Adiposity reduces the risk of osteoporosis in Chinese rural population: the Henan rural cohort study

Association between the cardiometabolic index and osteoporosis: a cross-sectional study of the NHANES

Background

The cardiometabolic index (CMI) is a novel metabolic biomarker, but research on its association with osteporosis (OP) is limited. The objective of this research was to clarify the relationship between CMI and OP in the older adult population of the United States.

Methods

This study conducted a cross-sectional analysis using NHANES data 2007-2018 with exclusion of 2011-2012 and 2015-2016 cycles. Logistic regression was used to investigate the relationship between CMI and OP prevalence. Restricted cubic spline curve (RCS) and threshold saturation analyses were performed to explore the nonlinear association between CMI and OP prevalence. Subgroup analyses, sensitivity analyses, and additional analyses were conducted to ensure the robustness and reliability of the findings.

Results

The study included 4,191 participants, revealing that those with OP had significantly lower CMI levels. Logistic regression revealed a strong inverse correlation between Log CMI and OP (OR = 0.72, 95% CI = 0.59-0.88), which persisted after adjusting for covariates. RCS analysis revealed a nonlinear inverse relationship with the critical threshold at CMI = 0.93. Below this threshold, each unit increase in CMI was associated with a 37% reduction in OP prevalence, but changes above this threshold were not significant. Subgroup and sensitivity analyses confirmed the robustness of the findings.

Conclusion

Elevated CMI exhibited a robust inverse correlation with the prevalence of OP in the older adult U.S. population. Maintaining a moderate CMI significantly diminishes the risk of developing OP.

Association Between Osteoporosis and Adiposity Index Reveals Nonlinearity Among Postmenopausal Women and Linearity Among Men Aged over 50 Years

PURPOSE

Previous research shows conflicting views on the relationship between obesity and osteoporosis, partly due to variations in obesity classification and the nonlinear nature of these relationships. This study investigated the association between adiposity indices and osteoporosis, diagnosed using dual-energy X-ray absorptiometry (DXA), employing nonlinear models and offering optimal thresholds to prevent further bone mineral density decline.

METHODS

In 2019, a prospective study enrolled males over 50 years and postmenopausal women. Anthropometric measurements, blood biochemistry, and osteoporosis measured by DXA were collected. Associations between adiposity indices and osteoporosis were analyzed using a generalized additive model and segmented regression model.

RESULTS

The study included 872 women and 1321 men. Indices such as abdominal volume index (AVI), visceral adiposity index (VAI), waist circumference (WC), hip circumference, body mass index (BMI), waist-to-hip ratio, and waist-to-height ratio (WHtR) were inversely associated with osteoporosis. In women, the relationship between the risk of osteoporosis and the adiposity indices was U-shaped, with thresholds of WC = 94 cm, AVI = 17.67 cm2, BMI = 25.74 kg/m2, VAI = 4.29, and WHtR = 0.61, considering changes in bone mineral density. Conversely, men exhibited a linear patterns for the inverse association.

CONCLUSION

The impact of obesity and adiposity on osteoporosis varies significantly between women and men. In postmenopausal women, the relationship is nonlinear (U-shaped), with both very low and very high adiposity linked to higher osteoporosis risk. In men over 50, the relationship is linear, with higher adiposity associated with lower osteoporosis risk. The study suggests that maintaining specific levels of adiposity could help prevent osteoporosis in postmenopausal women.

Association of nocturnal sleep duration and sleep midpoint with osteoporosis risk in rural adults: a large-scale cross-sectional study

BACKGROUND

Evidence has suggested the linkage between sleep habits and several metabolic diseases, but the association of sleep factors with bone health remains unclear, especially in regions with low economic levels. Thus, this study aimed to investigate the relationship of nocturnal sleep duration and sleep midpoint with the osteoporosis risk in a rural population.

METHOD

Eligible subjects were derived from the Henan Rural Cohort Study. The Pittsburgh Sleep Quality Index was applied to collect sleep information including sleep initiating time and wake-up time. The bone mineral density of the calcaneus was measured by the ultrasonic bone density apparatus. Multivariable logistic regression models and restricted cubic splines were utilized to evaluate the odds ratio (OR) and 95% confidence intervals (95% CI).

RESULTS

For 8033 participants, 1636 subjects suffered from osteoporosis. Compared with the reference group (7 ~ h group), the ORs and 95% CI of osteoporosis associated with duration of nocturnal sleep were 1.32 (1.10, 1.56), 1.59 (1.25, 2.01), and 1.82 (1.25, 2.65) in the 8 ~ h, 9 ~ h, and ≥ 10 h group, respectively. Additionally, the adjusted ORs and 95% CI were 1.20 (1.01, 1.44) in the early sleep midpoint group and 1.09 (0.92, 1.29) in the intermediate sleep midpoint, compared with the late. Furthermore, there was a joint effect of long duration of nocturnal sleep and the early sleep midpoint on osteoporosis.

