Creatine Improves Total Sleep Duration Following Resistance Training Days versus Non-Resistance Training Days among Naturally Menstruating Females

Table of Contents

Overall Summary

Overview

Creatine supplementation increased total sleep duration on resistance training days in naturally menstruating women compared to placebo. No significant changes were observed in chronic sleep quality (PSQI), strength gains, or body composition. Both groups experienced a decrease in caloric, protein, and fat intake during the study. The primary finding of increased total sleep duration on training days was specific to the creatine group and suggests a potential benefit for post-exercise recovery.

Key Points

Comprehensive Overview (written-content)
The abstract effectively summarizes the study's purpose, methodology, key findings, and implications.
Section: Abstract
Quantify Sleep Duration Increase (written-content)
The abstract would benefit from quantifying the increase in sleep duration on training days to provide a more concrete understanding of the effect size.
Section: Abstract
Clear Context and Rationale (written-content)
The introduction clearly establishes the research context and rationale by highlighting the underrepresentation of women in creatine and sleep studies.
Section: Introduction
State Research Question (written-content)
The introduction would be strengthened by explicitly stating a concise research question or hypothesis to guide the study.
Section: Introduction
Robust Experimental Design (written-content)
The methods section provides a robust experimental design with a double-blind, placebo-controlled, randomized approach.
Section: Materials and Methods
Detailed Training Protocol (written-content)
The methods section lacks a detailed description of the resistance training protocol, limiting reproducibility.
Section: Materials and Methods
Clear Visual Representation of Study Design (graphical-figure)
Figure 1 clearly communicates the experimental design and flow of participants.
Section: Materials and Methods
Enhance Figure 1 with Timeline and Sample Sizes (graphical-figure)
Figure 1 would benefit from adding a timeline and sample sizes at each stage for increased clarity.
Section: Materials and Methods
Clear Presentation of Primary Outcome (written-content)
The results section clearly presents the primary outcome related to increased sleep duration on training days.
Section: Results
Report Effect Sizes (written-content)
The results section lacks reported effect sizes for the observed changes, limiting the interpretation of the magnitude of the effects.
Section: Results
Effective Data Visualization (graphical-figure)
Figure 2 effectively visualizes the difference in total sleep duration between groups on workout and non-workout days.
Section: Results
Improve Figure 2 Labeling and Significance (graphical-figure)
Figure 2 would benefit from clearer axis labels and indications of statistical significance.
Section: Results
Connection to Existing Literature (written-content)
The discussion effectively connects the findings to existing literature on creatine's effects on sleep and cognitive function.
Section: Discussion
Discuss Limitations of Intervention Period (written-content)
The discussion would benefit from further exploration of the limitations of the 6-week intervention period and its implications for the non-significant findings related to body composition.
Section: Discussion
Clear Summary of Main Finding (written-content)
The conclusion clearly summarizes the main finding of increased sleep duration on training days.
Section: Conclusions
Discuss Practical Implications and Future Research (written-content)
The conclusion would be strengthened by discussing the practical implications of the findings and connecting future research directions to the study's limitations.
Section: Conclusions

Conclusion

This study presents moderate evidence for the positive effect of creatine supplementation on acute total sleep duration following resistance training in naturally menstruating women. The randomized, double-blind, placebo-controlled design is a significant strength, minimizing bias and supporting causal inferences. The use of objective sleep measures (Oura ring) and robust statistical analysis (MLM) further strengthens the evidence. However, the study's small sample size, the lack of reported effect sizes, the unexplained dietary changes during the intervention, and the limited 6-week timeframe somewhat limit the generalizability and long-term implications of the findings. While the study effectively demonstrates an acute effect on sleep duration on training days, the lack of significant changes in chronic sleep quality or strength gains warrants further investigation. Overall, the study makes a valuable contribution to the field by exploring the effects of creatine on sleep in a relatively understudied population, but further research is needed to confirm and expand upon these findings, particularly regarding long-term effects, optimal supplementation durations, and the interplay between creatine, sleep, and dietary intake.

