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Published in final edited form as: J Workplace Behav Health. 2014;29(3):210–223. doi: 10.1080/15555240.2014.928600

BINGE DRINKING, SMOKING AND MARIJUANA USE: THE ROLE OF WOMEN's LABOR FORCE PARTICIPATION

Carol B Cunradi 1, Genevieve M Ames 1, Hong Xiao 1,2
PMCID: PMC4217643  NIHMSID: NIHMS619657  PMID: 25379032

Abstract

This study analyzed the role of women's labor force participation in relation to binge drinking, smoking and marijuana use among employment age married/cohabiting women. The sample consisted of 956 women who were employed as construction workers (n=104), or were unemployed (n=101), homemakers (n=227) or employed in non-physically demanding occupations (n=524). Results of multivariate logistic regression analyses showed that women construction workers were at elevated risk for smoking and monthly binge drinking; unemployed women were more likely to use marijuana. Women in both categories were at risk for polysubstance use. Additional research is needed to explicate how labor force participation influences women's substance use.

Keywords: Women, substance use, labor force participation

INTRODUCTION

Alcohol and tobacco use each contribute 4% to the global burden of disease, with illicit drugs contributing an additional 0.8% (Rehm, Taylor, & Room, 2006). Within the developed regions of the world (e.g., U.S., Canada, Europe, Australia), the burden of disease attributable to alcohol and smoking is 9.2% and 12.2%, respectively; an additional 1.8% of disease is attributable to illicit drugs (Rehm et al., 2006). When examined by gender, the burden of disease from these substances is two to four times lower among women than men. Despite the lower risk, women's alcohol, tobacco and drug use resulted in an estimated 96,543,000 disability-adjusted life years (DALY) in the developed world (Rehm et al., 2006). This measure combines years of life lost due to premature mortality with years of life lived with disabling conditions (Murray, Salomon, & Mathers, 2000). In the U.S., binge drinking (drinking 5 or more drinks during a drinking occasion) results in more than half of the 79,000 annual deaths due to excessive drinking (Naimi, Nelson, & Brewer, 2010).

Numerous studies have found that risk for binge drinking and other hazardous alcohol use varies across occupational groups. For example, among respondents to the 2005 California Health Interview Survey, Barnes and Brown (2013) found that workers in physically demanding occupations such as construction and installation were at elevated risk for past-30 day binge drinking compared to white-collar professionals. Similarly, among a national sample of uninsured workers, those in construction/extraction occupations were significantly more likely to report binge drinking, or drug and alcohol use, compared to workers in service occupations (Waehrer, Zaloshnja, Miller, & Galvin, 2008). Both of these studies controlled for gender. To further explore gender differences in alcohol use by occupational characteristics, Barnes and Zimmerman (2013) conducted stratified analyses of a representative sample of U.S. workers ages 41-49. Among men, they found physical job demands were associated with number of past-30 day occasions in which 6 or more drinks were consumed. The same association was not observed for women; rather, physical job demands were associated with number of days in which they drank. Regarding international studies, Ansoleaga and Castillo-Carniglia (2013) found that risk for hazardous alcohol consumption was elevated among Chilean construction workers. In contrast, a study based on a national sample of Canadian workers found that those in blue-collar occupations were not more likely to misuse alcohol, nor were physical job demands related to the onset or recurrence of alcohol misuse (Marchand & Blanc, 2011).

Clearer social class gradients emerge when examining the associations between tobacco use and worker characteristics. For example, among employed and insured adults who participated in the 2004-2005 Behavioral Risk Factor Surveillance System, there is an inverse association between level of education and likelihood of smoking (Hughes, Hannon, Harris, & Patrick, 2010). Compared to college graduates, those with less than a high school education are more than 4 times as likely to smoke (Hughes et al., 2010). Among employed adults who participated in the 2006-2007 Current Population Survey – Tobacco Use Supplement, those in blue-collar occupations are at higher risk than those in white-collar occupations for current smoking (Ham et al., 2011). Moreover, construction workers are more likely to be current daily smokers than other blue-collar workers (Ham et al., 2011). It should be noted that females accounted for only 3% of construction workers in this national sample. Interestingly, among a sample of Massachusetts building trades apprentices, 43% reported current smoking at baseline (Chin, Hong, Gillen, Bates, & Okechukwu, 2012). Although females comprised only 4.8% of the sample, 50% of them were current smokers. Workers in this physically demanding, traditionally male occupation appear to have persistently elevated rates of smoking.

