Government-Implemented Population Osteoporosis Screening in Rural China: Achieving Universal Coverage with Portable DXA

Government-Implemented Population Osteoporosis Screening in Rural China: Achieving Universal Coverage with Portable DXA | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Government-Implemented Population Osteoporosis Screening in Rural China: Achieving Universal Coverage with Portable DXA Wenting Zhao, Qiong Wu, Qin Liu, Bin Huang, Ying Xiao, Fangfang Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7161500/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Oct, 2025 Read the published version in BMC Geriatrics → Version 1 posted 11 You are reading this latest preprint version Abstract Background​​: China's aging rural population faces a 30% prevalence of osteoporosis (OP), yet screening gaps persist owing to limited DXA access (<1 unit/100,000 older adults). Quantitative ultrasound (QUS) has poor sensitivity (<60%) and selection bias. This study evaluated a novel government-executed model using portable DXA (pDXA) for universal coverage. ​​ Methods​​: A cross-sectional study (2021) enrolled ​​all​​ eligible permanent residents ≥60 years (N=3,530) in Tongcun Community, Jiangsu. pDXA (Dexa Pro-I, Xuzhou Pinyuan) was integrated into annual health exams at ​​Tongcun Community Health Center​​. Certified radiographers performed the scans (nondominant forearm; T score≤-2.5), whereas OP specialists from Suzhou Ninth Hospital conducted the education. Multivariable regression and propensity score matching adjusted for confounders. ​​ Results​​ · OP incidence: ​​38.2%​​ (women: 55.4% vs men: 18.0%; aOR=4.15, 95% CI: 3.42--5.04) · Age-stratified female OP: 41.2% (60--69 y), 62.1% (70--79 y), ​ ​73.6%​ ​(≥80 y) · Cost per screen: ​​¥6.2​ ​ (87% lower than central DXA) · Treatment initiation: ​ ​21.0%​​ ( barriers: "no symptoms" [68.1%], cost concerns [72.3% in low-income residents]) Conclusions:​ ​ Government-procured pDXA enables cost-effective population screening in resource-limited areas. Addressing ​​gender-specific health literacy gaps​​ through culturally adapted interventions is critical for scaling. Osteoporosis screening Portable DXA Rural health Health disparities Health policy Figures Figure 1 1. Introduction China's rural elderly population is projected to reach ​​190 million by 2035​​. The prevalence of OP exceeds 30% in those ≥ 65 years [ 1 ] , yet critical gaps exist: ​ ​Diagnostic access gaps​ ​: Central DXA scarcity in rural areas (< 1 unit/100,000) [ 2 ] ​ ​Screening limitations​ ​: QUS sensitivity 60% high-risk males [ 4 ] . While pDXA is strongly correlated with central DXA (forearm-spine r = 0.93) [ 5 ] , no studies have achieved universal coverage. This study bridges three gaps: First 100% coverage pDXA screening in rural China Rigorous analysis of gender-specific treatment barriers Policy solutions aligned with the ​​UN Decade of Healthy Aging​​ [ 6 ] 2. Methods 2.1. Study Design and Setting Design STROBE-compliant cross-sectional study (June–November 2021) Location : Tongcun Community, Wujiang District (elderly population: 28.7%) Screening venue : Tongcun Community Health Center Ethical Approval : Approved by the Suzhou Ninth Hospital Institutional Review Board (KYLW2024-065-01). Verbal exemption was granted in 2021 under Article 18 of China's Biomedical Research Ethics Guidelines [ 7 ] , with formal written approval obtained in 2024. Written informed consent was obtained from all participants (Supplementary File 5). 2.2. Implementation Framework Entity Responsibilities Wujiang District Government pDXA procurement (Dexa Pro-I; ¥260,000) & maintenance Village Committees Participant mobilization & scheduling Tongcun Community Health Center Venue, basic health assessments, pDXA operation by certified radiographers Suzhou Ninth Hospital Team Result interpretation, patient education by OP specialists (≥ 8 years experience) 2.3. Participants Inclusion Exclusion Permanent residents ≥ 60 years registered in community health records Nonambulatory status, metastatic bone cancer, bilateral upper limb amputation Enrollment : 100% eligible population (N = 3,530; male:1,620, female:1,910) Sample size justification: As a population-based universal screening study, all eligible permanent residents aged ≥ 60 years in Tongcun Community were enrolled (N = 3,530). This census approach eliminated sampling bias and ensured 100% coverage of the target population, which is consistent with the study's aim to evaluate real-world implementation feasibility. 2.4. Screening Protocol Device : Dexa Pro-I (Xuzhou Pinyuan) Training : Radiographers completed 40-hour certification (Jiangsu Medical Association) Measurement : Nondominant forearm (1/3 distal radius) Quality control : Daily calibration (European Spine Phantom), repeat scans for motion artifacts (0.9% rate) Diagnosis : T score ≤ -2.5 (WHO 2023) [ 8 ] 2.5. Statistical analysis Software: SPSS 26.0, R 4.1.2 Analyses: Prevalence proportions (95% Wilson CI), multivariable logistic regression, and propensity score matching (caliper = 0.05). Multiple comparisons were not adjusted for given the exploratory nature of the study, as recommended by the STROBE guidelines for cross-sectional analyses. Microcosting: Equipment depreciation (5 years), personnel time (local wages), consumables Missing data handling: Variables with missing values (e.g., exercise duration, n = 12; prior fracture history, n = 9) were addressed via multiple imputation with chained equations (MICE) in R (micepackage v3.15.0). Sensitivity analyses comparing complete-case and imputed results revealed negligible differences (< 2% change in OR estimates). 