The effect of non-pharmacological interventions on bone health among patients with low bone mass: a systematic review and meta-analysis

Background and objective: Low bone mass represents a critical period for “watchful waiting” interventions to prevent osteoporosis. This systematic review provides a comprehensive overview of non-pharmacological interventions for patients with low bone mass.

Methods: We included randomized controlled trials (RCTs) investigating the efficacy of non-pharmacological interventions for improving bone health outcomes in participants with low bone mass. Publications were collected from three databases. A meta-analysis was performed for outcomes reported in three or more articles, with changes in outcomes expressed as mean differences (MD) or standardized mean differences (SMD) with 95% confidence intervals (CIs).

Results: A total of 26 eligible articles were included. Exercise interventions increased serum osteocalcin levels (SMD = 1.26, 95% CI: 0.22–2.31) compared to the control group. Narrative synthesis of studies showed a protective effect of exercise on lumbar spine and femoral neck BMD. For nutrition interventions, polyphenol extracts showed efficacy in improving lumbar spine BMD. The results of collagen supplements were inconsistent, and the effects of micronutrients were limited.

Conclusion: In conclusion, more evidence from RCTs, particularly those investigating comprehensive lifestyle interventions and tailored prevention for moderate and severe low bone mass, especially among older men, is necessary.

1 Introduction

The World Health Organization defined osteoporosis in 1994 as a “progressive systemic skeletal disease characterized by low bone mass and microarchitectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture” (1). Recently, multimodal and comprehensive approaches have been recommended for diagnosing osteoporosis, incorporating individual fracture risk, clinical history, physical examination, suggestive symptoms (e.g., height loss, back pain, and/or fractures), and vertebral imaging (2, 3). The prevalence of osteoporosis worldwide is estimated to be 18.3%, with higher rates among women (23.1%) compared to men (11.7%) (4). It is a leading cause of fractures and is associated with increased mortality risk among older individuals, making it a significant global public health concern (5–7).

Low bone mass—often referred to as osteopenia in postmenopausal women and men aged ≥ 50 years—is an intermediate stage between normal bone mineral density (BMD) and osteoporosis (3). It is characterized by a T-score derived from BMD value that falls more than 1 standard deviation (SD) but less than 2.5 SD below the BMD of the reference population. As the condition progresses, it reaches the diagnostic threshold for osteoporosis, defined by a T-score of BMD less than -2.5 (8). The prevalence of low bone mass was estimated to be 40.4% in the population aged over 50 years, more than double the prevalence of osteoporosis (9). Moreover, in women, it is estimated that more than 50% of fragility factures occur in those with low bone mass rather than osteoporosis (10). Thus, low bone mass as the pre-clinical stage of osteoporosis serves as a critical window for interventions aimed at slowing down the progression of low bone mass and reducing the risk of osteoporosis and fractures (11).

Pharmaceutical agents that target BMD are commonly used as a first-line treatment of osteoporosis, with their effect in reducing fracture risk by 30% to 50% (12). However, these medications are typically limited to osteoporotic patients, despite studies also showing that pharmacological treatment with zoledronate significantly reduced the risk of fractures in older women with low bone mass (2). In addition, barriers to adoption of pharmaceutical treatment to prevent and treat osteoporosis have been identified from both the perspective of patients and physicians (13). These factors further contribute to the risk of fracture in individuals with low bone mass.

Non-pharmacological management of osteoporosis mainly involves lifestyle modifications, including adopting healthier diets, calcium and vitamin D supplementation, adequate weight-bearing exercise, smoking cessation, and avoidance of excessive alcohol consumption (2). From a practitioner perspective, the stage of low bone mass is considered a period of “watchful waiting” to prevent transition into osteoporosis (14). Although direct evidence comparing intervention responses between populations with low bone mass and others (e.g., those with normal BMD or established osteoporosis) is limited, some studies provide indirect evidence suggesting that the effects may differ between these populations. For example, a trial found that the effect of exercise training on BMD changes depended on baseline BMD among postmenopausal women without osteoporosis treatment (including those with low bone mass and normal BMD), indicating lifestyle interventions may have greater effects among individuals with low BMD (15). Another systematic review and meta-analysis of randomized controlled trials (RCTs) showed that the effect of exercise on BMD varied across different health status and body sites (16). On the other hand, unlike in osteoporosis, where medications are essential for fracture prevention and non-pharmacological strategies serve as supplements, this may not be the case for low bone mass (3, 17, 18). Compared with individuals with established osteoporosis, people with low bone mass may retain greater residual bone remodeling capacity and exhibit higher adherence to lifestyle interventions due to the absence of overt disease or medication burden (19). To develop evidence-based approaches for maintaining bone health, preventing osteoporosis, and reducing the burden of fractures, it is important to understand the potential benefits and limitations of non-pharmacological treatments in addressing low bone mass. However, to date, there has been no comprehensive systematic review that specifically examines the effect of lifestyle interventions on low bone mass, despite existing reviews reporting benefits of exercise or nutritional interventions on bone health in mixed populations without distinguishing between osteopenia and osteoporosis (20, 21).

