Awareness of alcohol as a risk factor for cancer is associated with public support for alcohol policies

Awareness of alcohol as a risk factor for cancer is associated with public support for alcohol... Background: Globally, alcohol is causally related to 2.5 million deaths per year and 12.5% of these are due to cancer. Previous research has indicated that public awareness of alcohol as a risk factor for cancer is low and this may contribute to a lack of public support for alcohol policies. The aim of this study was to investigate the relationship between awareness of the alcohol-cancer link and support for a range of alcohol policies in an English sample and policy context. Methods: A cross-sectional survey of 2100 adult residents in England was conducted in which respondents answered questions regarding awareness of the link between alcohol and cancer and support for 21 policy proposals. Principal component analysis (PCA) was used to reduce the 21 policy proposals down to a set of underlying factors. Multiple regression analyses were conducted to estimate the relationship between awareness of the alcohol-cancer link and each of these policy factors. Results: Thirteen per cent of the sample were aware of the alcohol-cancer link unprompted, a further 34% were aware when prompted and 53% were not aware of the link. PCA reduced the policy items to four policy factors, which were named price and availability, marketing and information, harm reduction and drink driving. Awareness of the alcohol-cancer link unprompted was associated with increased support for each of four underlying policy factors: price and availability (Beta: 0.06, 95% CI: 0.01, 0.10), marketing and information (Beta: 0.05, 95% CI: 0.00, 0.09), harm reduction (Beta: 0.09, 95% CI: 0.05, 0.14), and drink driving (Beta: 0.16, 95% CI: 0.11, 0.20). Conclusions: Support for alcohol policies is greater among individuals who are aware of the link between alcohol and cancer. At the same time, a large proportion of people are unaware of the alcohol-cancer link and so increasing awareness may be an effective approach to increasing support for alcohol policies. Keywords: Cancer, Alcohol, Policy, Support Background states which are currently known to be associated with al- The global burden of illness and injury from alcohol con- cohol consumption [2] showing that, among many other sumption is high: alcohol is causally related to over 60 diseases, alcohol consumption plays a causal role in sev- major health conditions, is estimated to be responsible for eral types of cancer. The burden of alcohol-related harm 4.5% of the global burden of disease and injury and ac- is borne across society, for example through health, social counts for 2.5 million deaths a year worldwide [1]. Rehm care, justice and lost productivity costs [3, 4]. For example, and colleagues have listed the range of negative health in the UK in 2009–10 the cost to the National Health Service alone was £3.5 billion and, although the overall cost to society is difficult to estimate, the most widely cited figure, including crime and loss of productivity, is £21 billion a year [5]. Alcohol policy makers charged with * Correspondence: p.f.buykx@sheffield.ac.uk University of Sheffield, 30 Regent Street, Sheffield S1 4DA, UK Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), 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 (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Bates et al. BMC Public Health (2018) 18:688 Page 2 of 11 balancing government revenue generation, industry regu- health), likely positive outcomes of a policy [11] and lation, individual freedom and the burden of alcohol need awareness that alcohol can cause cancer [19] have been to prioritise the high levels of alcohol-related harm. associated with support for alcohol policies. So, aware- Globally, a range of policies are implemented to reduce ness of potential negative outcomes of alcohol consump- alcohol-related harm and promote social wellbeing; for tion may be a relevant factor in understanding public example by altering the drinking context, regulating avail- support for alcohol polices. ability and marketing, providing screening and brief inter- A recent review determined that alcohol is now recog- ventions or more intensive treatment for heavier drinkers, nised as a risk factor for seven types of cancer including protecting those at risk from drinkers’ actions, and enhan- of the liver, mouth and oropharynx and breast [2] how- cing the availability of information about the effects of ever there is an increasing amount of evidence that alco- alcohol [6, 7]. Policies with the strongest evidence of ef- hol has a casual role in other cancers [20] and as such fectiveness and cost-effectiveness are those that increase the list of cancers that are attributed to alcohol may the price of alcohol, and those that restrict availability and grow. Globally, 12.5% of all alcohol-attributable deaths marketing [6, 8]. The evidence that information and and 8.6% of alcohol-attributable Disability Adjusted Life education policies reduce alcohol-related harm is weaker, Years (DALYs) are associated with cancer [1]. Research although these approaches may be used to reduce the supports a linear dose-response relationship with an knowledge deficit and change public opinion on policies increase in average alcohol consumption positively asso- that are more effective and cost-effective [8]. ciated with an increased risk of cancer [21, 22] and even Public support for health-behaviour policy in general low levels of alcohol consumption have been associated has an inverse relationship with the intrusiveness and/or with a small increase in the absolute risk of some types restrictiveness of the policy, with people tending to prefer of cancer [23]. Despite this substantial negative health policies that they perceive to impact other people and not impact, an earlier analysis of the 2015 English popula- themselves [9]. This holds true for alcohol-related policies. tion survey data, on which the analyses in this paper are Internationally, the most effective policies, such as in- also based, found low levels of awareness of the link creasing price and restricting availability tend to be the between alcohol and cancer [24] with awareness varying least supported while those with less evidence of effective- by cancer type, from 18% for breast cancer to 80% for ness, such as education, are better supported [10]. For liver cancer. These findings echoed similarly low levels example, of 10 alcohol policy options presented to 1200 of awareness of the alcohol-cancer link in the UK re- UK adults, self-regulation of alcohol advertising gained ported six years earlier [25] and are also consistent with the most support, whilst a 20–40% reduction in outlets findings from an Australian survey [19]. and a minimum unit price of £1 were the least popular Awareness that alcohol is a risk factor for cancer has policy options [11]. Furthermore, support for increased been associated with greater support for alcohol policies tax and earlier closing times declined in Ireland between in the domains of pricing and taxation, availability, mar- 2002 and 2010, suggesting falling support for effective pol- keting and labelling in Australia [19]. While there has icies in that country [12]. The lack of public support may been some research within the North-east of England contribute to the limited political enthusiasm for some of that has examined the impact of a mass-media campaign the policies with the strongest evidence of effectiveness on awareness of the link between alcohol and cancer and cost-effectiveness by decision makers [13]; in short, and policy support [26], the authors of the current governments are likely to be sensitive to public attitudes paper were not able to locate any UK-based research towards policy options [9]. that has directly examined the relationship between There are several factors that are associated with awareness of the increased risk of cancer and support support for effective alcohol policies. Being female, for alcohol-related policies. Therefore, the aim of the increasing age and consuming none or lower levels of study was to assess which factors are associated with alcohol, compared to high levels, are associated with support for different alcohol policies, including aware- higher levels of support for more effective policies [11, ness of the alcohol-cancer link, in an English sample 14–17]. A higher level of education is associated with using policy options of relevance to current UK policy greater support for increasing price [16], promotion of context. limits and warnings, and controlling public spaces [18], and is associated with lower support for restricting avail- ability and greater law enforcement [16]. However, Methods demographic factors are largely non-modifiable. Modifi- Recruitment able factors such as knowledge have also been associated A cross-sectional online survey of 2100 adults was with support for alcohol policy. For example, knowledge conducted in England in July 2015. The sample size was of the domain specific (e.g. impact on crime, impact on determined by a pragmatic judgement and no power Bates et al. BMC Public Health (2018) 18:688 Page 3 of 11 calculations were conducted. The survey included items Measures on smoking and drinking behaviour, support for/oppos- To assess support for alcohol policies, respondents were ition to alcohol policy options, awareness of health condi- asked ‘To reduce the problems associated with excessive tions associated with alcohol use, and socio-demographic alcohol use, to what extent would you support or oppose information. A market research company (Vision One) each of the following policies…?’ followed by a list of 21 invited existing panel members aged 18 and over to par- alcohol-related policy options (Fig. 1). The question ticipate in a survey on ‘health and lifestyle behaviours'. originated from the Australian National Drug Strategy Quota sampling was used to ensure the sample was na- Household survey [28]. Six of the policy options repli- tionally representative with respect to age, sex, geographic cated those used in the Australian survey and the region and education. Of the 11,846 members that were remainder were adapted from a recent UK study [16]or sent an email invitation to participate, 5929 started the devised for this survey (see project report) [29] and survey. Following screening for quotas based on the popu- covered a range of policy domains (pricing, availability, lation distribution of sex (male/female), age (18–19, 20– drink driving counter measures, industry responsibility, 29, 30–39, 40–49, 50–59, 60+), region (North, Midlands labelling, advertising/marketing). Respondents recorded and London/South) and education (no qualifications, their response on a 5-point Likert scale (strongly oppose, below degree level, degree level and above) within Eng- oppose, neither support or oppose, support, strongly land, 2480 eligible respondents commenced the survey, of support). Awareness of the link between alcohol and whom 380 were subsequently excluded due to incomplete cancer was measured firstly in an open question; or invalid responses. To adjust for under-sampling of re- “Which, if any, health conditions do you think can result spondents without qualifications, sample weights were from drinking too much alcohol?”. Respondents were created with reference to the England and Wales 2011 then presented with a list of health conditions including census data [27] (see Table 1). cancer and asked “Which, if any, of the following health conditions can result from drinking too much alcohol?” (yes, no, don’t know). Using these two questions, re- spondents were categorised into those that listed cancer Table 1 Sociodemographic characteristics of the sample and weights applied (N = 2100) in the open question (awareness unprompted), those that selected ‘yes’ in the closed questions, but had not Unweighted Weights Applied already listed cancer in the open question (awareness N % N % prompted) and those that did not list cancer when Age prompted and selected ‘no’ or ‘don’t know’ in the closed 18–19 63 3.0 62 3.0 section. 20–29 339 16.1 325 15.5 Demographic information including age, gender, educa- 30–39 351 16.7 332 15.8 tion (none, below degree and degree or above) and post- 40–49 394 18.8 385 18.3 code was collected. Postcode data were used to identify 2015 Index of Multiple Deprivation (IMD) quintile, an 50–59 334 15.9 330 15.7 area-based deprivation measure calculated for 32,844 60+ 619 29.5 667 31.8 areas within England, which combines information from 7 Gender weighted domains; income deprivation (weighting factor Male 1021 48.6 1030 49.0 22.5%), employment deprivation (22.5%), education, skills Female 1079 51.4 1070 51.0 and training deprivation (13.5%), health deprivation and IMD Quintile disability (13.5%), crime (9.3%), barriers to housing and services (9.3%) and living environment deprivation (9.3%) Least deprived 362 17.2 349 16.6 [30]. IMD quintiles (least deprived, low deprivation, aver- Low deprivation 356 17.0 350 16.7 age, high deprivation, most deprived) were based on the Average 430 20.5 426 20.3 national ranking rather than the ranking within the High Deprivation 469 22.3 474 22.6 sample. Smoking status was assessed as never-smoker, Most Deprived 461 22.0 479 22.8 ex-smoker, or current (occasional or daily) smoker. Qualification Alcohol consumption was measured using the three-item consumption scale of the Alcohol Use Disorders Test None 178 8.5 315 15.0 (AUDIT-C) which assesses past year frequency and quan- Below degree 1238 59.0 1155 55.0 tity of any alcohol consumption and frequency of heavy Above degree 684 32.6 630 30.0 drinking [31]. AUDIT-C scores were categorised into Sample weights were created with reference to the England and Wales 2011 abstainers (0), lower risk drinkers (1–4), increasing risk census data to increase distribution fit between the sample and the population regarding level of qualification drinkers (5–8) and highest risk drinkers (9–12). Bates et al. BMC Public Health (2018) 18:688 Page 4 of 11 Fig. 1 Percentage of participants that support/oppose alcohol policies Statistical analyses sizes of over 250 and when the average communality is Data analyses were conducted using SPSS version 22 for 0.6 or larger [32]. Thirdly, to identify predictors of policy Windows. Analysis involved three stages. Firstly, descrip- support, four linear regression analyses were conducted tive analyses were carried out to determine proportion with the PCA factor scores as dependent variables. Age, of support in each of the demographic, health behaviour age (entered as continuous variables), gender, IMD quin- and knowledge categories. Secondly, given the large tile (5 categories from least deprived to most deprived), number of policy items included, Principal Component qualifications (no qualifications, qualifications below de- Analysis (PCA) was conducted to reduce these to fewer gree level, degree and above), smoking (never-smoker, factors which underlie patterns of support for individual ex-smoker, current smoker), alcohol consumption (highest policy items. The reduction to fewer factors may aid as- risk drinker, increasing risk, lower risk, abstainer), and sessment of generalisability of results to other policies cancer awareness (none, prompted, unprompted) were not included and avoids increasing the risk of type 1 entered as independent variables. Scatter plots of age and error by running several analyses. Theoretically there support for the four policy factors indicated that the could be correlation between support for one group of relationship may be quadratic and so age was included to policy items and another group so oblique rotation (pro- account for this possibility. max) was used to allow correlation between factors [32]. Sensitivity analysis was undertaken by introducing two The PCA generates a score for each individual on each sets of variables which were not considered in the initial factor. The Kaiser-Meyer-Olkin (KMO) measure was analysis but were highlighted by a reviewer as factors that used to assess whether there was an adequate sample could impact on policy support. The first was awareness size and if KMO values for individual policy items was of the link between alcohol and other diseases. There was above the acceptable limit of 0.5 [32]. Bartlett’s test was greater awareness of the link between alcohol and other run to indicate whether correlation between policy items diseases (heart disease, diabetes, liver disease, high choles- were sufficient for PCA. Kaiser’s criterion, an eigenvalue terol or overweight/obesity) than cancer [24]. The second above one, was used to determine which factors to retain was any history of a cancer diagnosis. These were both for further analyses. This criterion is reliable in sample included as covariates to examine whether controlling for Bates et al. BMC Public Health (2018) 18:688 Page 5 of 11 these impacted on the association between awareness of Bartlett’s test for sphericity was significant indicating the the alcohol-cancer link and policy support. correlations between policy items were sufficient for PCA. The Kaiser criterion was satisfied for the four pol- Results icy factors. The policy item Banning alcohol consump- The demographic characteristics are displayed in Table tion on trains had a factor loading of below 0.4 on all 1. One third (31.4%) of the respondents were current factors and there was no change to the factor structure smokers, 24.9% were ex-smokers and 43.7% were when running the PCA without the item so it was re- non-smokers. The proportions of respondents reporting moved. The factors explained 65.5% of the variance. highest risk, increasing risk, and lower risk drinking Table 2 shows the factor structure and loadings. The were 9.8, 31.5 and 46.8% respectively with 11.9% report- four factors identified were labelled Price and Availabil- ing no alcohol use. When asked about health conditions ity, Marketing and Information, Harm Reduction and related to drinking too much, 12.9% listed cancer un- Drink Driving based on the policy items in each factor. prompted and a further 34.3% selected ‘yes’ when cancer The degree of support for each policy option is pre- was listed as one of a number of potential health condi- sented in Fig. 1, ordered from most to least supported. tions resulting from drinking too much. The remaining The mean factor score for each variable of interested is 52.8% selected ‘no’ or ‘don’t know’. displayed in Table 3. Multiple regression analyses (Table 4) The PCA analysis revealed that there were correlations demonstrated that awareness of the relationship between between factors of over 0.5 confirming that orthogonal alcohol consumption and cancer (unprompted) was rotation would be inappropriate. The KMO measure in- significantly associated with support for all policy factors. dicated an adequate sample size and all KMO values for A significant association was also found for prompted individual policy items were above the acceptable limit. cancer awareness for all policy factors except drink Table 2 Principal Component analysis of 21 alcohol policy items – reduced to four factors Policy Item Price and Marketing and Harm Drink Availability Information Reduction driving Increasing the price of alcohol .872 −.149 .161 .006 Taxing alcoholic drinks on the basis of the percentage of alcohol they contain .834 −.128 .207 −.023 Reducing hours alcohol can be sold within off-licenses and supermarkets .772 .196 −.162 .004 Setting a minimum unit price below which a unit of alcohol cannot be sold .771 −.027 .177 −.037 Reducing the number of outlets that sell alcohol .754 .257 −.170 −.056 Reducing trading hours for all pubs and clubs .753 .157 −.192 .026 Banning outdoor advertising of alcohol such as on bill boards and bus stops .116 .899 −.117 −.087 Limiting advertising for alcohol on TV until after 9.00 pm −.050 .833 .082 −.019 Restricting the display of alcohol in shops and supermarkets to dedicated aisles .134 .773 .036 −.081 (e.g. not in the entrance) Banning alcohol sponsorship of sporting events .165 .697 −.182 .086 Requiring information on national drinking guidelines on all alcohol containers −.086 .607 .426 −.068 Specific health warnings on alcohol containers (e.g. like on tobacco packaging) .012 .580 .334 −.037 Banning having alcohol available to drink at school events where children are .057 .553 −.155 .324 present, such as fetes Making it compulsory that the number of alcohol units in a bottle or can of −.189 .525 .494 .038 alcoholic drink be shown on the label Increasing funding for alcohol treatment services −.036 −.131 .793 −.041 Introducing and promoting lower strength wine and lower strength or no .316 −.046 .552 .099 alcohol beer Doctors or health professionals ask patients about their drinking habits and, −.065 .393 .502 .045 where necessary, offer advice on how to reduce their alcohol consumption Offering and promoting smaller drink sizes in pubs and restaurants .396 .014 .441 .078 Reducing the drink driving limit −.017 −.101 −.010 .917 Introducing random breath alcohol testing for drivers −.037 .118 .068 .719 Banning alcohol consumption on trains had a factor loading below 0.4 and when removed from the analysis no change in the factor structure was observed and so was not included Bates et al. BMC Public Health (2018) 18:688 Page 6 of 11 Table 3 Mean factor based scores by variables of interest Sample Characteristic Factor Score Price and Availability Marketing and Information Harm Reduction Drink driving Mean Sd Mean Sd Mean Sd Mean Sd Age 18–34 − 0.08 0.98 − 0.14 0.94 0.07 0.99 −0.11 0.95 35–49 − 0.06 0.97 − 0.08 0.98 0.01 0.98 0.03 0.97 50–64 − 0.01 1.02 0.11 0.98 − 0.01 0.99 0.07 1.05 65+ 0.18 1.02 0.13 1.09 −0.09 1.04 0.01 1.03 Gender Male −0.11 1.00 −0.15 1.02 −0.14 1.04 −0.16 1.05 Female 0.11 0.99 0.15 0.96 0.14 0.94 0.16 0.93 IMD quintile Least deprived −0.04 0.93 −0.01 0.97 0.11 0.89 −0.06 0.95 Low deprivation −0.01 0.99 −0.03 1.02 − 0.05 1.03 −0.00 1.03 Average 0.03 1.00 0.04 0.98 −0.01 0.95 0.07 0.98 High Deprivation −0.02 1.02 0.01 0.99 −0.02 1.08 −0.03 1.01 Most Deprived 0.02 1.04 −0.02 1.03 − 0.03 1.01 0.02 1.02 Qualification None 0.16 1.10 0.14 1.18 −0.14 1.11 0.18 1.06 Below degree −0.06 0.97 − 0.05 0.96 −0.05 0.98 − 0.06 0.99 Above degree 0.02 1.00 0.02 0.98 0.14 0.97 0.02 0.99 Smoking Status Non smoker 0.10 0.99 0.07 0.94 0.09 0.98 0.01 0.99 Ex Smoker 0.01 0.94 0.09 1.00 −0.06 0.97 0.09 0.97 Smoker −0.14 1.05 −0.15 1.05 −0.07 1.04 −0.08 1.03 Alcohol Consumption None 0.86 0.92 0.59 0.92 0.38 0.95 0.36 0.97 Lower risk 0.15 0.92 0.13 0.96 0.07 0.96 0.10 0.95 Increasing risk −0.35 0.91 −0.27 0.95 − 0.13 0.97 − 0.20 1.00 Highest risk −0.49 0.95 −0.36 1.02 −0.30 1.17 −0.21 1.06 Cancer knowledge None −0.06 0.99 −0.08 0.99 −0.15 0.98 −0.06 0.98 Prompted 0.04 1.03 0.01 1.03 0.08 1.01 0.02 1.04 Unprompted 0.13 0.96 0.26 0.89 0.36 0.94 0.16 0.97 driving. Being female and lower levels of alcohol con- policies. Education above degree level was associated sumption were associated with support for all four policy with greater support for harm reduction policies and factors. Alcohol consumption was the strongest pre- education below degree level was associated with lower dictor of support for price and availability, marketing support for drink driving policies in comparison to no and information,and harm reduction policies; higher qualifications. For each of the policy types, the effect levels of alcohol consumption were associated with size of the association between awareness of the lower levels of support excluding the highest risk alcohol-cancer link and support for policies was small group. This highest risk group was associated with (Pearson coefficient ranged from 0.06 to 0.15). Of all lower support than the none/low risk groups but the policy types, the cancer awareness variable had the greater support than the increasing risk group. Increas- largest relative contribution to the degree of support ing age was the strongest predictor of drink driving for the harm reduction policies. Being an ex-smoker Bates et al. BMC Public Health (2018) 18:688 Page 7 of 11 Table 4 Multiple regression analyses – Variables predicting support for alcohol policy factor scores Price and Availability Marketing and Information Harm Reduction Drink driving Beta 95% CI P value Beta 95% CI P value Beta 95% CI P value Beta 95% CI P value Age −0.09 −0.37 0.19 0.52 0.13 −0.15 0.41 .350 −0.02 −0.32 0.29 .898 0.49 0.20 0.79 < 0.001 Age^2 0.18 0.18 0.18 0.21 −0.02 −0.16 0.00 .909 −0.01 −0.16 0.00 .922 −0.46 −0.46 0.05 < 0.001 Gender Male Female 0.05 0.01 0.09 0.02 0.11 0.07 0.16 < 0.001 0.09 0.04 0.13 < 0.001 0.13 0.09 0.18 < 0.001 IMD Quintile Least deprived Low deprivation 0.01 −0.04 0.06 −0.67 −0.01 −0.06 0.05 0.84 −0.05 −0.11 0.00 0.07 0.02 −0.04 0.08 0.47 Average 0.02 −0.03 0.08 .043 0.03 −0.03 0.08 0.39 −0.05 −0.10 0.01 0.11 0.05 −0.01 0.11 0.09 High Deprivation 0.01 −0.05 0.07 0.76 0.02 −0.04 0.07 0.56 −0.04 −0.10 0.01 0.14 0.01 −0.05 0.07 0.84 Most Deprived 0.05 −0.01 0.11 0.10 0.03 −0.03 0.09 0.27 −0.04 −0.10 0.02 0.18 0.04 −0.02 0.10 0.24 Qualification None Below degree 0.01 −0.05 0.07 0.80 0.00 −0.14 0.14 0.99 0.04 −0.04 0.11 .327 −0.09 −0.16 −0.02 0.02 Above degree 0.06 −0.01 0.13 0.09 0.05 −0.02 0.12 0.20 0.11 0.04 0.18 .003 −0.03 − 0.11 0.04 0.38 Smoking Status Non smoker Ex Smoker −0.01 − 0.06 0.03 0.55 0.02 −0.03 0.07 0.38 −0.02 −0.07 0.03 .445 0.06 0.01 0.11 0.02 Smoker −0.01 −0.06 0.04 0.67 −0.01 −0.06 0.04 0.58 −0.01 −0.06 0.05 .858 0.01 −0.04 0.06 0.66 Alcohol None Lower risk −0.35 −0.42 −0.28 < 0.001 −0.22 −0.29 −0.14 < 0.001 −0.15 −0.22 −0.07 < 0.001 −0.11 −0.19 −0.04 < 0.001 Increasing risk −0.55 −0.62 −0.48 < 0.001 −0.37 −0.44 −0.30 < 0.001 −0.24 −0.32 −0.17 < 0.001 −0.23 −0.30 −0.15 < 0.001 Highest risk −0.40 −0.45 −0.34 < 0.001 −0.26 −0.32 −0.20 < 0.001 −0.19 −0.25 −0.13 < 0.001 −0.15 −0.21 −0.09 < 0.001 Alcohol-cancer Awareness None Prompted 0.05 0.01 0.10 0.02 0.05 0.00 0.09 0.04 0.09 0.05 0.14 < 0.001 0.04 −0.01 0.08 0.12 Unprompted 0.06 0.01 0.10 0.01 0.11 0.06 0.15 < 0.001 0.16 0.11 0.20 < 0.001 0.07 0.02 0.11 < 0.001 p value representing significance are set in italics Bates et al. BMC Public Health (2018) 18:688 Page 8 of 11 was associated with higher support for drink driving associated with support for smoking policies [34]. It is policies. Deprivation was not associated with support likely that the widespread awareness of health risks as- forany of thepolicyfactors. sociated with smoking contributed to the public sup- port for restrictive tobacco policies [35]. In comparison, Sensitivity analysis the awareness of the alcohol-cancer link is low and thus Respondents that identified a link between alcohol and there is a need to increase awareness to allow the public at least one of heart disease, diabetes, liver disease, high to form informed opinions regarding alcohol policies. cholesterol or overweight/obesity were compared to Efforts to improve awareness of the alcohol-cancer link those who did not identify any of these links. This may contribute to decreasing the knowledge deficit. There awareness was significantly associated with three policy is some evidence that public campaigns can increase pub- factors (marketing and information, harm reduction and lic awareness of the link between alcohol and cancer [24]. drink driving), but the inclusion of this variable within In the North-east of England, people who were exposed to the regression had very little impact (change less than a mass-media campaign to raise awareness were more or equal to 0.01) on the size of the standardised coeffi- aware of the link between alcohol and cancer than those cient of the awareness unprompted of the who had not and support for alcohol policies increased alcohol-cancer link association. However, for the mar- following the campaign [26]. In Denmark, a week-long an- keting and information factor, the awareness of the nual alcohol campaign run over 10 years increased public alcohol-cancer link only when prompted was reduced knowledge of safe drinking limits [36]. Within this study, to non-significance. Whether or not respondents re- it is not known whether increased awareness has an ported a cancer diagnosis was not significantly associ- impact on support for policies; however, Pechey and ated with policy support and inclusion of these colleagues have demonstrated that preferences for policies variables did not impact on the coefficients of the could be altered if the probable positive outcomes are awareness of the alcohol-cancer link association. presented alongside the policy [11]. For example, the popularity of minimum unit pricing policies was much Discussion greater (supported by an additional one-fifth of partici- Awareness of alcohol as a risk factor for cancer is associ- pants) when all probable positive outcomes were pre- ated with greater support for four different types of pol- sented compared to when no outcomes were presented. A icies: Price and Availability and Marketing and study conducted in New Zealand found that public sup- Information, Harm Reduction and Drink Driving. This port for alcohol control policies was maintained in com- study used a three-category variable to distinguish be- munities exposed to alcohol-related health promotion tween those that were aware of the alcohol-cancer link media campaigns and community-based intervention ac- unprompted and prompted. This enabled the authors to tivities whereas it declined in those communities without identify that unprompted cancer awareness is a stronger any such intervention [37]. Together, these studies suggest predictor of support for alcohol policies across all four that public awareness of the health risks of alcohol con- factors compared with both those who indicated their sumption can be increased and that increased awareness awareness when prompted or those who were not aware may have an impact on public support for alcohol policy, of the risk. Being female and lower levels of alcohol con- particularly where there is a clear description of antici- sumption were also both associated with higher levels of pated policy effects. However, attempts to raise public support for all policies. awareness may be resisted by alcohol-funded organisa- These findings are broadly consistent with previous tions as has been reported to have occurred recently in re- Australian research, which identified 1) that a similar pro- sponse to warning labels on alcohol products in Canada portion of the population were aware (either prompted or [38]. Although there is evidence to indicate that increased unprompted) that alcohol is a risk factor for cancer, and 2) awareness does not necessarily reduce actual consumption that awareness alcohol consumption can cause cancer is of alcohol [39], this study indicates that awareness is associated with support for pricing, availability, marketing associated with greater support for policies and thus has and labelling polices [19]. Similarly