Abstract
Alcohol consumption is prevalent in young adult women and linked with breast cancer risk. Research to inform interventions targeting alcohol consumption as a breast cancer prevention strategy is limited. We examined young women’s awareness of alcohol use as a breast cancer risk factor, identified correlates of awareness, and determined how awareness and conceptual predictors relate to intentions to reduce drinking. Women aged 18–25 years who drank alcohol in the past month (N = 493) completed a cross-sectional survey. Measures captured sociodemographics, breast cancer risk factors, awareness of alcohol use as a breast cancer risk factor, intentions to reduce drinking, and conceptual predictors. Analyses examined correlates of awareness and associations between awareness, conceptual predictors, and intentions to reduce drinking. Awareness was low (28%) and intentions to reduce drinking were moderate (M = 2.60, SD = 0.73, range 1–4). In multivariable analyses, awareness was associated with greater worry about cancer, beliefs that there’s not much one can do to reduce cancer risk and everything causes cancer, higher perceived breast cancer risk, and stronger beliefs that reducing drinking reduces breast cancer risk. Awareness was not associated with intentions to reduce drinking. Younger age, older age of alcohol initiation, negative attitudes towards alcohol, fewer friends consuming alcohol, and stronger self-efficacy were associated with intentions to reduce drinking. Few young women recognize alcohol consumption as a breast cancer risk factor. Researchers and policymakers can apply our findings to design new or refine existing interventions to optimize their impact on awareness and alcohol consumption in young women.
Keywords: alcohol use, breast cancer, intentions to reduce alcohol use, young adult women, theory-guided design
A survey among young adult women identified new factors to increase the awareness of alcohol use as a breast cancer risk factor and reduce alcohol consumption.
Implications.
Practice: Practitioners can increase the salience of alcohol use as a breast cancer risk factor in young women by using messaging combining information about the breast cancer risks of alcohol consumption and the benefits of reducing drinking.
Policy: Policymakers can develop effective strategies for reducing alcohol consumption by targeting potential underlying determinants of drinking, including social and environmental factors (e.g. targeting initiation age and counter marketing strategies).
Research: Future research should further examine associations between behavioral beliefs (e.g. awareness of cancer risks), attitudes, subjective norms, and self-efficacy to inform interventions to reduce alcohol consumption in young women as a breast cancer prevention strategy.
Introduction
Alcohol is a known carcinogen, contributing to the development of at least seven different cancers, including female breast cancer [1]. Alcohol is hypothesized to increase breast cancer risk by increasing serum estrogen levels [2, 3]. During young adulthood, breast tissue is vulnerable to exposures that increase breast cancer risk later in life, including alcohol use, due to the rapid proliferation, and incomplete differentiation of breast cells between menarche and first full-term pregnancy [4–7]. Research has consistently shown dose-dependent associations between alcohol consumption before first pregnancy and breast cancer risk, with stronger associations observed among those with longer menarche to first pregnancy intervals [8]. Alcohol consumption during young adulthood is also consistently associated with increased risk of proliferative benign breast disease, a strong risk factor for breast cancer [8–10]. Taken together, this evidence indicates that young adulthood is a critical period where reducing alcohol consumption may be an important breast cancer prevention strategy [5].
Despite the evidence linking alcohol consumption with cancer, awareness of the cancer risks of alcohol consumption overall (i.e. not by specific cancer type) is disturbingly low [11]. Among U.S. adults awareness decreased from 38% in 2019 to 34% in 2021 [12], and research on awareness of alcohol consumption as a breast cancer risk factor among young adult women is extremely limited [13]. This is concerning because young adulthood is a period where substance use behaviors are often established and become entrenched [14] and where alcohol consumption, particularly binge drinking, is prevalent [15].
Alcohol companies have systematically influenced awareness of and beliefs about the cancer risks from alcohol consumption [16–19], and they have targeted breast cancer [20] by denying and misrepresenting the breast cancer risks from drinking alcohol [19]. Alcohol companies also “pinkwash” marketing with breast cancer awareness branding to promote positive brand imagery, convey philanthropic support, and direct public attention away from alcohol-associated breast cancer risks [20]. This industry behavior is concerning for young women who are regularly exposed to and targeted by alcohol marketing, which is associated with increased alcohol use [21–24], and further highlights the need for interventions.
