Advertisement

A Pathways Approach to the Metabolic Syndrome

  • Angele McGrady
  • Donald Moss
Chapter

Abstract

Psychosocial factors interact with genetics, environment, and lifestyle to increase risk for the metabolic syndrome (essential hypertension, Type 2 diabetes, hyperlipidemia, and obesity). Patients with the metabolic syndrome often suffer from anxious and depressive symptoms, negatively affecting motivation for self-management. A biopsychosocial approach is important in the care of patients such as Carmella, the case described in this chapter. Treatment of this multifaceted chronic disorder is complex and is best coordinated among multiple specialists and in addition requires the active participation of the patient. Based on the Pathways Model, the mental health provider’s role is to empower the patient in effective self-management. Psychophysiological therapies offer the opportunity for regulation of physiological stress responses, engaging the relaxation response. Patients learn to make daily decisions which benefit their short- and long-term health. The psychotherapies, particularly cognitive behavioral therapy are consistent with the theme of self-awareness, patient choices, and significant changes in behavior. One of the complementary therapies, Reiki is also utilized by Carmella to achieve her goal of better metabolic control.

Keywords

Metabolic syndrome Diabetes Hypertension Hyperlipidemia Obesity Pathways Model 

References

  1. Aguilar, M., Bhuket, T., Torres, S., Liu, B., & Wong, R. J. (2015). Prevalence of the metabolic syndrome in the United States, 2003-2012. Journal of the American Medical Association, 313(19), 1973–1974.CrossRefGoogle Scholar
  2. Aikens, J. E. (2012). Prospective associations between emotional distress and poor outcomes in type 2 diabetes. Diabetes Care, 35(12), 2472–2478. https://doi.org/10.2337/dc12-0181 CrossRefPubMedPubMedCentralGoogle Scholar
  3. American Diabetes Association (ADA). (2015a). Diagnosis and classification of diabetes mellitus. Diabetes Care, 38(Suppl. 1), S8–S16.CrossRefGoogle Scholar
  4. American Diabetes Association (ADA). (2015b). Standards of medical care in diabetes. Diabetes Care, 38(Suppl. 1), S1–S93.Google Scholar
  5. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.CrossRefGoogle Scholar
  6. American Academy of Pediatrics (2014). Adverse childhood experiences and the lifelong consequences of trauma. https://www.aap.org/en-us/Documents/ttb_aces_consequences.pdf.
  7. Baer, R. A. (2003). Mindfulness training as a clinical intervention: A conceptual and empirical review. Clinical Psychological Science Practicum, 10(2), 125–143.CrossRefGoogle Scholar
  8. Black, D., O’Reilly, G., Olmstead, R., Breen, E., & Irwin, M. (2015). Mindfulness meditation and improvement in sleep quality and daytime impairment among older adults with sleep disturbances: A randomized clinical trial. JAMA Internal Medicine, 175(4), 494–501.CrossRefGoogle Scholar
  9. Branth, S., Ronquist, G., Stridsberg, M., Hambraeus, L., Kindgren, E., Olsson, R., et al. (2007). Development of abdominal fat and incipient metabolic syndrome in young healthy men exposed to long-term stress. Nutrition, Metabolism, and Cardiovascular Diseases, 17, 427–435.CrossRefGoogle Scholar
  10. Brook, R. D., Appel, L. J., Rubenfire, M., Ogedegbe, G., Bisognano, J. D., Elliott, W. J., et al. (2013). Beyond medications and diet: Alternative approaches to lowering blood pressure. Hypertension, 61(6), 1360–1383.CrossRefGoogle Scholar
  11. Capuron, L., Su, S., Miller, A. H., Bremner, J. D., Goldbery, J., Vogt, G. J., et al. (2008). Depressive symptoms and metabolic syndrome: Is inflammation the underlying link? Biological Psychiatry, 64(10), 896–900.CrossRefGoogle Scholar
  12. Carnethon, M., & Craft, L. (2008). Autonomic regulation of the association between exercise and diabetes. Exercise and Sport Sciences Reviews, 36(1), 12–18.CrossRefGoogle Scholar
  13. Catapano, A. L., Graham, I., De Backer, G., Wiklund, O., Chapman, M. J., Drexel, H., et al. (2016). 2016 ESC/EAS guidelines for the management of dyslipidaemias: The Task Force for the Management of Dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS) developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). Atherosclerosis, 253, 281–344. https://doi.org/10.1016/j.atherosclerosis.2016.08.018 CrossRefPubMedGoogle Scholar
