Association between sleep duration, depression and breast cancer in the United States: a national health and nutrition examination survey analysis 2009–2018

References

• Mubarik S, Yu Y, Wang F, et al. Epidemiological and sociodemographic transitions of female breast cancer incidence, death, case fatality and DALYs in 21 world regions and globally, from 1990 to 2017: an age-Period-Cohort analysis. J Adv Res. 2022;37:1–10. Epub 2022/05/03. PubMed PMID: 35499053; PubMed Central PMCID: PMCPMC9039678. doi: 10.1016/j.jare.2021.07.012.
   PubMed Web of Science ®Google Scholar
• Li N, Deng Y, Zhou L, et al. Global burden of breast cancer and attributable risk factors in 195 countries and territories, from 1990 to 2017: results from the global burden of disease study 2017. J Hematol Oncol. 2019;12(1):140. Epub 2019/12/23. PubMed PMID: 31864424; PubMed Central PMCID: PMCPMC6925497. doi: 10.1186/s13045-019-0828-0.
   PubMed Web of Science ®Google Scholar
• Type and timing of menopausal hormone therapy and breast cancer risk: individual participant meta-analysis of the worldwide epidemiological evidence. Lancet. 394(10204):1159–1168. 2019Epub 2019/09/03. doi: 10.1016/s0140-6736(19)31709-x.PubMed PMID: 31474332; PubMed Central PMCID: PMCPMC6891893.
   PubMed Web of Science ®Google Scholar
• Newman LA. Breast cancer screening in low and Middle-income countries. Best Pract Res Clin Obstet Gynaecol. 2022;83:15–23. Epub 2022/05/20. doi: 10.1016/j.bpobgyn.2022.03.018.
   PubMed Web of Science ®Google Scholar
• Hirshkowitz M, Whiton K, Albert SM, et al. National sleep foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health. 2015;1(1):40–43. Epub 2015/03/01. doi: 10.1016/j.sleh.2014.12.010.
   PubMed Web of Science ®Google Scholar
• Wang P, Ren FM, Lin Y, et al. Night-shift work, sleep duration, daytime napping, and breast cancer risk. Sleep Med. 2015;16(4):462–468. Epub 2015/03/22. doi: 10.1016/j.sleep.2014.11.017.
   PubMed Web of Science ®Google Scholar
• Kamdar BB, Tergas AI, Mateen FJ, Bhayani NH, Oh J. Night-shift work and risk of breast cancer: a systematic review and meta-analysis. Breast Cancer Res Treat 2013;138(1):291–301. Epub 2013/02/13. doi: 10.1007/s10549-013-2433-1.
   PubMed Web of Science ®Google Scholar
• Qin Y, Zhou Y, Zhang X, et al. Sleep duration and breast cancer risk: a meta-analysis of observational studies. Int J Cancer. 2014;134(5):1166–1173. doi: 10.1002/ijc.28452.
   PubMed Web of Science ®Google Scholar
• Richmond RC, Anderson EL, Dashti HS, et al. Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study. BMJ. 2019;365:l2327. Epub 2019/06/28 PubMed PMID: 31243001; PubMed Central PMCID: PMCPMC6592406 at http://www.icmje.org/coi_disclosure.pdf. MKR reports receiving research funding from Novo Nordisk, consultancy fees from Novo Nordisk and Roche Diabetes Care, and modest owning of shares in GlaxoSmithKline, outside the submitted work. DAL reports receiving research support from Medtronic and Roche Diagnostics for research outside the submitted work. All other authors declare no support from any organisation for the submitted work, no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work. doi: 10.1136/bmj.l2327.
   PubMed Web of Science ®Google Scholar
• Liu Q, He H, Yang J, et al. Changes in the global burden of depression from 1990 to 2017: findings from the global burden of disease study. J Psychiatr Res. 2020;126:134–140. Epub 2019/08/24. doi: 10.1016/j.jpsychires.2019.08.002.
   PubMed Web of Science ®Google Scholar
• Hong C, Liu Z, Gao L, et al. Global trends and regional differences in the burden of anxiety disorders and major depressive disorder attributed to bullying victimisation in 204 countries and territories, 1999-2019: an analysis of the global burden of disease study. Epidemiol Psychiatr Sci. 2022;31:e85. Epub 2022/11/29. PubMed PMID: 36440549; PubMed Central PMCID: PMCPMC9714217. doi: 10.1017/s2045796022000683.
