Effect of body mass index on bone mineral density is age-specific

Effectiveness of synthetic versus autologous bone grafts in foot and ankle surgery: a systematic review and meta-analysis

BACKGROUND

All orthopaedic procedures, comprising foot and ankle surgeries, seemed to show a positive trend, recently. Bone grafts are commonly employed to fix bone abnormalities resulting from trauma, disease, or other medical conditions. This study specifically focuses on reviewing the safety and efficacy of various bone substitutes used exclusively in foot and ankle surgeries, comparing them to autologous bone grafts.

METHODS

The systematic search involved scanning electronic databases including PubMed, Scopus, Cochrane online library, and Web of Science, employing terms like 'Bone substitute,' 'synthetic bone graft,' 'Autograft,' and 'Ankle joint.' Inclusion criteria encompassed RCTs, case-control studies, and prospective/retrospective cohorts exploring different bone substitutes in foot and ankle surgeries. Meta-analysis was performed using R software, integrating odds ratios and 95% confidence intervals (CI). Cochrane's Q test assessed heterogeneity.

RESULTS

This systematic review analyzed 8 articles involving a total of 894 patients. Out of these, 497 patients received synthetic bone grafts, while 397 patients received autologous bone grafts. Arthrodesis surgery was performed in five studies, and three studies used open reduction techniques. Among the synthetic bone grafts, three studies utilized a combination of recombinant human platelet-derived growth factor BB homodimer (rhPDGF-BB) and beta-tricalcium phosphate (β-TCP) collagen, while four studies used hydroxyapatite compounds. One study did not provide details in this regard. The meta-analysis revealed similar findings in the occurrence of complications, as well as in both radiological and clinical evaluations, when contrasting autografts with synthetic bone grafts.

CONCLUSION

Synthetic bone grafts show promise in achieving comparable outcomes in radiological, clinical, and quality-of-life aspects with fewer complications. However, additional research is necessary to identify the best scenarios for their use and to thoroughly confirm their effectiveness.

LEVELS OF EVIDENCE

Level II.

Lipid metabolism mediates the association between body mass index change and bone mineral density: The Taizhou imaging study

BACKGROUND

Limited research explores the impact of body mass index (BMI) change on osteoporosis, regarding the role of lipid metabolism. We aimed to cross-sectionally investigate these relationships in 820 Chinese participants aged 55-65 from the Taizhou Imaging Study.

METHODS

We used the baseline data collected between 2013 and 2018. T-score was calculated by standardizing bone mineral density and was used for osteoporosis and osteopenia diagnosis. Multinomial logistic regression was used to examine the effect of BMI change on bone health status. Multivariable linear regression was employed to identify the metabolites corrected with BMI change and T-score. Exploratory factor analysis (EFA) and mediation analysis were conducted to ascertain the involvement of the metabolites.

RESULTS

BMI increase served as a protective factor against osteoporosis (OR = 0.79[0.71-0.88], P-value<0.001) and osteopenia (OR = 0.88[0.82-0.95], P-value<0.001). Eighteen serum metabolites were associated with both BMI change and T-score. Specifically, high-density lipoprotein (HDL) substructures demonstrated negative correlations (β = -0.08 to -0.06 and - 0.12 to -0.08, respectively), while very low-density lipoprotein (VLDL) substructions showed positive correlations (β = 0.09 to 0.10 and 0.10 to 0.11, respectively). The two lipid factors (HDL and VLDL) extracted by EFA acted as mediators between BMI change and T-score (Prop. Mediated = 8.16% and 10.51%, all P-value<0.01).

CONCLUSION

BMI gain among Chinese aged 55-65 is beneficial for reducing the risk of osteoporosis. The metabolism of HDL and VLDL partially mediates the effect of BMI change on bone loss. Our research offers novel insights into the prevention of osteoporosis, approached from the perspective of weight management and lipid metabolomics.

