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Individualised Preventive Measurements of Suboptimal Health

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All Around Suboptimal Health

Part of the book series: Advances in Predictive, Preventive and Personalised Medicine ((APPPM,volume 18))

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Abstract

This chapter discusses the phases of the disease’s natural history, preventive strategies, and individualised prevention. Suboptimal Health Status (SHS) is defined as an intermediate physical state between health and disease, it is reversible and can predict or prevent non-communicable diseases (NCDs) before the onset of diseases. In preventive medicine, the subjective tool, Suboptimal Health Status Questionnaire-25 (SHSQ-25), which has been developed and validated as a reliable and robust health measurement, has been widely employed to evaluate Suboptimal Health Status (SHS) in five domains: cardiovascular system, digestive system, fatigue, immune system, and mental status. Moreover, immunoglobulin G (IgG) N-glycan patterns are suggested as one of the ideal objective measures for detecting SHS as glycosylation plays a crucial role in the inflammatory processing at the molecular level. Therefore, in order to present a deep understanding of the prevention approaches of SHS, this chapter indicates six case studies for effectively preventing the SHS defined by both subjective and objective measurements.

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Abbreviations

ADCC:

Antibody-dependent cellular cytotoxicity

BMI:

Body mass index

CH2:

Constant heavy 2

E2:

Estradiol

Fc:

Fragment crystallisable

FcyRIIB:

Fc gamma receptor type IIB

FSH:

Follicle-stimulating hormone

GlcNAc:

N-acetylglucosamine

IgG:

Immunoglobulin G

LH:

Luteinising hormone

MBL:

Mannose-binding lectin

NCDs:

Non-communicable chronic diseases

PPPM/3PM:

Predictive, preventive, and personalised medicine

PTM:

Post-translational modification

RCT:

Randomised controlled trial

SHS:

Suboptimal health status

SHSQ-25:

Suboptimal Health Status Questionnaire-25

TNF-α:

Tumour necrosis factor alpha

WHO:

World Health Organization

References

  1. Kisling LA, Das JM (2021) Prevention strategies. In: StatPearls. StatPearls Publishing, Treasure Island, FL

    Google Scholar 

  2. WHO. Health promotion and disease prevention through population-based interventions, including action to address social determinants and health inequity. http://www.emro.who.int/about-who/public-health-functions/health-promotion-disease-prevention.html

  3. Kirch W (2008) Encyclopedia of public health. Springer Science & Business Media

    Book  Google Scholar 

  4. Health AIo, Welfare (2014) Australia’s health 2014. AIHW, Canberra

    Google Scholar 

  5. Zanetti AR, Van Damme P, Shouval D (2008) The global impact of vaccination against hepatitis B: a historical overview. Vaccine 26(49):6266–6273. https://doi.org/10.1016/j.vaccine.2008.09.056

    Article  PubMed  Google Scholar 

  6. Dorland WAN (2012) Dorland’s illustrated medical dictionary, 32nd edn. Saunders/Elsevier, Philadelphia, PA

    Google Scholar 

  7. Nolte E (2008) Disease prevention. In: Heggenhougen HK (ed) International encyclopedia of public health. Academic, Oxford, pp 222–234

    Chapter  Google Scholar 

  8. Greenfield SF (2010) Tertiary prevention. The corsini encyclopedia of psychology, pp 1–2

    Google Scholar 

  9. Quah SR (2016) International encyclopedia of public health. Academic

    Google Scholar 

  10. Boccia S, Ricciardi W, Pastorino R, Adany R, Barnhoorn F, Boffetta P, Cornel MC, De Vito C, Gray M, Jani A, Lang M, Roldan J, Rosso A, Sánchez JM, Van Dujin CM, Van El CG, Villari P, Zawati MH (2019) How to integrate personalized medicine into prevention? recommendations from the personalized prevention of chronic diseases (PRECeDI) consortium. Public Health Genomics 22(5-6):208-214. https://doi.org/10.1159/000504652

  11. Pastorino R, Loreti C, Giovannini S, Ricciardi W, Padua L, Boccia S (2021) Challenges of prevention for a sustainable personalized medicine. J Pers Med 11(4):311. https://doi.org/10.3390/jpm11040311

    Article  PubMed  PubMed Central  Google Scholar 

  12. Davies S (2017) Annual report of the chief medical officer 2016, generation genome

    Google Scholar 

  13. Guo Z, Meng R, Zheng Y, Li X, Zhou Z, Yu L, Tang Q, Zhao Y, Garcia M, Yan Y, Song M, Balmer L, Wen J, Hou H, Tan X, Wang W (2022) Suboptimal health study consortium (SHSC) and the global health epidemiology research group (GHERG). Translation and cross-cultural validation of a precision health tool, the suboptimal health status questionnaire-25, in Korean. J Glob Health 1(12):04077. https://doi.org/10.7189/jogh.12.04077