Finally, rates of illicit drug use have been shown to vary by employment status and worker characteristics. For example, among participants ages 18 to 64 in the 2002-2004 National Survey on Drug Use and Health, 18.6% of those unemployed reported past-month illicit drug use compared to 8.2% among those employed full-time (Larson, Eyerman, Foster, & Gfroerer, 2007). Among 19 major industrial categories, workers employed in accommodations and food services had the highest rate of past-month illicit drug use (16.9%), followed by those employed in construction (13.7%). When limited to marijuana, 12.9% of workers in construction/extraction reported past-month use (Larson et al., 2007).

Overall, these studies indicate that men who work in physically demanding occupations (e.g., construction) are more likely to binge drink and smoke compared to men in non-physically demanding jobs; rates of drug use are elevated among the unemployed. Little is known, however, about the substance use patterns of women in blue-collar construction jobs, and how their substance use differs from female peers in different occupational categories. The purpose of this study is to analyze the role of women's labor force participation in relation to binge drinking, smoking and marijuana use among a sample of employment age married/cohabiting women. Specifically, we sought to test whether women employed as construction workers would be at greater risk for each type of substance use compared to women employed in non-physically demanding occupations, after adjusting for relevant demographic factors (e.g., age; race/ethnicity) and psychosocial correlates of substance use, such as impulsivity (Leeman, Hoff, Krishnan-Sarin, Patock-Peckham, & Potenza, in press; Moreno et al., 2012) and adverse childhood experiences (Afifi, Henriksen, Asmundson, & Sareen, 2012; Anda et al., 2006). Identifying how women's labor force participation is related to substance use behaviors can help to inform prevention efforts, such as worksite health promotion programs.

METHODS

Sample and Data Collection

The current sample is derived from survey participants in a study that was carried out with the cooperation of a large union representing construction industry workers in Northern California (Cunradi, Bersamin, & Ames, 2009). The study sought to obtain a purposive sample of 1,000 union workers and their spouses or cohabiting partners (i.e., 1,000 couples) in order to conduct separate, confidential telephone interviews on work, job stress, drinking, and intimate partner violence. Population Research Systems (PRS), an experienced San Francisco-based survey research firm, conducted the survey data collection from August 2006 through January 2007. The research protocol required that initial contact be made with the union member, and that the worker's permission be obtained to contact their spouse/partner by telephone. Informed consent was obtained from each participant, and the voluntary, confidential nature of the study was emphasized. On average, telephone interviews lasted 30 minutes, and each respondent was given a $25.00 incentive fee for their participation. The research protocol was approved by the Institutional Review Board of Pacific Institute for Research and Evaluation.

Worker Recruitment and Participation

A detailed description of the worker recruitment protocol can be found in Cunradi, Bersamin, et al., 2009. Briefly, study eligibility requirements for workers were (1) membership in the construction industry union; (2) currently married or cohabiting with the same partner for at least 12 months; and (3) physically and mentally able to complete a telephone interview in English or Spanish. A total of 1,088 workers (90% males) completed telephone survey interviews. The response rate was 53.4% (Cunradi, Bersamin, et al., 2009).

Spouse/Partner Recruitment and Participation

Of 1,088 workers who completed the interview, 95.6% gave their consent for their spouse/partners to be contacted. Of 1,040 potential spouse/partner respondents, 35 (3.4%) were unable to be contacted (answering machine, busy signal, etc.), 56 eligible spouse/partners (5.4%) refused participation, and 927 spouses/partners completed the interview. An additional 21 spouse/partners met eligibility requirements and asked to be called back for the interview. Due to budgetary and time constraints, these spouse/partners were not re-contacted prior to the completion of data collection.

Current Study Sample

Because we sought to compare the substance use patterns of women by labor force participation, the current study's sample (n=956) was limited to 104 female construction workers and 852 female spouses/partners of construction workers between the ages of 18 and 65 (i.e., employment age) who provided information about their employment status.

Measures

Labor Force Participation

Female respondents who participated in the study as members of the construction union were categorized as construction workers. Spouses/partners of construction workers were asked, “What is your current employment status?” Response categories included: employed – work for pay; unemployed; student or training/vocational program; and homemaker. Women who indicated that they were students or in training programs were excluded from the analysis due to small numbers (n=17). A 4-level categorical variable was created for labor force participation, with those in the employed – work for pay category as the reference group (herein referred to as “other employed women”).