Approximation of bone mineral density and subcutaneous adiposity using T1-weighted images of the human head

Bones and brain are intricately connected and scientific interest in their interaction is growing. This has become particularly evident in the framework of clinical applications for various medical conditions, such as obesity and osteoporosis. The adverse effects of obesity on brain health have long been recognised, but few brain imaging studies provide sophisticated body composition measures. Here we propose to extract the following bone- and adiposity-related measures from T1-weighted MR images of the head: an approximation of skull bone mineral density (BMD), skull bone thickness, and two approximations of subcutaneous fat (i.e., the intensity and thickness of soft non-brain head tissue). The measures pertaining to skull BMD, skull bone thickness, and intensi-ty-based adiposity proxy proved to be reliable ( r =.93/.83/.74, p <.001) and valid, with high correlations to DXA-de-rived head BMD values (rho=.70, p <.001) and MRI-derived abdominal subcutaneous adipose volume (rho=.62, p <.001). Thickness-based adiposity proxy had only a low retest reliability ( r =.58, p <.001).The outcomes of this study constitute an important step towards extracting relevant non-brain features from available brain scans.

Validation of Opportunistic Artificial Intelligence-Based Bone Mineral Density Measurements in Coronary Artery Calcium Scans

BACKGROUND

Previously we reported a manual method of measuring thoracic vertebral bone mineral density (BMD) using quantitative CT in noncontrast cardiac CT scans used for coronary artery calcium (CAC) scoring. In this report, we present validation studies of an artificial intelligence-based automated BMD measurement (AutoBMD) that recently received FDA approval as an opportunistic add-on to CAC scans.

METHODS

A deep learning model was trained to detect vertebral bodies. Subsequently, signal processing techniques were developed to detect intervertebral discs and the trabecular components of the vertebral body. The model was trained using 132 CAC scans comprising 7,649 slices. To validate AutoBMD, we used 5,785 cases of manual BMD measurements previously reported from CAC scans in the Multi-Ethnic Study of Atherosclerosis.

RESULTS

Mean ± SD for AutoBMD and manual BMD were 166.1 ± 47.9 mg/cc and 163.1 ± 46 mg/cc, respectively (P = .006). Multi-Ethnic Study of Atherosclerosis cases were 47.5% male and 52.5% female, with age 62.2 ± 10.3. A strong correlation was found between AutoBMD and manual measurements (R = 0.85, P < .0001). Accuracy, sensitivity, specificity, positive predictive value and negative predictive value for AutoBMD-based detection of osteoporosis were 99.6%, 96.7%, 97.7%, 99.7% and 99.8%, respectively. AutoBMD averaged 15 seconds per report versus 5.5 min for manual measurements (P < .0001).

CONCLUSIONS

AutoBMD is an FDA-approved, artificial intelligence-enabled opportunistic tool that reports BMD with Z-scores and T-scores and accurately detects osteoporosis and osteopenia in CAC scans, demonstrating results comparable to manual measurements. No extra cost of scanning and no extra radiation to patients, plus the high prevalence of asymptomatic osteoporosis, make AutoBMD a promising candidate to enhance patient care.

Analysis of the association between osteoporosis and muscle strength in Korean adults: a national cross-sectional study

BACKGROUND

This study aimed to examine the associations between osteoporosis and hand grip strength (HGS), a surrogate marker of muscular strength, among Korean adults stratified by body mass index (BMI), age, and renal function.

METHODS

This study was conducted using the data obtained from the Korea National Health and Nutrition Examination Survey 2015-2019, a cross-sectional and nationally representative survey performed by the Korea Centers for Diseases Control and Prevention.

RESULTS

Of the 26,855 subjects included in this study, those with low muscle strength (LMS) and normal muscle strength were showed in 4,135 (15.4%) and 22,720 (84.6%) subjects, respectively. The osteoporotic subjects had a higher prevalence rate for LMS than those without osteoporosis after adjusting for age [odds ratio (OR), 1.684; 95% confidence interval (CI), 1.500-1.890). The subjects with osteoporosis and BMI < 18.5 kg/m2 also had a higher prevalence rate for LMS after adjusting for age compared to those with non-osteoporosis and BMI < 18.5 kg/m2 (OR, 1.872; 95% CI, 1.043-3.359). Compared to the non-osteoporotic subjects with estimated glomerular filtration rate (eGFR) ≥ 60 mL/min/1.73 m2, those with osteoporosis and eGFR ≥ 60 mL/min/1.73 m2 had a higher prevalence rate for LMS after controlling for age and sex (OR, 1.630; 95% CI, 1.427-1.862).

