While the majority of evidence with weight loss as an outcome do not suggest any particular advantage to morning energy intake, from the perspective of glycaemic control particularly in states of impaired glucose tolerance there is consistent evidence of a benefit to morning energy intake compared to later meal initiation for postprandial glucose responses.

While the studies in the previous section compared morning energy vs. fasting until lunch, the distribution of energy across the day appears to be an important consideration for glycaemic control. Bandín et al. conducted a controlled feeding intervention in otherwise healthy, lean females [26].

The study had both breakfast and dinner occurring at the same times 8 a. and 8 p. or later 4 p. In response to the late lunch 4 p. lunch, and blunted carbohydrate oxidation. While the initial rise in glucose in response to both lunches was similar, what characterised the later lunch glucose profile was a prolonged elevation in blood glucose levels, consistent with the impaired glucose tolerance observed later in the day [27].

Cu et al. compared the metabolic effects of having dinner at 6 p. or at 10 p. The times of the other meals were matched between the diets. In response to the 10 p. dinner, both glucose and insulin remained significantly elevated from 11 p.

Glucose levels over the entire day were also significantly higher in response to the later dinner. Leung et al. investigated the effects of low-glycaemic index meals consumed at 8 a.

They showed that postprandial glucose levels were significantly greater after the later meals, compared to the meal at 8 a. After the midnight meal, glucose levels remained significantly elevated above baseline three hours after the meal, while in the 8 a. conditions glucose had returned to baseline after three hours.

Morgan et al. investigated the effects of temporal distribution in a controlled feeding study [30] , comparing:. Each of these conditions was also tested with both high and low glycaemic index GI meals. Jakubowicz et al. have also conducted a number of interventions considering energy distribution.

In one study in participants with type 2 diabetes [31] , they compared two 1, kcal interventions:. Further, the timing of the peak in insulin secretion, the magnitude of the peak in insulin, and the post-prandial area under the curce AUC for insulin were all impaired in response to the kcal dinner, compared to the kcal breakfast.

Image origally from: Circadian Eating Lecture - Danny Lennon. In the Bath Breakfast Project [32] , participants were randomised to either consume more than kcal before 11 a.

or to fast until lunch at 12 p. Metabolic control was improved in the high-energy morning group compared to morning fasting. There was improved insulin sensitivity in the breakfast group, observed in both lean participants and participants with obesity.

In addition, participants with obesity in the breakfast group had lower nocturnal blood glucose levels. There is also evidence of an effect of macronutrient distribution.

Pearce et al. compared the effects of distributing a majority of daily carbohydrates to breakfast or lunch, carbohydrates equally distributed between meals across the day, or majority of carbohydrates distributed to dinner, in participants with poorly controlled T2D [33].

Distributing a majority of carbohydrate to breakfast or lunch resulted in significantly lower daily glucose excursions, compared to equal distribution or a majority at dinner. Kessler et al. investigated the effects of diurnal distribution of carbohydrates and fats on glycaemic control in participants with impaired glucose tolerance and participants with normal glucose tolerance [34].

The study compared two diets:. Each meal sequence was consumed for 4-weeks in a crossover design. In sum, the diurnal variation in glucose tolerance across the day suggests that the distribution of energy and carbohydrate may influence postprandial glucose metabolism.

Interventions comparing both energy and carbohydrate distribution suggest enhanced glycaemic responses with earlier temporal distribution compared to evening distribution. Meal frequency has been theorised to be a strategy to improve overall glycaemic control, particularly for diabetes management.

Early research from Professor David Jenkins and colleagues suggested that 'nibbling' patterns of eating were preferable to 'gorging' patterns in participants with type 2 diabetes [35]. This gave rise to the idea that smaller, more frequent meals might be a better option than larger, less frequent meals.

A more recent study by Hibi et al. compared the blood glucose respose to a meal frequency of either nine meals per day or three meals per day [36]. The study had participants follow their meal frequency for three consecutive days, with blood glucose levels being constantly monitored with continuous glucose monitors CGM.

This was then followed by testing responses to an OGTT on the 4th day. The participants then crossed over and completed the experiment again with the opposite diet. The study included both participants with impaired and normal glucose tolerance.

CGM data indicated that while average hour blood glucose did not differ between meal frequency patterns, peak glucose levels were lower in the 9-meal condition and time spent in a hyperglycaemic state was higher with the 3-meal condition, regadless of the participants glucose tolerance.