Substance Use

Monthly Binge Drinking. In accord with the NIAAA definition of binge drinking for females (National Institute on Alcohol Abuse and Alcoholism, Winter 2004), respondents were asked, “During the past 12 months, about how often did you drink 4 or more drinks in about 2 hours?” Responses to this question were measured on a 9-point Likert-type scale (1-9, indicating “not at all” to “every day”). Those who responded that they drank this quantity at least once a month were categorized as monthly binge drinkers. All others comprised the comparison group. Current Smoking. Those who responded “yes” to the question, “Did you smoke any cigarettes in the past 30 days?” were categorized as current smokers. Non-smokers comprised the comparison group. Past-Year Marijuana Use. Respondents were asked, “How often did you use marijuana without a doctor's instruction at any time during the past 12 months?” Responses to this question were measured on a 9-point Likert-type scale (1-9, indicating “not at all” to “every day”). Those that indicated any past-12 month use were categorized as marijuana users. Non-users comprised the comparison group. Polysubstance Use. Respondents who reported using at least 2 or more substances (as defined above) were categorized as polysubstance users. Those who had used only one substance, or no substances, comprised the comparison group.

Impulsivity

Impulsivity was measured with a set of questions previously used in national alcohol surveys (Schafer, 1994). Respondents were asked how well a series of statements describe them on a 4-point scale (1-4: not at all, a little, some, and quite a lot): (1) “I often act on the spur-of-the-moment without stopping to think;” (2) “You might say I act impulsively;” and (3) “Many of my actions seem to be hasty.” Cronbach's α for this measure was .78.

Adverse Childhood Experiences

Childhood exposure to violence, alcoholism, and other adverse events was measured with a modified version of the Adverse Childhood Experiences (ACE) scale (Felitti et al., 1998). The modified ACE (Cabrera, Hoge, Bliese, Castro, & Messer, 2007) asks respondents about the following experiences as a child: (1) parent/caregiver-perpetrated physical abuse; (2) psychological abuse; (3) sexual abuse; (4) alcoholism or problem drinking by a household member; (5) depression or mental illness of a household member; and (6) domestic violence toward mother or caregiver. A scale of exposure to adverse childhood experiences, ranging from 0-6, was created by summing the number of positive responses to each of the six categories.

Sociodemographic Characteristics

Respondents provided information on their age, race/ethnicity, and highest level of education. Age was re-categorized as 18-29; 30-44; and 45-65 (reference category). Race/ethnicity was re-categorized as Hispanic/Latina, non-Hispanic other, and non-Hispanic white (reference category). Education level was re-categorized as some high school, high school graduate, some college, and college graduate (reference category).

Analytic Strategy

The bivariate associations between sample characteristics and labor force participation were assessed with chi-square tests of independence (Table 1). Multivariate logistic regression models were used to obtain adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for four outcomes: monthly binge drinking, past-30 day smoking, past year marijuana use, and polysubstance use (Table 2). Each model was adjusted for sociodemographic characteristics, impulsivity, and adverse childhood experiences. All variables in the table were entered as a group in the analyses. Analyses were conducted with IBM SPSS software, v.20.

Table 1.

Sample Characteristics by Labor Force Participation.

