Calorie Cycling to Maximize Body Composition Outcomes for Bodybuilders in the Off-Season

Background

During the off-season, the main goal of a bodybuilder is to increase muscle size while minimizing increases in fat mass through the use of resistance training and maintaining positive energy balance (1). In order to accomplish this task, it is not only imperative for bodybuilders to consume a relatively high-protein diet (2) but one that is high in carbohydrates as well (3). The reason for this is multi-faceted. 

Bodybuilders traditionally utilize higher-repetition, moderate load training five to six times per week to promote skeletal muscle hypertrophy (4). This style of training primarily relies on glycolysis to provide ATP and results in great reductions in muscle glycogen stores. It has been reported that glycolysis provides ~82% of ATP demands during one set of biceps curls taken to the point of muscular failure (5). Furthermore, it has been shown that a single resistance training session can result in reductions in muscle glycogen stores by as much as 24-40% (5,6). 

As a result, adequate carbohydrate stores appear essential to fuel bodybuilding-style training and inadequate carbohydrate intake could impair performance and skeletal muscle hypertrophy adaptations. Indeed, a very-low-carbohydrate diet can limit the regeneration of ATP and the muscles’ ability to contract with high force (7,8).

Research has shown that a very-low-carbohydrate ketogenic diet is inferior to a higher carbohydrate diet for increasing muscle mass over an extended period (9,10). A possible explanation for these findings is that low glycogen availability, which is commonly observed with a very-low-carbohydrate ketogenic diet, may reduce the hypertrophic response to resistance training via inhibiting the mTOR pathway (11).

A high carbohydrate intake seems to be advantageous for other reasons as well. This includes its impact on recovery. The combination of carbohydrates and protein following resistance exercise could help reduce muscle damage (12). Sufficient carbohydrate intake is also critical to maintain immune health during intense high-volume training periods commonly employed by bodybuilders (13). Another benefit is that a surplus of calories from carbohydrates, in comparison to dietary fats, may lead to less accumulation of body fat(14). 

The Role of Insulin

Carbohydrates have a potent effect on insulin secretion and this hormone can positively influence skeletal muscle through reducing muscle protein breakdown (MPB) and increasing net balance protein acquisition (15). 

Insulin is primarily known for its role in nutrient storage. Some of its main metabolic effects include increasing the rate of transport of some amino acids into tissues, increasing the rate of protein synthesis in muscle and other tissues, decreasing the rate of protein degradation in muscle, increasing the rate of glucose transport across the cell membrane in muscle and adipose tissue, increasing the rate of glycolysis in muscle and adipose tissue, stimulating the rate of glycogen synthesis in muscle and other tissues, and inhibiting glycogenolysis and gluconeogenesis in the liver (16). For these reasons, insulin is generally referred to as an anabolic hormone that supports critical processes related to skeletal muscle adaptations.

While a caloric surplus consisting of a high proportion of carbohydrates is necessary to maximize accretions in muscle mass during a bodybuilder’s off-season, this style of diet can result in significant increases in body fat when used chronically (17). Excessive adipose tissue is an undesirable consequence for various reasons in this population. 

A primary concern of accumulating excess body fat is an increase in the duration or the severity of subsequent contest prep periods (1). Another concern of a chronic energy surplus is its impact on metabolic health. Higher levels of body fat coincide with an increased risk of type 2 diabetes (T2D) (18). This condition is characterized by a state of insulin resistance in skeletal muscle as well as impaired β-cell function. 

Insulin resistance is defined as an experimental or clinical condition in which insulin exerts a biological effect lower than expected. In insulin resistance, the target cells fail to respond to ordinary levels of circulating insulin (19). There is an impairment of glucose uptake in muscle accompanied by impaired glycogen synthesis and protein catabolism (19). This manifests as hyperglycemia both in the fasted and fed state. 

According to the American Diabetes Association, insulin resistance is evidenced by a fasting plasma glucose level ≥ 126 mg/dL, a two-hour postprandial plasma glucose ≥ 200 mg/dL following an oral glucose tolerance test of 75g of glucose, or an HbA1c ≥ 6.5% (20). Other markers of insulin sensitivity have been shown to be efficacious as well. This includes fasting insulin concentrations, which have been shown to significantly correlate with the metabolic clearance rate for glucose in healthy subjects (21).

It is generally accepted that the “gold standard method” to measure insulin resistance is through the hyperinsulinemic euglycemic clamp (22). This procedure assumes that at high doses of insulin infusion, the hyperinsulinemic state is sufficient to completely suppress hepatic glucose production and that there is no net change in blood glucose concentrations under steady state conditions (22). Under such conditions, the rate of glucose infused is equal to the rate of whole body glucose disposal or metabolizable glucose and reflects the amount of exogenous glucose necessary to fully compensate for hyperinsulinemia (22). 

The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and Quantitative Insulin Sensitivity Check Index (QUICKI) are other popular tools to measure insulin sensitivity. Both of these methods use fasting glucose and insulin concentrations to assess insulin resistance and have been reported to correlate reasonably well with the results of clamp studies (23). 

Insulin Sensitivity Affects Nutrient Partitioning

Individuals with normal weight and glucose tolerance are highly sensitive to insulin. In this population, skeletal muscle takes the major part of glucose uptake during hyperinsulinemia (75-80%), whereas a decrease in muscle glucose uptake is observed in insulin resistant individuals (24,25). 

It has been hypothesized that insulin resistance may protect skeletal muscle tissue from glucose overload by restraining glucose entry into cells (26). As a consequence of reduced uptake of nutrients in skeletal muscle, the storage of excess nutrients will be favored towards adipose tissue. Indeed, adipose tissue can act as a “glucose sink,” especially during periods of caloric excess (27). Very recent data has displayed a shift from insulin-induced skeletal muscle perfusion towards insulin-induced adipose tissue perfusion during the early stages of high caloric intake (28).  

Mitrou et al., compared glucose uptake in adipose tissue and skeletal muscle between obese and nonobese subjects (29). It was estimated that total muscle glucose uptake in nonobese subjects was equivalent to approximately 41% of meal carbohydrate ingested, whereas whole-body adipose tissue uptake was only 7%. 

In the obese subjects, only about 19% of ingested carbohydrate was taken up by muscle, while 17% was taken up by adipose tissue (29). This is in agreement with previous studies suggesting adipose tissue is not a major consumer of glucose in nonobese subjects (30), and an increase in the contribution of adipose tissue to whole-body glucose uptake occurs in those with obesity and/or T2D (31).

There is a strong link between body mass index (BMI) and body fat with abnormalities in glucose metabolism (32,33). Even in average fit, non-diabetic subjects, a correlation between fat mass and fasting blood glucose has been demonstrated (34). 

It cannot be certain whether insulin resistance is primarily driving fat accumulation, or if the presence of more fat is causing insulin resistance. Regardless, the two are strongly correlated and insulin sensitivity may play a primary role in the composition of weight-gain.

In line with these observations, it appears an individual’s baseline body composition is highly reflective of the composition of weight gain with overfeeding and this may be largely attributed to differences in insulin sensitivity. It has been reported that individuals with a higher initial body fat gain a smaller proportion of weight from fat free mass (FFM) (30-40%), while the weight gain of lean individuals comprises a much higher proportion of FFM (60-70%) (35).    

Related to this, it’s been shown that individuals with lower carbohydrate oxidation in response to insulin infusion during the hyperinsulinemic-euglycemic clamp experienced greater increases in fasting insulin, glucose, and HOMA-IR values after three days of overfeeding (36). These subjects also gained more total weight after 28 days of overfeeding (36). 

Together, the above findings suggest that greater insulin sensitivity could lead to superior body composition outcomes, or a more desirable proportion of FFM to fat mass with weight gain. In addition, less insulin sensitive individuals may efficiently store a higher percentage of excess calories in adipose tissue.

During periods of positive energy balance, both FFM and fat mass will contribute to changes in body weight. In the ideal scenario for a bodybuilder, insulin sensitivity would be high in skeletal muscle, resulting in the bulk of calories being funneled towards this tissue, and insulin sensitivity would be poor in adipose tissue, making it more difficult to store calories there (37). 

As such, for a bodybuilder to make the most of their off-season, it seems relevant to utilize a nutritional strategy that best manages insulin sensitivity. 

The Dynamic Nature of Insulin Sensitivity

Insulin sensitivity has been observed to rapidly adjust in response to substrate availability. Significant changes in the action of insulin have been observed with small perturbations in energy balance and without substantial changes in body weight over short time frames.

One day of overfeeding by 30% of estimated energy requirements (EER) has been shown to induce hepatic insulin resistance and increase nocturna plasma glucose and insulin concentrations in overweight/obese men (38,39). 

In another 24-hour overfeeding study, the effects of a more severe protocol (78% greater than daily energy requirements) in young healthy adults was examined. The results displayed a 28% decrease in whole-body insulin sensitivity as well as significant increases in plasma glucose and serum insulin in response to an oral glucose tolerance test (40). 

Significant reductions in insulin sensitivity have also been observed with three days of overfeeding in healthy subjects, and these consequences were only partially rescued by a bout of exercise (41). 

This dynamic nature of insulin sensitivity has been documented during acute periods of energy restriction as well. Total or modified fasting for 24-hours has been shown to significantly alter fasting glucose and insulin concentrations (42,43).

Considering the fact that insulin sensitivity rapidly adjusts in response to changes in energy intake, a nutritional strategy that modulates or “cycles” calories over the course of the week, such as intermittent fasting, could have a favorable effect on insulin sensitivity. 

Intermittent Fasting

Impact on Insulin Sensitivity

In recent years, intermittent fasting has attracted widespread interest as a dietary strategy to improve cardiometabolic outcomes and manage body weight (you can read more about the different types of intermittent fasting here). 

Over an acute timescale, severe energy restriction through complete fasting or modified fasting (energy restriction ≥ 70% of EER) elicits reciprocal shifts in fuel utilization in a seemingly dose-responsive manner; free fatty acid mobilization, fatty-acid oxidation, and ketogenesis progressively rise, favoring the conservation of glucose as its demand drops (44).  

From a chronic perspective, it has been speculated that these acute disturbances in fuel management may augment improvements in insulin sensitivity via the preferential reduction in the ectopic accumulation of lipid and associated cytosolic intermediaries, which are causally implicated in the development of insulin resistance (44).

Recent data has emerged demonstrating that intermittent fasting can significantly decrease fasting glucose levels and lower HOMA-IR independent of weight loss (45). Prior research on the topic has also confirmed marked improvements in insulin sensitivity can occur with energy restriction long before significant weight loss takes place (46,47,48,49). 