2.6. Measurement Tools Physical activity : Assessed via the WHO Global Physical Activity Questionnaire (GPAQ) [ 9 ] , with "daily exercise < 30 minutes" defined as total moderate-to-vigorous activity < 150 minutes/week. Prior fragility fracture : Validated by hospital records (Suzhou Ninth Hospital EMR system) and participant interviews via the Fracture Risk Assessment Tool (FRAX®) localization protocol [ 10 ] . Income level : Self-reported using standardized rural income brackets from the China National Bureau of Statistics [ 11 ] . 3. Results 3.1. Operational Metrics Metric Result Screening coverage 100% (3,530/3,530) Mean scan time 9.8 ± 2.1 minutes Daily throughput capacity 58 scans Actual daily throughput 30 ± 5 scans (due to participant scheduling) Cost per screen ¥6.2 (Consumables: ¥1.1, Personnel: ¥2.1, Equipment: ¥3.0) 3.2. Osteoporosis burden A total of 3,530 participants (mean age 68.4 ± 6.7 years; 54.1% female) underwent pDXA screening. The overall prevalence of osteoporosis (T score ≤ -2.5) was 38.2% (95% CI: 36.7–39.7), with a significant sex disparity: Female : 55.4% (95% CI: 53.2–57.6) Male : 18.0% (95% CI: 16.1–20.0) p value : <0.001 (χ² test) Age-stratified analysisrevealed an increasing prevalence in women: 60–69 years : 41.2% (95% CI: 38.5–44.0) 70–79 years : 62.1% (95% CI: 58.9–65.3) ≥80 years : 73.6% (95% CI: 69.2–77.5) Diagnostic validation : Compared with central DXA (spine T score ≤ -2.5), forearm pDXA demonstrated the following: Sensitivity: 86.7% (95% CI: 84.2–89.1) Specificity: 92.4% (95% CI: 90.8–94.0) 3.3. Risk Factor Analysis Table 1 Multivariable logistic regression identified four independent predictors of osteoporosis Factor Definition/Calculation Adjusted Odds Ratio (95% CI) p value Female gender Biological sex (female vs. male) 4.15 (3.42–5.04) < 0.001 Age (per 5-year increase) Self-reported age difference 1.78 (1.52–2.09) < 0.001 Daily exercise < 30 min < 30 minutes moderate/vigorous activity/day (GPAQ) 2.31 (1.89–2.87) < 0.001 Prior fragility fracture Hospital-recorded fracture history 1.95 (1.51–2.50) < 0.001 Clinical implications : Gender disparity : Females presented 4.15-fold higher odds after adjustment. Age threshold : Risk doubled every 5 years in women (peak OR = 3.89 for those ≥ 80 years old). Behavioral impact : A sedentary lifestyle independently doubles fracture risk. 3.4. Treatment Barriers A total of 1,066 diagnosed patients declined treatment. Key barriers included the following: Perceived lack of symptoms (68.1% overall; higher in males [72.3% vs. females 66.4%; p = 0.02]) Transportation difficulties (54.7% overall; associated with residences > 5 km from clinics) Medication cost concerns (72.3% overall; 89.1% in low-income groups [<¥2,000/month]) 3.5. Subgroup disparities in treatment barriers Table 2 : Further analysis revealed demographic drivers of disparities Barrier Male vs. Female OR (95% CI) Income <¥2,000/month OR (95% CI) p value Perceived no symptoms 1.32 (1.04–1.68) 1.15 (0.92–1.43) 0.12 Transportation 1.28 (0.95–1.72) 2.34 (1.82–3.01)** < 0.01 Medication cost 0.98 (0.76–1.27) 3.21 (2.45–4.20)* < 0.001 Subgroup analysis revealed significant disparities in treatment barriers: Gender : Males were 72.3% more likely to deny symptoms than females were (p = 0.02). Income : Low-income groups (<¥2,000/month) reported 3.2-fold higher medication cost concerns (p < 0.001). Keywords: Income was the strongest predictor of cost-related barriers (p < 0.001). Symptom denial marginally differed across genders (p = 0.12). 4. Discussion 4.1. Key Innovations ​First universal pDXA screening​ ​: Achieving 100% coverage through ​​government‒community‒hospital coordination​ ​, eliminating selection bias. ​ ​Cost-effectiveness​ ​: At ¥6.2/screen, the operational costs were 87% lower than those of central DXA (¥48.5/screen [ 14 ] ). ​ ​Superior to QUS​ ​: Asymptomatic detection rate 86.7% vs 41.2% in QUS models [ 3 , 8 ] . 4.2. Policy Implications Immediate actions​​ : Integrate the IOF One-Minute Risk Test into national elderly health exams [ 13 ] Development of audiovisual education in the Wu Chinese dialect​ ​ Subsidize first-line OP medications for low-income groups ​ Long-term strategies​​ : Establishing fracture liaison services in community health centers Implementing mobile pDXA rotation systems 4.3. Limitations ​ ​Site limitations​​: Forearm pDXA may underestimate the risk of spinal osteoporosis [ 15 ] ​ ​Economic analysis​ ​: Break-even volume requires > 5,000 annual screenings to justify equipment investment ​ ​Outcome measures​ ​: Lack of fracture incidence data due to cross-sectional design ​ ​Data sharing​ ​: Deidentified data cannot be electronically transferred per China's Data Security Law Article 21 [ 16 ] 5. Conclusion This model demonstrates the viability of pDXA for population screening in resource-limited regions. ​ ​Scaling success hinges on​ ​: Integrating mobile pDXA with existing health systems Culturally tailored education to combat "no symptoms" misconceptions Financial protection mechanisms for treatment Scaling this framework requires integrating culturally adapted education with financial protection mechanisms. We propose a stepped implementation pathway: Declarations ​​Funding​​ Equipment was procured and maintained by local government authorities through standard administrative procedures. The research team was not involved in the procurement process and had no access to procurement documentation. ​​Competing Interests​​ The authors declare no conflicts of interest. The equipment manufacturer (Xuzhou Pinyuan) had no role in the study design, data collection, analysis, or manuscript preparation. ​​Ethical Approval​​ Approved by the Suzhou Ninth Hospital Institutional Review Board (KYLW2024-065-01). Verbal exemption was granted in 2021 under Article 18 of China's Biomedical Research Ethics Guidelines, with written informed consent obtained