CONCLUSIONS

The results showed that osteoporosis was likely to contribute to an increased prevalence rate of LMS in terms of HGS. Aging, BMI, and renal function also had significant effects on the association between osteoporosis and LMS. This association is likely to assist in developing better strategies to estimate bone health in clinical or public health practice.

BMI trajectory of rapid and excessive weight gain during adulthood is associated with bone loss: a cross-sectional study from NHANES 2005-2018

BACKGROUND

Studies have examined the effect of weight change on osteoporosis, but the results were controversial. Among them, few had looked at weight change over the life span. This study aimed to fill this gap and investigate the association between lifetime body mass index (BMI) trajectories and bone loss.

METHODS

In this cross-sectional study, participants at age 50 and above were selected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Dual-energy X-ray Absorptiometry was used to measure the bone mineral density at the femoral neck and lumbar spine. Standard BMI criteria were used, with < 25 kg/m2 for normal, 25-29.9 kg/m2 for overweight, and ≥ 30 kg/m2 for obesity. The latent class trajectory model (LCTM) was used to identify BMI trajectories. Multinomial logistic regression models were fitted to evaluate the association between different BMI trajectories and osteoporosis or osteopenia.

RESULTS

For the 9,706 eligible participants, we identified four BMI trajectories, including stable (n = 7,681, 70.14%), slight increase (n = 1253, 12.91%), increase to decrease (n = 195, 2.01%), and rapid increase (n = 577, 5.94%). Compared with individuals in the stable trajectory, individuals in the rapid increase trajectory had higher odds of osteoporosis (OR = 2.25, 95% CI 1.19-4.23) and osteopenia (OR = 1.49, 95% CI 1.02-2.17). This association was only found in the lumbar spine (OR = 2.11, 95% CI 1.06-4.2) but not in the femoral neck. In early-stage (age 25-10 years ago) weight change, staying an obesity and stable weight seemed to have protective effects on osteoporosis (OR = 0.26, 95% CI 0.08-0.77) and osteopenia (OR = 0.46, 95% CI 0.25-0.84). Meanwhile, keeping an early-stage stable and overweight was related to lower odds of osteopenia (OR = 0.53, 95% CI 0.34-0.83). No statistically significant association between recent (10 years ago to baseline) weight change and osteoporosis was found.

CONCLUSIONS

Rapid and excess weight gain during adulthood is associated with a higher risk of osteoporosis. But this association varies by skeletal sites. Maintaining stable overweight and obesity at an early stage may have potentially beneficial effects on bone health.

A Prediction Model for Osteoporosis Risk Using a Machine-Learning Approach and Its Validation in a Large Cohort

BACKGROUND

Osteoporosis develops in the elderly due to decreased bone mineral density (BMD), potentially increasing bone fracture risk. However, the BMD is not regularly measured in a clinical setting. This study aimed to develop a good prediction model for the osteoporosis risk using a machine learning (ML) approach in adults over 40 years in the Ansan/Anseong cohort and the association of predicted osteoporosis risk with a fracture in the Health Examinees (HEXA) cohort.

METHODS

The 109 demographic, anthropometric, biochemical, genetic, nutrient, and lifestyle variables of 8,842 participants were manually selected in an Ansan/Anseong cohort and included in the ML algorithm. The polygenic risk score (PRS) of osteoporosis was generated with a genome-wide association study and added for the genetic impact of osteoporosis. Osteoporosis was defined with < -2.5 T scores of the tibia or radius compared to people in their 20s-30s. They were divided randomly into the training (n = 7,074) and test (n = 1,768) sets-Pearson's correlation between the predicted osteoporosis risk and fracture in the HEXA cohort.