As previously alluded to, there are many different types of intermittent fasting, each featuring a different duration and amount of energy restriction. For these reasons, some variants might do a better job of improving insulin sensitivity than others. In order to examine the efficacy of each method, it’s important to assess their effects on insulin sensitivity in both the fasted and postprandial state. 

While it has been observed that complete fasting can improve fasted markers of insulin sensitivity (43), similar improvements have been observed with less severe energy restriction (42). In a study by Antoni and colleagues, the early metabolic responses to varying degrees of energy restriction were examined. Similar improvements in fasted blood glucose and insulin with partial (75%) and total (100%) energy restriction were found (50).

In further consideration, complete fasting has been shown to result in a subsequent reduction in insulin sensitivity as evidenced by hyperinsulinemic-euglycemic clamp (51,52). A worsening of insulin sensitivity following a fast has also been evidenced by significantly increased glucose and insulin responses to an oral glucose tolerance test (51,53).  

In combination, the above findings have raised concern about the frequency and severity of energy restriction. It has been hypothesized that approaches such as alternate day total fasting may present too great of a metabolic challenge and could lead to aberrant, rather than beneficial, changes in peripheral insulin sensitivity over time (44). 

Indeed, intermittent fasting interventions in human and rodent subjects that have reported consequences such as impaired glucose tolerance, increased markers of oxidative stress, reduced GLUT content, and/or reduced mitochondrial markers in skeletal muscle, have all used alternate day total fasting protocols (44).

The “5:2” Diet as a Solution?

Another form of intermittent fasting, known as the “5:2” diet, has shown more encouraging outcomes and could be a viable strategy for bodybuilders in the off-season. 

The 5:2 diet, commonly referred to as intermittent energy restriction (IER), features five days of regular eating patterns interchanged with two days of “fasting” or an energy intake of approximately 25% of EER (54). This method has been found to result in superior improvements in insulin concentrations as well as HOMA-IR compared to continuous energy restriction with equal weight loss between dietary interventions (55). 

Evidence of the beneficial effects of IER primarily stems from research conducted by Harvie et al. (56,57). The first of these experiments was conducted in a population of 107 overweight or obese women without diagnosed diabetes or cardiovascular disease (56). The participants were randomized to a 5:2 diet (IER) or continuous energy restriction (CER) for six months. 

At the end of the intervention, there was comparable weight loss between groups with a non-significant greater decline in waist measurement in the IER group. In addition, while both groups experienced declines in fasting insulin and HOMA-IR, greater reductions were observed in the IER group.

In another trial led by Harvie, 115 overweight women were randomized to one of three dietary interventions for a three-month weight loss phase (57). This was followed by a one-month weight maintenance period. 

Each of the diets aimed to achieve an energy deficit of 25% of EER over the course of the week. This was done through either daily energy restriction (DER), a 5:2 format (IECR), or a dietary pattern very similar to the IECR protocol, but with unlimited protein and fat (IECR + PF).

At the end of the three-month weight loss period, there was similar weight loss between conditions. The IECR and IECR + PF groups experienced significantly greater reductions in body fat than the DER group. The greatest reductions in fasting serum insulin and HOMA-IR were seen in the IECR group, with similar reductions observed between IECR + PF and DER. 

During the weight maintenance period, the two IECR groups reduced the frequency of their energy restriction days from twice to once per week and this was found to be sufficient to preserve improvements in insulin sensitivity. 

In addition to these trials, Wegman et al. found that a diet alternating days of 175% of normal caloric intake with 25% of normal caloric intake was able to decrease fasting insulin during a period of weight stability (58). While these results are interesting, it is worth mentioning that this study did not feature a control or comparator condition. Other trials examining differences in insulin sensitivity between a 5:2 regimen and CER have failed to find any significant differences in insulin sensitivity between conditions (59,60,61).

It is difficult to extrapolate the findings of these trials to the average bodybuilder. The primary reasons for this include the populations studied, the goal of the dietary intervention, and heterogeneity in the markers used to determine insulin sensitivity. 

In contrast to bodybuilders, the subjects featured in these studies tend to be overweight with low levels of muscle mass. Second, the overwhelming majority of interventions use IER as a strategy to induce weight loss. To the author’s knowledge, there are currently no published trials that use IER to facilitate a state of positive energy balance. Lastly, a number of trials reporting null findings only measured fasted blood glucose (62,63), which may be insufficient to determine changes in insulin sensitivity.  With these issues in mind, it’s clear more direct research is needed to prove the efficacy of cycling calorie intake over the course of the week during periods of positive energy balance. 

Nonetheless, concerning the data showing superior improvements in markers of insulin sensitivity with similar weight loss between dietary interventions (56,57), the ability to improve fasting insulin during weight maintenance (58), and an upregulation of beneficial pathways with caloric restriction that may be independent of changes in body fat (64,65,66), it remains conceivable that incorporating acute bouts of energy restriction could have advantages over a continuous calorie surplus.

For the aforementioned reasons, a 5:2 diet could better preserve insulin sensitivity over the course of a bodybuilder’s off-season, and ultimately, lead to superior body composition outcomes. The following sections will cover how to potentially set up a 5:2 diet. This includes recommendations for energy intake, macronutrient distribution, and food choices for the five energy surplus (high) and two energy restricted (low) days. 

High Days

Energy Intake 

Current evidence indicates that an energy surplus is required to maximize increases in FFM with resistance exercise (67), but the size of the energy surplus should differ depending on the training status of the individual. 

It has been demonstrated that untrained subjects can benefit from a very large energy surplus upwards of 2,000kcal per day (68). In the advanced lifter, a surplus of this magnitude will likely lead to significant increases in body fat without concomitant increases in FFM (69). As such, it has been recommended that novice or intermediate bodybuilders consume an energy surplus of 10-20% above EER and advanced bodybuilders consume an energy surplus of 5-10% above EER (1).  

Nutrient Timing

An intense resistance training workout results in the depletion of a significant portion of stored fuels and causes damage to muscle fibers. Following a bout of resistance exercise, exogenous nutrients are required to create an anabolic environment to support muscle hypertrophy (70). 

The post-exercise period has been commonly referred to as the “anabolic window.” Theoretically, consuming the proper ratio (or a greater proportion) of nutrients during this time not only initiates the rebuilding of damaged tissue and restoration of energy reserves, but it does so in a supercompensated fashion that enhances both body composition and exercise performance (70). 

Research in this area predominantly centers around the impact of different quantities and qualities of protein and carbohydrates following exercise, with protein playing the star role due to its profound effects on muscle protein synthesis (MPS) (71).

In regards to carbohydrates, provided dietary protein is supplied at a level that would optimize MPS, carbohydrate co-ingestion does not appear to have an additive effect on post-exercise muscle protein synthetic rates (71), though it may promote greater net anabolism via a suppression of MPB (72,73). In addition to what some may consider a trivial effect, there are definitive benefits of carbohydrate ingestion post-exercise for glycogen resynthesis. 

After examining the totality of the evidence, the International Society of Sports Nutrition has reported that the scientific literature currently supports the consumption of carbohydrates plus protein in close proximity to a training session to optimize the adaptive response to exercise as well as recovery for subsequent training bouts (12).

Another reason to funnel a large proportion of the daily carbohydrate allotment towards the post-exercise period is related to increases in insulin sensitivity. An increase in glucose tolerance post-exercise may last up to 48 hours (74).

Following exercise, muscle glycogen synthase activity and glucose transport are increased, and an enhanced metabolic action of insulin has been reported (74). These changes appear to be closely tied to the amount of glycogen depletion that occurs during the exercise bout (74). Put simply, the lower the glycogen content post-exercise, the stronger the response to insulin. 

For these reasons, it’s likely advantageous to dose a large proportion of daily carbohydrate intake towards the post-workout period, and this should scale upwards with the volume and intensity of the training session. Portioning carbohydrates towards this window of time should result in a better postprandial glucose profile, improved recovery, and a greater likelihood that this energy will be funneled towards skeletal muscle as opposed to adipose tissue.  

Most bodybuilders perform resistance exercise about five times per week (4). In comparison to a continuous energy surplus, the utilization of a modified 5:2 diet that aligns training days with high days will lead to a greater number of calories to portion towards the anabolic window and thus, could maximize skeletal muscle adaptations.

Macronutrient Composition

As detailed above, bodybuilders should consume a relatively high-carbohydrate diet for a multitude of reasons. It has been recommended that bodybuilders consume approximately 4-7 g/kg/day (3) or roughly 55-60% of energy intake from carbohydrates (75). 

In the context of adequate energy intake, a minimum protein intake of 1.6 g/kg/day seems sufficient to support increases in FFM (76). With that being said, for those looking to leave no stone unturned and ensure maximum skeletal muscle adaptations from resistance exercise, it’s probably worthwhile to pursue a higher intake of protein in the area of 2.2 g/kg/day (2,76). Within these guidelines for total protein intake, it is recommended that this amount be split between at least four meals, each containing 0.4-0.55 g/kg of protein (77). 

Dietary fat should comprise roughly 20% of total daily energy intake (75) or a minimum of 0.5 g/kg/day (1). Fat is an essential nutrient vital for many functions in the body, but not much is known about its role in regard to skeletal muscle hypertrophy. Considering the significant impact of protein and carbohydrates on skeletal muscle adaptations, and the absence of data suggesting any positive effect of increasing dietary fat intake, it seems reasonable to consume the minimum amount of fat necessary to ensure an adequate consumption of essential fatty acids and fat-soluble vitamins (78) in order to displace the most amount of energy possible towards the other macronutrients. 

Low Days

Energy Intake

Low days restrict energy intake in order to promote acute increases in insulin sensitivity. In theory, these acute increases could lead to improved management of insulin sensitivity in the long-term, and thus, help maximize body composition outcomes during a bodybuilder’s off-season.

There are two primary factors that must be considered when establishing the size of the deficit for low days: its effects on markers of insulin sensitivity and its effects on muscle protein synthesis (MPS). 

In comparison to total fasting, it appears that a modified fast (~25% of EER) is not only sufficient for improving insulin sensitivity, but superior (50). 

In a trial by Assali et al., subjects were randomly assigned to one of two hypo-energetic diets for six weeks. The low calorie diet featured an energy deficit of 33% of EER and the very-low calorie diet featured an energy deficit of 66% of EER (46). This was followed by a four-week weight maintenance phase and then six weeks on the alternate hypo-energetic diet. 

