The clinical trial protocol for this study was approved by the Ethics Committee of Poznań University of Medical Sciences, Poland (approval no. 668/21 issued on 23 September 2021). Furthermore, the trial is registered with ClinicalTrials.gov under the identifier NCT05332626.¹ This investigation rigorously adheres to a comprehensive set of ethical and regulatory standards, as outlined in various legislations and regulations. Additionally, it complies with the CONSORT guidelines, ensuring transparent reporting of the study methodology and results. The study also aligns with the Declaration of Helsinki of the World Medical Association, which incorporates ethical principles for medical research involving humans and adheres to the guidelines set forth by the International Conference on Harmonization of Good Clinical Practice. This meticulous adherence to ethical and regulatory frameworks ensures the protection of participants’ rights, safety, and wellbeing throughout the entirety of the clinical trial.

Initial assessments of postmenopausal patients were conducted at the Department of Treatment of Obesity, Metabolic Disorders, and Clinical Dietetics, Poznań University of Medical Sciences, Poland. To qualify for participation, individuals had to meet specific inclusion criteria, including providing written informed consent, being aged between 45 and 70 years, with a body mass index (BMI) between 27.0 and 34.9 kg/m², and confirming postmenopausal status by experiencing spontaneous amenorrhea for 12 months or longer. Exclusion criteria included a diagnosis of diabetes, secondary obesity, gastrointestinal diseases, recent use of dietary supplements, or pharmacotherapy for lipid disorders or hypertension within the 3 months before enrollment, presence of active clinically significant inflammatory processes, recent antibiotic intake within the month before enrollment, participation in a body mass management study, or use of drugs known to affect body mass. Additionally, individuals who were current smokers or exhibited abuse of alcohol or drugs were also excluded from participation. Those meeting any exclusion criteria were not included in the study and were required to withdraw immediately if any exclusion criteria were identified during the course of the study. The study enrolled 64 subjects who met all inclusion criteria and provided written informed consent, undergoing the randomization procedure.

The study included 64 participants who were randomly assigned to two groups: the placebo group (n = 32) and the probiotic group (n = 32). Patient allocation was conducted in a blinded manner, ensuring both subjects and investigators remained unaware of the distribution. To uphold confidentiality, each participant received a unique identifier code from the study personnel. The randomization process was computer-generated, preventing any adjustments by the researcher directly involved with the patients. Despite stringent randomization procedures, baseline discrepancies were observed between the probiotic and placebo groups, particularly in body composition parameters and serum calcium levels. These differences may be attributed to the inherent challenges in achieving perfect homogeneity in participant characteristics, given the specific inclusion and exclusion criteria applied. While efforts were made to minimize these variations, such as rigorous screening protocols, it is acknowledged that residual confounding factors may have influenced the study outcomes. Out of the initial participants, 55 women completed the intervention and underwent subsequent statistical analysis, with 25 from the placebo group and 30 from the probiotic group. Figure 1 illustrates the study’s progression through a flowchart, showing the number of patients lost to follow-up and explaining the reasons for their exclusion. Moreover, the analyses involved daily records, body composition assessment using the InBody device, serum bone metabolism biomarkers using ELISA, hair and serum calcium analysis using AAS, and bone density profiles using the DXA scanner. The study intervention and measurements were conducted between January 2022 and December 2023.

The probiotic groups were given a daily oral dose of 1 × 10⁹ colony-forming units of L. acidophilus UALa-01™, with the excipient containing microcrystalline cellulose, silica, magnesium stearate, and a gelatin natural capsule. The probiotics were administered after meals in the morning time at 08:00 a.m (± 1 h). In contrast, the placebo group received only the excipient orally, designed to be indistinguishable in taste, smell, and appearance from the probiotic mixture. The placebo also consisted of microcrystalline cellulose, silica, magnesium stearate, and a gelatin natural capsule. The study intervention lasted for 12 weeks, during which participants were explicitly instructed not to modify their regular physical activity. Figure 2, a research flowchart, visually outlines the research process and provides an overview of the assessment of collected samples.

The nutritional content of participants’ daily diets was assessed using a standardized methodology involving a 3-day food recall procedure. This dietary assessment method utilized the 6.0 Diet Program (National Food and Nutrition Institute, Warsaw, Poland), known for its precision and reliability in capturing dietary intake data. Participants were given a questionnaire to record their dietary intake for 3 days before the start of the intervention and for 3 days preceding its conclusion. The 3-day food recall method allowed for the collection of detailed information on participants’ dietary intake, including the types and quantities of foods consumed, meal timing, and cooking methods. Trained research personnel supervised the dietary recalls to ensure accuracy and consistency in data collection. Participants were guided through recalling their dietary intake for the specified periods, with a focus on recording all foods and beverages consumed, along with portion sizes and preparation methods. After completing the dietary recall questionnaires, the collected data were entered into the 6.0 Diet Program for analysis. This software facilitated the calculation of nutrient intakes based on reported food consumption, enabling the assessment of energy, macronutrient, and micronutrient intake levels. Specifically, nutrient compositions such as energy (Kcal), protein (gram), fat (gram), carbohydrates (gram), fiber (gram), calcium (gram), phosphorus (gram), calcium/phosphorus ratio, and vitamin D (gram) were analyzed. The analysis provided insights into the overall nutritional adequacy of participants’ diets and allowed for comparisons between baseline and intervention phases to evaluate the impact of the dietary intervention on dietary quality and nutrient intake patterns.

