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The Cardiometabolic-Focused Exam for All Body Types

Physician and patient in a clinic setting
Read Time: 5 Minutes

Given the widespread and increasing prevalence of metabolic dysfunction,1,2 identifying it in our patients is increasingly important. For many, obesity may be the first indicator of metabolic issues, but research suggests that not all obese patients are metabolically unhealthy.3,4 The converse is also true: some normal-weight individuals defined as having a BMI from 18.5 to 24.9 kg/m2 have displayed metabolic disturbances.5 Moreover, certain conditions may predispose a patient to metabolic dysfunction, as can certain prescription medications. How do functional medicine clinicians move beyond BMI and use advanced physical exam skills and comprehensive testing to identify insulin resistance in individuals of all body types?

Cardiometabolic Physical Exam: Beyond BMI

For a patient who isn’t a textbook example of insulin resistance, there are some clues that point to such dysfunction as a possibility. Even for normal weight individuals, a brief physical exam offers numerous ways to highlight nutritional and metabolic concerns—and IFM’s Cardiometabolic Advanced Practice Module (APM) teaches you how to see these signs.

The physical exam offers numerous ways to zero in on nutritional and metabolic concerns to help the clinician precisely understand the pathophysiology of cardiometabolic disease and develop targeted lifestyle and pharmacological interventions. Researchers suggest that when a patient with normal weight has two or more parameters of metabolic syndrome, it is important to determine whether impaired glucose tolerance, fatty liver, or early atherosclerosis is present.6

With early diagnosis and intervention, the disease course of metabolic syndrome may be controlled or even reversed. In the following video, IFM educator Shilpa Saxena, MD, IFMCP, discusses several aspects of the physical exam that may indicate insulin resistance or metabolic dysfunction and help inform a patient’s treatment strategy.

(Video Time: 2 minutes) Shilpa Saxena, MD, IFMCP, is a board-certified family physician with over 15 years of progressive patient care at her successful medical practice.

One study suggests that manifestations of insulin resistance on the skin may be more reliable than other forms of diagnosis.7 Skin manifestations may also indicate severity of metabolic syndrome.8 Even in children and adolescents, the well-known sign acanthosis nigricans offers a reliable physical exam clue for metabolic syndrome.9 Other physical signs of metabolic disorders may include hirsutism,10,11 peripheral neuropathy,12 and xanthelasma palpebrarum.13

The first head-to-head comparison of a large number of cardiometabolic risk phenotypes revealed that normal-weight people may experience insulin secretion failure, insulin resistance, and increased carotid intima-media thickness (cIMT).6 According to this study, insulin secretion failure may be of major relevance for cardiometabolic risk in normal-weight patients as it promotes hyperglycemia. Furthermore, compared to people who are of normal weight and metabolically healthy, subjects who are of normal weight but metabolically unhealthy have a greater than three-fold higher risk of all-cause mortality and/or cardiovascular events.6,14

Clinicians may also consider screening adults for waist-to-height ratio (WHtR) and waist circumference (WC) for cardiometabolic risk. A systematic review and meta-analysis of more than 300,000 adults suggests that WHtR has significantly greater discriminatory power for detecting cardiometabolic risk factors in both sexes compared with BMI. The researchers suggest that WHtR should be considered a screening tool during the cardiometabolic physical exam.15

Influencing Factors

The prevalence of metabolic syndrome in the United States has been estimated at 36.9% based on statistics through 2016.1 Compared with prevalence rates from 2012, significant increases were noted for those aged 20 to 39 years, for women, and for Asian and Hispanic adults.1 A variety of factors may increase the likelihood of metabolic syndrome, including:

