Validation of a single factor representing the indicators of metabolic syndrome as a continuous measure of metabolic load and its association with health and cognitive function

PLoS ONE

Volumn 13, Issue 12, 2018, Pages

  Düzel, Sandra ^a   Buchmann, Nikolaus ^b   Drewelies, Johanna ^c   Gerstorf, Denis ^c   Lindenberger, Ulman ^a   Steinhagen Thiessen, Elisabeth ^b   Norman, Kristina ^b,d   Demuth, Ilja ^b  

^a MAX PLANCK INSTITUTE FOR HUMAN DEVELOPMENT   (Germany)

^b CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^c HUMBOLDT UNIVERSITY   (Germany)

^d GERMAN INSTITUTE OF HUMAN NUTRITION   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGE; AGED; ARTICLE; CLINICAL ASSESSMENT; COGNITION; COMPARATIVE STUDY; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; ESTIMATED GLOMERULAR FILTRATION RATE; FEMALE; FORCED EXPIRATORY VOLUME; GERMANY; GRIP STRENGTH; HEALTH; HUMAN; MALE; METABOLIC LOAD; METABOLIC PARAMETERS; METABOLIC SYNDROME X; MORBIDITY; OBSERVATIONAL STUDY; OUTCOME ASSESSMENT; RISK FACTOR; SEX DIFFERENCE; STRUCTURAL EQUATION MODELING; TREATMENT PLANNING; VALIDATION PROCESS; GLOMERULUS FILTRATION RATE; HAND STRENGTH; LUNG; METABOLISM; PATHOPHYSIOLOGY; PHYSIOLOGY; THEORETICAL MODEL;

AGED; COGNITION; FEMALE; GLOMERULAR FILTRATION RATE; HAND STRENGTH; HUMANS; LUNG; MALE; METABOLIC SYNDROME; MODELS, THEORETICAL; RISK FACTORS;

EID: 85058482661     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0208231     Document Type: Article

References (58)

