Abstract
The objective of the study was to examine the impact of a multi-strain probiotic (MSP) on sleep, physical activity, and body composition changes. We used a randomised, double-blind, placebo-controlled approach with 70 healthy men and women (31.0 ± 9.5 years, 173.0 ± 10.4 cm, 73.9 ± 13.8 kg, 24.6 ± 3.5 kg/m2) supplemented daily with MSP (4 × 109 live cells Limosilactobacillus fermentum LF16, Lacticaseibacillus rhamnosus LR06, Lactiplantibacillus plantarum LP01, and Bifidobacterium longum 04; Probiotical S.p.A., Novara, Italy) or placebo (PLA). In response to supplementation (after 0, 2, 4, and 6 weeks of supplementation) and 3 weeks after stopping supplementation, participants had subjective (Pittsburgh Sleep Quality Index, PSQI) and objective sleep indicators, body composition, daily physical activity and resting hemodynamics assessed. Subjective sleep quality indicators using the PSQI (sleep latency, sleep disturbance, and global PSQI score) improved (
Registered at clinicaltrials.gov: NCT05343533
1 Introduction
The existence of the gut-brain axis has been well-established and recognised as a bidirectional pathway in which the nervous, endocrine, and immune systems communicate back and forth with the intestinal microbiota of the gastrointestinal tract (GIT) (Grenham et al., 2011; Mayer, 2011; Mayer et al., 2014). Through this pathway, the GIT microbiota’s bacteria, intestinal neurons, neurotransmitters, and gut hormones are inter-connected. The GIT bacteria signals the brain to activate intestinal neurons, leading to the production of neurotransmitters and gut hormones, which help maintain homeostasis within a host (Ahmed et al., 2022; Muller et al., 2020). As the GIT alone has been estimated to have ten times more microorganisms than that of human cells in our bodies (Grenham et al., 2011). Consequently, disruptions within the GIT can easily occur, inhibiting the gut-brain axis (Mayer, 2011). With these factors being identified, research has focused on specific interventions to help combat potential disruptions, improve and/or maintain the gut-brain axis communication, and support the GIT microbiota to ensure signalling of all components are sufficient (Bagga et al., 2018a; Marotta et al., 2019; Tillisch et al., 2013).
Notably, probiotics have been investigated as a significant focal point for GIT microbiota interventions. Defined as live microorganisms that, when administered in adequate amounts, confer a health benefit on the host (Colin Hill, 2014), probiotics have been shown to significantly impact the microbial environment in the GIT. In particular, a 2018 study conducted by Bagga et al. (2018b) saw that four weeks of supplementation with a multi-strain probiotic in 45 healthy adults changed GIT microbiome profiles as seen through stool samples. Changes in brain activation patterns in response to emotional memory and decision-making tasks were also seen through functional magnetic resonance imaging (fMRI). Tillisch et al. (2013) also used fMRI to conduct a randomised, double-blind study in healthy females (n = 36) to investigate the effects of supplementation with a fermented milk product with probiotics (FMPP). After four weeks of FMPP consumption, brain activity was improved in the brain regions that control the central processing of emotion and sensation. Additionally, through focusing specifically on different aspects of mood, a six-week study that involved supplementation with a probiotic mixture in healthy adults (n = 38) resulted in significant improvements in overall mood and sleep quality, with reductions in a depressive mood state, anger, and fatigue (Marotta et al., 2019).
