Gastrointestinal health and serum proteins are associated with BMD in postmenopausal women: a cross-sectional study

Abstract

Background

With increasing age, the social and economic burdens of postmenopausal osteoporosis are steadily increasing. This study aimed to investigate the factors that influence the development of postmenopausal osteoporosis.

Methods

Postmenopausal women at the Affiliated Hospital of Jiangnan University from January 2023 to December 2023 were recruited for BMD examination. The patients were divided into a normal group, an osteopenia group and an osteoporosis group according to their T value. Questionnaires, including the Gastrointestinal Symptom Rating Scale and Short Form 12, were administered through face-to-face interviews. Bone turnover markers and serum protein levels of Fasting venous blood were detected.

Results

A total of 222 postmenopausal women met the inclusion criteria were recruited. Univariate analysis revealed statistically significant differences in age, education, BMI, supplementation with soy products, supplementation with dairy products, supplementation with other nutritional supplements, exercise frequency, gastrointestinal symptom score, quality of life, 25(OH)D, total protein, albumin and prealbumin among the three groups (P < 0.05). Pearson correlation analysis revealed that gastrointestinal symptoms (r = -0.518, P < 0.01) was negatively correlated with BMD in postmenopausal women, while PCS (r = 0.194, P = 0.004), MCS (r = 0.305, P < 0.01), 25(OH)D (r = 0.531, P < 0.01), total protein (r = 0.324, P < 0.01), albumin (r = 0.341, P < 0.01) and prealbumin (r = 0.259, P < 0.01) were positively correlated with BMD. Logistic regression analysis revealed that both the gastrointestinal symptom score and serum 25(OH)D level were found to have a significant association with BMD (both P < 0.01). This association remained significant even after adjusting for age, BMI, education level, dietary habits, and exercise frequency.

Conclusion

Gastrointestinal symptoms and serum 25(OH)D elevel are associated with increased risk of osteoporosis in postmenopausal women and may be useful in predicting osteoporosis in postmenopausal women.

Introduction

Postmenopausal osteoporosis is the most common type of osteoporosis and is characterized by decreased bone mineral density, disintegration of the bone microstructure, increased bone fragility, and increased fracture susceptibility [1]. With increasing age, the social and economic burdens of osteoporosis are steadily increasing. The proportion of women with osteoporosis increases with age, and bone mineral density (BMD) is significantly lower in postmenopausal women due to a decrease in serum estrogen levels [2]. As an increasingly serious public health problem, osteoporosis can seriously affect the quality of life of patients. Fractures are common adverse outcomes and include increased pain, disability, caregiving tasks, overall healthcare costs and death [3].

Although there are drugs clinically used to treat osteoporosis [4], there is currently no drug that can cure osteoporosis [5]. This disease continues to be underdiagnosed and undertreated [6], with a smaller number of patients receiving treatment compared to those who actually need it [7]. Therefore, how to recognize the risk of osteoporosis in a timely manner and prevent it effectively are currently popular research topics in the field of osteoporosis care.

At present, the clinical diagnosis of postmenopausal osteoporosis relies mainly on dual-energy X-rays for examining BMD, but this examination equipment is mostly deployed by large medical centers, and such examinations are expensive. This highlights the urgent need for simple, noninvasive predictors for early diagnosis of this disease.

Bone turnover markers (BTMs) are biomarkers of fracture risk and are used to diagnose and evaluate the effect of treatment on PMO, which include the following biomarkers: bone formation markers, including serum alkaline phosphatase (ALP) and total procollagen type 1 N-terminal propeptide (TP1NP); bone resorption markers, including β-collagen degradation product (β-CTX/β‐CROSSL); bone mineral metabolism indicators, including calcium (Ca) and phosphorus (P); and bone regulatory hormone indicators, including 25 hydroxyvitamin D (25(OH)D).

