Introduction Knee pain is a highly prevalent condition in the general population and is more common than knee osteoarthritis. Population-based evidence linking metabolic dysfunction to knee pain remains limited, and data on sex-specific effects are scarce. Therefore, we examined sex-specific associations between metabolic dysregulation and knee pain in a population-based cohort. Method We analyzed data from a population-based cohort of 1,512 adults (mean age 37.2 years at baseline), of whom 250 completed follow-up after a mean of 9.4 years. Metabolic dysfunction was assessed using a continuous MetS severity score (cMetS) derived from waist circumference, triglycerides, HDL cholesterol, fasting glucose, and systolic blood pressure. Knee pain at follow-up was defined using a combined measure based on a standardized question and a body manikin. Logistic regression models were used to examine associations between baseline cMetS and knee pain, including interaction analyses by sex. Results At follow-up, 28.5% of participants reported knee pain. Higher baseline cMetS was associated with increased odds of knee pain in males (odds ratio [OR] 1.41, 95% confidence interval [CI] 1.17-1.69) but not in females (OR 0.94, 95% CI 0.84-1.07), with evidence of interaction by sex (interaction P < 0.001). Findings were consistent across sensitivity analyses. Conclusions These results indicate that metabolic dysfunction is associated with knee pain in males but not in females, suggesting sex-specific mechanisms linking metabolic dysfunction and knee pain.
Wavelet analysis of human recombination rates demonstrates divergence on fine scales
Background: Recombination rates can be estimated across the genome, underpinning genetic analyses such as identification of regions under selection. Accurate recombination mapping requires observing a

