Abstract
Harms attributed to others’ alcohol use have been extensively studied in the US and internationally, but no studies have measured harms from others’ marijuana use. We utilize data from five cross-sectional waves of a survey series with representative samples of Washington state residents conducted every 6 months from 2014 to 2016, after the legalization of adult use marijuana. Harms attributed to others’ drinking and to others’ marijuana use included family and financial problems, assault, harassment and vandalism experiences and accidents due to impaired drivers. Past year harms attributed to others’ marijuana use were reported by 8.4% of the sample, while 21.3% reported alcohol-attributed harms and 4.3% experienced both. Women were more likely to experience harms from either substance. While heavy drinkers were most likely to experience alcohol harms from others’ use, frequent marijuana users reported the least harms from others. About three times as many individuals reported harassment, vandalism or family problems attributed to someone’s alcohol use compared those harms attributed to someone’s marijuana use, with a smaller ratio seen for financial trouble and a wider ratio for physical harm. Harms attributed to other’s marijuana use in Washington were found to be substantial, but lower than harms from others’ drinking.
Keywords: harms from others, externalities, marijuana, alcohol
Introduction
Assessments of harms experienced by individuals attributed to alcohol use by other people have offered an alternative and complimentary population perspective on alcohol-related problems in the US and other countries (Giesbrecht, Cukier & Steeves 2010; Warpenius & Tigerstedt 2016). In the 2005 US National Alcohol Survey (NAS) (Greenfield et al. 2009), a majority (60%) of the population aged 18+ reported ever having had at least one of six assessed harms attributed to another person’s drinking, and 9% experienced such harms in the prior 12 months. Trend comparisons through 2015 revealed few changes in prevalence of these harms over time, excepting financial harms attributed to other drinkers, which increased, potentially because of the economic recession (Greenfield et al. 2015). Here we extend the harms from others’ use paradigm to include secondhand harms due to others’ marijuana use in the context of the post-legalization period in the state of Washington.
Measuring harms from the victim’s perspective is also highly relevant for substances other than alcohol, such as marijuana, where family members, friends, associates and strangers may be affected by the behaviors of problematic users. A few international studies have measured harms attributed to others’ drug use in general (Callinan & Room 2014; Melberg et al. 2011), but none to our knowledge has focused on specific substances. An Australian study reported drug-related harms at rates ranging from 59% (gone out of your way to avoid drug users or places they are known to hang out) to 16% (verbal abuse from drug users) and 4% (for physical abuse by a person under the influence) in the prior 12 months (Callinan & Room 2014). Notably, these rates were lower than parallel items for harms attributed to drinkers. In a survey study of four Nordic capitals (Melberg et al. 2011) many respondents worried about the drug use of someone they knew (ranging by city from 13% to 28% in the past 12 months) and some (between 5% to 9%) had feared violence from a known drug user. Despite these important first steps in quantifying the population extent of harms attributed to others’ drug use in other countries, no studies of harms from others’ drug use have been based on US samples or focused on specific drugs such as marijuana, gaps our study aims to address.
Marijuana use in the US has increased substantially since 2009, and legal use has continued to spread (Cambron, Guttmannova & Fleming 2017). More than half of the 50 states have now legalized medicinal use of marijuana, and adult use is now legal in seven states and Washington, DC. In particular, Washington State was among the first to legalize adult use in 2012, with retail stores opening in July of 2014. Adult population rates of marijuana use in Washington rank among the highest in the US, with an estimated past-year use prevalence of 19.5% for 2015–16 compared to a national rate of 13.9% (Substance Abuse and Mental Health Services Administration 2018).
This study utilizes data from five cross-sectional waves of an alcohol- and marijuana-focused representative survey series of Washington adults conducted in 2014, 2015 and 2016. Studies utilizing these surveys have included retrospective analyses of the privatization of the liquor monopoly and cannabis legalization in 2012 (Kerr et al. 2018; Kerr et al. 2018). The present analyses will provide the first estimates of harms attributed to other people’s marijuana use. Comparisons with rates of reported harms attributed to other people’s alcohol use are included to provide perspective on these rates; the relative prevalence of different harm domains are also given to help understand differences between these subjective reports of the substances’ impacts.