In addition to serologic markers, there is a correlation between gastrointestinal (GI) health and bone health. The gastrointestinal tract is a very complex system that has many important functions, such as digestion, absorption, detoxification, immunity and disease resistance [8], and is critical to human health, because gastrointestinal disorders can directly or indirectly impact bone health by affecting nutritional status. GI symptoms are experienced by up to 52% of European patients being treated for osteoporosis. It is worth noting that inflammatory bowel disease (IBD) is a common gastrointestinal disorder. A cohort study found that IBD patients had a hip fracture rate approximately 60% higher than matched controls [9]. Similarly, another study revealed that patients with IBD had lower bone mineral density (BMD) and experienced significant bone loss in both cortical and trabecular bone compared to healthy controls [10]. Malnutrition is prevalent among patients with inflammatory bowel disease (IBD), with one study reporting that approximately 16–68% of them are malnourished [11]. This may explain why IBD patients are more prone to osteoporosis. Furthermore, a large cross-sectional study based on the National Health and Nutrition Examination Survey (NHANES) in the United States shows an inverse association between the Geriatric Nutritional Risk Index (GNRI) and the risk of osteoporosis in older adults [12]. This index was also found to increase alongside BMD in the Chinese population [13]. In patients with nutritional limitations due to gastrectomy, BMD in the proximal femoral region, including the femoral neck and total hip, decreased by 12% [14].

Given the above background, we conducted this study to explore the relationships between gastrointestinal health and nutritional status and bone health in postmenopausal women. We used gastrointestinal symptom questionnaires and serological indicators that patients could easily participate in the examination to reflect the bone mineral density of patients with a simpler test. This study aims to provide new ideas for the prevention and treatment of postmenopausal osteoporosis.

Methods

Participants and study design

A total of 222 postmenopausal female patients aged ≥ 40 years who underwent BMD examination at the Affiliated Hospital of Jiangnan University from January 2023 to September 2023 were recruited. The sample size calculation software G Power 3.1 was used to perfrom power analysis. At the test level α = 0.05, the test power 1-β = 0.95, the statistical effect size was 0.27, which was in the medium effect. Patients who had less than one year of menopause, secondary osteoporosis, or recent use of medications that may affect bone metabolism (such as thiazolidinediones, immunosuppressants, systemic glucocorticoids, or hormone replacement therapy) were excluded through the hospital’s electronic medical record system, combined with past medical history and current prescription. Patients who met the inclusion and exclusion criteria and provided informed consent were accompanied by the researchers to the imaging department for the purpose of bone mineral density measurement. According to the standards of the World Health Organization (WHO) [15], the subjects were divided into three groups according to their BMD status: the normal group (T≥-1), the osteopenia group (-2.5 < T < -1) and the osteoporosis group (T≤-2.5) (Fig. 1). The researchers, who all received the same training, used a precise height measuring device and weighing scale to measure the patients’ height and weight. These measurements were accurate to two decimal places. In addition, the researchers calculated the BMI of each patient. At the same time, the patients were interviewed about various aspects of their lives, such as their age, educational background, medical consultation history, past medical history, smoking and drinking habits, dietary preferences, and exercise routines. Furthermore, the patients completed the gastrointestinal symptoms scale and the quality of life scale. Afterward, a nursing researcher collected blood samples from the patients.

Fig. 1

Flow chart of the study. BMD, bone mineral density

Serum biochemical index measurements

Peripheral venous blood was collected from all subjects and sent to the laboratory department for measurement. The researchers of this project carried out the laboratory report query and data collection.

The serum ALP, Ca, P, albumin (ALB), total protein (TP), and prealbumin (Pa) concentrations were determined via an automatic biochemical analyzer. 25(OH)D, TP1NP, and β-CTX were detected by electrochemiluminescence. The normal reference values of these indicators are as follows: 25(OH)D (≥ 30 ng/mL); TP1NP (16–55 ng/mL); β-CTX (0-0.573 ng/mL); Ca (2.11–2.52 mmol/L); P (0.85–1.51 mmol/L); ALP (50-135U/L); ALB (40–55 g/L); TP (65–85 g/L); and Pa (180–350 mg/L).

BMD measurements

Bone densitometry was performed by the staff of the Department of Imaging at Jiangnan University using dual-energy X-ray absorptiometry (DXA). All tests were performed using the same instrument. The technicians were uniformly and formally trained, and the testing instrument was calibrated daily to rule out human error. The BMD machine was warmed by the staff, and a standardized periosteum was scanned point-to-point to obtain measurements at three fixed points (left femoral neck, total hip, and lumbar vertebrae L1-L4). The researchers gathered BMD reports and organized the data.

