Selection biases in observational studies affect associations between moderate alcohol consumption and mortality

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1 ADDICTION DEBATE doi: /add Selection biases in observational studies affect associations between moderate alcohol consumption and mortality Timothy S. Naimi 1,2, Timothy Stockwell 3, Jinhui Zhao 3, Ziming Xuan 2,FridaDangardt 4, Rich Saitz 3, Wenbin Liang 5 & Tanya Chikritzhs 5 Section of General Internal Medicine, Boston Medical Center, Boston, MA USA, 1 Department of Community Health Sciences, Boston University School of Public Health, Boston, MA USA, 2 Centre for Addiction Research of BC, University of Victoria, Victoria, British Columbia Canada, 3 University of Gothenburg, Gothenburg, Sweden 4 and National Drug Research Institute, Curtin University, Perth, Australia 5 ABSTRACT Selection biases may lead to systematic overestimate of protective effects from moderate alcohol consumption. Overall, most sources of selection bias favor low-volume drinkers in relation to non-drinkers. Studies that attempt to address these types of bias generally find attenuated or non-significant relationships between low-volume alcohol consumption and cardiovascular disease, which is the major source of possible protective effects on mortality from low-volume consumption. Furthermore, observed mortality effects among established low-volume consumers are of limited relevance to health-related decisions about whether to initiate consumption or to continue drinking purposefully into old age. Short of randomized trials with mortality end-points, there are a number of approaches that can minimize selection bias involving low-volume alcohol consumption. Keywords Alcohol, bias, epidemiology, moderate drinking, mortality, selection bias. Correspondence to: Timothy S. Naimi, Section of General Internal Medicine, Boston Medical Center, Boston, MA, USA. tim.naimi@bmc.org Submitted 11 December 2015; initial review completed 5 February 2016; final version accepted 12 May 2016 INTRODUCTION Although the adverse mortality effects of excessive alcohol consumption are relatively well established, the health effects of moderate (i.e. low-volume) alcohol consumption among populations in developed countries is an area of tremendous scientific controversy. Possible health benefits associated with low-volume alcohol consumption have relevance to burden-of-disease estimates, public health guidance about recommended drinking levels, policy development and public attitudes about alcohol consumption. To date, there has been no randomized clinical trial of low-volume alcohol consumption that has assessed any mortality outcome. Therefore, the literature about the mortality effects of alcohol consumption consists entirely of observational studies. Along with confounding, selection bias is a principal threat to the internal validity of observational studies. Selection bias is defined as a systematic error in the selection, enrollment and participation of study subjects that distorts the relationship between an exposure and an outcome [1,2]. However, apart from abstainer bias (sometimes referred to as the sick quitter bias), other types of selection bias have not been discussed in a single paper to gain an overview of how selection biases might distort the relationship between low-volume alcohol consumption and health. The purpose of this paper is to review the theory and existing evidence for various types of selection bias that pertain to studies of the relationship between low-volume alcohol consumption and mortality, and to describe the probable direction of those biases. We contend that most selection biases would lead to overestimates of mortality benefits from low-volume alcohol consumption relative to non-consumption. In this paper, we will examine potential biases according to the following themes: (1) self-selection bias related to an individual s alcohol consumption and study participation, (2) selection bias related to the timing of study enrollment and (3) selection bias related to data analyses. Although there is a limited literature pertaining specifically to selection bias in observational studies of alcohol consumption, the literature cited to inform our theoretical

2 208 Timothy S. Naimi et al. arguments comes from studies about specific aspects of selection bias (e.g. including former drinkers with life-time abstainers), information related to alcohol epidemiology generally (e.g. the timing and distribution of deaths from alcohol among the population) and findings and discussion points from observational studies about alcohol consumption and mortality. SELECTION BIAS RELATED TO AN INDIVIDUAL S ALCOHOL EXPOSURE OR STUDY PARTICIPATION Self-selection to consume alcohol or not Selection bias starts with the characteristics of those who self-select to drink (Fig. 1). A study of young adults aged years found that drinkers had higher incomes and better educational attainment, engaged in more physical activity and were less likely to have illness compared with non-drinkers [3]. Residual confounding from these favorable characteristics from young ages, which are similar to those that have been observed in the general population among low-volume drinkers [4,5], could bias results in their favor. Willingness or ability to participate