Section Analysis

Abstract

Key Aspects

Strengths

Suggestions for Improvement

Introduction

Key Aspects

Strengths

Suggestions for Improvement

Materials and Methods

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Figure 1. Experimental Design & Methodology Schematic. PARQ+, Physical Activity...
Full Caption

Figure 1. Experimental Design & Methodology Schematic. PARQ+, Physical Activity Readiness Questionnaire for Everyone; PSQI, Pittsburgh Sleep Quality Index; DHQ III, Diet History Questionnaire III; BIA, bioelectrical impedance analysis; DXA, dual energy x-ray absorptiometry; CR, creatine; PLA, placebo.

First Reference in Text
Once randomized, participants began supplementation and resistance training concurrently (Figure 1).
Description
  • Overall Study Design and Flow: The figure depicts the flow of participants through different stages of a research study. Initially, 35 potential participants are assessed for eligibility. Of these, 27 are enrolled in the study, with 2 dropping out before the pre-testing phase begins. The remaining 25 participants undergo pre-testing assessments including the Physical Activity Readiness Questionnaire (PARQ+ to ensure they are fit for the study), a health history review, a sleep quality assessment (PSQI), a dietary intake assessment (DHQ III), body composition analysis using bioelectrical impedance analysis (BIA - measuring body composition by passing a small electrical current through the body) and dual-energy X-ray absorptiometry (DXA - using low-dose X-rays to measure body fat and bone density), and a strength assessment using a TONAL device (a digital weight-training machine). Following pre-testing, participants are randomly divided into two groups: a creatine monohydrate supplementation group (CR, n=13) and a placebo group (PLA, n=12). Both groups then engage in a six-week intervention period involving daily supplement intake and bi-weekly resistance training using TONAL. During the intervention, daily data collection takes place, including sleep monitoring using an OURA ring, ovulation tracking, and adverse event monitoring. By the post-testing phase, 4 more participants have dropped out, leaving 21 (12 in the CR group and 9 in the PLA group) to complete the same assessments as in pre-testing. This figure serves as a roadmap to the study's methodology, showing how participants progressed through the experiment.
  • Randomization and Blinding: The randomization process is visually represented as a split after pre-testing, with participants being assigned to either the creatine (CR) or placebo (PLA) group. This signifies that group allocation is determined by chance, and this approach is used to minimize biases and ensure that the groups are as similar as possible before the intervention begins. The figure emphasizes that this is a double-blind study. This means that neither the participants nor the researchers administering the supplements know who is receiving creatine and who is receiving the placebo. This blinding is crucial for minimizing bias and ensuring the study results are accurate and reliable.
Scientific Validity
  • Concurrent Intervention Design: The concurrent initiation of supplementation and resistance training after randomization is a valid approach to assess the combined effect of these interventions. This design allows researchers to evaluate whether the combination of creatine and resistance training has a synergistic effect on the outcomes, compared to resistance training alone. Starting both interventions at the same time minimizes the potential for confounding variables to influence the results.
  • Study Design Rigor: The figure appropriately represents the double-blind, randomized, placebo-controlled design, a rigorous approach for minimizing bias and maximizing the internal validity of the study. This design allows for a strong causal inference regarding the effects of creatine supplementation.
  • Comprehensive Assessment Measures: The inclusion of multiple assessment methods (PARQ+, PSQI, DHQ III, BIA, DXA, TONAL strength assessment) enhances the study's ability to capture a comprehensive picture of the participants' health and performance. These measures provide both subjective (e.g., PSQI) and objective (e.g., DXA, BIA, TONAL) data, strengthening the validity and reliability of the findings.
Communication
  • Clarity and Structure: The figure effectively communicates the experimental design's temporal flow, clearly outlining the sequence of procedures from recruitment to post-testing. The use of distinct visual elements for each stage (pre-testing, intervention, post-testing) aids in comprehension. The color-coding of the supplementation groups (CR and PLA) within the intervention phase facilitates quick differentiation of the treatment arms.
  • Completeness and Detail: While the figure provides a good overview, it could benefit from minor improvements. Adding a timeline at the top or bottom would provide a more precise sense of the study's duration. Including the sample sizes (n) at each stage would enhance transparency and allow readers to track participant attrition. A brief description within the figure caption of the TONAL strength assessment, DXA, and BIA could enhance its stand-alone interpretability.