As research has shown that probiotics significantly affect the GIT microbiota and the bidirectional pathway of the gut-brain axis to improve various aspects of brain activation and mood, different factors associated with this bidirectional pathway that may be impacted by probiotics have been brought into question. Specifically, parameters of sleep and sleep quality in general have been investigated as to whether probiotics could improve the duration, quality, latency, and efficiency of sleep. For example, Takada et al. (2017) saw that 11 weeks of supplementation with 1 × 109 cfu/ml of Lactobacillus casei strain Shirota YIT 9029 (LcS) probiotic fermented milk in healthy adults (n = 94) positively improved subjective scores for sleepiness, sleep length, and sleep latency. Sleep was also investigated in a 2021 study in 20 healthy male adults, where after eight weeks of supplementation with 1 × 109 cfu/day of Bifidobacterium longum 1714 significant improvements in overall sleep quality and duration of sleep were observed using the Pittsburgh Sleep Quality Index (PSQI) (Moloney et al., 2021). As briefly mentioned earlier, Marotta et al. (2019) also examined the beneficial aspects of probiotic supplementation on sleep and administered six weeks of supplementation with 4 × 109 cfu/Active Fluorescent Unit (AFU) of 2.5 g freeze-dried powder of the probiotic mixture containing Lactobacillus fermentum LF16 (DSM 26956), L. rhamnosus LR06 (DSM 21981), L. plantarum LP01 (LMG P-21021), and Bifidobacterium longum BL04 (DSM 23233). Using the PSQI, improvements in sleep quality were seen along with improved sleep quality being correlated with improved anxiety/depressive symptoms, fatigue, anger, confusion, and vigour. Although examining sleep, mood, and brain functioning in relation to the beneficial effect probiotics have on the gut-brain axis are at the forefront of investigations and research studies, there are background factors that warrant discussion.
Levels of physical activity and body composition can also prove to be important factors to focus on regarding the gut-brain axis and probiotic supplementation. To date, limited research has explored the effect of probiotic supplementation on physical activity levels and changes in body composition in conjunction with sleep assessment. Briefly, Quero et al. (2021) supplemented young, sedentary and professional soccer players with a mixture of probiotic strains (Bifidobacterium lactis CBP-001010, Lactobacillus rhamnosus CNCM I-4036, and Bifidobacterium longum ES1) and the prebiotic fructooligosaccharides for four weeks and evaluated changes in inflammatory, immune, and stress biomarkers in addition to other questions and assessments related to physical and mental health. The more physically active group (the professional soccer players) experienced greater improvements in physical activity and sleep quality along with perceived levels of health, stress, and anxiety. Furthermore, differential responses were observed in IL-1β, CRH, and dopamine that were specific to each group. While more research is needed to explore the interaction between probiotics and physical activity levels, the links between mood, sleep, and brain functioning on physical activity and body composition have undergone more research. Motivation, for example, an aspect of mood and is a significant factor that can impact the physical activity level of an individual, which can extend to impact physical and mental health in addition to body composition (Frederick et al., 1996; Mayer, 2011). Motivation may also be an indicator of how well the GIT microbiota and brain are communicating via the bidirectional pathway (Ahmed et al., 2022; Mayer, 2011). Ensuring the gut-brain axis has efficient bidirectional communication can help to improve motivation specifically, but also mood, sleep, and brain functioning.
Although there is a strong foundation for research concerning probiotic supplementation on gastrointestinal function, immunity, and certain aspects of the gut-brain axis, less research is available that has explored the potential efficacy for probiotics to modulate sleep, physical activity, and body composition. Due to the need for research in this area, the purpose of this study was to investigate the efficacy of supplementing with a multi-strain probiotic on changes in sleep, physical activity, and body composition.
2 Materials and methods
Overview of research design
A randomised, double-blind, placebo-controlled, parallel group study was employed to evaluate the ability of a multi-strain probiotic to influence sleep quality and quantity, physical activity, body composition and hemodynamics. The primary outcomes for this investigation were the sleep quality and quantity while the outcomes related to physical activity, body composition, and hemodynamics were secondary outcomes. Healthy men and women between the ages of 18-50 years were assigned to one of two supplementation groups. They either received a multi-strain probiotic (1 × 109 live cells of each of the four strains: Limosilactobacillus fermentum LF16 (DSM 26956), Lacticaseibacillus rhamnosus LR06 (DSM 21981), Lactiplantibacillus plantarum LP01 (LMG P-21021), and Bifidobacterium longum 04 (DSM 23233); Bifizen™, Probiotical S.p.A., Novara, Italy) or a maltodextrin placebo (PLA). Prior to study engagement, all participants signed an IRB-approved informed consent document (Lindenwood University: IRB-19-212, approval date: 7/17/19, conformed to the standards set by the latest revision of the Declaration of Helsinki), completed a health history questionnaire, and answered a series of questions to determine study eligibility.
