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Breakfast and behavior in morning tasks: Facts or fads?
Journal of Affective Disorders (xxxx) xxxx–xxxx
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Review article
Breakfast and behavior in morning tasks: Facts or fads? ⁎
Valeria Edefonti , Francesca Bravi, Monica Ferraroni Branch of Medical Statistics, Biometry, and Epidemiology “G. A. Maccacaro”, Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
A R T I C L E I N F O
A BS T RAC T
Keywords: Breakfast Energy intake at breakfast Breakfast composition Cognitive performance Academic performance
Background: Most of the studies investigating the effects of breakfast on cognitive performance have compared performance in subjects who have or have not consumed this meal. However, characteristics of breakfast itself may influence mental abilities. Moreover, as far as the positive effects of having breakfast is more evident, research may focus on the specific characteristics of an adequate breakfast. Methods: To update an existing systematic review, published at the beginning of 2014, on the role of nutrient composition and/or energy intake at breakfast on the accomplishment of school-related tasks and cognition, we carried out a systematic review of the literature through PUBMED database. Results: From the literature search, we identified 39 papers, of which 2 were eligible according to our inclusion criteria. Both the selected papers concerned randomized crossover studies on the acute effect of breakfast carried out in a school setting in the United Kingdom. Both studies compared 2 iso-energetic breakfasts with a similar macronutrient composition; however, the alternative breakfasts were meant to differ in terms of glycemic index or glycemic load. The effects of breakfast composition were investigated on memory, attention, and information processing in both studies. However, different tests and subdomains were considered. Limitations: Studies on these issues are still inconsistent and quantitatively insufficient to draw firm conclusions. Conclusions: While the hypothesis of a better mental performance with breakfast > 20% daily energy intake still needs confirmation, there does appear to be extra evidence that a lower postprandial glycemic response is beneficial to mental performance.
1. Introduction More than two years have passed since the publication of our systematic review collecting evidence on the role of the amount of energy intake at breakfast and breakfast composition on various measures of cognitive/academic performance (Edefonti et al., 2014). Since then, there has been a growing interest on the several possible dimensions of the relation between breakfast and cognition. This is, in particular, witnessed by the publication of two very recent systematic reviews in the Supplement of the same number of Advances in Nutrition (Adolphus et al., 2016; Galioto and Spitznagel, 2016). Both the reviews are still dedicated in part to consolidate the available results on the acute effects of breakfast compared with the ‘no breakfast’ option. In accordance with previous literature, their main conclusions are, indeed, that breakfast has generally a short-term positive, domain-specific effect on cognitive function – measured within a few hours post ingestion – in healthy children/adolescents
(Adolphus et al., 2016) and adults (Galioto and Spitznagel, 2016). In detail, there is general agreement that memory domain benefits from having breakfast - as compared to fasting – whereas results on attention and executive functions are apparently different in children/adolescents and adults (Adolphus et al., 2016; Galioto and Spitznagel, 2016). Moreover, both the reviews have recognized the attention dedicated in the literature to the relation between breakfast composition and cognitive/academic performance, as initially suggested by Dye et al. (Dye et al., 2000) for any eating occasion and, more recently, by our review on breakfast only (Edefonti et al., 2014). However, they did not deal with the (possibly independent) role of energy intake from breakfast in short-term mental processes. In addition, the two mentioned reviews (Adolphus et al., 2016; Galioto and Spitznagel, 2016) and ours (Edefonti et al., 2014) differ with respect to several inclusion/ exclusion criteria, including the type of breakfast manipulation (acute/ chronic, experimental or not), the inclusion of laboratory-developed
Abbreviations: BF, breakfast; CHO, carbohydrate; CH=, cholesterol; d=, day; EI=, energy intake; F=, females; GI, glycemic index; GL=, glycemic load; h, hour; min, minutes; M, males; N=, no; P, protein; RAG=, rapidly available glucose; s=, seconds; SAG, slowly available glucose; Y=, yes; y, year ⁎ Correspondence to: Dipartimento di Scienze Cliniche e di Comunità, Università degli Studi di Milano, Via G. Venezian 1, 20133 Milano, Italy. E-mail address: [email protected] (V. Edefonti). http://dx.doi.org/10.1016/j.jad.2016.12.028 Received 30 June 2016; Received in revised form 29 November 2016; Accepted 17 December 2016 0165-0327/ © 2017 Elsevier B.V. All rights reserved.
Please cite this article as: Edefonti, V., Journal of Affective Disorders (2017), http://dx.doi.org/10.1016/j.jad.2016.12.028
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when the separate effect of different breakfast options during the morning was clearly reported.
macronutrient manipulations, the type of comparison (breakfast vs fasting, energy at breakfast, breakfast composition), the duration of the overnight fasting period allowed, and the target subpopulation of the analysis. For this reason, the overlapping between the selected studies is minimal. Finally, the indicated databases were searched until July 2014 (Adolphus et al., 2016) and May 2015 (Galioto and Spitznagel, 2016). The aim of the present paper is to provide an updated systematic review of the role of nutrient composition and/or energy intake at breakfast on objective cognitive/academic performance outcomes from any kind of studies in children, adolescents, and adults. Although it is still unclear whether breakfast is a determinant or a short-term indicator of cognitive performance, these issues may have important consequences in the definition of public health guidelines and in the assessment of the nutritional, educational and economic value of school breakfast programs (Ells et al., 2008).
2.2.3. Outcome measures Studies that assessed any outcome of objectively measured of cognitive, academic (school grades and standardized achievement tests) and school (enrollment, attendance, achievement, in-class behavior and behavior at school, and school drop-out) performance were considered. Acute (=performance assessed within 12 h of breakfast consumption) and chronic effects of breakfast manipulations (typically, through school breakfast programs) were included. When reported, we included the name of the adopted cognitive test, as well as the corresponding psychological construct assessed. Otherwise, we simply reported the specific neurocognitive construct. 2.2.4. Exposure measures
2. Methods
2.2.4.1. Energy intake at breakfast. Studies providing quantitative estimates of total energy intake for different breakfast options, including either absolute intakes or percentages of daily energy intake provided by breakfast, were included. Studies based on standardized breakfast options with a fixed quantitative estimate of energy intake were excluded. Information on energy intake at breakfast was consistently expressed in kilocalories throughout the paper.
2.1. Literature search We updated our previously published systematic review (Edefonti et al., 2014) with a more recent systematic search through MEDLINE via PubMed (http://www.ncbi.nlm.nih.gov/pubmed/) to identify all the articles on the relationship between cognitive/academic/school performance and breakfast composition/energy intake published as full texts in English from January 1st, 2013, up to May 31st, 2016, based on the following original string (breakfast OR “breakfast composition” OR “daily meal distribution”) & ("energy intake" OR "energy contribution" OR "energy expenditure" OR quality OR energy OR skipping OR “glycemic index”) & ("intellectual performance" OR "neuro-performance" OR "mental performance" OR "cognitive performance" OR “academic performance” OR “school performance” OR performance)”, following the guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) group (Moher et al., 2009). Two authors (F.B. and V.E.) independently reviewed the papers and carried out the selection. The reference lists of the selected articles and of other systematic reviews focusing on similar topics were also examined to identify other relevant papers, if any. Discrepancies in article selection were resolved by involving a third author (M.F.).
2.2.4.2. Breakfast composition. Studies providing quantitative estimates of the macronutrient composition of different breakfast options were considered. This included breakfast meals standardized for energy supply. When the authors stated in the papers that the considered breakfast options were iso-energetic or similar in energy intake, we reported this information in the tables. When the difference in energy content between treatments was higher than 10% and it was possible to distinguish the energy intake associated to each effect in the statistical models, we included the corresponding article in the analysis concerning energy intake at breakfast, too. We did not include studies assessing the relationship between cognition and the interaction between macronutrient composition of the breakfast and glucose tolerance, as there was no possibility to assess the separate effect of breakfast composition.
2.2. Inclusion and exclusion criteria 2.2.5. Association between exposure and outcome measures Studies considering any kind of relationship between cognition/ academic performance and energy intake at breakfast or breakfast composition were included. This included results obtained from different statistical approaches, including simpler tests and confidence intervals, correlation analysis, multiple regression models, and multivariate repeated measures ANOVA. Finally, we decided not to exclude studies on the basis of their quality, because of their limited number and of the high variation in the adequacy of descriptions provided.