CONCLUSION

Long duration of nocturnal sleep and early sleep midpoint were independently and jointly associated with higher risk of osteoporosis in rural areas.

TRIAL REGISTRATION

The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

The effect of overweight or obesity on osteoporosis: A systematic review and meta-analysis

BACKGROUND

Osteoporosis and obesity are closely related, and the relationships between different types of obesity and osteoporosis are inconsistent.

OBJECTIVE

Our objective was to summarize earlier data concerning the association between osteoporosis and obesity (general and central), and to compare the impacts of these two obesity indicators on osteoporosis.

METHODS

From inception to May 2021, a comprehensive search in electronic bibliographic databases was conducted, and the search was updated in December 2021, July 2022 and June 2023. The data were independently extracted and evaluated by two investigators from epidemiological studies that reported the impact of obesity on the odds of incident osteoporosis.

RESULTS

There were 24 studies included in the final analysis when it came to general obesity measured by body mass index (BMI). Individuals with overweight and obesity had decreased odds of osteoporosis (odds ratio (OR), 0.451, 95% confidence intervals (CIs): 0.366-0.557). Sensitivity analyses showed that both overweight and obesity were decreased odds of osteoporosis, with reductions of 48.6% and 70.1%, respectively (OR, 0.514, 95% CI: 0.407-0.649; OR, 0.299, 95% CI: 0.207-0.433). Conversely, individuals classified as underweight were found to have higher odds of osteoporosis (OR, 2.540, 95% CI: 1.483-4.350). In term of central obesity, the final analysis consisted of 7 studies. No significant association was observed between central obesity and osteoporosis (OR, 0.913, 95% CI: 0.761-1.096).

CONCLUSIONS

General overweight and obesity were associated with lower odds of developing osteoporosis, whereas underweight was associated with higher odds. However, central obesity did not show a significant association with osteoporosis. These findings underscore the importance of considering the impact of obesity on osteoporosis. Further research is necessary to reinforce the evidence and validate our findings.

Relationships among body weight, lipids and bone mass in elderly individuals with fractures: A case-control study

BACKGROUND

The prevalence of osteoporosis and low bone mass is steadily rising each year. Low body weight is commonly linked to diminished bone mass and serves as a robust predictor of osteoporosis. Nonetheless, the connection between body mass index (BMI), bone mineral density, and lipid profiles among the elderly remains elusive.

AIM

To examine the association between BMI and bone mass, explore the correlation between lipid profiles and bone mass, and delve into the interplay between lipid metabolism and bone health.

METHODS

The study included 520 patients aged ≥ 65 years (178 men and 342 women). Age, sex, weight, and height were recorded. Femoral neck bone mineral density and T scores were determined using a dual-energy X-ray absorptiometry scanner. Blood calcium (Ca), phosphorus (P), albumin (ALB), alkaline phosphatase (ALP), aspartate aminotransferase, alanine aminotransferase, triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL) and low-density lipoprotein (LDL) levels were measured. Patients were classified by sex (male and female), age (65-79 years and ≥ 80 years), and T score (normal bone mineral density, osteopenia and osteoporosis).

RESULTS

Age, sex, BMI, and ALP and TG levels were independent risk factors for osteoporosis. For the 65-79- and ≥ 80-year-old groups, females presented lower T scores than males. Ca, P, ALB, ALP, TC, HDL and LDL levels were significantly different between men and women in the 65-79-year-old group. In addition, BMI and TG levels were significantly decreased in osteoporotic patients compared with patients with normal bone mass. TC levels declined in 65- to 79-year-old male and female osteoporosis patients. In the group of women aged ≥ 80 years, osteoporotic patients showed significantly increased ALP levels. Furthermore, we found positive correlations between BMI and TG levels in the male and female patient groups. However, we found no significant differences in ALB, Ca, P, HDL and LDL levels in osteoporotic patients compared to patients with normal bone mass.

CONCLUSION

Osteoporotic patients showed significantly decreased BMI and TG levels compared with those with normal bone mass. BMI showed positive correlations with TG levels in male and female patients. These results indicate correlations between BMI and bone mass and between lipid profiles and bone mass.

Based on CT at the third lumbar spine level, the skeletal muscle index and psoas muscle index can predict osteoporosis

Background

With the increasing number of studies on osteoporosis and muscle adipose tissue, existing studies have shown that skeletal muscle tissue and adipose tissue are closely related to osteoporosis by dual-energy x-ray absorptiometry (DXA) measurement. However, few studies have explored whether the skeletal muscle and adipose tissue index measured at the lumbar spine 3 (L3) level are closely related to bone mineral density (BMD) and can even predict osteoporosis. Therefore, this study aimed to prove whether skeletal muscle and adipose tissue index measured by computed tomography (CT) images based on a single layer are closely related to BMD.