While acknowledging that the meaning of alcohol- and marijuana-related attributions may be significantly influenced by the base rates, social acceptance, and population attitudes about these substances’ respective use, several hypotheses will be evaluated. First, (1) harms attributed to others’ marijuana use will be lower than those seen to stem from alcohol. Additionally, (2) there may be important differences in the types of harms reported, as well as (3) differences in the characteristics of people reporting particular types of harms from the two substances. Despite the legality of cannabis in Washington State, the illegality of marijuana at the federal level may still be relevant to perceptions of harms, such that (4) non-users may have a lower threshold than users for attribution of problems due to someone else’s use of marijuana.
Materials and Methods
Sample
The study includes data from repeated cross-sectional telephone surveys of residents in the state of Washington. The institutional review boards of ICF, Inc., Fairfax, VA (the fieldwork organization), and the Public Health Institute, Oakland, CA, approved the study protocols. The sample (N=4,290) consists of five state-representative surveys of adults ages 18 and over. State probability sampling was accomplished through list-assisted random digit dialing (RDD), with more than 40% of cases acquired from cell phone exchanges. Surveys were conducted by computer-assisted telephone interviewing. Participants received a $10 gift card or code to a major online retailer. Sample sizes and interview dates are presented in Table 1. AAPOR2 cooperation rates ranged from 42% to 51% in the landline samples, and from 60% to 63% in the mobile samples (The American Association for Public Opinion Research 2011).
Table 1.
Sample Demographics from the Washington Surveys, by Year
|
2014 |
2015 |
2016 |
||||
| Fielding Period | August 2014 - October 2014 | March 2015 - November 2015 | March 2016 - December 2016 | |||
| Sample Size | 804 | 1,485 | 2,001 | |||
| Weighted % | (n’s) | Weighted % | (n’s) | Weighted % | (n’s) | |
| Sex | ||||||
| Male | 49.6% | (355) | 49.6% | (644) | 49.7% | (870) |
| Female | 50.4% | (449) | 50.4% | (841) | 50.4% | (1,131) |
| Age | ||||||
| 18–29 | 22.8% | (127) | 21.7% | (166) | 21.9% | (218) |
| 30–39 | 16.4% | (103) | 18.4% | (177) | 18.8% | (227) |
| 40–49 | 17.3% | (115) | 15.9% | (200) | 15.1% | (243) |
| 50–59 | 18.4% | (158) | 17.3% | (291) | 16.8% | (371) |
| 60+ | 25.1% | (286) | 26.7% | (600) | 27.3% | (901) |
| Race/Ethnicity | ||||||
| White | 75.1% | (665) | 75.0% | (1,273) | 73.5% | (1,687) |
| Black | 4.8% | (28) | 4.1% | (39) | 4.2% | (54) |
| Hispanic | 9.5% | (39) | 9.6% | (62) | 9.8% | (81) |
| Other | 10.7% | (72) | 11.4% | (111) | 12.5% | (179) |
| Education | ||||||
| <High School | 10.5% | (33) | 9.5% | (72) | 9.6% | (79) |
| High School | 24.9% | (146) | 24.4% | (278) | 25.0% | (328) |
| Some College | 33.8% | (256) | 34.6% | (455) | 34.3% | (601) |
| College | 30.9% | (365) | 31.5% | (672) | 31.2% | (991) |
| Marital Status | ||||||
| Never Married | 32.3% | (200) | 32.9% | (343) | 32.9% | (442) |
| Married | 48.3% | (411) | 47.4% | (734) | 46.8% | (1,052) |
| Separated/Divorced | 14.9% | (125) | 14.5% | (257) | 14.0% | (309) |
| Widowed | 4.5% | (65) | 5.2% | (141) | 6.3% | (193) |
| Drinking Status | ||||||
| 5+ Drinker | 15.3% | (89) | 13.4% | (143) | 12.9% | (179) |
| Drinker | 54.2% | (472) | 57.6% | (899) | 56.9% | (1,211) |
| Non-Drinker | 30.6% | (243) | 29.0% | (443) | 30.2% | (611) |
| Marijuana User | ||||||
| Daily User | 10.2% | (56) | 10.2% | (99) | 11.3% | (146) |
