Optimal Adiposity Measurement and Risk Stratification in Established Ischaemic Stroke

Olive Lennon, Catherine Blake

School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Ireland.

DOI: 10.4236/wjcd.2014.413077                

Abstract

Background: Prevention strategies post-stroke should target risk factor reduction which includes consideration of weight, diet and lipoprotein profiles. Limited data informs the optimal adiposity measurement post-stroke to target those at highest recurrent risk. This study aims to identify adiposity measurement/s post-stroke that best predict cardiovascular and co-morbid risk. Subjects and Methods: 142 stroke patients (100 males, 42 females; mean age 63 years) participated. Adiposity and metabolic profiles included BMI, waist circumference, waist to height ratio (WHR), triglyceride levels and hypertriglyceridemic waist. The predictive ability of these measures with indices of cardiovascular risk (Cardiovascular Risk Score) and co-morbidity (Charlson’s co-morbidity index) were examined. Results: In hierarchical multiple regression models, age and gender controlled, waist (p = 0.002), triglyceride levels (p = 0.006), BMI and WHR (p = 0.014), uniquely and significantly contributed to the variance in cardiovascular risk, in their models. Only one combination of measures (waist and triglyceride levels) improved the predictive ability of waist in cardiovascular risk stratification (p = 0.001). In men, waist (p = 0.013) and in women triglyceride levels (p = 0.012) performed as the best predictors of cardiovascular risk respectively. No combination of measures was superior to triglyceride levels in women or waist circumference measures in men in predicting cardiovascular risk. With Charlson’s co-morbidity index as the dependent variable, triglyceride levels significantly contributed to variance of the model with age and gender influences controlled (p = 0.047). No combination of measures improved the predictive ability of triglyceride levels for co-morbidity. Conclusion: Waist circumference and triglyceride levels should form a minimum dataset for adiposity when considering cardiovascular and comorbid risk post-stroke.