Gastrointestinal symptoms and quality of life

Gastrointestinal function assessment

Gastrointestinal symptoms were assessed using the Gastrointestinal Symptom Rating Scale (GSRS) [16], which has 15 items covering five different gastrointestinal symptoms: reflux, abdominal pain, diarrhea, constipation, and dyspepsia; each item is divided into 4 options. The higher the score is, the more severe the gastrointestinal symptoms and the poorer the patient’s intestinal health status.

Quality of life assessment

The subjects’ quality of life was assessed using the Short Form 12 (SF-12) [17], 8 dimensions: physical functioning (PF), role physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role emotional (RE) and mental health (MH). Based on the domains, two summary measures may be estimated—the Physical Component Summary (PCS) and Mental Component Summary (MCS). The SF-12 is scored on a percentage scale, and after the crude score is obtained, the scale is transformed to a standardized scale. The scale combines dichotomous (0 = yes; 1 = no) and 3- or 5-point Likert responses. To standardize the scores, the following equation was used: Standardized score = ((X - Min)/(Max- Min)) × 100 [18, 19]. The higher the score, the higher the quality of life of the patient.

Statistical analysis

All the data were statistically analyzed using SPSS25.0. Samples with missing values were excluded. The Kolmogorov‒Smirnov test was used to test the normality of the distribution. Continuous variables such as age, BMI, GSRS, and SF-12 were reported as the mean ± standard deviation (mean ± SD). The one-way analysis of variance (ANOVA) was used to compare the osteopenia group and the osteoporosis group in terms of education level and eating habits. The categorical variables such as education level, dietary habits, and exercise frequency were expressed as percentages (%) and were compared using the chi-square test. A Bonferroni correction was applied to avoid Type I errors when conducting multiple comparisons. Pearson correlation analysis was used to examine the correlation between BMD and gastrointestinal symptoms, quality of life, and serological indicators. Multiple linear regression analysis was used to investigate the differences in BMD and GSRS, 25(OH)D, TP, ALB, and Pa among the three groups, while adjusting for age, education level, BMI, dietary habits, and exercise frequency. Before the multiple linear regression analysis, the data were tested for multicollinearity, and the variance expansion coefficient (VIF) (≤ 10) indicated that independent variables could be included in the multivariate analysis. A P value < 0.05 was considered to indicate statistical significance. For the subgroup analyses, we divided the participants by GSRS and 25(OH)D (≤ 18 points, and ≥ 19 points; ≤20 ng/ml, 21–29 ng/ml and ≥ 30 ng/ml).

Results

Baseline characteristics

A total of 222 postmenopausal women who met the criteria were enrolled in this study, including 58 postmenopausal women with normal bone mass, 80 postmenopausal women with osteopenia and 84 postmenopausal women with osteoporosis. There were significant differences between the normal group, osteopenia group and osteoporosis group in age, education level, body mass index (BMI), dietary habits and exercise frequency (P < 0.05) (Table 1). The ages of the individuals in the normal, osteopenia and osteoporosis groups increased successively, and their BMI decreased successively. Greater bone loss occurred with age, and BMD was protected at higher BMIs within the normal range. The proportion of individuals in the normal group with a high school education and above was 36.2%, which was significantly greater than that in the osteopenia group (17.6%) and osteoporosis group (6%), and the proportions of individuals who supplemented with soy products, dairy products, and nutritional supplements (calcium, vitamin D, etc.) were greater than those in the osteopenia and osteoporosis groups. The frequency of exercise was significantly greater in the normal group than in the osteopenia and osteoporosis groups. Differences in diet and exercise may be related to differences in education. No significant differences were detected in the presence of other variables (such as alcohol consumption, smoking status, or common chronic diseases [hypertension, diabetes, and osteoarthritis]) among the three groups.

Table 1 Baseline characteristics of the normal, osteopenia, and osteoporosis groups

Gastrointestinal health of postmenopausal female subjects

There were significant differences in gastrointestinal health among the normal, osteopenia and osteoporosis groups (P < 0.05) (Table 2). Gastrointestinal symptom scores were significantly lower in the normal group than in the osteopenia and osteoporosis groups. The patients in the osteoporosis group had the highest gastrointestinal symptom scores of the three groups, and their gastrointestinal health was the worst.

