北京地区近10年骨质疏松症流行病学调查：一项单中心30 599例汉族人群双能X线吸收法骨密度检查结果分析

doi:10.12122/j.issn.1673-4254.2025.03.01

南方医科大学学报 ›› 2025, Vol. 45 ›› Issue (3): 443-452.doi: 10.12122/j.issn.1673-4254.2025.03.01

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北京地区近10年骨质疏松症流行病学调查：一项单中心30 599例汉族人群双能X线吸收法骨密度检查结果分析

周莹¹(), 张丹阳², 吴立凡³, 王桂杉¹, 母杰丹¹, 崔成文¹, 石秀秀¹, 董继革⁴, 王瑜², 许王莉², 李晓¹()

^1.中国人民解放军总医院第四医学中心骨科医学部康复医学科，国家骨科与运动康复临床医学研究中心，北京 100048
^2.中国人民大学统计科学研究中心，中国人民大学统计学院，北京 100872
^3.天津体育学院运动康复学院，天津 301617
^4.中国中医科学院望京医院康复治疗中心，北京 100102

收稿日期:2024-11-28 出版日期:2025-03-20 发布日期:2025-03-28
通讯作者: 李晓 E-mail:zhouying1018atnm@sina.com;lixiaoPLA@163.com
作者简介:周莹，硕士，E-mail: zhouying1018atnm@sina.com
基金资助:
国家重点研发项目(2023YFC3604905)

Epidemiological survey of osteoporosis in Beijing over the past decade: a single-center analysis of dual-energy X-ray absorptiometry scans from 30 599 individuals

Ying ZHOU¹(), Danyang ZHANG², Lifan WU³, Guishan WANG¹, Jiedan MU¹, Chengwen CUI¹, Xiuxiu SHI¹, Jige DONG⁴, Yu WANG², Wangli XU², Xiao LI¹()

^1.Department of Rehabilitation Medicine, Senior Department of Orthopedics, Fourth Medical Center of PLA General Hospital, National Clinical Research Center for Orthopedics, Sports Medicine & Rehabilitation, Beijing 100048, China
^2.Research Center for Statistical Science, School of Statistics, Renmin University of China, Beijing 100872, China
^3.School of Sports Rehabilitation, Tianjin University of Physical Education, Tianjin 301617, China
^4.Rehabilitation Center, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing 100102, China

Received:2024-11-28 Online:2025-03-20 Published:2025-03-28
Contact: Xiao LI E-mail:zhouying1018atnm@sina.com;lixiaoPLA@163.com

摘要/Abstract

摘要：

目的分析本中心DXA检查人群骨量分布及骨量的影响因素。方法收集2013年7月~2023年7月在本院行双能X线吸收法（DXA）骨密度检查的30 599例20岁以上汉族人群的骨密度结果，并收集其身高、体质量和性别等一般信息，使用R语言软件进行描述性和相关性统计学分析。结果本中心男性腰椎、股骨颈和全髋的骨量峰值分别为1.00±0.12 g/cm²、0.94±0.14 g/cm²、0.99±0.13 g/cm²，女性分别为0.99±0.12 g/cm²、0.79±0.11 g/cm²、0.88±0.11 g/cm²，男性显著高于女性（腰椎P=0.022，股骨颈P<0.001，全髋P<0.001）；成年男性和女性腰椎、股骨骨密度（BMD）值在达到峰值后随着年龄增长而降低；男性和女性各个部位BMD值与体质量指数（BMI）之间存在正向相关关系；2013~2014年男性和女性患者腰椎、髋部、股骨颈BMD值均为近10年最低值，2015~2023年男性和女性患者腰椎、髋部、股骨颈BMD值呈上升趋势。结论不同人群的BMD值存在差异。未来需要采用更精准的BMD检测技术，开展多中心有代表性人群的临床研究，以探索人群BMD值随人口统计学的变化特征。

关键词: 骨密度, 骨质疏松, 双能X射线吸收, 流行病学

Abstract:

Objective 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). Conclusion 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.

Key words: bone mineral density, osteoporosis, dual-energy X-ray, epidemiology

周莹, 张丹阳, 吴立凡, 王桂杉, 母杰丹, 崔成文, 石秀秀, 董继革, 王瑜, 许王莉, 李晓. 北京地区近10年骨质疏松症流行病学调查：一项单中心30 599例汉族人群双能X线吸收法骨密度检查结果分析[J]. 南方医科大学学报, 2025, 45(3): 443-452.

