A narrative review of alcohol consumption as a risk factor for global burden of disease
Identifieur interne : 000A37 ( Pmc/Corpus ); précédent : 000A36; suivant : 000A38A narrative review of alcohol consumption as a risk factor for global burden of disease
Auteurs : Jürgen Rehm ; Sameer ImtiazSource :
- Substance Abuse Treatment, Prevention, and Policy [ 1747-597X ] ; 2016.
Abstract
Since the original Comparative Risk Assessment (CRA) for alcohol consumption as part of the Global Burden of Disease Study for 1990, there had been regular updates of CRAs for alcohol from the World Health Organization and/or the Institute for Health Metrics and Evaluation. These studies have become more and more refined with respect to establishing causality between dimensions of alcohol consumption and different disease and mortality (cause of death) outcomes, refining risk relations, and improving the methodology for estimating exposure and alcohol-attributable burden. The present review will give an overview on the main results of the CRAs with respect to alcohol consumption as a risk factor, sketch out new trends and developments, and draw implications for future research and policy.
Url:
DOI: 10.1186/s13011-016-0081-2
PubMed: 27793173
PubMed Central: 5084343
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PMC:5084343Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A narrative review of alcohol consumption as a risk factor for global burden of disease</title><author><name sortKey="Rehm, Jurgen" sort="Rehm, Jurgen" uniqKey="Rehm J" first="Jürgen" last="Rehm">Jürgen Rehm</name><affiliation><nlm:aff id="Aff1">Institute for Mental Health Policy Research, CAMH, 33 Russell Street, T505, Toronto, ON M5S 2S1 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">Campbell Family Mental Health Research Institute, CAMH, 250 College Street, Toronto, ON M5T 1R8 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff3">Institute of Medical Science (IMS), University of Toronto, Medical Sciences Building, 1 King’s College Circle, Room 2374, Toronto, ON M5S 1A8 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff4">Department of Psychiatry, University of Toronto, 250 College Street, 8th Floor, Toronto, ON M5T 1R8 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff5">Dalla Lana School of Public Health, University of Toronto, 155 College Street, 6th Floor, Toronto, ON M5T 3M7 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff6">Institute for Clinical Psychology and Psychotherapy, TU Dresden, Chemnitzer Str. 46, 01187 Dresden, Germany</nlm:aff></affiliation></author><author><name sortKey="Imtiaz, Sameer" sort="Imtiaz, Sameer" uniqKey="Imtiaz S" first="Sameer" last="Imtiaz">Sameer Imtiaz</name><affiliation><nlm:aff id="Aff1">Institute for Mental Health Policy Research, CAMH, 33 Russell Street, T505, Toronto, ON M5S 2S1 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff3">Institute of Medical Science (IMS), University of Toronto, Medical Sciences Building, 1 King’s College Circle, Room 2374, Toronto, ON M5S 1A8 Canada</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">27793173</idno><idno type="pmc">5084343</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5084343</idno><idno type="RBID">PMC:5084343</idno><idno type="doi">10.1186/s13011-016-0081-2</idno><date when="2016">2016</date><idno type="wicri:Area/Pmc/Corpus">000A37</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000A37</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A narrative review of alcohol consumption as a risk factor for global burden of disease</title><author><name sortKey="Rehm, Jurgen" sort="Rehm, Jurgen" uniqKey="Rehm J" first="Jürgen" last="Rehm">Jürgen Rehm</name><affiliation><nlm:aff id="Aff1">Institute for Mental Health Policy Research, CAMH, 33 Russell Street, T505, Toronto, ON M5S 2S1 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">Campbell Family Mental Health Research Institute, CAMH, 250 College Street, Toronto, ON M5T 1R8 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff3">Institute of Medical Science (IMS), University of Toronto, Medical Sciences Building, 1 King’s College Circle, Room 2374, Toronto, ON M5S 1A8 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff4">Department of Psychiatry, University of Toronto, 250 College Street, 8th Floor, Toronto, ON M5T 1R8 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff5">Dalla Lana School of Public Health, University of Toronto, 155 College Street, 6th Floor, Toronto, ON M5T 3M7 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff6">Institute for Clinical Psychology and Psychotherapy, TU Dresden, Chemnitzer Str. 46, 01187 Dresden, Germany</nlm:aff></affiliation></author><author><name sortKey="Imtiaz, Sameer" sort="Imtiaz, Sameer" uniqKey="Imtiaz S" first="Sameer" last="Imtiaz">Sameer Imtiaz</name><affiliation><nlm:aff id="Aff1">Institute for Mental Health Policy Research, CAMH, 33 Russell Street, T505, Toronto, ON M5S 2S1 Canada</nlm:aff></affiliation><affiliation><nlm:aff id="Aff3">Institute of Medical Science (IMS), University of Toronto, Medical Sciences Building, 1 King’s College Circle, Room 2374, Toronto, ON M5S 1A8 Canada</nlm:aff></affiliation></author></analytic><series><title level="j">Substance Abuse Treatment, Prevention, and Policy</title><idno type="eISSN">1747-597X</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Since the original Comparative Risk Assessment (CRA) for alcohol consumption as part of the Global Burden of Disease Study for 1990, there had been regular updates of CRAs for alcohol from the World Health Organization and/or the Institute for Health Metrics and Evaluation. These studies have become more and more refined with respect to establishing causality between dimensions of alcohol consumption and different disease and mortality (cause of death) outcomes, refining risk relations, and improving the methodology for estimating exposure and alcohol-attributable burden. The present review will give an overview on the main results of the CRAs with respect to alcohol consumption as a risk factor, sketch out new trends and developments, and draw implications for future research and policy.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Murray, Cjl" uniqKey="Murray C">CJL Murray</name></author><author><name sortKey="Lopez, Ad" uniqKey="Lopez A">AD Lopez</name></author><author><name sortKey="Jamison, Dt" uniqKey="Jamison D">DT Jamison</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Murray, Cj" uniqKey="Murray C">CJ Murray</name></author><author><name sortKey="Acharya, Ak" uniqKey="Acharya A">AK Acharya</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Murray, Cjl" uniqKey="Murray C">CJL Murray</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Murray, Cjl" uniqKey="Murray 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Subst Abuse Treat Prev Policy</journal-id><journal-id journal-id-type="iso-abbrev">Subst Abuse Treat Prev Policy</journal-id><journal-title-group><journal-title>Substance Abuse Treatment, Prevention, and Policy</journal-title></journal-title-group><issn pub-type="epub">1747-597X</issn><publisher><publisher-name>BioMed Central</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">27793173</article-id><article-id pub-id-type="pmc">5084343</article-id><article-id pub-id-type="publisher-id">81</article-id><article-id pub-id-type="doi">10.1186/s13011-016-0081-2</article-id><article-categories><subj-group subj-group-type="heading"><subject>Review</subject></subj-group></article-categories><title-group><article-title>A narrative review of alcohol consumption as a risk factor for global burden of disease</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">http://orcid.org/0000-0001-5665-0385</contrib-id><name><surname>Rehm</surname><given-names>Jürgen</given-names></name><address><phone>1-416-535-8501</phone><email>jtrehm@gmail.com</email></address><xref