BackgroundEpidemiological evidence suggests an association between rheumatoid arthritis (RA) and myocardial infarction (MI). However, causality remains uncertain. Therefore, this study aimed to explore the causal association between RA and MI.MethodsUsing publicly available genome-wide association study summary datasets, bidirectional two-sample Mendelian randomization (TSMR) was performed using inverse-variance weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode methods.ResultsThe MR results for the causal effect of RA on MI (IVW, odds ratio [OR] = 1.041, 95% confidence interval [CI]: 1.007–1.076, P = 0.017; weighted median, OR = 1.027, 95% CI: 1.006–1.049, P = 0.012) supported a causal association between genetic susceptibility to RA and an increased risk of MI. MR results for the causal effect of MI on RA (IVW, OR = 1.012, 95% CI: 0.807–1.268, P = 0.921; weighted median, OR = 1.069, 95% CI: 0.855–1.338, P = 0.556) indicated that there was no causal association between genetic susceptibility to MI and an increased risk of RA.ConclusionBidirectional TSMR analysis supports a causal association between genetic susceptibility to RA and an increased risk of MI but does not support a causal association between genetic susceptibility to MI and an increased risk of RA.

BackgroundThe COVID pandemic has brought tremendous negative effects on the mental health of health care workers, such as anxiety, depression, and sleep disorders. We conducted this study to evaluate the sleep-related cognition of Chinese health care workers (HCWs) during the first wave of COVID-19 pandemic and analyze its association with sleep quality, so as to provide scientific reference for improving sleep of HCWs.Patients and methodsA total of 404 HCWs from Yijishan Hospital of Wuhu City, China were enrolled in the study, selected by randomized cluster sampling in May 2020. We made a questionnaire to collect the general demographic information of the participants. The Pittsburgh Sleep Quality Index (PSQI) and a brief version of Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16) were used to measure sleep quality and sleep-related cognition, respectively.ResultsThe results showed that 312 HCWs (77.2%) had false beliefs and attitudes about sleep, while only 92 HCWs (22.8%) had correct beliefs about sleep. In addition, we found that those HCWs who were older, married, with a bachelor’s degree or higher, nurses, more daily working hours (> 8 h) and monthly night shifts (≥ 5 times), had higher DBAS-16 scores (all p < 0.05). However, we did not find significant differences between men and women in DBAS-16 scores. According to the definition of PSQI, a total of 1/4 of the HCWs are poor sleepers and their DBAS-16 score was higher than good sleepers (t = 7.622, p < 0.001). In the end, we confirmed a positive correlation between sleep cognition and sleep quality (r = 0.392, p < 0.01).ConclusionOur study revealed false beliefs and attitudes about sleep were prevalent among HCWs during the first wave of COVID-19 pandemic, and these false beliefs about sleep were closely correlated to sleep quality. We recommend fighting against these false beliefs about sleep.

Objective To analyze the trend of stroke incidence in Chinese and Indian residents from 1990 to 2019, to discuss the effects of age, period, and birth cohort factors on the incidence of stroke in China and India, respectively, and to predict the future incidence trends to provide scientific reference for stroke prevention and control measures in China and India. Methods We downloaded the stroke incidence data of China and India residents from the GBD2019 database from 1990 to 2019 and fitted the trend of stroke incidence data of China city residents by using the Joinpoint regression model to calculate the annual percentage change (APC) and the average annual percentage change (AAPC). In addition, the effects of age, period, and birth cohort on the incidence of stroke were investigated by building an age-period-cohort model. Bayesian age-period-cohort models were used to predict stroke incidence by 2042. Results The overall trend in stroke incidence from 1990 to 2019 was downward in both China and India. Age-standardized incidence rates in China and India decreased from 221.51/100,000 and 121.35/100,000 in 1990 to 200.84/100,000 and 110.7/100,000 in 2019, respectively. Joinpoint regression models showed that stroke incidence in China declined by an average of 0.35% per year (AAPC = − 0.35%, P < 0.001), with the fastest decline occurring from 2005 to 2010 (AAPC = − 2.18%, P < 0.001), and that stroke incidence in India declined by an average of 0.32% per year (AAPC = − 0.32%, P < 0.001), with the fastest decline occurring from 1995 to 2000 (APC = − 1.57%, P < 0.001). Age-period-cohort models showed that the relative risk (RR) of stroke increased with age and period in both countries but decreased with birth cohort. Projections indicate a decreasing trend in the incidence of stroke in the Chinese population by 2042. The ASIR for men and women decreases to 186.87/100,000 and 161.97/100,000, respectively, while the incidence of stroke in the Indian population shows an upward trend, increasing to 133.85/100,000 and 209.16/100,000 for men and women, respectively. Conclusion The age-standardized incidence of stroke in both China and India showed a decreasing trend from 1990 to 2019. In both countries, the risk of stroke increased with increasing age and period and decreased with birth cohort. Increasing age is a key factor influencing stroke incidence in both countries, and stroke remains a major public health problem in both countries, especially because they are the two most populous countries in the world.