Participants were scheduled for four identical study visits between 06:00-10:00 h while attempts were made to standardise visit timing across the investigation. For all visits, subjects were instructed to undergo an 8-10 h fast (except water) and abstain from strenuous physical activity 48 hours prior to each visit. All participants supplemented for six weeks followed by a three-week washout period post-supplementation. As seen in Table 1, all participants completed 2-day food records and were evaluated for changes in sleep parameters, body composition, hemodynamics, and physical activity levels after 0, 2, 4, and 6 weeks of supplement administration and 3 weeks after supplementation ceased. This study protocol and design was registered on Clinicaltrials.gov on April 25, 2022, as NCT05343533. Outcomes related to self-assessed parameters of mood, anxiety, and personality have been published previously (Walden et al., 2023). The study design was powered, and sample size was determined based upon the required changes needed to investigate the impact of supplementation on self-assessed parameters of mood. Based upon previous data of Marotta et al. (2019) an a priori sample size evaluation indicated that if a moderate effect size was realised (
Overview of research design
Citation: Beneficial Microbes 15, 2 (2024) ; 10.1163/18762891-bja00002
Study participants
A total of 70 healthy men and women (31.0 ± 9.5 years, 173.0 ± 10.4 cm, 73.9 ± 13.8 kg, 24.6 ± 3.5 kg/m2) successfully completed the study protocol. A Consolidation Standards of Reporting Trials (CONSORT) diagram is provided in Figure 1. Participants were included in the study if they were between the ages of 18-50 years, had a body mass index (BMI) between 18.5-32 kg/m2 (if BMI was 30-32 kg/m2, participant was required to have body fat percentage < 25% for men and <35% for women for inclusion), were weight stable for the past three months (<5% variation in body mass), and deemed healthy through completion of a health history questionnaire. Participants were excluded if they were diagnosed or were being treated for any cardiac, respiratory, endocrine, psychiatric, musculoskeletal, renal, hepatic, neuromuscular or metabolic disease or disorder that precluded safe participation or would contraindicate quality control over the collected data, were diagnosed with or being treated for celiac disease, lactose intolerance, digestive insufficiencies, or other gastrointestinal complications such as irritable bowel syndrome, ulcerative colitis, etc., reported being a current smoker or had quit within the past six months, reported having used any illicit or recreational drugs including anabolic steroids within the past 30 days, reported the intake of any prescription or over-the-counter medications (i.e. antibiotics) that may impact study outcomes, reported the current use of any dietary supplements known to impact digestion or sleep quality for the past 30 days, reported taking a probiotic within the past 30 days, had been actively trying to lose weight, or were currently following a ketogenic or low carbohydrate diet within the past 30 days. Further, antibiotic use at any point in the study protocol led to removal from the study. Women who were pregnant, lactating, or indicated during screening they were actively trying to become pregnant were excluded from the study.
Procedures
Baseline demographics and hemodynamics
Body mass was determined using a digital scale (Tanita BWB-627A, Tokyo, Japan) and recorded to the nearest ± 0.1 kg. Height was measured using a standard wall-mounted stadiometer (Tanita, HR-200) and recorded to the nearest ± 0.5 cm. Both measurements were made after participants voided their bladders and removed their shoes. Participants then rested quietly for approximately 10 minutes before measuring resting heart rate and blood pressure (Omron BP785, Omron Corporation, Kyoto, Japan).
Diet assessment and control
Study participants completed the automated self-administered 24-h dietary assessment tool (ASA24; https://epi.grants.cancer.gov/asa24/). Healthy Eating Index values were computed from the completed food records. The Healthy Eating Index is a measure of diet quality that can be used to assess compliance with the Dietary Guidelines for Americans. From the collected food intake information, 13 different food categories (seafood and plant proteins, fatty acids, refined grains, sodium added sugars, saturated fats, total fruits, whole fruits, total vegetables, greens and beans, whole grains, dairy, and total protein foods) are populated and the amount of food and fluid consumed that aligns with that food category is evaluated against the recommended intake (https://epi.grants.cancer.gov/hei/interpret-visualise-hei-scores.html). Each category is then assigned a percentage and from there a Healthy Eating Index composite score is determined. Radar plots have been generated to evaluate the difference in Healthy Eating Index values between groups and to evaluate the extent to which composite Healthy Eating Index values changed across time.