Briefly, papers were included or excluded according to the following criteria. 2.2.1. Participants Studies involving children, adolescents or adults of either sex were included. We did not include studies on subjects with acquired metabolic disorders (such as hyperlipidemia, or type-2 diabetes). 2.2.2. Breakfast definition Breakfast was defined according to the descriptions provided in the papers. Although these varied, breakfast was generally considered as the first food/meal of the day, though some interventions did not provide explicit control for previous food consumption. Studies comparing different breakfast types were included. Studies comparing breakfast and “no breakfast” options were not included, unless when different breakfast options, with specified energy or composition, were compared. Studies were included no matter of the content of the meal. However, we excluded those studies where breakfast options differed by the presence/absence of coffee only. In addition, studies investigating the role of glucose-based or emulsion-based manipulations (including formula milk, foam like vanilla creams, gelatins resembling milkshakes in consistency, and spoonable creams) were not included. Studies considering intakes at other mealtimes were excluded, unless
2.3. Data extraction Information extracted included: 1. General characteristics of the studies (first author and year of publication, country, sponsorship, number/age of the participants, distribution by gender, inclusion/ exclusion criteria, and study setting); 2. Design and characteristics of the intervention, and presence of any school program in support of it (type of design, randomization, counterbalancing and crossover details, when available, number of days of observation and schedule, information on the dinner the night before and on explicitly stated overnight fast, schedule of the breakfast); 3. Breakfast definition: list of the breakfast options and corresponding details on absolute/relative values 2
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included subjects. One study included children 5–11 years old) (Young and Benton, 2015) and the other adolescents 11–13 years old) (Cooper et al., 2015). The size of the study samples was limited and the studies were of short duration ( < 1 month). One study was based on a mixed research design investigating the combined effect of 2 breakfast options and exercise/resting (Cooper et al., 2015). In both studies, there was a comparison between 2 iso-energetic breakfasts options with a different macro-nutrient composition. In detail, in one study, the alternative breakfast options are indicated as differing in terms of glycemic index (GI) (Cooper et al., 2015), while, in the other, they are expected to differ in their glycemic load (GL) (Young and Benton, 2015). The 2 breakfast options showed similar intakes of carbohydrate, fat, and protein, as well as energy, in both the studies (Cooper et al., 2015; Young and Benton, 2015). One of the two studies (Young and Benton, 2015) recorded the weight of uneaten food to estimate the actual energy intake and nutrition composition of the meal. Both the studies investigated the following cognitive domains: memory, attention, and information processing. However, the corresponding tests were different across studies and assessed the effect of breakfast on different subdomains. The schedule of test sessions after breakfast was different too. Memory ability was significantly sensitive, to various degrees, to breakfast compositions providing different glycemic responses in both studies (Cooper et al., 2015; Young and Benton, 2015). Although the nature of the meals did not influence any measure of cognition after 1 h, after 3 hs, verbal short-term memory (mean number of words recalled) improved after the low-GL breakfast; it also declined over the morning after eating the high-GL (but not the low-GL) breakfast (Young and Benton, 2015). In addition, immediate spatial memory was better in those children who had consumed the low-GL breakfast, as compared to the high-GL one, but only on the second day of testing (Young and Benton, 2015). As to working memory, although in the absence of a main effect of breakfast composition on both accuracy and response times to the Sternberg paradigm, response times were still improved across the morning following a low-GI breakfast, on the more complex test level and regardless of the exercise/resting trial (Cooper et al., 2015). However, following a high-GI breakfast, response times improved across the morning on the exercise trial only (Cooper et al., 2015). Finally, there was no differential effect of breakfast options differing in GL on verbal delayed memory (Young and Benton, 2015). Attention was also potentially influenced by different breakfast compositions, but results on this domain were inconsistent. In detail, the ability to sustain attention (number of lapses in the Shakow test) was not influenced by breakfast compositions differing in GL at the 3and 12- second delay in either days of testing (Young and Benton, 2015). In addition, in the Stroop test investigating selective attention in terms of both accuracy and response times, neither response times nor accuracy were significantly affected by the type of breakfast consumed. However, on the complex test level only, response times improved across the morning following the low-GI breakfast, no matter of the exercise or resting trials, although the greatest improvement was seen on the exercise trial (Cooper et al., 2015). Concerning speed of information processing and visual information processing, on the visual search test, no significant effects of the highvs low-GI breakfast were detected for either response times or accuracy (Cooper et al., 2015). Similarly, there was no significant difference between breakfast options differing in GL content when reaction times were considered (Young and Benton, 2015). However, even in the absence of a differential effect in speed on the first day, the consumption of the low-GL breakfast, rather than the high-GL one, was associated with a faster performance on the second day of testing (Young and Benton, 2015). Finally, one study (Young and Benton, 2015) was sponsored by industry, whereas the other was not. Table 2 shows a summary of findings on the relationship between
of energy intake and/or on the macronutrient composition of the different options; 4. Outcome definition according to the different standardized tests used and information on time and procedure performance was assessed with respect to breakfast (in the standardized time unit of minutes); 5. Main results on the relationship between breakfast characteristics and cognitive/academic performance (when multiple statistical models were provided in the original paper, we reported estimates adjusted for the largest number of confounding variables). 3. Results From the literature search through PUBMED database, we identified 39 full-text papers published between January 1st, 2013, and May 31st, 2016, all of which satisfied the filters on Humans and English language. Their full-texts were retrieved for detailed evaluation. After the exclusion of 2 review papers, 35 original research ones were also excluded because they met the exclusion criteria indicated previously. In detail, the most frequent reasons for exclusion were: absence of information about cognitive/academic performance and/or breakfast; lack of information on breakfast energy intake or macronutrient composition; a fixed estimate of energy intake; several breakfast options including no breakfast and 2 or more different breakfast meals, but with no available comparisons between alternative breakfast meals; other meals provided together with breakfast (e.g., mid-morning snack, evening meal, lunch), with no possibility to assess the individual contribution of energy/composition of each meal. No additional papers were identified from manual searches on reference lists of selected original and review papers. Therefore, 2 papers, providing information on 2 different studies, were included in our updated systematic review (Cooper et al., 2015; Young and Benton, 2015) (Fig. 1). Both the papers were published in 2015 by groups of researchers that contributed with original papers to our previous review (Edefonti et al., 2014) and concerned randomized crossover studies carried out in a school setting in the United Kingdom. The main characteristics of the 2 studies included in the previous review are shown in Table 1. The selected studies examined healthy, mixed sex populations (Cooper et al., 2015; Young and Benton, 2015). In one study (Young and Benton, 2015), the included subjects came from amongst the most socially deprived areas of Wales, as to the Welsh Index of Multiple Deprivation; in the other study (Cooper et al., 2015), there was no mention of the socio-economic conditions of the 39 records identified through searches of PubMed/MEDLINE database and screened
0 records excluded (no on Humans or no English language)
39 full-text articles assessed for eligibility
35 records excluded (title and/or abstract not relevant or not satisfying the inclusion criteria)
2 reviews excluded
0 additional articles identified from manual searches on reference lists of selected original and review papers 2 studies included in the updated systematic review Fig. 1. Flowchart of the study selection process for the systematic review.
3
4
(Young and Benton, 2015)
BF time not provided
Healthy subjects School setting No.=75
(N) Random crossover
Overnight fast
48% M 52% F
3 separate morning assessments 7-d apart (familiarisation session +3 testing sessions)
Self-selected similar dinner on each occasion
11–13 ys
UK
Balanced, randomized, crossover
Design and intervention (School program: Y/N)
Mean ~12.5 ys
No.=51 (42)
(Cooper et al., 2015)
(N)
Study subjects
Reference (Sponsorship: Y/N)
High-GL 337 kcal, 73.3 CHO, 9.2 P, 1.9 fat, GL 59.85
Recall of Objects test of the British Ability Scale: the test consisted in visualization of a card with 20 objects, with subsequent recall of the items (immediate verbal memory); then the position of the items
Tested in 2 sessions at 60 and 180 min after BF
No main effects of BF after 1 h on all memory domains. After 3 hs children's immediate verbal memory improved after the low-GL BF, while declined over the morning after eating high-GL BF. If children had eaten the low-GL BF on the second d of testing they had a better spatial memory later in the morning
2) Sternberg paradigm for working memory (3 levels with different memory loads);
low-GI (for a 50 kg participant: 420 kcal, 75.0 g CHO, 15.5 g P, 6.4 g fat, 36 GL, 48 GI) iso-energetic BF
3) Visual search test, consisting of two levels, each including 21 stimuli (simple visuo-motor speed and complex visual processing)
Each test was preceded by practice stimuli with a feedback to allow the participants to re-familiarise themselves
No main effect of BF on Stroop test response times or accuracy. Non significant four-way (treatment*exercise*assessment time* test level) interaction. On the complex test level only, response times improved across the morning following the low-GI breakfast on both the exercise and resting trials, though the improvement was greatest on the exercise trial. However, response times only improved significantly on the resting trial following the high-GI breakfast (significant treatment*exercise*assessment time interaction effect) No main effect of BF on the Sternberg paradigm response times or accuracy. Non significant four-way (treatment*exercise*assessment time* test level) interaction. On the more complicated level of the Sternberg paradigm, response times improved across the morning following the low-GI breakfast (regardless of exercise or resting trial) and only on the exercise trial following the high-GI breakfast (significant treatment*exercise*assessment time interaction) No main effect of BF on the visual search test response times or accuracy; for both response times and accuracy, no significant interaction of BF with exercise, session time, and test level, or of BF with exercise and session time
Tested in 2 sessions at 30 and 120 min after BF
Stroop selective attention task (baseline and colour-interference levels) (executive function and selective attention);
High-GI (for a 50 kg participant: 422 kcal, 75.0 g CHO, 14.3 g P, 7.2 g fat, 54 GL, 72 GI);
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No information on preliminary test practice
Statistical analysis: four-way ANOVA (BF*exercise*session time *test level). Indeed, order effects did not affect performance on any of the cognitive function tests (breakfast*exercise*session time*order interactions, all p > 0.05). All cognitive data are represented as changes across the morning, given that there were no differences in response times or accuracy at time point 1 between trials on any of the cognitive function tests (all p > 0.05). No information on habitual BF
The high- and low-GI BF had similar intakes of EI, CHO, fat and P and differed only in terms of GI and GL
Comments
Results
Measurements of the outcome
Definition of outcome
Definition of breakfast
Table 1 Studies evaluating the effect of breakfast composition on cognitive/academic performance in different settings: updated evidence.
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5–11 ys
Mean ~ 9 ys
UK
(Y: BENEO Group, member of the Sudzucker Group, Germany, funded the study and supplied Palatinose and glucosesweetened foods
5
2 separate morning assessment 7 d apart
Design and intervention (School program: Y/N)
low-GL 337 kcal, 73.3 CHO, 9.2 P, 1.9 fat, GL 31.63
Definition of breakfast
Ability of sustained attention according to the paradigm of Shakow, with evaluation of incidence of lapses in attention (very long response times)
should be reported in a blank grid (immediate spatial memory). About 20 min after the initial memory test a verbally recall of the items was required (delayed memory) Speed of information processing according to the British Ability Scale Reaction times test measuring the time necessary to press a button after a light signal
Definition of outcome
Measurements of the outcome
The high and low GL BF had similar intakes of EI, CHO, fat and P, and differed only in terms of GI and GL Statistical analysis: four-way ANOVA (BF*time after BF*immediate/delayed recall*order of BF consumption)
All children attended a school BF club, habitual BF consisting of a bowl of cereal with milk, a slice of toast and orange/apple juice
No effect of BF on the number of lapses after 1 h or 3 hs
Comments
No main effect of BF after 1 h. If children had eaten the low-GL BF on the second d of testing they were able to process information faster No effect of BF after 1 h or 3 hs
Results
Abbreviations: BF=breakfast; BMI=body mass index; CHO=carbohydrate; CH=cholesterol; d=day; F=females; GI=glycemic index; GL=glycemic load; M=males; min=minutes; N=no; P=protein; RAG= rapidly available glucose; s=seconds; SAG= slowly available glucose; SES=socio-economic status; Y=yes; y=year.