in future studies An individual s drinking behaviors, which are initiated typically during the teenage years, could affect the likelihood that the person would be unavailable, unable, unsuitable or unwilling to be enrolled into a study at a later time in life. For example, alcohol consumption may cause or contribute to mental illness, homelessness, unemployment, social isolation or mental and physical disabilities from alcohol-related injuries (e.g. traumatic brain injury). In this case healthier drinkers, more resilient drinkers or less risky drinkers would tend to be over-represented in study cohorts. Conversely, those with risky consumption patterns or those who have suffered alcohol-related Figure 1 Flow-chart depicting drinking status and possible enrollment in studies in which moderate (i.e. low-volume) drinkers are compared with non-drinkers consequences might be less likely to be included in studies. This is the non-mortal equivalent of the healthy survivor bias (discussed below), and may contribute to the lower prevalence of adverse confounding factors among drinkers who are enrolled subsequently into cohort studies and compared with non-drinkers. In support of this idea, previous research finds that drinkers in the general population tend to drink more and have more alcohol-related problems compared with drinkers who participate in health-related studies or surveys [6,7]. This is relevant in that binge drinking appears to nullify any apparent protective effects on coronary heart disease (CHD), even among those with relatively low levels of average consumption [8]. Therefore, due to higher rates of binge drinking in the general population, the potential benefits of low-volume average consumption might be overestimated among study cohorts relative to what would be experienced among low-volume average consumption among drinkers in real world scenarios. SELECTION BIAS RELATED TO THE TIMING OF STUDY ENROLLMENT Those who die prior to the enrollment period During the time gap between drinking initiation and possible study enrollment, those who die prematurely are not available be studied or analyzed (Fig. 1). With respect to alcohol, this results in what is sometimes referred to as a healthy survivor bias. This bias favors drinkers, assuming that deaths at relatively younger ages are due more probably to alcohol consumption among drinkers than they are due to a lack of consumption among non-drinkers. This is probably the case, as alcohol is a leading contributing cause of deaths from unintentional injuries and violence among young and middle-aged adults. Conversely, conditions for which there may be a protective association of low-volume ethanol (e.g. CHD, ischemic stroke) are relatively infrequent causes of death among those aged less than 45 years. Even cancer, for which some types are associated with alcohol consumption [9,10], represent alcohol-related competing risks that should be accounted for in studies of CHD mortality. In addition, approximately half of alcohol-related deaths are due to acute conditions with short latency periods between onset of the disease and death (e.g. unintentional injuries or violence) [11]. Therefore, independent of age of onset, deaths from acute conditions are more likely to be completed prior to cohort enrollment compared with diseases with longer latency periods. This further increases the likelihood that those dying from acute alcohol-related causes will be unavailable for cohort studies in which enrollment typically occurs several decades after drinking initiation.

3 Selection biases in studies of moderate drinking 209 Among those who die prematurely from alcohol-related causes, one might speculate that they may have been heavy drinkers all along, and therefore irrelevant in terms of a non-drinker versus low-volume drinker comparison. However, these drinkers may have initially been lowvolume consumers but ended up drinking more or in risky ways when their alcohol-related deaths occurred. In addition, while alcohol consumption is assessed typically on the basis of average consumption, most alcohol-related deaths among young and middle-aged adults stem typically from high per-occasion consumption (e.g. binge drinking). It is important to note that many who drink modest amounts on the basis of average consumption also binge drink. For example, in the United States more than 70% of all binge drinking episodes are accounted for by men who consume an average of 2USstandarddrinks per day and women who consume an average of 1drink per day [12]. Therefore, excess deaths from alcohol may accrue to drinkers who consume low volumes of alcohol on average. This type of bias is more than simply a theoretical concern in general and with respect to alcohol, in particular. For example, early-onset mortality from hormone replacement therapy may have accounted for differences between observational and randomized studies, in which observational evidence that suggested a reduced risk of CHD was contradicted subsequently by randomized clinical trials [13]. By evaluating the timing of hormone initiation and subsequent outcomes and using an intention-to-treat protocol, Hernan et al. re-analyzed observational data from the Nurses Health Study and found that CHD risk approximated more closely that of the randomized Women s Health