The effect of within-day energy distribution on lean body mass and body fat in athletes: A systematic review

Abstract

Nutritional practices have a significant effect on exercise performance as they determine not only acute energy availability for sport activities, but also long-term changes in body composition. This review summarizes the available evidence and explores the critical relationship between within-day energy balance and body composition, emphasizing the importance of even energy distribution for optimal athletic performance and health. Findings revealed that within-day energy balance is a significant factor in the regulation of body composition in athletes, and that negative within-day energy balance may impair muscle protein synthesis and promote fat accumulation. The available evidence suggests that athletes should have an energy intake that dynamically matches requirement (i.e., the portion of the day when energy expenditure is higher, should be matched with a higher energy intake) to avoid prolonged periods of energy restriction. The reviewed investigation emphasized the importance of hourly energy balance assessment, because reliance on 24-h energy status may be insufficient in athletes. However, due to the dearth of scientific evidence in competitive athletes, more research is needed to determine the optimal within-day energy balance, considering training goals, individual differences, and dietary preferences.

Keywords

Eating pattern food restriction protein synthesis skeletal muscle training

Introduction

Nutritional habits have a considerable effect on exercise performance as they determine both acute energy availability for sport activities, and long-term changes in body composition (BC) (muscle mass (MM) and fat mass (FM)). It has been recognized that athletes require higher energy and macronutrient intake to support their increased expenditure due to their high volume/intensity training and greater skeletal MM.^1,2 Unfortunately, it is often observed that many, especially female athletes, do not completely satisfy their macronutrient needs and are at risk of energy deficiency.^3–9 The failure to consume enough food to supply sufficient energy makes it impossible to maintain optimal body functions and inevitably causes MM loss in the affected athletes. Interestingly, research shows that body fat percentage is also often higher in athletes with unsatisfactory energy balance.^10,11 Along with suppressed resting metabolic rate, restrictive eating behavior can lead to serious health issues, including metabolic disturbances, hormonal alterations, osteoporosis and ultimately increase the risk of injuries in athletes.^10,12–14

Most athletes, especially those who participate in moderate to high intensity exercise, rely on carbohydrates as a primary fuel. Therefore, carbohydrate ingestion has a major impact on athletic performance and recovery from exercise by controlling skeletal muscle glycogen resynthesis.^11,15 Protein intake largely determines amino acid availability for muscle tissue growth and plays a role in the repair of muscle damage, especially as related to resistance exercise adaptations.^16–19 Naturally, sport nutrition research and practice has focused on carbohydrate and protein consumption and especially peri-exercise nutrient and energy availability.^20–25 However, pre-exercise, and postexercise nutrient provision can and should be considered in the context of overall energy and nutrient availability for the athlete.²³ In fact, when energy availability was lower than required in female participants during exercise training, myofibrillar and sarcoplasmic protein synthesis, lean mass (LM) and nitrogen balance were all reduced.¹⁴ Moreover, in an Australian study of general adult population, diet quality and micronutrient intake were higher in participants consuming ≥3 meals/day vs. < 3 meals/day.²⁶ In recent years, meal frequency/energy distribution has been a topic of interest in obesity research, however, there is not enough emphasis on this dietary practice in competitive athletes despite the importance of BC in athletic performance.^27–35

The distribution of meals and snacks throughout the day can affect within-day energy balance in athletes, which in turn can influence long-term adaptations and performance. This issue was first highlighted in the 1990's that within-day energy balance is an important determinant of BC in athletes.^12,15,36 The extent of energy surplus and energy deficiency has a large effect on lean body mass (LBM) and FM, that is the overall time an athlete achieves energy balance or suffers energy deficit (usually ±300–400 kcal, the theoretical values for an optimal energy balance, based on the predicted availability of liver glycogen)^12,13,37 during a single day can determine MM and BF accumulation. It has been suggested that the underlying benefits of consuming more frequent meals may include increased thermogenesis and the prevention of excessive fluctuations in blood glucose and insulin levels, which may have a long-term impact on BF accumulation and the maintenance of LBM.^11,28,38,39

This systematic review summarizes the available evidence on the effects of within-day energy balance on BF and LBM/MM in athletes. The review also discusses the practical implications of manipulating within-day energy balance for optimal BC in athletes and provides recommendations for nutritional habits to support athletic performance and health.