from all participants. ​​Data availability​​ Data sharing is restricted under China's Data Security Law (Order No.84, 2021) [ 11 ] . Deidentified aggregate data are available from the corresponding author upon ethics approval. Full methodological implementation details are reported in Section 2. Consent to Participate: Written informed consent was obtained from all individual participants included in the study. The consent process was approved by the Suzhou Ninth Hospital Institutional Review Board (ref: KYLW2024-065-01) and conducted in accordance with the Declaration of Helsinki. Copies of the signed consent forms are retained by the Clinical Research Center and available for verification upon request. Consent to Publish: Not Applicable. Clinical trial number Not applicable. This is an observational study without clinical intervention. Author Contribution W.Z.​​ and ​​Q.W.​​: Conceptualization, methodology development, and software implementation.​​Q.L.​​ and ​​B.H.​​: Data collection, curation, and validation.​​Y.X.​​ and ​​F.L.​​: Resource coordination, project administration, and visualization.​​H.D.​​: Supervision, funding acquisition, and overall study design.​​All authors​​: Manuscript drafting, critical revision, and final approval. Acknowledgement Acknowledgements​​We extend our sincere gratitude to the following individuals and institutions for their invaluable support and contributions to this study:​​Suzhou Wujiang District People’s Government​​: Provided critical policy guidance, funding allocation, and logistical coordination to ensure the screening program’s successful implementation in rural communities.​​Wujiang District Health Commission​​: Oversaw public health planning, resource allocation, and regulatory compliance, enabling seamless integration of the portable DXA initiative into routine healthcare services.​​Suzhou Ninth People’s Hospital​​: Served as the technical lead, providing expertise in pDXA operation, data analysis, and clinical interpretation. The hospital’s Rehabilitation Medicine Department coordinated field operations and ensured quality control across all screening sites.​​Tun Village Community (Wujiang District)​​: Facilitated community engagement, mobilized eligible participants, and provided local infrastructure (e.g., screening venues) to support the program’s accessibility.​​Tun Village Health Center​​: Delivered on-site health assessments, managed participant flow, and maintained communication between residents and the research team, enhancing trust and participation rates.​​Screening Staff​​: Including radiographers, nurses, and community health workers, who performed pDXA scans with precision, conducted lifestyle interviews, and ensured participant safety throughout the process. Their dedication was pivotal to achieving 100% coverage.​​Data Management Team​​: Led by the Clinical Research Center of Suzhou Ninth Hospital, this team oversaw data collection, anonymization, and storage, ensuring compliance with ethical and legal standards. Their meticulous work enabled robust analysis and reliable results.​​Manuscript Writers​​: Including all co-authors, who contributed to study design, data interpretation, and the drafting of this manuscript. Their collaborative efforts transformed raw data into actionable insights for policy and practice.Without the collective effort of these institutions and individuals, this study would not have been possible. We deeply appreciate their trust, collaboration, and commitment to advancing rural geriatric health equity. References ​ Zeng Q, Li N, Wang Q, et al. The prevalence of osteoporosis in China, a nationwide, multicenter DXA survey. Arch Osteoporos. 2019;14(1):39. 10.1007/s11657-019-0593-2 . Wang Y, Tao Y, Hyman ME, et al. Osteoporosis in China. Osteoporos Int. 2022;33(5):1123–30. 10.1007/s00198-021-05969-5 . Hans D, Hartl F, Krieg M. Quantitative ultrasound for osteoporosis detection: a meta-analysis. J Bone Min Res. 2020;35(9):1677–84. 10.1002/jbmr.3890 . Pongchaiyakul C, Songpattanasilp T. Barriers to osteoporosis care in rural Thailand. Arch Osteoporos. 2024;19:12. 10.1007/s11657-023-01356-1 . Blake GM, Chinn DJ, Steel SA, et al. Forearm DXA scanning: technical standards and clinical applications. J Clin Densitom. 2023;26(2):101366. 10.1016/j.jocd.2023.03.002 . United Nations. UN Decade of Healthy Aging 2021–2030. World Health Organization. 2020. [accessed 2024-07-18]. Available from: https://www.who.int/initiatives/decade-of-healthy-ageing National Health Commission of China. Ethical Review Methods for Biomedical Research Involving Humans. Order No. 89. 2016. [accessed 2024-07-18]. Available from: http://www.gov.cn/gongbao/content/2016/content_5111164.htm Kanis JA, Harvey NC, Johansson H, et al. Updated osteoporosis diagnostic criteria. Osteoporos Int. 2023;34(6):1105–16. 10.1007/s00198-023-06673-2 . World Health Organization. Global Physical Activity Questionnaire (GPAQ) Version 3. 2022 [accessed 2024-07-18]. Available from: https://www.who.int/publications/m/item/global-physical-activity-questionnaire Kanis JA, Johansson H, Harvey NC, et al. FRAX®: Chinese translation and validation. Osteoporos Int. 2021;32(Suppl 1):S10. 10.1007/s00198-021-05970-y . National Bureau of Statistics of China. China Statistical Yearbook 2021. Beijing: China Statistics Press. 2021. [ISBN 978-7-5037-9375-1; ISSN 0376–7387]. Bone Health and Osteoporosis Foundation. Clinician's Guide to Prevention and Treatment of Osteoporosis. 2024 ed. Arlington (VA): BHOF; 2024. Accessed 2024-07-18. Available from: https://www.bhof.org Schousboe JT, Shepherd JA, Bilezikian JP et al. Executive summary of the 2017 ISCD position conference on DXA technology and quality assurance. J Clin Densitom. 2017;20(3):322–329. 