Methods

A total of 180 participants were enrolled in this study to obtain skeletal muscle index (SMI), psoas muscle index (PMI), subcutaneous fat index (SFI), visceral fat index (VFI), and the visceral-to-subcutaneous ratio of the fat area (VSR) at L3 levels and divide them into osteoporotic and normal groups based on the T-score of DXA. Spearman rank correlation was used to analyze the correlation between SMI, PMI, SFI, VFI, VSR, and BMD. Similarly, spearman rank correlation was also used to analyze the correlation between SMI, PMI, SFI, VFI, VSR, and the fracture risk assessment tool (FRAX). Receiver operating characteristic (ROC) was used to analyze the efficacy of SMI, PMI, SFI, VFI, and VSR in predicting osteoporosis.

Results

BMD of L1-4 was closely correlated with SMI, PMI, VFI and VSR (r = 0.199 p = 0.008, r = 0.422 p < 0.001, r = 0.253 p = 0.001, r = 0.310 p < 0.001). BMD of the femoral neck was only correlated with PMI and SFI (r = 0.268 p < 0.001, r = − 0.164 p-0.028). FRAX (major osteoporotic fracture) was only closely related to PMI (r = − 0.397 p < 0.001). FRAX (hip fracture) was closely related to SMI and PMI (r = − 0.183 p = 0.014, r = − 0.353 p < 0.001). Besides, FRAX (major osteoporotic fracture and hip fracture) did not correlate with VFI, SFI, and VSR. SMI and PMI were statistically significant, with the area under the curve (AUC) of 0.400 (95% confidence interval 0.312-0.488 p = 0.024) and 0.327 (95% confidence interval 0.244-0.410 p < 0.001), respectively. VFI, SFI, and VSR were not statistically significant in predicting osteoporosis.

Conclusions

This study demonstrated that L3-based muscle index could assist clinicians in the diagnosis of osteoporosis to a certain extent, and PMI is superior to SMI in the diagnosis of osteoporosis. In addition, VFI, SFI, and VSR do not help clinicians to diagnose osteoporosis well.

Body Surface Area (BSA) is a Better Osteoporosis Associated Anthropometric Parameter Than Other Anthropometric Parameters in Elderly Population

Body surface area (BSA) is widely used for adjusting drug dose, while few studies have yet systematically evaluated its association with osteoporosis and compared its advantage with other anthropometric parameters in osteoporotic risk prediction. A total of 10,021 Chinese individuals aged over 65 years were enrolled in our study. Bone mineral density (BMD) was measured, and demographic information was also collected. Pearson correlation analysis, receiver operating characteristic (ROC) curves and predictive analysis were performed to assess the clinical practice of BSA for osteoporosis. BSA had the strongest correlation with BMD (0.544, p &lt; 0.001) compared with conventional anthropometric indices. Besides, BSA had the highest power in osteoporosis prediction, with an area under the curve (AUC) reaching 0.81. After incorporating BSA into the osteoporosis risk prediction model, the AUC improved from 0.82 to 0.83 (p &lt; 0.01). We found BSA provided additional diagnostic value beyond conventional anthropometric information with continuous and category NRIs were 30.40% (p &lt; 0.01) and 3.29% (p &lt; 0.01), respectively, and the IDI was 1.85% (p &lt; 0.01). BSA was positively associated with osteoporosis and showed superior discriminative ability for osteoporosis risk prediction compared with other anthropometric parameters in the Chinese elderly population.

Sex-different changes of body composition in aging: a systemic review

OBJECTIVE

Aging causes changes in body composition, in which differences in the distribution and amount of fat and muscle tissue affect the development of various diseases according to sex. We conducted a systemic review of the literature and examined the relationship between body composition differences and related health conditions or diseases in older men and women.

METHODS

Three different electronic databases (MEDLINE, Web of Science, and Embase) were used to find articles from 2000 until March 2022. Information on the study design characteristics, setting, measure of body composition, and health outcomes was extracted.

RESULTS

A total of 217 articles were retrieved, and 28 studies met the inclusion criteria. The included studies showed that older men have larger skeletal muscle mass (sMM) than women, while older women have larger fat mass (FM) than men. sMM has a favorable effect on physical performance, bone density, metabolism, cognitive function, and mortality in both men and women; however, the effects of sMM in women are less significant and even negligible compared to those in men. FM is significantly unfavorable for physical performance in women but sometimes favorable or unfavorable for glucose level and cognitive and lung function according to location. FM in men is usually less important for function, bone density, glucose level, and cognitive function than in women.

