Skip to main content

Does sucrose intake affect antropometric variables, glycemia, lipemia and C-reactive protein in subjects with type 1 diabetes?: a controlled-trial

Abstract

Background

It is unclear if the sugar intake may affect metabolic parameters in individuals with type 1 diabetes. Therefore, the purpose of this study was to evaluate the effects of sucrose intake in glycemic, lipemic, anthropometric variables, as well as in C-reactive protein (CRP) levels in these individuals.

Methods

Thirty-three subjects with type 1 diabetes were evaluated at baseline and 3-months after intervention. Volunteers were randomized into groups: sucrose-free (diet without sucrose) or sucrose-added (foods containing sucrose in composition). Both groups received the same macronutrient composition and used the carbohydrate counting methods. All underwent an interview and anthropometric evaluation. Blood was drawn for glycated haemoglobin, glucose, total cholesterol, HDL, and CRP measurement, and the medical charts were reviewed in all cases.

Results

At baseline, anthropometric, clinical and laboratory variables did not differ between groups, except for the triglycerides. Although at baseline triglycerides levels were higher in the sucrose-added group (p = 0.01), they did not differ between groups after the intervention (p = 0.92). After 3-months, CRP was higher in the sucrose-added than in the sucrose-free group (p = 0.04), but no further differences were found between the groups, including the insulin requirements, anthropometric variables, body composition, and glycemic control. Both groups showed sugars intake above the recommendations at baseline and after intervention.

Conclusions

Sucrose intake, along with a disciplined diet, did not affect insulin requirements, anthropometric variables, body composition, lipemic and glycemic control. However, although the sucrose intakes increase CRP levels, the amount of sugar in the diet was not associated with this inflammatory marker.

Background

Sucrose is a very attractive source of carbohydrate [1]. The preference for sucrose may be influenced by genetic factors [25], and others complex behaviors (such as craving, infant exposure, social habits, and personal dietary choices) [610]. The effect of sugars on lipid metabolism remains an extremely active area of inquiry because has been shown that high-sugar diets may increase triglycerides levels in subjects with type 2 diabetes [1113], but they do not seem to affect the lipid profile in subjects with type 1 diabetes, if optimal glycemic control is preserved [1418].

Carbohydrate is the major determinant of postprandial glucose levels. The carbohydrate counting is the best method for estimating the grams of carbohydrates in a meal and then calculating the pre-meal insulin dose based on the self-monitored blood glucose (SMBG) and insulin-to-carbohydrate ratio [1, 19].

The American Diabetes Association nutrition recommendations state that the meal plans based on carbohydrate counting remains a key strategy to achieve the glycemic control [1] because the adjustment of pre-prandial insulin doses to the amounts of dietary carbohydrates ingested during the subsequent meal resulted in improved in glycemic control [2024], self-management skills, quality of life, and dietary freedom [2529].

However, the basic and advanced carbohydrate counting are the common methods used currently in clinical practice [19, 22, 30]. In the basic method, the subjects are encouraged to eat constant amounts of carbohydrate at meals. This is useful to understand the effect of food, insulin and to identify the portion sizes, considering that one carbohydrate serving have an approximately 15 g of carbohydrates (these information are obtained from exchange lists, internet and from the nutrition facts). In the advanced method, the patients should have a good understanding of carbohydrate counting principles, as well as understanding pattern management and how to use insulin-to-carbohydrate ratios [1, 19, 30]. According to described, the inclusion of sucrose in the dietary plan of individuals with type 1 diabetes is quite appealing and has been a focus of interest, especially after the introduction of the carbohydrate counting methods. However, previous studies suggested that sugar intake may active inflammation pathways and increase circulatory levels of the inflammatory markers, such as C-reactive protein (CRP) both in health individuals [3133] and patients with type 2 diabetes [34]. However, clinical trials in type 1 diabetes are still lacking.

The goal of this study was to investigate the influence of sucrose intake on anthropometric variables, body composition, lipemia, glycemic control and CRP levels in subjects with type 1 diabetes.

Subjects and methods

This is a controlled clinical-trial was conducted between July 2009, and January 2011. Participants with type 1 diabetes (disease duration of 24 years or more) were recruited at the waiting room of the Clementino Fraga Filho University Hospital, Brazil. Patients with body mass index (BMI) ≥ 30 kg/m2, smokers, alcoholics, users of lipid-lowering or oral hypoglycemic medications and other diseases (such as hypertension, celiac disease, hypo- and hyperthyroidism) were not included.

The hospital database update on January 2010, the size of the universe is 200 outpatients. Of these, only 80 (40%) of these cases were eligible and were then contacted and invited to participate. Forty-five (22%) refused and 35 (17.5%) volunteers agreed to participate in the study. All signed an informed consent and the protocol was approved by the Ethical Committee (Institutional Review Board, protocol 050/09). During the follow-up, two patients were excluded (one had infection and another because did not use insulin properly) and a total of 33 (16.5%) participants completed the study. The sample is not representative and was selected for convenience, thus, results are not intended to represent exactly what would happen with a population [35].

All volunteers were assessed at baseline and after 3-months of intervention. They received three individual face-to-face consultation sessions which included advices on food purchased, food selection, portion sizes, cooking methods, and effect of food on glycemic control.

Participants were allocated into two groups, according to their sucrose intake reported in three 24-hour recalls. Individualized diet prescription based on the current recommendations (dietary energy content of 50-60% carbohydrates, 15-20% of protein, 25-35% of total fat, less than 7% of saturated fatty acids, a maximum of 10% 10% from polyunsaturated fatty acids, and 10-15% of monounsaturated fatty acids) [1].