Materials and methods

Eligibility criteria

Studies eligible for inclusion sampled athletes, over 14yrs old and were required to report data on the BC and energy balance within a day. Included studies were exclusively full text, peer-reviewed and published in English before 31^st of July 2024 (since the database available). To comply with our goal of examining within-day energy deficiency on BC in competitive athletes we did not include studies that evaluated non-healthy or non-athlete participants. In the analyzed studies athletes were NCAA division competitors, members of national- or university teams. Based on the eligibility criteria, thirteen studies were excluded from the final review with reasons of: duplicate studies, included non-athletes or non-healthy participants, had missing data on BC and the measure of energy balance did not assess within-day or hourly values.

Search strategy

Search strategy executed with Boolean operator⁴⁰ and included the combination of the following terms “meal frequency”, “eating frequency”, “feeding frequency”, “meal pattern “, “eating pattern”, “feeding pattern”, “meal distribution “, “eating distribution “, “feeding distribution”, “within-day energy balance”, “within-day energy deficit”, “body composition”, “lean mass”, “muscle mass”, and “athletes”. The search was conducted by two researchers (ZM, ZK) independently via the following databases Embase, PubMed, Scopus, SportDiscus and Web of Science. Additional manual search was conducted by screening through the reference list of the relevant articles.

Study records

Search results were uploaded into an Excel file and duplicates removed. Two reviewers (ZM, ZK) independently screened titles and abstracts against eligibility criteria. After initial screening, two reviewers (ZM, ZK) independently assessed the full text of the retrieved articles for compliance with eligibility criteria. A PRISMA⁴¹ flow diagram of the study selection procedure was created (Figure 1). Quality assessment of the included studies was conducted independently by two raters (GC and ZK), blinded to each other, and classified each article with a final consensus using the Physiotherapy Evidence Database (PEDro) scale for quality rating. The scale has 11 criteria, with a maximum score of 10 for the PEDro scale (Table 1). In all cases both during the screening and the quality assessment process, where the opinions of the two reviewers/raters differed from each other, the decision was made with the involvement of the third co-author.

Figure 1.

PRISMA flow diagram of the selection process for identified records from databases. *Web of Science.

Table 1.

PEDro scale for quality rating.

Study	Eligibility criteria specified	Random allocation	Groups similar at baseline	Less than 15% dropout	Intention-to-treat analysis	Between-group statistical comparisons	Point measures and variablity data	Total
Behrens et al. 2020	YES	0	0	1	1	1	1	4
Bellissimo et al. 2019	YES	0	1	1	1	0	1	4
Deutz et al. 1999	YES	0	0	1	1	1	1	4
Iwao et al. 1996	YES	1	1	0	1	1	1	5
Matshushita et al. 2019	YES	0	0	1	1	1	1	4
Taguchi et al. 2021	YES	1	1	1	1	1	1	5
Torstveit et al. 2017	YES	0	0	1	1	1	1	4

Results

The search identified 3831 unique papers; 20 were suitable for full text assessment and seven papers were included in the systematic review as shown in the flowchart (Figure 1). Due to the variability in study designs and the measured parameters, the available data could not be incorporated into a meta-analysis, however, we conducted a systematic review exploring the relationship between energy distribution and BC (BF and/or LMM) in athletes. Of the seven papers identified two used meal frequency as an indication of energy distribution, while five calculated hourly energy surplus and deficit to determine within-day energy balance. The characteristics of the analyzed studies are presented in Table 2. The average score on the PEDro scale checklist was 4 (the overall score ranges from 0 to 10, because item 1, which relates to external validity, is not counted). None of the included studies was of poor (score less than 4) quality, all seven studies were classified as being of fair methodological quality (score 4–5).^42,43 The subject-, therapist-, and assessor blinding criteria are less relevant as they are impractical in the dietary assessment of athletes, in terms of the selected outcomes, however the lack of points has impact on the average score. Full details of the PEDro scale checklist can be found in Table 1.

