Along with eating a high-fiber diet, meal timing is one of the top pieces of advice that Maria Adams, adjunct professor of nutrition at Endicott College, suggests. Many of us eat snacks on and off throughout the day. The healthiest course is to stick to three meals a day.

There is clear logic as to why eating regularly helps people with digestive problems. Bodies are biological machines. If you add in a lot of fuel at once and then none for long periods, your digestive tract has to work very hard very quickly and then weight.

It makes sense that that could lead to GI problems. As you know, your diet impacts the bacteria and microorganisms that live in your gut, helping you to stay healthy.

A study found that eating the bulk of calories early in the day, fasting at night and sticking to the pattern reduced inflammation, improved cell regeneration and aided GI problems.

Moreover, the researchers saw more microbial diversity in the gut. With all this in mind, if you have concerns for your gut health, want to aid your microbiome or want to be more regular, eating on a schedule may be a smart move.

People focus on numerous diets and nutrition plans to maintain their health but what they forget is the time at which we take those nutrients.

Yes, the question pertaining to what to eat and what not to eat has always remain prevalent but the time of the day you eat it, is somehow forgotten.

Meal timing plays a very significant role in taking care of your body, like other things, our body also follows a time cycle that needs to be kept in mind while taking any meal of the day.

Studies show that optimal health can be attained if we consume our calories earlier in the day instead taking it later. To make it simpler, you can eat a large breakfast, a modest lunch and small dinner. By time cycle we mean the body's internal clock that is also known as circadian rhythm.

It regulates various physiological processes, including metabolism, hormone secretion and sleep wake cycles. If we eat our meals on time, it can help synchronize the eating patterns with the body's circadian rhythms, which eventually promotes better digestion, nutrient absorption and energy levels throughout the day.

TRENDING NOW Also Read Want To Eat In A Guilt-Free Manner This Winter? Try These Healthy Recipes 4 Foods To Include In Your Diet To Combat Stress Key Nutrient-Packed Food Choices You Must Make For Healthy Pregnancy More News.

This innate 24 hour clock manages many different aspects of our health. Studies suggest that our metabolism becomes less efficient as the day progresses.

So a meal taken at 10 a. In the absence of pilot data, no formal power calculation was carried out prior to study initiation. However, decision to extend or discontinue the study was made following interim analysis of the data of the first participants.

Seventeen participants took part in this study 8 females and 9 males; mean [SD] age of Daily energy intake varied among participants, ranging from 1, to 3, kcal with an average SD of 2, kcal.

There was no significant mean weight change mean [SD]: 0. Total stool output i. Participants lost on average 5.

dinner 5. Similarly, the time of main meal consumption did not significantly associate with fecal energy output or content Table 1. Regardless of the way data were expressed, fecal SCFA were not significantly different between the 2 interventions Table 2. The last sample provided by each participant and for each intervention was sequenced using the V4 region of the 16S rRNA gene.

Using either the Bray-Curtis dissimilarity Fig. material 3. There was no deviation of any participants from their enterotype, suggesting that the effect of meal timing was unable to supersede the effect of enterotypes.

In differential analysis, the taxon relative abundance of 8 OTUs and 7 genera differed between the 2 interventions Fig. However, these significant effects vanished when analysis was corrected for multiple testing.

Otherwise, the microbiome profile remained unaffected between the 2 dietary interventions at OTU Fig. material 4. Effect of timing of main meal consumption on the gut microbiome of healthy volunteers.

a NMDS using Bray-Curtis distances of OTU community structure. b NMDS using weighted Unifrac distance analysis. c Rarefied richness. d Chao1 index. e Exponential of Shannon index eH. NMDS, nonmetric multidimensional scaling; OTU, operational taxonomic unit.

Log-relative abundance significant differences between the 2 dietary interventions. a OTU level. b Genus level. OTU, operational taxonomic unit. Effect of the timing of main meal consumption on the relative abundance of the top 20 common OTUs group mean. Mean microbiome profile of all participants per dietary intervention.

