E Jeffrey Metter

National Institute on Aging, Baltimore, Maryland, United States

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Publications (168)767.33 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Persons with diabetes have accelerated muscle loss compared with their counterparts. The relationship of hyperglycemia per se to declines in muscle function has not been explored, yet has implications for developing appropriate intervention strategies to prevent muscle loss.
    Diabetes Care 11/2014; · 8.57 Impact Factor
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    ABSTRACT: To examine differences in a proxy measure of muscle quality across the adult life span and explore potential mechanisms of muscle quality change through identification of cross-sectional correlates of muscle quality. Cross-sectional study. Baltimore Longitudinal Study of Aging. Seven hundred eighty-six individuals with a mean age of 66.3 (range 26-96) (N = 786). A sensitivity analysis was conducted in a subset of participants matched according to sex, muscle mass, and body size. Muscle quality was operationalized as the ratio of knee-extension strength (isokinetic dynamometry) to thigh muscle cross-sectional area (computed tomography). Differences in muscle strength, muscle area, and muscle quality ratio with age were evaluated, and the association between the muscle quality ratio and measures reflecting domains of cognitive function, motor control, peripheral nerve function, adiposity, glucose homeostasis, and inflammation were assessed through multivariate regression analyses. A linear relationship between age and muscle quality ratio was observed, suggesting a gradual decline in muscle quality over the adult life course. Associations were observed between muscle quality ratio and measures of adiposity, as well as peroneal nerve motor conduction velocity, finger tapping speed, and memory performance (P < .01). The association between muscle quality ratio and nerve conduction velocity was maintained after adjustment for anthropometric measurements (P < .05). Muscle quality declines progressively with age over the adult life span and is affected by obesity and neurological factors. Studies are needed to clarify the mechanisms of these associations and their implications for functional outcomes.
    Journal of the American Geriatrics Society 01/2014; · 4.22 Impact Factor
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    ABSTRACT: Repeated failure in the Army Physical Fitness Test (APFT) is associated with lower fitness level, premature discharge, and significant career disruption, at high economic and health costs to the individual soldier and the U.S. Army. We used cost-effectiveness analysis to estimate the health and economic implications of two exercise interventions for Army National Guard (ARNG) soldiers who had failed the APFT, a traditional remediation program and a new pedometer-based program called Fitness for Life, involving individual counseling and follow-up telephone calls. Effectiveness of the interventions was analyzed in terms of APFT pass rates and calculated 10-year coronary heart disease risk. Costs were calculated based on tracking of resources used in the programs. APFT pass rates were 54.3% and 47.9%, respectively, for traditional and Fitness for Life programs, p = not significant. Neither program affected 10-year coronary heart disease risk. For assumed APFT pass rates up to 40% without any formal remediation, both the traditional remediation program and the ARNG Fitness for Life intervention had cost savings without significant group differences. Depending on the ARNG unit and personnel preference, although the Fitness for Life Program was more expensive and thus less cost-effective, either program could be cost-effective and of benefit to the military.
    Military medicine. 12/2013; 178(12):1353-7.
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    ABSTRACT: IMPORTANCE Peripheral glucose homeostasis has been implicated in the pathogenesis of Alzheimer disease (AD). The relationship among diabetes mellitus, insulin, and AD is an important area of investigation. However, whether cognitive impairment seen in those with diabetes is mediated by excess pathological features of AD or other related abnormalities, such as vascular disease, remains unclear. OBJECTIVE To investigate the association between serial measures of glucose intolerance and insulin resistance and in vivo brain β-amyloid burden, measured with carbon 11-labeled Pittsburgh Compound B (11C-PiB), and AD pathology at autopsy. DESIGN Scores calculated from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) and Braak criteria were correlated with measures of hyperglycemia, hyperinsulinemia, glucose intolerance, and insulin resistance in 197 participants who underwent autopsy after death and who had undergone 2 or more oral glucose tolerance tests (OGTT) using grouped analyses and a continuous mixed-models analysis. The same measures of glucose intolerance and insulin resistance were also correlated with brain 11C-PiB retention in an additional 53 living subjects from the Baltimore Longitudinal Study of Aging neuroimaging study. SETTING Prospective, serially assessed cohort of community-dwelling subjects. PARTICIPANTS Cohort 1 consisted of 197 participants enrolled in the Baltimore Longitudinal Study of Aging who had 2 or more OGTTs during life and a complete brain autopsy after death. Cohort 2 consisted of 53 living subjects who had 2 or more OGTTs and underwent brain 11C-PiB positron emission tomography. EXPOSURES Autopsy and 11C-PiB positron emission tomography. MAIN OUTCOMES AND MEASURES The correlation of brain markers of AD, including CERAD score, Braak score, and 11C-PiB retention, with serum markers of glucose homeostasis using grouped and continuous mixed-models analyses. RESULTS We found no significant correlations between measures of brain AD pathology or 11C-PiB β-amyloid load and glucose intolerance or insulin resistance in subjects who had a mean (SD) of 6.4 (3.2) OGTTs during 22.1 (8.0) years of follow-up. Thirty subjects with frank diabetes mellitus who received medications also had AD pathology scores that were similar to those of the cohort as a whole. CONCLUSIONS AND RELEVANCE In this prospective cohort with multiple assessments of glucose intolerance and insulin resistance, measures of glucose and insulin homeostasis are not associated with AD pathology and likely play little role in AD pathogenesis. Long-term therapeutic trials are important to elucidate this issue.
