Body-fat indicators and kidney function decline in older post-myocardial infarction patients: The Alpha Omega Cohort Study

Kevin Esmeijer, Johanna M Geleijnse, Erik J Giltay, Theo Stijnen, Friedo W Dekker, Johan W de Fijter, Daan Kromhout, Ellen K Hoogeveen, Kevin Esmeijer, Johanna M Geleijnse, Erik J Giltay, Theo Stijnen, Friedo W Dekker, Johan W de Fijter, Daan Kromhout, Ellen K Hoogeveen

Abstract

Background Obesity increases risk of hypertension and diabetes, the leading causes of end-stage renal disease. The effect of obesity on kidney function decline in stable post-myocardial infarction patients is poorly documented. This relation was investigated in a large cohort of older post-myocardial infarction patients. Design Data were analysed from 2410 post-myocardial infarction patients in the Alpha Omega Trial, aged 60-80 years receiving optimal pharmacotherapy treatment (79% men, 18% diabetes). Methods Cystatin C based estimated glomerular filtration rate (eGFRcysC) was calculated at baseline and after 41 months, using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Obesity was defined as body mass index ≥ 30 kg/m2 and high waist circumference as ≥102 and ≥88 cm for men and women. The relation between body mass index, waist circumference and annual eGFRcysC decline was evaluated by linear regression. Results At baseline, mean (standard deviation) eGFRcysC was 81.5 (19.6) ml/min/1.73 m2, 23% of all patients were obese. After multivariable adjustment, the annual mean (95% confidence interval) eGFRcysC decline in men and women was -1.45 (-1.59 to -1.31) and -0.92 (-1.20 to -0.63) ml/min/1.73 m2, respectively ( p = 0.001). Obese versus non-obese patients and patients with high versus normal waist circumference experienced greater annual eGFRcysC decline. Men and women showed an additional annual eGFRcysC decline of -0.35 (-0.56 to -0.14) and -0.21 (-0.55 to 0.14) ml/min/1.73 m2 per 5 kg/m2 body mass index increment ( p for interaction 0.3). Conclusions High compared to normal body mass index or waist circumference were associated with more rapid kidney function decline in older stable post-myocardial infarction patients receiving optimal drug therapy.

Trial registration: ClinicalTrials.gov NCT03192410.

Keywords: Obesity; cardiovascular disease; kidney function; risk factors.

Figures

Figure 1.
Figure 1.
(a) Association between body mass index (BMI) and (b) waist circumference (WC) and annual kidney function decline for men and women. Linear regression coefficients for annual kidney function decline according to BMI or WC were modelled by separate restricted cubic splines. Patients with extreme values of BMI (2 (n = 22, 0.9%) and > 40 kg/m2 (n = 11, 0.5%)), or WC (<70 for women, <80 for men with BMI < 20 kg/m2 (n = 2 and n = 1) and >130 cm (n = 18)) were excluded. The model was adjusted for age, treatment group and current smoking. eGFRcysC: cystatin C based estimated glomerular filtration rate.