As a result of the intervention, significant increases in insulin sensitivity occurred. Most notably, two-thirds of this increase was seen during the first week of each hypo-energetic period. This suggests that an energy deficit of 33% of EER may be sufficient to promote acute increases in insulin sensitivity.

In the previously mentioned study conducted by Harvie et al., it was found that the 5:2 intervention that allowed ad libitum protein and fat consumption (IECR + PF) resulted in an energy deficit of approximately ~50% on “fasting” days and these bouts of energy restriction were sufficient to evoke acute reductions in insulin resistance (57). 

While the aforementioned energy deficits might be sufficient to induce acute increases in insulin sensitivity, this amount has also been shown to compromise the muscle protein synthetic response.  It has been demonstrated that a small energy deficit of 20% of EER can decrease basal MPS by 19% (79) and increase muscle fractional breakdown rate by 60% (80). 

However, numerous trials have now conclusively shown that resistance exercise combined with a protein intake of 1.6-2.4 g/kg/d can mitigate the decrease in MPS observed with energy restriction (81,82,83). Furthermore, increases in lean body mass have been documented in subjects undergoing a 40% energy deficit accompanied by a high protein diet (2.4 g/kg/d) and resistance exercise (84). 

While direct research is needed to tease out the nuances of this subject, the above findings suggest that an energy deficit of approximately 40%, in unison with resistance exercise and a minimum protein intake of 2.4 g/kg, is likely sufficient to induce acute increases in insulin sensitivity without compromising gains in FFM. 

Similar to this concept, Menno Henselmans has proposed the idea of utilizing a protein-sparing modified fast outside of the anabolic window (i.e. rest days) when elevations in MPS and insulin sensitivity are no longer evident (85). Anecdotally, he has reported that an energy intake of about 10x a protein intake of 2.2 g/kg is a sufficient minimum sustainable energy intake that does not possess an increased risk of muscle loss.

Macronutrient Composition

In order to counteract the reductions in MPS and increases in MPB observed with energy restriction, it is crucial to consume a higher protein intake on low days. The current evidence suggests that a minimum of 2.4 g/kg/day is likely sufficient to ensure the preservation of FFM (82,84), with an upper limit 3.5 g/kg/day being potentially beneficial as long as it does not displace sufficient fat or carbohydrate intake (86). 

For the ratio of carbohydrate to fat, in contrast to high days, a large proportion of energy from carbohydrates should be replaced by fat. More specifically, by unsaturated fat.

In a study conducted by Gadgil et al., participants followed three different diets for six weeks each (87). The CARB diet provided 58% of energy from carbohydrates, 15% from protein, and 27% from fat. The PROT diet replaced 10% of carbohydrate calories with protein and provided 48% of energy from carbohydrates, 25% from protein, and 27% from fat. The UNSAT diet replaced 10% of carbohydrate calories with unsaturated fat and provided 48% of energy from carbohydrates, 15% from protein, and 37% from fat. 

The increase in calories from fat primarily came from an increase in monounsaturated fat (MUFA) and featured sources such as olive, canola, and safflower oil as well as nuts and seeds. Each diet provided 6% of calories from saturated fat (SFA) and were designed to maintain a constant body weight. 

At the end of the trial, the researchers found that the UNSAT diet resulted in improvements in insulin sensitivity (as evidenced by improved QUICKI and HOMA-IR) to a greater degree than the CARB and PROT diets. These improvements were deemed both statistically and clinically significant. 

In further analysis of the results, it was revealed that normal weight participants experienced a greater increase in insulin sensitivity with the UNSAT diet compared to the CARB diet. This led the researchers to suggest that the choice of macronutrient to prevent insulin resistance is less important than overall weight loss in obese individuals, whereas partial replacement of carbohydrate with unsaturated fat can mitigate risk in those of normal weight.

The findings of this trial align closely with more recent reviews on the topic. In a systematic review and meta-analysis of randomized controlled feeding trials, MUFA consumption did not appear to significantly influence fasting glucose concentrations compared to other macronutrients. However, it was reported to reduce HbA1c and improve HOMA-IR in comparison to carbohydrate and SFA (88). 

In addition, isocaloric replacement of 5% of energy intake from either carbohydrates or SFA with polyunsaturated fat (PUFA) resulted in decreases in fasting plasma glucose, fasting plasma insulin, and HbA1c, and improved HOMA-IR and insulin secretion capacity (87). The improvement of some endpoints, such as insulin secretion capacity, remained even when substituting PUFA for MUFA. 

In another meta-analysis of randomized controlled feeding trials, the effect of plant-derived PUFA on markers of glucose metabolism and insulin resistance were examined primarily in non-diabetic subjects (89). It was found that plant-derived PUFA significantly decreased insulin concentrations and HOMA-IR. Moreso, subgroup analysis showed that studies with the highest PUFA dose (≥ 9% of energy increase) resulted in the greatest effects. 

Corresponding with these data points, large cohort studies have shown that circulating plasma PUFA levels, specifically, omega-3 and the omega-6 unsaturated fatty acid linoleic acid (18:2 ⍵-6), are inversely associated with T2D (90,91). 

The purported mechanism behind these findings is that PUFA can influence the action of insulin and modulate fuel partitioning in the cell. Increased PUFA intake may favorably alter cellular functions including membrane fluidity, ion permeability, and insulin receptor binding/affinity (92). PUFA can also upregulate the genes involved in lipid oxidation and downregulate the expression of genes coding for lipogenetic enzymes (93).

Liver fat content is a major determinant of insulin resistance and research on the topic suggests that the source of dietary fat determines its contribution to liver fat content.

In trials that compared consuming excess energy from SFA (palm oil) or PUFA (sunflower oil), significantly greater increases in liver and visceral fat content were found when additional calories were consumed from SFA, despite equal weight gain between groups (94,95).

Similar findings have been reported after ten weeks of an isocaloric diet either high in vegetable omega-6 PUFA or SFA mainly from butter (96). SFA has even been shown to result in a greater accumulation of liver fat than free sugars from candy and sugar-sweetened beverages (97). 

The current evidence indicates improvements in insulin sensitivity through an increase in energy intake from unsaturated fat, with the most robust improvements observed from increases in PUFA (omega-3 and omega-6 linoleic acid, specifically). This finding withstands whether you replace SFA or carbohydrates with PUFA (88). Concerning the primary importance of sufficient protein intake on low days, energy from carbohydrates will be reduced to account for increases in dietary fat.

How Much Dietary Fat?

Current evidence suggests that a very-high-fat or ketogenic diet has detrimental effects on insulin sensitivity. More specifically, while these diets have been shown to improve fasted markers of insulin sensitivity (98), they have also been shown to consistently result in impaired glucose tolerance.

In a study by Numao et al., healthy men consumed either a normal diet (67% carbohydrate, 22% fat, and 11% protein) or a low-carbohydrate high-fat diet (20% carbohydrate, 69% fat, and 11% protein) for three days each (99). An oral glucose tolerance test was performed after each three-day dietary intervention. 

The results displayed significantly higher plasma glucose concentrations during the oral glucose tolerance test in the low-carbohydrate high-fat condition. 

In another trial conducted in healthy men, subjects consumed three experimental diets (low-carbohydrate high-fat, intermediate-carbohydrate intermediate-fat, or control) for three days each (100). An oral meal tolerance test was performed after each three day dietary intervention. 

The control diet (C) consisted of 10% of daily energy intake from protein, 30% from fat, and 60% from carbohydrates. The intermediate-carbohydrate intermediate-fat diet (ICIF) consisted of 10% of daily energy intake from protein, 50% from fat, and 40% from carbohydrates, and the low-carbohydrate high-fat diet (LCHF) consisted of 10% of daily energy intake from protein, 70% from fat, and 20% from carbohydrates. 

In comparison to C, it was found that the LCHF diet excessively increased postprandial glucose concentrations and the intake of ICIF and C had similar effects on postprandial glucose metabolism.

Other trials using an intravenous glucose tolerance test (101) or euglycemic hyperinsulinemic clamp (102), did not observe decreases in insulin sensitivity with a diet containing ~50% of daily energy intake from fat compared to a high-carbohydrate control diet. 

Overall, it appears that a short-term intake of a diet containing ≥70% of daily calories from fat may aggravate postprandial metabolism, whereas a diet containing <50% of daily calories from fat may have little effect (100).

These results can be largely explained by changes in the enzymatic regulation of glucose disposal in human skeletal muscle. Glycogen synthase and pyruvate dehydrogenase are the rate-limiting enzymes that control glycogen synthesis and glucose oxidation in skeletal muscle (103). 

Decreased skeletal muscle glucose disposal via rapid reductions in pyruvate dehydrogenase has been observed with as little as 56-hours of a high-fat low-carbohydrate diet (103). In addition, glucose intolerance may be related to hepatic fat accumulation, and as a consequence, hepatic insulin resistance, resulting in the inability of insulin to suppress hepatic glucose output (104).

The above information might not be relevant to dedicated followers of the ketogenic diet, as they would not be experiencing oscillations in glucose-stimulated insulinemic conditions, but it is particularly relevant in the context of a modified 5:2 diet where low days are followed by high days with large volumes of carbohydrates. 

The long-term health effects of acute impairments in glucose tolerance are currently unknown, but research on the matter suggests an association between postprandial hyperglycemia and increased cardiovascular risk and mortality (105,106,107,108). Moreso, acute fluctuations in blood glucose levels can induce vascular endothelial dysfunction (109), oxidative stress, and inflammation (109).  

In consideration of these findings, a dietary fat intake of approximately 35-40% of calories on low days could be best in order to prevent blood glucose excursions on the days following. 

Food Choices: The Role of Polyphenols

A dietary fat intake of 35-40% of total energy closely aligns with what is found in the Mediterranean diet (MedDiet). The MedDiet is a plant-based, fat-rich dietary pattern characterized by a high intake of fruits, vegetables, legumes, fish, whole-grains, nuts, and olive oil; moderate consumption of dairy products and wine; and low intake of red and processed meats and foods that contain high amounts of added sugars.

Both epidemiological and intervention studies have shown promising results from following a MedDiet. This includes the diet’s ability to positively impact cardiometabolic outcomes and decrease the risk for conditions such as metabolic syndrome, cardiovascular disease, and diabetes (110). Higher adherence to a MedDiet is not only associated with a lower risk of T2D, but also with a 35% lower risk of impaired fasting glucose (111), and lower insulin concentrations in non-diabetic subjects (112).

In further advocacy of following a dietary approach similar to the MedDiet on low days, the primary carbohydrate sources in the diet have been shown to positively influence insulin sensitivity. Observational and interventional investigations provide evidence that habitual intake of vegetables and legumes enhances insulin sensitivity in non-diabetic subjects (113).  In addition, a high-intake of insoluble cereal fibers, or whole-grain products rich in cereal fibers, may reduce insulin resistance and the risk of developing T2D by 20-30% (114). 

