Sex- and Age-Specific Prevalence of Osteopenia and Osteoporosis: Sampling Survey.

BACKGROUND: Osteopenia and osteoporosis are posing a long-term influence on the aging population's health contributing to a higher risk of mortality, loss of autonomy, hospitalization, and huge health system costs and social burden. Therefore, more pertinent data are needed to demonstrate the current state of osteoporosis. OBJECTIVE: This sampling survey seeks to assess the trends in the prevalence of osteopenia and osteoporosis in a Chinese Han population. METHODS: A community-based cross-sectional study involving 16,377 participants used a multistage sampling method. Bone mineral density was measured using the quantitative ultrasonic densitometry. Student t test and Mann-Whitney U test were used to test the difference between normally and nonnormally distributed quantitative variables between male and female participants. A chi-square (χ2) test was used to compare categorized variables. Stratified analysis was conducted to describe the prevalence rates of osteoporosis (T score ≤-2.5) and osteopenia (T score -2.5 to -1.0) across age, sex, calcium intake, and menopause. A direct standardization method was used to calculate the age-standardized prevalence rates of osteoporosis and osteopenia. T-score was further categorized into quartiles (T1-T4) by age- and sex-specified groups. RESULTS: The prevalence rates of osteopenia and osteoporosis were 40.5% (6633/16,377) and 7.93% (1299/16,377), respectively, and the age-standardized prevalence rates were 27.32% (287,877,129.4/1,053,861,940) and 3.51% (36,974,582.3/1,053,861,940), respectively. There was an increase in osteopenia and osteoporosis prevalence from 21.47% (120/559) to 56.23% (754/1341) and 0.89% (5/559) to 17.23% (231/1341), respectively, as age increased from 18 years to 75 years old. The prevalence rates of osteopenia and osteoporosis were significantly higher in female participants (4238/9645, 43.94% and 1130/9645, 11.72%) than in male participants (2395/6732, 35.58% and 169/6732, 2.51%; P<.001), and in postmenopausal female participants (3638/7493, 48.55% and 1053/7493, 14.05%) than in premenopausal female participants (538/2026, 26.55% and 53/2026, 2.62%; P<.001). In addition, female participants with a history of calcium intake had a lower osteoporosis prevalence rate than female participants without any history of calcium intake in all age groups (P=.004). From low quartile to high quartile of T-score, the prevalence of diabetes mellitus (752/4037, 18.63%; 779/4029, 19.33%; 769/3894, 19.75%; and 869/3879, 22.4%) and dyslipidemia (2228/4036, 55.2%; 2304/4027, 57.21%; 2306/3891, 59.26%; and 2379/3878, 61.35%) were linearly increased (P<.001), while the prevalence of cancer (112/4037, 2.77%; 110/4029, 2.73%; 103/3894, 2.65%; and 77/3879, 1.99%) was decreased (P=.03). CONCLUSIONS: Our data imply that as people age, osteopenia and osteoporosis are more common in females than in males, particularly in postmenopausal females than in premenopausal females, and bone mineral density significantly affects the prevalence of chronic diseases. These findings offer information that can be applied to intervention programs meant to prevent or lessen the burden of osteoporosis in China.

Pregnancy and lactation-associated osteoporosis as a major type of premenopausal osteoporosis: a retrospective cohort study based on real-world data.

BACKGROUND: Pregnancy and lactation-associated osteoporosis (PLO), as well as premenopausal osteoporosis, might be a predictor of future fracture. This study aimed to describe the clinical features of PLO as a subtype of premenopausal osteoporosis and to evaluate medical interventions for it. METHODS: From an administrative claims database including 4,224,246 people in Japan, we classified women for whom the date of childbirth had been defined and who had suffered low-trauma fracture between the ages of 18-47 years as the premenopausal osteoporosis group. A fracture site for which the odds ratio for fractures occurring between 5 months before and 12 months after childbirth (around childbirth) was greater than 1 was considered the PLO site. We classified patients with a fracture at the PLO site around childbirth as the PLO group. The control group consisted of 500 women without fragility fractures. We investigated some drugs and diseases to explore fracture-causing factors, as well as medical interventions such as osteoporosis diagnosis, bone densitometry, anti-osteoporosis pharmacotherapy, and lactation inhibitors. RESULTS: In total, 231 parous women were classified into the premenopausal osteoporosis group. The most common fracture was vertebral fracture and was likely to occur around childbirth, followed by distal radius and sacral fractures, which were rare around childbirth. Considering vertebral, pelvic, and proximal femoral fractures as PLO sites, 56 women with 57 PLO fractures were classified into the PLO group. The incidence of PLO was estimated at 460 per million deliveries. Ovulation disorder and high maternal age were associated with the development of PLO. Vertebral fracture was the most common PLO fracture. It was mainly diagnosed a few months, and possibly up to 1 year, postpartum. PLO patients with vertebral fractures underwent more medical interventions than did those with other fractures, but they were still inadequate. CONCLUSIONS: PLO with vertebral fracture was one of the major types of premenopausal osteoporosis. The prevalence of PLO is considered to be higher than previously thought, indicating the presence of potentially overlooked patients. More timely interventions for PLO might lead to the improved management of latent patients with premenopausal osteoporosis and reduce future fracture risk.

