Abstract
Background
Cigarette smoking remains a leading cause of morbidity and mortality. Although gender differences in cigarette smoking in the U.S. population have been documented, information on these differences among working adults is limited.
Purpose
To describe the current smoking prevalence by gender among working U.S. adults and examine gender differences in smoking by occupation.
Methods
The 2004–2011 National Health Interview Survey data for adults aged ≥18 years that were working in the week prior to the interview (N=132,215) were analyzed in 2013. Current cigarette smokers were those who smoked at least 100 cigarettes in their lifetime and currently smoke every day or some days.
Results
During 2004–2011, an estimated 22.8% of men workers and 18.3% of women workers were current smokers. Of the current smokers, women workers had higher odds of being an everyday smoker (prevalence OR [POR]=1.17, 95% CI=1.09, 1.26); having poor self-rated emotional health (POR=1.28, 95% CI=1.15, 1.41); and having chronic obstructive pulmonary disease (POR=2.45, 95% CI=2.14, 2.80), heart disease (POR=1.27, 95% CI=1.12, 1.45), and current asthma (POR=2.21, 95% CI=1.96, 2.49) compared with men workers. Women in “supervisors, construction, and extraction” (38.9%) occupations and men in “extraction” (40.5%) occupations had the highest smoking prevalence.
Conclusion
Among working adults, women had lower prevalence of smoking than men, yet women who smoke were more likely than men to have adverse health outcomes, including self-rated poorer physical and emotional health.
Introduction
Cigarette smoking remains a leading cause of morbidity and mortality.1–4 In 2011, 21.6% of men and 16.5% of women were current smokers in the U.S.2 Similar patterns were observed among working adults (21.5% of men and 17.4% of women).5 Women who smoke have higher burden of smoking-related diseases than men who smoke.6–11 Women smokers have a 25% increased risk of developing coronary heart disease and chronic obstructive pulmonary disease (COPD) and a high incidence of lung cancer compared to men who smoke.6,10 The percentage of women in the workforce has also increased from 38% in 1970 to 47% in 2010.12
Furthermore, previous studies13–17 have demonstrated the additive effect of cigarette smoking on adverse health outcomes and certain occupational exposures. Understanding occupational factors, socioeconomic characteristics, and smoking behavior of working men and women may guide targeted gender-specific interventions and more effective policies, smoking-cessation programs, and counseling strategies.11,18 This study estimates gender-specific cigarette smoking prevalence by occupation and examines the association between smoking behaviors, select socioeconomic characteristics, and health status among working men and women.
Methods
The National Health Interview Survey (NHIS) collects health information from the U.S. civilian non-institutionalized population.19,20 The survey response rates ranged from 72.5% in 2004 to 66.3% in 2011.19,20
Data on current occupation were collected from adults who were working in the week prior to the interview.20 Because of small sample sizes, 94 available detailed occupations were collapsed into 45 occupations using National Center for Health Statistics criteria20 and into four major occupational categories using criteria of Ham et al.21 Current cigarette smokers were those who smoked at least 100 cigarettes in their lifetime and currently smoke “every day” or “some days.”19
Data from the 2004–2011 NHIS were combined to improve precision and reliability of the estimates.19 Bivariable logistic regression was used to calculate prevalence ORs (PORs) and multivariable logistic regression to calculate PORs adjusted for age, race/ethnicity, education, and combined family income.10,18,19,21 The referent group was all other currently employed adults who were not in the occupation of interest. All tests were two-sided, and differences were considered significant at α=0.05. Prevalence estimates with relative SE (RSE, calculated as SE of the estimate divided by the estimate) >30% and <50% are reported but may be unreliable. Estimates with RSE ≥50% were considered unreliable and are not reported.19 Analyses were conducted in 2013 using SAS, version 9.2 (SAS Institute Inc., Cary NC).
Results
During 2004–2011, of the 141 million U.S. adults working the week prior to the interview, 53.5% were men, 46.5% were women, and 20.7% were current cigarette smokers. Smoking prevalence was highest among non-Hispanic whites and those with education ≤high school, income <$35,000, no health insurance, and living in the Midwest (Table 1). Smoking declined among working men (3.0%, p<0.0001) and women (2.8%, p<0.0001) during 2004–2011.
Table 1.