ref-type="aff" rid="Aff1">1</xref><xref ref-type="aff" rid="Aff2">2</xref><xref ref-type="aff" rid="Aff3">3</xref><xref ref-type="aff" rid="Aff4">4</xref><xref ref-type="aff" rid="Aff5">5</xref><xref ref-type="aff" rid="Aff6">6</xref></contrib><contrib contrib-type="author"><name><surname>Imtiaz</surname><given-names>Sameer</given-names></name><address><email>sameer.imtiaz@gmail.com</email></address><xref ref-type="aff" rid="Aff1">1</xref><xref ref-type="aff" rid="Aff3">3</xref></contrib><aff id="Aff1"><label>1</label>Institute for Mental Health Policy Research, CAMH, 33 Russell Street, T505, Toronto, ON M5S 2S1 Canada</aff><aff id="Aff2"><label>2</label>Campbell Family Mental Health Research Institute, CAMH, 250 College Street, Toronto, ON M5T 1R8 Canada</aff><aff id="Aff3"><label>3</label>Institute of Medical Science (IMS), University of Toronto, Medical Sciences Building, 1 King’s College Circle, Room 2374, Toronto, ON M5S 1A8 Canada</aff><aff id="Aff4"><label>4</label>Department of Psychiatry, University of Toronto, 250 College Street, 8th Floor, Toronto, ON M5T 1R8 Canada</aff><aff id="Aff5"><label>5</label>Dalla Lana School of Public Health, University of Toronto, 155 College Street, 6th Floor, Toronto, ON M5T 3M7 Canada</aff><aff id="Aff6"><label>6</label>Institute for Clinical Psychology and Psychotherapy, TU Dresden, Chemnitzer Str. 46, 01187 Dresden, Germany</aff></contrib-group><pub-date pub-type="epub"><day>28</day><month>10</month><year>2016</year></pub-date><pub-date pub-type="pmc-release"><day>28</day><month>10</month><year>2016</year></pub-date><pub-date pub-type="collection"><year>2016</year></pub-date><volume>11</volume><elocation-id>37</elocation-id><history><date date-type="received"><day>28</day><month>7</month><year>2016</year></date><date date-type="accepted"><day>19</day><month>10</month><year>2016</year></date></history><permissions><copyright-statement>© The Author(s). 2016</copyright-statement><license license-type="OpenAccess"><license-p><bold>Open Access</bold>This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><abstract id="Abs1"><p>Since the original Comparative Risk Assessment (CRA) for alcohol consumption as part of the Global Burden of Disease Study for 1990, there had been regular updates of CRAs for alcohol from the World Health Organization and/or the Institute for Health Metrics and Evaluation. These studies have become more and more refined with respect to establishing causality between dimensions of alcohol consumption and different disease and mortality (cause of death) outcomes, refining risk relations, and improving the methodology for estimating exposure and alcohol-attributable burden. The present review will give an overview on the main results of the CRAs with respect to alcohol consumption as a risk factor, sketch out new trends and developments, and draw implications for future research and policy.</p></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Alcohol</kwd><kwd>Average level of consumption</kwd><kwd>Patterns of drinking</kwd><kwd>Comparative risk assessment</kwd><kwd>Relative risk</kwd><kwd>Burden of disease</kwd><kwd>Cause of death</kwd><kwd>Global</kwd></kwd-group><funding-group><award-group><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000027</institution-id><institution>National Institute on Alcohol Abuse and Alcoholism</institution></institution-wrap></funding-source><award-id>HHSN267200700041C</award-id><principal-award-recipient><name><surname>Rehm</surname><given-names>Jürgen</given-names></name></principal-award-recipient></award-group><award-group><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100004423</institution-id><institution>World Health Organization</institution></institution-wrap></funding-source><award-id>n.a.</award-id><principal-award-recipient><name><surname>Rehm</surname><given-names>Jürgen</given-names></name></principal-award-recipient></award-group></funding-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© The Author(s) 2016</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="Sec1" sec-type="introduction"><title>Background</title><p>The very first Global Burden of Disease (GBD) Study [<xref ref-type="bibr" rid="CR1">1</xref>, <xref ref-type="bibr" rid="CR2">2</xref>] only gave indications on burden of disease as measured in number of deaths or disability adjusted life years ((DALYs; [<xref ref-type="bibr" rid="CR3">3</xref>, <xref ref-type="bibr" rid="CR4">4</xref>]) by different disease categories. DALYs are a summary gap measure of health combining fatal and non-fatal indicators, specifically summing up the years of life lost due to premature mortality and years of life lost due to disability [<xref ref-type="bibr" rid="CR5">5</xref>]. The first GBD study was purely descriptive, but a major improvement from the situation in the past, when the sum of the number of deaths claimed by different causes by far exceeded the global number of deaths, even if only numbers within the same organization, such as the World Health Organization (WHO), were added up [<xref ref-type="bibr" rid="CR1">1</xref>, <xref ref-type="bibr" rid="CR6">6</xref>]. The second improvement of this study was that it was not restricted to fatal health outcomes, and with DALYs it included a summary measure combining fatal and non-fatal events [<xref ref-type="bibr" rid="CR5">5</xref>].</p><p>However, already at that stage it became apparent that more information was needed if one wanted to decrease the burden of disease. The concept of risk factor is key here [<xref ref-type="bibr" rid="CR7">7</xref>]; defined as any attribute, characteristic or exposure of an individual that increases the likelihood of developing a disease or injury [<xref ref-type="bibr" rid="CR8">8</xref>]. As a consequence, all future GBD studies included Comparative Risk Assessments (CRAs), which estimated the number of deaths and DALYs that could be avoided if certain risk factors were to be eliminated or shifted to a less detrimental distribution [<xref ref-type="bibr" rid="CR9">9</xref>–<xref ref-type="bibr" rid="CR12">12</xref>]. Such information was seen as important for health policy, especially in terms of primary prevention ([<xref ref-type="bibr" rid="CR1">1</xref>, <xref ref-type="bibr" rid="CR13">13</xref>]; specifically for alcohol see [<xref ref-type="bibr" rid="CR14">14</xref>, <xref ref-type="bibr" rid="CR15">15</xref>]). Alcohol consumption has always been part of the top 10 risk factors assessed in these CRAs in terms of the attributable global burden of disease.</p><p>This review will give an overview on the main results of the CRAs with respect to alcohol consumption, sketch out new trends and developments, and draw implications for future research and policy.</p></sec><sec id="Sec2"><title>Alcohol-attributable burden of mortality and disease in the various Comparative Risk Assessments</title><p>Table <xref rid="Tab1" ref-type="table">1</xref> gives an overview of the main CRAs conducted since 1996 on two main outcomes: all-cause mortality as measured in the number of deaths, and burden of disease as measured in DALYs (for a definition of DALYs see [<xref ref-type="bibr" rid="CR3">3</xref>, <xref ref-type="bibr" rid="CR4">4</xref>]).