Bone evaluation study-2: update on the epidemiology of osteoporosis in Germany.

Osteoporosis is the most common bone disorder. Our data gives an estimate of around 5.87 million cases of osteoporosis in the general German population in 2018. Only 30% of insured individuals who suffered an osteoporotic fracture and/or had a confirmed diagnosis of osteoporosis, received an appropriate prescription. PURPOSE: Osteoporosis is the most common bone disorder. It particularly affects elderly people and increases the risk of atraumatic fractures. The aim of this study was to estimate the prevalence of osteoporosis in the general German population aged ≥ 50 years and to collect data on the frequency of prescription of osteoporosis-specific medication in order to assess the treatment gap. METHODS: Retrospective analysis of anonymized data of individuals aged ≥ 50 years insured under statutory healthcare schemes from the database of the Institute for Applied Health Research Berlin (InGef) for 2018 (study population). Insured individuals with osteoporosis were identified based on osteoporosis diagnoses, osteoporosis-specific prescriptions, or osteoporotic fractures. Thus, we estimated the prevalence of osteoporosis in the general German population aged ≥ 50 years. The prevalence of diagnoses, fractures, and prescriptions was determined for the study population and stratified by age and gender. RESULTS: Within the study population of 1,599,299 insured individuals, a prevalence of osteoporosis of 15.9% was determined. This estimated approximately 5.87 million cases of osteoporosis for the general German population. 81.6% of the cases were women. Osteoporosis-specific prescriptions were received by 30.0% of the insured individuals in the study population who had been diagnosed with osteoporosis and/or suffered an osteoporotic fracture. CONCLUSIONS: Germany has a high prevalence of osteoporosis. Only a small portion of individuals who may require osteoporosis-specific treatment actually receive it.

FRAX predicts cardiovascular risk in women undergoing osteoporosis screening: the Manitoba bone mineral density registry.

Osteoporosis and cardiovascular disease (CVD) are highly prevalent in older women, with increasing evidence for shared risk factors and pathogenesis. Although FRAX was developed for the assessment of fracture risk, we hypothesized that it might also provide information on CVD risk. To test the ability of the FRAX tool and FRAX-defined risk factors to predict incident CVD in women undergoing osteoporosis screening with DXA, we performed a retrospective prognostic cohort study which included women aged 50 yr or older with a baseline DXA scan in the Manitoba Bone Mineral Density Registry between March 31, 1999 and March 31, 2018. FRAX scores for major osteoporotic fracture (MOF) were calculated on all participants. Incident MOF and major adverse CV events (MACE; hospitalized acute myocardial infarction [AMI], hospitalized non-hemorrhagic cerebrovascular disease [CVA], or all-cause death) were ascertained from linkage to population-based healthcare data. The study population comprised 59 696 women (mean age 65.7 ± 9.4 yr). Over mean 8.7 yr of observation, 6021 (10.1%) had MOF, 12 277 women (20.6%) had MACE, 2274 (3.8%) had AMI, 2061 (3.5%) had CVA, and 10 253 (17.2%) died. MACE rates per 1000 person-years by FRAX risk categories low (10-yr predicted MOF <10%), moderate (10%-19.9%) and high (≥20%) were 13.5, 34.0, and 64.6, respectively. Although weaker than the association with incident MOF, increasing FRAX quintile was associated with increasing risk for MACE (all P-trend <.001), even after excluding prior CVD and adjusting for age. HR for MACE per SD increase in FRAX was 1.99 (95%CI, 1.96-2.02). All FRAX-defined risk factors (except parental hip fracture and lower BMI) were independently associated with higher non-death CV events. Although FRAX is intended for fracture risk prediction, it has predictive value for cardiovascular risk.

