Alcohol and Noncommunicable Disease Risk - Springer Link

Current Addiction Reports (2018) 5:72–85 https://doi.org/10.1007/s40429-018-0189-8

ALCOHOL (M FARRELL AND E STOCKINGS, SECTION EDITORS)

Alcohol and Noncommunicable Disease Risk Jürgen Rehm 1,2,3,4,5,6 & Omer S. M. Hasan 1,5 & Sameer Imtiaz 1,3 & Charlotte Probst 1,6 & Michael Roerecke 1,5 & Kevin Shield 1,5 Published online: 26 February 2018 # Springer International Publishing AG, part of Springer Nature 2018, corrected publication March/2018

Abstract Purpose of Review Alcohol use is a major risk factor for noncommunicable diseases (NCDs), annually causing more than 1.8 million deaths, and approximately 52 million disability-adjusted life years lost globally. This review examines the relationship between alcohol use and NCDs in the context of current United Nations (UN) and World Health Organization (WHO) initiatives to reduce the burden of NCDs as well as the resulting policy implications. Recent Findings The importance of alcohol as a major risk factor for NCDs is evidenced by its inclusion as one of only four behavioral risk factors (tobacco use, unhealthy diet, physical inactivity, and harmful use of alcohol) into the World Health Organization’s Global Action Plan for the Prevention and Control of NCDs. Alcohol use also plays a major role in other strategic initiatives of the UN and WHO. Summary While these inclusions help enable policy measures to reduce harmful alcohol use, the Global NCD Action Plan in general disregards many diseases and injuries caused by alcohol, most notably liver cirrhosis and all mental disorders. Furthermore, the Global NCD Action Plan also fails to highlight interactions between risk factors; however, there is strong epidemiological evidence of the differential harms caused by alcohol use between poverty/socioeconomic strata. Thus, future policy plans should explicitly include consideration of health inequalities. Keywords Alcohol . Noncommunicable disease . Policy . Risk factor . Liver cirrhosis

This article is part of the Topical Collection on Alcohol Electronic supplementary material The online version of this article (https://doi.org/10.1007/s40429-018-0189-8) contains supplementary material, which is available to authorized users. * Jürgen Rehm [email protected] 1

Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), 33 Russell Street, Toronto, ON M5S 2S1, Canada

2

Campbell Family Mental Health Research Institute, CAMH, 250 College Street, Toronto, ON M5T 1R8, Canada

3

Institute of Medical Science (IMS), University of Toronto, Medical Sciences Building, 1 King’s College Circle, Room 2374, Toronto, ON M5S 1A8, Canada

4

Department of Psychiatry, University of Toronto, 250 College Street, 8th Floor, Toronto, ON M5T 1R8, Canada

5

Dalla Lana School of Public Health, University of Toronto, 155 College Street, 6th Floor, Toronto, ON M5T 3M7, Canada

6

Institute for Clinical Psychology and Psychotherapy, TU Dresden, Chemnitzer Str. 46, 01187 Dresden, Germany

Introduction: Alcohol Use as a Risk Factor for Noncommunicable Diseases Alcohol use is a major cause of mortality and disease globally [1••, 2, 3•]. Furthermore, alcohol use as a risk factor is unique in that it leads to an increased risk of death and disability from many different causes, with the harms caused by alcohol across these diseases, conditions and injuries cumulatively summing to a relatively large burden of disease [1••]. Specifically, alcohol is causally related to more than 200 International Classification of Disease (ICD-10) three-digit codes [4, 5], including infectious diseases, noncommunicable diseases (NCDs) [5••], and injuries. Due to global population aging, NCDs are now a major focus of national and global preventative efforts [6, 7, 8••]. For alcohol’s effect on NCDs, a recent systematic search on the topic across two major databases, returned more than 5600 reviews (see Web Appendix 1). Table 1 provides an overview of major NCD categories related to alcohol (based on [5••]). Given the global NCD burden caused by alcohol consumption, this article outlines the relationship between alcohol and