  14. Chandola, T., Brunner, E., & Marmot, M. (2006). Chronic stress at work and the metabolic syndrome: Prospective study. British Medical Journal, 332, 521–525.CrossRefGoogle Scholar
  15. Davies, S. J. C., Hood, S. D., Christmas, D., & Nutt, D. J. (2008). Psychiatric disorders and cardiovascular disease anxiety, depression and hypertension. In L. Sher (Ed.), Psychological factors and cardiovascular disorders: The role of psychiatric pathology and maladaptive personality features (pp. 69–96). Hauppauge, NY: Nova Scotia Publishers Inc..Google Scholar
  16. Davis, M., Eshelman, E., & McKay, M. (2008). The relaxation & stress reduction workbook (6th ed.). Oakland, CA: New Harbinger.Google Scholar
  17. Dixon, M. R., Lik, N. M. K., Green, L., & Myerson, J. (2013). Delay discounting of hypothetical and real money: The effect of holding reinforcement rate constant. Journal of Applied Behavior Analysis, 46(2), 512–517.CrossRefGoogle Scholar
  18. Froy, O. (2010). Metabolism and circadian rhythms—Implications for body weight. The Open Neuroendocrinology Journal, 3, 28–37.Google Scholar
  19. Gillespie, E., Gillespie, B. W., & Stevens, M. J. (2007). Painful diabetic neuropathy: Impact of an alternative approach. Diabetes Care, 30(4), 999–1001. https://doi.org/10.2337/dc06-1475 CrossRefPubMedGoogle Scholar
  20. Goldbacher, E. M., & Matthews, K. A. (2007). Are psychological characteristics related to risk of the metabolic syndrome?: A review of the literature. Annals of Behavioral Medicine, 34(3), 240–252.CrossRefGoogle Scholar
  21. Gonzalez, J. S., Peyrot, M., McCarl, L. A., Collins, E. M., Serpa, L., Mimiaga, M. J., et al. (2008). Depression and diabetes treatment nonadherence: A meta-analysis. Diabetes Care, 31(12), 2398–2403. https://doi.org/10.2337/dc08-1341 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Gonzalez, J. S., Shreck, E., Psaros, C., & Safren, S. A. (2015). Distress and Type-2 diabetes-treatment adherence: A mediating role for perceived control. Health Psychology, 34(5), 505–513.CrossRefGoogle Scholar
  23. Hamer, M., Taylor, A., & Steptoe, A. (2006). The effect of acute aerobic exercise on stress related blood pressure responses: A systematic review and meta-analysis. Biological Psychology, 71(2), 183–190.CrossRefGoogle Scholar
  24. High Blood Pressure (Hypertension): Tests and Diagnosis. (2016, September 9). Retrieved from http://www.mayoclinic.org/diseases-conditions/high-blood-pressure/basics/tests-diagnosis/con-20019580
  25. Ho, F. Y. Y., Chung, K. F., Yeung, W. F., Ng, T. H., Kwan, K. S., Yung, K. P., et al. (2015). Self-help cognitive-behavioral therapy for insomnia: A meta-analysis of randomized controlled trials. Sleep Medicine Reviews, 19, 17–28.CrossRefGoogle Scholar
  26. James, P. A., Oparil, S., Carter, B. L., Cushman, W. C., Dennison-Himmelfarb, C., Handler, J., et al. (2014). 2014 evidence-based guideline for the management of high blood pressure in adults: Report from the panel members appointed to the eighth Joint National Committee (JNC 8). JAMA, 311(5), 507–520.CrossRefGoogle Scholar
  27. Kim, K. H. C., Bursac, Z., DiLillo, V., White, D. B., & West, D. S. (2009). Stress, race, and body weight. Health Psychology, 28(1), 131–135.CrossRefGoogle Scholar
  28. Knutson, K., & Van Cauter, E. (2008). Associations between sleep loss and increased risk of obesity and diabetes. Annals of the New York Academy of Sciences, 1129, 287–304.CrossRefGoogle Scholar
  29. Kyrou, I., Chrousos, G. P., & Tsigos, C. (2006). Stress, visceral obesity, and metabolic complications. In G. P. Chrousos & C. Tsigos (Eds.), Stress, obesity, and metabolic syndrome: Annals of the New York Academy of Sciences (Vol. 1083, pp. 77–110). Boston, MA: Wiley-Blackwell.Google Scholar
  30. Linden, W., & McGrady, A. V. (2016). Essential hypertension. In M. S. Schwartz & F. Andrasik (Eds.), Biofeedback: A practitioner’s guide (pp. 383–399). New York: The Guilford Press.Google Scholar
  31. Lundahl, B., & Burke, B. L. (2009). The effectiveness and applicability of motivational interviewing: A practice-friendly review of four meta-analyses. Journal of Clinical Psychology, 65(11), 1232–1245.CrossRefGoogle Scholar