A1—A17, microbiome profile of each participant per dietary intervention; OTU, operational taxonomic units. The time of main meal consumption did not influence significantly the fecal concentration of total bacteria or other bacterial groups except for E. coli , which was significantly higher after the large lunch intervention.

This effect remained significant regardless of the approach used to express the data Table 3. Effect of timing of main meal consumption on blood biomarkers of cardiometabolic health. Box plots show means and quartiles. TAG, triglycerides; CRP, C-reactive protein.

White boxplot indicates the large dinner intervention, and gray boxplot indicates the large lunch intervention. One participant had a raised CRP after the end of the second intervention due to a recent cold. Repetition of statistical analysis after exclusion of this participant did not change the difference in the mean effects observed between the 2 interventions.

This study was set out to investigate the effect of the time of main meal consumption on the gastrointestinal microbiome and cardiometabolic factors of the host. Against our hypothesis, we found that the time at which the main meal was consumed had no acute effects on fecal pH, form and texture of feces, fecal water content, total energy loss in feces, total fecal SCFA output, and the global microbial community structure or taxon relative abundance inferred using high-throughput sequencing.

When we looked at the effect of the 2 interventions on the absolute concentration of dominant bacterial species, we observed a significant increase in the absolute concentration of E.

coli after consumption of the main meal as lunch. This effect is unlikely to be a random or spurious finding as it persisted when we expressed the amount of this species as the average concentration of all samples per participant, concentration, or total output over 3-day complete fecal sample collection.

Interestingly, this signal was not replicated using high-throughput sequencing most likely due to different expression of data absolute vs. relative abundance and other counterbalancing changes. With the exception of the significant effect of our intervention on E. coli , these findings are against our hypothesis and those results presented previously in cross-sectional research [ 5 ].

It could be postulated that the E. Kaczmarek et al. Another study investigating the effects of the Western diet on the gastrointestinal microbiome of mice found that it caused an increase in fecal E.

coli levels [ 15 ]. It is therefore possible that a similar response to the Western diet occurred in our participants. Diet has been previously shown to influence fecal SCFA content [ 16 ], but evidence implicating main meal timing is scarce. We found no significant differences between the lunch and dinner meal interventions for any of the 10 SCFA tested.

This observation agrees with previous cross-sectional research in which eating behavior i. Similarly, we found no difference between the 2 interventions on blood biomarkers of CVD risk.

This means that the time at which the main meal was consumed had no acute effects on blood CVD biomarkers such as blood lipids, insulin resistance, or low-grade inflammation, despite weight gain following the intervention with large dinner.

Supporting the findings from this study, a recent weight loss study comparing the effects of a large lunch with a large dinner [ 9 ] found that although a decrease in blood lipids was noted for both groups and in parallel to their weight loss, the change in blood lipid level was not significantly different between the 2 interventions.

Similarly, a crossover RCT investigating snacking times 10 a. found that time of consumption of a high-fat, high-carbohydrate snack had no significant effects on serum triglycerides and HDL cholesterol, but late snacking produced a significant increase in total and LDL cholesterol [ 17 ].

Neither fasted blood insulin, glucose, nor HOMA-IR was responsive to different timing of the main meal. These findings are supported by previous research and a recent meta-analysis where snacking time had no effect on HOMA-IR, insulin, or glucose levels [ 17, 18 ].

Contrary to this evidence, when meal times were delayed by 5 h, plasma glucose rhythms were also delayed by approximately 5 h and average glucose concentration decreased [ 19 ].

Madjd et al. This result was, however, dependent on weight loss, which in the current study was not observed in the intervention with lunch as the main meal, and although weight gain was observed in the other group, the magnitude of this effect was very modest and perhaps too small to evoke an acute effect in young otherwise healthy subjects.

Two proinflammatory cytokines and CRP were measured here as markers of low-grade systemic inflammation, particularly as these markers are often elevated in obese individuals [ 20 ].