<table-wrap id="Tab1"><label>Table 1</label><caption><p>Proportion of global mortality and DALYs attributable to alcohol (net burden)</p></caption><table frame="hsides" rules="groups"><thead><tr><th>Year</th><th>Proportion of global mortality attributable to alcohol</th><th>Proportion of global DALYs attributable to alcohol</th><th>Reference</th></tr></thead><tbody><tr><td>1990</td><td>1.5 %</td><td>3.5 %</td><td>[<xref ref-type="bibr" rid="CR12">12</xref>, <xref ref-type="bibr" rid="CR155">155</xref>]</td></tr><tr><td>2000</td><td>3.2 % (W: 0.6 %; M: 5.6 %)</td><td>4.0 % (W: 1.3 %; M: 6.5 %)</td><td>[<xref ref-type="bibr" rid="CR16">16</xref>, <xref ref-type="bibr" rid="CR156">156</xref>]</td></tr><tr><td>2004</td><td>3.8 % (W: 1.1 %; M: 6.3)</td><td>4.6 % (W: 1.4 %; M: 7.6 %)</td><td>[<xref ref-type="bibr" rid="CR157">157</xref>]</td></tr><tr><td>2010</td><td>5.2 % (W: 3.1 %; M: 6.9 %)</td><td>3.9 % (W: 2.0 %; M: 5.4 %)</td><td>[<xref ref-type="bibr" rid="CR10">10</xref>, <xref ref-type="bibr" rid="CR18">18</xref>]<sup>a</sup></td></tr><tr><td>2012</td><td>5.9 % (W: 4.0 %; M: 7.6 %)</td><td>5.1 % (W: 2.3 %; M: 7.4 %)</td><td>[<xref ref-type="bibr" rid="CR9">9</xref>]</td></tr><tr><td>2013</td><td>5.1 % (W: 3.1 %; M: 6.8 %)</td><td>4.1 % (W: 1.9 %; M: 5.9 %)</td><td>[<xref ref-type="bibr" rid="CR11">11</xref>, <xref ref-type="bibr" rid="CR18">18</xref>]<sup>a</sup></td></tr><tr><td>2015</td><td colspan="3">GBD 2015 and WHO Global Status Report on Alcohol and Health to be published in 2016</td></tr></tbody></table><table-wrap-foot><p><sup>a</sup>The given estimates for mortality are not available in the Lancet publications of the Global Burden of Disease Study 2010 and 2013 [<xref ref-type="bibr" rid="CR10">10</xref>, <xref ref-type="bibr" rid="CR11">11</xref>]. They were obtained from GDB Compare [<xref ref-type="bibr" rid="CR18">18</xref>]. Please note that these estimates may change when the methodology changes, so the date of assessment is important</p></table-wrap-foot></table-wrap></p><p>While Table <xref rid="Tab1" ref-type="table">1</xref> seems to indicate a substantial rise in both alcohol attributable mortality and disease burden, this is not the case. Any CRA estimates depend very much on methodology, and the majority of the variation between the first estimate for 1990 [<xref ref-type="bibr" rid="CR12">12</xref>] and the other estimates can be explained by the following factors (see also [<xref ref-type="bibr" rid="CR16">16</xref>, <xref ref-type="bibr" rid="CR17">17</xref>]:<list list-type="bullet"><list-item><p>Availability of and methodology used for cause of death and disability statistics on a global level.</p></list-item><list-item><p>Diseases and causes of death which are seen as causally impacted by alcohol.</p></list-item><list-item><p>Relative risk estimates used to estimate attributable disease burden.</p></list-item><list-item><p>Methodology used to derive attributable fractions.</p></list-item></list></p><p>These questions will be discussed separately under different headings below.</p><p>Having clarified this, there have been efforts to estimate real changes using the same methodology for comparisons in global or regional alcohol-attributable burden of disease between 1990 and 2010 [<xref ref-type="bibr" rid="CR10">10</xref>]; between 1990 and 2013 [<xref ref-type="bibr" rid="CR11">11</xref>, <xref ref-type="bibr" rid="CR18">18</xref>] or between for all years from 1990 to 2014 [<xref ref-type="bibr" rid="CR19">19</xref>, <xref ref-type="bibr" rid="CR20">20</xref>].</p></sec><sec id="Sec3"><title>Availability of and methodology used for cause of death and disability statistics on a global level</title><p>Alcohol has been causally linked to more than 230 ICD 10 three digit disease categories [<xref ref-type="bibr" rid="CR17">17</xref>], including about 40 that would not exist without alcohol (such as alcohol dependence or alcoholic liver cirrhosis; for a complete list see [<xref ref-type="bibr" rid="CR21">21</xref>]). However, this does not mean, the various global CRA efforts are including all of these disease categories. First, global health statistics are not that detailed. For most of the population worldwide, there are no vital registries with cause of death information. The World Health Organization (WHO) estimates that vital registries fail to cover about two thirds, or 38 million out of 56 million annual deaths globally [<xref ref-type="bibr" rid="CR22">22</xref>]. For the rest, i.e., the majority of cause of deaths globally, the basis are verbal autopsies and standardized algorithms to analyze these verbal autopsies and to scale up these results to wider regions [<xref ref-type="bibr" rid="CR23">23</xref>]. Obviously, the resulting cause of death categories are fewer and broader than the categories of the ICD, as it is impossible to determine detailed cause of deaths via verbal autopsy [<xref ref-type="bibr" rid="CR24">24</xref>]. As indicated above, burden of disease is composed of mortality and disability. For disability, the data situation is worse than for mortality [<xref ref-type="bibr" rid="CR25">25</xref>], and estimates are developed based on estimated prevalence of disease categories [<xref ref-type="bibr" rid="CR26">26</xref>] and disability weights; a disability weight is a factor that reflects the severity of the disease on a scale from 0 (perfect health) to 1 (equivalent to death) [<xref ref-type="bibr" rid="CR27">27</xref>].</p><p>Currently, there are two different organizations which produce estimates for global data on health outcomes: the Institute for Health Metrics and Evaluation (IHME) [<xref ref-type="bibr" rid="CR28">28</xref>] and the WHO [<xref ref-type="bibr" rid="CR29">29</xref>]. Methodologies for estimating deaths are overlapping but different, resulting in different estimates on cause of death by categories (e.g., [<xref ref-type="bibr" rid="CR30">30</xref>]). Secondly, different disability weights are applied for non-fatal outcomes, resulting in different estimates of burden of disease in DALYs ) [<xref ref-type="bibr" rid="CR31">31</xref>–<xref ref-type="bibr" rid="CR33">33</xref>]. However, the number of disease categories are the same between both organizations. For CRAs this means, that the number of deaths and DALYs, where attributable fractions are applied to, are different based on which underlying statistics are used. One of the main differences specifically for alcohol consumption as a risk factor are alcohol use disorders, which are defined differently by IHME and WHO, and where different disability weights have been applied (IHME restricted to dependence, WHO including harmful use of alcohol with a non-zero weight). A reconceptualization on heavy drinking over time may help overcome these differences [<xref ref-type="bibr" rid="CR34">34</xref>].</p><p>The availability of only broader categories on a global level has consequences for CRA. Diseases and causes of death like alcoholic cardiomyopathy or alcohol-induced chronic pancreatitis are relevant in many countries (for alcoholic cardiomyopathy: [<xref ref-type="bibr" rid="CR35">35</xref>]; for pancreatitis: [<xref ref-type="bibr" rid="CR36">36</xref>]), but there are no global statistics. As a consequence, the impact of alcohol can only indirectly be assessed by using larger categories such as cardiomyopathy or pancreatitis, for which global estimates exist. Unfortunately, often risk relations are missing for such larger categories: this is the case for cardiomyopathy, as there is neither a systematic review nor a meta-analyses for the impact of alcohol, and thus, this category will show no alcohol-attributable cases, even though we know, there are cases of alcoholic cardiomyopathy. For alcohol-induced chronic pancreatitis, the CRA has to rely on the larger category of pancreatitis and meta-analyses on the impact of alcohol on this category [<xref ref-type="bibr" rid="CR37">37</xref>, <xref ref-type="bibr" rid="CR38">38</xref>] to be included into alcohol-attributable deaths or burden of disease. As a consequence, the alcohol-attributable disease and cause of death categories boil down to a much lower number of less than 25. In sum, global estimates on alcohol-attributable mortality and disease burden rely only on selected large disease categories. This eliminates most categories, which are 100 % alcohol-attributable by definition, except for alcohol use disorders and fetal alcohol syndrome (for some background on burden attached for alcohol use disorders: [<xref ref-type="bibr" rid="CR39">39</xref>, <xref ref-type="bibr" rid="CR40">40</xref>]; for fetal alcohol syndrome [<xref ref-type="bibr" rid="CR41">41</xref>]), as well as smaller partially attributable categories of disease or causes of death.