Download full-text PDF

Reframing the science and policy of nicotine, illegal drugs and alcohol – conclusions of the ALICE RAP Project

Article (PDF Available) inF1000 Research 6:289 · March 2017with256 Reads
DOI: 10.12688/f1000research.10860.1
Abstract
In 2013, illegal drug use was responsible for 1.8% of years of life lost in the European Union, alcohol was responsible for 8.2% and tobacco for 18.2%, imposing economic burdens in excess of 2.5% of GDP. No single European country has optimal governance structures for reducing the harm done by nicotine, illegal drugs and alcohol, and existing ones are poorly designed, fragmented, and sometimes cause harm. Reporting the main science and policy conclusions of a transdisciplinary five-year analysis of the place of addictions in Europe, researchers from 67 scientific institutions addressed these problems by reframing an understanding of addictions. A new paradigm needs to account for evolutionary evidence which suggests that humans are biologically predisposed to seek out drugs, and that, today, individuals face availability of high drug doses, consequently increasing the risk of harm. New definitions need to acknowledge that the defining element of addictive drugs is ‘heavy use over time’, a concept that could replace the diagnostic artefact captured by the clinical term ‘substance use disorder’, thus opening the door for new substances to be considered such as sugar. Tools of quantitative risk assessment that recognize drugs as toxins could be further deployed to assess regulatory approaches to reducing harm. Re-designed governance of drugs requires embedding policy within a comprehensive societal well-being frame that encompasses a range of domains of well-being, including quality of life, material living conditions and sustainability over time; such a frame adds arguments to the inappropriateness of policies that criminalize individuals for using drugs and that continue to categorize certain drugs as illegal. A health footprint, modelled on the carbon footprint, and using quantitative measures such as years of life lost due to death or disability, could serve as the accountability tool that apportions responsibility for who and what causes drug-related harm.
Open Peer Review
Discuss this article
(0)Comments
OPINIONARTICLE
Reframing the science and policy of nicotine, illegal drugs and
alcohol – conclusions of the ALICE RAP Project [version 1;
referees: awaiting peer review]
PeterAnderson , VirginiaBerridge , PatriciaConrod , RobertDudley ,
MatildaHellman , DirkLachenmeier , AnneLingford-Hughes , DavidMiller ,
JürgenRehm , RobinRoom , LauraSchmidt , RogerSullivan ,
TamykoYsa , AntoniGual20,21
InstituteofHealth&Society,NewcastleUniversity,NewcastleuponTyne,UK
FacultyofHealth,MedicineandLifeSciences,MaastrichtUniversity,Maastricht,Netherlands
InstituteforMentalHealthPolicyResearch,CentreforAddictionandMentalHealth(CAMH),Toronto,Ontario,Canada
CentreforHistoryinPublicHealth,LondonSchoolofHygieneandTropicalMedicine,UniversityofLondon,London,UK
DepartmentofPsychiatry,UniversitédeMontréal,Montreal,Quebec,Canada
DepartmentofIntegrativeBiology,UniversityofCalifornia,Berkeley,California,USA
CenterforResearchonAddiction,ControlandGovernance(CEACG),DepartmentofSocialResearch,UniversityofHelsinki,Helsinki,
Finland
SchoolofSocialSciencesandHumanities,UniversityofTampere,Tampere,Finland
InstituteforClinicalPsychologyandPsychotherapy,TUDresden,Dresden,Germany
ChemischesundVeterinäruntersuchungsamt(CVUA)Karlsruhe,Karlsruhe,Germany
CentreforPsychiatry,DivisionofBrainSciences,ImperialCollege,HammersmithHospital,London,UK
DepartmentofSocial&PolicySciences,UniversityofBath,Bath,UK
DallaLanaSchoolofPublicHealth,UniversityofToronto,Toronto,Ontario,Canada
DepartmentofPsychiatry,UniversityofToronto,Toronto,Ontario,Canada
CentreforSocialResearchonAlcoholandDrugs,StockholmUniversity,Stockholm,Sweden
CentreforAlcoholPolicyResearch,LaTrobeUniversity,Melbourne,Australia
InstituteforHealthPolicyStudiesandDepartmentofAnthropology,HistoryandSocialMedicine,SchoolofMedicine,Universityof
California,SanFrancisco(UCSF),SanFrancisco,California,USA
DepartmentofAnthropology,CaliforniaStateUniversity,Sacramento,Sacramento,California,USA
Esade-GovandDepartmentofStrategy,EsadeBusinessSchool,RamonLlullUniversity,Barcelona,Spain
AddictionsUnit,DepartmentofPsychiatry,ClínicInstituteofNeurosciences(ICN),HospitalClínic,Barcelona,Spain
Institutd'InvestigacionsBiomèdiquesAugustPiiSunyer(IDIBAPS),Barcelona,Spain
Abstract
In2013,illegaldrugusewasresponsiblefor1.8%ofyearsoflifelostinthe
EuropeanUnion,alcoholwasresponsiblefor8.2%andtobaccofor18.2%,
imposingeconomicburdensinexcessof2.5%ofGDP.NosingleEuropean
countryhasoptimalgovernancestructuresforreducingtheharmdoneby
nicotine,illegaldrugsandalcohol,andexistingonesarepoorlydesigned,
fragmented,andsometimescauseharm.Reportingthemainscienceand
policyconclusionsofatransdisciplinaryfive-yearanalysisoftheplaceof
addictionsinEurope,researchersfrom67scientificinstitutionsaddressed
theseproblemsbyreframinganunderstandingofaddictions.Anewparadigm
needstoaccountforevolutionaryevidencewhichsuggeststhathumansare
1-3 4 5 6
7,8 9,10 11 12
3,9,13,14 15,16 17 18
19 20,21
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Referee Status: AWAITING PEER
REVIEW
17Mar2017, :289(doi: )First published: 6 10.12688/f1000research.10860.1
17Mar2017, :289(doi: )Latest published: 6 10.12688/f1000research.10860.1
v1
Page 1 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
needstoaccountforevolutionaryevidencewhichsuggeststhathumansare
biologicallypredisposedtoseekoutdrugs,andthat,today,individualsface
availabilityofhighdrugdoses,consequentlyincreasingtheriskofharm.New
definitionsneedtoacknowledgethatthedefiningelementofaddictivedrugsis
‘heavyuseovertime’,aconceptthatcouldreplacethediagnosticartefact
capturedbytheclinicalterm‘substanceusedisorder’,thusopeningthedoorfor
newsubstancestobeconsideredsuchassugar.Toolsofquantitativerisk
assessmentthatrecognizedrugsastoxinscouldbefurtherdeployedtoassess
regulatoryapproachestoreducingharm.Re-designedgovernanceofdrugs
requiresembeddingpolicywithinacomprehensivesocietalwell-beingframe
thatencompassesarangeofdomainsofwell-being,includingqualityoflife,
materiallivingconditionsandsustainabilityovertime;suchaframeadds
argumentstotheinappropriatenessofpoliciesthatcriminalizeindividualsfor
usingdrugsandthatcontinuetocategorizecertaindrugsasillegal.Ahealth
footprint,modelledonthecarbonfootprint,andusingquantitativemeasures
suchasyearsoflifelostduetodeathordisability,couldserveasthe
accountabilitytoolthatapportionsresponsibilityforwhoandwhatcauses
drug-relatedharm.
PeterAnderson( )Corresponding author: peteranderson.mail@gmail.com
AndersonP,BerridgeV,ConrodP How to cite this article: et al. Reframing the science and policy of nicotine, illegal drugs and alcohol –
2017, :289(doi:conclusions of the ALICE RAP Project [version 1; referees: awaiting peer review] F1000Research 6
)10.12688/f1000research.10860.1
©2017AndersonP .Thisisanopenaccessarticledistributedunderthetermsofthe ,Copyright: et al CreativeCommonsAttributionLicence
whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkisproperlycited.Dataassociatedwiththe
articleareavailableunderthetermsofthe (CC01.0Publicdomaindedication).CreativeCommonsZero"Norightsreserved"datawaiver
TheresearchleadingtothebasisofthispaperhasreceivedfundingfromtheEuropeanCommission'sSeventhFrameworkGrant information:
Programme(FP7)2007-2013,underGrantAgreementnº266813-AddictionsandLifestyleinContemporaryEurope–ReframingAddictions
Project(ALICERAP–www.alicerap.eu).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: PAandAGcoordinatedtheALICERAPproject.VB,PC,MH,DWL,AL-H,DM,JR,RR,LS,andTYundertookvarious
aspectsofresearchfortheALICERAPproject.PAreportsreceiptoffeesforpublichealthcommenttoABInBev’sgoalstoreducetheharmfuluse
ofalcohol,outsidethesubmittedwork.PCreportshavingservedasatechnicaladvisortoABInBevGlobalHealthFoundation,outsidethe
submittedwork.AGreportsgrantsandpersonalfeesfromLundbeck,grantsandpersonalfeesfromD&APharma,personalfeesfromAbbVie,
outsidethesubmittedwork.AL-HreportsgrantsandpersonalfeesfromLundbeck,outsidethesubmittedwork.JRreportsgrants,personaland
otherfeesfromLundbeck,outsidethesubmittedwork.Allotherauthorsreportnoconflictsofinterest.Theviewsexpressedherereflectonlythe
authors’andtheEuropeanUnionisnotliableforanyusethatmaybemadeoftheinformationcontainedtherein.Nofundswereusedtoprepare
thepaper.