Keywords

Stroke, Adiposity, Obesity, Abdominal, Measurement, Risk Factors

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Langhorne, P., Williams, B., Gilchrist, W. and Howie, K. (1993) Do Stroke Units Save Lives? The Lancet, 342, 395-398. http://dx.doi.org/10.1016/0140-6736(93)92813-9
[2]	Albers, G.W. (2010) Stroke: More Protection for Patients with Atrial Fibrillation. The Lancet Neurology, 9, 2-4. http://dx.doi.org/10.1016/S1474-4422(09)70306-0
[3]	Bennett, K., Kabir, Z., Unal, B., Shelley, E., Critchley, J., Perry, I., et al. (2006) Explaining the Recent Decrease in Coronary Heart Disease Mortality Rates in Ireland, 1985-2000. Journal of Epidemiology and Community Health, 60, 322-327. http://dx.doi.org/10.1136/jech.2005.038638
[4]	Touze, E., Coste, J., Voicu, M., Kansao, J., Masmoudi, R., Doumenc, B., et al. (2008) Importance of In-Hospital Initiation of Therapies and Therapeutic Inertia in Secondary Stroke Prevention—IMplementation of Prevention after a Cerebro-Vascular evenT (IMPACT) Study. Stroke, 39, 1834-1843. http://dx.doi.org/10.1161/STROKEAHA.107.503094
[5]	Hackam, D.G. and Spence, J.D. (2007) Combining Multiple Approaches for the Secondary Prevention of Vascular Events after Stroke: A Quantitative Modeling Study. Stroke, 38, 1881-1885. http://dx.doi.org/10.1161/STROKEAHA.106.475525
[6]	Sacco, R., Shi, T., Zamanillo, M. and Kargman, D. (1994) Predictors of Mortality and Recurrence after Hospitalized Cerebral In-Farction in an Urban Community: The Northern Manhattan Stroke Study. Neurology, 44, 626-34. http://dx.doi.org/10.1212/WNL.44.4.626
[7]	Hankey, G., Jamrozik, K., Broadhurst, R., Forbes, S., Burvill, P.W., Anderson, C.S., et al. (1998) Long-Term Risk of First Recurrent Stroke in the Perth Community Stroke Study. Stroke, 29, 2491-500. http://dx.doi.org/10.1161/01.STR.29.12.2491
[8]	Petty, G., Brown Jr., R., Whisnant, J., Sicks, J., O’Fallon, W. and Wiebers, D. (1998) Survival and Recurrence after First Cerebral In-Farction: A Population-Based Study in Rochester, Minnesota, 1975 through 1989. Neurology, 50, 208. http://dx.doi.org/10.1212/WNL.50.1.208
[9]	Suk, S.-H., Sacco, R.L., Boden-Albala, B., Cheun, J.F., Pittman, J.G., Elkind, M.S., et al. (2003) Abdominal Obesity and Risk of Is-Chemic Stroke the Northern Manhattan Stroke Study. Stroke, 34, 1586-1592. http://dx.doi.org/10.1161/01.STR.0000075294.98582.2F
[10]	Chrostowska, M., Szyndler, A., Hoffmann, M. and Narkiewicz, K. (2013) Impact of Obesity on Cardiovascular Health. Best Practice & Research Clinical Endocrinology & Metabolism, 27, 147-56. http://dx.doi.org/10.1016/j.beem.2013.01.004
[11]	Cornier, M.-A., Despres, J.-P., Davis, N., Grossniklaus, D.A., Klein, S., Lamarche, B., et al. (2011) Assessing Adiposity: A Scientific Statement from the American Heart Association. Circulation, 124, 1996-2019. http://dx.doi.org/10.1161/CIR.0b013e318233bc6a
[12]	Folsom, A.R., Kaye, S.A., Sellers, T.A., Hong, C.P., Cerhan, J.R., Potter, J.D., et al. (1993) Body Fat Distribution and 5-Year Risk of Death in Older Women. JAMA: The Journal of the American Medical Association, 269, 483-487. http://dx.doi.org/10.1001/jama.269.4.483 http://dx.doi.org/10.1001/jama.1993.03500040049035
[13]	Rheaume, C., Leblanc, M.-E. and Poirier, P. (2011) Adiposity Assessment: Explaining the Association between Obesity, Hypertension and Stroke. Expert Review of Cardiovascular Therapy, 9, 1557-1564. http://dx.doi.org/10.1586/erc.11.167
[14]	Kurth, T., Gaziano, J.M., Berger, K., Kase, C.S., Rexrode, K.M., Cook, N.R., et al. (2002) Body Mass Index and the Risk of Stroke in Men. Archives of Internal Medicine, 162, 2557. http://dx.doi.org/10.1001/archinte.162.22.2557
[15]	Lu, M., Ye, W., Adami, H. and Weiderpass, E. (2006) Prospective Study of Body Size and Risk for Stroke amongst Women below Age 60. Journal of Internal Medicine, 260, 442-450. http://dx.doi.org/10.1111/j.1365-2796.2006.01706.x
[16]	Winter, Y., Rohrmann, S., Linseisen, J., Lanczik, O., Ringleb, P.A., Hebebrand, J., et al. (2008) Contribution of Obesity and Abdominal Fat Mass to Risk of Stroke and Transient Ischemic Attacks. Stroke, 39, 3145-3151. http://dx.doi.org/10.1161/STROKEAHA.108.523001
[17]	Cheal, K., Abbasi, F., Lamendola, C., McLaughlin, T., Reaven, G. and Ford, E.D. (2004) Relationship to Insulin Resistance of the Adult Treatment Panel III Diagnostic Criteria for Identification of the Metabolic Syndrome. Diabetes and Vascular Disease Research, 53, 1195-1200.
[18]	Karcher, H.-S., Holzwarth, R., Mueller, H., Ludolph, A.C., Huber, R., Kassubek, J., et al. (2013) Body Fat Distribution as a Risk Factor for Cerebrovascular Disease: An MRI-Based Body Fat Quantification Study. Cerebrovascular Diseases, 35, 341-348. http://dx.doi.org/10.1159/000348703
[19]	Chiquete, E., Ruiz-Sandoval, J.L., Murillo-Bonilla, L., León-Jiménez, C., Ruiz-Madrigal, B., Martínez-López, E., et al. (2013) Central Adiposity and Mortality after First-Ever Acute Ischemic Stroke. European Neurology, 70, 117-123. http://dx.doi.org/10.1159/000350762