In response to the test meal, there was no significant differences in glucose metabolism in those with normal glucose tolerance. However, those with impaired glucose tolerance showed a significantly lower glucose peak following the 9-meal condition.

However, there is also evidence to the contrary from other studies. In crossover intervention in participants with type 2 diabetes, Kahleova et al. compared the effects of two diet structures [37] :. Both diets targeted a kcal calorie deficit, and participants completed each diet for 12 weeks.

Fasting glucose levels decreased by 0. Fasting insulin and HbA1c were comparably reduced by both conditions.

However, in this study no data was presented on the distribution of energy and carbohydrates between meals. Image from: Kahleova et al. Data are shown as changes from baseline in response to the regimen of six A6 and two meals B2 a day. A more recent intervention by Jakubowicz et al.

compared different meal frequencies but also useful information about energy distribution across the day [38]. In the study they compared:. The primary outcome of the study was total daily insulin dose TDID , and the 3-meal group saw their daily insulin use drop by 26 units from 60 to 34 units per day after 12 weeks.

Conversely, the 6-meals-per-day diet saw their daily dosage increase by 4 units. Also measured was the amount of time spent hyperglycemic each day. The 3-meal diet saw daily hyperglycemia drop from 8hr 59min at baseline to 3hr 3min at weeks. While there was no change in the 6-meal group. Of note, the 3-meal diet led to a loss of ~5 kg bodyweight, compared to no change in the 6-meal group.

While this would be expected to influence the results, there was no correlation between body weight and TDID, suggesting that the reduction in TDID occurred - to an extent - independent of weight loss.

Thus, the findings in relation to meal frequency appear to be contradictory. However, it may be possible to reconcile the apparent differences. For fats, instead, the third largest intake took place in the afternoon. Followed by the evening hours, most of the remaining alcohol was consumed in the afternoon and midday.

In the morning and night hours, instead, the mean alcohol intake was negligible. The hourly distributions of the macronutrients revealed that fat and protein intakes exhibited four peaks similar to those seen for energy intake Fig.

For carbohydrate intake, instead, a fifth smaller peak emerged at , suggesting an afternoon snack of relatively high carbohydrate content. Alcohol intake showed a gradual increase from late afternoon onwards, with the highest intakes at Individuals skipping breakfast were younger with shorter diabetes duration, and they had a higher mean reported blood glucose concentration, as compared to those who reported eating breakfast Table 3.

While the total energy intakes between the two groups were comparable, those skipping breakfast reported higher energy intake at night, afternoon, and evening Table 4. Visual inspection of the energy distribution throughout the day suggested that those skipping breakfast had relatively high energy intake during midday, afternoon, and evening, with multiple but shallower peaks Fig.

Moreover, compared to those eating breakfast, energy, carbohydrate, fat, and protein intakes peaked at an earlier hour in the midday, and at a later hour in the evening Fig. Hourly distributions of energy and macronutrient intakes divided by breakfast consumption. A Energy intake by breakfast consumption.

B Macronutrient intakes by breakfast consumption. We then investigated whether skipping breakfast was associated with glycaemic control. Adjusted for sex, diabetes duration, smoking, energy intake, physical activity and mode of insulin administration, we observed that breakfast skipping was associated with reduced odds of achieving good glycaemic control Table 5.

Moreover, skipping breakfast was associated with higher mean of the reported blood glucose measurements adjusted means 8. The number of reported meals ranged from 3 to 20, with a median of 6 interquartile range from 5 to 8.

In this sample of Finnish adults with type 1 diabetes, a circadian eating pattern with four major peaks of energy intake, timed at breakfast, lunch, dinner, and evening meal, emerged. While protein and fat intakes mirrored that of total energy intake, an additional smaller peak of carbohydrate intake was observed in the afternoon.

Alcohol intake was most pronounced in the evening hours. The overall circadian profile of the energy intake in those skipping breakfast differed significantly from those reporting energy intake in the morning hours. Of interest, the mean energy intake of the breakfast skippers remained at high levels throughout the rest of the day, leading to a total energy intake comparable to those who reported eating breakfast.

Importantly, breakfast skipping was associated with higher mean values of daily blood glucose measurements and lower odds of reaching good glycaemic control. A median of 6 daily meals was reported in the current study.

