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. Author manuscript; available in PMC: 2024 May 1.
Published in final edited form as: Soc Sci Med. 2023 Mar 29;324:115878. doi: 10.1016/j.socscimed.2023.115878

Structural Sexism Moderates Work and Occupational Risks for Alcohol Consumption and Binge Drinking Among US Women, 1989–2016

Sarah McKetta 1,2, Seth J Prins 2, Deborah Hasin 2, Megan E Patrick 3, Katherine M Keyes 2
PMCID: PMC10121897  NIHMSID: NIHMS1888415  PMID: 37003025

Abstract

Background

People in the labor force and in high-status careers consume alcohol at high rates. State-level structural sexism (sex inequality in political/economic status) is inversely related to alcohol use among women. We examine whether structural sexism modifies women’s labor force characteristics and alcohol consumption.

Methods

We surveyed frequency of alcohol consumption in the past month and any binge drinking in the past two weeks among women ages 19–45 in Monitoring the Future from 1989–2016 (N=16,571) in relation to occupational characteristics (including employment status, high-status career, and occupational gender composition) and structural sexism (measured using state-level indicators of gender inequality) with multilevel interaction models controlled for state-level and individual confounders.

Findings

Working women and women in high-status occupations had higher risks of alcohol consumption than non-working women; differences were most pronounced in lower-sexism states. At the lowest sexism levels, employed women consumed alcohol more frequently (2.61 occasions of use in past 30 days, 95% CI 2.57, 2.64) than unemployed women (2.32, 95% CI 2.27, 2.37). Patterns were more pronounced for frequency of alcohol consumption than binge drinking. Occupational gender composition did not influence alcohol consumption.

Interpretation

In lower sexism states, working and having a high-status career are associated with increased alcohol consumption for women. Labor force engagement extends positive health benefits to women, but it also confers specific risks, which are sensitive to the broader social context; these findings contribute to a growing literature suggesting that alcohol risks are changing in relation to shifting social landscapes.

Keywords: Alcohol epidemiology, Women’s health, Occupational health, Structural sexism

Background

Despite its substantial impact on premature mortality and morbidity,1 alcohol consumption remains highly prevalent among working-age adults in the United States.2 While alcohol consumption is prevalent and normalized in the United States, it is detrimental to health even at low levels.3,4 Over the past twenty years, the public health understanding of alcohol’s toxicity has shifted considerably. In the 1990s and early 2000s, observational research proposed a so-called “j-shaped” curve between alcohol consumption and mortality and morbidity, suggesting that low levels of drinking were beneficial, particularly to heart health.5,6 While these findings received intense media coverage,7–11 they have since been empirically disputed by both systematic analyses and Mendelian randomization studies.5,12,13 They have been further disputed after the discovery that the alcohol industry had funded research promoting the health benefits of low levels of drinking.14,15 Currently, evidence suggests that no level of alcohol consumption improves health, and that even at low levels alcohol consumption can lead to adverse health outcomes.16

Working adults consume alcohol and binge drink (i.e., consuming five or more drinks in a setting) more than unemployed working-age adults.17 Among workers, occupation is a source of heterogeneity for alcohol risks. Approximately 90% of workers in “white-collar” jobs (e.g., clerical, professional occupations) consume alcohol,18 and they report higher prevalence of any alcohol consumption, but lower risks of alcohol use disorders and binge drinking, than those in “blue collar” jobs (e.g., manual labor, food service).19 Similarly, higher occupational prestige—the social standing conferred by particular occupations—is associated with higher a probability of consuming alcohol.20,21 While those in higher status careers are more likely to report consuming alcohol than abstaining completely, they may be less likely to endorse binge drinking or other high-intensity alcohol consumption patterns.20,22–24 However, recent binge drinking trends suggest these associations may be changing: workers in higher status careers experienced disproportionately high increases in binge drinking in the past decade.25

Work context and climate are additional occupational characteristics that influence working adults’ alcohol risks.26,27 One such contextual determinant of alcohol consumption is occupational gender composition. Workers in male-dominated fields are more likely to report any alcohol consumption, risky drinking, and drinking with co-workers than those in female-dominated fields.28–30