Body composition
Body composition was obtained using dual-energy X-ray absorptiometry (DEXA) after 0 and 6 weeks of supplementation as well as three weeks after stopping supplementation to evaluate changes in fat mass, fat-free mass, and percent body fat. Calibration procedures were performed before each testing session and all scans were completed using a Hologic QDR Discovery A (Hologic, Bedford, MA, USA) and analysed using the accompanying software (Hologic APEX Software, Version 4.5.3). The test-retest reliability (ICC and CV) of these procedures has previously been determined to be 0.99% and 1.26% for DEXA fat and 0.99% and 0.75% for DEXA fat-free mass (data not shown). All results were calculated using the NHANES correction factor.
Sleep quality and quantity
The Pittsburgh Sleep Quality Index (PSQI) is a validated self-report questionnaire that subjectively evaluates various aspects of sleep quality over the past month (Buysse et al., 1989). The PSQI has 19 questions that inquire about usual bedtime, time to fall asleep, waking time, hours slept per night, and other aspects of sleep quality. Each item is weighted on 0-3 scale, whereby a score of 3 reflects the negative extreme on the scale. All scores are grouped in seven component scores (sleep duration, use of sleeping medications, sleep disturbances, subjective sleep quality, habitual sleep efficiency, daytime dysfunction, and sleep latency) and all component scores can be added together to yield a global score. Qualitatively, a global sum of 5 or greater indicates poor sleep quality. In addition to the PSQI, participants were outfitted with a wrist-based accelerometer (Fitbit Inspire 2, Fitbit, San Francisco, CA, USA) to quantitively and objectively evaluate additional sleep metrics (average total minutes slept, number of times restless, number of times awake, total minutes awake or restless).
Physical activity
Physical activity was not controlled throughout this study protocol. Eligible participants were instructed to maintain physical activity status throughout the study protocol, and to inform research staff if their physical activity habits changed throughout the study protocol. Further, wrist-based accelerometers (FitBit Inspire 2) were worn for one week prior to beginning the supplementation intervention and for the entire duration of the study. Weekly averages of step counts, minutes of sedentary activity, and total activity minutes per day were recorded and evaluated.
Supplementation protocol
Using a randomised, double-blind, placebo-controlled, parallel group fashion, participants were assigned to ingest a single capsule of either a maltodextrin placebo (PLA) or a mixture of four probiotic strains (MSP). Each probiotic dose was delivered in capsules containing a 1 × 109 live cells dose of each of the following strains (total daily dose of 4 × 109 live cells): Limosilactobacillus fermentum LF16 (DSM 26956), Lacticaseibacillus rhamnosus LR06 (DSM21981), Lactiplantibacillus plantarum LP01 (LMG P-21021), and Bifidobacterium longum 04 (DSM 23233) (Probiotical S.p.A., Novara, Italy). Capsules for the placebo and probiotic strain were identical in color, shape, size, and transparency and were packaged into identical, bottled, containers that contained the same number of capsules. Participants were instructed to consume each dose at approximately the same time each day with 240-360 ml of water and within two hours of consuming a meal. Product stability was monitored across the whole study up to 24 months at three different temperature conditions (refrigerated at 5 °C, Zone II at 25 °C and 65% relative humidity and Zone IVb at 30 °C and 75% relative humidity) confirming the threshold values of 4 × 109 live cells at the end of the 24 months program (Walden et al., 2023).
Adverse event reporting
Adverse events were collected via spontaneous reporting by the participants, clinical evaluation, interaction of a research team member with a participant, or through review of a participant’s research file throughout the entire duration of the protocol. This data has been previously reported (Walden et al., 2023).