Demographic characteristics and prevalence of cigarette smoking by gender among working U.S. adults
| Characteristics | Number in samplea
|
Estimatedb currently working population (in 1,000s)
|
Current smokers (prevalence % [95% CI])
|
|||
|---|---|---|---|---|---|---|
| Men | Women | Men | Women | Men | Women | |
| Age group (years) | ||||||
|
| ||||||
| 18–24 | 6,817 | 7,115 | 9,302 | 8,604 | 26.9 (25.5, 28.4) | 19.4 (18.2, 20.6) |
|
| ||||||
| 25–44 | 31,564 | 31,054 | 35,246 | 28,865 | 23.7 (23.1, 24.3) | 19.7 (19.1, 20.3) |
|
| ||||||
| 45–64 | 24,071 | 25,475 | 27,733 | 25,418 | 21.7 (21.0, 22.4) | 17.3 (16.7, 17.9) |
|
| ||||||
| >65 | 3,071 | 3,048 | 3,008 | 2,447 | 10.2 (8.9, 11.5) | 9.2 (8.0, 10.4) |
|
| ||||||
| Race/ethnicity | ||||||
|
| ||||||
| Hispanic | 13,233 | 11,279 | 11,865 | 7,587 | 18.6 (17.7, 19.5) | 10.1 (9.4, 10.8) |
|
| ||||||
| Non-Hispanic white | 40,318 | 40,104 | 52,016 | 45,862 | 24.0 (23.4, 24.6) | 20.9 (20.4, 21.5) |
|
| ||||||
| Non-Hispanic black | 7,836 | 11,453 | 7,367 | 8,332 | 22.7 (21.5, 23.9) | 15.3 (14.4, 16.1) |
|
| ||||||
| Other | 4,136 | 3,856 | 4,040 | 3,552 | 19.9 (18.4, 21.5) | 9.7 (8.4, 10.9) |
|
| ||||||
| Education | ||||||
|
| ||||||
| <High school | 9,126 | 6,744 | 9,340 | 5,496 | 32.5 (31.1, 33.9) | 26.0 (25.4, 28.2) |
|
| ||||||
| High school graduate | 17,290 | 16,277 | 20,489 | 16,256 | 31.7 (30.9, 32.6) | 25.7 (24.8, 26.6) |
|
| ||||||
| >High school | 38,631 | 43,240 | 44,911 | 43,173 | 16.8 (16.2, 17.3) | 14.5 (14.1, 15.0) |
|
| ||||||
| Unknown | 476 | 431 | 549 | 407 | —c | —c |
|
| ||||||
| Household income ($) | ||||||
|
| ||||||
| 0–34,999 | 18,155 | 22,125 | 15,943 | 16,113 | 32.3 (31.4, 33.3) | 26.1 (25.2, 26.9) |
|
| ||||||
| 35,000–74,999 | 21,118 | 20,578 | 24,131 | 20,318 | 25.1 (24.4, 25.8) | 19.7 (19.0, 20.4) |
|
| ||||||
| ≥75,000 | 19,035 | 17,026 | 26,676 | 21,742 | 15.8 (15.1, 16.5) | 12.1 (11.5, 12.7) |
|
| ||||||
| Unknown | 7,215 | 6,963 | 8,540 | 7,160 | 20.8 (19.5, 22.0) | 16.0 (15.0, 17.0) |
|
| ||||||
| Health insurance | ||||||
|
| ||||||
| Not insured | 14,279 | 10,995 | 14,866 | 9,663 | 35.2 (34.2, 36.3) | 28.2 (27.1, 29.4) |
|
| ||||||
| Insured | 51,038 | 55,484 | 60,135 | 55,436 | 19.7 (19.2, 20.3) | 16.6 (16.2, 17.0) |
|
| ||||||
| Unknown | 206 | 213 | 288 | 234 | —c | —c |
|
| ||||||
| Region | ||||||
|
| ||||||
| Northeast | 14,279 | 10,995 | 12,924 | 12,192 | 20.9 (19.6, 22.2) | 17.5 (16.7, 18.4) |
|
| ||||||
| Midwest | 51,038 | 55,484 | 18,226 | 16,447 | 25.3 (24.3, 26.3) | 21.4 (20.5, 22.3) |
|
| ||||||
| South | 23,610 | 24,436 | 26,950 | 23,099 | 24.4 (23.6, 25.1) | 19.2 (18.5, 19.8) |
|
| ||||||
| West | 16,547 | 15,276 | 17,190 | 13,595 | 19.3 (18.4, 20.2) | 13.9 (13.1, 14.6) |
|
| ||||||
| Total | 65,523 | 66,692 | 75,289 | 65,333 | 22.8 (22.4, 23.3) | 18.3 (17.9, 18.7) |
The 2004–2011 National Health Interview Survey respondents aged ≥18 years, working in the week prior to the survey
Estimated average annual populations are weighted to represent current U.S. men and women workers aged 18 years who were employed in the week prior to the interview.
Relative SE for the estimated number of people who currently smoke >30%; estimate suppressed.
After adjusting for covariates, women who smoked had significantly higher odds of being an everyday smoker (POR=1.16); making an attempt to quit smoking (POR=1.10); having poor self-rated physical health (POR=1.20); having poor self-rated emotional health (POR=1.28); missing work for >7 days at a job or business because of illness or injury (POR=1.76); and having COPD (POR=2.45), any cancer (POR=2.57), heart disease (POR=1.27), or current asthma (POR=2.21) than men who smoked (Table 2).
Table 2.