The nutrient density in the complex matrices of plant foods, together with a low glycemic load, likely explain the lower risk of metabolic syndrome and T2D observed with higher adherence to the MedDiet (115). The rich composition of bioactive nutrients and phytochemicals within the diet also seem to positively impact cardiometabolic health via their synergizing effects on different metabolic pathways (115). 

Polyphenols are a large heterogeneous group of phytochemicals containing phenol rings and are divided into flavonoids, phenolic acids, stilbenes, and lignans (116). Flavonoids are classified into flavones, flavonols, flavanols, flavanones, isoflavones, and anthocyanins (116). Polyphenols are the most abundant antioxidants in the diet and their intake has been associated with a reduced incidence of T2D, anti-inflammatory effects, and improvements in insulin sensitivity (117). Furthermore, there appears to be a dose-response nature between total intake of polyphenols and the magnitude of their effect in some instances (118).

Several potential mechanisms have been proposed to explain the hypoglycemic effects of dietary polyphenolic compounds. This includes the inhibition of glucose absorption, as well as the stimulation of insulin secretion, and protection of pancreatic β-cells against glucotoxicity (119). Polyphenols may also improve glucose uptake in peripheral tissues by modulating intracellular signaling (120).

Among all polyphenols, the beneficial effects of flavanols and their primary food sources (cocoa, chocolate, and red wine), have been the most extensively examined. In two separate meta-analyses, improvements in insulin sensitivity have been reported with increased intakes of cocoa and chocolate over a period of 2-18 weeks (121,122). Another source of flavanols, green tea, has been thoroughly studied. In a meta-analysis of 17 randomized controlled trials (RCTs), significant reductions in fasting glucose and HbA1c were reported with green tea consumption (123). 

Following suit with other popular beverages, coffee has been shown to have positive effects on insulin sensitivity. Its benefits are primarily attributed to its chlorogenic acid content. Numerous reviews have associated the habitual consumption of caffeinated or decaffeinated coffee with a lower risk of T2D (124,125). Results from the Nurses’ Health Study II reported that, compared to nondrinkers, a daily intake of at least four cups of coffee was associated with a 47% lower incidence of T2D (126). The observed positive effects of coffee on T2D risk might also be independent of BMI (127). 

Red wine is rich in phenolic compounds including flavonoids and stilbenes like resveratrol. In a randomized crossover trial comparing the effects of a moderate intake of red wine, an equivalent amount of dealcoholized red wine, and gin for four weeks, it was found that red wine with or without alcohol, but not gin, improved glucose metabolism as measured by HOMA-IR (128). In another study, it was found that consuming 150 mL of red wine with dinner modestly reduces cardiometabolic risk in type 2 diabetics (129). 

Transitioning to foods rich in polyphenols, extra-virgin olive oil includes several phenolic components such as oleuropein and hydroxytyrosol, flavones, and lignans (115). Evidence from the PREDIMED trial has shown that a MedDiet supplemented with extra-virgin olive oil can reduce fasting plasma glucose, and improve insulin resistance and inflammatory biomarkers (130,131).

The impact of nut consumption on insulin sensitivity has been assessed in many clinical trials with a variety of subject characteristics and intervention durations. Several trials have mainly tested the effects of walnuts and almonds and mixed results have been reported (132). In comparison, a meta-analysis of RCTs found that the consumption of tree nuts (~50 g/d) can modestly decrease triglycerides and fasting blood glucose (133).

Total fruit and vegetable intake is inversely associated with a variety of adverse health outcomes (134) and specific plants may possess unique benefits. For example, an increase in the consumption of green leafy and cruciferous vegetables is associated with a significantly reduced risk of T2D (135,136). 

Muraki et al. assessed the relationship of fruit intake with T2D risk and found the strongest inverse associations for blueberries, grapes/raisins, and apples/pears (137). Anthocyanins, a sub-class of flavonoids, appear to be especially potent. 

After pooling the results of three large cohorts, a higher intake of anthocyanin-rich fruits were found to be associated with a decreased risk of T2D, even when adjusting for multiple potential confounders (138). Berries are a particularly abundant source of anthocyanins. Blueberries have been shown to significantly improve insulin sensitivity measured by  hyperinsulinemic-euglycemic clamp (139). 

Conclusion

In this article, a modified version of the 5:2 diet is proposed as a nutritional strategy for bodybuilders in the off-season. In comparison to a continuous energy surplus, it is hypothesized that incorporating acute periods of energy restriction, combined with shifts in macronutrient distribution, could better preserve insulin sensitivity during a phase of positive energy balance, leading to a more desirable proportion of FFM to fat mass with weight gain.

While this model is largely speculative, and as such, needs direct research to prove its efficacy and effectiveness, the body of evidence suggests that this could be a plausible way to maximize body composition outcomes. Furthermore, if this approach is in fact superior, the effects would likely be trivial, and only begin to surface over an extended period of time. For these reasons, this is a nutritional strategy reserved for advanced athletes looking to eek out every percent advantage they can gain on their competition, or those who simply prefer to cycle their calorie intake over the course of the week.

Practical Application

High

Diet ComponentRecommendation
CaloriesNovice to intermediate: 10-20% above EERAdvanced: 5-10% above EER
ProteinMinimum 1.6 g/kg (aim for 2.2 g/kg/d if possible within calorie constraints)
Fat~20% of total calories (minimum of 0.5 g/kg)
Carbohydrates55-60% of total calories (at least 4 g/kg if possible within calorie constraints)

Low

Diet ComponentRecommendationFood Choices
Calories40% below EER
ProteinMinimum 2.4 g/kg
Fat35-40% of total calories (emphasis on PUFA)Vegetable oils (extra virgin olive, canola, soybean, safflower, etc.), nuts, seeds, dark chocolate, avocado, fatty fish (salmon, sardines, etc.), dairy (cheese, yogurt, etc.), egg yolks.
CarbohydratesRemaining caloriesWhole-grain starches (pasta, oatmeal, brown rice, etc.), legumes (peas, beans, lentils, etc.), fruits (berries, grapes, apples, etc.), vegetables (green leafy, broccoli, brussel sprouts,, etc.)

Example Calculation

Intermediate bodybuilder (energy surplus 15% above EER)

  • EER = 2500 calories 
  • Total weekly calories = 20,125 calories
    • Low day (2) = 1500 calories
    • High day (5) = 3425 calories