RESULTS

XGBoost, deep neural network, and random forest generated the prediction model with a high area under the curve (AUC, 0.86) of the receiver operating characteristic (ROC) with 10, 15, and 20 features; the prediction model by XGBoost had the highest AUC of ROC, high accuracy and k-fold values (> 0.85) in 15 features among seven ML approaches. The model included the genetic factor, genders, number of children and breastfed children, age, residence area, education, seasons to measure, height, smoking status, hormone replacement therapy, serum albumin, hip circumferences, vitamin B6 intake, and body weight. The prediction models for women alone were similar to those for both genders, with lower accuracy. When the prediction model was applied to the HEXA study, the correlation between the fracture incidence and predicted osteoporosis risk was significant but weak (r = 0.173, P < 0.001).

CONCLUSION

The prediction model for osteoporosis risk generated by XGBoost can be applied to estimate osteoporosis risk. The biomarkers can be considered for enhancing the prevention, detection, and early therapy of osteoporosis risk in Asians.

Opportunistic AI-enabled automated bone mineral density measurements in lung cancer screening and coronary calcium scoring CT scans are equivalent

Rationale and objectives

We previously reported a novel manual method for measuring bone mineral density (BMD) in coronary artery calcium (CAC) scans and validated our method against Dual X-Ray Absorptiometry (DEXA). Furthermore, we have developed and validated an artificial intelligence (AI) based automated BMD (AutoBMD) measurement as an opportunistic add-on to CAC scans that recently received FDA approval. In this report, we present evidence of equivalency between AutoBMD measurements in cardiac vs lung CT scans.

Materials and methods

AI models were trained using 132 cases with 7649 (3 mm) slices for CAC, and 37 cases with 21918 (0.5 mm) slices for lung scans. To validate AutoBMD against manual measurements, we used 6776 cases of BMD measured manually on CAC scans in the Multi-Ethnic Study of Atherosclerosis (MESA). We then used 165 additional cases from Harbor UCLA Lundquist Institute to compare AutoBMD in patients who underwent both cardiac and lung scans on the same day.

Results

Mean±SD for age was 69 ± 9.4 years with 52.4% male. AutoBMD in lung and cardiac scans, and manual BMD in cardiac scans were 153.7 ± 43.9, 155.1 ± 44.4, and 163.6 ± 45.3 g/cm3, respectively (p = 0.09). Bland-Altman agreement analysis between AutoBMD lung and cardiac scans resulted in 1.37 g/cm3 mean differences. Pearson correlation coefficient between lung and cardiac AutoBMD was R2 = 0.95 (p < 0.0001).

Conclusion

Opportunistic BMD measurement using AutoBMD in CAC and lung cancer screening scans is promising and yields similar results. No extra radiation plus the high prevalence of asymptomatic osteoporosis makes AutoBMD an ideal screening tool for osteopenia and osteoporosis in CT scans done for other reasons.

Reduced High-Density Lipoprotein Cholesterol Is an Independent Determinant of Altered Bone Quality in Women with Type 2 Diabetes

Type 2 diabetes mellitus (T2DM) is associated with an increased fracture risk. Our study aimed to explore differences in bone alterations between T2DM women and controls and to assess clinical predictors of bone impairment in T2DM. For this observational case control study, we recruited 126 T2DM female patients and 117 non-diabetic, age- and BMI-comparable women, who underwent clinical examination, routine biochemistry and dual-energy X-ray absorptiometry (DXA) scans for bone mineral density (BMD) and trabecular bone score (TBS) assessment-derived indexes. These were correlated to metabolic parameters, such as glycemic control and lipid profile, by bivariate analyses, and significant variables were entered in multivariate adjusted models to detect independent determinants of altered bone status in diabetes. The T2DM patients were less represented in the normal bone category compared with controls (5% vs. 12%; p = 0.04); T2DM was associated with low TBS (OR: 2.47, C.I. 95%: 1.19–5.16, p = 0.016) in a regression model adjusted for age, menopausal status and BMI. In women with T2DM, TBS directly correlated with plasma high-density lipoprotein cholesterol (HDL-c) (p = 0.029) and vitamin D (p = 0.017) levels. An inverse association was observed with menopausal status (p < 0.001), metabolic syndrome (p = 0.014), BMI (p = 0.005), and waist circumference (p < 0.001). In the multivariate regression analysis, lower HDL-c represented the main predictor of altered bone quality in T2DM, regardless of age, menopausal status, BMI, waist circumference, statin treatment, physical activity, and vitamin D (p = 0.029; R2 = 0.47), which likely underlies common pathways between metabolic disease and bone health in diabetes.

