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Why Lifestyle Medicine?

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Lifestyle Medicine

Abstract

The question ‘Why Lifestyle Medicine?’ is answered by discussing the concept of chronic diseases and their increased prevalence rates that are resistant to current care models. The great burden of this problem is described and the need for a new chronic disease care model is proposed. Epidemiological dimensions as well as issues with health messaging and campaigns that are scalable to address this problem are presented. A new lifestyle medicine paradigm that incorporates the facets of preventive medicine, wellness, and health promotion, and disease complexity and residual risk is proposed and involves novel tools and metrics, such as the disability-adjusted life year (DALY) and the quality-adjusted life year (QALY). In short, the need for lifestyle medicine is based on persistent drivers of chronic disease and inadequacy of current care models to address complexity, residual risk, and challenging health-care socioeconomics.

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Abbreviations

CDC:

Centers for Disease Control and Prevention

CVD:

Cardiovascular disease

DALY:

Disability-adjusted life year

GBD:

Global burden of disease

HBT:

Health-based target

MMWR:

Morbidity and Mortality Weekly Report

NCD:

Noncommunicable diseases

QALY:

Quality-adjusted life year

References

  1. Go AS, Mozaffarian D, Roger VL, et al. Heart disease and stroke statistics—2014 update: a report from the American Heart Association. Circulation. 2014. doi:10.1161/01.cir.0000441139.02102.80. Accessed 22 June 2014.

    Google Scholar 

  2. CDC. Million hearts: strategies to reduce the prevalence of leading cardiovascular disease risk factors—United States, 2011. MMWR Morb Mortal Wkly Rep. 2011;60:1248–51.

    Google Scholar 

  3. Centers for Disease Control and Prevention. Prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation—United States, 2010–2012. MMWR Morb Mortal Wkly Rep. 2013;62:869–92.

    Google Scholar 

  4. Coresh J, Selvin E, Stevens LA, et al. Prevalence of chronic kidney disease in the United States. JAMA. 2007;298:2038–47.

    Article  CAS  PubMed  Google Scholar 

  5. Alzheimer’s Association. Alzheimer’s facts and figures. 2015. http://www.alz.org/alzheimers_disease_facts_and_figures.asp#prevalence/alzheimers_disease_facts_and_figures.asp#prevalence. Accessed 22 June 2014.

  6. Wright NC, Looker AC, Saag KG, et al. The recent prevalence of osteoporosis and low bone mass in the United States based on bone mineral density at the femoral neck or lumbar spine. J Bone Mineral Res. 2014. doi:10.1002/jbmr.2269.

    Google Scholar 

  7. CDC. National Diabetes Statistics Report. 2014. http://www.cdc.gov/diabetes/pubs/statsreport14/national-diabetes-report-web.pdf/diabetes/pubs/statsreport14/national-diabetes-report-web.pdf. Accessed 22 June 2014.

  8. CDC. Current depression among adults—United States, 2006 and 2008. MMWR Morb Mortal Wkly Rep. 2010;59:1229–35.

    Google Scholar 

  9. American Lung Association, Epidemiology and Statistics Unit. Estimated prevalence and incidence of lung disease. 2014 http://www.lung.org/finding-cures/our-research/trend-reports/estimated-prevalence.pdf/finding-cures/our-research/trend-reports/estimated-prevalence.pdf. Accessed 22 June 2014.

  10. De Moor JS, Mariotto AB, Parry C, et al. Cancer survivors in the United States: prevalence across the survivorship trajectory and implications for care. Canc Epidemiol Biomark Prev. 2013;22:561–70.

    Article  Google Scholar 

  11. CDC. Diagnoses of HIV infection in the United States and Dependent Areas. 2011. http://www.cdc.gov/hiv/library/reports/surveillance/2011/surveillance_Report_vol_23.html#3/hiv/library/reports/surveillance/2011/surveillance_Report_vol_23.html#3. Accessed 22 June 2014.