Although the origin of this low-grade inflammation remains unknown, there is accumulating evidence to suggest that this might be due to the effect of diet on the gut microbiome and associated endotoxemia [ 2 ].

Our results suggest that time of main meal consumption is unlikely to be a contributor to low-grade inflammation, and this effect is unlikely to be associated with changes in the gut microbiome. Bomb calorimetry was used on all stool samples from all participants to estimate intestinal absorption capacity [ 21 ] and the effect of the 2 interventions on the percentage of fecal water content and the Bristol Stool Scale as proxies of gastrointestinal motility.

Nutrient load has previously been shown to be associated with changes to the microbiome and correlating with changes to energy loss in stool [ 22 ].

Nonetheless, this RCT is the first of its kind to investigate the associations between time of food consumption, energy content of stool, and microbiome changes and found no statistically significant association between time of main meal and cumulative energy content of fecal samples.

Average fecal energy content met expected healthy values for both interventions [ 23 ]. This well-controlled study is not without its limitations.

The study is of modest sample size, but the size effect and associated p values observed suggest that this study is unlikely to suffer from loss of statistical power. Recruitment of more participants is unlikely to have altered the primary findings presented; therefore, extension of recruitment was deemed unnecessary.

It is however possible that the discordant results for E. We are also unable to comment on long-term effects that meal timing may have on the gut microbiome and cardiometabolic factors. With this in mind, the current study has several strengths.

A robust study design was employed, with each participant acting as their own control. Furthermore, each participant had a personalized diet which equated their energy requirements and was based on their food preferences, and meals were provided to maximize compliance and accurate dietary intake assessment.

This hypothesis testing study investigating the effects of the time of main meal consumption on the microbiome and the host found that main meal timing had minimal acute effects on cardiometabolic factors in the blood, intestinal absorption capacity, or on microbiome composition or activity.

It is therefore unlikely that either a large lunch or a large dinner affects the diurnal rhythms of the gut microbiota and, by proxy, the onset of noncommunicable diseases influenced by the latter.

In a presumptive causal pathway between timing of meal and risk of CVD onset, the gut microbiota is likely not to be implicated, at least in the short term.

Future investigations should look to expand upon the findings of this study with longer duration of dietary interventions. The study received approval by the MLVS Research Ethics Committee at the University of Glasgow Reference number: Miss Katrina Ballantyne received a summer undergraduate student bursary by the Rank Prize Funds.

This leads to poor reaction time and slowness. Poor coordination as a result can lead to missteps, inattention, and injury. Additionally, chronic energy drain taking in fewer calories and nutrients than needed will increase your risk of overuse injuries over time.

Stress fractures are one example; poor tissue integrity can happen when athletes think solely about calories taken in but not the quality of the calories consumed.

Inadequate protein will also hinder the rebuilding of damaged muscles during training. If muscles are not completely repaired, they will not be as strong as they could be and will not function optimally.

The damaged muscle fibers can lead to soft-tissue injuries. Both protein and carbohydrate along with certain nutrients are needed to help with this repair. For instance, gummy bears may provide carbohydrate, but they don't contain any vitamin E, which is helpful in repairing soft-tissue damage that occurs daily during training.

Therefore, the goal is both an appropriate quantity and an appropriate quality in food selection. Previous Next. Call Us Hours Mon-Fri 7am - 5pm CST. Contact Us Get in touch with our team. FAQs Frequently asked questions. Home Excerpts Learn the advantages of nutrient timing.

What Are the Benefits of Nutrient Timing? The Nutrient Timing Principles NTP help you do the following: Optimize fuel use so that you remain energized throughout your training Ensure that you repair and strengthen your muscles to the best of your genetic potential Ingest sufficient nutrients to keep you healthy and able to fight off infection, limiting the suppression of the immune system often experienced with intense training Recover from your training so that you are ready for your next practice, event, or training session with well-fueled muscles Energy When sports nutritionists talk about energy, we are referring to the potential energy food contains.