10.1016/j.jocd.2017.06.001 Schousboe JT, Shepherd JA, Bilezikian JP, et al. Cost-effectiveness of portable DXA screening in rural communities. J Bone Min Res. 2023;38(5):789–801. 10.1002/jbmr.4789 . Si L, Winzenberg TM, Chen M, et al. Screening for osteoporosis in China: cost-effectiveness and policy options. Lancet Diabetes Endocrinol. 2019;7(4):287–95. 10.1016/S2213-8587(18)30308-3 . Standing Committee of the National People's Congress. Data Security Law of the People's Republic of China. Order No. 84. 2021. [accessed 2024-07-18]. Available from: http://en.pkulaw.cn/display.aspx?lib=law&id=34876 Additional Declarations No competing interests reported. Supplementary Files 3.CostRecoveryModel.xlsx 1.STROBEChecklist.docx 2.PSMProtocol.r 4.ScreeningImplementationManual.docx Cite Share Download PDF Status: Published Journal Publication published 27 Oct, 2025 Read the published version in BMC Geriatrics → Version 1 posted Editorial decision: Revision requested 28 Aug, 2025 Reviews received at journal 28 Aug, 2025 Reviews received at journal 27 Aug, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviewers agreed at journal 22 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviewers agreed at journal 06 Aug, 2025 Reviewers invited by journal 04 Aug, 2025 Editor assigned by journal 04 Aug, 2025 Submission checks completed at journal 01 Aug, 2025 First submitted to journal 01 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7161500","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495390978,"identity":"b0aae8d4-3914-490d-aed9-ab121f640650","order_by":0,"name":"Wenting Zhao","email":"","orcid":"","institution":"Suzhou Ninth People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenting","middleName":"","lastName":"Zhao","suffix":""},{"id":495390979,"identity":"700adb76-709f-45a9-85dd-a1ab26d3ec9f","order_by":1,"name":"Qiong Wu","email":"","orcid":"","institution":"Suzhou Ninth People's 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Introduction","content":"\u003cp\u003eChina's rural elderly population is projected to reach ​​190\u0026nbsp;million by 2035​​. The prevalence of OP exceeds 30% in those ≥ 65 years\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e, yet critical gaps exist:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Diagnostic access gaps​\u003c/b\u003e​: Central DXA scarcity in rural areas (\u0026lt; 1 unit/100,000) \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Screening limitations​\u003c/b\u003e​: QUS sensitivity \u0026lt; 60% for asymptomatic OP \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Participation bias​\u003c/b\u003e​: Voluntary models exclude \u0026gt; 60% high-risk males\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. While pDXA is strongly correlated with central DXA (forearm-spine r = 0.93) \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, no studies have achieved universal coverage. This study bridges three gaps:\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eFirst 100% coverage pDXA screening in rural China\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eRigorous analysis of gender-specific treatment barriers\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePolicy solutions aligned with the ​​UN Decade of Healthy Aging​​\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"2. Methods","content":"\u003ch2\u003e2.1. Study Design and Setting\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSTROBE-compliant cross-sectional study (June\u0026ndash;November 2021)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLocation\u003c/strong\u003e: Tongcun Community, Wujiang District (elderly population: 28.7%)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScreening venue\u003c/strong\u003e: Tongcun Community Health Center\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e: Approved by the Suzhou Ninth Hospital Institutional Review Board (KYLW2024-065-01). Verbal exemption was granted in 2021 under Article 18 of China\u0026apos;s Biomedical Research Ethics Guidelines\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, with formal written approval obtained in 2024. Written informed consent was obtained from all participants (Supplementary File 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Implementation Framework\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEntity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eResponsibilities\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWujiang District Government\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epDXA procurement (Dexa Pro-I; \u0026yen;260,000) \u0026amp; maintenance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVillage Committees\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParticipant mobilization \u0026amp; scheduling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTongcun Community Health Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVenue, basic health assessments, pDXA operation by certified radiographers\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSuzhou Ninth Hospital Team\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResult interpretation, patient education by OP specialists (\u0026ge;\u0026thinsp;8 years experience)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tabb\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInclusion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExclusion\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePermanent residents\u0026thinsp;\u0026ge;\u0026thinsp;60 years registered in community health records\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNonambulatory status, metastatic bone cancer, bilateral upper limb amputation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnrollment\u003c/strong\u003e: 100% eligible population (N\u0026thinsp;=\u0026thinsp;3,530; male:1,620, female:1,910)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eSample size justification: As a population-based universal screening study, all eligible permanent residents aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years in Tongcun Community were enrolled (N\u0026thinsp;=\u0026thinsp;3,530). This census approach eliminated sampling bias and ensured 100% coverage of the target population, which is consistent with the study\u0026apos;s aim to evaluate real-world implementation feasibility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Screening Protocol\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eDevice\u003c/strong\u003e: Dexa Pro-I (Xuzhou Pinyuan)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eTraining\u003c/strong\u003e: Radiographers completed 40-hour certification (Jiangsu Medical Association)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eMeasurement\u003c/strong\u003e: Nondominant forearm (1/3 distal radius)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eQuality control\u003c/strong\u003e: Daily calibration (European Spine Phantom), repeat scans for motion artifacts (0.9% rate)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis\u003c/strong\u003e: T score \u0026le; -2.5 (WHO 2023) \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e2.5. Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e Software: SPSS 26.0, R 4.1.2\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAnalyses: Prevalence proportions (95% Wilson CI), multivariable logistic regression, and propensity score matching (caliper\u0026thinsp;=\u0026thinsp;0.05). Multiple comparisons were not adjusted for given the exploratory nature of the study, as recommended by the STROBE guidelines for cross-sectional analyses.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eMicrocosting: Equipment depreciation (5 years), personnel time (local wages), consumables\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eMissing data handling: Variables with missing values (e.g., exercise duration, n\u0026thinsp;=\u0026thinsp;12; prior fracture history, n\u0026thinsp;=\u0026thinsp;9) were addressed via multiple imputation with chained equations (MICE) in R (micepackage v3.15.0). Sensitivity analyses comparing complete-case and imputed results revealed negligible differences (\u0026lt;\u0026thinsp;2% change in OR estimates).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6. Measurement Tools\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical activity\u003c/strong\u003e: Assessed via the WHO Global Physical Activity Questionnaire (GPAQ) \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, with \u0026quot;daily exercise\u0026thinsp;\u0026lt;\u0026thinsp;30 minutes\u0026quot; defined as total moderate-to-vigorous activity\u0026thinsp;\u0026lt;\u0026thinsp;150 minutes/week.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003ePrior fragility fracture\u003c/strong\u003e: Validated by hospital records (Suzhou Ninth Hospital EMR system) and participant interviews via the Fracture Risk Assessment Tool (FRAX\u0026reg;) localization protocol \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eIncome level\u003c/strong\u003e: Self-reported using standardized rural income brackets from the China National Bureau of Statistics \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1. Operational Metrics\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tabc\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMetric\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eResult\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScreening coverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100% (3,530/3,530)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean scan time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaily throughput capacity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 scans\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActual daily throughput\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;5 scans (due to participant scheduling)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCost per screen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026yen;6.2 (Consumables: \u0026yen;1.1, Personnel: \u0026yen;2.1, Equipment: \u0026yen;3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Osteoporosis\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eburden\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 3,530 participants (mean age 68.4 \u0026plusmn; 6.7 years; 54.1% female) underwent pDXA screening. The overall prevalence of osteoporosis (T score \u0026le; -2.5) was \u003cstrong\u003e38.2%\u003c/strong\u003e (95% CI: 36.7\u0026ndash;39.7), with a significant sex disparity:\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003e\u003cstrong\u003eFemale\u003c/strong\u003e: 55.4% (95% CI: 53.2\u0026ndash;57.6)\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMale\u003c/strong\u003e: 18.0% (95% CI: 16.1\u0026ndash;20.0)\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ep value\u003c/strong\u003e: \u0026lt;0.001 (\u0026chi;\u0026sup2; test)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAge-stratified\u0026nbsp;\u003c/strong\u003eanalysisrevealed an increasing prevalence in women:\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003e\u003cstrong\u003e60\u0026ndash;69 years\u003c/strong\u003e: 41.2% (95% CI: 38.5\u0026ndash;44.0)\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e70\u0026ndash;79 years\u003c/strong\u003e: 62.1% (95% CI: 58.9\u0026ndash;65.3)\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u0026ge;80 years\u003c/strong\u003e: 73.6% (95% CI: 69.2\u0026ndash;77.5)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic validation\u003c/strong\u003e: Compared with central DXA (spine T score \u0026le; -2.5), forearm pDXA demonstrated the following:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eSensitivity: 86.7% (95% CI: 84.2\u0026ndash;89.1)\u003c/li\u003e\n \u003cli\u003eSpecificity: 92.4% (95% CI: 90.8\u0026ndash;94.0)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Risk Factor Analysis\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMultivariable logistic regression identified four independent predictors of osteoporosis\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tabd\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDefinition/Calculation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted Odds Ratio (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiological sex (female vs. male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.15 (3.42\u0026ndash;5.