  12. Perrin EC, Newacheck P, Pless IB, et al. Issues involved in the definition and classification of chronic health conditions. Pediatrics. 1993;91:787–93.

    CAS  PubMed  Google Scholar 

  13. O’Halloran J, Miller GC, Britt H. Defining chronic conditions for primary care with ICPC-2. Fam Pract. 2004;21:381–6.

    Article  PubMed  Google Scholar 

  14. CDC. Chronic disease and health promotion. 2015. http://cdc.gov/chronicdisease/overview/index.htm. Accessed 18 July 2014.

  15. CDC. Healthy people 2020. 2011. http://www.cdc.gov/nchs/healthy_people/hp2020.htm. Accessed 22 June 2014.

  16. CDC. CDC grand rounds: childhood obesity in the United States. MMWR Morb Mortal Wkly Rep. 2011;60:42–6.

    Google Scholar 

  17. Chung A, Backholer K, Wong E, et al. Trends in child and adolescent obesity prevalence according to socioeconomic position: protocol for a systematic review. Systematic Rev. 2014;3:52–6.

    Article  Google Scholar 

  18. CDC. Awareness of prediabetes—United States, 2005–2010. MMWR. 2013;62:209–12.

    Google Scholar 

  19. Guariguata L, Whiting DR, Hambleton I, et al. Global estimates of diabetes prevalence for 2013 and projections for 2035. Diab Res Clin Pract. 2014;103:137–49.

    Article  CAS  Google Scholar 

  20. Slack T, Myers CA, Martin CK, et al. The geographic concentration of US adult obesity prevalence and associated social, economic, and environmental factors. Obesity. 2014;22:868–74.

    Article  PubMed  Google Scholar 

  21. Eilerman PA, Herzog CM, Luce BK, et al. A comparison of obesity prevalence: military health system and United States populations, 2009–2012. Military Med. 2014;179:462–70.

    Article  Google Scholar 

  22. Thomas DM, Weedermann M, Fuenmeler BF, et al. Dynamic model predicting overweight, obesity, and extreme obesity prevalence trends. Obesity. 2014;22:590–7.

    Article  PubMed  Google Scholar 

  23. CDC. Obesity—United States, 1999–2010. MMWR Surveill Summ. 2013;62:120–8.

    Google Scholar 

  24. Ostbye T, Stroo M, Eisenstein EL, et al. Is overweight and class I obesity associated with increased health claims costs? Obesity. 2014;22:1179–86.

    Article  PubMed  Google Scholar 

  25. Tarleton HP, Ryan-Ibarra S, Induni M. Chronic disease burden among cancer survivors in the California behavorial risk factor surveillance system, 2009–2010. J Cancer Surviv. 2014. doi:10.1007/s11764-014-0350-x.

    Google Scholar 

  26. Forster M, Veeman JL, Barendregt JJ, et al. Cost-effectiveness of diet and exercise interventions to reduce overweight and obesity. Int J Obes (Lond). 2011;35:1071–8.

    Article  CAS  Google Scholar 

  27. Devleesschauwer B, Havelaar AH, Maertens de Noordhout C, et al. Calculating disability-adjusted life years to quantify burden of disease. Int J Public Health. 2014;59:565–9.

    Article  PubMed  Google Scholar 

  28. Larson BA. Calculating disability-adjusted-life-years lost (DALYs) in discrete time. Cost Eff Res Alloc. 2013;11:18–24.

    Article  Google Scholar 

  29. Polinder S, Haagsma JA, Stein C, et al. Systematic review of general burden of disease using disability-adjusted life years. Popul Health Metr. 2012;10:21–36.

    Article  PubMed Central  PubMed  Google Scholar 

  30. Schroeder SA. Incidence, prevalence, and hybrid approaches to calculating disability-adjusted life years. Popul Health Metr. 2012;10:19–26.

    Article  PubMed Central  PubMed  Google Scholar 

  31. Struijk EA, May AM, Beulens JWJ, et al. Development of methodology for disability-adjusted life years (DALYs) calculation based on real-life data. PloS ONE. 2014;8:e74294. doi:10.1371/journal.pone.0074294.