Percent energy from macronutrients was similar in both groups [1, 36] and as well as the same instructions about carbohydrate counting, and exchange lists with sucrose-free or with foods containing sucrose in its compositions (for sucrose-added group). The lists have been developed based on “Choose your foods: Exchange lists for diabetes” [37] and contained more than 200 foods with a similar amount of carbohydrates (approximately 15 g of carbohydrates per serving), however we detailed listings in the catalogues of permitted and prohibited foods, based on the amount of sugar in each product were also provided to the participants. Diets and dietary records were analyzed using Software DietPró 5.5i (version 2008–2011) and the cutoff point for sucrose intake was < 7 or ≥ 7% to sucrose-free and sucrose-added group, respectively.

The carbohydrate counting method was selected as according to ability to the patient’s understand the management plan and how to use insulin-to-carbohydrate ratios properly [1, 19]. The basic and advanced carbohydrate counting were equally distributed between groups (p = 0.62). Basic method was used for 50% (n = 9) in sucrose-free and 53.33% (n = 8) in sucrose-added group, and the advanced method was used for 50 and 46.67% (n = 9 for each) of volunteers in sucrose-free and sucrose-added group, respectively.

Baseline dietary intake was evaluated from 3-day diet records. Volunteers were followed monthly when 24-hour recalls were performed to verify adherence to the diet. Additionally, they were followed once a week by telephone calls [38].

Insulin, glucometer and test strips to check their SMBG four-daily were provided to all participants. The insulin sensitivity factor was calculated as 1800 or 1500 (for rapid insulin analogs and regular insulin, respectively) divided by the total daily insulin dose. Insulin-to-carbohydrate ratios were calculated as 500 or 450 divided by the total daily insulin dose (for rapid insulin analogs and regular insulin, respectively) and frequently were adjusted 2-hour postprandial. Patients were instructed to calculate their premeal insulin bolus doses based on carbohydrate intake, individualized insulin-to-carbohydrate ratios, and theirs SMBG [39].

Blood sample were obtained after eight hours fasting, and events that could influence the results were considered (such as: infections, flu, fever). Glycated haemoglobin was performed by high-performance liquid chromatography [40]. Fasting glucose, total cholesterol, HDL and triglycerides were measured by enzymatic colorimetric method, and CRP was determined by ultrasensitive colorimetric enzyme-linked immunosorbent assay [41]. LDL cholesterol was calculated with the Friedewald equation [42].

Body mass index was calculated as body weight in kilograms divided by the square of height in meters [43]. Waist circumference was determined as the average of two measurements calculated to the nearest 0.1 cm midway between the lower rib margin and the iliac crest after a normal expiration [44]. Body composition was measured by tetrapolar bioelectrical impedance (biodynamic Model 450) [45].

Statistical analyzes were performed in SPSS software (version 16.0; SPSS Inc, Chicago, IL) with significance level of 5%. Quantitative variables were described as the mean and standard deviation. Mann–Whitney test was used for between-group comparison and Wilcoxon test to compare the effects of nutrition-knowledge in each group. Linear regression was used to determine the value of the triglycerides and CRP levels based upon the values of other variables.

Results

Thirty three patients with type 1 diabetes (21 men and 12 women) with a mean age of 21.7 ± 5 years old (range, 15 to 37) and mean duration of disease of 11.9 ± 6.4 years (range, 2 to 18) were included (Table 1). All were in a basal-bolus plan, 32 using multiple daily injections and one in insulin-pump.

Table 1 Anthropometric characteristics at baseline and after intervention in sucrose-free and sucrose-added groups

Ten patients used the carbohydrate counting method prior to the study (30%), and this proportion did not differ between groups (p = 0.33).

Anthropometric, biochemical and clinical basal characteristics were similar between groups, except for the triglycerides levels, that were higher in the sucrose-added group (p = 0.01) (Tables 1 and 2). Nevertheless, regression analysis showed no association between triglycerides and other variables (p > 0.05).

Table 2 Biochemical and clinical characteristics at baseline and after intervention in sucrose-free and sucrose-added groups

Anthropometric variables were not associated with insulin sensitivity factor, total daily insulin dose or insulin-to-carbohydrate ratio (p > 0.05).

Both groups had a hypocaloric, hyperprotein, normoglycidic, normolipidic and an adequate fiber intake, when compared with the American Diabetes Association [1] and Dietary Reference Intakes [36] current recommendations. There were no differences between groups in these parameters. Sucrose (p = 0.01) and saturated fatty acids (p = 0.03) intake were higher in the sucrose-added than in the sucrose-free group, however, both groups showed simple carbohydrate and saturated fatty acids intakes above the daily recommended intake based on the current guidelines [1, 36] (Table 3).

Table 3 Recommended dietary allowance and actual dietary intake at baseline and after intervention in sucrose-free and sucrose-added groups

Characteristics of groups after intervention

During the intervention, both groups remained in a hypocaloric, hyperprotein, normoglycidic, normolipidic and adequate fiber diet [1, 36]. The sucrose-added group continued to show a higher sucrose intake than sucrose-free group (p < 0.01), however both groups presented simple carbohydrate intake below the recommendations [1, 36]. The monounsaturated fatty acids intake was higher in the sucrose-added group, when compared to the sucrose-free group (p < 0.01), but both groups presented intakes below the recommendations [1, 36]. The other nutrients did not differ between groups (Table 3).

Comparing the intake before and after intervention, the sucrose-free group increased the sucrose, polyunsaturated and monounsaturated fatty acids intake, however reduced the energy and fiber intake (p < 0.05). The Sucrose-added group reduced energy, carbohydrate and fiber, while increased fat intake (p < 0.05) (Table 3).

The data included an average of 111 ± 15.57 SMBG per month for each participant. Insulin requirements, anthropometric and laboratory variables did not differ after the intervention, in any of the groups. The sucrose-added group presented higher CRP concentrations than others volunteers (p = 0.04), although other variables did not differ between groups (p > 0.05). CRP was not associated with any of the anthropometric or laboratory variables (p > 0.05). Regression analysis showed no association between the amount of sucrose intake and CRP levels in any of the groups (p > 0.05) (Table 2).