To fill this knowledge gap, the objective of this systematic review was to synthesize evidence from RCTs on the effects of non-pharmacological lifestyle interventions in populations with low bone mass. By focusing specifically on this population, we aimed to provide a comprehensive evaluation of intervention efficacy and limitations, thereby offering valuable insights for clinicians, researchers, and policymakers.

2 Materials and methods

We conducted a systematic review and meta-analysis following the guidelines outlined in the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement (Supplementary Table S1) (22). This study has been registered in PROSPERO (CRD42023466865).

2.1 Data sources and searches

The search strategy can be found in Supplementary Table S2. To ensure comprehensive coverage of relevant literature, we adopted a deliberately broad search approach. Searches were conducted for articles in PubMed, Web of Science, Embase, and CINAHL, spanning from the inception of the databases to May 17th, 2023, updated on January 28th, 2024. The search strategy employed a combination of free-text and Medical Subject Headings (MeSH) terms, involving a comprehensive set of terms related to the low bone mass (low bone mass, low BMD, osteopenia, etc.), “non-pharmacological treatment”, “lifestyle”, specific lifestyle factors (exercise, physical activity, sport, nutrition, dietary, food, supplement, smoking, alcohol, etc.), “randomized controlled trial (RCT)”, and “adults”. EndNote X9 was used for reference storage and management. Each retrieved record was independently assessed for eligibility by two reviewers, with any discrepancies resolved by consultation with a third reviewer.

2.2 Study selection

Specific inclusion criteria are detailed in Table 1. We included RCTs investigating the efficacy of non-pharmacological interventions in enhancing bone health outcomes in participants with low bone mass published in English. In cases where multiple publications reported overlapping data from the same RCT, the study with the largest sample size or the longest intervention duration was selected to avoid duplicate inclusion of participants.

Table 1

Table 1. PICOS criteria in this study.

2.3 Data extraction and quality assessment

Information from eligible articles was independently and directly extracted using standardized data extraction templates. The extracted data included the following information:

1. Study details: First author, title, and publication year;

2. Characteristics of the study and population: Sample size, study design, country where the study was conducted, baseline age of participants, and body sites of low bone mass;

3. Details of the lifestyle intervention: Type, content, dosage, frequency, and duration;

4. Measurement methods and value for outcomes, including baseline and post-intervention values, and change values, which available.

The revised Cochrane risk-of-bias tool for randomized trials (ROB 2) was used to assess the risk of bias of studies (23). This checklist consists of five domains: the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported results. The overall bias of each study was determined as “low risk of bias”, “some concerns”, and “high risk of bias”.

2.4 Categorization of evidence levels and statistical analysis

An evaluation system was utilized to assess the effects of intervention and categorize evidence levels adapted from a previous systematic review (24). The results for bone health outcomes from each study were recorded, excluding the intervention that solely reported by one study. Briefly, intervention effects were classified as “positive (+)”, “negative (-)”, “no effect (0)”, and “inconsistent (?)” according to the percentage of RCTs reporting significant effects. A “positive”, “negative”, or “no effect” classification was assigned if ≥ 60% of studies reported the respective outcome, a threshold chosen a priori based on previous systematic reviews (24). Conversely, an “inconsistent” classification was assigned when none of either three categories reached 60%, or only one study reported the outcome. The “inconsistent” label was applied when results were mixed, or the number of studies was insufficient, to reduce the risk of drawing misleading conclusions.

A meta-analysis was conducted to synthesize data across multiple studies for outcomes reported in three or more articles. The mean difference (MD) with 95% CIs of change value from baseline to endpoint was used as the summary statistic for continuous data. If the MD and the standard deviation (SD) for change was not reported, they were calculated using Equation 1 and Equation 2, as recommended by the Cochrane Handbook (25). This calculation assumed a correlation coefficient (R) of 0.5 for Equation 2. In cases where different assessment methods were employed or different unites that could not be unified across various articles, the standardized mean difference (SMD) was used as the summary statistic.