The patterning of alcohol risks in relation to occupational characteristics may be shifting, in part because the composition of the labor force has been changing in recent decades. Women outside the labor force (i.e., homemakers) are historically at lower risks for alcohol consumption and binge drinking than those in the labor force.31–33 However, increasing proportions of women have entered the work force and into high-status, historically male-dominated occupations.34,35 As a result, labor-related risks for alcohol use may be more salient for recent trends in women’s drinking than for recent trends in men’s drinking. As women increasingly enter these careers, their alcohol risks may increase commensurately. Indeed, working-age women have evidenced increases in both alcohol consumption and binge drinking over the past two decades,36,37 with increases most concentrated among women in high social positions and in high prestige occupations.25,38 As women have become stronger market participators, alcohol advertisers have taken note: the so-called “pinking” of the alcohol market has included promoting alcohol consumption as self-care for women, and targeting women with gender-specific products.39–42

Alcohol consumption and risky drinking are particularly relevant to women’s health given that, relative to men, women are more likely to suffer acute adverse consequences related to alcohol use (i.e., motor and cognitive deficits, injury) and to experience these consequences at lower levels of consumption.43–45 Regarding chronic consequences, alcohol risks are major contributors to women’s preventable morbidity and mortality risks; among the leading causes of death for women, the proportion related to alcohol use has increased dramatically, increasing 85% between 1999 and 2017—twice the rate of men, whose alcohol-related deaths increased 39% during the same time period.46 Identifying determinants of alcohol use among women, as well as specific subgroups for whom risky use is increasing, remains an essential priority for population disease prevention.

At the population level, shifts in the sex composition of the labor force—i.e., more representation of women in the workforce and in high-status careers—reflect decreases in structural sexism, defined as the “systematic gender inequality in power and resources favoring men within…U.S. state-level political, economic, and cultural institutions.”47 More representation of women in the labor force and in high-status careers at the state level, however, does not imply that every state resident is herself working in a high-status career or even working at all. Population-level exposures (e.g., structural sexism) may exacerbate or attenuate the risks conferred by individual-level exposures (e.g., being employed, occupational characteristics). Indeed, while at a population level previous research indicates that women living in lower structural sexism environments report higher rates of alcohol consumption and binge drinking than those in high structural sexism environments,48 these associations may vary across salient moderators. Women who work in high-status careers in a high structural sexism environment may have very different alcohol risks than those who work in high-status careers in a low structural sexism environment. High-status occupations often confer exposure to workplace norms that encourage alcohol consumption, and typically garner higher salaries which allow for purchase of luxury items, including alcohol.49,50 To what extent structural sexism, a population-level phenomenon, modifies the effects of women’s individual-level work-related alcohol risks remains unknown.

Cross-national data suggest that structural sexism indeed moderates the relationship between employment and women’s alcohol risks. In a cross-national comparison of women with children in 16 industrialized countries in the early 2000s, working mothers reported higher volumes of alcohol consumption than non-working mothers, but the strength of the association between work and alcohol consumption varied by country-level gender equality.51 In countries with lower levels of gender equality (i.e., more sexism), working mothers endorsed higher volumes of consumption than non-working mothers; but this relationship was attenuated in countries with higher levels of gender equality (i.e., less sexism), where working mothers endorsed lower volumes of consumption than non-working mothers.

To date, no study has examined this relationship within the United States, but related findings within the US suggest that the patterning of the relationships among structural sexism, work, and alcohol use may differ from the cross-national findings. In data collected among a select sample (mothers) before the time period when women’s alcohol consumption began to increase in the United States, women living in areas with the lowest levels of structural sexism report the highest alcohol consumption.52 Yet, alcohol consumption among mid-life women has risen precipitously since the early 2000s,53 and data show that the increases are concentrated among higher status women,54 and US workers in higher status and majority-male occupations consume alcohol at higher frequencies.2,55 Given that alcohol consumption increases are concentrated among higher status women25,38 and that workers in higher status and majority-male occupations consume alcohol at higher frequencies, we hypothesize that increased risks of alcohol use related to work characteristics will be exacerbated, rather than attenuated, in areas characterized by lower levels of sexism.

In sum, there is strong theoretical evidence linking occupational characteristics to alcohol risks; women have increasingly occupied managerial, high-prestige positions and moved into majority-male fields, and these characteristics are important determinants of alcohol use. Structural sexism may be an important modifier of these relationships, and in the current study we examine whether the associations between work characteristics and alcohol outcomes vary across levels of structural sexism. We hypothesize that employed women will evidence higher frequencies of alcohol consumption and binge drinking than unemployed women, consistent with prior research, but that employed women in low sexism environments will evidence the highest rates of both alcohol outcomes. We anticipate a similar pattern across high- versus low-status occupational characteristics, as well as comparing women in majority-male occupations to majority-female occupations: that is, the increased risks for alcohol use and binge drinking conferred by higher status occupations and by working in a majority-male occupation will be further amplified in low sexism environments.

