Table 3.
Included studies, by short-term and long-term measures
| Author | Study details | Mental disorder | Male prevalence % | Comparison population prevalence % | Significance testing |
|---|---|---|---|---|---|
| Studies using short-term measures | |||||
| Bültmann et al 2001 [55] | Study population: Employees of 45 Dutch companies (who were not absent from work or working under modified conditions) Total sample size: 11,020 (response rate 45%) Participant characteristics: age range: 18–65 y; 73% men Study design: Cross-sectional random Measure: GHQ-12 Prevalence time period: Past few wks Study strength: Moderate |
Psychological distress | Male and female employees∗: Delivery/truck drivers (n = 22): 9.1% Machinists (n = 200): 29.5% Plumber/gas fitters (n = 43): 9.3% Foremen (manufacturing) (n = 46): 10.9% |
Total sample: 23% | Delivery/truck drivers (z = 2.2, p < 0.05), plumbers/gas fitters (z = 3.0, p < 0.01), and foremen (z = 2.6, p < 0.05) sig. lower than total sample. Machinists sig. higher than total sample (z = 2.0, p = 0.05). |
| Cohidon et al 2009 [56]† | Study population: Respondents to 1999–2003 International Survey on Mental Health in the General Population (SMPG) Total sample size: 36,000 (response rate not reported) Participant characteristics: age: 18+ y; 46% men Study design: Cross-sectional stratified quota Measure: MINI Prevalence time period: Past 2 wks Study strength: Weak |
Depression | Farmers (n = 307): 3.3% Manual workers (n = 3,773): 8.8% |
All employed males (n = 10,968): 7.4% | Farmers sig. lower than all employed men (z = 3.9, p < 0.01). Manual workers sig. higher than all employed men (z = 2.7, p < 0.05). |
| Cohidon et al 2010 [57] | Study population: Employed respondents to 2002–2003 French Decennial Health Survey Total sample size: 11,985 (response rate 77.8%) Participant characteristics: age: 18+ y; 52% men Study design: Cross-sectional random Measure: CES-D Prevalence time period: Past fortnight Study strength: Moderate |
Depression | Farmers (n = 223): 13.5% Blue collar workers (n = 1,952): 12.6% |
All employed males (n = 6,232): 11.7% | No sig. differences found |
| Eaton et al 1990 [58] | Study population: Employed residents of five US metropolitan locations Total sample size: 11,789 (response rate 68–79%) Participant characteristics: age range: 18–64 y; sex not reported Study design: Cross-sectional random Measure: DIS Prevalence time period: Past y Study strength: Strong |
Depression | Construction workers (n = 75): 5% Welders (n = 58): 3% Carpenters (n = 78): 3% Painters/construction/maintenance (n = 51): 2% Repairers (industrial machinery) (n = 52): 2% Other repairers (n = 54): 2% Other construction workers (n = 238): 2% Engineers/architects/surveyors (n = 121): 2% Engineering & related technologists (n = 86): 1% Construction average: 2.4% Gardeners (n = 52): 6% Farming/forestry/fishing workers (n = 74): 5% Farm workers (n = 47): 2% Agriculture average: 4.3% Precision metal workers (n = 83): 6% Assemblers (n = 176): 5% Misc. machine operators (n = 111): 5% Machine operators/assemblers/inspectors (n = 66): 4% Metal and plastic machine operators (n = 89): 4% Operators (machine not specified) (n = 118): 4% Machine operators (assorted materials) (n = 177): 2% Precision workers (assorted materials) (n = 154): 2% Printing machine operators (n = 55): 2% Precision textile workers (n = 53): 0% Manufacturing average: 3.4% Truck drivers (n = 138): 4% Transport workers (n = 237): 4% Vehicle repairers (n = 67): 3% Movers (n = 58): 2% Clerks/traffic shipping receiving (n = 66): 2% Auto mechanics (n = 68): 0% Transport average: 2.5% Mail distributors (n = 110): 2% Misc. mechanics & repairers (n = 57): 0% Electrical equipment repairers (n = 69): 0% Utilities average: 0.7% Laborers (n = 102): 6% Handlers/equipment cleaners/laborers (n = 144): 3% Manual workers average: 4.5% |
Total sample: 4% | Other construction workers (z = 2.2, p < 0.05), engineering and related technologies (z = 2.7, p < 0.05), auto mechanics (z = 22.2, p < 0.01), electrical equipment repairers (z = 22.2, p < 0.01), misc. mechanics and repairers (z = 22.2, p < 0.01), and precision textile workers (z = 22.2, p < 0.01) sig. lower than total sample. |