Triglycerides showed a positively association with the mean of SMBG levels (r = 0.71; p = 0.00) only in the sucrose-added group, however, did not differ between groups after intervention (p = 0.92), as opposed to baseline (p = 0.01). There was a trend towards an increase in triglycerides levels in the sucrose-free group (p = 0.06), which was not observed in the sucrose-added group (p = 0.79) (Table 2). However, the amount of sucrose intake was positively associated to triglyceride levels (r = 0.52; p = 0.04).

Discussion

In this study we showed that the sugar intake did not affect the anthropometric variables, body composition and glycemic control after 3-months in subjects with type 1 diabetes. This was the first clinical trial to assess the influence of sucrose in these variables in individuals with type 1 diabetes and showed a link between sucrose intake and increase of CRP. Studies have reported that CRP levels are higher in subjects with type 1 [46] and type 2 diabetes [47] compared with those without diabetes, while another study not find any correlation between CRP levels and titer of autoantibodies in long-term type 1 individuals with type 1 diabetes [48].

Previous studies have shown positive correlation between sugar intake and CRP in rats [49, 50], healthy adults [5154], children [55], obese [32, 56], and individuals with type 2 diabetes [5759], suggesting several possible mechanisms. One explanation would be the stimulation of the inflammatory response as a consequence of hyperglycemia [53, 57, 60]. Another mechanism could be an effect of glucose and fructose in enzymatic pathways and in the transcription factors involved in lipogenesis. This could lead to peroxisome proliferation changes, microsomal enzyme induction, and transcription of inflammatory factors by the activating nuclear factor-κB [6163]. Alternatively, our third hypothesis is that the chronic hyperglycemia combined with sugar intake could induced release of the neuropeptide Y (a sympathetic neurotransmitter) directly into the adipose tissue, which stimulates endothelial cell (angiogenesis), and consequently leads to increase cytokines and acute phase proteins [64].

There are other hypotheses to explain why high sugars intake could lead to an increase in the levels of inflammatory markers. However, these mechanisms have been observed in mice [61, 62], healthy [53, 63], obese [63, 65] or individuals with type 2 [57, 63]. To our knowledge, this was the first study to examine the effect of sucrose intake in the CRP levels in the subjects with type 1 diabetes.

Even though the between-group differences in CRP in the present study were small, and CRP has been used as a consistent marker for evaluating the extent of cardiovascular diseases in subjects with type 1 diabetes [6670], we suggest that others determinants, such as genetic predisposition, coping mechanisms, and environmental factors, make individuals more susceptible to changes in this inflammatory marker. Therefore, further studies are necessary to understand the effect of sugar intake in CRP levels.

In addition, we showed that triglycerides levels did not differ between groups after intervention, in contrast to baseline, suggesting a trend toward an increased in triglycerides levels in sucrose-free group. Although, the increase in triglyceride levels was not statistically significant, a possible reason for this worsening might be the reduced fiber intake [71, 72].

Furthermore, the scarcity of controlled studies assessing the effect of sucrose intake on metabolic control in well controlled subjects with type 1 diabetes difficult the comparison with other studies. Controlled studies assessing the effect of sucrose in metabolic control of individuals with type 1 diabetes are still lacking because the studies have used fructose as sugar source [7375] or high-glycemic index diet [15, 76, 77]. Only one observational study reported an association between sugar-sweetened beverages and high triglycerides levels in subjects with type 1 diabetes [78], while a controlled trial showed no effect of foods with sucrose on triglycerides levels in this population [18]. Therefore, although our data suggests that the sucrose intake did not change triglycerides levels, further larger and longer studies are still necessary to elucidate this finding.

Furthermore, in this study, triglycerides had no relationship with CRP. This finding is opposite to other studies, which suggest that strategies to decrease inflammatory activity in type 1 diabetes should focus on the triglycerides levels [79]. Corroborating previous studies that have associated the glycemic control with triglycerides, we observed a positively association between triglycerides and SMBG, demonstrating the glycemic control is an important mediator of lipid abnormalities [16, 17, 80]. This may occur because the insulin influences the activity of lipase lipoprotein and inhibits the lipolysis of fats stored in the tissues by inhibition of hormone-sensitive lipase. Thus, such as endogenous insulin, the effective insulin treatments influence the lipid transfers in well-controlled patients with type 1 diabetes [16].

There are potential limitations regarding the interpretation of our data. Firstly, two characteristic (triglycerides levels and saturated fatty acids intake) differed between groups at baseline. In addition, the sucrose intake was not the only dietary factor that differed between groups during the intervention (sucrose-added group presented a higher monounsaturated fatty acids intake than the sucrose-free group). Interestingly, both groups had fatty acids intakes above the current recommendations, based on the American Diabetes Association guidelines [1]. The first and second limitations probably occurred because the sample was selected by convenience [35]. Furthermore, the adherence to the prescribed diet is difficult to accomplish [8184]. Thus, these results could not represent what would happen with the entire population [35].

In summary, although American Diabetes Association report that “unnecessarily restrict sucrose” [1] and all our subjects (both groups) had less than 10% of energy from sugars, we showed that intake of sucrose did not alter body weight, body composition, glycemic and lipemic control, however, there is a link between sucrose intake and increase of CRP. For this reason, according to the above result, we suggest that individuals with diabetes choose to avoid high-sucrose foods even they may eat a relatively small amount. Therefore, further clinical studies are needed to assess the relationship between sugars and CRP levels in subjects with type 1 diabetes.

Conclusions

Sucrose intake, along with a disciplined diet, compared with sucrose-free diet, did not affect insulin requirements, anthropometric variables, body composition, glycemic, and lipemic control. However, although the sucrose intakes increase CRP levels, the amount of sugar in the diet was not associated with this inflammatory marker.