Methods

We used data from Monitoring the Future (MTF), an ongoing, prospective cohort study followed from senior year of high school. Participants of both sexes are initially recruited using a multistage sampling procedure based on geography and school size and are ultimately drawn from 120–140 public and private high schools which are selected to provide a representative cross-section of high school seniors in the contiguous US in the year of recruitment (starting in in 1975 and ongoing).55 From these high school seniors, a subsample (approximately 2,450) is selected each year to be surveyed longitudinally, either starting one year later (modal age 19) or two years later (modal age 20). They continue to be surveyed approximately every 1–2 years until age 29/30, and then approximately every five years beginning at 35. Because most workers do not enter the labor force full-time until adulthood, the sample was restricted to the follow-up surveys only, beginning when respondents were 19/20 years old. Eligible respondents were MTF women who lived in the United States and were age 19/20 between 1989 and 2008, followed through 2016 (N=16,571). All respondents had the opportunity to respond to the 5th follow-up survey (at approximately age 27–28) and the oldest respondents had the opportunity to respond to the 6–9th follow-up surveys, corresponding to ages 35, 30, and 45 (Supplemental Table 1).

Outcomes.

Drinking frequency was ascertained by asking, “On how many occasions have you had any alcoholic beverage to drink – more than just a few sips – during the last 30 days?” Ordinal responses included “0 occasions,” “1–2 occasions,” “3–5 occasions,” “6–9 occasions,” “10–19 occasions,” “20–39 occasions,” and “40 or more occasions.” Binge drinking was ascertained by asking, “Think back over the last two weeks. How many times have you had five or more drinks in a row?” and was dichotomized as “none” or “any.”

Exposures.

We assessed employment status, working in a technical or professional occupation (hereafter, “professional status,” inclusive of management occupations, legal occupations, etc. [Appendix A]), prestige, and occupational gender composition at each wave. We examined employment status using two different operationalizations; first, dichotomously, as reporting at least one full time or part time job vs. not; next, as a categorical three-level variable, 1) as working more than one job/a single full-time job, 2) working part-time, or 3) unemployed. Respondents were asked to choose among options provided by MTF that best described their current or most recent primary job title and these were used to categorize occupational prestige, professional status, and gender ratio. To obtain numerical estimates of prestige and gender composition, we matched MTF occupation categories to US census standard occupation codes. These linkages and a description of how the numeric values were assigned are shown in Appendix A and Supplemental Table 2.

Professional status was operationalized based on classification systems commonly used by the Bureau of Labor Statistics, corresponding to a category described as “Management, professional, and related occupations” and corresponds to codes 11–0000–29–0000; examples include management occupations, business occupations, legal occupations, and life science occupations.56 For the MTF occupation options, managers or administrators, professionals without a doctoral degree, and professional with a doctoral degree were coded as professional status, and the remaining options were coded as not. Respondents were categorized as professional status or not based on their occupation at each observation.

Prestige measures were obtained from the General Social Survey, a nationally-representative opinion survey which in 2012 asked a sub-sample of respondents (N=1001) to rank samples of 9 occupations each by placing them on a “ladder” representing low to high social standing.57,58 Each respondent rated batches of 90 occupations total, which overall represented the possible occupations encoded by census codes (N=820 in 2012). Rankings were transformed into numerical values, ranging from a possible 0 (lowest prestige) to 100 (highest prestige) value; these were then fitted to a hierarchical linear model to predict average prestige score of each occupation with adjustment for inter-rater variability. MTF occupations were linked to these ratings (Supplemental Table 2) and an average score was calculated for each. Each of the 14 MTF occupations was coded as “high prestige” or “low prestige” based on whether they were above or below the average prestige level (mean score = 46.7). Of note, all of the managerial and professional occupations were ultimately categorized as high prestige.

Occupational gender composition was calculated by estimating the average proportion of women in each MTF occupation, using estimates from the Current Population Survey (for years 1989, 1991–1999) and the American Community Survey (for years 1990, 2000–2016). Occupations where women were fewer than 50% of the workers were classified as “majority men,” and occupations with 50% or greater women workers were classified as not.

Table 1 shows each MTF occupation, whether it is classified as professional, high or low prestige, and majority-men or not.