| National prevalence (past y, 1990–1992) [59]: 10.3% | Farming/forestry/fishing (z = 2.1, p < 0.05), construction workers (z = 2.1, p < 0.05), assemblers (z = 3.1, p < 0.01), misc. machine operators (z = 2.5, p < 0.05), machine operators/assemblers/inspectors (z = 2.6, p < 0.05), truck drivers (z = 3.7, p < 0.01), metal and plastic machine operators (z = 3.0, p < 0.01), operators (machine not specified) (z = 3.4, p < 0.01), transport workers (z = 4.7, p < 0.01), handlers/equipment cleaners/laborers (z = 3.7, p < 0.01), welders (z = 3.2, p < 0.01), vehicle repairers (z = 3.4, p < 0.01), carpenters (z = 3.7, p < 0.01), machine operators (assorted materials) (z = 7.4, p < 0.01), farm workers (z = 3.9, p < 0.01), painters/construction/maintenance (z = 4.1, p < 0.01), precision workers (assorted materials) (z = 6.9, p < 0.01), repairers (industrial machinery) (z = 4.1, p < 0.01), other repairers (z = 4.2, p < 0.01), mail distributors (z = 5.9, p < 0.01), printing machine operators (z = 4.3, p < 0.01), movers (z = 4.4, p < 0.01), other construction workers (z = 8.4, p < 0.01), engineers/architects/surveyors (z = 6.2, p < 0.01), clerks/traffic shipping receiving (z = 4.7, p < 0.01), engineering & related technologists (z = 8.1, p < 0.01), auto mechanics (z = 26.0, p < 0.01), electrical equipment repairers (z = 26.0, p < 0.01), misc. mechanics & repairers (z = 26.0, p < 0.01), and precision textile workers (z = 26.0, p < 0.01) sig. lower than national prevalence. | ||||
| Fragar et al 2010 [60] | Study population: Respondents to the Australian Rural Mental Health Study (ARMHS) Total sample size: 2,639 (response rate not reported) Participant characteristics: mean age: 55.1 y; 41% men Study design: Cross sectional stratified random Measure: K10 Prevalence time period: Past 4 wks Study strength: Weak |
Psychological distress | Machinery operators, drivers, & laborers (n = 153): 9.2% | Not reported | Unable to be conducted |
| Gann et al 1990 [61] | Study population: Employees of Scottish offshore oil mining company Total sample size: 796 (response rate 98%) Participant characteristics: mean age: 40.6 y; 96% male Study design: Cross-sectional convenience Measure: GADS Prevalence time period: “Recent” symptoms Study strength: Weak |
Depression | Total sample: 28% | National prevalence (1994, past y) [62]: 5% | Study sample sig. higher than national prevalence (z = 14.2, p < 0.01). |
| Hilton et al 2008 [17] | Study population: Employees of 58 large (> 1,000 employees) Australian government & private organizations Total sample size: 60,556 (response rate 24.7%) Participant characteristics: age: 18+ y; 42.4% male Study design: Cross-sectional purposive Measure: K6 Prevalence time period: Past 4 wks Study strength: Moderate |
Psychological distress | Agriculture: 3.4% Manufacturing: 3.4% Utilities: 4.2% |
Total sample: 4.5% All males (n = 25,697): 4.3% |
Unable to be conducted |
| Hilton et al 2009 [63] | Study population: Employed Australian heavy truck drivers Total sample size: 1,292 (response rate 8% (phase 1); 35.9% (phase 2) Participant characteristics: age: 18+ y; 98.3% male Study design: Cross-sectional convenience Measure: DASS-21 Prevalence time period: Past wk Study strength: Weak |
Depression | Total sample: 13.3% | DASS-21 Norms (n = 1,771): 18.3% | Sample sig. lower than normative data (z = 3.8, p < 0.01). |
| National prevalence (2007, past y) [4]: 4.1% | Study sample sig. higher than national prevalence (z = 9.5, p < 0.01). | ||||
| Hounsome et al 2012 [64] | Study population: Attendees of Welsh Agricultural Show 2002–2004 Total sample size: 784 (response rate not reported) Participant characteristics: age: 16+ y; 64.4% male Study design: Cross-sectional convenience Measure: GHQ-12 Prevalence time period: Past few wks Study strength: Weak |
Psychological distress | Farmers and their spouses (both men and women)∗(n = 287): 35% | Nonfarmers (n = 497): 27% | Farmers sig. higher than nonfarmers (z = 2.3, p < 0.05). |
