Insomnia and fracture risk
After excluding participants with missing data on the main covariates at baseline (n = 25,661), 14,005 out of the 417,853 participants (3.35%) developed an incident fracture during a median of 7.96 years of follow-up (Supplementary Table 6). In primary analysis (model 0), an association was observed between insomnia and incident fracture, with a 7.0% higher risk (hazard ratio [HR]: 1.070, 95% confidence interval [95% CI]: 1.045-1.096, P = 1.87×10-8) (Figure 1). Further adjustments for BMD (model 1) and falls (model 2) attenuated the estimated hazard ratios for the association between insomnia and the incidence of fracture (HR: 1.066, 95% CI: 1.040-1.091, P = 1.90×10-7 for model 1; HR: 1.044, 95% CI: 1.019-1.069, P = 4.19×10-4 for model 2) (Figure 1). Based on the fully adjusted model (model 3), insomnia was associated with incident fracture, with a 4.0 % higher risk (HR: 1.040, 95% CI: 1.015-1.065, P = 0.001) (Figure 1). In addition, we conducted a series of analyses to assess the mediating role of several covariates (i.e., BMD and falls) on the observed associations. Results from the mediation analysis showed that 26.0% and 10.0% of the intermediary effect of insomnia on the risk of fracture was mediated by falls and BMD, respectively (Supplementary Table 7 and Supplementary Table 8). These results suggested the mediating effect of falls was larger than BMD in the pathway between insomnia and fracture risk. Findings stratified by sex were consistent with the pooled results in model 0 (HR: 1.092, 95% CI: 1.052-1.135, P = 4.79×10-6 for male; HR: 1.052, 95% CI: 1.020-1.084, P =3.42×10-5 for female) (Figure 1). Besides, the PAR% for fracture was estimated as 13.4%, suggesting that 13.4% of the fracture cases could be removed if insomnia as a risk factor was removed.
In two-sample MR, genetically predicted insomnia was associated with increased risk of fracture (OR: 1.059, 95% CI: 1.028-1.090, P = 8.97×10-5) with the IVW approach. In the weighted median method, the magnitude of the causal association estimate was similar (Figure 1). MR-Egger regression showed no evidence of directional pleiotropy (P for intercept = 0.711). After excluding one outlier, the causal association estimate was consistently using the MR-PRESSO test (OR: 1.056, 95% CI: 1.027-1.086, P = 1.94×10-4) (Figure 1). The causality between insomnia and the incident fracture was replicated by one-sample MR analysis (HR: 1.077, 95% CI: 1.019-1.138, P = 0.008) (Figure 1). Although evidence from two-sample MR analyses did not support the association between genetically predicted insomnia and BMD (OR: 1.015, 95% CI: 0.995-1.035, P = 0.146), there was a causal relationship between insomnia and risk of falls (OR: 1.014, 95% CI: 1.006-1.022, P = 0.001), and to some degree supported the hypothesis that the mediating effect of falls was larger than BMD.
Sleep duration and fracture risk
In this prospective study, there was evidence of a U-shape association between sleep duration and fracture risk in model 0 (P < 0.001 for non-linearity), with the lowest risk of fracture at 7-8 hours per day of sleep duration (Figure 2 and Supplementary Figure 2). Compared to those who slept 7 or 8 hours per night, participants who were short (less than 7 hours of sleep) and long sleepers (more than 8 hours of sleep) had increased risk of fracture in model 0 (HR: 1.171, 95% CI: 1.127 to 1.217, P = 1.19×10-15; HR: 1.129, 95% CI:1.062-1.199, P = 1.01×10-4, respectively) (Table 1). We found that the effect of short or long sleep duration on fracture risk was attenuated by additionally adjusting for BMD and falls (model 1, model 2, and model 3) (Table 1). Falls and BMD were estimated to mediate 20.2% and 12.9% of the effect of sleep duration on fracture in observational analyses (Supplementary Table 9 and Supplementary Table 10). The results were consistent in the stratified analysis by sex (Supplementary Table 11). Interestingly, compared to participants who slept 7-8 hours per night, short and long sleep duration were estimated to explain a similar percentage (4.48%) of the population risk of developing a fracture.