The association between body mass index and osteoporosis in a Taiwanese population: a cross-sectional and longitudinal study.

This study investigates the correlation between body mass index (BMI) and osteoporosis utilizing data from the Taiwan Biobank. Initially, a comprehensive analysis of 119,009 participants enrolled from 2008 to 2019 was conducted to assess the association between BMI and osteoporosis prevalence. Subsequently, a longitudinal cohort of 24,507 participants, initially free from osteoporosis, underwent regular follow-ups every 2-4 years to analyze the risk of osteoporosis development, which was a subset of the main cohort. Participants were categorized into four BMI groups: underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 24 kg/m2), overweight (24 kg/m2 ≤ BMI < 27 kg/m2), and obese groups (BMI ≥ 27 kg/m2). A T-score ≤ - 2.5 standard deviations below that of a young adult was defined as osteoporosis. Overall, 556 (14.1%), 5332 (9.1%), 2600 (8.1%) and 1620 (6.7%) of the participants in the underweight, normal weight, overweight and obese groups, respectively, had osteoporosis. A higher prevalence of osteoporosis was noted in the underweight group compared with the normal weight group (odds ratio [OR], 2.20; 95% confidence interval [95% CI], 1.99 to 2.43; p value < 0.001) in multivariable binary logistic regression analysis. Furthermore, in the longitudinal cohort during a mean follow-up of 47 months, incident osteoporosis was found in 61 (9%), 881 (7.2%), 401 (5.8%) and 213 (4.6%) participants in the underweight, normal weight, overweight and obese groups, respectively. Multivariable Cox proportional hazards analysis revealed that the risk of incident osteoporosis was higher in the underweight group than in the normal weight group (hazard ratio [HR], 1.63; 95% CI 1.26 to 2.12; p value < 0.001). Our results suggest that BMI is associated with both the prevalence and the incidence of osteoporosis. In addition, underweight is an independent risk factor for developing osteoporosis. These findings highlight the importance of maintaining normal weight for optimal bone health.

Diabetes and osteoporosis: a two-sample mendelian randomization study.

BACKGROUND: The effects on bone mineral density (BMD)/fracture between type 1 (T1D) and type 2 (T2D) diabetes are unknown. Therefore, we aimed to investigate the causal relationship between the two types of diabetes and BMD/fracture using a Mendelian randomization (MR) design. METHODS: A two-sample MR study was conducted to examine the causal relationship between diabetes and BMD/fracture, with three phenotypes (T1D, T2D, and glycosylated hemoglobin [HbA1c]) of diabetes as exposures and five phenotypes (femoral neck BMD [FN-BMD], lumbar spine BMD [LS-BMD], heel-BMD, total body BMD [TB-BMD], and fracture) as outcomes, combining MR-Egger, weighted median, simple mode, and inverse variance weighted (IVW) sensitivity assessments. Additionally, horizontal pleiotropy was evaluated and corrected using the residual sum and outlier approaches. RESULTS: The IVW method showed that genetically predicted T1D was negatively associated with TB-BMD (ß = -0.018, 95% CI: -0.030, -0.006), while T2D was positively associated with FN-BMD (ß = 0.033, 95% CI: 0.003, 0.062), heel-BMD (ß = 0.018, 95% CI: 0.006, 0.031), and TB-BMD (ß = 0.050, 95% CI: 0.022, 0.079). Further, HbA1c was not associated with the five outcomes (ß ranged from - 0.012 to 0.075). CONCLUSIONS: Our results showed that T1D and T2D have different effects on BMD at the genetic level. BMD decreased in patients with T1D and increased in those with T2D. These findings highlight the complex interplay between diabetes and bone health, suggesting potential age-specific effects and genetic influences. To better understand the mechanisms of bone metabolism in patients with diabetes, further longitudinal studies are required to explain BMD changes in different types of diabetes.

Osteoporotic fracture risk in women with breast cancer treated with aromatase inhibitors: a health insurance claims database study in Japan.

