Systematic Review of Randomized
Controlled Trials: diet patterns and
food in sleep context.
Revisão Sistemática de Ensaios Clínicos
Randomizados: padrões alimentares e
alimentos no contexto do sono.
Gabriela Loewe
ORIENTADO POR: PROF. DOUTOR VITOR HUGO DA COSTA GOMES MOREIRA TEIXEIRA COORIENTADO POR: DR. JOÃO ALMEIDA LOPES
REVISÃO SISTEMÁTICA
1.º CICLO EM CIÊNCIAS DA NUTRIÇÃO | UNIDADE CURRICULAR ESTÁGIO
FACULDADE DE CIÊNCIAS DA NUTRIÇÃO E ALIMENTAÇÃO DA UNIVERSIDADE DO PORTO
TC
Abstract
Numerous epidemiological studies show that both the lack of sleep and sleep disorders affect a large number of people in the world and may lead to serious damage to the general health. Thus, it is an important goal to target health interventions to improve sleep quality, including nutritional interventions. The main objective of this systematic review is to thoroughly explore the preeminent scientific literature available, insofar as the impact of dietary patterns and dietary interventions on sleep quality is concerned. A systematic search was performed considering Pubmed, Web of Science and Scopus databases. A total of 938 were identified, and after removing duplicates, 404 were screened. Of these, 363 were excluded after title and abstract screening, while 26 studies met the eligibility criteria. After the selection process was complete, 19 studies were available for qualitative synthesis and risk of bias assessment. Eight of the included studies evaluated the effect of a specific food on sleep, while eleven focused on dietary pattern interventions. Studies investigating dietary patterns seem to underline the importance of both balance and quality pertaining macronutrients, especially aiming towards an improvement of the slow wave sleep. Studies testing cherry obtained significant improvements regarding sleep efficiency, as well as those who tested kiwi and oysters. In brief, several factors, including quality and balance of macronutrients, may improve sleep quality, especially when considering proteins and carbohydrates.
Resumo
Estudos epidemiológicos mostram que a falta de sono e os distúrbios do sono afetam um grande número de pessoas no mundo e podem causar sérios danos à saúde geral das pessoas afetadas. Melhorar a qualidade do sono pode ser visto como um importante alvo de intervenções de saúde, inclusive nutricionais. O principal objetivo desta revisão sistemática é explorar minuciosamente a melhor literatura científica disponível sobre o impacto dos padrões e intervenções alimentares na qualidade do sono. Uma pesquisa sistemática foi realizada no Pubmed, Web of Science e Scopus. Um total de 938 foram identificados e, após a remoção de duplicatas, 404 foram rastreados. Destes, 363 foram excluídos após triagem de título e resumo. 26 estudos preencheram os critérios de elegibilidade. Após a conclusão do processo de seleção, 19 estudos estavam disponíveis para síntese qualitativa e avaliação do risco de viés. Oito dos estudos incluídos avaliaram o efeito de um alimento específico no sono, enquanto onze focaram em intervenções nos padrões de dieta. Estudos que investigam padrões alimentares parecem trazer à luz a importância do equilíbrio e da qualidade dos macronutrientes, principalmente no que se refere à melhora do slow wave sleep. Estudos que testaram a cereja obtiveram melhorias significativas para a eficiência do sono, bem como aqueles que testaram kiwi e ostras. Em conclusão, parece haver uma série de fatores, incluindo a qualidade e o balanço de macronutrientes ingeridos que podem influenciar na melhoria da qualidade do sono, principalmente quando se trata de proteínas e carboidratos.
Palavras-chave: dieta; hidratos de carbono; cereja; Comida; índice glicêmico; kiwi; sono.
List of abbreviations and acronyms
BMI – Body Mass Index HGI – High Glycemic Index LGI – Low Glycemic Index PSG - Polysomnography
PSQI – Pittsburgh Sleep Quality Index QOL – Quality of Life
REM – Rapid Eye Movement
RCTs – Randomized Controlled Trials SE – Sleep Efficiency
SWS – Slow Wave Sleep SOL – Sleep-Onset Latency
Summary
Abstract ... i
List of abbreviations and acronyms ... iii
Summary ... iv
1.Introduction ... 1
2. Methodology ... 3
2.1 Design and registration ... 3
2.2 Search strategy ... 4
2.3 Eligibility Criteria ... 4
2.4 Studies’ selection and data extraction ... 5
2.5 Risk of bias assessment ... 6
3. Results ... 7
3.1 Study selection and characteristics ... 7
3.2 Risk of bias of included studies analysis ... 8
3.3 Included studies ... 8
3.3.1 Sleep quality Assessment ... 8
3.3.2 Participant demographics ... 9
3.3.3 Type of Intervention ... 9
4. Discussion ... 10
4.1 Diet patterns and sleep quality ... 11
4.1.1 Calorie Restriction and sleep quality ... 11
4.1.2 Macronutrients ... 12
4.2 Specific Foods and sleep quality ... 14
5.Conclusion ... 15
1.Introduction
Sleep is defined as one of the major key factors influencing health and wellbeing alongside with nutrition, regular exercise and non-smoking(1). Numerous
epidemiological studies have shown that both the lack of sleep and sleep disorders may affect a large number of people in the world, leading to serious damage to the general health(2). The promotion of adequate sleep has been included as a
health and funding priority in Healthy People 2020 in the United States of America(3).