Baseline and posttrial assessments included anthropometric measurements and body composition analyses. In a dedicated metabolic laboratory, all anthropometric measurements were meticulously conducted with participants wearing light clothing and no shoes, following an overnight fast and a period of rest. Body mass (kg) was measured using electronic scales with precision to the nearest 0.1 kg. BMI was calculated by dividing the mass by the square of the height (kg/m²). Waist circumference (cm) was measured to the nearest 0.5 cm at the end of normal expiration between the iliac crest and the lower rib, providing additional anthropometric insights. Hip circumference (cm) was measured at the widest part of the buttocks, also to the nearest 0.5 cm. The waist-hip ratio was calculated by dividing the waist circumference by the hip circumference. Body composition assessment utilized the InBody 270 system (Cerritos, CA, USA), ensuring a comprehensive analysis of body composition parameters. The InBody 270 device employs a multifrequency 8-point tetrapolar touch electrode system to accurately measure body composition. By applying a range of frequencies to assess impedance across various body segments, the system allows for precise analysis of body adiposity index (BAI) (%), minerals (kg), and lean body mass (kg). Measurements were taken by placing electrodes on the hands and feet, with the device applying a low-level electrical current to measure impedance. Proprietary algorithms were used to analyze impedance data and generate body composition results within seconds. To ensure accuracy and reliability, participants stood barefoot on the device’s foot electrodes while holding onto the hand electrodes during measurements. The InBody 270 then generated a comprehensive body composition report, including values for skeletal muscle mass (kg), body fat percentage (%), and visceral fat level (point). Quality control measures were implemented to maintain consistency and precision throughout the study period. In addition, we acknowledge that certain factors related to participants’ routines or health conditions could potentially affect the accuracy of the results. These factors may include hydration status, meal timing, exercise regimen, and specific health conditions affecting body composition (34). The InBody 270 was equipped with user-friendly software for easy data management and interpretation. Participant data were securely stored within the device’s database, and results were automatically generated and printed for review by the research team. Before data collection, all study personnel underwent training on the proper use of the InBody 270 to minimize measurement error and ensure standardized procedures across all participants.

Blood samples were obtained from a forearm vein after an overnight fast, both at baseline and upon completion of the trial. These samples were collected into serum-separating tubes for subsequent analysis of biochemical markers and minerals. Whole-blood morphological and biochemical parameters at baseline and endline were measured in a certified commercial laboratory (Alab Laboratories, Poznań, Poland) immediately after collection. The serum samples were promptly stored at −80°C to maintain their integrity until analysis. Concurrently, hair samples were gathered at the commencement and conclusion of the trial. Specifically, a hair sample was obtained from the occipital region, and when weighed as a whole, the average weight of the sample was found to be 0.5 grams. The samples were securely stored in individually labeled paper bags. Dyed and permed hair was not collected. Patients were explicitly instructed on the importance of adhering to this collection procedure for obtaining reliable results. Throughout the study, participants were instructed not to use hair spray or hair dye to ensure the purity of the collected samples. Additionally, the mass of each hair sample was meticulously measured. Hair samples were washed in acetone and deionized water, and then dried at 105°C.

Calcium contents in serum and hair samples were analyzed using flame atomic absorption spectrometry (AAS-3, Carl Zeiss, Jena, Germany) following appropriate dilution with deionized water and the addition of 0.5% Lanthanum (III) chloride (Merck KGaA, Darmstadt, Germany). The quantification of calcium content was carried out at a specific wavelength of 422.7 nm. To assess the precision and reliability of this analytical method, certified reference materials, including human serum (Hum Asy Control 2, Sero, Billingstad, Norway) and human hair (NCS DC73347a LGC, Teddington, UK), were used. Results obtained from analyzing these reference materials demonstrated a notably high level of method accuracy, achieving a calculated accuracy rate of 91–93% for calcium quantification.