Table 2.

Characteristics of the studies included in the systematic review.

Author, (Year)	Study population					Variables		Outcome Measures
Author, (Year)	Sample (N) / Groups		Mean age yr (SD)		Gender	Body composition	Study design	Total hours (SD or CI) in energy deficits (< 300-400 kcal)		Association with body composition
Behrens et al. (2020)⁴⁶	N = 20 Soccer		18.9 (1.0)		Female	BF% FM BIA	Cross-sectional Self-reported, diet record 3 days, activity log	7.0 (4.8)		r = .67 p = .01 BF%	r = .71 p = .01 FM
Bellissimo et al. (2019)⁴⁷	N = 19 Cheerleaders		25.4 (3.5)		Female	BF% LBM BIA	Cross-sectional Self-reported hourly unit 24 h recall, activity energy expenditure	13.3 (4.8)		r = −.55 p = 0.01 (BF%)	p = .55 p = .02 (LBM)
Deutz et al. (2000)⁴⁸	N = 62		Gymnasts: 15.5 (1.8)	Runners: 26.6 (4.5)	Female	BF% DEXA	Cross-sectional Simultaneous self-reported 24 h dietary- and activity recall	Gymnast: 17.98 (6.25)	Runners: 10.20 (8.61)	All: r = .407 p = .001
Deutz et al. (2000)⁴⁸	Gymnasts (N)= 42	Runners (N)= 20	Gymnasts: 15.5 (1.8)	Runners: 26.6 (4.5)	Female	BF% DEXA		Gymnast: 17.98 (6.25)	Runners: 10.20 (8.61)	All: r = .407 p = .001
Iwao et al. (1996)⁴⁴	N = 12		2M:20.3 (0.3) 6M:19.7 (0.5)		no data	BF (kg) LBM BIA	Longitudinal (2 weeks) -1200 kcal/day 2M:2× 600 kcal 6M:6× 200 kcal	n.a.		pre-post
Iwao et al. (1996)⁴⁴	Boxers: 2 M (N)= 6	Boxers: 6 M (N)= 6	2M:20.3 (0.3) 6M:19.7 (0.5)		no data	BF (kg) LBM BIA		n.a.		2M BF (−1.4 + 0.4) p = .05 LBM (−3.5 ± 0.3) p = .01	6M BF (−2.6 ± 0.4) p = .01 LBM (−2.4 ± 0.3) p = .01
Matsushita et al. (2018)⁴⁹	N = 57		RG: 18.9 (1.9)	Control: 21.5 (2.0)	Female	BF% BIA	Cross-sectional Self-reported, diet recall 3 days, daily energy expenditure calculation	no data		RG r = .343 p = .047	Control n.s.
Matsushita et al. (2018)⁴⁹	RG (N)= 34	Control (N)= 23	RG: 18.9 (1.9)	Control: 21.5 (2.0)	Female	BF% BIA		no data		RG r = .343 p = .047	Control n.s.
Taguchi et al. (2021)⁴⁵	N = 10		20.0 (1)		Male	BF% FM FFM DEXA	Crossover (8 weeks intervention and 5 weeks washout) +20 kcal/kg/BW, 3 M/day, 6 M/ day	n.a.		pre-post (Cohen's d)
Taguchi et al. (2021)⁴⁵	3 M (N)= 6	6 M (N)= 5	20.0 (1)		Male	BF% FM FFM DEXA		n.a.		3M BF% d = .5 FM d = .55 FFM d = .35	6M BF% d = .46 FM d = .52 FFM d = .37
Torstveit et al. (2017)¹³	N = 31 Endurance athletes		34.7 (8.1)		Male	BF% DEXA	Cross-sectional Self-reported, diet record 4 days, HR monitor activity record	18.8 (10.5–21.6)		Largest hourly deficit r = −.359 p = .047

Notes: BF%: Body fat %; BW: body weight (kg); FM: Fat Mass (kg); FFM: Free Fat Mass (kg); HR: heart rate; LBM: Lean Body Mass (kg); n.s: non-significant; n.a: not applicable; RG: Rhythmic Gymnastics; 2M: two meals/day; 6M: six meals/day; BIA: bioelectrical impedance analysis; DEXA: dual energy x-ray absorptiometry.