Smoking behavior and health characteristics of current smokers by gender among working U.S. adults
| Characteristics | Men (% [95% CI]) | Women (% [95% CI]) | Women compared with men (PORa [95% CI]) |
|---|---|---|---|
| Frequency of smoking | |||
| Every day | 76.8 (75.9, 77.7) | 79.4 (78.5, 80.3) | 1.16 (1.08, 1.24) |
| Some days | 23.2 (22.3, 24.1) | 20.6 (19.7, 21.5) | 0.86 (0.81, 0.93) |
| Attempted to quit smoking | |||
| Yes | 43.9 (42.8, 45.0) | 46.2 (45.0, 47.3) | 1.10 (1.03, 1.17) |
| No | 56.1 (55.0, 57.2) | 53.8 (52.7, 55.0) | 0.91 (0.86, 0.97) |
| Number of cigarettes/dayb | |||
| ≤14 | 51.9 (50.9, 53.0) | 62.4 (61.3, 63.4) | 1.55 (1.46, 1.65) |
| >14 | 48.1 (47.0, 49.1) | 37.6 (36.6, 38.7) | 0.65 (0.61, 0.68) |
| Age first started to smoke (years) | |||
| ≤18 | 69.4 (68.4, 70.4) | 68.0 (66.9, 69.0) | 1.03 (0.97, 1.11) |
| >18 | 30.6 (29.7, 31.2) | 32.0 (31.0, 33.1) | 0.97 (0.91, 1.03) |
| Self-rated physical health | |||
| Excellent/good | 92.0 (91.5, 92.5) | 90.6 (90.0, 91.2) | 0.83 (0.75, 0.92) |
| Poor/fair | 8.0 (7.5, 8.5) | 9.4 (8.8, 10.0) | 1.20 (1.09, 1.33) |
| Self-rated emotional health | |||
| Good | 42.5 (40.7, 44.4) | 37.0 (35.4, 38.6) | 0.78 (0.71, 0.87) |
| Poor | 57.3 (55.4, 59.1) | 63.0 (61.4, 64.6) | 1.28 (1.15, 1.41) |
| Chronic diseases | |||
| COPD | 3.8 (3.4, 4.2) | 8.9 (8.4, 9.5) | 2.45 (2.14, 2.80) |
| Heart disease | 4.3 (3.9, 4.7) | 5.4 (5.0, 5.9) | 1.27 (1.12, 1.45) |
| Any cancerf | 2.6 (2.3, 2.9) | 6.4 (5.8, 6.9) | 2.57 (2.23, 2.96) |
| Lung cancer | 3.9 (1.3, 6.5) | 1.1 (0.22, 1.89) | 0.35 (0.11, 1.05) |
| Current asthma | 4.4 (3.9, 4.8) | 9.1 (8.4, 9.7) | 2.21 (1.96, 2.49) |
| Asthma attack | 40.4 (35.4, 45.5) | 51.1 (47.4, 55.8) | 1.45 (1.13, 1.87) |
| Seen/talked to a physician | |||
| Yes | 51.4 (50.4, 52.4) | 66.0 (64.9, 67.1) | 1.81 (1.70, 1.93) |
| No | 48.6 (47.6, 49.6) | 34.0 (32.9, 35.1) | 0.55 (0.52, 0.59) |
| Light/moderate physical activity | |||
| Yes | 50.6 (49.5, 51.8) | 55.1 (53.9, 56.3) | 1.18 (1.11, 1.25) |
| No | 49.4 (48.2, 50.5) | 44.9 ( 43.7, 46.1) | 0.85 (0.79, 0.90) |
| Lost work days | |||
| 0 | 56.7 (55.7, 57.7) | 45.9 (44.8, 47.0) | 0.67 (0.63, 0.71) |
| 1–7 | 34.6 (33.6, 35.9) | 41.6 (40.5, 42.7) | 1.50 (1.41, 1.59) |
| >7 | 8.7 (8.1, 9.3) | 12.5 (11.7, 13.2) | 1.76 (1.59, 1.96) |
Note: Boldface indicates statistical significance; estimates are weighted to represent the U.S. working population.
POR represents the odds of women who are current smokers with specific smoking behaviors or health outcome compared with men who are current smokers with specific smoking behaviors or health outcome. PORs were adjusted for age, race, education, and income.
Overall average number of cigarettes smoked among working population who currently smoked was 14.
COPD, chronic obstructive pulmonary disease; POR, prevalence OR.
Men working in “precision production, craft, construction, repair operators, fabricators, and laborers” (POR=1.94) occupations had the highest odds of being a current smoker. Among detailed occupations, “vehicle and mobile equipment mechanics, installers, and repairers” (POR=1.88) had the highest POR (Table 3), and “legal” (0.33) occupations had the lowest POR.
Table 3.