$\begin{array}{ll}{\text{MD}}_{\text{change}}={\text{Mean}}_{\text{endpoint}}-{\text{Mean}}_{\text{baseline}}& (1)\end{array}$

$\begin{array}{ll}{\text{SD}}_{\text{change}}=\sqrt{{\text{SD}}_{\text{ baseline}}^2+{\text{SD}}_{\text{ endpoint}}^2-(2\times \text{R}\times {\text{SD}}_{\text{ baseline}}\times {\text{SD}}_{\text{ endpoint}})}& (2)\end{array}$

If multiple time points were reported for the outcomes, data from the last time point were selected. Heterogeneity among studies was assessed using the I-square statistic (I²) and categorized as low (I² ≤ 40%), moderate (40% < I² ≤ 70%), and high (I² > 70%) (26). Studies with p-values of ≥ 0.1 and I² of ≤ 40% were estimated using a fixed-effects model; otherwise, the random-effects model was applied. Egger’s test was employed to explore potential publication bias. All meta-analyses were performed using meta package (version 7.0-0) in R 4.1.1 (R Core Team, Vienna, Austria). A p-value of <0.05 was considered statistically significant.

3 Results

3.1 Characteristics of included articles

The study flowchart is shown in Figure 1. Twenty-six RCTs met the inclusion criteria: exercise alone (nine studies), nutrition alone (eighteen studies), and a comprehensive intervention combining exercise and nutrition (one study) (27–50). Among these articles, one study included multiple arms and investigated all three types of interventions. Most studies enrolled postmenopausal women; only one included both men and women. Overall, 2,143 individuals were included from 14 countries, across Europe (nine studies), Asia (six studies), North America (five studies), Oceania (two studies), and South America (two studies). Among them, 285 were allocated to exercise interventions, 853 to nutrition interventions, 37 to comprehensive interventions, and 968 to control groups.

Figure 1

Figure 1. Flowchart of study identification and screening.

The included studies assessed various bone health outcomes. BMD (g/cm²) at different skeletal sites was measured using dual-energy X-ray absorptiometry (DXA) (3). Two studies evaluated bone mineral content (BMC) at specific skeletal sites (51). Additionally, seventeen studies analyzed bone turnover markers (BTMs), including formation markers bone-specific alkaline phosphatase [BALP], osteocalcin [OC], and procollagen type I N-terminal propeptide [P1NP]), resorption markers (C-terminal telopeptide of collagen [CTX] and N-telopeptides of type I collagen [NTX], calcium and phosphorus metabolism markers (parathyroid hormone [PTH] and 25-hydroxyvitamin D [25-OH-D3]), as well as selected hormones and cytokines (interleukin 1 [IL-1], interleukin 6 [IL-6], tumor necrosis factor [TNF-α]). Detailed study characteristics are presented in Table 2.

Table 2

Table 2. Basic characteristics of included studies.

3.2 Quality assessments of included articles

Quality assessment results (ROB 2) are shown in Figure 2. Seventeen were rated as low risk of bias, 6 had some concerns, and 3 as high risk of bias, based on the ROB 2 tool.

Figure 2

Figure 2. Results of quality assessment for (A) all the studies and (B) each study.

3.3 Categorization of evidence levels and statistical analysis

3.3.1 Exercise

Nine studies examined exercise interventions, including single exercise types (e.g. resistance training, step aerobics, and Tai Chi) and multicomponent programs combining various exercise types (28, 29, 33, 39, 42, 48, 50, 52, 53). Four studies reported to follow American College of Sports Medicine (ACSM) guidelines (28, 33, 39, 50), and one adhered to exercise recommendations for postmenopausal women with osteoporosis (42), including parameters of frequency, intensity, and duration. Other studies, while not explicitly citing formal guidelines, described protocols with appropriate loading parameters (e.g., % 1RM resistance) or referenced supporting literature (29, 48, 52, 53). The intervention frequency and duration were similar, with sessions typically lasting 60 to 90 minutes. This duration included a warm-up period of 5 to 15 minutes, followed by a training session lasting 45 to 80 minutes. The interventions were typically conducted three times per week. However, the duration of the intervention periods varied across the studies, ranging from 8 weeks to 52 weeks.

Fewer than three trials examined any single exercise modality for a given outcome, limiting our ability to assess modality-specific effects. However, bone adaption is site-specific, meta-analyses were conducted on studies reporting outcomes at the same skeletal site.