    JAMA neurology. 07/2013;
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    ABSTRACT: Objective To identify a standard physical performance test, which can predict 3-year incident mobility disability independent of demographics. Design Longitudinal cohort study. Setting Population-based middle-aged and older adult cohort assessment performed at a local geriatric clinical center. Participants Community-living middle-aged and older persons (age, 50–85y) without baseline mobility disability (N=622). Interventions Not applicable. Main Outcome Measures Mobility disability was ascertained at baseline and at 3-year follow-up using an established self-report method: self-reported inability to walk a quarter mile without resting or inability to walk up a flight of stairs unsupported. Physical performance tests included self-selected usual gait speed, time required to complete 5 times sit-to-stand (5TSTS), and 400-m brisk walking. Demographic variables age, sex, height, and weight were recorded. Results Overall, 13.5% participants reported 3-year incident mobility disability. Usual gait speed <1.2m/s, requiring >13.6 seconds to complete 5TSTS, and completing 400m at <1.19m/s walking speed were highly predictive of future mobility disability independent of demographics. Conclusions Inability to complete 5TSTS in <13.7 seconds can be a clinically convenient guideline for monitoring and for further assessment of middle-aged and older persons, in order to prevent or delay future mobility disability.
    Archives of Physical Medicine and Rehabilitation 05/2013; 94(5):994–997. · 2.44 Impact Factor
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    ABSTRACT: OBJECTIVE: To investigate whether the performance on 5 times sit-to-stand test (5tSTS) can predict subsequent falls, fall-related fracture, and activities of daily living (ADL) and instrumental activities of daily living (IADL) disability in older persons. METHODS: A total of 948 older adults (age ≥ 60) participated in this study. Ability and the time to finish 5tSTS were recorded at baseline. Number of falls, fall-related fractures, and the ability to complete ADL and IADL without assistance were recorded retrospectively at baseline and at the 3-year follow-up. RESULTS: Inability to complete 5tSTS was a marginal predictor of falls (OR = 4.22) and a significant predictor of ADL- (OR = 24.70) and IADL-related disability (OR = 17.10) at 3-year follow-up. The need of longer time to complete 5tSTS was predictive of developing IADL-related disability at 3-year follow-up (OR = 4.22 [> 16.6 s]; OR = 2.49 [13.7 - 16.6 s]). DISCUSSION: 5tSTS is an easily administered tool which can be used to predict subsequent ADL- and IADL-related disability.
    Journal of Aging and Health 02/2013; · 1.56 Impact Factor
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    ABSTRACT: This study examined whether inability to perform adaptive locomotor tests predicts self-reported incident mobility disability. InCHIANTI study participants (N = 611; age, 50-85 yrs) who could walk 7 m at self-selected speed and who had no self-reported mobility disability at baseline were included. The ability to complete four adaptive locomotor tests was assessed: fast walking, walking on a narrow path, crossing obstacles while walking, and talking while walking. Mobility disability was recorded again at 3-yr follow-up. Failure in the fast-walking and narrow-path walking tests predicted approximately 2.5 times likelihood of reporting incident mobility disability (P = 0.009 and P = 0.011, respectively). Failure in the obstacle-crossing test predicted approximately two times likelihood of reporting incident mobility disability; however, this result did not reach statistical significance (P = 0.077). Failure in talking while walking did not predict incident mobility disability. Those who failed both the fast-walking and narrow-path walking tests were almost nine times as likely to report incident mobility disability.