Cigarette smoking prevalence and PORs by occupation and gender among working U.S. adults
| Occupation group | Men
|
Women
|
Women compared with men PORc (95% CI) | ||||
|---|---|---|---|---|---|---|---|
| Estimateda workers (in 1000’s) | Prevalence % (95% CI) | PORb (95% CI) | Estimateda workers (in 1000’s) | Prevalence % (95% CI) | PORb (95% CI) | ||
| Managerial and professional specialty technical, sales, and administrative support | 35,548 | 16.6 (16.0, 17.1) | 0.55 (0.52, 0.58) | 44,433 | 15.9 (15.5, 16.4) | 0.73 (0.69, 0.77) | 0.90 (0.86, 0.94) |
|
| |||||||
| Chief executives, general and operations managers, and legislators | 1,447 | 12.8 (10.5, 15.1) | 0.62 (0.50, 0.76) | 481 | 10.4 (7.7, 13.2) | 0.62 (0.46, 0.84) | 0.72 (0.50, 1.03) |
|
| |||||||
| Advertising, marketing, promotions, public relations, and sales managers | 503 | 13.2 (9.4, 17.1) | 0.60 (0.42, 0.85) | 366 | 16.4 (12.2, 20.5) | 0.96 (0.71, 1.30) | 1.09 (0.68, 1.75) |
|
| |||||||
| Operations specialties managers and other management | 6,357 | 16.9 (15.6, 18.2) | 0.75 (0.68, 0.82) | 3,964 | 16.1 (14.6, 17.7) | 1.00 (0.89, 1.12) | 0.93 (0.80, 1.09) |
|
| |||||||
| Business and financial operations | 2,739 | 13.7 (12.1, 15.3) | 0.64 (0.56, 0.74) | 3,213 | 15.0 (13.5, 16.6) | 0.94 (0.83, 1.06) | 1.06 (0.89, 1.27) |
|
| |||||||
| Computer and mathematical | 2,767 | 13.2 (11.5, 14.8) | 0.57 (0.49, 0.66) | 950 | 11.4 (9.2, 13.6) | 0.67 (0.53, 0.84) | 0.81 (0.61, 1.08) |
|
| |||||||
| Entertainers and performers, sports and related | 376 | 15.0 (10.3, 19.6) | 0.65 (0.45, 0.95) | 384 | 10.2 (6.6, 13.7) | 0.53 (0.38, 0.84) | 0.53 (0.33, 0.84) |
|
| |||||||
| Life, physical, and social science | 729 | 10.2 (7.7, 12.7) | 0.48 (0.36, 0.63) | 655 | 9.4 (6.7, 12.1) | 0.57 (0.41, 0.78) | 0.90 (0.58, 1.40) |
|
| |||||||
| Community and social services | 905 | 9.7 (7.5, 11.9) | 0.41 (0.32, 0.53) | 1,410 | 12.8 (10.8, 14.8) | 0.78 (0.65, 0.94) | 1.37 (1.00, 1.90) |
|
| |||||||
| Legal | 792 | 7.1 (5.0, 9.1) | 0.33 (0.24, 0.45) | 841 | 13.0 (10.0, 16.1) | 0.78 (0.60, 1.02) | 1.53 (0.99, 2.37) |
|
| |||||||
| Postsecondary teachers | 710 | 8.9 (6.5, 11.2) | 0.38 (0.28, 0.52) | 672 | 7.0 (4.9, 9.1) | 0.40 (0.29, 0.56) | 0.77 (0.48, 1.23) |
|
| |||||||
| Primary, secondary, and special education school teachers | 1,433 | 9.4 (7.5, 11.2) | 0.40 (0.32, 0.49) | 4,675 | 7.6 (6.7, 8.5) | 0.39 (0.34, 0.44) | 0.74 (0.57, 0.95) |
|
| |||||||
| Librarians, curators, and archivists and other education-related | 152 | 16.4 (9.8, 23.0) | 0.72 (0.45, 1.16) | 1,192 | 11.1 (8.8, 13.4) | 0.57 (0.45, 072) | 0.55 (0.31, 0.96) |
|
| |||||||
| Art and design | 523 | 17.8 (13.2, 22.3) | 0.93 (0.65, 1.27) | 494 | 14.7 (10.8, 18.6) | 0.93 (0.67, 1.27) | 0.78 (0.49, 1.24) |
|
| |||||||
| Architecture and engineering | 2,299 | 15.0 (12.9, 17.0) | 0.71 (0.61, 0.84) | 228 | 14.2 (9.1, 19.4) | 0.79 (0.52, 1.20) | 0.95 (0.54, 1.67) |
|
| |||||||
| Media and communication | 552 | 16.3 (12.7, 19.9) | 0.79 (0.60, 1.05) | 510 | 11.0 (8.2, 13.9) | 0.65 (0.48, 0.89) | 0.62 (0.41, 0.92) |
|
| |||||||
| Healthcare practitioners and technical | 1,810 | 8.8 (7.2, 10.3) | 0.37 (0.30, 0.45) | 5,320 | 13.7 (12.6, 14.8) | 0.82 (0.74, 0.91) | 1.56 (1.25, 1.94) |
|
| |||||||
| Supervisors, sales | 2,242 | 24.0 (21.7, 26.2) | 1.14 (1.00, 1.29) | 1,505 | 24.7 (21.8, 27.6) | 1.42 (1.21, 1.67) | 0.88 (0.72, 1.07) |
|
| |||||||
| Retail sales | 2,418 | 25.2 (23.1, 27.4) | 1.05 (0.93, 1.20) | 3,622 | 23.2 (21.5, 25.0) | 1.12 (1.01, 1.24) | 0.78 (0.66, 0.91) |
|
| |||||||
| Sales representatives, services, wholesale, and manufacturing | 2,813 | 17.3 (15.3, 19.3) | 0.84 (0.73, 0.97) | 1,917 | 17.8 (15.9, 19.8) | 1.06 (0.92, 1.22) | 0.93 (0.76, 1.14) |
|
| |||||||
| Supervisors, office and administrative support, and communication equipment operators | 1,057 | 20.0 (16.8, 23.1) | 0.86 (0.70, 1.05) | 3,216 | 17.2 (15.6, 18.8) | 0.92 (0.83, 1.04) | 0.77 (0.61, 0.97) |
|
| |||||||
| Administrative support | 3,827 | 23.2 (21.5, 24.9) | 0.95 (0.85, 1.05) | 10,230 | 19.5 (18.6, 20.5) | 1.08 (1.00, 1.16) | 0.79 (0.71, 0.89) |
|
| |||||||
| Services | 10,664 | 24.6 (23.4, 25.7) | 1.00 (0.93, 1.07) | 14,442 | 24.0 (23.1, 24.9) | 1.34 (1.27, 1.42) | 0.90 (0.83, 0.97) |
|
| |||||||