It is well established, that a high prevalence of acute sleep deprivation or lack of sleep quality is consistently reported within the general adult, adolescent and elderly populations and also physically active populations(4-7). Approximately
40 million people in the United States of America suffer from chronic long-term sleep disorders(8). In a cross-national study, an average of 24.2% of the total
European population reported sleep issues (9). A study analyzing the prevalence of
sleep disorders in over 20,000 Dutch patients reported an alarming prevalence of 27.3% sleeping disorders, including insufficient sleep time, with 21.2% and 33.2% of being reported by male and females, respectively(10).
It is recognized that sleep, specially the lack of it and /or its fragmentation, is associated with hormonal and metabolic changes, namely macronutrient modulation(11-15). In fact, a single night of partial sleep deprivation might impair
fasting insulin sensitivity(15). Furthermore, sleep restriction seems to significantly
increase ghrelin levels which are associated with higher energy intake(16).
increased intake of high fat foods(18), sugars(19) and more frequent snacking(16),
which may increase total daily energetic intake(20-25).
Sleep quality enhancement may be deemed an important item when considering other important lifestyle and health interventions, i.e. physical exercise, cognitive-behavioral treatments, educational interventions, reflexology, light therapy, pharmacological interventions, isolated compound supplementation (i.e. melatonin and 5- hydroxytryptophan), and off course, medical nutritional therapy and sleep-promoting foods(26, 27). Interestingly, sleep may affect our
dietary intake, while simultaneously nutrition is also a major factor impacting both sleep quality and duration.
Sleep quality is not clearly defined in the literature, thus frequently different criteria are used to characterize and measure this important parameter. Therefore, one should choose wisely the most suitable criteria bearing in mind the methods, aiming to obtain results with accuracy, sensitivity and specificity. All methods display strengths and weaknesses, thus, they should be combined and adapted to each specific context. Sleep quality may be screened applying objective measurements, i.e. polysomnography (which screens the amount of rapid eye movement (REM) plus the amount of slow wave sleep (SWS)), actigraphy (providing information about sleep-onset latency (SOL) as well as sleep efficiency (SE), duration of sleep and total sleep time (TST)), or with subjective measurements, applying questionnaires, either structured (such as the Pittsburgh Sleep Quality Index) or not.(28, 29).
Nutrition is a very broad field of investigation when aiming to improve sleep quality. There are complex interplays between nutrients, foods and dietary patterns, which suggests that no single element of a diet may account for the
dietary effect on any health outcome. In fact, recent advances in nutritional sciences have shown that food compounds act synergistically, thus dismissing a reductionist approach focused on isolated nutrients. Bearing this in mind, a systematic and holistic approach should be considered. When trying to explain interactions between nutrition and health outcomes, i.e. sleep quality, these may better modeled considering multicausal nonlinear relations, for example by dietary patterns or foods instead of using specific nutrients(30, 31).
The main objective of this systematic review is to thoroughly explore the preeminent scientific literature available, insofar as the impact of dietary patterns and dietary interventions on sleep quality is concerned. Furthermore, the data will be analyzed and critically synthesized to further provide insights regarding possible applications to the healthy population, based on the quality of the retrieved studies.
2. Methodology
2.1 Design and registration
This study was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines(32) and was registered
through the International Prospective Register of Systematic Reviews (PROSPERO) under registration no. CRD42020186837.
2.2 Search strategy
A systematic search was performed considering 3 scientific databases (Pubmed, Web of Science and Scopus) from their inception to April 24, 2020. The literature search was carried out between January and May 2020 with the assistance of an experienced librarian.
The main search strategy, performed on PubMed, was conducted by searching for selected keywords and medical subject headings combined with Boolean operators in the titles/abstracts (tiab) and MeSH terms (mh) specific to sleep, diet and humans: "Humans"[MeSH]) AND "Sleep"[MeSH]) AND "Diet"[MeSH]. Regarding Scopus, since the search box is different from PubMed, we manually replicated the search in the form of natural language: (nutrition OR nutrients OR food OR diet OR eating) AND (humans AND adults) AND (sleep AND (quality OR duration OR hygiene OR efficiency). On Web of Science we used the terms: (nutrition OR nutrients OR food OR diet OR eating) AND (humans AND adults) AND (*sleep*) AND (sleep quality OR sleep duration OR sleep hygiene OR sleep efficiency).
The reference list of retrieved experimental trials and included articles were screened to identify potential additional studies.