17Mar2017, :289(doi: )First published: 6 10.12688/f1000research.10860.1
Page 2 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
Introduction
A consortium of 67 scientific institutions from 24 European coun-
tries and beyond, covering over thirty scientific disciplines rang-
ing from anthropology to toxicology, responded to an invitation
by the European Commission to study the place of addictions in
contemporary European society. The resulting five-year endeavour,
the Addictions and Lifestyles in Contemporary Europe - Reframing
Addictions Project (ALICE RAP, www.alicerap.eu), went beyond
this. It reframed our understanding of addictions and formulated a
blueprint for re-designing the governance of addictions. This paper
summarizes the project’s conclusions, pointing to new understand-
ings of the science and policy of nicotine, illegal drugs and alcohol,
hereafter collectively referred to as ‘drugs’16. Although this paper
does not cover process addictions (e.g., gambling3), much of what
is said applies to addictions beyond drugs.
The paper starts by discussing why we need to re-think addictions.
It contrasts two powerful pieces of evidence: the harm done by
drugs, versus the poorly structured existing governance approaches
designed to manage such harm. The paper continues by consider-
ing three bases for re-thinking the addiction concept in ways that
could lead to improved strategies across different jurisdictions: rec-
ognition that there is a biological predisposition for people to seek
out and ingest drugs; that heavy use over time becomes a replace-
ment concept and descriptor for the term substance use disorder;
and that quantitative risk assessment can be used to standardize
harm across different drugs, based on drug potency and expo-
sure. The paper finishes by proposing two approaches that could
strengthen addictions governance: embedding governance within a
well-being frame, and adopting an accountability system—a health
footprint that apportions responsibility for who and what causes
drug-related harm.
Why do we need to re-think addictions?
The need to re-think addictions is exemplified by the extent of
harm caused by the drugs themselves, and by the fact that no single
country, at least in Europe, has fully overcome poorly managed and
fragmented governance structures.
Harm done by drugs
A standard way to document and describe the interference that
drugs have on human biology and functioning is to use years of
life lost to premature mortality (YLL) and disability adjusted life
years (DALYs). DALYs are a measure of health that sum up YLL
and years or life lost due to disability and detriments in functioning
(YLD). In 2013, illegal drug use was responsible for 1.8% of YLL
in the European Union (EU), alcohol was responsible for 8.2% and
tobacco for 18.2% (Table 1), imposing economic burdens in excess
of 2.5% of GDP7.
The data in Table 1 represents harm to the drug user. However, drug
use also harms the health of others. For instance, operating machin-
ery under the impact of illegal drugs can cause injury to others8,9.
Although decreasing globally, second-hand smoking was estimated
to kill more than 330 thousand people worldwide in 2013, and
caused about 7% of the burden of disease in DALYs attributable to
tobacco smoking10. The extent of harm to others caused by alcohol
consumption is estimated to be proportionally even larger, mainly
due to traffic accidents, violence, including homicide, and foetal
alcohol spectrum disorders11.
Dataset 1. Source data underlying the results presented in Table 1
http://dx.doi.org/10.5256/f1000research.10860.d154573
The data was based on the IHME Global burden of diseases,
injuries and risk factors study (http://www.healthdata.org/gbd).
Fragmented governance structures
Governance is defined as the processes and structures of public
policy decision making and management that engage people across
the boundaries of public agencies, levels of government, and public,
private and civic spheres to carry out a public purpose that cannot be
Table 1. Burden of disease caused by drug exposure in the European Union (EU) in 2013.
Source: own calculations based on IHME Global burden of diseases, injuries and risk factors study
(http://www.healthdata.org/gbd).
Risk factor Sex YLLs in
1,000
YLLs per
100,000
% of all
YLLs
DALYs
in 1,000
DALYs per
100,000
% of all
DALYs
Illegal drug use Men 1,069.8 428.5 2.5% 1,749.2 700.7 2.3%
Women 292.7 111.9 0.9% 580.5 222.0 0.8%
Total 1,362.5 266.6 1.8% 2,329.7 455.8 1.6%
Alcohol use Men 4,558.7 1,826.1 10.4% 5,981.4 2,396.0 7.9%
Women 1,584.0 605.8 5.1% 2,019.8 772.5 2.9%
Total 6,142.8 1,201.9 8.2% 8,001.2 1,565.5 5.5%
Tobacco use Men 10,036.4 4,020.3 23.0% 11,280.0 4,518.5 14.9%
Women 3,552.2 1,358.6 11.5% 4,405.0 1,684.7 6.4%
Total 13,588.6 2,658.6 18.2% 15,685.0 3,068.8 10.9%
YLL: Years of life lost due to premature mortality
DALYs: Disability adjusted life years
Source data available in Dataset 1102.
Page 3 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
accomplished by any one sector alone12. The involvement of mul-
tiple stakeholders in governance is not without risk. The exclusive
use of top-down bureaucratic approaches cannot maximize societal
benefits when dealing with ‘wicked problems’ that are highly resist-
ant to resolution13 (for definition of wicked problems, see ‘The New
Governance of Addictive Substances and Behaviours by Anderson
et al6). An analysis of 28 European countries found that no sin-
gle country had a comprehensive policy for all drugs (including
nicotine, illegal drugs and alcohol) within a broad societal well-
being approach. For more detail, see ‘Governance of Addictions:
European Public Policies’, by Albareda A et al1.
There are at least three reasons for ineffective and poorly inte-
grated governance. Firstly, the same harm done by drugs is defined
and understood in different ways in different countries and state
systems1416. Seen from a trans-national comparative perspective,
there is a lack of a common understanding of appropriate poli-
cies, and responses are often constrained by approaches that are
tied to assumptions that are not evidence-based4. Ways of thinking
about the harm done by drugs vary enormously, with considerable
heterogeneity between different drugs, and between international,
national and local levels of governance. For detail, see ‘Concepts
of Addictive Substances and Behaviours across Time and Place, by
Hellman et al4.
Secondly, a multitude of commercial, political and public stake-
holders are active in addictions governance on national and
international levels. In any given society, stakeholders that have
power, means and influence are likely to achieve an advantageous
influential position. The concepts of addiction are also shaped
by popular constructs promulgated by the mass media and cus-
toms in the general population. Stakeholder positions and percep-
tions of drug problems also vary over time and by area4, implying
that sustainable approaches must be interwoven into societal and
governance structures.
Thirdly, corporate power17, through multiple channels of influence,
can hinder evidence-based policy decisions5. Corporate strategies
often include attempts to influence civil society, science and the
media, as part of a wider aim to manage and, if possible, capture
institutions that set policy. Transparency is insufficient given that
the multiplicity of channels with corporate power is poorly
acknowledged and understood by policy makers. Therefore, the
rules in place to ensure level playing fields for discussions and
equitable decision-making across all factors are inadequate6.
Reframing addictions
The consensus reached under ALICE RAP was that there are at
least three ways to reframe addictions that could lead to improved
strategies across different jurisdictions. These include:
1) Recognition that humans have a biological predisposition for
seeking out and ingesting drugs;
2) Recognition that ‘heavy use over time’ should replace the con-
cept and term ‘substance use disorder’;
3) Recognition that a quantitative risk assessment accounting for
drug potency and drug exposure, can standardize measures of harm
across different drugs.
