Relationship between abdominal fat volume and bone base material pairs from dual-energy spectral computed tomography in young and middle-aged patients with metabolic syndrome

Introduction

Metabolic syndrome (MetS), also known as syndrome X and the insulin resistance syndrome, is a pathological condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia and which poses a threat to human health worldwide (1,2). By modifying body burden and hormonal and metabolic metabolism, among other processes, MetS exerts a complicated influence on bone (3). Previous studies have shown that obesity is a protective factor for bone mineral density (BMD) (4,5), but research in recent years has indicated that obesity is a critical risk factor for bone loss and osteoporosis in patients. It has further been suggested that MetS is associated with reduced BMD and increased risk of osteopenia or osteoporosis. Several studies using dual-energy X-ray absorptiometry (DXA) and quantitative ultrasound have reported that patients with MetS tend to have lower BMD, suggesting a higher susceptibility to bone fragility and fractures (4,6,7). DXA and quantitative computed tomography (QCT) are important methods for obtaining BMD measurements, but the former is highly susceptible to the overlapping of the adjacent tissues, and the latter is affected by body-mode correction factors and is not available in some centers (8,9). Therefore, developing a convenient and practical examination method to evaluate BMD is crucial for improved clinical practice.

The application of dual-energy spectral CT has been expanded to include the quantification of bone (10,11). Studies have shown that material decomposition technology based on dual-energy spectral CT can be used for bone quantification (12,13). Yue et al. (14) reported that calcium (water), i.e., Ca (water), can reflect age-related changes in the lumbar spine of adult women and is correlated with BMD, suggesting its suitability for BMD evaluation. Wang et al. (13) obtained various bone base material pair (BMP) indices, including bone Ca (water) and hydroxyapatite (water), i.e., HAP (water), BMPs, in the spinal vertebrae using the material decomposition technology of dual-energy spectral CT. They discovered a strong relationship between HAP (water) and BMD on QCT, which provided a high degree of diagnostic accuracy, and found that HAP (water) showed the best predictive capability in patients with osteopenia and osteoporosis. Hence, it is likely that Ca (water) and HAP (water) BMPs can be used for BMD evaluation. Therefore, in this study, we used the Ca (water) and HAP (water) measurement from dual-energy spectral CT to assess the bone status of patients with MetS.

In the past, the diagnosis and assessment of the degree of obesity focused mainly on body weight, body mass index (BMI), and abdominal circumference; however, in recent years, the quantification of abdominal fat in this context, especially visceral fat, has attracted extensive attention (15). Visceral fat is a key contributor to insulin resistance and a chronic inflammatory state and is closely linked to MetS and cardiovascular disease (16). Therefore, understanding the distribution of fat in patients can inform clinical judgment. Since abdominal obesity is characteristic of MetS, measuring and segmenting the abdominal fat volume may be critical for diagnosis, treatment, and follow-up. However, there has been limited research analyzing the relationship between BMPs and abdominal fat volume in patients with MetS.

This study had two main objectives: first, we aimed to use a set of dual-energy spectral CT indices, including Ca (water), HAP (water), and measurements of abdominal fat volumes to characterize the bone status and body composition in young and middle-aged patients with MetS. Second, we sought to clarify the associations between these parameters in order to provide a basis for clinical prevention and management of MetS. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-573/rc).

Methods

Study population

This study retrospectively collected data from patients with MetS scheduled for gastric sleeve resection at the Center for Obesity and Metabolic Diseases, Beijing Shijitan Hospital, Capital Medical University, from June to November 2021. Patients with MetS were included based on the 2006 International Diabetes Federation Diagnostic Criteria (2) which specifies a waist circumference >94 cm in men or >80 cm in women and the presence of two or more of the following: (I) blood glucose levels >5.6 mmol/L or a diagnosis of diabetes mellitus; (II) high-density lipoprotein cholesterol levels <1.0 mmol/L in men and <1.3 mmol/L in women or medication for low high-density lipoprotein cholesterol; (III) blood triglyceride levels >1.7 mmol/L or medication for elevated triglycerides; and (IV) blood pressure >130/85 mmHg or medication for hypertension.