BACKGROUND: Hormone therapy with aromatase inhibitors (AIs) for estrogen receptor-dependent breast cancer may expose patients to an increased osteoporosis risk. This study was performed to estimate fracture risk in women with breast cancer to whom AIs were prescribed in Japan. METHODS: This retrospective study used data from the Japanese Medical Data Vision database. Women with breast cancer prescribed AIs over a 12-month period were identified and matched to women not prescribed AIs using a propensity score. Fracture rates were estimated by a cumulative incidence function and compared using a cause-specific Cox hazard model. The proportion of women undergoing bone density tests was retrieved. RESULTS: For all fractures sites combined, cumulative fracture incidence at 10 years was 0.19 [95%CI: 0.16-0.22] in women prescribed AIs and 0.18 [95%CI: 0.15-0.21] without AIs. AI prescription was not associated with any changes in risk (adjusted hazard ratio: 1.08 [95%CI: 0.99-1.17] p = 0.08). Women prescribed AI more frequently underwent bone density testing (31.9% [95% CI: 31.2%; 32.6%] versus 2.2% [95% CI: 2.0%; 2.4%]). CONCLUSIONS: The anticipated association between AI exposure and osteoporotic fracture risk in Japanese women with breast cancer was not seen clearly.

Construction and verification of risk prediction model of osteoporotic fractures in patients with osteoporosis in China.

Objective: To explore the influencing factors of osteoporotic fractures (OPF) in patients with osteoporosis, construct a prediction model, and verify the model internally and externally, so as to provide reference for early screening and intervention of OPF in patients with osteoporosis. Methods: Osteoporosis patients in the First Affiliated Hospital of Soochow University were selected, and the medical records of patients were consulted through the Hospital Information System (HIS) and the data management platform of osteoporosis patients, so as to screen patients who met the criteria for admission and discharge and collect data. SPSS 26.0 software was used for single factor analysis to screen statistically significant variables (p < 0.05). The influencing factors of OPF were determined by multivariate analysis, and a binary Logistic regression model was established according to the results of multivariate analysis. Hosmer-Lemeshow (H-L) goodness of fit and receiver operating characteristic curve (ROC) were used to test the model's efficiency, and Stata 16.0 software was used to verify the Bootstrap model, draw the model calibration curve, clinical applicability curve and nomogram. Results: In this study, the data of modeling set and verification set were 1,435 and 580, respectively. There were 493 (34.4%) cases with OPF and 942 (65.6%) cases without OPF in the modeling set. There were 204 (35.2%) cases with OPF and 376 (64.8%) cases without OPF. The variables with statistically significant differences in univariate analysis are Age, BMI, History of falls, Usage of glucocorticoid, ALP, Serum Calcium, BMD of lumbar, BMD of feminist neck, T value of feminist neck, BMD of total hip and T value of total hip. The area under ROC curve of the risk prediction model constructed this time is 0.817 [95%CI (0.794 ~ 0.839)], which shows that the model has a good discrimination in predicting the occurrence of OPF. The optimal threshold of the model is 0.373, the specificity is 0.741, the sensitivity is 0.746, and the AUC values of the modeling set and the verification set are 0.8165 and 0.8646, respectively. The results of Hosmer and Lemeshow test are modeling set: (χ2 = 6.551, p = 0.586); validation set: [(χ2 = 8.075, p = 0.426)]. The calibration curve of the model shows that the reference line of the fitted curve and the calibration curve is highly coincident, and the model has a good calibration degree for predicting the occurrence of fractures. The net benefit value of the risk model of osteoporosis patients complicated with OPF is high, which shows that the model is effective. Conclusion: In this study, a OPF risk prediction model is established and its prediction efficiency is verified, which can help identify the high fracture risk subgroup of osteoporosis patients in order to choose stronger intervention measures and management.

Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data.

Osteoporosis is a major public health concern that significantly increases the risk of fractures. The aim of this study was to develop a Machine Learning based predictive model to screen individuals at high risk of osteoporosis based on chronic disease data, thus facilitating early detection and personalized management. A total of 10,000 complete patient records of primary healthcare data in the German Disease Analyzer database (IMS HEALTH) were included, of which 1293 diagnosed with osteoporosis and 8707 without the condition. The demographic characteristics and chronic disease data, including age, gender, lipid disorder, cancer, COPD, hypertension, heart failure, CHD, diabetes, chronic kidney disease, and stroke were collected from electronic health records. Ten different machine learning algorithms were employed to construct the predictive mode. The performance of the model was further validated and the relative importance of features in the model was analyzed. Out of the ten machine learning algorithms, the Stacker model based on Logistic Regression, AdaBoost Classifier, and Gradient Boosting Classifier demonstrated superior performance. The Stacker model demonstrated excellent performance through ten-fold cross-validation on the training set and ROC curve analysis on the test set. The confusion matrix, lift curve and calibration curves indicated that the Stacker model had optimal clinical utility. Further analysis on feature importance highlighted age, gender, lipid metabolism disorders, cancer, and COPD as the top five influential variables. In this study, a predictive model for osteoporosis based on chronic disease data was developed using machine learning. The model shows great potential in early detection and risk stratification of osteoporosis, ultimately facilitating personalized prevention and management strategies.

