A review of the effects of lunch on adults' short-term cognitive functioning.
Lunch provides a substantial portion of daily energy (1-4) and nutrients (2-4). For example, data from the 2004 Canadian Community Health Survey showed a 24% contribution of lunch to daily energy intake (1). However, irregular lunch consumption seems to be common in childhood and adulthood.
Although all-day schools are well established in many countries, in only some (e.g., the United States) is the provision of school lunch well organized (5). In other nations (e.g., Canada, European nations), school lunches lack uniformity (6,7). Furthermore, a relatively high percentage of children and adolescents skip school lunch when it is offered (8-10). Ten percent of fourth grade students from Maryland were reported to omit lunch at least three times a week (11).
In a review, Sparks et al. (12) concluded that working time has increased in various countries in recent decades. They found that employees who work for long hours are more prone to poor lifestyle habits such as an inadequate diet (12). In Germany, an association between daily working hours and irregular meal consumption has been observed in employees (13). Similarly, in a US sample of adults, the most frequently missed meal was lunch, with 28% of participants skipping lunch on at least one of two 24-hour recall days (14). Similarly, 22% of a Swedish adult sample reported no usual lunch consumption (15).
One argument often used against meal skipping is the impairment of short-term cognitive functioning. To date, research on the impact of meal consumption on short-term cognitive functioning has focused primarily on breakfast; findings suggest positive cognitive effects associated with having breakfast versus skipping it in children (16) and adults (17). However, the effects of lunch on early afternoon cognitive functioning in the classroom and at work are not yet well understood. This review is a summary of the literature on short-term effects of lunch on cognitive performance in children and adults. Underlying metabolic mechanisms and the role of potential effect modifiers are considered, and implications for future research are discussed.
A MEDLINE search was done in September 2012. The search strings listed in Table 1 were used, and were complemented with cross-referencing. Studies were included or excluded according to various criteria.
Participants and interventions
Studies on healthy participants of all ages and both sexes were included. All types of lunch studies were examined, including studies in which lunch was compared with no lunch, studies of different lunch sizes, and studies of different lunch compositions. Studies on the effects of longer-term school health/lunch programs were excluded, as their focus was on cognitive effects of modifying lunch provision and the lunch environment (e.g., cafeteria layout) (18-20). Hence, observed effects might not be due to lunch alone. Studies on the effects of fortified lunches were also excluded.
Included were studies in which objective measures of cognitive functioning were determined; excluded were those in which only subjective ratings of performance and fatigue were considered. Short-term performance was assessed--not longer-term cognitive effects of lunch modifications.
Figures 1 and 2 show the study selection process and the number of studies accessed and excluded at each stage. The process yielded 139 published studies with children and 170 published studies with adults. All of the studies with children and a Defined as identical reports accessed with several search strings 159 of the studies with adults were excluded because the inclusion criteria were not fulfilled. Therefore, 11 studies (12 papers) found through the MEDLINE search and cross-referencing were included; all were studies of adults.
No studies were found in which authors examined the short-term effects of lunch versus no lunch and of lunch character (size, composition) on children's cognitive functioning. In adults, 11 experimental studies published from 1981 to 1996 included examinations of the effects of lunch on short-term cognitive performance. Three were comparisons of the effects of having lunch with skipping lunch, two were evaluations of the effects of lunch size, five were determinations of the effects of lunch composition, and one was a determination of the effects of lunch size and composition (Table 2).
Lunch versus no lunch
Studies in which having lunch was compared with skipping lunch had inconsistent results. Two showed impaired cognitive performance in some but not all tasks. For example, Craig et al. (21) observed that the ability to discriminate was impaired by the "lunch condition" in comparison with the "pre-lunch condition," but was not altered by the "no lunch condition." With a sustained attention task, Smith and Miles (22) reported a slower response from the lunch group, but not from the no-lunch group in comparison with the pre-lunch condition; however, with a selective attention task they found no differences between the groups. In contrast, Kanarek and Swinney (23) found no lunch effects in experiment 1; in experiment 2, they found positive effects on a reading task after the "lunch condition" in comparison with the "no lunch condition," and no effects for other tasks.
