Racial Categories in Medical Practice: How Useful Are They?

Is it good medical practice for physicians to "eyeball" a patient's race when assessing their medical status or even to ask them to identify their race

Mortality Rate in Veterans with Multiple Chronic Conditions

Background: Among patients with multiple chronic conditions, there is increasing appreciation of the complex interrelatedness of diseases. Previous studies have focused on the prevalence and economic burden associated with multiple chronic conditions, much less is known about the mortality rate associated with specific combinations of multiple diseases. Objective: Measure the mortality rate in combinations of 11 chronic conditions. Design: Cohort study of veteran health care users. Participants Veterans between 55 and 64 years that used Veterans Health Administration health care services between October 1999 and September 2000. Measurements: Patients were identified as having one or more of the following: COPD, diabetes, hypertension, rheumatoid arthritis, osteoarthritis, asthma, depression, ischemic heart disease, dementia, stroke, and cancer. Mutually exclusive combinations of disease based on these conditions were created, and 5-year mortality rates were determined. Results: There were 741,847 persons included. The number in each group by a count of conditions was: none = 217,944 (29.34%); 1 = 221,111 (29.8%); 2 = 175,228 (23.6%); 3 = 86,447 (11.7%); and 4+ = 41,117 (5.5%). The 5-year mortality rate by the number of conditions was: none = 4.1%; 1 = 6.0%; 2 = 7.8%; 3 = 11.2%; 4+ = 16.7%. Among combinations with the same number of conditions, there was significant variability in mortality rates. Conclusions: Patients with multiple chronic conditions have higher mortality rates. Because there was significant variation in mortality across clusters with the same number of conditions, when studying patients with multiple coexisting illnesses, it is important to understand not only that several conditions may be present but that specific conditions can differentially impact the risk of mortality

R|S Atlas: Identifying Existing Cohort Study Data Resources to Accelerate Epidemiological Research on the Influence of Religion and Spirituality on Human Health

OBJECTIVE: Many studies have documented significant associations between religion and spirituality (R/S) and health, but relatively few prospective analyses exist that can support causal inferences. To date, there has been no systematic analysis of R/S survey items collected in US cohort studies. We conducted a systematic content analysis of all surveys ever fielded in 20 diverse US cohort studies funded by the National Institutes of Health (NIH) to identify all R/S-related items collected from each cohort\u27s baseline survey through 2014. DESIGN: An R|S Ontology was developed from our systematic content analysis to categorise all R/S survey items identified into key conceptual categories. A systematic literature review was completed for each R/S item to identify any cohort publications involving these items through 2018. RESULTS: Our content analysis identified 319 R/S survey items, reflecting 213 unique R/S constructs and 50 R|S Ontology categories. 193 of the 319 extant R/S survey items had been analysed in at least one published paper. Using these data, we created the R|S Atlas (https://atlas.mgh.harvard.edu/), a publicly available, online relational database that allows investigators to identify R/S survey items that have been collected by US cohorts, and to further refine searches by other key data available in cohorts that may be necessary for a given study (eg, race/ethnicity, availability of DNA or geocoded data). CONCLUSIONS: R|S Atlas not only allows researchers to identify available sources of R/S data in cohort studies but will also assist in identifying novel research questions that have yet to be explored within the context of US cohort studies

The Study on Stress, Spirituality, and Health (SSSH): Psychometric Evaluation and Initial Validation of the SSSH Baseline Spirituality Survey

This paper describes the development and initial psychometric testing of the baseline Spirituality Survey (SS-1) from the Study on Stress, Spirituality, and Health (SSSH) which contained a mixture of items selected from validated existing scales and new items generated to measure important constructs not captured by existing instruments. The purpose was to establish the validity of new and existing measures in our racially/ethnically diverse sample. Psychometric properties of the SS-1 were evaluated using standard psychometric analyses in 4,634 SSSH participants. Predictive validity of SS-1 scales was assessed in relation to the physical and mental health component scores from the Short-Form 12 Health Survey (SF-12). Scales exhibited adequate to strong psychometric properties and demonstrated construct and predictive validity. Overall, the correlational findings provide solid evidence that the SS-1 scales are associated with a wide range of relevant R/S attitudes, mental health, and to a lesser degree physical health

New research directions on disparities in obesity and type 2 diabetes

Obesity and type 2 diabetes disproportionately impact U.S. racial and ethnic minority communities and lowâ income populations. Improvements in implementing efficacious interventions to reduce the incidence of type 2 diabetes are underway (i.e., the National Diabetes Prevention Program), but challenges in effectively scalingâ up successful interventions and reaching atâ risk populations remain. In October 2017, the National Institutes of Health convened a workshop to understand how to (1) address socioeconomic and other environmental conditions that perpetuate disparities in the burden of obesity and type 2 diabetes; (2) design effective prevention and treatment strategies that are accessible, feasible, culturally relevant, and acceptable to diverse population groups; and (3) achieve sustainable health improvement approaches in communities with the greatest burden of these diseases. Common features of guiding frameworks to understand and address disparities and promote health equity were described. Promising research directions were identified in numerous areas, including study design, methodology, and core metrics; program implementation and scalability; the integration of medical care and social services; strategies to enhance patient empowerment; and understanding and addressing the impact of psychosocial stress on disease onset and progression in addition to factors that support resiliency and health.This report discusses a workshop convened by the National Institutes of Health to understand how to (1) address socioeconomic and other environmental conditions that perpetuate disparities in the burden of obesity and type 2 diabetes; (2) design effective prevention and treatment strategies that are accessible, feasible, culturally relevant, and acceptable to diverse population groups; and (3) achieve sustainable health improvement approaches in communities with the greatest burden of these diseases.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154507/1/nyas14270_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154507/2/nyas14270.pd

Investigating hyper-vigilance for social threat of lonely children

The hypothesis that lonely children show hypervigilance for social threat was examined in a series of three studies that employed different methods including advanced eye-tracking technology. Hypervigilance for social threat was operationalized as hostility to ambiguously motivated social exclusion in a variation of the hostile attribution paradigm (Study 1), scores on the Children’s Rejection-Sensitivity Questionnaire (Study 2), and visual attention to socially rejecting stimuli (Study 3). The participants were 185 children (11 years-7 months to 12 years-6 months), 248 children (9 years-4 months to 11 years-8 months) and 140 children (8 years-10 months to 12 years-10 months) in the three studies, respectively. Regression analyses showed that, with depressive symptoms covaried, there were quadratic relations between loneliness and these different measures of hypervigilance to social threat. As hypothesized, only children in the upper range of loneliness demonstrated elevated hostility to ambiguously motivated social exclusion, higher scores on the rejection sensitivity questionnaire, and disengagement difficulties when viewing socially rejecting stimuli. We found that very lonely children are hypersensitive to social threat

Multiple Chronic Conditions: Prevalence, Health Consequences, and Implications for Quality, Care Management, and Costs

Persons with multiple chronic conditions are a large and growing segment of the US population. However, little is known about how chronic conditions cluster, and the ramifications of having specific combinations of chronic conditions. Clinical guidelines and disease management programs focus on single conditions, and clinical research often excludes persons with multiple chronic conditions. Understanding how conditions in combination impact the burden of disease and the costs and quality of care received is critical to improving care for the 1 in 5 Americans with multiple chronic conditions. This Medline review of publications examining somatic chronic conditions co-occurring with 1 or more additional specific chronic illness between January 2000 and March 2007 summarizes the state of our understanding of the prevalence and health challenges of multiple chronic conditions and the implications for quality, care management, and costs

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group