Relationship between diet-related inflammation and bone health under different levels of body mass index

BACKGROUND

Osteoporosis is a major public health problem. Dietary inflammatory preference and body mass index (BMI) are emerging factors that tends to affect bone health. There is limited evidence regarding the joint influence of BMI and dietary status on the bone health. This study aimed to investigate the relationship between dietary inflammatory index (DII) and bone health among adults under different levels of BMI utilizing the National Health and Nutrition Examination Survey (NHANES).

METHODS

Data were collected from 2005-2010, 2013-2014 to 2017-2018 in NHANES. In total, 10,521 participants who aged ≥ 20 years and had complete data for dietary intake interview, bone mineral density (BMD) and bone mineral content (BMC) were included. DII was performed to evaluate the dietary inflammatory potential based on dietary intake interview. We evaluated bone health by femoral neck BMD and BMC measured by dual energy X-ray absorptiometry. Weighted multivariable linear regression and BMI-stratified subgroup analysis were performed.

RESULTS

The average DII score for 10,521 participants was 1.24 ± 0.04, mean femoral neck BMD was 0.82 ± 0.00 g/cm² and mean BMC was 4.37 ± 0.01 g. In the fully adjusted model, there was a negative correlation between DII with BMD (β = - 0.016, P < 0.001) and BMC (β = - 0.011, P < 0.001) in the most anti-inflammatory diet. Using BMI-stratified subgroup analysis, this correlation became more evident in both the overweight (BMD: β = - 0.024, P < 0.001; BMC: β = - 0.058, P = 0.042) and obese groups (BMD: β = - 0.015, P = 0.049; BMC: β = - 0.009, P = 0.042), while this correlation was opposite in DII tertile 2 (middle DII score) in the underweight group (BMD: β = 0.047, P = 0.038; BMC: β = 0.274, P = 0.010).

CONCLUSION

Relationship between higher consumption of pro-inflammatory and increased risk of lower BMD and BMC was only existed in overweight and obese participants.

Correlation of hemoglobin with osteoporosis in elderly Chinese population: A cross-sectional study

Introduction

In the elder population, both low hemoglobin (Hb)/anemia and osteoporosis (OP) are highly prevalent. However, the relationship between Hb and OP is still poorly understood. This study was to evaluate the correlation between Hb and OP in Chinese elderly population.

Methods

One thousand and sisty-eight individuals aged 55-85 years were enrolled into this cross-sectional study during June 2019-November 2019. Data on the demographics and clinical characteristics were recorded. Detections of complete blood count, liver/kidney function, glucose metabolism and lipid profile, and thoracolumbar X-ray were performed, and bone mineral density (BMD) at lumbar spine 1-4, femur neck, and total hip was measured by dual-energy X-ray absorptiometry (DXA). Univariate and multivariate linear regression analyses were employed to evaluate the correlation between Hb with BMD T-score. Logistic regression analysis was performed to access the correlation between different Hb levels and the odds ratio (OR) for OP.

Results

Compared with non-OP group, OP patients had lower level of Hb. Univariate linear regression analysis indicated Hb level was positively related to the BMD of lumbar spine 1-4, femur neck and total hip, and this relationship remained after adjusting confounding variables [gender, age, body mass index (BMI), diabetes mellitus (DM) and morphological vertebral fracture]. Logistic regression analysis showed the ORs for OP decreased with the increase of Hb. Compared with the subjects with the lowest quartile of Hb, the OR for OP in the highest quartile group was 0.60 (0.41-0.89) after adjusting for gender, age and BMI, and the OR for OP was 0.62 (0.41-0.92) after further adjustment for gender, age, BMI, DM, and lipid indexes.