Craig and Richardson (24) observed an increased number of errors after a large lunch and a trend toward a decreased number of errors after a small lunch, when each condition was compared with the pre-lunch condition. Similarly, Smith et al. (25) observed more errors with a selective attention task after a large lunch than after a "normal" lunch and a small lunch. Effects were modified by the size of the test lunch and the regular lunch (25,26).
Among the six studies in which lunch composition was examined, four studies focused on cognitive effects of low-fat versus high-fat lunches and two studies focused on high-protein versus high-carbohydrate lunches. For example, Smith et al. (26) observed that subjects responded more accurately but slowly after a high-fat lunch than after a low-fat lunch. In older subjects, Spring et al. (27) reported lower accuracy and more omission errors with a sustained attention task after a high-carbohydrate lunch than after a high-protein lunch. Smith et al. (28) also found more negative effects of a high-carbohydrate lunch than of a high-protein lunch, with slower reactions to peripheral targets. In general, cognitive effects of lunch composition were observed for some but not all tasks (Table 2).
Lunch versus no lunch
Only a few investigators have examined the effects on cognitive performance of having lunch versus skipping lunch; most found impairments in some but not all tasks after lunch. In adults, lunch therefore seems to have adverse effects on certain types of tasks. However, differences and limitations in the methodology of existing studies make a comparison of data difficult. For example, the cognitive aspects assessed (e.g., perceptual discrimination, attention, memory) differ between studies. Only Kanarek and Swinney (23) used a crossover design; in the remaining studies, investigators used randomized, controlled designs and standardization was sometimes inadequate. For instance, unlimited tea and coffee intake was allowed in two of three studies. Psychoactive substances such as caffeine may produce larger cognitive effects, which may mask smaller "true" lunch effects on cognitive functioning (26). Furthermore, the two lunch conditions possibly resulted in different caffeine absorption rates because of different gastric emptying rates; in turn, this may have influenced cognitive functioning.
Although only weak evidence exists for the detrimental effects of lunch on cognitive functioning, several explanations have been proposed. First, the so-called post-lunch dip has often been discussed. It may not be caused only by endogenous factors; it may also be influenced by exogenous factors (e.g., lunch size) (29). In a review, Kanarek (30) concluded that the suggestion the post-lunch dip may reflect an endogenous alertness rhythm was supported by observed declines in some afternoon tasks by both subjects who had eaten lunch and subjects who had skipped lunch. For other tasks, afternoon performance was more impaired in subjects who had eaten lunch than in those who had not, indicating that food intake may be partly responsible for the dip in the early afternoon (30).
The post-lunch dip is assumed to begin approximately one hour after lunch is started, with data suggesting that performance begins to recover approximately two hours after lunch (31). In most of the studies in which lunch was compared with no lunch, the authors examined post-lunch effects 60 to 75 minutes after a test meal (21,22,32). Only Kanarek and Swinney (23) administered cognitive assessments 210 minutes after lunch. Thus, little information is available on the effects that may appear later in the afternoon.
Another explanation for unfavourable short-term effects of lunch is a change in stress hormone status (e.g., glucocorticoid level). Cortisol is the major natural glucocorticoid in humans (33), and it rapidly increases to a lunch-related plasma peak about one hour after lunch (at approximately 1:00 p.m.). This is also the time when only a slow increase in plasma cortisol is observable in fasting subjects (34). An enhancement in plasma cortisol seems to be associated with a decrease in cognitive functioning (35). In their review, Lupien et al. (36) concluded that an endogenous increase of glucocorticoids is as efficient as an exogenous administration at inducing cognitive impairments. The effects of exogenous glucocorticoid administration on cognitive functioning were supported by the hippocampus and the frontal lobes, the brain regions with the largest concentrations of glucocorticoid receptors, and modulated according to an inverted U-shaped function (36).