    American journal of physical medicine & rehabilitation / Association of Academic Physiatrists 01/2013; · 1.56 Impact Factor
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    ABSTRACT: Using several variables known to be related to prostate cancer, a multivariate classification method is developed to predict the onset of clinical prostate cancer. A multivariate mixed-effects model is used to describe longitudinal changes in prostate specific antigen (PSA), a free testosterone index (FTI), and body mass index (BMI) before any clinical evidence of prostate cancer. The patterns of change in these three variables are allowed to vary depending on whether the subject develops prostate cancer or not and the severity of the prostate cancer at diagnosis. An application of Bayes' theorem provides posterior probabilities that we use to predict whether an individual will develop prostate cancer and, if so, whether it is a high-risk or a low-risk cancer. The classification rule is applied sequentially one multivariate observation at a time until the subject is classified as a cancer case or until the last observation has been used. We perform the analyses using each of the three variables individually, combined together in pairs, and all three variables together in one analysis. We compare the classification results among the various analyses and a simulation study demonstrates how the sensitivity of prediction changes with respect to the number and type of variables used in the prediction process.
    Journal of Applied Statistics 06/2012; 39(6):1151-1175. · 0.45 Impact Factor
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    ABSTRACT: Associations among personality as measured by the Five Factor Model, physical activity, and muscle strength were assessed using data from the Baltimore Longitudinal Study of Aging (N = 1220, age: mean = 58, SD = 16). General linear modeling with adjustment for age, sex, race, and body mass index, and bootstrapping for mediation were used. We found neuroticism and most of its facets to negatively correlate with strength. The extraversion domain and its facets of warmth, activity, and positive-emotions were positively correlated with strength, independent of covariates. Mediation analysis results suggest that these associations are partly explained by physical activity level. Findings extend the evidence of an association between personality and physical function to its strength component and indicate health behavior as an important pathway.
    Journal of Research in Personality 06/2012; 46(3):264-270. · 2.00 Impact Factor
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    ABSTRACT: The aim of the present study was to examine differences in gait characteristics across the adult lifespan and to test the hypothesis that such differences are attributable at least in part to the decline in muscle strength. The data presented here are from 190 participants of the Baltimore Longitudinal Study of Aging (BLSA) aged from 32 to 93 years. Based on two age thresholds that best capture the effect of age on walking speed, participants were divided into three age groups: middle-age (32-57 years; N=27), old-age (58-78 years; N=125), and oldest-age (79-93 years; N=38). Participants were asked to walk at their preferred and maximum speeds while recorded with 3D gait analysis system. In addition, maximum isokinetic knee extensor strength was assessed. While walking at preferred speed, range of motion (ROM) and mechanical work expenditure (MWE) of the ankle were lower within middle-age (p<0.001, p=0.047, respectively), while hip ROM and MWE were lower (p=0.006) and higher (p<0.001), respectively within oldest-age with older age. Deterioration in ankle function during customary walking initiates already at middle-age. Differences in the maximum walking speed and ankle ROM between middle-age and old-age were explained by knee strength.
    Archives of gerontology and geriatrics 05/2012; 55(2):474-9. · 1.36 Impact Factor
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    ABSTRACT: To study the relationships between muscle mass, regional adiposity, and adipokines and glucose disposal in an older population. Cross-sectional analysis. Community-dwelling volunteers from the Baltimore Longitudinal Study of Aging. Two hundred eighty men and 259 women with a mean age of 71.1 ± 0.4 (range 55-96) and complete data on fasting plasma adiponectin and leptin, oral glucose tolerance test (OGTT) (plasma glucose available at 0, 20, 40, 60, 80, 100, and 120 minutes), thigh computed tomography (CT), physical activity levels, and anthropometric measures. Participants were classified into eight groups according to the presence of global adiposity (body mass index > 27 kg/m(2)), central adiposity (waist circumference > 88 cm for women and > 102 cm for men), and low muscle mass (CT thigh, lowest sex-specific tertile (93.8 cm(2) in women and 110.7 cm(2) in men) of adjusted thigh muscle area). Linear regression models were used to estimate the contribution of these eight groups to early glucose area under the curve (AUC) (t = 0-40 minutes), late glucose AUC (t = 60-120 minutes), and total glucose AUC (t = 0-120 minutes) from the OGTT. Regardless of muscle mass, individuals with a combination of central and global adiposity were more likely to have delayed glucose disposal rates (P < .05). A strong negative association was also found between circulating adiponectin levels and glucose disposal rates (early AUC, β = -0.14; late AUC, β = -0.20; and total AUC, β = -0.20; P < .05 for all three AUCs) after adjusting for regional adiposity, muscle mass, circulating leptin levels, physical activity, age, and sex. Older individuals with global and central adiposity may be at risk of glucose intolerance unrelated to low muscle mass.
