Changes in Glycemic Control Among Individuals With Diabetes Who Used a Personalized Digital Nutrition Platform: Longitudinal Study
Bibliographic record
Abstract
Background Diabetes-related costs are the highest across all chronic conditions in the United States, with type 2 diabetes accounting for up to 95% of all cases of diabetes. A healthy diet is strongly associated with lowering glycated hemoglobin A1c (HbA1c) levels among individuals with diabetes, which can help curtail other health complications. Digital health platforms can offer critical support for improving diet and glycemic control among individuals with diabetes. Less is known about the characteristics of people with diabetes who use digital health platforms (specifically, a platform that integrates personalized healthy meal plans and food ordering) and changes in their HbA1c levels. Objective The aim of this study is to characterize Foodsmart users with diabetes and evaluate the longitudinal impact of Foodsmart—a personalized digital nutrition platform with meal planning, food ordering, and nutrition education features—on changes in HbA1c levels. Methods We retrospectively analyzed data collected from 643 adults with at least two self-reported HbA1c entries in the Foodsmart platform between January 2016 and June 2021. Participants self-reported their HbA1c levels, height, weight, health conditions, and diet in a 53-item food frequency questionnaire. Diabetes was defined as HbA1c ≥6.5%. We analyzed distributions of characteristics by baseline diabetes status and examined the association of characteristics with the likelihood of having diabetes at baseline. To evaluate the change in HbA1c levels among Foodsmart users, we calculated mean changes (absolute and percent) in HbA1c among participants with diabetes and by length of follow-up. We also compared changes in HbA1c and weight between participants with diabetes at baseline who achieved a normal HbA1c level and those who did not. Results We found that 43.5% (280/643) of the participants with at least two HbA1c level entries had diabetes at baseline. Participants with diabetes at baseline were more likely to be male, have a higher weight and BMI, report high blood pressure, and have a poorer diet in comparison to participants without diabetes. Using a multivariable logistic regression model, we found that being male and obese were statistically significantly associated with baseline diabetes. Among participants with diabetes at baseline, HbA1c was reduced, on average, by 0.46%. In addition, 21.4% (60/280) of participants with diabetes achieved a normal HbA1c level (<6.5%) in their last HbA1c level entry; this percentage increased with longer follow-up time (39% [7/18] at >24 months). In a sensitivity analysis, users with an HbA1c ≥7.0% at baseline had an average absolute change of –0.62% and 31.2% (62/199) of these participants achieved HbA1c levels of less than 7.0%. Conclusions This study assessed characteristics of individuals enrolled on the Foodsmart platform with HbA1c levels and found that users with diabetes had lower HbA1c levels over time and a sizable percentage of participants were successful in achieving normal levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".