Interventions using single exercise types aimed to increase muscle strength through activities such as isometrics, push-ups, and squats (29, 52), improve endurance through aerobic exercises like step aerobics and jump rope (29, 50), or enhance mind-body coordination through Tai Chi (48). Multicomponent programs incorporated various types of exercises and psychological elements, and repeating load bearing exercise through circuit training (39). Others combined a traditional Chinese medicine exercise practice known as Yi Jin Jing with elastic band resistance exercise, as well as a combination of resistance training, impact loading, and balance exercises (29, 33, 39, 42, 53).

3.3.1.1 Meta-analysis

Figure 3 shows the results of the meta-analysis for total hip BMD, lumbar spine BMD, and OC, respectively. Increased serum OC was also observed (SMD = 1.26, 95% CI: 0.22–2.31). The intervention included a mixture of multicomponent programs (isometric strengthening and high-impact exercises, Yi Jin Jing plus elastic band resistance exercise, and full-body strength training combination) and jump rope (28, 39, 42, 50). However, no significant difference was found for total hip and lumbar spine BMD. Egger’s test did not indicate small-study effects for lumbar spine (P = 0.365) or total hip (P = 0.233); the test for OC was borderline (P = 0.051). FN BMD data were insufficient for meta-analysis.

Figure 3

Figure 3. Forest plot of comparing (A) total hip bone mineral density, (B) lumbar spine bone mineral density, and (C) osteocalcin between exercise intervention and control group. CI, confidence interval; MD, mean difference; SD, standard deviation; SMD, standardized mean difference.

3.3.1.2 Narrative synthesis

The evidence categorization presented in Table 3 indicated a positive effect of exercise interventions on lumbar spine and FN BMD, as well as increased OC. No significant effects were observed on whole body BMD, whole body BMC, and the impact on other outcomes (total hip BMD, lower limb and total hip BMC, BALP CTX, NTX, PTH, BAP/TRAP5b, and 25-OH-D3) could not be determined due to the limited data.

Table 3

Table 3. Level of evidence examining the effects of different non-pharmacological interventions.

Single-mode exercise interventions demonstrated a positive impact on lumbar spine and FN BMD. However, the effects on BMD for other sites and BTMs varied (28, 48, 50, 52). Multicomponent exercise interventions demonstrated positive effect on FN BMD (29, 33, 39, 42, 53).

3.3.2 Nutrition intervention

A total of 18 studies investigated the effect of dietary or nutrition interventions, including micronutrient supplements (six studies), collagen or milk-derived protein matrix supplements (five studies), polyphenol extracts (four studies), dried plum (one study), probiotic supplement (one study), and creatine (one study). The intervention frequency was consistent across the studies, typically on a daily basis. However, the duration of the interventions varied, ranging from 12 weeks to 3 years. Most studies provided both intervention and placebo groups with calcium and vitamin D to meet essential nutrient needs.

3.3.2.1 Micronutrient supplements or fortified foods

Both single and multiple micronutrients (MMN) were tested. The most consistent finding was a decrease in undercarboxylated osteocalcin (ucOC) (Table 3). Two studies investigated the effects of vitamin K supplementation with one using vitamin K1 (31) and the other with vitamin K2 (46). For both studies, the effects of vitamin K on other outcomes could not be determined due to limited number of studies. Other single nutrients (potassium citrate, vitamin E) showed no BMD/BTM changes, except vitamin E reduced CTX (31, 46).

Two studies examined the effects of MMN. One study involved a combination of vitamin D3, vitamin K2, melatonin, and citrate, while the other study used a combination of vitamin C, vitamin E, selenium, and alpha-lipoic acid. Although both studies showed some benefits for bone health outcomes, the heterogeneous outcomes precluded firm conclusions (43, 44).

3.3.2.2 Collagen or other proteins supplements

Five studies investigated the effectiveness of protein supplements, with four using collagen supplements, reporting inconsistent findings, as shown in Table 3. Among them, two with calcium-collagen chelate or ossein hydroxyapatite and calcium carbonate complex improved whole BMD and pain (30, 34). However, these effects were not observed in the other two RCTs with collagen hydrolysate or collagen peptide (27, 32). Another RCT reported a calcium-fortified, milk-derived protein matrix increased P1NP levels and reduced CTX levels, while showing no effects on BMD or other serum markers (45).

3.3.2.3 Polyphenol extracts

Three studies examined the effects of polyphenol extracts from different sources, including red clover, olive, and green tea. As shown in Table 3, they all reported significant effects on improving lumbar spine BMD (35, 40, 48), but effects on other outcomes were inconsistent.

3.3.2.4 Food interventions

We only identified one study that investigated the effects of dried plum on bone health in the US (37). The study demonstrated a beneficial effect in improving several BTMs and bone BMD but not for other markers.