The lunch effect on short-term cognitive functioning in adults may also depend on lunch size, in terms of energy content (24,25) or weight (26). For example, Craig and Richardson (24) observed an increased number of errors after an energy intake of approximately 5.8 MJ and a trend toward a decreased number of errors after an energy intake of approximately 1.1 MJ, when each condition was compared with the pre-lunch condition. Smith et al. (25) report similar findings, with more errors on a search task after a large lunch (2.8 to 4.6 MJ) than after smaller lunches (1.4 to 3.5 MJ). Smith et al. (26) had inconsistent results.
In only three studies did the authors examine the effects of lunch size on cognitive functioning in the early afternoon; these studies differed in methodology (cognitive aspects assessed, definition of meal size). Furthermore, the studies are characterized by an inadequate description of methodology. For instance, Craig and Richardson (24) gave information only on meal type (three-course meal versus sandwich) and energy content. Smith et al. (25) provided more details of the test meal, but no information on participants' assignment to the intervention group or control group. Furthermore, although energy intake seems to be oriented toward participants' habitual energy intakes in Craig and Richardson's study (24), a lunchtime energy intake of 5.8 MJ appears to be relatively high. In general, for a detailed evaluation of the effects of lunch size on cognitive performance to be possible, test meal compositions should be almost identical. This is because the relative carbohydrate content also plays a role in postprandial glycemic response. Circulating blood glucose, in turn, seems to modify cognitive functioning (17). The current results could lead one to hypothesize that a large lunch would be accompanied by decreased cognitive performance.
Lunch composition may affect cognitive performance. Smith et al. (26) observed that subjects who had eaten a high-fat lunch responded more accurately but more slowly than did subjects who had eaten a low-fat lunch. This finding is consistent with that of Wells et al. (37), who showed that speed of correct responses was significantly slower after a high-fat lunch than after a low-fat lunch. Lloyd et al. (38) also reported a significantly longer reaction time after a high-fat/low-carbohydrate lunch than at baseline. However, different lunch conditions and cognitive tasks were used. Thus, we conclude only cautiously that a highfat lunch results in slower but more accurate responses.
Changes in the fat content of meals also accompany changes in carbohydrate and protein content. However, Smith et al. (26) have suggested that the effects mentioned above cannot be due to the changes in other macronutrients because their findings were very different from those of an earlier study, which included modified proportions of carbohydrates and protein (27). Further studies are needed to determine whether an isolated fat effect on cognition exists, and whether macronutrient substitution has no effect on cognition.
Some evidence indicates that the potential effects of lunch composition on short-term cognition may vary between sub groups. Spring et al. (27) classified subjects into younger (18 to 39 years) and older (40 to 65 years) age groups and gave both groups isocaloric high-protein and high-carbohydrate meals. The older subjects showed significantly impaired cognitive performance after consuming a high-carbohydrate lunch, whereas the younger subjects did not.
Another study showed that subjects who had eaten medium-fat/medium-carbohydrate lunches had improved simple reaction-time tasks when they were compared with subjects who had eaten low-fat/high-carbohydrate and high-fat/low-carbohydrate lunches, and when their reaction time was compared with baseline times (38). The medium-fat/medium-carbohydrate lunch was most similar to the subjects' usual eating habits in terms of meal size and macronutrient composition. One might suppose that this nutrient profile would be preferred intuitively because it benefits subjects' performance after lunch. Of note is the fact that the effects were mostly very small, inconsistent, and restricted to certain tasks (e.g., attention and search tasks) and subgroups (e.g., older subjects).
The studies evaluated had some inconsistent results. These differences between studies may be partly because of effect modifiers.
Female or male sex: Regardless of the nutritional intervention, men achieved more favourable results on visuospatial memory tests, whereas women tended to do better on verbal memory tests (39). Furthermore, sex seems to influence the way a meal affects cognitive functioning (e.g., male students had improved visuospatial memory after eating breakfast, but female students did not) (40). In contrast, Mahoney et al. (41) observed that, in comparison with boys, girls suffer more when they skip breakfast and benefit more when they eat a low glycemic index breakfast. Mahoney et al. (41) suggested that mood and usual breakfast habits may play a role in these differences. In a review, Blaak (42) concluded that impaired glucose tolerance in general and higher glycemic responses to glucose-containing meals are more common in women than in men. This may be due to men's higher muscle mass, which enables faster glucose uptake (42).
