Dataset Information

A pragmatic low carbohydrate diet intervention changes neither carbohydrate consumption nor glycemia in adolescents and young adults with type 1 diabetes in a randomized trial.

ABSTRACT:

Objective

Despite enthusiasm for low carbohydrate diets (LCDs) among patients with type 1 diabetes (T1DM), no prospective study has investigated outcomes in adolescent T1DM. We aimed to quantify a pragmatic LCD intervention's impact on glycemia, lipidemia, and quality of life (QOL) in adolescents with T1DM.

Research design and methods

At an academic center, we randomized 39 patients with T1DM aged 13-21 years to one of three 12-week interventions: an LCD, an isocaloric standard carbohydrate diet (SCD), or general diabetes education without a prescriptive diet. Glycemic outcomes included glycosylated hemoglobin (HbA1c) and continuous glucose monitoring.

Results

There were no significant differences in glycemic, lipidemic, or QOL parameters between groups at any timepoint. Median HbA1c was similar at baseline between groups and did not change appreciably (7.9%-8.4% in LCDs, 7.9%-7.9% in SCDs, and 8.2%-7.8% in controls). Change in carbohydrate consumption was minimal with only one participant reaching target carbohydrate intake.

Conclusions

This pragmatic LCD intervention did not alter carbohydrate consumption or glycemia. Although this study was unable to evaluate a highly controlled LCD, it indicates that adolescents are unlikely to implement an educational LCD intervention in routine clinic settings. Thus, this approach is unlikely to effectively mitigate hyperglycemia in adolescents.

SUBMITTER: Duffus SH

PROVIDER: S-EPMC10077495 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Publications

A pragmatic low carbohydrate diet intervention changes neither carbohydrate consumption nor glycemia in adolescents and young adults with type 1 diabetes in a randomized trial.

Duffus Sara H SH Slaughter James C JC Cooley William W Sharif Navila N Rainer Kimberly K Coate Katie C KC Jaser Sarah S SS Moore Daniel J DJ Niswender Kevin D KD Gregory Justin M JM

Pediatric diabetes 20220905 7

<h4>Objective</h4>Despite enthusiasm for low carbohydrate diets (LCDs) among patients with type 1 diabetes (T1DM), no prospective study has investigated outcomes in adolescent T1DM. We aimed to quantify a pragmatic LCD intervention's impact on glycemia, lipidemia, and quality of life (QOL) in adolescents with T1DM.<h4>Research design and methods</h4>At an academic center, we randomized 39 patients with T1DM aged 13-21 years to one of three 12-week interventions: an LCD, an isocaloric standard ca ...[more]

PMID: 36004391

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Project description:INTRODUCTION:Individuals with type 1 diabetes (T1D) present with diverse body weight status and degrees of glycemic control, which may warrant different treatment approaches. We sought to identify subgroups sharing phenotypes based on both weight and glycemia and compare characteristics across subgroups. RESEARCH DESIGN AND METHODS:Participants with T1D in the SEARCH study cohort (n=1817, 6.0-30.4 years) were seen at a follow-up visit >5 years after diagnosis. Hierarchical agglomerative clustering was used to group participants based on five measures summarizing the joint distribution of body mass index z-score (BMIz) and hemoglobin A1c (HbA1c) which were estimated by reinforcement learning tree predictions from 28 covariates. Interpretation of cluster weight status and glycemic control was based on mean BMIz and HbA1c, respectively. RESULTS:The sample was 49.5% female and 55.5% non-Hispanic white (NHW); mean±SD age=17.6±4.5 years, T1D duration=7.8±1.9 years, BMIz=0.61±0.94, and HbA1c=76±21?mmol/mol (9.1±1.9)%. Six weight-glycemia clusters were identified, including four normal weight, one overweight, and one subgroup with obesity. No cluster had a mean HbA1c <58?mmol/mol (7.5%). Cluster 1 (34.0%) was normal weight with the lowest HbA1c and comprised 85% NHW participants with the highest socioeconomic position, insulin pump use, dietary quality, and physical activity. Subgroups with very poor glycemic control (ie, ?108?mmol/mol (?12.0%); cluster 4, 4.4%, and cluster 5, 7.5%) and obesity (cluster 6, 15.4%) had a lower proportion of NHW youth, lower socioeconomic position, and reported decreased pump use and poorer health behaviors (overall p<0.01). The overweight subgroup with very poor glycemic control (cluster 5) showed the highest lipids and blood pressure (p<0.01). CONCLUSIONS:There are distinct subgroups of youth and young adults with T1D that share weight-glycemia phenotypes. Subgroups may benefit from tailored interventions addressing differences in clinical care, health behaviors, and underlying health inequity.

Project description:Aims: In this study, we aimed to estimate cross-sectional associations of fish or shellfish consumption with diabetes and glycemia in three South Asian mega-cities. Methods: We analyzed baseline data from 2010-2011 of a cohort (n = 16,287) representing the population ≥20 years old that was neither pregnant nor on bedrest from Karachi (unweighted n = 4017), Delhi (unweighted n = 5364), and Chennai (unweighted n = 6906). Diabetes was defined as self-reported physician-diagnosed diabetes, fasting plasma glucose ≥126 mg/dL (7.0 mmol/L), or glycated hemoglobin A1c (HbA1c) ≥6.5% (48 mmol/mol). We estimated adjusted and unadjusted odds ratios for diabetes using survey estimation logistic regression for each city, and differences in glucose and HbA1c using survey estimation linear regression for each city. Adjusted models controlled for age, gender, body mass index, waist-height ratio, sedentary lifestyle, educational attainment, tobacco use, an unhealthy diet index score, income, self-reported physician diagnosis of high blood pressure, and self-reported physician diagnosis of high cholesterol. Results: The prevalence of diabetes was 26.7% (95% confidence interval: 24.8, 28.6) in Chennai, 36.7% (32.9, 40.5) in Delhi, and 24.3% (22.0, 26.6) in Karachi. Fish and shellfish were consumed more frequently in Chennai than in the other two cities. In Chennai, the adjusted odds ratio for diabetes, comparing more than weekly vs. less than weekly fish consumption, was 0.81 (0.61, 1.08); in Delhi, it was 1.18 (0.87, 1.58), and, in Karachi, it was 1.30 (0.94, 1.80). In Chennai, the adjusted odds ratio of prevalent diabetes among persons consuming shellfish more than weekly versus less than weekly was 1.08 (95% CI: 0.90, 1.30); in Delhi, it was 1.35 (0.90, 2.01), and, in Karachi, it was 1.68 (0.98, 2.86). Conclusions: Both the direction and the magnitude of association between seafood consumption and glycemia may vary by city. Further investigation into specific locally consumed seafoods and their prospective associations with incident diabetes and related pathophysiology are warranted.

Dataset Information

A pragmatic low carbohydrate diet intervention changes neither carbohydrate consumption nor glycemia in adolescents and young adults with type 1 diabetes in a randomized trial.

Objective

Research design and methods

Results

Conclusions

Publications

A pragmatic low carbohydrate diet intervention changes neither carbohydrate consumption nor glycemia in adolescents and young adults with type 1 diabetes in a randomized trial.

Similar Datasets

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