| Literature DB >> 31548838 |
Martina Lundqvist1, Nicklas Ennab Vogel1, Lars-Åke Levin1.
Abstract
BACKGROUND: Breakfast is often described as the most important meal of the day. Several studies have focused on examining if breakfast habits have any short-term effects on school attendance, academic achievement, and general health in children and adolescents. Informed decisions of whether to promote eating breakfast or not require a more long-term perspective.Entities:
Keywords: adolescents; breakfast; children; effects; review; youth
Year: 2019 PMID: 31548838 PMCID: PMC6744840 DOI: 10.29219/fnr.v63.1618
Source DB: PubMed Journal: Food Nutr Res ISSN: 1654-661X Impact factor: 3.894
Search strategies
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Summary of studies included in the review
| First author (year), country | Participants | Study design | Study purpose | Outcomes | Author conclusion | Scientific quality assessment | ||
|---|---|---|---|---|---|---|---|---|
| Age | Gender (female) | |||||||
| Hallstrom et al. (2013), SE, ES, BE, DE, FR GR, IT, AU ( | 2,929 | 14.7 years | 53% | Cross-sectional, observational | To examine the association between breakfast consumption and cardiovascular disease (CVD) risk factors in European adolescents. | Cardiorespiratory fitness | Findings regarding European adolescents confirm previous data indications: adolescents who consume breakfast regularly have lower body fat content than other peers. Results also show that regular breakfast consumption (BC) is associated with higher cardiorespiratory fitness and (especially in male adolescents) with a healthier cardiovascular profile and negation of the effect of excess adiposity on TC and LDL-C. | Moderate |
| Marlatt et al. (2016), US ( | 367 | 14.7 years | 49% | Observational | To evaluate the relationship between both breakfast and fast food consumption on selected biomarkers and important cardiovascular and metabolic risk factors among healthy adolescents, and further examine the relationship between these dietary behaviors and the known risk factor clustering that occurs with the metabolic syndrome. | Body mass index (BMI) | The finding suggests that fast food and BC are associated with some metabolically important chronic disease risk factors in healthy adolescents. | Moderate |
| Moschiano et al. (2012), IT ( | 800 | 10≤ years | 40.6% | Observational | To assess the possible association between headache and specific habits and lifestyle factors. | Headache | Evidence of clear association between headache and irregular intake of meals (especially irregular breakfast) and sleep disturbance with significant differences when comparing subjects with and without headache. | Moderate |
| Papoutsou et al. (2014), CY, GR, DE, IT, SE, EE, BE, ES ( | 8,863 | 2 < 10 years | 48.8% | Cross-sectional | To investigate the relationship between breakfast routine and CVD risk factors in a multinational sample. | Blood glucose | Daily BC contributes to controlling school-aged children's weight and lipid profile. It promotes higher PA. | Moderate |
| Sese et al. (2012), ES, GB, FR, BE, DE, AU, HU, GR( | 826 | 14.8 years | 52% | Observational | To examine the associations of food behaviors and preferences with markers of insulin resistance and clustered metabolic risk factors score after controlling for potential confounders, including body fat in European adolescents. | TG | The results of this study indicate that insulin resistance and a clustered metabolic risk factors score are positively associated with food behaviors and preferences. Skipping breakfast explains part of the insulin resistance variance. | Moderate |
| Smith et al. (2010), AU ( | 2,184 | N/A | 53.3% | Longitudinal, observational; follow-up period: 21 years. | To examine longitudinal associations of breakfast skipping in childhood and adulthood with cardiometabolic risk factors in adulthood. | Mean weight | Participants skipping breakfast in both childhood and adulthood had larger waist circumferences, higher BMIs, and poorer cardiometabolic profiles than did those who reported eating breakfast at both time points. | Moderate |
| Walter (2014), US ( | 13,570 | 11–17 years | 51% | Cross-sectional | To study how lifestyle behaviors (skipping meals, water intake, tobacco use, alcohol use, and physical activity) and illness-related factors (depression, somatic complaints, insomnia, and obesity) work together to predict headache in an adolescent population. | Recurrent headache | Lifestyle behaviors and illness-related factors are associated with adolescent headache. | Moderate |
