The dataset offers comprehensive information on health factors influencing osteoporosis development, including demographic details, lifestyle choices, medical history, and bone health indicators. It aims to facilitate research in osteoporosis prediction, enabling machine learning models to identify individuals at risk. Analyzing factors like age, gender, hormonal changes, and lifestyle habits can help improve osteoporosis management and prevention strategies.

Potential Analysis:

Predictive Modeling: Develop machine learning models to predict the probability of osteoporosis based on the provided features. This analysis is crucial for identifying individuals at risk of osteoporosis, enabling early intervention and prevention strategies.

Feature Importance Analysis: Determine the importance of each feature in predicting osteoporosis risk. Understanding which factors have the most significant impact on osteoporosis risk can provide insights into the underlying mechanisms and guide targeted interventions.

Correlation Analysis: Examine correlations between different features and osteoporosis risk. Identifying strong correlations can help identify potential risk factors or associations that may warrant further investigation or intervention.

Subgroup Analysis: Analyze how osteoporosis risk varies across different subgroups based on demographics, lifestyle factors, or medical history. Understanding how risk factors interact within different population groups can inform personalized approaches to osteoporosis prevention and management.

Model Interpretation: Interpret the trained models to understand how different features contribute to osteoporosis risk prediction. This analysis can provide insights into the underlying relationships between variables and help healthcare professionals make informed decisions regarding patient care and management strategies.

Postmenopausal Osteoporosis Drugs Market Outlook

As of 2023, the global postmenopausal osteoporosis drugs market size is estimated to be approximately $10 billion and is projected to reach around $15 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 4.5%. This market is propelled by an increasing prevalence of osteoporosis among postmenopausal women and a rising awareness regarding early diagnosis and treatment options. With the aging population and a growing emphasis on women's health, the market is set for substantial growth in the coming decade.

The rising incidence of postmenopausal osteoporosis is one of the primary drivers of market growth. As the global population ages, the number of postmenopausal women increases, leading to a higher prevalence of osteoporosis. This demographic shift highlights the critical need for effective pharmaceutical interventions to manage bone density loss and prevent fractures. Advances in diagnostic techniques have also made early detection of osteoporosis more feasible, contributing to the increased demand for effective treatment regimens.

Innovations in drug development and the introduction of new therapeutic classes are also significant growth factors. Pharmaceutical companies are investing heavily in research and development to create more effective and safer medications. The emergence of biologics and advanced drug delivery systems has broadened the treatment options available, making it easier to manage the condition. Additionally, patient-centric approaches and personalized medicine are becoming more prevalent, further driving market expansion.

Public health initiatives and educational campaigns aimed at raising awareness about osteoporosis and the importance of early treatment are contributing to market growth. Governments and healthcare organizations are increasingly recognizing osteoporosis as a critical public health issue. Efforts to educate the public and healthcare providers about the risk factors, symptoms, and treatment options for postmenopausal osteoporosis are helping to improve diagnosis rates and treatment adherence, thereby boosting market demand.

Regionally, North America is currently the largest market for postmenopausal osteoporosis drugs, driven by a high prevalence of the condition, advanced healthcare infrastructure, and significant healthcare expenditure. Europe follows closely, benefiting from similar factors along with supportive government policies and increasing public awareness. The Asia Pacific region is poised for rapid growth, supported by an aging population, improving healthcare access, and rising disposable incomes. Latin America and the Middle East & Africa, though smaller in terms of market size, present significant growth opportunities due to improving healthcare systems and increasing awareness.

Bone Resorption Inhibitors play a crucial role in the management of postmenopausal osteoporosis by targeting the underlying process of bone loss. These inhibitors work by slowing down or halting the resorption of bone, a natural process where bone is broken down and its minerals released into the bloodstream. By reducing bone resorption, these drugs help maintain bone density and strength, thereby minimizing the risk of fractures. The development and use of bone resorption inhibitors have been pivotal in providing effective treatment options for women suffering from osteoporosis, especially those who are at a higher risk of fractures due to significant bone density loss. Ongoing research continues to enhance the efficacy and safety profile of these inhibitors, ensuring better patient outcomes.

Drug Type Analysis

The postmenopausal osteoporosis drugs market is segmented by drug type, with each category offering unique benefits and targeting specific aspects of the condition. Bisphosphonates are the most commonly prescribed drugs for osteoporosis. These drugs work by inhibiting bone resorption, thus maintaining bone density and reducing the risk of fractures. Popular bisphosphonates include Alendronate and Risedronate. Despite their effectiveness, long-term use of bisphosphonates is associated with potential side effects, including gastrointestinal issues and rare occurrences of atypical femoral fractures, which has led to ongoing research into safer alternatives.