    Article  Google Scholar 

  32. Gibney K, Sinclair M, O’Toole J, et al. Using disability-adjusted life years to set health-based targets: a novel use of an established burden of disease metric. J Public Health Policy. 2013;34:439–46.

    Article  PubMed Central  PubMed  Google Scholar 

  33. Murray CJ, Lopez AD. The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries and risk factors in 1990 and profected to 2020. Cambridge: Harvard University Press; 1996.

    Google Scholar 

  34. Lopez AD, Mathers CD, Ezzati M, et al. Global burden of disease and risk factors. New York: Oxford University Press; 2006.

    Book  Google Scholar 

  35. World Health Organization. The global burden of disease: 2004 update. 2015. http://www.who.int/healthinfo/global_burden_disease/2004_report_update/en/index.html. Accessed 12 July 2014.

  36. Murray CJ, Vos T, Lozano R, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2013;380:2197–223.

    Article  Google Scholar 

  37. Soerjomataram I, Lortet-Tieulent J, Parkin DM, et al. Global burden of cancer in 2008: a systematic analysis of disability-adjusted life-years in 12 world regions. Lancet. 2012;380:1840–50.

    Article  PubMed  Google Scholar 

  38. Russell LB. Preventing chronic disease: an important investment, but don’t count on cost savings. Health Aff. 2009;28:42–5.

    Article  Google Scholar 

  39. Zhang NJ, Wan THT, Rossiter LF, et al. Evaluation of chronic disease management on outcomes and cost of care for Medicaid beneficiaries. Health Policy. 2008;86:345–54.

    Article  PubMed  Google Scholar 

  40. Rajgopal R, Cox RH, Lambur M, et al. Cost-benefit analysis indicates the positive economic benefits of the Expanded Food and Nutrition Education Program related to chronic disease prevention. J Nutr Educ Behav. 2002;34:26–37.

    Article  PubMed  Google Scholar 

  41. Irvine L, Barton GR, Gasper AV, et al. Cost-effectiveness of a lifestyle intervention in preventing type 2 diabetes. Int J Technol Assess Health Care. 2011;27:275–82.

    Article  PubMed  Google Scholar 

  42. Guy GP, Yabroff KR, Ekwueme DU, et al. Estimating the health and economic burden of cancer among those diagnosed as adolescents and young adults. Health Aff. 2014;33:1024–31.

    Article  Google Scholar 

  43. Erdem E, Prada SI, Haffer SC. Medicare payments: how much do chronic conditions matter? Medicare Medicaid Res Rev. 2013;3:E1–15.

    Article  Google Scholar 

  44. Parekh AK, Kronick R, Tavenner M. Optimizing health for persons with multiple chronic conditions. JAMA. 2014. doi:10.1001/jama.2014.10181.

    Google Scholar 

  45. Ryan JG. Race, risk, and behaviors: race and disproportionate burdens of chronic disease. Clin Therapeutics. 2014;36:464–8.

    Article  Google Scholar 

  46. Campbell DJT, Ronksley PE, Manns BJ, et al. The association of income with health behavior change and disease monitoring among patients with chronic disease. PloS One. 2014;9:e94007. doi:10.1371/journal.pone.0094007.

    Article  PubMed Central  PubMed  Google Scholar 

  47. World Health Organization. The top 10 causes of death. http://www.who.int/mediacentre/factsheets/fs310/en/index2.html. Accessed 18 July 2014.

  48. President of the General Assembly, United Nations. Draft political declaration of the high-level meeting on the prevention and control of non-communicable diseases. http://www.un.org/en/ga/ncdmeeting2011/pdf/NCD_draft_political_declaration.pdf. Accessed 15 July 2014.

  49. World Health Organization. Non-communicable diseases and mental health. http://www.who.int/nmh/publications/9789241597418en/nmh/publications/9789241597418en/. Accessed 15 July 2014.