Recovery During the minutes and hours after exercise, your muscles are recovering from the work you just performed. Muscle Breakdown and Muscle Building Nutrient timing capitalizes on minimizing muscle tissue breakdown that occurs during and after training and maximizing the muscle repair and building process that occurs afterwards.

Immunity Nutrient timing can have a significant impact on immunity for athletes. Injury Prevention Did you know that dehydration and low blood sugar can actually increase your risk of injury?

Save Save More Excerpts From Nutrient Timing for Peak Performance. Get the latest insights with regular newsletters, plus periodic product information and special insider offers.

JOIN NOW. Latest Posts Sports Betting Stakeholders Gamification in the Gambling Market The Ethics of Gambling Advertising Interplay Between Federal Laws and State and Tribal Governance in Sports Betting Example Skill Variations for different movement patterns Strength training Modifications for Students With Disabilities.

Back to top. Purpose: The interaction of diet with gut microbiome has been implicated in the onset of cardiovascular disease. The gut microbiome displays diurnal rhythms, which may be influenced by meal timing.

Objective: This study aimed to investigate the effect of the timing of main meal consumption on the microbiome and cardiometabolic biomarkers of the host.

Methods: Seventeen healthy adults randomly consumed an isocaloric diet for 7 days, twice, by alternating lunch with dinner meals, and with a 2-week washout in-between.

Sixty percent of the participants' daily energy requirements was consumed either as lunch or dinner, respectively. Andreu Prados is a science and medical writer specializing in making trusted evidence of gut microbiome-related treatments understandable, engaging and ready for use for a range of audiences.

Follow Andreu on Twitter andreuprados. Alterations in the gut microbiome composition and functions are emerging as a potential target for managing IBS. Discover how microbiota-modifying treatments, including prebiotics, probiotics, antibiotics, and fecal microbiota transplantation, hold promise in alleviating symptoms of this vexing condition.

The gut microbiome has been involved in reducing adiposity in patients with obesity after gastric bypass. New research suggests that food intake, tryptophan metabolism, and gut microbiota composition can explain the glycemic improvement observed in patients after Roux-en-Y gastric bypass.

Celiac disease is a chronic immune-mediated enteropathy that may be unleashed by enteric viral infections. However, new findings in mice identified a commensal protist, Tritrichomonas arnold, that protects against reovirus-induced intolerance to gluten by counteracting virus-induced proinflammatory dendritic cell activation.

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages. More information about our Cookie Policy. The timing of food consumption influences the human salivary microbiota A recent study has found that meal timing affects the daily rhythm of the human salivary microbiota and that timing differences may have a deleterious effect on the metabolism of the host.

Facebook Twitter LinkedIn WhatsApp Email. Article: Collado MC, Engen PA, Bandín C, et al. By Andreu Prados. Tagged: Crohn's disease , Food , Inflammation , Metabolic diseases , Metabolic syndrome , Microbiome , Obesity. Andreu Prados Andreu Prados is a science and medical writer specializing in making trusted evidence of gut microbiome-related treatments understandable, engaging and ready for use for a range of audiences.

Related articles Non-prescription therapeutics for IBS: where are we? Reduced red meat intake and gut microbial metabolite indoleacetate linked to better insulin resistance after gastric bypass, new study finds 8 Jan by Joël Doré.

Change cookie settings Close GDPR Cookie Settings Privacy Overview 3rd Party Cookies Cookie Policy. Privacy Overview.

What does this mean for your mealtimes? Each of us requires a given amount of energy in calories each day. This energy is harvested from the carbs, proteins, and fats that we consume. When we fail to eat adequately throughout the day for example, only one or two meals , it can be challenging to meet our energy and nutritional needs.

Regular meal timing also helps to promote regular digestive patterns. I recommend consuming something within two hours of waking up regardless of feeling hungry or not. Sometimes we fail to recognize hunger early in the mornings because the body ceases hunger cues overnight during its powered-down state.