Selective Estrogen Receptor Modulators (SERMs) are another important class of drugs used to treat postmenopausal osteoporosis. These dru

JPOS is a comprehensive research project aimed at preventing fractures and osteoporosis in women. At the time of recruitment, participants were women aged 15 to 79 from seven municipalities across Japan, including Memuro, Iwate, Nishi-Aizu, Joetsu, Sanuki, Kousa, and Miyakojimaproviding a broad representation of the Japanese female population. At baseline, over 3,900 participants were included in the study. Follow-up surveys were conducted in 1999, 2002, 2006, 2011/12, and 2016/17 to monitor changes over time.

Incidence and hazard ratios of osteoporosis by demographic characteristics and comorbidity among patients with or without atopic dermatitis.

Bone loss occurs when the cellular events of bone formation are quantitatively larger than bone formation. This manuscript discusses the measurement of bone loss, occurrence in the population, risk factors and consequences of bone loss. Recent developments in bone mass measurement and biomarkers have improved our ability to assess bone loss. This process is a normal concomitant of ageing. There are a number of other risk factors, including sex hormone deficiency, physical inactivity, calcium/vitamin D deficiency, inflammatory arthritis, corticosteroids, smoking and alcohol. The major consequence of bone loss in our ageing society is fracture.

BackgroundOsteoporosis has already been a growing health concern worldwide. The influence of living area, lifestyle, socioeconomic, and medical conditions on the occurrence of osteoporosis in the middle-aged and elderly people in China has not been fully addressed.MethodsThe study was a multicenter cross-sectional study on the middle-aged and elderly permanent residents, which gathered information of 22,081 residents from June 2015 to August 2021 in seven representative regions of China. The bone mineral density of lumbar vertebrae and hip were determined using the dual-energy X-ray absorptiometry densitometer instruments. Serum levels of bone metabolism markers were also measured. Information about education, smoking, and chronic diseases were also collected through face-to-face interviews. Age-standardized prevalence and 95% confidence intervals (CIs) of osteopenia and osteoporosis by various criteria were estimated by subgroups and overall based on the data of China 2010 census. The relationships between the osteoporosis or osteopenia and sociodemographic variables or other factors were examined using univariate linear models and multivariable multinomial logit analyses.ResultsAfter screening, 19,848 participants (90%) were enrolled for the final analysis. The age-standardized prevalence of osteoporosis was estimated to be 33.49%(95%CI, 32.80–34.18%) in the middle-aged and elderly Chinese permanent residents, for men and women was 20.73% (95% CI, 19.58–21.87%) and 38.05% (95% CI, 37.22–38.89%), respectively. The serum concentrations of bone metabolic markers, and calcium and phosphorus metabolism were influenced by age, body mass index (BMI), gender, education level, regions, and bone mass status. Women, aged 60 or above, BMI lower than 18.5 kg/m2, low education level including middle school, primary school and no formal education as well as current regular smoking, a history of fracture were all significantly associated with a higher risk of osteoporosis and osteopenia in the middle-aged and elderly people.ConclusionsThis study revealed dramatic regional differences in osteoporosis prevalence in China, and female, aged 60 or older, low BMI, low education level, current regular smoking, and a history of fracture were associated with a high risk of osteoporosis. More prevention and treatment resources should be invested into particular population exposed to these risk factors.

The global bone health candy market is experiencing robust growth, driven by increasing awareness of bone health, particularly among aging populations and those at risk of osteoporosis. The market, valued at approximately $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching an estimated value of $4.5 billion by 2033. This growth is fueled by several key factors. Firstly, the rising prevalence of osteoporosis and other bone-related diseases, coupled with an aging global population, is creating a substantial demand for convenient and palatable bone health supplements. Secondly, the innovative formulations of bone health candies, incorporating essential nutrients like calcium, vitamin D, and other minerals, are attracting consumers seeking healthier alternatives to traditional supplements. Furthermore, the increasing consumer preference for natural and organic products is driving the adoption of bone health candies made with natural ingredients. The market's segmentation reflects diverse consumer preferences, with variations in flavor profiles, ingredient compositions, and targeted demographics. Leading players such as Vitafusion, Nature Made, and SmartyPants are leveraging strategic marketing and product innovations to capture significant market share. The market, however, faces certain restraints. The higher cost of bone health candies compared to other supplements could limit accessibility for some consumers. Furthermore, potential concerns about added sugar content in some products pose a challenge. Despite these challenges, the market is poised for continued expansion driven by consumer awareness campaigns, advancements in supplement formulations, and the entry of new market players offering diverse product lines. The market's regional distribution will see strong performance in North America and Europe, driven by high consumer awareness and established healthcare infrastructure. Emerging markets in Asia-Pacific and Latin America are expected to witness significant growth as health consciousness increases and disposable incomes rise within those regions. The continued focus on product innovation and targeted marketing will be key to success for companies operating within this dynamic market.