Interventions to raise awareness of the breast cancer risks from alcohol consumption may include public education messaging communicating the breast cancer risks associated with alcohol use, as has been successful to raise awareness in other settings [25–27]. Although such interventions may motivate some to reduce alcohol consumption, multiple strategies are likely needed to achieve the goals of raising awareness and decreasing alcohol consumption [28]. A recent review by Gapstur and colleagues [29] demonstrates that research to inform interventions to increase awareness of alcohol consumption as a breast cancer risk factor and reduce alcohol consumption as a breast cancer prevention strategy in young women is extremely limited and does not elucidate modifiable intervention targets (e.g. attitudes, beliefs). To address these research gaps, the objectives of this study were to: (i) characterize young adult women’s awareness of alcohol consumption as a breast cancer risk factor, (ii) examine correlates of awareness that may be intervention targets, and (iii) examine if awareness and other conceptual predictors are associated with intentions to change alcohol consumption. Our study was guided by prior research and health behavior theories. To examine correlates of awareness, we captured sociodemographics, known breast cancer risk factors (e.g. family history), and cancer-related beliefs associated with awareness of alcohol consumption as a risk factor for cancer in prior research [13, 30]. We also drew from health behavior theories indicating that beliefs about risk (e.g. perceived risks of breast cancer due to alcohol consumption) and efficacy (e.g. the belief that drinking less alcohol reduces breast cancer risk) are important targets of interventions to increase the salience of health risks [31, 32]. To assess associations with intentions to reduce alcohol consumption, we drew from the integrated behavioral model (IBM) to capture social norms, attitudes, and self-efficacy to change alcohol consumption [31]. We examined if awareness of alcohol consumption as a breast cancer risk factor, correlates of awareness, and constructs from the IBM are associated with intentions to reduce drinking.
Methods
Participants and procedures
From April to August 2022, we recruited young adults aged 18–25 years who identified their biological sex as female, resided in Ohio, and reported drinking alcohol at least once in the past 30 days for a cross-sectional online survey for “a study about what women know, think, and feel about alcohol consumption.” We recruited participants using social media advertising, university email distribution lists, and word of mouth referrals. Those responding to recruitment advertisements provided contact information and completed an online screener assessing age, sex, and alcohol consumption. We reviewed screener and survey responses for data quality using methods recommended for research using remote screening and data collection (e.g. accuracy of contact information, consistency of responses to sociodemographic questions, potential duplicate responses) [33]. We contacted potential participants when clarification was needed to confirm their responses and excluded those whose eligibility could not be confirmed or who did not meet data quality checks. We sent those meeting eligibility criteria a secure, personal web link to complete the survey. All participants provided informed consent and those completing the survey received a $20 gift card. The host university’s institutional review board approved study procedures. Eligible, consenting participants completed a self-report online survey with measures described below.
Measures
Dependent variables
Awareness of alcohol use as a breast cancer risk factor
We measured participants’ awareness of alcohol consumption as a risk factor for breast cancer using the following validated measure [34]: “How much do you agree or disagree that each of these can increase a woman’s chance of getting breast cancer?” A list of risk factors followed, including “Having more than 1 alcoholic drink a day.” Response options included, 1 = “Strongly Disagree,” 2 = “Disagree,” 3 = “Not Sure,” 4 = “Agree,” and 5 = “Strongly Agree.” We dichotomized this outcome and defined awareness as those who indicated Agree or Strongly Agree.
Intentions to reduce alcohol consumption
Two items assessed intentions to reduce alcohol consumption [35]. We asked, “Within the next week, how likely are you to avoid drinking alcohol completely?” and “Within the next week, how likely are you to reduce the amount of alcohol you have on each drinking occasion?” Responses were on a 1 (Definitely Will Not) to 4 (Definitely Will) scale and were averaged to create an intentions to reduce alcohol use variable (r = 0.52, Cronbach α = 0.69), with higher values indicating greater intentions.
Independent variables
Sociodemographic characteristics
We assessed sociodemographic characteristics, including age, ethnicity/race (non-Hispanic white, minority ethnic/racial group), and education (some college or less, college graduate or beyond).
Family breast cancer history
We assessed family history of breast cancer using a single item [36]. Participants were asked the following question: “Please indicate if your first-degree relatives have been diagnosed with any of the types of cancer listed below. Your first-degree relatives include your parents, brothers, sisters, and children if you have children.” Breast cancer was listed with response options of “Yes,” “No,” and “Not Sure.” We created a binary variable, defined as having first-degree family history of breast cancer for those who indicated yes, and those who indicated No or Not Sure as not having family history.
