The influence of chronotype on pain: a systematic review and meta-analysis
Abstract
Abstract: Sleep and circadian rhythms play critical roles in pain regulation, yet the influence of chronotype remains underexplored. This systematic review and meta-analysis synthesized evidence across 43 studies (cross-sectional, cohort, and Mendelian randomization designs) investigating associations between chronotype and pain outcomes. Participants ranged from small clinical cohorts to large-scale biobanks and represented diverse pain conditions, including fibromyalgia, temporomandibular disorders, migraine, musculoskeletal pain, and rheumatoid arthritis. Qualitative synthesis indicated that evening chronotypes were more frequently associated with adverse pain outcomes, including higher pain prevalence, greater intensity, and increased interference. These associations were particularly consistent in musculoskeletal pain and headache disorders, although some studies reported worse outcomes in morning types or bimodal chronotypes. A meta-analysis of 10 studies revealed that evening chronotypes had significantly higher odds of reporting chronic pain than non-evening types (odds ratios = 1.67, 95% confidence intervals: 1.40-1.99). In contrast, pooled results for pain intensity across 6 studies showed only a nonsignificant trend toward greater pain in evening chronotypes, with substantial heterogeneity and sensitivity to influential studies. Certainty of evidence was graded as moderate for pain prevalence and low for pain intensity. Findings support chronotype as a relevant…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.