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      Impact of advanced and basic carbohydrate counting methods on metabolic control in patients with type 1 diabetes

      Author(s):   , , ,
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      Journal: Nutrition
      Publisher: Elsevier BV

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          Nonnutritive sweetener consumption in humans: effects on appetite and food intake and their putative mechanisms.

          Richard D Mattes, Barry M. Popkin (2008)
          Nonnutritive sweeteners (NNS) are ecologically novel chemosensory signaling compounds that influence ingestive processes and behavior. Only about 15% of the US population aged >2 y ingest NNS, but the incidence is increasing. These sweeteners have the potential to moderate sugar and energy intakes while maintaining diet palatability, but their use has increased in concert with BMI in the population. This association may be coincidental or causal, and either mode of directionality is plausible. A critical review of the literature suggests that the addition of NNS to non-energy-yielding products may heighten appetite, but this is not observed under the more common condition in which NNS is ingested in conjunction with other energy sources. Substitution of NNS for a nutritive sweetener generally elicits incomplete energy compensation, but evidence of long-term efficacy for weight management is not available. The addition of NNS to diets poses no benefit for weight loss or reduced weight gain without energy restriction. There are long-standing and recent concerns that inclusion of NNS in the diet promotes energy intake and contributes to obesity. Most of the purported mechanisms by which this occurs are not supported by the available evidence, although some warrant further consideration. Resolution of this important issue will require long-term randomized controlled trials.
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            Need for technological innovation in dietary assessment.

            Frances Thompson, Amy Subar, Catherine M. Loria … (2010)
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              Carbohydrate counting accuracy and blood glucose variability in adults with type 1 diabetes.

              I Strychar, J M Ekoé, H Mircescu … (2012)
              Carbohydrate counting is an established approach used by patients with type 1 diabetes to improve their glycemic control. The aims of this study were to evaluate, in real life conditions, the accuracy of meal carbohydrate estimate and its impact on glycemic variability. In this cross-sectional study, we observed the ability of 50 adults (48% women) with type 1 diabetes (age: 42.7±11.1 years); diabetes duration: 21.4±12.7 years; HbA1c: 7.2±1.2% (60±10 mmol/mol) to accurately estimate carbohydrates by analyzing 72-h food records and their corresponding 72-h blood glucose excursions using a continuous glucose monitor. The mean meal carbohydrate difference, between the patients' estimates and those assessed by a dietitian using a computerized analysis program, was 15.4±7.8 g or 20.9±9.7% of the total CHO content per meal (72.4±34.7 g per meal). Sixty-three percent of the 448 meals analyzed were underestimated. Greater differences in CHO's estimates predicted higher glycemic variability, as measured by the MAGE index and glucose standard deviation, and decreased time with glucose values between 4 and 10 mmol/L (R²=0.110, 0.114 and 0.110, respectively; P<0.05). Inaccurate carbohydrate counting is frequent and associated with higher daily blood glucose variability in adults with type 1 diabetes. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
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                Author and article information

                Journal
                Title: Nutrition
                Abbreviated Title: Nutrition
                Publisher: Elsevier BV
                ISSN (Print): 08999007
                Publication date Created: March 2014
                Publication date (Print): March 2014
                Volume: 30
                Issue: 3
                Pages: 286-290
                Article
                DOI: 10.1016/j.nut.2013.08.010
                PubMed ID: 24360781
                SO-VID: a6643c44-3b37-4e1a-9f4a-4317a08268ac
                Copyright © © 2014
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                http://www.elsevier.com/tdm/userlicense/1.0/

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