Discussion

In conclusion, Lower Hb level is related to lower BMD in the elderly population. However, whether Hb level could be used to predict the risk of OP needs to be further determined in more longitudinal clinical studies.

Genomics and phenomics of body mass index reveals a complex disease network

Elevated body mass index (BMI) is heritable and associated with many health conditions that impact morbidity and mortality. The study of the genetic association of BMI across a broad range of common disease conditions offers the opportunity to extend current knowledge regarding the breadth and depth of adiposity-related diseases. We identify 906 (364 novel) and 41 (6 novel) genome-wide significant loci for BMI among participants of European (N~1.1 million) and African (N~100,000) ancestry, respectively. Using a BMI genetic risk score including 2446 variants, 316 diagnoses are associated in the Million Veteran Program, with 96.5% showing increased risk. A co-morbidity network analysis reveals seven disease communities containing multiple interconnected diseases associated with BMI as well as extensive connections across communities. Mendelian randomization analysis confirms numerous phenotypes across a breadth of organ systems, including conditions of the circulatory (heart failure, ischemic heart disease, atrial fibrillation), genitourinary (chronic renal failure), respiratory (respiratory failure, asthma), musculoskeletal and dermatologic systems that are deeply interconnected within and across the disease communities. This work shows that the complex genetic architecture of BMI associates with a broad range of major health conditions, supporting the need for comprehensive approaches to prevent and treat obesity.

Association between caffeine intake and lumbar spine bone mineral density in adults aged 20-49: A cross-sectional study

Background

Many epidemiological studies have investigated the connection between coffee intake and bone mineral density (BMD), but the results are controversial. This study aimed to assess the association between caffeine consumption and lumbar BMD in adults aged 20-49.

Methods

From a cross-sectional study based on a large sample of the National Health and Nutrition Examination Survey 2011-2018. After controlling for confounders, the weighted multivariate linear regression model was created and stratified by age, gender, and race for subgroup analysis. In addition, we simultaneously stratified analysis by age and sex and divided caffeine intake into quartiles to assess the association between coffee intake and BMD.

Results

Caffeine intake was not significantly linked with lumbar BMD in this study of 7041 adults. In subgroup studies stratified by age, there was a significant correlation between lumbar BMD and caffeine consumption in participants aged 30-39 and 40-49. In females, there was a positive correlation between lumbar BMD and coffee consumption stratified by gender. When evaluated by race, the association between lumbar BMD and caffeine intake was independent of race. Consequently, when stratifying for age, sex, and coffee intake quartiles, a significant positive correlation was discovered between the fourth coffee intake quartile and lumbar BMD in females aged 30-39. In addition, a negative correlation was discovered between coffee consumption and lumbar BMD in males aged 40-49.

Conclusions

Our research indicates that drinking coffee may benefit 30-39 women's lumbar BMD, but it may adversely affect men aged 40-49.

Suboptimal Plasma Vitamin C Is Associated with Lower Bone Mineral Density in Young and Early Middle-Aged Men: A Retrospective Cross-Sectional Study

Background: This study was conducted to evaluate associations between bone mineral density (BMD) and four selected circulating nutrients, particularly vitamin C, among adults aged 20−49 years. Methods: In this retrospective cross-sectional study, the lumbar spine BMD of 866 men and 589 women were measured by dual-energy X-ray absorptiometry and divided into tertiles, respectively. Logistic regressions were used to identify the predictors of low BMD by comparing subjects with the highest BMD to those with the lowest. Results: Multivariate logistic regressions identified suboptimal plasma vitamin C (adjusted odds ratio (AOR) 1.64, 95% confidence interval (CI) 1.16, 2.31), suboptimal serum vitamin B12 (AOR 2.05, 95% CI 1.02, 4.12), and low BMI (BMI < 23) (AOR 1.68, 95% CI 1.12, 2.53) as independent predictors for low BMD in men. In women, low BMI was the only independent predictor for low BMD. Plasma vitamin C, categorized as suboptimal (≤8.8 mg/L) and sufficient (>8.8 mg/L), was positively significantly correlated with the lumbar spine BMD in men, but there was no association in women. Conclusions: Plasma vitamin C, categorized as suboptimal and sufficient, was positively associated with the lumbar spine BMD in young and early middle-aged men. A well-designed cohort study is needed to confirm the findings.