However, I strongly encourage you to try having something small. This meal breaks the overnight fast and provides your body with fuel and nourishment to start and power throughout the day. Meals should include a protein -rich food, high-fiber starches, vegetables, fruits, and fat.

It is important to acknowledge and respond to your hunger cues regardless of a meal schedule. There are various approaches to eating, and having a meal plan that makes you feel your best may not exactly suit someone else and vice versa.

The sample schedule below may be a good place to start to see what works for you. Break your fast. This window is the most recommended time to have breakfast. The difference between dietary energy intake and energy loss in feces was calculated.

Fasted venous blood samples were collected at 8 a. the day after the intervention, in ethylenediaminetetraacetic acid tubes. Tubes containing blood samples were immediately placed on ice and then centrifuged at 4°C, at 3, rpm for 15 min. Plasma was dispensed in 0. High sensitivity interleukin-6 IL-6 Invitrogen, Cat BMSHS and high sensitivity tumor necrosis factor-α TNF-α Invitrogen, Cat BMSHS and insulin Mercodia, Cat were measured using ELISA kits.

Plasma glucose, total cholesterol, HDL cholesterol, LDL cholesterol, triglyceride, and high-sensitivity C-reactive protein CRP were measured at the Queen Elizabeth University Hospital accredited Clinical Biochemistry laboratories.

Operational taxonomic units OTUs were used to analyze the gut microbial i. The paired fastq files were combined, and a maximum error rate of 0. Sequences longer than bp and shorter than bp were filtered out. Chimera identification and removal was carried out using the VSEARCH implementation of the UCHIME de novo algorithm.

OTUs were taxonomically classified to genus level using the RDP naive Bayesian classifier method implemented in the dada2 R package. Statistical analysis was performed using Minitab 17 and R. Analysis of the microbiome data was performed using the phyloseq NMDS plots and vegan permutation ANOVA, richness, diversity, and evenness measurements packages in R.

Significantly different OTUs and genera were identified using paired t tests on the log proportional abundances of each OTU or genus with Benjamini-Hochberg corrections for multiple testing applied to the resultant p values.

As baseline samples were not collected, we performed differential analysis at the end of the 2 interventions. In the absence of pilot data, no formal power calculation was carried out prior to study initiation. However, decision to extend or discontinue the study was made following interim analysis of the data of the first participants.

Seventeen participants took part in this study 8 females and 9 males; mean [SD] age of Daily energy intake varied among participants, ranging from 1, to 3, kcal with an average SD of 2, kcal.

There was no significant mean weight change mean [SD]: 0. Total stool output i. Participants lost on average 5. dinner 5.

Similarly, the time of main meal consumption did not significantly associate with fecal energy output or content Table 1. Regardless of the way data were expressed, fecal SCFA were not significantly different between the 2 interventions Table 2.

The last sample provided by each participant and for each intervention was sequenced using the V4 region of the 16S rRNA gene. Using either the Bray-Curtis dissimilarity Fig. material 3. There was no deviation of any participants from their enterotype, suggesting that the effect of meal timing was unable to supersede the effect of enterotypes.

In differential analysis, the taxon relative abundance of 8 OTUs and 7 genera differed between the 2 interventions Fig.

However, these significant effects vanished when analysis was corrected for multiple testing. Otherwise, the microbiome profile remained unaffected between the 2 dietary interventions at OTU Fig.

material 4. Effect of timing of main meal consumption on the gut microbiome of healthy volunteers. a NMDS using Bray-Curtis distances of OTU community structure. b NMDS using weighted Unifrac distance analysis. c Rarefied richness. d Chao1 index. e Exponential of Shannon index eH.

NMDS, nonmetric multidimensional scaling; OTU, operational taxonomic unit. Log-relative abundance significant differences between the 2 dietary interventions. a OTU level.

b Genus level. OTU, operational taxonomic unit. Effect of the timing of main meal consumption on the relative abundance of the top 20 common OTUs group mean.