The inclusion criteria for this study were as follows: MetS diagnosed in the Obesity and Metabolic Disease Center of our hospital in young and middle-aged patients aged 23–59 years (17,18) (to minimize the confounding effects of age-related bone loss, especially those associated with the menopausal transition in women) who underwent an abdominal dual-energy spectral CT scan at the time of consultation. The exclusion criteria were as follows: (I) other diseases affecting bone metabolism (such as thyroid, pituitary, and adrenal diseases); (II) long-term use of drugs affecting bone metabolism (such as calcitonin, thyroid hormones, glucocorticoids, and hypoglycemic drugs), (III) presence of severe hepatic and/or renal insufficiency (severe hepatic insufficiency was defined as significant elevation in serum aminotransferases levels, approximately 15 times or more above the upper limit of normal; renal insufficiency was defined as an estimated glomerular filtration rate (eGFR) less than 60 mL/(min·1.73 m²), (IV) diabetic ketoacidosis, (V) experiencing stress state (19), (VI) incomplete clinical or imaging information, and (VII) the presence of the vertebral collapse or previous intervention/operation in the L1–L3 vertebrae (Figure 1). This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was approved by the Institutional Ethics Committee of Beijing Shijitan Hospital of Capital Medical University (No. IIT2023-029-001). The requirement for individual consent was waived due to the retrospective nature of the analysis.

Figure 1 Flowchart of participant selection. MetS, metabolic syndrome; CT, computed tomography.

Sample size

In our study, the sample size was determined based on an established rule in statistics, which recommends having at least 10 events for each predictor parameter that is being considered for inclusion in the prediction model equation (20). In our multiple linear regression analysis, we included a total of three variables. Therefore, adhering to the aforementioned rule, our sample size was at least 30 cases. This could ensure that our estimates of the model parameters were sufficiently stable and reliable.

Clinical information

Patient characteristics were collected from the electronic medical records and included age, sex, height, and weight. BMI was calculated as follows: weight (kg)/height² (m²). A venous blood sample was drawn under standard conditions after an overnight fasting period. Laboratory parameters included fasting plasma glucose level, fasting insulin C-peptide level, fasting insulin level, glycated hemoglobin 2-hour post-prandial glucose level, total cholesterol level, total triglyceride high-density lipoprotein cholesterol level, low-density lipoprotein cholesterol level, and total calcium concentrations.

Imaging information

The patient’s abdominal CT plain image was acquired with a GE Revolution CT device (GE HealthCare, Chicago, IL, USA) under the following scanning parameters: switching, 80/140 kVp (0.5 ms); automatic tube current, 200–485 mA; pitch, 0.992:1; anterior adaptive statistical iterative reconstruction, 40%; reconstructed layer thickness, 1.25 mm; and layer spacing, 1.25 mm. Images were transferred to an Advantage Workstation 4.7 (GE HealthCare) for postprocessing with the gemstone spectral imaging mode.

Quantitative analysis of the first to third lumbar vertebrae (L1–L3) was performed using Ca (water) and HAP (water) as the base substance. With the vertebral venous plexus and bone island being avoided, a 100- to 120-mm² region of interest (ROI) was placed at the central level of the vertebral body. The values of Ca (water) and HAP (water) in the L1–L3 vertebrae were measured twice, and the average values of the bone Ca (water) and HAP (water) BMPs in the L1–L3 vertebrae were obtained. In addition, the L1–L3 vertebrae level was selected to measure the patient’s fat volume, which mainly included total abdominal fat (TAF) volume, abdominal visceral fat (AVF) volume, and abdominal subcutaneous fat (ASF) volume. The ratio of visceral fat to subcutaneous fat volume (VF/SF) was calculated. This choice was informed by prior research demonstrating that a multislice approach provides a more representative measurement of abdominal fat distribution as compared to single-slice methods (21). Furthermore, the abdominal circumference at the level of the third lumbar vertebrae (L3) and the thickness of the subcutaneous fat adjacent to the posterior vertebral muscles were measured (recorded as the fat thickness), as shown in Figure 2.