C0-C08.9, D00.00-D00.07, D10.0-D10.5, D11-D11.9, D37.01-D37.04, D37.09a

C11-C11.9, D00.08, D10.6, D37.05a

C09-C10.9, C12-C13.9, D10.7a

C15-C15.9, D00.1, D13.0a

C18-C21.9, D01.0-D01.3, D12-D12.9, D37.3-D37.5a

C22-C22.9, D13.4a

C25-C25.9, D13.6-D13.7a

C32-C32.9, D02.0, D14.1, D38.0a

C50-C50.929, D05-D05.92, D24-D24.9, D48.6-D48.62, D49.3, N60-N60.99a

E10-E10.11, E10.3-E11.1, E11.3E12.1, E12.3-E13.11, E13.3E14.1, E14.3-E14.9, P70.0P70.2, R73-R73.9 F00-F03.91, G30-G31.1, G31.8-G31.9

Lip and oral cavity cancer

Nasopharyngeal cancer

Other pharyngeal cancer

Esophagus cancer

Colon and rectal cancer

Liver cancer

Pancreatic cancer

Laryngeal cancer

Female breast cancer

Diabetes mellitus

Alzheimer’s disease and other dementias

ICD-10 codes for cause of death, based on GBD [119]

Causality: Collins et al., 2009 [16] for potential pathways of protective effects of light to moderate use; Ridley et al., 2013 [17];

Causality: International Agency for Research on Cancer (IARC), 2010; 2012 [9, 10]: sufficient evidence for carcinogenicity in humansb CRA calculations: Bagnardi et al., 2015 [11] Causality: IARC, 2010; 2012 [9, 10]: sufficient evidence for carcinogenicity in humansb CRA calculations: Bagnardi et al., 2015 [11] Causality: IARC, 2010; 2012 [9, 10]: sufficient evidence for carcinogenicity in humansb CRA calculations: Bagnardi et al., 2015 [11] Causality: IARC, 2010; 2012 [9, 10]: sufficient evidence for carcinogenicity in humansb CRA calculations: Bagnardi et al., 2015 [11] Causality: IARC, 2010; 2012 [9, 10]: sufficient evidence for carcinogenicity in humansb CRA calculations: Bagnardi et al., 2015 [11] Causality: IARC, 2010; 2012 [9, 10]: sufficient evidence for carcinogenicity in humansb Meta-analysis: Corrao et al., 2004 [12]; Bagnardi et al., 2015 [11] CRA calculations: Bagnardi et al., 2015 [11] Causality: IARC, 2012 [10]: probably carcinogenic in humansb CRA calculations: Bagnardi et al., 2015 [11]; pancreatic cancer has been included in some CRA calculations where the threshold was set to include “probably carcinogenic” Causality: IARC, 2010; 2012 [9, 10]: sufficient evidence for carcinogenicity in humansb CRA calculations: Bagnardi et al., 2015 [11] Causality: IARC, 2010; 2012 [9, 10]: sufficient evidence for carcinogenicity in humansb (see also [13] specifically for effects of low level drinking) CRA calculations: Bagnardi et al., 2015 [11] Causality: Howard et al., 2004 [14] CRA calculations: Baliunas et al., 2009 [15]; currently in revision

Causality and reference to metaanalyses/selected systematic reviews

Major alcohol-attributable noncommunicable disease categories (see [5••])

Disease category

Table 1

Detrimental

Cumulated level of exposurec

Detrimental; potential beneficial effect for light to moderate drinking

Beneficial or detrimental, depending on patterns of drinking and populations

Detrimental


Level of drinking; patterns of drinking; different effects on different indicators for metabolic syndrome Level of drinking (patterns of drinking may also be a factor)

Detrimental

Detrimental



Detrimental

Detrimental



Detrimental


Detrimental

Detrimental



Effect

Dimension of alcohol

Curr Addict Rep (2018) 5:72–85 73

Has not been modeled in GBD as cause of death; F32–33

G40-G41.9

I11-I11.9

I20-I25.9

A39.52, B33.2-B33.24, D86.85, I40-I43.9, I51.4-I51.5 I48-I48.92

Epilepsy

Hypertensive heart disease

Ischemic heart disease

Cardiomyopathy

Ischemic stroke

G45-G46.8, I63-I63.9, I65I66.9, I67.2-I67.3, I67.5I67.6, I69.3-I69.398

F10

Mental and behavioral disorders due to use of alcohol Unipolar depressive disorders

Atrial fibrillation and flutter


Disease category

Table 1 (continued)