Results

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Table 1. Participant demographics at baseline.
First Reference in Text
Participant demographics at baseline are displayed in Table 1.
Description
  • Purpose of Baseline Data: This table presents the baseline characteristics of the participants in the study, separated into three groups: all participants, the placebo group, and the creatine group. These characteristics are measured before any intervention begins, providing a snapshot of the participants' initial state. This is important for understanding the composition of the study sample and for comparing the characteristics of the different treatment groups. It allows researchers to determine whether there are any pre-existing differences between groups that might influence the outcomes of the study.
  • Description of Variables: The table includes several key demographic and physical characteristics. "Age" is presented in years, "Height" in centimeters (cm), "Body mass" in kilograms (kg), and "BMI" (Body Mass Index) is calculated as weight in kilograms divided by height in meters squared (kg/m^2). BMI is a measure of body fat based on height and weight. The table also includes the "Menstrual cycle phase" at baseline, categorized as either "F" (follicular phase - the first half of the menstrual cycle) or "L" (luteal phase - the second half of the menstrual cycle). The percentage of participants in each phase is presented for each group. This allows researchers to see if menstrual cycle phase might influence the results and should be controlled for.
Scientific Validity
  • Relevance of Demographics: Reporting baseline demographics is crucial for ensuring the comparability of treatment groups and for assessing the generalizability of study findings. The chosen demographics (age, height, body mass, BMI, menstrual cycle phase) are relevant for a study investigating the effects of creatine supplementation and resistance training.
  • Appropriate Statistical Measures: The presentation of mean and SD for continuous variables (age, height, body mass, BMI) is standard practice and facilitates statistical comparisons between groups. Categorical variables (menstrual cycle phase) are presented as percentages, which is also appropriate.
  • Baseline Group Comparability: The lack of statistically significant differences between groups at baseline is essential for attributing any observed post-intervention differences to the treatment (creatine) rather than pre-existing group differences. This strengthens the internal validity of the study.
  • Missing Data: While the table notes that not all participants had confirmed menstrual cycle phases, the authors should clarify the criteria for "confirmation" and provide more detail on the distribution of missing data. This information is essential for understanding the potential impact of this missing data on the study's findings. The authors should consider exploring the reasons for the missing data and potentially address the missing data during analysis.
Communication
  • Clarity and Structure: The table is clearly structured, presenting the data in a logical order. The use of standard units (cm, kg, etc.) and abbreviations (F, L) is appropriate, though the abbreviations could be explicitly defined in a table footnote for increased clarity.
  • Data Presentation: Including the sample size (n) for each group and the overall sample enhances transparency and allows readers to assess the representativeness of the data. Providing both the mean and standard deviation (SD) allows for an understanding of the data distribution and variability within each group.
  • Transparency and Limitations: The note clarifying that not all participants had a confirmed menstrual cycle phase at baseline is important for transparency and addresses potential limitations in data interpretation. However, it would be beneficial to elaborate on the reasons for the missing data and its potential implications for the study's findings.
Figure 2. Model-estimated means (and standard errors) of total sleep duration...
Full Caption

Figure 2. Model-estimated means (and standard errors) of total sleep duration as a function of workout and group status. Note: The thick lines represent the average effect estimated by the fixed effect and the thinner lines represent the effects by participant (i.e., the random effect).