Figure 2 A 43-year-old man with metabolic syndrome. The method of acquisition of the patient’s bone base material pairs and abdominal fat volume. (A-C) The fat volume, Ca (water), and HAP (water) figures of the patient’s spine in the sagittal position are shown, with the horizontal line corresponding to the level of the L1–L3 vertebrae, respectively. (D-F) Segmentation of the visceral (red areas) and subcutaneous fat (blue areas). (G-I) Spectral CT images at 70 keV for (J-L) Ca (water) figures and (M-O) HAP (water) figures of the L1–L3 vertebrae. Ca, calcium; HAP, hydroxyapatite; CT, computed tomography.

Statistical analysis

Statistical analysis was performed using SPSS 26.0 software (IBM Corp., Armonk, NY, USA). Patients were categorized by sex, with the mean and standard deviation being calculated. The t-test was used to analyze the differences in clinical and imaging parameters between two groups. Pearson correlation coefficient was used to assess the relationship between the clinical and imaging indices of patients with MetS, and partial correlation analysis was performed in patients for fat volume corrected for age, sex, and bone BMPs. A correlation coefficient less than 0.30 was considered to be poor, 0.31–0.50 fair, 0.51–0.80 moderate, and greater than 0.80 substantial. Furthermore, age, sex, and TAF volume were analyzed using multiple linear regression, with the dependent variables being the Ca (water) and HAP (water) BMPs. Statistical significance was defined at a P value <0.05.

Results

Baseline characteristics

A total of 112 young and middle-aged patients with MetS were included in this study (Figure 1), including 85 females and 27 males, with a mean age of 37.99±8.60 (range, 23–59) years and a mean BMI of 35.22±4.92 (range, 26.57–51.19) kg/m². The average values of Ca (water) and HAP (water) BMPs in the L1–L3 vertebrae of patients with MetS were 58.27±10.81 and 124.23±22.74 mg/cm³, respectively. The average TAF volume was 5,418.83±1,688.07 mL, the AVF volume was 2,223.31±851.10 mL, and the ASF volume was 3,195.5±1,254.75 mL. Furthermore, the average abdominal circumference and fat thickness were 110.91±11.45 and 4.78±1.65 cm, respectively.

The patients were divided into two groups according to sex. In terms of imaging indicators, women had higher lumbar vertebral Ca (water) and HAP (water) BMPs (P<0.01). Additionally, the TAF volume, AVF volume, VF/SF ratio, and abdominal circumference were lower in women (P<0.01), as shown in Table 1 and Figure 3. In terms of clinical indicators, women had a lower fasting insulin C-peptide level (P=0.006), total calcium concentration (P=0.048), and a high-density lipoprotein cholesterol level (P=0.002), as shown in Table S1.

Figure 3 Correlation between BMPs, total abdominal fat volume, and age in patients with metabolic syndrome by sex. Ca, calcium; HAP, hydroxyapatite; BMP, base material pair.

Correlation and partial correlation analysis of fat volume and bone BMPs

We performed correlation analyses to identify variables associated with bone BMPs. The average Ca (water) and HAP (water) BMPs of the L1–L3 vertebrae of the patients were found to be negatively correlated with age (R=−0.408, fair correlation; R=−0.446, fair correlation; both P values <0.001) and BMI (R=−0.216, poor correlation; R=−0.230, poor correlation; both P values <0.05). Our results indicated that the volumes of TAF, AVF, and VF/SF ratio showed negative correlations with the average Ca (water) BMPs of the L1–L3 vertebrae in patients with MetS (TAF: R=−0.371, fair correlation; AVF: R=−0.499, fair correlation; VF/SF ratio: R=−0.295, poor correlation; all P values <0.01). Similarly, these fat parameters also showed negative correlations with HAP (water) BMPs (TAF: R=−0.374, fair correlation; AVF: R=−0.511, moderate correlation; VF/SF ratio: R=−0.305, poor correlation; all P values <0.01). Table 2 provides a detailed overview of these correlations. Furthermore, none of the clinical parameters assessed showed a statistically significant correlation with bone BMPs (P>0.05), as shown in Table S2. In addition, the correlations between bone BMPs and fat for patients with MetS of different sexes are shown in Table S3.