Daulatzai, 2015 [18], for mechanism of detrimental effects of heavy use; certain types of dementia are alcohol-attributable by definition [17] or strongly relation to alcohol use disorders [19] CRA calculations: not yet included in CRA; but see: Beydoun et al., 2014 [20] for a meta-analysis Causality: per definition CRA calculations: 100% alcohol-attributable by definition Causality: Rehm et al., 2004 [21]; Boden & Fergusson, 2011 [22]; Meta-analyses: Boden & Fergusson, 2011 [22]; Foulds et al., 2015 [23] CRA calculations: suggested to use Fergusson et al., 2009 [24] to be conservative, based on prevalence of alcohol use disorders Causality: Bartolomei, 2006 [25]; Barclay et al., 2008 [26]; Leach et al., 2012 [27] Meta-analysis and CRA calculations: Samokhvalov et al., 2010 [28] Causality: Puddey & Beilin, 2006 [29]; O’Keefe et al., 2014 [30]; in addition, we have good evidence that interventions leading to reductions of alcohol use will subsequently lead to reductions in blood pressure and hypertension. Xin et al., 2001 [31], Roerecke et al., 2017 [32] CRA calculations: Rehm et al., 2017 [33] Causality: Mukamal & Rimm, 2001 [35]; Collins et al., 2009 [16]; Roerecke & Rehm, 2014 [36] CRA calculations: Rehm et al., 2016 [37]; Roerecke & Rehm, 2014 [36] Causality: Iacovoni et al., 2010 [38]; George & Figueredo, 2011 [39]; Rehm et al., 2017 [40] CRA calculations: Manthey et al., 2017 [41] Causality: Rosenqvist, 1998 [42]; Rosenberg & Mukamal, 2012 [43] CRA calculations: Samokhvalov et al., 2010 [44] Causality: Puddey et al., 1999 [45]; Mazzaglia et al., 2001 [46]; Collins et al., 2009 [16] CRA calculations: Patra et al., 2010 [47]; Rehm et al., 2016 [37]


Detrimental

Detrimental

Level of drinking

Level and variability of drinking (for an overview see [34])

Level of drinking (patterns of drinking may also be a factor; for an overview see [34]) Level and patterns of drinking (for an overview see [34])

Heavy drinking occasions (for an overview see [34]

Beneficial or detrimental, dependent on level and patterns of drinking

Detrimental

Detrimental

Beneficial or detrimental, dependent on level and patterns of drinking

Detrimental

Level and patterns of drinking

Level and patterns of drinking (for an overview see [34]

Detrimental

Effect

Level and patterns of drinking


74 Curr Addict Rep (2018) 5:72–85

B18-B18.9, I85-I85.9, I98.2, K70-K70.9, K71.3-K71.51, K71.7, K72.1-K74.69, K74.9, K75.8-K76.0, K76.6-K76.7, K76.9 K80-K83.9

Cirrhosis of the liver

Causality: Puddey et al., 1999 [45]; Mazzaglia et al., 2001 [46]; CRA calculations: Patra et al., 2010 [47] Causality: see liver cirrhosis Global CRA calculations: not applicable, as category is too small. National CRA calculations: should be done with relative risk of liver cirrhosis Causality: A causal impact of alcohol is by definition, as for many liver diseases there are alcoholic sub-categories in the ICD (see Table 1); pathogenesis: Gao & Bataller, 2011 [48] CRA calculations: Rehm et al., 2010 [49] Causality: Not clear for the overall category (for gallbladder disease see [50]) CRA calculations: not relevant, as causality is not clear and the only meta-analysis showed no association between alcohol use and gallstones [51] Causality: not necessary, as there are two conditions of pancreatitis which are 100% alcohol attributable (see Table 1); for pathogenesis: Braganza et al., 2011 [52]; Yadav et al., 2013 [53]; Lankisch et al., 2015 [54]; Majumder & Chari, 2016 [55] CRA calculations: Samokhvalov et al., 2015 [56]


Potentially beneficial, but no relation to alcohol use in the only meta-analyses for gallstones Detrimental

Level of drinking

Level of drinking

c

b

a

Detrimental

Detrimental

Level of drinking

Level of drinking

Mainly detrimental, except for low doses

Effect

Level of drinking (for an overview see [36])


ex. = exposure; for calculations in CRA, cumulated level of exposure is operationalized via level of exposure when measured

For definitions of level of evidence, see [57]