Higher number of reported meals was associated with higher variability of the blood glucose measurements but better glycaemic control, measured as mean of the reported blood glucose concentrations and HbA 1c.

The question regarding the association between meal frequency and glycaemia has been addressed in a number of epidemiological studies among individuals with type 1 diabetes.

In one such study of adolescents with type 1 diabetes, similarly to the current observations, the reported number of meals was associated with lower HbA 1c 2. Øverby et al.

investigated the dietary practices of children and adolescents with type 1 diabetes 4. In their analyses, those who skipped meals were observed to have higher odds of suboptimal HbA 1c. Among the participants in the intensive treatment arm of the Diabetes Control and Complications Trial, instead, together with adherence to the prescribed diet, prompt treatment of hyperglycaemia, and avoidance of overtreatment of hypoglycaemia, avoidance of extra snacks appeared beneficial Along with the epidemiological studies of meal frequency and glycaemia, the question has also been addressed in a number of interventional trials.

In these trials, energy intake is typically kept constant with the number of meals being the only difference between the treatments. In one such study, 15 normal-weight middle-aged men and women underwent two 8-week diet interventions during which they consumed all the energy for weight maintenance in either 1 or 3 daily meals In a randomised cross-over design, the three meals were consumed at breakfast, lunch, and dinner, while in the one meal plan all foods were eaten during a four-hour time period in the early evening hours.

During the one meal dietary regimen, morning plasma glucose concentrations were significantly increased. Moreover, while fasting plasma insulin concentrations were not affected, the less frequent meal plan resulted in worse glucose tolerance as indicated by significantly greater and more prolonged elevation of plasma glucose concentrations.

Of importance, the detrimental effects on the glucose tolerance brought about by the one meal per day pattern were rapidly reversed upon returning to the thrice a day meal frequency, indicating that the diet caused no long-lasting effects on glucose metabolism.

In another study of 40 weight-stable women with polycystic ovary syndrome a 6-meal pattern significantly improved insulin sensitivity compared to a 3-meal pattern 5. Yet in another study among healthy lean men, two isoenergetic diets were consumed either over 3 or 14 daily eating occasions 9.

In that study, the area under curve of the hour glucose concentration was lower during the 3-meal plan, suggesting that extremely high eating frequencies may not be of additional benefit. In another study of multiple meals, however, mean blood glucose concentrations of healthy men were no different during interventions with 3 and 17 daily meals While we were not able to identify any interventions involving subjects with type 1 diabetes, a number of trials have been conducted among individuals with type 2 diabetes.

In one such study, for a duration of two weeks, the daily energy was consumed in random order as either three or eight meals 7. In that study, different meal frequencies were not associated with insulin sensitivity or the glucose and insulin responses to a high-carbohydrate test meal at the end of the intervention.

In another randomised crossover trial, individuals with type 2 diabetes followed a week weight-maintenance diet with either 3 or 6 daily meals 6. Finally, following an overnight fast, 12 individuals with type 2 diabetes were assigned in random order to two 8-hour observation periods During these periods, isoenergetic diets as either two or six meals were consumed.

Although, during the study period, there was no difference in the incremental blood glucose area between the interventions, the postprandial blood glucose fluctuations, insulin, and free fatty acid concentrations were lower with increasing meal frequency.

While there are differences in the methods used and populations investigated, in the studies described above, a cautious conclusion may be drawn that dividing the daily energy intake into multiple smaller meals may be of some benefit for individuals with type 1 diabetes.

Our observation showing that a higher number of meals was associated with better glycaemic control is in support of this conclusion. A number of phenomena may explain the benefit of dividing energy intake throughout the day.

First, spreading the nutrients into smaller meals could reduce the impact of glycaemic load at individual meals Second, distributing the total daily energy into multiple meals may be of benefit to individuals administering external insulin, as estimating carbohydrate content of the smaller meals is easier Finally, the elevated free fatty acid levels related to the increase in meal spacing is known to impact glucose metabolism by reducing insulin-mediated glucose disposal in the muscle, stimulating gluconeogenesis, and increasing hepatic glucose output.

While it is widely acknowledged that good glycaemic control is an important factor for the long-term vascular health, large variability of the blood glucose concentrations may additionally play a role in the pathology of end-organ damage in diabetes Therefore, identifying factors related to the blood glucose variability could be of importance.

Of interest higher number of meals, in the current study, was additionally associated with increased variability of the blood glucose measurements. It has to be acknowledged, however, that no data on hypoglycaemia episodes were available for the current analyses.

