Are Race, Ethnicity, and Medical School Affiliation Associated with NIH R01 Type Award Probability for Physician Investigators?

This is a non-final version of an article published in final form in Acad Med. 2012 November ; 87(11): 1516–1524. doi:10.1097/ACM.0b013e31826d726b.PURPOSE: To analyze the relationship among NIH R01 Type 1 applicant degree, institution type, and race/ethnicity, and application award probability. METHOD: The authors used 2000–2006 data from the NIH IMPAC II grants database and other sources to determine which individual and institutional characteristics of applicants may affect the probability of applications being awarded funding. They used descriptive statistics and probit models to estimate correlations between race/ethnicity, degree (MD or PhD), and institution type (medical school or other institution), and application award probability, controlling for a large set of observable characteristics. RESULTS: Applications from medical schools were significantly more likely than those from other institutions to receive funding, as were applications from MDs versus PhDs. Overall, applications from blacks and Asians were less likely than those from whites to be awarded funding; however, among applications from MDs at medical schools, there was no difference in funding probability between whites and Asians and the difference between blacks and whites decreased to 7.8 percentage points. The inclusion of human subjects significantly decreased the likelihood of receiving funding. CONCLUSIONS: Compared with applications from whites, applications from blacks have a lower probability of being awarded R01 Type 1 funding, regardless of the investigator’s degree. However, funding probability is increased for applications with MD investigators and for those from medical schools. To some degree, these advantages combine so that applications from black MDs at medical schools have the smallest difference in funding probability compared with those from whites

Publications as predictors of racial and ethnic differences in NIH research awards

This research expands efforts to understand differences in NIH funding associated with the self-identified race and ethnicity of applicants. We collected data from 2,397 NIH Biographical Sketches submitted between FY 2003 and 2006 as part of new NIH R01 Type 1 applications to obtain detailed information on the applicants’ training and scholarly activities, including publications. Using these data, we examined the association between an NIH R01 applicant’s race or ethnicity and the probability of receiving an R01 award. The applicant’s publication history as reported in the NIH biographical sketch and the associated bibliometrics narrowed the black/white funding gap for new and experienced investigators in explanatory models. We found that black applicants reported fewer papers on their Biosketches, had fewer citations, and those that were reported appeared in journals with lower impact factors. Incorporating these measures in our models explained a substantial portion of the black/white funding gap. Although these predictors influence the funding gap, they do not fully address race/ethnicity differences in receiving a priority score.HHSN276200700235U1R01AG36820-

Publications as predictors of racial and ethnic differences in NIH research awards

This research expands efforts to understand differences in NIH funding associated with the self-identified race and ethnicity of applicants. We collected data from 2,397 NIH Biographical Sketches submitted between FY 2003 and 2006 as part of new NIH R01 Type 1 applications to obtain detailed information on the applicants’ training and scholarly activities, including publications. Using these data, we examined the association between an NIH R01 applicant’s race or ethnicity and the probability of receiving an R01 award. The applicant’s publication history as reported in the NIH biographical sketch and the associated bibliometrics narrowed the black/white funding gap for new and experienced investigators in explanatory models. We found that black applicants reported fewer papers on their Biosketches, had fewer citations, and those that were reported appeared in journals with lower impact factors. Incorporating these measures in our models explained a substantial portion of the black/white funding gap. Although these predictors influence the funding gap, they do not fully address race/ethnicity differences in receiving a priority score

Race, Ethnicity, and NIH Research Awards

This is the author's accepted manuscript. The original is available at http://www.sciencemag.org/content/333/6045/1015.We investigated the association between a U.S. National Institutes of Health (NIH) R01 applicant’s self-identified race or ethnicity and the probability of receiving an award by using data from the NIH IMPAC II grant database, the Thomson Reuters Web of Science, and other sources. Although proposals with strong priority scores were equally likely to be funded regardless of race, we find that Asians are 4 percentage points and black or African-American applicants are 13 percentage points less likely to receive NIH investigator-initiated research funding compared with whites. After controlling for the applicant’s educational background, country of origin, training, previous research awards, publication record, and employer characteristics, we find that black or African-American applicants remain 10 percentage points less likely than whites to be awarded NIH research funding. Our results suggest some leverage points for policy intervention

Race, Ethnicity, and NIH Research Awards

This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science on 2011 August 19; 333(6045): 1015–1019., DOI: 10.1126/science.1196783.We investigated the association between a U.S. National Institutes of Health (NIH) R01 applicant’s self-identified race or ethnicity and the probability of receiving an award by using data from the NIH IMPAC II grant database, the Thomson Reuters Web of Science, and other sources. Although proposals with strong priority scores were equally likely to be funded regardless of race, we find that Asians are 4 percentage points and black or African-American applicants are 13 percentage points less likely to receive NIH investigator-initiated research funding compared with whites. After controlling for the applicant’s educational background, country of origin, training, previous research awards, publication record, and employer characteristics, we find that black or African-American applicants remain 10 percentage points less likely than whites to be awarded NIH research funding. Our results suggest some leverage points for policy intervention

