Browsing by Author "Kerr, David"

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    A Computational Analysis of Meal Events Using Food Diaries and Continuous Glucose Monitors
    (2023-04-21) Pai, Amruta; Sabharwal, Ashutosh; Allen, Genevera; Patel, Ankit; Beier, Margaret; Kerr, David
    Diet self-management, through its effect on weight and glycemic control, is one of the cornerstones of Type 2 Diabetes (T2D) prevention and management. A quantitative understanding of bio-behavioral mechanisms of diet is needed to create effective diet self-management tools. Smartphone diet-tracking applications and continuous glucose monitors (CGMs) are emerging devices that enable dense sampling of an individual's diet. Research in diet analysis of app-based food diaries and CGMs have mainly focused on developing aggregate measures of nutrient intake and glucose responses. However, innovative computational analysis is required to infer actionable insights. In this thesis, we develop computational measures for various bio-behavioral aspects of diet by leveraging meal event data collected with food diaries and CGMs. First, we establish recurrent consumption measures across meal events to characterize habitual behavior in an individual's diet. We leverage a large publicly available MyFitnessPal (MFP) food diary dataset to provide novel insights on differences in habitual behavior across individuals and temporal contexts. Next, we develop calorie compensation measures to characterize self-regulatory behavior. A quantitative analysis of calorie compensation measures on the MFP dataset reveals significant meal compensation patterns and their impact on adherence to self-set calorie goals. Finally, we designed an observational study using the MFP app and CGMs to evaluate the impact of meal events on glycemic control in adults with varying hemoglobin a1c levels. We developed elevated meal event count to characterize mealtime glucose responses by exploiting its association with hemoglobin a1c. Elevated meal event count significantly affected glycemic control, suggesting its value as a novel event-driven glycemic target metric. This thesis highlights the value of using CGMs and food diaries to broaden our understanding of diet. The developed measures augment existing intake measures and could be used as a digital bio-behavioral markers to personalize diet self-management strategies.
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    Dysglycemia in adults at risk for or living with non-insulin treated type 2 diabetes: Insights from continuous glucose monitoring
    (Elsevier, 2021) Barua, Souptik; Sabharwal, Ashutosh; Glantz, Namino; Conneely, Casey; Larez, Arianna; Bevier, Wendy; Kerr, David
    Background: Continuous glucose monitoring (CGM) has demonstrable benefits for people living with diabetes, but the supporting evidence is almost exclusively from White individuals with type 1 diabetes. Here, we have quantified CGM profiles in Hispanic/Latino adults with or at-risk of non-insulin treated type 2 diabetes (T2D). Methods: 100 participants (79 female, 86% Hispanic/Latino [predominantly Mexican], age 54·6 [±12·0] years) stratified into (i) at risk of T2D, (ii) with pre-diabetes (pre-T2D), and (iii) with non-insulin treated T2D, wore blinded CGMs for 2 weeks. Beyond standardized CGM measures (average glucose, glucose variability, time in 70–140 mg/dL and 70–180 mg/dL ranges), we also examined additional CGM measures based on the time of day. Findings: Standardized CGM measures were significantly different for participants with T2D compared to at-risk and pre-T2D participants (p<0·0001). In addition, pre-T2D participants spent more time between 140 and 180 mg/dL during the day than at-risk participants (p<0·01). T2D participants spent more time between 140 and 180 mg/dL both during the day and overnight compared to at-risk and pre-T2D participants (both p<0·0001). Time in 70–140 mg/dL range during the day was significantly correlated with HbA1c (r=-0·72, p<0·0001), after adjusting for age, sex, BMI, and waist circumference (p<0·0001). Interpretation: Standardized CGM measures show a progression of dysglycemia from at-risk of T2D, to pre-T2D, and to T2D. Stratifying CGM readings by time of day and the range 140–180 mg/dL provides additional metrics to differentiate between the groups. Funding US Department of Agriculture (Grant #2018-33800-28404) and NSF PATHS-UP ERC (Award #1648451).
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    Evaluating HbA1c-to-average glucose conversion with patient-specific kinetic models for diverse populations
    (Springer Nature, 2024) Sato Imuro, Sandra Emi; Sabharwal, Ashutosh; Bevier, Wendy; Kerr, David
    The discrepancy between estimated glycemia from HbA1c values and actual average glucose (AG) levels has significant implications for treatment decisions and patient understanding. Factors contributing to the gap include red blood cell (RBC) lifespan and glucose uptake into the RBC. Personalized models have been proposed to enhance AG prediction accuracy by considering interpersonal variation. This study contributes to our understanding of personalized models for estimating AG from HbA1c. Utilizing data from seven studies (340 participants), including Hispanic/Latino populations with or at risk of non-insulin-treated type 2 diabetes (T2D), we examined kinetic features across cohorts. Additionally, the study simulated scenarios to understand data requirements for improving accuracy. Personalized approaches improved agreement between AG estimations and CGM-AG, particularly with four or more weeks of training CGM data. A multiple linear regression model using kinetic parameters and added clinical features was shown to improve the accuracy of personalized models further. As CGM usage extends beyond type 1 diabetes, there is growing interest in leveraging CGM data for clinical decision-making. Patient-specific models offer a valuable tool for managing glycemic status in patients with discordant HbA1c and AG values.
