Purpose: This study assessed within a Midwestern LGBT population whether, and the extent to which, transgender identity was associated with elevated odds of reported discrimination, depression symptoms, and suicide attempts. Methods: Based on survey data collected online from respondents who self-identified as lesbian, gay, bisexual, and/or transgender persons over the age of 19 in Nebraska in 2010, this study performed bivariate t - or chi-square tests and multivariate logistic regression analysis to examine differences in reported discrimination, depression symptoms, suicide attempts, and self-acceptance of LGBT identity between 91 transgender and 676 nontransgender respondents. Results: After controlling for the effects of selected confounders, transgender identity was associated with higher odds of reported discrimination (OR=2.63, p <0.01), depression symptoms (OR=2.33, p <0.05), and attempted suicides (OR=2.59, p <0.01) when compared with nontransgender individuals. Self-acceptance of LGBT identity was associated with substantially lower odds of reporting depression symptoms (OR=0.46, p <0.001). Conclusion: Relative to nontransgender LGB individuals, transgender individuals were more likely to report discrimination, depression symptoms, and attempted suicides. Lack of self-acceptance of LGBT identity was associated with depression symptoms among transgender individuals.

In this study we seek to assess recent trends in complementary and alternative medicine (CAM) use based on a comparative analysis of data from the 2002 and 2007 National Health Interview Survey (NHIS). The findings suggest that CAM use, in particular the use of provider-based CAM therapies such as chiropractic care, massage, and acupuncture, have grown significantly in the U.S. This growth was more pronounced among non-Hispanic Whites than among racial and ethnic minorities, increasing an already existing White-minority gap in CAM use. Findings from this study also reveal that CAM use becomes more likely when access to conventional care has been restricted. In both 2002 and 2007, having unmet needs in medical care or having delayed care due to cost were associated with a higher chance of CAM use.

Background: It remains unclear how demographic and clinical characteristics are related to the risk of incident mild cognitive impairment (MCI) by its subtypes. Moreover, the contribution of the subtypes of incident MCI to the progression to dementia remains puzzling. Methods: We used data collected by the National Alzheimer Coordinating Center. Our analysis sample included cognitively normal subjects at baseline. The associations were examined using competing-risks survival regression models and Cox proportional hazards models. Results: About 16.3% of subjects developed incident MCI of whom 15.8% progressed to Alz­heimer disease (overall mean follow-up of 4.3 years). The risk of incident amnestic MCI (aMCI) was greater in subjects with 1 copy (subhazard ratio [SHR]: 1.23; 95% CI: 1.00–1.50) or 2 copies (SHR: 2.14; 95% CI: 1.49–3.05) of the APOE ε4 allele than in those who had no ε4 allele. Multiple-domain aMCI patients were more likely to progress to dementia than single-domain aMCI patients (hazard ratio: 2.14; 95% CI: 1.28–3.58). Conclusions: Cognitively normal subjects with an APOE ε4 allele had a higher likelihood of developing aMCI and the MCI subtype was associated with the dementia subtype. Our findings provide important information about practical indicators for the prediction of cognitive decline.

Background: The documented efficacy and promise of telemedicine in diabetes management does not necessarily mean that it can be easily translated into clinical practice. An important barrier concerns patient activation and engagement with telemedicine technology. Objective: To assess the importance of patient activation and engagement with remote patient monitoring technology in diabetes management among patients with type 2 diabetes. Methods: Ordinary least squares and logistic regression analyses were used to examine how patient activation and engagement with remote patient monitoring technology were related to changes in hemoglobin A1c (HbA1c) for 1,354 patients with type 2 diabetes monitored remotely for 3 months between 2015 and 2017. Results: Patients with more frequent and regular participation in remote monitoring had lower HbA1c levels at the end of the program. Compared to patients who uploaded their biometric data every 2 days or less frequently, patients who maintained an average frequency of one upload per day were less likely to have a postmonitoring HbA1c > 9% after adjusting for selected covariates on baseline demographics and health conditions. Conclusions: Higher levels of patient activation and engagement with remote patient monitoring technology were associated with better glycemic control outcomes. Developing targeted interventions for different groups of patients to promote their activation and engagement levels would be important to improve the effectiveness of remote patient monitoring in diabetes management.