(1) Background: We aimed to analyze rheumatic heart disease (RHD) mortality trends in China’s urban and rural areas and to determine the roles of age, period, and cohort effects. (2) Methods: Based on mortality data extracted from the China Health Statistics Yearbook, we calculated the crude mortality rate of RHD. Age–adjusted rates were computed by the direct method using the 2020 census as the standard population. The annual percentage change (APC) and average annual percentage change (AAPC) were determined by the JoinPoint regression model. The age–period–cohort model was used to estimate the effects of age, period, and cohort. (3) Results: From 2006 to 2020, the general trend in RHD standardized mortality declined. The RHD mortality rate was higher in rural than in urban areas and among females than males. The elderly (over 60 years old) were at high risk for RHD deaths in China. The age effect increased with age, and the cohort effect showed a declining trend as chronology grew, but the period effect was not significant. (4) Conclusions: China has achieved great success in RHD, but RHD mortality may increase with age. Compared with the period effect, age and cohort effects dominated the risk of RHD deaths.

Background Positive associations between the risk of schizophrenia and the level of white blood cells (WBC) count have been suggested by observational studies. However, the causality of this association is still unclear. Methods We used a group of bidirectional two-sample Mendelian randomization (MR) analyses to estimate the causal relationship between schizophrenia and WBC count traits (i.e., WBC count, lymphocyte count, neutrophil count, basophil count, eosinophil count, and monocyte count). The threshold of FDR-adjusted P < 0.05 was considered as showing potential evidence of a causal effect. Instrument variables were included based on the genome-wide significance threshold (P < 5 × 10− 8) and linkage disequilibrium (LD) clumping (r2 < 0.01). In total, 81, 95, 85, 87, 76, and 83 schizophrenia-related single nucleotide polymorphisms (SNPs) were used as genetic instruments from Psychiatric Genomics Consortium for six WBC count traits, respectively. And in reverse MR analysis, 458, 206, 408, 468, 473, and 390 variants extracted from six WBC count traits were utilized as genetic instruments, which were obtained from a recent large-scale Genome-Wide Association Study (GWAS). Results Genetically predicted schizophrenia was positively associated with the level of WBC count [odds ratio (OR) 1.017, 95% confidence interval (CI) 1.008–1.026; P = 7.53 × 10− 4], basophil count (OR 1.014, 95%CI 1.005–1.022; P = 0.002), eosinophil count (OR 1.021, 95%CI 1.011–1.031; P = 2.77 × 10− 4), monocyte count (OR 1.018, 95%CI 1.009–1.027; P = 4.60 × 10− 4), lymphocyte count (OR 1.021, 95%CI 1.012–1.030; P = 4.51 × 10− 5), and neutrophil count (OR 1.013, 95%CI 1.005–1.022; P = 0.004). WBC count traits are not associated with the risk of schizophrenia in our reverse MR results. Conclusion Schizophrenia is associated with elevated levels of WBC count (i.e., higher WBC count, lymphocyte count, neutrophil count, basophil count, eosinophil count, and monocyte count).

Background. Positive associations between the risk of schizophrenia and white blood cells (WBC) counts, have been suggested by observational studies. However, the causality of this association is still unclear. Methods. We used a group of bidirectional two-sample Mendelian randomization (MR) analyses to estimate the causal relationship between schizophrenia and WBC count traits (i.e., WBC count, lymphocyte count, neutrophil count, basophil count, eosinophil count, and monocyte count). In total, 81, 95, 85, 87, 76, 83 schizophrenia-related single nucleotide polymorphisms (SNPs) were used as genetic instruments from Psychiatric Genomics Consortium for six WBC count traits, respectively. And in reverse MR analysis, 458, 206, 408, 468, 473, 390 variants extracted from six WBC count traits were utilized as genetic instruments, which were obtained from a recent large-scale Genome-Wide Association Study (GWAS). Results. Genetically predicted schizophrenia was positively associated with the risk of WBC count [odds ratio (OR) 1.017, 95% confidence interval (CI) 1.008–1.026; P = 7.53×10− 4], basophil count (OR 1.014, 95%CI 1.005–1.022; P = 0.002), eosinophil count (OR 1.021, 95%CI 1.011–1.031; P = 2.77×10− 4), monocyte count(OR 1.018, 95%CI 1.009–1.027; P = 4.60×10− 4), lymphocyte count(OR 1.021, 95%CI 1.012–1.030; P = 4.51×10− 5), and neutrophil count (OR 1.013, 95%CI 1.005–1.022; P = 0.004). WBC count traits are not associated with the risk of schizophrenia in our reverse MR results. Conclusion. Schizophrenia is associated with increased risk of WBC count (i.e., high WBC count, lymphocyte count, neutrophil count, basophil count, eosinophil count, and monocyte count).

Background: The aim of this study was to analyze rheumatic heart disease (RHD) mortality trends in China’s urban and rural areas and to determine the roles of age, period, and cohort effects. Methods: Based on mortality data extracted from the Chinese Health Statistics Yearbook, we calculated the crude mortality rate of RHD in China. Age-adjusted rates were computed by the direct method using the 2020 census as the standard population. The annual percentage change (APC) and average annual percentage change (AAPC) were determined by the JoinPoint regression model. The age-period-cohort model and the intrinsic estimator (IE) algorithm were used to estimate the effects of age, period, and cohort. Results: From 2006 to 2020, the general trend in RHD standardized mortality declined. The RHD mortality rate was higher in rural than in urban areas and among females than males. JoinPoint regression showed that the elderly (over 60 years old) were at high risk for RHD deaths in China. The age effect increased with age, and the cohort effect showed an overall declining trend as chronology grew, but the period effect was not significant. Conclusions: China has achieved great success in RHD, but RHD mortality may increase with age. We should focus on publicity and education about RHD among the elderly. Compared with the period effect, age and cohort effects dominated the risk of RHD deaths.