Habitual lunch size: Craig and Richardson (24) categorized subjects as light lunchers or heavy lunchers, depending on their normal eating habits. All of them performed a sustained attention task, both before and after a light lunch and a heavy lunch. The largest drop in performance was observed in subjects who usually ate light lunches but in the test ate a heavy lunch, whereas the greatest improvement was observed in subjects who normally ate heavy lunches but in the test ate a light lunch. These results reflect the so-called conditioning hypothesis, which suggests that a physiological under- or over-reaction occurs with an unusual meal (24).
Habitual lunch consumption was considered in seven of the 11 studies. In two studies (23,43), only usual breakfast and lunch eaters were included, probably because habitual meal skipping may mask short-term lunch effects. In one study (22,32), most participants reported that the test meal was larger than their habitual lunch. The authors suggested that the observed faster completion of an afternoon task when lunch was skipped than when lunch was eaten might not have been due to the test lunch, but to a deviation from the usual lunch.
Biorhythm: Biorhythm seems to vary from individual to individual, with observable differences between so-called "morning people" and "evening people" (29). Morning people have better performance efficiency in the morning than in the evening. In contrast to morning people, who show a general decline throughout the day, evening people show a steady improvement throughout the day (44). May et al. (44) have suggested that the synchrony between optimal cognitive performances and testing times may be a critical variable in the determination of group differences in cognitive functioning. Furthermore, the likelihood of exhibiting a post-lunch dip may be greater in morning people. Horne et al. (45) found an obvious post-lunch dip in morning people, who showed a notable decline in performance between noon and 2:00 p.m., which was after lunch for most subjects. In contrast, evening people showed a slight improvement between noon and 2:00 p.m.
Implications for future research
To date, only a few studies with adults and no studies with children are available to permit conclusions about the effect on cognitive functioning of lunch character (size, composition) or lunch versus no lunch. Because of age- and growth-related issues affecting children (e.g., rapid growth, high metabolic rate), findings from adult studies are not necessarily transferable to children. Therefore, well-designed studies in children and adults are needed to permit scientifically well-founded conclusions. Crossover studies are well suited to this purpose because they can eliminate between-patient variations. Factors such as female or male sex, age, habitual lunch consumption, and biorhythm may modify the lunch effect and therefore also need to be considered.
Test lunches should be optimally adjusted to the subject's habitual lunch. Dye and Blundell (46) speculated that a meal's palatability could increase the subject's positive mood, which, in turn, could enhance cognitive performance. Therefore, providing a well-liked test meal in a familiar environment would be the most appropriate method for identifying the lunch effect. The establishment of standardized procedures (e.g., standardized test meals) is another condition for minimizing bias.
RELEVANCE TO PRACTICE
Only limited information from adult studies is available on the effects of lunch on short-term cognitive functioning, and all but one study suggest that eating lunch potentially impairs some aspects of cognitive functioning. Factors such as lunch size and lunch composition may be involved. However, we entertain these suggestions only cautiously because findings are based on a few studies with some design limitations, which further restrict the validity of the evidence. If nutritional recommendations are to be provided, additional well-designed studies in children and adults are needed. In the meantime, lunch should be part of an overall balanced diet in Canada and other coun tries, as it provides a considerable percentage of daily energy and nutrients and may positively affect subjects' longer-term general and cognitive health.