Abbreviations

BMI:

Body mass index

CRP:

C-reactive protein

SMBG:

Self-monitored blood glucose.

References

  1. 1.

    Bantle JP, Wylie-Rosett J, Albright AL, Apovian CM, Clark NG, Franz MJ, Hoogwerf BJ, Lichtenstein AH, Mayer-Davis E, Mooradian AD, et al: Nutrition recommendations and interventions for diabetes: a position statement of the American diabetes association. Diabetes Care. 2008, 31 (Suppl 1): S61-S78.

    CAS  PubMed  Google Scholar 

  2. 2.

    Le Floch JP, Le Lievre G, Sadoun J, Perlemuter L, Peynegre R, Hazard J: Taste impairment and related factors in type I diabetes mellitus. Diabetes Care. 1989, 12: 173-178. 10.2337/diacare.12.3.173.

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Gondivkar SM, Indurkar A, Degwekar S, Bhowate R: Evaluation of gustatory function in patients with diabetes mellitus type 2. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2009, 108: 876-880. 10.1016/j.tripleo.2009.08.015.

    Article  PubMed  Google Scholar 

  4. 4.

    Eny KM, Wolever TM, Corey PN, El-Sohemy A: Genetic variation in TAS1R2 (Ile191Val) is associated with consumption of sugars in overweight and obese individuals in 2 distinct populations. Am J Clin Nutr. 2010, 92: 1501-1510. 10.3945/ajcn.2010.29836.

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Perros P, MacFarlane TW, Counsell C, Frier BM: Altered taste sensation in newly-diagnosed NIDDM. Diabetes Care. 1996, 19: 768-770. 10.2337/diacare.19.7.768.

    CAS  Article  PubMed  Google Scholar 

  6. 6.

    Peres DS, Franco LJ, dos Santos MA: Eating behavior among type 2 diabetes women. Rev Saude Publica. 2006, 40: 310-317. 10.1590/S0034-89102006000200018.

    Article  PubMed  Google Scholar 

  7. 7.

    Beauchamp GK, Mennella JA: Flavor perception in human infants: development and functional significance. Digestion. 2011, 83 (Suppl 1): 1-6.

    PubMed Central  Article  PubMed  Google Scholar 

  8. 8.

    Reed DR, McDaniel AH: The human sweet tooth. BMC Oral Health. 2006, 6 (Suppl 1): S17-10.1186/1472-6831-6-S1-S17.

    PubMed Central  Article  PubMed  Google Scholar 

  9. 9.

    Avena NM, Rada P, Hoebel BG: Evidence for sugar addiction: behavioral and neurochemical effects of intermittent, excessive sugar intake. Neurosci Biobehav Rev. 2008, 32: 20-39. 10.1016/j.neubiorev.2007.04.019.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  10. 10.

    Yanovski S: Sugar and fat: cravings and aversions. J Nutr. 2003, 133: 835S-837S.

    CAS  PubMed  Google Scholar 

  11. 11.

    Nathan DM, Meigs J, Singer DE: The epidemiology of cardiovascular disease in type 2 diabetes mellitus: how sweet it is … or is it?. Lancet. 1997, 350 (Suppl 1): SI4-SI9.

    Article  PubMed  Google Scholar 

  12. 12.

    Brunner S, Holub I, Theis S, Gostner A, Melcher R, Wolf P, Amann-Gassner U, Scheppach W, Hauner H: Metabolic effects of replacing sucrose by isomaltulose in subjects with type 2 diabetes: a randomized double-blind trial. Diabetes Care. 2012, 35: 1249-1251. 10.2337/dc11-1485.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  13. 13.

    Blades B, Garg A: Mechanisms of increase in plasma triacylglycerol concentrations as a result of high carbohydrate intakes in patients with non-insulin-dependent diabetes mellitus. Am J Clin Nutr. 1995, 62: 996-1002.

    CAS  PubMed  Google Scholar 

  14. 14.

    Rabasa-Lhoret R, Garon J, Langelier H, Poisson D, Chiasson J: Effects of meal carbohydrate content on insulin requirements in type 1 diabetic patients treated intensively with the basal-bolus (ultralente-regular) insulin regimen. Diabetes Care. 1999, 22: 667-10.2337/diacare.22.5.667.

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Buyken A, Toeller M, Heitkamp G, Karamanos B, Rottiers R, Muggeo M, Fuller J, EURODIAB I: Glycemic index in the diet of European outpatients with type 1 diabetes: relations to glycated hemoglobin and serum lipids. Am J Clin Nutr. 2001, 73: 574-

    CAS  PubMed  Google Scholar 

  16. 16.

    Feitosa AC, Feitosa-Filho GS, Freitas FR, Wajchenberg BL, Maranhao RC: Lipoprotein metabolism in patients with type 1 diabetes under intensive insulin treatment. Lipids Health Dis. 2013, 12: 15-10.1186/1476-511X-12-15.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  17. 17.

    Alcantara LM, Silveira NE, Dantas JR, Araujo PB, de Oliveira MM, Milech A, Zajdenverg L, Rodacki M, de Oliveira JE: Low triglyceride levels are associated with a better metabolic control in patients with type 1 diabetes. Diabet Metab Syndr. 2011, 3: 22-10.1186/1758-5996-3-22.

    CAS  Article  Google Scholar 

  18. 18.

    Costa PC, Franco LJ: Introduction of sucrose in the diet plan of persons with type 1 diabetes: its influence in the glycemic control. Arq Bras Endocrinol Metabol. 2005, 49: 403-409.

    PubMed  Google Scholar 

  19. 19.

    Kulkarni KD: Carbohydrate counting: a practical meal-planning option for people with diabetes. Clinical Diabetes. 2005, 23: 120-122. 10.2337/diaclin.23.3.120.

    Article  Google Scholar 

  20. 20.