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    Farming for life: impact of medical prescriptions for fresh vegetables on cardiometabolic health for adults with or at risk of type 2 diabetes in a predominantly Mexican-American population
    (BMJ, 2020) Kerr, David; Barua, Souptik; Glantz, Namino; Conneely, Casey; Kujan, Mary; Bevier, Wendy; Larez, Arianna; Sabharwal, Ashutosh
    Introduction: Poor diet is the leading cause of poor health in USA, with fresh vegetable consumption below recommended levels. We aimed to assess the impact of medical prescriptions for fresh (defined as picked within 72 hours) vegetables, at no cost to participants on cardiometabolic outcomes among adults (predominantly Mexican-American women) with or at risk of type 2 diabetes (T2D). Methods: Between February 2019 and March 2020, 159 participants (122 female, 75% of Mexican heritage, 31% with non-insulin treated T2D, age 52.5 (13.2) years) were recruited using community outreach materials in English and Spanish, and received prescriptions for 21 servings/week of fresh vegetable for 10 weeks. Pre-post comparisons were made of weight; waist circumference; blood pressure; Hemoglobin A1c (HbA1c, a measure of long-term blood glucose control); self-reported sleep, mood and pain; vegetable, tortilla and soda consumption. After obtaining devices for this study, 66 of 72 participants asked, agreed to wear blinded continuous glucose monitors (CGM). Results: Paired data were available for 131 participants. Over 3 months, waist circumference fell (−0.77 (95% CI −1.42 to 0.12) cm, p=0.022), as did systolic blood pressure (SBP) (−2.42 (95% CI −4.56 to 0.28) mm Hg, p=0.037), which was greater among individuals with baseline SBP >130 mm Hg (−7.5 (95% CI −12.4 to 2.6) mm Hg, p=0.005). Weight reduced by −0.4 (−0.7 to –0.04) kg, p=0.029 among women. For participants with baseline HbA1c >7.0%, HbA1c fell by −0.35 (-0.8 to –0.1), p=0.009. For participants with paired CGM data (n=40), time in range 70–180 mg/dL improved (from 97.4% to 98.9%, p<0.01). Food insecurity (p<0.001), tortilla (p<0.0001) and soda (p=0.013) consumption significantly decreased. Self-reported sleep, mood and pain level scores also improved (all p<0.01). Conclusions: Medical prescriptions for fresh vegetables were associated with clinically relevant improvements in cardiovascular risk factors and quality of life variables (sleep, mood and pain level) in adults (predominantly Mexican-American and female) with or at risk of T2D.
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    Technology and health inequities in diabetes care: How do we widen access to underserved populations and utilize technology to improve outcomes for all?
    (Wiley, 2024) Ebekozien, Osagie; Fantasia, Kathryn; Farrokhi, Farnoosh; Sabharwal, Ashutosh; Kerr, David
    Abstract Digital health technologies are being utilized increasingly in the modern management of diabetes. These include tools such as continuous glucose monitoring systems, connected blood glucose monitoring devices, hybrid closed-loop systems, smart insulin pens, telehealth, and smartphone applications (apps). Although many of these technologies have a solid evidence base, from the perspective of a person living with diabetes, there remain multiple barriers preventing their optimal use, creating a digital divide. In this article, we describe many of the origins of these barriers and offer recommendations on widening access to digital health technologies for underserved populations living with diabetes to improve their health outcomes.
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    Temporal changes in bio-behavioral and glycemic outcomes following a produce prescription program among predominantly Hispanic/Latino adults with or at risk of type 2 diabetes
    (Elsevier, 2023) Sato Imuro, Sandra Emi; Sabharwal, Ashutosh; Conneely, Casey; Glantz, Namino; Bevier, Wendy; Barua, Souptik; Pai, Amruta; Larez, Arianna; Kerr, David
    In the United States (U.S.), consumption of fresh vegetables and fruits is below recommended levels. Enhancing access to nutritious food through food prescriptions has been recognized as a promising approach to combat diet-related illnesses. However, the effectiveness of this strategy at a large scale remains untested, particularly in marginalized communities where food insecurity rates and the prevalence of health conditions such as type 2 diabetes (T2D) are higher compared to the background population. This study evaluated the impact of a produce prescription program for predominantly Hispanic/Latino adults living with or at risk of T2D. A total of 303 participants enrolled in a 3-month observational cohort received 21 medically prescribed portions/week of fresh produce. A subgroup of 189 participants used continuous glucose monitoring (CGM) to assess the relationship between CGM profile changes and HbA1c level changes. For 247 participants completing the study (76% female, 84% Hispanic/Latino, 32% with T2D, age 56·6 ± 11·9 years), there was a reduction in weight (−1·1 [-1·6 to −0·6] lbs., p < 0.001), waist circumference (−0·4 [-1·0 to 0·6] cm, p = 0·007) and systolic blood pressure (SBP) for participants with baseline SBP >120 mmHg (−4·2 [-6·8 to −1·8] mmHg, p = 0·001). For participants with an HbA1c ≥ 7·0% at baseline, HbA1c fell significantly (−0·5 [-0·9 to −0·1] %, p = 0·01). There were also improvements in food security (p < 0·0001), self-reported ratings of sleep, mood, pain (all p < 0·001), and measures of depression (p < 0·0001), anxiety (p = 0·045), and stress (p = 0·002) (DASS-21). There was significant correlation (r = 0·8, p = 0·001) between HbA1c change and the change in average glucose for participants with worsening HbA1c, but not for participants with an improvement in HbA1c. In conclusion, medical prescription of fresh produce is associated with significant improvements in cardio-metabolic and psycho-social risk factors for Hispanic/Latino adults with or at risk of T2D.