Table 2 Differences in gastrointestinal function among the normal group, osteopenia group and osteoporosis group

Quality of life in postmenopausal female subjects

The normal, osteopenia and osteoporosis groups significantly differed (all P < 0.05) in the eight dimensions as well as in the combined physical and mental scores (Table 3). Among them, the osteoporosis group had the worst physical health, and the PCS score was significantly lower than that of the osteopenia group; the highest PCS score was in the normal group. The normal group also had the highest MCS score, which was significantly greater than that of the osteopenia group. Additionally, subjects in the osteoporosis group had the lowest MCS score among the three groups, with more severe negative emotions. Overall, the individuals in the osteoporosis group were strongly affected by the disease and had a poor quality of life.

Table 3 Differences in quality of life among the normal, osteopenia, and osteoporosis groups

Comparison of serum biochemical indices in postmenopausal female subjects

Significant differences in 25(OH)D, TP, ALB, and Pa were found among the normal, osteopenia, and osteoporosis groups (all P < 0.05) (Table 4). Serum 25(OH)D and protein levels were significantly lower in subjects with reduced bone mass than in subjects with normal bone mass, and malnutrition affects bone health. Although the differences in TP1NP and β-CTX among the three groups were not significant, the TP1NP levels in the osteopenia group and the osteopenia group were lower than those in the normal group, and the β-CTX was greater than that in the normal group, which led to an increase in bone conversion.

Table 4 Differences in the serum biochemical indices among the normal, osteopenia and osteoporosis groups

Associations of BMD with gastrointestinal health, quality of life, and serum marker levels

There were correlations between gastrointestinal health, quality of life, bone turnover markers, protein nutritional levels and BMD in postmenopausal female subjects (Table 5). Gastrointestinal health and BMD in postmenopausal female subjects were negatively correlated, and the more gastrointestinal symptoms was associated with lower levels of BMD; There were significant positive correlations of PCS, MCS, 25(OH)D, TP, ALB, and Pa with BMD in postmenopausal female subjects, and the high quality of life of the subjects was suggestive of their comparative bone health, and the subjects with high levels of 25(OH)D and protein also had greater BMD. There were no significant correlations of TP1NP, β-CTX, ALP, Ca, or P with BMD in postmenopausal women (P > 0.05).

Table 5 Correlation analysis of the quality of the GSRS score, SF-12 score, serum indices and BMD

Logistic regression prediction of osteoporosis in postmenopausal women

A collinearity diagnosis was performed prior to multivariate logistic regression analysis. All the VIFs calculated by SPSS25.0 were less than 5, indicating that the included variables do not have serious collinearity and can be entered into multiple linear regression analysis. After adjusting for age, education level, BMI, dietary habits, and exercise frequency, it was found that GSRS and 25(OH)D concentration were significant predictors of BMD, with BMD being the dependent variable (Table 6). These variables explained 70.3% of the observed changes in BMD in postmenopausal women. Those with higher 25(OH)D levels had a lower risk of osteoporosis; postmenopausal women who supplemented with soy products, supplemented with dairy products and exercised regularly had a lower risk of osteoporosis. All the covariates listed above are associated with an increased risk of osteoporosis.

Table 6 Subgroup analysis by GSRS and serum 25(OH)D level

The relationship between GSRS, serum 25(OH)D and the risk of osteoporosis in postmenopausal women

According to the median GSRS score of 18.5, postmenopausal women were classified into two subgroups based on their GI symptoms: a low GI symptoms subgroup (≤ 18, n = 86) and a high GI symptoms subgroup (≥ 19, n = 136). Additionally, the patients were also divided into three groups based on their serum 25(OH)D levels: a deficiency group (≤ 20 ng/ml, n = 176), an insufficiency group (21–29 ng/ml, n = 40), and a normal group (≥ 30 ng/ml, n = 6).

After adjusting for age, education level, BMI, diet, and exercise habits, a multiple linear regression analysis indicated that having more gastrointestinal symptoms and a lower serum 25(OH)D level were independent risk factors for osteoporosis in postmenopausal women (P < 0.05, referring to Table 7).

Table 7 Logistic regression analysis of risk factors for osteoporosis

Discussion

With the increase in human life expectancy and the aging of the population, osteoporosis has become a major global health concern. The prevalence of osteoporosis is particularly high among postmenopausal elderly women [20]. After menopause, bone density decreases by 2.5% per year, while premenopausal bone density decreases by approximately 0.13% per year [21]; thus, the premenopausal period is key for preventing and delaying the development of osteoporosis. Postmenopausal osteoporosis is affected by a variety of risk factors, and early symptoms are not obvious. The early identification of relevant risk factors and screening of high-risk groups should be prioritized in the clinic so that efforts can be made to control the loss of bone mass by adjusting lifestyle habits, dietary structure, and other measures, thus reducing the incidence of osteoporosis.

