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Longitudinal association between mental health and future antibiotic prescriptions in healthy adults: Results from the LOHAS

Tochitani, Kentaro 京都大学 DOI:10.14989/doctor.k24093

2022.05.23

概要

Antimicrobial resistance (AMR) has become a global problem in recent years. Currently, the number of deaths attributed to AMR is approximately 70,000 per year worldwide, and it is predicted to increase to 10 million by 2050 unless measures are taken [1]. To prevent AMR, it is necessary to use antibiotics appropriately and reduce their use. The World Health Organization launched a global action plan to combat antimicrobial-resistant bacteria in 2015, and it asked member countries to approve national action plans within 2 years [2]. In 2016, the government of Japan launched a national action plan, and the goal was to reduce antimicrobial use by 33% by the year 2020 [3].

Reducing antibiotic prescriptions involves understanding associated factors, mainly medical staff factors and patient factors. Medical staff factors include age or sex of the physicians, practice volume, and regional characteristics [4, 5]. Similarly, patient factors may include age, sex, smoking status, socioeconomic status, and comorbidities [6–8]. Regarding factors associated with mental health, psychological stress might be associated with an increased occurrence of infectious diseases [9, 10], but there have been no studies of whether people with lower quality of life (QOL) are likely to be prescribed antibiotics.

This study aimed to analyze the longitudinal associations of mental health and subjective physical functioning of healthy community-dwelling Japanese adults with their future antibiotic prescriptions to clarify the individual characteristics associated with the increase in antibiotic prescriptions.

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参考文献

1. Review on Antimicrobial Resistance. Tackling drug-resistant infections globally: final report and recom- mendations [Internet]. 2016. Available: https://amr-review.org/sites/default/files/160525_Final% 20paper_with%20cover.pdf

2. World Health Organization. Global action plan on antimicrobial resistance [Internet]. 2015. Available: https://apps.who.int/iris/bitstream/handle/10665/193736/9789241509763_eng.pdf

3. Government of Japan. National action plan on antimicrobial resistance (AMR) 2016–2020 [Internet]. 2016. Available: https://www.mhlw.go.jp/file/06-Seisakujouhou-10900000-Kenkoukyoku/0000138942. pdf

4. Fleming-Dutra KE, Bartoces M, Roberts RM, Hicks LA. Characteristics of primary care physicians asso- ciated with high outpatient antibiotic prescribing volume. Open Forum Infect Dis 2018; 5:ofx279. https:// doi.org/10.1093/ofid/ofx279 PMID: 30009196

5. Cadieux G, Tamblyn R, Dauphinee D, Libman M. Predictors of inappropriate antibiotic prescribing among primary care physicians. CMAJ 2007; 177:877–83. https://doi.org/10.1503/cmaj.070151 PMID: 17923655

6. Steinberg MB, Akincigil A, Kim EJ, Shallis R, Delnevo CD. Tobacco smoking as a risk factor for increased antibiotic prescription. Am J Prev Med 2016; 50:692–8. https://doi.org/10.1016/j.amepre. 2015.11.009 PMID: 26702478

7. Brauer R, Ruigomez A, Downey G, et al. Prevalence of antibiotic use: a comparison across various European health care data sources. Pharmacoepidemiol Drug Saf 2016; 25:11–20.

8. Covvey JR, Johnson BF, Elliott V, Malcolm W, Mullen AB. An association between socioeconomic dep- rivation and primary care antibiotic prescribing in Scotland. J Antimicrob Chemother 2014; 69:835–41. https://doi.org/10.1093/jac/dkt439 PMID: 24176983

9. Ojard C, Donnelly JP, Safford MM, Griffin R, Wang HE. Psychosocial stress as a risk factor for sepsis: a population-based cohort study. Psychosom Med 2015; 77:93–100. https://doi.org/10.1097/PSY. 0000000000000120 PMID: 25469683

10. Cohen S, Tyrrell DA, Smith AP. Psychological stress and susceptibility to the common cold. N Engl J Med 1991; 325:606–12. https://doi.org/10.1056/NEJM199108293250903 PMID: 1713648

11. Otani K, Takegami M, Fukumori N, et al. Locomotor dysfunction and risk of cardiovascular disease, quality of life, and medical costs: design of the Locomotive Syndrome and Health Outcome in Aizu Cohort Study (LOHAS) and baseline characteristics of the study population. J Orthop Sci 2012; 17:261–71. https://doi.org/10.1007/s00776-012-0200-5 PMID: 22526710

12. Sundararajan V, Henderson T, Perry C, Muggivan A, Quan H, Ghali WA. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol 2004; 57:1288–94. https:// doi.org/10.1016/j.jclinepi.2004.03.012 PMID: 15617955

13. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43:1130–9. https://doi.org/10.1097/01.mlr.0000182534. 19832.83 PMID: 16224307

14. Ware J Jr, Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and pre- liminary tests of reliability and validity. Med Care 1996; 34:220–33. https://doi.org/10.1097/00005650- 199603000-00003 PMID: 8628042

15. Fukuhara S, Suzukamo Y. Manual of SF-36v2 Japanese version. Kyoto: iHope International Inc.; 2004, 2015.

16. Yamazaki S, Fukuhara S, Green J. Usefulness of five-item and three-item Mental Health Inventories to screen for depressive symptoms in the general population of Japan. Health Qual Life Outcomes 2005; 3:48. https://doi.org/10.1186/1477-7525-3-48 PMID: 16083512

17. WHO Collaborating Centre for Drug Statistics Methodology. ATC/DDD Index 2020 [Internet]. 2020. Available: https://www.whocc.no/atc_ddd_index/

18. Muraki Y, Yagi T, Tsuji Y, et al. Japanese antimicrobial consumption surveillance: First report on oral and parenteral antimicrobial consumption in Japan (2009–2013). J Glob Antimicrob Resist 2016; 7:19–23. https://doi.org/10.1016/j.jgar.2016.07.002 PMID: 27973324

19. Fleming-Dutra KE, Hersh AL, Shapiro DJ, et al. Prevalence of inappropriate antibiotic prescriptions among US ambulatory care visits, 2010–2011. JAMA 2016; 315:1864–73. https://doi.org/10.1001/ jama.2016.4151 PMID: 27139059

20. Hashimoto H, Matsui H, Sasabuchi Y, et al. Antibiotic prescription among outpatients in a prefecture of Japan, 2012–2013: a retrospective claims database study. BMJ Open 2019; 9:e026251. https://doi.org/ 10.1136/bmjopen-2018-026251 PMID: 30948598

21. Rubin DB, Schenker N. Multiple imputation in health-care databases: an overview and some applica- tions. Stat Med 1991; 10:585–98. https://doi.org/10.1002/sim.4780100410 PMID: 2057657

22. Cohen S. Psychological stress and susceptibility to upper respiratory infections. Am J Respir Crit Care Med 1995; 152:S53–8. https://doi.org/10.1164/ajrccm/152.4_Pt_2.S53 PMID: 7551414

23. Cohen S, Doyle WJ, Turner RB, Alper CM, Skoner DP. Emotional style and susceptibility to the com- mon cold. Psychosom Med 2003; 65:652–7. https://doi.org/10.1097/01.psy.0000077508.57784.da PMID: 12883117

24. Kao LT, Liu SP, Lin HC, Lee HC, Tsai MC, Chung SD. Poor clinical outcomes among pneumonia patients with depressive disorder. PloS One 2014; 9:e116436. https://doi.org/10.1371/journal.pone. 0116436 PMID: 25551389

25. Song H, Fall K, Fang F, et al. Stress related disorders and subsequent risk of life threatening infections: population based sibling controlled cohort study. BMJ 2019; 367:l5784. https://doi.org/10.1136/bmj. l5784 PMID: 31645334

26. Jiang T, Farkas DK, Ahern TP, Lash TL, Sorensen HT, Gradus JL. Posttraumatic stress disorder and incident infections: a nationwide cohort study. Epidemiology 2019; 30:911–7. https://doi.org/10.1097/ EDE.0000000000001071 PMID: 31584893

27. Kimura Y, Fukuda H, Hayakawa K, et al. Longitudinal trends of and factors associated with inappropri- ate antibiotic prescribing for non-bacterial acute respiratory tract infection in Japan: a retrospective claims database study, 2012–2017. PloS One 2019; 14:e0223835. https://doi.org/10.1371/journal. pone.0223835 PMID: 31618258

28. Yamasaki D, Tanabe M, Muraki Y, Kato G, Ohmagari N, Yagi T. The first report of Japanese antimicro- bial use measured by national database based on health insurance claims data (2011–2013): compari- son with sales data, and trend analysis stratified by antimicrobial category and age group. Infection 2018; 46:207–14. https://doi.org/10.1007/s15010-017-1097-x PMID: 29273972

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Longitudinal association between mental health and future antibiotic prescriptions in healthy adults: Results from the LOHAS

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Longitudinal association between mental health and future antibiotic prescriptions in healthy adults: Results from the LOHAS

概要

この論文で使われている画像

関連論文

Gender with marital status, cultural differences, and vulnerability to hypertension: Findings from the national survey for noncommunicable disease risk factors and mental health using WHO STEPS in Bhutan

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