A cross-sectional study to estimate associations between education level and osteoporosis in a Chinese postmenopausal women sample.
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Our research aims to investigate the associations between education level and osteoporosis (OP) in Chinese postmenopausal women.A large-scale, community-based, cross-sectional study was conducted to examine the associations between education level and OP. A self-reported questionnaire was used to access the demographical information and medical history of the participants. A total of 1905 postmenopausal women were available for data analysis in this study. Multiple regression models controlling for confounding factors to include education level were performed to investigate the relationship with OP.The prevalence of OP was 28.29% in our study sample. Multivariate linear regression analyses adjusted for relevant potential confounding factors detected significant associations between education level and T-score (β = 0.025, P-value = 0.095, 95% CI: -0.004-0.055 for model 1; and β = 0.092, P-value = 0.032, 95% CI: 0.008-0.175 for model 2). Multivariate logistic regression analyses detected significant associations between education level and OP in model 1 (P-value = 0.070 for model 1, Table 5), while no significant associations was reported in model 2 (P value = 0.131). In participants with high education levels, the OR for OP was 0.914 (95% CI: 0.830-1.007).The findings indicated that education level was independently and significantly associated with OP. The prevalence of OP was more frequent in Chinese postmenopausal women with low educational status.Keywords:
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Background Functional constipation (FC) is the most common gastrointestinal disorder of childhood and has a multifactorial etiology.We aimed to assess dietary habits in Greek children with FC compared to the general population (control group, CG).Methods This was a subgroup analysis of a school-based, cross-sectional study carried out in children 6-18 years of age, between January and June 2014, using the Rome III criteria for the diagnosis of FC.Dietary parameters, as well as socioeconomic and demographic data and their association with the likelihood of FC, were analyzed through multivariate logistic regression analysis and expressed as odds ratios (OR).Results A total of 1439 children (1218 CG, 221 FC) were included in the analysis.The final model showed that consumption of was the only dietary parameter significantly related to FC; higher frequency of consumption was inversely related to the likelihood of FC (OR: 0.98, 95% CI: 0.96, 0.99, P=0.048).Significant socioeconomic confounders with a positive association with FC were: parental educational level, victimization, physical activity and number of adults at home. ConclusionIncreased frequency of fiber consumption is significantly associated with higher odds of FC irrespective of socioeconomic background and lifestyle parameters.Interventional studies are required to validate these cross-sectional observations.
Functional constipation
Cross-sectional study
Odds
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In the care of patients with voice disorders, physicians, speech pathologists, and other health care professionals routinely make diagnoses, recommend treatment, and evaluate outcomes. Although objective and subjective measures exist, unfortunately, there is no widely accepted, valid method for classifying voice disorders and assessing outcome after voice treatment. In the present research, the relationship between two previously created multivariate objective voice function indices, the weighted odds ratio index and the multivariate logistic regression index, and subjective assessment of voice function was evaluated. Twenty-three adult patients presenting to a speech science laboratory for evaluation of voice disorders were studied in this prospective observational study together with 12 normal volunteers as controls. Vocal function was measured on 14 different parameters with a protocol that included a multichannel input for simultaneous assessment of acoustic and physiological parameters. Each patient was recorded reading the standard passage “The North Wind and the Sun,” and recordings were then evaluated by the GRBAS scale. Overall, there was a statistically significant relationship between the weighted odds ratio index and multivariate logistic regression index and mean GRBAS scores. This research demonstrates that the voice function values calculated from two different multivariate objective voice function indices are significantly associated with subjective voice assessments. These multivariate objective voice indices may be appropriate for use in clinical trials and outcomes research on treatment effectiveness for voice disorders.
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Third-Variable effect refers to the intervening effect from a third variable (called mediators or confounders) to the observed relationship between an exposure and an outcome. The general multiple third-variable effect analysis method (TVEA) allows consideration of multiple mediators/confounders (MC) simultaneously and the use of linear and nonlinear predictive models for estimating MC effects. Previous studies have found that compared with non-Hispanic White population, Blacks and Hispanic Whites suffered disproportionally more with obesity and related chronic diseases. In this paper, we extend the general TVEA to deal with multivariate/multi-categorical predictors and multivariate response variables. We designed algorithms and an R package for this extension and applied MMA on the NHANES data to identify MCs and quantify the indirect effect of each MC in explaining both racial and ethnic disparities in obesity and the body mass index (BMI) simultaneously. We considered a number of socio-demographic variables, individual factors, and environmental variables as potential MCs and found that some of the ethnic/racial differences in obesity and BMI were explained by the included variables.