The yield of routine laboratory examination in osteoporosis evaluation in primary care.

This study evaluated the yield of routine laboratory examination in a large population of older women in primary care. The prevalence of laboratory abnormalities was low and the clinical consequences in follow-up were limited. There was a weak association of laboratory abnormalities with osteoporosis but no association with vertebral fractures and recent fractures. PURPOSE: Most osteoporosis guidelines advice routine laboratory examination. We have investigated the yield of laboratory examinations in facture risk evaluation of elderly women in primary care. METHODS: We assessed the prevalence of laboratory abnormalities and their association with risk factors for fractures, recent fractures, low bone mineral density (BMD), and prevalent vertebral fracture in 8996 women ≥ 65 years of age participating in a primary care fracture risk screening study. In a sample of 2208 of these participants, we also evaluated the medical consequences in the medical records during a follow-up period of ≥ 1 year. RESULTS: Vitamin D deficiency (< 30 nmol/L) was present in 13% and insufficiency (< 50 nmol/L) in 43% of the study sample. The prevalence of other laboratory abnormalities (ESR, calcium, creatinine, FT4) was 4.6% in women with risk factors for fractures, 6.1% in women with low BMD (T-score ≤ - 2.5), 6.0% after a prevalent vertebral fracture, 5.2% after a recent fracture and 2.6% in the absence of important risk factors for fractures. Laboratory abnormalities other than vitamin D were associated with low BMD (OR 1.4, 95%CI 1.1-1.8) but not with prevalent vertebral fractures nor recent fractures. Low BMD was associated with renal failure (OR 2.0, 95%CI 1.3-3.4), vitamin D insufficiency (OR 1.2, 95%CI 1.0-1.3) and deficiency (OR 1.3, 95%CI 1.1-.5). In the follow-up period, 82% of the laboratory abnormalities did not result in a new diagnosis or treatment reported in the medical records. CONCLUSIONS: We identified a low prevalence of laboratory abnormalities in a primary care population of older women and the majority of these findings had no medical consequences.

Challenges of fracture risk assessment in Asian and Black women.

OBJECTIVES: Bone mineral density (BMD) and fracture risk calculators (eg, the Fracture Risk Assessment Tool [FRAX]) guide primary prevention care in postmenopausal women. BMD scores use non-Hispanic White (NHW) reference data for T-score classification, whereas FRAX incorporates BMD, clinical risk factors, and population differences when calculating risk. This study compares findings among Asian, Black, and NHW women who underwent osteoporosis screening in a US health care system. STUDY DESIGN: Retrospective cross-sectional study. METHODS: Asian, Black, and NHW women aged 65 to 75 years who underwent BMD testing (with no recent fracture, osteoporosis therapy, metastatic cancer, multiple myeloma, metabolic bone disorders, or kidney replacement therapy) were compared across the following measures: femoral neck BMD (FN-BMD) T-score (normal ≥ -1, osteoporosis ≤ -2.5), high FRAX 10-year hip fracture risk (FRAX-Hip ≥ 3%), FRAX risk factors, and diabetes status. RESULTS: Among 3640 Asian women, 23.8% had osteoporosis and 8.7% had FRAX-Hip scores of at least 3% (34.5% among those with osteoporosis). Among 11,711 NHW women, 12.3% had osteoporosis and 17.2% had FRAX-Hip scores of at least 3% (84.8% among those with osteoporosis). Among 1711 Black women, 68.1% had normal FN-BMD, 4.1% had BMD-defined osteoporosis, and 1.8% had FRAX-Hip scores of at least 3% (32.4% among those with osteoporosis). Fracture risk factors differed by group. Diabetes was 2-fold more prevalent in Black and Asian (35% and 36%, respectively) vs NHW (16%) women. CONCLUSIONS: A large subset of Asian women have discordant BMD and FRAX scores, presenting challenges in osteoporosis management. Furthermore, FN-BMD and especially FRAX scores identified few Black women at high fracture risk warranting treatment. Studies should examine whether fracture risk assessment can be optimized in understudied racial minority populations, particularly when findings are discordant.

Sedentary behavior does not predict low BMD nor fracture-population-based Canadian Multicentre Osteoporosis Study.