  32. Matthews, K. A., & Gallo, L. C. (2011). Psychological perspectives on pathways linking socioeconomic status and physical health. Annual Review of Psychology, 62, 501–530. https://doi.org/10.1146/annurev.psych.031809.130711 CrossRefPubMedPubMedCentralGoogle Scholar
  33. Maty, S. C., Lynch, J. W., Raghunathan, T. E., & Kaplan, G. A. (2008). Childhood socioeconomic position, gender, adult body mass index, and incidence of type 2 diabetes mellitus over 34 years in the Alameda County Study. American Journal of Public Health, 98(8), 1486–1494.CrossRefGoogle Scholar
  34. McGinnis, R. A., McGrady, A., Cox, S. A., & Grower-Dowling, K. A. (2005). Biofeedback-assisted relaxation in type 2 diabetes. Diabetes Care, 28(9), 2145–2149.CrossRefGoogle Scholar
  35. McGrady, A., & Lakia, D. (2016). Diabetes mellitus. In M. S. Schwartz & F. Andrasik (Eds.), Biofeedback: A practitioner’s guide (4th ed., pp. 400–421). New York: The Guilford Press.Google Scholar
  36. McIntyre, R. S., Soczynski, J. K., Konarski, J. Z., Woldeyohannes, H. O., Law, C. W. Y., Miranda, A., et al. (2007). Should depressive syndromes be reclassified as “metabolic syndrome type II?”. Annals of Clinical Psychiatry, 19(4), 257–264.CrossRefGoogle Scholar
  37. McSharry, J., Moss-Morris, R., & Kendrick, T. (2011). Illness perceptions and glycaemic control in diabetes: A systematic review with meta-analysis. Diabetic Medicine, 28, 1300–1310. https://doi.org/10.1111/j.1464-5491.2011.03298.x CrossRefGoogle Scholar
  38. Moskowitz, J. T., Epel, E. S., & Acree, M. (2008). Positive affect uniquely predicts lower risk of mortality in people with diabetes. Health Psychology, 27(1 Suppl), S73–S82.CrossRefGoogle Scholar
  39. National Center for Complementary and Alternative Medicine. (2015). Reiki: An introduction. Retrieved from http://nccam.nih.gov/health/reiki/introduction.htm
  40. Ogden, C. L., Carroll, M. D., Curin, L. R., McDowell, M. A., Tabak, C. J., & Flegal, K. M. (2006). Prevalence of overweight and obesity in the United States, 1999-2004. Journal of the American Medical Association, 295, 1549–1555.CrossRefGoogle Scholar
  41. Patel, S. R. (2009). Reduced sleep as an obesity risk factor. Obesity Reviews, 2(10), 61–68.CrossRefGoogle Scholar
  42. Petry, N. M., Cengiz, E., Wagner, J. A., Hood, K. K., Carria, L., & Tamborlane, W. V. (2013). Incentivizing behavior change to improve diabetes care. Diabetes, Obesity, and Metabolism, 15(12), 1071–1076.CrossRefGoogle Scholar
  43. Rice, B. I. (2007). Clinical benefits of training patients to voluntarily increase peripheral blood flow. Diabetes Educator, 33(3), 442–454.CrossRefGoogle Scholar
  44. Simon, G. E., Ludman, E. J., Linde, J. A., Operskalski, B. H., Ichikawa, L., Rohde, P., et al. (2008). Association between obesity and depression in middle-aged women. General Hospital Psychiatry, 30, 32–39.CrossRefGoogle Scholar
  45. Steptoe, A., O’Donnell, K., Marmot, M., & Wardle, J. (2008). Positive affect and psychosocial processes related to health. British Journal of Psychology, 99, 211–227. https://doi.org/10.1348/000712607X218295 CrossRefPubMedGoogle Scholar
  46. Thrane, S., & Cohen, S. M. (2014). Effect of Reiki therapy on pain and anxiety in adults: An in-depth literature review of randomized trials with effect size calculations. Pain Management Nursing, 15(4), 897–908. https://doi.org/10.1016/j.pmn.2013.07.008 CrossRefPubMedPubMedCentralGoogle Scholar
  47. West, D. S., DiLillo, V., Bursac, Z., Gore, S. A., & Greene, P. G. (2007). Motivational interviewing improves weight loss in women with type 2 diabetes. Diabetes Care, 30, 1081–1087.CrossRefGoogle Scholar
  48. Wickrama, K., O’Neal, C. W., Lee, T. K., & Wickrama, T. (2015). Early socioeconomic adversity, youth positive development, and young adults’ cardio-metabolic disease risk. Health Psychology, 34(9), 905–914.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Angele McGrady
    • 1
  • Donald Moss
    • 2
  1. 1.Department of PsychiatryUniversity of ToledoToledoUSA
  2. 2.College of Integrative Medicine and Health SciencesSaybrook UniversityOaklandUSA

Personalised recommendations