Postprandial glucose has been linked to the development of chronic metabolic diseases

Postprandial glucose has been linked to the development of chronic metabolic diseases

Background

Postprandial glycemia has been implicated in the development of the chronic metabolic disease such as obesity, type 2 diabetes, and cardiovascular disease.

Methods

Male and female students in the NUTR 6332 spring 2020 course between 22 and 46 years of age and body mass index (BMI) 17 to 39 kg/m² were included in the study. Students who are allergic to the ingredients used in the test meal were excluded from the study.

Results

The average BMI was 26.49 kg/m², the average age of 30.70 years, an average of height was 64.5 inches, and an average weight of 157.95 pounds. The average (mean ± SD) age, body mass, height, and weight index was 30.70 ± 7.23 years, 26.49 ± 6.47 kg/m², 64.65 ± 3.23 inches, 157.95 ±42.53 respectively. The average (mean ± SD) of carbohydrate glucose concentration was 88.10 – 5.34, 80.40 – 7.71, 96.30 – 6.41, 125.20 -7.35, 143.70 – 16.28 and 115.30 – 17.66 at the interval of 0, 15, 30, 45, 60 and 90 respectively.  For the sandwich average (mean ± SD) 82.30 – 8.96, 95.60 – 11.27, 126.00 – 10.03, 141.80 – 6.14, 131.90 – 6.67 and 103.60 – 4.58 at the interval of 0, 15, 30, 45, 60 and 90 respectively.

Conclusion

The findings suggested that the timing of carbohydrate intake during a meal may have significant effects on postprandial glucose excursions.

Introduction

            Postprandial glucose has been linked to the development of chronic metabolic diseases like obesity, type 2 diabetes mellitus (T2DM), and cardiovascular disease (CVD) (Pedersen, 2017). It is the core determinant of glucose control at glycated hemoglobin (HbA1c) values below 7.3%. Since the quantity and type of Carbohydrate consumed in the body are the main predictors of glycemic response, it has led to the development of nutritional strategies that are aiming to reduce its effect. The effect of post-meal glucose can be reduced through proteins and fat preloads. It also is reduced by dietary fiber and modified macronutrient composition that entails proteins.

There is restricted information, nonetheless, with respect to the effect of the worldly success of starch ingestion during food intake on postprandial glycemia. In a past pilot investigation of 11 patients with metformin-treated T2DM, the research showed that the ingestion of protein and vegetables before starch prompted lower postprandial glucose. Furthermore, insulin outings for 120 min, contrasted, and eating similar nourishments in the turnaround request. No examination has examined the impacts of the planning of starch ingestion during a dinner on postprandial glucose, insulin, what’s more, incretin hormone outings.

A study done by Flatt proposed that people who continue to oxidize Carbohydrate in the post-absorptive state usually finish their endogenous carbohydrate stores, leading to food intake stimulation. Therefore, increasing food intake to help in replacing diminished carbohydrate stores and increasing storage of fats. It is also hypothesized that high postprandial fat oxidation may inhibit food intake (Leonhardt and Langhans, 2002). Through these mechanisms, inter-individual differences in substrate selection may have an impact on energy balance and may play a role in the development of obesity and subsequently, T2DM.

The objective of this study is to assess the postprandial glucose response based on macronutrient consumption of carbohydrates during the last meal. The study is based in a setting that will help in determining the effects of postprandial glycemia on the development of chronic metabolic diseases. The diseases include obesity, type 2 diabetes and cardiovascular. The assumption of the study was that a person consuming proteins and vegetables as the first course against taking Carbohydrate would help in lowering the post-meal glucose excursions. However, when a person consumes proteins, vegetables, and Carbohydrate at the same time will lead to reverse effects.

Research design and methods

Subject inclusion and exclusion criteria

            Male and female students in the NUTR 6332 spring 2020 course between 22 and 46 years of age and body mass index (BMI) 17 to 39 kg/m² were included in the study. Students who are allergic to the ingredients used in the test meal were excluded from the study.

Study protocol

Participants of the study were instructed to makes sure that they last for 12 hours before the begging of the exercise on Thursday at 6 am. They were warned on doing a strenuous activity on Wednesday; hence they were urged to be calm during that day and cat normally. Participants were cautioned against taking alcohol before taking part in the study. However, they were allowed to take water. They supposed to consume their breakfast on Thursday before 6 am. The breakfast

taken by the participants was supposed to consist of 30 g carbohydrates, 14 g protein, and 10 g fat.