1. Alberti K, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. (2009) Harmonizing the metabolic syndrome a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity. Circulation 120: 1640–1645. https://doi.org/10.1161/CIRCULATIONAHA.109.192644 PMID: 19805654
2. Isomaa B, Almgren P, Tuomi T, Forsén B, Lahti K, et al. (2001) Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes care 24: 683–689. PMID: 11315831
3. Strange RC, Shipman KE, Ramachandran S (2015) Metabolic syndrome: A review of the role of vitamin D in mediating susceptibility and outcome. World journal of diabetes 6: 896. https://doi.org/10.4239/wjd.v6.i7.896 PMID: 26185598
4. Eckstein N, Buchmann N, Demuth I, Steinhagen-Thiessen E, Nikolov J, et al. (2016) Association between metabolic syndrome and bone mineral density-data from the Berlin Aging Study II (BASE-II). Gerontology 62: 337–344. https://doi.org/10.1159/000434678 PMID: 26821158
5. Sayer AA, Syddall HE, Dennison EM, Martin HJ, Phillips DIW, et al. (2007) The relationship between grip strength and features of the metabolic syndrome: findings from the Hertfordshire Cohort Study. QJM: monthly journal of the Association of Physicians 100: 707–713. PMID: 17951315
6. Song H, Wang X, Cai Q, Ding W, Huang S, et al. (2014) Association of metabolic syndrome with decreased glomerular filtration rate among 75,468 Chinese adults: a cross-sectional study. PLoS One 9: e113450. https://doi.org/10.1371/journal.pone.0113450 PMID: 25415451
7. Ford ES, Cunningham TJ, Mercado CI (2014) Lung function and metabolic syndrome: Findings of National Health and Nutrition Examination Survey 2007–2010. J Diabetes 6: 603–613. https://doi.org/10.1111/1753-0407.12136 PMID: 26677470
8. Buchmann N, Norman K, Steinhagen-Thiessen E, Demuth I, Eckardt R (2015) Lung function in elderly subjects with metabolic syndrome and type II diabetes. Zeitschrift für Gerontologie und Geria-trie: 1–9.
9. Rantanen T, Guralnik JM, Foley D, Masaki K, Leveille S, Curb JD, et al. (1999) Midlife hand grip strength as a predictor of old age disability. JAMA 281: 558–560. PMID: 10022113
10. Norman K, Stobäus N, Gonzalez MC, Schulzke J-D, Pirlich M (2011) Hand grip strength: outcome predictor and marker of nutritional status. Clinical nutrition 30: 135–142. https://doi.org/10.1016/j.clnu.2010.09.010 PMID: 21035927
11. Bohannon RW (2008) Hand-Grip Dynamometry Predicts Future Outcomes in Aging Adults. Journal of Geriatric Physical Therapy 31: 3–10. PMID: 18489802
12. Magnussen C, Ojeda FM, Rzayeva N, Zeller T, Sinning CR, et al. (2017) FEV1 and FVC predict all-cause mortality independent of cardiac function—Results from the population-based Gutenberg Health Study. Int J Cardiol 234: 64–68. https://doi.org/10.1016/j.ijcard.2017.02.012 PMID: 28214081
13. Dodd JW (2015) Lung disease as a determinant of cognitive decline and dementia. Alzheimer’s Research & Therapy 7: 32.
14. Yates KF, Sweat V, Yau PL, Turchiano MM, Convit A (2012) Impact of Metabolic Syndrome on Cognition and Brain: A Selected Review of the Literature. Arteriosclerosis, Thrombosis, and Vascular Biology 32: 2060–2067. https://doi.org/10.1161/ATVBAHA.112.252759 PMID: 22895667
15. Taylor VH, MacQueen GM (2007) Cognitive dysfunction associated with metabolic syndrome. Obes Rev 8: 409–418. https://doi.org/10.1111/j.1467-789X.2007.00401.x PMID: 17716298
16. Buchmann N, Norman K, Demuth I, Steinhagen-Thiessen E Surrogatmarker der Insulinresistenz bei Stu-dienteilnehmern mit metabolischem Syndrom–Daten der Berliner Altersstudie II. LaboratoriumsMedizin.
17. Kaur J (2014) A Comprehensive Review on Metabolic Syndrome. Cardiology Research and Practice 2014: 21.
18. Juutilainen A, Kortelainen S, Lehto S, Ronnemaa T, Pyorala K, et al. (2004) Gender difference in the impact of type 2 diabetes on coronary heart disease risk. Diabetes Care 27: 2898–2904. 1. Alberti K, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity. Circulation. 2009;120(16):1640–5. PMID: 15562204
19. Mendelsohn ME, Karas RH. Molecular and cellular basis of cardiovascular gender differences. Science. 2005; 308(5728):1583–7. https://doi.org/10.1126/science.1112062 PMID: 15947175.
20. Li C, Ford ES. Is there a single underlying factor for the metabolic syndrome in adolescents? A confirmatory factor analysis. Diabetes Care. 2007; 30(6):1556–61. https://doi.org/10.2337/dc06-2481 PMID: 17363752
21. Shen B-J, Todaro JF, Niaura R, McCaffery JM, Zhang J, Spiro A Iii, et al. Are Metabolic Risk Factors One Unified Syndrome? Modeling the Structure of the Metabolic Syndrome X. American Journal of Epidemiology. 2003; 157(8):701–11. https://doi.org/10.1093/aje/kwg045 PMID: 12697574