Evolutionary evidence for biological predisposition
The idea that human exposure to drugs did not occur until late in
human evolution—thus leaving our species inexperienced—is often
posited as one of the reasons that these substances cause so much
harm18. However, multidisciplinary scientific evidence suggests
otherwise. Many substances consumed today are not evolutionary
novelties18,19. In the story of terrestrial life over the last 400 mil-
lion years or so, one ongoing theme has been the “battle” between
plants and the animals that eat them. Of the many defence mecha-
nisms in existence, plants produce numerous chemicals, including
tetrahydrocannabinol, cocaine, nicotine, and opiates, all of which
are potent neurotoxins that deter consumption of plant tissue by
animals18. From an evolutionary perspective, we thus find natu-
ral selection for compounds that discourage consumption of the
plant via punishment of potential consumers. By contrast, there
has been no natural selection for expression of psychoactive
compounds which encourage consumption (i.e., via consumer
reward), which has also been predicted by neurobiological and
behavioural psychology theories of reward and reinforcement for
contemporary drugs20.
Counterbalancing the development of plant neurotoxins, plant-
eating animals have evolved to counter-exploit plants’ pro-
duction of drugs, for instance by exploiting the anti-parasitic
properties of some of them18. Many species of invertebrates and
vertebrates engage in pharmacophagy, the deliberate consumption
and sequestration of plant toxins, to dissuade parasites and preda-
tors. In a human context, present day examples of pharmacophagy
may be seen with Congo basin hunter gatherers, amongst whom the
quantity of cannabis21 and nicotine22 consumed is titrated against
intestinal worm burden - the higher the intake, the lower the worm
burden. In individuals treated with the anti-worm drug abendazole,
the number of nicotine-containing cigarettes smoked is reduced22.
Although parasite-host co-evolution is recognized as a potent selec-
tive force in nature, other, subtler evolutionary dynamics may affect
human and animal interactions with plant-based drugs, including
that they may buffer against nutritional and energetic constraints on
signalling in the central nervous system23. Ethnographic research
reveals that many indigenous groups classify “drugs” as food,
rather than psychoactive entities, and that they are perceived as
having food-like effects, most notably for increasing tolerance
for fatigue, hunger and thermal stress in nutritionally-constrained
environments23. The causes of these perceived effects have not
been a research question, but there are clues that the “food” clas-
sification may be literal rather than allegorical. Common plant
toxins not only mimic mammalian neurotransmitters, they are also
synthesized from the same nutritionally-constrained amino acid
precursors, such as tyrosine and tryptophan. In harsh environ-
ments, toxic plants could function as a “famine food” providing
essential dietary building blocks, or, may function as a direct
substitute for nutritionally-constrained endogenous neurotrans-
mitters. There is some evidence to support this hypothesis in
animal research; for example, wood rats in cold environments
reduce thermoregulatory costs by modulating body temperature
with plant toxins consumed from the juniper plant24.
In the case of ethanol, its presence within ripe fruit suggests
low-level but chronic dietary exposure for all fruit-eating animals,
Page 4 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
with volatilized alcohols potentially serving in olfactory localiza-
tion of nutritional resources (i.e., animals can use the smell of alco-
hol to locate food over long distances)19. Molecular evolutionary
studies indicate that an oral digestive enzyme capable of rapidly
metabolizing ethanol was modified in human ancestors near the
time that they began extensively using the forest floor, about 10
million years ago25; humans have retained the fast-acting enzyme to
this day. By contrast, the same alcohol dehydrogenase in our more
ancient and mostly tree-dwelling ancestors did not oxidize etha-
nol as efficiently. This evolutionary switch suggests that exposure
to dietary sources of ethanol became more common as hominids
adapted to bipedal life on the ground. Ripe fruits accumulating on
the forest floor could provide substantially more ethanol cues and
result in greater caloric gain relative to fruits ripening within the
forest canopy, and our contemporary patterns of alcohol consump-
tion and excessive use may accordingly reflect millions of years of
natural dietary exposure19.
This evolutionary evidence does not imply that humans also evolved
to specifically consume nicotine, for example, or that nicotine use is
beneficial in the modern world. What is novel in the modern world
is the high degree of availability, and high concentration of psy-
choactive agents and routes of consumption that promote intoxica-
tion. What is different with alcohol in the modern world is novel
availability through fermentative technology, enabling humans to
consume it as a beverage, devoid of food bulk, with higher ethanol
content, and artificially higher salience than that which character-
izes fruit fermenting in the wild. The evolutionary evidence has two
implications: firstly, policies that prohibit the use of drugs are likely
to fail because people have a biological predisposition to seek out
chemicals with varying nutritional and pharmacological properties;
and secondly, in present-day society, drug delivery systems have
been developed that are beyond what is reflected in the natural envi-
ronment, particularly with respect to levels of potency, availability
and taste, which could be argued as being the more central driv-
ers of harm. Potency is largely determined by producer organisa-
tions operating in markets, which, from the perspective of overall
societal well-being, are inadequately managed26. Better regulation
of potency can become a major opportunity for additional policy
interventions - for example with alcohol, see ‘Evidence of reducing
ethanol content in beverages to reduce harmful use of alcohol’ by
Rehm et al.27.
Heavy use over time
To better understand the interference of drugs in human biology
and functioning, the consensus reached in ALICE RAP was that the
concept and term ‘heavy use over time’ should be proposed as the
replacement for ‘substance use disorder’. In medical settings and
indeed often in academic and lay settings, heavy users of drugs are
commonly dichotomized into those with a ‘substance use disorder’
or not. ‘Substance use disorder’ is a clinical construct that is often
used as a shorthand to identify individuals who might benefit from
advice or treatment. But as a condition in itself, it is a medical arte-
fact which occurs in all grades of severity, with no natural distinc-
tion between ‘health’ and ‘disease’28,29.
This is illustrated with alcohol. The associated chronic organ dam-
age (e.g., liver cirrhosis, cancers) exponentially increases in risk as
alcohol consumption accumulates over time30,31. Unmanaged heavy
drinking is associated with subsequent heavy drinking, often culmi-
nating in brain damage32, itself a consequence of heavy drinking33,34
but also a driver of future behaviour.
Alcohol consumption itself is close to log-normally distributed in
drinking populations, skewed towards heavy drinking35. There is
no natural cut-off point above which “alcohol use disorder” defini-
tively exists and below which it does not. “Alcohol use disorder” is
clinically defined as a score on a checklist of symptoms, and there
is a smooth line exponential relationship between levels of alco-
hol consumption and the score on the checklist29,36. Heavy drink-
ing is a cause of the items on the checklist, including compulsion
to drink more, which can also be a consequence of brain damage,
itself caused by heavy drinking. Thus, “alcohol use disorder” is a
diagnostic artefact. No more is needed to consider what is called
“alcohol use disorder” other than heavy use over time28,29.
For alcohol (and other drugs as well), this approach does not imply
that heavy use over time is the only cause of harm. There are other
factors involved that that drive heavy alcohol use and harm3 that
are independent of, or in interaction with, molecular and cellular
levels (e.g., alcohol dehydrogenase polymorphisms37), individual
levels (e.g., income38 and personality39) and environmental levels
(e.g., stigma)
There is an ongoing discussion as to whether or not sugar is an
‘addictive’ substance that should be captured in the same category
as drugs26. Framing the problem as one of heavy use over time
provides insight into this debate. As with alcohol and high blood
pressure40, chronic disease risk associated with plasma glu-
cose levels has a continuous exponential relationship with sugar
consumption41. The distribution of blood glucose levels is close
to log-normally distributed in populations and skewed towards
high consumption levels42. There is no natural cut-off point above
which diabetes (or any other disease manifestation) linked to sugar
definitively exists and below which it does not. Similar to the alco-
hol model where heavy use of alcohol over time leads to further
heavy use of alcohol from the resulting brain damage, heavy use of
sugar over time damages hippocampal function43, which leads to
further heavy use of sugar over time44. Thus, in the ‘heavy use over
time’ frame, sugar can be placed in the same category as alcohol
and other drugs, and managed with similar governance approaches
that promote public health.
Quantitative risk assessment
A core way to document the interference of drugs in human biol-
ogy and functioning is to use quantitative risk assessment (QRA).
QRA is a method applied in regulatory toxicology, for example, to
evaluate water contaminants, and before safety approvals for food
additives or pesticides. QRA has not been widely applied to drugs.
Previous approaches for ranking harm have mostly been based on
expert judgements45,46 which have been criticized as being arbitrary
and biased47.