A genetic correlation scan identifies blood proteins associated with bone mineral density

Background

Osteoporosis is a common metabolic bone disease that is characterized by low bone mass. However, limited efforts have been made to explore the functional relevance of the blood proteome to bone mineral density across different life stages.

Methods

Using genome-wide association study summary data of the blood proteome and two independent studies of bone mineral density, we conducted a genetic correlation scan of bone mineral density and the blood proteome. Linkage disequilibrium score regression analysis was conducted to assess genetic correlations between each of the 3283 plasma proteins and bone mineral density.

Results

Linkage disequilibrium score regression identified 18 plasma proteins showing genetic correlation signals with bone mineral density in the TB-BMD cohort, such as MYOM2 (coefficient = 0.3755, P value = 0.0328) among subjects aged 0 ~ 15, POSTN (coefficient = − 0.5694, P value = 0.0192) among subjects aged 30 ~ 45 and PARK7 (coefficient = − 0.3613, P value = 0.0052) among subjects aged over 60.

Conclusions

Our results identified multiple plasma proteins associated with bone mineral density and provided novel clues for revealing the functional relevance of plasma proteins to bone mineral density.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05453-z.

Association between obesity and bone mineral density in middle-aged adults

BACKGROUND

The relationship between obesity and bone mineral density (BMD) varies in different studies. Our aim in this study was to explore the association between obesity (body mass index ≥ 30) and BMD among adults 40-59 years of age.

METHODS

This study was conducted on a sample of 2218 participants (986 men and 1232 women) aged 40 to 59 years from the National Health and Nutrition Examination Survey 2011-2018. The independent variable was body mass index (BMI). The outcome variable was lumbar BMD. The associations of BMI with lumbar BMD were examined using multivariable linear regression models.

RESULTS

BMI was positively associated with lumbar BMD after adjusting for other covariates [β 0.006; 95% confidence interval (CI) 0.003-0.008]. An inverted U-shaped association between BMI and lumbar BMD was further identified, with the point of infection at approximately 50 kg/m². In the subgroup analyses, the relationship between BMI and lumbar BMD in women and blacks was an inverted U-shape.

CONCLUSION

Based on the results, it may be beneficial to appropriately increase BMI to promote BMD. However, considering the inverted U-shaped association, excessive BMI may be harmful to bone health in women and blacks.

Effect of obesity status on adolescent bone mineral density and saturation effect: A cross-sectional study

BACKGROUND

The effect of obesity status on bone mineral density (BMD) in adolescents and whether there is a saturation effect is still insufficient. A cross-sectional study of adolescents aged 12-19 was conducted to investigate them.

METHODS

Weighted multivariate linear regression models were used to assess the relationship between obesity status and BMD via datasets from the National Health and Nutrition Examination Survey 2011-2018. The nonlinear relationships and saturation values were ascertained by fitting smooth curves and analyzing saturation effects. At the same time, the subgroup stratified analysis was also performed.

RESULTS

4056 adolescents were included in this study. We found that body mass index (BMI) and waist circumference (WC) were significantly associated with total BMD, which remained significant in subgroups stratified by age, gender, standing height, and ethnicity. We also noticed an inverse correlation between left leg fat/lean mass and left leg BMD, which was only significant in males and other races. Fitting smooth curve and saturation effect analysis showed that BMI, WC, left leg fat/lean mass, and BMD had a specific saturation effect. There was a saturation effect on bone mineral density in adolescents with a BMI of 22 kg/m², a WC of 70.5 cm, or a left leg fat/lean mass of 0.2994.

CONCLUSIONS

We found a positive saturation effect of BMI and WC with BMD and a negative saturation effect of left leg fat/lean mass with BMD. Appropriate obesity status allows adolescents to have better bone mass development but not excessive obesity.