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Muscle Mass As A Potential Predictor For Metabolic Syndrome In Normal Weight Individuals

Muscle Mass As A Potential Predictor For Metabolic Syndrome In Normal Weight Individuals. Julia Humphrey Central Washington University. Overview. Introduction Metabolic Syndrome MONW & metabolic syndrome Sarcopenia & metabolic syndrome Hypothesis/Purpose Methods & Statistics Results

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Muscle Mass As A Potential Predictor For Metabolic Syndrome In Normal Weight Individuals

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  1. Muscle Mass As A Potential Predictor For MetabolicSyndrome In Normal Weight Individuals Julia Humphrey Central Washington University

  2. Overview • Introduction • Metabolic Syndrome • MONW & metabolic syndrome • Sarcopenia & metabolic syndrome • Hypothesis/Purpose • Methods & Statistics • Results • Discussion

  3. Introduction

  4. Metabolic Syndrome • Cluster of symptoms correlated with risk of CVD and Type 2 DM • 1988 termed syndrome-X by Reaven • NCEP ATP III Definition • 3 or more of the following: • Abdominal obesity • Elevated triglyceride • Low HDL-C • High blood pressure • Elevated fasting glucose • Other definitions

  5. Metabolic Syndrome • Prevalence is increasing • 34% of U.S. population • Younger adults & children increasingly diagnosed • Risk of developing chronic disease • 2-fold increase of CVD • 5-fold increase of type 2 DM • Increased risk via: • Diet, physical inactivity, genetics

  6. Metabolically Obese Normal Weight • Identification • Subtype of at-risk individuals • BMI within normal range • have abnormal metabolic properties associated with obesity • Association with metabolic syndrome • Risk of developing CVD & type 2 DM • Dangers presented • Not detected due to normal BMI & young age • Increased mortality risk

  7. Metabolically Obese Normal Weight • Body Composition • Increased body fat • Decreased muscle mass • Decreased physical activity • Possible genetic predisposition • Family history of type 2 DM & obesity • Parents have triglyceridemia • Increased body fat in comparison

  8. The Obese Without Cardiometabolic Risk Factor Clustering and the Normal Weight With Cardiometabolic Risk Factor ClusteringWildman et al. 2008 • Subjects • 5440 NHANES 1999-2004 • ≥ 20 years, BMI ≥ 18.5 kg/m2, fasted, no history of CVD • Methods • Cardiometabolic Abnormality • Elevated BP • Elevated TG • Decreased HDL-C • Elevated fasting glucose • Insulin resistance • Systemic inflammation • Normal weight metabolically abnormal • BMI < 25 kg/m2 + 2 cardiometabolic abnormalities • Behavior & physical activity questionnaire

  9. The Obese Without Cardiometabolic Risk Factor Clustering and the Normal Weight With Cardiometabolic Risk Factor ClusteringWildman et al. 2008 • 23.5% of normal weight individuals • 8.1% of entire population

  10. The Obese Without Cardiometabolic Risk Factor Clustering and the Normal Weight With Cardiometabolic Risk Factor ClusteringWildman et al. 2008 • Mean age 54.7 years • 46.6% reported no physical activity

  11. Skeletal Muscle & Metabolic Syndrome • Skeletal muscle • Primary site for glucose uptake • Decreased MM = decreased glucose uptake • Can lead to insulin resistance • Sarcopenia • Correlated with type 2 DM • Relationship to cardiometabolic syndrome • Associated with insulin resistance & prediabetes

  12. Relative muscle mass is inversely associated with insulin resistance and prediabetes. Srikanthan et al. 2011 • Purpose • Examine the association of skeletal muscle mass with insulin resistance and dysglycemia in a nationally representative sample • Subjects • 13,644 subjects • > 20 years, not pregnant, fasted, BIA measurements, BMI ≥ 16 kg/m2, body weight > 35 kg, no self-reported cardiac failure • Methods • SMI via BIA measurements • Serum insulin, plasma glucose, HOMA-IR, HbA1C • SMI in quartiles, unadjusted • Differences between SMI quartiles & risk factors

  13. Relative muscle mass is inversely associated with insulin resistance and prediabetes. Srikanthan et al. 2011

  14. National Health and Nutrition Examination Survey • Continuous program • 2-year intervals • Nationally representative data • Sample of 5,000 from all age & major ethnic groups • Health examination & interview • Demographic, socioeconomic, dietary, & health related questions

  15. Hypothesis, Purpose, & Methods

  16. Hypothesis • MONW • Decreased physical activity, Increased fat mass, & Decreased muscle mass • Sarcopenic studies • Inverse relationship between muscle mass & metabolic syndrome • Studied in Korea on national scale, not in U.S. • NHANES • Muscle mass & insulin resistance • Metabolic syndrome in normal weight • No studies looking at muscle mass & metabolic syndrome in normal weight • Purpose • To study the relationship between decreased muscle mass and metabolic syndrome in normal weight subjects using NHANES data

  17. Methods • Subjects • 1826 men and women NHANES 1999-2006 • Controls • Age ≥ 20 years • BMI 18.5 - 25 kg/m2 • DXA - not preg or lactating, complete • Sarcopenia Definition • Calculated ASM Index = ASM/ht2 via DXA measurements • Separated by gender • Divided into tertiles • Based on gender • Separated by age • Lowest tertile = sarcopenic

  18. Methods • Statistics • Chi-square analysis • Tertiles separated by gender • Differences between prevalence rates for each risk factor within tertiles • Separated by age • Odds Ratio • Odds of risk for metabolic syndrome and each risk factor • Referencing highest muscle group • SAS 9.2