The advantage of QRA is that it provides a formal scientific method
to rank the harm-potential of drugs, making optimum use of avail-
able data48. There are several approaches for QRA available, with
Page 5 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
Margin of Exposure (MOE) suggested by WHO49 as being most
suitable for prioritizing risk management. In the alcohol field, MOE
has been applied to evaluate the liver cirrhosis risk of ethanol, which
is the single most important chronic disease condition attributable
to alcohol globally50. MOE results have replicated those behind
existing guidelines for low-risk drinking51. In a detailed study of the
components in alcoholic beverages, ethanol was confirmed as the
compound with highest risk52. In a detailed comparison between
ethanol and non-metabolically produced acetaldehyde contained
in beverages, it was also judged that the risk of ethanol comprises
more than 99% of the total risk53. It can be concluded that the risk
of alcoholic beverages can be evaluated by looking at the effects
of ethanol alone. The situation is less clear for tobacco, for which
some industry MOE studies find toxicants other than nicotine54,55.
An MOE analysis of electronic cigarette liquids indicated that nico-
tine is the compound posing the highest risk56.
MOEs are calculated as the ratio of a toxic dose of the drug (usu-
ally the benchmark dose BMDL10, the lowest dose which is 95%
certain to cause no more than a 10% negative outcome incidence)
with the dose consumed either individually or on a population
scale47. The higher the MOE, the lower the level of risk, with low
risk not implying safety. An MOE of 100 means that the drug is
being consumed at one hundredth of the benchmark dose; an MOE
of 1 means that the drug is being consumed at this toxic dose. The
MOE for drugs can be calculated taking into account a range of
hazard outcomes in health and other well-being domains, as long as
suitable dose-response data are available (which is not the case for
most drugs and many well-being indicators). Therefore, analyses
to date are primarily restricted to lethal outcomes based on animal
studies. Results for European adults are summarized in Figure 1.
The low MOE for alcohol (and thus high risk) is due to the high
levels of consumption by European adults. The MOE results are
consistent with the consensus of expert rankings in which cannabis
is ranked with lower risk and alcohol with higher risk than current
policies assume45,46. The MOE is inherent to the drug itself; it does
not account for the harms that arise from drug delivery systems,
for example, smoked tobacco, or from secondary effects such as
unclean syringes used for heroin intake.
Of course, MOE, as presented here, focuses on the physical body
of the adult user as the locus of harm. It does not take into account
the sex and age of the user, or harm to individuals other than the
user or at collective levels, which are a primary source of social dif-
ferentiation between drugs. It also focuses on mortality, rather than
intoxication in the moment. Differences between the intoxicating
power of substances in the moment, and in the behavioural con-
sequences of taking them, are primary reasons why, for example,
societies have treated alcohol differently to tobacco. Nevertheless,
we believe that MOE should be applied at the current stage even
when the underlying toxicological data are incomplete, to provide
a better alignment of prioritization of policy to the drugs associated
with higher risks, which in this case are nicotine, cocaine, heroin
and alcohol.
Towards better governance
We have described three harmonizing approaches to reframe our
understanding of addictions: biological predisposition to seek out
psychoactive substances; heavy use over time as a fruitful charac-
terisation; and quantitative risk assessment. Here, we propose two
Figure 1. Margin of exposure for daily drug use estimated using probabilistic analysis. Source: Lachenmeier & Rehm (2015)47.
Page 6 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
Figure 2. Well-being framework, reproduced with permission from the OECD Better Life Index initiative. Source: OECD. (2011), How’s
Life?: Measuring Well-being, OECD Publishing, Paris. DOI: http://dx.doi.org/10.1787/9789264121164-en57.
underlying pillars for a re-design of the governance of drug con-
trols: embedding drugs governance within a comprehensive model
of societal well-being; and creating a health footprint which, mod-
elled on the carbon footprint, promotes accountability by identify-
ing who causes what harm to whom from drugs.
Societal well-being
We propose that societal well-being should be our overarching
frame for a more integrated governance and monitoring of drug
control policies. Societal well-being, as captured by OECD57,
includes quality of life (health, education and skills, social connec-
tions, civic engagement, and personal security), material conditions
(income, employment and housing) and sustainability over time
(see Figure 2). Gross domestic product (GDP) is included as a sep-
arate domain, recognizing that, while economic well-being is an
important component of societal well-being, GDP has significant
limitations. GDP excludes, for example, non-market household
activity such as parenting, and activities such as conservation of
natural resources. GDP also includes activities which do not con-
tribute to well-being, such as pollution and crime, termed regret-
tables that are depicted within GDP but outside well-being. The use
of and harm done by drugs are affected by and affect all well-being
dimensions58.
Well-being analyses have found that, whilst some illegal drug poli-
cies may reduce health harms, they often come with adverse side
effects including criminalization, social stigma and social exclusion,
all of which exacerbate health harms59. Humans are hard-wired to be
social animals60, with social networks strongly influencing tobacco
use61 and alcohol intake62. Punitive drug policies bring about the
opposite: social exclusion due to stigma and social isolation6365.
Engagement with illegal drugs conveys especially strong social
meanings and can lead to stigma of marginalized heavy users, as
opposed to the supposedly more responsible mainstream users66.
This can lead to punitive societal responses. Meanwhile, exclusion
from the mainstream may allow harms to continue unchecked. If a
user is caught using drugs in a country with “zero tolerance” to ille-
gal drugs, the ensuing criminal sanctions will impede civic engage-
ment and any improvements in quality of life and material living
conditions. For more detail, see ‘Well-being as a frame for under-
standing addictive substances’ by Stoll & Anderson58. Changes in
life expectancy in Mexico illustrate the negative consequences of
criminalization67. After six decades of gains in life expectancy in
Mexico, the trend stagnated after 2000 for both men and women,
and for men was reversed after 200568. This was largely due to an
unprecedented rise in homicide rates, mostly as a result of drug
policies promoting ‘gang wars’ and conflicts between gangs, the
police and army69.
A well-being frame calls for whole-of-society approaches that pro-
gressively legalize illegal drugs to reduce violence and personal
insecurity, while focusing on substances as drivers of harm6,70. It
balances the complex factors impacting drug use and related harm
through the continuous monitoring of policy effects in a proactive
way, with regulations embedded in international coordination. It
calls for whole-of-society approaches that avoid criminalization
Page 7 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
where possible and where costs of addressing the problem are
equally distributed across society. Governance strategies manage
nicotine, illegal drugs and alcohol as a whole to avoid overlaps,
contradictions, gaps and inequalities1. The concern should be
focused on harms, both to the user and to others, including family
and friends, communities and society as a whole. The structures
to support the strategies should be coordinated and multi-sectoral,
involving high-level coordination of health, social welfare, and jus-
tice agencies in the context of international treaties, and, impor-
tantly, equitable across the lifespan, between genders and cultural
groups. To increase the pace of policy change, regional and local
public policies can create policy communities and networks within
a common international framework.
Managing ‘wicked problems’ requires clear rules of private sector
engagement in policy making, particularly when private interests
go against societal well-being6. An evolved governance system
must include measures to avoid industry co-optation, through trans-
parency, checks and balances. Private sector stakeholders should
operate within established rules.
Accountability
The ongoing monitoring of outcomes within a well-being framework
would promote accountability. Modelled on the carbon footprint, we
propose a health footprint as the accountability tool. Footprints were
developed in the ecological field as a measure of human demand on
ecosystems71, including water footprints72 and carbon footprints that
apportion greenhouse gas emissions to certain activities, products
and populations73. The central reason for estimating a carbon foot-
print is to help reduce the risk of climate change through enabling
targeted and effective reductions in greenhouse gas emissions74.
The health footprint can be considered a measure of the total
amount of risk factor attributable disability adjusted life years
(DALYs)75 of a defined population, sector or action within a spatial
(e.g., jurisdiction) or temporal boundary (e.g. one year). It can be
calculated using standard risk factor-related YLL and DALY meth-
odologies of the Global Burden of Disease Study10 and of the World
Health Organization75. Health footprints are a starting point. To
be accountable, we ultimately need to understand what drives the
health footprint (Figure 3).
Structural drivers
Above the health footprint of Figure 3 are the structural driv-
ers of harm that directly influence the size of the health footprint.
Biological attributes and functions include, for example, the bio-
logical pre-disposition to seek out and use drugs. Genetic vari-
ants, for example, could be those that affect the function of alcohol
dehydrogenase, influencing consumption levels and harm8,76.