Moreover, we did not identify indications for food intake. Indeed, it is highly probable that a number of eating occasions took place in order to treat hypoglycaemia. Therefore, the observations related to the association between the number of meals and increased blood glucose variability could reflect the need to correct low blood glucose values upon experiencing hypoglycaemia.

To the best of our knowledge, the current study is amongst the first ones to describe the circadian energy intake and breakfast habits of adult individuals with type 1 diabetes.

Evident in girls, skipping breakfast and lunch were both associated with worse glycaemic control, while breakfast omission was additionally associated with higher eating disorder psychopathology including insulin omission due to weight concerns.

Similar to the previous observations 21 , breakfast omission in the current study was associated with a lower total number of meals.

However, as the energy intake of those reporting and not reporting eating breakfast was comparable, those omitting breakfast compensated for the missed morning energy intake during the subsequent eating occasions, suggesting a pattern of larger but fewer meals. Given the lower median meal frequency, this observation suggests that the breakfast skippers of the current study are, amongst themselves, quite heterogeneous in their meal timings.

The association between breakfast consumption and glycaemic fate has been investigated in various populations. In the Health Professionals Follow-Up Study, for example, eating patterns of 29, US men were assessed and participants were followed-up for 16 years Over that period, incident cases of type 2 diabetes were identified.

Amongst the clinical trials, in this field, is a randomised controlled trial by Betts et al. In their study, individuals fasting until noon for a 6-week period experienced increased glycaemic variability during afternoons and evenings. Instead, the practice of regularly consuming breakfast helped to maintain more stable blood glucose responses.

In another study with a randomised crossover design, Kobayashi et al. assessed the blood glucose concentrations of eight young men in two experimental conditions In one of the conditions, participants ate breakfast, lunch, and dinner, while in the other condition the same amount of energy was consumed at lunch and dinner times only.

Skipping breakfast increased the average blood glucose concentration during afternoon and sleep, subsequently resulting in overall increased hour average blood glucose concentration. Nas et al. investigated the glucose metabolism of healthy adults in conditions of breakfast skipping and dinner skipping In their study, compared to omitting dinner, breakfast skipping resulted in higher glucose concentrations and insulin resistance after lunch.

Moreover, the observed increase in post-lunch fat oxidation, occurring despite of increased insulin concentration, was suggestive of metabolic inflexibility after prolonged fasting.

Also, in type 2 diabetes, omission of breakfast was associated with an increased glycaemic response after lunch and dinner, when compared to the glycaemic responses taking place after lunch and dinner when breakfast was consumed Observations related to the breakfast omission, subsequent larger meals timed at later hours, and compromised glycaemic control may be related to a decrease in insulin sensitivity and glucose tolerance towards evening.

Indeed, independent of the behavioural cycle, postprandial blood glucose concentrations are significantly higher in the evening compared to the morning Of note, the above variations in glucose tolerance seemed to be explained by different mechanisms.

The decreased pancreatic beta cell function was effective during the evening, while decreased insulin sensitivity seemed to be behind the effect during circadian misalignment.

In line with the above observations, compared with a high-energy dinner, a high-energy breakfast resulted in greater improvements in fasting glucose, insulin, and insulin resistance, despite an overall similar energy intake throughout the day Moreover, following the lunch of similar energy contents, serum glucose and insulin responses were significantly lower when the high-energy breakfast was consumed.

The above described reduced glycaemia related to a meal consumed after breakfast is known as the second meal phenomenon. This phenomenon could be due to a breakfast-induced increase in beta cell responsiveness seen during the second meal. Here, beta cell memory and the magnitude of insulin release is enhanced by the earlier glucose exposure.

Of importance, the second meal phenomenon is not restricted to the post-breakfast lunch, but seems to persist throughout the day as breakfast omission not only worsened the postprandial glucose and impaired insulin secretion at lunch, but also at dinner We acknowledge that the current study was observational in nature and applied dietary data collected using a self-report method.

While some reservations may be related to the self-reported energy intake, we are not aware if the self-report method impacts the reporting of meals and their timings.

In the current analyses, data from only one day per participant were used. Whether the selected day is representative of the dietary practices of the participants at large, is not known.

HbA 1c was measured at the study visit, and was therefore measured prior to the dietary assessment. In case the reported dietary practices were not representative of the typical diet, the results relying on the reverse assessments of HbA 1c and dietary exposure could be biased.