First Reference in Text
There were no other group differences or effects by workout for deep sleep, REM sleep, and light sleep duration.
Description
  • Graph Interpretation: The graph shows the average total sleep duration, measured in minutes, for participants in two groups: those taking creatine (CR) and those taking a placebo (PLA). The x-axis separates the data into "Non-Workout" and "Workout" days, allowing for a comparison of sleep duration on days with and without resistance training. The graph displays model-estimated means, representing the average sleep duration predicted by a statistical model (Multilevel Modeling or MLM), and standard errors, which represent the uncertainty around those estimated means. MLM is used to analyze repeated measurements within individuals, accounting for individual differences and potential correlations between data points. The thick lines represent the overall average effect of creatine or placebo across all participants (fixed effect), while the thinner lines show the individual trajectories for each participant (random effects), highlighting how individual responses to the intervention can vary.
Scientific Validity
  • Statistical Methodology: The use of MLM is justified given the repeated measures design of the study, allowing the researchers to account for individual variation in sleep patterns. The inclusion of both fixed and random effects provides a comprehensive understanding of the treatment effect at both the group and individual levels. The note regarding no other significant group differences or effects by workout for deep, REM, and light sleep durations suggests that the observed effect on total sleep duration is not driven by changes in specific sleep stages but rather by a more general increase in overall sleep time.
  • Specificity of Creatine's Effect: While the figure presents valuable information about the effect of creatine on total sleep duration, it's important to consider the reference text stating no significant effects on other sleep parameters. This suggests that creatine's primary effect might be on sleep quantity rather than quality (i.e., distribution of sleep stages). Future research could explore the mechanisms behind this observed increase in total sleep duration and its potential implications for recovery and performance.
  • Impact on Sleep Architecture: The figure and the accompanying reference text provide strong evidence for the selective impact of creatine on total sleep duration following workout days. However, the absence of effects on deep sleep, REM sleep, and light sleep necessitates further investigation into the mechanisms underlying creatine's influence on sleep architecture and its implications for recovery and performance.
Communication
  • Clarity of Presentation: The figure clearly presents the model-estimated means of total sleep duration, differentiating between workout and non-workout days and between the creatine (CR) and placebo (PLA) groups. The use of different line styles and markers effectively distinguishes the groups, and the inclusion of error bars (standard errors) provides a visual representation of the uncertainty in the estimates.
  • Caption Clarity: The figure caption could be improved by briefly explaining what "fixed effect" and "random effect" mean in the context of the MLM analysis. This would help readers who are not familiar with statistical modeling to understand the figure's interpretation.
  • Axis Labeling: The y-axis label could be more informative by stating "Total Sleep Duration (minutes)". While the units are implied by the caption, explicitly stating them on the axis label would enhance clarity.
  • Statistical Significance: While the visualization effectively shows the differences in total sleep duration, it lacks information about the statistical significance of these differences. Adding symbols (e.g., asterisks) to indicate significant differences between groups or conditions would strengthen the visual communication of the results.
Table 2. Body Composition Metrics.
First Reference in Text
Although there were significant differences in TBW, ICW, and ECW from pre-intervention to ovulation testing, there were no differences in these metrics from ovulation to post-intervention.
Description
  • Body Composition Measurements: This table displays various body composition measurements taken at three different time points: before the intervention (pre), during ovulation, and after the intervention (post). The data is separated into placebo and creatine groups, allowing for comparison of how body composition changes over time in response to creatine supplementation. The table shows values for body mass (BM), fat mass (FM) as both a percentage and in kg, soft tissue (ST) as both a percentage and lean soft tissue in kg, visceral adipose tissue (VAT), and appendicular lean soft tissue index (ALSTI). It also includes measurements of total body water (TBW), intracellular water (ICW - water inside cells), and extracellular water (ECW - water outside cells). These metrics provide a comprehensive assessment of how the body's composition is affected by the intervention, including changes in fat, muscle, and water distribution.
  • DXA and BIA Measurements: DXA uses two different X-ray energies to distinguish between bone, fat, and lean tissue, providing highly accurate measurements of body composition. BIA measures the body's resistance to a small, harmless electrical current. Because lean tissue contains more water and conducts electricity better than fat tissue, BIA can estimate body fat percentage. These methods offer complementary information about body composition changes.
  • BCI Calculation: BCI stands for Body Composition Index and is calculated as: BCI = [(LST_post - LST_pre) + (FM_pre - FM_post)]. This formula represents the net change in body composition. A positive BCI value indicates a favorable change, with an increase in lean soft tissue (LST) and a decrease in fat mass (FM). Pre and post refer to pre-intervention and post-intervention, respectively.
Scientific Validity
  • Validity of Measurement Methods: The inclusion of both DXA and BIA data provides a more comprehensive assessment of body composition changes. DXA is considered the gold standard for measuring body composition, while BIA offers a more accessible and portable alternative.