Alcohol consumption
We assessed age of initiation by asking “How old were you the first time you had an alcoholic drink, this is more than a couple of sips?” and drinks per drinking day consumed by asking “During the past 30 days, on the days when you drank, about how many alcoholic drinks did you have on average?” with response options ranging from 1 to 30.
Cancer beliefs
We measured cancer worry [30] by asking “How worried are you about getting cancer?” with five response options ranging from “Not at all” to “Extremely.” We assessed cancer fatalism and cancer cause ambiguity with two items where participants indicated their level of agreement or disagreement on a 4-point scale. We assessed cancer cause ambiguity [30] using “It seems like everything causes cancer” and cancer fatalism [30] using “There’s not much you can do to lower your chances of getting cancer.”
Health literacy
We defined health literacy as the sum score of the brief health literacy screening tool (BRIEF) 4-item screener [37], with higher scores indicating more adequate health literacy (Cronbach’s α = 0.78).
Risk and efficacy beliefs
We assessed risk beliefs using two items capturing cognitive and affective aspects of perceived risks [32, 38]. We measured perceived likelihood of risk by asking “What do you think is your chance of getting breast cancer from drinking alcohol?” Responses were on a 1 (No chance) to 7 (Certain to Happen) scale. We measured worry about risk by asking “How worried are you about getting breast cancer if you continue to drink alcohol?” Responses ranged from 1 (Not at all) to 7 (Very Much).
We measured efficacy beliefs using two items [39]. We captured self-efficacy surrounding alcohol consumption and breast cancer by asking “How confident are you that you can reduce the amount of alcohol you drink to lower your chances of getting breast cancer?” We measured response-efficacy by asking “How likely will it be that your risk of getting breast cancer will be lower if you reduce the amount of alcohol you drink?” Items used a 7-point scale ranging from “Not at all confident/likely” to “Very confident/likely.”
IBM measures
We measured global attitudes towards alcohol consumption by averaging responses to 10 items with a 1 to 9 bipolar scale [38] with higher scores indicating increasingly negative attitudes (Cronbach’s α = 0.87). We measured alcohol norms [40] by asking, “How many of your five closest friends drink alcohol at least once a month?” Self-efficacy was defined as the average response of two items asking, “How confident are you that you can drink less alcohol?” and “How easy will it be for you to drink less alcohol?” on a 7-point scale from 1 = “Not at all confident/Not at all easy” to 7 = “Completely confident/very easy”. Higher scores indicated higher self-efficacy (Cronbach’s α = 0.81) [41].
Statistical analysis
We used descriptive statistics to characterize the sample and awareness of alcohol consumption as a breast cancer risk factor. We used bivariate analyses to assess associations between study outcomes (awareness and intentions to reduce alcohol consumption) and all other study measures, including Pearson’s correlation for continuous variables and independent samples t-test/Chi-square test for categorical variables. For each outcome, we used a series of multivariable regression models to examine factors associated with awareness of alcohol consumption as a breast cancer risk factor (logistic) and how awareness and other conceptual predictors are associated with intentions to reduce alcohol consumption (linear). We added blocks of variables sequentially based on theoretical reasoning [42] and compared the nested models. For awareness, the first block included sociodemographics, alcohol consumption measures, and cancer risk factors and beliefs. The second block included measures of risk beliefs and efficacy beliefs. For intentions to reduce alcohol consumption, the first block included all the predictors examined for awareness, in addition to awareness. The second block included IBM predictors. We report model summary statistics for each independent variable. Missingness was minimal (<1%) so we conducted a complete case analysis. All model assumptions were checked and satisfied, and we conducted all analyses with SAS 9.4 (Cary, NC).
Results
Participant characteristics
In total, 663 participants completed screening, 579 met initial eligibility screening (87.3%), and 497 (85.8%) of eligible participants satisfied data quality checks and completed procedures. Of those 497, four had missing information on study outcomes, leaving 493 included in the analyses. The average age of participants was 22.0 (SD = 1.94) years with an average age of alcohol initiation of 17.0 (SD = 2.10) years. Most participants were non-Hispanic White (81.3%) and had some college or less education (50.7%) (Table 1). The overall cancer worry (M = 2.93, SD = 1.04, range 1–5), cancer cause ambiguity (M = 2.08, SD = 0.74, range 1–4), breast cancer risk worry (M = 3.91, SD = 1.52, range 1–7), and attitudes towards alcohol (M = 4.95, SD = 1.14, range 1–9) were moderate (Table 1). Additionally, the overall cancer fatalism (M = 2.97, SD = 0.74, range 1–4), self-efficacy of alcohol use and breast cancer (M = 5.77, SD = 1.36, range 1–7), response-efficacy of alcohol use and breast cancer (M = 5.03, SD = 1.65, range 1–7), and alcohol self-efficacy (M = 5.21, SD = 0.97, range 1–7) were high (Table 1).