| Healthcare support | 389 | 20.9 (16.0, 25.8) | 0.83 (0.60, 1.14) | 2,719 | 26.3 (24.3, 28.3) | 1.43 (1.29, 1.59) | 1.22 (0.86, 1.72) |
|
| |||||||
| Protective service | 2,167 | 15.5 (13.6, 17.4) | 0.63 (0.54, 0.74) | 597 | 22.8 (18.7, 26.9) | 1.26 (0.99, 1.60) | 1.46 (1.09, 1.95) |
|
| |||||||
| Supervisors, food preparation, and serving | 479 | 33.9 (28.5, 39.3) | 1.72 (1.31, 2.25) | 424 | 30.3 (24.9, 35.7) | 1.69 (1.30, 2.20) | 0.75 (0.52, 1.10) |
|
| |||||||
| Cooks and food preparation | 1,322 | 36.0 (32.2, 39.8) | 1.45 (1.22, 1.74) | 1,237 | 24.7 (21.7, 27.7) | 1.11 (0.93, 1.32) | 0.53 (0.42, 0.68) |
|
| |||||||
| Food and beverage serving and related | 1,233 | 34.3 (30.2, 38.3) | 1.48 (1.22, 1.80) | 2,325 | 34.0 (31.5, 36.5) | 1.91 (1.70, 2.15) | 0.92 (0.75, 1.13) |
|
| |||||||
| Supervisors, building and grounds cleaning and maintenance | 364 | 23.3 (17.6, 29.0) | 1.05 (0.74, 1.50) | 122 | 33.9 (24.2, 43.6) | 2.10 (1.29, 3.56) | 1.43 (0.78,2.63) |
|
| |||||||
| Building cleaning and pest control | 1,753 | 25.3 (22.5, 28.1) | 0.92 (0.79, 1.08) | 2,048 | 21.0 (18.8, 23.2) | 0.83 (0.72, 0.96) | 0.69 (0.56, 0.85) |
|
| |||||||
| Grounds maintenance | 1,160 | 27.3 (23.8, 30.8) | 1.00 (0.82, 1.22) | 81 | 34.4 (22.5, 46.4) | 2.57 (1.40, 4.69) | 1.55 (0.84, 2.83) |
|
| |||||||
| Personal care and service | 893 | 23.3 (20.0, 26.7) | 0.93 (0.76, 1.14) | 3,480 | 20.3 (18.5, 22.0) | 1.03 (0.92, 1.15) | 0.80 (0.63, 1.01) |
|
| |||||||
| Farming, fishing, and forestry | 765 | 23.9 (19.8, 28.0) | 0.79 (0.62, 1.02) | 209 | 13.3 (8.0, 18.5) | 0.47 (0.30, 0.75) | 0.37 (0.22, 0.63) |
|
| |||||||
| Precision production, craft, construction, repair operators, fabricators, and laborers | 25,818 | 31.3 (30.6, 32.1) | 1.94 (1.83, 2.06) | 4,473 | 27.2 (25.5, 28.8) | 1.46 (1.33, 1.61) | 0.68 (0.62, 0.74) |
|
| |||||||
| Supervisors, construction, and extraction | 792 | 31.4 (27.1, 35.7) | 1.48 (1.20, 1.83) | 24 | 38.9 (16.2, 61.6) | 3.00 (1.07, 8.44) | 1.46 (0.49, 4.35) |
|
| |||||||
| Construction trade workers and helpers | 7,064 | 34.1 (32.5, 35.7) | 1.62 (1.49, 1.77) | 176 | 36.3 (28.0, 44.5) | 2.38 (1.62, 3.51) | 0.96 (0.64, 1.43) |
|
| |||||||
| Extraction | 159 | 40.5 (28.8, 52.2) | 1.83 (1.13, 2.95) | 0 | nc | nc | 0.58 (0.31, 1.09) |
|
| |||||||
| Supervisors of installation, maintenance, and repair | 301 | 24.2 (17.7, 30.8) | 1.27 (0.86, 1.89) | 25 | 33.3 (6.6, 60.0) | 2.41 (0.66, 8.75) | 1.35 (0.34, 5.44) |
|
| |||||||
| Electrical and electronic equipment mechanics, installers, and repairers | 720 | 23.5 (19.6, 27.4) | 1.19 (0.94, 1.50) | 75 | 25.8 (14.2, 37.5) | 1.99 (1.08, 3.65) | 1.21 (0.63, 2.33) |
|
| |||||||
| Vehicle and mobile equipment mechanics, installers, and repairers | 3,851 | 31.3 (29.4, 33.1) | 1.88 (1.43, 1.75) | 106 | 33.7 (24.3, 43.2) | 1.86 (1.18, 2.94) | 0.86 (0.54, 1.37) |
|
| |||||||
| Supervisors, production | 633 | 28.7 (24.1, 33.2) | 1.52 (1.20, 1.94) | 157 | 25.8 (17.9, 33.7) | 1.46 (0.92, 2.31) | 0.68 (0.42, 1.13) |
|
| |||||||
| Assemblers and fabricators | 794 | 27.6 (23.4, 31.8) | 1.11 (0.89, 1.40) | 521 | 28.4 (23.6, 33.1) | 1.42 (1.10, 1.83) | 0.88 (0.64, 1.22) |
|
| |||||||
| Food processing | 341 | 29.7 (23.4, 35.9) | 1.07 (0.77, 1.48) | 228 | 30.7 (22.6, 38.8) | 1.48 (1.00, 2.18) | 0.92 (0.57, 1.49) |
|
| |||||||
| Metal and plastic workers | 1,552 | 35.7 (32.6, 38.8) | 1.77 (1.52, 2.06) | 232 | 26.5 (19.9, 33.2) | 1.35 (0.93, 1.96) | 0.53 (0.35, 0.80) |
|
| |||||||
| Printing workers | 261 | 31.7 (24.4, 39.0) | 1.60 (1.10, 2.34) | 84 | 19.6 (9.2, 30.0) | 1.13 (0.56, 2.29) | 0.50 (0.24, 1.03) |
|
| |||||||
| Textile, apparel, and furnishings | 246 | 24.7 (18.3, 31.2) | 0.92 (0.63, 1.36) | 454 | 18.8 (14.9, 22.7) | 0.75 (0.58, 0.98) | 0.59 (0.37, 0.93) |
|
| |||||||
| Wood workers, plant and system operators, other production | 2,383 | 28.2 (26.0, 30.4) | 1.21 (1.07, 1.37) | 1,042 | 26.4 (22.9, 29.8) | 1.28 (1.07, 1.55) | 0.77 (0.61, 0.95) |
|
| |||||||
| Transportation and material moving | 6,720 | 30.5 (29.1, 32.0) | 1.35 (1.25, 1.46) | 1,347 | 28.3 (25.6, 31.1) | 1.48 (1.28, 1.72) | 0.77 (0.65, 0.90) |
|
| |||||||
| Refused, not ascertained, do not know | 2,494 | 15.9 (13.5, 18.3) | nc | 1,728 | 10.4 (8.6, 12.1) | nc | 0.59 (0.46, 0.77) |
|
| |||||||
| Total | 75,289 | 22.8 (22.4, 23.3) | nc | 65,333 | 18.3 (17.9, 18.7) | nc | 0.71 (0.69, 0.74) |