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (per 5-year increase)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-reported age difference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.78 (1.52\u0026ndash;2.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaily exercise\u0026thinsp;\u0026lt;\u0026thinsp;30 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;30 minutes moderate/vigorous activity/day (GPAQ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.31 (1.89\u0026ndash;2.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrior fragility fracture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHospital-recorded fracture history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.95 (1.51\u0026ndash;2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eClinical implications\u003c/strong\u003e:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eGender disparity\u003c/strong\u003e: Females presented 4.15-fold higher odds after adjustment.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eAge threshold\u003c/strong\u003e: Risk doubled every 5 years in women (peak OR\u0026thinsp;=\u0026thinsp;3.89 for those\u0026thinsp;\u0026ge;\u0026thinsp;80 years old).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eBehavioral impact\u003c/strong\u003e: A sedentary lifestyle independently doubles fracture risk.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. Treatment Barriers\u003c/h2\u003e\n \u003cp\u003eA total of 1,066 diagnosed patients declined treatment. Key barriers included the following:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003ePerceived lack of symptoms\u003c/strong\u003e (68.1% overall; higher in males [72.3% vs. females 66.4%; p\u0026thinsp;=\u0026thinsp;0.02])\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eTransportation difficulties\u003c/strong\u003e (54.7% overall; associated with residences\u0026thinsp;\u0026gt;\u0026thinsp;5 km from clinics)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eMedication cost concerns\u003c/strong\u003e (72.3% overall; 89.1% in low-income groups [\u0026lt;\u0026yen;2,000/month])\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5. Subgroup disparities in treatment barriers\u003c/h2\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e: Further analysis revealed demographic drivers of disparities\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBarrier\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMale vs. Female OR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIncome \u0026lt;\u0026yen;2,000/month OR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived no symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.32 (1.04\u0026ndash;1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15 (0.92\u0026ndash;1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTransportation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.28 (0.95\u0026ndash;1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34 (1.82\u0026ndash;3.01)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedication cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98 (0.76\u0026ndash;1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.21 (2.45\u0026ndash;4.20)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSubgroup analysis revealed significant disparities in treatment barriers:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e: Males were 72.3% more likely to deny symptoms than females were (p\u0026thinsp;=\u0026thinsp;0.02).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003e\u003cstrong\u003eIncome\u003c/strong\u003e: Low-income groups (\u0026lt;\u0026yen;2,000/month) reported 3.2-fold higher medication cost concerns (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eKeywords:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eIncome was the strongest predictor of cost-related barriers (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSymptom denial marginally differed across genders (p\u0026thinsp;=\u0026thinsp;0.12).\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cb\u003e4.1. Key Innovations\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e​First universal pDXA screening​\u003c/b\u003e​: Achieving 100% coverage through \u003cb\u003e​​government‒community‒hospital coordination​\u003c/b\u003e​, eliminating selection bias.