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Does higher serum 25-hydroxyvitamin D levels will harm bone mineral density?: a cross-sectional study

BMC Endocrine Disorders volume 24, Article number: 250 (2024) Cite this article

Abstract

Objective

Vitamin D plays a critical role in the prevention and management of osteoporosis. However, there is an ongoing debate regarding the most effective vitamin D supplementation strategies for maintaining optimal bone mineral density (BMD) levels in adults. This study sought to establish the correlation between serum 25-hydroxyvitamin D [25(OH)D] levels and total BMD in a substantial population sample.

Methods

Data from the National Health and Nutrition Examination Survey (NHANES) for the 2011–2018 cycles, encompassing 11,375 adult participants, were analyzed. The primary variables of interest were serum 25(OH)D levels and BMD. A multivariable logistic regression model was utilized to account for relevant variables associated with these correlations.

Results

A U-shaped relationship between serum 25(OH)D levels and BMD was observed. In males, a significant positive association was identified for 25(OH)D levels below 84.8 nmol/L (p < 0.0001), while levels above this threshold showed no significant correlation (p = 0.3377). In females, those with 25(OH)D levels below 31.4 nmol/L exhibited a significant positive association with BMD (p = 0.0010), but this association weakened and became marginally significant above this threshold (p = 0.0650).

Conclusions

For adult males, the optimal serum 25(OH)D level is 84.8 nmol/L, beyond which higher levels do not lead to increased BMD. A deficiency threshold for adult females should be above 31.4 nmol/L, as lower 25(OH)D levels are not conducive to BMD. These findings underscore the importance of maintaining appropriate vitamin D levels for bone health in both genders.

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Introduction

Vitamin D is integral to maintaining bone health and calcium homeostasis [1, 2]. Vitamin D, in its active form 1,25-dihydroxyvitamin D [1,25(OH)₂D], binds to the vitamin D receptor (VDR) in various tissues, facilitating calcium and phosphate absorption in the intestines and promoting bone mineralization. It also regulates parathyroid hormone (PTH) levels, essential for calcium balance [3, 4]. Insufficiency of vitamin D results in diminished calcium absorption, secondary hyperparathyroidism, and heightened bone resorption, potentially leading to compromised bone integrity and an increased susceptibility to osteoporosis and fractures [5]. Bone mineral density (BMD) is recognized as the most important predictor of osteoporosis, and fracture is the ultimate manifestation [6]. Epidemiologic studies have shown that a 10% increase in PBM at the population level reduces the risk of fracture later in life by 50% [7].

However, observational studies have yielded varying conclusions regarding the relationship between vitamin D levels and bone mineral density (BMD) [8]. Some studies suggest that vitamin D supplementation does not prevent fractures or falls nor has a clinically meaningful effect on bone mineral density [9]. The discussion persists regarding the optimal levels of 25-hydroxyvitamin D necessary for achieving the highest possible skeletal health outcomes [10, 11]. Indeed, there does not appear to be a causal relationship between higher 25(OH)D concentrations and higher BMD in the general healthy population [12]. Furthermore, a weak relationship between serum 25(OH)D and bone microarchitecture was observed in a population with a mean serum 25-hydroxyvitamin D level as high as 137 nmol/L [13].

This inconsistency in findings highlights the complexity of the relationship between vitamin D and bone health. It suggests the possibility of a U-shaped association, where both low and high levels of serum 25-hydroxyvitamin D may be associated with adverse bone health outcomes [10, 14, 15]. Such a pattern would imply an optimal range for serum 25-hydroxyvitamin D levels, within which bone mineral density is maximized, and deviations on either side could lead to reduced bone health. This study aims to clarify these relationships by examining a large, nationally representative sample of adults in the US, using data from NHANES collected between 2011 and 2018.

Methods

Study design and participants

The National Health and Nutrition Examination Survey (NHANES) serves as a crucial tool for understanding the health and nutrition landscape of the United States [16]. Participants are selected randomly to take part in NHANES. The NHANES health interview covers a wide range of health-related topics, including demographic information such as age, sex, race, dietary data, laboratory tests, examination tests, and questionnaires. By carefully selecting participants and collecting comprehensive data, NHANES offers valuable insights into health and nutrition trends.

This research data was obtained from the NHANES survey spanning from 2011 to 2018. The study specifically examined the levels of 25-hydroxyvitamin D and total bone mineral density. It is important to note that NHANES (2011–2018) does not include total bone mineral density information for individuals over 60. After excluding respondents with missing 25-hydroxyvitamin D and total bone mineral density data, the analysis included 11,375 adults (refer to Fig. 1).

Fig. 1
figure 1

Flowchart of participant selection. Abbreviations: 25(OH)D = 25-hydroxyvitamin D. BMD = bone mineral density. NHANES = National Health and Nutrition

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Measurement of BMD

Dual-energy X-ray absorptiometry (DXA) is widely regarded as the most widely accepted method for measuring total bone mineral density (BMD) due, in part, to its rapidity, ease of use, and minimal radiation exposure [17]. The examination was open to participants aged 8–59 years. Exclusion criteria for the DXA examination included the following: 1. Pregnancy, as confirmed by a positive urine pregnancy test or self-reported at the time of the DXA examination. 2. Self-reported radiographic contrast material (barium) use within the past seven days. 3. Self-reported weight exceeding 450 pounds or height exceeding 6’5” due to limitations of the DXA Table [18].

Measurement of 25(OH)D

The CDC method used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantitatively detect 25-hydroxyvitamin D3 (25OHD3), 3-epi-25-hydroxyvitamin D3 (epi-25OHD3), and 25-hydroxyvitamin D2 (25OHD2) in human serum for NHANES 2011 to 2018. The analysis focused on total 25-hydroxyvitamin D, which includes the combined levels of 25OHD3 and 25OHD2 but not epi-25OHD3.