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KATRIN MULLER, MSc, LARS LIBUDA, PhD, ANNA MARIA TERSCHLUSEN, Dipl-Oecotroph, MATHILDE KERSTING, PhD, Research Institute of Child Nutrition (FKE), Dortmund, Germany
Table 1 Search strings used in the literature review 1 Lunch AND children/adults AND cogniti* 2 "Lunch composition" AND children/adults AND cogniti * 3 Lunch AND children/adults AND memory 4 Lunch AND children/adults AND attention 5 Lunch AND children/adults AND vigilance 6 Lunch AND children/adults AND "reaction time" 7 Lunch AND children/adults AND spatial 8 Lunch AND children/adults AND visuo-spatial 9 Lunch AND children/adults AND "problem solving" * Denotes word truncation Table 2 Eleven experimental studies of lunch and cognitive functioning in adults Study Sample Lunch versus no lunch Craig et al.. 40 adults 1981, UK 63% male (21) Median age 23 years Smith and Publ. 1 Miles, 1986, 48 adults UKa (22,32) 38% male Age not provided (university students) Publ. 2 see publ. 1 Kanarek and Exp. 1 Swinney, 10 men 1990, USA Mean age 21 (23) years Exp. 2 8 men College-aged Lunch size Craig and 24 men Richardson, (12 LL, 12 1989, UK HL) (24) Median age 23 years Smith et al., 35 women 1991, UK Mean age (25) 26 years Lunch composition Spring 184 adults et al., (lunch n=92) 1982, 70% male USA 18-39 years (27) (n=81) 40-65 years (n=103) Smith 11 adults et al., 46% male 1988, Mean age UK 27 years (28) Lloyd 18 adults et al., 17% male 1994, Mean age UK 27 years (39) Wells 16 men et al., (lunch n=8) 1995, Mean age UK 23 years (38) Wells 18 men and (lunch n=9) Read, Mean age 1996, 27 years UK (43) Lunch size and composition Smith 46 adults et al., 43% male 1994, Age not UK provided (26) (university students) Design and lunch Study intervention Lunch versus no lunch Craig et al.. Randomized controlled 1981, UK intervention study with 2 (21) conditions: a. Lunch: standard 3-course meal b. No lunch: tea or coffee, walk Intervention from 12:00- 13:00 Smith and Miles, 1986, Randomized controlled UKa (22,32) intervention study with 2 conditions: a. Lunch: standard 3-course meal b. No lunch Intervention from 12:00- 13:15 (early) and 13:15- 14:30 (late) See publ. 1 Kanarek and Counterbalanced crossover Swinney, with 4 lunch conditions: 1990, USA a. Lunch/caloric snack (23) b. Lunch/non-caloric snack c. No lunch/caloric snack d. No lunch/non-caloric snack Lunch at 12:00 (early) or 12:30 (late) See exp. 1 Different caloric snack (fruit- flavoured yogurt instead of confectionery product) Lunch size Craig and Counterbalanced crossover Richardson, with 2 conditions: 1989, UK a. Large: 3-course meal (24) (5.8 MJ) b. Small: sandwich (1.1 MJ) Lunch from 12:00-13:00 Smith et al., Intervention study with 3 1991, UK conditions: (25) a. Normal (2.5-3.5 MJ) b. Large (2.8-4.6 MJ): 40% more energy than EIR c. Small (1.4-3.1 MJ): 40% less energy than EIR Lunch at 12:30, 13:00, and 13:30 (staggered starting) Lunch composition Spring Randomized intervention study with et al., 2 lunch conditions: 1982, a. High-protein: ~57 g P, 4 g F, 1 g USA CH, 30-90 mg choline (27) b. High-carbohydrate: 0 g P, ~4 g F, 57 g CH Lunch between 11:00 and 13:00 Smith Counterbalanced crossover with 3 et al., conditions: 1988, a. High-protein: 55% of energy as P, UK 30% as F, 14% as starch, and 1% (28) as sugar b. High-starch: 15% of energy as P, 30% as F, 40% as starch, and 15% as sugar c. High-sugar: 15% of energy as P, 30% as F, 15% as starch, and 40% as sugar Lunch at 13:00 Lloyd Counterbalanced crossover with 3 et al., conditions: 1994, a. LFHO: 54% of energy as CH, 29% UK as F, and 15% as P (39) b. MFMC: 42% of energy as CH, 45% as F, and 12% as P c. HFLC: 24% of energy as CH, 62% as F, and 13% as P Lunch from 12:30-12:45 Wells Counterbalanced crossover with 2 et al., lunch conditions: 1995, a. HFLC: 18% of energy as CH, 64% UK as F, and 18% as P (38) b. LFHC: 75% of energy as CH, 7% as F, and 18% as P 30-min