Risk factors for vertebral fracture in menopausal or postmenopausal Japanese women with rheumatoid arthritis: a cross-sectional and longitudinal study

2006 ◽  
Vol 24 (2) ◽  
pp. 118-124 ◽  
Author(s):  
Katsumitsu Arai ◽  
Tadamasa Hanyu ◽  
Hiroya Sugitani ◽  
Takehiro Murai ◽  
Junichi Fujisawa ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Longitudinal Study ◽  
Vertebral Fracture ◽  
Japanese Women ◽  
Cross Sectional

Incidence of and risk factors for spondylolisthesis, scoliosis, and vertebral fracture in rheumatoid arthritis

2021 ◽  
Author(s):  
Kentaro Yamada ◽  
Akinobu Suzuki ◽  
Shinji Takahashi ◽  
Kentaro Inui ◽  
Tatsuya Koike ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Vertebral Fracture

scholarly journals Risk Factors for Infection with Soil Transmitted Helminths, Cryptosporidium spp., and Giardia duodenalis in Children Enrolled in Preschools in Kafue District, Zambia

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Joyce Siwila ◽  
Annette Olsen
Keyword(s):  
Risk Factors ◽  
Longitudinal Study ◽  
Significant Risk ◽  
Giardia Duodenalis ◽  
Significant Risk Factor ◽  
Cross Sectional Study ◽  
Parasitic Infections ◽  
Cross Sectional ◽  
Low Socioeconomic ◽  
Soil Transmitted Helminths

Intestinal parasitic infections are common among children worldwide. This study was aimed at determining risk factors for infection with soil transmitted helminths, Cryptosporidium spp., and Giardia duodenalis, among children in preschools. The study was in two parts: a cross-sectional study in which data were collected from 403 children from 10 preschools and a longitudinal study in which 100 children from four preschools from the previous 10 were selected. Prevalence of Ascaris lumbricoides was 12.0%, while that of hookworm was 8.3%. Overall prevalence of Cryptosporidium and G. duodenalis was 28.0% and 29.0%, respectively. Low education level of parent/guardian was a significant risk factor for A. lumbricoides (OR = 2.35, 95% CI: 1.02–5.41; P=0.04), while roofing types other than corrugated iron sheets were found to be protective for G. duodenalis infection in both bivariate and multivariate analyses (multivariate: OR = 0.67, 95% CI: 0.45–0.99; P=0.04). Low socioeconomic level was found to be protective for Cryptosporidium spp. infection in multivariate analysis (OR = 0.59, 95% CI: 0.35–0.99; P=0.04). In the longitudinal study, none of the factors were associated with either infection. These findings may have implications for other preschools in other districts in Zambia.

scholarly journals The Impact of Newer Biological Disease Modifying Anti-Rheumatic Drugs on Cardiovascular Risk Factors: A 12-Month Longitudinal Study in Rheumatoid Arthritis Patients Treated with Rituximab, Abatacept and Tociliziumab

PLoS ONE ◽  
2015 ◽  
Vol 10 (6) ◽  
pp. e0130709 ◽  
Author(s):  
Sella Aarrestad Provan ◽  
Inger Jorid Berg ◽  
Hilde Berner Hammer ◽  
Alexander Mathiessen ◽  
Tore Kristian Kvien ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Cardiovascular Risk ◽  
Longitudinal Study ◽  
Cardiovascular Risk Factors ◽  
Disease Modifying ◽  
The Impact

scholarly journals A Bayesian Model to Analyze the Association of Rheumatoid Arthritis With Risk Factors and Their Interactions

2021 ◽  
Vol 9 ◽  
Author(s):  
Leon Lufkin ◽  
Marko Budišić ◽  
Sumona Mondal ◽  
Shantanu Sur
Keyword(s):  
Rheumatoid Arthritis ◽  
Risk Factors ◽  
Characteristic Curve ◽  
Strong Association ◽  
Mixed Data ◽  
Validation Dataset ◽  
Individual Risk ◽  
Third Order ◽  
Cross Sectional ◽  
Organ Systems

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that commonly manifests as destructive joint inflammation but also affects multiple other organ systems. The pathogenesis of RA is complex where a variety of factors including comorbidities, demographic, and socioeconomic variables are known to associate with RA and influence the progress of the disease. In this work, we used a Bayesian logistic regression model to quantitatively assess how these factors influence the risk of RA, individually and through their interactions. Using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES), a set of 11 well-known RA risk factors such as age, gender, ethnicity, body mass index (BMI), and depression were selected to predict RA. We considered up to third-order interactions between the risk factors and implemented factor analysis of mixed data (FAMD) to account for both the continuous and categorical natures of these variables. The model was further optimized over the area under the receiver operating characteristic curve (AUC) using a genetic algorithm (GA) with the optimal predictive model having a smoothed AUC of 0.826 (95% CI: 0.801–0.850) on a validation dataset and 0.805 (95% CI: 0.781–0.829) on a holdout test dataset. Apart from corroborating the influence of individual risk factors on RA, our model identified a strong association of RA with multiple second- and third-order interactions, many of which involve age or BMI as one of the factors. This observation suggests a potential role of risk-factor interactions in RA disease mechanism. Furthermore, our findings on the contribution of RA risk factors and their interactions to disease prediction could be useful in developing strategies for early diagnosis of RA.

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