Other covariates

Poverty can present a barrier to accessing adequate nutrition, leading to an increased risk of osteoporosis. A cross-sectional study indicated that individuals over the age of 50 living below the poverty line exhibit a higher relative risk of osteoporosis compared to those residing above the poverty line [19]. Furthermore, a retrospective study conducted in the UK between 2005 and 2015 highlighted an association between Vitamin D deficiency and economic hardship [20]. This research integrated the ratio of family income to poverty, setting values exceeding 5.00 at 5.00 for the analysis.

BMI is an important indicator for measuring physical health [21]. A higher BMI is associated with low 25(OH) D levels [22, 23], while a higher BMI may have a beneficial effect on BMD, masking the impact of reduced 25(OH) D levels [24]. One cross-sectional study showed a significant positive and saturated association between BMI and BMD in adolescents [25].

Smoking has been shown to diminish bone mineral density (BMD) values in individuals [26]. Smokers are more likely to have osteoporosis or osteopenia, and the level of cotinine in the blood, a marker of tobacco exposure, is strongly linked to the presence of osteoporosis or osteopenia [27, 28]. Clinical studies have demonstrated that smoking disrupts bone health and is an independent risk factor for osteoporosis [26]. In our study, we used serum cotinine as an objective measure of the impact of tobacco use on individuals.

The consumption of alcohol, as well as smoking, has been identified as risk factors in the process of attaining peak bone mass [6]. However, the impact of low-dose alcohol consumption remains uncertain as individuals categorized as light drinkers exhibit even higher bone mineral density (BMD) in comparison to abstainers [25]. A cross-sectional study has indicated that heavy alcohol consumption may be linked to lower BMD in men [29]. Furthermore, a Mendelian randomization study has suggested a potential positive correlation between the frequency of alcohol consumption and BMD, although the causative relationship was not statistically significant [30]. Consequently, alcohol intake was incorporated as a covariate in our research. As per the Alcohol Use Questionnaire, participants were stratified into four groups based on their drinking frequency: weekly drink, monthly drink, yearly drink, or no drink.

Physical activity (PA) and sedentary activity (SA) have been shown to have distinct impacts on bone mineral density (BMD) [31, 32]. Guidelines recommend physical activity for the management of osteoporosis [33]. Observational studies have indicated a positive correlation between physical activity and bone health [34, 35]. Conversely, individuals engaging in sedentary activities, such as those confined to bed, have exhibited a high prevalence of vitamin D deficiency, with no discernible association with nutritional risk or level of dementia [36]. Physical activity assessment was based on the MET values of the type, frequency, and duration of activities per week, calculated using the formula: PA (MET-min/wk) = MET × weekly frequency × duration of each PA [37]. Sedentary activity was quantified by the number of minutes per day that subjects spent in a sedentary state [38].

Sunlight exposure triggers the synthesis of vitamin D in the skin, leading to the natural production of 25(OH)D facilitated by UV radiation [39]. Research has demonstrated the substantial influence of cumulative UV radiation exposure on skeletal health [40]. Sun exposure was measured by asking participants how much time they spent outdoors between 9 a.m. and 5 p.m. per week over the past 30 days.

Statistical analysis

The study population’s baseline data is presented based on the 25(OH)D subgroup. Continuous variables are expressed as means ± standard deviations and were analyzed using weighted linear regression models. The “mice” package employed the random forest algorithm to interpolate the missing data. Multivariate linear regression analysis determined beta values and 95% confidence intervals (CIs) between 25(OH)D and BMD. Furthermore, a log-likelihood ratio test compared the one-line linear regression model with a two-piecewise linear model. Pearson’s test was utilized to analyze the correlation between 25(OH)D and BMD. The statistical analysis was performed using the statistical computing and graphics software R (version 4.4.0) and Empower Stats (version 4.1).

The multivariate test was built using three models: Crude Model: no variables adjusted; Model I: adjusted for gender, age, and race; Model II: adjusted for gender, age, race, education level, family income to poverty ratio, body mass index, alcohol consumption frequency, serum cotinine, physical activity, sedentary activity, Sun Exposure, and HbA1C. We conducted tests to examine linear trends by utilizing the median value of each 25(OH)D category as a continuous variable in the models. Simultaneously, we performed smoothed curve fits by adjusting the variables. Furthermore, an analysis model for threshold effects was employed to investigate the relationship and saturation value between 25(OH)D and BMD. A significance level of P < 0.05 was deemed statistically significant, and a weighting approach was implemented to mitigate the substantial volatility present in our dataset.

Results

Baseline characteristics

In this study, a total of 11,375 respondents were included based on specific inclusion and exclusion criteria (Fig. 1). The average age of the participants was 38.62 years, with a standard deviation of 12.23 years (Table 1). The mean (SD) concentrations of 25(OH)D and total BMD were 66.40 nmol/L ± 26.10 and 1.11 g/cm2 ± 0.11, respectively. Table 1 delineates the clinical characteristics of the study participants. The participants were stratified into three groups based on their 25(OH)D levels. Those in the highest tertile exhibited characteristics such as older age, higher income, a more significant proportion of Non-Hispanic White individuals, and higher education levels, as well as increased alcohol intake and lower BMI (P < 0.05) compared to those in the lowest tertile. Furthermore, those with higher 25(OH)D levels appeared to engage in more physical activity and less sedentary activity, although this contrast lacked statistical significance (P > 0.05).

Table 1 Baseline characteristics of participants (N = 11 375)
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The univariate analysis of total BMD

This single-factor analysis table presents statistical insights into the relationships between various factors and bone mineral density (BMD). The findings revealed significant correlations between BMD and factors such as 25 (OH)D, gender, age, body mass index (BMI), race, education level, family income to poverty ratio, physical activity, sedentary Activity, Sun Exposure, and HbA1C (Table 2).