2.3 Eligibility Criteria
Briefly, studies were eligible for this systematic review if they investigated the effect of specific foods or diet patterns on sleep, were Randomized Controlled
Trials (RCTs) or Randomized Trials with crossover design, conducted in healthy adult humans over 18 years old and under 65 years old from both genders, written in English, and published until April 24, 2020.
Studies were excluded if they evaluated the effect of supplements on sleep, were not written in English, were conducted in children or adolescents or adults with specific conditions (e.g. obesity or overweight, HIV, cancer, diabetes, cardiovascular disease; anxiety, depression or other psychological situation, such as bipolar behavior or forensic patients; bariatric surgery; organ transplant patients; dermatological diseases, such as eczema, psoriasis; use of other airway devices for sleep apnea (e.g. CPAP); hormone or hemodialysis therapy). The following article types were excluded: editorials, systematic reviews, letters to the editor, commentaries, duplicated publications.
2.4 Studies’ selection and data extraction
Following the initial search in each database, all records found were transferred to Endnote version X9 and a first removal step was performed (duplicated studies). Secondly, the articles’ titles and abstracts were screened to assess eligibility according to the previously described criteria, by two reviewers (GL and FT), being analyzed afterwards. In case of disagreement, the two reviewers discussed the merits of selection and if a consensus could not be
reached a third reviewer (VHT) was consulted.
Selected studies that fulfil the inclusion criteria were accessed, in full, and critically appraised, with the article data being extracted into an Excel
spreadsheet file by 1 author (GL) and reviewed for compliance by the other author (FT) using a customized form. If required, differences were debated with the intervention of a third reviewer.
Data extraction included 1) study characteristics (author, reference, etc.); 2) participant characteristics (sample size, sex, etc.); and 3) methodological characteristics (length of intervention, methods to assess sleep, outcomes, etc.) and 4) other characteristics (risk of bias, etc.).
2.5 Risk of bias assessment
This analysis was performed on RCTs, in which participants were randomly allocated on both intervention or control group. Albeit RCTs being considered the research gold standard, they are also subject to bias, either due to sample bias selection, measurement bias of the variables analyzed, or due to inherent difficulties associated with controlling other confounding factors.
Therefore, an assessment of the risk of bias was independently performed by 2 reviewers (GL and FT) according to the Cochrane collaboration risk-of-bias tool (Cochrane Handbook for Systematic Reviews of Interventions version 6.0)(33).
The following parameters were considered: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and other sources of bias. When disagreements between the two reviewers (GL and FT) were not solved by consensus, a third reviewer (VHT) reviewed the paper and yielded a decision.
“some concerns.” Studies were not excluded on the basis of risk-of-bias assessment score. Instead, quality appraisal was used to identify studies whose results should be carefully interpreted.
3. Results
3.1 Study selection and characteristics
The study search, identification, and selection process using the PRISMA flow diagram is summarized in figure 1. After searching 3 databases, 5676 studies were identified: 1127 at PubMed, 3846 at Web of Science and 2990 at Scopus. Filters, such as: articles published between January 2010 and April 2020, and English language, were applied independently according to the database. The other filters: RCTs, Humans, adults +18 years old, as well as source type being journals (Scopus) were applied manually according to each database. A total of 938 were identified, and after removing duplicates via Endnote, 404 were screened. Of these, 363 were excluded after title and abstract screening. The remaining 41 articles were screened in full text and 26 studies met the eligibility criteria (Figure 1 – Flow Chart). Once the selection process was complete, 19 studies were available for qualitative synthesis.
All 26 articles considered for eligibility were full-text read by two reviewers and the data was extracted to an excel spread sheet independently (in which information concerning sample, demographic characteristics of the sample, study design, intervention description, protocol duration, primary outcome, instruments to assess sleep quality, correlation/association and main conclusions, were
extracted). 7 studies were excluded for not meeting the eligibility criteria. The main characteristics of the 19 included studies is reported in Table 1 and 2. The 19 studies comprised a total of 943 adults. Of the 19 trials, seven(34-40) reported
outcomes on SOL, three(36-38) on SWS, eight(6, 34-36, 39-42) on SE, nine(6, 35-37, 39, 41-44)
on TST, two(37, 42) on REM, two on Actual Sleep Time(6, 40), two(6, 41) on Time in Bed,
three(36, 45, 46) on sleepiness, two(45, 47) on Sleep Duration and six(43, 44, 48-51) on
subjective sleep quality, and the studies often used more than one of the parameters mentioned above.
3.2 Risk of bias of included studies analysis
Each domain was analyzed independently by two reviewers with regard to the risk of bias, and the overall judgment of each study was decided by reaching a consensus. No study was excluded, even those considered to be at high risk of bias (n=5)(35, 42, 45, 47, 49). The results of the risk of bias analysis of the studies
included in this review are illustrated in a weighted summary plot (Figure 2) and in a traffic light plot (Figure 3), using the robvis tool(52). The quality of the included
studies was predominantly suboptimal. Eight of the 19 trials were considered low risk, 6 trials had some concerns for risk, and 5 trials were considered at high risk of bias.