The relationships between alcohol use and the respective cancer sites are based on studies with ICD-10 C codes; the D codes were listed only, as we wanted to show compatibility with the GBD

Shaded rows indicate noncommunicable diseases as defined in the Global Action Plan for the Prevention and Control of NCDs 2013–2020 [7])

Pancreatitis

Gall bladder and bile duct disease

K85-K86.9

I60-I61.9, I62.0-I62.03, I67.0-I67.1, I68.1-I68.2, I69.0-I69.298 I85

Hemorrhagic and other nonischemic stroke

Oesophageal varices


Disease category

Table 1 (continued)

Curr Addict Rep (2018) 5:72–85 75

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NCDs in the context of current United Nations and World Health Organization (WHO) initiatives to reduce the burden of NCDs as well as the resulting policy implications.

Alcohol Use and Noncommunicable Diseases in the WHO Global Action Plan for the Prevention and Control of Noncommunicable Diseases 2013–2020 and Other WHO strategies Alcohol is one of the four major risk factors for NCDs mentioned in the WHO’s Global Action Plan for the Prevention and Control of NCDs 2013–2020, with a specific target of reducing the harmful use of alcohol by 10% [58, 59]. This is a relatively less ambitious target compared to other risk factors mentioned in the Global Action Plan, and its potential contribution to the overall reduction of NCDs was estimated to be smaller than achieving the targets set for other risk factors [60, 61]. Furthermore, within the WHO Global Action Plan for NCDs [58], a restrictive definition of NCDs was used, which is limited to cardiovascular disease, cancer, chronic lung diseases, and diabetes. This definition was based mainly on mortality caused by these disease categories [58], and thus overlooked mental disorders, where a large portion of the global disability caused by alcohol is concentrated [62–64]. Moreover, the NCD Global Action Plan excluded gastrointestinal diseases, which are a leading source of the disease burden globally and responsible for the stagnating life expectancies observed in some countries [65–69]. For example, in the USA, the mortality rate due to NCDs such as cardiovascular diseases or cancers has declined; however, mortality rates due to gastrointestinal diseases and other alcohol-related categories have increased, in large part contributing to stagnating overall life expectancies [68]. Contrary to the Global Action Plan, the WHO’s Global strategy to reduce the harmful use of alcohol [59] is not restricted to “classic” NCDs in particular and health harms in general as it includes all harms caused by alcohol, including harms caused by the drinking of others [70–72]. However, this strategy has not had the level of endorsement and/or the impact of the NCD initiatives on a global level (i.e., both by international organizations and by countries).

Alcohol Use and the Resulting Noncommunicable Disease Burden

Curr Addict Rep (2018) 5:72–85

proportions by category for both years of life lost due to premature mortality (YLLs) and years of life lost to living with disability (YLDs). Added together, these two components form the disability-adjusted life years (DALYs) lost measure [73, 74]. The annual global burden of alcohol-attributable NCD burden is large, with more than 1.8 million deaths, approximately 52 million YLLs, and close to 29 million YLDs. The distribution of the alcohol-attributable NCD burden across disease categories is notably different for deaths, YLLs and YLDs. Most deaths and YLLs attributable to alcohol stem from cancers, cardiovascular diseases and gastrointestinal disorders in general, with alcohol-attributable deaths due to cardiovascular diseases (especially stroke; see Table 2) and alcohol-attributable YLLs due to gastrointestinal diseases (mainly liver cirrhosis; see Fig. 1) being leading causes of these burdens. In contrast, 98% of the alcohol-attributable YLDs are due to neuropsychiatric disorders, in particular alcohol use disorders (i.e., alcohol dependence and harmful use of alcohol; see Fig. 2). Thus, the current restrictive definition of the NCD Global Action Plan and monitoring framework [58, 75] excludes most of the nonfatal NCD disease burden attributable to alcohol. It is notable that for diabetes mellitus, alcohol use was found to be net protective in terms of deaths, YLLs and YLDs (based on [15]). However, recent reviews cast doubt on these findings [76]. Furthermore, for YLDs due to cardiovascular diseases, a net protective effect of alcohol was observed mainly due to ischemic disease categories [37]. However, the cardioprotective effect has been widely debated [34, 77] despite the plausible biological pathways (e.g., [78, 79]; see also the discussion on alcohol and hypertension below).