</p></sec><sec id="Sec4"><title>Diseases and causes of death seen as causally impacted by alcohol</title><p>The number of alcohol-attributable disease categories in CRAs over the past decades has been increasing for three reasons. First, while the overall number is still small, more disease categories have been included into the global statistics (both as cause of death and as burden of disease in DALYs). To give two examples relevant for alcohol, pancreatitis and cardiac arrhythmias were added for the CRA of GBD study 2010 [<xref ref-type="bibr" rid="CR17">17</xref>, <xref ref-type="bibr" rid="CR24">24</xref>]. Second, evidence on the causal impact of alcohol consumption became stronger and more convincing for certain disease categories, and third, better models for quantification of such causal impact were established.</p><sec id="Sec5"><title>Alcohol-attributable cancers</title><p>For the second reason specified above, take alcohol-attributable cancers as an example [<xref ref-type="bibr" rid="CR42">42</xref>]. While the first monograph from the meeting of the International Agency for Research on Cancer on alcohol use and cancer established sufficient evidence for a causal relationship between alcohol consumption and the cancer categories of nasopharyngeal cancer, esophageal cancer, laryngeal cancer, and liver cancer [<xref ref-type="bibr" rid="CR43">43</xref>], the next meeting added female breast and colorectal cancers [<xref ref-type="bibr" rid="CR44">44</xref>, <xref ref-type="bibr" rid="CR45">45</xref>]. The underlying evidence led to inclusion of breast cancer into the CRAs from the GDB study 2000 onwards, and for colorectal cancers from 2010 onwards. Currently other types of cancer are discussed as potentially alcohol-attributable, such as cancer categories of pancreas or stomach cancer, as heavy drinking has been consistently associated with increased risk for these categories [<xref ref-type="bibr" rid="CR46">46</xref>, <xref ref-type="bibr" rid="CR47">47</xref>]; thus, more cancer categories will likely be added to future CRAs.</p></sec><sec id="Sec6"><title>Alcohol-attributable infectious diseases and causes of death</title><p>Of the alcohol-attributable disease categories, infectious diseases and causes of death constitute the most important overall change within the past two decades. Even though pneumonia and tuberculosis had been seen as impacted by heavy drinking as early as in the 18<sup>th</sup> century [<xref ref-type="bibr" rid="CR48">48</xref>], the causality had to be re-established using current criteria [<xref ref-type="bibr" rid="CR49">49</xref>]. The first step was conducted in a consensus meeting in 2008, which established causality for tuberculosis and pneumonia [<xref ref-type="bibr" rid="CR50">50</xref>]. This led to inclusion of these categories from 2010 onwards (underlying documentation: tuberculosis [<xref ref-type="bibr" rid="CR51">51</xref>]; pneumonia [<xref ref-type="bibr" rid="CR52">52</xref>]).</p><p>The open question was HIV/AIDS, where the meeting did not find enough evidence of causality despite consistent associations [<xref ref-type="bibr" rid="CR53">53</xref>–<xref ref-type="bibr" rid="CR55">55</xref>]. There was a clear causal association which could be quantified for one pathway: the impact of alcohol consumption on medication adherence, which had impact on mortality [<xref ref-type="bibr" rid="CR56">56</xref>]. This association was implemented for the 2012 CRA, which was the basis of the WHO 2014 Global status report [<xref ref-type="bibr" rid="CR9">9</xref>]. Moreover, in a number of recent systematic reviews based on experimental research, it could be established that alcohol has a causal impact on decisions to engage in unsafe sex [<xref ref-type="bibr" rid="CR57">57</xref>, <xref ref-type="bibr" rid="CR58">58</xref>]. This allows for estimation of alcohol impacting the incidence of HIV as an additional component in future CRAs, and the responsible WHO technical advisory group has decided to include this component. This addition will markedly change the estimates of alcohol-attributable mortality and burden of disease in Sub-Saharan Africa [<xref ref-type="bibr" rid="CR59">59</xref>].</p></sec><sec id="Sec7"><title>Alcohol use and mental disorders</title><p>It may be surprising that since 2010 no other mental disorders than alcohol use disorders have been included (i.e., alcohol dependence and the harmful use of alcohol according to ICD 10). Clearly most mental disorders have consistent associations with alcohol use, especially heavy drinking, and alcohol use disorders (e.g., [<xref ref-type="bibr" rid="CR60">60</xref>–<xref ref-type="bibr" rid="CR62">62</xref>]; we give only references for alcohol use disorders, as heavy drinking is very closely related to these disorders [<xref ref-type="bibr" rid="CR63">63</xref>], and has even been suggested as a better definition for kind of disorders [<xref ref-type="bibr" rid="CR64">64</xref>]). In addition to these associations, both DSM-5 and ICD 10 [<xref ref-type="bibr" rid="CR65">65</xref>, <xref ref-type="bibr" rid="CR66">66</xref>] list alcohol-induced mental disorders, thus establishing causality. However, there is a problem in quantifying the causal impact. While alcohol consumption impacts mental disorders, there is also reverse causality, and we cannot exclude genetic vulnerability as a third variable impacting both alcohol consumption and mental disorders [<xref ref-type="bibr" rid="CR16">16</xref>]. Thus, quantification of causality is difficult. It has been attempted in the GBD study 2000 for major depressive disorders [<xref ref-type="bibr" rid="CR16">16</xref>], but later committees did not see this attempt as convincing enough. Maybe some of the newer research on alcohol and depression [<xref ref-type="bibr" rid="CR67">67</xref>, <xref ref-type="bibr" rid="CR68">68</xref>] will allow for better modelling in future CRAs.</p></sec><sec id="Sec8"><title>Other alcohol-attributable disease and injury categories</title><p>Other categories of alcohol-attributable disease and mortality included in current CRAs are fetal alcohol syndrome (by definition), epilepsy [<xref ref-type="bibr" rid="CR69">69</xref>], gastrointestinal disease (liver cirrhosis [<xref ref-type="bibr" rid="CR70">70</xref>] and pancreatitis [<xref ref-type="bibr" rid="CR37">37</xref>, <xref ref-type="bibr" rid="CR38">38</xref>]; the latter new for the CRA associated with GBD study 2010 and after), diabetes [<xref ref-type="bibr" rid="CR71">71</xref>], cardiovascular disease [<xref ref-type="bibr" rid="CR72">72</xref>] hypertensive disease [<xref ref-type="bibr" rid="CR73">73</xref>], ischemic heart disease [<xref ref-type="bibr" rid="CR74">74</xref>], stroke [<xref ref-type="bibr" rid="CR75">75</xref>], and cardiac arrhythmias [<xref ref-type="bibr" rid="CR76">76</xref>], the last one new for the CRAs 2010 and after, and almost all categories of injury [<xref ref-type="bibr" rid="CR77">77</xref>, <xref ref-type="bibr" rid="CR78">78</xref>]. The last systematic overview on alcohol use and causal relations to different disease and cause of death categories can be found in [<xref ref-type="bibr" rid="CR17">17</xref>].