Background: It has previously been shown that low back pain (LBP) often presents already in the teenage years and that previous LBP predicts future LBP. It is also well documented that there is a large degree of comorbidity associated with LBP, both in adolescents and adults. The objective of this study is to gain a deeper insight into the etiology of low back pain and to possibly develop a tool for early identification of high-risk groups. This is done by investigating whether different types of morbidity in adolescence are associated with LBP in adulthood.
Methods: Almost 10,000 Danish twins born between 1972 and 1982 were surveyed by means of postal questionnaires in 1994 and again in 2002. The questionnaires dealt with various aspects of general health, including the prevalence of LBP, classified according to number of days affected during the previous year (0, 1-7, 8-30, >30). The predictor variables used in this study were LBP, headache, asthma and atopic disease at baseline; the outcome variable was persistent LBP (>30 days during the past year) at follow-up. Associations between morbidity in 1994 and LBP in 2002 were investigated.
Results: LBP, headache and asthma in adolescence were positively associated with future LBP. There was no association between atopic disease and future LBP. Individuals with persistent LBP at baseline had an odds ratio of 3.5 (2.8-4.5) for future LBP, while the odds ratio for those with persistent LBP, persistent headache and asthma was 4.5 (2.5-8.1). There was a large degree of clustering of these disorders, but atopic disease was not part of this pattern.
Conclusion: Young people from 12 to 22 years of age with persistent LBP during the previous year have an odds ratio of 3.5 persistent LBP eight years later. Both headache and asthma are also positively associated with future LBP and there is a large clustering of LBP, headache and asthma in adolescence.
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http://dx.doi.org/10.1186/1471-2474-7-29 | DOI Listing |
Alzheimers Dement
December 2024
University of Technology and Applied Sciences, Muscat, Muscat, Oman.
Background: Recent breakthroughs in Quantum Calculus (QC) have given new opportunities for texture analysis. Motivated by QC, QELBP examines subtle variations in grayscale within MRI, which may provide early signs of textural changes associated with AD.
Method: 13500 images were extracted from 150 images (90 slices/patient).
Arch Physiother
December 2024
Department of Physiotherapy, Integral University, Lucknow - India.
Introduction: Physiotherapists exhibit different degrees of adherence to clinical guidelines for low back pain (LBP). The preferences and expectations of their patients significantly influence physiotherapists' adherence to these guidelines. Therefore, it is crucial to have a comprehensive analysis of the patients' perspectives, which can identify the factors that prevent the implementation of an active approach.
View Article and Find Full Text PDFJ Clin Med
December 2024
Collegium Medicum, Jan Kochanowski University in Kielce, al. IX Wieków Kielc 19a, 25-516 Kielce, Poland.
Lumbopelvic pain (LBP) is a prevalent condition during pregnancy, affecting a significant proportion of pregnant women. It arises from hormonal, biomechanical, and postural changes, often exacerbating discomfort and impairing quality of life. This study aimed to evaluate the effects of targeted motor control interventions focusing on sternal alignment on spinal alignment, pain, and muscle activity in pregnant women at risk of preterm birth.
View Article and Find Full Text PDFBr J Pain
December 2024
Department of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Background: Chronic pain poses a significant public health challenge. We present the global and regional data on Prevalence, Incidence and Years Lived with Disability (YLDs) for Chronic pain from the Global burden of disease (GBD) study 2019 data and analyze their associations with Socio-demographic index (SDI), age, and gender, and the future trends from 2020 to 2035.
Methods: Regional trends in the burden of chronic pain and its association with age, gender, and SDI were assessed from 1990 to 2019.
Introduction: Low back pain (LBP) is a significant global health burden, with variable treatment outcomes and an unclear underlying molecular mechanism. Effective prediction of treatment responses remains a challenge. In this study, we aimed to develop gene signature-based machine learning models using transcriptomic data from peripheral immune cells to predict treatment outcomes in patients with LBP.
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