Resumen
Background: Low back pain (LBP) and musculoskeletal disorders are highly prevalent among agricultural workers. However, there is limited epidemiological evidence from rural regions of Ecuador, where working and living conditions may differ substantially from those in other settings. This study aimed to identify predictors of LBP among farmers in rural Ecuador to inform locally relevant prevention strategies. Methods: Participants aged 30 to 60 years (n = 103) were recruited through a traveling health clinic. Participants were assessed with behavioral and sociodemographic self-report questionnaires and anthropometric measurements. Low back pain (LBP) was assessed using the Standardized Nordic Musculoskeletal Questionnaire, which asked about symptoms experienced in the past 12 months. Bivariate (Chi-square and Fisher exact tests) and multivariate (binary logistic regression) analyses were conducted to explore associations between risk factors and LBP in individuals aged 30 to 60 years. Results: LBP was highly prevalent, affecting 78.6% of participants. Behavioral patterns were mixed, with low rates of smoking and moderate alcohol and coffee consumption associated with LBP. A normal body mass index (BMI) was observed in 66% of the sample, and over half reported stable mood and good self-perceived health. In the binary logistic regression analysis, only education level significantly predicted LBP, with secondary education acting as a protective factor. Conclusions: While lower back pain was widespread in the population studied, most risk factors that were analyzed were not significantly associated with its presence.
Idioma original | Español (Ecuador) |
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Páginas (desde-hasta) | 1-15 |
Publicación | International Journal of Environmental Research and Public Health |
Volumen | 22 |
N.º | 885 |
DOI | |
Estado | Publicada - 31 may. 2025 |
Financiación
This study was funded by the Pontificia Universidad Católica del Ecuador. The APC were partially funded by the Vice President for Research at Ohio University.
Palabras clave
- low back pain
- risk factors
- prediction model