Note: Boldface indicates statistical significance.
Estimated annual average populations are weighted to represent current U.S. male/female workers aged ≥18 years by 45 regrouped occupations.
PORs represent the odds of workers that are current smokers belonging to a specific occupation of interest compared with the odds of all other workers. Analysis was done separately for men and women; PORs are adjusted for age, race, education, and income.
PORs represent the odds of women being a current smoker in a specific occupation of interest, as compared with the same odds of men being current smokers in the same occupation group of interest. nc, not calculated; POR, prevalence OR.
Women working in “services” (POR=1.34) occupations had the highest odds of being a current smoker. Among detailed occupations, “supervisors, construction, and extraction” (POR=3.00) had the highest POR and “primary, secondary, and special education school teachers” (POR=0.39) had the lowest POR. After adjusting for age, race, education and income, women in “healthcare practitioners and technical” (POR=1.56); “protective service” (POR=1.46); and “community and social services” (POR=1.37) occupations had significantly higher smoking prevalence than men (Table 3).
Discussion
During 2004–2011, significantly more men (22.8%) than women (18.3%) were current smokers. Women smokers were more likely to report poor physical and mental health, COPD, heart disease, cancer, and current asthma than men who smoke. Factors associated with smoking and adverse health outcomes in women (e.g., biological factors, genetic and hormonal factors, socioeconomic factors, occupational exposure, job stress, personal lifestyles, secondhand smoke exposure, or a combination of these factors) have been reported previously.10,11,23–25
In both men and women, cigarette smoking prevalence varied widely by occupational group. In certain occupations, the prevalence of smoking was three times greater than the Healthy People 2020 goal that aims to reduce cigarette smoking prevalence to ≤12%.26 Similar findings have been previously documented.21,22,27
Women in health care–related occupations had higher smoking prevalence than men. This finding is underscored by the fact that more women than men work in this sector and that healthcare providers are critical in the delivery of clinical preventive services for reducing tobacco use. Social or cultural factors related to the occupation may be associated with higher smoking prevalence.21
Holahan and colleagues28 found that presence of smokers in the workplace and at home was significantly associated with higher odds of being a current smoker. Our findings of lowest prevalence among women in teaching-related occupations and among men in “legal” occupations are supported by previous reports.6,21,29 The observed differences of smoking prevalences by job type could be explained, in part, by occupational and environmental factors, such as low educational level, increased job stressors, workplace culture, exposure to dusts and chemicals, and low rates of tobacco control programs and policies.21,27,29
Although the NHIS data did not include measures to assess workplace policies or exposures to secondhand smoke, other national surveys21,27,29 have shown that the proportion of smoke-free worksites are lower in mining, production, food services, and construction occupations than in professional and related services occupations, and the current results show that smoking prevalences are higher among these occupations. Detailed description of current smoking among working men and women by occupation will inform interventions that can be targeted to specific worksite settings. These interventions may include a combination of effective strategies such as tobacco-free policies, cessation programs, and educational campaigns.30–33
Study limitations include the use of self-reported smoking information that was not validated by biochemical tests.34,35 Cross-sectional analysis of NHIS data does not assess the long-term health effects of smoking or causal inferences between smoking and health outcomes. The study only included currently employed adults; however, additional analyses examining longest-held job found similar results in both men and women.