Commercial enzyme-linked immunosorbent assay (ELISA) kits procured from Qayee Bio-Technology Co., Ltd., Shanghai, China, were used along with absorption spectrophotometry (LEDetect96, Labexim, Lengau, Austria) to measure serum levels of markers associated with bone metabolism. Specifically, CTX and TRAP-5b, indicating bone resorption, were assessed, along with BSAP and PINP, biomarkers reflecting bone formation.

All participants, both before and after the intervention, underwent a DXA scan at the Department of Human Nutrition and Dietetics, Poznań University of Life Sciences, Poland, administered by the same researcher using a GE Lunar Prodigy^® machine (General Electric Healthcare, Madison, WI, USA). During the procedure, participants were asked to remove all metal components from their clothing and accessories to ensure accurate measurements. The BMD (g/cm²) of the L1–L4 lumbar spines, left femur, and total body was assessed using the DXA software (enCORE by General Electric Healthcare, Madison, WI, US). Daily rigorous calibration and quality control of the DXA equipment were carried out to maintain the stability and reliability of the system. This meticulous approach to DXA scanning enhances the precision and credibility of the BMD assessments in our study.

IBM^® SPSS^® Statistics version 22 for Windows (Chicago, IL, US) was used for statistical analysis and figure generation. Measurements were presented as mean and median values, accompanied by their corresponding standard deviations with interquartile range. This approach provides a comprehensive depiction of the data distribution and variability, ensuring a thorough understanding of the central tendency and spread within the dataset. In addition to the analysis conducted, the normality of the data distribution was assessed using the Shapiro–Wilk test to ensure adherence to statistical assumptions crucial for subsequent analyses. Statistical analysis was performed to ascertain the significance of observed differences. For comparisons within the same group before and after the intervention (dependent groups), the Wilcoxon matched pairs test was used. For comparisons between the placebo and probiotic groups (independent groups), the Mann-Whitney U test was employed. The predetermined significance threshold for all observed differences was set at a 5% probability level. To investigate the relationships among serum calcium levels, bone biomarkers, and BMD profiles, Spearman’s correlation analysis was employed. Furthermore, careful consideration was given to determining an appropriate sample size, with a minimum requirement of 25 subjects in each group established. This study followed the methodology outlined in the study by Soleimani et al. (35). A power calculation was performed considering a type I error (α) of 0.05 and a type II error (β) of 0.20, resulting in a power of 80%. Based on these parameters, it was determined that a minimum of 25 subjects in each group would be necessary to detect statistically significant differences. This calculation accounted for the primary outcome measures, including changes in serum and hair calcium levels, as well as BMD profiles. This meticulous approach to assessing data distribution and determining sample size contributes to the methodological rigor of the study, enhancing its ability to produce robust and reliable findings within the specified statistical framework.

Table 1 depicts the dietary patterns of the study participants at baseline and endline. Before the intervention, no significant differences were observed in dietary intake variables between the placebo and probiotic groups. However, after the 12-week intervention, the probiotic group displayed a noticeable increase in energy, protein, carbohydrates, calcium, and phosphorus intake compared to the placebo group. Moreover, the placebo group exhibited a significant decrease in energy intake from preintervention to postintervention. Conversely, the probiotic group demonstrated a significant increase in dietary calcium intake at endline across all observed variables compared to the baseline period.

Table 2 displays the body composition and anthropometric profiles of study participants at baseline and endline. Before the intervention, significant differences were observed between the placebo and probiotic groups, including body mass, BMI, waist circumference, hip circumference, and BAI, with the probiotic group demonstrating lower values in these variables compared to the placebo group. Following the 12-week intervention, the probiotic group exhibited a noteworthy reduction in the percentage of body fat and visceral fat between preintervention and postintervention assessments. However, it is important to note that these changes were not significantly different when compared to the placebo group.

Table 3 illustrates the blood morphology profiles of study participants before and after a 12-week intervention. Before the intervention, significant differences were observed between the placebo and probiotic groups in hemoglobin, hematocrit, and triglyceride levels, with the probiotic group exhibiting significantly lower levels of these variables than the placebo group. Following the intervention period, the placebo group demonstrated significant decreases in hemoglobin and hematocrit values compared to the preintervention period. It is noted that the probiotic group exhibited significantly lower levels of hemoglobin, hematocrit, and triglycerides compared to placebo group at the preintervention period. Conversely, the placebo group demonstrated a significant decrease in hemoglobin and hematocrit levels following the intervention period. However, it is important to note that despite these changes, all values remained within the normal physiological range for postmenopausal women, and there were no significant differences observed between the probiotic and placebo groups. In contrast, the probiotic group exhibited a significant increase in glucose concentration from the preintervention to the postintervention period. However, it is noteworthy that no significant difference in glucose concentration was observed between the probiotic group and placebo group at the postintervention period.