3.3 Included studies
3.3.1 Sleep quality Assessment
quality (Table 1 and Table 2). Eleven studies used at least one objective assessment method, such as polysomnography alone (PSG, n=3) (37, 39, 42) or
actigraphy (n=1)(40), while 3 studies used only subjective tools, such as the
Pittsburgh Sleep Quality Index (PSQI)(47, 51) or other (49). Most of the investigations
used mixed methodologies, with subjective assessment tools with actigraphy (n=7)
(6, 34, 40, 41, 43-45) or with PSG (n=3)(35, 38, 48), or yet with a subjective assessment tool
together with an objective tool different than those cited above (n=2)(36, 46).
3.3.2 Participant demographics
The majority of the included studies (n=9) examined adults (aged 25 to 44), only two studies included young adults (aged 19 to 24) and three middle aged individuals (45 - 64 years), however some studies analyzed mixed age individuals (n=5).
3.3.3 Type of Intervention
Eight of the included studies evaluated the effect of a specific food on sleep
(34-36, 40-44), while the remainder focused on dietary pattern interventions (6, 37-39, 45-51). The duration of the intervention protocols lasted from < 1 week (n=2)(37, 42),
between 1-3 weeks (n=8) (6, 36, 38-41, 45, 46), between 3-5 weeks (n=3) (35, 44, 49),
between 5-8 weeks (n=1)(48), 12 weeks (n=4)(34, 43, 50, 51) and a study was designed
3.3.4 Findings
Studies that evaluated energy restriction found no association or no improvements in parameters associated with sleep quality (37, 51), with the
exception of one study (47), in which the energy restriction significantly improved
sleep duration. The current body of evidence, regarding the macronutrient influence on sleep quality, yields inconsistent and equivocal data. In fact, some did not find a significant impact on sleep duration or subjective sleep quality (45, 48), while others reported that a high-carbohydrate diet significantly shortened
wake times(50), decreased sleep time(6), or was not associated with more
arousals(38). Other specific diets, such as the low FODMAPs and sodium diets, were
associated with an improvement on subjective sleep quality and reduced sleepiness, respectively(46, 49).
Furthermore, some inconsistency was also observed, regarding studies that evaluated specific sleep-inducing foods. However, it should be highlighted that both studies testing cherry obtained significant improvements for SE(40, 41), as well
as those who tested kiwi(35) and oysters(34).
4. Discussion
We systematically reviewed and summarized the results of the studies investigating the effects of specific foods and dietary patterns regarding sleep.
4.1 Diet patterns and sleep quality
Nutrients and components that promote sleep, such as tryptophan and melatonin, are widely discussed(53, 54). However, it is unlikely that a single
component of the diet may account for the whole spectrum of observed effects of a diet when improving sleep quality(30). Studies investigating dietary patterns
seem to bring to light the importance of both the balance and the quality of macronutrients in this context, especially regarding improvements on SWS(38).
4.1.1 Calorie Restriction and sleep quality
Dieting is widely discussed regarding the management of sleep disorders(38).
A calorie restriction (CR) diet (25% CR from baseline ad libitum energy intake) for 2 years increased sleep duration compared to an Ad libitum (AL) diet in 200 healthy adults(47). As the CR group lost more weight (7.6 vs. 0.5 kg), the effect on
sleep quality may be due to weight loss and not due to energy restriction, in accordance with other study (28). In line with this explanation, when a “normal”
diet was compared to a CR diet (from 300 to 500 kcal/day, combined with two days/week of fasting for 3 months)(51), no significant differences were found
between groups in respect to sleep quality, despite a higher weight loss in the CR group (51). A group of 14 healthy individuals was submitted to four different
conditions: (1) high caloric intake with regular sleep and (2) with total sleep deprivation, and (3) low caloric intake with regular sleep or (4) with total sleep deprivation. No significant association was found between energy intake and sleep conditions(37). These results suggest that these small observed improvements on
4.1.2 Macronutrients
Carbohydrate intake has been linked to increases on plasma concentrations of tryptophan and its transport by insulin, so that the availability for synthesis of serotonin and melatonin is greater (55, 56). Regarding the benefit of carbohydrates
to improve sleep quality, whereas some studies find a positive effect(7, 50), others
observe no significant differences, when comparing to diets with lower carbohydrate content(45, 48). Lindseth and Murray found that a high carbohydrate
(HC) diet (80% of total energy intake from carbohydrate) for 4 weeks was significantly associated with shortened wake times, when comparing to high protein diet (45% of total energy intake from protein), high fat diet (65% of total energy intake from fat) or control diet (50). On the other hand, when the effect of
the amount of carbohydrate in sports drinks (low carbohydrate vs. high carbohydrate) was tested in athletes, the results revealed that only the drink with less carbohydrate content displayed improvements on sleep measures(6). In this
context, a post-workout meal with high glycemic carbohydrates appeared related to better TST and SE when compared to a low glycemic index meal(39). However,
athletes must be careful regarding the intake of carbohydrate-electrolyte beverages, especially when caffeine is included, since it may damage the level of
SE and TST(42).