    Bishop FK, Maahs DM, Spiegel G, Owen D, Klingensmith GJ, Bortsov A, Thomas J, Mayer-Davis EJ: The carbohydrate counting in adolescents with type 1 diabetes (CCAT) study. Diabetes Spectrum. 2009, 22: 56-62. 10.2337/diaspect.22.1.56.

    Article  Google Scholar 

  21. 21.

    Spiegel G, Bortsov A, Bishop FK, Owen D, Klingensmith GJ, Mayer-Davis EJ, Maahs DM: Randomized nutrition education intervention to improve carbohydrate counting in adolescents with type 1 diabetes study: is more intensive education needed?. J Acad Nutri Dietetics. 2012, 112: 1736-1746. 10.1016/j.jand.2012.06.001.

    Article  Google Scholar 

  22. 22.

    Bantle J, Wylie-Rosett J, Albright A, Apovian C, Clark N, Franz M, Hoogwerf B, Lichtenstein A, Mayer-Davis E, Mooradian A: Nutrition recommendations and interventions for diabetes: a position statement of the American diabetes association. Diabetes Care. 2008, 31: S61-

    CAS  Article  PubMed  Google Scholar 

  23. 23.

    Chiesa G, Piscopo MA, Rigamonti A, Azzinari A, Bettini S, Bonfanti R, Viscardi M, Meschi F, Chiumello G: Insulin therapy and carbohydrate counting. Acta Biomed. 2005, 76 (Suppl 3): 44-48.

    PubMed  Google Scholar 

  24. 24.

    Dias VM, Pandini JA, Nunes RR, Sperandei SL, Portella ES, Cobas RA, Gomes Mde B: Effect of the carbohydrate counting method on glycemic control in patients with type 1 diabetes. Diabet Metab Syndr. 2010, 2: 54-10.1186/1758-5996-2-54.

    Article  Google Scholar 

  25. 25.

    Martins MR, Ambrosio AC, Nery M, Aquino RD, Queiroz MS: Assessment guidance of carbohydrate counting method in patients with type 2 diabetes mellitus. Prim Care Diabetes. 2013, [Epub ahead of print]

    Google Scholar 

  26. 26.

    Waldron S, Hanas R, Palmvig B: How do we educate young people to balance carbohydrate intake with adjustments of insulin?. Horm Res. 2002, 57 (Suppl 1): 62-65.

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Wylie-Rosett J, Aebersold K, Conlon B, Ostrovsky NW: Medical nutrition therapy for youth with type 1 diabetes mellitus: more than carbohydrate counting. J Acad Nutri Dietetics. 2012, 112: 1724-1727. 10.1016/j.jand.2012.07.033. United States

    Article  Google Scholar 

  28. 28.

    Marigliano M, Morandi A, Maschio M, Sabbion A, Contreas G, Tomasselli F, Tommasi M, Maffeis C: Nutritional education and carbohydrate counting in children with type 1 diabetes treated with continuous subcutaneous insulin infusion: the effects on dietary habits, body composition and glycometabolic control. Acta Diabetol. 2013, [Epub ahead of print]

    Google Scholar 

  29. 29.

    Trento M, Borgo E, Kucich C, Passera P, Trinetta A, Charrier L, Cavallo F, Porta M: Quality of life, coping ability, and metabolic control in patients with type 1 diabetes managed by group care and a carbohydrate counting program. Diabetes Care. 2009, 32: e134-10.2337/dc09-0903.

    Article  PubMed  Google Scholar 

  30. 30.

    Lopes Souto D, Lopes Rosado E: Use of carb counting in the dietary treatment of diabetes mellitus. Nutr Hosp. 2010, 25: 18-25.

    PubMed  Google Scholar 

  31. 31.

    Liu S, Manson J, Buring J, Stampfer M, Willett W, Ridker P: Relation between a diet with a high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged women. Am J Clin Nutr. 2002, 75: 492-

    CAS  PubMed  Google Scholar 

  32. 32.

    Sørensen L, Raben A, Stender S, Astrup A: Effect of sucrose on inflammatory markers in overweight humans. Am J Clin Nutr. 2005, 82: 421-

    PubMed  Google Scholar 

  33. 33.

    Levitan EB, Cook NR, Stampfer MJ, Ridker PM, Rexrode KM, Buring JE, Manson JE, Liu S: Dietary glycemic index, dietary glycemic load, blood lipids, and C-reactive protein. Metabolism. 2008, 57: 437-10.1016/j.metabol.2007.11.002.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  34. 34.

    Malik VS, Popkin BM, Bray GA, Després J-P, Willett WC, Hu FB: Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care. 2010, 33: 2477-10.2337/dc10-1079.

    PubMed Central  Article  PubMed  Google Scholar 

  35. 35.

    Lwanga SK, Lemeshow S: Sample size determination in health studies: a practical manual/SK Lwanga and S. Lemeshow. 1991, England: World Health Organization

    Google Scholar 

  36. 36.

    Trumbo P, Schlicker S, Yates AA, Poos M: Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids. J Am Diet Assoc. 2002, 102: 1621-1630. 10.1016/S0002-8223(02)90346-9.

    Article  PubMed  Google Scholar 

  37. 37.

    Geil PB: Choose your foods: exchange lists for diabetes: the 2008 revision of exchange lists for meal planning. Diabetes Spectrum. 2008, 21: 281-283. 10.2337/diaspect.21.4.281.

    Article  Google Scholar 

  38. 38.

    Wasson J, Gaudette C, Whaley F, Sauvigne A, Baribeau P, Welch H: Telephone care as a substitute for routine clinic follow-up. JAMA. 1992, 267: 1788-1793. 10.1001/jama.1992.03480130104033.

    CAS  Article  PubMed  Google Scholar 

  39. 39.