| Wennberg et al. (2015), SE ( | 889 | 16 years | 52.2% | Longitudinal, observational, follow-up period: 27 years. | To analyze whether poor breakfast habits in adolescence predict the metabolic syndrome and its components in adulthood. | Metabolic syndrome | Poor breakfast habits in adolescence predicted the metabolic syndrome in adulthood. Of the metabolic syndrome components, poor breakfast habits in adolescence predicted central obesity and high fasting glucose in adulthood. | Moderate |
| Wennberg et al. (2016), SE ( | 889 | 16 years | 52.2% | Longitudinal, observational; follow-up period: 27 years. | To investigate whether irregular eating of meals in adolescence predicts the metabolic syndrome and its components in adulthood, and if any specific meal is of particular importance. | Metabolic syndrome | Irregular eating of meals in adolescence predicted the metabolic syndrome in adulthood, but not independently of BMI and lifestyle in adolescence. Poor breakfast in adolescence was the only specific meal associated with future metabolic syndrome, even after adjustments. | Moderate |
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| Cooper et al. (2011), GB ( | 96 | 13.3 years | 62.5% | Randomized crossover design | To examine the effects of breakfast consumption on cognitive function, mood and blood glucose concentration in adolescent schoolchildren. | Modified Activation–Deactivation Checklist (AD ACL) (mood questionnaire) | BC improved the accuracy of responses on the visual search and Stroop tests. BC also improved response times on the more complex levels of the Sternberg paradigm, but did not have consistent effects on response times on the other tests conducted. BC was particularly beneficial for the more cognitively demanding tasks, whereas the simpler tasks could be performed to a similar level following breakfast omission. | Moderate |
| Defeyter and Russo (2013), GB ( | 40 | 14.2 years | 52.5% | Crossover design | To investigate the effect of breakfast consumption on cognitive performance and mood in adolescents, and any interaction that breakfast consumption might have with cognitive load. | Bond-Lader (mood scale) | Overall, it appeared that after breakfast, participants felt more alert, satiated, and content. Only in the recall task did performance appear to be significantly modulated by the interactive combination of the effect of BC and task difficulty, with improved performance at time two when the task was harder. | Moderate |
| Hjorth et al. (2016), DK ( | 710–828 | 9.9 years | 49% | Cluster-randomized crossover design | To examine the independent associations between weight status and lifestyle indicators with cognitive performance in 8- to 11-year-old Danish children. | Children’s Sleep Habits Questionnaire (CSHQ) | Normal weight children had higher cognitive performance compared to overweight/obese and underweight children. Daily BC was associated with higher cognitive performance in the d2-test, mathematics and/or sentence-reading test. | Moderate |
| Wesnes et al. (2003), GB ( | 29 | 12 years | 51.7% | Randomized, four-way crossover design | To determine the extent to which breakfast cereals would help to prevent declines in cognitive function in school children. | Cognitive drug research (CDR) test: Word presentation, immediate word recall, picture presentation, simple reaction time, digit vigilance, choice reaction time, spatial and numeric working memory, delayed word recall, word and picture recognition (attention, working memory, episodic secondary memory) | Skipping breakfast impairs attention and episodic memory, increasing in magnitude over the morning. Ingesting carbohydrates in the form of breakfast cereals reduces attention deficit by more than half and, for some aspects of memory (immediate word recall), prevents the deficit altogether. No benefits to attention or episodic memory with the glucose drink; in fact, greater initial impairment with the drink than with no drink or breakfast. Improvements in alertness and contentment did occur for 90 min following the glucose drink, but effects faded thereafter, whereas the benefits continued from the two cereals. | Moderate |
| Wesnes et al. (2012), GB ( | 1,386 | 10.59 years | 52% | Controlled trial | To determine the extent to which breakfast cereals would help to prevent declines in cognitive function in school children. | Power of attention | Power of Attention, a score reflecting the ability to focus attention and avoid distraction, was slowed by 7% in those children who did not have breakfast. The ability to sustain attention was also compromised, 7% less targets being detected in the digit vigilance task while 23% more false alarms were made. The ability to correctly identify pictures was impaired by 9% and speed was slowed by 9%. Finally, the response speed variability was 10% greater in children who did not have breakfast. These scores reflect every aspect of cognitive performance assessed, showing a comprehensive difference between the two groups. | Moderate |