Consistent with the hypothesis discussed earlier, a study found no significant association between the amount of carbohydrate intake (high vs. low) and sleep duration. However, the body mass index of the participants appeared as a possible confounding factor in this relationship, suggesting that the effect in
sleepiness or sleep duration is, at least, partially explained by BMI and not by the amount of carbohydrates consumed (45). Still, it should be noted that the daily
dietary intake was not controlled and that a control group was not considered, which impaired the overall quality of this study.
Taking into consideration the putative effect of carbohydrates on sleep latency, it would be interesting to analyze how a ketogenic diet may impact sleep. In this context, Iacovides et al. found no significant difference in sleep quality parameters between a ketogenic diet and a HC diet. However, the small sample size of the study may have affected the results, due to power analysis issues (48).
Macronutrients proportions have also been tested (38), with results pointing
towards a relationship between sleep quality and the quality of the ingested macronutrients. St-Onge et al. demonstrated that a low nutritional quality diet (high in saturated fat or high in sugar) seems to worsen the sleep quality (38), while
greater fiber intake predicted more SWS. In another study, a Low-FODMAP diet has been shown to improve overall sleep quality and trouble falling asleep when compared with a modified diet (avoiding trigger foods, alcohol and caffeine in excess), since some of the components present in FODMAPs rich foods (such as lactose, fructose, sorbitol or mannitol) are frequently found in less nutritional density foods, it may be assumed that a diet low in FODMAPs tends to, eventually, lower the intake of low nutritional quality food(49). Beyond this hypothesis to
improve sleep quality, we propose that the quality of the macronutrients ingested, might be the major impacting factor. Additionally, in a group of 54 men, a sodium-restricted diet (maximum sodium intake of 3g/day) was significantly associated with reduced sleepiness(46).
4.2 Specific Foods and sleep quality
In the context of sleep-inducing foods there is a limited but growing body of evidence for potential interventions, although most of the research quality remains moderate-weak. It is important to note that only two of the eight studies included in this review had a low risk of bias assessment, and two had a high risk.
Cherries have allegedly a sleep-inducing effect due to their phenolic components and significant amounts of tryptophan and melatonin, specially tart cherries(57). An intervention with tart cherry juice supplementation (2 servings of
30 mL/day) resulted in an increased time in bed, increased total sleep duration (+34 min) and improved SE (82.3%)(41). In a very similar study design, considering
a group of 30 individuals, a cherry-based product (2 servings of 125 mL/day) showed improvements in actual sleep time and SE (77.6%). Sleep efficiency also appears to be ameliorated through other foods, such as oysters, and this is explained by mechanisms involving zinc(34). Similarly, kiwi intake before bed
showed positive effect on SE, and also in subjective quality sleep measures. However, it is known that the absorption of serotonin from foods does not cross the blood-brain barrier, which hampers the practical application of this intervention(35).
In a less conventional and more daring approach, we found three studies which dealt with very specific food components. Firstly, an enzyme-treated asparagus extract improved insomnia symptoms, and tend to improve TST(43). In
the same line, PS rhizome extract (500mg/day) also appeared to decrease insomnia symptoms and improve TST(44). Another study investigated the intake of
associated with SWS(36). Nevertheless, these studies used very small doses to be
considered nutritional interventions, so in practical terms they may not be promising.
We may cite as one of the main limitations of this review the fact that the sample of included studies consisted of only adult non-diseased populations, which may have precluded semi-relevant articles involving less serious diseases (such as obesity) or involving younger populations.
5.Conclusion
Currently, there is no sufficient evidence to suggest specific foods or diets to improve sleep quality, in fact, weight management is possibly the most effective approach. In brief, several factors, including quality and balance of macronutrients, may improve sleep quality, especially when considering proteins and carbohydrates. Future research is warranted to investigate both subjective and objective measures to provide further insights on this topic.
Acknowledgments
I would like to express my gratitude to Doctor Filipe Teixeira, who participated in a large part of the development of this monograph, his contribution was extremely helpful in all the work.
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Appendices Summary Appendix A ... 22 Appendix B ... 23 Appendix C ... 24 Appendix D ... 25 Appendix E ... 27
Appendix A
Figure 1. Appendix A. PRISMA Flow Diagram. Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flow diagram indicating the number of records identified, screened, included and excluded.