3.3.2.5 Other nutrition interventions

Other nutrition interventions included probiotics and creatine. One RCT reported that the probiotic supplement reduced BALP, CTX, and PTH but did not affect BMD or other BTMs (38). Another RCT with creatine supplementation showed no significant effects on BMD, microarchitecture parameters, or BTMs (47).

The summary of the results is shown in Figure 4.

Figure 4

Figure 4. Summary of effect of non-pharmacological interventions on bone health among patients with low bone mass. Created in BioRender. ZHANG, J. (2025) https://BioRender.com/01390wd.

4 Discussion

This systematic review and meta-analysis identified twenty-six non-pharmacological intervention studies focused on individuals with low bone mass. In this review, low bone mass was defined as a T-score between −1.0 and −2.5, based on the diagnostic criteria established by the World Health Organization expert working group (54). Our analysis suggested that exercise interventions led to a significant increase in lumbar spine and FN BMD as well as OC levels in participants with low bone mass. In terms of nutrition interventions, we found that polyphenol extracts from various plant sources showed effectiveness in improving lumbar spine BMD. However, the effects of other nutrition interventions reviewed were found to be limited.

4.1 Exercise and low bone mass

Physical exercise is the most effective non-pharmaceutical fracture prevention strategy (55). However, the precise mechanisms through which exercise impacts bone health are not yet fully understood. Exercise affects bone health by influencing apoptosis, inflammatory response, and autophagy (56). It may also affect the epigenetic mechanisms of bone metabolism by regulating non-coding RNAs and DNA methylation (56). Exercise may also increase serum vitamin D levels and affect BTMs (57). According to our synthesis of studies, exercise intervention programs designed with frequency, intensity and time parameters in line with established exercise guidelines for bone health—such as those from the ACSM or recommendations for postmenopausal women—resulted in increased lumbar spine and FN BMD. However, we did not observe similar effects on BMD at other sites. These findings align with previous reviews conducted in individuals aged 65 years and above (58, 59) as well as in patients with osteoporosis and low bone mass (58, 59).

Furthermore, our study showed that exercise increased OC, but not other BTMs. While we did not find similar reviews specific to population with low bone mass, previous reviews in the general population have demonstrated effects of acute exercise on various BTMs, including increased OC (60, 61). It is important to note that some studies have observed a negative association between OC level and BMD (62). As exercise can influence multiple functions of OC (60), OC alone may not be a reliable marker of high bone turnover status in postmenopausal osteoporosis, considering the fact that changes in OC levels may not solely reflect alterations in bone metabolism (63). Of note, Egger’s test yielded a borderline result (P = 0.051), suggesting a possible risk of publication bias that should be interpreted with caution. Therefore, the significance of the increase in OC through exercises and its relation to long-term outcomes in population with low bone mass need further verification.

Notably, according to the studies, half of the exercise protocols were reported to meet recommendations for bone health in adults by ACSM, typically involving 60- to 90-min sessions for three times a week (64, 65). Moreover, although the two included short-term studies may limit the interpretation of long-term effects (shorter than three months), one of them still demonstrated measurable improvements in bone health. The role of exercise in maintaining or increasing BMD remains inconclusive. Nevertheless, even older individuals with frailty are advised to remain physically active according to standard exercise recommendations, due to the rapid and profound effects of immobilization on low bone mass and the poor prognosis for mineral recovery after remobilization (66). Notably, safety considerations should be taken into account, and the type, frequency, and duration of exercise may need to be adjusted (67). For example, both higher-impact activities and resistance exercises with higher impact have demonstrated greater benefits for bone health compared to lower impact sports, but individual responses to exercise can vary, leading to the conservative prescription of training loads to balance efficacy and safety.

The effects of different exercise interventions on BMD vary depending on whether single type or multicomponent exercises are utilized, but the limited number of studies examining each type of intervention, particularly for single type exercises, hinders a comprehensive evaluation of their diverse impacts on specific outcomes in population with low bone mass. Current guidelines for osteoporosis prevention and treatment recommend weight-bearing exercises for BMD benefits, while strengthening exercises and balance training may help maintain bone mass and prevent of fall-related fractures. A meta-analysis suggests that combining different exercises in postmenopausal women appears to be effective in preserving BMD at various skeletal sites (68). This is believed to be achieved by generating diverse mechanical strains and impacting different loading areas of the bones.

Therefore, future research should prioritize investigating the minimum effective dosage and impact of different exercise types, including the combined effect of diverse exercises, as an exercise intervention for low bone mass. Such investigations will enhance our understanding of the specific role of exercise in managing low bone mass and improving bone health.