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This study aims to identify significant predictors of 3 outcomes in the aged patients and non-elderly with multi-space infections of the head and neck: the number of incisions, the length of hospital stay, and complications.A retrospective study was conducted on 242 patients receiving treatment for severe multi-space infections of the head and neck region. Study variables were categorized as demographics, clinical parameters, and laboratory values. The outcome variables were the number of incisions, length of hospital stay, and complications. Multivariate linear and logistic regression techniques were used to measure associations between study variables and the outcome variables. Statistical analyses of the results between groups were performed using the Student t test and χ.Multivariate analyses, controlling for confounding variables, indicated that the number of spaces affected was a predictor of the number of incisions and complications in the elderly group. In the non-elderly group, the number of spaces affected was a predictor of the number of incisions and length of hospital stay. Admission blood glucose level and admission white blood cell count were the predictors of complications in the non-elderly.This study identifies different study variables as predictors of outcomes in treating multi-space infections of the head and neck in the elderly and non-elderly group. The number of spaces affected is the most important predictor.
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Background: Our research aims to investigate the associations between education level and osteoporo- sis (OP) in Chinese postmenopausal women. Methods: A large-scale, community-based, cross-sectional study was conducted to examine the associations between education level and OP. A self-reported questionnaire was used to access the demographical information and medical history of the participants. A total of 1905 postmenopausal women were available for data analysis in this study. Multiple regression models controlling for confounding factors to include education level were performed to investigate the relationship with OP. Results: The prevalence of OP was 28.29% in our study sample. Multivariate linear regression analyses adjusted for relevant potential confounding factors detected significant associations between education level and T-score (β = 0.025, P-value = 0.095, 95% CI: -0.004-0.055 for model 1; and β = 0.092, P-value = 0.032, 95% CI: 0.008-0.175 for model 2). Multivariate logistic regression analyses detected significant associations between education level and OP in model 1 (P-value = 0.070 for model 1, Table 5), while no significant associations was reported in model 2 (P value = 0.131). In participants with high education levels, the OR for OP was 0.914 (95% CI: 0.830-1.007). Conclusion: The findings indicated that education level was independently and significantly associated with OP. The prevalence of OP was more frequent in Chinese postmenopausal women with low educational status.
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The results of univariate and multivariate statistical analysis were compared in identifying predictive factors of the development of recurrent acuta otitis media (RAOM) after an initial episode of acute otitis media (AOM) in 121 children. Univariate correlations between the development of RAOM and potential risk factors were analysed, and variables at p <0.10 were incorporated into the stepwise multiple logistic regression analysis. The comparisons between the univariate and multivariate analysis in identifying the predictive factors were made and the importance of changing the dependent variables in the multivariate analysis was analysed. It seems that univariate analysis is over-sensitive, but multivariate analysis is over-conservative in finding possible predictors of RAOM. Choosing the right and accurate dependent and independent variables in the multivariate analysis is extremely important, when this method is used.
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Univariate analysis
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Self-reported diet is prone to measurement error. Analytical models of diet may include several foods or nutrients to avoid confounding. Such multivariate models of diet may be affected by errors correlated among the dietary covariates, which may introduce bias of unpredictable direction and magnitude. The authors used 1993–1998 data from the European Prospective Investigation into Cancer and Nutrition in Norfolk, United Kingdom, to explore univariate and multivariate regression models relating nutrient intake estimated from a 7-day diet record or a food frequency questionnaire to plasma levels of vitamin C. The purpose was to provide an empirical examination of the effect of two different multivariate error structures in the assessment of dietary intake on multivariate regression models, in a situation where the underlying relation between the independent and dependent variables is approximately known. Emphasis was put on the control for confounding and the effect of different methods of controlling for estimated energy intake. The results for standard multivariate regression models were consistent with considerable correlated error, introducing spurious associations between some nutrients and the dependent variable and leading to instability of the parameter estimates if energy was included in the model. Energy adjustment using regression residuals or energy density models led to improved parameter stability.
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Background: The variety of characteristics related to odontoma research, including an unexplored one such as size, merits a multivariate approach that allows the adequate drawing of inferences with pertinent conclusions.The objective of this study is to establish the possible association between some characteristics related to the odontoma, tumor size among them.Material and Methods: The sociodemographic characteristics of 60 patients were evaluated.Diagnosis, size, location, type of treatment performed, and prognosis were determined.These data were analyzed descriptively and through multivariate models.Results: Thirty-four compound and 26 complex odontomas in 32 men and 28 women were observed.The age average of patients was 15.6±11 years.Most of the odontomas presented a size inferior to 10 mm.A statistically significant association was observed between the routine radiographic finding and the absence of dental eruption (p=0.0001).The model of linear regression adjusted between odontoma size and age (β=0.321,p=0.01), as well as the model of logistic regression adjusted between gender (men) and tumor size (OR=12; 1.7 -93 IC 95%, (p=0.01) were statistically significant.Conclusions: Statistically significant associations between odontoma size and age, and between the male gender and odontomas smaller than 10 mm were found adjusting by other confounding variables.These results could grant clinicians a greater knowledge of the context of odontoma characteristics, which in turn could favor a better diagnostic and therapeutic decision-making.
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