After adjustments were made for age and sex, a partial correlation analysis of fat volume and BMPs was performed, as shown in Table 3. The results demonstrated that the volumes of TAF, AVF, and ASF were negatively correlated with the average Ca (water) and HAP (water) BMPs of the L1–L3 vertebrae, respectively (P<0.01). Specifically, TAF volume showed a fair negative correlation with average Ca (water) (r=−0.362; P<0.001) and HAP (water) BMPs (r=−0.383; P<0.001). AVF volume had a poor negative correlation with average Ca (water) (r=−0.270; P=0.004) and a fair negative correlation with HAP (water) BMPs (r=−0.301; P=0.001). ASF volume showed a fair negative correlation with average Ca (water) (r=−0.339; P<0.001) and HAP (water) BMPs (r=−0.349; P<0.001). The VF/SF ratio showed no significant correlation with either average Ca (water) or HAP (water) BMPs (P>0.05). The univariate analysis of fat factors associated with bone BMPs in young and middle-aged patients with MetS is shown in Table S4.

Multiple linear regression models

Multiple linear regression equations were fitted for age, sex, TAF volume, ASF volume, and AVF volume, with the average L1–L3 vertebral Ca (water) and HAP (water) BMPs serving as dependent variables. Age, sex, TAF volume, and AVF volume were found to be significantly associated with Ca (water) and HAP (water) BMPs of patients with MetS, while ASF volume was excluded from the model. As shown in Table 4, the Ca (water) and HAP (water) BMPs decreased with increasing age and TAF volume (P<0.001). ASF volume was excluded from the final multiple linear regression model. The equation fitted to the average L1–L3 vertebral Ca (water) and HAP (water) BMPs versus age, sex, and TAF volume was as follows:

Bone Ca (water) BMPs = 76.469 − 0.500 age + 6.762 sex − 0.002 TAF volume;

Bone HAP (water) BMP =171.704 − 1.138 age + 11.825 sex − 0.004 TAF volume.

Discussion

MetS is a series of clinical syndromes characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Among them, abdominal obesity is a key manifestation. Consequently, it holds immense importance in segmenting and quantifying abdominal fat. Previous research has indicated that obesity has a positive impact on BMD (22). More recent research, however, has brought attention to the possible link between obesity and osteopenia and osteoporosis (4,6,7). Therefore, clarifying the relationship between abdominal fat content and fat distribution and BMD among individuals diagnosed with MetS holds considerable clinical significance. In this study, the abdominal fat volume and bone Ca (water) and HAP (water) BMPs at the L1–L3 vertebral levels in patients with MetS were obtained using dual-energy spectral CT, the differences between patients with MetS of different sexes were compared, and the relationship between the above parameters and laboratory indices was analyzed. Furthermore, a comprehensive analysis of the association between abdominal fat volume, distribution, and bone Ca (water) and HAP (water) BMPs demonstrated that increased levels of abdominal fat in patients with MetS were a significant contributing factors to osteoporosis.

Previous studies using linear regression analysis on cancellous bone CT values while accounting for factors related to body composition, such as HAP, demonstrated that the use of quantitative CT can obtain accurate measurements of BMD (23,24). Precise evaluations of bone geometric parameters can also be obtained using QCT; however, QCT is dependent on the scanning process and calibration model (9). As an opportunistic mode of CT (using the imaging modality beyond the primary diagnostic purpose), dual-energy CT allows for the screening of bone Ca (water), HAP (water), and abdominal fat volume without additional radiation and cost. Recent research findings have demonstrated that dual-energy spectral CT can provide precise quantitative data on bone composition and structure. Wang et al. (13) examined the application of dual-energy spectral CT for quantifying the bone HAP (water) BMPs in accurately reflecting changes in bone microstructure among patients. They compared the BMD indexes obtained from dual-energy spectral CT and quantitative CT, providing valuable insights for evaluating vertebral BMD and diagnosing osteoporosis. Therefore, we aimed to evaluate the Ca (water) and HAP (water) BMPs in the L1–L3 vertebral body as indicators of mineral density. Moreover, previous research mostly assessed the distribution of fat in the abdominal region at the level of the L3 vertebral body to ascertain the total distribution of fat in patients (15). Assessing the fat distribution of patients with MetS solely based on a single layer’s fat area is challenging despite the presence of primary manifestations of abdominal obesity. Therefore, in our study, abdominal fat volume was measured at the L1–L3 vertebral level to accurately depict abdominal obesity features among patients. Additionally, subcutaneous and visceral fat were categorized to provide a comprehensive understanding of fat distribution characteristics.