22. Gerstorf D, Bertram L, Lindenberger U, Pawelec G, Demuth I, Steinhagen-Thiessen E, et al. Editorial. Gerontology. 2016; 62(3):311–5. https://doi.org/10.1159/000441495 PMID: 26820471
23. Bertram L, Böckenhoff A, Demuth I, Düzel S, Eckardt R, Li S-C, et al. Cohort profile: the Berlin aging study II (BASE-II). International journal of epidemiology. 2013; 43(3):703–12. https://doi.org/10.1093/ije/dyt018 PMID: 23505255
24. Organization WH. Screening for Type 2 diabetes. Report of a World Health Organization and International Diabetes Federation meeting. 2003. Geneva, Switzerland. World Health Organization http://www.who.int/diabetes/publications/en/ Accessed Mar. 2012;3.
25. Taekema DG, Gussekloo J, Maier AB, Westendorp RG, de Craen AJ. Handgrip strength as a predictor of functional, psychological and social health. A prospective population-based study among the oldest old. Age Ageing. 2010; 39(3):331–7. https://doi.org/10.1093/ageing/afq022 PMID: 20219767.
26. Infurna FJ, Gerstorf D. Linking perceived control, physical activity, and biological health to memory change. Psychology and aging. 2013; 28(4):1147. https://doi.org/10.1037/a0033327 PMID: 24364415
27. Hill K, Goldstein RS, Guyatt GH, Blouin M, Tan WC, Davis LL, et al. Prevalence and underdiagnosis of chronic obstructive pulmonary disease among patients at risk in primary care. Cmaj. 2010; 182(7):673–8. Epub 2010/04/08. https://doi.org/10.1503/cmaj.091784 PMID: 20371646
28. Pottel H, Hoste L, Dubourg L, Ebert N, Schaeffner E, Eriksen BO, et al. An estimated glomerular filtration rate equation for the full age spectrum. Nephrology, dialysis, transplantation: official publication of the European Dialysis and Transplant Association—European Renal Association. 2016; 31(5):798–806. Epub 2016/03/05. https://doi.org/10.1093/ndt/gfv454 PMID: 26932693.
29. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of chronic diseases. 1987; 40(5):373–83. PMID: 3558716
30. Meyer A, Salewsky B, Spira D, Steinhagen-Thiessen E, Norman K, Demuth I. Leukocyte telomere length is related to appendicular lean mass: cross-sectional data from the Berlin Aging Study II (BASE-II). The American journal of clinical nutrition. 2016; 103(1):178–83. https://doi.org/10.3945/ajcn.115. 116806 PMID: 26675777
31. Little TD, Lindenberger U, Nesselroade JR. On selecting indicators for multivariate measurement and modeling with latent variables: When" good" indicators are bad and" bad" indicators are good. Psychological Methods. 1999; 4(2):192.
32. Jackson DL, Gillaspy JA, Purc-Stephenson R. Reporting practices in confirmatory factor analysis: an overview and some recommendations. Psychol Methods. 2009; 14(1):6–23. https://doi.org/10.1037/ a0014694 PMID: 19271845.
33. Schermelleh-Engel K, Kerwer M, Klein AG. Evaluation of model fit in nonlinear multilevel structural equation modeling. Frontiers in Psychology. 2014; 5:181. https://doi.org/10.3389/fpsyg.2014.00181PMID: 24624110
34. Lt Hu, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal. 1999; 6(1):1–55.
35. Meredith W. Measurement invariance, factor analysis and factorial invariance. Psychometrika. 1993; 58(4):525–43. https://doi.org/10.1007/bf02294825
36. Cheung GW, Rensvold RB. Evaluating goodness-of-fit indexes for testing measurement invariance. Structural equation modeling. 2002; 9(2):233–55.
37. Buchmann N, Nikolov J, Spira D, Demuth I, Steinhagen-Thiessen E, Eckardt R, et al. Identifying Sarco-penia in Metabolic Syndrome: Data from the Berlin Aging Study II. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2016; 71(2):265–72.
38. Meigs JB. Invited commentary: insulin resistance syndrome? Syndrome X? Multiple metabolic syndrome? A syndrome at all? Factor analysis reveals patterns in the fabric of correlated metabolic risk factors. Am J Epidemiol. 2000; 152(10):908–11; discussion 12. Epub 2000/11/25. PMID: 11092432.
39. Hanley AJ, Karter AJ, Festa A, D’Agostino R, Wagenknecht LE, Savage P, et al. Factor Analysis of Metabolic Syndrome Using Directly Measured Insulin Sensitivity The Insulin Resistance Atherosclerosis Study. Diabetes. 2002; 51(8):2642–7. PMID: 12145182
40. Abbasi F, Kohli P, Reaven GM, Knowles JW. Hypertriglyceridemia: A simple approach to identify insulin resistance and enhanced cardio-metabolic risk in patients with prediabetes. diabetes research and clinical practice. 2016; 120:156–61. https://doi.org/10.1016/j.diabres.2016.07.024 PMID: 27565692
41. Morigny P, Houssier M, Mouisel E, Langin D. Adipocyte lipolysis and insulin resistance. Biochimie. 2016; 125:259–66. https://doi.org/10.1016/j.biochi.2015.10.024 PMID: 26542285