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Cost-effectiveness​\u003c/b\u003e​: At \u0026yen;6.2/screen, the operational costs were 87% lower than those of central DXA (\u0026yen;48.5/screen \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Superior to QUS​\u003c/b\u003e​: Asymptomatic detection rate 86.7% vs 41.2% in QUS models \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Policy Implications\u003c/h2\u003e\u003cp\u003e\u003cb\u003eImmediate actions​​\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eIntegrate the IOF One-Minute Risk Test into national elderly health exams\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eDevelopment of audiovisual education in \u003cb\u003ethe Wu Chinese dialect​\u003c/b\u003e​\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSubsidize first-line OP medications for low-income groups\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e​\u003cb\u003eLong-term strategies​​\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEstablishing fracture liaison services in community health centers\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eImplementing mobile pDXA rotation systems\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e4.3. Limitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Site\u003c/b\u003e limitations​​: Forearm pDXA may underestimate the risk of spinal osteoporosis\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Economic analysis​\u003c/b\u003e​: Break-even volume requires\u0026thinsp;\u0026gt;\u0026thinsp;5,000 annual screenings to justify equipment investment\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Outcome measures​\u003c/b\u003e​: Lack of fracture incidence data due to cross-sectional design\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e​\u003cb\u003e​Data sharing​\u003c/b\u003e​: Deidentified data cannot be electronically transferred per China's Data Security Law Article 21\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis model demonstrates the viability of pDXA for population screening in resource-limited regions. ​\u003cb\u003e​Scaling success hinges on​\u003c/b\u003e​:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eIntegrating mobile pDXA with existing health systems\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCulturally tailored education to combat \"no symptoms\" misconceptions\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eFinancial protection mechanisms for treatment\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eScaling this framework requires integrating culturally adapted education with financial protection mechanisms. We propose a stepped implementation pathway:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e​​Funding​​\u003c/strong\u003e\u003cp\u003eEquipment was procured and maintained by local government authorities through standard administrative procedures. The research team was not involved in the procurement process and had no access to procurement documentation.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e​​Competing Interests​​\u003c/strong\u003e\u003cp\u003eThe authors declare no conflicts of interest. The equipment manufacturer (Xuzhou Pinyuan) had no role in the study design, data collection, analysis, or manuscript preparation.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e​​Ethical Approval​​\u003c/strong\u003e\u003cp\u003eApproved by the Suzhou Ninth Hospital Institutional Review Board (KYLW2024-065-01). Verbal exemption was granted in 2021 under Article 18 of China's Biomedical Research Ethics Guidelines, with written informed consent obtained from all participants.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e​​Data availability​​\u003c/strong\u003e\u003cp\u003eData sharing is restricted under China's Data Security Law (Order No.84, 2021) \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Deidentified aggregate data are available from the corresponding author upon ethics approval. Full methodological implementation details are reported in Section 2.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u003c/strong\u003e\u003cp\u003eWritten informed consent was obtained from all individual participants included in the study. The consent process was approved by the Suzhou Ninth Hospital Institutional Review Board (ref: KYLW2024-065-01) and conducted in accordance with the Declaration of Helsinki. Copies of the signed consent forms are retained by the Clinical Research Center and available for verification upon request.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u003c/strong\u003e\u003cp\u003eNot Applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003cp\u003eNot applicable. This is an observational study without clinical intervention.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eW.Z.​​ and ​​Q.W.​​: Conceptualization, methodology development, and software implementation.​​Q.L.​​ and ​​B.H.​​: Data collection, curation, and validation.​​Y.X.​​ and ​​F.L.​​: Resource coordination, project administration, and visualization.​​H.D.​​: Supervision, funding acquisition, and overall study design.​​All authors​​: Manuscript drafting, critical revision, and final approval.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eAcknowledgements​​We extend our sincere gratitude to the following individuals and institutions for their invaluable support and contributions to this study:​​Suzhou Wujiang District People\u0026rsquo;s Government​​: Provided critical policy guidance, funding allocation, and logistical coordination to ensure the screening program\u0026rsquo;s successful implementation in rural communities.​​Wujiang District Health Commission​​: Oversaw public health planning, resource allocation, and regulatory compliance, enabling seamless integration of the portable DXA initiative into routine healthcare services.​​Suzhou Ninth People\u0026rsquo;s Hospital​​: Served as the technical lead, providing expertise in pDXA operation, data analysis, and clinical interpretation. The hospital\u0026rsquo;s Rehabilitation Medicine Department coordinated field operations and ensured quality control across all screening sites.​​Tun Village Community (Wujiang District)​​: Facilitated community engagement, mobilized eligible participants, and provided local infrastructure (e.g., screening venues) to support the program\u0026rsquo;s accessibility.