   PubMed Web of Science ®Google Scholar
• Patel RB, Rao HR, Thakkar DV, et al. Comprehending the potential of metallic, lipid, and polymer-based nanocarriers for treatment and management of depression. Neurochem Int. 2022;153:105259. Epub 2021/12/24. doi: 10.1016/j.neuint.2021.105259.
   PubMed Web of Science ®Google Scholar
• Zhu GL, Xu C, Yang KB, et al. Causal relationship between genetically predicted depression and cancer risk: a two-sample bi-directional mendelian randomization. BMC Cancer. 2022;22(1):353. Epub 2022/04/02 PubMed PMID: 35361153; PubMed Central PMCID: PMCPMC8973550. doi: 10.1186/s12885-022-09457-9.
   PubMed Web of Science ®Google Scholar
• Wang X, Wang N, Zhong L, et al. Prognostic value of depression and anxiety on breast cancer recurrence and mortality: a systematic review and meta-analysis of 282,203 patients. Mol Psychiatry. 2020;25(12):3186–3197. Epub 2020/08/21. PubMed PMID: 32820237; PubMed Central PMCID: PMCPMC7714689. doi: 10.1038/s41380-020-00865-6.
   PubMed Web of Science ®Google Scholar
• Handelman GS, Kok HK, Chandra RV, et al. eDoctor: machine learning and the future of medicine. J Intern Med. 2018;284(6):603–619. Epub 2018/08/14. doi: 10.1111/joim.12822.
   PubMed Web of Science ®Google Scholar
• Li F, Su Y, Lin F, et al. A deep-learning system predicts glaucoma incidence and progression using retinal photographs. J Clin Invest. 2022;132(11) Epub 2022/06/02. PubMed PMID: 35642636; PubMed Central PMCID: PMCPMC9151694. doi: 10.1172/jci157968.
   Web of Science ®Google Scholar
• Xia F, Li Q, Luo X, et al. Association between urinary metals and leukocyte telomere length involving an artificial neural network prediction: findings based on NHANES 1999-2002. Front Public Health. 2022;10:963138. Epub 2022/09/30. PubMed PMID: 36172207; PubMed Central PMCID: PMCPMC9511050. doi: 10.3389/fpubh.2022.963138.
   PubMed Web of Science ®Google Scholar
• Xia F, Li Q, Luo X, et al. Machine learning model for depression based on heavy metals among aging people: a study with national health and nutrition examination survey 2017-2018. Front Public Health. 2022;10:939758. Epub 2022/08/23. PubMed PMID: 35991018; PubMed Central PMCID: PMCPMC9386350. doi: 10.3389/fpubh.2022.939758.
   PubMed Web of Science ®Google Scholar
• Wang K, Xia F, Li Q, et al. The associations of weekend warrior activity patterns with the visceral adiposity index in US adults: repeated cross-sectional study. JMIR Public Health Surveill. 2023;9:e41973. Epub 2023/01/12. PubMed PMID: 36630179; PubMed Central PMCID: PMCPMC9878365. doi: 10.2196/41973.
   PubMedGoogle Scholar
• Xia F, Li Q, Luo X, et al. Identification for heavy metals exposure on osteoarthritis among aging people and machine learning for prediction: a study based on NHANES 2011-2020. Front Public Health. 2022;10:906774. Epub 2022/08/19. PubMed PMID: 35979456; PubMed Central PMCID: PMCPMC9376265. doi: 10.3389/fpubh.2022.906774.
   PubMed Web of Science ®Google Scholar
• Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–613. Epub 2001/09/15. PubMed PMID: 11556941; PubMed Central PMCID: PMCPMC1495268. doi: 10.1046/j.1525-1497.2001.016009606.x.
   PubMed Web of Science ®Google Scholar
• Maske UE, Buttery AK, Beesdo-Baum K, et al. Prevalence and correlates of DSM-IV-TR major depressive disorder, self-reported diagnosed depression and current depressive symptoms among adults in Germany. J Affect Disord. 2016;190:167–177. Epub 2015/11/01. doi: 10.1016/j.jad.2015.10.006.