42. Riccardi G, Giacco R, Rivellese A. Dietary fat, insulin sensitivity and the metabolic syndrome. Clinical nutrition. 2004; 23(4):447–56. https://doi.org/10.1016/j.clnu.2004.02.006 PMID: 15297079
43. Boden G, Shulman G. Free fatty acids in obesity and type 2 diabetes: defining their role in the development of insulin resistance and β-cell dysfunction. European journal of clinical investigation. 2002; 32:14–23. PMID: 12028371
44. Cassis LA, Police SB, Yiannikouris F, Thatcher SE. Local adipose tissue renin-angiotensin system. Curr Hypertens Rep. 2008; 10(2):93–8. PMID: 18474174.
45. Viitasalo A, Lakka TA, Laaksonen DE, Savonen K, Lakka H-M, Hassinen M, et al. Validation of metabolic syndrome score by confirmatory factor analysis in children and adults and prediction of cardiometabolic outcomes in adults. Diabetologia. 2014; 57(5):940–9. https://doi.org/10.1007/s00125-014-3172-5 PMID: 24463933
46. Llabre MM, Arguelles W, Schneiderman N, Gallo LC, Daviglus ML, Chambers EC, et al. Do all components of the metabolic syndrome cluster together in U.S. Hispanics/Latinos? Results from the Hispanic Community Health study/Study of Latinos. Annals of Epidemiology. 2015; 25(7):480–5. https://doi.org/10.1016/j.annepidem.2015.02.010 PMID: 25818844
47. Fitzpatrick SL, Lai BS, Brancati FL, Golden SH, Hill-Briggs F. Metabolic syndrome risk profiles among African American adolescents: national health and nutrition examination survey, 2003–2010. Diabetes Care. 2013; 36(2):436–42. Epub 2012/10/25. https://doi.org/10.2337/dc12-0828 PMID: 23093663
48. Esler M, Hastings J, Lambert G, Kaye D, Jennings G, Seals DR. The influence of aging on the human sympathetic nervous system and brain norepinephrine turnover. American journal of physiology Regulatory, integrative and comparative physiology. 2002; 282(3):R909–16. Epub 2002/02/08. https://doi.org/10.1152/ajpregu.00335.2001 PMID: 11832414.
49. Yoon HE, Choi BS. The renin-angiotensin system and aging in the kidney. The Korean Journal of Internal Medicine. 2014; 29(3):291–5. https://doi.org/10.3904/kjim.2014.29.3.291 PMID: 24851061
50. Vasconcellos F, Seabra A, Katzmarzyk PT, Kraemer-Aguiar LG, Bouskela E, Farinatti P. Physical Activity in Overweight and Obese Adolescents: Systematic Review of the Effects on Physical Fitness Components and Cardiovascular Risk Factors. Sports Medicine. 2014; 44(8):1139–52. https://doi.org/10.1007/s40279-014-0193-7 PMID: 24743931
51. Leone N, Courbon D, Thomas F, Bean K, Jégo B, Leynaert B, et al. Lung function impairment and metabolic syndrome: the critical role of abdominal obesity. American journal of respiratory and critical care medicine. 2009; 179(6):509–16. https://doi.org/10.1164/rccm.200807-1195OC PMID: 19136371
52. Yaffe K. Metabolic syndrome and cognitive disorders: is the sum greater than its parts? Alzheimer Disease & Associated Disorders. 2007; 21(2):167–71.
53. Tournoy J, Lee DM, Pendleton N, O’Neill TW, O’Connor DB, Bartfai G, et al. Association of cognitive performance with the metabolic syndrome and with glycaemia in middle-aged and older European men: the European Male Ageing Study. Diabetes/metabolism research and reviews. 2010; 26(8):668–76. https://doi.org/10.1002/dmrr.1144 PMID: 21043047
54. Schuur M, Henneman P, Van Swieten J, Zillikens M, de Koning I, Janssens A, et al. Insulin-resistance and metabolic syndrome are related to executive function in women in a large family-based study. European journal of epidemiology. 2010; 25(8):561–8. https://doi.org/10.1007/s10654-010-9476-y PMID: 20585974
55. Haley AP, Gonzales MM, Tarumi T, Miles SC, Goudarzi K, Tanaka H. Elevated cerebral glutamate and myo-inositol levels in cognitively normal middle-aged adults with metabolic syndrome. Metabolic brain disease. 2010; 25(4):397–405. https://doi.org/10.1007/s11011-010-9221-y PMID: 21063759
56. Hassenstab JJ, Sweat V, Bruehl H, Convit A. Metabolic syndrome is associated with learning and recall impairment in middle age. Dementia and geriatric cognitive disorders. 2010; 29(4):356–62. https://doi.org/10.1159/000296071 PMID: 20424454
57. Cavalieri M, Ropele S, Petrovic K, Pluta-Fuerst A, Homayoon N, Enzinger C, et al. Metabolic syndrome, brain magnetic resonance imaging, and cognition. Diabetes Care. 2010; 33(12):2489–95. https://doi.org/10.2337/dc10-0851 PMID: 20852031
58. Dik MG, Jonker C, Comijs HC, Deeg DJ, Kok A, Yaffe K, et al. Contribution of metabolic syndrome components to cognition in older individuals. Diabetes care. 2007; 30(10):2655–60. https://doi.org/10.2337/ dc06-1190 PMID: 17563341