    Ginsberg BH: System for determining insulin dose using carbohydrate to insulin ratio and insulin sensitivity factor. Book System for determining insulin dose using carbohydrate to insulin ratio and insulin sensitivity factor. 2008, Frankin Lakes, NJ (US): United States Patent, Patent number: US 7,404,796 B2

    Google Scholar 

  40. 40.

    Mosca A, Goodall I, Hoshino T, Jeppsson JO, John WG, Little RR, Miedema K, Myers GL, Reinauer H, Sacks DB, et al: Global standardization of glycated hemoglobin measurement: the position of the IFCC working group. Clin Chem Lab Med. 2007, 45: 1077-1080.

    CAS  Article  PubMed  Google Scholar 

  41. 41.

    Rifai N, Tracy R, Ridker P: Clinical efficacy of an automated high-sensitivity C-reactive protein assay. Clin Chem. 1999, 45: 2136-

    CAS  PubMed  Google Scholar 

  42. 42.

    Friedewald WT, Levy RI, Fredrickson DS: Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972, 18: 499-502.

    CAS  PubMed  Google Scholar 

  43. 43.

    World Health Organization: Report of a WHO Expert Committee. Technical Report Series, n. 854. Physical status: the use and interpretation of anthropometry. 1995, Geneva: WHO

    Google Scholar 

  44. 44.

    World Health Organization: Waist circumference and waist-hip ratio: report of a WHO expert consultation. 2008, Geneva: World Health Organixation, 8-11.

    Google Scholar 

  45. 45.

    Lukaski HC, Johnson PE, Bolonchuk WW, Lykken GI: Assessment of fat-free mass using bioelectrical impedance measurements of the human body. Am J Clin Nutr. 1985, 41: 810-817.

    CAS  PubMed  Google Scholar 

  46. 46.

    Turker Y, Aslantas Y, Aydin Y, Demirin H, Kutlucan A, Tibilli H, Turker Y, Ozhan H: Heart rate variability and heart rate recovery in patients with type 1 diabetes mellitus. Acta Cardiol. 2013, 68: 145-150.

    PubMed  Google Scholar 

  47. 47.

    King DE, Mainous AG, Buchanan TA, Pearson WS: C-reactive protein and glycemic control in adults with diabetes. Diabetes Care. 2003, 26: 1535-1539. 10.2337/diacare.26.5.1535.

    Article  PubMed  Google Scholar 

  48. 48.

    Treszl A, Szereday L, Doria A, King GL, Orban T: Elevated C-reactive protein levels do not correspond to autoimmunity in type 1 diabetes. Diabetes Care. 2004, 27: 2769-2770. 10.2337/diacare.27.11.2769.

    Article  PubMed  Google Scholar 

  49. 49.

    Fuente-Martin E, Garcia-Caceres C, Diaz F, Argente-Arizon P, Granado M, Barrios V, Argente J, Chowen JA: Hypothalamic inflammation without astrogliosis in response to high sucrose intake is modulated by neonatal nutrition in male rats. Endocrinology. 2013, 154: 2318-2330. 10.1210/en.2012-2196.

    CAS  Article  PubMed  Google Scholar 

  50. 50.

    Roncal-Jimenez CA, Lanaspa MA, Rivard CJ, Nakagawa T, Sanchez-Lozada LG, Jalal D, Andres-Hernando A, Tanabe K, Madero M, Li N, et al: Sucrose induces fatty liver and pancreatic inflammation in male breeder rats independent of excess energy intake. Metabolism. 2011, 60: 1259-1270. 10.1016/j.metabol.2011.01.008.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  51. 51.

    Moreto F, de Oliveira EP, Manda RM, Torezan GA, Teixeira O, Michelin E, Burini RC: Pathological and behavioral risk factors for higher serum C-reactive protein concentrations in free-living adults–a Brazilian community-based study. Inflammation. 2013, 36: 15-25. 10.1007/s10753-012-9515-9.

    CAS  Article  PubMed  Google Scholar 

  52. 52.

    Yaghoobi N, Al-Waili N, Ghayour-Mobarhan M, Parizadeh SM, Abasalti Z, Yaghoobi Z, Yaghoobi F, Esmaeili H, Kazemi-Bajestani SM, Aghasizadeh R, et al: Natural honey and cardiovascular risk factors; effects on blood glucose, cholesterol, triacylglycerole, CRP, and body weight compared with sucrose. Sci World J. 2008, 8: 463-469.

    CAS  Article  Google Scholar 

  53. 53.

    de Koning L, Malik VS, Kellogg MD, Rimm EB, Willett WC, Hu FB: Sweetened beverage consumption, incident coronary heart disease, and biomarkers of risk in men. Circulation. 2012, 125: 1735-1741. 10.1161/CIRCULATIONAHA.111.067017. S1731

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  54. 54.

    Aeberli I, Gerber PA, Hochuli M, Kohler S, Haile SR, Gouni-Berthold I, Berthold HK, Spinas GA, Berneis K: Low to moderate sugar-sweetened beverage consumption impairs glucose and lipid metabolism and promotes inflammation in healthy young men: a randomized controlled trial. Am J Clin Nutr. 2011, 94: 479-485. 10.3945/ajcn.111.013540.

    CAS  Article  PubMed  Google Scholar 

  55. 55.

    Kosova EC, Auinger P, Bremer AA: The relationships between sugar-sweetened beverage intake and cardiometabolic markers in young children. J Acad Nutri Dietetics. 2013, 113: 219-227. 10.1016/j.jand.2012.10.020.

    Article  Google Scholar 

  56. 56.

    Nicklas JM, Sacks FM, Smith SR, Leboff MS, Rood JC, Bray GA, Ridker PM: Effect of dietary composition of weight loss diets on high-sensitivity c-reactive protein: the randomized POUNDS LOST trial. Obesity. 2013, 21: 681-689. 10.1002/oby.20072.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  57. 57.