a British survey that the potential to reduce alcohol-related harm indirectly indicated awareness of the link between alcohol and can- through generating an environment where restrictive pol- cer was around 50% in 2015 [33]. We were able to build icies are more likely to be implemented. on this study by examining differential effects of alterna- This study has limitations; the respondents were re- tive measures of awareness and using PCA in order to cruited from an existing market research panel and there- examine support for different policy types, thereby in- fore membership of the sampling frame is self-selecting creasing the potential generalisability of our results. The and limited to those who have access to, and are confident findings also reflect results from tobacco-control research using, the internet. Furthermore, of the people that in which knowledge of the negative impact of smoking is received the email, only approximately 50% started the Bates et al. BMC Public Health (2018) 18:688 Page 9 of 11 survey and information is not available about those that policies in the North-East of England [26] future prospect- did not respond so any potential differences between the ive research could usefully examine whether exposure to responders and non-responders is not known. These fac- information and an increase in awareness, is associated tors may have generated a selection bias. However, quota with a change in policy support in a wider population. sampling was used with the aim of creating a representa- This would help us to develop a better understanding of tive sample of England based on age, gender, region, and how increasing awareness might change public opinion on education level and weights were applied to adjust for dif- effective policies that are politically challenging to imple- ferences between the sample and the population in order ment (e.g. minimum unit pricing). Future research could to maximise the generalisability of the study findings. The examine the combined effect of increased awareness of analyses focussed on awareness of alcohol as a risk factor the general health risks of alcohol in addition to providing for cancer in general and did not examine whether aware- more detailed information about anticipated policy effects. ness of the risk of certain cancers are stronger or weaker Finally, future research could examine health or other predictors of support for policies, especially as awareness risks not only to the individual but also people close to of the role of alcohol as a risk factor varies depending on them as a predictor of policy support. A previous study the type of cancer [40]. Further, the policy items presented examining support for restrictions on tobacco found were simply descriptive (e.g. ‘increasing the price of alco- awareness of the potential harm to others strongly pre- hol’) and did not detail what the anticipated policy effects dicted support [34] and it may be that a similar relation- might be and for whom. Including likely positive out- ship exists for alcohol. comes of a policy has been associated with preferences for alcohol policy and thus this may have impact on outcomes Conclusions [11] .Support for policy may also be influenced by per- The extent to which any individual supports a govern- sonal experience. Greater support has been found among ment policy is dependent on a range of factors including those who have experienced alcohol related-harm or the behaviour the policy targets (e.g. smoking, alcohol alcohol-related disturbance [41] and so those who have consumption), the type of policy and how intrusive it is experience of alcohol-attributable cancer may report (e.g. taxation, regulation), who the policy targets (e.g. greater support for policy. This may have confounded the children), and the extent to which the individual in association found between awareness and support for pol- question will be affected by the policy. Some predictors icy. Although information about the type of cancer (i.e. of support for policies are modifiable. Awareness, and es- whether it was alcohol-attributable) and personal experi- pecially unprompted awareness, of the link between alco- ence of cancer other than a personal diagnosis (i.e. a diag- hol consumption and cancer may be one such modifiable nosis of a friend or family) was not available, the impact of predictor, given that awareness of the risk is a significant any cancer diagnosis was controlled for in sensitivity ana- predictor of support for range of alcohol policies. There- lysis and this did not have an impact on the association fore, improving awareness of the link between alcohol between alcohol-cancer awareness and policy support. Fi- consumption and cancer may increase public support for nally, we cannot be certain that reported support repre- effective alcohol policies that are otherwise relatively un- sents actual support however any increase in support may popular. These results are useful for policy-makers, be- create environment in which these policies are more likely cause it highlights that understanding of a policy and its to be implemented. context is an important determinant of support and that Whilst the methods used in the PCA were directed increasing awareness of the specific harms being ad- by research recommendations [32], alternative methods dressed may result in greater support for alcohol policies. could be employed relating to, amongst other things, rotation method and factor selection. Several alterna- Acknowledgements We would like to thank the Policy and Information Sounding Board at tive methods were examined, but they did not have an Cancer Research UK who took part in developing and testing the survey and appreciable impact on the findings reported here. Like- Melanie Lovatt and Petra Meier for their contribution to survey development. wise, alternative regression methods could have been We acknowledge that the survey reported in this study replicates and extends on a survey originally conducted in Australia by the Cancer Council NSW. employed, however, the distribution of the dependent variables would strongly suggest that linear regression Funding is the most appropriate method, and this approach is This work was supported by Policy Research Centre for Cancer Prevention, commonplace among other analogous studies. Cancer Research UK. The authors are solely responsible for the content of this paper. Several potential future research questions arise from this study. The study was cross-sectional. While previous Availability of data and materials research has demonstrated that alcohol-awareness cam- The data that support the findings of this study are available from CRUK but paigns can raise awareness of the link between alcohol restrictions apply to the availability of these data, which were used under and cancer [39] and can increase support for alcohol licence for the current study, and so are not publicly available. Data are Bates et al. BMC Public Health (2018) 18:688 Page 10 of 11 however available from the authors upon reasonable request and with 16. Li J, Lovatt M, Eadie D, Dobbie F, Meier P, Holmes J, Hastings G, permission of CRUK. MacKintosh AM. Public attitudes towards alcohol control policies in Scotland and England: results from a mixed-methods study. Soc Sci Authors’ contributions Med. 2017;177:177–89. SB, PB, JH and SD conceptualised the study. PB, JL, LG, LH, EGM & JH 17. NatCen Soc Res: Attitudes to alcohol - Findings from the 2015 British Social contributed to survey development; PB prepared ethics; PB, LG & LH Attitudes survey. In.; 2015. undertook stakeholder engagement; SB, PB, JH & SD contributed to analyses 18. Wilkinson C, Room R, Livingston M. Mapping Australian public opinion and interpretation; SB, PB, JL, LG, LH, EGM, SD, BW & JH contributed to on alcohol policies in the new millennium. Drug Alcohol Rev. 2009; writing. All authors read and approved the final manuscript. 28(3):263–74. 19. Buykx P, Gilligan C, Ward B, Kippen R, Chapman K. Public support for Ethics approval and consent to participate alcohol policies associated with knowledge of cancer risk. Int J Drug Policy. This project was approved by the ScHARR ethics committee, University of 2015;26(4):371–9. Sheffield (project ID: 03670). A market research company (Vision One) invited 20. Zhao J, Stockwell T, Roemer A, Chikritzhs T. Is Alcohol consumption a risk existing panel members to participate in the study. If they selected the link factor for prostate cancer? A systematic review and meta-analysis. BMC Cancer; to the survey, they were directed to an information page about the study 2016;16:1–13. Available from: https://doi.org/10.1186/s12885-016-2891-z and provided consent by selecting the link to begin the survey. 21. Bagnardi V, Blangiardo M, La Vecchia C, Corrao G: A meta-analysis of alcohol drinking and cancer risk. Br J Cancer 2001, 85(11):1700. Competing interests 22. Ellison RC, Zhang Y, McLennan CE, Rothman KJ. Exploring the relation The authors declare that they have no competing interests. of alcohol consumption to risk of breast Cancer. Am J Epidemiol. 2001; 154(8):740–7. 23. Bagnardi V, Rota M, Botteri E, Tramacere I, Islami F, Fedirko V, Scotti L, Jenab M, Publisher’sNote Turati F, Pasquali E, et al. Alcohol consumption and site-specific cancer risk: a Springer Nature remains neutral with regard to jurisdictional claims in comprehensive dose–response meta-analysis. Br J Cancer. 2015;112:580–93. published maps and institutional affiliations. 24. Buykx P, Li J, Gavens L, Hooper L, Lovatt M. Gomes de Matos E, Meier P, Holmes J: public awareness of the link between alcohol and cancer in Author details England in 2015: a population-based survey. BMC Public Health. 2016; 1 2 University of Sheffield, 30 Regent Street, Sheffield S1 4DA, UK. Institut für 16(1):1194. Therapieforschung, Munich, Germany. Monash University, Bendigo 3550, 25. Sanderson SC, Waller J, Jarvis MJ, Humphries SE, Wardle J. Awareness of 4 5 Australia. Cancer Research UK, London, UK. dosomething.org, New York, lifestyle risk factors for cancer and heart disease among adults in the UK. USA. Patient Educ Couns. 2009;74(2):221–7. 26. Martin N, Buykx P, Shevills C, Sullivan C, Clark L, Newbury-Birch D. 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Awareness of alcohol as a risk factor for cancer is associated with public support for alcohol policies