According to the National Health Survey, around 853.6 thousand people in Australia suffered from osteoporosis in the financial year 2022. This marked a decrease from 924 thousand people in the financial year 2018.

This dataset presents information on age-sex specific incidence rates of osteoporosis for Alberta, expressed as per 100,000 population.

Financial overview and grant giving statistics of Foundation For Osteoporosis Research And Education Dba American Bone Health

BackgroundLow bone mineral density (LBMD), including osteoporosis and low bone mass, has becoming a serious public health concern. We aimed to estimate the disease burden of LBMD and its related fractures in 204 countries and territories over the past 30 years.MethodsWe collected detailed information and performed a secondary analysis for LBMD and its related fractures from the Global Burden of Disease Study 2019. Numbers and age-standardized rates related to LBMD of disability-adjusted life-years (DALYs) and deaths in 204 countries and territories were compared by age, gender, socio-demographic index (SDI), and location.ResultsGlobal deaths and DALYs number attributable to LBMD increased from 207 367 and 8 588 936 in 1990 to 437 884 and 16 647 466 in 2019, with a raise of 111.16% and 93.82%, respectively. DALYs and deaths number of LBMD-related fractures increased 121.07% and 148.65% from 4 436 789 and 121248 in 1990 to 9 808 464 and 301 482 in 2019. In 2019, the five countries with the highest disease burden of DALYs number in LBMD-related fractures were India (2 510 288), China (1 839 375), United States of America (819 445), Japan (323 094), and Germany (297 944), accounting for 25.59%, 18.75%, 8.35%, 3.29%, and 3.04%. There was a quadratic correlation between socio-demographic index (SDI) and burden of LBMD-related fractures: DALYs rate was 179.985-420.435SDI+417.936SDI2(R2 = 0.188, p<0.001); Deaths rate was 7.879-13.416SDI+8.839 SDI2(R2 = 0.101, p<0.001).ConclusionsThe global burden of DALYs and deaths associated with LBMD and its related fractures has increased significantly since 1990. There were differences in disease burden between regions and countries. These estimations could be useful in priority setting, policy-making, and resource allocation in osteoporosis prevention and treatment.

This dataset is no longer updated as of April 2023.

Basic Metadata *Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population.

**Blank Cells: Rates not calculated for fewer than 5 events. Rates not calculated in cases where zip code is unknown.

***API: Asian/Pacific Islander. ***AIAN: American Indian/Alaska Native.

Prepared by: County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2019.

Code Source: ICD-9CM - AHRQ HCUP CCS v2015. ICD-10CM - AHRQ HCUP CCS v2018. ICD-10 Mortality - California Department of Public Health, Group Cause of Death Codes 2013; NHCS ICD-10 2e-v1 2017.

Data Guide, Dictionary, and Codebook: https://www.sandiegocounty.gov/content/dam/sdc/hhsa/programs/phs/CHS/Community%20Profiles/Public%20Health%20Services%20Codebook_Data%20Guide_Metadata_10.2.19.xlsx

In 2017-2018, around 19.6 percent of women in the United States aged 50 years and older had osteoporosis, compared to just 4.4 percent of men aged 50 years and older. This statistic shows the prevalence of osteoporosis among adults aged 50 and over in the United States from 2017 to 2018, by gender and age.