Table 1.
Study sample characteristics (N = 493)
| N (%) | M (SD) | |
|---|---|---|
| Race/Ethnicity | ||
| Non-Hispanic White | 401 (81.3) | |
| Minority ethnic/racial group | 92 (18.7) | |
| Education | ||
| Some college or less | 250 (50.7) | |
| College graduate or beyond | 243 (49.3) | |
| Age, years | 22.0 (1.94) | |
| Alcohol age of Initiation, years | 17.0 (2.10) | |
| Drinks per drinking day in past 30 days | 3.1 (3.97) | |
| First-degree relatives cancer history | ||
| No | 469 (95.1) | |
| Yes | 24 (4.9) | |
| Cancer worry (scale 1–5) | 2.93 (1.04) | |
| Cancer fatalism (scale 1–4) | 2.97 (0.74) | |
| Cancer cause ambiguity (scale 1–4) | 2.08 (0.74) | |
| Perceived Likelihood of Risk of Breast Cancer (Scale 1–7) | 3.63 (1.05) | |
| Breast cancer risk worry (scale 1–7) | 3.91 (1.52) | |
| Self-efficacy of alcohol use and breast cancer (scale 1–7) | 5.77 (1.36) | |
| Response-efficacy of alcohol use and breast cancer (scale 1–7) | 5.03 (1.65) | |
| BRIEF Health Literacy Score | 17.59 (2.47) | |
| Attitudes towards alcohol (scale 1–9) | 4.95 (1.14) | |
| Alcohol subjective norms (scale 0–5) | 4.24 (1.14) | |
| Alcohol self-efficacy (scale 1–7) | 5.21 (0.97) | |
| Awareness of alcohol as risk factor for breast cancer | ||
| No | 357 (72.4) | |
| Yes | 136 (27.6) | |
| Intentions to reduce alcohol use (scale 1–4) | 2.60 (0.73) | |
Awareness of alcohol consumption as a breast cancer risk factor
Overall, 28% of participants were aware that alcohol use is a breast cancer risk factor. In bivariate analyses, participants who reported awareness were significantly more likely to be college graduates or higher, older age, reported higher worry about cancer, higher cancer fatalism, lower cancer cause ambiguity, and higher health literacy than those who were not aware (Table 2). Additionally, those who were aware of alcohol consumption as a breast cancer risk factor had higher average scores for perceived risk of breast cancer (3.90, SD = 1.15) and response-efficacy of alcohol use and breast cancer risk (5.43, SD = 1.59) than those who were not aware (3.53, SD = 0.99; 4.88, SD= 1.65; P < .01; respectively) (Table 2).
Table 2.
Bivariate associations with awareness of alcohol and intentions to change alcohol use
| Alcohol awareness | P-value | Intentions to change alcohol use | ||||||
|---|---|---|---|---|---|---|---|---|
| No | Yes | Mean (SD) | r | P-Value | ||||
| N (%) | Mean (SD) | N (%) | Mean (SD) | |||||
| Race/Ethnicity | .68 | .08 | ||||||
| Non-Hispanic White | 292 (81.8) | 109 (80.2) | 2.57 (0.72) | |||||
| Minority ethnic/racial group | 65 (18.2) | 27 (19.8) | 2.72 (0.77) | |||||
| Education | <.01 | .21 | ||||||
| Some college or less | 194 (54.3) | 56 (41.2) | 2.64 (0.73) | |||||
| College graduate or beyond | 163 (45.7) | 80 (58.8) | 2.56 (0.73) | |||||
| Age | 21.81 (1.93) | 22.45 (1.87) | <.01 | −0.11 | .02 | |||
| Alcohol initiation age | 17.10 (2.00) | 16.88 (2.33) | .33 | 0.17 | <.01 | |||
| Drinks per drinking day in past 30 days | 3.16 (4.54) | 2.86 (1.72) | .29 | −0.10 | .03 | |||
| First-degree relatives cancer history | .77 | .90 | ||||||
| No | 339 (95.0) | 130 (95.6) | 2.60 (0.73) | |||||
| Yes | 18 (5.0) | 6 (4.4) | 2.58 (0.76) | |||||
| Cancer worry | 2.84 (1.05) | 3.16 (0.98) | <.01 | −0.01 | .75 | |||