Table 1:

MTF occupations, work characteristics, and linkage to SOC major occupation codes

MTF occupation category Professional status Prestige, dichotomous Occupation is majority men
1. Laborer (custodian, material mover, maid, landscape worker, farm worker) No Low prestige Yes
2. Service worker (food preparer or food service worker including fast food, waiter/waitress, call center worker, stock clerk, order filler, nursing aide/orderly, teacher assistant, childcare worker) No Low prestige No
3. Operative or semi-skilled worker (bus or truck driver, maintenance or repair worker, assembly line worker) No Low prestige Yes
4. Sales clerk in a retail store or by phone (cashier, supervisor of retail workers) No Low prestige No**
5. Clerical or office worker (secretary, receptionist, bookkeeper, supervisor of office workers, bank teller, postal clerk or carrier) No Low prestige No
6. Protective service (police, firefighter, paramedic) No High prestige Yes
7. Military service No High prestige Yes
8. Craftsman or skilled worker (carpenter, mechanic, machinist, welder) No Low prestige Yes
9. Farm owner, farm manager No Low prestige Yes
10. Owner of a small business No High prestige Yes
11. Sales representative (insurance agent, real estate) No High prestige Yes
12. Manager or administrator (office manager, government official, sales manager) Yes High prestige No
13. Professional without doctoral degree (registered nurse, school teacher, accountant, architect, artist, information technology worker) Yes High prestige No
14. Professional with doctoral degree or equivalent (lawyer, physician, dentist, scientist, college professor) Yes High prestige Yes
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**

In one survey year (1995), occupation was <50% women (49% women); because it was ≥ 50% women for all other years, this category was coded as not majority men

Moderator.

Structural sexism was operationalized using a factor-analytically derived measure described in McKetta et al (2022)52 and composed of state-level indicators of gender inequality (the percentage of male state legislators; the male/female ratio for residents living at or above the federal poverty line; the male/female ratio for the proportion of adults ages 16 and over in the labor force; the male/female ratio for the proportion of working adults in management occupations; and the male/female ratio for the proportion of working adults who are self-employed). The scores were time-varying, such that each state was assigned a model-based factor score for each year, with a 1-unit increase corresponding to 1 standard deviation from the mean. In the analytic sample, the mean score was −0.42 (range: −4.62 to 6.98).

Covariates.

We adjusted for state- and individual-level covariates that influence work characteristics, exposure to structural sexism, and alcohol patterns. The state-level confounders were alcohol policy climate, rurality, poverty rate, GINI coefficient, and religious conservatism—all were time-varying. Time-varying individual-level covariates were current age, marriage status, highest educational attainment, personal religiosity, and rurality. Time-invariant individual-level confounders were race/ethnicity, paternal education, and baseline (12th grade) alcohol consumption, rurality, and religiosity. Measure descriptions and data sources are described in Supplemental Table 3.

The eligible sample consisted of 16,571 unique respondents with 94,822 observations. The modal source of missingness in MTF was attrition, thus all analyses were weighted using attrition weights developed by MTF, which account for baseline substance use and demographic characteristics related to both subsequent alcohol patterns and study retention. Item non-response is the second source of missing data in this sample. Of the 94,822 observations for sample women, 71,481 (75%) had complete covariate information. To account for potential biases by selective item non-response, we used multiple imputation using chained equations to impute missing values into 10 data sets, which were combined using Rubin’s Rules to estimate model parameters.60 Due to computational barriers to performing post-estimation procedures (i.e., pooling model-based predicted probabilities or calculating an F–statistic for interaction test)61 from pooled models, analyses with complete cases are shown in the main text, with imputed model parameters in the Supplement.

Analysis.

We first examined bivariate associations between work characteristics and alcohol outcomes using weighted, covariate-controlled multilevel models with random effects for both individuals and states with respondents nested within states. We examined interactions between structural sexism and employment status using the full eligible complete case sample (N=71,481 observations) and interactions between structural sexism and occupational characteristics (professional status, prestige, gender composition) using a subsample of respondents who either currently worked or who were currently unemployed but had worked (N=56,388 observations), excluding those who were had never worked or no longer in the labor force (e.g., homemakers). Drinking frequency was modeled using a Poisson distribution, and binge drinking using a logistic distribution. Effect modification was assessed using an interaction term between structural sexism and the occupational characteristic under examination to produce estimates for relative statistics (i.e., risk ratio and odds ratio) for each stratum and to test heterogeneity across strata. Figures were produced based on model-based predictions, fixed at the mean covariate values for the analytic samples. We used SAS 9.4 for analyses and figures.

Results

Table 2 shows the covariate distribution across observations in the sample, stratified across levels of state structural sexism, dichotomized using a median split and with p-values derived from Rao-Scott chi-square tests which account for clustering of repeated measures. Overall, a high proportion of women in the sample were employed (80%). Respondents in states with lower levels of structural sexism had higher probabilities of alcohol consumption (69% vs. 65%), post-college education (26% vs. 11%), being in a professional occupation (47% vs. 29%), and being in a high-prestige occupation (55% vs. 33%). Supplemental Figure 1 shows the proportion of women who are employed, employed full-time, in professional occupations, in high prestige occupations, and in majority-men occupations over time.