| Inoue & Kawakami 2010 [65] | Study population: Employees of nine Japanese manufacturing companies Total sample size: 20,313 (response rate 85%) Participant characteristics: mean age: 37 y; 85.6% men Study design: Cross-sectional purposive Measure: CES-D Prevalence time period: Past fortnight Study strength: Moderate |
Depression | High SES (n = 6,045): 20% Moderate SES (n = 3,882): 22.1% Low SES (n = 7,463): 26.8% All: 23.38% |
Total sample: 24% | High (z = 6.7, p < 0.01) and moderate SES (z = 2.6, p < 0.01) sig lower than total sample. Low SES sig. higher than total sample (z = 4.7, p < 0.01). |
| National prevalence (2002–2003, past y) [66]: 2.9% | High (z = 27.7, p < 0.01), moderate (z = 25.7, p < 0.01), and low (z = 38.8, p < 0.01) SES sig. higher than national prevalence. | ||||
| Kawakami et al 1995 [67] | Study population: Employees of a Japanese electrical manufacturing company Total sample size: 468 (response rate 91%) Participant characteristics: mean age: 37.8 y; 100% men Study design: Prospective cohort Measure: SDS Prevalence time period: Past several days Study strength: Weak |
Depression | Total sample: 13% | National prevalence (2002–2003, past y) [66]: 2.9% | Study sample sig. higher than national prevalence (z = 6.3, p < 0.01). |
| Niedhammer et al 1998 [68] | Study population: Employees of national French utility company who participated in 1995–1996 Gazel Cohort longitudinal study Total sample size: 11,552 (response rate 64.1%) Participant characteristics: age range: 41–56 y; 73% men Study design: Prospective cohort Measure: CES-D Prevalence time period: Past fortnight Study strength: Moderate |
Depression | All men (n = 8,422): 24.9% | Total sample: 25.7% | Unable to be conducted |
| National prevalence (1999–2003, past fortnight) [56]: Men: 8.9% | Study sample sig. higher than national prevalence (z = 32.4, p < 0.01). | ||||
| Sanne et al 2004 [69] | Study population: Employed respondents to 1997–1999 Norwegian Hordaland Health Study survey Total sample size: 17,295 (response rate 65%) Participant characteristics: age range: 40–49 y; 46% men Study design: Cross-sectional random Measure: HADS Prevalence time period: Past wk Study strength: Moderate |
Depression | Farmers (n = 917): 17.3% | Male nonfarmers (n = 1 6,378): 9.3% | Farmers sig. higher than nonfarmers (z = 6.3, p < 0.01). |
| Scarth et al 2000 [70] | Study population: Farmers residing in Iowa and Colorado Total sample size: 855 (Iowa = 385, Colorado = 470); (response rate 32.8%) Participant characteristics: mean age: 50.12 y; 100% men Study design: Cross-sectional random Measure: CES-D Prevalence time period: Past fortnight Study strength: Moderate |
Depression | Farmers in Iowa (n = 385): 12.2% Farmers in Colorado (n = 470): 7.4% Total sample: 9.8% |
National prevalence (2001–2003, past y) [71]: 6.7% | Total study sample sig. higher than national prevalence (z = 3.0, p < 0.01) |
| Stansfeld et al 2011 [39] | Study population: Employed UK residents Total sample size: 5,497 (response rate 65.9%) Participant characteristics: age range: 16–64 y; sex not reported Study design: Cross-sectional random Measure: CIS-R Prevalence time period: Past wk Study strength: Moderate |
Common mental disorders | Skilled construction trades: 13% Drivers/mobile machine operators: 7% Industrial plant and machine operators/assemblers: 9% Science/engineering associate professionals: 6% Other elementary occupations: 8% |
Total sample: 13% | Unable to be conducted |
| Velander et al 2010 [72] | Study population: Employees of WA gold mining company Total sample size: 591 (response rate 61%) Participant characteristics: mean age: 35.8 y; 90% men Study design: Cross-sectional convenience Measure: DASS-21 Prevalence time period: Past wk Study strength: Weak |
Depression | All men (n = 530): 19.3% |
Total sample: 16% National rural and remote population: 5.4% |
Unable to be conducted |
| National prevalence (2007, past y) [4]: 4.1% | Study sample sig. higher than national prevalence (z = 8.8, p < 0.01). | ||||
| Studies using long-term measures | |||||