Table 4 presents the results of calcium concentration in serum, hair, and bone metabolism biomarkers of study participants before and after a 12-week intervention. Before the intervention, the placebo group exhibited significantly lower calcium concentration in serum compared to the probiotic group, although no significant differences were observed in calcium concentration in hair and bone metabolism biomarkers between the two groups at baseline.

At the endline period, no significant differences were found between the placebo and probiotic groups. Additionally, the placebo group exhibited a significant increase in serum calcium levels compared to the baseline period. Furthermore, after the 12-week intervention, the placebo group showed a significant decrease in CTX levels and a significant increase in TRAP-5b levels compared to the baseline period. In contrast, the probiotic group demonstrated a significant decrease in serum calcium levels compared to the baseline period. No significant differences were noted in hair calcium, bone resorption, and bone formation biomarkers within the probiotic group between the preintervention and postintervention periods.

Table 5 displays the BMD profiles of the lumbar spine, left femur, and total body before and after a 12-week intervention period. No significant changes in BMD levels were observed in either the placebo or probiotic groups from baseline to endline. However, it is worth noting that during the baseline period, the probiotic group exhibited a significantly lower BMD level at the left femur compared to the placebo group.

Table 6 presents a comparison of differences in BMD profiles assessed by DXA between the placebo and probiotic groups at baseline and endline. Although significant differences in the comparison between preintervention and postintervention periods were not observed in either the placebo or probiotic groups, it is noteworthy that the probiotic group, consumed by postmenopausal women for 12 weeks, demonstrated slightly larger differences in BMD across the spine, left femur, and total body, ranging from −0.01 to 0.00 g/cm², compared to the placebo group, which showed no change.

The strengths of our study are rooted in its rigorous methodology, which includes a controlled and randomized clinical design, meticulous measurement of key parameters, and comprehensive analysis of outcomes. Additionally, the use of advanced devices like the InBody for body composition assessment and DXA as the gold standard for assessing BMD enhances the reliability and precision of our findings. These robust methodological approaches bolster the reliability and validity of our findings, providing valuable insights into the potential clinical implications of probiotic supplementation in this demographic.

While our study represents a significant step forward, it is crucial to acknowledge certain limitations. These include the omission of measurements for inflammatory cytokine markers (70) and short-chain fatty acids (56), which are essential for a comprehensive understanding of the gut microbiota–bone interaction. Additionally, a detailed exploration of gut microbiota composition (51), intervention duration (59), and calcium transporter markers (71) was beyond the scope of our study, allowing for further investigation in subsequent research endeavors.

Furthermore, the short-term intervention period of 3 months in our study might not entirely capture the long-term benefits of probiotic consumption for menopausal women. Prior studies have indicated the beneficial effects of probiotics on bone health following longer intervention durations, spanning from 6 months (21, 70) to 12 months (72–74). Future studies with extended intervention periods could offer valuable insights into the sustained impact of probiotic supplementation on bone health outcomes in postmenopausal women.

Therefore, while our study provides valuable insights into the effects of probiotic supplementation on calcium status, bone metabolism biomarkers, and bone mineral density profiles in postmenopausal women, several limitations must be addressed. Firstly, we acknowledge that not screening for osteoporosis at baseline could impact the interpretation of our results, given that menopause is a known risk factor for osteoporosis. Secondly, although randomization was employed to minimize confounders, the lack of homogeneity in the study group remains a concern, potentially introducing variability among participants. Additionally, we recognize the importance of analyzing the composition of the gut microbiome at baseline and post-intervention to assess the effects of administering L. acidophilus, a consideration for future research. Furthermore, while our study was conducted over a 12-week period, future studies with longer durations at least a year are warranted to evaluate the sustained benefits of probiotic administration on overall bone health. Lastly, self-reported data may be prone to recall bias and might not accurately capture the intricacies of participants’ dietary habits. Moreover, relying solely on questionnaires lacks real-time or objective measures of dietary intake, potentially introducing inaccuracies into the analysis. Additionally, our study did not include continuous monitoring of dietary intake throughout the entire 12-week intervention period, representing another limitation. Continuous monitoring could offer valuable insights into changes in dietary patterns over time and their impact on study outcomes. By delving into these unexplored facets, researchers can contribute to the development of more effective nutritional interventions aimed at improving bone health in postmenopausal women.

Our study carries significant clinical implications for the bone health of postmenopausal women. The findings highlight the potential advantages of probiotic supplementation in managing bone health parameters. Understanding the effects of probiotics on calcium status, bone metabolism biomarkers, and BMD profiles offers valuable insights for healthcare providers. Integrating probiotic supplementation into tailored nutritional interventions for postmenopausal women could potentially reduce the risk of osteoporotic fractures and improve overall bone health. This study adds to the increasing body of evidence advocating for the incorporation of probiotics into clinical practice to optimize bone health outcomes in this population.