Prevalence and Patterns of Risk of Osteoporosis in Bangladeshi Adult Population: An Analysis of Calcaneus Quantitative Ultrasound Measurements

Ali, Mohammad; Uddin, Zakir; Hossain, Ahmed

doi:10.3390/osteology1040018

Cited by 5 publications

(6 citation statements)

References 40 publications

(48 reference statements)

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“…Furthermore, consistent with our findings, the prevalence of vitamin D deficiency among patients in India experiencing low back pain was approximately 50% [23]. However, we did not find a significant sex-specific difference in vitamin D deficiency, which is incongruent with the findings of previous studies [17,24].…”

Section: Discussionsupporting

confidence: 67%

Factors associated with vitamin D deficiency among patients with musculoskeletal disorders seeking physiotherapy intervention: a hospital-based observational study

Ali

Uddin

2022

BMC Musculoskelet Disord

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Background A considerable number of studies have suggested that there is a strong correlation between 25-hydroxyvitamin D or vitamin D levels and overall health, with reported impacts ranging from mental health and vital organ health to musculoskeletal health. This study aimed to determine the prevalence of 25-hydroxyvitamin D deficiency and identify its associated factors among patients with musculoskeletal disorders (MSDs) currently seeking medical attention. Methods A total of 143 patients with MSDs were randomly selected for blood sample collection to measure serum 25-hydroxyvitamin D levels. Descriptive statistics were used to describe the demographic and clinical characteristics of the study participants. Multiple logistic regression analyses were performed to compute the adjusted odds ratio. Results Overall, 53.1% of patients had vitamin D deficiency. Vitamin D deficiency was more prevalent among patients with higher body mass index, a bachelor’s degree, lower sun exposure time, and lower serum calcium levels and those living in an urban setting. The multiple logistic regression model suggested that the duration of weekly sun exposure and living location were the independent predictors of vitamin D deficiency. Conclusion It is recommended for patients with MSDs to participate in routine physical exercise, consume calcium- and vitamin D-enriched foods, and have regular sun exposure for minimizing the risk of vitamin D deficiency.

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Section: Discussionsupporting

confidence: 67%

Factors associated with vitamin D deficiency among patients with musculoskeletal disorders seeking physiotherapy intervention: a hospital-based observational study

Ali

Uddin

2022

BMC Musculoskelet Disord

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“…Ali et al [9] conducted a cross-sectional study on 526 adults Bangladeshi people based on risk factors such as age, BMI, smoking habit, physical activity, education, previous disease (diabetes, cardiovascular disease, etc.) history, Quantitative Ultrasound (QUS) bone health test, etc.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Dataset Approach Performance (%) et al [20] BMD & Dental panoramic radiography data CNN, VGG16, VGG16-TR, VGG16-TR-FT 0.840 Yamamoto et al [25] Hip radiography image data ResNet (18, 34, 50, 101, 152) 0.809 Faysal et al [22] Clinical attributes data Cross-sectional study Not available Ali et al [9] Clinical attributes data Cross-sectional study Not available Wani et al [27] Knee x-ray image & Clinical attributes dataset AlexNet, VGGNet-16, ResNet, VGGNet-19 90.91 Iliou et al [28] Clinical attributes dataset RBFNetwork, NBTree, REPTree, LWL 71.74 Shim et al [23] KNHANES-V1 and V2 KNN, DT, RF, GBM, SVM, ANN, LR 74.9 Lin et al [29] Wan Fang Hospital, Taiwan clinical data ANN, LR, SVM, RF 75.00 Huang et al [30] CT scan images LR, RF, SVM, XGBoost, GNB, GBM 0.81 Bui et al [31] Health Information System Clinical database LR, SVM, NN, RF, OSTA 0.85 Kim et al [24] KNHANES-V1 SVM, RF, ANN, LR, OST 76.70 Devikanniga et al [26] Lumber spine & Femoral neck image data MBO-ANN for Lumber spine 97.9 Engels et al [21] Clinical attributes data LR, RUS Boost, Super learner, XGBoost 70.4 Bold indicates the results of the proposed method.…”

Section: Authormentioning

confidence: 99%

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Intensive Statistical Exploration to Identify Osteoporosis Predisposing Factors and Optimizing Recognition Performance With Integrated GP Kernels