In addition to the effects of age gain and sex hormone reduction, factors such as gastrointestinal health, nutritional status, and bone conversion indices should not be ignored. In this study, we included various factors such as age, BMI, education level, dietary habits, exercise frequency, gastrointestinal symptoms, 25(OH)D, total protein, albumin, and prealbumin of postmenopausal women in our regression analysis. Our aim was to determine the impact of these factors on bone mineral density, which served as the dependent variable. The results of our analysis revealed that gastrointestinal health status and serum 25(OH)D concentration were significant predictors of osteoporosis risk in postmenopausal women. Additionally, we found that age, education level, BMI, dietary habits, and exercise frequency also had associations with bone mineral density, serving as important controlling factors.

Previous studies have shown that BMI can be used as an independent protective factor for BMD [22], but the relationship between BMI and osteoporosis has not been consistent among existing studies [23,24,25,26,27].In this study, the risk of osteoporosis increased with decreasing BMI. Although the BMI of the normal group was significantly greater than that of the osteopenia group and osteoporosis group, the BMI of the patients in each group was still within the normal range or was slightly overweight and did not reach the obesity level. The reason for the low risk of osteoporosis in the normal group under these conditions may be that adipose tissue can produce aromatase, which synthesizes estrogen outside the gonads and protects the bones [28]. Therefore, it is recommended that postmenopausal women try to gain weight within the normal BMI range.

In addition, dietary habits and exercise can also affect bone health. Studies have shown that supplementation with soy products, dairy products, nutritional supplements (calcium and vitamin D, etc.), and adherence to exercise have positive effects on BMD and bone metabolism [29,30,31]. Protein malnutrition reduces bone mass and changes muscle strength, leading to the development of osteoporotic fractures [32]. The results from the First National Health and Nutrition Examination Survey (NHANES I) also showed that hip fractures were more common in patients with low energy intake and low serum ALB levels [33]. In this study, the concentrations of total protein, albumin and prealbumin in the osteoporosis group were lower than those in the osteopenia group and much lower than those in the normal group. The reduction in protein led to a reduction in BMD, which was confirmed by the correlation analysis results. At the same time, among the participants included in this study, compared with those in the low-BMD population, those in the high-BMD population had relatively higher education levels and may have been more familiar with health care, which may have led to better lifestyle habits, such as the habit of consuming soy products, dairy products, nutritional supplements (calcium and vitamin D, etc.), and exercising regularly, which would result in healthier bones. Therefore, it is necessary to strengthen health education for middle-aged and elderly women with low educational attainment, promote reasonable supplementation with soy and dairy products and other nutritional supplements such as calcium and vitamin D, and increase the amount of exercise appropriately to prevent the occurrence of osteoporosis.

Dietary habits are also associated with gastrointestinal symptoms. The presence of gastrointestinal symptoms indicated that a subject had gastrointestinal disease or was in the predisease stage. The high gastrointestinal symptom scores in the osteopenia and osteoporosis groups in this study may indicate that gastrointestinal disorders lead to impaired bone health. Intestinal inflammation can adversely affect the accumulation of bone minerals [34,35,36], and patients with celiac disease have many gastrointestinal symptoms and are prone to osteoporosis or osteopenia [37]. Decreased bone density is a common consequence of gastrointestinal disease and in turn leads to a decreased quality of life in postmenopausal osteoporosis patients. Osteoporosis in postmenopausal women can lead to pain, fracture, and spinal deformation and may also be accompanied by sleep disorders, hot flashes, and night sweats, which can trigger anxiety, fear, depression, and other adverse psychological states. In this study, the PCS score of the normal group was greater than that of the osteopenia group and osteoporosis group. These findings indicate that elderly postmenopausal women with osteopenia or osteoporosis were more likely to suffer pain and fracture than were those with normal bone mass, which could lead to a decrease in the self-care ability and mobility of postmenopausal women. In this study, the normal group had the highest MCS, the osteopenia group had the second highest score, and the osteoporosis group had the lowest score. Bone pain, sleep disorders, and night sweats caused by reduced bone density can increase the susceptibility of postmenopausal osteoporosis patients to depression and anxiety, which can seriously affect their mental health.