    Sonestedt E, Overby NC, Laaksonen DE, Birgisdottir BE: Does high sugar consumption exacerbate cardiometabolic risk factors and increase the risk of type 2 diabetes and cardiovascular disease?. Food Nutr Res. 2012, 56: DOI: 10.3402/fnr.v56i0.19104. [Epub 2012 Jul 30]

    Google Scholar 

  58. 58.

    Al-Waili NS: Natural honey lowers plasma glucose, C-reactive protein, homocysteine, and blood lipids in healthy, diabetic, and hyperlipidemic subjects: comparison with dextrose and sucrose. J Med Food. 2004, 7: 100-107. 10.1089/109662004322984789.

    CAS  Article  PubMed  Google Scholar 

  59. 59.

    Wolever T, Gibbs A, Mehling C, Chiasson J, Connelly P, Josse R, Leiter L, Maheux P, Rabasa-Lhoret R, Rodger N: The Canadian trial of carbohydrates in diabetes (CCD), a 1-y controlled trial of low-glycemic-index dietary carbohydrate in type 2 diabetes: no effect on glycated hemoglobin but reduction in C-reactive protein. Am J Clin Nutr. 2008, 87: 114-

    CAS  PubMed  Google Scholar 

  60. 60.

    Esposito K, Nappo F, Marfella R, Giugliano G, Giugliano F, Ciotola M, Quagliaro L, Ceriello A, Giugliano D: Inflammatory cytokine concentrations are acutely increased by hyperglycemia in humans: role of oxidative stress. Circulation. 2002, 106: 2067-2072. 10.1161/01.CIR.0000034509.14906.AE.

    CAS  Article  PubMed  Google Scholar 

  61. 61.

    Janevski M, Ratnayake S, Siljanovski S, McGlynn MA, Cameron-Smith D, Lewandowski P: Fructose containing sugars modulate mRNA of lipogenic genes ACC and FAS and protein levels of transcription factors ChREBP and SREBP1c with no effect on body weight or liver fat. Food Funct. 2012, 3: 141-149. 10.1039/c1fo10111k.

    CAS  Article  PubMed  Google Scholar 

  62. 62.

    Koo HY, Wallig MA, Chung BH, Nara TY, Cho BH, Nakamura MT: Dietary fructose induces a wide range of genes with distinct shift in carbohydrate and lipid metabolism in fed and fasted rat liver. Biochim Biophys Acta. 2008, 1782: 341-348. 10.1016/j.bbadis.2008.02.007.

    CAS  Article  PubMed  Google Scholar 

  63. 63.

    Mucci L, Santilli F, Cuccurullo C, Davi G: Cardiovascular risk and dietary sugar intake: is the link so sweet?. Intern Emerg Med. 2012, 7: 313-322. 10.1007/s11739-011-0606-7.

    Article  PubMed  Google Scholar 

  64. 64.

    Kuo LE, Czarnecka M, Kitlinska JB, Tilan JU, Kvetnansky R, Zukowska Z: Chronic stress, combined with a high-fat/high-sugar diet, shifts sympathetic signaling toward neuropeptide Y and leads to obesity and the metabolic syndrome. Ann N Y Acad Sci. 2008, 1148: 232-237. 10.1196/annals.1410.035.

    PubMed Central  Article  PubMed  Google Scholar 

  65. 65.

    Bray GA: Fructose and risk of cardiometabolic disease. Curr Atheroscler Rep. 2012, 14: 570-578. 10.1007/s11883-012-0276-6.

    CAS  Article  PubMed  Google Scholar 

  66. 66.

    Hayaishi-Okano R, Yamasaki Y, Katakami N, Ohtoshi K, Gorogawa S, Kuroda A, Matsuhisa M, Kosugi K, Nishikawa N, Kajimoto Y, Hori M: Elevated C-reactive protein associates with early-stage carotid atherosclerosis in young subjects with type 1 diabetes. Diabetes Care. 2002, 25: 1432-1438. 10.2337/diacare.25.8.1432.

    CAS  Article  PubMed  Google Scholar 

  67. 67.

    Ladeia AM, Stefanelli E, Ladeia-Frota C, Moreira A, Hiltner A, Adan L: Association between elevated serum C-reactive protein and triglyceride levels in young subjects with type 1 diabetes. Diabetes Care. 2006, 29: 424-426. 10.2337/diacare.29.02.06.dc05-2033.

    CAS  Article  PubMed  Google Scholar 

  68. 68.

    Du M, Basu A, Fu D, Wu M, Centola M, Jenkins AJ, Hanssen KF, Garg SK, Hammad SM, Scardo JA, et al: Serum inflammatory markers and preeclampsia in type 1 diabetes: a prospective study. Diabetes Care. 2013, 36: 2054-2061. 10.2337/dc12-1934.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  69. 69.

    Strychar I, Cohn JS, Renier G, Rivard M, Aris-Jilwan N, Beauregard H, Meltzer S, Belanger A, Dumas R, Ishac A, et al: Effects of a diet higher in carbohydrate/lower in fat versus lower in carbohydrate/higher in monounsaturated fat on postmeal triglyceride concentrations and other cardiovascular risk factors in type 1 diabetes. Diabetes Care. 2009, 32: 1597-1599. 10.2337/dc08-2322.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  70. 70.

    Delahanty LM, Nathan DM, Lachin JM, Hu FB, Cleary PA, Ziegler GK, Wylie-Rosett J, Wexler DJ, Diabetes C: Complications trial/epidemiology of D: association of diet with glycated hemoglobin during intensive treatment of type 1 diabetes in the diabetes control and complications trial. Am J Clin Nutr. 2009, 89: 518-524. 10.3945/ajcn.2008.26498.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  71. 71.

    Harold MR, Reeves RD, Bolze MS, Guthrie RA, Guthrie DW: Effect of dietary fiber in insulin-dependent diabetics: insulin requirements and serum lipids. J Am Diet Assoc. 1985, 85: 1455-1461.