| Cancer fatalism | 2.89 (0.76) | 3.15 (0.64) | <.01 | 0.07 | .15 | |||
| Cancer cause ambiguity | 2.12 (0.75) | 1.96 (0.70) | .03 | −0.06 | .19 | |||
| BRIEF Health Literacy Score | 17.45 (2.46) | 17.95 (2.48) | .04 | −0.08 | .08 | |||
| Perceived likelihood of risk of breast cancer | 3.53 (0.99) | 3.90 (1.15) | <.01 | −0.07 | .11 | |||
| Breast cancer risk worry | 3.83 (1.50) | 4.13 (1.56) | .06 | 0.07 | .12 | |||
| Self-efficacy of alcohol use and breast cancer | 5.74 (1.39) | 5.83 (1.28) | .53 | 0.30 | <.01 | |||
| Response-efficacy of alcohol use and breast cancer | 4.88 (1.65) | 5.43 (1.59) | <.01 | 0.14 | <.01 | |||
| Alcohol awareness | .12 | |||||||
| No | 2.57 (0.71) | |||||||
| Yes | 2.68 (0.79) | |||||||
| Attitudes towards alcohol | 0.23 | <.01 | ||||||
| Alcohol subjective norms | −0.24 | <.01 | ||||||
| Alcohol self-efficacy | 0.33 | <.01 | ||||||
Bold values indicate significant results.
The final multivariable model with sociodemographic, alcohol-related variables, and risk and efficacy beliefs significantly improved the prediction of awareness of alcohol as a breast cancer risk factor (LR = 13.08, P = .01; Table 3). Cancer worry (OR = 1.27, P = .04), cancer fatalism (OR = 1.69, P < .01), cancer cause ambiguity (OR = 0.71, P = .04), perceived likelihood of risk of breast cancer (OR = 1.35, P = .02) and response-efficacy of alcohol consumption and breast cancer risk (OR = 1.19, P = .03) were associated with awareness of alcohol as a risk factor for breast cancer (Table 3).
Table 3.
Multivariable analysis of factors associated with awareness of alcohol as a breast cancer risk factor
| Block I | Blocks I and II | |||||
|---|---|---|---|---|---|---|
| OR (95% CI) | P-value | OR (95% CI) | P-value | |||
| Race/Ethnicity | ||||||
| Non-Hispanic White | Ref | Ref | ||||
| Minority ethnic/racial group | 1.33 (0.78, 2.26) | .30 | 1.23 (0.71, 2.10) | .46 | ||
| Education | ||||||
| Some college or less | Ref | Ref | ||||
| College grad or beyond | 1.01 (0.55, 1.85) | .97 | 1.01 (0.54, 1.86) | .98 | ||
| Age | 1.16 (0.99, 1.36) | .07 | 1.17 (1.00, 1.38) | .06 | ||
| Alcohol initiation age | 0.91 (0.82, 1.01) | .09 | 0.93 (0.83, 1.03) | .17 | ||
| Drinks per drinking day in past 30 days | 0.97 (0.89, 1.05) | .48 | 0.97 (0.88, 1.05) | .44 | ||
| First-degree relatives cancer history | ||||||
| No | Ref | Ref | ||||
| Yes | 0.59 (0.22, 1.61) | 0.55 (0.19, 1.54) | .25 | |||
| Cancer worry | 1.31 (1.06, 1.63) | .01 | 1.27 (1.00, 1.60) | .04 | ||
| Cancer fatalism | 1.79 (1.31, 2.43) | <.01 | 1.69 (1.23, 2.31) | <.01 | ||
| Cancer cause ambiguity | 0.70 (0.51, 0.95) | .02 | 0.71 (0.52, 0.98) | .04 | ||
| BRIEF Health Literacy Score | 1.06 (0.96, 1.17) | .23 | 1.06 (0.96, 1.17) | .23 | ||
| Perceived likelihood of risk of breast cancer | 1.35 (1.06, 1.72) | .02 | ||||
| Breast cancer risk worry | 0.91 (0.76, 1.10) | .33 | ||||
| Self-efficacy of alcohol use and breast cancer | 1.04 (0.87, 1.24) | .69 | ||||
| Response-efficacy of alcohol use and breast cancer | 1.19 (1.02, 1.38) | .03 | ||||
| Block | LL | LR | df | Pr > LR | AIC | BIC |
| 1 | −268.6725 | 42.77 | 10 | <0.01 | 559.3449 | 605.5282 |
| 2 | −262.1321 | 13.08 | 4 | 0.01 | 554.2642 | 617.2414 |
Bold values indicate significant results.