  • Celiac disease: As with other autoimmune diseases, celiac disease may increase the risk of cardiovascular diseases due to chronic inflammation; however, research evidence is inconsistent.16 Removing gluten from the diet is a primary treatment for celiac disease; however, ensuring patients follow a nutrient-dense, gluten-free diet is essential. Studies have suggested that some patients showed an increased risk of developing metabolic syndrome after starting a gluten-free diet.17,18 Potential causes were suggested, such as increased consumption of foods that were higher in sugar, fat, and calories after going gluten-free.17
  • Polycystic ovary syndrome (PCOS): In women with polycystic ovary syndrome, the risk of developing gestational diabetes is approximately three times greater than in non-PCOS women,19 and insulin resistance occurs in 30% of lean women with PCOS.20 Regarding cardiometabolic risk profiles, a 2020 meta-analysis of 11 studies (n=2,851) found that Black women with PCOS had a greater risk of adverse profiles that included increased fasting insulin, insulin resistance, and systolic blood pressure compared to white women with PCOS.21
  • Gestational diabetes mellitus (GDM): Results from a 2020 meta-analysis of 23 studies (n=10,230) indicated that those women with a personal history of GDM had a greater risk of developing metabolic syndrome compared to those without a history of GDM.22 The risk was even more increased among those women with increased BMI compared to controls.22
  • Stress: A five-year longitudinal study in a rapid response police unit supports the hypothesis that work-related stress induces metabolic syndrome, particularly through its effects on blood lipids.23 In addition, a 2019 meta-analysis of cross-sectional studies found that adults who identified in a high-stress group had 45% higher odds of having metabolic syndrome than adults who identified in a low-stress group.24

Conclusion

Primary care physicians are ideally placed to address cardiometabolic risk factors with their patients, and functional medicine helps synthesize the latest medical research with a model of care that integrates lifestyle factors and focuses on the whole person—beyond BMI. IFM’s Cardiometabolic Advanced Practice Module will help clinicians understand the physiology underlying cardiometabolic syndrome and cardiovascular disease, new approaches to effective assessments and treatments, and how to integrate these lifesaving tools into practice.

Clinicians will learn to evaluate and utilize new assessment approaches for identifying chronic inflammation, oxidative stress, autoimmunity, toxicity, and hormonal dysregulation in patients with cardiometabolic dysfunction. Attendees will also receive 30-day access to IFM’s Toolkit, with hundreds of downloadable clinician resources that can be accessed and used in practice immediately after the course.

