Amount and Type of Dietary Fat, Postprandial

Diabetes Care Volume 43, January 2020 59 Kirstine J. Bell,1 Chantelle Z. Fio,1 Amount and Type of Dietary Fat, CLIN CARE/EDUCATION/NUTRITION/PSYCHOSOCIAL Stephen Twigg,1,2 Sally-Anne Duke,3 Postprandial Glycemia, and Gregory Fulcher,3 Kylie Alexander,3 Margaret McGill,2 Jencia Wong,2 Insulin Requirements in Type 1 Jennie Brand-Miller,1 and Garry M. Steil4,5 Diabetes: A Randomized Within-Subject Trial Diabetes Care 2020;43:59–66 | https://doi.org/10.2337/dc19-0687 OBJECTIVE The American Diabetes Association recommends individuals with type 1 diabetes (T1D) adjust insulin for dietary fat; however, optimal adjustments are not known. This study aimed to determine 1) the relationship between the amount and type of dietary fat and glycemia and 2) the optimal insulin adjustments for dietary fat. RESEARCH DESIGN AND METHODS Adults with T1D using insulin pump therapy attended the research clinic on 9–12 occasions. On the first six visits, participants consumed meals containing 45 g carbohydrate with 0 g, 20 g, 40 g, or 60 g fat and either saturated, monounsaturated, or polyunsaturated fat. Insulin was dosed using individual insulin/carbohydrate ratio as a dual-wave 50/50% over 2 h. On subsequent visits, participants repeated the 20–60-g fat meals with the insulin dose estimated using a model predictive bolus, up to twice per meal, until glycemic control was achieved. RESULTS 1Charles Perkins Centre, The University of Syd- With the same insulin dose, increasing the amount of fat resulted in a significant ney, Sydney, New South Wales, Australia 2Royal Prince Alfred Hospital Diabetes Centre, dose-dependent reduction in incremental area under the curve for glucose Sydney, New South Wales, Australia 3 (iAUCglucose) in the early postprandial period (0–2h;P = 0.008) and increase in Royal North Shore Hospital Diabetes Centre, – P Sydney, New South Wales, Australia iAUCglucose in the late postprandial period (2 5h; = 0.004). The type of fat made no 4 fi Harvard Medical School, Boston, MA signi cant difference to the 5-h iAUCglucose. To achieve glycemic control, on average 5Boston Children’s Hospital, Boston, MA participants required dual-wave insulin bolus: for 20 g fat, +6% insulin, 74/26% over Corresponding author: Kirstine J. Bell, kirstine 73 min; 40 g fat, +6% insulin, 63/37% over 75 min; and 60 g fat, +21% insulin, 49/51% [email protected] over 105 min. Received 5 April 2019 and accepted 21 July 2019 CONCLUSIONS Clinical trial reg. no. ACTRN12617000828325, www.anzctr.org.au This study provides clinical guidance for mealtime insulin dosing recommendations This article contains Supplementary Data online for dietary fat in T1D. at http://care.diabetesjournals.org/lookup/suppl/ doi:10.2337/dc19-0687/-/DC1. The impact of dietary fat on glycemia has been highlighted by those living with type 1 © 2019 by the American Diabetes Association. Readers may use this article as long as the work diabetes (T1D) who, despite accurate carbohydrate counting, have found glycemic is properly cited, the use is educational and not control difficult to achieve when consuming high-fat meals. Clinical research supports for profit, and the work is not altered. More infor- their experience, with dietary fat having been shown to modulate the postprandial mation is available at http://www.diabetesjournals glucose response in all seven studies included in a recent systematic review (1). We .org/content/license. have previously shown that in adults with T1D, the addition of both fat and protein to a See accompanying article, p. 13. 60 Dietary Fat and T1D Diabetes Care Volume 43, January 2020 carbohydrate meal doubled the glycemic (Royal Prince Alfred Hospital zone), and treated appropriately. Capillary BGLs response over 6 h and that insulin doses the trial was registered with the Australian were obtained at 0 min, 15 min, 30 need to be increased by an average of New Zealand Clinical Trials Registry min, 45 min, 1 h, 1.5 h, 2 h, 2.5 h, 65% to maintain glycemic control (2). (ACTRN12617000828325). 3 h, 3.5 h, 4 h, 4.5 h, and 5 h using a Given the diabetes complications arising In the 2 weeks prior to the first test HemoCue Glucose 201 Analyzer. from poor glycemic control, improving meal, participants’ glucose data were the insulin-dosing algorithm is an impor- reviewed by the clinical team and their Test Meals tant clinical priority. insulin pump rates adjusted as needed. Test meals consisted of equal amounts of The American Diabetes Association Participants also underwent a venous carbohydrate (pane di casa bread; 45 g recommends that fat and protein be blood test to determine baseline HbA1c, carbohydrate) and varying types or incorporated into mealtime insulin dos- C-peptide, cholesterol and triglycerides, amounts of dietary fat (Supplementary ing (3); however, the optimal insulin dose and C-reactive protein to assess glycemic Table 1). Four amounts of fat (0 