In addition to the factors mentioned above, it is important to consider the relationship between bone turnover markers and the risk of osteoporosis. TPIN is a specific marker of type I collagen deposition that is formed by shearing off the amino-terminal prepeptide of type I procollagen under the action of protease during the formation of bone organic type I collagen; moreover, TPIN is a specific marker of type I collagen deposition. It can be used as a metabolite to directly assess the activity of osteoblasts after entry into the bloodstream and can sensitively reflect the state of bone formation in the whole body [38]. Alkaline phosphatase, a widely distributed membrane-bound glycoprotein, is also a marker of bone formation [39]. β-CTX is a known marker of bone resorption and reflects the degree of bone matrix degradation. Mature type I collagen in the bone matrix degrades into β-CTX and is released into the blood during bone metabolism [40].

In this study, all three groups of subjects were postmenopausal women, which may be the reason why there was no statistical difference in the above indicators. However, it can be seen from the data that the TP1N and CROSSL of the three groups were higher than the normal reference range, the patients all exhibited high bone turnover; the bone absorption indices (β-CTX) of patients in the osteoporosis group and osteopenia group were lower than those of patients in the normal group; and the bone formation indices (TP1NP) were greater than those of patients in the normal group. These findings may be related to the low bone mass of postmenopausal women, which further activated the high bone turnover state and resulted in more active osteoblasts and osteoclasts. Although TP1NP and β-CTX do not predict osteoporosis risk in postmenopausal women, Vasikaran et al. collated evidence from prospective PubMed studies published between 2001 and 2010 and concluded that bone turnover markers can predict fracture risk independently of other risk factors in postmenopausal women [41]. Therefore, it is meaningful to use these two indicators to evaluate bone health in postmenopausal women.

25(OH)D is the main source of vitamin D in the body, it is involved in regulating the metabolism of calcium and phosphorus, and is one of the essential components for intestinal calcium and phosphorus absorption and bone mineralization [42]; in addition, it can promote the activity of calcium and phosphorus, osteoblast and osteoclast proliferation [43].In this study, since all three groups of subjects were postmenopausal women, the serum 25(OH)D level remained below normal in the normal group, although it was significantly greater than that in the osteopenia and osteoporosis groups. Lieben et al. reported that the levels of calcium and 25(OH)D in the body are related to the quality and content of bone [44]. A low serum 25(OH)D concentration is considered an important risk factor for low BMD, and the serum 25(OH)D concentration in the lumbar spine and femoral neck of premenopausal women is positively correlated with BMD [45]. Therefore, increasing the serum 25(OH)D concentration is relevant for the prevention of osteoporosis in postmenopausal women.

Conclusion

Cross-sectional analysis revealed a negative correlation between intestinal health and the risk of osteoporosis in postmenopausal women. Furthermore, 25(OH)D, TP, ALB, and Pa were found to have a positive correlation with the risk of osteoporosis. On the other hand, osteoporosis itself was found to have a negative correlation with quality of life. TP1NP was higher in postmenopausal women with reduced BMD and β-CTX was lower than in postmenopausal women with normal BMD. These findings suggest that clinical health care providers should monitor the gastrointestinal health of postmenopausal women in their work. For this group of people, we can consider increasing the detection of biological indicators such as bone turnover markers and serum proteins during physical health examinations to help individuals identify and screen for osteoporosis at an early stage and provide individualized health education in a targeted manner, suggesting that they treat gastrointestinal diseases in a timely manner and improve gastrointestinal symptoms. Patients should also be instructed to consume appropriate amounts of vitamin D, calcium and protein, which are clinically useful for the prediction, diagnosis and treatment of osteoporosis.

Since all the patients in this study were postmenopausal women recruited from the same hospital and agreed to undergo BMD measurement, it is important to note that they may not accurately represent the broader postmenopausal population. Furthermore, our study did not include data from patients with early menopause (age < 40 years). Additionally, it is essential to recognize that this study was cross-sectional and no causal relationship can be determined. Therefore, a follow-up multicenter study with a larger sample size is needed to address selection bias and validate the findings of this experiment.