Healthy subjects School setting in a socially deprived area
37% M 63% F
Study subjects
Reference (Sponsorship: Y/N)
Table 1 (continued)
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Verbal memory: immediate and delayed combined
Visuo-spatial delayed memory (delayed spatial memory)
Delayed memory Verbal delayed memory (delayed word recall)
Working memory
Verbal short-term memory with secondary motor taskb Visuo-spatial short-term memory (immediate spatial memory)
MEMORY Short-term and working memory Verbal short-term memory (short-term (primary) memory, immediate verbal memory, immediate word recall, (immediate) free word recall)a
Cognitive/academic modality
100 vs 133 kcal BF (Ingwersen et al., 2007)
424 vs 12 kcal BF (Cromer et al., 1990)
Better with high-SAG (low-GI) BF under certain conditions (Benton et al., 2003) Better with high-SAG (low-GI) BF under
Better with high-GI BF with remembering/ forgetting indices under certain conditions (Smith and Foster, 2008)b
Better with high GI-BF, but nonsignificant GI and GL interaction (Micha et al., 2011) Better with low-GI BF under certain conditions (Cooper et al., 2012)d Better with low-GI, with high-GL BF and with high-GL/low-GI BF (Micha et al., 2010) Better response times with low-GI BF under certain conditions (Cooper et al., 2015)
Better with low-GL BF under certain conditions (Young and Benton, 2015)
Different GL/GI BF (Micha et al., 2011)
Better with low-GI BF under certain conditions (Mahoney et al., 2005) Better with high-GI BF, but non significant GI and GL interaction (Micha et al., 2010) Better with low-GL BF under certain conditions (Young and Benton, 2015)
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Different GI BF and no BF (Mahoney et al., 2005)c
Different GL BF (Benton et al., 2007)
Different GL BF (Benton et al., 2007) Different GL/GI BF (Micha et al., 2011) Different GI BF with raw memory retention scores (Smith and Foster, 2008)b Different GL/GI BF (Micha et al., 2010) Different GL BF (Young and Benton, 2015)
On accuracy for different GI BF (Cooper et al., 2015)
Different GL/dairy products BF (Brindal et al., 2012)
Different GI BF (Nilsson et al., 2012)d
Different GI BF (Ingwersen et al., 2007)
Different GI BF and no BF (Mahoney et al., 2005)c
Different GI BF (Smith and Foster, 2008) different GL BF (Benton et al., 2007)
Different GI BF and no BF (Mahoney et al., 2005)
Different GL/dairy products BF (Brindal et al., 2012)
Different fat/CHO BF and no BF (Lloyd et al., 1996)
Nonsignificant effect
Better with low-GL BF under certain conditions (Benton et al., 2007)
Significant effect
Significant effect
Nonsignificant effect
Breakfast composition
Amount of energy intake at breakfast
Table 2 Summary of findings on the relationship between amount of energy intake at breakfast/breakfast composition and cognitive/academic performance, grouped by cognitive domain (row) and research question (column).
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INFORMATION PROCESSING AND
Attention switching
f
Selective attention – reaction time/completion time
Selective attention Selective attention – number of correct responses or accuracyf,g
Auditory sustained attention – rates of hits, misses and false alarms Auditory sustained attention – reaction times to hits and false alarms
Visual sustained attention – time on task, speed of sustained attention, reaction times to hits and false alarms
Sustained attention Visual sustained attention – number of correct responses, accuracy, number of lapses in attention, rates of hits, misses and false alarms
ATTENTION/CONCENTRATION
Speed of memory
Long-term (secondary) memory
Cognitive/academic modality
Table 2 (continued)
Better with 100 vs 133 kcal BF (Ingwersen et al., 2007)
Better with 100 vs 133 kcal BF (Ingwersen et al., 2007)e e
100 vs 133 kcal BF (Ingwersen et al., 2007)
424 vs 12 kcal BF (Cromer et al., 1990)
100 vs 133 kcal BF (Ingwersen et al., 2007)
Better with high-GL/high-GI BF (Micha et al., 2011) Better with high-GI as to the Stroop test (Cooper et al., 2012) Better with low-GI BF under certain conditions (Cooper et al., 2015)
Better with high-GI BF, but nonsignificant GI and GL interaction (Micha et al., 2011) Better with low-GI BF, under certain conditions (Nilsson et al., 2012) Better with low-GI BF, overall and under certain conditions (Cooper et al., 2012)
Better with low-GI BF under certain conditions (Mahoney et al., 2005)
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Different GL/dairy products BF (Brindal et al., 2012)
Different GL/GI BF (Micha et al., 2010)
Different GI BF as to the Flanker test (Cooper et al., 2012)
Different GI BF (Nilsson et al., 2012)
Different GI BF (Cooper et al., 2015)
Different GI BF and no BF (Mahoney et al., 2005)
Different GI BF and no BF (Mahoney et al., 2005) different GL BF (Young and Benton, 2015)
Different GI BF (Ingwersen et al., 2007)
Different RAG or SAG (GI) BF and no BF (Benton and Nabb, 2004) Different GL BF (Young and Benton, 2015)
Better with low-GL BF under certain conditions (Benton et al., 2007)
Better with low-GL BF under certain conditions (Benton et al., 2007)
Different GI BF and no BF (Mahoney et al., 2005)
Different GI BF and no BF (Mahoney et al., 2005)c Different GI BF (Ingwersen et al., 2007)e
Nonsignificant effect
Better with low-GI BF (Ingwersen et al., 2007)
Better with low-GI BF (Ingwersen et al., 2007)e
certain conditions (Benton and Nabb, 2004)
Significant effect
Significant effect
Nonsignificant effect
Breakfast composition
Amount of energy intake at breakfast
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8 Better with ≥20% vs < 20% EI BF (Lopez-Sobaler et al., 2003)j
424 vs 12 kcal BF (Cromer et al., 1990)
Better with low-GI BF, but nonsignificant GI and GL interaction (Micha et al., 2011)
Better with high-GL BF, but nonsignificant GI and GL interaction (Micha et al., 2010)
Abbreviations: BF=breakfast; CHO=carbohydrate; EI=energy intake; F=females; GI=glycemic index; GL=glycemic load; M=males; RAG= rapidly available glucose; SAG= slowly available glucose.
≥20% vs < 20% EI BF (Lopez-Sobaler et al., 2003)j
> 20% (536i and 434i kcal for M and F, respectively) vs < 10% (170i and 121ikcal for M and F, respectively) EI BF (Wyon et al., 1997) ≥20% vs < 20% EI BF (Lopez-Sobaler et al., 2003)j
MATH
VERBAL ABILITIES Command of language Fluency
424 vs 12 kcal (Cromer et al., 1990)
Better with > 20% vs < 10% EI BF among M only (536ivs 170i) (Wyon et al., 1997)
> 20% (536i and 434i kcal for M and F, respectively) vs < 10% (170i and 12i kcal for M and F, respectively) EI BF (Wyon et al., 1997)
LEARNINGA
CREATIVITY
Inductive
Logical
REASONING Grammatical
IMPULSIVITY
Psychomotor skill (motor speed)
Inspection time
Different GL/GI BF (Micha et al., 2010)
Different GL/dairy products BF (Brindal et al., 2012)
Different GL/GI BF (Micha et al., 2011)
Different GL/dairy products BF (Brindal et al., 2012) Different GL/dairy products BF (Brindal et al., 2012) Different fat/CHO BF and no BF (Lloyd et al., 1996)
Perceptual speed
Different GL/dairy products BF (Brindal et al., 2012)
Different fat/CHO BF and no BF (Lloyd et al., 1996) Different RAG or SAG (GI) BF and no BF (Benton and Nabb, 2004) Different GL BF (Young and Benton, 2015)
Nonsignificant effect
Different fat/CHO BF and no BF (Lloyd et al., 1996) On both response times and accuracy for different GI BF (Cooper et al., 2015)
Better with high-GI BF, but nonsignificant GI and GL interaction (Micha et al., 2011) Better with low-GL BF only under certain conditions (Young and Benton, 2015) Better with low-GI BF and with high-GL BF, but nonsignificant GI and GL interaction (Micha et al., 2010)
Significant effect
Significant effect
Nonsignificant effect
Breakfast composition
Amount of energy intake at breakfast
Visual information processing
Speed of information processing, speed of processingf
PSYCHOMOTOR SPEED Simple and choice reaction timesh
Cognitive/academic modality
Table 2 (continued)
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amount of energy intake at breakfast/breakfast composition and cognitive/academic performance, grouped by broad cognitive domain (row) and research question (column). Specific subdomains of interest are reported in separate rows, including also for reference the original terms provided in the corresponding papers. Significant and non significant results are reported in separate columns. Results from the previous systematic review were added to provide a complete picture of the relations between energy intake at breakfast/breakfast composition and cognitive/academic performance. Results from the current review are indicated in bold and italics to highlight the new evidence collected. 4. Discussion The current review updates a previous systematic review of ours (Edefonti et al., 2014) published in 2014 and based on 15 papers. Unfortunately, after 2 years and a half, our search provided 2 new pertinent papers only. Both of them were published in 2015. It is, therefore, evident that our current conclusions will be mostly in line with the previous ones from the 2014 review (Edefonti et al., 2014). Seventeen papers are still not a reasonable body of evidence to base any conclusions. In addition, heterogeneity and inconsistency in research designs, interventions, cognitive tests, and statistical analyses still make these reviews a preliminary attempt to understand which information the literature provides on 2 important, but definitely difficult, themes. However, this update allows us to track some general trends of the literature on breakfast consumption and cognitive/academic performance that are worth of note. The predominance of studies on children and adolescents, as compared to adults, is confirmed by our updated systematic review. Eleven out of 15 studies from the previous review concerned children and adolescents (Edefonti et al., 2014). The new studies included in the update are based on children (Young and Benton, 2015) and adolescents (Cooper et al., 2015), too. These categories may be particularly sensitive to the nutritional effects of breakfast on brain activity and associated cognitive/academic outcomes. Beyond other mechanisms (such as hunger alleviation (Alaimo et al., 2001; Kleinman et al., 1998) and changes in neurotransmitter concentrations (Pollitt and Mathews, 1998)), children and adolescents have a higher metabolic rate of glucose utilization, a higher average cerebral blood flow and oxygen utilization, than do adults (Chiron et al., 1992; Kennedy and Sokoloff, 1957). Their higher sleep demand implies a longer overnight fasting, which can deplete glycogen stores overnight (Thorleifsdottir et al., 2002). Thus, breakfast consumption provides an important supply of energy and nutrients to modulate the short-term metabolic responses to fasting conditions. Further, it may provide long-term effects, including an improved nutrient balance and distribution, with important fallouts on cognitive processes, too (Pollitt and Mathews, 1998). Finally, breakfast may affect cognitive performance indirectly, through improved subjective feelings of mood, alertness, and motivation (Cooper et al., 2011). In addition, the new studies were still conducted in the United Kingdom by 2 independent groups of researchers that have contributed with one (Cooper et al., 2012) or more papers (Benton et al., 2007, 2003; Benton and Nabb, 2004) to the previous review (Edefonti et al., 2014). This confirms that researchers from the United Kingdom, with 10 out of 17 papers in total from the two reviews, have been by far among the most active groups in the world to deal with the themes of the current review. However, this could limit generalizability of the findings, also in consideration of the substantial lack of evidence from developing countries. Concerning the type of breakfast, both the included papers added evidence on the effect of breakfast composition and cognitive/academic performance, testing the effect of two iso-energetic breakfast options differing in GI or GL (Cooper et al., 2015; Young and Benton, 2015). More evidence is, therefore, accumulating on breakfast composition
b
a
The Rey auditory-verbal learning test assessed both verbal learning and immediate verbal memory. Therefore, we reported its results in the corresponding 2 rows of the table, as indicated in Rampersaud et al. (Rampersaud et al., 2005). In Smith et al. (Smith and Foster, 2008), verbal memory was assessed with a simultaneous secondary motor task, so under conditions of divided attention. Therefore, we presented its results in a separate row in the verbal memory section. However, the paper did not provide the corresponding results for the motor task. Moreover, the tasks were expressed in terms of both raw memory retention scores and derived remembering/forgetting indices, calculated to control for individual differences in the total items recalled in the previous recall phase. Although the paper did not provide any detail, the statistical analyses for the 2 outcome measures were probably different, with the latter analysis including one time or delay effect allowing for comparisons between short and long delay results. Therefore, we separated the corresponding results on verbal memory in the short-term (immediate and short-delay) and delayed sections. As results from retention scores and remembering/forgetting indices were inconsistent at the long delay, we summarized them in 2 separate cells. c In Mahoney et al. (Mahoney et al., 2005), the so-called spatial memory and visual perception domains belonged both to the visuo-spatial memory category. Both of them were assessed at the level of short- and long-term memory and then contributed to both immediate/short-term and long-term memory categories. Results for short-term memory were consistent across these domains, and therefore we included them in the same cell. Results on long-term memory for visual perception and spatial learning were also consistent with those of a verbal memory test. Therefore, we included the information on long-term memory from the 3 tests in a single cell. Visual perception was also assessed as a delayed recall and then contributed to the visuo-spatial delayed memory category too. d The tasks were expressed in terms of both response/reaction times and accuracy (proportion/number of correct responses), but results were consistent and therefore we summarized them in 1 cell only. e The paper by Ingwersen et al. (Ingwersen et al., 2007) assessed cognitive performance referring to the selection of tests from the Cognitive Drug Research computerized assessment system and adopted its cognitive assessment factor scores. These are combined scores obtained from individual measures derived from simpler tests. Whenever they did not seem to us to be comparable to the simpler test measures provided by the other papers, we put them in a separate row. f In Micha et al. (Micha et al., 2011), number search task assessed both speed of information processing and selective attention, and therefore we reported its results in the corresponding 2 rows of the table. In Brindal et al. (Brindal et al., 2012), speed of processing was a composite measure based on the responses to different reaction time tasks. g In Cooper et al. (Cooper et al., 2012), selective attention was assessed using both the Stroop and the Flanker tests. When results were consistent, we reported them in 1 cell; otherwise, we filled in 2 cells, and indicated from which test result came from. h Although reaction time is commonly used as a dependent variable in many tests of cognitive function, some studies include direct measures of reaction time where reaction time is not a proxy measure for a more complex function. i Mean intakes for each treatment option and sex. j The paper by López-Sobaler et al. (Lopez-Sobaler et al., 2003) considered both an overall score measuring verbal, reasoning, and calculation abilities and its single domains. Here, we presented results for the single domains only.