Sedentary behavior (SB) or sitting is associated with multiple unfavorable health outcomes. Bone tissue responds to imposed gravitational and muscular strain with there being some evidence suggesting a causal link between SB and poor bone health. However, there are no population-based data on the longitudinal relationship between SB, bone change, and incidence of fragility fractures. This study aimed to examine the associations of sitting/SB (defined as daily sitting time), areal BMD (by DXA), and incident low trauma (fragility) osteoporotic fractures (excluding hands, feet, face, and head). We measured baseline (1995-7) and 10-yr self-reported SB, femoral neck (FN), total hip (TH), and lumbar spine (L1-L4) BMD in 5708 women and 2564 men aged 25 to 80+ yr from the population-based, nationwide, 9-center Canadian Multicentre Osteoporosis Study. Incident 10-yr fragility fracture data were obtained from 4624 participants; >80% of fractures were objectively confirmed by medical records or radiology reports. Vertebral fractures were confirmed by qualitative morphological methods. All analyses were stratified by sex. Multivariable regression models assessed SB-BMD relationships; Cox proportional models were fit for fracture risk. Models were adjusted for age, height, BMI, physical activity, and sex-specific covariates. Women in third/fourth quartiles had lower adjusted FN BMD versus women with the least SB (first quartile); women in the SB third quartile had lower adjusted TH BMD. Men in the SB third quartile had lower adjusted FN BMD than those in SB first quartile. Neither baseline nor stable 10-yr SB was related to BMD change nor to incident fragility fractures. Increased sitting (SB) in this large, population-based cohort was associated with lower baseline FN BMD. Stable SB was not associated with 10-yr BMD loss nor increased fragility fracture. In conclusion, habitual adult SB was not associated with subsequent loss of BMD nor increased risk of fracture.

The number of hours of sitting in a day (often called "sedentary behavior") is currently understood to be "bad for bone health" both because of increased bone loss and a higher risk for fractures. Very few studies in randomly sampled men and women from a whole population have consistently asked about hours of sitting and examined baseline bone density. Fewer still have compared hours of sitting and its changes over 10 yr with changes in bone density and the number of new fractures that occurred. The Canadian Multicentre Osteoporosis Study obtained sitting hours from 5708 women and 2564 men aged 25 to 80+ yr and compared it with the spine, total hip (TH), and femoral neck (FN) bone density values. The average sitting at 7.4 h in men was associated with slightly lower adjusted femoral neck bone density; in women, sitting 6.7 h/d was associated with slightly lower adjusted FN and TH bone density. Ten-year follow-up data (now in about 5000 people) showed no relationship between the slightly longer sitting (an increase of 18% in men and 22% in women) and bone loss or new bone fractures. In this large country-wide population-based study, hours of sitting each day were not associated with 10-yr BMD loss in women or men nor did sitting more associate with new bone fractures. These data are reassuring; women and men who walk regularly and have some moderate-vigorous physical activity each day, despite more sitting, do not seem to be at greater risk for osteoporosis.

Associations of residential greenness with bone mineral density and osteoporosis: the modifying effect of genetic susceptibility.

OBJECTIVES: To investigate the associations of residential greenness with bone mineral density and incident osteoporosis, and further evaluate the potential modifying effect of genetic susceptibility. METHODS: We used the Normalised Difference Vegetation Index (NDVI) at various buffer distances, including 300 m (NDVI300m), 500 m (NDVI500m), 1000 m (NDVI1000m) and 1500 m (NDVI1500m), to serve as indicators of greenness. We fitted linear regression, logistic regression and Cox proportional hazard models to assess the associations of residential greenness with estimated bone mineral density (eBMD), prevalent osteoporosis and incident osteoporosis, respectively. With the Polygenic Risk Score (PRS) for osteoporosis, we further assessed the joint effects of genetic risk and greenness on the risk of osteoporosis. We conducted causal mediation analyses to explore potential mediators. RESULTS: Each IQR increase in NDVI300m was associated with 0.0007 (95% CI 0.0002 to 0.0013) increase in eBMD, 6% lower risk of prevalent osteoporosis (OR 0.94; 95% CI 0.92 to 0.97) and 5% lower risk of incident osteoporosis (HR 0.95; 95% CI 0.93 to 0.98). The joint effects of greenness and PRS on the risk of osteoporosis displayed a clear dose-response pattern. Compared with individuals exposed to low NDVI levels and high genetic risk, those exposed to high NDVI levels and low genetic risk had a 56% (95% CI 51% to 61%) lower risk of osteoporosis. The primary mediators in the association between greenness and incident osteoporosis were identified as PM2.5 and NO2. CONCLUSIONS: Residential greenness was associated with higher bone mineral density and decreased risk of incident osteoporosis.