Ying ZHOU, Danyang ZHANG, Lifan WU, Guishan WANG, Jiedan MU, Chengwen CUI, Xiuxiu SHI, Jige DONG, Yu WANG, Wangli XU, Xiao LI. Epidemiological survey of osteoporosis in Beijing over the past decade: a single-center analysis of dual-energy X-ray absorptiometry scans from 30 599 individuals[J]. Journal of Southern Medical University, 2025, 45(3): 443-452.

图/表 12

参考文献 40

1	Alejandro P, Constantinescu F. A review of osteoporosis in the older adult[J]. Rheum Dis Clin N Am, 2018, 44(3): 437-51.
2	Willers C, Norton N, Harvey NC, et al. Osteoporosis in Europe: a compendium of country-specific reports[J]. Arch Osteoporos, 2022, 17(1): 23.
3	Chen ZN, Wen Y, Qiu ML, et al. The pattern and trends of disease burden due to low bone mineral density from 1990 to 2019 in China: findings from the Global Burden of Disease Study 2019[J]. Arch Osteoporos, 2022, 17(1): 39.
4	Dong YM, Kang HL, Peng RP, et al. Global, regional, and national burden of low bone mineral density from 1990 to 2019: results from the global burden of disease study 2019[J]. Front Endocrinol, 2022, 13: 870905.
5	Fuggle NR, Beaudart C, Bruyère O, et al. Evidence-Based Guideline for the management of osteoporosis in men[J]. Nat Rev Rheumatol, 2024, 20(4): 241-51.
6	Ensrud KE, Crandall CJ. Osteoporosis[J]. Ann Intern Med, 2024, 177(1): ITC1-ITC16.
7	Wáng YXJ. Estimation of osteoporosis prevalence among a population is reasonable only after the concerned reference bone mineral density database and cutpoint T-score have been validated[J]. Osteoporos Int, 2023, 34(2): 417-8.
8	王亮, 马远征, 张妍, 等. 北京地区9103例体检人群骨密度流行病学调查研究[J]. 中国骨质疏松杂志, 2014, 20(8): 952-5.
9	罗薇, 刘珍, 刘海丹, 等. 北京地区3859名体检人群骨密度调查及骨量异常患病率分析[J]. 中国骨质疏松杂志, 2020, 26(5): 719-22.
10	张娅惠, 薛秋艳, 谷洁, 等. 北京海淀部分人群骨质疏松流行病学及相关危险因素研究[J]. 现代生物医学进展, 2020, 20(13): 2545-50.
11	刘宁, 张国强, 兰雅智. 北京某社区60岁以上老年人群骨质疏松症发病特点及影响因素分析[J]. 中国骨与关节损伤杂志, 2022, 37(12): 1327-30.
12	Cui P, Wang W, Wang Z, et al. The association between body mass index and bone mineral density in older adults: a cross-sectional study of community population in Beijing[J]. BMC Musculoskelet Disord, 2024, 25(1): 655.
13	姚立彬, 张林华, 李百战, 等. 邢台山区老年人骨质疏松症流行病学调查及危险因素分析[J]. 解放军预防医学杂志, 2020, 38(2): 58-60.
14	Canbek U, Rosberg DBH, Rosberg HE, et al. The effect of age, BMI, and bone mineral density on the various lumbar vertebral measurements in females[J]. Surg Radiol Anat, 2021, 43(1): 101-8.
15	Zeng Q, Li N, Wang QQ, et al. The prevalence of osteoporosis in China, a nationwide, multicenter DXA survey[J]. J Bone Miner Res, 2019, 34(10): 1789-97.
16	Cherukuri L, Kinninger A, Birudaraju D, et al. Effect of body mass index on bone mineral density is age-specific[J]. Nutr Metab Cardiovasc Dis, 2021, 31(6): 1767-73.
17	Eghbali P, Becce F, Goetti P, et al. Age- and sex-specific normative values of bone mineral density in the adult glenoid[J]. J Orthop Res, 2023, 41(2): 263-70.
18	中华人民共和国国家卫生健康委员会医政司. 肥胖症中国诊疗指南(2024年版) [J/OL]. 协和医学杂志, 1-60[2025-01-09].
19	中华医学会骨质疏松和骨矿盐疾病分会. 原发性骨质疏松症诊疗指南(2022)[J]. 中华骨质疏松和骨矿盐疾病杂志, 2022, 15(6): 573-611.
20	Tang YC, Peng B, Liu JM, et al. Systemic immune-inflammation index and bone mineral density in postmenopausal women: a cross-sectional study of the national health and nutrition examination survey (NHANES) 2007-2018[J]. Front Immunol, 2022, 13: 975400.
21	Kojima A, Kamiya K, Kajita E, et al. Association between dairy product intake and risk of osteoporotic fractures in postmenopausal Japanese women: secondary analysis of 15-year follow-up data from the Japanese population-based osteoporosis (JPOS) cohort study[J]. J Nutr Health Aging, 2023, 27(3): 228-37.