| Weekly User | 5.1% | (35) | 6.1% | (81) | 8.1% | (105) |
| Monthly or less | 11.7% | (77) | 9.9% | (137) | 12.3% | (228) |
| Non-User | 73.1% | (632) | 73.8% | (1,158) | 68.3% | (1,517) |
Note: 2014 involved one cross-sectional survey; 2015 and 2016 each involved two cross-sectional surveys
Measures
Alcohol-attributed harms were determined using a series of questions from the National Alcohol Survey (NAS) series (Greenfield et al. 2015; Karriker-Jaffe, Greenfield & Kaplan 2017) assessing harms attributed to others’ drinking in the last 12 months. Family/marital problems, financial trouble, and vandalism were determined using the following questions: “How many times in the last 12 months have you had family problems or marriage difficulties due to someone else’s drinking”, “…had financial trouble because of someone else’s drinking” and “…had your house, car or property vandalized by someone who had been drinking?” The following question was used to determine if respondents experienced any assault from others drinking: “How many times in the last 12 months did someone who had been drinking harm you physically?” Response options were: “More than once”, “Once”, or “Never in the last 12 months”. Lastly, vehicular harm from others’ drinking (yes/no) used the question: “In the last 12 months, has someone else who had been drinking been responsible for a traffic accident you were involved in?”
Marijuana-attributed harms in the 2014 and 2015 surveys were determined using one ‘collapsed’ question covering the five above harms: “How many times in the last 12 months have you experienced any problems because of someone else’s use of marijuana, such as family or marriage difficulties, traffic accidents, vandalism, physical harm or financial difficulties?” The response options for this question were “More than once”, “Once”, or “Never in the last 12 months”. In 2016 only, the surveys assessed marijuana harms individually. Five items detailed above were worded equivalently to the questions for alcohol-attributed harms (e.g., “family or marital problems due to someone else’s use of marijuana”). The sixth item, asked separately for alcohol and marijuana, was: “How many times in the last 12 months did someone who had been [drinking/using marijuana] harass or bother you?” with the same three response options for all but the vehicular harm item, which was dichotomous (yes/no).
We used the following demographic variables: sex (male vs. female as referent); age (18–29, 30–39, 40–49, 50–59 vs. 60+ as referent); race/ethnicity (Black, Hispanic, Other [all other groups, mainly Asian, Pacific Islander and American Indian] vs. White as referent); educational attainment (less than high school, high school graduate, some college vs. college graduate or higher as referent); and marital status (never married, separated/divorced, widowed vs. married/living with partner as referent). Rates of harm also were reported for groups defined by drinking status (current drinker with at least one day of 5+ drinks in the last 12 months, current drinker with no 5+ days vs. 12-month non-drinker as referent) and past-year marijuana use (daily or near daily user, weekly user, monthly or less user vs. non-user as referent).
Statistical Analyses
The data were weighted to adjust for unequal probabilities of selection and to make the weighted sample representative of all adults (18 and older) residing in the State of Washington at the time of data collection. The sample weights were post-stratified to reflect the population estimates from the American Community Survey for education, gender by age, and gender by race/ethnicity using a raking system.