Selected Interactions Between Alcohol Use and Other Risk Factors, Confounding The effects of alcohol as operationalized by the comparative risk assessment studies [80–82] assume immediate effects with a counterfactual scenario of no alcohol use at all [83, 84] (as outlined in Table 2). As a consequence, all interactions between alcohol and other risk factors, as well as the indirect effects of alcohol use, will be included, as under the counterfactual scenario of no alcohol use these interactions or indirect effects do not take place. Furthermore, in many cases, these interactions lead to widening health inequities, and thus have major policy implications.

Genetics Table 2 provides an overview of the impact of alcohol on NCD categories based on the last Global Status Report on Alcohol and Health [1••], updated using the new estimation methodology for alcohol-attributable ischemic disease mortality and disability [37]. Figures 1 and 2 give the respective

Globally, genetic variations which affect alcohol consumption and NCDs’ risk relationships differ between populations. These genetic interactions are thus relevant for population health and policy [85, 86]. Variations in the genes that encode

Curr Addict Rep (2018) 5:72–85 Table 2 Alcohol-attributable deaths and burden of disease by noncommunicable disease categories—2012

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Disease name

Cancer site Oral cavity and pharynx

Attributable deaths

Attributable YLLs

Attributable YLDs

Deaths AAF (%)

DALYs AAF (%)

89,826

2,923,701

57,816

30%

31%

Esophagus Colorectum

89,006 71,606

2,335,780 1,747,819

18,461 62,157

22% 10%

23% 10%

Liver

86,462

2,604,664

18,444

12%

12%

Pancreas Breast

13,180 41,291

326,115 1,303,873

1591 82,771

4% 8%

4% 8%

Larynx All cancers combined

18,218 409,589

522,525 11,764,477

16,877 258,117

23%

24%

− 30,552

− 686,310

−664,535

− 2%

− 2%

Diabetes mellitus Neuropsychiatric disorders Epilepsy

23,616

1,126,037

1,016,319

12%

10%

107,016

4,115,963

27,891,475

100%

100%

Both neuropsychiatric 130,632 combined Cardiovascular diseases (CVDs) Hypertensive disease 94,714

5,242,000

28,907,794

2,263,465

42,331

8%

10%

204,620 378,757 87,082 15,208

3,391,676 9,638,063 1,579,398 197,344

− 400,476 64,833 60,913 223,045

3% 11% 3% 8%

2% 11% 3% 8%

780,381

17,069,946

− 9354

508,815 24,472 533,287

17,702,083 903,375 18,605,458

236,358 57,507 293,865

50% 25%

50% 27%

1,823,337

51,995,571

28,785,887

Alcohol use disorders

Ischemic heart disease Hemorrhagic stroke Ischemic stroke Conduction disorder and other dysrythmias All CVDs combined Gastrointestinal disorders Liver cirrhosis Pancreatitis Both gastrointestinal disorders combined All NCDs combined

Based on [1••] with corrections of [37] Italic areas are summaries of the above disease categories

the enzymes responsible for the metabolism of alcohol and its carcinogenic metabolite acetaldehyde are hypothesized to modify the risk relationship between alcohol and disease risk, including but not limited to alcohol use disorders [87] which are characterized by heavy drinking over time [88, 89]. Furthermore, there are detrimental effects of acetaldehyde on disease outcomes other than cancer, such as headaches, nausea, tachycardia, and cardiovascular outcomes in general [85, 90]. This section outlines the interactions between alcohol consumption and genetic influences, focusing mainly on cancer outcomes. Variations in the genes that encode the enzymes alcohol dehydrogenase (ADH) and cytochrome (CYP) P450 2E1, which enzymes oxidize ethanol into acetaldehyde, may modify the risk relationship between alcohol and cancer. The gene ADH1B has two common alleles; ADH1B*1 is the predominant allele in most populations, while the ADH1B*2 allele (substitution of arginine to histidine at

residue 47 (rs1229984)) is less common. When compared to the enzymes encoded by ADH1B*2/*2, the enzymes encoded by ADH1B*1/*2 and ADH1B*1/*1 have 1.0 and 0.5% of the oxidation capability, respectively [91]. Thus, people with an ADH1B*2/*2 genotype may have a higher exposure to acetaldehyde following alcohol consumption and a higher risk of cancer. Furthermore, there also may be an interaction between variations in the ADH1B gene and the incidence of coronary heart disease and ischemic stroke [92]. Specifically, in a Mendelian randomization meta-analysis of 56 epidemiological studies, carriers of the ADH1B *1 had lower risks of coronary heart disease and ischemic stroke [92]. The ADH1C gene has two alleles, ADH1C*1 and ADH1C*2, that code for the γ1 and γ2 enzyme subunits, respectively. The enzymes encoded by the ADH1C*1 allele metabolize ethanol into acetaldehyde at 2.5 times the rate of the enzymes encoded by the ADH1C*2 allele [93]. Therefore,