Table 2:

Outcome and covariate distributions among sample women in MTF follow-up surveys, 1989–2016, dichotomized by structural sexism level

Low sexism* (N=35,732 observations)
N (%) (categorical)
Mean (S.D.) (continuous)		 High sexism* (N=35,749 observations)
N (%) (categorical)
Mean (S.D.) (continuous)		 p-value
Alcohol outcomes
Reported any alcohol consumption (dichotomous) 24,609 (69%) 23,388 (65%) <0.001
Reported any binge drinking (dichotomous) 9,761 (27%) 10,363 (29%) <0.001
Occupational characteristics
Currently employed 29,173 (82%) 27,823 (78%) <0.001
 • One full-time job, or multiple jobs 22,915 (64.1%) 18,525 (51.8%) <0.001
 • One part-time job 6,258 (17.5%) 9,298 (26.0%)
In the labor force 33,071 (93%) 33,933 (95%) <0.001
 • Managerial/professional occupation 14,216 (47%) 7,960 (29%) <0.001
 • High prestige occupation 15,857 (55%) 9,160 (33%) <0.001
 • Majority-men occupations 3,522 (12.3%) 2,743 (9.9%) <0.001
State-level covariates
Percentage of residents who are 18.0 (0.1) 16.9 (0.1) <0.001
religious conservatives
Poverty rate 13.5 (2.9) 12.7 (3.2) <0.001
Population density 207.4 (230.0) 186.7 (212.0) <0.001
Alcohol policy climate scale 42.6 (7.3) 38.5 (9.3) <0.001
GINI coefficient 0.61 (0.04) 0.58 (0.03) <0.001
Individual-level covariates
Father has college degree 14,011 (39%) 12,994 (36%) <0.001
Rural 14,147 (40%) 14,620 (41%) <0.001
Rural at baseline 19,136 (54%) 18,843 (53%) <0.001
White 29,461 (82%) 29,229 (82%) 0.074
Married 15,417 (43%) 9,608 (27%) <0.001
More than 5 years of college education 9,365 (26%) 4,090 (11%) <0.001
Religious 20,709 (58%) 23,037 (64%) <0.00
Religious at baseline 21,968 (61%) 22,007 (62%) 0.818
Any alcohol consumption at baseline 17,754 (50%) 18,966 (50%) <0.001
Any binge drinking at baseline 9,243 (26%) 9,330 (26%) 0.604
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*

For descriptive statistics, high structural sexism refers to states with at or above median level; low structural sexism refers to states below median level

Table 3 shows the associations between work status and occupational characteristics and drinking frequency and odds of binge drinking. Those who worked (either at all, or full-time or part-time) evidenced relatively higher past-month drinking frequencies and odds of binge drinking in the past two weeks than those who did not (RR for drinking frequency for employed women compared to unemployed women = 1.057, 95% CI 1.046, 1.068); OR for binge drinking = 1.191, 95% CI 1.136, 1.250). Professional status was associated with greater drinking frequency (RR=1.050, 95% CI 1.040, 1.061), but was inversely associated with binge drinking odds (OR = 0.936, 95% CI 0.894, 0.980 compared to those not in professional status occupations). Working in a higher prestige occupation was unrelated to binge drinking but associated with greater drinking frequency (RR=1.056, 95% CI 1.045, 1.066) relative to those working in a lower-prestige occupation. Working in a majority-male occupation was unrelated to either drinking frequency or binge drinking odds.

Table 3:

Associations between work status and occupational characteristics and alcohol consumption outcomes, MTF women 1989–2016, adjusted for individual and state-level covariates

N observations Alcohol consumption*
RR (95% CI)		 Binge drinking*
OR (95% CI)
Employed respondents 56,996 1.057 (1.046, 1.068) 1.191 (1.136, 1.250)
Unemployed respondents 14,485 Ref Ref
Respondents working full-time or working more than one job 41,440 1.067 (1.056, 1.079) 1.245 (1.184, 1.309)
Respondents working one part-time job 15,556 1.031 (1.017, 1.044) 1.080 (1.018, 1.145)
Unemployed respondents 14,485 Ref Ref
Respondents in professional status occupations** 22,176 1.050 (1.040, 1.061) 0.936 (0.894, 0.980)
Respondents not in professional status occupations** 34,212 Ref Ref
Respondents in high prestige occupations** 25,017 1.056 (1.045, 1.066) 0.977 (0.934, 1.022)
Respondents in low prestige occupations** 31,371 Ref Ref
Respondents in majority-men occupations** 6,265 1.003 (0.990, 1.017) 0.980 (0.919, 1.044)
Respondents in majority-women occupations** 50,123 Ref Ref
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*