In comparing experience of any of the five harms for alcohol and marijuana, we used a dichotomous (yes/no) variable including the same content as the single marijuana question posed in 2014 and 2015. Affirming any of the five items was taken as harm from another drinker in the last 12 months. In 2016, individual dichotomous variables were created for the six distinct marijuana and alcohol harms in the prior 12 months. An additional indicator variable (yes/no) identified those experiencing both an alcohol harm and a marijuana harm from another user(s). We examined the prevalence of alcohol, marijuana and both harms across demographic groups. Next, for the combined 2016 survey data, we examined the individual prevalence of each of the six specific alcohol and marijuana harm domains and tested prevalence differences between substances using McNemar’s test (Hays 1994). Finally, we examined trends in the five alcohol and marijuana harms in order to assess the stability of reported harms over time and potential trends. All analyses were performed in STATA version 14 (Stata Corp., 2015), which generated robust standard errors for analyses applying sampling weights.
Results
Table 1 presents the sample characteristics across the three years. The samples are generally very similar, but there was an increase in the prevalence of past-year marijuana use in 2016, as shown in prior analyses (Subbaraman & Kerr 2020). Population and subgroup rates of experiencing any of five harms from others’ alcohol or marijuana use, and rates of experiencing harms from both substances, are presented in Table 2. Each characteristic was tested separately in each column to identify significant group differences. Women were significantly more likely than men to report both alcohol- and marijuana-attributed harms from others. Age patterns differed between alcohol- and marijuana-attributed harms, with the highest rates in the 18–39 groups for alcohol, while for marijuana (and both substances) rates of harms from others were similar among age groups. Race/ethnicity groups differed in rates of harms for each substance, with the “Other” ethnicities group reporting more harms from other drinkers, but fewer harms from both substances. Educational attainment had a significant association with rates of marijuana harms with the some college education (but no degree) group having the highest rates of harms from others’ marijuana use and both types of harms. Compared to married respondents, those never married had especially high exposure to harms from others’ alcohol use, while separated or divorced individuals reported more (though not significantly) harms from others’ marijuana use.
Table 2.
Associations of Individual Characteristics with Alcohol, Marijuana and Both Harms from Others’ in Washington 2014 – 2016 (combined total n= 4,290)
| Alcohol Harmsa | Marijuana Harmsa | Both Harmsb | ||||
|---|---|---|---|---|---|---|
| n=1,004 | n=369 | n=175 | ||||
| Weighted % | (95% CI) | Weighted % | (95% CI) | Weighted % | (95% CI) | |
| Total | 21.3% | (19.5, 23.1) | 8.4% | (7.4, 9.5) | 4.3% | (3.6, 5.2) |
| Year | ||||||
| 2014 (ref) | 24.4% | (20.8, 28.3) | 9.0% | (7.0, 11.6) | 4.1% | (2.8, 6.1) |
| 2015 | 19.2%* | (16.6, 22.0) | 8.6% | (7.0, 10.5) | 3.8% | (2.7, 5.2) |
| 2016 | 21.8% | (19.0, 24.9) | 7.9% | (6.3, 9.8) | 4.9% | (3.6, 6.5) |