Intentions to reduce alcohol consumption
The overall mean intentions to reduce alcohol use was 2.60 (SD = 0.73, range 1–4). In bivariate analyses, greater intentions to reduce alcohol consumption were correlated with lower age (r = −0.11, P = .02), higher alcohol initiation age (r = 0.17, P < .01), and fewer drinks per drinking day (r = −0.10, P = .03). Greater intentions to reduce alcohol consumption were correlated with higher self-efficacy (r = 0.30, P < .01) and response-efficacy of alcohol use and breast cancer (r = 0.14, P < .01), increasingly negative attitudes towards alcohol (r = 0.23, P < .01), favorable alcohol subjective norms (i.e. lower number of friends who use alcohol) (r = −0.24, P < .01), and higher alcohol self-efficacy (r = 0.33, P < .01) (Table 2).
The final model with sociodemographic, alcohol-related variables, risk and efficacy beliefs, and IBM constructs explained 23.0% of the variance in intentions to reduce alcohol consumption and significantly improved the prediction (R2 = 0.2302, F = 14.68, P < .01). Age (β = −0.05, P = .03), alcohol initiation age (β = 0.04, P = .02), attitudes towards alcohol (β = 0.07, P < .01), subjective norms (β = −0.11, P < .01), and alcohol self-efficacy (β = 0.15, P < .01) were associated with intentions to reduce alcohol consumption (Table 4).
Table 4.
Multivariable analysis of factors associated with behavioral intentions to reduce alcohol consumption
| Block I | Blocks I and II | |||||||
|---|---|---|---|---|---|---|---|---|
| β (95% CI) | P-value | β (95% CI) | P-value | |||||
| Age | −0.05 (−0.10, −0.01) | .02 | −0.05 (−0.10, −0.01) | .03 | ||||
| Race/Ethnicity | ||||||||
| Non-Hispanic White | Ref | Ref | ||||||
| Minority ethnic/racial group | 0.11 (−0.05, 0.27) | .17 | 0.10 (−0.05, 0.26) | .18 | ||||
| Education | ||||||||
| Some college or less | Ref | Ref | ||||||
| College grad or beyond | 0.02 (−0.16, 0.20) | .82 | 0.07 (−0.11, 0.24) | .45 | ||||
| Alcohol initiation age | 0.05 (0.02, 0.08) | <.01 | 0.04 (0.01, 0.07) | .02 | ||||
| Drinks per drinking day in past 30 days | −0.01 (−0.03, 0.00) | .14 | −0.01 (−0.02, 0.01) | .31 | ||||
| First-degree relatives cancer history | ||||||||
| No | Ref | Ref | ||||||
| Yes | 0.04 (−0.25, 0.32) | .80 | 0.05 (−0.23, 0.32) | .75 | ||||
| Cancer worry | −0.01 (−0.08, 0.05) | .67 | −0.02 (−0.08, 0.04) | .56 | ||||
| Cancer fatalism | 0.05 (−0.04, 0.14) | .27 | 0.04 (−0.05, 0.12) | .37 | ||||
| Cancer cause ambiguity | −0.08 (−0.17, 0.01) | .08 | −0.08 (−0.16, 0.01) | .08 | ||||
| BRIEF Health Literacy Score | −0.02 (−0.04, 0.01) | .24 | −0.01 (−0.04, 0.01) | .41 | ||||
| Perceived likelihood of risk of breast cancer | −0.04 (−0.11, 0.02) | .20 | −0.02 (−0.09, 0.05) | .51 | ||||
| Breast cancer risk worry | 0.01 (−0.04, 0.07) | .61 | 0.02 (−0.03, 0.07) | .41 | ||||
| Self-efficacy of alcohol use and breast cancer | 0.14 (0.09, 0.18) | <.01 | 0.05 (−0.01, 0.11) | .08 | ||||
| Response-efficacy of alcohol use and breast cancer | 0.02 (−0.02, 0.06) | .39 | 0.02 (−0.02, 0.06) | .40 | ||||
| Alcohol awareness | ||||||||
| No | Ref | Ref | ||||||
| Yes | 0.13 (−0.11, 0.27) | .07 | 0.10 (−0.03, 0.24) | .14 | ||||
| Attitudes towards alcohol | 0.07 (0.02, 0.13) | .01 | ||||||
| Alcohol subjective norms | −0.11 (−0.17, −0.06) | <.01 | ||||||
| Alcohol self-efficacy | 0.15 (0.08, 0.23) | <.01 | ||||||
| Block | F | Block df | Residual df | Pr > F | R 2 | Change in R2 | Adjusted R2 | Change in adjusted R2 |
| 1 | 5.98 | 15 | 476 | <0.01 | 0.1585 | 0.1320 | ||
| 2 | 14.68 | 3 | 473 | <0.01 | 0.2302 | 0.0717 | 0.2009 | 0.0689 |
Bold values indicate significant results.