In the two-sample MR, we found that genetically determined increased sleep duration was inversely associated with fracture risk (OR: 0.997, 95% CI: 0.995-0.999, P = 0.004) (Table 1). After excluding one outlier, similar findings were observed in MR-PRESSO test (OR: 0.997, 95% CI: 0.995-0.999, P = 0.009) (Table 1). The evidence from the MR-Egger regression also did not support the presence of directional pleiotropy (P = 0.229 for intercept). Furthermore, findings from two-sample MR, which genetically predicted sleep duration was associated with a decreased risk of falls (OR: 0.999, 95% CI: 0.999-0.999, P < 0.001), but not with BMD (OR: 1.000, 95% CI: 0.998-1.002, P = 0.624).
Snoring, excessive daytime sleepiness, chronotype, and fracture risk
In the observational study (model 0), we found that snoring was associated with a decreased risk of fracture (HR: 0.947, 95% CI: 0.912-0.984, P = 0.005) (Supplementary Table 12). However, while digging into our data, we were aware that participants with snoring were less likely to have insomnia and unnormal sleep duration (Supplementary Table 13). Then, we conducted sensitivity analyses stratified by insomnia symptoms and sleep duration and found that in the participants free of insomnia and with normal sleep duration, and found that the association between snoring and fracture risk was not statistically significant (HR: 0.953, 95% CI: 0.868-1.045, P = 0.305) (Supplementary Table 12). Similarly, evidence from one-sample MR and two-sample MR did not support this association (OR: 1.214, 95% CI: 0.770-1.913, P = 0.402 for two-sample MR; HR: 1.765, 95% CI: 0.794-3.921, P = 0.163 for one-sample MR) (Supplementary Table 12). These results suggested that since participants with snoring were more likely in the low-risk group for other sleep factors (i.e., never/rarely had insomnia and had normal sleep duration), the observational estimates may not reflect the causal effects of snoring on fracture risk.
In multivariable Cox regression (model 0), we found statistically significant associations of daytime sleepiness with the risk of fracture (HR: 1.086, 95% CI: 1.052-1.122, P = 5.70×10-7), and being morning preference was a protective factor for fracture risk (HR: 0.963, 95% CI: 0.945-0.982, P = 1.13×10-4) (Supplementary Table 14). However, in the two-sample MR, there was no evidence of the association of chronotype (OR: 0.986, 95% CI: 0.954-1.020, P = 0.425), which was consistent with results from the one-sample MR (HR: 0.983, 95% CI: 0.921-1.048, P = 0.595) (Supplementary Table 14).
The sleep risk score and fracture risk
Finally, we included four potential fracture-related sleep factors (i.e., insomnia, sleep duration, chronotype, and daytime sleepiness) to develop a sleep risk score (SRS). Each participant received a score of 1 for each of the following sleep behaviors: insomnia (“sometimes” or “usually”), abnormal sleep duration (less than 7 hours per day or more than 8 hours per day), late chronotype (“evening” or “evening than morning”), and frequent daytime sleepiness (“often” or “all the time”) (Table 2). All these component scores were summed to generate an SRS, ranging from 0 to 4. The higher scores indicated poor sleep quality.
By generating the sleep risk score, we assessed the joint effect of sleep behaviors on fracture risk and found that the risk of fracture increased significantly with an increasing SRS (i.e., poor sleep quality) (HR: 1.095, 95% CI: 1.073-1.118, P < 2×10-16) (Figure 3). When stratified by sex, the effect estimates of the association between sleep risk score and fracture risk in men were slightly larger than in women (HR: 1.107, 95% CI: 1.071-1.144, P = 1.74×10-9 for male; HR: 1.080, 95% CI: 1.052-1.109, P = 8.77×10-9 for female) (Figure 3). Besides, the PAR% for fracture was estimated as 19.4%, suggesting that 19.4% of incident fracture cases in this study would be removed if all participants had been in healthy sleep behaviors.
Based on the baseline characteristics, participants with healthy sleep quality (i.e., lower sleep risk score) have a decreased risk of falls and higher BMD (Table 2). Therefore, to obtain a deeper understanding of the potential mechanisms for the observation, we further included BMD and falls as mediators in the adjusted model. We found that the magnitude of the associations of SRS with fracture risk was attenuated, with wider confidence intervals (HR: 1.058, 95% CI: 1.036-1.080, P = 1.07×10-7 for model 3) (Figure 3). the mediation analyses showed that 19.0% and 11.6% of the intermediary effect of SRS on the risk of fracture was mediated by falls and BMD (Supplementary Table 15 and Supplementary Table 16).