References

  1. Iraki J, Fitschen P, Espinar S, Helms E. Nutrition Recommendations for Bodybuilders in the Off-Season: A Narrative Review. Sports (Basel, Switzerland). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680710/. Published June 26, 2019. Accessed June 23, 2020.
  2. Ribiero AS, Nunes JP, Schoenfeld BJ. Should Competitive Bodybuilders Ingest More Protein than Current Evidence-Based Recommendations? Sports Medicine. https://link.springer.com/article/10.1007/s40279-019-01111-y?shared-article-renderer. Published April 26, 2019. Accessed June 23, 2020.
  3. Slater G, Phillips SM. Nutrition guidelines for strength sports: Sprinting, weightlifting, throwing events, and bodybuilding. Taylor & Francis. https://www.tandfonline.com/doi/full/10.1080/02640414.2011.574722. Published March 21, 2011. Accessed June 23, 2020.
  4. Hackett DA, Johnson NA, Chow C-M. Training Practices and Ergogenic Aids Used by Male Bodybuilders. The Journal of Strength and Conditioning Research. https://journals.lww.com/nsca-jscr/Fulltext/2013/06000/Training_Practices_and_Ergogenic_Aids_Used_by_Male.20.aspx. Published June 2013. Accessed June 23, 2020.
  5. MacDougall JD, Ray S, Sale DG, McCartney N, Lee P, Garner S. Muscle Substrate Utilization and Lactate Production. Canadian journal of applied physiology = Revue canadienne de physiologie appliquee. https://pubmed.ncbi.nlm.nih.gov/10364416/. Published June 24, 1999. Accessed June 23, 2020.
  6. Tesch PA, Colliander EB, Kaiser P. Muscle metabolism during intense, heavy-resistance exercise. European Journal of Applied Physiology. https://link.springer.com/article/10.1007/BF00422734. Published August 1986. Accessed June 23, 2020.
  7. Leveritt M, Abernethy PJ. Effects of Carbohydrate Restriction on Strength Performance . The Journal of Strength and Conditioning Research. https://journals.lww.com/nsca-jscr/abstract/1999/02000/effects_of_carbohydrate_restriction_on_strength.10.aspx. Published February 1999. Accessed June 23, 2020.
  8. Jacobs I, Kaiser P, Tesch P. Muscle Strength and Fatigue After Selective Glycogen Depletion in Human Skeletal Muscle Fibers. European journal of applied physiology and occupational physiology. https://pubmed.ncbi.nlm.nih.gov/7194784/. Published 1981. Accessed June 23, 2020.
  9. Vargas S, Romance R, Petro JL, et al. Efficacy of ketogenic diet on body composition during resistance training in trained men: a randomized controlled trial. Journal of the International Society of Sports Nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6038311/. Published July 9, 2018. Accessed June 23, 2020.
  10. Vargas-Molina S, Petro JL, Romance R, et al. Effects of a ketogenic diet on body composition and strength in trained women. Journal of the International Society of Sports Nutrition. https://jissn.biomedcentral.com/articles/10.1186/s12970-020-00348-7. Published April 10, 2020. Accessed June 23, 2020.
  11. Mata F, Valenzuela PL, Gimenez J, et al. Carbohydrate Availability and Physical Performance: Physiological Overview and Practical Recommendations. Nutrients. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6566225/. Published May 16, 2019. Accessed June 23, 2020.
  12. Kerksick CM, Arent S, Schoenfeld BJ, et al. International society of sports nutrition position stand: nutrient timing. Journal of the International Society of Sports Nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5596471/. Published August 29, 2017. Accessed June 23, 2020.
  13. Walsh NP. Recommendations to Maintain Immune Health in Athletes. European journal of sport science. https://pubmed.ncbi.nlm.nih.gov/29637836/. Published July 18, 2018. Accessed June 23, 2020.
  14. Horton TJ, Drougas H, Brachey A, Reed GW, Peters JC, Hill JO. Fat and carbohydrate overfeeding in humans: different effects on energy storage. OUP Academic. https://academic.oup.com/ajcn/article-abstract/62/1/19/4651677?redirectedFrom=fulltext. Published July 1, 1995. Accessed June 23, 2020.
  15. Abdulla H, Smith K, Philip J., Idris I. Role of Insulin in the Regulation of Human Skeletal Muscle Protein Synthesis and Breakdown: A Systematic Review and Meta-Analysis. Diabetologia. https://pubmed.ncbi.nlm.nih.gov/26404065/. Published September 24, 2015. Accessed June 23, 2020.
  16. Dimitriadis G, Mitrou P, Lambadiari V, Maratou E, Raptis SA. Insulin effects in muscle and adipose tissue. Diabetes Research and Clinical Practice. https://www.sciencedirect.com/science/article/abs/pii/S0168822711700146. Published August 21, 2011. Accessed June 23, 2020.
  17. Ribiero AS, Nunes JP, Schoenfeld BJ, Aguiar AF, Cyrino ES. Effects of Different Dietary Energy Intake Following Resistance Training on Muscle Mass and Body Fat in Bodybuilders: A Pilot Study. Journal of human kinetics. https://pubmed.ncbi.nlm.nih.gov/31915482/. Published November 30, 2019. Accessed June 23, 2020.
  18. Peña JE-de la, Ramírez-Hernández JA, Fernández-Ramos MT, González-Figueroa E, Champagne B. Body Fat Percentage Rather than Body Mass Index Related to the High Occurrence of Type 2 Diabetes. Archives of Medical Research. https://www.sciencedirect.com/science/article/abs/pii/S0188440919310045. Published May 29, 2020. Accessed June 23, 2020.
  19. Ormazabal V, Nair S, Elfeky O, Aguayo C, Salomon C, Zuñiga FA. Association between insulin resistance and the development of cardiovascular disease. Cardiovascular diabetology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6119242/. Published August 31, 2018. Accessed June 23, 2020.
  20. American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2020. Diabetes Care. https://care.diabetesjournals.org/content/43/Supplement_1/S14. Published January 1, 2020. Accessed June 23, 2020.
  21. Gupta AK, Jain SK. A Study to Evaluate Surrogate Markers of Insulin Resistance in Forty Euglycemic Healthy Subjects. The Journal of the Association of Physicians of India. https://pubmed.ncbi.nlm.nih.gov/15645980/. Published July 2004. Accessed June 23, 2020.
  22. Tam CS, Xie W, Johnson WD, Cefalu WT, Redman LM, Ravussin E. Defining insulin resistance from hyperinsulinemic-euglycemic clamps. Diabetes care. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3379600/. Published July 2012. Accessed June 23, 2020.
  23. Park SE, Park C-Y, Sweeney G. Biomarkers of Insulin Sensitivity and Insulin Resistance: Past, Present and Future. Critical reviews in clinical laboratory sciences. https://pubmed.ncbi.nlm.nih.gov/26042993/. Published June 4, 2015. Accessed June 23, 2020.
  24. Defronzo RA. Banting Lecture. From the triumvirate to the ominous octet: a new paradigm for the treatment of type 2 diabetes mellitus. Diabetes. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2661582/. Published April 2009. Accessed June 23, 2020.
  25. Honka M-J, Latva-Rasku A, Bucci M, et al. Insulin-stimulated glucose uptake in skeletal muscle, adipose tissue and liver: a positron emission tomography study. European journal of endocrinology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5920018/. Published May 2018. Accessed June 23, 2020.
  26. Nolan CJ, Ruderman NB, Kahn SE, Pedersen O, Prentki M. Insulin Resistance as a Physiological Defense Against Metabolic Stress: Implications for the Management of Subsets of Type 2 Diabetes. Diabetes. https://diabetes.diabetesjournals.org/content/64/3/673. Published March 1, 2015. Accessed June 23, 2020.
  27. Mitrou P, Raptis SA, Dimitriadis G. Insulin Action in Morbid Obesity: A Focus on Muscle and Adipose Tissue. Hormones (Athens, Greece). https://pubmed.ncbi.nlm.nih.gov/23933689/. Published 2013. Accessed June 23, 2020.
  28. Emanuel AL, Meijer RI, Woerdeman J, et al. Effects of a Hypercaloric and Hypocaloric Diet on Insulin-Induced Microvascular Recruitment, Glucose Uptake, and Lipolysis in Healthy Lean Men. Arteriosclerosis, Thrombosis, and Vascular Biology. https://www.ahajournals.org/doi/abs/10.1161/ATVBAHA.120.314129. Published May 14, 2020. Accessed June 23, 2020.
  29. Mitrou P, Boutati E, Lambadiari V, et al. Rates of Glucose Uptake in Adipose Tissue and Muscle in Vivo after a Mixed Meal in Women with Morbid Obesity. OUP Academic. https://academic.oup.com/jcem/article/94/8/2958/2597085. Published August 1, 2009. Accessed June 23, 2020
  30. Coppack SW, Fisher RM, Humphreys SM, Clark ML, Pointon JJ, Frayn KN. Carbohydrate Metabolism in Insulin Resistance: Glucose Uptake and Lactate Production by Adipose and Forearm Tissues in Vivo Before and After a Mixed Meal. Clinical science (London, England : 1979). https://pubmed.ncbi.nlm.nih.gov/8665779/. Published May 1996. Accessed June 23, 2020.
  31. Virtanen KA, Iozzo P, Hällsten K, et al. Increased Fat Mass Compensates for Insulin Resistance in Abdominal Obesity and Type 2 Diabetes. Diabetes. https://diabetes.diabetesjournals.org/content/54/9/2720.long. Published September 1, 2005. Accessed June 23, 2020.
  32. Abbasi A, Juszczyk D, van Jaarsveld CHM, Gulliford MC. Body Mass Index and Incident Type 1 and Type 2 Diabetes in Children and Young Adults: A Retrospective Cohort Study. Journal of the Endocrine Society. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5686575. Published April 25, 2017. Accessed June 23, 2020.
  33. Zegarra-Lizana PA, Ramos-Orosco EJ, Guarnizo-Poma M, et al. Relationship between body fat percentage and insulin resistance in adults with Bmi values below 25 Kg/M2 in a private clinic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. https://www.sciencedirect.com/science/article/abs/pii/S1871402118306283?via=ihub. Published July 27, 2019. Accessed June 23, 2020.
  34. Preuss HG, Kaats GR, Mrvichin N, Aruoma OI, Bagchi D. Interplay Between Insulin Resistance and Body Fat Mass in Evolution of Perturbations Linked to the Metabolic Syndrome in Non-Diabetics: Emphasis on Inflammatory Factors. Taylor & Francis. https://www.tandfonline.com/doi/abs/10.1080/07315724.2020.1792376. Published August 6, 2020. Accessed August 21, 2020.
  35. Forbes GB. Body Fat Content Influences the Body Composition Response to Nutrition and Exercise. The New York Academy of Sciences. https://nyaspubs.onlinelibrary.wiley.com/doi/abs/10.1111/j.1749-6632.2000.tb06482.x?sid=nlm:pubmed. Published January 25, 2006. Accessed June 23, 2020.
  36. Samocha-Bonet D, Campbell LV, Viardot A, et al. A Family History of Type 2 Diabetes Increases Risk Factors Associated With Overfeeding. Diabetologia. https://pubmed.ncbi.nlm.nih.gov/20461357/?dopt=Abstract. Published May 12, 2010. Accessed June 23, 2020.
  37. McDonald L. A Guide to Calorie Partitioning ” Bodyrecomposition. Bodyrecomposition. https://bodyrecomposition.com/muscle-gain/a-guide-to-calorie-partitioning. Published September 6, 2008. Accessed June 23, 2020.
  38. Smith GI, Magkos F, Reeds DN, Okunade AL, Patterson BW, Mittendorfer B. One day of mixed meal overfeeding reduces hepatic insulin sensitivity and increases VLDL particle but not VLDL-triglyceride secretion in overweight and obese men. The Journal of clinical endocrinology and metabolism. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733854/. Published August 2013. Accessed June 23, 2020.
  39. Magkos F, Smith GI, Reeds DN, Okunade A, Patterson BW, Mittendorfer B. One day of overfeeding impairs nocturnal glucose but not fatty acid homeostasis in overweight men. Wiley Online Library. https://onlinelibrary.wiley.com/doi/pdf/10.1002/oby.20562. Published September 10, 2013. Accessed June 23, 2020.
  40. Parry SA, Woods RM, Hodson L, Hulston CJ. A Single Day of Excessive Dietary Fat Intake Reduces Whole-Body Insulin Sensitivity: The Metabolic Consequence of Binge Eating. Nutrients. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5579612/. Published July 29, 2017. Accessed June 23, 2020.
  41. Hagobian TA, Braun B. Interactions Between Energy Surplus and Short-Term Exercise on Glucose and Insulin Responses in Healthy People With Induced, Mild Insulin Insensitivity. Metabolism: clinical and experimental. https://pubmed.ncbi.nlm.nih.gov/16483886/. Published March 2006. Accessed June 23, 2020.
  42. Clayton DJ, Biddle J, Maher T, et al. 24-h Severe Energy Restriction Impairs Postprandial Glycaemic Control in Young, Lean Males. The British journal of nutrition. https://pubmed.ncbi.nlm.nih.gov/30401004/. Published November 2018. Accessed June 23, 2020.
  43. Gannon MC, Nuttall FQ, Lane JT, Fang S, Gupta V, Sandhofer CR. Effect of 24 hours of starvation on plasma glucose and insulin concentrations in subjects with untreated non-insulin-dependent diabetes mellitus. Metabolism. https://www.sciencedirect.com/science/article/abs/pii/S0026049596902255. Published April 1996. Accessed June 23, 2020.
  44. Antoni R, Johnston KL, Collins AL, Robertson MD. Effects of intermittent fasting on glucose and lipid metabolism: Proceedings of the Nutrition Society. Cambridge Core. https://www.cambridge.org/core/journals/proceedings-of-the-nutrition-society/article/effects-of-intermittent-fasting-on-glucose-and-lipid-metabolism/8803CC1517F53CEF2BF8BFDC06A816D6. Published January 16, 2017. Accessed June 23, 2020.
  45. Cho Y, Hong N, Kim K-W, et al. The Effectiveness of Intermittent Fasting to Reduce Body Mass Index and Glucose Metabolism: A Systematic Review and Meta-Analysis. Journal of clinical medicine. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832593/. Published October 9, 2019. Accessed June 23, 2020
  46. Assali AR, Ganor A, Beigel Y, Shafer Z, Hershcovici T, Fainaru M. Insulin Resistance in Obesity: Body-Weight or Energy Balance? The Journal of endocrinology. https://pubmed.ncbi.nlm.nih.gov/11691649/. Published November 2001. Accessed June 23, 2020.
  47. Pories WJ, Swanson MS, MacDonald KG, et al. Who would have thought it? An operation proves to be the most effective therapy for adult-onset diabetes mellitus. Annals of surgery. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1234815/. Published September 1995. Accessed June 23, 2020.
  48. Kelley DE, Wing R, Buonocore C, Sturis J, Polonsky K, Fitzsimmons M. Relative Effects of Calorie Restriction and Weight Loss in Noninsulin-Dependent Diabetes Mellitus. The Journal of clinical endocrinology and metabolism. https://pubmed.ncbi.nlm.nih.gov/8077323/. Published November 1993. Accessed June 23, 2020.