22	Wang LH, Yu W, Yin XJ, et al. Prevalence of osteoporosis and fracture in China: the China osteoporosis prevalence study[J]. JAMA Netw Open, 2021, 4(8): e2121106.
23	Schultz K, Wolf JM. Emerging technologies in osteoporosis diagnosis[J]. J Hand Surg Am, 2019, 44(3): 240-3.
24	Ichchou L, Allali F, Rostom S, et al. Relationship between spine osteoarthritis, bone mineral density and bone turn over markers in post menopausal women[J]. BMC Womens Health, 2010, 10: 25.
25	Yoshimura N, Iidaka T, Horii C, et al. Trends in osteoporosis prevalence over a 10-year period in Japan: the ROAD study 2005-2015[J]. J Bone Miner Metab, 2022, 40(5): 829-38.
26	Rathnayake H, Lekamwasam S, Wickramatilake C, et al. Trabecular bone score and bone mineral density reference data for women aged 20-70 years and the effect of local reference data on the prevalence of postmenopausal osteoporosis: a cross-sectional study from Sri Lanka [J]. Arch Osteoporos, 2019, 14(1): 91.
27	Wáng YXJ, Chan WP, Yu W, et al. Quantitative CT lumbar spine BMD cutpoint value for classifying osteoporosis among older Chinese men can be the same as that of older Chinese women, both much lower than the value for Caucasians[J]. Skeletal Radiol, 2025, 54(2): 193-8.
28	Lloyd JT, Alley DE, Hawkes WG, et al. Body mass index is positively associated with bone mineral density in US older adults[J]. Arch Osteoporos, 2014, 9: 175.
29	Glinkowski WM, Narloch J. Bone Density at the Entry Point Correlates With the Trabecular Bone of the Thoracolumbar Vertebral Bodies-Quantitative Computed Tomography Study[J]. Clin Densitom, 2019, 22(3): 367-73.
30	Ng AC, Joseph Melton L 3rd, Atkinson EJ, et al. Relationship of adiposity to bone volumetric density and microstructure in men and women across the adult lifespan[J]. Bone, 2013, 55(1): 119-25.
31	Wang LJ, You XL, Zhang LL, et al. Mechanical regulation of bone remodeling[J]. Bone Res, 2022, 10(1): 16.
32	Farley A, Gnyubkin V, Vanden-Bossche A, et al. Unloading-induced cortical bone loss is exacerbated by low-dose irradiation during a simulated deep space exploration mission[J]. Calcif Tissue Int, 2020, 107(2): 170-9.
33	Agostini F, de Sire A, Sveva V, et al. Rehabilitative good clinical practice in the treatment of osteoporosis: a comprehensive review of clinical evidences[J]. Disabil Rehabil, 2024: 1-15.
34	Izquierdo M, de Souto Barreto P, Arai H, et al. Global consensus on optimal exercise recommendations for enhancing healthy longevity in older adults (ICFSR)[J]. J Nutr Health Aging, 2025, 29(1): 100401.
35	Chen P, Li ZZ, Hu YH. Prevalence of osteoporosis in China: a meta-analysis and systematic review[J]. BMC Public Health, 2016, 16(1): 1039.
36	Qian Y, Mao JC. The association between night shift work and osteoporosis risk in adults: a cross-sectional analysis using NHANES[J]. Heliyon, 2024, 10(6): e28240.
37	Rubæk M, Hitz MF, Holmberg T, et al. Effectiveness of patient education for patients with osteoporosis: a systematic review[J]. Osteoporos Int, 2022, 33(5): 959-77.
38	Hejazi K, Askari R, Hofmeister M. Effects of physical exercise on bone mineral density in older postmenopausal women: a systematic review and meta-analysis of randomized controlled trials[J]. Arch Osteoporos, 2022, 17(1): 102.
39	黄宏兴, 晁爱军, 程群.中国健康促进基金会医疗机构骨质疏松专科建设专家共识委员会.医疗机构骨质疏松专科建设专家共识[J].中国骨质疏松杂志, 2024, 30(6): 781-9.
40	刘功稳, 朱柯雨, 陆政峰.骨质疏松症和骨质疏松性骨折防治的现状及挑战[J]. 中华骨质疏松和骨矿盐疾病杂志, 2024, 17(5): 409-18.