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accurate control for confounding factors. Finally, in studies assessing the effect of energy intake at breakfast, we recommend to compare breakfast options with a similar composition; similarly, in studies assessing the effect of breakfast composition, we recommend to compare iso-energetic breakfast interventions differing in a single nutrient component, when possible, to provide more effective messages of public health.
and, in particular, on breakfast varying in GI, GL, or both, as already mentioned in our previous review (Edefonti et al., 2014) and in another one on any eating occasions (Philippou and Constantinou, 2014). However, we are still far from the possibility to draw firm conclusions in regard to the impact of breakfast type on cognition in healthy subjects. Although the quality of much of these works – particularly studies conducted in recent years – is good, methodological differences across studies appear to lead to inconsistency in findings. In particular, heterogeneity and limited consistency between studies dominate the definition of the cognitive performance measures under comparison. In the case of the current review, the same 3 domains were under investigation in both studies. However, there was no overlapping between the specific subdomains that was tested in the 2 studies (Cooper et al., 2015; Young and Benton, 2015). This materially prevents any possibility of a fair comparison. However, to integrate the new findings with the previous ones, we have updated Table 3 from the previous review – summarizing the findings on the relationship between breakfast characteristics and cognitive performance, according to cognitive domain and research question (Edefonti et al., 2014) – and inserted it in the current manuscript as Table 2. The accurate reclassification of the cognitive and academic measures employed should help the reader to compare results from the different studies. Although in the past most experiments have examined cognitive performance at only one time-point after breakfast (Kanarek, 1997), information is now generally available on the time-course of the effects of breakfast on behavioral measures. This new trend is confirmed in the present review, where both the new included studies (Cooper et al., 2015; Young and Benton, 2015) allowed for testing subjects more than once after breakfast on the same day. This also argues in favor of the highest quality of more recent studies. However, the different time intervals between breakfast and testing sessions, i.e. 30 and 120 min (Cooper et al., 2015) vs 60 and 180 min (Young and Benton, 2015) from breakfast, even for the same domains under investigations, still prevents from a fair comparison between studies. This may reflect a difference in the specific research questions of the papers (for instance, Nilsson and coauthors considered the course of glycaemia with particular attention to the later postprandial period) and/or a still limited knowledge of the mechanisms linking breakfast to cognitive performance (Brindal et al., 2012; le Coutre and Schmitt, 2008; Nilsson et al., 2012). In conclusion, after two extra years of accumulating evidence, there is still insufficient quantity and consistency among studies to draw firm conclusions on the relationship between amount of energy intake at breakfast and breakfast composition and cognitive/academic performance. The hypothesis of a better and more sustained mental performance with breakfast equivalent to or > than 20% daily energy intake still needs substantiation, as we were not able to identify extra evidence on this issue. In addition, the identified papers still support the hypothesis that a lower postprandial glycemic response is beneficial to cognitive performance. However, the results from the 2 reviews did not show large breakfast-induced advantages for cognitive performance. The evidence likely points to a subtle relationship, demonstrated only under specific conditions (i.e. on some test levels or on some testing sessions only) or in specific subgroups of the sample (i.e. in males or younger subjects only). It also remains unclear whether this effect is specifically due to GI or GL solely, or to both, or to other effects unrelated to glycemic response. Finally, even after controlling one for the other, it remains unclear whether GI- or GL-based breakfast meals selectively facilitate different cognitive domains. Future research will benefit from well-matched study conditions and selected populations of interest, including the least represented adolescent category. In addition, tests of cognitive performance should be chosen among those that proved to be sensitive to nutritional manipulations; they should be standardized as far as possible and scheduled at standardized time points. Studies should provide an
Funding sources The work was supported by the Italian Ministry of Health (EUROMED-UpM 2014/2015) and the Italian Foundation for Research on Cancer (FIRC). The funding agencies had no role in the conduction of the systematic review. Acknowledgements VE wrote the manuscript. VE and FB collected the existing literature and selected the included papers. FB prepared Table 1 and added the new information from the included studies in Table 2, which was previously published as Table 3 by Edefonti et al. (2014). VE revised Tables 1 and 2. MF provided useful suggestions to summarize details on design and statistical analysis of the included studies. All authors read and approved the final version of the manuscript. The authors declare that they have no conflict of interest. Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at doi:10.1016/j.jad.2016.12.028. References Adolphus, K., Lawton, C.L., Champ, C.L., Dye, L., 2016. The effects of breakfast and breakfast composition on cognition in children and adolescents: a systematic review. Adv. Nutr. 7, 590S–612S. Alaimo, K., Olson, C.M., Frongillo, E.A., Jr., 2001. Food insufficiency and American school-aged children's cognitive, academic, and psychosocial development. Pediatrics 108, 44–53. Benton, D., Nabb, S., 2004. Breakfasts that release glucose at different speeds interact with previous alcohol intake to influence cognition and mood before and after lunch. Behav. Neurosci. 118, 936–943. Benton, D., Maconie, A., Williams, C., 2007. The influence of the glycaemic load of breakfast on the behaviour of children in school. Physiol. Behav. 92, 717–724. Benton, D., Ruffin, M.P., Lassel, T., Nabb, S., Messaoudi, M., Vinoy, S., Desor, D., Lang, V., 2003. The delivery rate of dietary carbohydrates affects cognitive performance in both rats and humans. Psychopharmacology 166, 86–90. Brindal, E., Baird, D., Danthiir, V., Wilson, C., Bowen, J., Slater, A., Noakes, M., 2012. Ingesting breakfast meals of different glycaemic load does not alter cognition and satiety in children. Eur. J. Clin. Nutr. 66, 1166–1171. Chiron, C., Raynaud, C., Maziere, B., Zilbovicius, M., Laflamme, L., Masure, M.C., Dulac, O., Bourguignon, M., Syrota, A., 1992. Changes in regional cerebral blood flow during brain maturation in children and adolescents. J. Nucl. Med. 33, 696–703. Cooper, S.B., Bandelow, S., Nevill, M.E., 2011. Breakfast consumption and cognitive function in adolescent schoolchildren. Physiol. Behav. 103, 431–439. Cooper, S.B., Bandelow, S., Nute, M.L., Morris, J.G., Nevill, M.E., 2012. Breakfast glycaemic index and cognitive function in adolescent school children. Br. J. Nutr. 107, 1823–1832. Cooper, S.B., Bandelow, S., Nute, M.L., Morris, J.G., Nevill, M.E., 2015. Breakfast glycaemic index and exercise: combined effects on adolescents' cognition. Physiol. Behav. 139, 104–111. Cromer, B.A., Tarnowski, K.J., Stein, A.M., Harton, P., Thornton, D.J., 1990. The school breakfast program and cognition in adolescents. J. Dev. Behav. Pediatr. 11, 295–300. Dye, L., Lluch, A., Blundell, J.E., 2000. Macronutrients and mental performance. Nutrition 16, 1021–1034. Edefonti, V., Rosato, V., Parpinel, M., Nebbia, G., Fiorica, L., Fossali, E., Ferraroni, M., Decarli, A., Agostoni, C., 2014. The effect of breakfast composition and energy contribution on cognitive and academic performance: a systematic review. Am. J. Clin. Nutr. 100, 626–656. Ells, L.J., Hillier, F.C., Shucksmith, J., Crawley, H., Harbige, L., Shield, J., Wiggins, A., Summerbell, C.D., 2008. A systematic review of the effect of dietary exposure that could be achieved through normal dietary intake on learning and performance of school-aged children of relevance to UK schools. Br. J. Nutr. 100, 927–936. Galioto, R., Spitznagel, M.B., 2016. The effects of breakfast and breakfast composition on
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breakfast predict cognitive function and mood in school children: a randomised controlled trial. Br. J. Nutr. 106, 1552–1561. Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., Group, P., 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 339, b2535. Nilsson, A., Radeborg, K., Bjorck, I., 2012. Effects on cognitive performance of modulating the postprandial blood glucose profile at breakfast. Eur. J. Clin. Nutr. 66, 1039–1043. Philippou, E., Constantinou, M., 2014. The influence of glycemic index on cognitive functioning: a systematic review of the evidence. Adv. Nutr. 5, 119–130. Pollitt, E., Mathews, R., 1998. Breakfast and cognition: an integrative summary. Am. J. Clin. Nutr. 67, 804S–813S. Rampersaud, G.C., Pereira, M.A., Girard, B.L., Adams, J., Metzl, J.D., 2005. Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. J. Am. Diet. Assoc. 105, 743–760, (quiz 761-742). Smith, M.A., Foster, J.K., 2008. The impact of a high versus a low glycaemic index breakfast cereal meal on verbal episodic memory in healthy adolescents. Nutr. Neurosci. 11, 219–227. Thorleifsdottir, B., Bjornsson, J.K., Benediktsdottir, B., Gislason, T., Kristbjarnarson, H., 2002. Sleep and sleep habits from childhood to young adulthood over a 10-year period. J. Psychosom. Res. 53, 529–537. Wyon, D.P., Abrahamsson, L., Jartelius, M., Fletcher, R.J., 1997. An experimental study of the effects of energy intake at breakfast on the test performance of 10-year-old children in school. Int J. Food Sci. Nutr. 48, 5–12. Young, H., Benton, D., 2015. The effect of using isomaltulose (Palatinose) to modulate the glycaemic properties of breakfast on the cognitive performance of children. Eur. J. Nutr. 54, 1013–1020.