Initiative Study [14]. The authors concluded that the discrepancies between estimates could be largely explained by differences in the distribution of time since menopause and the length of follow-up. However, alcohol is established more widely as a risk factor for early-onset mortality than is hormone replacement, and the time gap between the onset of exposure and enrollment into a study cohort would be decades longer for alcohol than for hormone replacement based on the typical ages for initiation for alcohol consumption versus hormone replacement therapy. Effect modification based on the age of study cohorts Distinct from the issue of premature mortality discussed above, age may be an effect modifier of the relationship between alcohol consumption and mortality among those who are alive and enrolled into studies. Alcohol can have health effects throughout the entire period in which it is consumed, and different causes of death tend to occur at different ages. Most cohort studies that are used to evaluate the relationship between alcohol consumption and mortality were designed to study deaths from chronic disease, and are comprised typically of middle- and olderaged adults. Although it is impractical for studies to have life-long follow-up, ideally the cumulative age distribution of cohorts included in meta-analyses should be representative of the population starting at ages in which alcohol consumption is initiated, or studies could be weighted to achieve this objective. Based on the typical age at which people are recruited for cohort studies, the years of peak risk for acute causes of alcohol-related death have passed, and those for cardiovascular disease (for which low-volume alcohol consumption may be protective) lie in the future. Compared with more representative age distributions, the overrepresentation of older age groups among cohort studies would therefore lead to underestimates of mortality risk among drinkers relative to non-drinkers. In a recent meta-analysis assessing the relationship between alcohol consumption and all-cause mortality, the weighted median age of all study participants was 55 years of age at enrollment [15]. This is years after most people begin drinking, and is substantially older than the median age of people in developed nations (e.g. in 2012, the median age was 42 years in Switzerland and 37 years in the United States) [16]. Figure 2, which shows net deaths (deaths caused minus deaths averted) based on two hypothetical studies, demonstrates how the age of a cohort might influence the number of deaths attributable to alcohol consumption. SELECTION BIAS-RELATED TO DATA ANALYSIS Comparing established moderate drinkers with non-drinkers In a trial with an intention-to-treat protocol in which lifelong non-drinkers were randomized to drink alcohol, outcomes would accrue to the groups according to their status at randomization, whether or not they continued to drink or to drink at levels prescribed by the study protocol. Intention-to-treat analyses are generally preferred because they assess the effect of a particular treatment based on the way it is actually used, rather than how it is supposed to be used. This would be an important consideration for a substance with intoxicating and potentially addictive qualities. By contrast, in cohort studies people are not randomized to drink moderately; rather, they choose to consume alcohol or not (Fig. 1). Although they may ultimately become or remain moderate drinkers, it is also possible that they quit drinking or become heavy drinkers. Therefore, those who remain established low-volume drinkers constitute a select group of drinkers. Accordingly, conclusions from observational studies should be interpreted in terms of health effects among those who already drink

4 210 Timothy S. Naimi et al. Figure 2 Hypothetical relationships between alcohol consumption and mortality, with example illustrations of how the number of net deaths (deaths averted minus deaths caused) might be influenced by the age of a study cohort moderately, rather than used as a basis to recommend that non-drinkers should initiate alcohol consumption or continue purposefully to drink for health reasons [17]. Heavy drinkers are obviously not included in analyses comparing low-volume drinkers with non-drinkers. However, from an intention-to-treat perspective, heavy drinking is a possible outcome of drinking initiation, and those who drink in excess of levels used typically to define moderate drinking have higher mortality than their more moderatedrinking counterparts [18]. In addition, there are a number of adverse confounding factors associated with heavy drinking. In a randomized trial these factors would be distributed equally among drinkers, at least initially. However, in observational studies, heavy drinkers also bear a disproportionate burden of negative confounding factors compared with low-volume drinkers, whose relative social advantage may confound the apparent relationship between low-volume consumption and health. People not analyzed due to poor baseline health status Many studies exclude those with poor baseline health status or pre-existing health conditions. This is done with the intention of mitigating confounding. In theory, excluding those with health problems, participants would begin a study with