Meal frequency

Iwao and coworkers⁴⁴ examined changes in body weight (BW), LM, and FM in 12 boxers during food restriction (weight cutting), in response to two different meal frequencies. The athletes consumed identical diets with 1200 Kcal energy content either twice (2/d) or six times a day (6/d). Although, BW decreased to the same extent in both groups during the 2-week intervention, the less frequent meal schedule led to a significantly larger loss of LBM. Moreover, a slight, albeit non-significant difference (2.6 ± 0.4 kg vs. 1.4 ± 0.4 kg) in the loss of FM was also observed, favoring the more frequent meal schedule. Interestingly, skinfold thickness measurements indicated that only the 6/d group decreased subcutaneous fat in the analyzed regions (subscapular, brachial). Thus, the authors concluded that a more even daily energy distribution preserved LM during weight loss compared to low frequency meal consumption. This notion was also supported by the lower urinary 3-methylhistidine level in case of the 6/d meal schedule.

As opposed to these findings, Taguchi et al.⁴⁵ did not detect any differences in BW, FM and fat free mass (FFM) between athletes on a regular- (3/d) or a high frequency (6/d) eating plan using identical isocaloric diets during weight gain. It must be mentioned that this study used a cross-over design with eight-week interventions and a five-week washout period between the conditions, which might have influenced the results as acknowledged by the authors. It is also possible that when the goal is to increase lean mass, maintaining a large energy surplus over 24 h ensures a constant positive energy balance, making the timing and frequency of meals less important. In fact, in this study the athletes on both diets have achieved an almost identical positive energy balance of over 1300 kcal/day, therefore it is likely even in the absence of hourly energy balance measurement that both feeding frequencies yielded similar number of hours spent in energy surplus for the day.

Hourly energy balance

Weight loss and weight gain pose specific challenges to an athlete's energy provision and metabolism, and are usually restricted to a specified, limited time, therefore these interventions may not represent the normal daily energy balance in the long-term. Other researchers analyzed the effect of within-day/hourly energy distribution on BF and LBM.^13,46–49 Deutz and colleagues⁴⁸ analyzed the diets of 62 competitive female gymnasts and runners with a validated procedure to estimate 24-h total energy intake and within-day energy distribution. This study reported a significant positive correlation (r = 0.407; p = 0.001) between BF % as measured by dual energy x-ray absorptiometry (DEXA) and the hours spent in negative energy balance of >300 kcal regardless of the age and the sport of the participants. It also has to be mentioned that the proportion of total daily energy intake relative to predicted energy requirements plays a significant role in body fat percentage among athletes. Despite the similarity in total energy intake, the rhythmic gymnasts had significantly greater within-day energy deficits and a significantly greater body fat percent. Along the same lines, Bellissimo et al.⁴⁷ determined that professional cheerleaders who spent more hours in positive energy balance (+300 kcal) had a significantly lower BF% (p = 0.01), and those with less time in negative energy balance (−300 kcal) had lower BF% (p = 0.04) and higher LBM (p = 0.04). In this study, total energy intake was significantly below the recommended level for athletes with 31.6% of the participants having energy restrictive diets. Similarly to the weight loss intervention in a past investigation by Iwao et al.,⁴⁴ also supported the importance of within-day energy distribution/energy balance in the preservation of LBM. A study conducted by Behrens et al.⁴⁶ indicated that on average, female soccer players (n = 20) spent 7.0 ± 4.8 h in <400 kcal energy deficit, 13.9 ± 3.4 h in ±400 kcal energy balance, and 3.1 ± 2.9 h in >400 kcal energy surplus. The main outcome of this investigation was the positive association between the total time spent in energy balance and in energy surplus and lower FM. On the other hand, time spent in energy deficit was associated with higher FM. As most studies measure energy balance across a 24-h period, the authors stated that assessment of hourly, rather than daily energy balance would assist with the development of tailored approaches to target energy balance to enhance performance, BC, and the overall well-being of athletes. Along with non-athlete controls, Matsushita and colleagues⁴⁹ analyzed 34 Japanese rhythmic gymnasts and reported that there was no significant relationship between BF% and total energy intake and energy balance in the group. However, there was a significant negative relationship with energy intake ratio % (calculated as the individual energy intake during each mealtime divided by the total energy intake over the day) in the evening (r = −0.371, p = 0.031) and a significant positive relationship with the energy intake ratio % at night (r = 0.353, p = 0.041). The authors also conducted a multiple linear regression analysis, using substitution models to further analyze the relationship between BF % and ER %. According to the researcher's interpretation of the overall results, the daily distribution of energy intake plays a major role in optimal BC and BF.

