Charlson F, van Ommeren M, Flaxman A, Cornett J, Whiteford H, Saxena S. New WHO prevalence estimates of mental disorders in conflict settings: a systematic review and meta-analysis. Lancet. 2019;394(10194):240–8. https://doi.org/10.1016/S0140-6736(19)30934-1

Article  PubMed  Google Scholar 

Davy Vancampfort M, Hallgren F, Schuch B, Stubbs L, Smith S, Rosenbaum, et al. Sedentary behavior and depression among community-dwelling adults aged ≥ 50 years: results from the Irish longitudinal study on ageing. J Affect Disord. 2020;262:389–96. https://doi.org/10.1016/j.jad.2019.11.066

Article  PubMed  Google Scholar 

Megan Teychenne K, Ball J, Salmon. Sedentary behavior and depression among adults: a review. Int J Behav Med. 2010;17(4):246–54. https://doi.org/10.1007/s12529-010-9075-z

Article  PubMed  Google Scholar 

Davy Vancampfort J, Firth FB, Schuch S, Rosenbaum J, Mugisha M, Hallgren, et al. Sedentary behavior and physical activity levels in people with schizophrenia, bipolar disorder and major depressive disorder: a global systematic review and meta-analysis. World Psychiatry. 2017;16(3):308–15. https://doi.org/10.1002/wps.20458

Article  PubMed  PubMed Central  Google Scholar 

Kevin Dang P, Ritvo J, Katz D, Gratzer Y, Knyahnytska A, Ortiz, et al. The role of daily steps in the treatment of major depressive disorder: secondary analysis of a randomized controlled trial of a 6-month internet-based, mindfulness-based cognitive behavioral therapy intervention for youth. Interact J Med Res. 2023;8:12e46419. https://doi.org/10.2196/46419

Article  Google Scholar 

Schuch FB, Vasconcelos-Moreno MP, Borowsky C, Zimmermann AB, Rocha NS, Fleck MP. Exercise and severe major depression: effect on symptom severity and quality of life at discharge in an inpatient cohort. J Psychiatr Res. 2015;61:25–32. https://doi.org/10.1016/j.jpsychires.2014.11.005

Article  CAS  PubMed  Google Scholar 

Loretta Garvey AC, Benson D, Benger T, Short H, Banyard K-L, Edward. The perceptions of mental health clinicians integrating exercise as an adjunct to routine treatment of depression and anxiety. Int J Ment Health Nurs. 2023;32(2):502–12. https://doi.org/10.1111/inm.13089

Article  PubMed  Google Scholar 

Peter J, Carek SE, Laibstain SM, Carek. Exercise for the treatment of depression and anxiety. Int J Psychiatry Med. 2011;41(1):15–28. https://doi.org/10.2190/PM.41.1.c

Widding-Havneraas T, Zachrisson HD. A gentle introduction to instrumental variables. J Clin Epidemiol. 2022;149:203–5. https://doi.org/10.1016/j.jclinepi.2022.06.022

Article  PubMed  Google Scholar 

Chen X, Kong J, Diao X, Cai J, Zheng J, Xie W, et al. Depression and prostate cancer risk: a Mendelian randomization study. Cancer Med. 2020;9(23):9160–7. https://doi.org/10.1002/cam4.3493

Article  CAS  PubMed  PubMed Central  Google Scholar 

Luo J, Xu Z, Noordam R, van Heemst D, Li-Gao R. Depression and inflammatory bowel disease: a bidirectional two-sample Mendelian randomization study. J Crohns Colitis. 2022;16(4):633–42. https://doi.org/10.1093/ecco-jcc/jjab191

Article  PubMed  Google Scholar 

Li GH, Cheung CL, Chung AK, Cheung BM, Wong IC, Fok MLY, et al. Evaluation of bi-directional causal association between depression and cardiovascular diseases: a Mendelian randomization study. Psychol Med. 2022;52(9):1765–76. https://doi.org/10.1017/S0033291720003566

Article  PubMed  Google Scholar 

Ruan X, Chen J, Sun Y, Zhang Y, Zhao J, Wang X, et al. Depression and 24 gastrointestinal diseases: a Mendelian randomization study. Transl Psychiatry. 2023;13(1):146. https://doi.org/10.1038/s41398-023-02459-6

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sekula P, Del GMF, Pattaro C, Köttgen A. Mendelian randomization as an approach to assess causality using observational data. J Am Soc Nephrol. 2016;27(11):3253–65. https://doi.org/10.1681/ASN.2016010098

Article  PubMed  PubMed Central  Google Scholar 

Yordi J, van de Vegte MA, Said M, Rienstra, Pim van der Harst Niek Verweij. Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours. Nat Commun. 2020;11(1):1770. https://doi.org/10.1038/s41467-020-15553-w