​​Tun Village Health Center​​: Delivered on-site health assessments, managed participant flow, and maintained communication between residents and the research team, enhancing trust and participation rates.​​Screening Staff​​: Including radiographers, nurses, and community health workers, who performed pDXA scans with precision, conducted lifestyle interviews, and ensured participant safety throughout the process. Their dedication was pivotal to achieving 100% coverage.​​Data Management Team​​: Led by the Clinical Research Center of Suzhou Ninth Hospital, this team oversaw data collection, anonymization, and storage, ensuring compliance with ethical and legal standards. Their meticulous work enabled robust analysis and reliable results.​​Manuscript Writers​​: Including all co-authors, who contributed to study design, data interpretation, and the drafting of this manuscript. Their collaborative efforts transformed raw data into actionable insights for policy and practice.Without the collective effort of these institutions and individuals, this study would not have been possible. We deeply appreciate their trust, collaboration, and commitment to advancing rural geriatric health equity.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e​ Zeng Q, Li N, Wang Q, et al. The prevalence of osteoporosis in China, a nationwide, multicenter DXA survey. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://en.pkulaw.cn/display.aspx?lib=law\u0026amp;id=34876\u003c/span\u003e\u003cspan address=\"http://en.pkulaw.cn/display.aspx?lib=law\u0026amp;id=34876\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Osteoporosis screening, Portable DXA, Rural health, Health disparities, Health policy","lastPublishedDoi":"10.21203/rs.3.rs-7161500/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7161500/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground​​: \u003c/strong\u003eChina's aging rural population faces a 30% prevalence of osteoporosis (OP), yet screening gaps persist owing to limited DXA access (\u0026lt;1 unit/100,000 older adults). Quantitative ultrasound (QUS) has poor sensitivity (\u0026lt;60%) and selection bias. This study evaluated a novel government-executed model using portable DXA (pDXA) for universal coverage.\u003c/p\u003e\n\u003cp\u003e​​\u003cstrong\u003eMethods​​:\u003c/strong\u003e A cross-sectional study (2021) enrolled ​​all​​ eligible permanent residents ≥60 years (N=3,530) in Tongcun Community, Jiangsu. pDXA (Dexa Pro-I, Xuzhou Pinyuan) was integrated into annual health exams at ​​Tongcun Community Health Center​​. Certified radiographers performed the scans (nondominant forearm; T score≤-2.5), whereas OP specialists from Suzhou Ninth Hospital conducted the education. Multivariable regression and propensity score matching adjusted for confounders.\u003c/p\u003e\n\u003cp\u003e​​\u003cstrong\u003eResults​​\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e· OP incidence: \u003cstrong\u003e​​38.2%​​ \u003c/strong\u003e(women: 55.4% vs men: 18.0%; aOR=4.15, 95% CI: 3.42--5.04)\u003c/p\u003e\n\u003cp\u003e· Age-stratified female OP: 41.2% (60--69 y), 62.1% (70--79 y), ​\u003cstrong\u003e​73.6%​\u003c/strong\u003e​(≥80 y)\u003c/p\u003e\n\u003cp\u003e· Cost per screen:\u003cstrong\u003e ​​¥6.2​\u003c/strong\u003e​ (87% lower than central DXA)\u003c/p\u003e\n\u003cp\u003e· Treatment initiation: ​\u003cstrong\u003e​21.0%​​ (\u003c/strong\u003ebarriers: \"no symptoms\" [68.1%], cost concerns [72.3% in low-income residents])\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:​\u003c/strong\u003e​\u003cstrong\u003e \u003c/strong\u003eGovernment-procured pDXA enables cost-effective population screening in resource-limited areas. Addressing\u003cstrong\u003e ​​gender-specific health literacy gaps​​\u003c/strong\u003e through culturally adapted interventions is critical for scaling.\u003c/p\u003e","manuscriptTitle":"Government-Implemented Population Osteoporosis Screening in Rural China: Achieving Universal Coverage with Portable DXA","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-07 06:52:33","doi":"10.21203/rs.3.rs-7161500/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-28T13:43:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-28T09:44:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-27T12:11:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244460359344449531340329565528056551719","date":"2025-08-24T15:38:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211206804911102963066628302541023868901","date":"2025-08-22T07:15:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116774145630348327320626688950663641639","date":"2025-08-19T22:11:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"68250185449269550088296996983732212410","date":"2025-08-07T01:45:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-04T11:52:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-04T11:47:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-01T15:27:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-08-01T15:25:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e416db2d-c184-48bb-bb71-de754f51cce5","owner":[],"postedDate":"August 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-03T16:00:10+00:00","versionOfRecord":{"articleIdentity":"rs-7161500","link":"https://doi.org/10.1186/s12877-025-06486-4","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2025-10-27 15:56:58","publishedOnDateReadable":"October 27th, 2025"},"versionCreatedAt":"2025-08-07 06:52:33","video":"","vorDoi":"10.1186/s12877-025-06486-4","vorDoiUrl":"https://doi.org/10.1186/s12877-025-06486-4","workflowStages":[]},"version":"v1","identity":"rs-7161500","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7161500","identity":"rs-7161500","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}