cognition in adults. Adv. Nutr. 7, 576S–589S. Ingwersen, J., Defeyter, M.A., Kennedy, D.O., Wesnes, K.A., Scholey, A.B., 2007. A low glycaemic index breakfast cereal preferentially prevents children's cognitive performance from declining throughout the morning. Appetite 49, 240–244. Kanarek, R., 1997. Psychological effects of snacks and altered meal frequency. Br. J. Nutr. 77 (Suppl 1), 118–120. Kennedy, C., Sokoloff, L., 1957. An adaptation of the nitrous oxide method to the study of the cerebral circulation in children; normal values for cerebral blood flow and cerebral metabolic rate in childhood. J. Clin. Investig. 36, 1130–1137. Kleinman, R.E., Murphy, J.M., Little, M., Pagano, M., Wehler, C.A., Regal, K., Jellinek, M.S., 1998. Hunger in children in the United States: potential behavioral and emotional correlates. Pediatrics 101, E3. le Coutre, J., Schmitt, J.A., 2008. Food ingredients and cognitive performance. Curr. Opin. Clin. Nutr. Metab. Care 11, 706–710. Lloyd, H.M., Rogers, P.J., Hedderley, D.I., Walker, A.F., 1996. Acute effects on mood and cognitive performance of breakfasts differing in fat and carbohydrate content. Appetite 27, 151–164. Lopez-Sobaler, A.M., Ortega, R.M., Quintas, M.E., Navia, B., Requejo, A.M., 2003. Relationship between habitual breakfast and intellectual performance (logical reasoning) in well-nourished schoolchildren of Madrid (Spain). Eur. J. Clin. Nutr. 57 (Suppl 1), S49–S53. Mahoney, C.R., Taylor, H.A., Kanarek, R.B., Samuel, P., 2005. Effect of breakfast composition on cognitive processes in elementary school children. Physiol. Behav. 85, 635–645. Micha, R., Rogers, P.J., Nelson, M., 2010. The glycaemic potency of breakfast and cognitive function in school children. Eur. J. Clin. Nutr. 64, 948–957. Micha, R., Rogers, P.J., Nelson, M., 2011. Glycaemic index and glycaemic load of
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Review article
Breakfast and behavior in morning tasks: Facts or fads? ⁎
Valeria Edefonti , Francesca Bravi, Monica Ferraroni Branch of Medical Statistics, Biometry, and Epidemiology “G. A. Maccacaro”, Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
A R T I C L E I N F O
A BS T RAC T
Keywords: Breakfast Energy intake at breakfast Breakfast composition Cognitive performance Academic performance
Background: Most of the studies investigating the effects of breakfast on cognitive performance have compared performance in subjects who have or have not consumed this meal. However, characteristics of breakfast itself may influence mental abilities. Moreover, as far as the positive effects of having breakfast is more evident, research may focus on the specific characteristics of an adequate breakfast. Methods: To update an existing systematic review, published at the beginning of 2014, on the role of nutrient composition and/or energy intake at breakfast on the accomplishment of school-related tasks and cognition, we carried out a systematic review of the literature through PUBMED database. Results: From the literature search, we identified 39 papers, of which 2 were eligible according to our inclusion criteria. Both the selected papers concerned randomized crossover studies on the acute effect of breakfast carried out in a school setting in the United Kingdom. Both studies compared 2 iso-energetic breakfasts with a similar macronutrient composition; however, the alternative breakfasts were meant to differ in terms of glycemic index or glycemic load. The effects of breakfast composition were investigated on memory, attention, and information processing in both studies. However, different tests and subdomains were considered. Limitations: Studies on these issues are still inconsistent and quantitatively insufficient to draw firm conclusions. Conclusions: While the hypothesis of a better mental performance with breakfast > 20% daily energy intake still needs confirmation, there does appear to be extra evidence that a lower postprandial glycemic response is beneficial to mental performance.
1. Introduction More than two years have passed since the publication of our systematic review collecting evidence on the role of the amount of energy intake at breakfast and breakfast composition on various measures of cognitive/academic performance (Edefonti et al., 2014). Since then, there has been a growing interest on the several possible dimensions of the relation between breakfast and cognition. This is, in particular, witnessed by the publication of two very recent systematic reviews in the Supplement of the same number of Advances in Nutrition (Adolphus et al., 2016; Galioto and Spitznagel, 2016). Both the reviews are still dedicated in part to consolidate the available results on the acute effects of breakfast compared with the ‘no breakfast’ option. In accordance with previous literature, their main conclusions are, indeed, that breakfast has generally a short-term positive, domain-specific effect on cognitive function – measured within a few hours post ingestion – in healthy children/adolescents
(Adolphus et al., 2016) and adults (Galioto and Spitznagel, 2016). In detail, there is general agreement that memory domain benefits from having breakfast - as compared to fasting – whereas results on attention and executive functions are apparently different in children/adolescents and adults (Adolphus et al., 2016; Galioto and Spitznagel, 2016). Moreover, both the reviews have recognized the attention dedicated in the literature to the relation between breakfast composition and cognitive/academic performance, as initially suggested by Dye et al. (Dye et al., 2000) for any eating occasion and, more recently, by our review on breakfast only (Edefonti et al., 2014). However, they did not deal with the (possibly independent) role of energy intake from breakfast in short-term mental processes. In addition, the two mentioned reviews (Adolphus et al., 2016; Galioto and Spitznagel, 2016) and ours (Edefonti et al., 2014) differ with respect to several inclusion/ exclusion criteria, including the type of breakfast manipulation (acute/ chronic, experimental or not), the inclusion of laboratory-developed
Abbreviations: BF, breakfast; CHO, carbohydrate; CH=, cholesterol; d=, day; EI=, energy intake; F=, females; GI, glycemic index; GL=, glycemic load; h, hour; min, minutes; M, males; N=, no; P, protein; RAG=, rapidly available glucose; s=, seconds; SAG, slowly available glucose; Y=, yes; y, year ⁎ Correspondence to: Dipartimento di Scienze Cliniche e di Comunità, Università degli Studi di Milano, Via G. Venezian 1, 20133 Milano, Italy. E-mail address: [email protected] (V. Edefonti). http://dx.doi.org/10.1016/j.jad.2016.12.028 Received 30 June 2016; Received in revised form 29 November 2016; Accepted 17 December 2016 0165-0327/ © 2017 Elsevier B.V. All rights reserved.
Please cite this article as: Edefonti, V., Journal of Affective Disorders (2017), http://dx.doi.org/10.1016/j.jad.2016.12.028
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when the separate effect of different breakfast options during the morning was clearly reported.
macronutrient manipulations, the type of comparison (breakfast vs fasting, energy at breakfast, breakfast composition), the duration of the overnight fasting period allowed, and the target subpopulation of the analysis. For this reason, the overlapping between the selected studies is minimal. Finally, the indicated databases were searched until July 2014 (Adolphus et al., 2016) and May 2015 (Galioto and Spitznagel, 2016). The aim of the present paper is to provide an updated systematic review of the role of nutrient composition and/or energy intake at breakfast on objective cognitive/academic performance outcomes from any kind of studies in children, adolescents, and adults. Although it is still unclear whether breakfast is a determinant or a short-term indicator of cognitive performance, these issues may have important consequences in the definition of public health guidelines and in the assessment of the nutritional, educational and economic value of school breakfast programs (Ells et al., 2008).
2.2.3. Outcome measures Studies that assessed any outcome of objectively measured of cognitive, academic (school grades and standardized achievement tests) and school (enrollment, attendance, achievement, in-class behavior and behavior at school, and school drop-out) performance were considered. Acute (=performance assessed within 12 h of breakfast consumption) and chronic effects of breakfast manipulations (typically, through school breakfast programs) were included. When reported, we included the name of the adopted cognitive test, as well as the corresponding psychological construct assessed. Otherwise, we simply reported the specific neurocognitive construct. 2.2.4. Exposure measures
2. Methods
2.2.4.1. Energy intake at breakfast. Studies providing quantitative estimates of total energy intake for different breakfast options, including either absolute intakes or percentages of daily energy intake provided by breakfast, were included. Studies based on standardized breakfast options with a fixed quantitative estimate of energy intake were excluded. Information on energy intake at breakfast was consistently expressed in kilocalories throughout the paper.
2.1. Literature search We updated our previously published systematic review (Edefonti et al., 2014) with a more recent systematic search through MEDLINE via PubMed (http://www.ncbi.nlm.nih.gov/pubmed/) to identify all the articles on the relationship between cognitive/academic/school performance and breakfast composition/energy intake published as full texts in English from January 1st, 2013, up to May 31st, 2016, based on the following original string (breakfast OR “breakfast composition” OR “daily meal distribution”) & ("energy intake" OR "energy contribution" OR "energy expenditure" OR quality OR energy OR skipping OR “glycemic index”) & ("intellectual performance" OR "neuro-performance" OR "mental performance" OR "cognitive performance" OR “academic performance” OR “school performance” OR performance)”, following the guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) group (Moher et al., 2009). Two authors (F.B. and V.E.) independently reviewed the papers and carried out the selection. The reference lists of the selected articles and of other systematic reviews focusing on similar topics were also examined to identify other relevant papers, if any. Discrepancies in article selection were resolved by involving a third author (M.F.).