Statistical analysis
Before any statistical tests were performed, raw data was screened for data entry and organisation errors, and then analysed for normality, skewness, and kurtosis. Any non-normally distributed value was normalised, if possible, using log-transformations. All data is reported as mean ± standard deviation. For all statistical tests, data was considered statistically significant when the probability of type I error is 0.05 or less. A trend or a tendency for change was determined when the probability of type I error was
3 Results
Confirmation of probiotic viability
As reported previously (Walden et al., 2023), the finished supplementation product was analysed (Biolab srl., Novara, Italy) via flow cytometry (ISO 19344, 2015: IDF 232: 2015) upon batch release which resulted in a cell count of >4 × 109 Active Fluorescent Unit (AFU)/g and plate count method as cfu (Internal Method 014-06).
Supplementation compliance
Compliance to the supplementation protocol was calculated and reported herein. Participants assigned to the MSP condition reported compliance between 76.2-100.0% (mean ± standard deviation (SD): 93.7 ± 7.3%) while compliance in the PLA group ranged from 71.4-100.0% (mean ± SD: 94.6 ± 7.1%).
Adverse event reporting
Participants self-reported adverse events throughout the study protocol. Twelve adverse events were reported in MSP (constipation, n = 1; tired in morning, n = 1, flatulence, n = 4, bloating, n = 3; lower back pain, n = 2; lower abdominal pain, n = 1) while 46 adverse events were reported by participants assigned to the PLA condition (constipation, n = 3; tired in morning, n = 1, burping, n = 3; flatulence, n = 6, bloating, n = 4; lower back pain, n = 2; lower abdominal pain, n = 1; acid reflux, n = 4; irritated oesophagus, n = 2; skin irritation, n = 13, dry eyes, n = 4, fatigue, n = 2, and increased need to use bathroom, n = 1). All reported adverse events, independent of supplement assignment, were mild or moderate in severity. No serious adverse events were reported.
Dietary intake
Of the 70 participants who completed the current study, 60 of them provided suitable dietary data and this data has been presented previously (Walden et al., 2023). Four additional participants provided suitable baseline dietary data but did not provide a suitable follow-up measure. For these four cases, missing data was replaced by carrying the baseline value forward. No differences were identified between groups for energy (MSP: 1,891 ± 569 kcals/day vs PLA: 2,050 ± 618 kcals/day,
(A) Changes in PSQI Sleep Latency scores from baseline. (B) Changes in Global PSQI scores from baseline. * = Significantly different from baseline (
Citation: Beneficial Microbes 15, 2 (2024) ; 10.1163/18762891-bja00002
Baseline characteristics
Table 2 provides age, height, body mass, percent body fat, and BMI values at baseline for all participants (n = 70), men (n = 35), and women (n = 35). No differences were present prior to supplementation.
Baseline characteristics1
Citation: Beneficial Microbes 15, 2 (2024) ; 10.1163/18762891-bja00002
Hemodynamics
All hemodynamic data can be found in Table 3. Resting heart rate values indicated no changes in the group × time interaction (
Hemodynamic parameters after 0, 2, 4, and 6 weeks of supplementation as well as 3 weeks after stopping supplementation (week 9)1
Citation: Beneficial Microbes 15, 2 (2024) ; 10.1163/18762891-bja00002
Body mass and body composition
Changes in body mass indicated no significant group × time interaction (
Body composition data after 0 and 6 weeks of supplementation as well as 3 weeks after stopping supplementation (week 9)1
Citation: Beneficial Microbes 15, 2 (2024) ; 10.1163/18762891-bja00002
Perceived sleep and wearable sleep outcomes
As seen in Table 5, perceived sleep parameters were evaluated using the Pittsburgh Sleep Quality Index. Within the PSQI, seven subscales and a global score were analysed. No changes across time were observed within each group using the Friedman test for subjective sleep (MSP,
Pittsburgh Sleep Quality Index (PSQI) after 0, 2, 4, and 6 weeks of supplementation as well as 3 weeks after stopping supplementation (week 9)1
Citation: Beneficial Microbes 15, 2 (2024) ; 10.1163/18762891-bja00002
For the PSQI – Sleep Latency scores, a notable main effect of time was identified for MSP (
In addition to PSQI, sleep was assessed using a wearable sleep tracking device and this data can be found in Table 6. No significant group × time interaction (
Wearable sleep and physical activity data after 0 and 6 weeks of supplementation as well as 3 weeks after stopping supplementation (week 9)1
Citation: Beneficial Microbes 15, 2 (2024) ; 10.1163/18762891-bja00002
Physical activity
All physical activity data can be found in Table 6. A significant main effect of time was observed for total calories burned as calories expended decreased across the study protocol (
4 Discussion