g, 20 g, adjustments for dietary fat are unclear. control, endogenous insulin secretion, 40 g, and 60 g fat provided as avocado) Important clinical questions highlighted baseline lipids, and inflammation, respec- and three types of fat, which were rich in by our international collaborative review tively. Thereafter, participants were ad- monounsaturated fatty acid (MUFA), group (1) remain unanswered and are the mitted to the Charles Perkins Centre polyunsaturated fatty acid (PUFA), or focus of the current study in which we clinical research center on 9–12 occasions saturated fat (SFA) (all meals contained aimed to 1) determine the effect of to complete study sessions (number of 20 g of total fat as avocado, margarine, or amount and type of dietary fat on the sessions was dependent on the number of butter), were studied. Meals were all postprandial glucose response in adults attempts required to optimize glycemia). consumed with 250 mL of plain water. with T1D and 2) determine the insulin The order of test meals was randomized dose adjustments needed to achieve using a computer-generated random Insulin Dosing postprandial glycemic control following sequence prior to subjects beginning In aim 1, insulin doses for each partic- meals of varying fat content. the study (with meals being repeated ipant were calculated from their insulin/ We hypothesize that increasing the in aim 2 if target glucose control was not carbohydrate ratio (ICR) (i.e., same dose amount of fat in a meal will cause signif- achieved). Test meals and target glucose for each meal as the amount of carbo- icantly more hyperglycemia when meals control are defined below. hydrate was identical). Doses were de- are controlled with the same insulin dose In the 24 h prior to each test session, livered 15 min prior to consuming the (aim 1 hypothesis) or equivalently that a participants were instructed to avoid meal using a dual wave with a 50/50% meal containing more fat will require alcohol and exercise. On the day of split over 2 h in order to reduce the risk of more insulin to achieve postprandial gly- each session, participants were in- early hypoglycemia (and thus session cemic control (aim 2 hypothesis). structed to avoid, or minimize, insulin termination) known to occur with adjustments overnight to minimize dif- high-fat meals (1). For aim 2, insulin RESEARCH DESIGN AND METHODS ferences among study days and not make doses, including dual-wave split and du- This randomized, within-subject trial any manual insulin adjustments within ration, were estimated using a Model compared capillary postprandial glyce- 3 h of commencing their session. In the Predicted Bolus (MPB) estimator, as de- mia and insulin requirements for varying case of overnight hypoglycemia, they scribed below. types and amounts of dietary fat over 5 h were instructed to treat their glucose MPB in adults with T1D using insulin pump levels according to their usual practice, Optimal bolus amount, split, and dura- therapy. and their test session was rescheduled. tion for the high-fat meals was obtained Participants were included if they were Participants arrived at the Charles with the iterative model-predictive dos- aged 18–65years,hadbeendiagnosed Perkins Centre clinical research center at ing algorithm previously described (2). with T1D for $1 year, used insulin pump The University of Sydney between 7:00 Briefly, a two-step approach was used. In therapy $6 months, had HbA1c #8.5% and 9:00 A.M. after an overnight fast. On step 1, parameters defining a metabolic (69 mmol/mol), performed an average of arrival, a baseline capillary blood glucose model were identified from the blood fourormorebloodglucose checks per day, test was performed to confirm eligibility glucose response obtained in aim 1 to and were fluent in English. Participants to commence the testing session (fasting assess the response to meals containing were excluded if they were diagnosed glucose level: 4.0–10.0 mmol/L). If eligi- varying amounts of fat, obtained using with concurrent medical issues including ble, capillary blood samples were taken the patient’s ICR. In step 2, an optimal celiac disease or gastroparesis; had food 30, 15, and 0 min prior to consumption of dose and dual-wave split and duration allergies,intolerances,oreatingdisorders; the test meal, with the insulin dose were obtained by minimizing the sum were using medication(s), other than in- administered 15 min prior to consuming square difference between the model’s sulin, known to influence blood glucose the meal. Participants were given 12 min predicted response for that meal and the level (BGL); or were pregnant or lactating. to consume the test meal. Plain water patient’s target glucose value, subject Participants were recruited through Royal was permitted ad libitum from 1 h fol- to five constraints: 1) that hypoglycemia North Shore Hospital, Royal Prince Alfred lowing the test meal.

Load more