Osteoporosis among household women: A growing but neglected phenomenon

Hiremath, Ravishekar N; Yadav, Amita; Ghodke, Sandhya; Yadav, Jyoti; Latwal, Sumit; Kotwal, Atul

doi:10.1016/j.mjafi.2016.09.007

Cited by 12 publications

(7 citation statements)

References 27 publications

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“…1,4 The same has been mentioned in the article as one of the limitation of the study and discussed. 5 We agree with the conclusion drawn by the reader that ''this particular study at best gives us an indication that there is an increased risk of fracture among this cohort of patient and there is a need for educating the target population regarding bone health and preventive measures. However, based on the data of QUS alone, it is premature to draw conclusion of increased osteoporosis or low bone mass in this cohort'' (sic).…”

supporting

confidence: 78%

Qualitative ultrasonography for bone health: Are we there yet?

Verma

Menon

2018

Medical Journal Armed Forces India

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supporting

confidence: 78%

Qualitative ultrasonography for bone health: Are we there yet?

Verma

Menon

2018

Medical Journal Armed Forces India

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“…65 Unadjusted BMD data were not reported for 1 study. 66 Nine additional studies were excluded from this systematic review and meta-analysis because LS, FN, or WB BMD data were not presented; 5 of these studies measured BMD at the calcaneum, 61,[67][68][69][70] 3 measured it at the radius (mid and distal), [71][72][73] and 1 measured it at the proximal phalanx of the third finger. 74 Consequently, the final sample consisted of 20 articles (15 including BMD and 5 including fracture rate data) ( Figure 1).…”

Section: Search Summarymentioning

confidence: 99%

Veganism, vegetarianism, bone mineral density, and fracture risk: a systematic review and meta-analysis

et al. 2018

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The numbers of vegans and vegetarians have increased in the last decades. However, the impact of these diets on bone health is still under debate. Objective: This systematic review and meta-analysis sought to study the impact of vegetarian and vegan diets on bone mineral density (BMD) and fracture risk. Data Sources: A systematic search was conducted of PubMed, Scopus, and Science Direct, covering the period from the respective start date of each database to November 2017. Data Extraction: Two investigators evaluated 275 studies against the inclusion criteria (original studies in humans, written in English or Spanish and including vegetarian or vegan diets and omnivorous diets as factors with BMD values for the whole body, lumbar spine, or femoral neck and/or the number of fractures as the outcome) and exclusion criteria (articles that did not include imaging or studies that included participants who had suffered a fracture before starting the vegetarian or vegan diet). The quality assessment tool for observational cohort and cross-sectional studies was used to assess the quality of the studies. Results: Twenty studies including 37 134 participants met the inclusion criteria. Compared with omnivores, vegetarians and vegans had lower BMD at the femoral neck and lumbar spine and vegans also had higher fracture rates. Conclusions: Vegetarian and vegan diets should be planned to avoid negative consequences on bone health. Systematic Review Registration: PROSPERO registration no. CRD42017055508.

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“…We found that the top five predictors were age, gender, disease history (DM, hypertension), and living habits (smoking). The results of Hiremath [28] uncovered that the risk increased by 20% with every 5 years increase of age. Besides, Fu et al [29] believed that the most people aged 45-50 may suffer from osteoporosis, which is almost a common feature of human aging, and the incidence of a fracture depends on the age of the subject.…”

Section: Establishment Of the Prediction Models For Osteoporosismentioning

confidence: 98%

Prediction model for the risk of osteoporosis incorporating factors of disease history and living habits in physical examination of population in Chongqing, Southwest China: based on artificial neural network

Wang

Sun

et al. 2021

BMC Public Health

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Background Osteoporosis is a gradually recognized health problem with risks related to disease history and living habits. This study aims to establish the optimal prediction model by comparing the performance of four prediction models that incorporated disease history and living habits in predicting the risk of Osteoporosis in Chongqing adults. Methods We conduct a cross-sectional survey with convenience sampling in this study. We use a questionnaire From January 2019 to December 2019 to collect data on disease history and adults’ living habits who got dual-energy X-ray absorptiometry. We established the prediction models of osteoporosis in three steps. Firstly, we performed feature selection to identify risk factors related to osteoporosis. Secondly, the qualified participants were randomly divided into a training set and a test set in the ratio of 7:3. Then the prediction models of osteoporosis were established based on Artificial Neural Network (ANN), Deep Belief Network (DBN), Support Vector Machine (SVM) and combinatorial heuristic method (Genetic Algorithm - Decision Tree (GA-DT)). Finally, we compared the prediction models’ performance through accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) to select the optimal prediction model. Results The univariate logistic model found that taking calcium tablet (odds ratio [OR] = 0.431), SBP (OR = 1.010), fracture (OR = 1.796), coronary heart disease (OR = 4.299), drinking alcohol (OR = 1.835), physical exercise (OR = 0.747) and other factors were related to the risk of osteoporosis. The AUCs of the training set and test set of the prediction models based on ANN, DBN, SVM and GA-DT were 0.901, 0.762; 0.622, 0.618; 0.698, 0.627; 0.744, 0.724, respectively. After evaluating four prediction models’ performance, we selected a three-layer back propagation neural network (BPNN) with 18, 4, and 1 neuron in the input layer, hidden and output layers respectively, as the optimal prediction model. When the probability was greater than 0.330, osteoporosis would occur. Conclusions Compared with DBN, SVM and GA-DT, the established ANN model had the best prediction ability and can be used to predict the risk of osteoporosis in physical examination of the Chongqing population. The model needs to be further improved through large sample research.

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Osteoporosis among household women: A growing but neglected phenomenon

Cited by 12 publications

References 27 publications

Qualitative ultrasonography for bone health: Are we there yet?

Qualitative ultrasonography for bone health: Are we there yet?

Veganism, vegetarianism, bone mineral density, and fracture risk: a systematic review and meta-analysis

Prediction model for the risk of osteoporosis incorporating factors of disease history and living habits in physical examination of population in Chongqing, Southwest China: based on artificial neural network

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