[20]	Lemieux, I., Pascot, A. and Couillard, C. (2000) Hypertri-glyceridemic Waist: A Marker of the Atherogenic Metabolic Triad (Hyperinsulinemia; Hyperapolipoprotein B; Small, Dense LDL) in Men? Circulation, 102, 179-184. http://dx.doi.org/10.1161/01.CIR.102.2.179
[21]	Kahn, H. and Valdez, R. (2003) Metabolic Risks Identified by the Combination of Enlarged Waist and Elevated Triacylglycerol Concentration. The American Journal of Clinical Nutrition, 78, 928-934.
[22]	Raji, A. and Plutzky, J. (2002) Insulin Resistance, Diabetes, and Atherosclerosis: Thiazolidinediones as Therapeutic Interventions. Current Cardiology Reports, 4, 514-521. http://dx.doi.org/10.1007/s11886-002-0116-3
[23]	Hanley, A.J., Williams, K., Stern, M.P. and Haffner, S.M. (2002) Homeostasis Model Assessment of Insulin Resistance in Relation to the Incidence of Cardiovascular Disease: The San Antonio Heart Study. Diabetes Care, 25, 1177-1184. http://dx.doi.org/10.2337/diacare.25.7.1177
[24]	Tanko, L.B., Bagger, Y.Z., Alexandersen, P., Larsen, P.J. and Christiansen, C. (2003) Peripheral Adiposity Exhibits an Independent Dominant Antiatherogenic Effect in Elderly Women. Circulation, 107, 1626-1631. http://dx.doi.org/10.1161/01.CIR.0000057974.74060.68
[25]	Fisher, M. (2006) Cardiometabolic Disease: The New Challenge? Practical Diabetes International, 23, 95-97. http://dx.doi.org/10.1002/pdi.909
[26]	Thompson, W.R., Gordon, N.F. and Pescatello, L.S., American College of Sports Medicine, et al. (2010) ACSM’s Guidelines for Exercise Testing and Prescription: 2010. Lippincott Williams & Wilkins, Philadelphia.
[27]	Friedewald, W., Levy, R. and Frederickson, D. (1972) Estimation of VLDL- and LDL-Cholesterol. Clinical Chemistry, 18, 499-502.
[28]	National Institutes of Health (2001) Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). NIH Publication No. 01-3670.
[29]	Wilson, P., D’Agostino, R., Levy, D., Belanger, A., Silbershatz, H. and Kannel, W. (1998) Prediction of Coronary Heart Disease Using Risk Factor Categories. Circulation, 97, 1837-1847. http://dx.doi.org/10.1161/01.CIR.97.18.1837
[30]	Charlson, M.E., Pompei, P., Ales, K.L. and MacKenzie, C.R. (1987) A New Method of Classifying Prognostic Comorbidity in Longitudinal Studies: Development and Validation. Journal of Chronic Diseases, 40, 373-383. http://dx.doi.org/10.1016/0021-9681(87)90171-8
[31]	Franzosi, M.G. (2006) Should We Continue to Use BMI as a Cardiovascular Risk Factor? The Lancet, 368, 624-625. http://dx.doi.org/10.1016/S0140-6736(06)69222-2
[32]	Chen, M.M., Lear, S.A., Gao, M., Frohlich, J.J. and Birmingham, C.L. (2001) Intraobserver and Interobserver Reliability of Waist Circumference and the Waist to Hip Ratio. Obesity Research, 9, 651-651. http://dx.doi.org/10.1038/oby.2001.87
[33]	Cronin, O., Morris, D., Walker, P. and Golledge, J. (2013) The Association of Obesity with Cardiovascular Events in Patients with Peripheral Artery Disease. Atherosclerosis, 228, 316-323. http://dx.doi.org/10.1016/j.atherosclerosis.2013.03.002
[34]	Pouliot, M.-C., Despres, J.-P., Lemieux, S., Moorjani, S., Bouchard, C., Tremblay, A., et al. (1994) Waist Circumference and Abdominal Sagittal Diameter: Best Simple Anthropometric Indexes of Abdominal Visceral Adipose Tissue Accumulation and Related Cardiovascular Risk in Men and Women. The American Journal of Cardiology, 73, 460-468. http://dx.doi.org/10.1016/0002-9149(94)90676-9
[35]	de Koning, L., Merchant, A.T., Pogue, J. and Anand, S.S. (2007) Waist Circumference and Waist-to-Hip Ratio as Predictors of Cardiovascular Events: Meta Regression Analysis of Prospective Studies. European Heart Journal, 28, 850-856. http://dx.doi.org/10.1093/eurheartj/ehm026
[36]	Tatsumi, Y., Watanabe, M., Kokubo, Y., Nishimura, K., Higashiyama, A., Okamura, T., et al. (2013) Effect of Age on the Association between Waist-to-Height Ratio and Incidence of Cardiovascular Disease: The Suita Study. Journal of Epidemiology, 23, 351-359.
[37]	Daniel, M., Paquet, C., Kelly, S., Zang, G., Rowley, K.G., McDermott, R., et al. (2013) Hypertriglyceridemic Waist and Newly-Diagnosed Diabetes among Remote-Dwelling Indigenous Australians. Annals of Human Biology, 40, 496-504. http://dx.doi.org/10.3109/03014460.2013.806588
[38]	Chen, H.-J., Bai, C.-H., Yeh, W.-T., Chiu, H.-C. and Pan, W.-H. (2006) Influence of Metabolic Syndrome and General Obesity on the Risk of Ischemic Stroke. Stroke, 37, 1060-1064. http://dx.doi.org/10.1161/01.STR.0000206458.58142.f3
[39]	Shah, N., Huffman, M., Ning, H. and Lloyd-Jones, D. (2013) Trends in Vascular Risk Factor Treatment and Control in US Stroke Survivors. The National Health and Nutrition Examination Surveys (1999-2010). Circulation: Cardiovascular Quality and Outcomes, 6, 270-277. http://dx.doi.org/10.1161/CIRCOUTCOMES.113.000112
[40]	Tohidi, M., Mohebi, R., Cheraghi, L., Hajsheikholeslami, F., Aref, S., Nouri, S., et al. (2013) Lipid Profile Components and Incident Cerebrovascular Events versus Coronary Heart Disease; The Result of 9 Years Follow-Up in Tehran Lipid and Glucose Study. Clinical Bio-chemistry, 46, 716-721. http://dx.doi.org/10.1016/j.clinbiochem.2013.03.012
[41]	Steevens, J. (1996) Applied Multivariate Statistics for the Social Sciences. 3rd Edition, Lawrence Erblaum Associates, Mahwah, New Jersey.