    CAS  PubMed  Google Scholar 

  72. 72.

    Anderson JW, Randles KM, Kendall CW, Jenkins DJ: Carbohydrate and fiber recommendations for individuals with diabetes: a quantitative assessment and meta-analysis of the evidence. J Am Coll Nutr. 2004, 23: 5-17. 10.1080/07315724.2004.10719338.

    Article  PubMed  Google Scholar 

  73. 73.

    Couch SC, Crandell JL, Shah AS, Dolan LM, Merchant AT, Liese AD, Lawrence JM, Pihoker C, Mayer-Davis EJ: Fructose intake and cardiovascular risk factors in youth with type 1 diabetes: SEARCH for diabetes in youth study. Diabetes Res Clin Pract. 2013, 100: 265-271. 10.1016/j.diabres.2013.03.013.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  74. 74.

    Bantle JP, Laine DC, Thomas JW: Metabolic effects of dietary fructose and sucrose in types I and II diabetic subjects. JAMA. 1986, 256: 3241-3246. 10.1001/jama.1986.03380230065027.

    CAS  Article  PubMed  Google Scholar 

  75. 75.

    Bantle JP, Swanson JE, Thomas W, Laine DC: Metabolic effects of dietary fructose in diabetic subjects. Diabetes Care. 1992, 15: 1468-1476. 10.2337/diacare.15.11.1468.

    CAS  Article  PubMed  Google Scholar 

  76. 76.

    Giacco R, Parillo M, Rivellese AA, Lasorella G, Giacco A, D’Episcopo L, Riccardi G: Long-term dietary treatment with increased amounts of fiber-rich low-glycemic index natural foods improves blood glucose control and reduces the number of hypoglycemic events in type 1 diabetic patients. Diabetes Care. 2000, 23: 1461-1466. 10.2337/diacare.23.10.1461.

    CAS  Article  PubMed  Google Scholar 

  77. 77.

    Wolever TM, Hamad S, Chiasson JL, Josse RG, Leiter LA, Rodger NW, Ross SA, Ryan EA: Day-to-day consistency in amount and source of carbohydrate intake associated with improved blood glucose control in type 1 diabetes. J Am Coll Nutr. 1999, 18: 242-247. 10.1080/07315724.1999.10718858.

    CAS  Article  PubMed  Google Scholar 

  78. 78.

    Bortsov A, Liese A, Bell R, Dabelea D, D’Agostino R, Hamman R, Klingensmith G, Lawrence J, Maahs D, McKeown R: Sugar-sweetened and diet beverage consumption is associated with cardiovascular risk factor profile in youth with type 1 diabetes. Acta Diabetol. 2011, 48: 275-10.1007/s00592-010-0246-9.

    CAS  Article  PubMed  Google Scholar 

  79. 79.

    Neithercott T: 30 Tips for successful carb counting. Top pointers from real people with diabetes. Diabetes Forecast. 2011, 64: 34-39.

    PubMed  Google Scholar 

  80. 80.

    Guy J, Ogden L, Wadwa RP, Hamman RF, Mayer-Davis EJ, Liese AD, D’Agostino R, Marcovina S, Dabelea D: Lipid and lipoprotein profiles in youth with and without type 1 diabetes: the SEARCH for diabetes in youth case–control study. Diabetes Care. 2009, 32: 416-420. 10.2337/dc08-1775.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  81. 81.

    Price KJ, Lang JD, Eiser C, Tripp JH: Prescribed versus unrestricted carbohydrate diets in children with type 1 diabetes. Diabet Med. 1993, 10: 962-967. 10.1111/j.1464-5491.1993.tb00013.x.

    CAS  Article  PubMed  Google Scholar 

  82. 82.

    Kornides ML, Nansel TR, Quick V, Haynie DL, Lipsky LM, Laffel LM, Mehta SN: Associations of family meal frequency with family meal habits and meal preparation characteristics among families of youth with type 1 diabetes. Child Care Health Dev. 2013, [Epub ahead of print]

    Google Scholar 

  83. 83.

    Kulkarni K, Castle G, Gregory R, Holmes A, Leontos C, Powers M, Snetselaar L, Splett P, Wylie-Rosett J: Nutrition practice guidelines for type 1 diabetes mellitus positively affect dietitian practices and patient outcomes. The diabetes care and education dietetic practice group. J Am Diet Assoc. 1998, 98: 62-70. 10.1016/S0002-8223(98)00017-0. quiz 71–62

    CAS  Article  PubMed  Google Scholar 

  84. 84.

    Hanestad BR, Albrektsen G: Quality of life, perceived difficulties in adherence to a diabetes regimen, and blood glucose control. Diabet Med. 1991, 8: 759-764. 10.1111/j.1464-5491.1991.tb01696.x.

    CAS  Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank Marcus M.S. Oliveira, Maria Adelaide M. Santos, Joana R. Dantas, Érika S. Lima, Mariana P. Miranda, and Priscila M. Leal for help with data collection. José Egídio Paulo de Oliveira to allow data collection and our patients for their cooperation.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Débora Lopes Souto.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

DLS draft the manuscript, conceived, performed and coordinated the study. LZ and MR helped in the data collecting and contributed to draft the manuscript. ELR participated in design and coordination and draft the manuscript. All authors read and approved the final manuscript.

Débora Lopes Souto, Lenita Zajdenverg, Melanie Rodacki and Eliane Lopes Rosado contributed equally to this work.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Souto, D.L., Zajdenverg, L., Rodacki, M. et al. Does sucrose intake affect antropometric variables, glycemia, lipemia and C-reactive protein in subjects with type 1 diabetes?: a controlled-trial. Diabetol Metab Syndr 5, 67 (2013). https://doi.org/10.1186/1758-5996-5-67

Download citation

Keywords

  • Diabetes
  • Sucrose
  • Body composition
  • C-reactive protein
  • Carbohydrate