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Obesity and osteoporosis are health problems with high impact on the morbidity and mortality rate. While the association between BMI and bone density is known, the combined effects of obesity and metabolic components on bone health have not yet been revealed. The objectives of this study were to determine the association between bone health and different phenotypes of obesity in an elderly population.This cross-sectional study was conducted on the data collected in the Bushehr Elderly Health Program (BEHP). The participants were classified in four groups based on the metabolic phenotypes of obesity (metabolic healthy obese (MHO), metabolic non-healthy non-obese (MNHNO), metabolic non-healthy obese (MNHO), and metabolic healthy non-obese (MHNO)). The association between osteoporosis and TBS and the metabolic phenotypes of obesity were assessed using multiple variable logistic regression models.Totally, 2378 people (1227 women) were considered for analyses. The prevalence of MHNO, MHO, MNHNO, and MNHO were 902 (39.9%), 138 (6.1%), 758 (33.5%), and 464 (20.5%), respectively. In the multivariate logistic regression models, those with MHO (OR 0.22; 95% CI 0.12-0.36), MNHNO (OR 0.52; 95% CI 0.4-0.66), and MNHO phenotypes (OR 0.22; 95% CI 0.16-0.3) had a significantly lower risk of osteoporosis. Likewise, those having MHO (OR 2.38; 95% CI 1.51-3.76), MNHNO (OR 1.49; 95% CI 1.11-2), and MNHO (OR 2.50; 95% CI 1.82-3.42) phenotypes were found to had higher risk of low bone quality as confirmed by TBS.The obese subjects have lower bone quality, regardless of their obesity phenotype.

The main findings of this study on the self-care behaviors contain "identification of knowledge gaps," "established networking for seeking information," "information from trust-to-distrust," "information-seeking inhibiting factors," "information-seeking facilitating factors," and "self-care behaviors based on required knowledge."Health information-seeking behavior affects self-care and could promote quality of life and life expectancy. This study aimed at assessing health information-seeking and self-care behaviors of women with osteoporosis in Iran.This study was conducted using a content analysis approach. Data were collected through semi-structured interviews with 15 women with osteoporosis aged above 50 years. The participants were selected by purposeful sampling. The data were analyzed by the conventional content analysis method using MAXQdata software version 10.From in-depth descriptions of the participants' experiences, 246 primary codes were extracted. Subsequently, constant comparison analysis was done and 35 sub-categories and 6 main categories have appeared from the data.Based on the experiences of women with osteoporosis, they received limited information from the health care providers, so they were seeking reliable information sources to meet their information needs. They obtained most of their information from other patients, family members, and network of friends. In the process of seeking information, they face various barriers such as lack of time in the health care team that affect their ability to self-care.The results can guide health policymakers, patient educators, health care providers, information specialists, and patients and their families.

Our purpose was to investigate the co-authorship network of Iranian researchers in the field of osteoporosis. We used 1328 documents retrieved from databases of PubMed, Scopus, and Web of Science in the analysis. The network had 183 authors in 13 clusters, low cohesion, and slow information flow between its members.This study aims to investigate the pattern and characteristics of cooperation between Iranian researchers in the field of osteoporosis through the co-authorship social network analysis.All papers on osteoporosis with at least one Iranian author were retrieved from medical databases of PubMed, Scopus, and Web of Science from 2009 to 2019. After the removal of duplicates, the title and abstract of the papers were reviewed by two independent reviewers, and screening was performed according to the inclusion and exclusion criteria. The data were entered into the BibExecl software, and the different spelling forms in the author names were manually merged. The authors' co-occurrence matrix was then developed and entered into the UCINET software and the cohesion indexes (density, diameter, and average distance) and centrality indexes (degree, betweenness, closeness, and eigenvector) for the co-authorship network were estimated. The institutions and countries of the authors of the entered papers were also used in the network analysis and their socio-graphs were drawn.We used 1328 documents in the analysis. The co-authorship network was constructed only for authors with at least 5 papers. The network had 183 nodes (authors) in 13 clusters. Its density was 0.063 and its number of components was 2. The large component encompassed 95.6% and the small component 4.4% of authors. The average distance in the main component of the network was 3 and its diameter was 6. Larijani B was ranked first in the network in terms of degree, betweenness, closeness, and eigenvector centrality. In terms of the contribution of organizations in osteoporosis publications, Tehran University of Medical Sciences (with 35.5% of papers published in WoS database), Shahid Beheshti University of Medical Sciences (14.7%), and Shiraz University of Medical Sciences (9.3%) retained in the first to third place, respectively. In papers published on the WoS, most Iranian authors have collaborated with authors from the USA, Belgium, Canada, and the UK respectively.The co-authorship network had low cohesion with slow information flow between its members. The collaboration with young researchers by the network's active, efficient, and broker authors will lead to the maintenance and development of the network.