Effectiveness of the Travelers Summer Research Fellowship Program in Preparing Premedical Students for a Career in Medicine

This study measured the effectiveness of the Travelers Summer Research Fellowship (T-SRF) Program for Premedical Students. No in-depth study has been conducted on the impact of its activities. A program-oriented qualitative summative evaluation approach and a logic model design were used to analyze survey responses for participants from four program years randomly chosen from 2000 to 2015, medical school enrollment records for participants from 1969 to 2015, physician practice locations for participants from 1969 to 2009, and interviews with a purposeful random sample of 10 physicians who were program participants from 2004 to 2008. Narrative inquiry consisted of audio recording, transcription, and analysis of individual accounts and participant experiences. The study revealed that participants valued interactions with physicians from backgrounds underrepresented in medicine. Talks on careers in medicine increased participants’ knowledge, and research projects helped develop skills. Cardiovascular physiology lectures introduced participants to the medical school learning experience and increased their confidence to apply to medical school successfully. T-SRF enhanced participants’ medical school applications and sharpened interviewing skills; 83% matriculated into medical school, 90% graduated, and 45% practice in HPSAs, MUAs/Ps, and rural areas. Recommendations included improving program orientation, making the cardiovascular physiology lectures and examinations more valuable experiences, re-evaluating the study skills curriculum, providing more clinical experiences, increasing the weekly stipend, improving maintenance of the alumni database, formally partnering admissions with the T-SRF program, helping alumni return to Weill Cornell as residents or fellows, and considering other ways to measure social concern. Further studies of T-SRF should be undertaken

The choice of self-rated health measures matter when predicting mortality: evidence from 10 years follow-up of the Australian longitudinal study of ageing

BACKGROUND Self-rated health (SRH) measures with different wording and reference points are often used as equivalent health indicators in public health surveys estimating health outcomes such as healthy life expectancies and mortality for older adults. Whilst the robust relationship between SRH and mortality is well established, it is not known how comparable different SRH items are in their relationship to mortality over time. We used a dynamic evaluation model to investigate the sensitivity of time-varying SRH measures with different reference points to predict mortality in older adults over time. METHODS We used seven waves of data from the Australian Longitudinal Study of Ageing (1992 to 2004; N = 1733, 52.6% males). Cox regression analysis was used to evaluate the relationship between three time-varying SRH measures (global, age-comparative and self-comparative reference point) with mortality in older adults (65+ years). RESULTS After accounting for other mortality risk factors, poor global SRH ratings increased mortality risk by 2.83 times compared to excellent ratings. In contrast, the mortality relationship with age-comparative and self-comparative SRH was moderated by age, revealing that these comparative SRH measures did not independently predict mortality for adults over 75 years of age in adjusted models. CONCLUSIONS We found that a global measure of SRH not referenced to age or self is the best predictor of mortality, and is the most reliable measure of self-perceived health for longitudinal research and population health estimates of healthy life expectancy in older adults. Findings emphasize that the SRH measures are not equivalent measures of health status.This study was funded by the South Australian Health Commission, the Australian Rotary Health Research Fund, the US National Institute of Health (Grant No. AG 08523-02) and the National Health and Medical Research Council (NHMRC; Grant No.229936). KJA is supported by NHMRC Fellowship No.366756

Infertility problems and mental health symptoms in a community-based sample: depressive symptoms among infertile men, but not women

Most researchers agree that men’s and women’s experiences of infertility are fundamentally different, and impacts upon the nature of psychological distress encountered. However, design flaws, including non-random samples unrepresentative of the general population, compromise many existing studies. Data derived from a random general community sample provides prevalence of current infertility, and permits examination of longitudinal associations between mental health symptoms and infertility among 1,978 participants aged 28-32 years. In the previous 12-months, infertility was experienced by 2.1% and 5.4% partnered men and women. Infertility independently predicted depressive symptomatology in men, and anxiety symptoms among women. Gender differences were sustained, even controlling for prior depression and anxiety. Health professionals are encouraged to proactively enquire about affective symptoms experienced by both women and men with infertility problems

Deriving prevalence estimates of depressive symptoms throughout middle and old age in those living in the community