   PubMed Web of Science ®Google Scholar
• Levis B, Benedetti A, Thombs BD, DEPRESsion Screening Data (DEPRESSD) Collaboration. Accuracy of patient health questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis. BMJ. 2019;365:l1476. Epub 2019/04/11. PubMed PMID: 30967483; PubMed Central PMCID: PMCPMC6454318 at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work other than that described above; no financial relationships with any organizations that might have an interest in the submitted work in the previous three years with the following exceptions: NJ and SP received a grant, outside the submitted work, from the University of Calgary Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer; Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain; JCNC is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD, and Pfizer and has received sponsorships and honorariums for giving lectures and providing consultancy, and her affiliated institution has received research grants from these companies; UH was an advisory board member for Lundbeck and Servier, a consultant for Bayer Pharma, and a speaker for Roche Pharma and Servier and has received personal fees from Janssen, all outside the submitted work; MI has received a grant from Novartis Pharma and personal fees from Meiji, Mochida, Takeda, Novartis, Yoshitomi, Pfizer, Eisai, Otsuka, MSD, Technomics, and Sumitomo Dainippon, all outside of the submitted work; no other relationships or activities that could appear to have influenced the submitted work. doi: 10.1136/bmj.l1476.
   PubMed Web of Science ®Google Scholar
• Pilevarzadeh M, Amirshahi M, Afsargharehbagh R, et al. Global prevalence of depression among breast cancer patients: a systematic review and meta-analysis. Breast Cancer Res Treat. 2019;176(3):519–533. Epub 2019/05/16. doi: 10.1007/s10549-019-05271-3.
   PubMed Web of Science ®Google Scholar
• Carreira H, Williams R, Müller M, et al. Associations between breast cancer survivorship and adverse mental health outcomes: a systematic review. J Natl Cancer Inst. 2018;110(12):1311–1327. Epub 2018/11/08. PubMed PMID: 30403799; PubMed Central PMCID: PMCPMC6292797. doi: 10.1093/jnci/djy177.
   PubMedGoogle Scholar
• Kruk J, Aboul-Enein BH, Bernstein J, et al. Psychological stress and cellular aging in cancer: a meta-analysis. Oxid Med Cell Longev. 2019;2019:1270397–1270323. Epub 2019/12/10. PubMed PMID: 31814865; PubMed Central PMCID: PMCPMC6877941. doi: 10.1155/2019/1270397.
   PubMedGoogle Scholar
• Ye Z, Ganesan K, Wu M, et al. Crosstalk between depression and breast cancer via hepatic epoxide metabolism: a Central comorbidity mechanism. Molecules. 2022;27(21):7269. Epub 2022/11/12. PubMed PMID: 36364213; PubMed Central PMCID: PMCPMC9655600. doi: 10.3390/molecules27217269.
   PubMed Web of Science ®Google Scholar
• Ren Q, Luo F, Ge S, et al. Major depression disorder may causally associate with the increased breast cancer risk: evidence from two-sample mendelian randomization analyses. Cancer Med. 2023;12(2):1984–1996. Epub 2022/07/20. PubMed PMID: 35852181; PubMed Central PMCID: PMCPMC9883582. doi: 10.1002/cam4.5043.
   PubMed Web of Science ®Google Scholar
• Xiao Q, Signorello LB, Brinton LA, et al. Sleep duration and breast cancer risk among black and white women. Sleep Med. 2016;20:25–29. Epub 2016/06/19. PubMed PMID: 27318222; PubMed Central PMCID: PMCPMC4913026. doi: 10.1016/j.sleep.2015.11.010.
   PubMed Web of Science ®Google Scholar
• Qian X, Brinton LA, Schairer C, et al. Sleep duration and breast cancer risk in the breast cancer detection demonstration project follow-up cohort. Br J Cancer. 2015;112(3):567–571. Epub 2014/12/05. PubMed PMID: 25474248; PubMed Central PMCID: PMCPMC4453641. doi: 10.1038/bjc.2014.600.
   PubMed Web of Science ®Google Scholar
• Wong ATY, Heath AK, Tong TYN, et al. Sleep duration and breast cancer incidence: results from the million women study and meta-analysis of published prospective studies. Sleep. 2021;44(2)Epub 2020/09/05. PubMed PMID: 32886784; PubMed Central PMCID: PMCPMC7879408. doi: 10.1093/sleep/zsaa166.
   Web of Science ®Google Scholar
• Blask DE. Melatonin, sleep disturbance and cancer risk. Sleep Med Rev. 2009;13(4):257–264. Epub 2008/12/20. doi: 10.1016/j.smrv.2008.07.007.
   PubMed Web of Science ®Google Scholar
• Jiang X, Xu C. Deep learning and machine learning with grid search to predict later occurrence of breast cancer metastasis using clinical data. J Clin Med. 2022;11(19):5772. Epub 2022/10/15. PubMed PMID: 36233640; PubMed Central PMCID: PMCPMC9570670. doi: 10.3390/jcm11195772.
   PubMed Web of Science ®Google Scholar