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Neuropsychiatric disorders 10%

Cancer 23%

Gastrointesnal disorders 36%

CVD & Diabetes 31%

Fig. 1 Alcohol-attributable years of life lost in 2012 due to premature mortality resulting from noncommunicable diseases, by cause of death [1••]

drinkers with an ADH1C*1/*2 or ADH1C*1/*1 genotype may have a higher risk of cancer [94–96]. When blood alcohol levels are high, microbes and the CYP2E1 gene metabolize ethanol into acetaldehyde, with this process producing reactive oxygen species (ROS) and leading to the conversion of procarcinogens into carcinogens and retinoic acid into polar metabolites [97–99]. Two-point mutations have been identified upstream of the CYP2E1 gene in regulatory elements at nucleotides − 1259 and − 101 [100] (i.e., the wild-type c1 allele and the c2 variant). Individuals who are c2/c2 have increased transcriptional activity, elevated protein levels, and increased enzyme activity compared to people who are c1/c1, and thus may be at a higher risk of alcohol-related cancers [100]. Furthermore, people who are c2/c2 have been found to have an increased risk of oral cavity and pharyngeal cancers when compared to people who are c1/ c1 [101]. Variations in the gene that encodes the enzyme acetaldehyde dehydrogenase 2 (ALDH2), which oxidizes acetaldehyde into acetate, may also affect the risk of cancer. The Cancer 1%

Gastrointestinal disorders 1%

Neuropsychiatric disorders 98%

Fig. 2 Alcohol-attributable years of life lost in 2012 due to living with a disability resulting from noncommunicable diseases, by disease category [1••]

ALDH2 allele, ALDH2*2 (commonly known as the “flushing gene”) results from a substitution of glutamate to lysine at residue 487. Individuals who are ALDH2*2 homozygous have no ALDH2 activity, while those who are heterozygous have approximately 6% residual activity when compared to people who are ALDH2*1 homozygous. Therefore, drinkers with an ALDH*1/*2 or ALDH2*2/*2 genotype may have a higher risk of cancer [102]. Alcohol consumption inhibits the one-carbon metabolism (OCM) pathway, which is a major donor of methyl groups for DNA methylation [103]. Thus, variations in the methylenetetrahydrofolate reductase (MTHR) gene (C677T (cytosine-tothymine) mutation) which plays a key role in this pathway may increase the risk of cancer among drinkers who have a low dietary intake of folate (as folate is a key nutrient in the OCM pathway). In particular, alcohol drinkers who were homozygous MTHR T/T and who had low dietary folate intakes were observed to be at a higher risk of breast and colorectal cancers when compared to alcohol drinkers who were homozygous MTHR C/C [104, 105]. In sum, there are important interactions between genetic variations and alcohol on NCD outcomes, which have been shown to be relevant for population health [85, 86], and thus for policy.

Blood Pressure The alcohol-cardiovascular disease relationship is complex. Favorable and unfavorable cardiovascular effects from alcohol consumption may be specific to acute and prolonged alcohol consumption (e.g., ischemic heart disease [36]), depending on the amount consumed at a drinking occasion, rather than just total average volume over a week or month. However, most research to date has focused on average volume of alcohol use and disregarded drinking patterns, most importantly irregular heavy drinking occasions (five or more drinks on one occasion for men, four or more for women). Despite strong epidemiological and biological evidence for a causal long-term effect of chronic heavy drinking on the risk for hypertension [106, 107], less is known about the impact of low and moderate alcohol intake on blood pressure (BP). Evidence from observational studies indicates a linear increase in the risk in men, and a threshold effect with no increased risk for one to two drinks in women. There are not enough data to make firm conclusions on potential effect modification by race/ethnicity, but differences have been observed [108, 109]. The negative effect of alcohol on BP is reversible within a few days if consumption is reduced. Systematic experimental evidence from mid- to long-term randomized controlled trials showed that a reduction in alcohol consumption resulted in a reduction of BP in a dose-response relationship, with the largest reduction in BP observed in usual drinkers of 72 g of pure


