OBJECTIVE: To analyze the demographic and clinical characteristics of inpatients with osteoporotic vertebral compression fractures (OVCF) and provide a basis for clinical prevention and treatment. METHODS: A retrospective analysis was performed on the clinical data of 744 inpatients diagnosed with OVCF between January 2017 and December 2021 who met the inclusion criteria. Among them, 146 were male and 598 were female, with age ranging from 50 to 95 years (mean, 69.37 years). The demographic characteristics (gender, age, ethnicity, occupation, regional distribution, urban-rural distribution, and seasonal incidence) and clinical features [causes of injury, history of vertebral fractures, smoking and drinking history in males, comorbidities (hypertension, diabetes, coronary atherosclerotic heart disease, cerebral infarction), body mass index (BMI), blood lipid levels, menopausal age in females, vertebral bone mineral density T-value, number of vertebral fractures, and fracture segment distribution] of OVCF patients were analyzed. Multiple linear regression was used to analyze the independent risk factors of vertebral osteoporosis. RESULTS: The demographic analysis indicated that female patients with OVCF were significantly younger than male patients ( P<0.05). Significant differences were observed in the age distribution of OVCF between males and females ( P<0.05), with the highest proportion of male patients in the 70-79 years group (37.0%) and the highest proportion of female patients in the 60-69 years group (40.0%). From 2017 to 2021, the age of onset for OVCF gradually increased, with a similar trend observed for both genders. The distribution of occupations between genders also showed significant differences ( P<0.05); with the top three occupations for males being farmers (48.6%), retirees (24.7%), and workers (13.7%), while for females, the leading occupations were farmers (51.5%), retirees (19.4%), and service workers (10.0%). Female OVCF patients had higher BMI, vertebral bone mineral density T-value, history of vertebral fractures, hypertension prevalence, and blood lipid levels compared to male patients ( P<0.05). No significant difference between the males and the females was found in ethnicity, seasonal distribution, regional distribution, urban-rural distribution, causes of injury, number of vertebral fractures, or prevalence of comorbidities (except hypertension) ( P>0.05). Among the 744 OVCF patients, a total of 1 309 vertebrae were involved, with 628 thoracic vertebrae (48.0%) and 681 lumbar vertebrae (52.0%). The most common fracture segments were L ₁ (22.5%), T ₁₂ (21.2%), followed by L ₂ (12.2%) and T ₁₁ (10.2%). No significant gender difference was observed in the distribution of fracture segments ( P>0.05). Multiple linear regression analysis indicated that older age, female, and lower BMI were independent risk factors for vertebral osteoporosis ( P<0.05). CONCLUSION The age of onset of OVCF patients is increasing year by year. The number of fractured vertebral bodies, age distribution of morbidity, occupational distribution, BMI, history of vertebral fracture, hypertension, and blood lipid levels are related to gender. The occurrence of OVCF is mainly in the thoracolumbar segment. The female, older age, and lower BMI are independent risk factors of osteoporosis.
Humans ; Male ; Female ; Aged ; Middle Aged ; Retrospective Studies ; Spinal Fractures/etiology* ; Aged, 80 and over ; Osteoporotic Fractures/etiology* ; Fractures, Compression/etiology* ; Risk Factors ; Bone Density ; China/epidemiology* ; Osteoporosis/epidemiology* ; Comorbidity ; Inpatients ; Sex Factors ; Age Factors

OBJECTIVE:  To estimate the population attributable disease burden (PAD) of low bone mineral density (LBMD) related fractures (fragility fractures) among Chinese people over 50 years old from 1990 to 2023, using data from the Global Burden of Disease Study 2023 (GBD 2023), and to provide evidence for prevention strategies and health resource allocation. METHODS:   Based on the GBD 2023, the LBMD summary exposure values (SEV), fracture incidence, years lived with disability (YLDs), and LBMD-related falls YLDs of Chinese people over 50 years old from 1990 to 2023 were extracted. PAD was calculated with population attributable fraction (PAF), and an entropy-weight method was applied to evaluate the contribution of individual fracture sites. Temporal trends and sex differences were examined with Joinpoint regression. RESULTS:  From 1990 to 2023, the age-standardized SEV of LBMD in people over 50 years old showed an overall decline [average annual percent change (AAPC)=-0.564%]. Age-standardized fracture incidence, fracture YLDs rate, and LBMD-related falls YLDs rate all exhibited W-shaped upward trends (AAPC=1.045%, 0.296%, and 0.724%, respectively). PAF-based estimates indicated that LBMD-attributable fracture incidence likewise increased in a "W-shaped" manner (AAPC=0.558%), whereas the corresponding YLDs rate showed an overall W-shaped decline (AAPC=-0.193%). In international comparison, China and the global average displayed broadly concordant directions of change, with greater volatility in China and a progressive narrowing of the gap after 2015. Regarding sex differences, fracture YLDs rates were consistently higher in the males, whereas the other burden indicators were higher in the females; the temporal patterns were similar in both sexes. Entropy weight method identified hip fractures as contributing most to incidence (weight 0.133), and pelvic fractures as the largest contributor to YLDs rate (weight 0.115). CONCLUSION Since 1990, the LBMD attributable fracture burden in China's older population has risen, with female and hip or pelvic fractures bearing the heaviest load. Strengthened osteoporosis screening, improved insurance coverage, and targeted health education are urgently needed to curb further increases in disease burden.