In this investigation, we sought to examine the presence of any changes in indicators of sleep quality and quantity, physical activity, hemodynamics, and body composition in a mixed gender cohort of healthy adults after supplementing with a multi-strain probiotic preparation for six weeks and also three weeks after ceasing supplementation. The primary findings from this investigation indicate that probiotic supplementation improved perceived global sleep scores, sleep latency, and sleep disturbance scores as assessed by the Pittsburgh Sleep Quality Index whereas daytime dysfunction ratings were improved in the placebo group. Additionally, a trend was observed (
MSP supplementation did not impact how much physical activity was completed by our study participants. Clear links have been established between psychological health and physical activity status in healthy, non-clinical populations (Peluso and Guerra de Andrade, 2005; Rebar et al., 2015), which may in part be due to the known impact of physical activity on the bacterial communities found in the microbiome (Dziewiecka et al., 2022). Currently, limited data is available that has examined any ability of probiotics to influence physical activity. A 2022 study by Akhgarjand et al. (2022) reported that 12 weeks of supplementation with two different probiotic strains in 90 patients diagnosed with Alzheimer’s disease improved physical activity levels greater than what was observed in a placebo in one but not both physical activity scales. Two key differences from this study and the present study were the psychological health of the study participants and the length of supplementation (12 weeks vs 6 weeks). Regardless, more research is needed to fully explore the ability of probiotic supplementation to impact physical activity. Another key difference in terms of physical activity was the type of assessment. The previous work of Akhgarjand et al. (2022) used validated questionnaires that evaluated the quantity of activities of daily living that were completed while the present study utilised a commercially available wrist-based fitness tracker. However, many other studies have been published using these types of trackers to evaluate changes in physical activity (Brickwood et al., 2019; Ferguson et al., 2022) thus it remains more likely that MSP supplementation either did not produce a measurable impact in our healthy cohort or the supplementation period was not long enough (or both).
Results from the present study failed to identify any ability of the MSP to influence changes in body composition. Other studies have evaluated the ability of probiotics to impact body composition and obesity status with these studies demonstrating conflicting outcomes regarding the ability of probiotics to mitigate body mass and body fat changes. For example, Osterberg et al. (2015) had 20 non-obese males supplement with either a probiotic (VSL#3) or a placebo for four weeks while consuming a high fat, hypercaloric diet. Supplementation with the probiotic effectively offset the observed gains in fat mass and body mass that was seen in those participants consuming a placebo. Coman et al. (2022) also reported that probiotic use was responsible for improved weight loss, body mass index, and waist circumference values supplementing for 90 days with L. plantarum IMC 510 (1.5 × 1010 bacterial cells) in 19 overweight and obese volunteers while no changes were observed with placebo supplementation. Two other studies, one by Dechelotte et al. (2021) reported that supplementing with the probiotic Hafnia alvei HA4597 (100 billion bacteria per day) in combination with a hypocaloric diet over a 12-week period led to a significantly greater number of people who lost at least 3% of their body mass than the placebo group (54.9% vs 41.4%) and another by Cho et al. (2022) reported greater weight loss when a probiotic was added to a reduced calorie diet in 100 healthy obese and overweight subjects after 12 weeks. In contrast, not all studies have demonstrated the ability of a probiotic to positively influence body mass loss or fat loss. Choi et al. (2023) supplemented 152 overweight adults for 12 weeks with either a placebo or L. rhamnosus HA-114 (1 × 1010 cfu/day) and reported no difference in weight loss or fat loss in the probiotic group when compared to the placebo. While previous results do conflict as to whether probiotics can be considered successful weight loss agents, key considerations from the present study and these other studies include the length of supplementation and the inclusion of a hypocaloric diet. To this point, all studies which reported an enhanced potential for weight loss with probiotic use were at least 90 days in duration while our study only lasted for six weeks. Moreover, optimal practices for weight loss studies should include a hypocaloric diet to be followed alongside any supplementation as this is considered ‘best practice’ to achieve weight loss (Miller et al., 1997).