  14. Wang Y, Ge S, Yan Y, Wang A, Zhao Z, Yu X, Qiu J, Alzain MA, Wang H, Fang H, Gao Q, Song M, Zhang J, Zhou Y, Wang W (2016) China suboptimal health cohort study: rationale, design and baseline characteristics. J Transl Med 14(1):291. https://doi.org/10.1186/s12967-016-1046-y

  15. Wang W (2020) Cardiovascular health in China: low level vs high diversity. Lancet Reg Health West Pac 3. https://doi.org/10.1016/j.lanwpc.2020.100038

  16. Wang H, Tian Q, Zhang J, Liu H, Zhang X, Cao W, Zhang J, Anto EO, Li X, Wang X, Liu D, Zheng Y, Guo Z, Wu L, Song M, Wang Y, Wang W (2020) Population-based case-control study revealed metabolomic biomarkers of suboptimal health status in Chinese population-potential utility for innovative approach by predictive, preventive, and personalized medicine. EPMA J 11(2):147–160. https://doi.org/10.1007/s13167-020-00200-7

  17. Kupaev V, Borisov O, Marutina E, Yan YX, Wang W (2016) Integration of suboptimal health status and endothelial dysfunction as a new aspect for risk evaluation of cardiovascular disease. EPMA J 7(1):19. https://doi.org/10.1186/s13167-016-0068-0

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ge S, Wang Y, Song M, Li X, Yu X, Wang H, Wang J, Zeng Q, Wang W (2018) Type 2 diabetes mellitus: integrative analysis of multiomics data for biomarker discovery. OMICS 22(7):514–523. https://doi.org/10.1089/omi.2018.0053

  19. Boccia S, Ricciardi W (2020) Personalized prevention and population health impact: how can public health professionals be more engaged? Eur J Pub Health 30(3):391–392. https://doi.org/10.1093/eurpub/ckaa018

    Article  Google Scholar 

  20. Yan YX, Liu YQ, Li M, Hu PF, Guo AM, Yang XH, Qiu JJ, Yang SS, Shen J, Zhang LP, Wang W (2009) Development and evaluation of a questionnaire for measuring suboptimal health status in urban Chinese. J Epidemiol 19(6):333–341. https://doi.org/10.2188/jea.je20080086

  21. Penedo FJ, Dahn JR (2005) Exercise and well-being: a review of mental and physical health benefits associated with physical activity. Curr Opin Psychiatry 18(2):189–193. https://doi.org/10.1097/00001504-200503000-00013

  22. Jones BM (2001) Changes in cytokine production in healthy subjects practicing Guolin qigong: a pilot study. BMC Complement Altern Med 1:8. https://doi.org/10.1186/1472-6882-1-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. McCaffrey R, Fowler NL (2003) Qigong practice: a pathway to health and healing. Holist Nurs Pract 17(2):110–116. https://doi.org/10.1097/00004650-200303000-00006

    Article  PubMed  Google Scholar 

  24. Sancier KM (1999) Therapeutic benefits of qigong exercises in combination with drugs. J Altern Complementary Med (New York, NY) 5(4):383–389. https://doi.org/10.1089/acm.1999.5.383

    Article  CAS  Google Scholar 

  25. Liu XY, Gao J, Yin BX, Yang XY, Bai DX (2016) Efficacy of Ba Duan Jin in improving balance: a study in Chinese community-dwelling older adults. J Gerontol Nurs 42(5):38–46. https://doi.org/10.3928/00989134-20160201-03

    Article  CAS  PubMed  Google Scholar 

  26. Liao Y, Lin Y, Zhang C, Xue XL, Mao QX, Zhang Y, Dai JG, Wang TF (2015) Intervention effect of baduanjin exercise on the fatigue state in people with fatigue-predominant subhealth: a cohort study. J Altern Complement Med 21(9):554-562 https://www.liebertpub.com/doi/10.1089/acm.2014.0395

  27. Dalal PK, Agarwal M (2015) Postmenopausal syndrome. Indian J Psychiatry 57(Suppl 2):S222–SS32. https://doi.org/10.4103/0019-5545.161483

    Article  PubMed  PubMed Central  Google Scholar 

  28. Zheng L, Jing Y (2011) Clinical analysis on combined acupuncture and ginger-partitioned moxibustion for perimenopause syndrome. Shanghai J Acu-mox 30(10):673–674

    Google Scholar 

  29. Shen J, Ai B, Shen M (2018) Effectiveness of mild moxibustion for sub-health conditions in pre- and post-menopausal women: a randomized controlled clinical trial. Med Sci Monit 24:2907–2911. https://doi.org/10.12659/msm.909721