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Medicine & Public Health; Public Health; Medicine/Public Health, general; Epidemiology; Environmental Health; Biostatistics; Vaccine
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Abstract

Background: Globally, alcohol is causally related to 2.5 million deaths per year and 12.5% of these are due to cancer. Previous research has indicated that public awareness of alcohol as a risk factor for cancer is low and this may contribute to a lack of public support for alcohol policies. The aim of this study was to investigate the relationship between awareness of the alcohol-cancer link and support for a range of alcohol policies in an English sample and policy context. Methods: A cross-sectional survey of 2100 adult residents in England was conducted in which respondents answered questions regarding awareness of the link between alcohol and cancer and support for 21 policy proposals. Principal component analysis (PCA) was used to reduce the 21 policy proposals down to a set of underlying factors. Multiple regression analyses were conducted to estimate the relationship between awareness of the alcohol-cancer link and each of these policy factors. Results: Thirteen per cent of the sample were aware of the alcohol-cancer link unprompted, a further 34% were aware when prompted and 53% were not aware of the link. PCA reduced the policy items to four policy factors, which were named price and availability, marketing and information, harm reduction and drink driving. Awareness of the alcohol-cancer link unprompted was associated with increased support for each of four underlying policy factors: price and availability (Beta: 0.06, 95% CI: 0.01, 0.10), marketing and information (Beta: 0.05, 95% CI: 0.00, 0.09), harm reduction (Beta: 0.09, 95% CI: 0.05, 0.14), and drink driving (Beta: 0.16, 95% CI: 0.11, 0.20). Conclusions: Support for alcohol policies is greater among individuals who are aware of the link between alcohol and cancer. At the same time, a large proportion of people are unaware of the alcohol-cancer link and so increasing awareness may be an effective approach to increasing support for alcohol policies. Keywords: Cancer, Alcohol, Policy, Support Background states which are currently known to be associated with al- The global burden of illness and injury from alcohol con- cohol consumption [2] showing that, among many other sumption is high: alcohol is causally related to over 60 diseases, alcohol consumption plays a causal role in sev- major health conditions, is estimated to be responsible for eral types of cancer. The burden of alcohol-related harm 4.5% of the global burden of disease and injury and ac- is borne across society, for example through health, social counts for 2.5 million deaths a year worldwide [1]. Rehm care, justice and lost productivity costs [3, 4]. For example, and colleagues have listed the range of negative health in the UK in 2009–10 the cost to the National Health Service alone was £3.5 billion and, although the overall cost to society is difficult to estimate, the most widely cited figure, including crime and loss of productivity, is £21 billion a year [5]. Alcohol policy makers charged with * Correspondence: p.f.buykx@sheffield.ac.uk University of Sheffield, 30 Regent Street, Sheffield S1 4DA, UK Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), 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 (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Bates et al. BMC Public Health (2018) 18:688 Page 2 of 11 balancing government revenue generation, industry regu- health), likely positive outcomes of a policy [11] and lation, individual freedom and the burden of alcohol need awareness that alcohol can cause cancer [19] have been to prioritise the high levels of alcohol-related harm. associated with support for alcohol policies. So, aware- Globally, a range of policies are implemented to reduce ness of potential negative outcomes of alcohol consump- alcohol-related harm and promote social wellbeing; for tion may be a relevant factor in understanding public example by altering the drinking context, regulating avail- support for alcohol polices. ability and marketing, providing screening and brief inter- A recent review determined that alcohol is now recog- ventions or more intensive treatment for heavier drinkers, nised as a risk factor for seven types of cancer including protecting those at risk from drinkers’ actions, and enhan- of the liver, mouth and oropharynx and breast [2] how- cing the availability of information about the effects of ever there is an increasing amount of evidence that alco- alcohol [6, 7]. Policies with the strongest evidence of ef- hol has a casual role in other cancers [20] and as such fectiveness and cost-effectiveness are those that increase the list of cancers that are attributed to alcohol may the price of alcohol, and those that restrict availability and grow. Globally, 12.5% of all alcohol-attributable deaths marketing [6, 8]. The evidence that information and and 8.6% of alcohol-attributable Disability Adjusted Life education policies reduce alcohol-related harm is weaker, Years (DALYs) are associated with cancer [1]. Research although these approaches may be used to reduce the supports a linear dose-response relationship with an knowledge deficit and change public opinion on policies increase in average alcohol consumption positively asso- that are more effective and cost-effective [8]. ciated with an increased risk of cancer [21, 22] and even Public support for health-behaviour policy in general low levels of alcohol consumption have been associated has an inverse relationship with the intrusiveness and/or with a small increase in the absolute risk of some types restrictiveness of the policy, with people tending to prefer of cancer [23]. Despite this substantial negative health policies that they perceive to impact other people and not impact, an earlier analysis of the 2015 English popula- themselves [9]. This holds true for alcohol-related policies. tion survey data, on which the analyses in this paper are Internationally, the most effective policies, such as in- also based, found low levels of awareness of the link creasing price and restricting availability tend to be the between alcohol and cancer [24] with awareness varying least supported while those with less evidence of effective- by cancer type, from 18% for breast cancer to 80% for ness, such as education, are better supported [10]. For liver cancer. These findings echoed similarly low levels example, of 10 alcohol policy options presented to 1200 of awareness of the alcohol-cancer link in the UK re- UK adults, self-regulation of alcohol advertising gained ported six years earlier [25] and are also consistent with the most support, whilst a 20–40% reduction in outlets findings from an Australian survey [19]. and a minimum unit price of £1 were the least popular Awareness that alcohol is a risk factor for cancer has policy options [11]. Furthermore, support for increased been associated with greater support for alcohol policies tax and earlier closing times declined in Ireland between in the domains of pricing and taxation, availability, mar- 2002 and 2010, suggesting falling support for effective pol- keting and labelling in Australia [19]. While there has icies in that country [12]. The lack of public support may been some research within the North-east of England contribute to the limited political enthusiasm for some of that has examined the impact of a mass-media campaign the policies with the strongest evidence of effectiveness on awareness of the link between alcohol and cancer and cost-effectiveness by decision makers [13]; in short, and policy support [26], the authors of the current governments are likely to be sensitive to public attitudes paper were not able to locate any UK-based research towards policy options [9]. that has directly examined the relationship between There are several factors that are associated with awareness of the increased risk of cancer and support support for effective alcohol policies. Being female, for alcohol-related policies. Therefore, the aim of the increasing age and consuming none or lower levels of study was to assess which factors are associated with alcohol, compared to high levels, are associated with support for different alcohol policies, including aware- higher levels of support for more effective policies [11, ness of the alcohol-cancer link, in an English sample 14–17]. A higher level of education is associated with using policy options of relevance to current UK policy greater support for increasing price [16], promotion of context. limits and warnings, and controlling public spaces [18], and is associated with lower support for restricting avail- ability and greater law enforcement [16]. However, Methods demographic factors are largely non-modifiable. Modifi- Recruitment able factors such as knowledge have also been associated A cross-sectional online survey of 2100 adults was with support for alcohol policy. For example, knowledge conducted in England in July 2015. The sample size was of the domain specific (e.g. impact on crime, impact on determined by a pragmatic judgement and no power Bates et al. BMC Public Health (2018) 18:688 Page 3 of 11 calculations were conducted. The survey included items Measures on smoking and drinking behaviour, support for/oppos- To assess support for alcohol policies, respondents were ition to alcohol policy options, awareness of health condi- asked ‘To reduce the problems associated with excessive tions associated with alcohol use, and socio-demographic alcohol use, to what extent would you support or oppose information. A market research company (Vision One) each of the following policies…?’ followed by a list of 21 invited existing panel members aged 18 and over to par- alcohol-related policy options (Fig. 1). The question ticipate in a survey on ‘health and lifestyle behaviours'. originated from the Australian National Drug Strategy Quota sampling was used to ensure the sample was na- Household survey [28]. Six of the policy options repli- tionally representative with respect to age, sex, geographic cated those used in the Australian survey and the region and education. Of the 11,846 members that were remainder were adapted from a recent UK study [16]or sent an email invitation to participate, 5929 started the devised for this survey (see project report) [29] and survey. Following screening for quotas based on the popu- covered a range of policy domains (pricing, availability, lation distribution of sex (male/female), age (18–19, 20– drink driving counter measures, industry responsibility, 29, 30–39, 40–49, 50–59, 60+), region (North, Midlands labelling, advertising/marketing). Respondents recorded and London/South) and education (no qualifications, their response on a 5-point Likert scale (strongly oppose, below degree level, degree level and above) within Eng- oppose, neither support or oppose, support, strongly land, 2480 eligible respondents commenced the survey, of support). Awareness of the link between alcohol and whom 380 were subsequently excluded due to incomplete cancer was measured firstly in an open question; or invalid responses. To adjust for under-sampling of re- “Which, if any, health conditions do you think can result spondents without qualifications, sample weights were from drinking too much alcohol?”. Respondents were created with reference to the England and Wales 2011 then presented with a list of health conditions including census data [27] (see Table 1). cancer and asked “Which, if any, of the following health conditions can result from drinking too much alcohol?” (yes, no, don’t know). Using these two questions, re- spondents were categorised into those that listed cancer Table 1 Sociodemographic characteristics of the sample and weights applied (N = 2100) in the open question (awareness unprompted), those that selected ‘yes’ in the closed questions, but had not Unweighted Weights Applied already listed cancer in the open question (awareness N % N % prompted) and those that did not list cancer when Age prompted and selected ‘no’ or ‘don’t know’ in the closed 18–19 63 3.0 62 3.0 section. 20–29 339 16.1 325 15.5 Demographic information including age, gender, educa- 30–39 351 16.7 332 15.8 tion (none, below degree and degree or above) and post- 40–49 394 18.8 385 18.3 code was collected. Postcode data were used to identify 2015 Index of Multiple Deprivation (IMD) quintile, an 50–59 334 15.9 330 15.7 area-based deprivation measure calculated for 32,844 60+ 619 29.5 667 31.8 areas within England, which combines information from 7 Gender weighted domains; income deprivation (weighting factor Male 1021 48.6 1030 49.0 22.5%), employment deprivation (22.5%), education, skills Female 1079 51.4 1070 51.0 and training deprivation (13.5%), health deprivation and IMD Quintile disability (13.5%), crime (9.3%), barriers to housing and services (9.3%) and living environment deprivation (9.3%) Least deprived 362 17.2 349 16.6 [30]. IMD quintiles (least deprived, low deprivation, aver- Low deprivation 356 17.0 350 16.7 age, high deprivation, most deprived) were based on the Average 430 20.5 426 20.3 national ranking rather than the ranking within the High Deprivation 469 22.3 474 22.6 sample. Smoking status was assessed as never-smoker, Most Deprived 461 22.0 479 22.8 ex-smoker, or current (occasional or daily) smoker. Qualification Alcohol consumption was measured using the three-item consumption scale of the Alcohol Use Disorders Test None 178 8.5 315 15.0 (AUDIT-C) which assesses past year frequency and quan- Below degree 1238 59.0 1155 55.0 tity of any alcohol consumption and frequency of heavy Above degree 684 32.6 630 30.0 drinking [31]. AUDIT-C scores were categorised into Sample weights were created with reference to the England and Wales 2011 abstainers (0), lower risk drinkers (1–4), increasing risk census data to increase distribution fit between the sample and the population regarding level of qualification drinkers (5–8) and highest risk drinkers (9–12). Bates et al. BMC Public Health (2018) 18:688 Page 4 of 11 Fig. 1 Percentage of participants that support/oppose alcohol policies Statistical analyses sizes of over 250 and when the average communality is Data analyses were conducted using SPSS version 22 for 0.6 or larger [32]. Thirdly, to identify predictors of policy Windows. Analysis involved three stages. Firstly, descrip- support, four linear regression analyses were conducted tive analyses were carried out to determine proportion with the PCA factor scores as dependent variables. Age, of support in each of the demographic, health behaviour age (entered as continuous variables), gender, IMD quin- and knowledge categories. Secondly, given the large tile (5 categories from least deprived to most deprived), number of policy items included, Principal Component qualifications (no qualifications, qualifications below de- Analysis (PCA) was conducted to reduce these to fewer gree level, degree and above), smoking (never-smoker, factors which underlie patterns of support for individual ex-smoker, current smoker), alcohol consumption (highest policy items. The reduction to fewer factors may aid as- risk drinker, increasing risk, lower risk, abstainer), and sessment of generalisability of results to other policies cancer awareness (none, prompted, unprompted) were not included and avoids increasing the risk of type 1 entered as independent variables. Scatter plots of age and error by running several analyses. Theoretically there support for the four policy factors indicated that the could be correlation between support for one group of relationship may be quadratic and so age was included to policy items and another group so oblique rotation (pro- account for this possibility. max) was used to allow correlation between factors [32]. Sensitivity analysis was undertaken by introducing two The PCA generates a score for each individual on each sets of variables which were not considered in the initial factor. The Kaiser-Meyer-Olkin (KMO) measure was analysis but were highlighted by a reviewer as factors that used to assess whether there was an adequate sample could impact on policy support. The first was awareness size and if KMO values for individual policy items was of the link between alcohol and other diseases. There was above the acceptable limit of 0.5 [32]. Bartlett’s test was greater awareness of the link between alcohol and other run to indicate whether correlation between policy items diseases (heart disease, diabetes, liver disease, high choles- were sufficient for PCA. Kaiser’s criterion, an eigenvalue terol or overweight/obesity) than cancer [24]. The second above one, was used to determine which factors to retain was any history of a cancer diagnosis. These were both for further analyses. This criterion is reliable in sample included as covariates to examine whether controlling for Bates et al. BMC Public Health (2018) 18:688 Page 5 of 11 these impacted on the association between awareness of Bartlett’s test for sphericity was significant indicating the the alcohol-cancer link and policy support. correlations between policy items were sufficient for PCA. The Kaiser criterion was satisfied for the four pol- Results icy factors. The policy item Banning alcohol consump- The demographic characteristics are displayed in Table tion on trains had a factor loading of below 0.4 on all 1. One third (31.4%) of the respondents were current factors and there was no change to the factor structure smokers, 24.9% were ex-smokers and 43.7% were when running the PCA without the item so it was re- non-smokers. The proportions of respondents reporting moved. The factors explained 65.5% of the variance. highest risk, increasing risk, and lower risk drinking Table 2 shows the factor structure and loadings. The were 9.8, 31.5 and 46.8% respectively with 11.9% report- four factors identified were labelled Price and Availabil- ing no alcohol use. When asked about health conditions ity, Marketing and Information, Harm Reduction and related to drinking too much, 12.9% listed cancer un- Drink Driving based on the policy items in each factor. prompted and a further 34.3% selected ‘yes’ when cancer The degree of support for each policy option is pre- was listed as one of a number of potential health condi- sented in Fig. 1, ordered from most to least supported. tions resulting from drinking too much. The remaining The mean factor score for each variable of interested is 52.8% selected ‘no’ or ‘don’t know’. displayed in Table 3. Multiple regression analyses (Table 4) The PCA analysis revealed that there were correlations demonstrated that awareness of the relationship between between factors of over 0.5 confirming that orthogonal alcohol consumption and cancer (unprompted) was rotation would be inappropriate. The KMO measure in- significantly associated with support for all policy factors. dicated an adequate sample size and all KMO values for A significant association was also found for prompted individual policy items were above the acceptable limit. cancer awareness for all policy factors except drink Table 2 Principal Component analysis of 21 alcohol policy items – reduced to four factors Policy Item Price and Marketing and Harm Drink Availability Information Reduction driving Increasing the price of alcohol .872 −.149 .161 .006 Taxing alcoholic drinks on the basis of the percentage of alcohol they contain .834 −.128 .207 −.023 Reducing hours alcohol can be sold within off-licenses and supermarkets .772 .196 −.162 .004 Setting a minimum unit price below which a unit of alcohol cannot be sold .771 −.027 .177 −.037 Reducing the number of outlets that sell alcohol .754 .257 −.170 −.056 Reducing trading hours for all pubs and clubs .753 .157 −.192 .026 Banning outdoor advertising of alcohol such as on bill boards and bus stops .116 .899 −.117 −.087 Limiting advertising for alcohol on TV until after 9.00 pm −.050 .833 .082 −.019 Restricting the display of alcohol in shops and supermarkets to dedicated aisles .134 .773 .036 −.081 (e.g. not in the entrance) Banning alcohol sponsorship of sporting events .165 .697 −.182 .086 Requiring information on national drinking guidelines on all alcohol containers −.086 .607 .426 −.068 Specific health warnings on alcohol containers (e.g. like on tobacco packaging) .012 .580 .334 −.037 Banning having alcohol available to drink at school events where children are .057 .553 −.155 .324 present, such as fetes Making it compulsory that the number of alcohol units in a bottle or can of −.189 .525 .494 .038 alcoholic