Characteristic	Total (n=30 599)	Men (n=11 228)	Women (n=19 371)	P
Age [year, n (%)]				<0.001
≤19	83 (0.3%)	48 (0.4%)	35 (0.2%)
20-24	663 (2.2%)	503 (4.5%)	160 (0.8%)
25-29	851 (2.8%)	546 (4.9%)	305 (1.6%)
30-34	1001 (3.3%)	553 (4.9%)	448 (2.3%)
35-39	1112 (3.6%)	522 (4.6%)	590 (3.0%)
40-44	1524 (5.0%)	619 (5.5%)	905 (4.7%)
45-49	2,403 (7.9%)	876 (7.8%)	1527 (7.9%)
50-54	3828 (13.0%)	1175 (10.0%)	2653 (14.0%)
55-59	4157 (14.0%)	1206 (11.0%)	2951 (15.0%)
60-64	4319 (14.0%)	1370 (12.0%)	2949 (15.0%)
65-69	3680 (12.0%)	1218 (11.0%)	2462 (13.0%)
70-74	2768 (9.0%)	951 (8.5%)	1817 (9.4%)
75-79	2227 (7.3%)	780 (6.9%)	1447 (7.5%)
≥80	1983 (6.5%)	861 (7.7%)	1122 (5.8%)
BMI^# [kg/m², n (%)]				<0.001
<18.5	1073 (3.5%)	272 (2.4%)	801 (4.2%)
18.5-23.9	13 545 (45%)	4244 (38%)	9301 (48%)
24-27.9	11 539 (38%)	4807 (43%)	6732 (35%)
≥28	4174 (14%)	1803 (16%)	2371 (12%)
Year of BMD measurement				<0.001
2013	2633 (8.6%)	724 (6.4%)	1909 (9.9%)
2014	4041 (13%)	1307 (12%)	2734 (14%)
2015	3018 (9.9%)	1017 (9.1%)	2001 (10%)
2016	3073 (10%)	1145 (10%)	1928 (10.0%)
2017	2817 (9.2%)	1130 (10%)	1687 (8.7%)
2018	2715 (8.9%)	1000 (8.9%)	1715 (8.9%)
2019	2503 (8.2%)	944 (8.4%)	1559 (8.0%)
2020	1102 (3.6%)	410 (3.7%)	692 (3.6%)
2021	3488 (11%)	1432 (13%)	2056 (11%)
2022	3048 (10.0%)	1212 (11%)	1836 (9.5%)
2023	2161 (7.1%)	907 (8.1%)	1254 (6.5%)