The analysis revealed a robust positive correlation between bone mineral density (BMD) and both family income to poverty ratio (PIR) and body mass index (BMI), with regression coefficients of β = 0.0033 (95% CI: 0.0021, 0.0045) and β = 0.0023 (95% CI: 0.0020, 0.0025) respectively. Conversely, age exhibited a negative correlation with BMD (β = -0.0007, 95% CI: -0.0008, -0.0005). Notably, females displayed lower BMD levels than males (β = -0.0682, 95% CI: -0.0719, -0.0645). Substantial disparities in BMD were evident across various racial groups, with Non-Hispanic White and Non-Hispanic Black individuals manifesting notably higher BMD levels than the reference group (β = 0.0157, 95% CI: 0.0094, 0.0220; β = 0.0763, 95% CI: 0.0681, 0.0844). Furthermore, higher educational attainment was linked to elevated BMD (β = 0.0170, 95% CI: 0.0092, 0.0249) (Table 2). Increased physical activity and reduced sedentary behavior were associated with heightened BMD levels.

Table 2 The results of univariate analysis for BMD(g/cm2)
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Association between 25(OH)D and total BMD

Table 3 displays the results of the multivariate regression analysis that explored the connection between 25(OH)D levels and total BMD (Bone Mineral Density) across three models: Crude, Model I, and Model II. In the Crude model, 25(OH)D is negatively linked to BMD. After adjustment, the relationship becomes positive. The β values are 0.0003 in Model I and 0.0003 in Model II, both showing highly significant P-values (p < 0.0001). This indicates a strong positive impact of higher 25(OH)D levels on BMD across adjusted models.

Comparatively, higher tertiles of 25(OH)D, when compared to the reference group (Q1, < 47.9 nmol/L), exhibit progressively stronger positive relationships with BMD. In Model II, Q2 (47.9–67.9 nmol/L) had a β of 0.0072 (P = 0.004411), and Q3 (≥ 67.9 nmol/L) had a β of 0.0241 (p < 0.000001). The trend analysis confirmed that increasing levels of 25(OH)D were significantly associated with higher BMD across all models, with P-values for trends all below 0.001.

The multiple regression analysis was conducted to investigate the correlation between 25(OH)D levels and total BMD through data stratification based on gender, age, and race. Upon stratification by gender, a consistent and strong positive association between 25(OH)D levels and BMD was observed among males across all models, with the most pronounced association identified in Model II (β = 0.0006, 95% CI: 0.0005, 0.0008). Conversely, females exhibited a slight negative association in the unadjusted model (β = -0.0001, 95% CI: -0.0002, -0.0000), which transitioned to a weak and non-significant positive association in Model I, subsequently becoming slightly significant in Model II (β = 0.0001, 95% CI: 0.0000, 0.0002). Stratification by age revealed that younger adults (18-39.9 years) initially demonstrated a weak negative association in the unadjusted model, which notably transformed into a significantly positive association in the adjusted models. In contrast, older adults (40–59 years) displayed no significant association in the unadjusted model but exhibited a noteworthy positive association in adjusted models (β = 0.0003, p < 0.001). Analysis by race indicated that Mexican Americans, non-Hispanic whites, and other racial groups consistently displayed positive and significant associations in adjusted models. Non-Hispanic Blacks exhibited variable associations, with predominantly favorable results in adjusted models, underscoring the importance of considering demographic factors when assessing the impact of 25(OH)D on BMD.

Table 3 Relationship between 25(OH)D(nmol/L) and total BMD(g/cm2)
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Subgroup analysis for the association between 25(OH)D and total BMD

Table 4 displays the results of a subgroup analysis on the association between serum 25(OH)D levels and total BMD across different demographic and clinical subgroups. The analysis shows a consistent association between 25(OH)D and BMD across age and BMI categories, with minimal variation among racial/ethnic groups. Overall, the association between 25(OH)D levels and BMD remains stable across these subgroups.

Table 4 Subgroup analysis for the association between 25(OH)D and total BMD
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Nonlinearity and saturation effect analysis between 25(OH)D and total BMD

Figure 2 illustrates the dose-response relationship between 25-Hydroxyvitamin D (25(OH)D) and total Bone Mineral Density (BMD) using a generalized additive model (GAM). Figure 2A shows the association without any adjustments, while Fig. 2B depicts the relationship after total adjustment for variables such as age, gender, and income level. A nonlinear association is evident in both figures, with the solid red line representing the smooth curve fit between 25(OH)D levels and BMD. The blue bands indicate the 95% confidence intervals for the fit. The adjusted model (Fig. 2B) shows a more pronounced and evident relationship, highlighting the significance of these covariates in understanding the association between 25(OH)D and BMD.

Table 3 delineates that a stratified analysis exposes the distinctiveness of the relationship between 25(OH)D and BMD in females. Subsequently, Fig. 2C visually demonstrates the non-linear correlation between 25(OH)D levels and BMD, segmented by gender. The red data points correspond to males, revealing an elevation in BMD up to a specific threshold of 25(OH)D, succeeded by a plateau and minor decline. In contrast, the green data points pertain to females, indicating a more gradual escalation in BMD with increasing 25(OH)D levels, exhibiting less pronounced fluctuations compared to males. The segregation of the two curves accentuates the disparate patterns in the 25(OH)D and BMD relationship between the male and female cohorts.

