| Literature DB >> 30161259 |
Justice Afrifa1, Wisdom Djange Ogbordjor2, Ruth Duku-Takyi1.
Abstract
BACKGROUND: Mercury can be very toxic to human health even at low dose of exposure. Artisanal small-scale miners (ASGMs) use mercury in gold production, hence are at risk of mercury-induced organ dysfunction. AIM: We determined the association between mercury exposure, thyroid function and work-related factors among artisanal small-scale gold miners in Bibiani- Ghana.Entities:
Mesh:
Substances:
Year: 2018 PMID: 30161259 PMCID: PMC6117084 DOI: 10.1371/journal.pone.0203335
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Socio-demographic characteristics, thyroid function markers and blood mercury concentrations of study participants stratified by mercury levels above occupational threshold.
| Variable | Exposed | Non-Exposed | P-value |
|---|---|---|---|
| 26(22.25–35.75) | 30(24.0–39.0) | 0.0949 | |
| ≤20 | 6(7.5) | 10(17.5) | 0.0005 |
| 21–39 | 59(73.8) | 34(59.7) | |
| 40–59 | 5(6.3) | 13(22.8) | |
| ≥60 | 9(11.3) | 0(0.00) | |
| 0.1054 | |||
| Married | 65(81.3) | 39(68.4) | |
| Single | 15(18.7) | 18(31.6) | |
| 0.0148 | |||
| None | 29(36.25) | 34(59.65) | |
| Primary | 29(36.25) | 7(12.28) | |
| Secondary | 22(27.5) | 16(28.07) | |
| 8.0(7.0–9.0) | 4.0(3.0–4.0) | <0.0001 | |
| ≥5 | 74(92.50) | 8(14.04) | <0.0001 |
| <5 | 6(7.50) | 49(85.96) | |
| T3(nmol/L) | 1.54 ± 0.93 | 2.46 ± 1.47 | <0.0001 |
| T4(ug/dl) | 5.44 ± 1.36 | 9.6 ± 2.87 | <0.0001 |
| TSH(mIU/L) | 1.70 ± 0.54 | 1.67 ± 0.90 | 0.7749 |
| Blood Mercury(ug/L) | 8.0(6.0–9.0) | 1.0(1.0–3.0) | <0.0001 |
Values are presented as frequency (percentages), Mean± SD, Median (IQR)
MMann Whitney U-test;
tstudent sample t-test;
cchi-square test
Fig 1Percentage frequencies of occupational activities among small scale miners stratified by mercury exposure.
GM- Gold amalgamation, SEM- sucking of excess mercury, TM- transport of mercury, SWP- standing in water pool, SM- smelting of gold, EL- Educational level, WD-work duration.
Association of various work-related factors and educational status with mercury exposure.
| Mercury Exposure | ||||
|---|---|---|---|---|
| Variable | Exposed | Non-exposed | Odds Ratio(95%CI) | P-value |
| Yes | 75 | 18 | 32.5(11.23–81.89) | <0.0001 |
| No | 5 | 39 | ||
| Gold smelting | ||||
| Yes | 62 | 16 | 8.83 (3.94–19.08) | <0.0001 |
| No | 18 | 41 | ||
| Mercury transport | ||||
| Yes | 71 | 54 | 0.44(0.12–1.75) | 0.3586 |
| No | 9 | 3 | ||
| Standing in water pool | ||||
| Yes | 75 | 54 | 0.83(0.21–3.36) | >0.9999 |
| No | 5 | 3 | ||
| Sucking of excess mercury | ||||
| Yes | 68 | 18 | 12.28(5.41–26.89) | <0.0001 |
| No | 12 | 39 | ||
| Educational Level | ||||
| None | 29 | 34 | ||
| Primary | 29 | 7 | 0.21(0.08–0.53) | 0.0013 |
| Secondary | 22 | 16 | 0.62(0.28–1.44) | 0.3059 |
| Work Duration | ||||
| ≥5 | 74 | 8 | 75.54(23.09–208.4) | <0.0001 |
| <5 | 6 | 49 | ||
*reference variable
Fig 2Scatter plot and correlation matrix among blood mercury, work duration, T3, T4 and TSH among study participants.
** indicates significant correlation numbers show the correlation coefficient.