Excess Mortality Due to External Causes in Women in the South African Mining Industry: 2013–2015
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Management
2.2. Statistical Analysis
3. Results
Underlying Causes of Death
4. Discussion
Strengths and Limitations of This Study
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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All Women n = 594,114 | All Men n = 650,857 | All Women Miners n = 763 | Male Miners n = 6020 | Manufacturing Women Laborers n = 541 | Manufacturing Male Laborers n = 783 | |
---|---|---|---|---|---|---|
Age at death Median (years) | 60 | 53 | 44 | 55 | 53 | 52 |
Education (percentage) | ||||||
None | 20.1 | 13.2 | 10.5 | 11.3 | 5.4 | 10.3 |
Primary school | 33.0 | 34.9 | 17.1 | 39.7 | 33.3 | 35.7 |
High school | 43.6 | 47.9 | 66.3 | 46.5 | 45.9 | 52.7 |
Tertiary | 3.3 | 4.0 | 6.2 | 2.5 | 3.7 | 1.3 |
Smoking (percentage) | 14.1 | 46.8 | 11.1 | 47.3 | 17.3 | 50.3 |
Marital status (percentage) | ||||||
Never married | 50.1 | 53.7 | 53.6 | 35.0 | 53.7 | 51.4 |
Married | 27.0 | 36.9 | 26.7 | 53.7 | 21.4 | 38.1 |
Divorced | 20.4 | 6.6 | 16.9 | 8.1 | 21.4 | 7.9 |
Widowed | 2.5 | 2.7 | 2.8 | 3.2 | 2.6 | 2.6 |
External Cause of Death | Women Miners PMR (95% CI) | Women Manufacturing Laborers PMR (95% CI) | Unemployed Women | Male Miners PMR (95% CI) | Male Manufacturing Laborers PMR (95% CI) | Unemployed Men PMR (95% CI) |
---|---|---|---|---|---|---|
Total external causes (V01-Y34) | 183 (136–246) | 66 (45–97.5) | 102 (93.5–110) | 80 (76.2–84) | 76 (64–92) | 152 (147–158) |
Car occupant transport accident (V49) | 467 (151–1447) | 106 (15–752) | 50 (40–62) | 165 (124–220) | 33 (5–231) | 38 (32–45) |
Vehicle accidents of unspecified vehicle type (V89) | 243 (127–467) | 54 (17–167) | 82 (76–88) | 109 (94.8–124) | 59 (33–104) | 32 (30–35) |
Discharge from unspecified firearm (W34) | 464 (221–974) | 0 | 105 (94–117) | 47 (38–58) | 85 (50–144) | 168 (162–174) |
Accidental hanging or strangulation (W76) | 97 (14–685) | 60 (9–425) | 238 (220–258) | 58 (46–73) | 91(49–170) | 219 (211–227) |
Unspecified exposure to smoke and fire (X09) | 93 (13–663) | 60 (9–426) | 217 (200–235) | 38 (26–56) | 154 (69–343) | 196 (183–209) |
Exposure to unspecified factor (X59) | 218 (138–347) | 64 (32–129) | 90 (86–95) | 90 (82–99) | 68 (48–98) | 122 (119–125) |
Contact with sharp object (Y28) | 215 (30.3–1529) | 139 (20–983) | 115 (97–137) | 62.8 (41–95) | 30 (4–215) | 200 (186–215) |
Contact with blunt object (Y29) | 2220 (833–5915) | 360 (51–2556) | 1180 (108–1286) | 86 (71–103) | 72 (37–138) | 139 (133–146) |
Industry | Men | Women |
---|---|---|
Private Households | Ref | Ref |
Not economically active | 1.19 0.000 | 1.44 0.000 |
Unemployed people | 1.39 0.000 | 1.41 0.000 |
Unspecified activities | 1.04 0.335 | 1.06 0.106 |
Other activities | 1.40 0.000 | 1.29 0.000 |
Growing of crops | 1.33 0.000 | 1.77 0.000 |
Mining and quarrying | 1.36 0.000 | 2.20 0.000 |
Manufacture | 1.13 0.024 | 1.23 0.040 |
Production of electricity | 1.37 0.000 | 2.33 0.000 |
Building | 1.23 0.000 | 2.39 0.000 |
Other retail trade | 1.28 0.000 | 1.47 0.000 |
Repair of motor vehicles | 1.15 0.230 | - |
Other land transport | 1.51 0.000 | 1.86 0.000 |
Business activities | 1.18 0.014 | 1.64 0.000 |
Educational services | 1.14 0.042 | 1.48 0.000 |
Other service activities | 1.42 0.000 | 1.69 0.000 |
Age groups | ||
15–19 | 40.97 0.000 | 14.58 0.000 |
20–24 | 53.40 0.000 | 7.68 0.000 |
25–29 | 26.00 0.000 | 4.33 0.000 |
30–34 | 13.15 0.000 | 3.27 0.000 |
35–39 | 8.21 0.000 | 2.73 0.000 |
40–44 | 6.05 0.000 | 2.65 0.000 |
45–49 | 5.10 0.000 | 2.54 0.000 |
50–54 | 4.00 0.000 | 2.46 0.000 |
55–59 | 3.08 0.000 | 1.92 0.000 |
60–64 | 2.39 0.000 | 1.54 0.000 |
65–69 | 1.66 0.000 | 1.37 0.000 |
70–74 | 1.36 0.000 | 1.18 0.001 |
75–79 | 1.15 0.009 | 1.12 0.016 |
80+ | Ref | Ref |
Education | ||
None | Ref | Ref |
Primary school | 1.25 0.000 | 1.10 0.001 |
Secondary school | 1.72 0.000 | 1.42 0.000 |
Tertiary education | 2.42 0.000 | 2.41 0.000 |
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Wilson, K.S.; Kootbodien, T.; Naicker, N. Excess Mortality Due to External Causes in Women in the South African Mining Industry: 2013–2015. Int. J. Environ. Res. Public Health 2020, 17, 1875. https://doi.org/10.3390/ijerph17061875
Wilson KS, Kootbodien T, Naicker N. Excess Mortality Due to External Causes in Women in the South African Mining Industry: 2013–2015. International Journal of Environmental Research and Public Health. 2020; 17(6):1875. https://doi.org/10.3390/ijerph17061875
Chicago/Turabian StyleWilson, Kerry S., Tahira Kootbodien, and Nisha Naicker. 2020. "Excess Mortality Due to External Causes in Women in the South African Mining Industry: 2013–2015" International Journal of Environmental Research and Public Health 17, no. 6: 1875. https://doi.org/10.3390/ijerph17061875