  19. Results

  20. Subject Characteristics

  21. Results – Not Separated by Age

  22. Results – Not Separated by Age

  23. Results Recap • Not separating by age: • Prevalence • Males & Females • All significant except HDL • Odds • Male & Female • 2-fold increase in hyperglycemia • 3-fold increase in BP • 2-fold increase in TG • Metabolic Syndrome • Male – 7-fold increase • Female – 2-fold increase • Noticeable trends with age & decreased muscle mass • Men more prevalent

  24. Results – Separated by Age Men

  25. Results – Separated by Age Men

  26. Results – Separated by Age Female

  27. Results – Separated by Age Female

  28. Results Recap • Significant differences separating by age • Prevalence: • Males 60+= BP • Females 40-59 = TG & metabolic syndrome • Odds ratio • Males • 5-fold increase for metabolic syndrome age 40-59 • 6-fold increase for metabolic syndrome age 60 + • 3-fold increase for BP age 60 + • Females • 2-fold increase for TG age 40-59 • 3-fold increase for metabolic syndrome age 40-59

  29. Discussion

  30. Discussion: Metabolic Syndrome & Muscle • Wildman et al. 2008 • Cardiometabolic abnormality 23.5% of normal-weight • Srikanthan et al. 2011 • Inverse relationship between muscle mass & insulin resistance/dysglycemia • My study • Not separated by age • Men: 12.19% vs. 1.75% • Women: 15.25% vs. 6.16% • Separated by age • 20-39: 6.92% men, 0% women • 40-59: 11.5% men, 19.48% women • 60+: 20.14% men, 21.69% women

  31. Discussion: Metabolic Syndrome Risk Factors • Not separated by age • Separated by age • Men: 60+ BP • Women: 40-59 High Triglycerides & Metabolic Syndrome • Most prevalent: Hyperglycemia, BP, TG • Male trends • Prevalence & odds increase w/ age • prevalence of all factors increased as muscle decreased

  32. Discussion: Sedentary Behavior • MONW Overlooked • Physical activity inversely related to metabolic syndrome • Wildman et al. 46.6% MONW no physical activity • Conus et al. MONW greater portion of time watching TV • Ford et al. prevalence of metabolic syndrome increased w/ TV time • Importance of physical activity regardless of BMI

  33. Limitations • Excluded multiple imputed subjects • Controlling for fasted subjects decreased sample sizes • Separating by age decreased sample sizes in tertiles • 20-39 age category vs. 60+

  34. Questions?

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  36. , Kim NH, Baik SH, Choi DS, Choi KM. Prevalence and determinant factors of sarcopenia in patients with type 2 diabetes. Diabetes Care 2010;33;7:1497-1499. • Park SW, Goodpaster BH, Strotmeyer ES, de Rekeneire N, Harris TB, Schwartz AV, Tylavsky FA, Newman AB. Decreased muscle strength and quality in older adults with type 2 diabetes: the health, aging, and body composition study. Diabetes 2006;55:1813-1818. • Kim J. Gender differences in association between appendicular skeletal mass and cardiometabolic abnormalities in normal-weight and obese adults: Korea National Health and Nutrition Examination Survery (KNHANES) IV-3 and V-I. Asia-Pacific Journal of Public Health 2012;1:1-8. • SrikanthanP, Karlamangla AS. Relative muscle mass is inversely associated with insulin resistance and prediabetes. Findings from the Third National Health and Nutrition Examination Survey. Journal of Clinical Endocrinology and Metabolism 2011;96;9:2898-2903. • Centers for Disease Control and Prevention, National Center for Health Statistics. National Health and Nutrition Examination Survey: Technical documentation for the 1999-2004 Dual Energy X-ray Absorptiometry (DXA) multiple imputation data files. 2008. p. 3-6. • Baumgartner RN. Body Composition in Healthy Aging. Ann N Y AcadSci 2000;904:437-448. • Kim TN, Yang SJ, Yoo HJ, Lim KI, Kang HJ, Song W, Seo JA, Kim SG, Kim NH, Baik SH, Choi DS, Choi KM. Prevalence of sarcopenia and sarcopenic obesity in Korean adults: the Korean sarcopenic obesity study. International Journal of Obesity 2009;33;885-892. • Parikh RM, Mohan V. Changing definitions of metabolic syndrome. Indian Journal of Endocrinology and Metabolism 2012;16;1:7-12. • Dominguez LJ. The cardiometabolic syndrome and sarcopenic obesity in older persons. The Journal of cardiometabolic Syndrome 2007:183-189. • ConusF, Rabasa-Lhoret R, Réronnet F. Characteristics of metabolically obese normal-weight (MONW) subjects. ApplPhysiolNutrMetab 2007;32:4-12. • Hamilton MT, Hamilton DG, Zderie TW. Role of low energy expenditure and sitting in obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease. Diabetes 2007;56:2655-2667. • Wildman RP, Muntner P, Reynolds K, McGinn AP, Rajpathak S, Wylie-Rosett J, Sowers MR. The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering. Arch Intern Med 2008;168;15:1617-1624. • McAuleyPA, Artero EG, Sui X, Lee D, Church TS, Lavie CJ, Myers JN, España-Romero V, Blair SN. The obesity paradox, cardiorespiratory fitness, and coronary heart disease. Mayo Clinic Proceedings 2012;87;5:443-451. • Kokkinos P, Myers J, Faselis C, Doumas M, Kheirbek R, Nylen E. BMI-mortality paradox and fitness in African American and Caucasian men with type 2 diabetes. Diabetes Care 2012;35:1021-1027.

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