Discussion
National cancer organizations have called for research to address alcohol use as a preventable cause of cancer in the U.S., highlighting the need for innovative interventions to increase awareness of the cancer risks associated with drinking and to decrease alcohol consumption [1, 28]. A recent review supports these calls to action, finding that factors that predict awareness of the cancer risks from alcohol use are not well understood, and limited evidence for behavior change interventions [29]. Our study uniquely contributes to this research area by focusing on alcohol consumption as a breast cancer risk factor in young adult women, because this is a developmental period where drinking is prevalent [15] and vulnerability to the risks of breast cancer from alcohol consumption is increased [4–10]. Our study also advances this research area by providing evidence on predictors of awareness of alcohol use as breast cancer risk factor and predictors of intentions to reduce alcohol consumption. These findings have implications for future research on interventions to raise awareness of the breast cancer risks from drinking alcohol and on interventions to reduce alcohol consumption in young women as a breast cancer prevention strategy.
Our finding that awareness of alcohol consumption as a breast cancer risk factor was low is consistent with population survey data where only 31%–46% of U.S. adults recognize that drinking alcohol is a risk factor for cancer generally [12, 30]. In studies of awareness of alcohol consumption as a breast cancer risk factor in young people, 10% of U.S. college aged young women [43] and 25% of U.S. young women aged 15–44 [13] endorsed awareness. Differences in awareness relative to our findings could be due to study samples (e.g. population-based versus convenience), timing of data collection (e.g. some data collected >15 years ago), or measurement (i.e. different awareness measures). Despite these differences, our findings are consistent with these studies indicating that awareness of alcohol consumption as a risk factor for breast cancer is low in young women and support the need for targeted interventions.
Novel findings from our study include beliefs about risk (i.e. perceived risk of breast cancer from alcohol consumption) and efficacy (i.e. the belief that reducing alcohol consumption can reduce breast cancer risk) that are specific to breast cancer and alcohol are predictors of awareness. In population survey data, general self-efficacy beliefs (i.e. higher confidence to take care of one’s health) and cancer risk perceptions (i.e. higher perceived likelihood of getting cancer) were associated with awareness of cancer risks from alcohol consumption in U.S. adults [12, 30]. Our findings are consistent with these studies, but we used measures specific to breast cancer and alcohol consumption. Potential interventions to raise awareness include approaches such as public education campaigns [1, 28, 29]. Public education campaigns communicating the risks of breast cancer from alcohol consumption in other countries were effective at raising awareness [26, 27]. Our findings and behavioral theories guiding this work [13, 30, 31] indicate interventions seeking to raise awareness of the breast cancer risks from alcohol consumption in young women should include information about the risks of breast cancer from alcohol and emphasize the benefits of reducing drinking to reduce breast cancer risk.
Although raising awareness about the breast cancer risks from alcohol consumption is an important initial step to foster behavior change, reducing alcohol consumption likely requires additional interventions [1, 28, 30]. Our findings support this, demonstrating that awareness was not associated with intentions to reduce drinking and correlates of intentions to reduce drinking were negative attitudes towards alcohol, less favorable subjective norms, and higher self-efficacy to reduce drinking. This suggests interventions targeting these IBM constructs to reduce alcohol consumption, drawing from prior successful IBM-based interventions [44, 45], warrant testing. Notably, although our analysis provides new evidence on correlates of intentions to reduce drinking, our study design precludes examining more complex associations that could inform intervention development. For example, behavioral beliefs such as awareness, risk beliefs, and efficacy beliefs may directly or indirectly affect some IBM constructs (e.g. attitudes about drinking), which in turn influence behavioral intentions to reduce alcohol consumption [31, 32]. Future studies can build from this work by using more methodologically robust designs (e.g. prospective data) to test these associations and more precisely inform intervention design.