2.2.4.2. Breakfast composition. Studies providing quantitative estimates of the macronutrient composition of different breakfast options were considered. This included breakfast meals standardized for energy supply. When the authors stated in the papers that the considered breakfast options were iso-energetic or similar in energy intake, we reported this information in the tables. When the difference in energy content between treatments was higher than 10% and it was possible to distinguish the energy intake associated to each effect in the statistical models, we included the corresponding article in the analysis concerning energy intake at breakfast, too. We did not include studies assessing the relationship between cognition and the interaction between macronutrient composition of the breakfast and glucose tolerance, as there was no possibility to assess the separate effect of breakfast composition.
2.2. Inclusion and exclusion criteria 2.2.5. Association between exposure and outcome measures Studies considering any kind of relationship between cognition/ academic performance and energy intake at breakfast or breakfast composition were included. This included results obtained from different statistical approaches, including simpler tests and confidence intervals, correlation analysis, multiple regression models, and multivariate repeated measures ANOVA. Finally, we decided not to exclude studies on the basis of their quality, because of their limited number and of the high variation in the adequacy of descriptions provided.
Briefly, papers were included or excluded according to the following criteria. 2.2.1. Participants Studies involving children, adolescents or adults of either sex were included. We did not include studies on subjects with acquired metabolic disorders (such as hyperlipidemia, or type-2 diabetes). 2.2.2. Breakfast definition Breakfast was defined according to the descriptions provided in the papers. Although these varied, breakfast was generally considered as the first food/meal of the day, though some interventions did not provide explicit control for previous food consumption. Studies comparing different breakfast types were included. Studies comparing breakfast and “no breakfast” options were not included, unless when different breakfast options, with specified energy or composition, were compared. Studies were included no matter of the content of the meal. However, we excluded those studies where breakfast options differed by the presence/absence of coffee only. In addition, studies investigating the role of glucose-based or emulsion-based manipulations (including formula milk, foam like vanilla creams, gelatins resembling milkshakes in consistency, and spoonable creams) were not included. Studies considering intakes at other mealtimes were excluded, unless
2.3. Data extraction Information extracted included: 1. General characteristics of the studies (first author and year of publication, country, sponsorship, number/age of the participants, distribution by gender, inclusion/ exclusion criteria, and study setting); 2. Design and characteristics of the intervention, and presence of any school program in support of it (type of design, randomization, counterbalancing and crossover details, when available, number of days of observation and schedule, information on the dinner the night before and on explicitly stated overnight fast, schedule of the breakfast); 3. Breakfast definition: list of the breakfast options and corresponding details on absolute/relative values 2
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included subjects. One study included children 5–11 years old) (Young and Benton, 2015) and the other adolescents 11–13 years old) (Cooper et al., 2015). The size of the study samples was limited and the studies were of short duration ( < 1 month). One study was based on a mixed research design investigating the combined effect of 2 breakfast options and exercise/resting (Cooper et al., 2015). In both studies, there was a comparison between 2 iso-energetic breakfasts options with a different macro-nutrient composition. In detail, in one study, the alternative breakfast options are indicated as differing in terms of glycemic index (GI) (Cooper et al., 2015), while, in the other, they are expected to differ in their glycemic load (GL) (Young and Benton, 2015). The 2 breakfast options showed similar intakes of carbohydrate, fat, and protein, as well as energy, in both the studies (Cooper et al., 2015; Young and Benton, 2015). One of the two studies (Young and Benton, 2015) recorded the weight of uneaten food to estimate the actual energy intake and nutrition composition of the meal. Both the studies investigated the following cognitive domains: memory, attention, and information processing. However, the corresponding tests were different across studies and assessed the effect of breakfast on different subdomains. The schedule of test sessions after breakfast was different too. Memory ability was significantly sensitive, to various degrees, to breakfast compositions providing different glycemic responses in both studies (Cooper et al., 2015; Young and Benton, 2015). Although the nature of the meals did not influence any measure of cognition after 1 h, after 3 hs, verbal short-term memory (mean number of words recalled) improved after the low-GL breakfast; it also declined over the morning after eating the high-GL (but not the low-GL) breakfast (Young and Benton, 2015). In addition, immediate spatial memory was better in those children who had consumed the low-GL breakfast, as compared to the high-GL one, but only on the second day of testing (Young and Benton, 2015). As to working memory, although in the absence of a main effect of breakfast composition on both accuracy and response times to the Sternberg paradigm, response times were still improved across the morning following a low-GI breakfast, on the more complex test level and regardless of the exercise/resting trial (Cooper et al., 2015). However, following a high-GI breakfast, response times improved across the morning on the exercise trial only (Cooper et al., 2015). Finally, there was no differential effect of breakfast options differing in GL on verbal delayed memory (Young and Benton, 2015). Attention was also potentially influenced by different breakfast compositions, but results on this domain were inconsistent. In detail, the ability to sustain attention (number of lapses in the Shakow test) was not influenced by breakfast compositions differing in GL at the 3and 12- second delay in either days of testing (Young and Benton, 2015). In addition, in the Stroop test investigating selective attention in terms of both accuracy and response times, neither response times nor accuracy were significantly affected by the type of breakfast consumed. However, on the complex test level only, response times improved across the morning following the low-GI breakfast, no matter of the exercise or resting trials, although the greatest improvement was seen on the exercise trial (Cooper et al., 2015). Concerning speed of information processing and visual information processing, on the visual search test, no significant effects of the highvs low-GI breakfast were detected for either response times or accuracy (Cooper et al., 2015). Similarly, there was no significant difference between breakfast options differing in GL content when reaction times were considered (Young and Benton, 2015). However, even in the absence of a differential effect in speed on the first day, the consumption of the low-GL breakfast, rather than the high-GL one, was associated with a faster performance on the second day of testing (Young and Benton, 2015). Finally, one study (Young and Benton, 2015) was sponsored by industry, whereas the other was not. Table 2 shows a summary of findings on the relationship between
of energy intake and/or on the macronutrient composition of the different options; 4. Outcome definition according to the different standardized tests used and information on time and procedure performance was assessed with respect to breakfast (in the standardized time unit of minutes); 5. Main results on the relationship between breakfast characteristics and cognitive/academic performance (when multiple statistical models were provided in the original paper, we reported estimates adjusted for the largest number of confounding variables). 3. Results From the literature search through PUBMED database, we identified 39 full-text papers published between January 1st, 2013, and May 31st, 2016, all of which satisfied the filters on Humans and English language. Their full-texts were retrieved for detailed evaluation. After the exclusion of 2 review papers, 35 original research ones were also excluded because they met the exclusion criteria indicated previously. In detail, the most frequent reasons for exclusion were: absence of information about cognitive/academic performance and/or breakfast; lack of information on breakfast energy intake or macronutrient composition; a fixed estimate of energy intake; several breakfast options including no breakfast and 2 or more different breakfast meals, but with no available comparisons between alternative breakfast meals; other meals provided together with breakfast (e.g., mid-morning snack, evening meal, lunch), with no possibility to assess the individual contribution of energy/composition of each meal. No additional papers were identified from manual searches on reference lists of selected original and review papers. Therefore, 2 papers, providing information on 2 different studies, were included in our updated systematic review (Cooper et al., 2015; Young and Benton, 2015) (Fig. 1). Both the papers were published in 2015 by groups of researchers that contributed with original papers to our previous review (Edefonti et al., 2014) and concerned randomized crossover studies carried out in a school setting in the United Kingdom. The main characteristics of the 2 studies included in the previous review are shown in Table 1. The selected studies examined healthy, mixed sex populations (Cooper et al., 2015; Young and Benton, 2015). In one study (Young and Benton, 2015), the included subjects came from amongst the most socially deprived areas of Wales, as to the Welsh Index of Multiple Deprivation; in the other study (Cooper et al., 2015), there was no mention of the socio-economic conditions of the 39 records identified through searches of PubMed/MEDLINE database and screened
0 records excluded (no on Humans or no English language)
39 full-text articles assessed for eligibility
35 records excluded (title and/or abstract not relevant or not satisfying the inclusion criteria)
2 reviews excluded
0 additional articles identified from manual searches on reference lists of selected original and review papers 2 studies included in the updated systematic review Fig. 1. Flowchart of the study selection process for the systematic review.
3
4
(Young and Benton, 2015)
BF time not provided
Healthy subjects School setting No.=75
(N) Random crossover
Overnight fast
48% M 52% F
3 separate morning assessments 7-d apart (familiarisation session +3 testing sessions)
Self-selected similar dinner on each occasion
11–13 ys
UK
Balanced, randomized, crossover
Design and intervention (School program: Y/N)
Mean ~12.5 ys
No.=51 (42)
(Cooper et al., 2015)
(N)
Study subjects
Reference (Sponsorship: Y/N)
High-GL 337 kcal, 73.3 CHO, 9.2 P, 1.9 fat, GL 59.85
Recall of Objects test of the British Ability Scale: the test consisted in visualization of a card with 20 objects, with subsequent recall of the items (immediate verbal memory); then the position of the items
Tested in 2 sessions at 60 and 180 min after BF
No main effects of BF after 1 h on all memory domains. After 3 hs children's immediate verbal memory improved after the low-GL BF, while declined over the morning after eating high-GL BF. If children had eaten the low-GL BF on the second d of testing they had a better spatial memory later in the morning
2) Sternberg paradigm for working memory (3 levels with different memory loads);
low-GI (for a 50 kg participant: 420 kcal, 75.0 g CHO, 15.5 g P, 6.4 g fat, 36 GL, 48 GI) iso-energetic BF
3) Visual search test, consisting of two levels, each including 21 stimuli (simple visuo-motor speed and complex visual processing)
Each test was preceded by practice stimuli with a feedback to allow the participants to re-familiarise themselves
No main effect of BF on Stroop test response times or accuracy. Non significant four-way (treatment*exercise*assessment time* test level) interaction. On the complex test level only, response times improved across the morning following the low-GI breakfast on both the exercise and resting trials, though the improvement was greatest on the exercise trial. However, response times only improved significantly on the resting trial following the high-GI breakfast (significant treatment*exercise*assessment time interaction effect) No main effect of BF on the Sternberg paradigm response times or accuracy. Non significant four-way (treatment*exercise*assessment time* test level) interaction. On the more complicated level of the Sternberg paradigm, response times improved across the morning following the low-GI breakfast (regardless of exercise or resting trial) and only on the exercise trial following the high-GI breakfast (significant treatment*exercise*assessment time interaction) No main effect of BF on the visual search test response times or accuracy; for both response times and accuracy, no significant interaction of BF with exercise, session time, and test level, or of BF with exercise and session time
Tested in 2 sessions at 30 and 120 min after BF
Stroop selective attention task (baseline and colour-interference levels) (executive function and selective attention);
High-GI (for a 50 kg participant: 422 kcal, 75.0 g CHO, 14.3 g P, 7.2 g fat, 54 GL, 72 GI);
(continued on next page)
No information on preliminary test practice
Statistical analysis: four-way ANOVA (BF*exercise*session time *test level). Indeed, order effects did not affect performance on any of the cognitive function tests (breakfast*exercise*session time*order interactions, all p > 0.05). All cognitive data are represented as changes across the morning, given that there were no differences in response times or accuracy at time point 1 between trials on any of the cognitive function tests (all p > 0.05). No information on habitual BF
The high- and low-GI BF had similar intakes of EI, CHO, fat and P and differed only in terms of GI and GL
Comments
Results
Measurements of the outcome
Definition of outcome
Definition of breakfast
Table 1 Studies evaluating the effect of breakfast composition on cognitive/academic performance in different settings: updated evidence.