| Sex | ||||||
| Male (ref) | 17.0% | (14.7, 19.7) | 6.8% | (5.5, 8.5) | 3.1% | (2.2, 4.3) |
| Female | 25.4%** | (23.0, 28.0) | 9.9%** | (8.4, 11.6) | 5.5%** | (4.4, 6.9) |
| Age | ||||||
| 18–29 (ref) | 29.2% | (24.7, 34.2) | 8.2% | (5.9, 11.1) | 4.6% | (3.0, 7.2) |
| 30–39 | 28.3% | (23.4, 33.8) | 9.4% | (6.7, 13.0) | 5.8% | (3.8, 8.9) |
| 40–49 | 18.2%** | (14.6, 22.6) | 7.5% | (5.3, 10.4) | 3.1% | (1.8, 5.2) |
| 50–59 | 20.9%** | (17.2, 25.1) | 10.1% | (7.6, 13.3) | 5.9% | (4.1, 8.4) |
| 60+ | 12.7%** | (10.8, 14.9) | 7.5% | (6.0, 9.3) | 2.7% | (2.0, 3.8) |
| Race/Ethnicity | ||||||
| White (ref) | 19.8% | (18.1, 21.6) | 8.6% | (7.5, 9.9) | 4.3% | (3.5, 5.3) |
| Black | 19.8% | (10.9, 33.3) | 12.5% | (7.2, 20.9) | 9.1% | (4.6, 17.2) |
| Hispanic | 26.3% | (19.1, 34.9) | 7.6% | (4.2, 13.3) | 4.5% | (2.2, 9.1) |
| Other | 27.1%* | (21.2, 33.9) | 5.9% | (3.7, 9.3) | 2.1%* | (1.0, 4.3) |
| Education | ||||||
| <High School | 27.6% | (20.2, 36.6) | 8.0% | (4.5, 14.0) | 3.2% | (1.6, 6.5) |
| High School (ref) | 20.8% | (17.2, 24.8) | 5.6% | (3.9, 8.0) | 3.2% | (1.9, 5.3) |
| Some College | 23.1% | (20.2, 26.3) | 11.3%** | (9.3, 13.6) | 5.8%* | (4.3, 7.8) |
| College | 17.8% | (15.6, 20.1) | 7.6% | (6.3, 9.1) | 3.8% | (2.9, 5.0) |
| Marital Status | ||||||
| Never Married | 27.2%** | (23.6, 31.2) | 7.8% | (6.0, 10.0) | 4.9% | (3.4, 6.9) |
| Married (ref) | 17.9% | (15.8, 20.2) | 7.9% | (6.6, 9.5) | 3.7% | (2.9, 4.9) |
| Separated/Divorced | 22.1% | (18.0, 26.7) | 11.6% | (8.5, 15.6) | 4.8% | (2.9, 7.7) |
| Widowed | 13.5% | (9.5, 18.9) | 8.1% | (5.3, 12.1) | 4.5% | (2.4, 8.4) |
| Drinking Status | ||||||
| 5+ Drinker | 30.3%** | (24.6, 36.7) | 8.9% | (6.0, 12.8) | 4.0% | (2.3, 7.0) |
| Drinker | 19.1% | (17.0, 21.5) | 6.8%** | (5.7, 8.2) | 3.8% | (2.9, 4.9) |
| Non-Drinker (ref) | 21.2% | (18.2, 24.4) | 11.1% | (9.0, 13.6) | 5.4% | (4.0, 7.3) |
| Marijuana User | ||||||
| Daily User | 31.6%** | (24.9, 39.2) | 3.5%** | (1.9, 6.3) | 2.5%* | (1.2, 5.3) |
| Weekly User | 29.3%** | (21.9, 38.0) | 7.1% | (3.3, 14.6) | 3.6% | (1.5, 8.5) |
| Monthly or Less | 30.2%** | (24.5, 36.5) | 6.7% | (4.3, 10.4) | 4.3% | (2.3, 7.8) |
| Non-User (ref) | 17.5% | (15.7, 19.4) | 9.5% | (8.3, 10.9) | 4.6% | (3.8, 5.7) |
Note:
Experiencing any of the five harms from other’s (physical harm, traffic accident, vandalism, family problems, and financial trouble)
Subsample with both alcohol and marijuana harms, also included in other two columns
p<0.05
p<0.01
The prevalence of harms from others also varied greatly by respondents’ own drinking and marijuana use status. Heavy drinkers who reported at least one day consuming 5 or more drinks in the past year had significantly higher rates of harms attributed to other drinkers than lighter drinkers and non-drinkers. Marijuana users, regardless of use frequency, also had higher rates of harms from others’ alcohol use than non-users. In contrast, the lowest rates of harms due to others’ marijuana use were seen among non-heavy drinkers while harms from both alcohol and marijuana use by others did not differ by drinker type. Marijuana use frequency was related to harms from others’ use and to having both alcohol and marijuana harms, with daily or near-daily users reporting significantly lower rates of harms than non-users, while less frequent users did not differ from non-users.