The participants were expected to consume the test meal under 30 minutes and were randomly assigned to each condition:

1. First, they were to consume protein and fat over 10 minutes, then a 10 minutes interval. Carbohydrate was supposed to be consumed last over 10 minutes.
2. All meal components together as a sandwich with each half-consumed with half the orange juice over 10 minutes and a 10 minutes interval in between.

Participants were monitored closely to ensure that the consumption of all the meals was entirely within the time that was allocated to them. Blood samples were drawn from the participants, and blood glucose was measured using a glucometer (freestyle lite) at baseline (just before meal ingestion) and at 15, 30, 45, 60, and 90 minutes after ingestion.

Statistical Analysis

Demographics for participants were described as mean ± standard deviation. Glucose concentration means for Carbohydrate last was done on an interval of 0, 15, 30, 45, 60 and 90 minutes glucose concentration mean was calculated on the interval of 0, 15, 30, 45, 60 and 90 The sandwich and OJ incremental glucose peaks were also described as mean ± SEM. Linear mixed-effects models accounting for correlation within the same participant were implemented for each outcome of interest to compare the three groups. To get a graphical preview of the data of the experiment. The means of Carbohydrate last and sandwich OJ were placed against time under the interval of 0, 15, 30, 45, 60, and 90. Hence being able to do the analysis of glucose concentration.

Results

The study population included 20 participants students in NUTR 6332 spring 2020 course. The average BMI was 26.49 kg/m², the average age of 30.70 years, an average of height was 64.5 inches, and an average weight of 157.95 pounds. The average (mean ± SD) age, body mass, height, and weight index was 30.70 ± 7.23 years, 26.49 ± 6.47 kg/m², 64.65 ± 3.23 inches, 157.95 ±42.53 respectively. The average (mean ± SD) of carbohydrate glucose concentration was 88.10 – 5.34, 80.40 – 7.71, 96.30 – 6.41, 125.20 -7.35, 143.70 – 16.28 and 115.30 – 17.66 at the interval of 0, 15, 30, 45, 60 and 90 respectively.  For the sandwich average (mean ± SD) 82.30 – 8.96, 95.60 – 11.27, 126.00 – 10.03, 141.80 – 6.14, 131.90 – 6.67 and 103.60 – 4.58 at the interval of 0, 15, 30, 45, 60 and 90 respectively. The average from Carbohydrate last and sandwich OJ in the interval of 0,15, 30, 45, 60, and 90 minutes, are shown in the table below.

Table 2: Postprandial glucose levels

There was no difference between the two meals baseline glucose concentration conditions. Carbohydrate last (CL) had a decrease in the concentration at 15 minutes, then a significant increase in glucose concentration until at 60 minutes when it started decreasing. It had a decrease of 8.7% at 15 minutes. It then had an increase of 19.78%, 29.80%, 14.78% at 30, 45, and 60 minutes, respectively. It then had a reduction of 19.76% at 90. Sandwich OJ had a significant increment until 45 minutes when it experiences a decline. It increased by 13.3%, 31.80%, 12.54% at intervals of 15, 30 and 45 respectively. A decline of 6.98%,21.45% at an interval of 60 and 90 minutes, respectively. It can be noted that glucose production had minimal deviation between the two meals.

Discussion

In this investigation, there is a clear demonstration that the temporal sequence of carbohydrate ingestion during a meal has a significant role in impacting postprandial glucose regulation. The findings have clearly demonstrated that if a person consumes protein and vegetables first, then follow by Carbohydrate, it helps in reducing glucose. Focusing on the curve of the sandwich, it shows high rate production of glucose. Therefore, when a person combines carbohydrates and proteins at the same time there is higher production of glucose. The comparison between CL and SO shows that CL has a higher optimal level compared to CL in the production of glucose; hence eating Carbohydrate lasts leads to a higher optimal level for the production of glucose. The findings, therefore, suggest the timing of carbohydrate intake during a meal may have major effects on postprandial glucose excursions.

According to Stevenson, Thelwall, Thomas, Smith, Brand-Miller, and Trenell, (2009). The insulin reaction following sugar ingestion assumes two powerful jobs, invigorating glucose stockpiling as glycogen through the initiation of glycogen synthase and stifling nonesterified unsaturated fat (NEFA) discharge and, as an outcome, diminishing circling grouping of NEFA. Therefore, the postprandial insulin reaction makes a fine harmony between upgrading glycogen recuperation versus keeping up lipid accessibility, a fundamental fuel for continuance works out. In accordance with this, considers have indicated that sugars, which are quickly caught up in the course and produce a huge insulin reaction [termed high glycemic list (GI)], advance the pace of glycogen resynthesis and capacity after exercise. Alternately, we have, as of late, exhibited that transient taking care of blended meals varying by GI alone impacts both lipid accessibility and oxidation. A high-GI diet decreases NEFA accessibility and builds dependence on intramuscular lipid oxidation during exercise. The exchange between glycogen stockpiling in skeletal muscle and liver and NEFA accessibility and lipid oxidation following high-and low-GI recuperation slims down is essential to practice execution, yet as far as anyone is concerned is yet to be assessed. The point of the present investigation was to inspect the impact of recuperation diets of contrasting GI alone on glycogen stockpiling and use in skeletal muscle and liver, and lipid accessibility and use in skeletal muscle during ensuing activity. In particular, the examination planned to assess whether the concealment of circling NEFA and expanded dependence on intramuscular lipids following a high-GI recuperation diet was joined by an expansion in skeletal muscle and liver glycogen stockpiling and use.