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5–11 ys
Mean ~ 9 ys
UK
(Y: BENEO Group, member of the Sudzucker Group, Germany, funded the study and supplied Palatinose and glucosesweetened foods
5
2 separate morning assessment 7 d apart
Design and intervention (School program: Y/N)
low-GL 337 kcal, 73.3 CHO, 9.2 P, 1.9 fat, GL 31.63
Definition of breakfast
Ability of sustained attention according to the paradigm of Shakow, with evaluation of incidence of lapses in attention (very long response times)
should be reported in a blank grid (immediate spatial memory). About 20 min after the initial memory test a verbally recall of the items was required (delayed memory) Speed of information processing according to the British Ability Scale Reaction times test measuring the time necessary to press a button after a light signal
Definition of outcome
Measurements of the outcome
The high and low GL BF had similar intakes of EI, CHO, fat and P, and differed only in terms of GI and GL Statistical analysis: four-way ANOVA (BF*time after BF*immediate/delayed recall*order of BF consumption)
All children attended a school BF club, habitual BF consisting of a bowl of cereal with milk, a slice of toast and orange/apple juice
No effect of BF on the number of lapses after 1 h or 3 hs
Comments
No main effect of BF after 1 h. If children had eaten the low-GL BF on the second d of testing they were able to process information faster No effect of BF after 1 h or 3 hs
Results
Abbreviations: BF=breakfast; BMI=body mass index; CHO=carbohydrate; CH=cholesterol; d=day; F=females; GI=glycemic index; GL=glycemic load; M=males; min=minutes; N=no; P=protein; RAG= rapidly available glucose; s=seconds; SAG= slowly available glucose; SES=socio-economic status; Y=yes; y=year.
Healthy subjects School setting in a socially deprived area
37% M 63% F
Study subjects
Reference (Sponsorship: Y/N)
Table 1 (continued)
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Verbal memory: immediate and delayed combined
Visuo-spatial delayed memory (delayed spatial memory)
Delayed memory Verbal delayed memory (delayed word recall)
Working memory
Verbal short-term memory with secondary motor taskb Visuo-spatial short-term memory (immediate spatial memory)
MEMORY Short-term and working memory Verbal short-term memory (short-term (primary) memory, immediate verbal memory, immediate word recall, (immediate) free word recall)a
Cognitive/academic modality
100 vs 133 kcal BF (Ingwersen et al., 2007)
424 vs 12 kcal BF (Cromer et al., 1990)
Better with high-SAG (low-GI) BF under certain conditions (Benton et al., 2003) Better with high-SAG (low-GI) BF under
Better with high-GI BF with remembering/ forgetting indices under certain conditions (Smith and Foster, 2008)b
Better with high GI-BF, but nonsignificant GI and GL interaction (Micha et al., 2011) Better with low-GI BF under certain conditions (Cooper et al., 2012)d Better with low-GI, with high-GL BF and with high-GL/low-GI BF (Micha et al., 2010) Better response times with low-GI BF under certain conditions (Cooper et al., 2015)
Better with low-GL BF under certain conditions (Young and Benton, 2015)
Different GL/GI BF (Micha et al., 2011)
Better with low-GI BF under certain conditions (Mahoney et al., 2005) Better with high-GI BF, but non significant GI and GL interaction (Micha et al., 2010) Better with low-GL BF under certain conditions (Young and Benton, 2015)
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Different GI BF and no BF (Mahoney et al., 2005)c
Different GL BF (Benton et al., 2007)
Different GL BF (Benton et al., 2007) Different GL/GI BF (Micha et al., 2011) Different GI BF with raw memory retention scores (Smith and Foster, 2008)b Different GL/GI BF (Micha et al., 2010) Different GL BF (Young and Benton, 2015)
On accuracy for different GI BF (Cooper et al., 2015)
Different GL/dairy products BF (Brindal et al., 2012)
Different GI BF (Nilsson et al., 2012)d
Different GI BF (Ingwersen et al., 2007)
Different GI BF and no BF (Mahoney et al., 2005)c
Different GI BF (Smith and Foster, 2008) different GL BF (Benton et al., 2007)
Different GI BF and no BF (Mahoney et al., 2005)
Different GL/dairy products BF (Brindal et al., 2012)
Different fat/CHO BF and no BF (Lloyd et al., 1996)
Nonsignificant effect
Better with low-GL BF under certain conditions (Benton et al., 2007)
Significant effect
Significant effect
Nonsignificant effect
Breakfast composition
Amount of energy intake at breakfast
Table 2 Summary of findings on the relationship between amount of energy intake at breakfast/breakfast composition and cognitive/academic performance, grouped by cognitive domain (row) and research question (column).
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INFORMATION PROCESSING AND
Attention switching
f
Selective attention – reaction time/completion time
Selective attention Selective attention – number of correct responses or accuracyf,g
Auditory sustained attention – rates of hits, misses and false alarms Auditory sustained attention – reaction times to hits and false alarms
Visual sustained attention – time on task, speed of sustained attention, reaction times to hits and false alarms
Sustained attention Visual sustained attention – number of correct responses, accuracy, number of lapses in attention, rates of hits, misses and false alarms
ATTENTION/CONCENTRATION
Speed of memory
Long-term (secondary) memory
Cognitive/academic modality
Table 2 (continued)
Better with 100 vs 133 kcal BF (Ingwersen et al., 2007)
Better with 100 vs 133 kcal BF (Ingwersen et al., 2007)e e
100 vs 133 kcal BF (Ingwersen et al., 2007)
424 vs 12 kcal BF (Cromer et al., 1990)
100 vs 133 kcal BF (Ingwersen et al., 2007)
Better with high-GL/high-GI BF (Micha et al., 2011) Better with high-GI as to the Stroop test (Cooper et al., 2012) Better with low-GI BF under certain conditions (Cooper et al., 2015)
Better with high-GI BF, but nonsignificant GI and GL interaction (Micha et al., 2011) Better with low-GI BF, under certain conditions (Nilsson et al., 2012) Better with low-GI BF, overall and under certain conditions (Cooper et al., 2012)
Better with low-GI BF under certain conditions (Mahoney et al., 2005)
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Different GL/dairy products BF (Brindal et al., 2012)
Different GL/GI BF (Micha et al., 2010)
Different GI BF as to the Flanker test (Cooper et al., 2012)
Different GI BF (Nilsson et al., 2012)
Different GI BF (Cooper et al., 2015)
Different GI BF and no BF (Mahoney et al., 2005)
Different GI BF and no BF (Mahoney et al., 2005) different GL BF (Young and Benton, 2015)
Different GI BF (Ingwersen et al., 2007)
Different RAG or SAG (GI) BF and no BF (Benton and Nabb, 2004) Different GL BF (Young and Benton, 2015)
Better with low-GL BF under certain conditions (Benton et al., 2007)
Better with low-GL BF under certain conditions (Benton et al., 2007)
Different GI BF and no BF (Mahoney et al., 2005)
Different GI BF and no BF (Mahoney et al., 2005)c Different GI BF (Ingwersen et al., 2007)e
Nonsignificant effect
Better with low-GI BF (Ingwersen et al., 2007)
Better with low-GI BF (Ingwersen et al., 2007)e
certain conditions (Benton and Nabb, 2004)
Significant effect
Significant effect
Nonsignificant effect
Breakfast composition
Amount of energy intake at breakfast
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8 Better with ≥20% vs < 20% EI BF (Lopez-Sobaler et al., 2003)j
424 vs 12 kcal BF (Cromer et al., 1990)
Better with low-GI BF, but nonsignificant GI and GL interaction (Micha et al., 2011)
Better with high-GL BF, but nonsignificant GI and GL interaction (Micha et al., 2010)
Abbreviations: BF=breakfast; CHO=carbohydrate; EI=energy intake; F=females; GI=glycemic index; GL=glycemic load; M=males; RAG= rapidly available glucose; SAG= slowly available glucose.