In the surveys conducted in 2016 only, respondents reported their experiences with six individual types of harms from drinkers and/or marijuana users, adding being harassed or bothered by someone who had been drinking/using marijuana. Table 3 presents the rate of each distinct harm reported for 2016, enabling comparisons between substances in terms of the ratio of rates of alcohol-attributed harms to rates of marijuana-attributed harms (from others). The combined and individual rates of harm attributed to someone else’s drinking were significantly higher than those for someone else’s marijuana use, with the exception of traffic accidents attributed to another driver’s substance use (where the base rates are very low). More than twice as many individuals reported experiencing an alcohol harm than a marijuana harm, with a ratio of 5:2. A 3:1 ratio was the most common for the individual harms, holding for marital/family problems, vandalism and harass/bother, which were the three most prevalent harm types for alcohol. Physical harm was proportionally even greater from alcohol users, with five times the prevalence compared to physical harm from marijuana users. Financial trouble from other users had a closer ratio of about 2:1, and no significant difference was seen for traffic accidents.
Table 3.
Individual Alcohol and Marijuana Harm prevelence in Washington, 2016
| Alcohol | Marijuana | Ratioa | ||||||
|---|---|---|---|---|---|---|---|---|
| % | 95% CI | (N) | % | 95% CI | (N) | |||
| Any of 6-Harms | 35.2% | (32.1, 38.5) | (608) | 13.5%* | (11.5, 15.9) | (281) | 5:2 | |
| Physical Harm | 3.6% | (2.6, 5.0) | (53) | 0.7%* | (0.4, 1.2) | (17) | 5:1 | |
| Traffic Accident | 1.4% | (0.8, 2.4) | (21) | 0.9% | (0.4, 2.3) | (12) | n.s. | |
| Harass/bother | 26.8% | (23.9, 30.0) | (451) | 9.4%* | (7.7, 11.4) | (196) | 3:1 | |
| Vandalism | 6.4% | (4.8, 8.4) | (94) | 2.1%* | (1.3, 3.3) | (43) | 3:1 | |
| Family Problems | 14.3% | (12.0, 17.0) | (243) | 4.9%* | (3.7, 6.5) | (101) | 3:1 | |
| Financial Trouble | 5.2% | (3.8, 7.2) | (80) | 2.5%* | (1.7, 3.7) | (40) | 5:2 | |
Ratio is the approximate ratio of the prevalence of harms due to another’s alcohol use to the prevalence of harms due to someone’s marijuana use
p<0.05, n.s. not significant
Figure 1 presents trends in the five combined harms for alcohol, marijuana and both substances from 2014 to 2016. Although there is some variation in rates, there is no evidence of upward or downward trends over time. Analyses comparing the survey years in Table 2 show that harms from others’ alcohol use were lower in 2015 than in 2014, while no differences between years were found for marijuana harms or experiencing both substances’ harms. As the surveys were sampled and conducted using identical methods and the questions of interest – and most other content – were comparable in the different surveys, the findings of repeatedly high rates of alcohol-attributed harms compared to marijuana-attributed harms in separate random samples strengthens the case for confidence in the relative magnitude of these estimates.
Figure 1.
Prevalence of reporting harms from others’ alcohol and marijuana use for 2014, 2015 and 2016.
Discussion
Although there have been comparisons between alcohol and ‘drug’ attributed harms from others, as noted in the introduction, this study provides the first estimates of harms attributed to others’ marijuana use. Further, it does so for a US state where marijuana use is prevalent, given that adult use and sales were legal under state law. As hypothesized, perceived harms from others’ marijuana use were consistently found to be lower than those from alcohol use, but the relative difference varied across the types of harm. Physical harms were rarely attributed to marijuana, being reported at one-fifth the rate of alcohol-related physical harm from others’ use. This is consistent with the physiological effects of the substances, with alcohol causing sedation at only very high doses compared to a general sedative effect for marijuana. Alcohol use also has been found to be involved in expectancies that lead to aggressive actions (Tedor et al. 2018) and to lead to alcohol myopia (Steele & Josephs 1990), where drinkers focus on proximal stimuli that situationally lead to violent reactivity, with reduced influence of both social controls and the expectation of later consequences. Thus, alcohol use has been associated with violence; indeed, evidence suggests it is a contributing cause to certain types of violence (Boles & Miotto 2003) such as intimate partner violence (Murphy & Ting 2010). Further, at the time of our surveys, there were no on-premise marijuana establishments allowed in Washington. Other work suggests on-premise bars and clubs are associated with alcohol-related violence (Popova et al. 2009; Treno et al. 2008).