alcohol per day (five standard drinks) (− 5.5 mmHg SBP, 95% CI − 6.7 to − 4.3) [32]. No effect was observed in usual drinkers of two or less drinks per day. However, there were few data on women, people with hypertension who usually drink moderately, and irregular heavy drinkers, although several observational studies have reported an increase in mortality from hypertension among binge drinkers [110, 111]. Indeed, several studies have suggested that the effect of alcohol on BP depends on the usual drinking pattern, time since the last drink, and time and type of BP measurement [112, 113]. Several questions remain unanswered. Randomized controlled trials have reported conflicting results regarding acute BP changes after ingestion of alcohol, ranging from a decrease [114, 115] to no change [116, 117] to an increase [118, 119]. These contradictory findings may be the result of simultaneously occurring constrictive and dilative effects depending on race/ethnicity, amount of alcohol intake, and time since last drink [120]. Furthermore, cardiovascular disease mortality and morbidity may be reduced at even lower BP levels than what current hypertension guidelines define as hypertension (currently > 140/90 mmHg) [121–123]. That is, even people with a BP reading lower than these values may benefit from lowering their BP. That means that even in people without hypertension, there may be no safe limit in terms of alcohol consumption and the risk for detrimental effects from increased BP. In sum, although there may be a beneficial association of alcohol use with ischemic heart disease (even among people with hypertension [124]), the main risk factor for cardiovascular diseases, namely elevated BP, is negatively impacted by alcohol consumption. As the effect of alcohol on BP is both preventable and reversible, screening and intervention for both risk factors in primary care may provide synergistic health gains [125].

Tobacco Smoking Tobacco smoking is a leading risk factor for the global burden of mortality and disease, with 6.3 million attributable deaths and 155.1 million DALYs lost attributable to tobacco smoke in 2016 [2]. Accordingly, tobacco smoking is also specifically mentioned in the Global Action Plan [7]. Alcohol use and tobacco smoking interact multiplicatively towards the development of several NCDs [126]. Although alcohol-tobacco interactions have been examined for both cardiovascular diseases and cancers, the evidence is most convincing for the latter [126, 127]. Alcohol acts as a solvent for the carcinogens found in tobacco smoke [128], and epidemiological studies have found a multiplicative effect of alcohol and tobacco smoking in the risk of developing oral cavity, pharyngeal, laryngeal, and esophageal cancers [126, 129–132]. There is also some epidemiological evidence

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for an interaction between alcohol consumption and tobacco smoke for other cancer sites [126]. Based on a multicenter case-control analysis of approximately 4000 Europeans, alcohol use and tobacco smoking resulted in a population-attributable risk of 73% for upper aerodigestive tract cancers [129]. Further disaggregation of this population-attributable risk revealed that less than 1% of upper aerodigestive tract cancers were due to alcohol use alone, 29% was due to tobacco smoking alone, and 44% was due to combined alcohol use and tobacco smoking [129]. Given the alcohol- and tobacco-attributable NCD burdens, the interaction between these risk factors, and the observation that people who smoke are more likely to consume relatively heavy amounts of alcohol [133], the alcohol-tobacco interaction is an especially important consideration in NCD prevention policies.

Socioeconomic Status There is an interaction between alcohol use and socioeconomic status on mortality and other serious health problems. Part of the health inequities between different socioeconomic strata is due to alcohol use [134•, 135–137], and current drinkers of lower socioeconomic status reported higher levels of alcohol use and more irregular heavy drinking occasions in some countries [138, 139]. However, the prevalence of abstinence from alcohol use was also found to be higher among people of lower socioeconomic status in many countries [140–142]. Furthermore, differences in alcohol-attributable mortality and morbidity persisted even after adjusting for differences in drinking patterns [143, 144], suggesting interactive effects between alcohol use and socioeconomic status. As of now, only a few studies have investigated interactive and effect modifying aspects of socioeconomic status with regard to alcohol use and NCD risks [145]. Some researchers have hypothesized that the socioeconomic differences in alcohol-attributable mortality might be explained by a clustering of other behavioral risk factors for NCDs, such as smoking, being overweight, or lack of exercise. These other risk factors might have multiplicative effects with alcohol use, putting people of low socioeconomic status at a higher risk [146]. Indeed, the evidence shows a socioeconomic gradient in other NCD risk factors, such as smoking, fruit and vegetable intake, obesity, and physical inactivity (the latter two mainly in high-income countries) [138, 141, 146–148]. A recent study investigated six of the seven major factors for NCD mortality that were identified as priorities in the WHO NCD Global Action Plan [7, 147]. After adjusting for alcohol intake, current smoking, diabetes, physical inactivity, hypertension, and obesity, people of lower socioeconomic status still had a significantly increased mortality risk. For example, the hazard ratio of dying from cardiovascular disease was 1.52 (95% confidence interval 1.37–1.67) before adjustment