a clean slate health-wise, such that baseline health status might be associated less with alcohol consumption status [19]. However, excluding those with health conditions that are caused or exacerbated by alcohol consumption would magnify the healthy drinker bias among drinkers who are included in analyses. Among life-long non-drinkers, however, no excludable baseline health conditions could be attributable to alcohol consumption. The European Prospective Investigation into Cancer (EPIC) study assessed mortality from multiple and competing causes among a large cohort (n > ) [20]. Reduced risk of death from heart disease was associated with alcohol consumption, but only when participants with a history of poor health were excluded from analysis. The authors concluded: The apparent health benefit of low to moderate alcohol-use found in observational studies could therefore in large part be due to various selection biases and competing risks, which are related to both lifetime alcohol use and risk of disease, usually occurring later in life. Using simulation models and cohort data to examine the relationship between cholesterol and CHD risk factors, Marschner et al. demonstrated how selecting participants on the basis of prior illness can produce spurious threshold effects and J-shaped curves when the underlying relationship is, in fact, linear [21]. In addition, the exclusion of participants on the basis of existing health conditions can also reduce sample size markedly and makes findings less generalizable [22]. Misclassification or exclusion of former drinkers Those who stop drinking (i.e. former drinkers) tend to have poor general health, and are often referred to as sick quitters [23,24]. Former drinkers are misclassified commonly as non-drinkers [25]. Although this is technically accurate (they do not currently drink), the terminology may be misleading and may contribute to misunderstandings and biased conclusions about possible harms from not drinking. Moreover, including former drinkers with life-time abstainers contaminates the non-drinking reference group with less healthy individuals, including some whose poor

5 Selection biases in studies of moderate drinking 211 health is attributable to alcohol. In order to mitigate this bias, it is now recognized that the reference group of nondrinkers should be comprised only of those who have never or only rarely consume alcohol. Unfortunately, however, it is not possible to separate life-time abstainers from former drinkers in the large proportion of studies that only obtain information about current alcohol consumption at a single point in time. Addressing the former drinker bias affects the observed relationship between alcohol consumption and mortality. Fillmore et al. classified prospective studies on alcohol and health according to their definition of an abstainer, i.e. the reference group with which all classes of drinker are typically compared in these studies [26]. When analyses excluded former and occasional drinkers from the abstainer reference group, there was limited evidence of protection from low-volume alcohol consumption [25]. In a recent meta-analysis of the relationship of alcohol consumption and total mortality by Stockwell et al., the J-shaped curve for alcohol consumption and total mortality was replicated [15]. However, after accounting for former drinker bias and other factors related to study quality, there was no significant protective effect for low-volume drinkers compared with abstainers or occasional drinkers. In addition, from an intention-to-treat perspective, simply excluding former drinkers from the non-drinking reference group still biases studies in favor of moderate drinkers by selectively removing a frail group of drinkers whose poor outcomes would otherwise accrue to drinking groups [27]. When Kerr et al.analyzedparticipantsonthe basis of their life-course drinking history and retained former drinkers among drinking groups, rather than analyzing them separately, they found a non-significant increase in heart problems among life-time non-heavy (i.e. moderate) drinkers compared with life-time abstainers. However, the opposite was the case when analyzing groups on the basis of current drinking status, even when analyzing former drinkers separately [28]. When Liang & Chikritzhs reclassified former drinkers based on their imputed previous drinking status, rather than simply excluding them from the non-drinking reference group, the protective effects of low-volume alcohol consumption were attenuated [27]. Those who survive beyond the study period Assuming that cohorts following people into progressively older age ranges would tend to enroll those with older ages at baseline, the issue of alcohol-related healthy survivor bias would be magnified, as would issues related to confounding factors that are more prevalent among lowvolume drinkers that are also associated with greater longevity, irrespective of alcohol consumption. However, failure to capture deaths among the elderly might bias studies against low-volume drinkers assuming benefits for CHD mortality among older people surviving past the study period. CONCLUSIONS After reviewing the possible sources of selection bias in observational studies about the relationship between lowvolume alcohol consumption and mortality, selection