IntroductionOsteoporosis, characterized by low bone mineral density (BMD), is an increasingly serious public health issue. So far, several traditional regression models and machine learning (ML) algorithms have been proposed for predicting osteoporosis risk. However, these models have shown relatively low accuracy in clinical implementation. Recently proposed deep learning (DL) approaches, such as deep neural network (DNN), which can discover knowledge from complex hidden interactions, offer a new opportunity to improve predictive performance. In this study, we aimed to assess whether DNN can achieve a better performance in osteoporosis risk prediction.MethodsBy utilizing hip BMD and extensive demographic and routine clinical data of 8,134 subjects with age more than 40 from the Louisiana Osteoporosis Study (LOS), we developed and constructed a novel DNN framework for predicting osteoporosis risk and compared its performance in osteoporosis risk prediction with four conventional ML models, namely random forest (RF), artificial neural network (ANN), k-nearest neighbor (KNN), and support vector machine (SVM), as well as a traditional regression model termed osteoporosis self-assessment tool (OST). Model performance was assessed by area under ‘receiver operating curve’ (AUC) and accuracy.ResultsBy using 16 discriminative variables, we observed that the DNN approach achieved the best predictive performance (AUC = 0.848) in classifying osteoporosis (hip BMD T-score ≤ −1.0) and non-osteoporosis risk (hip BMD T-score > −1.0) subjects, compared to the other approaches. Feature importance analysis showed that the top 10 most important variables identified by the DNN model were weight, age, gender, grip strength, height, beer drinking, diastolic pressure, alcohol drinking, smoke years, and economic level. Furthermore, we performed subsampling analysis to assess the effects of varying number of sample size and variables on the predictive performance of these tested models. Notably, we observed that the DNN model performed equally well (AUC = 0.846) even by utilizing only the top 10 most important variables for osteoporosis risk prediction. Meanwhile, the DNN model can still achieve a high predictive performance (AUC = 0.826) when sample size was reduced to 50% of the original dataset.ConclusionIn conclusion, we developed a novel DNN model which was considered to be an effective algorithm for early diagnosis and intervention of osteoporosis in the aging population.

Women’s demographics (n = 37).

The bone density testing market is experiencing robust growth, driven by an aging global population, increasing prevalence of osteoporosis and related fractures, and advancements in diagnostic technology. The market, estimated at $2 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching approximately $3.5 billion by 2033. This growth is fueled by several key factors. The rising awareness about osteoporosis and its debilitating consequences is leading to increased screening and early diagnosis. Technological advancements, such as the development of more portable and user-friendly devices, are making bone density testing more accessible and affordable. Furthermore, the integration of bone density testing into routine healthcare check-ups, particularly for older adults and post-menopausal women, is significantly contributing to market expansion. However, the market faces some restraints, including high costs associated with advanced imaging techniques and limited access to sophisticated testing equipment in certain regions. The competitive landscape is characterized by a mix of established players like Hologic and GE Healthcare and emerging companies specializing in innovative technologies. These companies are focusing on developing advanced diagnostic tools with improved accuracy and efficiency. Regional variations in market growth are expected, with North America and Europe maintaining a significant share due to high healthcare expenditure and advanced infrastructure. However, developing economies in Asia-Pacific and Latin America are poised for considerable growth, driven by rising healthcare awareness and increasing disposable incomes. The market segmentation is primarily based on technology type (DEXA, QUS, etc.), application (osteoporosis diagnosis, fracture risk assessment, etc.), and end-user (hospitals, clinics, etc.). Future growth will depend heavily on the continued development and adoption of innovative technologies, expansion into emerging markets, and government initiatives promoting osteoporosis awareness and prevention.

Osteoporosis Drugs Market Outlook

The global osteoporosis drugs market size in 2024 is valued at USD 13.8 billion, according to the latest research, with a steady compound annual growth rate (CAGR) of 4.7% projected from 2025 to 2033. With this growth trajectory, the market is forecasted to reach USD 20.9 billion by 2033. This upward trend is primarily driven by the increasing prevalence of osteoporosis worldwide, the rising geriatric population, and ongoing advancements in drug development and delivery methods.

One of the primary growth factors propelling the osteoporosis drugs market is the aging global population. Osteoporosis is predominantly observed in older adults, particularly postmenopausal women, due to hormonal changes that accelerate bone density loss. As the proportion of the elderly continues to rise, especially in developed economies, the incidence of osteoporosis and related fractures is expected to increase significantly. This demographic shift is prompting healthcare systems and pharmaceutical companies to invest more in osteoporosis screening, prevention, and management, thereby driving demand for effective drug therapies. Additionally, the growing awareness about osteoporosis and its complications, fostered by numerous public health campaigns and educational initiatives, is encouraging early diagnosis and prompt treatment, further fueling market growth.

Another significant driver is the ongoing innovation in osteoporosis drug development. Pharmaceutical companies are focusing on developing novel therapeutics with improved efficacy, safety profiles, and convenient dosing regimens. The introduction of new drug classes, such as RANK ligand inhibitors and parathyroid hormone analogs, has expanded the therapeutic arsenal available to clinicians. These advancements are not only improving patient outcomes but also attracting investments in research and development, thereby accelerating the introduction of next-generation osteoporosis drugs. Furthermore, the adoption of combination therapies and personalized medicine approaches is gaining traction, enabling tailored treatment strategies that address individual patient needs and enhance overall disease management.