Appendix B
Appendix C
Appendix D. Table 1. Diet Patterns and Sleep. Study Number randomi zed Participants Demographics (Age;Gender) Study
Design Intervention Description Type of diet Protocol Durati on
Primary
Outcome Instrument to assess sleep qualit y Findings Conclusion Teng et al.(51) (2011) 25 Age 58.8 ±
5.1; Only men RCT Control or FCR group (two days Muslim fasting + calorie restriction) + dietary counseling Fasting plus calorie restricti on 12
weeks Mood, quality of life, sleep quality, depressio n and stress Pittsburgh Sleep Quality Index (PSQI) Both groups showed significant improvements in sleep quality (p<0.05)*, however, no significant difference was observed between groups There were no significant changes in sleep quality and stress level between the groups as a result of the intervention Herzo g et. al.(37) (2012) 14 Age: 23.3 ± 0.5 years (MEAN ± SEM) Rando mized, balanc ed cross-over 1- high caloric (HC) intake + regular sleep 2- low caloric (LC) intake + regular sleep 3- HC + total sleep deprivation (TSD) 4- LC + TSD High caloric or low caloric 2 days Memory consolidat ion, plasma glucose and sleep recordings Polysomnogr aphy (Digital electroence phalography ) No association (p≥0.73) was found between energy intake and any sleep condition (SWS, TST, SOL, REM onset latency) Changes in daytime energy intake may not affect sleep architecture as revealed by the EEG recordings Nehm e et. al.(58) (2014) 24 Age: 30.8 ±
5.5; Only men RCT, DB 1st week: no change in night meal food composition . 2nd week: carbohydrat e intake increased in night meal 3rd week: protein intake increased in night meal Increase d carbohy drate and increase d protein 3
weeks Sleep duration, sleepiness Actigraph devices (Ambulatory Monitoring, Ardsley, NY) + Karolinska Sleepiness Scale No significant differences were found (p=0.98) among conditions related to sleep duration and diet. Repeated-measures ANOVA showed a significant increase in sleepiness for all three conditions (p<0.01) at 3am and it seems to be mediated by BMI The effect of the night meal content on sleep duration seems to be mediated by BMI. A carbohydrate-rich meal increased the duration of sleep in obese individuals, and may influence sleepiness Eswar an et al. (49) (2016) 92 Placebo: 42.6 years (median);65 women RCT, prospe ctive, single-center , single-blind. Diet 1: Low FODMAP diet or Diet 2: Modified diet - small frequent meals, avoid trigger foods, and avoid excess alcohol and caffeine (mNICE) Low FODMAP diet or Modified diet (mNICE) 4
weeks Quality of life, anxiety, depressio n, activity impairme nt and sleep quality. SLEEP-50 questionnair e (adapted) Low FODMAP diet improved overall sleep quality (95% CI, 1.62 to -0.10) and trouble falling asleep (95% CI, -0.65 to -0.03) when compared to diet 2. Between groups differences were not significantly different Low-FODMAP diet experienced improvements in overall sleep quality and trouble falling asleep when compared with normal diet
Lindse th & Murra y(50) (2016) 36 Age: 20.9 years of Age (SD = 1.9) Rando mized, within -subjec ts, crosso ver study 1 - High protein diet (HP) 2 - High carbohydrat e diet (HC) 3- High fat diet (HF) 4- Control High protein or high carbohy drate 12 weeks (4 days interv ention with 2-week washo ut interv als) Sleep measures, serotonin, glucose and lipid levels Actiwatch (Royal Philip; Bens, OR) + Pittsburgh Sleep Quality Index (PSQI) HC intake was significantly associated (p<0.001) with shorted wake times. HF intake was significantly associated with better sleep (p<0.05) compared to other diets (Tukey’s post hoc test) The proportions of specific macronutrient s in a diet may influence a person’s sleep quality, by either inducing or reducing sleep time Martin et. al.(47) (2016) 220 Age: 37.9 ± 7.0;69.7% female Rando mized, multisi te, parall el-group, clinica l Trial 1: Calorie Restriction (CR) 2: Ad libitum (AL) with the ratio 2:1 in favor of CR group Calorie Restricti on 2
years Mood, quality of live (QOL), sleep, sexual function Pittsburgh Sleep Quality Index (PSQI) Compared with the AL group, the CR group has significantly improved sleep duration at month 12 (p=0.03) 2 years of CR is unlikely to negatively affect sleep in healthy adults; rather, it is likely to provide some improvement St-Onge et. al.(38) (2016) 26 Age: 35.1 ± 5.1;14 men and 13 women Rando mized, crosso ver, inpati ent study 2 phases of 5 nights: short or habitual sleep. During the first 4 days, participants consumed a controlled diet; on day 5, food intake was ad libitum Controll ed diet (31% fat, with approxi mately 7.5% from saturate d fat, 53% carbohy drates, and 17% protein) 5 weeks (10 days interv ention with 3-week washo ut period ) Sleep