Characteristic	Total (n=30 599)	Men (n=11 228)	Women (n=19 371)	P
Age [year, n (%)]				<0.001
≤19	83 (0.3%)	48 (0.4%)	35 (0.2%)
20-24	663 (2.2%)	503 (4.5%)	160 (0.8%)
25-29	851 (2.8%)	546 (4.9%)	305 (1.6%)
30-34	1001 (3.3%)	553 (4.9%)	448 (2.3%)
35-39	1112 (3.6%)	522 (4.6%)	590 (3.0%)
40-44	1524 (5.0%)	619 (5.5%)	905 (4.7%)
45-49	2,403 (7.9%)	876 (7.8%)	1527 (7.9%)
50-54	3828 (13.0%)	1175 (10.0%)	2653 (14.0%)
55-59	4157 (14.0%)	1206 (11.0%)	2951 (15.0%)
60-64	4319 (14.0%)	1370 (12.0%)	2949 (15.0%)
65-69	3680 (12.0%)	1218 (11.0%)	2462 (13.0%)
70-74	2768 (9.0%)	951 (8.5%)	1817 (9.4%)
75-79	2227 (7.3%)	780 (6.9%)	1447 (7.5%)
≥80	1983 (6.5%)	861 (7.7%)	1122 (5.8%)
BMI^# [kg/m², n (%)]				<0.001
<18.5	1073 (3.5%)	272 (2.4%)	801 (4.2%)
18.5-23.9	13 545 (45%)	4244 (38%)	9301 (48%)
24-27.9	11 539 (38%)	4807 (43%)	6732 (35%)
≥28	4174 (14%)	1803 (16%)	2371 (12%)
Year of BMD measurement				<0.001
2013	2633 (8.6%)	724 (6.4%)	1909 (9.9%)
2014	4041 (13%)	1307 (12%)	2734 (14%)
2015	3018 (9.9%)	1017 (9.1%)	2001 (10%)
2016	3073 (10%)	1145 (10%)	1928 (10.0%)
2017	2817 (9.2%)	1130 (10%)	1687 (8.7%)
2018	2715 (8.9%)	1000 (8.9%)	1715 (8.9%)
2019	2503 (8.2%)	944 (8.4%)	1559 (8.0%)
2020	1102 (3.6%)	410 (3.7%)	692 (3.6%)
2021	3488 (11%)	1432 (13%)	2056 (11%)
2022	3048 (10.0%)	1212 (11%)	1836 (9.5%)
2023	2161 (7.1%)	907 (8.1%)	1254 (6.5%)

Age group (year)	BMI (kg/m²)	Lumbar spine 1-4 BMD (g/cm²)	Total femur BMD (g/cm²)	Femoral neck BMD (g/cm²)
≤19	21.42±3.45	0.90±0.15	0.86±0.17	0.79±0.16
20-24	22.69±3.42	0.98±0.11	0.96±0.14	0.90±0.15
25-29	22.84±3.66	0.99±0.12	0.94±0.15	0.87±0.15
30-34	23.63±3.82	0.98±0.12	0.91±0.13	0.83±0.13
35-39	24.00±3.85	0.99±0.12	0.90±0.12	0.81±0.13
40-44	24.26±3.59	0.99±0.12	0.90±0.12	0.80±0.12
45-49	24.42±3.45	0.98±0.14	0.90±0.13	0.79±0.12
50-54	24.47±3.41	0.95±0.14	0.87±0.13	0.76±0.12
55-59	24.60±3.38	0.90±0.15	0.84±0.13	0.73±0.12
60-64	24.55±3.31	0.89±0.16	0.82±0.13	0.70±0.12
65-69	24.73±3.34	0.88±0.18	0.80±0.14	0.69±0.13
70-74	24.52±3.45	0.88±0.19	0.78±0.14	0.66±0.12
75-79	24.00±3.42	0.88±0.19	0.75±0.14	0.63±0.13
≥80	23.50±3.36	0.91±0.21	0.74±0.15	0.62±0.13

Age group (year)	BMI (kg/m²)	Lumbar spine 1-4 BMD (g/cm²)	Total femur BMD (g/cm²)	Femoral neck BMD (g/cm²)
≤19	21.42±3.45	0.90±0.15	0.86±0.17	0.79±0.16
20-24	22.69±3.42	0.98±0.11	0.96±0.14	0.90±0.15
25-29	22.84±3.66	0.99±0.12	0.94±0.15	0.87±0.15
30-34	23.63±3.82	0.98±0.12	0.91±0.13	0.83±0.13
35-39	24.00±3.85	0.99±0.12	0.90±0.12	0.81±0.13
40-44	24.26±3.59	0.99±0.12	0.90±0.12	0.80±0.12
45-49	24.42±3.45	0.98±0.14	0.90±0.13	0.79±0.12
50-54	24.47±3.41	0.95±0.14	0.87±0.13	0.76±0.12
55-59	24.60±3.38	0.90±0.15	0.84±0.13	0.73±0.12
60-64	24.55±3.31	0.89±0.16	0.82±0.13	0.70±0.12
65-69	24.73±3.34	0.88±0.18	0.80±0.14	0.69±0.13
70-74	24.52±3.45	0.88±0.19	0.78±0.14	0.66±0.12
75-79	24.00±3.42	0.88±0.19	0.75±0.14	0.63±0.13
≥80	23.50±3.36	0.91±0.21	0.74±0.15	0.62±0.13