| Widenhorn-Müller (2008), DE ( | 104 | 17.2 years | 46% | Randomized crossover design | To determine whether breakfast had effects on the cognitive performance and mood of high school students. | d2-Test (concentration speed and attention) | This crossover trial demonstrated positive short-term effects of breakfast on cognitive functioning and self-reported alertness in high school students. | Moderate |
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| Page et al. (2009), US, SK, HU, RO, CZ ( | 3,121 | 16.6 years | 54.7% | Cross-sectional | To investigate self-rated health (SRH) in Central and Eastern European (CEE) adolescents and determine its association with psychosocial functioning and other dimensions of adolescent health. | Self-Rated Health
| Self-rated Health appears to be associated with psychosocial functioning and other dimensions of adolescent health in CEE youth. | Moderate |
| Richards and Smith (2016), GB ( | 2,307 | 13.6 years | 51.5% | Longitudinal study with two cross-sections; follow-up period: 6 months. | To investigate the effects of consuming energy drinks and missing breakfast on stress, anxiety, and depression in a cohort of secondary school children. | The Diet and Behavior Scale | The current study has provided evidence to suggest that high stress, anxiety, and depression levels in adolescents are associated with breakfast omission. The relationship is unlikely to be causal in nature and there may be bi-directional mechanisms involved, with mental health also influencing whether or not breakfast is consumed. | Moderate |
| Smith (2010), GB ( | 213 | 8.11 years | 50.7% | Separate groups design | To examine the effects of consuming different breakfast cereals on parents' perceptions of the alertness, cognitive function and other aspects of the well-being of their children. | Questionnaire measures of well-being (alertness, cognitive difficulties, anxiety, depression, emotional distress, fatigue, somatic symptoms, positive/negative mood, symptoms, bowel problems). | Breakfast cereal consumption by children is associated with greater well-being. | Moderate |
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| Boschloo et al. (2012), NL ( | 605 | 14.81 years | 56% | Cross-sectional | To investigate whether adolescents who habitually skip breakfast have lower end-of-term grades than adolescents who eat breakfast daily. | BC | Study shows that breakfast skipping and school performance are related, partially mediated by attention. | Moderate |
| Burrows et al. (2017), AU ( | 4,245 | 11.33 years | 50.55% | Observational | To conduct secondary analysis to examine associations between a range of dietary behaviors and children's academic achievement. | Dietary behaviors | The findings demonstrate the association between dietary behaviors and higher academic achievement. Breakfast was only significantly associated with the academic domain of writing. | Moderate |
| Faught et al. (2017), CA ( | 28,608 | 14.1 years | 50.9% | Observational | To characterize the associations between health behaviors and self-reported academic achievement. | Questionnaire (academic achievement, PA, healthy eating habits, sleep, screen time, body weight [BW]-status, socioeconomic status [SES]) | The present findings demonstrate that lifestyle behaviors are associated with academic achievement. | Moderate |
| Lien (2007), NO ( | 7,305 | 15–16 years | 50.6% | Cross-sectional survey | To examine the relationship between mental distress, academic performance and regular breakfast consumption across gender and immigration status. | Average grade for mathematics, written Norwegian, English and social science. | The implications of skipping breakfast on mental distress and academic performance are stronger for boys than girls and stronger for Norwegians than immigrants. | Moderate |
| Littlecott et al. (2016), GB ( | 3,093 (baseline), 3,055 (follow-up) | 9–11 years | 50.8% (baseline) 49.5% (follow-up) | Observational | To examine the link between breakfast consumption in 9- to 11-year-old children and educational outcomes obtained 6–18 months later. | Educational outcomes: scholastic assessment test (SAT)-scores | Significant positive association between self-reported BC and educational outcomes. | Moderate |
