Dietary glycemic index and retinal microvasculature in adults: a cross-sectional study

Natalia Sanchez-Aguadero, Rosario Alonso-Dominguez, Jose I Recio-Rodriguez, Maria C Patino-Alonso, Manuel A Gomez-Marcos, Carlos Martin-Cantera, Yolanda Schmolling-Guinovart, Luis Garcia-Ortiz, EVIDENT II Group, Natalia Sanchez-Aguadero, Rosario Alonso-Dominguez, Jose I Recio-Rodriguez, Maria C Patino-Alonso, Manuel A Gomez-Marcos, Carlos Martin-Cantera, Yolanda Schmolling-Guinovart, Luis Garcia-Ortiz, EVIDENT II Group

Abstract

Objective: To analyze the relationship between dietary glycemic index (GI) and retinal microvasculature in adults.

Methods: This was a cross-sectional study of 300 subjects from the EVIDENT II study. Dietary GI was calculated using a validated, semi-quantitative food frequency questionnaire. Retinal photographs were digitized, temporal vessels were measured in an area 0.5-1 disc diameter from the optic disc and arteriolar-venular index (AVI) was estimated with semi-automated software.

Results: AVI showed a significant difference between the tertiles of GI, after adjusting for potential confounders. The lowest AVI values were observed among subjects in the highest tertile of GI, whereas the greatest were found among those in the lowest tertile (estimated marginal mean of 0.738 vs. 0.768, p = 0.014).

Conclusions: In adults, high dietary GI implies lowering AVI values regardless of age, gender and other confounding variables.

Trial registration: Clinical Trials.gov Identifier: NCT02016014 . Registered 9 December 2013.

Keywords: Carbohydrates; Glycemic index; Microcirculation; Retinal vessels.

Figures

Fig. 1
Fig. 1
Multivariate analysis. Retinal arteriolar-venular index (AVI), retinal arteriolar caliber and retinal venular caliber by tertiles of glycemic index (GI). Model adjusted for age, gender, total energy intake, body mass index (BMI), systolic blood pressure (SBP), antihypertensive drugs, antidiabetic drugs and lipid-lowering drugs. Tertiles (T) GI: T1 (Lowest through 45.98); T2 (45.98 through 50.52); T3 (50.52 through Highest). AVI differences by tertiles of GI: p = 0.033 between T1 and T3, p = 0.031 between T2 and T3. Post-hoc contrasts were performed by the Bonferroni test

References

    1. Monro JA, Shaw M. Glycemic impact, glycemic glucose equivalents, glycemic index, and glycemic load: definitions, distinctions, and implications. Am J Clin Nutr. 2008;87:237s–243s.
    1. Ma XY, Liu JP, Song ZY. Glycemic load, glycemic index and risk of cardiovascular diseases: meta-analyses of prospective studies. Atherosclerosis. 2012;223:491–496. doi: 10.1016/j.atherosclerosis.2012.05.028.
    1. Mitchell P, Wang JJ, Wong TY, Smith W, Klein R, Leeder SR. Retinal microvascular signs and risk of stroke and stroke mortality. Neurology. 2005;65:1005–1009. doi: 10.1212/.
    1. Gopinath B, Flood VM, Wang JJ, Smith W, Rochtchina E, Louie JC, Wong TY, Brand-Miller J, Mitchell P. Carbohydrate nutrition is associated with changes in the retinal vascular structure and branching pattern in children. Am J Clin Nutr. 2012;95:1215–1222. doi: 10.3945/ajcn.111.031641.
    1. Kaushik S, Wang JJ, Wong TY, Flood V, Barclay A, Brand-Miller J, Mitchell P. Glycemic index, retinal vascular caliber, and stroke mortality. Stroke. 2009;40:206–212. doi: 10.1161/STROKEAHA.108.513812.
    1. Goldin A, Beckman JA, Schmidt AM, Creager MA. Advanced glycation end products: sparking the development of diabetic vascular injury. Circulation. 2006;114:597–605. doi: 10.1161/CIRCULATIONAHA.106.621854.
    1. Hu Y, Block G, Norkus EP, Morrow JD, Dietrich M, Hudes M. Relations of glycemic index and glycemic load with plasma oxidative stress markers. Am J Clin Nutr. 2006;84:70–76.
    1. Huffman KM, Orenduff MC, Samsa GP, Houmard JA, Kraus WE, Bales CW. Dietary carbohydrate intake and high-sensitivity C-reactive protein in at-risk women and men. Am Heart J. 2007;154:962–968. doi: 10.1016/j.ahj.2007.07.009.
    1. Recio-Rodriguez JI, Martin-Cantera C, Gonzalez-Viejo N, Gomez-Arranz A, Arietaleanizbeascoa MS, Schmolling-Guinovart Y, Maderuelo-Fernandez JA, Perez-Arechaederra D, Rodriguez-Sanchez E, Gomez-Marcos MA, Garcia-Ortiz L. Effectiveness of a smartphone application for improving healthy lifestyles, a randomized clinical trial (EVIDENT II): study protocol. BMC Public Health. 2014;14:254. doi: 10.1186/1471-2458-14-254.
    1. Martin-Moreno JM, Boyle P, Gorgojo L, Maisonneuve P, Fernandez-Rodriguez JC, Salvini S, Willett WC. Development and validation of a food frequency questionnaire in Spain. Int J Epidemiol. 1993;22:512–519. doi: 10.1093/ije/22.3.512.
    1. Garcia-Ortiz L, Recio-Rodriguez JI, Parra-Sanchez J, Gonzalez Elena LJ, Patino-Alonso MC, Agudo-Conde C, Rodriguez-Sanchez E, Gomez-Marcos MA. A new tool to assess retinal vessel caliber. Reliability and validity of measures and their relationship with cardiovascular risk. J Hypertens. 2012;30:770–777. doi: 10.1097/HJH.0b013e3283506628.
    1. Wong TY, Knudtson MD, Klein R, Klein BE, Meuer SM, Hubbard LD. Computer-assisted measurement of retinal vessel diameters in the Beaver Dam Eye study: methodology, correlation between eyes, and effect of refractive errors. Ophthalmology. 2004;111:1183–1190. doi: 10.1016/j.ophtha.2003.09.039.
    1. Ikram MK, de Jong FJ, Vingerling JR, Witteman JC, Hofman A, Breteler MM, de Jong PT. Are retinal arteriolar or venular diameters associated with markers for cardiovascular disorders? The Rotterdam study. Invest Ophthalmol Vis Sci. 2004;45:2129–2134. doi: 10.1167/iovs.03-1390.
    1. Lim LS, Cheung N, Saw SM, Yap M, Wong TY. Does diet influence the retinal microvasculature in children? Stroke. 2009;40:e473–474. doi: 10.1161/STROKEAHA.108.545616.

Source: PubMed

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