Age group (year)	BMI (kg/m²)	Lumbar spine 1-4 BMD (g/cm²)	Total femur BMD (g/cm²)	Femoral neck BMD (g/cm²)
≤19	21.72±3.62	0.89±0.16	0.88±0.20	0.80±0.19
20-24	23.21±3.28	0.98±0.12	0.99±0.13	0.94±0.14
25-29	23.80±3.38	1.00±0.12	0.98±0.15	0.91±0.15
30-34	24.96±3.50	0.99±0.12	0.95±0.12	0.87±0.12
35-39	25.57±3.76	0.99±0.13	0.94±0.13	0.86±0.13
40-44	25.64±3.42	0.98±0.14	0.93±0.13	0.83±0.13
45-49	25.85±3.42	0.97±0.14	0.92±0.13	0.82±0.12
50-54	25.51±3.43	0.98±0.15	0.91±0.13	0.80±0.12
55-59	25.41±3.26	0.97±0.15	0.91±0.13	0.79±0.12
60-64	25.03±3.13	0.98±0.16	0.90±0.13	0.78±0.12
65-69	24.97±3.08	1.00±0.17	0.90±0.13	0.77±0.12
70-74	24.61±3.12	1.00±0.18	0.88±0.13	0.74±0.12
75-79	23.80±3.14	1.01±0.18	0.86±0.13	0.72±0.13
≥80	23.53±3.14	1.03±0.20	0.83±0.14	0.70±0.12

北京地区近10年骨质疏松症流行病学调查：一项单中心30 599例汉族人群双能X线吸收法骨密度检查结果分析

Epidemiological survey of osteoporosis in Beijing over the past decade: a single-center analysis of dual-energy X-ray absorptiometry scans from 30 599 individuals

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Age group (year)	BMI (kg/m²)	Lumbar spine 1-4 BMD (g/cm²)	Total femur BMD (g/cm²)	Femoral neck BMD (g/cm²)
≤19	21.02±3.21	0.92±0.13	0.84±0.13	0.78±0.12
20-24	21.04±3.35	0.96±0.11	0.87±0.11	0.79±0.11
25-29	21.13±3.52	0.97±0.11	0.86±0.11	0.78±0.10
30-34	22.00±3.57	0.98±0.12	0.86±0.12	0.77±0.12
35-39	22.61±3.36	0.99±0.12	0.87±0.11	0.77±0.10
40-44	23.31±3.39	0.99±0.12	0.88±0.11	0.78±0.11
45-49	23.60±3.20	0.98±0.13	0.88±0.12	0.77±0.12
50-54	24.01±3.30	0.94±0.14	0.86±0.12	0.75±0.11
55-59	24.27±3.37	0.87±0.14	0.81±0.12	0.70±0.11
60-64	24.33±3.36	0.84±0.13	0.78±0.11	0.67±0.10
65-69	24.61±3.46	0.82±0.15	0.75±0.12	0.64±0.10
70-74	24.48±3.60	0.82±0.15	0.73±0.12	0.61±0.10
75-79	24.11±3.56	0.81±0.15	0.70±0.12	0.58±0.10
≥80	23.48±3.51	0.83±0.16	0.66±0.12	0.56±0.10

BMI (kg/m²)	Lumbar spine 1-4 BMD (g/cm²)	Total femur BMD (g/cm²)	Femoral neck BMD (g/cm²)
Men
<18.5	0.76±0.13	0.87±0.16	0.67±0.13
18.5-23.9	0.87±0.13	0.96±0.15	0.77±0.14
24-27.9	0.92±0.13	1.01±0.15	0.81±0.13
≥28	0.97±0.13	1.05±0.16	0.85±0.13
Women
<18.5	0.69±0.14	0.79±0.16	0.61±0.13
18.5-23.9	0.77±0.13	0.86±0.15	0.67±0.12
24-27.9	0.81±0.13	0.90±0.15	0.70±0.12
≥28	0.85±0.13	0.94±0.15	0.73±0.13