Article  CAS  Google Scholar 

Aiden Doherty K, Smith-Byrne T, Ferreira MV, Holmes C, Holmes, et al. GWAS identifes 14 loci for device-measured physical activity and sleep duration. Nat Commun. 2018;9(1):5257. https://doi.org/10.1038/s41467-018-07743-4

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yann C, Klimentidis DA, Raichlen J, Bea DO, Garcia NE, Wineinger LJ, Mandarino, et al. Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifes multiple variants including CADM2 and APOE. Int J Obes (Lond). 2018;42(6):1161–76. https://doi.org/10.1038/s41366-018-0120-3

Article  CAS  Google Scholar 

Bahls M, Leitzmann MF, Karch André, Teumer A, Dörr M, Stephan B, Felix, et al. Physical activity, sedentary behavior and risk of coronary artery disease, myocardial infarction and ischemic stroke: a two-sample Mendelian randomization study. Clin Res Cardiol. 2021;110(10):1564–73. https://doi.org/10.1007/s00392-021-01846-7

Article  CAS  PubMed  PubMed Central  Google Scholar 

Howard DM, Adams MJ, Shirali M, Clarke TK, Marioni RE, Davies G, et al. Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nat Commun. 2018;9(1):1470. https://doi.org/10.1038/s41467-018-03819-3

Article  CAS  PubMed  PubMed Central  Google Scholar 

Vassily Trubetskoy, Antonio F, Pardiñas T, Qi G, Panagiotaropoulou S, Awasthi, Tim B, Bigdeli, et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature. 2022;604(7906):502–8. https://doi.org/10.1038/s41586-022-04434-5

Article  CAS  Google Scholar 

Niamh Mullins AJ, Forstner, Kevin S, O’Connell B, Coombes, Jonathan RI, Coleman Z, Qiao, et al. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat Genet. 2021;53(6):817–29. https://doi.org/10.1038/s41588-021-00857-4

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512–25. https://doi.org/10.1093/ije/dyv080

Article  PubMed  PubMed Central  Google Scholar 

Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40(4):304–14. https://doi.org/10.1002/gepi.21965

Article  PubMed  PubMed Central  Google Scholar 

Zhu Z, Zheng Z, Zhang F, Wu Y, Trzaskowski M, Maier R, et al. Causal associations between risk factors and common diseases inferred from GWAS summary data. Nat Commun. 2018;9(1):224. https://doi.org/10.1038/s41467-017-02317-2

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mandrekar J, Petitti DB. Overlooked shortcomings of observational studies of interventions in coronavirus disease 2019: an illustrated review for the clinician. Open Forum Infect Dis. 2021;8(8):ofab317. https://doi.org/10.1093/ofid/ofab317

Article  CAS  PubMed  PubMed Central  Google Scholar 

Tom G, Richardson E, Sanderson, Tom M, Palmer M, Ala-Korpela, Brian A, Ference GD, Smith, et al. Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: a multivariable Mendelian randomisation analysis. PLoS Med. 2020;17(3):e1003062. https://doi.org/10.1371/journal.pmed.1003062

Article  CAS  Google Scholar 

Morris AP, Voight BF, Teslovich TM, Ferreira T, Segrè AV, Steinthorsdottir V, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44(9):981–90. https://doi.org/10.1038/ng.2383

Article  CAS  PubMed  PubMed Central  Google Scholar 

Manning AK, Hivert MF, Scott RA, Grimsby JL, Bouatia-Naji N, Chen H, et al. A genome-wide approach accounting for body mass index identifes genetic variants infuencing fasting glycemic traits and insulin resistance. Nat Genet. 2012;44(6):659–69. https://doi.org/10.1038/ng.2274

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gortmaker SL, Must A, Sobol AM, Peterson K, Colditz GA, Dietz WH. Television viewing as a cause of increasing obesity among children in the United States, 1986–1990. Arch Pediatr Adolesc Med. 1996;150(4):356–62. https://doi.org/10.1001/archpedi.1996.02170290022003

Article  CAS  PubMed  Google Scholar 

Wilmot EG, Edwardson CL, Achana FA, Davies MJ, Gorely T, Gray LJ, et al. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia. 2012;55(11):2895–905. https://doi.org/10.1007/s00125-012-2677-z

Article  CAS  PubMed  Google Scholar 

Schmid D, Leitzmann MF. Television viewing and time spent sedentary in relation to cancer risk: a meta-analysis. J Natl Cancer Inst. 2014;106(7):dju098. https://doi.org/10.1093/jnci/dju098

Article  PubMed  Google Scholar 

Patterson R, McNamara E, Tainio M, de Sá TH, Smith AD, Sharp SJ, et al. Sedentary behaviour and risk of all-cause, cardiovascular and cancer mortality, and incident type 2 diabetes: a systematic review and dose response meta-analysis. Eur J Epidemiol. 2018;33(9):811–29. https://doi.org/10.1007/s10654-018-0380-1

Article  PubMed  PubMed Central  Google Scholar