References

    1. World Health Organization. Obesity: Preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000; 894: 839–868.
    1. Grubbs V, Lin F, Vittinghoff E, et al. Body mass index and early kidney function decline in young adults: A longitudinal analysis of the CARDIA (Coronary Artery Risk Development in Young Adults) study. Am J Kidney Dis 2014; 63: 590–597.
    1. Lim CC, Teo BW, Ong PG, et al. Chronic kidney disease, cardiovascular disease and mortality: A prospective cohort study in a multi-ethnic Asian population. Eur J Prev Cardiol 2015; 22: 1018–1026.
    1. Hoogeveen EK, Geleijnse JM, Giltay EJ, et al. Kidney function and specific mortality in 60–80 years old post-myocardial infarction patients: A 10-year follow-up study. PLoS One 2017; 12: e0171868– e0171868.
    1. Eijkelkamp WB, de Graeff PA, van Veldhuisen DJ, et al. Effect of first myocardial ischemic event on renal function. Am J Cardiol 2007; 100: 7–12.
    1. Holzmann MJ, Carlsson AC, Hammar N, et al. Chronic kidney disease and 10-year risk of cardiovascular death. Eur J Prev Cardiol 2016; 23: 1187–1194.
    1. Bavbek N, Isik B, Kargili A, et al. Association of obesity with inflammation in occult chronic kidney disease. J Nephrol 2008; 21: 761–767.
    1. Tomaszewski M, Charchar FJ, Maric C, et al. Glomerular hyperfiltration: A new marker of metabolic risk. Kidney Int 2007; 71: 816–821.
    1. Lu JL, Kalantar-Zadeh K, Ma JZ, et al. Association of body mass index with outcomes in patients with CKD. J Am Soc Nephrol 2014; 25: 2088–2096.
    1. Lu JL, Molnar MZ, Naseer A, et al. Association of age and BMI with kidney function and mortality: A cohort study. Lancet Diabetes Endocrinol 2015; 3: 704–714.
    1. KDIGO Kidney disease – improving global outcomes: KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int 2013; 3: 18–23.
    1. Kromhout D, Giltay EJ, Geleijnse JM, et al. n-3 Fatty acids and cardiovascular events after myocardial infarction. N Engl J Med 2010; 363: 2015–2026.
    1. Inker LA, Schmid CH, Tighiouart H, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012; 367: 20–29.
    1. Hoogeveen EK, Geleijnse JM, Kromhout D, et al. Effect of omega-3 fatty acids on kidney function after myocardial infarction: The Alpha Omega Trial. Clin J Am Soc Nephrol 2014; 9: 1676–1683.
    1. Hoogeveen EK, Geleijnse JM, Kromhout D, et al. No effect of n-3 fatty acids on high-sensitivity C-reactive protein after myocardial infarction: The Alpha Omega Trial. Eur J Prev Cardiol 2014; 21: 1429–1436.
    1. Bozeman SR, Hoaglin DC, Burton TM, et al. Predicting waist circumference from body mass index. BMC Med Res Methodol 2012; 12: 115– 115.
    1. Harrell FJ. Regression modelling strategies: With applications to linear models, logistic regression, and survival analysis, New York: Springer Science + Business Media, 2001.
    1. Glymour MM, Weuve J, Berkman LF, et al. When is baseline adjustment useful in analyses of change? an example with education and cognitive change. Am J Epidemiol 2005; 162: 267–278.
    1. Shlipak MG, Katz R, Kestenbaum B, et al. Rate of kidney function decline in older adults: A comparison using creatinine and cystatin C. Am J Nephrol 2009; 30: 171–178.
    1. Turin TC, Jun M, James MT, et al. Magnitude of rate of change in kidney function and future risk of cardiovascular events. Int J Cardiol 2016; 202: 657–665.
    1. Silverwood RJ, Pierce M, Thomas C, et al. Association between younger age when first overweight and increased risk for CKD. J Am Soc Nephrol 2013; 24: 813–821.
    1. Bolignano D, Zoccali C. Effects of weight loss on renal function in obese CKD patients: A systematic review. Nephrol Dial Transplant 2013; 28: iv82–iv98.
    1. Wang Y, Chen X, Song Y, et al. Association between obesity and kidney disease: A systematic review and meta-analysis. Kidney Int 2008; 73: 19–33.
    1. Gierach M, Gierach J, Ewertowska M, et al. Correlation between body mass index and waist circumference in patients with metabolic syndrome. ISRN Endocrinol 2014; 2014: 514589–514589.
    1. Malkina A, Katz R, Shlipak MG, et al. Association of obesity and kidney function decline among non-diabetic adults with eGFR > 60 ml/min/1.73 m2: Results from the Multi-Ethnic Study of Atherosclerosis (MESA). Open J Endocr Metab Dis 2013; 3: 103–112.
    1. Flegal KM, Graubard BI, Williamson DF, et al. Excess deaths associated with underweight, overweight, and obesity. JAMA 2005; 293: 1861–1867.
    1. Gupta J, Mitra N, Kanetsky PA, et al. Association between albuminuria, kidney function, and inflammatory biomarker profile in CKD in CRIC. Clin J Am Soc Nephrol 2012; 7: 1938–1946.
    1. Kwong YT, Stevens LA, Selvin E, et al. Imprecision of urinary iothalamate clearance as a gold-standard measure of GFR decreases the diagnostic accuracy of kidney function estimating equations. Am J Kidney Dis 2010; 56: 39–49.
    1. Rosolowsky ET, Niewczas MA, Ficociello LH, et al. Between hyperfiltration and impairment: Demystifying early renal functional changes in diabetic nephropathy. Diabetes Res Clin Pract 2008; 82: S46–S53.

Source: PubMed

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