    Journal of the American Geriatrics Society 03/2012; 60(4):707-12. · 4.22 Impact Factor
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    ABSTRACT: •  To determine whether the prostate-specific antigen velocity (PSAV) risk count (i.e. the number of times PSAV exceeds a specific threshold) could increase the specificity of screening for prostate cancer and potentially life-threatening tumours. •  From 1989 to 2001, we calculated two serial PSAV measurements in 18 214 prostate cancer screening-study participants, of whom 1125 (6.2%) were diagnosed with prostate cancer. •  The PSAV risk count was determined as the number of PSAV measurements of >0.4 ng/mL/year (0, 1, or 2). •  We used receiver operating characteristic (ROC) and reclassification analyses to examine the ability of PSAV risk count to predict screen-detected and high-grade prostate cancer. •  The PSAV was >0.4 ng/mL/year twice (risk count 2) in 40% of prostate cancer cases compared with only 4% of those with no cancer (P < 0.001). •  After adjusting for age and PSA level, a PSAV risk count of 2 was associated with an 8.2-fold increased risk of prostate cancer (95% confidence interval 7.0-9.6, P < 0.001) and 5.4-fold increased risk of Gleason score 8-10 prostate cancer on biopsy. •  Compared with a model with age and PSA level, the addition of the PSAV risk count significantly improved discrimination (area under the ROC curve 0.625 vs 0.725, P= 0.031) and reclassified individuals for the risk of high-grade prostate cancer (net reclassification, P < 0.001). •  Sustained rises in PSA indicate a significantly greater risk of prostate cancer, particularly high-grade disease. •  Compared with men with a risk count of ≤1, those with two PSAV measurements of >0.4 ng/mL/year (risk count 2) had an 8-fold increased risk of prostate cancer and 5.4-fold increased risk of Gleason 8-10 disease on biopsy, adjusting for age and PSA level. •  Compared to PSA alone, PSAV risk count may be useful in reducing unnecessary biopsies and the diagnosis of low-risk prostate cancer.
    BJU International 02/2012; 109(4):508-13; discussion 513-4. · 3.13 Impact Factor
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    ABSTRACT: Study Type--Prognostic (cohort). Level of Evidence 2b. What's known on the subject? And what does the study add? Previous studies have attempted to characterize the normal biological variability in PSA among men without prostate cancer. These reports suggest that PSA variability is unrelated to age, but there are conflicting data on its association with the baseline PSA level. There are limited published data regarding the effects of prostate volume on PSA variability. A prior study assessing whether prostate volume changes would confound the use of PSA velocity in clinical practice reported that prostate volume changes were not significantly related to PSA changes. This study did not directly address the effect of baseline prostate volume on serial PSA variability. The objective of the current study was to further examine the relationship between prostate volume and PSA variability. Our hypothesis was that larger baseline prostate volume would be associated with increased PSA variability in men without known prostate cancer and in those with suspected small-volume disease. The results of the study suggest that baseline PSA, not prostate volume, is the primary driver of PSA variability in these populations. • To clarify the relationship between serial prostate-specific antigen (PSA) variability and prostate volume in both cancer-free participants from the Baltimore Longitudinal Study of Aging (BLSA) and patients with low-risk prostate cancer from the Johns Hopkins Active Surveillance Program (AS). • In all, 287 men from the BLSA and 131 patients from the AS were included in the analysis, all with at least two PSA measurements and concurrent prostate volume measurements. • PSA variability was calculated in ng/mL per year, and a linear mixed-effects model was used to determine the relative effects of prostate volume, baseline PSA and age on PSA change over time. • In a model with prostate volume, age and baseline PSA, there was no significant relationship between prostate volume and PSA variability (BLSA, P= 0.57; AS, P= 0.49). • Only baseline PSA showed a significant relationship to PSA yearly variability (PSAYV) (P < 0.001). Specifically, a one unit higher baseline PSA (ng/mL) corresponded on average to 0.09 and 0.06 ng/mL per year higher PSAYV in the BLSA and AS populations, respectively. • The results of the present study suggest that the primary driver of PSA variability is the baseline PSA level, rather than prostate volume. • Clinicians might consider the baseline PSA level to help predict the expected variability in serial PSA measurements.