Changes in global population size and structure can increase
absolute numbers of drug-related DALYs, even though rates per
person can decrease over the same time7. As sociodemographic
status improves in lower income countries, so do drug-related
DALYs10; yet, for the same amount of drug use, people with lower
incomes suffer more drug-related DALYs than people with higher
incomes77.
Figure 3. Drivers of harm done by drugs and addictive behaviour.
Page 8 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
Circumstantial drivers
Above the structural drivers are the circumstantial drivers, those
that can change. Related to drug potency and exposure, an MOE
target for all drugs no greater than 10 has been argued6. Policies
could achieve such a result by either reducing drug exposure or
by reducing the potency of the drug. Technological developments
have led to electronic nicotine delivery systems (widely known as
e-cigarettes) as widespread alternatives to smoked tobacco, with
current best estimates showing e-cigarettes to be considerably less
harmful to health than smoked cigarettes7880. It may be that once
e-cigarettes are heavily produced and marketed by the tobacco
industry, that society will see cigarette-like levels of sustained
heavy use of nicotine. However, e-cigarette’s harm quotient
should stay low, provided they are properly regulated in terms
of their components, including nicotine. Social influences and
attitudes drive harm through stigma, social exclusion and social
marginalization; these are often side-effects of drug policies, which
can bring more harm than drug use itself81,82.
Policies and measures
Policies that reduce exposure to drugs are essentially those that
limit availability by increasing the price and reducing physical
availability59,83,84. The absence of such evidence-based policies is
an important driver of harm. Limits to availability bring a range of
co-benefits to educational achievement and productivity, for exam-
ple, but they can also bring adverse effects – for example, the well-
documented violence, corruption and loss of public income
associated with some existing ‘illegal’ drug policies58,85. Individual
choices and behaviour that drive harm from drug use are determined
by the environment in which those choices and behaviours operate86.
Banning commercial communications, increasing price and
reducing availability are all incentives that impact individual behav-
iour. Research and development can be promoted to reduce the
potency of existing drugs87 and their drug delivery packages27,56,78.
Unfortunately, there remain enormous gaps between the supply
and demand of evidence-based prevention, advice and treatment
programmes8892. Called for by United Nations Sustainable Devel-
opment Goal 3.593, their supply can bring many co-benefits to soci-
ety, including reduced social costs and increased productivity94. The
harm driven by the gaps is due in large part to insufficient resources
and insufficient implementation of effective evidence-based pre-
vention and treatment programmes95. Currently these programmes
represents less than 1% of all costs incurred to society by drugs96.
Similar to medicines agencies (such as the European Medicines
Agency) that assess and approve drugs, prevention agencies could
be created95. Compounding the gap between supply and demand is
the fact that often, considerable marginalization and stigmatization
happens in the path to treatment, and this is then further exacer-
bated by the treatment itself82. The use of pharmacotherapy as an
adjunct may be further limited due to ideological stances, poorly
implemented guidelines, lack of appropriate medication, and even a
perceived lack of effect, if the drug is available97.
The private sector is a core driver of harm, through commercial
communications which include all actions undertaken by produc-
ers of drugs to persuade consumers to buy and consume more98.
There are international models encouraging better control of
commercial communications in the public health interest, the most
notable being the Framework Convention on Tobacco Control83. In
addition to commercial communications, the private sector drives
harm through shaping drug policies, leading to more drug-related
deaths5. Governance structures thus need to have the capability and
expertise to supervise industry movements that shape drug-related
legislation and regulations, including regulating and restricting
political lobbying. One of the difficulties here is that politically
driven change in difficult areas, such as drug policies, is highly
dependent on collective decisions99 and influenced by what has
been termed specular interaction100, in which a politician’s actions
may be less determined by their own conviction, and more by their
evaluation of beliefs of their rivals and friends.
The health footprint is the accountability system for who and what
causes drug-related harm. Jurisdictional entities can be ranked
according to their overall health footprint, in order to identify the
countries that contribute most to drug attributable ill-health and pre-
mature death, and where the most health gain could be achieved
at country level. Jurisdictional footprints could include ‘policy
attributable health footprints’ which estimate the health footprint
between current policy and ideal health policy. This would address
the question: ‘what would be the improvement in the health foot-
print compared to present policies, were the country to implement
strengthened or new policies?’ Conversely, the health footprint can
provide accountability for when such evidence-based policy is not
implemented correctly.
A range of sectors are involved in nicotine and alcohol related risk
factors. These include producer and retail organizations such as
large supermarket chains, and service provider companies such as
advertising and marketing industries. There is considerable overlap
between sectors, and estimates will need to determine appropri-
ate boundaries for health footprint calculations. Companies could
report their health footprints and choose to commit to reducing them
by a specified amount over a five to ten-year time frame. Direct
examples of producer action could include switching from higher to
lower alcohol concentration products27, and switching from smoked
tobacco cigarettes to e-cigarettes80.
Conclusions
The points stated above underscore the need to redesign the gov-
ernance of drugs; in Europe, and globally. Margins of exposure
estimates for four drugs (nicotine, cocaine, heroin and alcohol) are
exceedingly high and thus call for determined action. Drugs are
responsible for a high proportion of years of life lost in the Euro-
pean Union; tobacco accounted for 18.2% of life years lost, illegal
drugs for 1.8%, and alcohol for 8.2% in 2013. There are many side
effects of existing policies, such as stigma, social exclusion, lack of
personal security, civil unrest and homicide58.
Under the auspices of ALICE RAP, a large, multidisciplinary
team of addiction scientists put forward a range of arguments for
moving progressively towards regulated legalization of certain
illegal drugs, proposing a well-being frame that calls for whole-
of-society approaches and continuously monitors and accounts
for adverse side effects of drug policy. Humans have a biological
pre-disposition to seek out a range of drugs, so prohibitionist
Page 9 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
policies are likely to run into difficulty - and they have. Legaliza-
tion does not imply that drug governance is left to market forces
alone - the experience of nicotine and alcohol demonstrates that this
is not possible. Instead, drug governance requires comprehensive
regulation, with adequate and transparent rules of the game for
stakeholder involvement, and appropriate international regulatory
frameworks. With a health footprint, it can be documented who
causes what harm from nicotine, illegal drugs and alcohol in the
public and private sectors. Public bodies and private companies
should be required to publish their health footprints on an annual
basis, and indicate their plans for reducing the health footprint.
The consensus that ALICE RAP reached will not come without
push-back. Without input from evolutionary theory, neurobiol-
ogy will continue to maintain that human drug use is initiated
and sustained by reward and reinforcement at both biological and
behavioural levels, compounded by mistaken views that the human
encounter with drugs is a relatively new evolutionary experience,
and human vulnerability to drugs in moral, behavioural, and bio-
logical dimensions. Disease classification systems are based not
only on measurement, but on qualification, and thus payment, for
treatment. The concept heavy use over time does not prevent the use
of qualification definitions for treatments. Threshold consumption
levels determining treatment can be defined as levels above which
advice and treatment have been shown to reduce the development
or progression of end-organ damage. Extending margin of exposure
analyses for a range of outcomes beyond mortality will overcome
concern of one metric for drug policy - its strength is that it allows
standard comparison across drugs and indicates options for chang-
ing both dose and exposure.
Whilst measuring societal well-being as a whole has gained
support, the implications for drug policy that favour regulated
legalization will meet resistance from those who favour prohibi-
tion, particularly as prohibition is based more on a moral than an
evidence-based standpoint, as has been the case with alcohol101.
The footprint implies responsibility, which is often difficult for
both public and private sectors to accept, in particular for producer
companies whose vested interests might be challenged.
What we propose in this paper are large adjustments to our under-
standing of addictions and to what needs to be done to effectively
reduce the widespread harms done by drugs. We hope that what
we have written might start a process for better drug policy for the
good of the public.
Data availability
Dataset 1: Source data underlying the results presented in Table 1.
The data was based on the IHME Global burden of diseases,
injuries and risk factors study (http://www.healthdata.org/gbd).
DOI, 10.5256/f1000research.10860.d154573102
Author contributions
PA, VB, PC, RD, MH, DWL, AL-H, DM, JR, RR, LS, RS, TY
and AG drafted sections of the text and read the final manuscript,
for which consensus was agreed. PA coordinated the drafting and
edited the text.