  50. Mokdad AH, Marks JS, Stroup DF, et al. Actual causes of death in the United States, 2000. JAMA. 2004;29:1238–45.

    Article  Google Scholar 

  51. American Association of Clinical Endocrinologists. 2014 AACE/ACE Consensus Conference of Obesity. http://mms.businesswire.com/media/20140325006164/en/408761/1/aace.pdf [see EC.5. in document]. Accessed 18 July 2014.

  52. Harmon P. A glossary of commonly used business process terms. http://www.ispi.org/archives/Glossary/PHarmon.pdf. Accessed 7 Sept 2014.

  53. Sturmberg JP. Multimorbidity and chronic disease: an emergent perspective. J Eval Clin Pract. 2014. doi:10.1111/jep.12126.

    Google Scholar 

  54. McGrath JW, Winchester MS, Kaawa-Mafigiri D, et al. Challenging the paradigm: anthropological perspectives on HIV as a chronic disease. Med Anthropol. 2014. doi:10.1080/01459740.2014.892483.

    Google Scholar 

  55. Higgins JP. Nonlinear systems in medicine. Yale J Biol Med. 2001;75:247–60.

    Google Scholar 

  56. Vanuzzo D. The epidemiological concept of residual risk. Intern Emerg Med. 2011;6(Suppl 1):S45–51.

    Article  Google Scholar 

  57. Dieci MV, Arnedos M, Delaloge S, et al. Quantification of residual risk of relapse in breast cancer patients optimally treated. Breast. 2013;22:S92–5.

    Article  PubMed  Google Scholar 

  58. Bradbury KE, Appleby PN, Key TJ. Fruit, vegetable, and fiber intake in relation to cancer risk: findings from the European Prospective Investigation into Cancer and Nutrition (EPIC). Am J Clin Nutr. 2014;100(suppl 1):394S–8S.

    Article  CAS  PubMed  Google Scholar 

  59. Jacka FN, Cherbuin N, Anstey KJ, et al. Dietary patterns and depressive symptoms over time: examining the relationships with socioeconomic positions, health behaviours and cardiovascular risk. PloS One. 2014;9:e87657. doi:10.1371/journal.pone.0087657.

    Article  PubMed Central  PubMed  Google Scholar 

  60. Riley TA, Janosky JE. Moving beyond the medical model to enhance primary care. Popul Health Manage. 2012;15:189–93.

    Article  Google Scholar 

  61. Sadler LS, Newlin KH, Johnson-Spruill I, et al. Beyond the medical model: interdisciplinary programs of community-engaged health research. Clin Transl Sci. 2011;4:285–97.

    Article  PubMed Central  PubMed  Google Scholar 

  62. Dyer AR. The need for a new ‘New Medical Model’: a bio-psychosocial-spiritual model. South Med J. 2011;104:297–8.

    Article  PubMed  Google Scholar 

  63. Buja A, Damiani G, Gini R, et al. Systematic age-related differences in chronic disease management in a population-based cohort study: a new paradigm of primary care is required. PloS One. 2014;9:e91340. doi:10.1371/journal.pone.0091340.

    Article  PubMed Central  PubMed  Google Scholar 

  64. Rieck AM. Exploring the nature of power distance on general practitioner and community pharmacist relations in a chronic disease management context. J Interprof Care. 2014. doi:10.3109/13561820.2014.906390.

    Google Scholar 

  65. Liddy C, Mill K. An environmental scan of policies in support of chronic disease self-management in Canada. Chr Dis Inj Can. 2014;34:55–63.

    CAS  Google Scholar 

  66. Simmons LA, Wolever RQ, Bechard EM, et al. Patient engagement as a risk factor in personalized health care: a systematic review of the literature on chronic disease. Genome Med. 2014;6:16–29.

    Article  PubMed Central  PubMed  Google Scholar 

  67. Mackenzie L. Can chronic disease management plans including occupational therapy and physiotherapy services contribute to reducing falls risk in older people? Austr Fam Phys. 2014;43:211–5.

