Publications by authors named "Daria Igudesman"

5 Publications

  • Page 1 of 1

Methodology for altering omega-3 EPA+DHA and omega-6 linoleic acid as controlled variables in a dietary trial.

Clin Nutr 2021 Jun 12;40(6):3859-3867. Epub 2021 May 12.

Department of Neurology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Background & Aims: Increasing dietary intake of n-3 EPA+DHA and lowering dietary n-6 LA is under investigation as a therapeutic diet for improving chronic pain syndromes as well as other health outcomes. Herein we describe the diet methodology used to modulate intake of n-3 and n-6 PUFA in a free living migraine headache population and report on nutrient intake, BMI and diet acceptability achieved at week 16 of the intensive diet intervention and week 22 follow-up time-point.

Methods: A total of 178 participants were randomized and began one of three diet interventions: 1) a high n-3 PUFA, average n-6 PUFA (H3) diet targeting 1500 mg EPA+DHA/day and 7% of energy (en%) from n-6 linoleic acid (LA), 2) a high-n-3 PUFA, low-n-6 PUFA (H3L6) targeting 1500 mg EPA+DHA/day and <1.8 en% n-6 LA or 3) a Control diet with typical American intakes of both EPA+DHA (<150 mg/day) and 7 en% from n-6 LA. Methods used to achieve diet change to week 16 include diet education, diet counseling, supply of specially prepared foods, self-monitoring and access to online diet materials. Only study oils and website materials were provided for the follow-up week 16 to week 22 periods. Diet adherence was assessed by multiple 24 h recalls administered throughout the trial. Diet acceptability was assessed in a subset of participants at 4 time points by questionnaire.

Results: At week 16 H3 and H3L6 diet groups significantly increased median n-3 EPA+DHA intake from 48 mg/2000 kcals at baseline to 1484 mg/2000 kcals (p < 0.0001) and from 44 mg/2000 kcals to 1341 mg/2000 kcals (p < 0.0001), respectively. In the Control group, EPA+DHA intake remained below the typical American intake with baseline median at 60 mg/2000 kcals and 80 mg/2000 kcals (p = 0.6) at week 16. As desired, LA intake was maintained in the H3 and Control group with baseline median of 6.5 en% to 7.1 en% (p = 0.4) at week 16 and from 6.5 en% to 6.8 en% (p = 1.0) at week 16, respectively. In the H3L6 group, n-6 LA decreased from 6.3 en% at baseline to 3.2 en% (p < 0.0001) at week 16. There were no significant changes in BMI or diet acceptability throughout the trial or between diet groups.

Conclusions: We find this diet method to be acceptable to research participants and successful in altering dietary n-3 EPA+DHA with and without concurrent decreases in n-6 LA. If n-6 LA of less than 3 en% is desired, additional techniques to limit LA may need to be employed.
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http://dx.doi.org/10.1016/j.clnu.2021.04.050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293619PMC
June 2021

Impact of Hurricane Matthew on Diabetes Self-Management and Outcomes.

N C Med J 2021 Mar-Apr;82(2):100-107

Distinguished professor of Nutrition and Medicine, chair, Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.

Background: Individuals with diabetes require extensive self-management. Little is known about how Hurricane Matthew (Matthew) or Hurricane Florence (Florence) impacted diabetes self-management and outcomes in Robeson County, North Carolina.

Methods: Mixed methods were used to assess the impact of hurricanes on diabetes self-management and outcomes. Individuals with diabetes were recruited for focus groups to understand the perceived impact on diabetes self-management. Health care providers were recruited for parallel key informant interviews. Mean hemoglobin A1c (HbA1c) and frequency of diabetic ketoacidosis (DKA) from hospital data six months before and after Matthew were compared using Student t-tests.

Results: A demographic breakdown of 34.25% white, 21.70% Black or African American, and 21.38% American Indian or Alaska Native was observed from focus groups. Qualitative results highlight a limited access to a balanced diet and medications. No significant differences were found between mean HbA1c values before and after Matthew (before Matthew: mean HbA1c 8.34 ± 1.87%; after Matthew: mean HbA1c 8.31 ± 1.93 %; = .366). The period prevalence (PP) of DKA was higher after Matthew than before (before Matthew: 39 cases out of 4,025 visits, PP = .010; after Matthew: 87 cases out of 3,779 visits, PP = .023; <.0001).

Limitations: Limitations include non-random sampling and limited sample sizes. Also, the cross-sectional panel approach did not follow the same individuals over time.

Conclusions: The period prevalence of DKA was higher in the six-month time period following Matthew compared to before the hurricane. Future interventions may improve outcomes via increased access to foods and medications recommended for those with diabetes.
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http://dx.doi.org/10.18043/ncm.82.2.100DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8230667PMC
March 2021

Dietary intake on days with and without hypoglycemia in youth with type 1 diabetes: The Flexible Lifestyle Empowering Change trial.