Adjusted for alcohol policy climate, state- and individual-level rurality, poverty rate, GINI coefficient, state- and individual-level religiosity, race/ethnicity, age, paternal education, marriage status, highest education completed, rurality at baseline, religiosity at baseline, alcohol outcome at baseline

**

Not adjusted for education because within occupations (particularly among professional occupations) education is frequently invariant and/or hiring is contingent on educational credentials.

We next examined effect modification across these associations by structural sexism. Structural sexism was inversely associated with both drinking frequency (RR: 0.973, 95% CI 0.970, 0.976) and binge drinking (OR: 0.895, 95% CI: 0.882, 0.909). Figure 1 shows model-based estimates for the relationship between employment status and drinking frequency and probability of binge drinking, across levels of structural sexism, corresponding to Table 4. We observed heterogeneity in the relationship between employment and both outcomes across levels of structural sexism (p<0.01). As sexism values decreased, the risks for both alcohol outcomes increased, but the risks among employed women increased faster, creating a widening disparity at lower levels of sexism and a convergence of risk at higher levels of sexism. For drinking frequency, at the lowest level of structural sexism, employed women reported higher past-month frequencies (2.61, 95% CI 2.57, 2.64) then unemployed women (2.32, 95% CI 2.27, 2.37). Similarly, at lower levels of sexism, employed women reported binge drinking over the past two weeks at higher probabilities than unemployed women (predicted probabilities = 0.32, 95% CI 0.31, 0.33; and 0.23, 95% CI 0.22, 0.25, respectively). Similar trends were observed when employment status was decomposed into three categories (full time, part time, or no job); structural sexism moderated these relationships in an apparent dose-response manner, with women working full-time endorsing both the highest occasions of alcohol consumption and probabilities of binge drinking, and women not working endorsing the lowest (Table 4), but only in low structural sexism contexts (p<0.01).

Figure 1:

Figure 1:

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Associations between employment status and alcohol consumption frequency (left) and binge drinking probability (right), across levels of structural sexism, among MTF women 1989–2016

Table 4:

Associations between work status and occupational characteristics, with effect modification by structural sexism, MTF women 1989–2016, adjusted for individual and state-level covariates

Stratum Risk ratio for alcohol consumption frequency with every 1 SD increase in sexism (95% CI) Model-based predicted alcohol consumption frequency across levels of sexism* Odds ratio for binge drinking with every 1 SD increase in sexism (95% CI) Model-based predicted probability of binge drinking across levels of sexism*
Min** Mean Max Min** Mean Max
Employed respondents 0.970 (0.967, 0.973) 2.61 2.30 1.83 0.883 (0.873, 0.893) 0.32 0.22 0.10
Unemployed respondents 0.985 (0.980, 0.990) 2.32 2.18 1.95 0.943 (0.926, 0.960) 0.23 0.19 0.13
Interaction between structural sexism and dichotomous employment status F=37.39, p<0.01 F=46.35, p<0.01
Full-time 0.968 (0.964, 0.972) 2.65 2.31 1.82 0.874 (0.859, 0.889) 0.32 0.21 0.09
Part-time 0.977 (0.971, 0.982) 2.48 2.24 1.88 0.910 (0.888, 0.932) 0.26 0.19 0.10
Unemployed 0.984 (0.979, 0.990) 2.33 2.18 1.93 0.938 (0.915, 0.962) 0.22 0.18 0.12
Interaction between structural sexism and categorical employment status F=16.36, p<0.01 F=14.75, p<0.01
Respondents in managerial/professional occupations*** 0.964 (0.960, 0.969) 2.78 2.91 1.83 0.888 (0.872, 0.904) 0.32 0.22 0.10
Respondents not in managerial/professional occupations*** 0.972 (0.969, 0.975) 2.59 2.30 1.86 0.892 (0.881, 0.904) 0.33 0.24 0.12
Interaction between structural sexism and managerial/professional status F=10.19, p<0.01 F=0.30 p=0.59
Respondents in high prestige occupations*** 0.962 (0.958, 0.967) 2.81 2.39 1.80 0.886 (0.871, 0.901) 0.32 0.22 0.10
Respondents in low prestige occupations*** 0.973 (0.970, 0.977) 2.55 2.29 1.89 0.895 (0.883, 0.907) 0.32 0.23 0.12
Interaction between structural sexism and prestige F=24.34, p<0.01 F=1.18, p=0.28
Respondents in majority-men occupations*** 0.962 (0.955, 0.969) 2.75 2.34 1.75 0.879 (0.855, 0.903) 0.33 0.23 0.10
Respondents not in majority-men occupations*** 0.970 (0.966, 0.973) 2.66 2.34 1.86 0.894 (0.883, 0.905) 0.32 0.23 0.12
Interaction between structural sexism and occupational gender composition F=5.08, p=0.02 F=1.48, p=0.22
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*