We used dual-energy CT to analyze fat and bone composition in individuals with MetS of different sexes. We found that females had higher lumbar vertebral Ca (water) and HAP (water) BMPs, while their TAF volume, visceral fat volume, VF/SF ratio, and abdominal circumference were relatively lower. The distribution of fat and BMD is significantly influenced by sex. Notably, there are significant differences in fat distribution between males and females. In our study, males exhibited significantly higher levels of visceral fat compared to females, consistent with previous research (25,26). Males typically have 10–20% of their total body fat as visceral fat, whereas females tend to have 5–10% (27,28). Females may exhibit a more advantageous thermogenic capacity and increased neuroregulation of adipose tissues, which could play a crucial role in promoting a healthier metabolic profile in adipose tissues compared to their male counterparts (25). This sexual dimorphism in fat biology is attributed to genetic differences, including the impact of sex hormones, receptor functionality, and gene expression patterns. Sex hormones play a crucial role in adipocyte development, fat cell proliferation, and modulation of gene expression related to insulin resistance and lipid metabolism (29).

Sex hormones have a significant impact on skeletal development and metabolism, similar to adipose tissue distribution. Male individuals demonstrate enhanced bone strength, elongated long bones with increased width, and elevated peak bone mineral content, which is primarily attributable to the modulation of sex hormones (30). The androgen hormone and its derivative dihydrotestosterone directly interact with androgen receptors, thereby augmenting bone trabecular density. Conversely, estrogen facilitates periosteum development and bone trabeculae, while also regulating the activities of osteoblasts and osteoclasts (31,32). The results of this study, however, demonstrate that female patients exhibited increased levels of bone Ca (water) and HAP (water) BMPs in the lumbar spine. The potential explanation for this could be that women tend to exhibit lower overall abdominal fat volume and visceral fat volume, thereby reinforcing the association between adiposity and bone health.

In this study, bone Ca (water) and HAP (water) demonstrated a significant inverse association with the TAF volumes, visceral fat, and subcutaneous fat in patients with MetS. An increase in abdominal fat volume was associated with a relative decrease in both bone Ca (water) and HAP (water). Previous research suggests that visceral fat presents a substantial threat to BMD as a result of its increased metabolic activity (33,34). Multiple mechanisms are implicated in facilitating this impact. (I) Visceral fat releases proinflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) to affect bone metabolism. The nuclear factor-κB (NF-κB) signaling pathway is activated in obese individuals as a result of TNF-α stimulation, leading to an upregulation of colony-stimulating factor receptor, RANK, and its ligand RANKL. This enhances osteoclast activity and ultimately culminates in bone loss (35). Moreover, IL-6 predominantly facilitates osteoclastogenesis and bone resorption, while also promoting osteoblast proliferation and early differentiation, thus influencing skeletal architecture (35,36). (II) The release of free fatty acids and other substances by visceral fat impedes the expression of insulin receptors, leading to the development of insulin resistance. However, it is important to note that insulin is crucial for promoting bone formation and preventing bone loss. In cases where insulin resistance occurs, the ability of insulin to stimulate osteoblasts is diminished while bone resorption is enhanced, thereby impacting an individual’s BMD (37,38).

The focus of this study was patients with MetS. Previous research has indicated that the level of visceral fat can serve as a predictive factor for the occurrence and progression of MetS, with insulin resistance being a key component. Consequently, a previous study found that compared to individuals without MetS in the general population, those affected by MetS have more pronounced skeletal alterations (39). The current understanding of the association between subcutaneous fat and bone remains inconclusive, but our study identified an inverse relationship between them. These findings are in line with the investigations conducted by Lin et al. and Katzmarzyk et al. (36,40). Similarly, the study conducted by Zhang et al. (41) yielded similar findings to our own, as they also observed no significant association between BMD and the levels of subcutaneous fat and visceral fat in males. The aforementioned results may be attributed to factors such as the size of the sample, the age distribution, and the sex composition of the enrolled population. Consequently, it is imperative to further augment the sample size to advance our research.