bias is another reason to suggest that existing research may overestimate protective effects systematically from moderate alcohol consumption. There are a number of sources of selection bias inherent in comparing established lowvolume drinkers with non-drinkers. Low-volume drinkers who are enrolled into studies constitute a particular group of drinkers who chose to begin drinking, tolerated or enjoyed its effects, did not die prior to study enrollment, did not become heavy drinkers, did not stop drinking and were of sufficient physical and mental capacity to be enrolled into studies several decades after drinking initiation (Fig. 1). Overall, most sources of selection bias favor low-volume drinkers in relation to non-drinkers (Table 1). Studies that attempt to address these types of bias generally find attenuated or non-significant relationships between low-volume alcohol consumption and cardiovascular disease, which is the major source of possible protective effects on mortality. Furthermore, observed mortality effects among established low-volume drinkers are of limited relevance to health-related decisions about whether to begin drinking or whether to continue drinking purposefully into old age. Apart from randomized trials [29], there are a number of ways to reduce selection bias and improve the validity of estimates between alcohol consumption and all-cause mortality. Because most study cohorts under-represent the distribution of the population aged years, one approach would be to give added statistical weight to relatively younger cohorts. Secondly, cohort studies should assess alcohol consumption at multiple points in time to be able to discern former drinkers from non-drinkers, account for life-time consumption patterns and, for example, incorporate former drinkers with current drinkers according to their usual past level of consumption. Thirdly, long-term occasional drinkers (e.g. < 1 drink per week or per month) should serve as the reference group to which low-volume drinkers are compared. This is because long-term occasional drinkers resemble low-volume drinkers more closely than do non-drinkers in terms of potential confounding characteristics, and consume such low amounts of alcohol so infrequently that their favorable health characteristics are related implausibly to alcohol itself [30]. Fourthly, studies should collect information on alcohol consumption patterns (e.g. atypical drinking

6 212 Timothy S. Naimi et al. Table 1 Relevant exposure groups missed by observational studies and probable direction of distortion of relative risk estimates for moderate levels of alcohol consumption relative to non-drinkers. Group Reason for omission Comment Direction of the distortion probably favorable to: Died prior to cohort inception Unavailable Both drinkers and non-drinkers can die, but alcohol is a leading risk factor for mortality among young and early middle-aged adults (e.g. unintentional injuries, suicide). Those drinkers who remain alive to the time of cohort inception may represent healthy survivors Alive, but not enrolled into cohort Unavailable for enrollment, unsuitable for enrolment or unwilling to enroll Enrolled, but not analysed due to poor baseline health status Heavy drinkers Excluded from non-drinkers versus low-volume drinker comparison Risk factors for not being studied may be alcohol-related as alcohol is a risk factor for medical, social and economic morbidity among young and early middle-aged adults. Research finds that those not enrolled into studies tend to have riskier patterns of consumption and/or more alcohol-related adverse outcomes than those enrolled into studies Excluded Might mitigate confounding and make health outcomes prospective from the point of cohort enrollment. However, excluding those with poor baseline health status related to prior alcohol use would exacerbate healthy survivor bias, at least with respect to alcohol Heavy drinking is associated with adverse confounding factors; in a randomized trial the risk from these confounders would be distributed equally among drinkers. In addition, from an intention-to-treat perspective heavy drinking is a possible outcome of drinking initiation, and heavy drinking is associated with increased mortality Low-volume drinkers Low-volume drinkers Unclear, probably low-volume drinkers Low-volume drinkers Former drinkers (quitters) (a) Misclassified as non-drinkers (a) Former drinkers are generally unhealthy, therefore contaminate the non-drinker group Low-volume drinkers Those who survive beyond the study period (b) Excluded from non-drinker versus moderate drinker comparison Neither drinkers nor non-drinkers are followed to the point of death (b) Outcomes for former drinkers should accrue to drinking groups (intention-to-treat); in addition, as only drinkers can become former drinkers, exclusion selectively cleanses drinking groups but not the non-drinker group Effect might depend upon the age range for cohort recruitment and duration of follow-up, which would influence the distribution of causes of death that might be attributable to drinking or not drinking. Older age at recruitment might exacerbate healthy survivor bias or the influence of confounding factors that result in longer life expectancy Unclear

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