Humans ; China/epidemiology* ; Middle Aged ; Female ; Male ; Bone Density ; Aged ; Incidence ; Osteoporotic Fractures/epidemiology* ; Aged, 80 and over ; Accidental Falls/statistics & numerical data* ; Cost of Illness ; Global Burden of Disease ; Osteoporosis/complications* ; Disability-Adjusted Life Years ; Fractures, Bone/epidemiology*

OBJECTIVE: To explore the epidemiological characteristics of knee osteoarthritis (KOA) among the elderly in the community, and its correlation with bone mass loss. METHODS: A cross-sectional study was conducted on elderly community population over 50 year old from 12 community health service centers in Zhejiang province. Their gender, age, body mass index (BMI), T value and KOA diagnosis were collected using face to face questionnaire survey. Univariate regression was used to analyze the influence of age, gender, BMI and bone loss on KOA. Logistic multivariate regression model was used to analyze the independent effect of bone mass loss on KOA. RESULTS: Among 4 173 subjects in this study, 1 710 of them were had a KOA. The prevalence rate was 40.9%. The mean age, the proportion of females and the mean BMI in KOA patients were (65.5±3.8) years old, 67.7%(1 158/1 710) and(24.59±1.28) kg·m^-2, respectively, which were significantly higher than (58.5±3.2) years old, 51.3%(1 263/2 463), and (23.48±1.25) kg·m^-2 in non-KOA subjects (P<0.001). In the population aged from 60 to 69 years old, the influence of osteopenia and osteoporosis on the prevalence of KOA was[OR=1.21, 95%CI(1.00, 1.46), P=0.053 2], [OR=1.42, 95%CI(1.14, 1.78), P=0.002 2]. The influence of male and female osteoporosis on the prevalence of KOA was [OR=1.52, 95%CI(1.16, 1.99), P=0.002 7] and [OR=1.87, 95%CI(1.51, 2.32), P<0.000 1], respectively. In the population of 24 kg·m^-2≤BMI<28 kg·m^-2, the influence of osteopenia and osteoporosis on the prevalence of KOA was [OR=1.47, 95%CI(1.21, 1.80), P=0.000 1], [OR=2.69, 95%CI(2.11, 3.42), P<0.000 1], respectively. After controlling the confounding factors of age, gender and BMI, compared with people with normal bone mass, the effect of osteopenia on the prevalence of KOA was [OR=1.34, 95%CI(1.08, 1.67), P=0.009 2], and the effect of osteoporosis on the prevalence of KOA was [OR=1.38, 95%CI(1.06, 1.79), P=0.017 9]. CONCLUSION Elderly overweight women are more likely to develop KOA. Bone mass loss is an independent risk factor for KOA, which will significantly increase the prevalence of KOA in people overweight or aged 60 to 69 years old.