Fig. 2
figure 2

Dose-response relationship between 25-hydroxyvitamin D and bone mineral density. (A: no adjustment, B: full adjustment, C: full adjustment, stratified by gender). A nonlinear association between 25-hydroxyvitamin D and bone mineral density in a generalized additive model (GAM). The solid red line represents the smooth curve fit between variables. Blue bands represent the 95% confidence interval from the fit. Full adjustment was made for gender, age, race, education level, family income to poverty ratio, body mass index, alcohol consumption frequency, serum cotinine, physical activity, sedentary activity, sun exposure, and HbA1C

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Table 5 shows the threshold effect analysis of 25-hydroxyvitamin D (25(OH)D) on bone mineral density (BMD) using piece-wise linear regression. In the crude model, 25(OH)D levels below 81 nmol/L were significantly positively associated with BMD (β = 0.0002, 95% CI: 0.0001, 0.0003). In the adjusted model, a significant positive association is observed for 25(OH)D levels below 81.1 nmol/L (β = 0.0007, 95% CI: 0.0005, 0.0008), but levels at or above 81.1 nmol/L also show a non-significant negative association (β = -0.0001, 95% CI: -0.0003, 0.0000). Likelihood ratio tests indicate significant threshold effects for both models (p < 0.001).

Table 5 Threshold effect analysis of 25(OH)D and total BMD using piece-wise linear regression
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Table 6 shows the threshold effect analysis of 25(OH)D and BMD using piece-wise linear regression stratified by gender. For males below 84.8 nmol/L, there is a significant positive association (β = 0.0009, 95% CI: 0.0008, 0.0011), while above this threshold, the association is non-significant and slightly negative (β = -0.0003, 95% CI: -0.0005, 0.0002). For females below 31.4 nmol/L, there is a significant positive association (β = 0.0021, 95% CI: 0.0008, 0.0033), and above this threshold, the association remains positive but weaker and slightly significant (β = 0.0001, 95% CI: -0.0000, 0.0002). The likelihood ratio test confirms the statistical significance of these threshold effects for both males (P < 0.001) and females (P = 0.002).

Table 6 Threshold effect analysis of 25(OH)D and total BMD using piece-wise linear regression (stratified by gender)
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Discussion

This study examined the potential association between serum 25-hydroxyvitamin D levels and total bone mineral density in adult individuals in the US. To investigate this relationship, we used multivariate regression and nonlinearity analyses to analyze data from the NHANES. Our findings reveal a U-shaped association between serum 25-hydroxyvitamin D levels and bone mineral density in the US adult population.

After adjusting for all variables (refer to Table 5), we found that the serum 25(OH)D concentration associated with the highest bone mineral density was 81.1 nmol/L, as determined by threshold effect analysis. This finding aligns with previous reports (Wang et al. [41], 2023; Nakamura et al. [42], 2008; Swanson et al. [43]2015). However, unlike our study, a previous trial found no significant correlation between serum 25(OH)D levels and BMD at any anatomical site [8]. The discrepancies between studies may be attributed to differences in sample sizes, which affect the statistical power, and variations in analytical methods. Another study found no association between serum 25(OH)D levels and BMD in postmenopausal women [44]. These conflicting results could be due to differences in study populations or the failure to account for important confounding factors such as physical activity and socioeconomic status [20, 33]. It’s crucial to address these confounders to accurately assess the relationship between serum 25(OH)D levels and BMD.

In Table 5, there was a noticeable correlation: bone mineral density decreased as serum 25(OH)D levels increased (β, -0.0001; 95% CI, -0.0003 to 0.0000) in participants with serum 25(OH)D levels ≥ 81.1 nmol/L. This finding aligns with previous research (Burt et al. [5], 2019), which has suggested that tibial bone mineral density is notably reduced in individuals receiving a daily dose of 10,000 IU of vitamin D [5]. This effect may be associated with an elevation in the plasma marker of bone resorption (CTx) and the suppression of parathyroid hormone (PTH) linked to high vitamin D intake [45]. Studies have indicated that intact PTH (iPTH) levels do not decline rapidly when serum 25(OH)D levels are ≥ 46.25 nmol/L (18.9 ng/mL) [46]. Furthermore, a study has identified two critical 25(OH)D thresholds through segmented regression analysis: at 55 nmol/L, PTH levels begin to plateau, while at 22 nmol/L, PTH levels sharply rise [47]. Notably, circulating 25(OH)D concentrations are nearly 1000 times higher than 1,25(OH)2D, potentially leading to the accumulation of 25(OH)D in parathyroid cells at concentrations sufficient to activate vitamin D receptors (VDR) and directly inhibit PTH mRNA synthesis [48, 49]. An animal study administering 1α,25(OH)2D3 (5 µg/kg body weight/day) to wild-type mice for four days increased the number of osteoclasts in bone and serum concentrations of C-terminal crosslinked telopeptide of type I collagen (CTX-I, a bone resorption marker) [50]. This study also demonstrated that the pro-resorptive, hypercalcemic, and toxic actions of high-dose 1α,25(OH)2D3 are mediated by vitamin D receptors (VDR) in osteoblast-lineage cells [50].

The data in Table 6 suggests that different strategies for 25(OH) D levels should be used to improve bone mineral density (BMD) for males and females. There is a significant positive association below 84.8 nmol/L for males, indicating that increasing 25(OH)D levels within this range could benefit bone health. However, there is a lack of substantial association above this threshold, suggesting a potential plateau effect where further increases in 25(OH)D may not yield additional BMD benefits. Maintaining levels above 84.8 nmol/L for adult males may adversely affect bone density.

For females, a significant positive association below 31.4 nmol/L suggests that small increases in 25(OH)D could substantially impact bone health. However, the positive association weakens above this threshold, indicating diminishing returns. These findings underscore the importance of maintaining adequate 25(OH)D levels, particularly in populations at risk for deficiency, and suggest that supplementation strategies might need to be tailored to each gender to optimize bone health outcomes. For adult females, it is crucial to set the threshold for vitamin D deficiency above 31.4 nmol/L. Higher 25-hydroxyvitamin D levels are more beneficial for increasing bone density in adult females.

