
• Three distinct crisis– Opioid, then heroin, now fentanyl
• All are all related– Opioids led to heroin
– Heroin led to fentanyl
44
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Part 1: The Rise of OxyContin
45
Re-analysis of pain management
• <1990s, opioids mainly used for acute pain– Post surgery, cancer
• 1990s movement to use for chronic pain– 1996 – Consensus statement of two professional pain
societies –• “an epidemic of untreated pain”• Urged a more general use of opioids• < 1% of opioid users become addicted
– 1998 – Federation of State Medical Boards – MDs will not face discipline for heavy use of pain meds
– 2001 Joint Commission – pain is the “5th vital sign”
46
Enter OxyContin
• Synthetic drug with similar properties to heroin• Active ingredient is Oxycodone– Been around since 1917– Introduced to US in 1935– Percodan – Oxycodone and aspirin (1950)– Percocet – Oxycodone and acetaminophen (1974)
• OxyContin introduced in 1996– Purdue Pharma (Sackler Family)– Extended release (ER) drug – high mg content – $35 billion in worldwide sales through 2015
47
Enter OxyContin
• Released at same time as reform taking place
• Purdue actively marketed to doctors
• Originally marketed as “non habit forming”– Purdue trained sales force to mislead about addiction
– Porter and Jick (1980)
48
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49
Enter OxyContin
• Released at same time as reform taking place• Purdue actively marketed to doctors• Originally marketed as “non habit forming”– Purdue trained sales force to mislead about addiction– Porter and Jick (1980)– In 1996, Purdue was allowed to say addiction is rare
when appropriately used– Forced to stop in 2001– 2007 – Paid $600 million in fines to Feds
50
Advertising plan
• 1996 – advertise OxyContin for cancer patients
• 1997 and on – push for chronic pain sufferers
• Budgeted $640 million to advertise from 1996-2000
51 52
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Triplicate Prescription Pad states
• 9 states in 1995 (CA, HI, ID, IL, IN, MI, NY, RI, TX)• 3 copies
– For Schedule II drugs• Narcotic analgesics (including OxyContin)• Barbituates• Stimulants
– One kept by the Doc– Two given to pharmacy – one sent to state– State monitors use
• Schedule III drugs included at the time – Vicodin– Codeine– Combination drugs– Dihydrocodeinone
53
Purdue and Triplicate states
• Focus groups – Doc’s don’t like triplicate pads – “Based on the discussion with the two groups of doctors in the
triplicate state, albeit a small sample, it did not appear that they used Class II narcotics for treatment of non-cancer pain. Most did not want to go through the trouble involved, and they did not want to give the Government an excuse to monitor their activities”
• Heavy use of Schedule III drugs– “Writing triplicate prescriptions was more trouble than others, due
to the details of the forms and the various people that need to be copied on them. To the extent that they can avoid this extra effort, they will try to follow alternate protocols”
54
Purdue and Triplicate states
• Especially true for acute pain– “For the most severe conditions, such as those occurring as a result of
trauma or post-operative conditions, they would prescribe a narcotic. In the non-triplicate states, this was often a class II Opioid, whereas in the one triplicate state we visited, it was a Class III opioid” (p.26)
• Barrier to success in these states– “However, because oxycodone is a Class II opioid, prescribing
OxyContin will entail a triplicate prescription in those states requiring them. In addition, Class II opioids cannot be phoned in to the pharmacy, while Class III opioids can. These regulations create a barrier when positioning OxyContin versus the Class III opioids”
55
• Advertising strategy – avoid triplicate states– “Among the physicians in this triplicate state who do use
Class II narcotics in the treatment of non-cancer pain, our research suggests the absolute number of prescriptions they would write each year is very small, and probably would not be sufficient to justify any separate marketing effort” (p. 59)
56
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57
0
2
4
6
8
10
12
14
16
18
20
1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Dea
ths/
100K
Year
Drug Death Rates by Triplicate Status
non-TriplicateStates
TriplicateStates
58
0
2
4
6
8
10
12
14
16
18
20
1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Dea
ths/
100K
Year
Drug Death Rates by Triplicate Status
non-TriplicateStates
TriplicateStates
59
0
2
4
6
8
10
12
14
16
18
20
1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Dea
ths/
100K
Year
Drug Death Rates by Triplicate Status
non-TriplicateStates
TriplicateStates
Forecasts based < 1996 data
60
0
2
4
6
8
10
12
14
16
18
20
1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Dea
ths/
100K
Year
Drug Death Rates by Triplicate Status
non-TriplicateStates
TriplicateStates
Forecasts based < 1996 data
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16
61
0
2
4
6
8
10
12
14
16
18
20
1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Dea
ths/
100
K
Year
Opioid Death Rates by Triplicate States
non-Triplicatestates
Triplicatestates
62
0
2
4
6
8
10
12
14
16
18
20
1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Dea
ths/
100K
Year
Non-Opioid Death Rate by Triplicate Status
non-Triplicatestates
Triplicatestates
Part 2: The Movement to Heroin
63
Oxy reformulation
• Purdue Pharma responds to critics by releasing abuse-resistant version
• FDA approves reformulation on April 5, 2010
• New formulation is released without notice on August 10, 2010
