Objective: The aim of the study was to estimate the extent to which the co-occurrence of poor sleep quality and low back pain is due to the same genetic and/or environmental risk factors or due to a causal association.
Methods: Cross-sectional data on sleep quality (Pittsburgh Sleep Quality index) and low back pain were collected in a population-based sample of adult twins (N = 2134) registered with the Murcia Twin Registry. Bivariate analysis and structural equation modeling were used.
Results: The phenotypic correlation between sleep quality and low back pain was 0.23 (95% confidence interval [CI] = 0.17-0.28). The best-fitting bivariate model included additive genetic and unique environmental factors. Genetic factors accounted for 26% (95% CI = 10-40) and 34% (95% CI = 25-43) of the variability of low back pain and sleep quality, respectively. The correlation between the genetic factors underlying each trait was rG of 0.33 (95% CI = 0.03-0.66), and this overlap of genetic factors explained 42.5% of the phenotypic correlation. On the other hand, nonshared environmental factors of each variable were only fairly correlated rE of 0.19 (95% CI = 0.06-0.31), although this overlap explained 57.5% of the phenotypic correlation. In addition, twins in monozygotic pairs with poorer sleep quality presented more often with low back pain than their co-twins (ρ^ = 0.25, p < .0001).
Conclusions: The data are compatible with a causal effect of sleep quality on low back pain (or the reverse effect), because the correlations between the genetic and unique environmental factors for each trait were significant and there was a significant correlation between the monozygotic twins' difference scores. Apart from environmental factors that affect both characteristics, there are many individual-specific events that influence low back pain but differ from those influencing sleep quality.
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http://dx.doi.org/10.1097/PSY.0000000000000548 | DOI Listing |
Res Child Adolesc Psychopathol
January 2025
Nutrition and Mental Health Research Group (NUTRISAM), Universitat Rovira I Virgili (URV), Carretera de Valls, S/N, 43007, Tarragona, Spain.
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View Article and Find Full Text PDFWomens Health (Lond)
January 2025
Faculty of Health Sciences, Department of Physiotherapy, University of Granada, Granada, Spain.
Background: After breast cancer (BC), women may face other severe symptoms such as sleep problems. The use of simple, fast, and reliable scales is necessary in the clinic to improve patient benefits, and sleep is an important aspect to be addressed.
Objective: This study was conducted to adapt and validate the Spanish version of the satisfaction, alertness, timing, efficiency, and duration (SATED) scale for measuring sleep health in women who have completed treatment for BC in Spain (SATED-BC).
Sensors (Basel)
December 2024
GIKAFIT Research Group, University of the Basque Country (UPV/EHU), 01007 Vitoria-Gasteiz, Spain.
The main aim of the present study was to uncover multivariate relationships between sleep quantity and quality using principal component analysis (PCA) in professional female soccer players. A second aim was to examine the extent to which objective sleep quantity and quality variables can discriminate between perceived sleep. Ten objective sleep variables from the multisensory sleep-tracker were analyzed.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, CreativeLab Research Community, 5000-801 Vila Real, Portugal.
Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented insights and tools that enhance training, performance, and health management. This work examines how AI is advancing the role of sports scientists, particularly in team sports environments, by improving training load management, sports performance, and player well-being. It explores key dimensions such as load optimization, injury prevention and return-to-play, sports performance, talent identification and scouting, off-training behavior, sleep quality, and menstrual cycle management.
View Article and Find Full Text PDFSensors (Basel)
December 2024
College of Material Science and Technology, Beijing Forestry University, Beijing 100083, China.
Mattress firmness is a critical factor influencing sleep quality. This study investigates the effects of time, mattress firmness, and anthropometric parameters on surface electromyographic (sEMG) activity during supine rest. Eleven participants were analyzed, and the values for lower back sEMG on three mattresses were measured as 8.
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