  • Interpretation of Findings: The observed increase in FM despite no change in relative FM percentage might indicate an increase in overall body mass, which should be further investigated. The lack of significant changes in LST, despite improvements in strength, might suggest neuromuscular adaptations rather than muscle hypertrophy.
  • Fluid Balance and Ovulation: The changes in TBW, ICW, and ECW around ovulation raise interesting questions about the interplay between hormonal fluctuations and fluid balance. The lack of changes in these metrics from ovulation to post-intervention suggests that these fluctuations might be transient and not significantly influenced by the intervention.
  • Sample Size Considerations: The small sample size, especially for the ovulation data (n=4 for placebo, n=12 for creatine), limits the statistical power of the study and might explain the lack of significant changes in some metrics. Future research with larger sample sizes is needed to confirm these findings.
Communication
  • Comprehensive Metrics: The table effectively presents a comprehensive range of body composition metrics, including both absolute and relative measures of fat mass (FM) and lean soft tissue (LST). The inclusion of visceral adipose tissue (VAT) and appendicular lean soft tissue index (ALSTI) provides additional valuable information about fat distribution and muscle mass, respectively.
  • Clear Structure and Presentation: The structure of the table, with clear column headings and appropriate units, facilitates easy comparison of pre-, ovulation, and post-intervention measurements for both the placebo and creatine groups. The use of superscripts to denote statistically significant changes improves readability and highlights key findings.
  • Footnote Clarity: The table footnote defines the abbreviations used and explains the statistical annotations, which is crucial for proper interpretation of the data. However, the footnote could be more concise and avoid redundant phrasing.
  • Explanation of BCI: The table would benefit from a more detailed explanation of the BCI calculation in the footnote. While the formula is provided, it would enhance understanding to explicitly state what a positive or negative BCI value indicates.
Table 3. Dietary Intake.
First Reference in Text
Relative protein (p = 0.009; g/kg) and carbohydrate (p = 0.023; g/kg) significantly decreased from pre- to post-intervention (Table 3).
Description
  • Dietary Intake Measures: This table presents what participants ate and drank. Specifically, it looks at their calorie intake (measured in kilocalories, which is a measure of energy), protein intake (in grams and grams per kilogram of body weight), carbohydrate intake (in grams and grams per kilogram of body weight), fat intake (in grams), and how much creatine they consumed from food (in grams). These measurements were taken before the start of the study (Pre) and after the six-week study period (Post). The data is presented for two groups: one group who took creatine supplements and one group who took a placebo. This allows the researchers to observe changes in dietary patterns in response to the intervention.
  • Mean and Standard Deviation: The values presented are the mean (average) values for each group at each time point. The standard deviation (SD) is also included, which is a measure of the spread or variability of the data around the average. It shows how much the individual values tend to differ from the mean.
Scientific Validity
  • Dietary Assessment Method: The use of a validated dietary assessment tool (DHQ III) is a strength of the study. However, it is crucial to acknowledge the limitations of self-reported dietary intake data, such as recall bias and social desirability bias, which can affect the accuracy of the reported values.
  • Dietary Changes and Confounding Factors: The observed decrease in total calories, protein, fat, and relative protein and carbohydrate intake from pre- to post-intervention raises concerns about potential confounding factors influencing the study's findings. It is crucial for the authors to discuss the possible reasons for these dietary changes and explore whether they might have influenced the observed outcomes, particularly in relation to body composition and sleep.
  • Habitual Creatine Intake: The low habitual creatine intake values at both pre- and post-testing, even among non-vegetarians/vegans, raises questions about the participants' typical dietary patterns and protein sources. This information is relevant for interpreting the effects of creatine supplementation and warrants further discussion.
  • Adequacy of Protein and Carbohydrate Intake: The significant decreases in relative protein and carbohydrate intake raise concerns about the adequacy of the participants' diets, particularly in the context of a resistance training program. The authors should address the potential implications of these dietary changes for muscle protein synthesis, recovery, and overall performance.
Communication
  • Clear Data Presentation: The table clearly presents dietary intake data for both the placebo and creatine groups at pre- and post-intervention time points. The inclusion of both absolute values (grams) and relative values (grams per kilogram of body weight) for protein and carbohydrates provides a comprehensive view of dietary changes.
  • Standard Units and Headings: The use of standard units (kcal, g, g/kg) and clear column headings facilitates understanding and comparison of the data. The superscript notation effectively highlights statistically significant changes from pre- to post-intervention.
  • Additional Context and Energy Intake: While the table presents the data effectively, adding a brief explanation in the footnote about the method used to assess dietary intake (DHQ III) would enhance the context and transparency of the reported values. Additionally, it would be beneficial to present energy intake as both absolute values (kilocalories) and relative to body weight (kilocalories per kilogram). This would provide a more complete picture of energy balance.

Discussion

Key Aspects

Strengths

Suggestions for Improvement

Conclusions

Key Aspects

Strengths

Suggestions for Improvement

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