Pediatr Diabetes 2020 12 5;21(8):1475-1484. Epub 2020 Oct 5.

Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, 27599, USA.

Objective: To address a common perception that hypoglycemia is associated with increased dietary intake, we examined calorie and carbohydrate consumption on days with and without hypoglycemia among adolescents with type 1 diabetes (T1D).

Methods: Days (N = 274) with 24-hour dietary recalls and continuous glucose monitoring were available for 122 adolescents with T1D in the Flexible Lifestyle Empowering Change trial (age 13-16 years, diabetes duration >1 year, hemoglobin A1c 8%-13%). Days with no hypoglycemia, clinical hypoglycemia (54-69 mg/dL) or clinically serious hypoglycemia (<54 mg/dL) were further split into night (12-5:59 am) and day (6 am-11:59 pm). Mixed models tested whether intake of calories or carbohydrates was greater on days with than without hypoglycemia.

Results: Fifty-nine percent, 23% and 18% of days had no hypoglycemia, clinical hypoglycemia and clinically serious hypoglycemia, respectively. Intake of calories and carbohydrates was not statistically significantly different on days with clinical hypoglycemia (57.2 kcal [95% CI -126.7, 241.5]; 12.6 g carbohydrate [95% CI -12.7, 38.0]) or clinically serious hypoglycemia (-74.0 kcal [95% CI -285.9, 137.9]; (-7.8 g carbohydrate [95% CI -36.8, 21.1]), compared to days without hypoglycemia. Differences by day and night were not statistically significant.

Conclusions: Among adolescents with T1D, daily intake of calories and carbohydrates did not differ on days with and without hypoglycemia. It is possible that hypoglycemic episodes caused by undereating relative to insulin dosing, followed by overeating, leading to a net neutral difference. Given the post-hoc nature of these analyses, larger studies should be designed to prospectively test the hypoglycemia-diet relationship.
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http://dx.doi.org/10.1111/pedi.13132DOI Listing
December 2020

The interplay of type 1 diabetes and weight management: A qualitative study exploring thematic progression from adolescence to young adulthood.

Pediatr Diabetes 2019 11 15;20(7):974-985. Epub 2019 Aug 15.

Department of Nutrition, University of North Carolina, Chapel Hill, North Carolina.

Background: The impact of weight management in persons with type 1 diabetes (T1D) from childhood into adulthood has not been well described. The purpose of the study was to explore qualitative themes presented by young adults with T1D with respect to the dual management of weight and T1D.

Methods: We analyzed focus group data from 17 young adults with T1D (65% female, age 21.7 ± 2.1 years, HbA1c 8.1% ± 1.5) via inductive qualitative analysis methods. Major themes were compared to themes presented by youth with T1D ages 13-16 years in previously published study in order to categorize thematic progression from early adolescence through adulthood.

Results: Themes from young adults with T1D, when compared to those from youth were categorized as: (a) persistent and unchanged themes, (b) evolving themes, and (c) newly reported themes. Hypoglycemia and a sense of futility around exercise was an unchanged theme. Importance of insulin usage and a healthy relationship with T1D evolved to gather greater conviction. Newly reported themes are unique to integration of adulthood into T1D, such as family planning and managing T1D with work obligations. Young adults also reported negative experiences with providers in their younger years and desire for more supportive provider relationships.

Conclusions: Issues identified by youth regarding the dual management of T1D and weight rarely resolve, but rather, persist or evolve to integrate other aspects of young adulthood. Individualized and age-appropriate clinical support and practice guidelines are warranted to facilitate the dual management of weight and T1D in persons with T1D.
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http://dx.doi.org/10.1111/pedi.12903DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196280PMC
November 2019

Gut-Brain Interactions: Implications for a Role of the Gut Microbiota in the Treatment and Prognosis of Anorexia Nervosa and Comparison to Type I Diabetes.

Gastroenterol Clin North Am 2019 09 25;48(3):343-356. Epub 2019 Jun 25.

Department of Nutrition, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, 101 Manning Drive, Chapel Hill, NC 27599, USA; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. Electronic address:

Anorexia nervosa has poor prognosis and treatment outcomes and is influenced by genetic, metabolic, and psychological factors. Gut microbes interact with gut physiology to influence metabolism and neurobiology, although potential therapeutic benefits remain unknown. Type 1 diabetes is linked to anorexia nervosa through energy dysregulation, which in both disease states is related to the gut microbiota, disordered eating, and genetics.
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http://dx.doi.org/10.1016/j.gtc.2019.04.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686879PMC
September 2019
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