    Google Scholar 

  68. Brooks AT, Andrade RE, Middleton KR, et al. Social support: a key variable for health promotion and chronic disease management in Hispanic patients with rheumatic diseases. Clin Med Insights Arthr Musculoskel Dis. 2014;7:21–6.

    Google Scholar 

  69. Drutchas A, Anandarajah G. Spirituality and coping with chronic disease in pediatrics. Rhode Island Med J. 2014;97:26–30.

    Google Scholar 

  70. Vorderstrasse AA, Ginsberg GS, Kraus WE, et al. Health coaching and genomics—potential avenues to elicit behavior change in those at risk for chronic disease: protocol for personalized medicine effectiveness study in Air Force primary care. Global Adv Health Med. 2013;2:26–38.

    Article  Google Scholar 

  71. Hussey PS, Schneider EC, Rudin RS, et al. Continuity and the costs of care for chronic disease. JAMA Intern Med. 2014;174:742–8.

    Article  PubMed Central  PubMed  Google Scholar 

  72. Jones A, Hedges-Chou J, Bates J, et al. Home telehealth for chronic disease management: selected findings of a narrative synthesis. Telemed e-Health. 2014;20:346–80.

    Article  Google Scholar 

  73. Owen N, Salmon J, Koohsari MJ, et al. Sedentary behavior and health: mapping environmental and social contexts to underpin chronic disease prevention. Br J Sports Med. 2014;48:174–7.

    Article  PubMed  Google Scholar 

  74. Shaughnessy AF. Focusing on patient-oriented evidence that matters in the care of patients with diabetes mellitus. Pharmacotherapy. 2004;24:295–7.

    Article  PubMed  Google Scholar 

  75. Wigg AJ, Chinnaratha MA, Wundke R, et al. A chronic disease management model for chronic liver failure. Hepatology. 2014. doi:10.1002/hep.27152.

    Google Scholar 

  76. Ritsema TS, Bingenheimer JB, Scholting P, et al. Differences in the delivery of health education to patients with chronic disease by provider type, 2005–2009. Prev Chronic Dis. 2014;11:130175. doi:10.5888/pcd11.130175.

    Article  Google Scholar 

  77. Bloem BR, Munneke M. Revolutionising management of chronic disease: the ParkinsonNet approach. BMJ. 2014;348:g1838. doi:http://dx.doi.org/10.1136/bmj.g1838.

    Article  PubMed  Google Scholar 

  78. Bain L, Kennedy C, Archibald D, et al. A training program designed to improve interprofessional knowledge, skills and attitudes in chronic disease settings. J Interprof Care. 2014. doi:10.3109/13561820.2014.898622.

    Google Scholar 

  79. Patel KK. Practical and policy implications of a changing health care workforce for chronic disease management. J Ambul Care Manage. 2013;36:302–4.

    Article  PubMed  Google Scholar 

  80. Clarke JL. Preventive medicine: a ready solution for a health care system in crisis. Popul Health Manage. 2010;10:S3–11.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Division of Endocrinology, Diabetes and Bone Disease, Icahn School of Medicine at Mount Sinai, 1192 Park Avenue, 10128, New York, NY, USA

    Jeffrey I. Mechanick MD

  2. Northwestern Comprehensive Center on Obesity, Northwestern University Feinberg School of Medicine, 750 North Lake Shore Drive Rubloff 9-976, 60611, Chicago, IL, USA

    Robert F. Kushner MD

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  1. Jeffrey I. Mechanick MD
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Correspondence to Jeffrey I. Mechanick MD .

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Editors and Affiliations

  1. New York, USA

    Jeffrey I. Mechanick MD

  2. Chicago, USA

    Robert F. Kushner MD

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Mechanick, J., Kushner, R. (2016). Why Lifestyle Medicine?. In: Mechanick, J., Kushner, R. (eds) Lifestyle Medicine. Springer, Cham. https://doi.org/10.1007/978-3-319-24687-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-24687-1_1

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