Amin,

Reza,

Maniruzzaman

et al. 2023

IEEE Access

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O STEOPOROSIS, a common skeletal disorder, necessitates the identification of its risk factors to develop effective preventive measures. It is crucial to identify the underlying risk factors and their relationships with the response class attribute. Different machine learning (ML) algorithms and feature selection approaches are used to estimate the risk of osteoporosis. However, ML-based algorithms may struggle to detect risk factors as well as grading of osteoporosis due to different measurement scale of data and their probability distributional assumptions. Violation of these assumptions and results interpretation may be improper in the presence of heteroscedasticity, or unequal variance in data. In this study, we seek to overcome distribution assumption constraints and improve the interpretability of our results by using rigorous statistical approaches, ensuring a robust and trustworthy study of osteoporosis risk variables. The study dataset consists of 40 clinical, lifestyle, and genetic attributes, allowing for a comprehensive analysis of potential risk factors associated with osteoporosis. In the analysis, after confirming the normality assumption using Kolmogorov-Smirnov and Shapiro-Wilk tests, independent t-test assess the factor ALT, FBG, HDL-C, LDL-C, FNT, TL, TLT, and URIC has a substantial impact on the risk of developing osteoporosis. The Mann-Whitney U test for the non-normal FN variable likewise showed a p-value of less than 0.05, indicating that this variable has a significant effect on the likelihood of developing osteoporosis. Based on the chi-square test p-values for the categorical factors, gender, calcium, calcitriol, bisphosphonate, calcitonin, COPD, CAD, and drinking have a severe significant risk of osteoporosis. For developing the predictive Gaussian Process (GPs) model, we proposed two customized integrated GP kernels into the analysis to enhance the modeling of complex relationships within the data. The proposed GP kernel model (modified kernel 2) outperforms the other individual kernels in this experiment and has the best accuracy score of 86.64% and AUC score of 86.63% on osteoporosis data. Moreover, a simulation study is also conducted to robustify the proposed model, the results are improved by different evaluation matrices ranging in accuracy from 0.60-11.41% and AUC from 0.50-11.60%.

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“…Previous studies have reported a high prevalence of osteoporosis among women living in the community of Bangladesh, emphasizing the considerable physical and economic burdens imposed by osteoporosis and osteopenia on individuals and society within the country 22 . Given the substantial burden of osteopenia/osteoporosis in Bangladeshi women, it is imperative to implement appropriate intervention strategies aimed at minimizing future fractures and reducing the associated social and economic impact on society 23 .…”

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confidence: 99%

Unveiling the Burden of Osteoporosis: Exploring the Prevalence and Risk Factors among Postmenopausal Women in North Central Bangladesh.

Kha,

Kibria,

Hossain

et al. 2024

CeMeC Journal

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Background: Osteoporosis affects 30% of women globally between the ages of 40 and 50. This disease is among the top causes of death and disability among the elderly. This study aimed to examine the prevalence of primary osteoporosis and poor bone density in postmenopausal women, as well as their socio demographic, obstetric, and lifestyle risk factors. Aim: The purpose of this study is to investigate at the prevalence of osteoporosis and the risk factors linked with it in postmenopausal women. Methods: The present prospective cross-sectional study was conducted on postmenopausal women who visited orthopedics, gynecology, and medicine outpatient departments between August 2022 and March 2023; 539 women aged 45 to 80 years with verified menopause were recruited. The final recommendation was for 539 women to have bone mineral density testing utilizing dual energy X-ray absorptiometry. Socio-individual, obstetric-medical, short-form physical activity, and anthropometric questionnaires were administered. Chi-square and Student's t-tests were applied to categorical and continuous data, respectively, to assess the differences between the groups. In SPSS 26, P<0.05 was regarded to indicate significant connections. Results: In our study, 38.0% of participants were between56 and 60 years of age. The majority of the individuals (51.9%) were illiterate. 37.7% of respondents reported having six or more children. 3.6% of the sample smoked or chewed tobacco. 61.0 percent of individuals had menopause after the age of 45, and 48.8% of subjects had experienced menopause for more than ten years at the time of enrollment in the research. 83.5% of postmenopausal women were affected by osteoporotic fractures (osteoporosis: 40.0% and osteopenia: 43.5%). The incidence of osteoporosis rose as parity and abortion rates increased. The prevalence of osteoporosis was greater (P< 0.05) among those with a familial history of osteoporosis-related symptoms and fragility fracture, as well as a personal history of fragility fracture. Conclusion: Given the significant prevalence of primary osteoporosis and poor bone density in postmenopausal women, health education is essential for minimizing modifiable risk factors and mitigating the disease's consequences. Central Medical College Journal Vol 7 No 1 January 2023 Page: 32-40

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Prevalence and Patterns of Risk of Osteoporosis in Bangladeshi Adult Population: An Analysis of Calcaneus Quantitative Ultrasound Measurements

Cited by 5 publications

References 40 publications

Factors associated with vitamin D deficiency among patients with musculoskeletal disorders seeking physiotherapy intervention: a hospital-based observational study

Factors associated with vitamin D deficiency among patients with musculoskeletal disorders seeking physiotherapy intervention: a hospital-based observational study

Intensive Statistical Exploration to Identify Osteoporosis Predisposing Factors and Optimizing Recognition Performance With Integrated GP Kernels

Unveiling the Burden of Osteoporosis: Exploring the Prevalence and Risk Factors among Postmenopausal Women in North Central Bangladesh.

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