Race, Ethnicity, and NIH Research Awards

We investigated the association between a U.S. National Institutes of Health (NIH) R01 applicant’s self-identified race or ethnicity and the probability of receiving an award by using data from the NIH IMPAC II grant database, the Thomson Reuters Web of Science, and other sources. Although proposals with strong priority scores were equally likely to be funded regardless of race, we find that Asians are 4 percentage points and black or African-American applicants are 13 percentage points less likely to receive NIH investigator-initiated research funding compared with whites. After controlling for the applicant’s educational background, country of origin, training, previous research awards, publication record, and employer characteristics, we find that black applicants remain 10 percentage points less likely than whites to be awarded NIH research funding. Our results suggest some leverage points for policy intervention

Diversity in Academic Biomedicine: An Evaluation of Education and Career Outcomes with Implications for Policy

Currently, the U.S. population is undergoing major racial and ethnic demographic shifts that could affect the pool of individuals interested in pursuing a career in biomedical research. To achieve its mission of improving health, the National Institutes of Health must recruit and train outstanding individuals for the biomedical workforce. In this study, we examined the educational transition rates in the biomedical sciences by gender, race, and ethnicity, from high school to academic career outcomes. Using a number of educational databases, we investigated gender and racial/ethnic representation at typical educational and career milestones en route to faculty careers in biomedicine. We then employed multivariate regression methods to examine faculty career outcomes, using the National Science Foundation’s Survey of Doctorate Recipients. We find that while transitions between milestones are distinctive by gender and race/ethnicity, the transitions between high school and college and between college and graduate school are critical points at which underrepresented minorities are lost from the biomedical pipeline, suggesting some specific targets for policy intervention

Size and characteristics of the biomedical research workforce associated with U.S. National Institutes of Health extramural grants

The U.S. National Institutes of Health (NIH) annually invests approximately $22 billion in biomedical research through its extramural grant programs. Since fiscal year (FY) 2010, all persons involved in research during the previous project year have been required to be listed on the annual grant progress report. These new data have enabled the production of the first-ever census of the NIH-funded extramural research workforce. Data were extracted from All Personnel Reports submitted for NIH grants funded in FY 2009, including position title, months of effort, academic degrees obtained, and personal identifiers. Data were de-duplicated to determine a unique person count. Person-years of effort (PYE) on NIH grants were computed. In FY 2009, NIH funded 50,885 grant projects, which created 313,049 full- and part-time positions spanning all job functions involved in biomedical research. These positions were staffed by 247,457 people at 2,604 institutions. These persons devoted 121,465 PYE to NIH grant-supported research. Research project grants each supported 6 full- or part-time positions, on average. Over 20% of positions were occupied by postdoctoral researchers and graduate and undergraduate students. These baseline data were used to project workforce estimates forFYs 2010–2014 and will serve as a foundation for future research

Size and characteristics of the biomedical research workforce associated with U.S. National Institutes of Health extramural grants

The U.S. National Institutes of Health (NIH) annually invests approximately $22 billion in biomedical research through its extramural grant programs. Since fiscal year (FY) 2010, all persons involved in research during the previous project year have been required to be listed on the annual grant progress report. These new data have enabled the production of the first-ever census of the NIH-funded extramural research workforce. Data were extracted from All Personnel Reports submitted for NIH grants funded in FY 2009, including position title, months of effort, academic degrees obtained, and personal identifiers. Data were de-duplicated to determine a unique person count. Person-years of effort (PYE) on NIH grants were computed. In FY 2009, NIH funded 50,885 grant projects, which created 313,049 full- and part-time positions spanning all job functions involved in biomedical research. These positions were staffed by 247,457 people at 2,604 institutions. These persons devoted 121,465 PYE to NIH grant-supported research. Research project grants each supported 6 full- or part-time positions, on average. Over 20% of positions were occupied by postdoctoral researchers and graduate and undergraduate students. These baseline data were used to project workforce estimates forFYs 2010–2014 and will serve as a foundation for future research

Coenzyme A-transferase-independent butyrate re-assimilation in Clostridium acetobutylicum - evidence from a mathematical model

The hetero-dimeric CoA-transferase CtfA/B is believed to be crucial for the metabolic transition from acidogenesis to solventogenesis in Clostridium acetobutylicum as part of the industrial-relevant acetone-butanol-ethanol (ABE) fermentation. Here, the enzyme is assumed to mediate re-assimilation of acetate and butyrate during a pH-induced metabolic shift and to faciliate the first step of acetone formation from acetoacetyl-CoA. However, recent investigations using phosphate-limited continuous cultures have questioned this common dogma. To address the emerging experimental discrepancies, we investigated the mutant strain Cac-ctfA398s::CT using chemostat cultures. As a consequence of this mutation, the cells are unable to express functional ctfA and are thus lacking CoA-transferase activity. A mathematical model of the pH-induced metabolic shift, which was recently developed for the wild type, is used to analyse the observed behaviour of the mutant strain with a focus on re-assimilation activities for the two produced acids. Our theoretical analysis reveals that the ctfA mutant still re-assimilates butyrate, but not acetate. Based upon this finding, we conclude that C. acetobutylicum possesses a CoA-tranferase-independent butyrate uptake mechanism that is activated by decreasing pH levels. Furthermore, we observe that butanol formation is not inhibited under our experimental conditions, as suggested by previous batch culture experiments. In concordance with recent batch experiments, acetone formation is abolished in chemostat cultures using the ctfa mutant