| Cohidon et al 2009 [56]† | Study population: Respondents to 1999–2003 International Survey on Mental Health in the General Population (SMPG) Total sample size: 36,000 (response rate not reported) Participant characteristics: age: 18+ y; 46% men Study design: Cross-sectional stratified quota Measure: MINI Prevalence time period: Lifetime Study strength: Weak |
Depression | Farmers (n = 307): 1.4% Manual workers (n = 3,773): 4.4% |
All employed men (n = 10,968): 3.9% | Farmers sig. lower than all employed males (z = 3.6, p < 0.01). |
| Joensuu et al 2010 [73] | Study population: Participants in Still Working Study of Forestry workers who had not been admitted to hospital for a mental disorder in past 15 y Total sample size: 13,868 (response rate 76%) Participant characteristics: age range: 16–65 y; 75% men Study design: Prospective cohort Measure: ICD-9 Prevalence time period: Past 15 y Study strength: Strong |
Depression | All men (n = 10,620): 1.3% | Total sample: 1.3% | Unable to be conducted |
| National prevalence (2000–2001, past y) [74]: 4.9% | Study sample sig. lower than national prevalence (z = 13.2, p < 0.01) | ||||
| Petersen & Zwerling 1998 [75] | Study population: Males born between 1931–1941 who responded to Wave 1 (1992) of US Health and Retirement Study Total sample size: 4,092 (response rate not reported) Participant characteristics: age range: 51–61 y; 100% men Study design: Cross-sectional random Measure: Single item: “Has a doctor ever told you that you had emotional, nervous, or psychiatric problems?” Prevalence time period: Lifetime Study strength: Weak |
Emotional/psychiatric problems | Construction workers (n = 312): 11.3% | White collar workers in other industries (n = 2,064): 5.3% Blue collar workers in other industries (n = 1,716): 6.4% |
Construction workers sig. higher than white (z = 3.2, p < 0.01) & blue (z = 2.6, p < 0.05) collar workers in other industries. |
| Thompson et al 2011 [76] | Study population: Alberta residents who had been employed in the last 12 months (2009) Total sample size: 2,817 (response rate 42.3%) Participant characteristics: age: 18+ y; 39.8% male Study design: Cross-sectional random Measure: MINI Prevalence time period: Lifetime Study strength: Moderate |
Depression | Agriculture/mining (n = 324): 10.3% Construction (n = 183): 11.0% Manufacturing (n = 132): 2.6% Transport (n = 121): 8.5% |
Total sample: 13.1% | Manufacturing sig. lower than total sample (z = 6.9, p < 0.01). |
| National prevalence (2012, past y) [77]: 4.7% | Agriculture/mining (z = 3.3, p < 0.01) and construction (z = 2.7, p < 0.01) sig higher than national prevalence. | ||||
| Wieclaw et al 2005 [40] | Study population: Danish residents with an affective disorder or stress-related diagnosis 1995–1998 Total sample size: 28,971 cases & 144,855 referents Participant characteristics: age range: 18–65 y; 36.1% men Study design: Population level nested case control Measure: ICD-10 Prevalence time period: Lifetime Study strength: Strong |
Affective disorders | Skilled agriculture & fishery workers (n = 760): 16.18% Extraction & building workers (n = 1,264): 13.69% Metal/machinery workers (n = 1,528): 12.57% Precision, handcraft, printing (n = 159): 12.59% Other craft workers (n = 225): 17.78% Stationary plant operators (n = 125): 14.40% Machine operators/assemblers (n = 759): 15.81% Drivers/mobile plant operators (n = 781): 13.70% Agriculture/fishery laborers (n = 60): 8.33% Other laborers (n = 664): 13.25% |
Not reported | Unable to be conducted |
CES-D, Center for Epidemiologic Studies Depressive Symptoms Scale; CIS-R, Clinical Interview Schedule; DASS-21, Depression, Anxiety, and Stress Scale; DIS, National Institute of Mental Health Diagnostic Interview Schedule; GADS, Goldberg Anxiety and Depression Scale; GHQ-12, General Health Questionnaire; HADS, Hospital Anxiety and Depression Scale; ICD. International Classification of Disease codes; K6, Kessler 6; K10, Kessler 10; MINI, Mini International Neuropsychiatric Interview; SDS, Zung Self-rating Depression Scale; SES, socioeconomic status.
∗
Data unable to be disaggregated by gender.
†
This study used both short- and long-term measures. Results have been separated accordingly and are reported in two places in the table.