</p><p>The alcohol-attributable burden in all CRAs has almost entirely been estimated as the effect of drinking on the drinkers themselves. However, as with smoking, there is significant harm to others [<xref ref-type="bibr" rid="CR79">79</xref>, <xref ref-type="bibr" rid="CR80">80</xref>] (for some first estimation within a CRA: [<xref ref-type="bibr" rid="CR81">81</xref>]). In the CRAs thus far, only some of the effect of mothers’ drinking on newborns (in the last CRAs only fetal alcohol syndrome; before low birth weight – [<xref ref-type="bibr" rid="CR82">82</xref>]) and unsystematically some of the effects on harm to others in traffic injuries have been captured.</p><p>In sum, with respect to changes of alcohol-attributable disease categories over time, there have been some categories added since 1990, mainly based on more disease categories available on a global basis. In addition, the evidence base has expanded in recent years to include and quantify the contribution of infectious disease categories as being alcohol-attributable. However, effects of alcohol consumption on others than the drinker have not been covered systematically.</p></sec></sec><sec id="Sec9"><title>Relative risk estimates used to estimate attributable disease burden</title><p>Table <xref rid="Tab2" ref-type="table">2</xref> gives an overview on the relative risk estimates used for the WHO Global status report on alcohol and health [<xref ref-type="bibr" rid="CR9">9</xref>] for all countries except for Russia and surrounding countries (for graphical displays of the dose-response relationships between average volume of consumption and outcomes see [<xref ref-type="bibr" rid="CR83">83</xref>]; for the estimates used for Russia and surrounding countries see [<xref ref-type="bibr" rid="CR84">84</xref>]).<table-wrap id="Tab2"><label>Table 2</label><caption><p>Categories of alcohol-attributable diseases and the sources used for determining risk relations from the WHO 2014 Global Status Report on Alcohol and Health [<xref ref-type="bibr" rid="CR9">9</xref>]<sup>a</sup></p></caption><table frame="hsides" rules="groups"><thead><tr><th>Condition</th><th>ICD 10 Code</th><th>Sources of risk relations (for calculating alcohol-attributable fractions)</th></tr></thead><tbody><tr><td>Infectious and parasitic diseases</td><td></td><td></td></tr><tr><td> Tuberculosis</td><td>A15-A19</td><td>[<xref ref-type="bibr" rid="CR158">158</xref>]</td></tr><tr><td>Human immunodeficiency virus/ Acquired immune deficiency syndrome</td><td>B20-B24</td><td>[<xref ref-type="bibr" rid="CR56">56</xref>] for estimate on the impact of alcohol on worsening the disease course via disrupting the medication schedule</td></tr><tr><td>Malignant neoplasms</td><td></td><td></td></tr><tr><td> Mouth and oropharynx cancers</td><td>C00-C14</td><td>(based on relative risks from [<xref ref-type="bibr" rid="CR87">87</xref>])</td></tr><tr><td> Esophageal cancer</td><td>C15</td><td>(based on relative risks from [<xref ref-type="bibr" rid="CR87">87</xref>])</td></tr><tr><td> Liver cancer</td><td>C22</td><td>(based on relative risks from [<xref ref-type="bibr" rid="CR87">87</xref>])</td></tr><tr><td> Laryngeal cancer</td><td>C32</td><td>(based on relative risks from [<xref ref-type="bibr" rid="CR87">87</xref>])</td></tr><tr><td> Breast cancer</td><td>C50</td><td>(based on relative risks from [<xref ref-type="bibr" rid="CR87">87</xref>])</td></tr><tr><td> Colon cancer</td><td>C18</td><td rowspan="2">(combined risk taken from [<xref ref-type="bibr" rid="CR47">47</xref>])</td></tr><tr><td> Rectal cancer</td><td>C20</td></tr><tr><td>Diabetes</td><td></td><td></td></tr><tr><td> Diabetes mellitus</td><td>E10-E14</td><td>[<xref ref-type="bibr" rid="CR71">71</xref>]</td></tr><tr><td>Neuro-psychiatric conditions</td><td></td><td></td></tr><tr><td> Alcoholic psychoses (part of AUD)</td><td>F10.0, F10.3-F10.9</td><td>100 % alcohol attributable by definition</td></tr><tr><td> Alcohol abuse (part of AUD)</td><td>F10.1</td><td rowspan="2"></td></tr><tr><td> Alcohol dependence (part of AUD)</td><td>F10.2</td></tr><tr><td> Accidental poisoning by and exposure to alcohol</td><td>X45</td><td></td></tr><tr><td> Epilepsy</td><td>G40-G41</td><td>[<xref ref-type="bibr" rid="CR69">69</xref>]</td></tr><tr><td>Cardiovascular disease</td><td></td><td></td></tr><tr><td> Hypertensive disease</td><td>I10-I15</td><td>[<xref ref-type="bibr" rid="CR73">73</xref>]</td></tr><tr><td> Ischemic heart disease</td><td>I20-I25</td><td>[<xref ref-type="bibr" rid="CR89">89</xref>, <xref ref-type="bibr" rid="CR90">90</xref>, <xref ref-type="bibr" rid="CR159">159</xref>]</td></tr><tr><td>For any CRA after GBD 2013 see: [<xref ref-type="bibr" rid="CR89">89</xref>]</td><td></td><td></td></tr><tr><td> Cardiac arrhythmias</td><td>I47-I49</td><td>[<xref ref-type="bibr" rid="CR76">76</xref>]</td></tr><tr><td> Ischemic stroke</td><td>I60-I62</td><td>[<xref ref-type="bibr" rid="CR75">75</xref>, <xref ref-type="bibr" rid="CR89">89</xref>]</td></tr><tr><td> Hemorrhagic and other non-ischemic stroke</td><td>I63-I66</td><td>[<xref ref-type="bibr" rid="CR75">75</xref>]</td></tr><tr><td>Digestive diseases</td><td></td><td></td></tr><tr><td> Cirrhosis of the liver</td><td>K70, K74</td><td>[<xref ref-type="bibr" rid="CR70">70</xref>]</td></tr><tr><td> Acute and chronic pancreatitis</td><td>K85, K86.1</td><td>[<xref ref-type="bibr" rid="CR37">37</xref>]</td></tr><tr><td>Respiratory infections</td><td></td><td></td></tr><tr><td> Lower respiratory infections</td><td>J10–J18, J20–J22</td><td>[<xref ref-type="bibr" rid="CR52">52</xref>]</td></tr><tr><td>Conditions arising during the prenatal period</td><td></td><td></td></tr><tr><td> Fetal alcohol syndrome</td><td>Q86.0</td><td>100 % alcohol attributable by definition</td></tr><tr><td>Unintentional injuries</td><td></td><td></td></tr><tr><td> Motor vehicle accidents</td><td><sup>b</sup></td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr><tr><td> Poisonings</td><td>X40-X49 except X45</td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr><tr><td> Falls</td><td>W00-W19</td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr><tr><td> Fires</td><td>X00-X09</td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr><tr><td> Drowning</td><td>W65-W74</td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr><tr><td> Other Unintentional injuries</td><td><sup>c</sup>Rest of V-series and W20-W64, W 75-W99, X10-X39, X50-X59, Y40-Y86, Y88, Y89</td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr><tr><td>Intentional injuries</td><td></td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr><tr><td> Self-inflicted injuries</td><td>X60-X84, Y87.0</td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr><tr><td> Homicide</td><td>X85-Y09, Y87.1</td><td>[<xref ref-type="bibr" rid="CR87">87</xref>]</td></tr></tbody></table><table-wrap-foot><p><sup>a</sup>Due to lack of data on very specific categories of death, diseases where alcohol is a necessary cause (other than Alcohol Use Disorders), such as alcohol poisonings, were modelled using RRs for the broader category</p><p><sup>b</sup>V021–V029, V031–V039, V041–V049, V092, V093, V123–V129, V133–V139, V143–V149, V194–V196, V203–V209, V213–V219, V223–V229, V233–V239, V243–V249, V253–V259, V263–V269, V273– V279, V283–V289, V294–V299, V304–V309, V314–V319, V324–V329, V334–V339, V344–V349, V354–V359, V364–V369, V374–V379, V384–V389, V394–V399, V404–V409, V414–V419, V424–V429, V434–V439, V444–V449, V454–V459, V464– V469, V474–V479, V484–V489, V494–V499, V504–V509, V514–V519, V524–V529, V534–V539, V544–V549, V554–V559, V564–V569, V574–V579, V584–V589, V594–V599, V604–V609, V614–V619, V624–V629, V634–V639, V644–V649, V654– V659, V664–V669, V674–V679, V684–V689, V694–V699, V704–V709, V714–V719, V724–V729, V734–V739, V744–V749, V754–V759, V764–V769, V774–V779, V784–V789, V794–V799, V803–V805, V811, V821, V830–V833, V840–V843, V850– V853, V860–V863, V870–V878, V892</p><p><sup>c</sup>Rest of V = V-series MINUS <sup>b</sup></p></table-wrap-foot></table-wrap></p><p>While new meta-analyses on the risk relations between level of consumption and various disease/mortality outcomes appear regularly, this does not change the burden estimates dramatically. Take breast cancer as an example: there have been more than 100 single studies and 16 systematic reviews with meta-analyses over the past 20 years [<xref ref-type="bibr" rid="CR85">85</xref>]. However, the main conclusions on relative risk did not change: there is a clear dose-response relationship with no protective effect for any level of drinking compared to lifetime abstainers [<xref ref-type="bibr" rid="CR85">85</xref>]. Even drinking as low as one drink on average is associated with increased risk for breast cancer [<xref ref-type="bibr" rid="CR85">85</xref>, <xref ref-type="bibr" rid="CR86">86</xref>]. The quantification for the different levels of alcohol-attributable risk for breast cancer had been quite similar over the years [<xref ref-type="bibr" rid="CR85">85</xref>], as they had been for cancer in general (e.g., [<xref ref-type="bibr" rid="CR87">87</xref>], which has been used to date for the CRAs, and [<xref ref-type="bibr" rid="CR47">47</xref>]; which will be used in the future).</p><p>The field of cardiovascular outcomes has been less stable, in part, because two dimensions of alcohol consumption need to be taken into consideration, average volume and patterns of drinking, in particular heavy drinking occasions (in general: [<xref ref-type="bibr" rid="CR88">88</xref>]; for cardiovascular in particular see [<xref ref-type="bibr" rid="CR16">16</xref>, <xref ref-type="bibr" rid="CR89">89</xref>]), and because there are much fewer underlying studies (for some endpoints less than 10 studies; see the underlying studies on heavy drinking occasions and ischemic heart disease: [<xref ref-type="bibr" rid="CR74">74</xref>, <xref ref-type="bibr" rid="CR90">90</xref>]), and because part of the effect is on acute drinking and part on chronic drinking with different methodologies which are hard to reconcile in meta-analytic approaches (acute drinking risks have been mainly measured via case-crossover studies such as [<xref ref-type="bibr" rid="CR91">91</xref>]; chronic risks have been mainly measured in cohort studies such as [<xref ref-type="bibr" rid="CR92">92</xref>]). Another problem is the fact that risk curves differ between fatal and non-fatal outcomes for many endpoints such as stroke [<xref ref-type="bibr" rid="CR75">75</xref>] or ischemic heart disease [<xref ref-type="bibr" rid="CR89">89</xref>]. Overall this makes the estimation of alcohol-attributable mortality and burden of disease challenging, and in almost each new CRA, a different approach has been used. As well, newest calculations in the WHO European Region suggest, that relatively small changes in exposure resulted in marked changes of cardiovascular mortality over the past 25 years [<xref ref-type="bibr" rid="CR20">20</xref>].</p><p>Relative risks for other outcomes can be classified as in between cancer and cardiovascular disease in their complexity. For many outcomes, fatal and non-fatal risk relations differ. Thus, it has been found that for liver cirrhosis, the risk curves are steeper (more exponential) for mortality compared to non-fatal outcomes [<xref ref-type="bibr" rid="CR70">70</xref>]. The explanation is simple: it takes quite a lot of alcohol consumption to cause liver cirrhosis often via different stages of liver disease [<xref ref-type="bibr" rid="CR93">93</xref>], but once liver cirrhosis is established, no matter of what etiology, relatively small amounts of alcohol may be fatal [<xref ref-type="bibr" rid="CR70">70</xref>, <xref ref-type="bibr" rid="CR94">94</xref>]. Heavy drinking occasions may play an additional role here, but we do not have enough data to quantify this relationship [<xref ref-type="bibr" rid="CR95">95</xref>].</p><p>Similarly, for injury, acute alcohol use has been linked to more severe and in particular to fatal injuries [<xref ref-type="bibr" rid="CR16">16</xref>, <xref ref-type="bibr" rid="CR96">96</xref>]. For CRA this means that different risk relations have to be used for mortality and for the non-fatal outcomes.</p><p>One of the main problems with the relative risks is that it is assumed, that they are biological constants and the same for all countries, and thus it does not matter, that the current estimates are derived from meta-analyses of select cohort studies from a few high income countries with a limited variation of drinking patterns (see above and [<xref ref-type="bibr" rid="CR97">97</xref>], box on “Methodological issues relevant to studies of alcohol-related morbidity and mortality). Unfortunately, this assumption is not correct. It has been shown that the usual relative risks derived differ from the analogous risks found in Russia or surrounding countries [<xref ref-type="bibr" rid="CR98">98</xref>, <xref ref-type="bibr" rid="CR99">99</xref>], and thus would lead to underestimates of alcohol-attributable burden [<xref ref-type="bibr" rid="CR100">100</xref>]. In the most recent CRAs after 2010, this has been acknowledged and country specific relative risks have been used [<xref ref-type="bibr" rid="CR84">84</xref>]. We suspect that different relative risks could be necessary for other countries with high <italic>per capita</italic> consumption per drinker (see [<xref ref-type="bibr" rid="CR9">9</xref>], for a listing of countries), or for countries with irregular heavy-drinking patterns (e.g., countries with festive drinking such as Mexico; [<xref ref-type="bibr" rid="CR101">101</xref>, <xref ref-type="bibr" rid="CR102">102</xref>]). Unfortunately, as of now, we have no evidence base to implement country- or region-specific relative risks for these patterns. Another problem is genetic predisposition, which sometimes interacts with alcohol consumption to produce different risks. As an example, the flushing gene [<xref ref-type="bibr" rid="CR103">103</xref>], which is clearly associated with higher risks for alcohol-attributable cancer with an acetaldehyde pathway [<xref ref-type="bibr" rid="CR104">104</xref>], clearly indicated different relative risk estimates for countries where this genetic constellation is prevalent (such as China, Japan and South Korea).</p><p>In sum, global estimates of risk relations tend to only minimally change for outcomes with many underlying studies such as cancer outcomes. This changes for cardiovascular outcomes, where more than one exposure dimension is relevant, and where there are few studies to quantify the risk relations. In future, more country- or region-specific relative risk estimates will be necessary to include genetic variability and more extreme drinking patterns, which are not measured in most cohort studies (see the box on “Methodological issues relevant to studies of alcohol-related morbidity and mortality” and [<xref ref-type="bibr" rid="CR97">97</xref>] for further discussion of the limitations of cohort studies).</p></sec><sec id="Sec10"><title>Methodology used to derive attributable fractions</title><p>While the overall methodology for CRAs has been fairly stable (for a description see [<xref ref-type="bibr" rid="CR105">105</xref>, <xref ref-type="bibr" rid="CR106">106</xref>]) based on original epidemiological concepts of the 1980s [<xref ref-type="bibr" rid="CR107">107</xref>, <xref ref-type="bibr" rid="CR108">108</xref>], there are important shifts in details:<list list-type="bullet"><list-item><p>The first CRAs until and including the 2010 study were based on discrete categories of exposure and associated relative risks, whereas the latter were based on a continuous distribution of both exposure and risk (for theoretical background: [<xref ref-type="bibr" rid="CR109">109</xref>]; for a comparison of both methods in the same sample: [<xref ref-type="bibr" rid="CR110">110</xref>])</p></list-item><list-item><p>This implicated different ways to define exposure and to triangulate between national <italic>per capita</italic> consumption and surveys (see [<xref ref-type="bibr" rid="CR16">16</xref>, <xref ref-type="bibr" rid="CR111">111</xref>] and [<xref ref-type="bibr" rid="CR110">110</xref>, <xref ref-type="bibr" rid="CR112">112</xref>] for the categorical, and the continuous approach respectively). However, the differences between the categorical and the continuous approach for alcohol as a risk factor in CRAs are not that large [<xref ref-type="bibr" rid="CR109">109</xref>].