Healthcare infrastructure improvements and expanding access to medical care, particularly in emerging markets, are also contributing to the growth of the osteoporosis drugs market. As healthcare systems in Asia Pacific, Latin America, and other regions strengthen their diagnostic and treatment capabilities, more patients are being identified and treated for osteoporosis. The increasing penetration of health insurance and government-led initiatives to promote bone health are further supporting market expansion. Moreover, the rising adoption of digital health technologies, such as telemedicine and e-prescriptions, is making it easier for patients to access osteoporosis medications and adhere to treatment regimens, thereby improving clinical outcomes and boosting market revenues.

From a regional perspective, North America currently leads the osteoporosis drugs market, accounting for the largest share due to its advanced healthcare infrastructure, high disease awareness, and robust reimbursement policies. Europe follows closely, supported by a well-established pharmaceutical industry and proactive government initiatives for osteoporosis management. The Asia Pacific region is expected to witness the fastest growth during the forecast period, driven by a rapidly aging population, increasing healthcare expenditure, and growing awareness about osteoporosis. Latin America and the Middle East & Africa, while smaller in market size, are also exhibiting steady growth as healthcare access improves and educational efforts intensify. Overall, the regional outlook for the osteoporosis drugs market remains positive, with significant opportunities for expansion in both developed and emerging economies.

Drug Class Analysis

The osteoporosis drugs market is segmented by drug class into bisphosphonates, selective estrogen receptor modulators (SERMs), parathyroid hormone therapy, calcitonin, RANK ligand inhibitors, and others. Among these, bisphosphonates continue to dominate the market due to their proven efficacy in reducing bone resorption and fracture risk. Widely prescribed for both prevention and treatment, bisphosphonates such as alendronate and risedronate are considered first-line therapies for osteoporosis. Their long-standing safety profile, cost-effectiveness, and availability in both oral and intravenous formulations make them the preferred choice for

Background Osteoporosis presents a significant global health challenge, compromising bone quality and elevating fracture susceptibility. While dual-energy x-ray absorptiometry (DXA) stands as the gold standard for bone mineral density (BMD) assessment and osteoporosis diagnosis, its costliness and complexity impede widespread screening adoption. Predictive modeling of BMD, leveraging genetic and clinical data, emerges as a more viable and cost-effective approach for osteoporosis and fracture risk evaluation. Methods and Findings We developed BMD prediction models for the femoral neck (FNK) and lumbar spine (SPN) using various methods within a UK Biobank (UKBB) training set comprising 17,964 individuals from the British white population. Models based on Regression with Least Absolute Shrinkage and Selection Operator (LASSO), selected based on the coefficient of determination (R2) from a model selection subset of 5,973 individuals from the British white population, underwent testing on five UKBB test sets and 12 independent cohorts of diverse ancestries, totaling over 15,000 individuals. Furthermore, we assessed the correlation of predicted BMDs with fragility fractures in a distinct case-control set of over 287,000 participants lacking DXA-BMDs in the UKBB of the European white population. Incorporating genetic factors marginally improved predictions, capturing an additional 2.3% variation for FNK-BMD and 3% for SPN-BMD over clinical factors alone. Predicted BMDs exhibited significant associations with fragility fracture risk in the European white population. Nonetheless, the predictive model's performance varied between the UKBB population of other ethnic groups and the independent cohorts. Conclusions Our study yields novel insights into predicting osteoporosis and fracture risk. Genetic factors enhance BMD predictive performance beyond clinical factors alone. Adjusting inclusion thresholds for genetic variants (e.g., 5×10^(-6) or 5×10^(-7)) rather than solely considering genome-wide association study (GWAS)-significant variants may further refine the model's explanatory power for BMD variations. This study also underscores the imperative for training models on diverse population to bolster predictive performance across various ethnic and geographical populations.

The database contains the following clinical, questionnaire and socio-demographic data suitable for cross-sectional and longitudinal analyses:-Body composition: dual-energy x-ray absorptiometry (DXA) measures of the lumbar spine (posterior-anterior projection), proximal femur, whole body and forearm (ultradistal forearm and distal 33%)-Other clinical assessments: body weight, height, arm span, waist and hip circumferences, blood pressure, visual acuity, muscle strength, functional reach test and timed ‘up-&-go’ test.-Mental health: Major axis psychiatric disorders diagnosed using a Structured Clinical Interview.-Blood and urine collections: blood and urine collected after an overnight fast.-Questionnaires: exposure to disease, use of medications and supplements, diet, mobility, physical activity, sleep, sun exposure, falls and fractures, alcohol and tobacco use, reproductive history, family history of fractures and disease, quality of life, pain, anxiety and depression.-Socio-demographics: Country of birth, ethnicity, marital status, education, housing and employment status, occupation, socioeconomic Index for Areas (SEIFA) scores.