CONCLUSION

Changes in muscle and fat distribution according to aging and their correlation with health outcomes differ according to sex. Muscle mass may not always be favorable, and fat mass may not always be unfavorable in older adults.

The relationship between central obesity and bone mineral density: a Mendelian randomization study

BACKGROUND

The relationship between obesity and osteoporosis is an important public health issue. The goal of this study was to investigate whether and to what extent central obesity traits affect bone mineral density (BMD).

METHODS

We conducted a two-sample Mendelian randomization analysis. Genomewide significant single nucleotide polymorphisms associated with waist circumference, hip circumference, waist-to-hip ratio, waist circumference adjusted by body mass index (WCadjBMI), hip circumference adjusted by BMI (HCadjBMI) and waist-to-hip ratio adjusted by BMI (WHRadjBMI) were obtained from a large-scale database containing 224,459 samples. The BMD summary dataset was obtained from a UK Biobank database including 265,627 participants.

RESULTS

The results provided strong evidence that the HCadjBMI trait was causally and negatively associated with BMD (β: - 0.135, 95% CI - 0.216 to - 0.054; P = 0.001), while the WHR trait was causally and positively associated with BMD (β: 0.194, 95% CI 0.062 to 0.325, P = 0.004). No significant effects were observed for other traits on BMD.

CONCLUSIONS

This study indicates variations in the abilities of different central obesity traits to influence BMD. These results should be considered in further studies and public health measures on obesity and osteoporosis prevention strategies.

Metabolic syndrome is not associated to an increased risk of low bone mineral density in men at risk for osteoporosis

PURPOSE

We have recently demonstrated a significant association between osteoporosis (Op) and metabolic syndrome (MetS) in Caucasian women examined by Dual-energy X-ray absorptiometry (DXA) for suspected Op. This cross-sectional study was performed to evaluate the association between MetS and Op in Caucasian men enrolled in the same geographical area, with identical criteria and in the same time range.

METHODS

Among subjects enrolled in the SIMON study, we selected the medical records of all free-living men who performed a contextual evaluation of both bone mineral density (BMD) by DXA and MetS constitutive elements (arterial blood pressure, waist circumference, serum levels of triglycerides, high-density lipoprotein cholesterol, and fasting glucose). All enrolled subjects refer to "COMEGEN" general practitioners' cooperative operating in Naples, Southern Italy.

RESULTS

Overall, the medical records of 880 men were examined. No significant association between MetS and Op was observed. Among MetS constitutive elements, waist circumference was inversely related to Op risk.

CONCLUSION

In Caucasian men examined by DXA for suspected Op, no significant association was observed between Op and MetS. The study results contrast to those observed in women enrolled in the same geographical area, with identical criteria and in the same time range and may be related to sexual dimorphism occurring in clinical expressiveness of both MetS and Op.

Lower Central Fat Increase Risk of One-Year Muscle Mass Loss in Menopausal Women

Background

Hormonal changes had been found in menopausal women. Muscle and bone mass decline after menopause and with aging, increasing the risk for sarcopenia and osteoporosis in later life. Only a few studies suggest that menopausal hormonal changes have an effect on the decline in muscle mass.

Objectives

This study aimed at evaluating the risk of muscle mass loss in menopausal women.

Materials and Methods

Menopausal women from routine physical health examination were eligible for this study. Muscle mass was determined using dual-energy X-ray absorptiometry at baseline and 1 year later. All of the patients underwent the assessments for liver and kidney function, diabetes, and hypertension, and associated comorbidities were recorded.

Results

A total of 172 patients were enrolled. 70 patients had muscle loss at 1 year, and the other 102 did not had loss. The mean age was 70.26 ± 9.93 years at the muscle loss group, while 69.25 ± 10.50 at the nonprogress group (p = 0.531). The mean body mass index was 22.96 ± 1.91 kg/m² at the muscle loss group, while 23.33 ± 3.71 kg/m² at the nonprogress group (p = 0.433). The baseline trunk limb fat mass ratio was 1.01 ± 0.20 in the muscle loss group and 1.12 ± 0.26 in the no muscle loss (p = 0.004). Using muscle mass loss as the outcome, logistical regression analysis showed that a baseline trunk limb mass ratio could predict muscle loss, and a higher baseline trunk limb mass ratio was associated with less muscle loss, while a lower trunk limb mass ratio was associated with increased muscle mass loss (p = 0.01).

Conclusion

This is the first study to investigate the risk of muscle mass loss in menopausal women. Menopausal women with higher central fat had less muscle mass loss, while lower central fat was a risk factor for muscle mass loss. Chronic kidney disease was also a risk factor for muscle mass loss in menopausal women in this study.