Competing interests
PA and AG coordinated the ALICE RAP project. VB, PC, MH,
DWL, AL-H, DM, JR, RR, LS, and TY undertook various aspects
of research for the ALICE RAP project. PA reports receipt of fees
for public health comment to AB InBev’s goals to reduce the harm-
ful use of alcohol, outside the submitted work. PC reports having
served as a technical advisor to ABInBev Global Health Founda-
tion, outside the submitted work. AG reports grants and personal
fees from Lundbeck, grants and personal fees from D&A Pharma,
personal fees from AbbVie, outside the submitted work. AL-H
reports grants and personal fees from Lundbeck, outside the
submitted work. JR reports grants, personal and other fees from
Lundbeck, outside the submitted work. All other authors report
no conflicts of interest. The views expressed here reflect only the
authors’ and the European Union is not liable for any use that may
be made of the information contained therein. No funds were used
to prepare the paper.
Grant information
The research leading to the basis of this paper has received
funding from the European Commission’s Seventh Framework
Programme (FP7) 2007–2013, under Grant Agreement nº 266813
- Addictions and Lifestyle in Contemporary Europe Reframing
Addictions Project (ALICE RAP – www.alicerap.eu).
The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.
References
1. Ysa T, Colom J, Albareda A, et al.: Governance of Addictions: European Public
Policies. Oxford: Oxford University Press, 2014.
Reference Source
2. Anderson P, Rehm J, Room R: The Impact of Addictive Substances and
Behaviours on Individual and Societal Well-Being. Oxford, Oxford University
Press, 2015.
Reference Source
3. Gell L, Bühringer G, McLeod J, et al.: What Determines Harm from Addictive
Substances and Behaviours? Oxford: Oxford University Press, 2016.
Reference Source
4. Hellman M, Berridge V, Duke K, et al.: Concepts of Addictive Substances and
Behaviours across Time and Place. Oxford: Oxford University Press, 2016.
Reference Source
5. Miller D, Harkins C, Schlögl M, et al.: Impact of Market Forces on Addictive
Page 10 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
Substances and Behaviours: The web of influence of addictive industries.
Oxford: Oxford University Press, in press. 2017.
Reference Source
6. Anderson P, Braddick F, Conrod PJ, et al.: The New Governance of Addictive
Substances and Behaviours. Oxford: Oxford University Press, in press. 2017.
Reference Source
7. Shield KD, Rehm J: The effects of addictive substances and addictive
behaviours on physical and mental health. In Eds. Anderson P, Rehm J, & Room
R. The Impact of Addictive Substances and Behaviours on Individual and Societal
Well-Being. Oxford, Oxford University Press, 2015.
Publisher Full Text
8. World Health Organization: Global status report on traffic safety 2015. Geneva:
World Health Organization, 2015.
Reference Source
9. Degenhardt L, Hall W: Extent of illicit drug use and dependence, and their
contribution to the global burden of disease. Lancet. 2012; 379(9810): 55–70.
Publisher Full Text
10. GBD 2013 DALYs and HALE Collaborators: Global, regional and national
disability-adjusted life years (DALYs) for 306 diseases and injuries and
healthy life expectancy (HALE) for 188 countries, 1990–2013: quantifying the
epidemiological transition. Lancet. 2015; 386(1009): 2145–2191.
Publisher Full Text
11. Gell L, Ally A, Buykx P, et al.: Alcohol’s harm to others. Accessed 1 August 2016;
2015.
Reference Source
12. Emerson K, Nabatchi T, Balogh S: An integrative framework for collaborative
governance. J Public Adm Res Theory. 2012; 22(1): 1−29.
Publisher Full Text
13. Roberts N: Wicked problems and network approaches to resolution. Int Public
Manage Rev. 2000; 1(1): 1–19.
Reference Source
14. Hellman M, Room R: What’s the story on addiction? Popular myths in the USA
and Finland. Critical Public Health. 2015; 25(5): 582–598.
Publisher Full Text
15. Hellman M, Majamäki M, Rolando S, et al.: What causes addiction problems?
Environmental, biological and constitutional explanations in press portrayals
from four European welfare societies. Subst Use Misuse. 2015; 50(4): 419–438.
PubMed Abstract
|
Publisher Full Text
16. Egerer M, Hellman M, Rolando S, et al.: General practitioners’ position on
problematic gambling in three European welfare states. In: Hellman M, Berridge
V, Duke K, Mold A. Concepts of Addictive Substances and Behaviours across Time
and Place. 7Oxford University Press, 2016; 169–192.
Publisher Full Text
17. Solana J, Saz-Carranza A: The Global Context: How Politics, Investment, and
Institutions Impact European Businesses. Barcelona: ESADE, 2016; Accessed
1 October 2016.
Reference Source
18. Sullivan RJ, Hagen EH: Passive vulnerability or active agency? An
evolutionarily ecological perspective of human drug use. In Anderson P,
Rehm J, & Room R, (Eds), The Impact of Addictive Substances and Behaviours
on Individual and Societal Well-Being. Oxford, Oxford University Press, 2015.
Publisher Full Text
19. Dudley R: The Drunken Monkey: Why We Drink and Abuse Alcohol. Berkeley:
University of California Press, 2014.
Reference Source
20. Sullivan RJ, Hagen EH, Hammerstein P: Revealing the paradox of drug reward in
human evolution. Proc Biol Sci. 2008; 275(1640): 1231–1241.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
21. Roulette CJ, Kazanji M, Breurec S, et al.: High prevalence of cannabis use
among Aka foragers of the Congo Basin and its possible relationship to
helminthiasis. Am J Hum Biol. 2016; 28(1): 5–15.
PubMed Abstract
|
Publisher Full Text
22. Roulette CJ, Mann H, Kemp B, et al.: Tobacco use vs. helminths in Congo basin
hunter-gatherers: self-medication in humans? Evol Hum Behav. 2014; 35(5):
397–407.
Publisher Full Text
23. Sullivan RJ, Hagen EH: Psychotropic substance-seeking: evolutionary
pathology or adaptation? Addiction. 2002; 97(4): 389–400.
PubMed Abstract
|
Publisher Full Text
24. Forbey JS, Harvey A, Huffman MA, et al.: Exploitation of secondary metabolites
by animals: A response to homeostatic challenges. Integr Comp Biol. 2009;
49(3): 314–328.
PubMed Abstract
|
Publisher Full Text
25. Carrigan MA, Uryasev O, Frye CB, et al.: Hominids adapted to metabolize
ethanol long before human-directed fermentation. Proc Natl Acad Sci U S A.
2015; 112(2): 458–463.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
26. Schmidt LA: What are addictive substances and behaviours and how far
do they extend? In: Anderson P, Rehm J, Room R, eds. Impact of addictive
substances and behaviours on individual and societal well-being. Oxford University
Press, 2015.
Publisher Full Text
27. Rehm J, Lachenmeier DW, Jané Llopis E, et al.: Evidence of reducing ethanol
content in beverages to reduce harmful use of alcohol. Lancet Gastroenterol
Hepatol. 2016; 1(1): 78–83.
Publisher Full Text
28. Rehm J, Marmet S, Anderson P, et al.: Defining substance use disorders: do
we really need more than heavy use? Alcohol Alcohol. 2013; 48(6): 633–640.
PubMed Abstract
|
Publisher Full Text
29. Rehm J, Anderson P, Gual A, et al.: The tangible common denominator of
substance use disorders: a reply to commentaries to Rehm et al. (2013a).
Alcohol Alcohol. 2014; 49(1): 118–122.
PubMed Abstract
|
Publisher Full Text
30. Shield KD, Parry C, Rehm J: Chronic diseases and conditions related to alcohol
use. Alcohol Res. 2013; 35(2): 155–173.
PubMed Abstract
|
Free Full Text
31. Rehm J, Roerecke M: Reduction of drinking in problem drinkers and all-cause
mortality. Alcohol Alcohol. 2013; 48(4): 509–513.
PubMed Abstract
|
Publisher Full Text
32. Rando K, Hong KI, Bhagwagar Z, et al.: Association of frontal and posterior
cortical gray matter volume with time to alcohol relapse: a prospective study.
Am J Psychiatry. 2011; 168(2): 183–192.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
33. Paul CA, Au R, Fredman L, et al.: Association of alcohol consumption with
brain volume in the Framingham Study. Arch Neurol. 2008; 65(10): 1363–1367.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
34. Ding J, Eigenbrodt ML, Moslet TH Jr, et al.: Alcohol intake and cerebral
abnormalities on magnetic resonance imaging in a community-based
population of middle-aged adults: the Atherosclerosis Risk in Communities
(ARIC) study. Stroke. 2004; 35(1): 16–21.
