Nicole J Kellow1,2,3, Melinda T Coughlan4,5, Christopher M Reid5. 1. Glycation, Nutrition and Metabolism Laboratory, Baker IDI Heart and Diabetes Institute, Melbourne, Australia. nicole.kellow@monash.edu. 2. Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia. nicole.kellow@monash.edu. 3. Be Active Sleep and Eat (BASE) Facility, Department of Nutrition, Dietetics and Food, Monash University, Level 1, 264 Ferntree Gully Road, Notting Hill, VIC, 3168, Australia. nicole.kellow@monash.edu. 4. Glycation, Nutrition and Metabolism Laboratory, Baker IDI Heart and Diabetes Institute, Melbourne, Australia. 5. Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Abstract
PURPOSE: Advanced glycation endproducts (AGEs) are produced endogenously and also enter the body during the consumption of AGEs present in heat-processed food. It is unknown whether AGEs of dietary origin accumulate within the body of healthy individuals. AGEs can deposit within skin tissue long-term by crosslinking extracellular matrix proteins. The fluorescent nature of many AGEs enables their detection within the skin by non-invasively measuring skin autofluorescence (SAF). This study aimed to identify habitual dietary and lifestyle behaviours cross-sectionally associated with SAF in an adult population sample. METHODS: 251 Healthy adult volunteers completed validated food frequency and physical activity questionnaires. Waist circumference, BMI, blood pressure and blood glucose was also measured. SAF was measured using an AGE Reader. RESULTS: Significant positive correlations were found between SAF and chronological age (r = 0.63, P < 0.001), waist circumference (r = 0.28, P < 0.01), body weight (r = 0.24, P < 0.05), BMI (r = 0.23, P < 0.05) and consumption of meat and meat products (r = 0.22, P < 0.05). A negative correlation was found between SAF and cereal consumption (r = -0.21, P < 0.05). Cigarette smokers also had a significantly higher SAF than non-smokers (2.4 vs 2.0 U, P < 0.05). Regression analysis identified age, cigarette smoking, waist circumference and intake of meat products as significant predictors of SAF. The regression model explained 48% of the variation in SAF. CONCLUSIONS: Age, cigarette smoking, waist circumference and dietary consumption of meat/meat products were positively associated with SAF in this sample. Further research is required to determine whether frequent consumption of foods containing large quantities of dietary AGEs contribute to pathological disease processes in healthy individuals.
PURPOSE: Advanced glycation endproducts (AGEs) are produced endogenously and also enter the body during the consumption of AGEs present in heat-processed food. It is unknown whether AGEs of dietary origin accumulate within the body of healthy individuals. AGEs can deposit within skin tissue long-term by crosslinking extracellular matrix proteins. The fluorescent nature of many AGEs enables their detection within the skin by non-invasively measuring skin autofluorescence (SAF). This study aimed to identify habitual dietary and lifestyle behaviours cross-sectionally associated with SAF in an adult population sample. METHODS: 251 Healthy adult volunteers completed validated food frequency and physical activity questionnaires. Waist circumference, BMI, blood pressure and blood glucose was also measured. SAF was measured using an AGE Reader. RESULTS: Significant positive correlations were found between SAF and chronological age (r = 0.63, P < 0.001), waist circumference (r = 0.28, P < 0.01), body weight (r = 0.24, P < 0.05), BMI (r = 0.23, P < 0.05) and consumption of meat and meat products (r = 0.22, P < 0.05). A negative correlation was found between SAF and cereal consumption (r = -0.21, P < 0.05). Cigarette smokers also had a significantly higher SAF than non-smokers (2.4 vs 2.0 U, P < 0.05). Regression analysis identified age, cigarette smoking, waist circumference and intake of meat products as significant predictors of SAF. The regression model explained 48% of the variation in SAF. CONCLUSIONS: Age, cigarette smoking, waist circumference and dietary consumption of meat/meat products were positively associated with SAF in this sample. Further research is required to determine whether frequent consumption of foods containing large quantities of dietary AGEs contribute to pathological disease processes in healthy individuals.
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