{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T18:09:09Z","timestamp":1774980549754,"version":"3.50.1"},"reference-count":58,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Psychosom Med"],"published-print":{"date-parts":[[2018,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n          <jats:sec>\n            <jats:title>Objective<\/jats:title>\n            <jats:p>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.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>Cross-sectional data on sleep quality (Pittsburgh Sleep Quality index) and low back pain were collected in a population-based sample of adult twins (<jats:italic toggle=\"yes\">N<\/jats:italic> = 2134) registered with the Murcia Twin Registry. Bivariate analysis and structural equation modeling were used.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>The phenotypic correlation between sleep quality and low back pain was 0.23 (95% confidence interval [CI] = 0.17\u20130.28). The best-fitting bivariate model included additive genetic and unique environmental factors. Genetic factors accounted for 26% (95% CI = 10\u201340) and 34% (95% CI = 25\u201343) of the variability of low back pain and sleep quality, respectively. The correlation between the genetic factors underlying each trait was <jats:italic toggle=\"yes\">r<\/jats:italic>\n                                 <jats:sub>G<\/jats:sub> of 0.33 (95% CI = 0.03\u20130.66), 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 <jats:italic toggle=\"yes\">r<\/jats:italic>\n                                 <jats:sub>E<\/jats:sub> of 0.19 (95% CI = 0.06\u20130.31), 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 (\u03c1\u02c6 = 0.25, <jats:italic toggle=\"yes\">p<\/jats:italic> &lt; .0001).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>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.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1097\/psy.0000000000000548","type":"journal-article","created":{"date-parts":[[2017,12,14]],"date-time":"2017-12-14T14:09:54Z","timestamp":1513260594000},"page":"263-270","source":"Crossref","is-referenced-by-count":24,"title":["Genetic and Environmental Contributions to Sleep Quality and Low Back Pain: A Population-Based Twin Study"],"prefix":"10.1097","volume":"80","author":[{"given":"Marina B.","family":"Pinheiro","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose J.","family":"Morosoli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manuela 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