BACKGROUND: There is considerable debate about the prevalence of depression in old age. Epidemiological surveys and clinical studies indicate mixed evidence for the association between depression and increasing age. We examined the prevalence of probable depression in the middle aged to the oldest old in a project designed specifically to investigate the aging process. METHODS: Community-living participants were drawn from several Australian longitudinal studies of aging that contributed to the Dynamic Analyses to Optimise Ageing (DYNOPTA) project. Different depression scales from the contributing studies were harmonized to create a binary variable that reflected "probable depression" based on existing cut-points for each harmonized scale. Weighted prevalence was benchmarked to the Australian population which could be compared with findings from the 1997 and 2007 National Surveys of Mental Health and Well-Being (NSMHWB). RESULTS: In the DYNOPTA project, females were more likely to report probable depression. This was consistent across age levels. Both NSMHWB surveys and DYNOPTA did not report a decline in the likelihood of reporting probable depression for the oldest old in comparison with mid-life. CONCLUSIONS: Inconsistency in the reports of late-life depression prevalence in previous epidemiological studies may be explained by either the exclusion and/or limited sampling of the oldest old. DYNOPTA addresses these limitations and the results indicated no change in the likelihood of reporting depression with increasing age. Further research should extend these findings to examine within-person change in a longitudinal context and control for health covariates.NHMRC (National Health and Medical Research Council of Australia

Applying a cumulative deficit model of frailty to dementia: progress and future challenges

The article by Song and colleagues presents findings from the Canadian Study of Health and Aging showing that the accumulation of health deficits, defined dichotomously and unqualified by severity or domain, predicted late-life dementia independent of chronological age. We identify strengths of this model, and also areas for future research. Importantly, this article broadens the perspective of research into measuring risk of dementia from focusing on specific neuropathological markers of dementia subtypes, to mechanisms underlying more general bodily vitality and health, as well as dysfunctions in repair. This work places late-life dementia in a new context, influenced more broadly by health maintenance, and less by specific neurological disease. While useful at a global level, the lack of specificity of this approach may ultimately limit its application to individual patients because without linking risk to etiology, assessment does not indicate an intervention. Ultimately, the article has value for stimulating debate about approaches to risk identification and risk reduction, suggesting that the current focus on cardiometabolic risk factors may be too limited.KJA is funded by NHMRC Research Fellowship # 1002560. RAD is supported in part by a Canada Research Chair (Tier 1). The research is supported by the Dementia Collaborative Research Centres (to KJA) and the National Institutes of Health (National Institute on Aging, R01 AG008235, to RAD)

Influence of the quasi-biennial oscillation on the extratropical winter stratosphere in an atmospheric general circulation model and in reanalysis data

The interannual variability of the stratospheric polar vortex during winter in both hemispheres is observed to correlate strongly with the phase of the quasi-biennial oscillation (QBO) in tropical stratospheric winds. It follows that the lack of a spontaneously generated QBO in most atmospheric general circulation models (AGCMs) adversely affects the nature of polar variability in such models. This study examines QBO–vortex coupling in an AGCM in which a QBO is spontaneously induced by resolved and parameterized waves. The QBO–vortex coupling in the AGCM compares favorably to that seen in reanalysis data [from the 40-yr ECMWF Re-Analysis (ERA-40)], provided that careful attention is given to the definition of QBO phase. A phase angle representation of the QBO is employed that is based on the two leading empirical orthogonal functions of equatorial zonal wind vertical profiles. This yields a QBO phase that serves as a proxy for the vertical structure of equatorial winds over the whole depth of the stratosphere and thus provides a means of subsampling the data to select QBO phases with similar vertical profiles of equatorial zonal wind. Using this subsampling, it is found that the QBO phase that induces the strongest polar vortex response in early winter differs from that which induces the strongest late-winter vortex response. This is true in both hemispheres and for both the AGCM and ERA-40. It follows that the strength and timing of QBO influence on the vortex may be affected by the partial seasonal synchronization of QBO phase transitions that occurs both in observations and in the model. This provides a mechanism by which changes in the strength of QBO–vortex correlations may exhibit variability on decadal time scales. In the model, such behavior occurs in the absence of external forcings or interannual variations in sea surface temperatures

The influence of smoking, sedentary lifestyle and obesity on cognitive impairment-free life expectancy

