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Background Major depressive disorder (MDD) is a highly heterogeneous mental illness and a major public health problem worldwide. A large number of observational studies have demonstrated a clear association between MDD and coronary heart disease (CHD), and some studies have even suggested that the relationship is bidirectional. However, it was unknown whether any causal relationship existed between them and whether causality was bidirectional in such an instance. Thus, we aimed to determine whether there is a bidirectional causal relationship between major depressive disorders and coronary heart disease. Methods Our two-sample Bidirectional Mendelian Randomization Study consisted of two parts: forward MR analysis regarded MDD as exposure and CHD as the outcome, and reverse MR analysis considered CHD as exposure and MDD as the outcome. Summary data on MDD and CHD were obtained from the IEU Open GWAS database. After screening criteria(P < $$5\times {10}^{-8}$$ 5 × 10 - 8 ), 47 MDD-associated SNPs and 39 CHD-associated SNPs were identified. The inverse-variance weighted (IVW) method, ME-Egger regression, and weighted median method were used to estimate causality. In addition, sensitivity methods, including the heterogeneity test, horizontal pleiotropy test, and leave-one-out method, were applied to ensure the robustness of causal estimation. Results Based on the MR-Egger regression intercept test results, there did not appear to be any horizontal pleiotropy in this study (MDD: intercept = -0.0000376, P = 0.9996; CHD: intercept = -0.0002698, P = 0.920). Accordingly, IVW results suggested consistent estimates of causal effect values. The results showed that people with MDD increased the risk of CHD by 14.7% compared with those without MDD (OR = 1.147, 95%CI: 1.045–1.249, P = 0.009). But there was no direct evidence that CHD would increase the risk of MDD(OR = 1.008, 95%CI: 0.985–1.031, P = 0.490). The heterogeneity test and funnel plot showed no heterogeneity in 47 SNPs of MDD (Q = 42.28, $${I}^{2}$$ I 2 =0, P = 0.629), but there was heterogeneity in 39 SNPs of CHD (Q = 62.48, $${I}^{2}$$ I 2 =39.18%, P = 0.007). The leave-one-out method failed to identify instances where a single SNP was either biased toward or dependent on the causation. Conclusion Our study supports a one-way causal relationship between MDD and CHD, but there is no bidirectional causal relationship. MDD increases the risk of CHD, but there is no evidence that CHD increases the risk of MDD. Therefore, the influence of psychological factors should also be considered in the prevention and treatment of CHD. For MDD patients, it is necessary to prevent cardiovascular diseases.

ObjectiveCervical cancer has one of the highest incidence and mortality rates of any malignant tumor of the female reproductive tract, and its longer treatment period will place significant financial strain on patients and their families. Little is known about how health insurance policies influence cervical cancer prognosis, particularly in developing countries. The relationship between cervical cancer specific death and cervical cancer all-cause mortality with public health insurance, self-payment rate, and the combined effect of public health insurance and self-payment rate was investigated in this study.Materials and methodsFrom 2015 to 2019, a prospective longitudinal cohort study on cervical cancer was carried out in Chongqing, China. We chose 4,465 Chongqing University Cancer Hospital patients who had been diagnosed with cervical cancer between 2015 and 2019. The self-payment rate and public health insurance are taken into account in our subgroup analysis. After applying the inclusion and exclusion criteria, we describe the demographic and clinical traits of patients with various insurance plans and self-payment rates using the chi-square test model. The relationship between cervical cancer patients with various types of insurance, the self-payment rate, and treatment modalities is examined using the multivariate logistic regression model. After applying the inclusion and exclusion criteria, we summarize the demographic and clinical traits of patients with various insurance plans and self-payment rates using the chi-square test model. The association between cervical cancer patients with various types of insurance, the self-payment rate, and treatment modalities is examined using the multivariate logistic regression model. The cumulative hazard ratio of all-cause death and cervical cancer-specific mortality for various insurance types and self-payment rates was then calculated using the Cox proportional hazard model and the competitive risk model.ResultsThis study included a total of 3,982 cervical cancer patients. During the follow-up period (median 37.3 months, 95% CI: 36.40–38.20), 774 deaths were recorded, with cervical cancer accounting for 327 of them. Patients who obtained urban employee-based basic medical insurance (UEBMI) had a 37.1% lower risk of all-cause death compared to patients who received urban resident-based basic medical insurance (URBMI) (HRs = 0.629, 95% CI: 0.508–0.779, p = 0.001). Patients with a self-payment rate of more than 60% had a 26.9% lower risk of cervical cancer-specific mortality (HRs = 0.731, 95% CI: 0.561–0.952, p &lt;0.02).ConclusionsThe National Medical Security Administration should attempt to include the more effective self-paid anti-tumor medications into national medical insurance coverage within the restrictions of restricted medical insurance budget. This has the potential to reduce not only the mortality rate of cervical cancer patients, but also their financial burden. High-risk groups, on the other hand, should promote cervical cancer screening awareness, participate actively in the state-led national cancer screening project and enhance public awareness of HPV vaccine. This has the potential to reduce both cervical cancer patient mortality and the financial burden and impact.