≥20% vs < 20% EI BF (Lopez-Sobaler et al., 2003)j
> 20% (536i and 434i kcal for M and F, respectively) vs < 10% (170i and 121ikcal for M and F, respectively) EI BF (Wyon et al., 1997) ≥20% vs < 20% EI BF (Lopez-Sobaler et al., 2003)j
MATH
VERBAL ABILITIES Command of language Fluency
424 vs 12 kcal (Cromer et al., 1990)
Better with > 20% vs < 10% EI BF among M only (536ivs 170i) (Wyon et al., 1997)
> 20% (536i and 434i kcal for M and F, respectively) vs < 10% (170i and 12i kcal for M and F, respectively) EI BF (Wyon et al., 1997)
LEARNINGA
CREATIVITY
Inductive
Logical
REASONING Grammatical
IMPULSIVITY
Psychomotor skill (motor speed)
Inspection time
Different GL/GI BF (Micha et al., 2010)
Different GL/dairy products BF (Brindal et al., 2012)
Different GL/GI BF (Micha et al., 2011)
Different GL/dairy products BF (Brindal et al., 2012) Different GL/dairy products BF (Brindal et al., 2012) Different fat/CHO BF and no BF (Lloyd et al., 1996)
Perceptual speed
Different GL/dairy products BF (Brindal et al., 2012)
Different fat/CHO BF and no BF (Lloyd et al., 1996) Different RAG or SAG (GI) BF and no BF (Benton and Nabb, 2004) Different GL BF (Young and Benton, 2015)
Nonsignificant effect
Different fat/CHO BF and no BF (Lloyd et al., 1996) On both response times and accuracy for different GI BF (Cooper et al., 2015)
Better with high-GI BF, but nonsignificant GI and GL interaction (Micha et al., 2011) Better with low-GL BF only under certain conditions (Young and Benton, 2015) Better with low-GI BF and with high-GL BF, but nonsignificant GI and GL interaction (Micha et al., 2010)
Significant effect
Significant effect
Nonsignificant effect
Breakfast composition
Amount of energy intake at breakfast
Visual information processing
Speed of information processing, speed of processingf
PSYCHOMOTOR SPEED Simple and choice reaction timesh
Cognitive/academic modality
Table 2 (continued)
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amount of energy intake at breakfast/breakfast composition and cognitive/academic performance, grouped by broad cognitive domain (row) and research question (column). Specific subdomains of interest are reported in separate rows, including also for reference the original terms provided in the corresponding papers. Significant and non significant results are reported in separate columns. Results from the previous systematic review were added to provide a complete picture of the relations between energy intake at breakfast/breakfast composition and cognitive/academic performance. Results from the current review are indicated in bold and italics to highlight the new evidence collected. 4. Discussion The current review updates a previous systematic review of ours (Edefonti et al., 2014) published in 2014 and based on 15 papers. Unfortunately, after 2 years and a half, our search provided 2 new pertinent papers only. Both of them were published in 2015. It is, therefore, evident that our current conclusions will be mostly in line with the previous ones from the 2014 review (Edefonti et al., 2014). Seventeen papers are still not a reasonable body of evidence to base any conclusions. In addition, heterogeneity and inconsistency in research designs, interventions, cognitive tests, and statistical analyses still make these reviews a preliminary attempt to understand which information the literature provides on 2 important, but definitely difficult, themes. However, this update allows us to track some general trends of the literature on breakfast consumption and cognitive/academic performance that are worth of note. The predominance of studies on children and adolescents, as compared to adults, is confirmed by our updated systematic review. Eleven out of 15 studies from the previous review concerned children and adolescents (Edefonti et al., 2014). The new studies included in the update are based on children (Young and Benton, 2015) and adolescents (Cooper et al., 2015), too. These categories may be particularly sensitive to the nutritional effects of breakfast on brain activity and associated cognitive/academic outcomes. Beyond other mechanisms (such as hunger alleviation (Alaimo et al., 2001; Kleinman et al., 1998) and changes in neurotransmitter concentrations (Pollitt and Mathews, 1998)), children and adolescents have a higher metabolic rate of glucose utilization, a higher average cerebral blood flow and oxygen utilization, than do adults (Chiron et al., 1992; Kennedy and Sokoloff, 1957). Their higher sleep demand implies a longer overnight fasting, which can deplete glycogen stores overnight (Thorleifsdottir et al., 2002). Thus, breakfast consumption provides an important supply of energy and nutrients to modulate the short-term metabolic responses to fasting conditions. Further, it may provide long-term effects, including an improved nutrient balance and distribution, with important fallouts on cognitive processes, too (Pollitt and Mathews, 1998). Finally, breakfast may affect cognitive performance indirectly, through improved subjective feelings of mood, alertness, and motivation (Cooper et al., 2011). In addition, the new studies were still conducted in the United Kingdom by 2 independent groups of researchers that have contributed with one (Cooper et al., 2012) or more papers (Benton et al., 2007, 2003; Benton and Nabb, 2004) to the previous review (Edefonti et al., 2014). This confirms that researchers from the United Kingdom, with 10 out of 17 papers in total from the two reviews, have been by far among the most active groups in the world to deal with the themes of the current review. However, this could limit generalizability of the findings, also in consideration of the substantial lack of evidence from developing countries. Concerning the type of breakfast, both the included papers added evidence on the effect of breakfast composition and cognitive/academic performance, testing the effect of two iso-energetic breakfast options differing in GI or GL (Cooper et al., 2015; Young and Benton, 2015). More evidence is, therefore, accumulating on breakfast composition
b
a
The Rey auditory-verbal learning test assessed both verbal learning and immediate verbal memory. Therefore, we reported its results in the corresponding 2 rows of the table, as indicated in Rampersaud et al. (Rampersaud et al., 2005). In Smith et al. (Smith and Foster, 2008), verbal memory was assessed with a simultaneous secondary motor task, so under conditions of divided attention. Therefore, we presented its results in a separate row in the verbal memory section. However, the paper did not provide the corresponding results for the motor task. Moreover, the tasks were expressed in terms of both raw memory retention scores and derived remembering/forgetting indices, calculated to control for individual differences in the total items recalled in the previous recall phase. Although the paper did not provide any detail, the statistical analyses for the 2 outcome measures were probably different, with the latter analysis including one time or delay effect allowing for comparisons between short and long delay results. Therefore, we separated the corresponding results on verbal memory in the short-term (immediate and short-delay) and delayed sections. As results from retention scores and remembering/forgetting indices were inconsistent at the long delay, we summarized them in 2 separate cells. c In Mahoney et al. (Mahoney et al., 2005), the so-called spatial memory and visual perception domains belonged both to the visuo-spatial memory category. Both of them were assessed at the level of short- and long-term memory and then contributed to both immediate/short-term and long-term memory categories. Results for short-term memory were consistent across these domains, and therefore we included them in the same cell. Results on long-term memory for visual perception and spatial learning were also consistent with those of a verbal memory test. Therefore, we included the information on long-term memory from the 3 tests in a single cell. Visual perception was also assessed as a delayed recall and then contributed to the visuo-spatial delayed memory category too. d The tasks were expressed in terms of both response/reaction times and accuracy (proportion/number of correct responses), but results were consistent and therefore we summarized them in 1 cell only. e The paper by Ingwersen et al. (Ingwersen et al., 2007) assessed cognitive performance referring to the selection of tests from the Cognitive Drug Research computerized assessment system and adopted its cognitive assessment factor scores. These are combined scores obtained from individual measures derived from simpler tests. Whenever they did not seem to us to be comparable to the simpler test measures provided by the other papers, we put them in a separate row. f In Micha et al. (Micha et al., 2011), number search task assessed both speed of information processing and selective attention, and therefore we reported its results in the corresponding 2 rows of the table. In Brindal et al. (Brindal et al., 2012), speed of processing was a composite measure based on the responses to different reaction time tasks. g In Cooper et al. (Cooper et al., 2012), selective attention was assessed using both the Stroop and the Flanker tests. When results were consistent, we reported them in 1 cell; otherwise, we filled in 2 cells, and indicated from which test result came from. h Although reaction time is commonly used as a dependent variable in many tests of cognitive function, some studies include direct measures of reaction time where reaction time is not a proxy measure for a more complex function. i Mean intakes for each treatment option and sex. j The paper by López-Sobaler et al. (Lopez-Sobaler et al., 2003) considered both an overall score measuring verbal, reasoning, and calculation abilities and its single domains. Here, we presented results for the single domains only.
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accurate control for confounding factors. Finally, in studies assessing the effect of energy intake at breakfast, we recommend to compare breakfast options with a similar composition; similarly, in studies assessing the effect of breakfast composition, we recommend to compare iso-energetic breakfast interventions differing in a single nutrient component, when possible, to provide more effective messages of public health.
and, in particular, on breakfast varying in GI, GL, or both, as already mentioned in our previous review (Edefonti et al., 2014) and in another one on any eating occasions (Philippou and Constantinou, 2014). However, we are still far from the possibility to draw firm conclusions in regard to the impact of breakfast type on cognition in healthy subjects. Although the quality of much of these works – particularly studies conducted in recent years – is good, methodological differences across studies appear to lead to inconsistency in findings. In particular, heterogeneity and limited consistency between studies dominate the definition of the cognitive performance measures under comparison. In the case of the current review, the same 3 domains were under investigation in both studies. However, there was no overlapping between the specific subdomains that was tested in the 2 studies (Cooper et al., 2015; Young and Benton, 2015). This materially prevents any possibility of a fair comparison. However, to integrate the new findings with the previous ones, we have updated Table 3 from the previous review – summarizing the findings on the relationship between breakfast characteristics and cognitive performance, according to cognitive domain and research question (Edefonti et al., 2014) – and inserted it in the current manuscript as Table 2. The accurate reclassification of the cognitive and academic measures employed should help the reader to compare results from the different studies. Although in the past most experiments have examined cognitive performance at only one time-point after breakfast (Kanarek, 1997), information is now generally available on the time-course of the effects of breakfast on behavioral measures. This new trend is confirmed in the present review, where both the new included studies (Cooper et al., 2015; Young and Benton, 2015) allowed for testing subjects more than once after breakfast on the same day. This also argues in favor of the highest quality of more recent studies. However, the different time intervals between breakfast and testing sessions, i.e. 30 and 120 min (Cooper et al., 2015) vs 60 and 180 min (Young and Benton, 2015) from breakfast, even for the same domains under investigations, still prevents from a fair comparison between studies. This may reflect a difference in the specific research questions of the papers (for instance, Nilsson and coauthors considered the course of glycaemia with particular attention to the later postprandial period) and/or a still limited knowledge of the mechanisms linking breakfast to cognitive performance (Brindal et al., 2012; le Coutre and Schmitt, 2008; Nilsson et al., 2012). In conclusion, after two extra years of accumulating evidence, there is still insufficient quantity and consistency among studies to draw firm conclusions on the relationship between amount of energy intake at breakfast and breakfast composition and cognitive/academic performance. The hypothesis of a better and more sustained mental performance with breakfast equivalent to or > than 20% daily energy intake still needs substantiation, as we were not able to identify extra evidence on this issue. In addition, the identified papers still support the hypothesis that a lower postprandial glycemic response is beneficial to cognitive performance. However, the results from the 2 reviews did not show large breakfast-induced advantages for cognitive performance. The evidence likely points to a subtle relationship, demonstrated only under specific conditions (i.e. on some test levels or on some testing sessions only) or in specific subgroups of the sample (i.e. in males or younger subjects only). It also remains unclear whether this effect is specifically due to GI or GL solely, or to both, or to other effects unrelated to glycemic response. Finally, even after controlling one for the other, it remains unclear whether GI- or GL-based breakfast meals selectively facilitate different cognitive domains. Future research will benefit from well-matched study conditions and selected populations of interest, including the least represented adolescent category. In addition, tests of cognitive performance should be chosen among those that proved to be sensitive to nutritional manipulations; they should be standardized as far as possible and scheduled at standardized time points. Studies should provide an
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