4.2 Nutrition intervention and low bone mass

Previous meta-analyses and clinical guidelines have already established that individuals with osteoporosis should receive calcium and vitamin D supplementation to reduce fracture risk and improve bone health (3, 69); therefore, none of the included studies specifically examined these two nutrients as standalone interventions. Our review identified nutrition interventions that go beyond calcium and vitamin D with the aim of enhancing bone health outcomes in population with low bone mass. These interventions include micronutrients, collagen supplementation, polyphenol extracts, and other nutrition solutions such as probiotics, dried plum, creatine, and milk-derived protein matrix fortified with calcium. The rationale behind these interventions is to improve calcium absorption efficiency, promote bone metabolism, and provide antioxidant properties to individuals with low bone mass.

However, the number of studies investigating similar nutrition interventions was limited, which hindered the possibility of conducting a meta-analysis to evaluate effect of interventions on bone health outcome. The level of evidence evaluation yielded a mixed result.

4.2.1 Vitamin K and multiple micronutrient supplementations

The studies in this review included the effects of vitamin K supplementation and the use of a multi-micronutrient approach.

For vitamin K, two RCTs showed that vitamin K had no significant effect on BMD for population with low bone mass. Vitamin K is recognized as an essential nutrient for bone health as it participates in carboxylation of bone-related proteins, regulates the genetic transcription of osteoblastic markers, and helps regulate bone reabsorption (70, 71). However, different reviews examining the relationship between vitamin K supplementation and bone health outcomes have reported inconsistent conclusions due to heterogeneity across studies (72, 73). A subgroup analysis from the meta-analysis conducted by Huang et al. indicated a significant improvement in vertebral BMD for postmenopausal women with osteoporosis in the vitamin K2 group, but no significant difference in BMD changes was observed in the non-osteoporosis subgroup (74). The authors suggested that two potential reasons: 1) higher baseline BMD in non-osteoporotic participants yields smaller relative percent changes for the same absolute change; 2) greater baseline mineralization may limit additional mineral accrual. In this review, the two included studies utilized different forms of vitamin K, with only one study each, thus limiting the ability to reach conclusions.

Moreover, vitamin K supplements decreased total OC level, which differed from previous studies showing that vitamin K increased OC and decreased ucOC (75, 76). The decreased OC observed in our study might be explained by two hypotheses: (1) improved vitamin K status leads to more OC being carboxylated to its bioactive form, resulting in less OC being needed, synthesized, and released into the circulation (31); (2) more functional OC will be bound to bone rather than circulating in the blood stream, thereby lowering the serum total OC level (77). However, it should be noted that the included studies exhibited methodological heterogeneity, with variations in the type of vitamin K supplements (vitamin K₁ and K₂) which have different bioavailability and half-lives (78). Therefore, for population with low bone mass, further studies are needed to draw conclusive evidence on the effects of vitamin K combined with vitamin D or calcium on bone health outcome, as it has been suggested that this combination may have a greater synergistic effect in reducing low bone mass (79, 80).

For MMN, two studies were included with both reporting observed favorable effects on bone health. However, due to the limited number of only 2 studies available using different MMN combination, we were unable to draw a definitive conclusion. Nevertheless, existing evidence has shown that micronutrients such as calcium, vitamin D, vitamin C, and vitamin E play important roles in preventing low bone mass (81, 82). Although there has not been a comprehensive review on the relationship between MMN supplements and bone health, increasing evidence suggests that through synergistic effect, combined effects of two or more nutrients working together have a greater physiological impact on the body than when each nutrient is consumed individually (83). Therefore, to further examine the health effects of MMN on low bone mass, studies with a clear mechanism-driven approach that target the combined use of different micronutrients for population with low bone mass are needed.

4.2.2 Collagen supplementations

Collagen, a major component of the organic bone matrix, may promote osteoblastic cell growth and differentiation while reducing osteoclastic activity, thereby supporting bone formation and mineralization. It increases osteoblastic cell growth and differentiation while reducing osteoclastic cells (84). Additionally, collagen may play a role in downregulating the production of pro-inflammatory molecules implicated in osteoporosis and low bone mass development (85).

In our study, the results for dietary collagen supplementation on bone health outcome in women with low bone mass were mixed. Few reviews have examined the effects of collagen or calcium-collagen chelate in patients with osteoporosis, with only one systematic review published in 2016 concluded that collagen might have a positive effect on osteoporosis, based only on two animal experiments (84).