Mean microbiome profile of all participants per dietary intervention. A1—A17, microbiome profile of each participant per dietary intervention; OTU, operational taxonomic units. The time of main meal consumption did not influence significantly the fecal concentration of total bacteria or other bacterial groups except for E.

coli , which was significantly higher after the large lunch intervention. This effect remained significant regardless of the approach used to express the data Table 3. Effect of timing of main meal consumption on blood biomarkers of cardiometabolic health.

Box plots show means and quartiles. TAG, triglycerides; CRP, C-reactive protein. White boxplot indicates the large dinner intervention, and gray boxplot indicates the large lunch intervention. One participant had a raised CRP after the end of the second intervention due to a recent cold.

Repetition of statistical analysis after exclusion of this participant did not change the difference in the mean effects observed between the 2 interventions. This study was set out to investigate the effect of the time of main meal consumption on the gastrointestinal microbiome and cardiometabolic factors of the host.

Against our hypothesis, we found that the time at which the main meal was consumed had no acute effects on fecal pH, form and texture of feces, fecal water content, total energy loss in feces, total fecal SCFA output, and the global microbial community structure or taxon relative abundance inferred using high-throughput sequencing.

When we looked at the effect of the 2 interventions on the absolute concentration of dominant bacterial species, we observed a significant increase in the absolute concentration of E.

coli after consumption of the main meal as lunch. This effect is unlikely to be a random or spurious finding as it persisted when we expressed the amount of this species as the average concentration of all samples per participant, concentration, or total output over 3-day complete fecal sample collection.

Interestingly, this signal was not replicated using high-throughput sequencing most likely due to different expression of data absolute vs. relative abundance and other counterbalancing changes. With the exception of the significant effect of our intervention on E.

coli , these findings are against our hypothesis and those results presented previously in cross-sectional research [ 5 ]. It could be postulated that the E. Kaczmarek et al.

Another study investigating the effects of the Western diet on the gastrointestinal microbiome of mice found that it caused an increase in fecal E.

coli levels [ 15 ]. It is therefore possible that a similar response to the Western diet occurred in our participants. Diet has been previously shown to influence fecal SCFA content [ 16 ], but evidence implicating main meal timing is scarce.

We found no significant differences between the lunch and dinner meal interventions for any of the 10 SCFA tested. This observation agrees with previous cross-sectional research in which eating behavior i.

Similarly, we found no difference between the 2 interventions on blood biomarkers of CVD risk. This means that the time at which the main meal was consumed had no acute effects on blood CVD biomarkers such as blood lipids, insulin resistance, or low-grade inflammation, despite weight gain following the intervention with large dinner.

Supporting the findings from this study, a recent weight loss study comparing the effects of a large lunch with a large dinner [ 9 ] found that although a decrease in blood lipids was noted for both groups and in parallel to their weight loss, the change in blood lipid level was not significantly different between the 2 interventions.

Similarly, a crossover RCT investigating snacking times 10 a. found that time of consumption of a high-fat, high-carbohydrate snack had no significant effects on serum triglycerides and HDL cholesterol, but late snacking produced a significant increase in total and LDL cholesterol [ 17 ].

Neither fasted blood insulin, glucose, nor HOMA-IR was responsive to different timing of the main meal. These findings are supported by previous research and a recent meta-analysis where snacking time had no effect on HOMA-IR, insulin, or glucose levels [ 17, 18 ].

Contrary to this evidence, when meal times were delayed by 5 h, plasma glucose rhythms were also delayed by approximately 5 h and average glucose concentration decreased [ 19 ]. Madjd et al. This result was, however, dependent on weight loss, which in the current study was not observed in the intervention with lunch as the main meal, and although weight gain was observed in the other group, the magnitude of this effect was very modest and perhaps too small to evoke an acute effect in young otherwise healthy subjects.