Humans ; Female ; Male ; Aged ; Osteoarthritis, Knee/etiology* ; Middle Aged ; Cross-Sectional Studies ; Bone Density ; Aged, 80 and over ; Incidence ; Body Mass Index ; China/epidemiology* ; Osteoporosis/epidemiology*

OBJECTIVE: To explore the co-morbid influencing factors of postmenopausal osteoporosis(PMOP) and dyslipidemia, and to provide evidence-based basis for clinical co-morbidity management. METHODS: Based on the 2017 to 2018 Beijing community cross-sectional survey data, PMOP patients were included and divided into the dyslipidemia group and the uncomplicated dyslipidemia group according to whether they were comorbid with dyslipidemia. Demographic characteristics, living habits and disease history were collected through questionnaires, and bone mineral density and bone metabolism biomarkers (osteocalcin, blood calcium, serum typeⅠprocollagen N-terminal prepeptide, etc.) were detected on site. Co-morbidity risk factors were analyzed using binary logistic regression. RESULTS: Three hundred and twenty patients with PMOP were included, including the comorbid group (75 patients) and the uncomplicated group (245 patients). The results showed that history of cardiovascular disease [OR=1.801, 95%CI(1.003, 3.236), P=0.049], history of cerebrovascular disease [OR=2.923, 95%CI(1.460, 5.854), P=0.002], frying and cooking methods[OR=5.388, 95%CI(1.632, 17.793), P=0.006], OST results[OR=0.910, 95%CI(0.843, 0.983), P=0.016], and blood Ca results [OR=60.249, 95%CI(1.862, 1 949.926), P=0.021] were the influencing factors of PMOP complicated with dyslipidemia. CONCLUSION Focus should be placed on the influencing factors of PMOP and dyslipidemia co-morbidities, with emphasis on multidimensional assessment, combining lifestyle interventions with bone metabolism marker monitoring to optimize co-morbidity management.
Humans ; Dyslipidemias/epidemiology* ; Female ; Middle Aged ; Osteoporosis, Postmenopausal/metabolism* ; Aged ; Cross-Sectional Studies ; Risk Factors ; Bone Density

BACKGROUND: High visceral fat mass (FM) is associated with a high risk of cardiometabolic morbidity. Meanwhile, loss of skeletal muscle (lean mass, LM) has been suggested to contribute to metabolic diseases. METHODS: We investigated associations between cardiometabolic diseases and dual energy X-ray absorptiometry (DXA)-measured body composition indices, including the FM index (FM/height²), percent body fat, trunk-to-appendicular fat ratio (TAR), trunk-to-leg fat ratio (TLR), LM index (LM/height²) and FM-to-LM ratio in 595 community-dwelling elderly Japanese men (mean age, 74 years; standard deviation, 6; range, 65 to 94). Hypertension was identified as high blood pressure and/or the use of antihypertensive drugs. Diabetes was identified as high hemoglobin A1c and/or the use of antidiabetic drugs. The ability of DXA-based indices to discriminate between the presence and absence of cardiometabolic diseases was evaluated using area under the curve (AUC) calculated by receiver operating characteristic curve analysis. RESULTS: Body mass index, FM index, percent body fat, TAR, TLR and FM-to-LM ratio were significantly associated with hypertension (P < 0.05). TAR and TLR, but not body mass index, FM index, percent body fat, LM index and FM-to-LM ratio, showed significant positive associations with diabetes. The AUC for the LM index was significantly lower than those for the FM index, percent body fat and FM-to-LM ratio. No associations were observed between the LM index and hypertension, dyslipidemia and diabetes. CONCLUSION The association between cardiometabolic function and LM, which includes skeletal muscle, may not be as pronounced or stronger than associations between cardiometabolic function and FM. Further detailed studies are needed to clarify how skeletal muscle contributes to cardiometabolic disease.
Humans ; Male ; Absorptiometry, Photon ; Aged ; Japan/epidemiology* ; Body Composition ; Aged, 80 and over ; Hypertension/epidemiology* ; Cardiovascular Diseases/epidemiology* ; Body Mass Index ; Muscle, Skeletal ; Osteoporosis/epidemiology* ; Diabetes Mellitus/epidemiology* ; Risk Factors ; East Asian People

OBJECTIVES: To analyze bone mass distribution and the factors affecting bone mass in a general Chinese Han cohort undergoing physical examinations at our center. METHODS: We retrospectively collected the data of bone mineral density (BMD) measurements from 30 599 healthy Han Chinese adults (age≥20 years) who underwent dual-energy X-ray absorptiometry scans at our hospital from July, 2013 to July, 2023. Basic parameters including height, body weight, and gender were recorded, and descriptive statistics and correlation analyses were performed using R software. RESULTS: In this cohort, the male individuals had a mean peak BMD of 1.00±0.12 g/cm² in the lumbar vertebrae, 0.94±0.14 g/cm² in the femoral neck, and 0.99±0.13 g/cm² in the total hip, significantly higher than the values in the female individuals [0.99±0.12 g/cm² in the lumbar vertebrae (P=0.022), 0.79±0.11 g/cm² in the femoral neck (P<0.001), and 0.88±0.11 g/cm² in the total hip (P<0.001)]. In the overall cohort, the BMD values of the lumbar spine and femur decreased with age after reaching their peak levels. There was a positive correlation between BMD value and body mass index (BMI) in both male and female individuals. The 2013-2014 period recorded the lowest BMD values in the lumbar, hip, and femoral neck, which tended to increase steadily in the following years (2015-2023). CONCLUSIONS Our data suggest that the BMD values vary among different populations, and future multi-center studies using more accurate BMD detection technology are warranted to capture the variation patterns of BMD with demographic characteristics of specific populations.