Certain limitations to our study should be discussed. First, this study involved a retrospective design with a limited sample size. To gain deeper insights, large-sample, prospective studies should be conducted. Additionally, the research population of this study consisted exclusively of young and middle-aged patients with MetS. In future studies, it is advisable to broaden the sample by including patients with MetS from all age groups and implementing stratification. Moreover, this study did not include a direct measurement of BMD using QCT, and future studies incorporating QCT would be beneficial to provide a more comprehensive assessment of bone status in patients with MetS. Finally, we did not evaluate the modifications in patients with MetS after sleeve gastrectomy.

Conclusions

In summary, the dual-energy spectral CT analysis revealed a significant inverse correlation of bone Ca (water) and HAP (water) with abdominal fat volume in young and middle-aged female patients with MetS, suggesting that elevated levels of abdominal fat volume may be crucial in the pathogenesis of osteopenia among individuals with MetS. Therefore, it is imperative for individuals with MetS to actively engage in weight management and reduce fat volume to mitigate bone loss. Simultaneously, spectral CT is highly valuable to the acquisition of bone density indexes. Parameters such as bone Ca (water) and HAP (water) BMPs can be used as crucial measures to assess bone changes, thereby providing relevant assistance for clinical applications.

Acknowledgments

Funding: This study was financially supported by the National Natural Science Foundation of China (No. 61876216).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-573/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-573/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was approved by the Institutional Ethics Committee of Beijing Shijitan Hospital, Capital Medical University (no. IIT2023-029-001). The requirement for individual consent was waived due to the retrospective nature of the analysis.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. McCracken E, Monaghan M, Sreenivasan S. Pathophysiology of the metabolic syndrome. Clin Dermatol 2018;36:14-20. [Crossref] [PubMed]
2. Saklayen MG. The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep 2018;20:12. [Crossref] [PubMed]
3. Chin KY, Wong SK, Ekeuku SO, Pang KL. Relationship Between Metabolic Syndrome and Bone Health - An Evaluation of Epidemiological Studies and Mechanisms Involved. Diabetes Metab Syndr Obes 2020;13:3667-90. [Crossref] [PubMed]
4. Al-Dawood E, Zafar M. Association between metabolic syndrome and bone mineral density among menopausal Saudi women: Case-control study. Med J Islam Repub Iran 2021;35:26. [Crossref] [PubMed]
5. Asomaning K, Bertone-Johnson ER, Nasca PC, Hooven F, Pekow PS. The association between body mass index and osteoporosis in patients referred for a bone mineral density examination. J Womens Health (Larchmt) 2006;15:1028-34. [Crossref] [PubMed]
6. da Silva VN, Fiorelli LN, da Silva CC, Kurokawa CS, Goldberg TB. Do metabolic syndrome and its components have an impact on bone mineral density in adolescents? Nutr Metab (Lond) 2017;14:1. [Crossref] [PubMed]
7. Lee CY, Chuang YS, Lee CH, Wu MT. Linking metabolic syndrome with low bone mass through insights from BMI and health behaviors. Sci Rep 2023;13:14393. [Crossref] [PubMed]
8. Shalof H, Dimitri P, Shuweihdi F, Offiah AC. Which skeletal imaging modality is best for assessing bone health in children and young adults compared to DXA? A systematic review and meta-analysis Bone 2021;150:116013. [Crossref] [PubMed]