Variables	Total femur			Femoral neck			Lumbar spine 1-4
Variables	β	SE	P	β	SE	P	β	SE	P
Women
Age groups (year)
20-24	0.025	0.021	0.238	0.014	0.019	0.487	0.026	0.025	0.295
25-29	0.001	0.020	0.955	-0.016	0.019	0.405	0.014	0.024	0.557
30-34	-0.026	0.020	0.183	-0.038	0.018	0.040	0.000	0.024	0.991
35-39	-0.038	0.020	0.051	-0.054	0.018	0.003	-0.017	0.024	0.459
40-44	-0.045	0.020	0.022	-0.065	0.018	<0.001	-0.041	0.024	0.078
45-49	-0.054	0.020	0.006	-0.071	0.018	<0.001	-0.057	0.024	0.015
50-54	-0.078	0.020	<0.001	-0.096	0.019	<0.001	-0.097	0.024	<0.001
55-59	-0.128	0.020	<0.001	-0.140	0.019	<0.001	-0.159	0.024	<0.001
60-64	-0.176	0.020	<0.001	-0.186	0.019	<0.001	-0.214	0.025	<0.001
65-69	-0.224	0.021	<0.001	-0.228	0.019	<0.001	-0.257	0.025	<0.001
70-74	-0.264	0.021	<0.001	-0.265	0.020	<0.001	-0.280	0.026	<0.001
75-79	-0.305	0.022	<0.001	-0.304	0.020	<0.001	-0.307	0.026	<0.001
≥80	-0.347	0.022	<0.001	-0.337	0.021	<0.001	-0.309	0.027	<0.001
BMI (kg/m²)
18.5-23.9	0.046	0.004	<0.001	0.038	0.004	<0.001	0.035	0.005	<0.001
24-27.9	0.070	0.006	<0.001	0.061	0.005	<0.001	0.043	0.007	<0.001
≥28	0.071	0.008	<0.001	0.064	0.007	<0.001	0.039	0.010	<0.001
Age×BMI	0.000	0.000	<0.001	0.000	0.000	<0.001	0.000	0.000	<0.001
Menopause	-0.051	0.003	<0.001	-0.044	0.003	<0.001	-0.082	0.004	<0.001
Men
Age groups (year)
20-24	0.082	0.019	<0.001	0.108	0.019	<0.001	0.061	0.023	0.008
25-29	0.054	0.019	0.005	0.070	0.019	<0.001	0.053	0.023	0.020
30-34	-0.005	0.019	0.816	0.005	0.019	0.799	0.000	0.023	0.996
35-39	-0.035	0.020	0.074	-0.029	0.019	0.129	-0.030	0.023	0.201
40-44	-0.074	0.020	<0.001	-0.071	0.019	<0.001	-0.068	0.024	0.004
45-49	-0.104	0.020	<0.001	-0.102	0.020	<0.001	-0.105	0.024	<0.001
50-54	-0.126	0.021	<0.001	-0.125	0.020	<0.001	-0.125	0.025	<0.001
55-59	-0.149	0.021	<0.001	-0.153	0.021	<0.001	-0.160	0.025	<0.001
60-64	-0.169	0.022	<0.001	-0.169	0.021	<0.001	-0.163	0.026	<0.001
65-69	-0.191	0.023	<0.001	-0.191	0.022	<0.001	-0.173	0.027	<0.001
70-74	-0.222	0.023	<0.001	-0.233	0.023	<0.001	-0.190	0.028	<0.001
75-79	-0.249	0.024	<0.001	-0.257	0.023	<0.001	-0.196	0.029	<0.001
≥80	-0.292	0.025	<0.001	-0.293	0.024	<0.001	-0.205	0.030	<0.001
BMI (kg/m²)
18.5-23.9	0.070	0.009	<0.001	0.063	0.008	<0.001	0.039	0.010	<0.001
24-27.9	0.098	0.010	<0.001	0.090	0.010	<0.001	0.047	0.012	<0.001
≥28	0.092	0.013	<0.001	0.088	0.012	<0.001	0.037	0.015	0.015
Age×BMI	0.000	0.000	<0.001	0.000	0.000	<0.001	0.000	0.000	<0.001