BACKGROUND Smoking, sedentary lifestyle and obesity are risk factors for mortality and dementia. However, their impact on cognitive impairment-free life expectancy (CIFLE)has not previously been estimated. METHODS Data were drawn from the DYNOPTA dataset which was derived by harmonizing and pooling common measures from five longitudinal ageing studies. Participants for whom the Mini-Mental State Examination was available were included (N¼8111,48.6% men). Data on education, sex, body mass index, smoking and sedentary lifestyle were collected and mortality data were obtained from Government Records via data linkage.Total life expectancy (LE), CIFLE and years spent with cognitive impairment (CILE)were estimated for each risk factor and total burden of risk factors. RESULTS CILE was approximately 2 years for men and 3 years for women, regardless of age. For men and women respectively, reduced LE associated with smoking was 3.82and 5.88 years, associated with obesity was 0.62 and 1.72 years and associated with being sedentary was 2.50 and 2.89 years. Absence of each risk factor was associated with longer LE and CIFLE, but also longer CILE for smoking in women and being sedentary in both sexes. Compared with participants with no risk factors, those with 2þ had shorter CIFLE of up to 3.5 years depending on gender and education level. CONCLUSIONS Population level reductions in smoking, sedentary lifestyle and obesity increase longevity and number of years lived without cognitive impairment. Years lived with cognitive impairment may also increase.This work was supported by a National Health and Medical Research Council grant # 410215 and by the Australian Research Council Centre of Excellence in Population Ageing Research (CE110001029). K.J.A is funded by NHMRC Fellowship #1002560. C.J. is funded by the AXA Research Fund

A self-report risk index to predict occurrence of dementia in three independent cohorts of older adults: The ANU-ADRI

Background and Aims: The Australian National University AD Risk Index (ANU-ADRI, http://anuadri.anu.edu.au) is a self-report risk index developed using an evidence-based medicine approach to measure risk of Alzheimer's disease (AD). We aimed to evaluate the extent to which the ANU-ADRI can predict the risk of AD in older adults and to compare the ANU-ADRI to the dementia risk index developed from the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study for middle-aged cohorts. Methods: This study included three validation cohorts, i.e., the Rush Memory and Aging Study (MAP) (n = 903, age ≥53 years), the Kungsholmen Project (KP) (n = 905, age ≥75 years), and the Cardiovascular Health Cognition Study (CVHS) (n = 2496, age ≥65 years) that were each followed for dementia. Baseline data were collected on exposure to the 15 risk factors included in the ANU-ADRI of which MAP had 10, KP had 8 and CVHS had 9. Risk scores and C-statistics were computed for individual participants for the ANU-ADRI and the CAIDE index. Results: For the ANU-ADRI using available data, the MAP study c-statistic was 0.637 (95% CI 0.596-0.678), for the KP study it was 0.740 (0.712-0.768) and for the CVHS it was 0.733 (0.691-0.776) for predicting AD. When a common set of risk and protective factors were used c-statistics were 0.689 (95% CI 0.650-0.727), 0.666 (0.628-0.704) and 0.734 (0.707-0.761) for MAP, KP and CVHS respectively. Results for CAIDE ranged from c-statistics of 0.488 (0.427-0.554) to 0.595 (0.565-0.625). Conclusion: A composite risk score derived from the ANU-ADRI weights including 8-10 risk or protective factors is a valid, self-report tool to identify those at risk of AD and dementia. The accuracy can be further improved in studies including more risk factors and younger cohorts with long-term follow-up. © 2014 Anstey et al

Longitudinal associations between activity and cognition vary by age, activity type, and cognitive domain

The demonstration of correlated change is critical to understanding the relationship between activity engagement and cognitive functioning in older adulthood. Changes in activity have been shown to be related to changes in cognition, but little attention has been devoted to how this relationship may vary between specific activity types, cognitive domains, and age groups. Participants initially aged 65−98 years (M = 77.46 years) from the Australian Longitudinal Study of Ageing (n = 1,321) completed measurements of activity (i.e., cognitive, group social, one-on-one social, and physical) and cognition (i.e., perceptual speed, and immediate and delayed episodic memory) at baseline, 2, 8, 11, and 15 years later. Bivariate latent growth curve models covarying for education, sex, and baseline age and medical conditions revealed multiple positive-level relations between activity and cognitive performance, but activity level was not related to later cognitive change. Change in perceptual speed over 15 years was positively associated with change in cognitive activity, and change in immediate episodic memory was positively associated with change in one-on-one social activity. Old-old adults showed a stronger change−change covariance for mentally stimulating activity in relation to perceptual speed than did young-old adults. The differentiation by activity type, cognitive domain, and age contributes to the growing evidence that there is variation in the way cognitive ability at different ages is related to activity.NHMRC Fellowship No. 1002560 and the ARC Centre of Excellence in Population Ageing Research (project # CE110001029)