9. Giambini H, Dragomir-Daescu D, Huddleston PM, Camp JJ, An KN, Nassr A. The Effect of Quantitative Computed Tomography Acquisition Protocols on Bone Mineral Density Estimation. J Biomech Eng 2015;137:114502. [Crossref] [PubMed]
10. Wang M, Wu Y, Zhou Y, Dong J, Hou P, Gao J. The new fast kilovoltage-switching dual-energy computed tomography for measuring bone mineral density. Quant Imaging Med Surg 2023;13:801-11. [Crossref] [PubMed]
11. Ye H, Li X, Yao N, Shi Y, Wang Y, Yu W. Effect of abdominal adipose content on spine phantom bone mineral density measured by rapid kilovoltage-switching dual-energy CT and quantitative CT. Quant Imaging Med Surg 2022;12:4914-23. [Crossref] [PubMed]
12. Wang M, Wu Y, Zhou Y, Dong J, Hu S, Hou P, Gao J. Application of Dual-Energy Spectral Computed Tomography in Bone Mineral Density Measurement: Phantom and Clinical Research. Int J Gen Med 2022;15:6887-96. [Crossref] [PubMed]
13. Wang X, Li B, Tong X, Fan Y, Wang S, Liu Y, Fang X, Liu L. Diagnostic Accuracy of Dual-Energy CT Material Decomposition Technique for Assessing Bone Status Compared with Quantitative Computed Tomography. Diagnostics (Basel) 2023;13:1751. [Crossref] [PubMed]
14. Yue D, Li Fei S, Jing C, Ru Xin W, Rui Tong D, Ai Lian L, Luo YH. The relationship between calcium (water) density and age distribution in adult women with spectral CT: initial result compared to bone mineral density by dual-energy X-ray absorptiometry. Acta Radiol 2019;60:762-8. [Crossref] [PubMed]
15. Yu D, Zou M, Pan Q, Song Y, Li M, Zhang X, Zhou Y, Wang X, Guo L. Effects of liraglutide or lifestyle interventions combined with other antidiabetic drugs on abdominal fat distribution in people with obesity and type 2 diabetes mellitus evaluated by the energy spectrum ct: A prospective randomized controlled study. Front Endocrinol (Lausanne) 2022;13:951570. [Crossref] [PubMed]
16. Neeland IJ, Ross R, Després JP, Matsuzawa Y, Yamashita S, Shai I, Seidell J, Magni P, Santos RD, Arsenault B, Cuevas A, Hu FB, Griffin B, Zambon A, Barter P, Fruchart JC, Eckel RHInternational Atherosclerosis Society. International Chair on Cardiometabolic Risk Working Group on Visceral Obesity. Visceral and ectopic fat, atherosclerosis, and cardiometabolic disease: a position statement. Lancet Diabetes Endocrinol 2019;7:715-25. [Crossref] [PubMed]
17. Walker SN, Volkan K, Sechrist KR, Pender NJ. Health-promoting life styles of older adults: comparisons with young and middle-aged adults, correlates and patterns. ANS Adv Nurs Sci 1988;11:76-90. [Crossref] [PubMed]
18. Rustøen T, Wahl AK, Hanestad BR, Lerdal A, Paul S, Miaskowski C. Age and the experience of chronic pain: differences in health and quality of life among younger, middle-aged, and older adults. Clin J Pain 2005;21:513-23. [Crossref] [PubMed]
19. Kyrou I, Tsigos C. Stress hormones: physiological stress and regulation of metabolism. Curr Opin Pharmacol 2009;9:787-93. [Crossref] [PubMed]
20. Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, Moons KGM, Collins G, van Smeden M. Calculating the sample size required for developing a clinical prediction model. BMJ 2020;368:m441. [Crossref] [PubMed]
21. Hong JH, Hong H, Choi YR, Kim DH, Kim JY, Yoon JH, Yoon SH. CT analysis of thoracolumbar body composition for estimating whole-body composition. Insights Imaging 2023;14:69. [Crossref] [PubMed]