The biological and physiological differences between males and females may explain the observed gender differences in the relationship between serum 25-hydroxyvitamin D levels and bone mineral density (BMD). The interaction between vitamin D and sex hormones varies between genders [51, 52]. Studies have shown that elevated prolactin levels in females reduce sex hormone levels, affecting bone metabolism [53]. Estrogen helps maintain bone health in women by promoting osteoblast activity and inhibiting osteoclasts [54, 55]. In contrast, androgens are crucial in maintaining bone health in men. In vitro studies show that androgens stimulate osteoblast proliferation, upregulate TGF-β and IGF-1, and downregulate IL-6 [56]. Testosterone replacement therapy has been shown to increase serum estradiol and testosterone levels, improving BMD in men with hypogonadism [57]. Biological and lifestyle differences between genders, including variations in physical activity levels, BMI, and body composition, may influence how vitamin D is metabolized and its effects on bone density in men and women.

Non-Hispanic black individuals had significantly higher bone mineral density (BMD) compared to other ethnic groups, according to the findings (Table 2). This difference could be attributed to genetic factors, variances in calcium metabolism, or diverse levels of physical activity and sun exposure, as indicated in existing literature [2, 4, 58,59,60]. Differences in cultural, economic, and social factors, such as dietary habits, across ethnic groups can also impact bone density [24, 61,62,63].

Vitamin D deficiency is a global problem that has increased the use of vitamin D supplements [20, 64]. According to SUCRA’s findings, daily vitamin D supplementation ranked higher than intermittent supplementation when the same doses were given. However, the daily and intermittent supplementation groups observed no statistically significant differences in 25(OH)D concentrations [65]. Vitamin D comes in 2 distinct forms: D2 and D3. Studies have shown that D3 is more effective than D2 in raising 25(OH)D concentrations [66]. The standard for vitamin D intake was 528.4 IU/day (~ 13.21 µg/day) to achieve the optimal serum 25(OH) D in Korean Postmenopausal Women [46]. A Randomized Clinical Trial investigating the effect of high-dose Vitamin D supplementation found that suitable daily doses of vitamin D3 intake range from 400 IU/day to 4000 IU/day [5]. In a study that included 116 randomized controlled trials with 11,376 participants, network meta-analysis was used to assess the effectiveness of different vitamin D supplementation regimens. The analysis found that daily supplementation of 2,000 IU of vitamin D was the most effective in achieving optimal 25(OH)D concentrations (> 75 nmol/L) [65]. Our research can be a reference for selecting 25(OH)2D levels.

Our study of 11,375 adults using NHANES data found a U-shaped relationship between serum 25-hydroxyvitamin D levels and bone mineral density (BMD), with the highest BMD observed at a serum concentration of 81.1 nmol/L. This relationship remained significant after adjusting for various covariates, highlighting the complex impact of vitamin D on bone health. Our findings offer valuable insights into the optimal vitamin D levels for maintaining bone health and can inform dietary and supplementation guidelines for both genders.

Our study had some limitations. Firstly, it was a cross-sectional study of disease prevalence rather than incidence, so there is uncertainty about whether exposure preceded the observed outcomes. Secondly, the NHANES database only assessed total bone mineral density in participants aged 8–59 years, leaving the impact of serum 25-hydroxyvitamin D on older individuals inconclusive. Thirdly, although we tried to adjust for numerous confounding factors, there is still a possibility of unmeasured confounders. Additionally, some important covariates, such as alcohol consumption frequency, physical activity, and sedentary activity, were based on participant questionnaire surveys. NHANES also does not provide explicit data on the season during which serum 25-hydroxyvitamin D levels were measured, which could introduce potential bias as vitamin D levels fluctuate with seasonal sun exposure. The lack of occupational data further limits our ability to directly analyze the impact of seasonality and indoor versus outdoor work on vitamin D levels and bone health.

Conclusion

Our study demonstrated a clear association between serum 25-hydroxyvitamin D levels and total bone mineral density among the adult US population. We also revealed a significant U-shaped relationship, indicating that the serum 25(OH)D concentration associated with the highest bone mineral density was 81.1 nmol/L. The optimal 25-hydroxyvitamin D level for adult males is 84.8 nmol/L. For adult females, setting the threshold for vitamin D deficiency above 31.4 nmol/L is crucial, as lower 25(OH)D levels are not conducive to BMD. Moreover, they provide clinicians and researchers with a critical reference point for designing and implementing targeted interventions to optimise bone health outcomes in this population. Our study advances our understanding of the interplay between vitamin D status and bone health, paving the way for more effective strategies to combat osteoporosis and related conditions.

Data availability

The datasets presented in this study can be found in online repositories. The names of the repositories and accession number(s) can be found below: Http://www.cdc.gov/nchs/nhanes/.

References

  1. Morris HA. Vitamin D activities for Health outcomes. Ann Lab Med. 2014;34:181–6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Morin SN, Berger C, Papaioannou A, Cheung AM, Rahme E, Leslie WD, et al. Race/ethnic differences in the prevalence of osteoporosis, falls and fractures: a cross-sectional analysis of the Canadian longitudinal study on aging. Osteoporos Int. 2022;33:2637–48.

    Article  PubMed  CAS  Google Scholar 

  3. Bargagli M, Arena M, Naticchia A, Gambaro G, Mazzaferro S, Fuster D, et al. The role of Diet in Bone and Mineral metabolism and secondary hyperparathyroidism. Nutrients. 2021;13:2328.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Shanshan Xue, Xue S, Oumer Kemal, Kemal O, Meihan Lu, Lu M, et al. Age at attainment of peak bone mineral density and its associated factors: the National Health and Nutrition Examination Survey 2005–2014. Bone. 2020;131:115163.

    Article  Google Scholar 

  5. Burt LA, Billington EO, Rose MS, Raymond DA, Hanley DA, Boyd SK. Effect of high-dose vitamin D supplementation on volumetric bone density and bone strength: a Randomized Clinical Trial. JAMA. 2019;322:736–45.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Zhu X, Zheng H. Factors influencing peak bone mass gain. Front Med. 2021;15:53–69.