The mixed results observed in our study can be attributed to several factors. Firstly, the efficacy of bone protection is influenced by the structure and quantity of peptides derived from collagen (84). Included interventions comprised collagen hydrolysates and calcium-collagen chelates, which may differ in digestion, absorption and bioavailability. Additionally, the calcium status of the subjects may have an impact on calcium retention and bone resorption, which could further contribute to the variability in the results (32). Therefore, further research direction should focus on the following aspects: (1) characterize the structure and number of peptides that relevant to low bone mass improvement; (2) considering calcium condition of the subjects when designing intervention research with collagen.

4.2.3 Polyphenol extracts supplementations

In our study, the included RCTs using polyphenol extracts showed significant improvements in lumbar spine BMD but not in other outcomes of bone health. A recently published systematic review differed slightly from our results, indicating that polyphenol supplements increased BALP among postmenopausal women, while a significant effect on lumbar spine BMD only emerged for intervention with duration of lasting over 24 months (86). Trials used different types of polyphenols, which may exert distinct mechanisms relevant to bone health (87). Isoflavones, one of the most important categories of polyphenols, exert a pro-estrogenic activity on bone, and thereby inducing osteoclast apoptosis (88). Further exploration is needed to determine the effectiveness of different types of polyphenol extracts on bone health among individuals with low bone mass, using more robust evidence.

4.2.4 Whole food supplementations (dried plum)

We found only one study involving a whole-food intervention with dried plums, or prunes, as intervention. Daily consumption of dried plum was reported to improve low bone mass in older, postmenopausal women with low bone mass (89). However, since there is only one RCT available, the evidence for its effect on low bone mass remains unverified.

Furthermore, while the role of foods such as dairy products in improving bone health has been well-established, which have found that dairy products, with or without vitamin D, increase BMD (90), further studies focusing on effect of whole food and dietary pattern as interventions may provide valuable evidence to investigate the potential benefits for population with low bone mass. These types of interventions are more likely to promote compliance and provide a comprehensive understanding of the impact of dietary patterns on bone health outcomes.

4.2.5 Other nutrition supplementations

This review also identified other nutrition interventions, including one study on probiotics and another on creatine, for improving bone health in individuals with low bone mass. However, due to the limited number of studies available, no definitive conclusions can be drawn. Currently, there is a growing focus on researching the health benefits of probiotics, although their impact on population with low bone mass is less explored and merits further investigation.

4.3 Other research gaps on non-pharmacological intervention for low bone mass

This review has identified several research gaps regarding non-pharmacological interventions for low bone mass. Firstly, there is a research gap in the availability of comprehensive non-pharmacological interventions for low bone mass. Currently, only one RCT has been found that involves a combination of interventions targeting various lifestyle factors such as exercise, nutrition, smoking and drinking cessation, and health education. Comprehensive approach may have the potential to yield more significant effects for managing low bone mass (91). Therefore, further investigation is warranted to explore the effectiveness of comprehensive non-pharmacological therapies for low bone mass.

Secondly, the serum markers for bone turnover and resorption examined in the included studies may not be fully specific or sensitive for low bone mass, as they were primarily suitable for osteoporosis (92). BTMs, including OC, are influenced by factors such as circadian rhythm, dietary intake, comorbidities, and assay variability, which may limit their reliability as sole markers of intervention efficacy (93, 94). Furthermore, BTM changes often reflect short-term alterations in bone remodeling dynamics and may not directly correlate with long-term skeletal outcomes such as BMD gains or fracture reduction (95). Therefore, BTM results should be considered supportive rather than definitive evidence, and should be interpreted with caution. Moreover, the use of DXA to assess BMD was limited by asymptomatic nature of low bone mass (96). Other well-established clinical risk factors, such as fall history and composite risk assessment tools like the FRAX score, are recommended in clinical practice for fracture risk evaluation. However, their utility for guiding non-pharmacological interventions in populations with low bone mass remains unclear (97). Further investigation is needed to determine their utility in guiding and tailoring nonpharmacological interventions for this specific population.

Lastly, most studies included in the research focused on postmenopausal women, with only one study included both men and women. This is reasonable considering the higher prevalence of osteoporosis and related fractures in postmenopausal women, attributed to the pivotal role of estrogen in maintaining bone health (4). The decline in BMD begins with reduced estrogen levels around menopause and continues thereafter, as estrogen directly and indirectly influences bone by inhibiting bone resorption and promoting calcium excretion (98). Approximately half of women experience accelerated low bone mass, ranging from 10% to 20%, during the 5–6 years surrounding menopause (99). However, evidence suggests that the global male population also suffers from osteoporosis (11.7%) but is often not evaluated or treated in line with guidelines (4, 100). Considering the societal structure of an aging population, there is a need to investigate intervention strategies for older men with low bone mass. Further research should focus on addressing this gap.