PubMed Abstract
|
Publisher Full Text
35. Kehoe T, Gmel G, Shield KD, et al.: Determining the best population-level
alcohol consumption model and its impact on estimates of alcohol-
attributable harms. Popul Health Metr. 2012; 10(1): 6.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
36. Rubinsky AD, Dawson DA, Williams EC, et al.: AUDIT-C Scores as a scaled
marker of mean daily drinking, alcohol use disorder severity, and probability
of alcohol dependence in a U.S. general population sample of drinkers. Alcohol
Clin Exp Res. 2013; 37(8): 1380–1390.
PubMed Abstract
|
Publisher Full Text
37. Peng Y, Shi H, Qi XB, et al.: The ADH1B Arg47His polymorphism in east Asian
populations and expansion of rice domestication in history. BMC Evol Biol.
2010; 10: 15.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
38. Hosseinpoor AR, Parker LA, Tursan d'Espaignet E, et al.: Socioeconomic
inequality in smoking in low-income and middle-income countries: results
from the World Health Survey. PLoS One. 2012; 7(8): e42843.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
39. Conrod PJ, Nikolaou K: Annual Research Review: On the developmental
neuropsychology of substance use disorders. J Child Psychol Psychiatry. 2016;
57(3): 371–94.
PubMed Abstract
|
Publisher Full Text
40. National Heart, Lung and Blood Institute: The Seventh Report of the Joint
National Committee on Prevention, Detection, Evaluation, and Treatment of
High Blood Pressure (JNC 7). 2004; Accessed 1 August 2016.
Reference Source
41. Vistisen D, Colagiuri S, Borch-Johnsen K, et al.: Bimodal distribution of glucose
is not universally useful for diagnosing diabetes. Diabetes Care. 2009; 32(3):
397–403.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
42. The Emerging Risk factors Collaboration, Sarwar N, Gao P, et al.: Diabetes
mellitus, fasting blood glucose concentration, and risk of vascular disease:
a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;
375(9733): 2215–22.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
43. Jacka FN, Cherbuin N, Anstey KJ, et al.: Western diet is associated with a
smaller hippocampus: a longitudinal investigation. BMC Med. 2015; 13: 215.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
44. Hargrave SL, Jones S, Davidson TL: The Outward Spiral: A vicious cycle model
of obesity and cognitive dysfunction. Curr Opin Behav Sci. 2016; 9: 40–46.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
45. Nutt D, King LA, Saulsbury W, et al.: Development of a rational scale to assess
the harm of drugs of potential misuse. Lancet. 2007; 369(9566): 1047–1053.
PubMed Abstract
|
Publisher Full Text
46. van Amsterdam J, Opperhuizen A, Koeter M, et al.: Ranking the harm of alcohol,
tobacco and illicit drugs for the individual and the population. Eur Addict Res.
2010; 16(4): 202–207.
PubMed Abstract
|
Publisher Full Text
47. Lachenmeier DW, Rehm J: Comparative risk assessment of alcohol, tobacco,
cannabis and other illicit drugs using the margin of exposure approach. Sci
Rep. 2015; 5: 8126.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
48. Hertz-Picciotto I: Epidemiology and quantitative risk assessment: a bridge from
science to policy. Am J Public Health. 1995; 85(4): 484–491.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
49. WHO IPCS: Environmental Health Criteria 239. Principles for modelling
Page 11 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
dose–response for the risk assessment of chemicals. WHO, Geneva, Switzerland.
2009.
Reference Source
50. Rehm J, Shield KD: Global alcohol-attributable deaths from cancer, liver
cirrhosis, and injury in 2010. Alcohol Res. 2013; 35(2): 174–183.
PubMed Abstract
|
Free Full Text
51. Lachenmeier DW, Kanteres F, Rehm J: Epidemiology-based risk assessment
using the benchmark dose/margin of exposure approach: the example of
ethanol and liver cirrhosis. Int J Epidemiol. 2011; 40(1): 210–218.
PubMed Abstract
|
Publisher Full Text
52. Pflaum T, Hausler T, Baumung C, et al.: Carcinogenic compounds in alcoholic
beverages: an update. Arch Toxicol. 2016; 90(10): 2349–67.
PubMed Abstract
|
Publisher Full Text
53. Lachenmeier DW, Gill JS, Chick J, et al.: The total margin of exposure of ethanol
and acetaldehyde for heavy drinkers consuming cider or vodka. Food Chem
Toxicol. 2015; 83: 210–214.
PubMed Abstract
|
Publisher Full Text
54. Cunningham FH, Fiebelkorn S, Johnson M, et al.: A novel application of the
Margin of Exposure approach: segregation of tobacco smoke toxicants. Food
Chem Toxicol. 2011; 49(11): 2921–2933.
PubMed Abstract
|
Publisher Full Text
55. Xie J, Marano KM, Wilson CL, et al.: A probabilistic risk assessment approach
used to prioritize chemical constituents in mainstream smoke of cigarettes
sold in China. Regul Toxicol Pharmacol. 2012; 62(2): 355–362.
PubMed Abstract
|
Publisher Full Text
56. Hahn J, Monakhova YB, Hengen J, et al.: Electronic cigarettes: overview of
chemical composition and exposure estimation. Tob Induc Dis. 2014; 12(1): 23.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
57. OECD: How’s Life? 2015. Paris: OECD, 2015; accessed 1 October 2016.
Reference Source
58. Stoll L, Anderson P: Well-being as a framework for understanding addictive
substances. In Anderson P, Rehm J & Room R, (Eds.) The Impact of Addictive
Substances and Behaviours on Individual and Societal Well-Being. Oxford, Oxford
University Press, 2015.
Publisher Full Text
59. Babor T, Caulkins J, Edwards E, et al.: Drug Policy and the Public Good. Oxford
and London, Oxford University Press, 2010.
Publisher Full Text
60. Christakis NA, Fowler JH: Friendship and natural selection. Proc Natl Acad Sci U S A.
2014; 111(Suppl 3): 10796–10801.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
61. Christakis NA, Fowler JH: The collective dynamics of smoking in a large social
network. N Engl J Med. 2008; 358(21): 2249–2258.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
62. Rosenquist JN, Murabito J, Fowler JH, et al.: The spread of alcohol consumption
behavior in a large social network. Ann Intern Med. 2010; 152(7): 426–433, W141.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
63. Kurzban R, Leary MR: Evolutionary origins of stigmatization: the functions of
social exclusion. Psychol Bull. 2001; 127(2): 187–208.
PubMed Abstract
|
Publisher Full Text
64. Oaten M, Stevenson RJ, Case TI: Disease avoidance as a functional basis for
Stigmatization. Philos Trans R Soc Lond B Biol Sci. 2011; 366(1583): 3433–3452.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
65. Hawkley LC, Capitanio JP: Perceived social isolation, evolutionary fitness and
health outcomes: a lifespan approach. Philos Trans R Soc Lond B Biol Sci. 2015;
370(1669): pii: 20140114.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
66. Room R: Addiction and personal responsibility as solutions to the
contradictions of neoliberal consumerism. Crit Public Health. Accessed 15 April
2013, 2011; 21(2): 141–151.
Publisher Full Text
67. Rehm J, Anderson P, Fischer B, et al.: Policy implications of marked reversals of
population life expectancy caused by substance use. BMC Med. 2016; 14: 42.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
68. Aburto JM, Beltrán-Sánchez H, García-Guerrero VM, et al.: Homicides In Mexico
Reversed Life Expectancy Gains For Men And Slowed Them For Women, 2000–10.
Health Aff (Millwood). 2016; 35(1): 88–95.
PubMed Abstract
|
Publisher Full Text
69. Gamlin J: Violence and homicide in Mexico: a global health issue. Lancet. 2015;
385(9968): 605–6.
PubMed Abstract
|
Publisher Full Text
70. Werb D, Rowell G, Guyatt G, et al.: Effect of drug law enforcement on drug
market violence: a systematic review. Int J Drug Policy. 2011; 22(2): 87–94.
PubMed Abstract
|
Publisher Full Text
71. Rees WE: Ecological footprints and appropriated carrying capacity: what
urban economics leaves out. Environ Urban. 1992; 4(2): 121–130.
Publisher Full Text
72. Hoekstra AY: The water footprint of modern consumer society. London,
Routledge, 2013.
Reference Source
73. Wright LA, Kemp S, Williams I: Carbon footprinting: towards a universally
accepted definition. Carbon Manage. 2011; 2(1): 61–72.