BMD	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
n	2633	4041	3018	3073	2817	2715	2503	1102	3488	3048	2161
Lumbar spine 1-4 BMD(g/cm²)	0.89±0.16	0.92±0.16	0.92±0.16	0.93±0.16	0.93±0.16	0.92±0.17	0.93±0.17	0.93±0.16	0.93±0.17	0.93±0.17	0.93±0.17
Total femur BMD(g/cm²)	0.82±0.14	0.82±0.14	0.83±0.14	0.85±0.15	0.84±0.15	0.82±0.15	0.83±0.15	0.84±0.15	0.84±0.15	0.86±0.15	0.85±0.15
Femoral neck BMD(g/cm²)	0.70±0.13	0.71±0.13	0.72±0.14	0.73±0.14	0.73±0.14	0.73±0.14	0.74±0.14	0.73±0.15	0.73±0.15	0.75±0.16	0.74±0.15

Variables	Lumbar spine 1-4		Femoral neck		Total femur
Variables	Age group (year)	BMD value	Age group (year)	BMD value	Age group (year)	BMD value
Men	25-29	1.00±0.12	20-24	0.94±0.14	20-24	0.99±0.13
Women	40-44	0.99±0.12	40-44	0.79±0.11	20-24	0.88±0.11
P		0.022		<0.001		<0.001

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Year of Measure-ment	Prevalence of osteoporosis						Prevalence of osteopenia
	Men		Women		All		Men		Women		All
	n	%	n	%	n	%	n	%	n	%	n	%
2013	138	19.38%	709	37.47%	847	32.53%	545	76.54%	1570	82.98%	2115	81.22%
2014	222	17.24%	886	32.83%	1108	27.79%	941	73.06%	2158	79.96%	3099	77.73%
2015	159	15.88%	640	32.54%	799	26.92%	717	71.63%	1563	79.46%	2280	76.82%
2016	162	14.25%	603	31.52%	765	25.08%	798	70.18%	1520	79.46%	2318	76.00%
2017	172	15.33%	523	31.19%	695	24.83%	792	70.59%	1300	77.52%	2092	74.74%
2018	161	16.16%	560	32.88%	721	26.71%	715	71.79%	1358	79.74%	2073	76.81%
2019	156	16.58%	481	30.93%	637	25.52%	642	68.23%	1198	77.04%	1840	73.72%
2020	70	17.11%	210	30.48%	280	25.50%	271	66.26%	549	79.68%	820	74.68%
2021	209	14.76%	701	34.50%	910	26.39%	980	69.21%	1643	80.86%	2623	76.07%
2022	149	12.42%	638	34.86%	787	25.97%	755	62.92%	1445	78.96%	2200	72.61%
2023	119	13.16%	443	35.50%	562	26.12%	583	64.49%	1006	80.61%	1589	73.84%

Year of Measure-ment	Prevalence of osteoporosis						Prevalence of osteopenia
	Men		Women		All		Men		Women		All
	n	%	n	%	n	%	n	%	n	%	n	%
2013	138	19.38%	709	37.47%	847	32.53%	545	76.54%	1570	82.98%	2115	81.22%
2014	222	17.24%	886	32.83%	1108	27.79%	941	73.06%	2158	79.96%	3099	77.73%
2015	159	15.88%	640	32.54%	799	26.92%	717	71.63%	1563	79.46%	2280	76.82%
2016	162	14.25%	603	31.52%	765	25.08%	798	70.18%	1520	79.46%	2318	76.00%
2017	172	15.33%	523	31.19%	695	24.83%	792	70.59%	1300	77.52%	2092	74.74%
2018	161	16.16%	560	32.88%	721	26.71%	715	71.79%	1358	79.74%	2073	76.81%
2019	156	16.58%	481	30.93%	637	25.52%	642	68.23%	1198	77.04%	1840	73.72%
2020	70	17.11%	210	30.48%	280	25.50%	271	66.26%	549	79.68%	820	74.68%
2021	209	14.76%	701	34.50%	910	26.39%	980	69.21%	1643	80.86%	2623	76.07%
2022	149	12.42%	638	34.86%	787	25.97%	755	62.92%	1445	78.96%	2200	72.61%
2023	119	13.16%	443	35.50%	562	26.12%	583	64.49%	1006	80.61%	1589	73.84%