drink be shown on the label Increasing funding for alcohol treatment services −.036 −.131 .793 −.041 Introducing and promoting lower strength wine and lower strength or no .316 −.046 .552 .099 alcohol beer Doctors or health professionals ask patients about their drinking habits and, −.065 .393 .502 .045 where necessary, offer advice on how to reduce their alcohol consumption Offering and promoting smaller drink sizes in pubs and restaurants .396 .014 .441 .078 Reducing the drink driving limit −.017 −.101 −.010 .917 Introducing random breath alcohol testing for drivers −.037 .118 .068 .719 Banning alcohol consumption on trains had a factor loading below 0.4 and when removed from the analysis no change in the factor structure was observed and so was not included Bates et al. BMC Public Health (2018) 18:688 Page 6 of 11 Table 3 Mean factor based scores by variables of interest Sample Characteristic Factor Score Price and Availability Marketing and Information Harm Reduction Drink driving Mean Sd Mean Sd Mean Sd Mean Sd Age 18–34 − 0.08 0.98 − 0.14 0.94 0.07 0.99 −0.11 0.95 35–49 − 0.06 0.97 − 0.08 0.98 0.01 0.98 0.03 0.97 50–64 − 0.01 1.02 0.11 0.98 − 0.01 0.99 0.07 1.05 65+ 0.18 1.02 0.13 1.09 −0.09 1.04 0.01 1.03 Gender Male −0.11 1.00 −0.15 1.02 −0.14 1.04 −0.16 1.05 Female 0.11 0.99 0.15 0.96 0.14 0.94 0.16 0.93 IMD quintile Least deprived −0.04 0.93 −0.01 0.97 0.11 0.89 −0.06 0.95 Low deprivation −0.01 0.99 −0.03 1.02 − 0.05 1.03 −0.00 1.03 Average 0.03 1.00 0.04 0.98 −0.01 0.95 0.07 0.98 High Deprivation −0.02 1.02 0.01 0.99 −0.02 1.08 −0.03 1.01 Most Deprived 0.02 1.04 −0.02 1.03 − 0.03 1.01 0.02 1.02 Qualification None 0.16 1.10 0.14 1.18 −0.14 1.11 0.18 1.06 Below degree −0.06 0.97 − 0.05 0.96 −0.05 0.98 − 0.06 0.99 Above degree 0.02 1.00 0.02 0.98 0.14 0.97 0.02 0.99 Smoking Status Non smoker 0.10 0.99 0.07 0.94 0.09 0.98 0.01 0.99 Ex Smoker 0.01 0.94 0.09 1.00 −0.06 0.97 0.09 0.97 Smoker −0.14 1.05 −0.15 1.05 −0.07 1.04 −0.08 1.03 Alcohol Consumption None 0.86 0.92 0.59 0.92 0.38 0.95 0.36 0.97 Lower risk 0.15 0.92 0.13 0.96 0.07 0.96 0.10 0.95 Increasing risk −0.35 0.91 −0.27 0.95 − 0.13 0.97 − 0.20 1.00 Highest risk −0.49 0.95 −0.36 1.02 −0.30 1.17 −0.21 1.06 Cancer knowledge None −0.06 0.99 −0.08 0.99 −0.15 0.98 −0.06 0.98 Prompted 0.04 1.03 0.01 1.03 0.08 1.01 0.02 1.04 Unprompted 0.13 0.96 0.26 0.89 0.36 0.94 0.16 0.97 driving. Being female and lower levels of alcohol con- policies. Education above degree level was associated sumption were associated with support for all four policy with greater support for harm reduction policies and factors. Alcohol consumption was the strongest pre- education below degree level was associated with lower dictor of support for price and availability, marketing support for drink driving policies in comparison to no and information,and harm reduction policies; higher qualifications. For each of the policy types, the effect levels of alcohol consumption were associated with size of the association between awareness of the lower levels of support excluding the highest risk alcohol-cancer link and support for policies was small group. This highest risk group was associated with (Pearson coefficient ranged from 0.06 to 0.15). Of all lower support than the none/low risk groups but the policy types, the cancer awareness variable had the greater support than the increasing risk group. Increas- largest relative contribution to the degree of support ing age was the strongest predictor of drink driving for the harm reduction policies. Being an ex-smoker Bates et al. BMC Public Health (2018) 18:688 Page 7 of 11 Table 4 Multiple regression analyses – Variables predicting support for alcohol policy factor scores Price and Availability Marketing and Information Harm Reduction Drink driving Beta 95% CI P value Beta 95% CI P value Beta 95% CI P value Beta 95% CI P value Age −0.09 −0.37 0.19 0.52 0.13 −0.15 0.41 .350 −0.02 −0.32 0.29 .898 0.49 0.20 0.79 < 0.001 Age^2 0.18 0.18 0.18 0.21 −0.02 −0.16 0.00 .909 −0.01 −0.16 0.00 .922 −0.46 −0.46 0.05 < 0.001 Gender Male Female 0.05 0.01 0.09 0.02 0.11 0.07 0.16 < 0.001 0.09 0.04 0.13 < 0.001 0.13 0.09 0.18 < 0.001 IMD Quintile Least deprived Low deprivation 0.01 −0.04 0.06 −0.67 −0.01 −0.06 0.05 0.84 −0.05 −0.11 0.00 0.07 0.02 −0.04 0.08 0.47 Average 0.02 −0.03 0.08 .043 0.03 −0.03 0.08 0.39 −0.05 −0.10 0.01 0.11 0.05 −0.01 0.11 0.09 High Deprivation 0.01 −0.05 0.07 0.76 0.02 −0.04 0.07 0.56 −0.04 −0.10 0.01 0.14 0.01 −0.05 0.07 0.84 Most Deprived 0.05 −0.01 0.11 0.10 0.03 −0.03 0.09 0.27 −0.04 −0.10 0.02 0.18 0.04 −0.02 0.10 0.24 Qualification None Below degree 0.01 −0.05 0.07 0.80 0.00 −0.14 0.14 0.99 0.04 −0.04 0.11 .327 −0.09 −0.16 −0.02 0.02 Above degree 0.06 −0.01 0.13 0.09 0.05 −0.02 0.12 0.20 0.11 0.04 0.18 .003 −0.03 − 0.11 0.04 0.38 Smoking Status Non smoker Ex Smoker −0.01 − 0.06 0.03 0.55 0.02 −0.03 0.07 0.38 −0.02 −0.07 0.03 .445 0.06 0.01 0.11 0.02 Smoker −0.01 −0.06 0.04 0.67 −0.01 −0.06 0.04 0.58 −0.01 −0.06 0.05 .858 0.01 −0.04 0.06 0.66 Alcohol None Lower risk −0.35 −0.42 −0.28 < 0.001 −0.22 −0.29 −0.14 < 0.001 −0.15 −0.22 −0.07 < 0.001 −0.11 −0.19 −0.04 < 0.001 Increasing risk −0.55 −0.62 −0.48 < 0.001 −0.37 −0.44 −0.30 < 0.001 −0.24 −0.32 −0.17 < 0.001 −0.23 −0.30 −0.15 < 0.001 Highest risk −0.40 −0.45 −0.34 < 0.001 −0.26 −0.32 −0.20 < 0.001 −0.19 −0.25 −0.13 < 0.001 −0.15 −0.21 −0.09 < 0.001 Alcohol-cancer Awareness None Prompted 0.05 0.01 0.10 0.02 0.05 0.00 0.09 0.04 0.09 0.05 0.14 < 0.001 0.04 −0.01 0.08 0.12 Unprompted 0.06 0.01 0.10 0.01 0.11 0.06 0.15 < 0.001 0.16 0.11 0.20 < 0.001 0.07 0.02 0.11 < 0.001 p value representing significance are set in italics Bates et al. BMC Public Health (2018) 18:688 Page 8 of 11 was associated with higher support for drink driving associated with support for smoking policies [34]. It is policies. Deprivation was not associated with support likely that the widespread awareness of health risks as- forany of thepolicyfactors. sociated with smoking contributed to the public sup- port for restrictive tobacco policies [35]. In comparison, Sensitivity analysis the awareness of the alcohol-cancer link is low and thus Respondents that identified a link between alcohol and there is a need to increase awareness to allow the public at least one of heart disease, diabetes, liver disease, high to form informed opinions regarding alcohol policies. cholesterol or overweight/obesity were compared to Efforts to improve awareness of the alcohol-cancer link those who did not identify any of these links. This may contribute to decreasing the knowledge deficit. There awareness was significantly associated with three policy is some evidence that public campaigns can increase pub- factors (marketing and information, harm reduction and lic awareness of the link between alcohol and cancer [24]. drink driving), but the inclusion of this variable within In the North-east of England, people who were exposed to the regression had very little impact (change less than a mass-media campaign to raise awareness were more or equal to 0.01) on the size of the standardised coeffi- aware of the link between alcohol and cancer than those cient of the awareness unprompted of the who had not and support for alcohol policies increased alcohol-cancer link association. However, for the mar- following the campaign [26]. In Denmark, a week-long an- keting and information factor, the awareness of the nual alcohol campaign run over 10 years increased public alcohol-cancer link only when prompted was reduced knowledge of safe drinking limits [36]. Within this study, to non-significance. Whether or not respondents re- it is not known whether increased awareness has an ported a cancer diagnosis was not significantly associ- impact on support for policies; however, Pechey and ated with policy support and inclusion of these colleagues have demonstrated that preferences for policies variables did not impact on the coefficients of the could be altered if the probable positive outcomes are awareness of the alcohol-cancer link association. presented alongside the policy [11]. For example, the popularity of minimum unit pricing policies was much Discussion greater (supported by an additional one-fifth of partici- Awareness of alcohol as a risk factor for cancer is associ- pants) when all probable positive outcomes were pre- ated with greater support for four different types of pol- sented compared to when no outcomes were presented. A icies: Price and Availability and Marketing and study conducted in New Zealand found that public sup- Information, Harm Reduction and Drink Driving. This port for alcohol control policies was maintained in com- study used a three-category variable to distinguish be- munities exposed to alcohol-related health promotion tween those that were aware of the alcohol-cancer link media campaigns and community-based intervention ac- unprompted and prompted. This enabled the authors to tivities whereas it declined in those communities without identify that unprompted cancer awareness is a stronger any such intervention [37]. Together, these studies suggest predictor of support for alcohol policies across all four that public awareness of the health risks of alcohol con- factors compared with both those who indicated their sumption can be increased and that increased awareness awareness when prompted or those who were not aware may have an impact on public support for alcohol policy, of the risk. Being female and lower levels of alcohol con- particularly where there is a clear description of antici- sumption were also both associated with higher levels of pated policy effects. However, attempts to raise public support for all policies. awareness may be resisted by alcohol-funded organisa- These findings are broadly consistent with previous tions as has been reported to have occurred recently in re- Australian research, which identified 1) that a similar pro- sponse to warning labels on alcohol products in Canada portion of the population were aware (either prompted or [38]. Although there is evidence to indicate that increased unprompted) that alcohol is a risk factor for cancer, and 2) awareness does not necessarily reduce actual consumption that awareness alcohol consumption can cause cancer is of alcohol [39], this study indicates that awareness is associated with support for pricing, availability, marketing associated