    BJU International 11/2011; 109(9):1304-8. · 3.13 Impact Factor
  • Stacy Loeb, E Jeffrey Metter, H Ballentine Carter
    CancerSpectrum Knowledge Environment 09/2011; 103(21):1636-7; author reply 1637. · 14.07 Impact Factor
  • Journal of Clinical Oncology 08/2011; 29(24):3337-3337. · 17.88 Impact Factor
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    ABSTRACT: To determine the relationship between hearing loss and cognitive function as assessed with a standardized neurocognitive battery. We hypothesized a priori that greater hearing loss is associated with lower cognitive test scores on tests of memory and executive function. A cross-sectional cohort of 347 participants ≥ 55 years in the Baltimore Longitudinal Study of Aging without mild cognitive impairment or dementia had audiometric and cognitive testing performed in 1990-1994. Hearing loss was defined by an average of hearing thresholds at 0.5, 1, 2, and 4 kHz in the better-hearing ear. Cognitive testing consisted of a standardized neurocognitive battery incorporating tests of mental status, memory, executive function, processing speed, and verbal function. Regression models were used to examine the association between hearing loss and cognition while adjusting for confounders. Greater hearing loss was significantly associated with lower scores on measures of mental status (Mini-Mental State Exam), memory (Free Recall), and executive function (Stroop Mixed, Trail Making B). These results were robust to analyses accounting for potential confounders, nonlinear effects of age, and exclusion of individuals with severe hearing loss. The reduction in cognitive performance associated with a 25 dB hearing loss was equivalent to the reduction associated with an age difference of 6.8 years. Hearing loss is independently associated with lower scores on tests of memory and executive function. Further research examining the longitudinal association of hearing loss with cognitive functioning is needed to confirm these cross-sectional findings.
    Neuropsychology 07/2011; 25(6):763-70. · 3.58 Impact Factor
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    Nandini Deshpande, E Jeffrey Metter, Luigi Ferrucci
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    ABSTRACT: To identify sensorimotor and psychosocial factors independently associated with an inability to perform adaptive walking tasks in older adults. Cross-sectional cohort study. Population-based older cohort. Community-living elderly (N=720; age ≥65y) who could walk 7m at self-selected normal speed. Not applicable. Walking performance was assessed in 4 walking tests: fast walking, obstacle crossing, narrow-based walking, and walking while talking. Possible correlates of the inability to perform the walking test included knee extensor strength, lower limb coordination, Cumulative Somatosensory Impairment Index (CSII), visual acuity and contrast sensitivity, cognition, depression, personal mastery, social support, and years of education. The results of binary logistic regression analyses, adjusted for demographics and self-selected normal speed, demonstrated that poor knee extensor strength was associated with an inability to perform tasks demanding an increase in walking speed (fast walking and obstacle crossing). Both poor lower limb coordination and higher CSII were significantly associated with failure in tests that demanded precise control over foot placement (obstacle crossing and narrow-based walking). Higher CSII was associated with failure in all tests except in the walking while talking. In contrast, poor cognition was associated with an inability to perform walking while talking. Poor personal mastery was the only variable that was associated with failure in all walking tests. The results demonstrated a systematic and coherent pattern in these associations and indicated possible sensorimotor and psychological parameters that should be specifically investigated and should be intervened if a patient reports a difficulty/inability in walking in certain situations.
    Archives of physical medicine and rehabilitation 07/2011; 92(7):1074-9. · 2.18 Impact Factor
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    ABSTRACT: Physical inactivity plays a central role in the age-related decline in muscle strength, an important component in the process leading to disability. Personality, a significant determinant of health behaviors including physical activity, could therefore impact muscle strength throughout adulthood and affect the rate of muscle strength decline with aging. Personality typologies combining "high neuroticism" (N ≥ 55), "low extraversion" (E < 45), and "low conscientiousness" (C < 45) have been associated with multiple risky health behaviors but have not been investigated with regards to muscle strength. The purpose of this study is to investigate associations between individual and combined typologies consisting of high N, low E, and low C and muscle strength, and whether physical activity and body mass index act as mediators. This cross-sectional study includes 1,220 participants from the Baltimore Longitudinal Study of Aging. High N was found among 18%, low E among 31%, and low C among 26% of the sample. High levels of N, particularly when combined with either low E or low C, were associated with lower muscle strength compared with having only one or none of these personality types. Facet analyses suggest an important role for the N components of depression and hostility. Physical activity level appears to partly explain some of these associations. Findings provide support for the notion that the typological approach to personality may be useful in identifying specific personality types at risk of low muscle strength and offer the possibility for more targeted prevention and intervention programs.