Two proinflammatory cytokines and CRP were measured here as markers of low-grade systemic inflammation, particularly as these markers are often elevated in obese individuals [ 20 ].

Although the origin of this low-grade inflammation remains unknown, there is accumulating evidence to suggest that this might be due to the effect of diet on the gut microbiome and associated endotoxemia [ 2 ]. Our results suggest that time of main meal consumption is unlikely to be a contributor to low-grade inflammation, and this effect is unlikely to be associated with changes in the gut microbiome.

Bomb calorimetry was used on all stool samples from all participants to estimate intestinal absorption capacity [ 21 ] and the effect of the 2 interventions on the percentage of fecal water content and the Bristol Stool Scale as proxies of gastrointestinal motility.

Nutrient load has previously been shown to be associated with changes to the microbiome and correlating with changes to energy loss in stool [ 22 ]. For these reasons, the findings in much of the research that supports nutrient timing may not apply to everyone. Nutrient timing has been around for several decades.

The anabolic window is the most commonly referenced part of nutrient timing 7. However, even though research on the anabolic window is far from conclusive, it is regarded as an important fact by many professionals and fitness enthusiasts.

Both of these principles are correct to some extent, but human metabolism and nutrition are not as black and white as many people like to think.

One main aspect of the anabolic window is carb replenishment, since carbs are stored in the muscles and liver as glycogen. Research has shown that glycogen is replenished faster within 30—60 minutes after working out, which supports the anabolic window theory 8 , 9.

However, timing may only be relevant if you are training several times a day, or have multiple athletic events within a day. For the average person who works out once a day, there is plenty of time to replenish glycogen at each meal Additionally, some research actually shows training with lower muscle glycogen to be beneficial, especially if your goal is fitness and fat loss New research has even shown immediate replenishment may reduce the fitness benefits you receive from that session So although immediate glycogen synthesis makes sense in theory, it does not apply to most people in most situations.

The second aspect of the anabolic window is the use of protein to stimulate muscle protein synthesis MPS , which plays a key role in recovery and growth. Instead, focus on your total daily protein intake , and make sure you eat high-quality protein at each meal A recent meta-analysis by leading researcher Dr.

Brad Schoenfeld also arrived at this conclusion, summarizing that daily protein and nutrient intake is the priority In short, if you meet your total daily needs for protein, calories and other nutrients, the anabolic window is less important than most people believe.

Two exceptions are elite athletes or people who train several times per day, who may need to maximize fuel replenishment between sessions. The anabolic window is a period of time after workouts that is said to be crucial for nutrient intake.

Depending on your goals, the correct timing for taking certain supplements may actually aid performance For example, performance-enhancing supplements like caffeine must be taken at the right time in order to have the proper effect This also applies to food.

A well-balanced, easily digestible meal eaten 60— minutes before a workout may improve performance, especially if you have not eaten for several hours In contrast, if your goal is fat loss, training with less food may help you burn fat, improve insulin sensitivity and provide other important long-term benefits 17 , Hydration is also closely linked to health and performance.

Many people tend to be dehydrated before working out, so it may be important to drink around 12—16 oz — ml of water and electrolytes before the workout 19 , 20 , Additionally, vitamins may affect workout performance, and may even reduce training benefits.

So although vitamins are important nutrients, it may be best not to take them close to your workout Nutrient timing may play an important role in pre-workout nutrition, especially if you want to maximize performance, improve body composition or have specific health goals.

Instead, what you eat for breakfast has become the hot topic. Many professionals now recommend a low-carb, high-fat breakfast, which is claimed to improve energy levels, mental function, fat burning and keep you full.

However, while this sounds great in theory, most of these observations are anecdotal and unsupported by research Additionally, some studies show that protein-based breakfasts have health benefits.

However, this is likely due to the many benefits of protein, and timing probably does not play a role Your breakfast choice should simply reflect your daily dietary preferences and goals. There is no evidence to support one best approach for breakfast.

Your breakfast should reflect your dietary preferences and goals.