Analysis of related factors for sarco-osteoporosis in middle-aged and elderly inpatients and development and validation of a nomogram.

BACKGROUND: Sarco-osteoporosis is a skeletal muscle disease associated with aging and complex pathological factors. At present, there are few studies on the analysis of its related factors, and a nomogram to estimate the risk of sarco-osteoporosis in middle-aged and elderly patients is not available. METHODS: A total of 386 patients admitted to our hospital from October 2021 to October 2022 were collected, and the general demographic data and clinical data of the patients were collected.386 subjects were enrolled in the study and randomly divided into training set and validation set at a ratio of 7:3. In the training set, the Least absolute shrinkage and selection operator(LASSO)regression technique was used to select the optimal predictive features, and multivariate logistic regression was used to screen the factors associated with sarco-osteoporosis, and a nomogram was constructed using meaningful variables from multivariate analysis. The performance of the nomograms was assessed and validated by Area Under Curve (AUC) and calibration curves. RESULTS: There were no significant differences in baseline characteristic of individuals in training set and validation set, six variables with non-zero coefficients were screened based on LASSO regression in the training set. Multivariate logistic regression analysis showed that the related factors for sarco-osteoporosis in middle-aged and elderly inpatients included age (OR = 1.08, 95%CI 1.03 ∼ 1.14), regular exercise (OR = 0.29, 95%CI 0.15 ∼ 0.56), albumin (OR = 0.9, 95%CI 0.82 ∼ 0.98), height (OR = 0.93, 95%CI 0.88 ∼ 0.99) and lean mass index (OR = 0.66, 95%CI 0.52 ∼ 0.85), and a nomogram was constructed based on the above factors. AUC of nomogram were 0.868(95%CI 0.825 ∼ 0.912) in the training set and 0.737(95%CI 0.646 ∼ 0.828) in the validation set. Calibration curve analysis showed that the predicted probability of sarco-osteoporosis had high consistency with the actual probability, and the absolute error of the training set and verification set was 0.018 and 0.03, respectively. CONCLUSIONS: Our research showed that the occurrence of sarco-osteoporosis was associated with age, regular exercise, albumin, height and lean mass index, and we have developed a nomogram that can be effectively used in the preliminary and in-depth risk prediction of sarco-osteoporosis in middle-aged and elderly hospitalized patients.

Association between pharmacotherapy and secondary vertebral fracture managed with a brace in a real-world setting: A nationwide database study in Japan.

AIM: This retrospective cohort study assessed the association between the incidence of secondary vertebral fracture managed with a brace (SVF) and pharmacotherapy. METHODS: The association between the incidence of SVF and the presence, type, and medication possession ratio (MPR) of pharmacotherapy was investigated using medical insurance data acquired from the National Database of Health Insurance Claims and Specific Health Checkups of Japan. RESULTS: The data of female patients (n = 637 303) were analyzed. The 2-year incidence of SVF was 73.5 per 10 000 patients (n = 4687). Approximately 0.73% of patients without medications and 0.74% with medications had SVF. Patients taking bisphosphonates (0.87), denosumab (0.77), and selective estrogen receptor modulators (0.88) had significantly lower standardized incidence ratios (SIRs) than patients not taking medications after the occurrence of primary fracture; meanwhile, patients taking parathyroid hormone medications had considerably higher SIRs than those not taking medications. The non-SVF group (59.1%) had a significantly higher mean MPR than the SVF group (55.5%). Patients taking denosumab in the non-SVF group (68.2%) had the highest mean MPR. The proportion of patients taking denosumab with an MPR of ≥80% in the non-SVF group was significantly higher than that in the SVF group. CONCLUSION: Patients taking medications were at a lower risk of developing SVF than those not taking medications. Although this study did not compare the medications' SVF prevention effects, patients taking denosumab had a 0.77 SIR of SVF in Japan. The effect of pharmacotherapy on SVF prevention might be affected by the MPR of each medication. Geriatr Gerontol Int 2024; 24: 390-397.

Significance of non-motor symptoms and development of a screening tool for osteoporosis in Parkinson's disease.