Humans ; Bone Density ; Absorptiometry, Photon ; Male ; Female ; Retrospective Studies ; Osteoporosis/diagnostic imaging* ; Adult ; Middle Aged ; Lumbar Vertebrae/diagnostic imaging* ; China/epidemiology* ; Femur Neck/diagnostic imaging* ; Aged ; Beijing/epidemiology* ; Young Adult

OBJECTIVE: Because of the limited number of studies and small sample sizes, whether metabolic syndrome (MS) leads to the occurrence and progression of osteoporosis and the possible underlying mechanisms require further investigation. This study aimed to investigate the association between MS and osteoporosis, along with its influencing factors. METHODS: This observational cross-sectional study included 139,470 individuals aged ≥ 18 years who underwent health examinations from September 2014 to March 2022. Based on bone mineral density (BMD) screening results, the participants were categorized into a suspected osteoporosis or non-osteoporosis group (control). Participants were further divided into those who met 0 MS criteria, 1 MS criterion, 2 MS criteria, and ≥ 3 MS criteria (MS group). Participants who had undergone health examinations at least twice formed the follow-up cohort; a self-matched analysis was performed on those with follow-up periods ≥ 5 years and unchanged MS grouping. RESULTS: Several examination indicators in the suspected osteoporosis group showed statistically significant differences compared with the control group. The proportion of suspected osteoporosis in the MS group was significantly increased compared with that in the 0 MS criteria group (odds ratio [ OR]: 1.215, Z = 29.11, P < 0.001, 95% confidence interval: 1.199-1.231). After adjusting for age, sex, smoking, and alcohol consumption, the 2 MS criteria group and MS group still had OR values > 1 ( P < 0.001). In the follow-up cohort, the proportion of suspected osteoporosis increased gradually with an increase in the number of MS criteria met at baseline and during each follow-up visit ( P < 0.05), with the highest proportion observed in the MS group. However, the proportion of suspected osteoporosis did not increase significantly over time in the different MS groups ( P > 0.05). In the follow-up cohort, the proportion of individuals transitioning from normal BMD to suspected osteoporosis was higher in the MS group after ≥ 5 years of follow-up compared with the group meeting 0 MS criteria (0.08% versus 1.15%, χ ² = 10.76, P = 0.001). There was no significant difference in BMD values for the 0 MS criteria group after 5 years ( P > 0.05), whereas the other three groups experienced a significant decrease in BMD values after 5 years ( P < 0.05). CONCLUSION MS is an independent risk factor for osteoporosis, and the effect of risk factors related to MS on osteoporosis may exceed that of aging alone. The specific mechanisms warrant further investigation.
