Effect of Extremely Low-Frequency (ELF) Electromagnetic Fields on Musculoskeletal Disorders and Role of Oxidative Stress
Abstract
Effect of Extremely Low-Frequency (ELF) Electromagnetic Fields on Musculoskeletal Disorders and Role of Oxidative Stress Hosseinabadi MB, Khanjani N. The Effect of Extremely Low-Frequency Electromagnetic Fields on the Prevalence of Musculoskeletal Disorders and the Role of Oxidative Stress. Bioelectromagnetics. Published online June 18, 2019. doi.org Abstract Extremely low-frequency electromagnetic fields (ELF-EMFs) may cause negative health effects. This study aimed to investigate the direct and indirect effects of chronic exposure to extremely low-frequency electric and magnetic fields on the prevalence of musculoskeletal disorders (MSDs). In this cross-sectional study, 152 power plant workers were enrolled. The exposure level of employees was measured based on the IEEE Std C95.3.1 standard. Superoxide dismutase (SOD), catalase (Cat), glutathione peroxidase (GPx), total antioxidant capacity (TAC), and malondialdehyde (MDA) (independent variables) were measured in the serum of subjects. The Nordic musculoskeletal questionnaire was used to assess MSDs (dependent variable). The mean exposure of electric and magnetic fields were 4.09 V/m (standard deviation [SD] = 4.08) and 16.27 µT (SD = 22.99), respectively. Increased levels of SOD, Cat, GPx, and MDA had a direct significant relation with MSDs. In the logistic regression model, SOD (odds ratio [OR] = 0.952, P = 0.026), GPx (OR = 0.991, P = 0.048), and MDA (OR = 0.741, P = 0.021) were significant predictors of MSDs. ELF-EMFs were not related to MSDs directly; however, increased levels of oxidative stress may cause MSDs. onlinelibrary.wiley.com
AI evidence extraction
Main findings
In 152 power plant workers, mean electric and magnetic field exposures were 4.09 V/m and 16.27 µT, respectively. ELF-EMF exposure was not directly related to MSDs; however, several oxidative stress/antioxidant biomarkers (SOD, Cat, GPx, MDA) showed significant associations with MSDs, and SOD, GPx, and MDA were significant predictors in logistic regression.
Outcomes measured
- Musculoskeletal disorders (MSDs) prevalence (Nordic musculoskeletal questionnaire)
- Oxidative stress/antioxidant biomarkers in serum (SOD, catalase, GPx, TAC, MDA)
Limitations
- Cross-sectional design (cannot establish temporality/causality)
- Exposure frequency not reported in abstract
- MSDs assessed by questionnaire (self-reported outcome)
Suggested hubs
-
occupational-exposure
(0.9) Study population is power plant workers with measured ELF electric and magnetic field exposure.
View raw extracted JSON
{
"study_type": "cross_sectional",
"exposure": {
"band": "ELF",
"source": "occupational",
"frequency_mhz": null,
"sar_wkg": null,
"duration": "chronic"
},
"population": "Power plant workers",
"sample_size": 152,
"outcomes": [
"Musculoskeletal disorders (MSDs) prevalence (Nordic musculoskeletal questionnaire)",
"Oxidative stress/antioxidant biomarkers in serum (SOD, catalase, GPx, TAC, MDA)"
],
"main_findings": "In 152 power plant workers, mean electric and magnetic field exposures were 4.09 V/m and 16.27 µT, respectively. ELF-EMF exposure was not directly related to MSDs; however, several oxidative stress/antioxidant biomarkers (SOD, Cat, GPx, MDA) showed significant associations with MSDs, and SOD, GPx, and MDA were significant predictors in logistic regression.",
"effect_direction": "mixed",
"limitations": [
"Cross-sectional design (cannot establish temporality/causality)",
"Exposure frequency not reported in abstract",
"MSDs assessed by questionnaire (self-reported outcome)"
],
"evidence_strength": "low",
"confidence": 0.7800000000000000266453525910037569701671600341796875,
"peer_reviewed_likely": "yes",
"keywords": [
"extremely low-frequency",
"ELF-EMF",
"electric field",
"magnetic field",
"power plant workers",
"occupational exposure",
"musculoskeletal disorders",
"oxidative stress",
"SOD",
"catalase",
"glutathione peroxidase",
"TAC",
"MDA",
"Nordic musculoskeletal questionnaire"
],
"suggested_hubs": [
{
"slug": "occupational-exposure",
"weight": 0.90000000000000002220446049250313080847263336181640625,
"reason": "Study population is power plant workers with measured ELF electric and magnetic field exposure."
}
]
}
AI can be wrong. Always verify against the paper.
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