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and 1.29 (95% confidence interval 1.16–1.43) after adjustment [147]. The socioeconomic differences observed in the study by Katikireddi and colleagues [143] that investigated alcoholattributable mortality specifically were even larger. After adjusting for alcohol use as well as body mass index and smoking status, people of low socioeconomic status were still over twice as likely to die from an alcohol-attributable cause of death as their counterparts of high socioeconomic status. Overall, the evidence shows that socioeconomic status has to be taken into consideration when investigating associations between alcohol use and NCD, as well as with regard to respective interventions [149]. The interaction between alcohol use and socioeconomic status seems to be crucial for policy development, especially in light of increasing economic inequality [150, 151••] and socioeconomic differences in alcohol-attributable mortality in many countries [134•].

Policy Implications As part of the NCD framework, the WHO has introduced policies which are “best buys” [58, 152]. A “best buy” is a more pragmatic concept introduced into the discussion of interventions for NCD that extends beyond the economic efficiency and cost-effectiveness of an intervention (e.g., [153]). It is defined as an intervention for which there is compelling evidence that it is not only highly cost-effective but is also feasible, low-cost, and appropriate to implement within the constraints of the local resources. For alcohol, the best buys consist of reductions in availability, increases in taxation, and bans on marketing and advertising (for an overview on policy options: [154–157]. Furthermore, implementation of these policies are advocated for in the UN’s Sustainable Development Goals [8••]. However, these policies are not popular with politicians and decision makers, who face opposition by the alcohol industry when implementing these policies, and fear that the population will not support price increases for any consumer goods [156•]. There are a few policy alternatives which may also be effective; however, there is a smaller empirical evidence base for these alternatives than for the best buys. Notably, minimum pricing policies may reduce alcohol-attributable harms [158] and inequities [159]. Furthermore, a reduction of alcohol content in alcoholic beverages, which could be achieved either by producers reducing the strength of alcoholic beverages on their own (e.g., reduction of average strength/alcohol content of beer, wine or spirits by 10%) or by state interventions such as differential taxation that promote these reductions, may reduce alcohol-attributable harms [160]. Given the above interaction with socioeconomic status, new approaches to alcohol policy are needed where the focus is on interventions which not only reduce overall alcoholattributable harm but which also reduce health inequities


[137]. This is especially important given the aforementioned stagnation of life expectancies in the USA, which decline is disproportionally caused by alcohol and substance use in lower socioeconomic and rural strata [67, 68, 161]. Reducing health inequalities within countries [162] is also an important Sustainable Development Goal [8••].

Conclusions Alcohol use has been identified as a major risk factor for population health [70–72] and recognized in major global health strategies, such as the WHO’s Global Action Plan for the Prevention and Control of NCDs 2013–2020 [7]. However, this Global Action Plan is limited, as some of the health effects of alcohol use on NCDs are not covered by the Global Action Plan (such as liver disease or mental disorders). Furthermore, a focus on NCDs also ignores the impact of alcohol on infectious diseases and injuries. This is especially problematic in several high-income countries, where the alcohol-attributable mortality and disease burden that falls outside of the classic NCDs has been increasing and causing a stagnation in life expectancies [67]. Furthermore, current policies, such as the WHO best buys, do not consider interactions between alcohol and other risk factors, and thus there is a need to consider these interactions in future population health strategies. Health inequalities should play a crucial role here.

Compliance with Ethical Standards Conflict of Interest The authors declare that they have no conflict of interest. Human and Animal Rights and Informed Consent This article does not contain any studies with human or animal subjects performed by any of the authors.

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