    Article  PubMed  Google Scholar 

  7. Gordon CM, Zemel BS, Wren TAL, Leonard MB, Bachrach LK, Rauch F, et al. The determinants of peak bone Mass. J Pediatr. 2017;180:261–9.

    Article  PubMed  Google Scholar 

  8. Marwaha RK, Tandon N, Garg MK, Kanwar R, Narang A, Sastry A, et al. Bone health in healthy Indian population aged 50 years and above. Osteoporos Int. 2011;22:2829–36.

    Article  PubMed  CAS  Google Scholar 

  9. Bolland MJ, Grey A, Avenell A. Effects of vitamin D supplementation on musculoskeletal health: a systematic review, meta-analysis, and trial sequential analysis. Lancet Diabetes Endocrinol. 2018;6:847–58.

    Article  PubMed  CAS  Google Scholar 

  10. Ross AC, Manson JE, Abrams SA, Aloia JF, Brannon PM, Clinton SK, et al. The 2011 report on dietary reference intakes for calcium and Vitamin D from the Institute of Medicine: what clinicians need to know. J Clin Endocrinol Metab. 2011;96:53–8.

    Article  PubMed  CAS  Google Scholar 

  11. Dawson-Hughes B, Heaney RP, Holick MF, Lips P, Meunier PJ, Vieth R. Estimates of optimal vitamin D status. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA. 2005;16:713–6.

    Article  CAS  Google Scholar 

  12. Larsson SC, Melhus H, Michaëlsson K. Circulating serum 25-Hydroxyvitamin D levels and bone Mineral density: mendelian randomization study. J Bone Min Res. 2018;33:840–4.

    Article  CAS  Google Scholar 

  13. Boyd SK, Burt LA, Sevick LK, Hanley DA. The relationship between serum 25(OH)D and bone density and microarchitecture as measured by HR-pQCT. Osteoporos Int. 2015;26:2375–80.

    Article  PubMed  CAS  Google Scholar 

  14. Anagnostis P, Bosdou JK, Kenanidis E, Potoupnis M, Tsiridis E, Goulis DG. Vitamin D supplementation and fracture risk: evidence for a U-shaped effect. Maturitas. 2020;141:63–70.

    Article  PubMed  CAS  Google Scholar 

  15. Grant WB, Karras SN, Bischoff-Ferrari HA, Annweiler C, Boucher BJ, Juzeniene A, et al. Do studies reporting ‘U’-shaped serum 25-hydroxyvitamin D–health outcome relationships reflect adverse effects? Dermatoendocrinol. 2016;8:e1187349.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Taylor CL, Madans JH, Chapman NN, Woteki CE, Briefel RR, Dwyer JT, et al. Critical data at the crossroads: the National Health and Nutrition Examination Survey faces growing challenges. Am J Clin Nutr. 2023;117:847–58.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Messina C, Albano D, Gitto S, Tofanelli L, Bazzocchi A, Ulivieri FM, et al. Body composition with dual energy X-ray absorptiometry: from basics to new tools. Quant Imaging Med Surg. 2020;10:1687–98.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Yan Z, Xiong X, Tao J, Wang S. Association of bone mineral density with trichlorophenol: a population-based study. BMC Musculoskelet Disord. 2023;24:202.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Marshall K, Teo L, Shanahan C, Legette L, Mitmesser SH. Inadequate calcium and vitamin D intake and osteoporosis risk in older americans living in poverty with food insecurities. PLoS ONE. 2020;15:e0235042.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Crowe FL, Jolly K, MacArthur C, Manaseki-Holland S, Gittoes N, Hewison M, et al. Trends in the incidence of testing for vitamin D deficiency in primary care in the UK: a retrospective analysis of the Health Improvement Network (THIN), 2005–2015. BMJ Open. 2019;9:e028355.

  21. Nuttall FQ. Body Mass Index: obesity, BMI, and Health a critical review. Nutr Today. 2015;50:117–28.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Powe CE, Evans MK, Wenger J, Zonderman AB, Berg AH, Nalls M, et al. Vitamin D-binding protein and vitamin D status of black americans and white americans. N Engl J Med. 2013;369:1991–2000.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Walsh JS, Evans AL, Bowles S, Naylor KE, Jones KS, Schoenmakers I, et al. Free 25-hydroxyvitamin D is low in obesity, but there are no adverse associations with bone health. Am J Clin Nutr. 2016;103:1465–71.

    Article  PubMed  CAS  Google Scholar 

  24. Yuan C, Wang J, Zhang W, Yi H, Shu B, Li C, et al. Effects of obesity with reduced 25(OH)D levels on bone health in elderly Chinese people: a nationwide cross-sectional study. Front Immunol. 2023;14:1162175.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Godos J, Giampieri F, Chisari E, Micek A, Paladino N, Forbes-Hernández TY, et al. Alcohol consumption, bone Mineral Density, and risk of osteoporotic fractures: a dose-response Meta-analysis. Int J Environ Res Public Health. 2022;19:1515.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Jing Z, Li Y, Zhang H, Chen T, Yu J, Xu X, et al. Tobacco toxins induce osteoporosis through ferroptosis. Redox Biol. 2023;67:102922.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Hou W, Chen S, Zhu C, Gu Y, Zhu L, Zhou Z. Associations between smoke exposure and osteoporosis or osteopenia in a US NHANES population of elderly individuals. Front Endocrinol. 2023;14:1074574.

    Article  Google Scholar 

  28. Merianos AL, Stone TM, Jandarov RA, Mahabee-Gittens EM, Choi K. Sources of Tobacco smoke exposure and their associations with serum cotinine levels among US children and adolescents. Nicotine Tob Res off J Soc Res Nicotine Tob. 2023;25:1004–13.

    Article  CAS  Google Scholar 

  29. Cho Y, Choi S, Kim K, Lee G, Park SM. Association between alcohol consumption and bone mineral density in elderly Korean men and women. Arch Osteoporos. 2018;13:46.