Adjusted for alcohol policy climate, state- and individual-level rurality, poverty rate, GINI coefficient, state- and individual-level religiosity, race/ethnicity, age, paternal education, marriage status, highest education completed, rurality at baseline, religiosity at baseline, alcohol outcome at baseline

**

Lowest level of sexism = −4.62; mean = −0.47; highest = 6.98

***

Not adjusted for education as it is frequently invariant among higher status careers due to minimum education requirements

Figure 2 shows model-based estimates for the relationships between structural sexism and professional status, prestige, and occupational gender composition, respectively. For alcohol consumption, higher status careers (i.e., professional occupations, high prestige occupations) were associated with higher occasions of consumption relative to lower status careers in low-sexism contexts, but not in high-sexism contexts. However, the associations between professional status, prestige, and binge drinking probability did not vary across levels of structural sexism (Table 4) and predicted probabilities did not meaningfully vary at different levels of sexism. For both alcohol outcomes, associations with working in a majority-male occupation did not meaningfully vary across levels of sexism. Supplemental Table 4 shows pooled parameters from models on imputed data, compared to complete case analysis; imputation of missing data did not meaningfully change results or interpretation.

Figure 2:

Figure 2:

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Associations between occupational characteristics (from top to bottom: professional status, prestige, and occupational gender composition) and alcohol consumption frequency (left) and binge drinking probability (right), across levels of structural sexism, among MTF women 1989–2016

Discussion

The present study of women in the United States between 1989–2016 had four central findings. First, working was associated with more frequent past 30-day drinking and higher probability of past two-week binge drinking, especially in low sexism environments. Second, at the highest levels of sexism, there were no differential associations between any occupational characteristic and alcohol outcomes. Third, having a high-status occupation (i.e., high prestige, professional status) was associated with higher drinking frequency, which was potentiated in low sexism environments, but belonging to a high-status occupation was not meaningfully related to binge drinking, regardless of structural sexism. Finally, occupational gender composition was unrelated to alcohol outcomes, regardless of structural sexism. Overall, the findings suggest that in low sexism environments, working is associated with more alcohol consumption by women across multiple drinking patterns and having a high-status occupation is associated with increased drinking frequency but not riskier alcohol patterns (i.e., binge drinking).

In general, at low levels of sexism, all subgroups had more frequent drinking and higher probabilities of binge drinking. These findings were consistent with the study hypothesis that working women in low sexism environments would evidence higher alcohol consumption than both non-working women or women in high sexism environments. Two mechanisms are commonly used to explain why employment increases alcohol consumption: financial resources and occupational drinking cultures.2,49,50 Relative to non-working women, women who work may have and be in control of more disposable financial resources, thus be more able to afford to consume alcohol regularly. Women who work are also exposed to occupational drinking cultures: many professions and occupations cultivate work-related alcohol consumption (e.g., drinking at or after work, drinking with co-workers) as ways to develop community and camaraderie, as well as to recruit clients.50,62 Occupational drinking cultures have historically influenced worker alcohol consumption behaviors,2,63 and when employees engage in alcohol consumption patterns that are adherent to the culture at their workplace, they receive meaningful rewards in terms of relationship- and rapport-building, despite the health risks.50,62 Both of these mechanisms may be more salient in contexts with more permissive drinking norms, which would explain not only the differential associations between employment status and both outcomes at low levels of sexism, but also the lack of association between employment and either alcohol outcome at the very highest levels of sexism, where alcohol norms are more restrictive.52 When consuming alcohol is more socially appropriate, women who have more resources and more exposure to permissive occupational drinking cultures may engage in alcohol consumption at higher rates than those who do not; but in less permissive contexts, women’s alcohol consumption may be equally unacceptable regardless of employment or status differences.64