In contrast to the previous studies, the only study showing a significant, albeit weak negative relationship (r = −0.366) between energy balance and BF % examined 31 male endurance athletes and concluded that those in energy deficit (larger number of hours in within-day balance of <0 kcal) exhibited lower BF %.¹³ However, energy deficit of < −400 kcal, below the theoretical values for an optimal energy balance,^12,37 did not show significant correlation with BF % in this study. This research focused on the health-related consequences of energy deficiency and emphasized the importance of hourly energy balance assessment, because reliance on 24-h energy status may be insufficient to detect metabolic disturbances and other health risk to athletes. To support this notion the authors reported that despite no difference in 24-h energy intake, participants with suppressed resting metabolic rate spent more time in energy deficits (p = 0.023) and had larger single-hour energy deficits (p = 0.023) compared to athletes with normal values.

It is important to recognize that the studies mentioned here are observational in nature, which means that these data do not allow for the establishment of a cause-and-effect relationship between hourly energy distribution and changes in body composition.

Discussion

The main findings of this review are that within-day energy balance may be an important factor in the regulation of BC in athletes, and that negative within-day energy balance may impair muscle protein synthesis and promote fat accumulation. The observation that increased fat mass is associated with suboptimal energy intakes calls for further controlled investigations to objectively explore the contributing factors. Furthermore, the available evidence suggests that athletes should have an energy intake that dynamically matches requirement (i.e., the portion of the day when energy expenditure is higher, should be matched with a higher energy intake) to avoid prolonged periods of energy restriction. During food restriction (weight cutting), a more frequent meal schedule may help preserve LM and reduce FM by maintaining a higher metabolic rate and stimulating protein synthesis. On the other hand, in athletes aiming for gain of lean mass a large 24-h energy surplus may ensure a greater number of hours in positive energy balance. The primary limitation of the studies selected for this systematic review is the self-reported dietary intake, which may result in underreporting energy intake.^50–52 Despite its importance, the dearth of available research on hourly energy balance also makes it difficult to formulate a definite conclusion about the association between energy distribution and LBM.

It is possible that during weight gain, a large 24-h energy surplus ensures continuous positive energy balance, and the timing and the frequency of meals are not as important. In a study by Taguchi et al.,⁴⁵ athletes on a regular- (3/d) or a high frequency (6/d) diets had an almost identical positive energy balance of over 1300 kcal/day, therefore it is likely that both feeding frequencies yielded similar number of hours of energy surplus for the day. Weight loss and weight gain pose specific challenges to an athlete's energy status and metabolism, and are usually restricted to a specified, limited time, therefore these interventions may not represent the normal daily energy distribution in the long-term.