  49. MD AAG, MD IMM, MD GHB. Changes in Insulin Resistance Following Bariatric Surgery: Role of Caloric Restriction and Weight Loss. Obesity Surgery. https://link.springer.com/article/10.1381/0960892053723367. Published April 1, 2005. Accessed June 23, 2020.
  50. Antoni R, Johnston KL, Collins AL, Robertson MD. Investigation into the acute effects of total and partial energy restriction on postprandial metabolism among overweight/obese participants: British Journal of Nutrition. Cambridge Core. https://www.cambridge.org/core/journals/british-journal-of-nutrition/article/investigation-into-the-acute-effects-of-total-and-partial-energy-restriction-on-postprandial-metabolism-among-overweightobese-participants/53531AD2D87F6EAF46882955EC832A80. Published January 28, 2016. Accessed June 23, 2020.
  51. Hutchison AT, Liu B, Wood RE, et al. Effects of Intermittent Versus Continuous Energy Intakes on Insulin Sensitivity and Metabolic Risk in Women with Overweight. Wiley Online Library. https://onlinelibrary.wiley.com/doi/full/10.1002/oby.22345. Published December 20, 2018. Accessed June 23, 2020.
  52. Bergman BC, Search for more papers by this author, Cornier M-A, et al. Effects of fasting on insulin action and glucose kinetics in lean and obese men and women. American Journal of Physiology-Endocrinology and Metabolism. https://journals.physiology.org/doi/full/10.1152/ajpendo.00613.2006?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub 0pubmed. Published October 1, 2007. Accessed June 23, 2020.
  53. Shashkin PN, Huang LC, Larner J, Vandenhoff GE, Katz A. Fasting decreases the content of D-chiroinositol in human skeletal muscle. International journal of experimental diabetes research. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2478579/. Published 2002. Accessed June 23, 2020
  54. Harris L, Hamilton S, Azevedo LB, et al. Intermittent fasting interventions for treatment of overweight and obesity in adults: a systematic review and meta-analysis. JBI Evidence Synthesis. https://journals.lww.com/jbisrir/Abstract/2018/02000/Intermittent_fasting_interventions_for_treatment.16.aspx. Published February 2018. Accessed June 23, 2020.
  55. Cioffi I, Evangelista A, Ponzo V, et al. Intermittent versus continuous energy restriction on weight loss and cardiometabolic outcomes: a systematic review and meta-analysis of randomized controlled trials. Journal of translational medicine. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6304782/. Published December 24, 2018. Accessed June 23, 2020
  56. Harvie MN, Pegington M, Mattson MP, et al. The effects of intermittent or continuous energy restriction on weight loss and metabolic disease risk markers: a randomized trial in young overweight women. International journal of obesity (2005). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3017674/. Published May 2011. Accessed June 23, 2020.
  57. Harvie M, Wright C, Pegington M, et al. The effect of intermittent energy and carbohydrate restriction v. daily energy restriction on weight loss and metabolic disease risk markers in overweight women. The British journal of nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857384/. Published October 2013. Accessed June 23, 2020.
  58. Wegman MP, Guo MH, Bennion DM, et al. Practicality of intermittent fasting in humans and its effect on oxidative stress and genes related to aging and metabolism. Rejuvenation research. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4403246/. Published April 2015. Accessed June 23, 2020.
  59. Schübel R, Nattenmüller J, Sookthai D, et al. Effects of intermittent and continuous calorie restriction on body weight and metabolism over 50 wk: a randomized controlled trial. The American journal of clinical nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6915821/. Published November 1, 2018. Accessed June 23, 2020.
  60. Pinto AM, Bordoli C, Buckner LP, et al. Intermittent Energy Restriction Is Comparable to Continuous Energy Restriction for Cardiometabolic Health in Adults With Central Obesity: A Randomized Controlled Trial; The Met-IER Study. Clinical nutrition (Edinburgh, Scotland). https://pubmed.ncbi.nlm.nih.gov/31409509/. Published June 2020. Accessed June 23, 2020.
  61. Antoni R, Johnston KL, Collins AL, Robertson MD. Intermittent v. continuous energy restriction: differential effects on postprandial glucose and lipid metabolism following matched weight loss in overweight/obese participants: British Journal of Nutrition. Cambridge Core. https://www.cambridge.org/core/journals/british-journal-of-nutrition/article/intermittent-v-continuous-energy-restriction-differential-effects-on-postprandial-glucose-and-lipid-metabolism-following-matched-weight-loss-in-overweightobese-participants/B165A5BA52A6B625B7A98067D3B2F39B. Published March 6, 2018. Accessed June 23, 2020.
  62. Sundfor TM, Svendsen M, Tonstad S. Effect of Intermittent Versus Continuous Energy Restriction on Weight Loss, Maintenance and Cardiometabolic Risk: A Randomized 1-year Trial. Nutrition, metabolism, and cardiovascular diseases : NMCD. https://pubmed.ncbi.nlm.nih.gov/29778565/. Published March 29, 2018. Accessed June 23, 2020.
  63. Conley M, Le Fevre L, Haywood C, Proietto J. Is Two Days of Intermittent Energy Restriction Per Week a Feasible Weight Loss Approach in Obese Males? A Randomised Pilot Study. Nutrition & dietetics: the journal of the Dietitians Association of Australia. https://pubmed.ncbi.nlm.nih.gov/28791787/. Published February 2018. Accessed June 23, 2020.
  64. Yaribeygi H, Atkin SL, Ramezani M, Sahebkar A. A Review of the Molecular Pathways Mediating the Improvement in Diabetes Mellitus Following Caloric Restriction. Journal of cellular physiology. https://pubmed.ncbi.nlm.nih.gov/30426486/. Published June 2019. Accessed June 23, 2020.
  65. Fontana L. The Scientific Basis of Caloric Restriction Leading to Longer Life. Current opinion in gastroenterology. https://pubmed.ncbi.nlm.nih.gov/19262201/. Published March 2009. Accessed June 23, 2020.
  66. Masoro EJ. Overview of caloric restriction and ageing. Mechanisms of Ageing and Development. https://www.sciencedirect.com/science/article/abs/pii/S0047637405000783?via=ihub. Published May 10, 2005. Accessed June 23, 2020.
  67. Slater GJ, Dieter BP, Marsh DJ, Helms ER, Shaw G, Iraki J. Is an Energy Surplus Required to Maximize Skeletal Muscle Hypertrophy Associated With Resistance Training. Frontiers. https://www.frontiersin.org/articles/10.3389/fnut.2019.00131/full. Published August 2, 2019. Accessed June 24, 2020.
  68. Rozenek R, Ward P, Long S, Garhammer J. Effects of High-Calorie Supplements on Body Composition and Muscular Strength Following Resistance Training. The Journal of sports medicine and physical fitness. https://pubmed.ncbi.nlm.nih.gov/12094125/. Published September 2002. Accessed June 24, 2020.
  69. Garthe I, Raastad T, Refsnes PE, Sundgot-Borgen J. Effect of Nutritional Intervention on Body Composition and Performance in Elite Athletes. European journal of sport science. https://pubmed.ncbi.nlm.nih.gov/23679146/. Published 2013. Accessed June 24, 2020.
  70. Aragon AA, Schoenfeld BJ. Nutrient timing revisited: is there a post-exercise anabolic window? Journal of the International Society of Sports Nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3577439/. Published January 29, 2013. Accessed June 24, 2020.
  71. Moore DR. Maximizing Post-exercise Anabolism: The Case for Relative Protein Intakes. Frontiers. https://www.frontiersin.org/articles/10.3389/fnut.2019.00147/full#B1. Published August 23, 2019. Accessed June 24, 2020.
  72. Børsheim E, Cree MG, Tipton KD, Elliott TA, Aarsland A, Wolfe RR. Effect of carbohydrate intake on net muscle protein synthesis during recovery from resistance exercise. Journal of Applied Physiology. https://journals.physiology.org/doi/full/10.1152/japplphysiol.00333.2003. Published February 1, 2004. Accessed June 24, 2020.
  73. Glynn EL, Fry CS, Drummond MJ, et al. Muscle protein breakdown has a minor role in the protein anabolic response to essential amino acid and carbohydrate intake following resistance exercise. American journal of physiology. Regulatory, integrative and comparative physiology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2928613/. Published August 2010. Accessed June 24, 2020.
  74. Richter EA, Derave W, Wojtaszewski JF. Glucose, exercise and insulin: emerging concepts. The Journal of physiology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2278791/. Published September 1, 2001. Accessed July 23, 2020.
  75. Lambert CP, Frank LL, Evans WJ. Macronutrient Considerations for the Sport of Bodybuilding. Semantic Scholar. https://www.semanticscholar.org/paper/Macronutrient-Considerations-for-the-Sport-of-Lambert-Frank/51170e76f7d21cbbc1448ed10b273a3a238a9aaf. Published 2004. Accessed June 24, 2020.
  76. Morton RW, Murphy KT, McKellar SR, et al. A systematic review, meta-analysis and meta-regression of the effect of protein supplementation on resistance training-induced gains in muscle mass and strength in healthy adults. British journal of sports medicine. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5867436/. Published March 2018. Accessed June 24, 2020.
  77. Schoenfeld BJ, Aragon AA. How much protein can the body use in a single meal for muscle-building? Implications for daily protein distribution. Journal of the International Society of Sports Nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5828430/. Published February 27, 2018. Accessed June 24, 2020.
  78. Fats and fatty acids in human nutrition. World Health Organization. https://www.who.int/nutrition/publications/nutrientrequirements/fatsandfattyacids_humannutrition/en/. Published April 4, 2014. Accessed June 24, 2020.
  79. Pasiakos SM, Vislocky LM, Carbone JW, et al. Acute Energy Deprivation Affects Skeletal Muscle Protein Synthesis and Associated Intracellular Signaling Proteins in Physically Active Adults. The Journal of nutrition. https://pubmed.ncbi.nlm.nih.gov/20164371/. Published April 2010. Accessed June 23, 2020.
  80. Carbone JW, Pasiakos SM, Vislocky LM, Anderson JM, Rodriguez NR. Effects of Short-Term Energy Deficit on Muscle Protein Breakdown and Intramuscular Proteolysis in Normal-Weight Young Adults. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme. https://pubmed.ncbi.nlm.nih.gov/24945715/. Published August 2014. Accessed June 23, 2020
  81. Hector AJ, McGlory C, Damas F, Mazara N, Baker SK, Phillips SM. Pronounced Energy Restriction With Elevated Protein Intake Results in No Change in Proteolysis and Reductions in Skeletal Muscle Protein Synthesis That Are Mitigated by Resistance Exercise. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. https://pubmed.ncbi.nlm.nih.gov/28899879/. Published January 2018. Accessed June 23, 2020.
  82. Pasiakos SM, Cao JJ, Margolis LM, et al. Effects of High-Protein Diets on Fat-Free Mass and Muscle Protein Synthesis Following Weight Loss: A Randomized Controlled Trial. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. https://pubmed.ncbi.nlm.nih.gov/23739654/. Published September 2013. Accessed June 23, 2020.
  83. Areta JL, Burke LM, Camera DM, et al. Reduced Resting Skeletal Muscle Protein Synthesis Is Rescued by Resistance Exercise and Protein Ingestion Following Short-Term Energy Deficit. American journal of physiology. Endocrinology and metabolism. https://pubmed.ncbi.nlm.nih.gov/24595305/. Published April 2014. Accessed June 23, 2020.
  84. Longland TM, Oikawa SY, Mitchell CJ, Devries MC, Phillips SM. Higher compared with lower dietary protein during an energy deficit combined with intense exercise promotes greater lean mass gain and fat mass loss: a randomized trial. OUP Academic. https://academic.oup.com/ajcn/article/103/3/738/4564609. Published January 27, 2016. Accessed July 23, 2020.
  85. Lennon D, Helms E, Henselmans M. Diet Breaks, Calorie Cycling & Muscle Retention. Sigma Nutrition Radio Episode 290. July 2019. https://sigmanutrition.com/wp-content/uploads/2016/04/Ep-290-Menno-and-Eric.pdf. Accessed June 24, 2020.
  86. Roberts BM, Helms ER, Trexler ET, Fitschen PJ. Nutritional Recommendations for Physique Athletes. Journal of human kinetics. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052702/. Published January 31, 2020. Accessed June 24, 2020.
  87. Gadgil MD, Appel LJ, Yeung E, Anderson CAM, Sacks FM, Miller ER. The effects of carbohydrate, unsaturated fat, and protein intake on measures of insulin sensitivity: results from the OmniHeart trial. Diabetes care. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3631872/. Published May 2013. Accessed June 24, 2020.
  88. Imamura F, Micha R, Wu JHY, et al. Effects of Saturated Fat, Polyunsaturated Fat, Monounsaturated Fat, and Carbohydrate on Glucose-Insulin Homeostasis: A Systematic Review and Meta-analysis of Randomised Controlled Feeding Trials. PLoS medicine. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4951141/. Published July 19, 2016. Accessed June 24, 2020
  89. Wanders AJ, Blom WAM, Zock PL, Geleijnse JM, Brouwer IA, Alssema M. Plant-derived polyunsaturated fatty acids and markers of glucose metabolism and insulin resistance: a meta-analysis of randomized controlled feeding trials. BMJ open diabetes research & care. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398820/. Published February 8, 2019. Accessed June 24, 2020
  90. Wu JHY, Marklund MHY, Imamura FHY, et al. Omega-6 fatty acid biomarkers and incident type 2 diabetes: pooled analysis of individual-level data for 39 740 adults from 20 prospective cohort studies. The Lancet Diabetes & Endocrinology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029721/. Published December 2017. Accessed June 24, 2020.
  91. Forouhi NG, Imamura F, Sharp SJ, et al. Association of Plasma Phospholipid n-3 and n-6 Polyunsaturated Fatty Acids with Type 2 Diabetes: The EPIC-InterAct Case-Cohort Study. PLoS medicine. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4951144/. Published July 19, 2016. Accessed June 24, 202
  92. Risérus U, Willett WC, Hu FB. Dietary fats and prevention of type 2 diabetes. Progress in Lipid Research. https://www.sciencedirect.com/science/article/abs/pii/S0163782708000593?via=ihub. Published November 7, 2008. Accessed June 24, 2020.