lunch at 12:45 Wells Counterbalanced crossover with 2 and lunch conditions: Read, a. HFLC: 3181 kJ, F:CH energy ratio 1996, 54:41 UK b. LFHC: 3599 kJ, F:CH energy ratio (43) 7:88 Lunch at 12:30 Lunch size and composition Smith Randomized intervention study with 4 et al., conditions: 1994, a. Low-fat, small: 29 g P, 18 g F, 148 g UK CH, 840 kcal, meal wt: 600 g (26) b. Low-fat, large: 34 g P, 23 g F, 144 g CH, 880 kcal, meal wt: 860 g c. High-fat, small: 47 g P, 79 g F, 103 g CH, 1290 kcal, meal wt: 530 g d. High-fat, large: 28 g P, 84 g F, 118 g CH, 1300 kcal, meal wt: 840 g Lunch at 12:30 (early) and 13:15 (late) Cognitive Study assessment Lunch versus no lunch Craig et al.. Perceptual discrimination 1981, UK 1 h CA at 11:00 and 13:00 (21) Subjects tested individually Smith and Miles, 1986, Sustained attention UKa (22,32) (5CSRTT) Selective attention (Stroop effect) 45 min CA at 10:45/13:15 (early) and 12:00/14:30 (late) Subjects tested in pairs Sustained attention (DORN, PROP) See publ. 1 Kanarek and Working memory (DST) Swinney, Arithmetic reasoning 1990, USA Reading (23) Sustained attention CA at 15:30 (early) or 16:00 (late) Participants tested individually See exp. 1 Lunch size Craig and Sustained attention (LCT) Richardson, 30 min CA at 11:15 and 1989, UK 13:15 (24) Participants tested individually Smith et al., Selective attention 1991, UK (CRTT, ST) (25) CA at 11:50, 12:20, 12:50, and 13:50, 14:20, 14:50 Subjects tested in small groups Lunch composition Spring Alertness (SRTT) et al., Sustained attention 1982, (DS) USA CA from 13:00-15:00 (27) Participants tested individually Smith CRTT et al., ST 1988, CA at 12:15 and UK 14:15 (28) Lloyd Working memory, et al., sustained attention 1994, (BT) UK Motor speed (TFTT) (39) Short-term memory (FRT) SRTT CA 30 min before and 30, 90, and 150 min after lunch Standardized conditions Wells Sustained-attention et al., task 1995, CA from 9:00-17:00 UK (at hourly intervals) (38) Participants tested individually Wells BT and SRTT Read, CRTT 1996, CA at 12:00 and at UK 13:30, 14:30, 15:30 (43) Subjects tested individually Lunch size and composition Smith Logical reasoning et al., Selective attention 1994, (FAT, ST) UK BT (26) CA at 11:30 and 14:00 (early) and 12:15 and 14:45 (late) Study Reported findings Lunch versus no lunch Craig et al.. Ability to discriminate 1981, UK impaired by condition a. (21) when compared with pre- lunch condition, but not altered by condition b. Smith and Miles, 1986, 5CSRTT: response times UKa (22,32) longer after condition a. when compared with pre- lunch condition, but not after condition b. Stroop effect: no lunch effects DORN: detection of fewer targets after condition a. when compared with pre- lunch condition, but not after condition b. PROP: no lunch effects Kanarek and DST, arithmetic reasoning, Swinney, reading, sustained attention: 1990, USA no lunch effects (23) Reading: faster after conditions a. and b. when compared with conditions c. and d. DST, arithmetic reasoning, sustained attention: no lunch effects Lunch size Craig and Omission errors increased Richardson, after condition a. when 1989, UK compared with pre-lunch (24) condition and tended to decrease after condition b.; effects modified by habitual lunch size Smith et al., CRTT: no lunch effects 1991, UK ST: more errors after condition (25) b. when compared with conditions a. and c. Lunch composition Spring SRTT: no lunch effects et al., DS: in older subjects accuracy lower 1982, and omission errors higher after USA condition b. when compared with (27) condition a. Smith CRTT: no lunch effects et al., ST: slower reactions to peripheral 1988, targets after condition b. and c. UK when compared with condition a. (28) Lloyd SRTT: shorter reaction time 90 et al., and 150 min after condition b. 1994, when compared with condition UK a., condition c. and pre-lunch (39) condition; longer reaction time 90 min after condition c. when compared