with greater support for policies and thus has and labelling polices [19]. Similarly a British survey that the potential to reduce alcohol-related harm indirectly indicated awareness of the link between alcohol and can- through generating an environment where restrictive pol- cer was around 50% in 2015 [33]. We were able to build icies are more likely to be implemented. on this study by examining differential effects of alterna- This study has limitations; the respondents were re- tive measures of awareness and using PCA in order to cruited from an existing market research panel and there- examine support for different policy types, thereby in- fore membership of the sampling frame is self-selecting creasing the potential generalisability of our results. The and limited to those who have access to, and are confident findings also reflect results from tobacco-control research using, the internet. Furthermore, of the people that in which knowledge of the negative impact of smoking is received the email, only approximately 50% started the Bates et al. BMC Public Health (2018) 18:688 Page 9 of 11 survey and information is not available about those that policies in the North-East of England [26] future prospect- did not respond so any potential differences between the ive research could usefully examine whether exposure to responders and non-responders is not known. These fac- information and an increase in awareness, is associated tors may have generated a selection bias. However, quota with a change in policy support in a wider population. sampling was used with the aim of creating a representa- This would help us to develop a better understanding of tive sample of England based on age, gender, region, and how increasing awareness might change public opinion on education level and weights were applied to adjust for dif- effective policies that are politically challenging to imple- ferences between the sample and the population in order ment (e.g. minimum unit pricing). Future research could to maximise the generalisability of the study findings. The examine the combined effect of increased awareness of analyses focussed on awareness of alcohol as a risk factor the general health risks of alcohol in addition to providing for cancer in general and did not examine whether aware- more detailed information about anticipated policy effects. ness of the risk of certain cancers are stronger or weaker Finally, future research could examine health or other predictors of support for policies, especially as awareness risks not only to the individual but also people close to of the role of alcohol as a risk factor varies depending on them as a predictor of policy support. A previous study the type of cancer [40]. Further, the policy items presented examining support for restrictions on tobacco found were simply descriptive (e.g. ‘increasing the price of alco- awareness of the potential harm to others strongly pre- hol’) and did not detail what the anticipated policy effects dicted support [34] and it may be that a similar relation- might be and for whom. Including likely positive out- ship exists for alcohol. comes of a policy has been associated with preferences for alcohol policy and thus this may have impact on outcomes Conclusions [11] .Support for policy may also be influenced by per- The extent to which any individual supports a govern- sonal experience. Greater support has been found among ment policy is dependent on a range of factors including those who have experienced alcohol related-harm or the behaviour the policy targets (e.g. smoking, alcohol alcohol-related disturbance [41] and so those who have consumption), the type of policy and how intrusive it is experience of alcohol-attributable cancer may report (e.g. taxation, regulation), who the policy targets (e.g. greater support for policy. This may have confounded the children), and the extent to which the individual in association found between awareness and support for pol- question will be affected by the policy. Some predictors icy. Although information about the type of cancer (i.e. of support for policies are modifiable. Awareness, and es- whether it was alcohol-attributable) and personal experi- pecially unprompted awareness, of the link between alco- ence of cancer other than a personal diagnosis (i.e. a diag- hol consumption and cancer may be one such modifiable nosis of a friend or family) was not available, the impact of predictor, given that awareness of the risk is a significant any cancer diagnosis was controlled for in sensitivity ana- predictor of support for range of alcohol policies. There- lysis and this did not have an impact on the association fore, improving awareness of the link between alcohol between alcohol-cancer awareness and policy support. Fi- consumption and cancer may increase public support for nally, we cannot be certain that reported support repre- effective alcohol policies that are otherwise relatively un- sents actual support however any increase in support may popular. These results are useful for policy-makers, be- create environment in which these policies are more likely cause it highlights that understanding of a policy and its to be implemented. context is an important determinant of support and that Whilst the methods used in the PCA were directed increasing awareness of the specific harms being ad- by research recommendations [32], alternative methods dressed may result in greater support for alcohol policies. could be employed relating to, amongst other things, rotation method and factor selection. Several alterna- Acknowledgements We would like to thank the Policy and Information Sounding Board at tive methods were examined, but they did not have an Cancer Research UK who took part in developing and testing the survey and appreciable impact on the findings reported here. Like- Melanie Lovatt and Petra Meier for their contribution to survey development. wise, alternative regression methods could have been We acknowledge that the survey reported in this study replicates and extends on a survey originally conducted in Australia by the Cancer Council NSW. employed, however, the distribution of the dependent variables would strongly suggest that linear regression Funding is the most appropriate method, and this approach is This work was supported by Policy Research Centre for Cancer Prevention, commonplace among other analogous studies. Cancer Research UK. The authors are solely responsible for the content of this paper. Several potential future research questions arise from this study. The study was cross-sectional. While previous Availability of data and materials research has demonstrated that alcohol-awareness cam- The data that support the findings of this study are available from CRUK but paigns can raise awareness of the link between alcohol restrictions apply to the availability of these data, which were used under and cancer [39] and can increase support for alcohol licence for the current study, and so are not publicly available. Data are Bates et al. BMC Public Health (2018) 18:688 Page 10 of 11 however available from the authors upon reasonable request and with 16. Li J, Lovatt M, Eadie D, Dobbie F, Meier P, Holmes J, Hastings G, permission of CRUK. MacKintosh AM. Public attitudes towards alcohol control policies in Scotland and England: results from a mixed-methods study. Soc Sci Authors’ contributions Med. 2017;177:177–89. SB, PB, JH and SD conceptualised the study. PB, JL, LG, LH, EGM & JH 17. NatCen Soc Res: Attitudes to alcohol - Findings from the 2015 British Social contributed to survey development; PB prepared ethics; PB, LG & LH Attitudes survey. In.; 2015. undertook stakeholder engagement; SB, PB, JH & SD contributed to analyses 18. Wilkinson C, Room R, Livingston M. Mapping Australian public opinion and interpretation; SB, PB, JL, LG, LH, EGM, SD, BW & JH contributed to on alcohol policies in the new millennium. Drug Alcohol Rev. 2009; writing. All authors read and approved the final manuscript. 28(3):263–74. 19. Buykx P, Gilligan C, Ward B, Kippen R, Chapman K. Public support for Ethics approval and consent to participate alcohol policies associated with knowledge of cancer risk. Int J Drug Policy. This project was approved by the ScHARR ethics committee, University of 2015;26(4):371–9. Sheffield (project ID: 03670). A market research company (Vision One) invited 20. Zhao J, Stockwell T, Roemer A, Chikritzhs T. Is Alcohol consumption a risk existing panel members to participate in the study. If they selected the link factor for prostate cancer? A systematic review and meta-analysis. BMC Cancer; to the survey, they were directed to an information page about the study 2016;16:1–13. Available from: https://doi.org/10.1186/s12885-016-2891-z and provided consent by selecting the link to begin the survey. 21. Bagnardi V, Blangiardo M, La Vecchia C, Corrao G: A meta-analysis of alcohol drinking and cancer risk. Br J Cancer 2001, 85(11):1700. Competing interests 22. Ellison RC, Zhang Y, McLennan CE, Rothman KJ. Exploring the relation The authors declare that they have no competing interests. of alcohol consumption to risk of breast Cancer. Am J Epidemiol. 2001; 154(8):740–7. 23. Bagnardi V, Rota M, Botteri E, Tramacere I, Islami F, Fedirko V, Scotti L, Jenab M, Publisher’sNote Turati F, Pasquali E, et al. Alcohol consumption and site-specific cancer risk: a Springer Nature remains neutral with regard to jurisdictional claims in comprehensive dose–response meta-analysis. Br J Cancer. 2015;112:580–93. published maps and institutional affiliations. 24. Buykx P, Li J, Gavens L, Hooper L, Lovatt M. Gomes de Matos E, Meier P, Holmes J: public awareness of the link between alcohol and cancer in Author details England in 2015: a population-based survey. BMC Public Health. 2016; 1 2 University of Sheffield, 30 Regent Street, Sheffield S1 4DA, UK. Institut für 16(1):1194. Therapieforschung, Munich, Germany. Monash University, Bendigo 3550, 25. Sanderson SC, Waller J, Jarvis MJ, Humphries SE, Wardle J. Awareness of 4 5 Australia. Cancer Research UK, London, UK. dosomething.org, New York, lifestyle risk factors for cancer and heart disease among adults in the UK. USA. Patient Educ Couns. 2009;74(2):221–7. 26. Martin N, Buykx P, Shevills C, Sullivan C, Clark L, Newbury-Birch D. 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