The associations between modifiable risk factors and constipation: a comprehensive mendelian randomization study

Autor: Hong Chang, Jing Ouyang, Meng Tian, Jin Yang, Jie Gao, Mengjiao Yang, Meng Zhang, Hao Yuan, Ya Zheng, Yuping Wang, Zhaofeng Chen
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: BMC Gastroenterology, Vol 24, Iss 1, Pp 1-16 (2024)
Druh dokumentu: article
ISSN: 1471-230X
DOI: 10.1186/s12876-024-03384-8
Popis: Abstract Objective Early identification of modifiable risk factors is crucial for the prevention of constipation. This study systematically investigated the relationship between genetically predicted modifiable risk factors and constipation. Methods The inverse variance weighting (IVW) method was employed as the primary analytical approach. For similar exposure indicators, the multivariate Mendelian randomization (MVMR) method was used to adjust for potential biases in univariate MR analysis. The robustness of the results was further evaluated using the MR-Egger intercept test, Cochran’s Q test, and leave-one-out analysis. Bonferroni correction was applied to reduce the false positive rate in the results. Results The IVW analysis indicated a significant causal association between genetically predicted gastroesophageal reflux disease [OR (95% CI) = 1.192 (1.079–1.315), P = 0.0005], atorvastatin use [OR (95% CI) = 16.995 (3.327–86.816), P = 0.0007], and constipation. Additionally, there was a potential causal association between education level [OR (95% CI) = 0.859 (0.767–0.964), P = 0.009], major depressive disorder [OR (95% CI) = 1.206 (1.041–1.399), P = 0.013], hypothyroidism [OR (95% CI) = 2.299 (1.327–3.985), P = 0.003], and aspirin use [OR (95% CI) = 4.872 (1.174–20.221), P = 0.029] with constipation. No causal associations were found for the other included indicators. Sensitivity analysis demonstrated the absence of evidence for heterogeneity and pleiotropy in any positive results. Conclusion This study identified several risk factors that could be targeted for the prevention of constipation, offering valuable insights for public health policies.
Databáze: Directory of Open Access Journals
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