Total Sample (N=956) Construction Worker (N=104) Unemployed (N=101) Homemaker (N=227) Other Employed (N=524) Chi square, degrees of freedom
Age
18-29 214 (22.4) 12 (11.5) 18 (17.8) 72 (31.7) 112 (21.4) χ2=56.7, 6df p < 0.001
30-44 428 (44.7) 55 (52.9) 26 (25.7) 106 (46.7) 241 (46.0)
45-65 314 (32.8) 37 (35.6) 57 (56.4) 49 (21.6) 171 (32.6)
Race/ethnicity*
Other 148 (15.6) 32 (31.1) 18 (17.8) 21 (9.5) 77 (14.8) χ2=74.4, 6df p < 0.001
Hispanic/Latina 299 (31.7) 28 (27.1) 23 (22.8) 114 (51.8) 134 (25.7)
White 497 (52.6) 43 (41.8) 60 (59.4) 85 (38.6) 309 (59.4)
Education
<High School 136 (14.2) 10 (9.6) 10 (9.9) 71 (31.3) 45 (8.6) χ2=107.8, 9df p < 0.001
HS graduate 266 (27.8) 35 (33.6) 32 (31.7) 73 (32.1) 126 (24.0)
Some college 410 (42.9) 46 (44.2) 50 (49.5) 72 (31.7) 242 (46.1)
College+ 144 (15.1) 13 (12.5) 9 (8.9) 11 (4.8) 111 (21.2)
Monthly Binge Drinking
Yes 33 (3.5) 11 (10.6) 6 (5.9) 2 (0.9) 14 (2.7) χ2=23.2, 3df p < 0.001
No 923 (96.5) 93 (89.4) 95 (94.1) 225 (99.1) 510 (97.3)
Smoking
Yes 190 (19.9) 32 (30.8) 28 (27.7) 34 (15.0) 96 (18.3) χ2=15.9, 3df p < 0.01
No 766 (80.1) 72 (69.2) 73 (72.3) 193 (85.0) 428 (81.7)
Marijuana Use
Yes 61 (6.4) 9 (8.7) 13 (13.0) 8 (3.5) 31 (6.0) χ2=11.5, 3df p < 0.05
No 891 (93.6) 95 (91.3) 87 (87.0) 219 (96.5) 490 (94.0)
Polysubstance Use
Yes 44 (4.6) 11 (10.6) 9 (8.9) 7 (3.1) 17 (3.2) χ2=11.1, 3df p < 0.01
No 912 (95.4) 93 (89.4) 92 (91.1) 220 (96.9) 507 (96.7)
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*

race/ethnicity missing for 12 women

Table 2.

Odds Ratios (OR) and 95% Confidence Intervals (CI) from Logistic Regression Models of Binge Drinking, Smoking, Marijuana Use, and Polysubstance Use: The Role of Women's Labor Force Participation

Monthly Binge Drinking Past-30 Day Smoking Past Year Marijuana Use Polysubstance Use (2+ more)
Labor Force Participation 0R (95% CI) 0R (95% CI) 0R (95% CI) 0R (95% CI)
Construction Worker 4.01 (1.68, 9.59)** 1.94 (1.18, 3.21)* 1.37 (0.59, 3.20) 3.21 (1.40, 7.38)**
Unemployed 2.68 (0.96, 7.53) 1.64 (0.98, 2.76) 2.57 (1.22, 5.42)* 2.76 (1.13, 6.73)*
Homemaker 0.30 (0.07, 1.37) 0.89 (0.56, 1.42) 0.74 (0.32, 1.71) 0.94 (0.36, 2.43)
Other Employed 1.00 1.00 1.00 1.00
Race/ethnicity
Other 0.65 (0.21, 2.07) 0.85 (0.54, 1.35) 0.84 (0.41, 1.75) 1.13 (0.49, 2.58)
Hispanic/Latina 1.74 (0.75, 4.04) 0.33 (0.20, 0.53)*** 0.34 (0.14, 0.78)* 0.64 (0.27, 1.51)
White 1.00 1.00 1.00 1.00
Age
18-29 2.54 (0.83, 7.78) 1.25 (0.77, 2.03) 3.32 (1.59, 6.94)** 2.48 (1.04, 5.92)*
30-44 2.59 (0.99, 6.82) 1.27 (0.86, 1.88) 1.40 (0.71, 2.78) 1.40 (0.64, 3.08)
45-65 1.00 1.00 1.00 1.00
Education
Less than High School 1.44 (0.21, 9.68) 1.87 (0.89, 3.91) 0.91 (0.23, 3.53) 2.77 (0.60, 12.73)
High School graduate 1.94 (0.40, 9.46) 1.78 (1.01, 3.11)* 0.98 (0.37, 2.55) 1.78 (0.48, 6.65)
Trade school/some college 3.20 (0.71, 14.4) 1.29 (0.76, 2.18) 1.36 (0.57, 3.24) 2.24 (0.64, 7.84)
College graduate 1.00 1.00 1.00
Adverse childhood events 1.13 (0.91, 1.40) 1.24 (1.12, 1.38)*** 1.31 (1.12, 1.54)** 1.24 (1.04, 1.49)*
Impulsivity 1.92 (1.22, 3.03)** 0.99 (0.78, 1.25) 1.33 (0.93, 1.90) 1.67 (1.13, 2.47)**
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*

p < 0.05

**

p < 0.01

***

p < 0.001.