    International Journal of Behavioral Medicine 05/2011; 19(3):382-90. · 2.63 Impact Factor
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    ABSTRACT: To compare the effects of a pedometer-based behavioral intervention (Fitness for Life [FFL] program) and a traditional high-intensity fitness (TRAD) program on physical activity (PA), Army Physical Fitness Test (APFT), and coronary heart disease risk factors in Army National Guard members who failed the APFT 2-mile run. From a pool of 261 Army National Guard, a total of 156 were randomized to TRAD or FFL for 24 weeks consisting of a 12-week progressive conditioning program followed by 12 weeks of maintenance. For both groups, the total APFT score and 2-mile run time/score improved from baseline to 12 weeks (FFL: down 7.4%, p = 0.03; TRAD: down 5%, p = 0.08) but at 24 weeks they had regressed toward baseline. PA improved modestly and coronary risk profile changed minimally in both groups. A pedometer-based exercise intervention had results similar to a high-intensity program for improving PA, APFT, and 2-mile run times/score. Neither group sustained the improved run times over the 12 weeks of maintenance.
    Military medicine 05/2011; 176(5):592-600. · 0.77 Impact Factor
  • The Journal of Urology 04/2011; 185(4). · 3.75 Impact Factor

Publication Stats

6k Citations
767.33 Total Impact Points


  • 1989–2013
    • National Institute on Aging
      • • Clinical Research Branch (CRB)
      • • Laboratory of Clinical Investigation (LCI)
      • • Laboratory of Personality and Cognition (LPC)
      Baltimore, Maryland, United States
  • 2012
    • Loyola University Maryland
      • Department of Mathematics and Statistics
      Baltimore, MD, United States
    • University of Missouri - St. Louis
      • School of Social Work
      Saint Louis, MI, United States
    • Chonnam National University
      • School of Mechanical Systems Engineering
      Yeoju, Gyeonggi, South Korea
    • New York University
      • Department of Urology
      New York City, NY, United States
  • 2011
    • University of North Carolina at Charlotte
      • School of Nursing
      Charlotte, NC, United States
  • 2010–2011
    • Queen's University
      • School of Rehabilitation Therapy
      Kingston, Ontario, Canada
    • University of Maryland, Baltimore
      Baltimore, Maryland, United States
    • CUNY Graduate Center
      New York City, New York, United States
  • 2002–2011
    • Johns Hopkins University
      • • Department of Medicine
      • • School of Nursing
      Baltimore, MD, United States
    • Dokkyo Medical University
      • Division of Rehabilitation Medicine
      Tochigi, Tochigi-ken, Japan
  • 1997–2011
    • Johns Hopkins Medicine
      • • Department of Urology
      • • Department of Neurology
      Baltimore, MD, United States
  • 2009–2010
    • Università degli studi di Parma
      • Department of Clinical and Experimental Medicine
      Parma, Emilia-Romagna, Italy
    • Kansas City VA Medical Center
      Kansas City, Missouri, United States
    • University Hospital of Parma
      Parma, Emilia-Romagna, Italy
  • 2005–2010
    • National Institutes of Health
      • Clinical Research Branch (CRB)
      Maryland, United States
  • 2004–2008
    • University of Maryland, College Park
      • Department of Kinesiology
      College Park, MD, United States
    • NASA
      • Neurosciences Laboratories
      Washington, WV, United States
    • Greater Baltimore Medical Center
      Baltimore, Maryland, United States
  • 2007
    • Uniformed Services University of the Health Sciences
      • Graduate School of Nursing
      Bethesda, MD, United States
  • 2006
    • National Institute of Clinical Research
      Georgia, United States
  • 2000–2006
    • University of Maryland Eastern Shore
      • Department of Physical Therapy
      Princess Anne, MD, United States
  • 1983–2006
    • University of California, San Diego
      • Division of Urology
      San Diego, CA, United States
  • 2003–2005
    • Johns Hopkins Bloomberg School of Public Health
      • Department of Epidemiology
      Baltimore, MD, United States
  • 2002–2003
    • University of Pittsburgh
      • Department of Human Genetics
      Pittsburgh, PA, United States
  • 2001–2002
    • Osaka City University
      Ōsaka, Ōsaka, Japan
  • 1988
    • Children's Hospital Los Angeles
      • DIvision of Neurology
      Los Angeles, California, United States
  • 1987
    • University of California, Los Angeles
      • Department of Medicine
      Los Angeles, California, United States