    Article  PubMed  Google Scholar 

  30. Lai B, Jiang H, Gao R, Zhou X. Association between alcohol intake and bone mineral density: results from the NHANES 2005–2020 and two-sample mendelian randomization. Arch Osteoporos. 2024;19:21.

    Article  PubMed  Google Scholar 

  31. Lin Z, Shi G, Liao X, Huang J, Yu M, Liu W, et al. Correlation between sedentary activity, physical activity and bone mineral density and fat in America: National Health and Nutrition Examination Survey, 2011–2018. Sci Rep. 2023;13:10054.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Kim YA, Lee Y, Lee JH, Seo JH. Effects of physical activity on bone mineral density in older adults: Korea National Health and Nutrition Examination Survey, 2008–2011. Arch Osteoporos. 2019;14:103.

  33. Brooke-Wavell K, Skelton DA, Barker KL, Clark EM, De Biase S, Arnold S, et al. Strong, steady and straight: UK consensus statement on physical activity and exercise for osteoporosis. Br J Sports Med. 2022;56:837–46.

    Article  PubMed  Google Scholar 

  34. Pinheiro MB, Oliveira J, Bauman A, Fairhall N, Kwok W, Sherrington C. Evidence on physical activity and osteoporosis prevention for people aged 65 + years: a systematic review to inform the WHO guidelines on physical activity and sedentary behaviour. Int J Behav Nutr Phys Act. 2020;17:150.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Nilsson M, Ohlsson C, Mellström D, Lorentzon M. Previous sport activity during childhood and adolescence is associated with increased cortical bone size in young adult men. J Bone Min Res off J Am Soc Bone Min Res. 2009;24:125–33.

    Article  Google Scholar 

  36. Leite NP, Alvarez TS, Fonseca FLA, Hix S, Sarni ROS. Vitamin D deficiency in bedridden elderly people at home. Rev Assoc Médica Bras. 2023;69:61–5.

    Article  Google Scholar 

  37. Chen L, Cai M, Li H, Wang X, Tian F, Wu Y, et al. Risk/benefit tradeoff of habitual physical activity and air pollution on chronic pulmonary obstructive disease: findings from a large prospective cohort study. BMC Med. 2022;20:70.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Cao C, Friedenreich CM, Yang L. Association of Daily Sitting Time and leisure-time physical activity with Survival among US Cancer survivors. JAMA Oncol. 2022;8:395–403.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Wintermeyer E, Ihle C, Ehnert S, Stöckle U, Ochs G, de Zwart P, et al. Crucial role of vitamin D in the Musculoskeletal System. Nutrients. 2016;8:319.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Thompson MJW, Aitken DA, Otahal P, Cicolini J, Winzenberg TM, Jones G. The relationship between cumulative lifetime ultraviolet radiation exposure, bone mineral density, falls risk and fractures in older adults. Osteoporos Int. 2017;28:2061–8.

    Article  PubMed  CAS  Google Scholar 

  41. Wang D, Yang Y, Nakamura, et al. 13, 2008Hydroxyvitamin D levels and osteoporosis in Postmenopausal Women. Clin Interv Aging. 2023;18:619–27.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Nakamura K, Tsugawa N, Saito T, Ishikawa M, Tsuchiya Y, Hyodo K, et al. Vitamin D status, bone mass, and bone metabolism in home-dwelling postmenopausal Japanese women: Yokogoshi Study. Bone. 2008;42:271–7.

    Article  PubMed  CAS  Google Scholar 

  43. Swanson CM, Srikanth P, Lee CG, Cummings SR, Jans I, Cauley JA, et al. Associations of 25-Hydroxyvitamin D and 1,25-Dihydroxyvitamin D with bone Mineral Density, Bone Mineral Density Change, and Incident Nonvertebral fracture. J Bone Min Res. 2015;30:1403–13.

    Article  CAS  Google Scholar 

  44. Hosseinpanah F, Rambod M, Hossein-nejad A, Larijani B, Azizi F. Association between vitamin D and bone mineral density in Iranian postmenopausal women. J Bone Min Metab. 2008;26:86–92.

    Article  CAS  Google Scholar 

  45. Grimnes G, Joakimsen R, Figenschau Y, Torjesen PA, Almås B, Jorde R. The effect of high-dose vitamin D on bone mineral density and bone turnover markers in postmenopausal women with low bone mass—a randomized controlled 1-year trial. Osteoporos Int. 2012;23:201–11.

    Article  PubMed  CAS  Google Scholar 

  46. Shin HR, Lee YJ, Ly SY. Optimal serum 25(OH)D levels and Vitamin D Intake Comparison of the effect of daily vitamin D2 and vitamin D3 supplementation on serum 25-Hydroxyvitamin D concentration. Nutrients. 2023;15:1856.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Gong M, Wang K, Sun H, Wang K, Zhou Y, Cong Y, et al. Threshold of 25(OH)D and consequently adjusted parathyroid hormone reference intervals: data mining for relationship between vitamin D and parathyroid hormone. J Endocrinol Invest. 2023;46:2067–77.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Chen X, Chu C, Doebis C, Xiong Y, Cao Y, Krämer BK, et al. Vitamin D status and its association with parathyroid hormone in 23,134 outpatients. J Steroid Biochem Mol Biol. 2022;220:106101.

    Article  PubMed  CAS  Google Scholar 

  49. Tsuprykov O, Chen X, Hocher C-F, Skoblo R. Lianghong Yin null, Hocher B. Why should we measure free 25(OH) vitamin D? J Steroid Biochem Mol Biol. 2018;180:87–104.