with pre-lunch condition BT, TFTT, FRT: no lunch effects Wells Correct responses slower after et al., condition a. than condition b. 1995, Accuracy declined after condition UK a. when compared with pre-lunch (38) condition Wells BT, SRTT, CRTT: no lunch effects and Read, 1996, UK (43) Lunch size and composition Smith Selective attention: et al., Slower but more accurate 1994, responses after conditions c. and UK d. when compared with conditions (26) a. and b. (P value not provided) Degree of distraction from near and far distractors and accuracy of responses to central and peripheral targets influenced by meal weight Logical reasoning, BT: no lunch effects Study Comments Lunch versus no lunch Craig et al.. No crossover design 1981, UK Unlimited intake of tea or (21) coffee No information on the consumption of other foods Groups well matched in terms of age and male-to- female ratio Smith and Miles, 1986, No crossover design UKa (22,32) No standardization of test meal Coffee, tea, and smoking allowed Test meal larger than participants' habitual lunch See publ. 1 Kanarek and Standardization of breakfast Swinney, Determination of dietary 1990, USA habits (23) Irregular meal consumption as exclusion criterion Participants asked not to eat or drink except for test meals Small sample size See exp. 1 Lunch size Craig and Crossover design Richardson, Protein-to-carbohydrate ratio 1989, UK of both lunch conditions (24) almost identical No detailed information on meal composition Determination of habitual lunch size Smith et al., No crossover design 1991, UK No information on (25) assignment to groups Standardization of breakfast Nutrient composition of lunch conditions identical Determination of habitual lunch size Lunch composition Spring No crossover design et al., No baseline data 1982, Standardization of USA breakfast and abstaining (27) from food until test meal Smith Crossover design et al., Standardization of 1988, breakfast UK No tea or coffee permitted (28) until completion of test session No information on testing environment Small sample size Lloyd Crossover design et al., Participants asked to eat a 1994, similar breakfast on each UK test day and not to eat or (39) drink except for test lunch Determination of habitual lunch intake Lunch conditions similar in energy and protein content Wells No information on et al., assignment to testing order 1995, Conditions similar in energy UK and protein content (38) Standardization of breakfast Small sample size Wells Crossover design and Determination of quantity Read, and quality of sleep the night 1996, before UK Smoking, illness, and irregular (43) meal consumption as exclusion criteria Determination of usual eating habits Small sample size Lunch size and composition Smith No crossover design et al., Determination of usual 1994, eating habits UK (26) (a) Results from a single study presented in two publications (publ. 1, publ. 2) 5CSRTT = five-choice serial reaction time task; BT = Bakan task; CA = cognitive assessment; CH = carbohydrates; CRTT = choice reaction time task; DORN = detection of repeated numbers; DS = dichotic shadowing; DST = digit span task; EIR = estimated individual requirement; exp. = experiment; F = fat; FAT = focused attention task; FRT = free recall task; HFLC = high-fat/low-carbohydrate; HL = heavy lunche LCT = letter cancellation task; LFHC = low-fat/high-carbohydrate; LL = light luncher; MFMC = medium fat/medium carbohydrate; P = protein; PROP = estimation of the proportions of two classes of events in a signal stream; publ. = publication; SRTT = simple reaction time task; ST = search task; TFTT = two-finger tapping task
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|Author:||Muller, Katrin; Libuda, Lars; Terschlusen, Anna Maria; Kersting, Mathilde|
|Publication:||Canadian Journal of Dietetic Practice and Research|
|Date:||Jan 1, 2013|
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