Learn More About Cardiometabolic Function

The Right Food Plan for Cardiometabolic Patients

Exercise Prescriptions for Cardiometabolic Health

Cardiometabolic Conditions and the Microbiome

References

  1. Hirode G, Wong RJ. Trends in the prevalence of metabolic syndrome in the United States, 2011-2016. JAMA. 2020;323(24):2526-2528. doi:1001/jama.2020.4501
  2. Noubiap JJ, Nansseu JR, Lontchi-Yimagou E, et al. Global, regional, and country estimates of metabolic syndrome burden in children and adolescents in 2020: a systematic review and modelling analysis. Lancet Child Adolesc Health. 2022;6(3):158-170. doi:1016/S2352-4642(21)00374-6
  3. Jung CH, Lee WJ, Song KH. Metabolically healthy obesity: a friend or foe? Korean J Intern Med. 2017;32(4):611-621. doi:3904/kjim.2016.259
  4. Buscemi S, Chiarello P, Buscemi C, et al. Characterization of metabolically healthy obese people and metabolically unhealthy normal-weight people in a general population cohort of the ABCD study. J Diabetes Res. 2017;2017:9294038. doi:1155/2017/9294038
  5. Gujral UP, Vittinghoff E, Mongraw-Chaffin M, et al. Cardiometabolic abnormalities among normal-weight persons from five racial/ethnic groups in the United States: a cross-sectional analysis of two cohort sAnn Intern Med. 2017;166(9):628-636. doi:10.7326/M16-1895
  6. Stefan N, Schick F, Häring HU. Causes, characteristics, and consequences of metabolically unhealthy normal weight in humans. Cell Metab. 2017;26(2):292-300. doi:1016/j.cmet.2017.07.008
  7. González-Saldivar G, Rodríguez-Gutiérrez R, Ocampo-Candiani J, González-González JG, Gómez-Flores M. Skin manifestations of insulin resistance: from a biochemical stance to a clinical diagnosis and management. Dermatol Ther. 2017;7(1):37-51. doi:1007/s13555-016-0160-3
  8. Huang Y, Chen J, Wang X, Li Y, Yang S, Qu S. The clinical characteristics of obese patients with acanthosis nigricans and its independent risk factors. Exp Clin Endocrinol Diabetes. 2017;125(3):191-195. doi:1055/s-0042-123035
  9. Velazquez-Bautista M, López-Sandoval JJ, González-Hita M, Vázquez-Valls E, Cabrera-Valencia IZ, Torres-Mendoza BM. Association of metabolic syndrome with low birth weight, intake of high-calorie diets and acanthosis nigricans in children and adolescents with overweight and obesity. Endocrinol Diabetes Nutr. 2017;64(1):11-17. doi:1016/j.endinu.2016.09.004
  10.  Talaei A, Adgi Z, Mohamadi Kelishadi M. Idiopathic hirsutism and insulin resistance. Int J Endocrinol. 2013;2013:593197. doi:1155/2013/593197
  11.  Azziz R. Polycystic ovary syndrome. Obstet Gynecol. 2018;132(2):321-336. doi:1097/AOG.0000000000002698
  12.  Stino AM, Smith AG. Peripheral neuropathy in prediabetes and the metabolic syndrome. J Diabetes Investig. 2017;8(5):646-655. doi:1111/jdi.12650
  13.  Nair PA, Singhal R. Xanthelasma palpebrarum – a brief review. Clin Cosmet Investig Dermatol. 2017;11:1-5. doi:2147/CCID.S130116
  14.  Schulze MB. Metabolic health in normal-weight and obese individuals. Diabetologia. 2019;62(4):558-566. doi:1007/s00125-018-4787-8
  15.  Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev. 2012;13(3):275-286. doi:1111/j.1467-789x.2011.00952.x
  16.  Laurikka P, Kivelä L, Kurppa K, Kaukinen K. Review article: systemic consequences of coeliac disease. Aliment Pharmacol Ther. 2022;56(Suppl 1):S64-S72. doi:1111/apt.16912
  17.  Tortora R, Capone P, De Stefano G, et al. Metabolic syndrome in patients with coeliac disease on a gluten-free diet. Aliment Pharmacol Ther. 2015;41(4):352-359. doi:1111/apt.13062
  18.  Ciccone A, Gabrieli D, Cardinale R, et al. Metabolic alterations in celiac disease occurring after following a gluten-free diet. Digestion. 2019;100(4):262-268. doi:1159/000495749
  19.  Yao K, Bian C, Zhao X. Association of polycystic ovary syndrome with metabolic syndrome and gestational diabetes: aggravated complication of pregnancy. Exp Ther Med. 2017;14(2):1271-1276. doi:3892/etm.2017.4642
  20.  Baldani DP, Skrgatic L, Ougouag R. Polycystic ovary syndrome: important underrecognised cardiometabolic risk factor in reproductive-age women. Int J Endocrinol. 2015;2015:786362. doi:1155/2015/786362
  21.  Kazemi M, Kim JY, Parry SA, Azziz R, Lujan ME. Disparities in cardio-metabolic risk between Black and White women with polycystic ovary syndrome: a systematic review and meta-analysis. Am J Obstet Gynecol. 2021;224(5):428-444.e8. doi:1016/j.ajog.2020.12.019
  22.  Tranidou A, Dagklis T, Tsakiridis I, et al. Risk of developing metabolic syndrome after gestational diabetes mellitus – a systematic review and meta-analysis. J Endocrinol Invest. 2021;44(6):1139-1149. doi:1007/s40618-020-01464-6
  23.  Garbarino S, Magnavita N. Work stress and metabolic syndrome in police officers. A prospective study. PLoS One. 2015;10(12):e0144318. doi:1371/journal.pone.0144318
  24.  Kuo WC, Bratzke LC, Oakley LD, Kuo F, Wang H, Brown RL. The association between psychological stress and metabolic syndrome: a systematic review and meta-analysis. Obes Rev. 2019;20(11):1651-1664. doi:1111/obr.12915

 

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