BACKGROUND AND PURPOSE: Parkinson's disease (PD) patients have a higher likelihood of having osteoporosis compared to controls, therefore deserving special attention. This study was to 1) investigate the association of non-motor symptoms with osteoporosis amongst PD patients, and 2) develop screening tools for osteoporosis. MATERIALS AND METHODS: PD Patients were included (n = 109). The factors/variables were obtained from clinical records due to the retrospective nature of this study. The bone mineral density (BMD) of the lumbar spine and femoral neck was examined using a dual-energy X-ray absorptiometry machine, according to which they were categorized as either having (T-score ≤ -2.5) or not having osteoporosis (T-score>-2.5) at the two sites. The non-motor symptoms were assessed using clinical scales, including non-motor experiences of daily living, depression, anxiety, cognitive function, and autonomic function. The potential covariates included demographic and clinical factors/variables, such as age and sex. Logistic regression was used to investigate the associations and establish the screening tools. RESULTS: Patients with autonomic dysfunction had significantly (p = 0.011) higher odds of having femoral neck osteoporosis compared to those with no/minimal dysfunction after adjusting for sex, disease duration, and body mass index, demonstrating a strong association (odds ratio=12.81). Based on the four factors/variables, a screening tool with a good accuracy was established (C-statistic = 0.85). CONCLUSION: PD patients with autonomic dysfunction had greater odds of having femoral neck osteoporosis compared to those with no/minimal dysfunction. The screening tool may lay a foundation for developing screening models with higher accuracy to identify which PD patients may require a BMD test.

Exploring complex links: inflammatory rheumatic diseases and men's health.

This article examines the complex interactions between inflammatory rheumatic diseases (IRDs) and men's health. It delves into the effects of IRDs on reproductive health, erectile dysfunction, prostate involvement, male osteoporosis, body composition, physical activity, and coping mechanisms. The findings show that the prevalence of sexual dysfunction varies among different diseases, underscoring the necessity for comprehensive counseling. The link between IRDs and prostate health, with a substantial rise in benign prostatic hyperplasia among IRD patients, demonstrates the condition's importance. In contrast to popular belief, osteoporosis mostly affects women; the current study highlights the growing identification of male osteoporosis, particularly in the setting of IRDs. Male RA patients had a significant loss in bone mineral density, highlighting the importance of increasing awareness and tailored therapy to address osteoporosis in men. IRDs affect body composition, with male RA patients showing imbalances characterized by decreased lean body mass and increased fat mass. Given the dynamic nature of these conditions, coping with IRDs necessitates thorough and individualized diversified approaches. The complex link between IRDs and men's health demands continuing research, including longitudinal studies and tailored therapies. The essay promotes a patient-centered approach, recognizing the unique obstacles that males with IRDs confront.

Association between alcohol intake and bone mineral density: results from the NHANES 2005-2020 and two-sample Mendelian randomization.

We used the data from the NHANES cross-sectional study among 14,113 participants and indicated a positive correlation between alcohol intake frequency and bone mineral density in different body sites. Mendelian randomization was conducted, and no causal relationship is significant between these two variables. The study can provide some suggestions on the daily consumption of alcohol for osteoporosis patients. PURPOSE: The effect of alcohol intake on bone mineral density (BMD) remains unclear. This study explored the association and causality between alcohol intake and BMD. METHODS: Based on the 2005-2020 National Health and Nutrition Examination Survey including 14,113 participants, we conducted co-variate-adjusted multilinear regression analyses to explore the association between alcohol intake levels and spine or femur BMD. To evaluate the causal association between alcohol intake frequency and bone mineral density, the inverse variance weighted approach of two-sample Mendelian randomization (MR) was used with genetic data from the Medical Research Council Integrative Epidemiology Unit (462,346 cases) for alcohol intake frequency and the Genetic Factors for Osteoporosis Consortium (28,496 cases) for lumbar spine and femur neck BMD (32,735 cases). RESULTS: Compared with non-drinkers, total femur BMDs but not total spine BMD increased with daily alcohol intake in males (ß = 3.63*10-2 for mild drinkers, ß = 4.21*10-2 for moderate drinkers, and ß = 4.26*10-2 for heavy drinkers). By contrast, the higher total spine BMD in females was related to higher alcohol intake levels (ß = 2.15*10-2 for mild drinkers, ß = 2.59*10-2 for moderate drinkers, and ß = 3.88*10-2 for heavy drinkers). Regarding the two-sample MR results, no causal relationship was observed between alcohol intake frequency and lumbar spine BMD (odds ratio [OR] = 1.016, P = 0.789) or femur neck BMD (OR = 1.048, P = 0.333). CONCLUSION: This study suggests a positive association between alcohol intake frequency and BMD, although the causal relationship was not significant.