Beyond the IBM, researchers could test and policymakers could leverage successful strategies from other cancer prevention domains. For example, counter marketing—an intervention strategy designed to highlight industry’s marketing and deceitful practices—is an effective strategy to reduce tobacco use in young people [46, 47]. Given similarities between the alcohol and tobacco industries’ behavior [16–24], counter marketing may be a promising strategy that could be adapted to address alcohol consumption as a breast cancer risk factor as well [48]. Research testing these and other innovative intervention strategies is needed to address the preventable breast cancer risk from alcohol consumption in young women. Leveraging the identified IBM factors and other innovative strategies such as counter marketing, researchers and policymakers can develop effective interventions for reducing alcohol consumption to reduce young women’s long-term breast cancer risk.
These findings should be interpreted considering the limitations of the study. Our study was cross-sectional, so we cannot establish temporal associations between predictors and study outcomes. We assessed participants’ intentions to reduce alcohol consumption within the next week. It is possible participants’ responses were impacted by preceding questions (e.g. about the risks of alcohol consumption and benefits of behavior change) and measures capturing longer-term behavior change intentions (e.g. 3 months) could produce different results. We used a convenience sample of young adult women residing in Ohio, which may limit the generalizability of our findings to other populations. Larger and more representative studies are needed to replicate our findings. We also did not examine other constructs that may be important to inform intervention development, such as alcohol industry beliefs. Future studies can advance research targeting alcohol consumption in young adult women as a breast cancer prevention strategy by assessing these and other beliefs to inform intervention development.
Despite these limitations, our study findings advance the research on alcohol consumption among young women as a target for breast cancer prevention. Our results indicate that awareness of breast cancer risks associated with alcohol consumption is low among young women, and highlight alcohol and breast cancer risk (e.g. perceived likelihood) and efficacy (e.g. perceived benefits of reducing drinking) beliefs as potential targets of interventions designed to raise awareness. Our results also indicate awareness of the breast cancer risks from drinking alcohol is not associated with intentions to reduce drinking and beliefs such as attitudes towards alcohol consumption, subjective norms, and self-efficacy to change are potential targets to consider for interventions to reduce alcohol consumption. These results emphasize the need to target specific factors associated with intentions to reduce alcohol consumption during this high-risk developmental period among young women, in addition to raising awareness of alcohol consumption as a breast cancer risk factor.
Acknowledgements
The authors thank members of the Big Ten Cancer Research Consortium Population Science Clinical Trials Working Group for their feedback on the study concept.
Contributor Information
Mahmood A Alalwan, Department of Internal Medicine, College of Medicine, The Ohio State University, Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Lauren Long, Department of Internal Medicine, College of Medicine, The Ohio State University, Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Kelly A Hirko, Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA.
Noelle K LoConte, Department of Medicine, Division of Hematology/Oncology/Palliative Care, and Carbone Cancer Center, University of Wisconsin School of Medicine, Madison, WI, USA.
Courtney L Scherr, Department of Communication Studies, Northwestern University, Evanston, IL, USA.
Brittney Keller-Hamilton, Department of Internal Medicine, College of Medicine, The Ohio State University, Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Leanne Atkinson, Department of Internal Medicine, College of Medicine, The Ohio State University, Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Sriya Suraapaneni, Department of Internal Medicine, College of Medicine, The Ohio State University, Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Margaret E Gatti-Mays, Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Sharon Manne, Behavioral Sciences, Rutgers Cancer Institute of New Jersey, Rutgers The State University of New Jersey, New Brunswick, NJ, USA.
Darren Mays, Department of Internal Medicine, College of Medicine, The Ohio State University, Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Funding
This research was supported by The Ohio State University Comprehensive Cancer Center – the James. This research was also partially supported by grant number P30CA016058 from the National Cancer Institute of the National Institutes of Health. The sponsors had no role in the study design; in the collection, analysis, or interpretation of the data; in the writing of the report; or in the decision to submit the manuscript for publication.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Human Rights
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards (The Ohio State University Institutional Review Board Protocol number 2021C0207, and approval date February 07, 2022).
Informed Consent
Informed consent was obtained from all individual participants included in the study.
Welfare of Animals
This article does not contain any studies with animals performed by any of the authors.
Transparency Statements
Study Registration: This study was not registered. Analytic Plan Pre-registration: The analysis plan was not formally pre-registered. Data Availability: De-identified data from this study are not available in a public archive. De-identified data from this study will be made available (as allowable according to institutional IRB standards) by emailing the corresponding author. Analytic Code Availability: Analytic code used to conduct the analyses presented in this study are not available in a public archive. They may be available by emailing the corresponding author. Materials Availability: Materials used to conduct the study are not publicly available. They may be available by emailing the corresponding author.
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