Publisher Full Text
74. Williams I, Kemo S, Coello J, et al.: A beginner’s guide to carbon footprinting.
Carbon Manage. 2012; 3(1): 55–67.
Publisher Full Text
75. Ezzati M, Lopez A, Rodgers A, et al.: Comparative quantification of health risks.
Global and regional burden of disease attributable to selected major risk
factors. Geneva, Switzerland, World Health Organization, 2004.
Reference Source
76. Holmes MV, Dale CE, Zuccolo L, et al.: Association between alcohol and
cardiovascular disease: Mendelian randomisation analysis based on
individual participant data. BMJ. 2014; 349: g4164.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
77. Room R, Sankaran S, Schmidt LA, et al.: Addictive substances and
socioeconomic development. In: Anderson P, Rehm J & Room R eds. The Impact
of Addictive Substances and Behaviours on Individual and Societal Well-Being.
Oxford, Oxford University Press, 2015.
Publisher Full Text
78. McNeill A, Brose LS, Calder R, et al.: E-cigarettes: an evidence update. London:
Public Health England, 2015; accessed 1 October 2016.
Reference Source
79. Brose LS, Brown J, Hitchman SC, et al.: Perceived relative harm of electronic
cigarettes over time and impact on subsequent use. A survey with 1-year and
2-year follow-ups. Drug Alcohol Depend. 2015; 157: 106–11.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
80. Tobacco Advisory Group of the Royal College of Physicians: Nicotine without
smoke—tobacco harm reduction. Royal College of Physicians, 2016.
Reference Source
81. Schmidt LA, Mäkelä P, Rehm J, et al.: Alcohol: equity and social determinants.
In: Blas E & Sivasankara Kurup A, eds., Equity, Social
Determinants and Public Health Programmes. Geneva: World Health Organization,
2010; 11–29.
Reference Source
82. Moskalewicz J, Klingemann JI: Addictive substances and behaviours and social
justice. In Anderson P, Rehm J, Room R, Eds. The impact of addictive substances
and behaviours on individual and societal well-being. Oxford: Oxford University
Press, 2015.
Publisher Full Text
83. Bettcher D, da Costa e Silva VL: Tobacco or Health. In Leppo K, et al. eds. Health
in All Policies. Helsinki, Ministry of Social Affairs and Health, 2013.
Reference Source
84. Anderson P, Casswell S, Parry C, et al.: Alcohol. In Leppo K, et al. eds. Health in
All Policies. Helsinki, Ministry of Social Affairs and Health, 2013.
Reference Source
85. Kleiman MAR, Caulkins JP, Jacobson T, et al.: Violence and drug control policy.
In: Donnelly PD & Ward CL, eds. Oxford Textbook of Violence Prevention. Oxford:
Oxford University Press, 2014.
Publisher Full Text
86. Anderson P, Harrison O, Cooper C, et al.: Incentives for health. J Health Commun.
2011; 16(Suppl 2): 107–133.
PubMed Abstract
|
Publisher Full Text
87. Kupferschmidt K: The dangerous professor. Science. 2014; 343(6170): 478–481.
PubMed Abstract
|
Publisher Full Text
88. Conrod P, Brotherhood A, Sumnall H, et al.: Drug and Alcohol Policy for
European Youth: Current evidence and recommendations for integrated
policies and research strategies. In: Anderson P, Rehm J, Room R, (Eds.).
Impact of addictive substances and behaviours on individual and societal well-being.
Oxford: Oxford University Press, 2015.
Publisher Full Text
89. Grant BF, Goldstein RB, Saha TD, et al.: Epidemiology of DSM-5 Alcohol Use
Disorder: Results From the National Epidemiologic Survey on Alcohol and
Related Conditions III. JAMA Psychiatry. 2015; 72(8): 757–66.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
90. Grant BF, Saha TD, Ruan WJ, et al.: Epidemiology of DSM-5 Drug Use Disorder:
Results From the National Epidemiologic Survey on Alcohol and Related
Conditions-III. JAMA Psychiatry. 2016; 73(1): 39–47.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
91. Rehm J, Allamani A, Elekes Z, et al.: Alcohol dependence and treatment
utilization in Europe - a representative cross-sectional study in primary care.
BMC Fam Prac. 2015; 16: 90.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
92. Rehm J, Shield K, Rehm M, et al.: Alcohol consumption, alcohol dependence,
and attributable burden of disease in Europe: Potential gains from effective
interventions for alcohol dependence. Toronto, ON, Health, C. F. a. a. M, 2012.
Publisher Full Text
93. IAEG-SDGs: Report of the Inter-Agency and Expert Group on the Sustainable
Development Goal Indicators. 791 UHC Economic and Social Council, 2016.
Reference Source
94. OECD: Tackling Harmful Alcohol Use. Paris, OECD Publishing, 2015.
Reference Source
95. Faggiano F, Allara E, Giannotta F, et al.: Europe needs a central, transparent,
Page 12 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
and evidence-based approval process for behavioural prevention
interventions. PLoS Med. 2014; 11(10): e1001740.
PubMed Abstract
|
Publisher Full Text
|
Free Full Text
96. Rehm J, Gnam W, Popova S, et al.: The costs of alcohol, illegal drugs, and
tobacco in Canada, 2002. J Stud Alcohol Drugs. 2007; 68(6): 886–895.
PubMed Abstract
|
Publisher Full Text
97. Lingford-Hughes AR, Welch S, Peters L, et al.: BAP updated guidelines:
evidence-based guidelines for the pharmacological management of substance
abuse, harmful use, addiction and comorbidity: recommendations from BAP.
J Psychopharmacol. 2012; 26(7): 899–952.
PubMed Abstract
|
Publisher Full Text
98. National Cancer Institute (NCI): The Role of the Media in Promoting and
Reducing Tobacco Use. Davis RM, Gilpin EA, Loken B, Viswanath K & Wakefield
MA (Eds.) NCI Tobacco Control Monograph Series No. 19. Bethesda, MD: U.S.
Department of Health and Human Services, National Institutes of Health, National
Cancer Institute. NIH Pub. No. 07-6242, 2008.
Reference Source
99. Granovetter M:Threshold models of collective behaviour. Am J Sociol. 1978; 83:
14209–43.
Reference Source
100. Coceht Y: Green eschatology. In: Hamilton C, Bonneuil C & Gemenne F, eds. The
Anthropocene and the Global Environmental Crisis. London: Routledge, 2015.
Reference Source
101. McGirr L: The war on alcohol. New York: WW Norton & Company, 2016.
Reference Source
102. Anderson P, Berridge V, Conrod P, et al.: Dataset 1 in: Reframing the science
and policy of nicotine, illegal drugs and alcohol – conclusions of the ALICE
RAP Project. F1000Research. 2017.
Data Source
Page 13 of 13
F1000Research 2017, 6:289 Last updated: 17 MAR 2017
Project
Alcohol-related harm is a major social order issue which requires evidence-based policy. This project capitalises on a unique window of policy adoption within Queensland to investigate the introduc…" [more]
Project
The main aims of this project were to study the alcohol and drug treatment system both at the level of treatment agencies and at the level of clients coming into the system. We studied the populati…" [more]
Project
Bryggan City: Gästerna, deras nätverk, problem, behov och resurser. The aim of this one-year study, funded by Mobilisering mot narkotika (MOB) (the Swedish National Drug Policy Coordinator), is to…" [more]
Article
    Purpose of review: To discuss the health risks due to exposure to alcohol, illegal drugs and nicotine and how these risks might be reduced. Recent findings: In 2016, worldwide, alcohol, illegal drugs and nicotine were responsible for some 10 million deaths. There is evolutionary and biological evidence that humans are predisposed to consuming alcohol, illegal drugs and nicotine -... [Show full abstract]
    Article
    December 2016 · BMC Medicine
      Background Life expectancy has been increasing steadily over the past century in most countries, with only a few exceptions such as during wartimes. Discussion Marked reversal of life expectancy has been linked to substance use and related policies. Three such examples are discussed herein, namely the double reversal of life expectancy trends (first to positive, then to negative) associated... [Show full abstract]
      Article
      October 2014 · BMC Medicine
        Background Societies tend to accept much higher risks for voluntary behaviours, those based on individual decisions (for example, to smoke, to consume alcohol, or to ski), than for involuntary exposure such as exposure to risks in soil, drinking water or air. In high-income societies, an acceptable risk to those voluntarily engaging in a risky behaviour seems to be about one death in 1,000 on... [Show full abstract]
        Discover more