Smoking is the most important modifiable risk factor associated with various health outcomes. Women had lower prevalence of smoking, yet a higher prevalence of adverse health outcomes when compared with men. For some occupations, women smoked more than men. Future studies should explore methods to include indicators on individual’s industry and occupation, smoking behaviors, gender, and health outcomes for designing targeted intervention programs specific to the group. Targeting occupations with high smoking prevalence while considering gender differences may further reduce smoking and improve overall well-being. Results of this study can be used to implement existing, effective tobacco control strategies in coordination with gender-specific interventions.27,28,30–33
Acknowledgments
The authors would like to thank Cecil M. Burchfiel, PhD, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, and Robert B. Gerzoff, MS, Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, CDC, for their helpful comments.
Footnotes
No financial disclosures were reported by the authors of this paper.
References
- 1.CDC. The health consequences of smoking—50 years of progress: a report of the surgeon general. Atlanta GA: USDHHS, CDC, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2014. www.surgeongeneral.gov/library/reports/50-years-of-progress/exec-summary.pdf. [Google Scholar]
- 2.CDC. Current cigarette smoking among adults—U.S. 2011. MMWR Morb Mortal Wkly Rep. 2012;61(44):889–94. [PubMed] [Google Scholar]
- 3.CDC. Smoking-attributable mortality, years of potential life lost, and productivity losses—U.S. 2000–2004. MMWR Morb Mortal Wkly Rep. 2008;57(45):1226–8. [PubMed] [Google Scholar]
- 4.USDHHS. Health consequences of smoking: a report of the Surgeon General. cdc.gov/tobacco/data_statistics/sgr/2004/
- 5.CDC. Current cigarette smoking prevalence among working adults—U.S. 2004–2010. MMWR Morb Mortal Wkly Rep. 2011;60(38):1305–9. [PubMed] [Google Scholar]
- 6.Freedman ND, Leitzmann MF, Hollenbeck AR, Schatzkin A, Abnet CC. Cigarette smoking and subsequent risk of lung cancer in men and women: analysis of a prospective cohort study. Lancet Oncol. 2008;9(7):649–56. doi: 10.1016/S1470-2045(08)70154-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.CDC. Curent cigarette smoking among adults—U.S. 2006. MMWR Morb Mortal Wkly Rep. 2007;56(44):1157–61. [PubMed] [Google Scholar]
- 8.Chen Y, Dales R, Krewski D, Breithaupt K. Increased effects of smoking and obesity on asthma among female Canadians: the National Population Health Survey, 1994–1995. Am J Epidemiol. 1999;150(3):255–62. doi: 10.1093/oxfordjournals.aje.a009996. [DOI] [PubMed] [Google Scholar]
- 9.Kennedy SM, Chambers R, Du W, Dimich-Ward H. Environmental and occupational exposures: do they affect chronic obstructive pulmonary disease differently in women and men? Proc Am Thorac Soc. 2007;4(8):692–4. doi: 10.1513/pats.200707-094SD. [DOI] [PubMed] [Google Scholar]
- 10.Huxley RR, Woodward M. Cigarette smoking as a risk factor for coronary heart disease in women compared with men: a systematic review and meta-analysis of prospective cohort studies. Lancet. 2011;378(9799):1297–5. doi: 10.1016/S0140-6736(11)60781-2. [DOI] [PubMed] [Google Scholar]
- 11.Kirkland S, Greaves L, Devichand P. Gender differences in smoking and self-reported indicators of health. BMC Womens Health. 2004;(4S1):S7. doi: 10.1186/1472-6874-4-S1-S7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.U.S. Census Bureau. How do we know? America’s changing labor force. Washington DC: U.S. Census Bureau; 2011. www.census.gov/how/pdf/EEO_infographic.pdf. [Google Scholar]
- 13.Markowitz SB, Levin SM, Miller A, Morabia A. Asbestos, asbestosis, smoking, and lung cancer. New findings from the North American Insulator Cohort. Am J Respir Crit Care Med. 2013;188(1):90–6. doi: 10.1164/rccm.201302-0257OC. [DOI] [PubMed] [Google Scholar]
- 14.Kurihara N, Wada Silicosis and smoking strongly increase lung cancer risk in silica-exposed workers. Industrial Health. 2004;42(3):303–14. doi: 10.2486/indhealth.42.303. [DOI] [PubMed] [Google Scholar]
- 15.Blanc PD, Iribarren C, Trupin L, et al. Occupational exposures and the risk of COPD: dusty trades revisited. Thorax. 2009;64(1):6–12. doi: 10.1136/thx.2008.099390. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Matheson MC, Benke G, Raven J, et al. Biological dust exposure in the workplace is a risk factor for chronic obstructive pulmonary disease. Thorax. 2005;60(8):645–51. doi: 10.1136/thx.2004.035170. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Sunyer J, Zock JP, Kromhout H, et al. Lung function decline, chronic bronchitis, and occupational exposures in young adults. Am J Respir Crit Care Med. 2005;172(9):1139–45. doi: 10.1164/rccm.200504-648OC. [DOI] [PubMed] [Google Scholar]