</p></list-item><list-item><p>The biggest difference will come in via the triangulation of survey and <italic>per capita</italic> consumption. Overall <italic>per capita</italic> consumption is considered as most validly representing the overall consumption level in a population [<xref ref-type="bibr" rid="CR113">113</xref>], especially if it is for countries with high proportion of recorded consumption ( [<xref ref-type="bibr" rid="CR9">9</xref>] for the proportion of recorded to overall consumption). However, as <italic>per capita</italic> consumption is derived from administrative records [<xref ref-type="bibr" rid="CR114">114</xref>], it allows no differentiation by sex and age. That is where surveys become indispensable. The problem is that general population surveys only cover part of the real consumption, and this proportion, usually labelled coverage rate [<xref ref-type="bibr" rid="CR115">115</xref>, <xref ref-type="bibr" rid="CR116">116</xref>], is highly variable. The known variation of coverage rates is between 20 % and 90 % (for an example of low coverage: 27 % in Canada [<xref ref-type="bibr" rid="CR117">117</xref>]; for high coverage see 87 % in Sweden [<xref ref-type="bibr" rid="CR118">118</xref>] or close to 90 % in New Zealand [<xref ref-type="bibr" rid="CR119">119</xref>]).</p></list-item><list-item><p>So triangulation basically assumes the distribution by sex and age of the survey, and a consumption level of 80 % of the <italic>per capita</italic> consumption [<xref ref-type="bibr" rid="CR110">110</xref>]. The reason for not assuming 100 % of <italic>per capita</italic> consumption which is sold is, that there is some spillage and other waste of alcohol, and that exposure is applied to risk relation estimates which may also underestimate consumption. However, the degree of underestimation is not clear, as there is no gold standard for such studies. There are some indications that cohort studies with their specific forms of assessment often in a medical environment tend to show less underestimation of true consumption [<xref ref-type="bibr" rid="CR120">120</xref>–<xref ref-type="bibr" rid="CR122">122</xref>]. Moreover, lack of coverage does not only reflect individuals underestimating or misrepresenting their consumption. It also reflects the sample frame of the survey, which usually excludes high drinking populations such as military or institutionalized people [<xref ref-type="bibr" rid="CR123">123</xref>]. As a result it is hard to calibrate a certain proportion of <italic>per capita</italic> consumption, but the WHO technical advisory committee after reviewing all the underlying evidence decided for 80 %. The impact of different triangulations can be considerable [<xref ref-type="bibr" rid="CR117">117</xref>, <xref ref-type="bibr" rid="CR124">124</xref>], so it is good to be conservative [<xref ref-type="bibr" rid="CR125">125</xref>].</p></list-item></list></p></sec><sec id="Sec11"><title>Implications for research</title><p>In the above, we described the methodology to conduct a CRA for alcohol consumption. In this methodology, instantaneous effects are assumed: i.e., exposure to alcohol consumption in a certain year is assumed to result in changes in mortality for this year. This clearly is a simplification, as there is usually a lag time between alcohol consumption and disease outcomes [<xref ref-type="bibr" rid="CR126">126</xref>]. Moreover, individual consumption may vary, and many risk relations assume more or less a constant consumption over time [<xref ref-type="bibr" rid="CR127">127</xref>]. Future CRAs should address this problem and take into consideration the lag time between consumption and outcomes (e.g., using methodology such as [<xref ref-type="bibr" rid="CR128">128</xref>, <xref ref-type="bibr" rid="CR129">129</xref>]). However, such a step would need a reconfiguration of the conceptual model for all CRAs for all risk factors, as one of the main objectives of any CRA is to be comparative between risk factors and time.</p><p>In addition we expect the following methodological changes for future CRAs for alcohol:<list list-type="bullet"><list-item><p>With respect to modelling exposure, methods to triangulate irregular heavy drinking occasions with <italic>per capita</italic> consumption are needed. As indicated above, currently the only triangulation is between average level of alcohol consumption and <italic>per capita</italic> consumption [<xref ref-type="bibr" rid="CR110">110</xref>, <xref ref-type="bibr" rid="CR112">112</xref>]. For irregular heavy drinking occasions [<xref ref-type="bibr" rid="CR130">130</xref>, <xref ref-type="bibr" rid="CR131">131</xref>], we accept self-reports from surveys as true, even if we know, that they usually underestimate true frequency and number of drinks per occasion. In the future, we need to develop ways to triangulate self-report and objective measurement for irregular heavy drinking occasions.</p></list-item><list-item><p>We have already mentioned the rather strong assumption, that risk relations taken from the most comprehensive meta-analysis are seen as a global constant with exception of Russia and surrounding countries (where the risk relations are based on [<xref ref-type="bibr" rid="CR98">98</xref>, <xref ref-type="bibr" rid="CR99">99</xref>]; see also [<xref ref-type="bibr" rid="CR84">84</xref>]). Given the genetic and environmental differences, we would expect some differences in risk relations between alcohol consumption and disease/mortality outcomes in different regions (e.g. based on the interaction between genetics and alcohol consumption in causing cancer; see [<xref ref-type="bibr" rid="CR104">104</xref>, <xref ref-type="bibr" rid="CR132">132</xref>]). Future CRAs for alcohol consumption will have to more and more regionalize risk relations, not only based on genetic predisposition, but also based on socially determined risks such as the risks for injury outcomes [<xref ref-type="bibr" rid="CR133">133</xref>, <xref ref-type="bibr" rid="CR134">134</xref>].</p></list-item><list-item><p>Finally, we expect that future CRAs will have explicit separation on harm to drinkers and harm to others. The conceptual framework is there [<xref ref-type="bibr" rid="CR135">135</xref>], the underlying data for major categories such as traffic injury [<xref ref-type="bibr" rid="CR136">136</xref>] or for fetal alcohol syndrome/fetal alcohol spectrum disorders is there (the latter estimated via drinking in pregnant women; [<xref ref-type="bibr" rid="CR137">137</xref>, <xref ref-type="bibr" rid="CR138">138</xref>]) and there are major efforts to improve the methodology for quantification (e.g., in the Netherlands based on the <italic>per se</italic> law on substance use and violence – [<xref ref-type="bibr" rid="CR139">139</xref>]; in Germany within a comprehensive effort to estimate alcohol-attributable harm to others for the Ministry – personal communication of Prof. L. Kraus).