| Ptomey et al. (2016), US ( | 698 | 7.5 years | 50.5% | Cluster-randomized controlled trial | To determine whether breakfast consumption or content affects academic achievement measured by standardized tests. | Wechsler individual achievement test (3-components) (WIAT-III) | Both BC and breakfast content may be associated with improved standardized test performance in elementary school students. | Moderate |
| Sampasa-Kanyinga & Hamilton (2017), CA ( | 9,912 | 15.2 years | 48.6% | Observational | To investigate the association between breakfast consumption and school connectedness and to extend previous research on the association between breakfast consumption and academic achievement. | School connectedness (questionnaire) | Provides supporting evidence for the association between regular BC and higher school connectedness and academic performance. | Moderate |
| Stea and Torstveit (2014), NO ( | 2,432 | 15–17 years | 51% | Cross-sectional study | To examine the associations between several lifestyle habits and academic achievement in adolescent girls and boys. | Self-reporting questionnaire (dietary, PA, smoking, and snuffing habits, academic achievement) | Regular meal pattern, intake of healthy food items and being physically active were all associated with increased odds of high academic achievement, whereas the intake of unhealthy food and beverages, smoking cigarettes and snuffing were associated with decreased odds of high academic achievement. | Moderate |
Compilation of results from the studies
| First author | Cognitive performance | Academic achievement | Morbidity risk factors | QoL/well-being |
|---|---|---|---|---|
| Hallstrom et al. ( | N/A | N/A | + | N/A |
| Marlatt et al. ( | N/A | N/A | + | N/A |
| Moschiano et al. ( | N/A | N/A | + | N/A |
| Papoutsou et al. ( | N/A | N/A | + | N/A |
| Sese et al. ( | N/A | N/A | + | N/A |
| Smith et al. ( | N/A | N/A | + | N/A |
| Walter ( | N/A | N/A | + | N/A |
| Wennberg et al. ( | N/A | N/A | + | N/A |
| Wennberg et al. ( | N/A | N/A | + | N/A |
| Cooper et al. ( | + | N/A | N/A | N/A |
| Defeyter and Russo ( | + | N/A | N/A | N/A |
| Hjorth et al. ( | + | N/A | N/A | N/A |
| Wesnes et al. ( | + | N/A | N/A | N/A |
| Wesnes et al. ( | + | N/A | N/A | N/A |
| Widenhorn-Müller ( | +/− | N/A | N/A | N/A |
| Page et al. ( | N/A | N/A | N/A | + |
| Richards and Smith ( | N/A | N/A | N/A | + |
| Smith ( | N/A | N/A | N/A | + |
| Boschloo et al. ( | + | + | N/A | N/A |
| Burrows et al. ( | N/A | + | N/A | N/A |
| Faught et al. ( | N/A | + | N/A | N/A |
| Lien ( | N/A | + | N/A | + |
| Littlecott et al. ( | N/A | + | N/A | N/A |
| Ptomey et al. ( | N/A | + | N/A | N/A |
| Sampasa-Kanyinga & Hamilton ( | N/A | + | N/A | N/A |
| Stea and Torstveit ( | N/A | + | N/A | N/A |
| Number of studies indicating positive effects | 7 (100%) | 8 (100%) | 9 (100%) | 4 (100%) |
| Number of studies indicating negative effects | 1 (14%) | 0 (0%) | 0 (0%) | 0 (0%) |
| Number of studies indicating no effects | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
+ = positive effect, − = negative effect, 0 = no effect, N/A= not applicable.
Fig. 1Flow chart of the work process: PRISMA 2009 Flow Diagram.
Excluded studies because of low quality, with reasons for exclusion
| Exclusion no. | First author (year) | Title | Reason for low-quality rating |
|---|---|---|---|
| 1 | Adolphus et al. (2015) ( | The relationship between habitual breakfast consumption frequency and academic performance in British adolescents | 1, 6 |
| 2 | Benton and Jarvis (2007) ( | The role of breakfast and a mid-morning snack on the ability of children to concentrate at school | 1, 3, 5 |
| 3 | Karatzi et al. (2014) ( | Dietary patterns and breakfast consumption in relation to insulin resistance in children: The healthy growth study | 1, 7 |
| 4 | Kral et al. (2012) ( | Effects on cognitive performance of eating compared with omitting breakfast in elementary schoolchildren | 1, 3, 5 |
| 5 | López-Sobaler et al. (2003) ( | Relationship between habitual breakfast and intellectual performance (logical reasoning) in well-nourished schoolchildren of Madrid (Spain) | 2 |
| 6 | Maffeis et al. (2012) ( | Breakfast skipping in prepubertal obese children: Hormonal, metabolic and cognitive consequences | 5 |
| 7 | McIsaac et al. (2015) ( | The association between health behaviors and academic performance in Canadian elementary school students: A cross-sectional study | 1, 6 |
| 8 | Overby et al. (2013) ( | Self-reported learning difficulties and dietary intake in Norwegian adolescents | 1, 3 |
Matters causing low-quality rating: (1) No RCT, (2) lack of adequate control group(s), (3) lack of control for confounders, (4) insufficiently described experimental design, (5) insufficient statistical power, (6) non-relevant outcome measures, and (7) non-consistency between reported results and conclusions.