Humans ; Osteoporosis/etiology* ; Female ; Male ; Metabolic Syndrome/complications* ; Middle Aged ; Cross-Sectional Studies ; China/epidemiology* ; Aged ; Adult ; Bone Density ; Risk Factors

OBJECTIVE: To explore the characteristics of comorbidities in patients with osteoporosis(OP) and factors associated health-related quality of life, so as to provide decision-making reference for improving the ability of disease co-prevention and co-treatment and the patient's life-cycle quality of life. METHODS: From November 2017 to July 2018, clinical information and biological samples from residents in 10 communities in Chaoyang District and Fengtai Distric of Beijing were collected, and bone density testing was conducted. Based on the Charlson comorbidity index (CCI), the comorbidity of the population was quantified, and grouped according to factors such as gender, age, and the differences between the groups were explored. Combined with the clinical information of patients, the difference characteristics of comorbidity and non-comorbidity population were analyzed. Pearson/Spearman correlation analysis and binary Logistic regression analysis were used to explore the factors affecting the health-related quality of life in patients with OP. RESULTS: Among the 521 OP patients, 121 patients had no comorbidities, and there were 153, 106, 65, and 30 patients with one, two, three, and four comorbidities, respectively, 46 patients with 5 or more kinds of comorbidites. Hypertension was the most common comorbidity in OP patients, accounting for 21.60%;followed by hyperlipidemia, accounting for 13.51%. The most common combination of the two diseases was hypertension plus hyperlipidemia (64 cases, 12.28%). Through the analysis of differences between age groups, it was found that the older patients, showed higher the CCI, and the difference between groups was statistically significant(Z=1.93, P=0.05). There were significant differences in the total EQ-5D score and the dimensions of anxiety and depression between patients with comorbidities (CCI≠0) and non-comorbidities (CCI=0) (Z=-2.67, P=0.01;Z=-2.44, P=0.02). Correlation analysis found that CCI, history of fracture, history of falls, hip bone mineral density T value and parathyroid hormone were all related to the health-related quality of life in OP patients (P<0.05). Binary Logistic regression analysis suggested that the right hip bone mineral density T value (P=0.02), CCI (P=0.01), fracture history (P=0.03) and fall history (P=0.01) were the risk factors that affect the health-related quality of life in OP patients. CONCLUSION The burden of comorbidities among middle-aged and elderly OP populations in Beijing is relatively heavy, and the health management of such populations should be further strengthened, specifically the combination of multiple comorbidities should be given high priority. Comorbid factors are of great importance for the diagnosis and treatment strategy of OP patients, which could further improve the quality of life.
Aged ; Middle Aged ; Humans ; Quality of Life ; Osteoporosis/epidemiology* ; Comorbidity ; Risk Factors ; Fractures, Bone ; Hypertension/epidemiology*

OBJECTIVE: To analyze the clinical features of overweight and obese rheumatoid arthritis (RA)patients, and the relationship between body mass index (BMI) and disease characteristics. METHODS: The demographic data, extra-articular manifestations, comorbidities, and disease activity of RA patients admitted to the Rheumatology and Immunology Department of Peking University Third Hospital from January 2015 to December 2020 were collected, and the above characteristics of overweight and obese RA patients were retrospectively analyzed. According to the WHO, BMI≥30 kg/m² referred to obese individuals, 25≤BMI < 30 kg/m² referred to overweight individuals, 18.5≤BMI < 25 kg/m² referred to normal individuals, BMI < 18.5 kg/m² referred to reduced body mass individuals. t test was used for the quantitative data in accordance with normal distribution. Wilcoxon rank sum test was used for the quantitative data of non-normal distribution. The qualitative data were analyzed by chi square test. But while 1≤theoretical frequency < 5, Chi square test of corrected four grid table was used. And Fisher exact probability method was used when theoretical frequency < 1. Analyzing whether overweight or obesity was associated with comorbidities using Logistic regression adjusted confounding factors. RESULTS: A total of 481 RA patients were included in this study, with an average BMI value of (23.28±3.75) kg/m².Of the patients, 31 cases (6.5%) were with BMI < 18.5 kg/m², 309 cases (64.2%) with 18.5≤ BMI < 25 kg/m², amounting to 340 cases (70.7%). There were 119 overweight individuals (25≤ BMI < 30 kg/m², 24.7%) and 22 obese individuals (BMI≥30 kg/m², 4.6%), totaling 141 (29.3%).The proportion of the overweight and obese RA patients suffering from hypertension (57.4% vs. 39.1%, P < 0.001), diabetes (25.5% vs. 15.0%, P=0.006), hyperlipidemia (22.7% vs. 10.9%, P=0.001), fatty liver (28.4% vs. 7.4%, P < 0.001), osteoarthritis (39.0% vs. 29.4%, P=0.040) was significantly higher, and the proportion of the patients with osteoporosis(59.6% vs. 70.9%, P=0.016) and anemia (36.2% vs. 55.6%, P < 0.001) was significantly lower. However, there was no difference between the two groups in coronary heart disease (5.7% vs. 7.6%, P=0.442), cerebrovascular disease (6.4% vs. 8.8%, P=0.372) and peripheral atherosclerosis (9.2% vs. 7.6%, P=0.565).The median C-reactive protein (CRP, 1.52 mg/dL vs. 2.35 mg/dL, P=0.008), median erythrocyte sedimentation rate (ESR, 34.0 mm/h vs. 50.0 mm/h, P=0.003), pain visual simulation score (VAS) (3.66±3.08 vs. 4.40±2.85, P=0.011), and 28 joint disease activity scores (DAS-28, 5.05±1.60 vs. 5.45±1.52, P=0.010) in the overweight and obese RA group were all lower than those in the normal and reduced weight groups. Multivariate regression analysis showed that overweight and obesity was an independent risk factor for hypertension, diabetes, hyperlipidemia and fatty liver, and had protective effects on osteoporosis and anemia. CONCLUSION In RA patients, RA disease activity is lower in overweight and obesity patients. Overweight and obesity is associated with hypertension, diabetes and hyperlipidemia, but not with cardiovascular and cerebrovascular diseases.