4.4 Strengths and limitations

To the best of our knowledge, this study is the first systematic review and meta-analysis summarizing the efficacy of non-pharmacological interventions in population with low bone mass. However, this study has some limitations. Firstly, although we have searched literature comprehensively and examined the publication bias, this bias is still a potential limitation of systematic reviews. Secondly, most studies did not report medical treatment condition of the participants. Because pharmacotherapy is uncommon in low bone mass, unreported concomitant treatments could bias estimates and potentially underestimate or confound intervention effects. Third, because of the limited number of eligible studies, our analysis did not account for the specific skeletal sites targeted by each exercise intervention, which may have influenced the observed results. Finally, limited number of studies with scattered interventions and outcomes were included, contributing to high heterogeneity and underestimation of these interventions. The limited number of included studies, which prevents categorization of evidence levels and increases the susceptibility to publication bias. Future research, as more original studies become available, should aim to conduct meta-analyses to provide more precise and unbiased estimates.

5 Conclusion

In summary, addressing low bone mass is important for interventions aimed at improving bone health and preventing the associated morbidity and mortality from fractures. This has significant implications for public health. Low bone mass, similar to conditions like prediabetes, prehypertension, and borderline high cholesterol, represents an intermediate risk group with unclear boundaries. However, what makes low bone mass a critical phase is the large number of individuals affected by it, making this group a significant portion of the population at risk for fractures. This highlights the importance of targeting interventions towards individuals with low bone mass in order to effectively reduce the burden of fractures by improving bone health.

Non-pharmacological interventions, such as exercise and specific nutrition strategies, hold promise in maintaining bone health in individuals with low bone mass. In the included studies, exercise programs of approximately 60–90 minutes per session, performed three times per week and aligned with existing guidelines, were associated with modest BMD benefits at some skeletal sites, but we did not compare the effect size of different intervention parameter, and the parameter for other exercises warrants further investigation. Regarding nutrition interventions, polyphenol extracts showed efficacy on lumbar spine BMD, while the results of collagen supplements were mixed, and the effects of micronutrients supplements were limited.

However, it is important to acknowledge that these conclusions are preliminary due to the limited evidence currently available. More high-quality RCTs are needed to fill the research gap on comprehensive lifestyle interventions. Additionally, precise prevention strategies tailored for individuals in the lower range of low bone mass (e.g., using a T-score below -2.0 to identify those at higher risk of progressing to osteoporosis) should be further investigated. It is also important to evaluate the specific needs of older men, as interventions for this population are currently limited. Further research in these areas will enhance our understanding and enable the development of more evidence-based interventions for individuals with low bone mass.

Author contributions

XN: Conceptualization, Methodology, Writing – review & editing, Visualization, Writing – original draft, Software, Formal Analysis, Data curation, Resources. YY: Visualization, Methodology, Data curation, Writing – review & editing, Conceptualization, Software. HY: Software, Methodology, Visualization, Writing – review & editing, Conceptualization, Data curation. ZC: Methodology, Data curation, Conceptualization, Software, Writing – review & editing. XQ: Conceptualization, Writing – review & editing, Software, Data curation, Methodology. JZ: Formal Analysis, Visualization, Project administration, Supervision, Validation, Conceptualization, Writing – review & editing. MC: Validation, Conceptualization, Project administration, Writing – review & editing, Supervision, Formal Analysis, Visualization. DW: Visualization, Project administration, Conceptualization, Validation, Supervision, Formal Analysis, Writing – review & editing. DB: Writing – review & editing, Formal Analysis, Visualization, Project administration, Validation, Supervision, Conceptualization. KY: Writing – review & editing, Validation, Conceptualization, Investigation, Supervision, Resources, Formal Analysis, Project administration, Visualization. AZ: Conceptualization, Validation, Resources, Project administration, Visualization, Supervision, Investigation, Writing – review & editing, Formal Analysis. ZL: Investigation, Visualization, Conceptualization, Validation, Project administration, Supervision, Writing – review & editing, Resources, Formal Analysis.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fendo.2025.1612739/full#supplementary-material

Abbreviations

BALP, Bone-specific alkaline phosphatase; BMC, Bone mineral content; BMD, Bone mineral density; BTM, Bone turnover markers; CTX, C-terminal telopeptide of collagen; IL, Interleukin; OC, Osteocalcin; NTX, N-telopeptides of type I collagen; P1NP, Procollagen type I N-terminal propeptide; PTH, Parathyroid hormone; TNF-α, Tumor necrosis factor.

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