• Old drugs immediately pulled from market
64
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Old and New OxyContin crushed
65
Problem
• Demand for opioids is still there
• The ability to get high is NOT
• Solution: switch to a close substitute
• That alternative: heroin
66
Heroin markets in US
• Historically – heroin markets divided by the Mississippi River– East was white powder heroin from SE Asia
–West was black tar heroin from Mexico
• Largest markets: NE and MW
• Mexican heroin making larger inroads all across US– Taken over Chicago, Philly, DC, NJ, part of NY
67
New suppliers: Xalisco Boys cartel
• Pioneered new distribution system:
• Cell owner supplies heroin from Mexico
• Cell manager in US city/town – receives shipments
– runs the business
• Telephone operator stays in an apartment all day receiving orders and relays these to drivers
• Drivers meet consumers and sell the heroin
68
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• High focus on product quality and customer service
• When they enter a city they sought out high users
• Now– US awash in heroin
– Amazingly high quality
– Very low price
69
Real heroin prices
70
0
500
1,000
1,500
2,000
2,500
3,000
3,500
1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013
Pri
ce p
er g
ram
pur
e, 2
012
US
Dol
lars
Year
Dating the switch to heroin
71
Dating the heroin crisis
• Examine lots of national time series– Opioid use/abuse
– Heroin abuse
• Use a statistical procedure to date a “structural break”
• All series break right after the reformuation of OxyContin
72
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73
0
1
2
3
4
5
6
7
8
9
2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01
RX
s/10
00
Year.Month
Monthly RXs for Oxycodone/1000 Subscribers, Marketscan Data
Actual Predicted
8/2010
74
0
10
20
30
40
50
60
2004.1 2006.1 2008.1 2010.1 2012.1 2014.1
KG
s /1
000
Year.Month
KGs of Oxycodone Shipments/1000, ARCOS Data
Actual Predicted
2010:Q3
75
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
2004.1 2006.1 2008.1 2010.1 2012.1 2014.1
% 3
0-d
ay U
se
Year.Month
% Use Pain Meds Recreationally in past 30 Days, NDUHS
Actual Predicted
2010:Q2
76
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
2004.01 2005.01 2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01 2014.01
Dea
ths/
100,
000
Year.Month
Monthly Heroin Deaths/100,000
Actual Predicted
9/2010
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20
77
0.00
0.01
0.02
0.03
0.04
0.05
2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01
En
cou
nte
rs/
1000
Year.Month
Inpatient and Outpatient Encounters for Heroin Poisoning /1000 Subscribers, Marketscan Data
Actual Predicted
9/2010
Heroin + Opioid Death Rates
78
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
2004.01 2005.01 2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01 2014.01
Dea
ths/
100,
000
Year.Month
Heroin + Opioid Deaths
79
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
2004.01 2005.01 2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01 2014.01
Dea
ths/
100,
000
Year.Month
Actual Predicted
4/2012
The results
• Reformulation of OxyContin brought about a shift to heroin
• The decline in deaths to opioids was compensated 1-for-1 with deaths from heroin
• Problem: Federal governments’ only solution to the opioid crisis SO FAR has been to encourage abuse-deterrent formulation
• Little likelihood of success as long as heroin and fantanyl is so prevalent
80
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Part 3: The Movement to Fentanyl
81
Fentanyl
• ~2013, heroin begins to be laced with fentanyl
• Fentanyl 50 x more potent than morphine– Prince died of a fentanyl OD
• Source– Legal diversion
– Created in clandestine labs
• Mixed w/ heroin
• Counterfeit opioid pills
82
Amount needed to OD, Heroin and Fentanyl
83
How is Fentanyl making it to the US?
• Order by mail from China– “The most common distribution medium is via the
U.S. Postal Service,” US Treasury
– FedEx/UPS subject to electroic tracking of foreign packages to identify source USPS is not
–Work in small independent networks
– 700 fentanyl-related sales listing on English language dark web sites
84
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How is Fentanyl making it to the US
• Mexican drug gangs– Produced in Mexico– $32,000 in raw ingredients can produce 1 million
pills w/a street value of $20 million– Brought in as a raw drug– Any mixing with other drugs is done at the retail and
not wholesale level– Sinaloa Jalisco cartels are the most likely sources– Few years ago, going wholesale price for
heroin/pound in Mexico was $600. Now $100
85
Tradeoffs
• Chinese mail-order– Lower volume, high purity (90%)
• Mexican gangs–Much higher volume, lower purity (<10%)
86
87
0
1
2
3
4
5
6
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Dea
th r
ate
Year
Fentanyl Death Rate, 1999-2017
Fentanyl alone
Fentanyl withheroin, or with heroinand opioids
Fentanyl withopioids
88
0
2
4
6
8
10
12
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Dea
th r
ate
Year
Fentayl Death Rates by State Heroin Death Rate in 2009
Highest 1/3
Middle 1/3
Lowest 1/3
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Restrictions
• 2018 – At G-20 dinner with Trump and Xi in Buenos Aires, Xi agreed to reclassify fentanyl controlled substance
• Makes these dark web sites in China subject to enforcement by state government
89
• Some success– Has decreased darkweb sellers
– Of USPS seized with fentanyl, most are now from US
• Some concerns– China may now be shipping precursors to Mexico
–Mexico produces the fentanyl
90