While still lower than alcohol-attributed harm rates, rates reported for traffic accidents and financial harm attributed to others’ marijuana use were closer to rates of these harms attributed to alcohol. If following patterns for alcohol harms (Karriker-Jaffe, Greenfield & Kaplan 2017), traffic harms may come mainly from friends’ or strangers’ marijuana use, while financial harms are mostly likely attributed to use of family members or significant others (partners/spouses). Financial harms might include spending on marijuana, which remains expensive under the legal sales regime in Washington (Smart et al. 2017), and also could include employment problems related to chronic marijuana use (or related to any use, in jobs requiring drug testing), as well as potential costs of dealing with a family member’s or partner’s substance use disorder. The three most common types of harm attributed to alcohol (being harassed/bothered, family/marital problems, vandalism) had a 3:1 ratio to parallel reported harms attributed to marijuana. Alcohol use remains more prevalent and more public than marijuana use, which may contribute to perceptions of its involvement in vandalism and harassment. Even with legal sales, there were no on-premise establishments allowing marijuana use, and public use was also prohibited by state law, making marijuana use less visible than alcohol (Dilley et al. 2017). These restrictions may be less relevant for perceptions of family problems, and future research should investigate contextual interventions and policies with potential to help control these secondhand harms due to others’ marijuana use.
While women reported more harms from others’ use of both alcohol and marijuana in similar proportions, some other key characteristics of people harmed differed between the substances, particularly age. Alcohol harms from others declined with age, being highest among those under 40 and lowest for those 60 and older, while marijuana harms did not vary significantly by age. This suggests that marijuana harms from others may occur more often within families. Perhaps relatedly, alcohol harms from others’ use were reported most frequently by never married respondents, while marijuana harms showed no significant differences across groups defined by marital status.
In Washington, reported rates of harms attributed to other marijuana users were lowest among the most frequent users, in contrast with harms attributed to other drinkers, which tend to be highest among heavier drinkers (Karriker-Jaffe, Greenfield & Kaplan 2017). This could be due in part to attributional bias, where frequent users are less likely to attribute problems to others’ marijuana use than others, despite likely greater exposure to others’ marijuana use. Exposure to other heavy drinkers has been invoked as accounting for greater secondhand alcohol harms among heavier drinkers (Greenfield et al. 2016; Kaplan, Karriker-Jaffe & Greenfield 2017). Frequent marijuana users may also be more likely to have a medical recommendation, which has been linked to lower risk for alcohol problems (Subbaraman & Kerr 2018). This finding differed from our hypothesis that marijuana users would be less likely to report harms than non-users. Weekly and monthly users did not have significantly lower rates of marijuana harms from others compared to non-users. Future studies should consider how the most frequent users may differ from others in both their experience and attribution of marijuana harms.