22. Qiao D, Li Y, Liu X, Zhang X, Qian X, Zhang H, Zhang G, Wang C. Association of obesity with bone mineral density and osteoporosis in adults: a systematic review and meta-analysis. Public Health 2020;180:22-8. [Crossref] [PubMed]
23. Qiang L, Jinpeng Y, Wei Y. Application of bone mineral density measurement by quantitative CT. Chinese Journal of Radiology 2009;43:3.
24. Ling W, Huishu Y, Xiaoguang C. Promoting actively the clinical application of quantitative CT. Chinese Journal of Radiology 2021;55:3.
25. Pan R, Chen Y. Fat biology and metabolic balance: On the significance of sex. Mol Cell Endocrinol 2021;533:111336. [Crossref] [PubMed]
26. Baarts RB, Jensen MR, Hansen OM, Haddock B, Prescott E, Hovind P, Simonsen L, Bülow J, Suetta C. Age- and sex-specific changes in visceral fat mass throughout the life-span. Obesity (Silver Spring) 2023;31:1953-61. [Crossref] [PubMed]
27. Bjune JI, Strømland PP, Jersin RÅ, Mellgren G, Dankel SN. Metabolic and Epigenetic Regulation by Estrogen in Adipocytes. Front Endocrinol (Lausanne) 2022;13:828780. [Crossref] [PubMed]
28. Palmer BF, Clegg DJ. The sexual dimorphism of obesity. Mol Cell Endocrinol 2015;402:113-9. [Crossref] [PubMed]
29. Chang E, Varghese M, Singer K. Gender and Sex Differences in Adipose Tissue. Curr Diab Rep 2018;18:69. [Crossref] [PubMed]
30. Riggs BL, Khosla S, Melton LJ 3rd. Sex steroids and the construction and conservation of the adult skeleton. Endocr Rev 2002;23:279-302. [Crossref] [PubMed]
31. Khosla S, Monroe DG. Regulation of Bone Metabolism by Sex Steroids. Cold Spring Harb Perspect Med 2018;8:a031211. [Crossref] [PubMed]
32. Rui Z, Xueyan W. Progress in the effects of sex steroids on bone mineral density and morphology. Chinese Journal of Endocrinology and Metabolism 2019;35:986.
33. Campos RM, Lazaretti-Castro M, Mello MT, Tock L, Silva PL, Corgosinho FC, Carnier J. Piano Ad, Sanches PL, Masquio DC, Tufik S, Dâmaso AR. Influence of visceral and subcutaneous fat in bone mineral density of obese adolescents. Arq Bras Endocrinol Metabol 2012;56:12-8. [Crossref] [PubMed]
34. Yerges-Armstrong LM, Miljkovic I, Cauley JA, Sheu Y, Gordon CL, Wheeler VW, Bunker CH, Patrick AL, Zmuda JM. Adipose tissue and volumetric bone mineral density of older Afro-Caribbean men. J Bone Miner Res 2010;25:2221-8. [Crossref] [PubMed]
35. Gkastaris K, Goulis DG, Potoupnis M, Anastasilakis AD, Kapetanos G. Obesity, osteoporosis and bone metabolism. J Musculoskelet Neuronal Interact 2020;20:372-81.
36. Lin Y, Zhong X, Lu D, Yao W, Zhou J, Wu R, Feng F. Association of visceral and subcutaneous fat with bone mineral density in US adults: a cross-sectional study. Sci Rep 2023;13:10682. [Crossref] [PubMed]
37. Lei WS, Kindler JM. Insulin resistance and skeletal health. Curr Opin Endocrinol Diabetes Obes 2022;29:343-9. [Crossref] [PubMed]
38. Lingling Y, Hong W. Relationship between insulin resistance and osteoporosis in elderly males with type 2 diabetes. Chinese Journal of Osteoporosis 2012;18:401-3,419.
39. Lind L, Ärnlöv J, Lampa E. The Interplay Between Fat Mass and Fat Distribution as Determinants of the Metabolic Syndrome Is Sex-Dependent. Metab Syndr Relat Disord 2017;15:337-43. [Crossref] [PubMed]
40. Katzmarzyk PT, Barreira TV, Harrington DM, Staiano AE, Heymsfield SB, Gimble JM. Relationship between abdominal fat and bone mineral density in white and African American adults. Bone 2012;50:576-9. [Crossref] [PubMed]
41. Zhang X, Zhao W, Chen Y, Zhao Y, Hu S, Yan J, Zhao J, Li S. Correlation between bone mineral density of lumbar vertebra and age, gender, physical parameters and abdomen fat. Chinese Journal of Medcial Imaging Technology 2015;31:762-5.