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lauche R, Spitzer J, Schwahn B, Ostermann T, Bernardy K, Cramer H, Dobos G, Langhorst J (2016) Efficacy of cupping therapy in patients with the fibromyalgia syndrome-a randomised placebo controlled trial. Sci Rep 6:37316. https://doi.org/10.1038/srep37316

  31. Huber R, Emerich M, Braeunig M (2011) Cupping—is it reproducible? Experiments about factors determining the vacuum. Complement Ther Med 19(2):78–83. https://doi.org/10.1016/j.ctim.2010.12.006

    Article  CAS  PubMed  Google Scholar 

  32. Chi LM, Lin LM, Chen CL, Wang SF, Lai HL, Peng TC (2016) The effectiveness of cupping therapy on relieving chronic neck and shoulder pain: a randomized controlled trial. Evid Based Complement Alternat Med 2016:7358918. https://doi.org/10.1155/2016/7358918

    Article  PubMed  PubMed Central  Google Scholar 

  33. Yang Y, Ma LX, Niu TL, Niu X, Yang XZ, Wang JX, Lu Y, Gao LJ, Chen TY, Zhang YJ, Wu YJ, Song Y (2018) Effects of pulsatile cupping on body pain and quality of life in people with suboptimal health: a randomized controlled exploratory trial. Med Acupuncture 30(6):326–335. https://doi.org/10.1089/acu.2018.1313

  34. Martinić Kavur M, Lauc G, Pezer M (2021) Systems glycobiology: immunoglobulin G Glycans as biomarkers and functional effectors in aging and diseases. Comprehensive Glycoscience (Second Edition), Elsevier 1:439-478. https://doi.org/10.1016/B978-0-12-819475-1.00086-9

  35. Russell A, Adua E, Ugrina I, Laws S, Wang W (2018) Unravelling immunoglobulin G fc N-glycosylation: a dynamic marker potentiating predictive, preventive and personalised medicine. Int J Mol Sci 19(2):390. https://doi.org/10.3390/ijms19020390

  36. Štambuk T, Klasić M, Zoldoš V, Lauc G (2020) N-glycans as functional effectors of genetic and epigenetic disease risk. Mol Asp Med 79:100891. https://doi.org/10.1016/j.mam.2020.100891

    Article  CAS  Google Scholar 

  37. Franceschi C, Garagnani P, Parini P, Giuliani C, Santoro A (2018) Inflammaging: a new immune-metabolic viewpoint for age-related diseases. Nat Rev Endocrinol 14(10):576–590. https://doi.org/10.1038/s41574-018-0059-4

    Article  CAS  PubMed  Google Scholar 

  38. Tijardović M, Marijančević D, Bok D, Kifer D, Lauc G, Gornik O, Keser T (2019) Intense physical exercise induces an antiinflammatory change in IgG N-glycosylation profile. Front Physiol 10:1522. https://doi.org/10.3389/fphys.2019.01522

  39. Jurić J, Kohrt WM, Kifer D, Gavin KM, Pezer M, Nigrovic PA, Lauc G (2020) Effects of estradiol on biological age measured using the glycan age index. Aging 12(19):19756–19765. https://doi.org/10.18632/aging.104060

  40. Shea KL, Gavin KM, Melanson EL, Gibbons E, Stavros A, Wolfe P, Kittelson JM, Vondracek SF, Schwartz RS, Wierman ME, Kohrt WM (2015) Body composition and bone mineral density after ovarian hormone suppression with or without estradiol treatment. Menopause (New York, NY) 22(10):1045–1052. https://doi.org/10.1097/gme.0000000000000430

  41. Nguyen NT, Kim E, Vu S, Phelan M (2018) Ten-year outcomes of a prospective randomized trial of laparoscopic gastric bypass versus laparoscopic gastric banding. Ann Surg 268(1):106–113. https://doi.org/10.1097/sla.0000000000002348

    Article  PubMed  Google Scholar 

  42. Greto VL, Cvetko A, Štambuk T, Dempster NJ, Kifer D, Deriš H, Cindrić A, Vučković F, Falchi M, Gillies RS, Tomlinson JW, Gornik O, Sgromo B, Spector TD, Menni C, Geremia A, Arancibia-Cárcamo CV, Lauc G (2021) Extensive weight loss reduces glycan age by altering IgG N-glycosylation. Int J Obes (Lond) 45(7):1521–1531. https://doi.org/10.1038/s41366-021-00816-3

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Correspondence to Manshu Song .

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Guo, Z., Zheng, Y., Song, M. (2024). Individualised Preventive Measurements of Suboptimal Health. In: Wang, W. (eds) All Around Suboptimal Health . Advances in Predictive, Preventive and Personalised Medicine, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-031-46891-9_11

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