A surprising finding was that rates of some harm types attributed to others’ alcohol use in Washington were found to be substantially larger than concurrent US population rates. In the 2015 US National Alcohol Survey, where the same questions were utilized (Greenfield et al. 2015), the rate of family/marital problems was 3.7% compared to the current estimate of 14.3% in Washington, the rate of financial troubles was 1.9% compared to 5.2% in Washington, and the rate of vandalism was 2.8% compared to 6.4% in Washington. However, the rate of experiencing physical harm from someone else’s drinking was 3.8%, similar to the 3.6% reported here for Washington. Washington is one of the heaviest marijuana-using states (Hughes, Lipari & Williams 2016), and it was among the first states to allow legal medical marijuana and, later, marijuana sales for adult use. Thus, relatively high rates of harms would be expected. However, population means for common alcohol use indicators are not especially high for Washington (Kerr 2010). For example, per capita consumption of ethanol was below the national average in 2014, 2015 and 2016 (Martinez et al. 2019). Additionally, estimates from the National Survey on Drug Use and Health for Washington show that the proportion of drinkers in the past month was higher than the national average, while the proportions of past month binge drinkers and those with alcohol use disorders were lower (Center for Behavioral Health Statistics and Quality 2017). However, the rates of alcohol-attributed harms from others seen in these Washington samples suggest a need for national surveys to include additional measures of alcohol problems to better account for alcohol-related harms. Our surveys also have documented high rates of simultaneous alcohol and marijuana use in Washington (Kerr et al. 2018), with increased rates of alcohol problems among this group (Subbaraman & Kerr 2015). Thus, co-use may create a situation where heavy alcohol use is more problematic for the user, as well as to others around the user. In the future it will be important to estimate harms owing to multiple substances, especially co-use of alcohol and marijuana.
Study limitations include the inherently subjective nature of these rather broad types of harm from others’ use and particularly their attribution to alcohol and marijuana. Some people report both types of harms, and we do not have details regarding overlap in purported perpetrators, or whether both substances were perceived to have contributed to the same harm event in some cases. Alleged perpetrators in either instance (alcohol or marijuana) may also have used other drugs such as opioids, cocaine, or methamphetamine, which would also be expected to engender harms to others. Additionally, perceived perpetrators might have mental health issues that interact with alcohol and/or marijuana use, resulting in problematic behaviors in general. We do not assess the severity or frequency of each harm type, but this will vary and may be important for identifying the most significant impacts of secondhand harms. Additionally, in the earlier surveys, harms from others’ marijuana use were asked in a composite item, which limited our ability to look at specific harm types over time.
Among its strengths, this study provides the first estimates of perceived harms from others’ marijuana use and compares these with harms in the same domains, and for the same timeframe, to those attributed to others’ alcohol use. The findings indicate the importance of studying perceptions of harms stemming from others’ marijuana use in the population. These results also suggest the potential for and importance of measuring harms attributed to others’ use of additional prevalent drug types, including opioid painkillers, heroin, cocaine or methamphetamine. The harms from others approach also offers an alternative to surveys of individuals’ own use and self-reported social problems, arrests and substance-related consequences (Warpenius & Tigerstedt 2016). We know that there is potentially substantial under-reporting of use and problems, particularly for illegal substances (Kerr et al. 2018). Reports from the victim’s perspective may be important to supplement individual’s reports of their own use and problems. In survey studies, there often is limited assessment of domains such as criminal activity and serious health and social impacts on others in the community from a participant’s own substance use. Further, such self-reports may be biased downward by denial, and reports from victims may be useful for fully describing the public health impacts of substance use.
Interventions are unequivocally needed to reduce secondhand harms from alcohol and marijuana use. The self-identified victim may not always be correct in their attributions, but we believe their perspective needs to be taken into account, especially when robust, counterfactual methods suggest these perceived harms, in the case of heavy drinking others, may be associated with lower mental health compared to like individuals who do not report such harms (Karriker-Jaffe, Li & Greenfield 2018). Extension of the harm to others paradigm to other drugs—here, marijuana—provides an opportunity to document a broader range of harms, including those to specific individuals and to society at large. Future research and policy work in this area should take care to balance a public health approach with more individualistic, targeted measures (Karriker-Jaffe et al. 2018) to reduce harms attributed to marijuana and other drugs.
Acknowledgements:
This work was supported by the U.S. National Institute on Alcohol Abuse and Alcoholism (NIAAA) at the National Institutes of Health (NIH) (grant numbers R01 AA021742, R01 AA022791 and P50 AA005595). Content and opinions are those of authors and do not reflect official positions of NIAAA or the National Institutes of Health.
Footnotes
Declaration of Interest: None to declare.
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