</p></list-item></list></p></sec><sec id="Sec12"><title>Implications for alcohol policy</title><p>As indicated above, all CRAs resulted in marked burden of disease caused by alcohol consumption. Two dimensions were identified as important to cause harm: overall level of consumption and patterns of drinking [<xref ref-type="bibr" rid="CR88">88</xref>]. Policies need to address both dimensions.</p><p>There are effective and cost-effective policies to lower overall level of consumption in societies [<xref ref-type="bibr" rid="CR140">140</xref>, <xref ref-type="bibr" rid="CR141">141</xref>], such as the so-called ‘best buys’, i.e., increase of taxation leading to increases in price of alcoholic beverages, decrease in availability, and ban of marketing and advertisement [<xref ref-type="bibr" rid="CR142">142</xref>, <xref ref-type="bibr" rid="CR143">143</xref>]. However, these policies do not to seem to be too popular with governments, and in fact alcohol has become more available and affordable in most parts of the world over the past decades (e.g., in the European Union, see [<xref ref-type="bibr" rid="CR144">144</xref>]). Other potential ways to decrease overall level of alcohol consumption would be a decrease in alcoholic strength, which is technically possible for all beverages, and which could be achieved via government regulation, taxation or industry initiatives [<xref ref-type="bibr" rid="CR145">145</xref>]. It should be noted however, that a reduction in overall level of alcohol consumption does not necessarily mean a reduction in total alcohol-attributable mortality or burden of disease, as monitoring of the last 25 years for the WHO European Region has shown [<xref ref-type="bibr" rid="CR20">20</xref>]. In addition, it has to be assured, that the heaviest drinkers do not increase their drinking (e.g., via treatment [<xref ref-type="bibr" rid="CR146">146</xref>]), and that patterns of drinking do not get worse (see also [<xref ref-type="bibr" rid="CR20">20</xref>]).</p><p>Regarding patterns of drinking, there are other promising policies such as minimum pricing [<xref ref-type="bibr" rid="CR147">147</xref>, <xref ref-type="bibr" rid="CR148">148</xref>], and specific policies to decrease heavy drinking occasions in certain situation, such as in participation in traffic [<xref ref-type="bibr" rid="CR136">136</xref>] or while operating machinery at the workplace [<xref ref-type="bibr" rid="CR149">149</xref>]. Obviously, harm would be minimized, if in such situations abstinence was the norm.</p><p>Finally, the composition of alcohol-attributable burden of disease and mortality will have different implications for policy [<xref ref-type="bibr" rid="CR150">150</xref>]. A high proportion of traffic injury could be reduced with specific measures for drink driving such as introduction and enforcement of a <italic>per se</italic> law regarding blood alcohol concentration, or reduction of the blood alcohol concentration threshold in existing laws [<xref ref-type="bibr" rid="CR140">140</xref>, <xref ref-type="bibr" rid="CR151">151</xref>]. On the other hand, high alcohol-attributable intentional injury will ask for specific measures such as measures against binge drinking or <italic>per se</italic> laws on criminal prosecution [<xref ref-type="bibr" rid="CR150">150</xref>]. To give one final example concerning chronic disease: high levels of alcohol-attributable liver disease mortality point to high overall level of consumption [<xref ref-type="bibr" rid="CR152">152</xref>, <xref ref-type="bibr" rid="CR153">153</xref>], or to relatively high level of consumption combined with other etiological factors for liver disease such as HIV (as even comparatively small levels of alcohol consumption may cause liver mortality in people with liver cirrhosis no matter which etiology – see above for further detail and [<xref ref-type="bibr" rid="CR20">20</xref>], for examples). Reductions of overall alcohol consumption, no matter how achieved, will lead to reductions in alcohol-attributable liver mortality [<xref ref-type="bibr" rid="CR20">20</xref>].</p></sec><sec id="Sec13" sec-type="conclusion"><title>Conclusions</title><p>The CRA methodology has been evolving and for comparisons over time it is necessary to use the latest methodology and calculate backwards using the same methodology. If this principle is used, then CRAs can potentially inform the health policy process and yield important information for decision makers. Obviously, interventions will depend not only on the size and shape of the burden, but also on how much of the alcohol-attributable burden is avoidable [<xref ref-type="bibr" rid="CR154">154</xref>], and on aspects on feasibility, costs and cost-effectiveness of interventions [<xref ref-type="bibr" rid="CR14">14</xref>, <xref ref-type="bibr" rid="CR15">15</xref>]. For alcohol consumption, in principle all of the burden is avoidable, but any intervention will have to take into consideration the role alcohol has been playing in our society for thousands of years [<xref ref-type="bibr" rid="CR13">13</xref>]. However, despite these general limitations, information about attributable burden will also be one major building block towards better policies [<xref ref-type="bibr" rid="CR19">19</xref>, <xref ref-type="bibr" rid="CR150">150</xref>].</p></sec></body><back><glossary><title>Abbreviations</title><def-list><def-item><term>AIDS</term><def><p>Acquired Immune Deficiency Syndrome</p></def></def-item><def-item><term>AUD</term><def><p>Alcohol Use Disorder</p></def></def-item><def-item><term>CRA</term><def><p>Comparative Risk Assessment</p></def></def-item><def-item><term>DALYs</term><def><p>Disability Adjusted Life Years</p></def></def-item><def-item><term>DSM</term><def><p>Diagnostic and Statistical Manual of Mental Disorders</p></def></def-item><def-item><term>GBD</term><def><p>Global Burden of Disease</p></def></def-item><def-item><term>HIV</term><def><p>Human Immunodeficiency Virus</p></def></def-item><def-item><term>ICD</term><def><p>International Classification of Disease</p></def></def-item><def-item><term>IHME</term><def><p>Institute for Health Metrics and Evaluation</p></def></def-item><def-item><term>WHO</term><def><p>World Health Organization</p></def></def-item></def-list></glossary><ack><p>We would like to thank more than 1000 collaborators who helped in the various CRAs by contributing data and comments.</p><sec id="FPar1"><title>Funding</title><p>The first author received grants and contracts from NIAAA (contract # HHSN267200700041C and various amendments), the WHO and the Global Burden of Disease study for contributions to the Comparative Risk Assessment for 2000, and all other CRAs since.</p></sec><sec id="FPar2"><title>Availability of data and materials</title><p>This is a review of published materials. The original underlying data can be found at the websites of the Institute for Health Metrics and Evaluation (<ext-link ext-link-type="uri" xlink:href="http://www.healthdata.org/">http://www.healthdata.org/</ext-link>) and the WHO Global Information System on Alcohol and Health (<ext-link ext-link-type="uri" xlink:href="http://www.who.int/gho/alcohol/en/">http://www.who.int/gho/alcohol/en/</ext-link>). All specific sources cited are referenced in the text.</p></sec><sec id="FPar3"><title>Authors’ contributions</title><p>JR did a first draft of the paper. SI collected the information for Table <xref rid="Tab1" ref-type="table">1</xref>. Both authors helped in revising the manuscript and approved of the final draft.</p></sec><sec id="FPar4"><title>Competing interest</title><p>The authors declare that they have no competing interests.</p></sec><sec id="FPar5"><title>Consent for publication</title><p>Not applicable.</p></sec><sec id="FPar6"><title>Ethics approval and consent to participate</title><p>This is a narrative review of published sources. No ethical approval was necessary. 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