RESULTS

Sample Characteristics and Rates of Substance Use

As shown in the “Total Sample” column of Table 1, about 20% were ages 18-29 years old, nearly 45% were 30-44 years old, and one third were 45-65 year old. Approximately half of the sample was white, and nearly one-third was Hispanic/Latina. Most women had at least a high school education. Regarding substance use, 3.5% reported monthly binge drinking, nearly 20% were current smokers, 6.4% reported past-year marijuana use, and 4.6% used more than one substance.

Significant differences by labor force participation were seen for each of these characteristics. For example, larger proportions of homemaker women were younger, Hispanic/Latina, and had lower levels of education compared to women in the other employment categories. In terms of substance use, construction worker women had the highest rate (10.6%) of monthly binge drinking (X2=23.2; 3df, p<0.001). Rates of current smoking ranged from 15% among homemakers to 30.8% among construction workers (X2=15.9; 3df, p<0.01). Rates of marijuana use were highest among unemployed women (13%) and lowest among homemakers (3.5%; X2=11.5; 3df, p<0.05). Polysubstance use rates were highest among construction workers (10.6%) and lowest among homemakers and other employed women (3.1% and 3.2%, respectively; (X2=11.1; 3df, p<0.01).

Labor Force Participation and Substance Use

Multivariate correlates of each substance use outcome are shown in Table 2. Those who are construction workers were 4 times more likely to report monthly binge drinking (OR=4.01; 95% CI 1.68, 9.59; p<0.01) compared to women in the “other employed” category. Demographic factors (age, race/ethnicity) were not significantly associated with monthly binge drinking, nor were adverse childhood experiences. Impulsivity was positively associated with monthly binge drinking (OR=1.92; 95% CI 1.22, 3.03; p<0.01).

Construction worker women were nearly twice as likely to be current smokers compared to other employed women (OR=1.94; 95% CI 1.18, 3.21; p<0.05). Hispanic/Latina women were significantly less likely than white women to smoke (OR=0.33; 95% CI 0.20, 0.53; p<0.001). Compared to college graduates, women with a high school-level education were at elevated risk for smoking (OR=1.78; 95% CI 1.101, 3.11; p<0.01). Adverse childhood experiences were positively associated with likelihood of smoking (OR=1.24; 95% CI 1.23, 1.38; p<0.001).

Unemployed women were more than twice as likely as other employed women to report past-year marijuana use (OR=2.57; 95% CI 1.22, 5.42; p<0.05). As with smoking, Hispanic/Latina women were significantly less likely than white women to use marijuana (OR=0.34; 95% CI 0.14, 0.78; p<0.05). Women in the 18-29 year old age group were more likely to use marijuana than women in the 45-65 year old age group (OR=3.32; 95% CI 1.59, 6.94; p<0.01). Adverse childhood experiences were also positively associated with likelihood of marijuana use (OR=1.31; 95% CI 1.12, 1.54; p<0.01).

Compared to other employed women, construction workers were at elevated risk for polysubstance use (OR=3.21; 95% CI 1.40, 7.38; p<0.01), as were unemployed women (OR=2.76; 95% CI 1.13, 6.75; p<0.05). Women in the youngest age group were more likely to be polysubstance users than women in the oldest age group (OR=2.48; 95% CI 1.04, 5.92; p<0.05). Both adverse childhood experiences (OR=1.24; 95% CI 1.04, 1.49; p<0.05) and impulsivity (OR=1.67; 95% CI 1.13, 2.47; p<0.01) were significantly associated with polysubstance use.

DISCUSSION

The current study is the first to analyze the substance use patterns of female construction workers in relation to the female spouses/partners of male construction workers. It builds upon previous analyses of drinking-related behaviors that were conducted among the study's male construction workers and their female spouse/partners (n=848 couples). When measured using the AUDIT (Alcohol Use Disorders Identification Test), a 10-item screener developed by the World Health Organization to identify those whose drinking may have become harmful to their health (Babor, Higgins-Biddle, Saunders, & Monteiro, 2001), approximately 17% of the male workers were categorized as problem drinkers, compared to 10% of their female spouses/partners (Cunradi, Todd, Duke, & Ames, 2009). Another analysis, limited to the study's 502 dual-earner couples (i.e., construction worker males and their employed female spouses/partners), found that 40% of the men reported feeling intoxicated in the past 12 months, compared to 27% of the women. Moreover, among those who ever felt drunk, men reported an average of 18.9 days of feeling drunk, compared with an average of 6.8 days among women (Ames, Cunradi, Duke, Todd, & Chen, 2013).