At lower levels of sexism, we observed an association between high-status careers and increases in occasions of alcohol consumption, but not binge drinking; financial resources and occupational drinking cultures may also explain this discrepancy across outcomes. Indeed, working in a high-status career is a well-established risk for alcohol consumption (compared to abstention),19,65 but it is less consistently related to binge drinking or other patterns of high-intensity consumption,66 as the current study demonstrated. Women in high-status careers—which frequently require higher educations—may have high health literacy and have internalized public health messaging (which has since been discredited1,67) that moderate alcohol consumption is healthy and only excess consumption is risky. Next, workers in higher status careers are exposed to more permissive drinking cultures and more opportunities for work-related drinking than those in low-status careers,68 but only to a certain degree: among higher status careers, moderate alcohol consumption is frequently normative, but excess or risky consumption (e.g., binge drinking, working while intoxicated) is not.63,69 While it is encouraging that high-status women are not at differentially increased risks of binge drinking (a consumption pattern with more severe adverse consequences), no level of alcohol consumption is beneficial for health.1

Finally, in this sample, occupational gender composition was unrelated to either alcohol outcome, regardless of structural sexism. This null association was inconsistent with the study hypotheses. While prior research has demonstrated a positive relationship between working in a male-dominated occupation and alcohol risk, these studies rarely stratified by gender. Studies that have examined the effects of occupational gender composition on women’s outcomes—rather than on outcomes with men and women pooled together—show that women working in male-dominated occupations do experience increased risks of adverse mental health and stress,70 but there is conflicting evidence for whether alcohol risks increase.29,71 Therefore, the pathways mediating the relationship between high-status careers and alcohol outcomes may be distinct from the ones mediating the relationships between occupational gender composition and other health outcomes for women. Finally, occupational gender composition may be less influential for women’s health behaviors than workplace gender composition; that is, being a majority-male field may be less relevant for women’s alcohol consumption than the more proximal work environment of being in a majority-male firm.72

The study findings should be evaluated in light of their limitations. First, measures of current employment status mask heterogeneity in temporary vs. permanent unemployment. This lack of precision regarding employment status (i.e., mixing the long-term unemployed with the temporarily unemployed) was not plausibly differential by state and likely any bias would be towards, rather than away from, a null effect. Similarly, the MTF job categories do not precisely correspond to established, commonly-used labor codes, and linking them may have resulted in further non-differential misclassification, thus a conservative bias towards a null effect. Next, the measurement of prestige relied on a single, time-invariant measure from a national opinion survey. However, prestige is a stable construct with regards to historical time,73 and though individual occupations have changed between 1989 and 2016, the overall occupational categories have not. Finally, these findings do not rule out the possibility of selection; respondents who consume alcohol at higher rates may have selected into the labor force or higher status careers. However, selection alone would not explain the variation across levels of sexism. We did not present associations among the male subsample of MTF adults because structural sexism is not as strongly associated with men’s alcohol outcomes as women’s, and because we were centrally interested in how these associations varied in ways that were salient to women’s alcohol outcomes. However, these associations are available by request. Finally, these data were collected prior to the Covid-19 pandemic, which dramatically altered the workplace context, and how these changing contexts have influenced workplace alcohol norms is still being determined.

While reductions in structural sexism leading to greater gender equality are a general social good, such reductions have may have unintended harmful risks for some health behaviors.52 Similarly, labor force engagement extends positive health benefits to women, but it also confers specific risks, which are sensitive to the broader social context.74 The implications of this research are not that women should disengage from the labor force or avoid pursuing high-status careers because of the risks of alcohol consumption, nor that the world should become less equal to protect women’s health. Rather, these findings contribute to a growing literature suggesting that population alcohol patterns are changing in relation to shifting social landscapes, and understanding these changes is essential for identifying higher risk groups for education, screening, and intervention. Indeed, occupational interventions for alcohol consumption have an extensive research base and can be very effective,75 as working adults spend a large portion of their waking hours at their place of employment (i.e., a captive audience) and employers have a financial interest in keeping them healthy. Measuring and exploring the changing dynamics and determinants of alcohol consumption, and how these vary across different social dimensions, is paramount to not only alcohol treatment and intervention but also prevention of a multitude of health consequences later in life.

Supplementary Material

1

Highlights.

  • Labor force engagement and high-status careers are related to increased alcohol use

  • It is unknown whether structural sexism impacts these associations for women

  • Low sexism contexts exacerbated alcohol use among working women and those in high-status careers

  • Findings varied by alcohol patterning and were less pronounce for binge drinking

  • Structural sexism may be an important modifier of established risks for alcohol use

Funding

NIH R01s AA026861, DA016575, and AA026574 supported this work.

Footnotes

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