- 18.Task Force on Community Preventive Services. Recommendations for worksite-based interventions to improve workers’ health. Am J Prev Med. 2010;38(2S):S232–S236. doi: 10.1016/j.amepre.2009.10.033. [DOI] [PubMed] [Google Scholar]
- 19.CDC. Data file documentation, National Health Interview Survey. Hyattsville MD: CDC, National Center for Health Statistics; 2010. ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHIS/2010/srvydesc.pdf. [Google Scholar]
- 20.CDC. Data file documentation, National Health Interview Survey. Hyattsville MD: CDC, National Center for Health Statistics; 2004–2009. ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHIS/2004_2009_IO_note_to_users.pdf. [Google Scholar]
- 21.Ham DC, Przybeck T, Strickland JR, Luke DA, Bierut LJ, Evanoff BA. Occupation and workplace policies predict smoking behaviors: analysis of national data from current population survey. J Occup Environ Med. 2011;53(11):1337–45. doi: 10.1097/JOM.0b013e3182337778. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Bang KM, Kim JH. Prevalence of cigarette smoking by occupation and industry in the U. S Am J Ind Med. 2001;40(3):233–9. doi: 10.1002/ajim.1094. [DOI] [PubMed] [Google Scholar]
- 23.Denton M, Prus S, Walters V. Gender differences in health: a Canadian study of the psychosocial, structural and behavioral determinants of health. Soc Sci Med. 2004;58(12):2585–600. doi: 10.1016/j.socscimed.2003.09.008. [DOI] [PubMed] [Google Scholar]
- 24.Kouvonen A, Kivimäki M, Virtanen M, Pentti J, Vahtera J. Work stress, smoking status, and smoking intensity: an observational study of 46,190 employees. J Epidemiol Community Health. 2005;59(1):63–9. doi: 10.1136/jech.2004.019752. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Ng DM, Jeffery RW. Relationships between perceived stress and health behaviors in a sample of working adults. Health Psychol. 2003;22(6):638–42. doi: 10.1037/0278-6133.22.6.638. [DOI] [PubMed] [Google Scholar]
- 26.USDHHS. Healthy People 2020. Objective TU-1.1: Cigarette smoking. healthypeople.gov/2020/topicsobjectives2020/objectiveslist.aspx?topicId=41#285350.
- 27.Chin DL, Hong O, Gillen M, Bates MN, Okechukwu CA. Cigarette smoking in building trades workers: the impact of work environment. Am J Ind Med. 2012;55(5):429–39. doi: 10.1002/ajim.22031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Holahan CK, Holahan CJ, Li X, Jung S. Social influences on smoking in American workers: the role of the presence of smokers in the workplace and in the home. Am J Health Promot. 2013;28(2):105–7. doi: 10.4278/ajhp.120604-ARB-283. [DOI] [PubMed] [Google Scholar]
- 29.Shopland DR, Anderson CM, Burns DM, Gerlach KK. Disparities in smoke-free workplace policies among food service workers. J Occup Environ Med. 2004;46(4):347–56. doi: 10.1097/01.jom.0000121129.78510.be. [DOI] [PubMed] [Google Scholar]
- 30.CDC. Best practices for comprehensive tobacco control programs—2007. Atlanta GA: USDHHS, CDC, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2007. [Google Scholar]
- 31.Cahill K, Moher M, Lancaster T. Workplace interventions for smoking cessation. Cochrane Database Syst Rev. 2008;(4):CD003440. doi: 10.1002/14651858.CD003440.pub3. [DOI] [PubMed] [Google Scholar]
- 32.Fiore MC, Jaen CR, Baker TB, et al. Clinical practice guideline. Rockville MD: USDHHS, Public Health Service; 2008. Treating tobacco use and dependence: 2008 update. www.surgeongeneral.gov/tobacco/treating_tobacco_use08.pdf. [Google Scholar]
- 33.Farrelly MC, Evans WN, Sfekas AE. The impact of workplace smoking bans: results from a national survey. Tob Control. 1999;8(3):272–7. doi: 10.1136/tc.8.3.272. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Caraballo RS, Giovino GA, Pechacek TF, Mowery PD. Factors associated with discrepancies between self-reports on cigarette smoking and measured serum cotinine levels among person aged 17 years or older: Third National Health and Nutrition Examination Survey, 1988–1994. Am J Epidemiol. 2001;153(8):807–14. doi: 10.1093/aje/153.8.807. [DOI] [PubMed] [Google Scholar]
- 35.Patrick DL, Cheadle A, Thompson DC, Diehr P, Koepsell T, Kinne S. The validity of self-reported smoking: a review and meta-analysis. Am J Public Health. 1994;84(7):1087–93. doi: 10.2105/ajph.84.7.1086. [DOI] [PMC free article] [PubMed] [Google Scholar]