The current study's findings indicate that rates of monthly binge drinking, smoking, and past-year marijuana use varied significantly among the women based on labor force participation. Rates of binge drinking (10.6%) and smoking (30.8%) were highest among construction worker women; marijuana use was highest among unemployed women (13%). When comparing these findings to those of other studies, it is important to note that the current sample consisted entirely of married/cohabiting women, a marital status often shown to be protective for substance use relative to those never married, single, widowed, or divorced/separated (Fagan, Shavers, Lawrence, Gibson, & O'Connell, 2007; Grant et al., 2009). For example, 9.3% of respondents who participated in the 2003-2004 California Women's Health Survey (CWHS) reported past-month binge drinking, but 45% of the CWHS sample were not married. In fact, women who weren't married were more than twice as likely to report past-month bingeing compared to married CWHS study participants (Timko, Sutkowi, Pavao, & Kimerling, 2008). Similarly, in an analysis of drinking among a national sample of women of child-bearing age, Caetano et al. (2006) found that those never married or single (including widowed, divorced or separated) were at elevated risk for past-year binge drinking compared to married women. Among non-pregnant women, those who were categorized as homemakers or retired were less likely to binge drink compared to those employed (Caetano et al., 2006).

The results of this study suggest that labor force participation is associated with multiple substance use outcomes among a sample of married/cohabiting women residing in northern California blue-collar households. Specifically, compared to other employed women, those who work in construction are at greater risk for monthly binge drinking and smoking; unemployed women are at greater risk for marijuana use. Women in both categories were at elevated risk for polysubstance use. These results remained significant after adjusting for age, race/ethnicity and education, as well as adverse childhood experiences and impulsivity, two psychosocial variables that are linked with substance use outcomes. Women construction workers may be at elevated risk for binge drinking due to similar mechanisms that are associated with excessive drinking among male workers in physically demanding jobs (e.g., Barnes & Zimmerman, 2013). Additionally, women working in construction, a traditionally male-dominated occupation, may be exposed to unique circumstances and pressures that may facilitate heavier drinking (Duke, Bergmann, Cunradi, & Ames, 2013).

This study has a number of strengths. First, the study was conducted with the cooperation of the construction union, which may have had a positive impact on worker (and spouse/partner) study participation. Second, the purposive sampling frame – married or cohabiting unionized construction workers and their spouses or partners – provided the study with a unique sample of female construction workers, as well as employment-age female spouses and partners of the male workers. This enabled a comparison of substance use patterns among women who are employed as construction workers, and women whose spouses/partners are employed in the same blue-collar occupation. While this limits to some extent the generalizability of the findings, it provides evidence about the relationship between labor force participation and substance use among women in blue-collar households. Third, survey data were collected for numerous substance use behaviors, which is important because of the often co-occurring use of alcohol, tobacco and drugs. Fourth, as noted above, the analysis was able to account for demographic and psychosocial factors that are associated with substance use.

A number of limitations should be noted. The cross-sectional study design precludes causal inference. It is possible, for example, that women who are heavier substance users select into blue-collar occupations, such as construction work. Moreover, life course socioeconomic position has also been shown to influence the likelihood of alcohol, tobacco, and marijuana use (Bowes, Chollet, Fombonne, Galéra, & Melchior, 2012; Oesterle, Hawkins, & Hill, 2011; Redonnet, Chollet, Fombonne, Bowes, & Melchior, 2012). The current study did not obtain information on these contextual variables. Another limitation is that no information was collected on potentially mediating factors, such as work-family conflicts (Roos, Lahelma, & Rahkonen, 2006). Likewise, no information was collected on home-smoking policies, which have been shown to influence likelihood of smoking and cessation among blue-collar workers (Okechukwu, Dutra, Bacic, El Ayadi, & Emmons, 2013)

In conclusion, the findings suggest that women in physically demanding male-dominated occupations and the unemployed wives/partners of blue-collar workers may be at elevated risk for multiple types of substance use. Prevention efforts aimed at reducing substance use behaviors among women in blue-collar jobs, such as construction, should be incorporated into worksite health promotion programs. Additional research is needed to explicate how labor force participation influences women's substance use.

ACKNOWLDEGEMENTS

Data collection for this project was supported by Grant Number R01 AA015444 from the National Institute on Alcohol Abuse and Alcoholism. The content is solely the responsibility of the authors and does not necessarily represent the National Institute on Alcohol Abuse and Alcoholism or the National Institutes of Health.

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