  93. Manco M, Calvani M, Mingrone G. Effects of dietary fatty acids on insulin sensitivity and secretion. Diabetes, Obesity and Metabolism. https://dom-pubs.onlinelibrary.wiley.com/doi/abs/10.1111/j.1462-8902.2004.00356.x. Published October 8, 2004. Accessed June 24, 2020.
  94. Rosqvist F, Kullberg J, Ståhlman M, et al. Overeating Saturated Fat Promotes Fatty Liver and Ceramides Compared With Polyunsaturated Fat: A Randomized Trial. The Journal of clinical endocrinology and metabolism. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6839433/. Published December 1, 2019. Accessed June 24, 2020.
  95. Rosqvist F, Iggman D, Kullberg J, et al. Overfeeding Polyunsaturated and Saturated Fat Causes Distinct Effects on Liver and Visceral Fat Accumulation in Humans. Diabetes. https://diabetes.diabetesjournals.org/content/63/7/2356.long. Published July 1, 2014. Accessed June 24, 2020.
  96. Bjermo H, Iggman D, Kullberg J, et al. Effects of n-6 PUFAs compared with SFAs on liver fat, lipoproteins, and inflammation in abdominal obesity: a randomized controlled trial. OUP Academic. https://academic.oup.com/ajcn/article/95/5/1003/4576714. Published April 4, 2012. Accessed June 24, 2020.
  97. Parry SA, Rosqvist F, Mozes FE, et al. Intrahepatic Fat and Postprandial Glycemia Increase After Consumption of a Diet Enriched in Saturated Fat Compared With Free Sugars. Diabetes Care. https://care.diabetesjournals.org/content/early/2020/03/12/dc19-2331. Published March 12, 2020. Accessed June 24, 2020.
  98. Gershuni VM, Yan SL, Medici V. Nutritional Ketosis for Weight Management and Reversal of Metabolic Syndrome. Current nutrition reports. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6472268/. Published September 2018. Accessed June 24, 2020.
  99. Numao S, Kawano H, Endo N, et al. Short-term low carbohydrate/high-fat diet intake increases postprandial plasma glucose and glucagon-like peptide-1 levels during an oral glucose tolerance test in healthy men. Nature News. https://www.nature.com/articles/ejcn201258. Published June 6, 2012. Accessed June 24, 2020
  100. Numao S, Kawano H, Endo N, et al. Short-term High-Fat Diet Alters Postprandial Glucose Metabolism and Circulating Vascular Cell Adhesion molecule-1 in Healthy Males. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme. https://pubmed.ncbi.nlm.nih.gov/27454856/. Published August 2016. Accessed June 24, 2020.
  101. Anderson AS, Haynie KR, McMillan RP, et al. Early skeletal muscle adaptations to short‐term high‐fat diet in humans before changes in insulin sensitivity. Wiley Online Library. https://onlinelibrary.wiley.com/doi/full/10.1002/oby.21031. Published March 27, 2015. Accessed June 24, 2020.
  102. Branis NM, Etesami M, Walker RW, Berk ES, Albu JB. Effect of a 1-week, eucaloric, moderately high-fat diet on peripheral insulin sensitivity in healthy premenopausal women. BMJ Open Diabetes Research & Care. https://drc.bmj.com/content/3/1/e000100. Published July 1, 2015. Accessed June 24, 2020.
  103. Pehleman TL, Peters SJ, Heigenhauser GJF, Spriet LL. Enzymatic regulation of glucose disposal in human skeletal muscle after a high-fat, low-carbohydrate diet. Journal of Applied Physiology. https://journals.physiology.org/doi/full/10.1152/japplphysiol.00686.2004. Published January 1, 2005. Accessed June 24, 2020.
  104. Grandl G, Straub L, Rudigier C, et al. Short-term feeding of a ketogenic diet induces more severe hepatic insulin resistance than an obesogenic high-fat diet. The Journal of physiology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6166091/. Published October 2018. Accessed June 24, 2020.
  105. Blaak EE, Antoine J-M, Benton D, et al. Impact of postprandial glycaemia on health and prevention of disease. Obesity reviews : an official journal of the International Association for the Study of Obesity. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3494382/. Published October 2012. Accessed June 23, 2020.
  106. Barr ELM, Boyko EJ, Zimmet PZ, Wolfe R, Tonkin AM, Shaw JE. Continuous Relationships Between Non-Diabetic Hyperglycaemia and Both Cardiovascular Disease and All-Cause Mortality: The Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study. Diabetologia. https://pubmed.ncbi.nlm.nih.gov/19130039/. Published March 2009. Accessed June 23, 2020.
  107. Nakagami T. Hyperglycaemia and Mortality From All Causes and From Cardiovascular Disease in Five Populations of Asian Origin. Diabetologia. https://pubmed.ncbi.nlm.nih.gov/14985967. Published March 2004. Accessed June 23, 2020.
  108. Balkau B, Shipley M, Jarrett RJ, et al. High Blood Glucose Concentration Is a Risk Factor for Mortality in Middle-Aged Nondiabetic Men. 20-year Follow-Up in the Whitehall Study, the Paris Prospective Study, and the Helsinki Policemen Study. Diabetes care. https://pubmed.ncbi.nlm.nih.gov/9540016/. Published March 1998. Accessed June 23, 2020.
  109. Kawano H, Motoyama T, Hirashima O, et al. Hyperglycemia rapidly suppresses flow-mediated endothelium- dependent vasodilation of brachial artery. Journal of the American College of Cardiology. https://www.sciencedirect.com/science/article/pii/S0735109799001680?via=ihub. Published June 25, 1999. Accessed June 23, 2020.
  110. Sánchez-Sánchez ML, García-Vigara A, Hidalgo-Mora JJ, García-Pérez M-Á, Tarín J, Cano A. Mediterranean diet and health: A systematic review of epidemiological studies and intervention trials. Maturitas. https://www.sciencedirect.com/science/article/abs/pii/S0378512220302231. Published April 11, 2020. Accessed June 24, 2020.
  111. Mozaffarian D;Marfisi R;Levantesi G;Silletta MG;Tavazzi L;Tognoni G;Valagussa F;Marchioli R; Incidence of New-Onset Diabetes and Impaired Fasting Glucose in Patients With Recent Myocardial Infarction and the Effect of Clinical and Lifestyle Risk Factors. Lancet (London, England). https://pubmed.ncbi.nlm.nih.gov/17720018/. Published August 2007. Accessed June 24, 2020.
  112. Abiemo EE, Alonso A, Nettleton JA, et al. Relationships of the Mediterranean dietary pattern with insulin resistance and diabetes incidence in the Multi-Ethnic Study of Atherosclerosis (MESA). The British journal of nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4002212/. Published April 28, 2013. Accessed June 24, 2020.
  113. Adeva-Andany MM, Gonzalez-Lucan M, Fernandez-Fernandez C, Carneiro-Freire N, Seco-Filgueira M, Pedre-pineiro AM. Effect of Diet Composition on Insulin Sensitivity in Humans. Clinical nutrition ESPEN. https://pubmed.ncbi.nlm.nih.gov/31451269/. Published October 2019. Accessed June 24, 2020.
  114. Weickert MO, Pfeiffer AFH. Impact of Dietary Fiber Consumption on Insulin Resistance and the Prevention of Type 2 Diabetes. OUP Academic. https://academic.oup.com/jn/article/148/1/7/4823705. Published January 25, 2018. Accessed June 24, 2020
  115. Guasch-Ferré M, Merino J, Sun Q, Fitó M, Salas-Salvadó J. Dietary Polyphenols, Mediterranean Diet, Prediabetes, and Type 2 Diabetes: A Narrative Review of the Evidence. Oxidative medicine and cellular longevity. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5572601/#B50. Published 2017. Accessed June 25, 2020.
  116. Pandey KB, Rizvi SI. Plant polyphenols as dietary antioxidants in human health and disease. Oxidative medicine and cellular longevity. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2835915/. Published 2009. Accessed June 25, 2020.
  117. Xiao JB, Hogger P. Dietary Polyphenols and Type 2 Diabetes: Current Insights and Future Perspectives. Current medicinal chemistry. https://pubmed.ncbi.nlm.nih.gov/25005188/. Published 2015. Accessed June 25, 2020.
  118. Liu Y-J, Zhan J, Liu X-L, Wang Y, Ji J, He Q-Q. Dietary Flavonoids Intake and Risk of Type 2 Diabetes: A Meta-Analysis of Prospective Cohort Studies. Clinical nutrition (Edinburgh, Scotland). https://pubmed.ncbi.nlm.nih.gov/23591151/. Published February 2014. Accessed June 25, 2020.
  119. Kim Y, Keogh JB, Clifton PM. Polyphenols and Glycemic Control. Nutrients. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4728631/#B143-nutrients-08-00017. Published January 5, 2016. Accessed June 25, 2020.
  120. Hanhineva K, Törrönen R, Bondia-Pons I, et al. Impact of dietary polyphenols on carbohydrate metabolism. International journal of molecular sciences. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2871121/. Published March 31, 2010. Accessed June 25, 2020.
  121. Shrime MG, Bauer SR, McDonald AC, Chowdhury NH, Coltart CEM, Ding EL. Flavonoid-rich Cocoa Consumption Affects Multiple Cardiovascular Risk Factors in a Meta-Analysis of Short-Term Studies. The Journal of nutrition. https://pubmed.ncbi.nlm.nih.gov/21956956. Published November 2011. Accessed June 25, 2020.
  122. Hooper L, Kay C, Abdelhamid A, et al. Effects of chocolate, cocoa, and flavan-3-ols on cardiovascular health: a systematic review and meta-analysis of randomized trials. OUP Academic. https://academic.oup.com/ajcn/article/95/3/740/4576702. Published February 1, 2012. Accessed June 25, 2020.
  123. Liu K, Zhou R, Wang B, et al. Effect of green tea on glucose control and insulin sensitivity: a meta-analysis of 17 randomized controlled trials. OUP Academic. https://academic.oup.com/ajcn/article/98/2/340/4577179. Published June 26, 2013. Accessed June 25, 2020.
  124. Floegel A, Pischon T, Bergmann MM, Teucher B, Kaaks R, Boeing H. Coffee consumption and risk of chronic disease in the European Prospective Investigation into Cancer and Nutrition (EPIC)–Germany study. OUP Academic. https://academic.oup.com/ajcn/article/95/4/901/4576798. Published February 15, 2012. Accessed June 25, 2020.
  125. Grosso G, Godos J, Galvano F, Giovannucci EL. Coffee, Caffeine, and Health Outcomes: An Umbrella Review. Annual Reviews. https://www.annualreviews.org/doi/abs/10.1146/annurev-nutr-071816-064941. Published August 2017. Accessed June 25, 2020.
  126. Dam RMvan, Willett WC, Manson JAE, Hu FB. Coffee, Caffeine, and Risk of Type 2 Diabetes. Diabetes Care. https://care.diabetesjournals.org/content/29/2/398.long. Published February 1, 2006. Accessed June 25, 2020.
  127. Ley SH, Ardisson Korat AV, Sun Q, et al. Contribution of the Nurses’ Health Studies to Uncovering Risk Factors for Type 2 Diabetes: Diet, Lifestyle, Biomarkers, and Genetics. American journal of public health. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4981796/. Published September 2016. Accessed July 23, 2020.
  128. Chiva-Blanch G, Urpi-Sarda M, Ros E, et al. Effects of Red Wine Polyphenols and Alcohol on Glucose Metabolism and the Lipid Profile: A Randomized Clinical Trial. Clinical nutrition (Edinburgh, Scotland). https://pubmed.ncbi.nlm.nih.gov/22999066/. Published April 2013. Accessed June 25, 2020.
  129. Gepner Y, From Ben-Gurion University of the Negev and Soroka Medical Center, Golan R, et al. Effects of Initiating Moderate Alcohol Intake on Cardiometabolic Risk in Adults With Type 2 Diabetes. Annals of Internal Medicine. https://www.acpjournals.org/doi/abs/10.7326/M14-1650?rfr_dat=cr_pub 0pubmed&url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&journalCode=aim. Published October 15, 2015. Accessed June 25, 2020.
  130. Estruch R, From Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Martínez-González MÁ, et al. Effects of a Mediterranean-Style Diet on Cardiovascular Risk Factors. Annals of Internal Medicine. https://www.acpjournals.org/doi/abs/10.7326/0003-4819-145-1-200607040-00004?rfr_dat=cr_pub 0pubmed&url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&journalCode=aim. Published July 4, 2006. Accessed June 25, 2020.
  131. Salas-Salvadó J, From the Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición, Bulló M, et al. Prevention of Diabetes With Mediterranean Diets. Annals of Internal Medicine. https://www.acpjournals.org/doi/abs/10.7326/M13-1725?rfr_dat=cr_pub 0pubmed&url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&journalCode=aim. Published January 7, 2014. Accessed June 25, 2020.
  132. Hernández-Alonso P, Camacho-Barcia L, Bulló M, Salas-Salvadó J. Nuts and Dried Fruits: An Update of Their Beneficial Effects on Type 2 Diabetes. Nutrients. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537788/#B108-nutrients-09-00673. Published June 28, 2017. Accessed June 25, 2020.
  133. Blanco Mejia S, Kendall CWC, Viguiliouk E, et al. Effect of tree nuts on metabolic syndrome criteria: a systematic review and meta-analysis of randomised controlled trials. BMJ open. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120343/. Published July 29, 2014. Accessed June 25, 2020.
  134. Aune D, Giovannucci E, Boffetta P, et al. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies. International journal of epidemiology. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837313/. Published June 1, 2017. Accessed June 25, 2020
  135. Li M, Fan Y, Zhang X, Hou W, Tang Z. Fruit and vegetable intake and risk of type 2 diabetes mellitus: meta-analysis of prospective cohort studies. BMJ open. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4225228/. Published November 5, 2014. Accessed June 25, 2020.
  136. Wang P-Y, Fang J-C, Gao Z-H, Zhang C, Xie S-Y. Higher intake of fruits, vegetables or their fiber reduces the risk of type 2 diabetes: A meta-analysis. Journal of diabetes investigation. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4718092/. Published January 2016. Accessed June 25, 2020.
  137. Muraki I, Imamura F, Manson JE, et al. Fruit consumption and risk of type 2 diabetes: results from three prospective longitudinal cohort studies. BMJ (Clinical research ed.). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978819/. Published August 28, 2013. Accessed June 25, 2020.
  138. Wedick NM, Pan A, Cassidy A, et al. Dietary flavonoid intakes and risk of type 2 diabetes in US men and women. The American journal of clinical nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3302366/. Published April 2012. Accessed June 25, 2020.
  139. Stull AJ, Cash KC, Johnson WD, Champagne CM, Cefalu WT. Bioactives in blueberries improve insulin sensitivity in obese, insulin-resistant men and women. The Journal of nutrition. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3139238/. Published October 2010. Accessed June 25, 2020

