The Causal Association Between Blood Lead and Sleep Disorders: Evidence from National Health and Nutrition Examination Survey and Mendelian Randomization Analysis

Abstract

Background Poor sleep quality is a global public health concern. This study aimed to identify the risk factors for sleep disorders and clarify their causal effects. Methods Data were obtained from the National Health and Nutrition Examination Survey (NHANES) and Mendelian randomization (MR)-Base databases. Baseline characteristics of individuals with and without sleep disorders were compared. A multivariate logistic regression analysis was performed to calculate the effects of each variable on sleep disorders. Causal effects of blood lead levels and hypertension on sleep disorders were assessed using MR analysis. Results In total, 3660 individuals were enrolled in the study. The prevalence of self-reported sleep disorders was 26.21%. Serum lead level, serum mercury level, serum retinol level, prevalence of hypertension, and daily vigorous work duration were significantly higher for those in the sleep disorders group than the control group. After adjusting for various covariates, the effects of serum lead and hypertension on sleep disorders were stable from logistic regression models 1–4. MR analysis showed that blood lead levels were causally related to the risk of sleep disorders (odds ratio (OR) = 1.09, 95% confidence interval (CI) 1.01–1.17, P = 0.030). There was no causal link between elevated blood pressure and sleep disorders (OR = 0.99, 95% CI 0.94–1.04, P = 0.757). Goodness-of-fit tests and sensitivity analyses were used to verify the reliability of the results. Conclusions Blood lead is positively and causally associated with an increased risk of sleep disorders. These findings provide a novel perspective regarding sleep protection. Taking effective measures to reduce lead exposure may significantly improve sleep health.

Genetic Association between Lipid-Regulating Drug Targets and Diabetic Retinopathy: A Drug Target Mendelian Randomization Study

“…The odds ratio (OR) and 95% confidence interval (CI) values were calculated. Sensitivity analyses including heterogeneity test, horizontal pleiotropy test, and leave-one-out method have been described in detail in our previous study [ 33 , 34 ]. All analyses were performed using the TwoSampleMR R package (version 0.5.7).…”