Humans ; Body Mass Index ; Overweight/epidemiology* ; Retrospective Studies ; Arthritis, Rheumatoid/epidemiology* ; Obesity/epidemiology* ; Diabetes Mellitus ; Hypertension/complications* ; Fatty Liver/complications* ; Hyperlipidemias/complications* ; Osteoporosis/complications* ; Anemia

Objective: To understand the prevalence of osteoporosis and related factors in postmenopausal women aged ≥40 years in China and provide scientific evidence for osteoporosis prevention and control. Methods: Data of this study were from the 2018 China Osteoporosis Epidemiological Survey, covering 44 counties (districts) in 11 provinces in China. Related variables were collected by questionnaire survey and physical measurement, and the BMD of lumbar spine and proximal femur was measured by dual-energy X-ray absorption method. The prevalence of osteoporosis and its 95%CI in postmenopausal women aged ≥40 years were estimated with complex sampling weights. Results: A total of 5 728 postmenopausal women aged ≥40 years were included in the analysis and the prevalence of osteoporosis was 32.5% (95%CI: 30.3%-34.7%). The prevalence of osteoporosis in postmenopausal women aged 40-49 years, 50-59 years, 60-69 years, 70-79 years, and ≥80 years were 16.0% (95%CI:4.5%-27.5%), 18.4% (95%CI:15.9%-20.8%), 37.5% (95%CI:34.5%-40.4%), 52.9% (95%CI: 47.5%-58.3%), and 68.0% (95%CI:55.9%-80.1%) respectively. The prevalence of osteoporosis was higher (P<0.001) in those with education level of primary school or below (47.2%, 95%CI: 43.0%-51.3%) and in those with individual annual income less than 10 000 Yuan, (40.3%, 95%CI: 36.9%-43.7%). The prevalence of osteoporosis was 35.1% in rural areas (95%CI: 32.0%-38.1%), which was higher than that in urban areas (P<0.001). The prevalence of osteoporosis in low weight, normal weight, overweight and obese groups were 69.9% (95%CI: 59.0%-80.8%), 42.2% (95%CI: 38.7%-45.7%), 24.2% (95%CI: 21.3%-27.1%) and 14.6% (95%CI: 11.1%-18.0%), respectively. The prevalence of osteoporosis in those with menstrual maintenance years ≤30 years and in those with menopause years ≥11 years were 46.1% (95%CI:40.8%-51.3%) and 48.2% (95%CI:45.0%-51.3%), respectively. Multivariate logistic analysis showed that age ≥60 years, education level of primary school or below, annual household income per capita less than 10 000 Yuan, low body weight, menstrual maintenance years ≤30 years, menopause years ≥11 years were risk factors of osteoporosis in postmenopausal women in China. Conclusions: The prevalence of osteoporosis was high in postmenopausal women aged ≥40 years in China, and there were differences in osteoporosis prevalence among different socioeconomic groups. Effective interventions should be taken for the prevention and control of osteoporosis in key groups in the future.
Absorptiometry, Photon ; Bone Density ; China/epidemiology* ; Female ; Humans ; Lumbar Vertebrae ; Osteoporosis/epidemiology* ; Osteoporosis, Postmenopausal/etiology* ; Postmenopause ; Prevalence ; Risk Factors