Sustained energy deficit in athletes can lead to serious health issues, including metabolic disturbances, hormonal alterations, osteoporosis and ultimately increase the risk of injuries.^7,53–58 Athletes with poor dietary choices and/or restricted energy consumption are likely susceptible to suboptimal micronutrient intake, while a positive association was reported between meal frequency and micronutrient intake and diet quality.²⁶ Another investigation reported that 65% of the athletes exhibited depressed resting metabolic rate (RMR) and although they had similar energy availability to those with normal RMR, the time spent in energy deficit as well as their single-hour energy deficit were significantly greater.¹³ The results of this study suggest that male endurance athletes with suppressed RMR also exhibit negative effects of energy deficiency, such as increased cortisol levels and reduced testosterone/cortisol ratio. Energy deficit was also reported in young (under 16) soccer players, especially as related to pre- and post-training requirements.⁵⁹ These hormonal changes may lead to impairments in performance and recovery, as well as general health and well-being. Insufficient energy intakes can compromise training adaptations because energy deficiency triggers the breakdown of lean tissue for fuel, resulting in a loss of strength and reduced sport performance. In addition, metabolic rate also decreases, resulting in higher BF %.^{1,10,12,37,60,61} A seven-day dietary analysis of Korean soccer players also demonstrated that energy intake was significantly higher in participants with normal RMR compared to those with suppressed RMR (7-day total: 3660 ± 347 vs. 3024 ± 491 kcal/day, p = 0.046).⁶² The same researchers also showed an association between low energy availability and metabolic suppression in a prior study.⁶³ Interestingly, a greater risk of muscle tissue loss due to insufficient energy intake has been reported in athletes compared to sedentary cohorts.^64,65 On the other hand, when in positive energy balance, moderate amount of protein consumption (15–30 g) with regular frequency was associated with lower BW-adjusted FM and higher FFM in female soccer players.²⁵

It is especially important for athletes and coaches that apart from total daily energy intake and expenditure, they also monitor the extent of energy availability (deficit/surplus) throughout the day. In fact, regardless of the study outcomes, the reviewed investigation emphasized the importance of hourly energy balance assessment, because reliance on 24-h energy status may be insufficient to detect metabolic disturbances and other health risk to athletes. In addition, assessment of hourly, rather than daily energy balance would assist with the development of tailored approaches to target energy balance to enhance performance and BC of athletes. However, considering the scarcity of scientific evidence in competitive athletes, more research is needed to determine the optimal within-day energy balance for achieving the most favorable BC, taking into account training goals, individual differences, and dietary preferences. Studies, analyzing the association between energy distribution/energy balance and LBM are especially needed - using similar methods for estimated energy balance - as the majority of the available literature only included measures of FM.

Conclusions

It is essential for athletes to plan their food intake based on their training and competition schedules and follow some general guidelines for optimal meal timing: –

athletes should aim to have a dynamic energy intake that matches requirement throughout the day to avoid prolonged periods of energy restriction, as this helps preserve lean mass (LM) and reduce fat mass (FM);

–

eat a balanced breakfast within one hour of waking up, or at least 90 min preceding the morning workout;

–

include healthy snacks between meals if necessary to meet energy and nutrient requirements;

–

consume high glycemic index carbohydrate and protein rich (∼20–30gr depending on BW) snack within ∼30 min after exercise to replenish glycogen stores and promote muscle remodeling;

–

large 24-h energy surpluses may be sufficient for athletes aiming for lean mass gain, as meal timing and frequency become less critical in such scenarios.^{2,10,11,15,18,20–22,24,37,54,66,67}

Footnotes

Contributors

The authors listed qualify for authorship based on making one or more of the substantial contributions to the intellectual content of conception and design (ZsM); and/or acquisition of data (ZsM); and/or analysis and interpretation of data (ZsM, ZsK); and/or participated in drafting of the manuscript (ZsM, ZsK, GC) and/or critical revision of the manuscript for important intellectual content (ZsM, ZsK, GC). All authors provided critical feedback and helped shape the research, analysis and manuscript.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Zsolt Murlasits

Zsuzsanna Kneffel

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