patterns Sleep Disorders Inventory Questionnai re + Epworth Sleepiness Scale + Pittsburgh Sleep Quality Index + Polysomnogr aphy (PSG) Sleep after ad libitum eating had less SWS (p=0.0430) and longer SOL (p=0.0085). Greater fiber intake predicted more SWS (p=0.0286). Percent of energy from saturated fat predicted less SWS (p=0.0422) and higher percent of energy from sugar (p=0.032) and some carbohydrates was associated with arousals (p=0.0481)
Low fiber and high saturated fat and sugar intake is associated with lighter, less restorative sleep with more arousals Killer et. al.(6) (2017) 13 Age: 25.0 ±
5.8 years Randomized counte rbalan ced, crosso ver, DB 1: (HCHO) high carbohydrat e (HC) beverage before and during exercise + HC and protein recovery; beverage after exercise 2: Control (CON): lower carbohydrat e and protein beverages before, during and after training High carbohy drate or low carbohy drate before, during and after intensifi ed training 18 days (2 x 9-day period s) Sleep markers, mood, exercise performa nce Actiwatch and Fragmentati on Index. (MotionWat ch 8, CamNtech, Cambridges hire, UK) Actual sleep time was significantly higher in CON than HCHO throughout intensified training (p=0.03). For both diets percentage TST fell during intensified training (p<0.05), time in bed increased (p=0.02) and SE decreased (p<0.05) Throughout intensified training conditions low carbohydrate meals before, during and after training may be useful to enhance actual sleep time
Fiori et. al. (46) (2018) 54 Placebo: 46.5 ±7.4 y, Diet: 45.2 ±8.3 y, Diuretic 42.9 ±10.6;Only men RCT, three-arm, parall el, placeb o-contro lled, explan atory 1: Placebo 2: Sodium-restricted diet: placebo pill + sodium-restricted diet 3: Diuretic: spironolacto ne + furosemide Sodium-restricte d diet (maxim um sodium intake of 3g per day) 1
week Change in apnea-hypopnea index (AHI), sleep quality. Epworth sleepiness scale and Sleep Apnea Testing - Somnocheck Effort (Weinmann GmbH, Hamburg, Germany) Sleepiness was significantly reduced only in the sodium-restricted diet group (p<0.007) for the time x group interactions. Sodium-restricted diet intervention to reduce bodily fluid content in men may promote a limited decrease of sleepiness Vlaho yianni s et. al. (39) (2018) 10 Age: 23.2 ±
1.8;Only men Randomized, counte rbalan ced, crosso ver, DB, trial Sprint interval training (ST) + Post-exercise meal: 1. HGI - High glycemic index or 2. LGI - low glycemic index High glycemi c post-exercise meal or Low glycemi c post-exercise meal 18
days Sleep quality and quantity, next day's exercise performa nce Polysomnogr aphy (PSG) TST (p=0.019) and SE (p=0.049) were greater in the HGI trial compared to the LGI trial (p<0.05). SOL in the HGI trial found to be decreased by four-fold compared to the LGI trial (p=0.026). A moderate to strong correlation was found between the difference in TST between groups (p<0.05) A HGI meal, following a single spring interval training session, can improve both sleep duration and SE, while reducing SOL Iacovi des et. al.(48) (2019) 11 Age: 30 ± 9 years; Gender ratio (men:women) 1:10 RCT, crosso ver 1: High-carbohydrat e, low-fat diet (HCLF) 2: High fat ketogenic diet (KD) High carbohy drate low fat diet or Ketogen ic diet 8
weeks Cognitive function, sleep quality and mood Daily questionnair es + Pittsburgh Sleep Quality Index (PSQI) Sleep quality did not different across dietary interventions (F(2,9) = 2.83, p= 0.083, repeated-measures ANOVA) 3 weeks of sustained nutritional ketosis had no effect on subjective sleep quality in a sample of healthy individuals
Appendix E. Table 2. Foods and Sleep
Study Number
randomized Participants Demographic
s (Age/ (Mean± SD); Gender) Study Design Intervention Descriptio n Food Protocol
Duration Primary Outcome Instrument to assess sleep quality Findings Conclusio n Howat son et. al.(41) (2012) 20 Age: 26.6 ±4.6 years; 50% female Randomi zed controlle d trial (RCT), double-blind (DB), placebo-controlle d Placebo (no melatonin or anthocyan ins) or Tart cherry juice concentra te Cherry
juice 3 weeks Urinary melatonin levels, sleep quality Polysomnogr aphy (PSG) + Actigraphy (Actiwatch 7, CamnTech, Cambridge, UK) + Self-reporting sleep diaries Tart cherry juice ingestion was significantly associated (p<0.05) with increased time in bed, TST and SE total when evaluated by actigraphy, while, when evaluated by subjective questionnair e there were no differences between groups Consumpt ion of a tart cherry juice concentra te may provide an increase in exogenou s melatonin and increase sleep quality Garrid o et. al.