The blood glucose measurements were, however, conducted at the time of the dietary assessment. A large study sample of well-characterised individuals and the use of a record instead of a memory-relying recall method to collect data on dietary intake and blood glucose measurements are also considered strengths of this study.

In conclusion, large variation in meal frequencies was observed in this sample of adult individuals with type 1 diabetes. Despite this, a pattern of 4 major peaks of energy intake was evident in the whole population. Individuals reporting and not reporting eating breakfast had comparable total energy intakes but distinctive patterns of circadian distribution of dietary energy.

Finally, our observations support the practice of a regular meal pattern, with breakfast and multiple smaller daily meals for better glycaemic control. Study subjects were participants of the Finnish Diabetic Nephropathy FinnDiane Study. Type 1 diabetes was defined as diabetes onset before the age of 40 years, and permanent insulin treatment initiated within a year from the diagnosis.

The Ethics Committee of The Helsinki and Uusimaa Hospital District approved the study protocol. The study was carried out in accordance with the relevant guidelines and regulations. Written informed consent was obtained from all individuals prior to study participation.

At the FinnDiane Study visit, participants were thoroughly examined. This included measurements of height, weight, and blood pressure. Non-fasting, early morning blood samples were collected and sent to a central laboratory to measure serum lipid and lipoprotein concentrations.

HbA 1c was measured at each study site using a photometric, enzymatic assay. Smoking was self-reported, and those reporting current smoking were identified for the analyses. Mode of insulin administration was self-reported.

Physical activity was assessed using a questionnaire on leisure-time physical activity as previously described Here, for the preceding 12 months, mean frequency, single session duration, and intensity of 21 common forms of leisure-time activities were assessed.

In order to calculate the physical activity as the metabolic equivalent of task hours METh , the activity- and intensity-specific metabolic equivalents were multiplied by the duration of the activity.

The METh was used as a continuous variable in the analyses. Two methods were used to assess dietary intake, as described by Ahola et al. In the questionnaire, the participants report their customary consumption habits of tea, coffee, liquid milk products, breads, spreads, cooking fats, salt, probiotics containing foodstuffs and dietary supplements.

Additionally, adherence to any special diets and to the dietary recommendations provided by the health-care personnel were queried.

Included was also a item food frequency questionnaire where, on a 7-level scale, the consumption frequencies of fish dishes, meat dishes, poultry, sausages and cold cuts, eggs, legumes, fresh vegetables, cooked vegetables, potatos, pasta and rice, fruits and berries, fatty cheese, low-fat cheese, yoghurt and curd, ice cream, soft drinks, sweet pastries, sweets and chocolates, and fried and grilled foods were reported.

The questionnaire has previously been validated in the FinnDiane Study population of participants with type 1 diabetes Upon returning the diet questionnaire, participants were sent an allocated 3-day diet record covering two weekdays and one weekend day consecutive Sunday-Tuesday or Thursday-Saturday.

Know portion sizes. Find the total amount of carbohydrates carbs in the meal. Add the carbs of each item in the meal together. Calculating the percentage of carbohydrates carbs that each item in the meal contributes. Example: To figure out the percentage of carbs the oatmeal contributes take 22 the oatmeal and divide it by 46 total carbs in the meal to get 0.

Verify the results from the previous step. All of the numbers calculated in the last step should add up to be 1. Find the value of each item on the glycemic index. com simply type in the name of the item into the search bar on their front-page.

Find the percentage glycemic value of each item. Take the percentage we calculated in step 3 for each item and multiply it by the GI value of that item. Example: Oatmeal: 0. Find the total glycemic value of the meal. Example: Oatmeal Find the total amount of dietary fiber.

Add the dietary fiber of each item in the meal together. This information can be found on the nutrition label of most foods. Find the net carbs. Take the total amount of carbs in the meal found in step 2 and subtract the total amount of dietary fiber from the last step.

Find the glycemic load of the meal. Take the total glycemic value of the meal from step 7 and multiply it by the net carbs of the meal from the previous step and then divide your answer by Example: All done! You now know the glycemic load of the meal. A glycemic load of under 10 is considered low and any glycemic load of over 20 is considered high.

In our example the meal has a glycemic load of Include your email address to get a message when this question is answered. Submit a Tip All tip submissions are carefully reviewed before being published.

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