Findings from the present study also suggested improvements in systolic blood pressure secondary to MSP supplementation. Similar results were reported by Mahboobi et al. (2014) who recruited 60 prediabetic patients to supplement with either a placebo or a probiotic for 8 weeks. Moreover, a meta-analysis by Khalesi et al. (2014) summarised the probiotic literature and also reported that probiotic administration exerts a modest ability to improve blood pressure. Hemodynamic outcomes were considered a secondary outcome in our investigation and this would be the first time these outcomes have been reported after supplementing with this combination of probiotic strains. As such, any underlying mechanisms as to why blood pressure levels would be improved are currently unknown. Future research should further examine the potential ability of probiotics to positively impact observed blood pressure levels.
Considering the outcomes presented, some limitations of our study should be acknowledged. First, while dietary patterns have been previously shown to impact the bacterial communities present in the microbiome (Beam et al., 2021; Bibbo et al., 2016; Singh et al., 2017), participants were not required to follow or abide by any specific type of dietary pattern throughout the study protocol. Evaluation of the dietary intake of our participants did determine that no changes in energy or macronutrient intake occurred throughout the study protocol. Moreover, Healthy Eating Index values were calculated and determined that there were no differences in the proportion of various food groups consumed by each group occurred across the study protocol (Walden et al., 2023). These findings limit the possibility that foods containing prebiotics and synbiotics were consumed in varying amounts between the groups. One of the primary underlying mechanisms to explain the changes we observed in sleep quality implies that MSP supplementation altered the composition of the intestinal microbiota which impacted the production of various biomarkers that may have impacted sleep, physical activity, and body composition changes. As such, collecting blood and stool samples would have provided objective outcomes to combine with our subjective assessments to foster a deeper understanding of any underlying mechanistic reasons for our observed outcomes.
5 Conclusions
In conclusion, results from this study indicate that a six-week regimen of a MSP consisting of four probiotic strains (Limosilactobacillus fermentum LF16 (DSM 26956), Lacticaseibacillus rhamnosus LR06 (DSM 21981), Lactiplantibacillus plantarum LP01 (LMG P-21021), and Bifidobacterium longum 04 (DSM 23233 providing a total dosage of 4 × 109 live cells/day) in a cohort of 70 healthy men and women improved subjective ability to fall asleep and daytime dysfunction, which resulted in improved in overall sleep quality.
Corresponding author; e-mail: ckerksick@lindenwood.edu
Acknowledgements
The authors would like to thank Angela Amoruso from Probiotical Research srl, in Novara, Italy for their efforts and support in this project. Your patience and professionalism have helped to make this project a success. In addition, the authors would like to thank the study participants for their commitment to this protocol.
Authors’ contribution
Conception or design of the study: CMK, RJ, MP. Acquisition of data / data collection: KEW, AMH, JMK, JMM, CJG, LEA, PWM, CMK. Analysis and interpretation of data: CMK, PWM, AMH. Drafting work and/or providing critical edits: all authors. Approved final version and agree to be held accountable for its contents: all authors.
Conflict of interest
RJ is scientific advisor to Ashland. For this part, RJ assisted with study design and was not involved in collecting or analysing the data. MP is an employee of Probiotical, the sponsor of the study. All other authors report no conflicts of interest.
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.
Funding
This study was co-sponsored by Probiotical S.p.A. (Italy) and Ashland (USA). The sponsors had no role in collecting the data, analysing the data, interpreting the results, or preparing the manuscript.
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