    Article  PubMed  CAS  Google Scholar 

  50. Mori T, Horibe K, Koide M, Uehara S, Yamamoto Y, Kato S, et al. The vitamin D receptor in Osteoblast-Lineage cells is essential for the Proresorptive activity of 1α,25(OH)2D3 in vivo. Endocrinology. 2020;161:bqaa178.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Wierzbicka A, Oczkowicz M. Sex differences in vitamin D metabolism, serum levels and action. Br J Nutr. 2022;128:2115–30.

    Article  PubMed  CAS  Google Scholar 

  52. Dupuis ML, Pagano MT, Pierdominici M, Ortona E. The role of vitamin D in autoimmune diseases: could sex make the difference? Biol Sex Differ. 2021;12:12.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Nicks KM, Fowler TW, Gaddy D. Reproductive hormones and Bone. Curr Osteoporos Rep. 2010;8:60–7.

    Article  PubMed  Google Scholar 

  54. Kim H-N, Ponte F, Nookaew I, Ucer Ozgurel S, Marques-Carvalho A, Iyer S, et al. Estrogens decrease osteoclast number by attenuating mitochondria oxidative phosphorylation and ATP production in early osteoclast precursors. Sci Rep. 2020;10:11933.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Khosla S, Oursler MJ, Monroe DG. Estrogen and the skeleton. Trends Endocrinol Metab. 2012;23:576–81.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Ferrari SL, Abrahamsen B, Napoli N, Akesson K, Chandran M, Eastell R, et al. Diagnosis and management of bone fragility in diabetes: an emerging challenge. Osteoporos Int. 2018;29:2585–96.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Seftel AD, Kathrins M, Niederberger C. Critical update of the 2010 Endocrine Society Clinical Practice Guidelines for male hypogonadism. Mayo Clin Proc. 2015;90:1104–15.

  58. Chen H-Y, Robinson JK, Jablonski NG. A cross-cultural exploration on the psychological aspects of skin color aesthetics: implications for sun-related behavior. Transl Behav Med. 2020;10:234–43.

    PubMed  Google Scholar 

  59. Aggarwal A, Pal R, Bhadada SK, Ram S, Garg A, Bhansali A, et al. Bone mineral density in healthy adult Indian population: the Chandigarh Urban Bone Epidemiological Study (CUBES). Arch Osteoporos. 2021;16:17.

    Article  PubMed  Google Scholar 

  60. Noel SE, Santos MP, Wright NC. Racial and ethnic disparities in Bone Health and outcomes in the United States. J Bone Min Res. 2021;36:1881–905.

    Article  Google Scholar 

  61. Borba-Pinheiro CJ, Drigo AJ, de Alencar Carvalho MCG, da Silva NSL, Dantas EHM. Factors that contribute to Low Bone Density in Postmenopausal women in different amazonian communities. Ther Adv Musculoskelet Dis. 2011;3:81–90.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Shen B, Mode NA, Noren Hooten N, Pacheco NL, Ezike N, Zonderman AB, et al. Association of Race and Poverty Status with DNA methylation-based age. JAMA Netw Open. 2023;6:e236340.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Struffolino E, Van Winkle Z. Gender and race differences in pathways out of in-work poverty in the US. Soc Sci Res. 2021;99:102585.

    Article  PubMed  Google Scholar 

  64. Cashman KD, Dowling KG, Škrabáková Z, Gonzalez-Gross M, Valtueña J, De Henauw S, et al. Vitamin D deficiency in Europe: pandemic?12. Am J Clin Nutr. 2016;103:1033–44.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Zhuang Y, Zhu Z, Chi P, Zhou H, Peng Z, Cheng H, et al. Efficacy of intermittent versus daily vitamin D supplementation on improving circulating 25(OH)D concentration: a bayesian network meta-analysis of randomized controlled trials. Front Nutr. 2023;10:1168115.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Van Den EGhm H, Lips P, Schoonmade LJ, Lanham-New SA, Van Schoor NM. Comparison of the Effect of Daily Vitamin D2 and vitamin D3 supplementation on serum 25-Hydroxyvitamin D concentration (total 25(OH)D, 25(OH)D2, and 25(OH)D3) and importance of body Mass Index: a systematic review and Meta-analysis. Adv Nutr. 2024;15:100133.

    Article  Google Scholar 

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Acknowledgements

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Funding

This research was supported by grants from the Scientific Research Project of the Wuhan Municipal Health Commission (WX23Z07).

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Author notes

  1. Bingcheng Xu and Qiai Li contributed equally to this work.

Authors and Affiliations

  1. Department of Geriatrics, Wuhan Wuchang Hospital, Wuhan, 430063, China

    Bingcheng Xu & Bo Luo

  2. Department of Dermatology, Wuhan Wuchang Hospital, Wuhan, 430063, China

    Qiai Li

  3. Department of Orthopaedics, Wuhan Wuchang Hospital, Wuhan, 430063, China

    Hao Liu

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  1. Bingcheng Xu
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Contributions

Conceptualization, Bingcheng Xu and Hao Liu; methodology, Bingcheng Xu; software, Qiai Li; validation, Bo Luo; formal analysis, Qiai Li; investigation, Bingcheng Xu; data curation, Bingcheng Xu; writing—original draft preparation, Bingcheng Xu and Qiai Li; writing—review and editing, Hao Liu; supervision, Bo Luo; project administration, Hao Liu; funding acquisition, Hao Liu. and S.Y.L. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Hao Liu.

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The study protocols were approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board (ERB). The relevant protocol numbers are Protocol #2011-17 (effective from 2011 to October 26, 2017) and Protocol #2018-01 (effective from October 26, 2017 onwards). Informed consent was obtained from all participants involved in the study.

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Xu, B., Li, Q., Luo, B. et al. Does higher serum 25-hydroxyvitamin D levels will harm bone mineral density?: a cross-sectional study. BMC Endocr Disord 24, 250 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12902-024-01760-9

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Keywords

BMC Endocrine Disorders

ISSN: 1472-6823

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