ArticlePain research & management2021
Low Back Pain and Associated Factors among Hairdressers in Northern Ethiopia: A Cross-Sectional Study.
Article in Pain research & management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Prevalence of Low Back Pain and Associated Factors Among University Students in Bangladesh: A Cross-Sectional Study.Health science reports · 2026Article
- Low back pain among academic staff at a university in Ethiopia: a cross-sectional study.BMJ open · 2025Article
- The prevalence of occupational-related low back pain among working populations in sub-saharan Africa: a systematic review and meta-analysis.Journal of occupational medicine and toxicology (London, England) · 2024Article
- The Impact of Lower Extremity Fatigue on Lower Quadrant Dysfunction and Health Profile in Hairdressers.La Medicina del lavoro · 2023Article
- The cost of beauty: Perspectives of salon workers in Kisumu City, Kenya.PLOS global public health · 2023Article
- Predictors of Low Back Pain Risk among Rubber Harvesters.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Low back pain is one of the major occupational health problems ranked the highest in terms of years lived with disability, and it has an economic burden on individuals and society in general. Hairdressers are high-risk professionals, but they are usually getting less attention in research and policy actions. The objective of this study is to assess the magnitude and associated factors of low back pain among hairdressers working in female beauty salons of Mekelle, Northern Ethiopia. A cross-sectional study was employed from January up to March 2018. A simple random sampling was applied to select 344 participants. Interviewer-administered, pretested, and structured questionnaire was used. Bivariate and multivariate binary logistic regression analyses were performed using SPSS version 23. A
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