(40) (2013) 30 Age: (20–30 years old, n=10; 5 men and 5 women); (35–55 years old, n=10; 5 men and 5 women) and (65–85 years old, n=10;5 men and 5 women) Randomi zed, blind, placebo-controlle d, crossover Placebo product or Jerte Valley cherry-based product made with fresh cherries (JVCP) were consumed twice a day, as lunch and dinner desserts Cherry based product 3 weeks Sleep quality, urinary 6-sulfatoxy melatonin levels, serum concentra tion of interleuki n-1, tumor necrosis factor α (TnF-α) and interleuki n-8 (il-8) Actigraphy (Actiwatch, Cambridge neurotechno logy ltd., Cambridge, UK) Number of awakenings and total nocturnal activity has a substantial diminution (p<0.05). Actual sleep time was elevated (p<0.05). SE only increased significantly in elderly (p<0.05).* Sleep latency largely decreased (p<0.05) in both middle-aged and elderly Consumpt ion of Jerte Valley cherries may be able to establish a high-quality sleep, and the fruit can be used as a nutraceut ical for a better sleep quality Ito et. al.(43) (2014) 20 Age: 39.1 years (MEAN); Only men 1st study: RCT, DB 2nd study: Randomi zed placebo-controlle d, crossover trial, DB 1st study: Placebo and ETAS (enzyme-treated asparagus extract) group ingested 3 capsules after dinner for 7 days. 2nd study: Group A (placebo capsules) and Group B (ETAS) Aspara gus extract 1st study:12 weeks; 2nd study: 4 weeks Heat shock protein 70, Stress indices, and sleep Actigraphy (Micro-MotionLogge r Actigraph, Ambulatory Monitoring, Inc., Ardsley, NY) + Athens Insomnia Scale (AIS) + Oguri- Shirakawa-Azumi Sleep Inventory No significant differences in 1st study. In the 2nd study, group B significantly improved AIS score (p<0.05), indicating better sleep quality and tendency to improve the sleeping time (p=0.093) Enzyme-treated asparagus extract intake may be effective to modulate sleep time among those with low sleep efficiency and excess sleep time
Miller et. al.(42)(
2014)
6 Age: 27.5 ±
6.9 years Randomized, placebo-controlle d crossover , DB 1. Caffeine and carbohydr ate-electrolyt e beverage (CEB) or 2. Combined placebo and CEB ingestion Pre and during training session Caffein e and carboh ydrate-electro lyte bevera ge 2 days Cycling performan ce and nocturnal sleep Polysomnogr
aphy (PSG) Caffeine ingestion was significantly associated with increased SOL, decreased SE, decreased REM sleep and decreased TST (p = 0.028) Athletes should consider caffeine deleterio us effects on sleep quality Monoi et. al.(36)( 2016) 68 Age: SE = 38.2 ± 1.1 years;35 female and 33 males Randomi zed placebo-controlle d, crossover clinical study, DB Placebo or sake yeast tablets (125 mg sake yeast powder per tablet) 1 hour before sleep Sake
yeast 2 (two 4-day weeks periods separated by a 3-day washout period) Activation of adenosine A2a receptors and sleep quality Electroence phalographi c (EEG) device (Sleepscope , Sleep-well) + Ogri-Shirakawa– Azumi sleep questionnair e (OSA) Sake yeast ingestion was significantly associated (p=0.03) with increased SWS and improved sleepiness (p=0.02). No significant differences were seen in SOL, SE and TST Sake yeast tables may be an effective and safe way to support daily high-quality, deep sleep. The subjectiv e improvem ent in sleep quality presumab ly reflect good sleep resulting from improved deep SWS after taking the sake yeast tables Nodtv edt et. al (2017) 74 Age: 24.3 ± 3.2 years;18 males and 56 females RCT Placebo (pear) or Kiwi before sleep (130g)
Kiwi 5 weeks Sleep
quality Actigraphy (Actiwatch 2 from Philips/Resp ironics) + Bergen Insomnia Scale + Pittsburgh Sleep Questionnai re Index + Sleep diary Kiwi ingestion showed significant main effect time on all subjective sleep measures (SOL, SE, sleep quality), but no effect was found for TST (p<0.01) Although there were no such effects using objective measures, the results suggest that kiwi may possess some sleep improving properties Saito et. al.(34) (2017) 120 Age: 20-84 years; mixed database Randomi zed placebo-controlle 1. placebo (40g of scallop),
Oyster 12 weeks Sleep
quality Pittsburgh Sleep Quality Index (PSQI) SE was significantly improved in group 2 (p Zinc-rich food such as oyster may
group trial, DB (40g oyster) 3. of zinc and astaxanth in-rich food (40g of oyster + 20g of krill powder containin g astaxanth in) 4. placebo + zinc-enriched yeast and astaxanth in oil significantly improved in group 2 (p=0.032) and group 4 (p=0.004) compared to placebo onset latency as well as sleep efficiency in healthy individual s Ha et. al.(44) (2019) 80 Age: Placebo 39.8 ± 13.0, PS 39.0 ±12.5; Placebo 46.2% female; PS 52.5% female RCT, DB, placebo-controlle d PS rhizome extract (500 mg/day n = 40, PS group) or placebo (n = 40, placebo group) PS rhizom e 4 weeks Sleep
quality Athens Insomnia Scale (AIS) + Actigraphy (Actigraph GT3X+, Pensacola, FL, USA) PS group showed a significant better sleep subjective score (AIS) compared to the placebo group (p=0.035). Ps group showed significant increase in TST(p=0.046) PS rhizome extract can be an effective natural ingredient for improving sleep disturban ces in the form of sleep quality and sleep duration in mild insomnia