According to Shukla et al. 2017, the arrangement of starch ingestion during a meal has huge sway on postprandial glucose guidelines. These discoveries affirm and expand results from our past pilot study, the incorporation of a third supplement request condition, a sandwich, effects affected glucose outings contrasted, and CL versus CF. Past examinations researching the impact of premeal ingestion of whey protein have exhibited that the glucose-bringing down impact is joined by an insulinotropic response. Interestingly, the outcomes illustrated that utilization of protein and vegetables first, followed via sugar, decreases both post-meal glucose furthermore, insulin trips, recommending that the CL feast design requires less insulin controlling for sugar sum. Adjusting the pace of supplement ingestion is a restorative rule of specific importance to diabetes. A conceivable clarification for the weakened glycemic reaction saw with the CL feast design is postponed gastric exhausting and thus more slow paces of starch retention, a component that would not be completely intervened by GLP-1. The finding of lower insulin iAUC with regards to expanded GLP-1 journeys appears differently in relation to the impact of protein preloads that enlarge both GLP-1 and insulin secretion and recommends a job for vegetable fiber in directing this reaction. The impact of nourishment request on postprandial glycemia right now tantamount to the greatness watched with pharmacological specialists that specially target postprandial glycemia; acarbose and Nateglinide decrease iAUCs by 31% and 64%, individually, contrasted and placebo. In non-insulin treated patients, oversaw with diet/oral hypoglycemic specialists, pramlintide was appeared to bring down glucose trips by 57%. Hence, suggest that the timing of carbohydrate intake during a meal may have major effects on postprandial glucose excursions comparable in magnitude to any hypoglycemic drugs.

Basing on this study, there is a need for people suffering from obesity, type 2 diabetes, and cardiovascular disease. Consider taking meals containing proteins and fats and then the finalize by taking of carbohydrates. It is because of the consumption of carbohydrates as the last meal helps in regulating the production of glucose. Trying to adapt new eating methods may end up essential since carbohydrate intake during a meal has a major impact on postprandial glucose excursions.

Conclusion

The main challenge to this study is that the sample size was small, and the issue of part of the selected sample that was excluded was allergic to the meals used in the experiment. The main strength of the study is the use of a well-designed study design and the application of real-world food in the research. From the study, it can be concluded timing of carbohydrate intake during a meal may have major effects on postprandial glucose excursions.

References

Flatt, J. P. (1996). Carbohydrate balance and body-weight regulation. Proceedings of the Nutrition Society, 55(1B), 449-465.

Leonhardt, M., & Langhans, W. (2002). Hydroxycitrate has long-term effects on feeding behavior, body weight regain, and metabolism after body weight loss in male rats. The Journal of nutrition, 132(7), 1977-1982.

Pedersen, B. K. (2017). Anti‐inflammatory effects of exercise: role in diabetes and cardiovascular disease. European Journal of clinical investigation, 47(8), 600-611.

Shukla, A. P., Andino, J., Touhamy, S. H., Casper, A., Iliescu, R. G., Mauer, E., … & Aronne, L. J. (2017). Carbohydrate-last meal pattern lowers postprandial glucose and insulin excursions in type 2 diabetes. BMJ Open Diabetes Research and Care, 5(1), e000440.

Stevenson, E. J., Thelwall, P. E., Thomas, K., Smith, F., Brand-Miller, J., & Trenell, M. I. (2009). Dietary glycemic index influences lipid oxidation but not muscle or liver glycogen oxidation during exercise—American Journal of Physiology-Endocrinology and Metabolism, 296(5), E1140-E1147.

Turton, M. D., O’shea, D., Gunn, I., Beak, S. A., Edwards, C. M. B., Meeran, K., … & Wilding, J. P. H. (1996). A role for glucagon-like peptide-1 in the central regulation of feeding. Nature, 379(6560), 69-72.