29 thoughts on “Calorie Cycling to Maximize Body Composition Outcomes for Bodybuilders in the Off-Season

  1. I do agree with all the ideas you have presented in your post. They are very convincing and will certainly work. Still, the posts are very short for beginners. Could you please extend them a little from next time? Thanks for the post.

  2. Hey There. I found your blog using msn. This is a very well written article. I will make sure to bookmark it and return to read more of your useful info. Thanks for the post. I抣l certainly comeback.

  3. Aw, this was a very nice post. In idea I would like to put in writing like this moreover ?taking time and actual effort to make a very good article?but what can I say?I procrastinate alot and in no way appear to get one thing done.

  4. Thanks a lot for providing individuals with such a nice opportunity to read articles and blog posts from this web site. It is often very kind plus stuffed with a great time for me and my office acquaintances to visit your web site really 3 times weekly to learn the latest things you have got. Of course, I am at all times satisfied concerning the extraordinary advice served by you. Some 2 areas in this article are unequivocally the most suitable we have all had.

  5. Nice blog here! Additionally your website so much up very fast! What web host are you the usage of? Can I get your associate hyperlink for your host? I want my site loaded up as quickly as yours lol

  6. I’m so happy to read this. This is the type of manual that needs to be given and not the random misinformation that is at the other blogs. Appreciate your sharing this best doc.

  7. This is relevant knowledge for my followers, so I’ll link back to this article and you will probably get a few extra subscribers. It’s better than anything else I’ve seen when it comes to this subject. Thank you for the inspired viewpoint!

Leave a Reply

Your email address will not be published. Required fields are marked *