Assessing changes in the underrepresentation of Blacks, Latinx/Hispanics, and Native American doctoral students in U.S. Geography Programs, and a model for change: the Michigan State University model.

This study used critical race theory to examine the changes in awarding of doctoral degrees in Departments of Geography to American citizens who are Black, Latinx, and/or Native American. Data were obtained from the Integrated Postsecondary Education Data System (IPEDS), 1997-2019. The data show that of 4918 doctoral degrees awarded from 1997 to 2019, only 86 or 1.64% were awarded to African American students, 122 or 2.39% were awarded to Hispanic American students, and 25 or 0.53% were awarded to Native American students. The differential awarding of degrees was related to the differential funding by race and ethnicity to support their completion of the doctorate degrees. Critical race theory may lead to consciousness for students to review the practice as disparate impact racial discrimination. If policies and practices in departments of geography are not changed there will continue to be few doctoral degrees obtained by Blacks, Hispanics, and Native Americans. The paper offers a model for change.

Exploring Persistent Racial and Ethnic Representation Disparity in U.S. Geography Doctoral Programs: The Disciplinary Underrepresentation Gap.

Underrepresentation among U.S. citizen racial and ethnic minorities in geography has a long history, one perpetuated through-and readily measurable by-its doctoral degree-granting record. This article examines the history of efforts to redress underrepresentation since the 1960s, explores modern underrepresentation, measures the degree of its persistence in the discipline and within individual departments, and identifies drivers that exacerbate the racial and ethnic representation disparity among U.S. citizens in geography doctoral programs. To quantify the degree to which the discipline is underperforming demographically, we contrasted the rate of domestic underrepresented minority doctoral degree conferrals with those of White doctoral recipients in geography, the social sciences, and the entire academy over a twenty-three-year period from 1997 through 2019. During that span, geography consistently trailed the social sciences and the academy: This underrepresentation gap has widened in the past decade. Four drivers were identified: (1) lack of dedicated funding for underrepresented minority doctoral students, (2) minimal prior exposure to academic and professional geography, (3) passive recruitment strategies, and (4) pervasive Whiteness of departments. We conclude with a call to action for geographers to meet the moral imperative of racial and ethnic representational equity by becoming agents of measurable change.

The Advancing Geography Through Diversity Program: A Framework to Address the Persistent Underrepresentation of Domestic Racial and Ethnic Minorities in U.S. Geography Doctoral Programs.

Domestic racial and ethnic minorities have been persistently underrepresented in U.S. geography doctoral programs. Efforts to improve diversity have taken many forms over the years, but most have been short-lived with limited success. In this article, we introduce the Advancing Geography Through Diversity Program (AGTDP), a four-pronged cohort-based model that systematically and sustainably increases the presence of African Americans, Hispanic Americans, and Native Americans in geography doctoral programs. The program is currently in its fourth year in the Department of Geography, Environment, and Spatial Sciences at Michigan State University. Context for the development of the framework is provided, followed by a detailed discussion of each pillar of the program: recruitment, support, engagement, and retention. We evaluate the current state of the program along with lessons learned for successful implementation. To date, the program has effectively increased the representation across all three underrepresented groups within the department's doctoral program. We believe the AGTDP can serve as a model for more widespread deployment to other geography departments.

Explained and unexplained racial and regional inequality in obesity prevalence in the United States.

Objective: There are substantial racial and regional disparities in obesity prevalence in the United States. This study partitioned the mean Body Mass Index (BMI) and obesity prevalence rate gaps between non-Hispanic blacks and non-Hispanic whites into the portion attributable to observable obesity risk factors and the remaining portion attributable to unobservable factors at the national and the state levels in the United States (U.S.) in 2010. Design: This study used a simulated micro-population dataset combining common information from the Behavioral Risk Factor Surveillance System and the U.S. Census data to obtain a reliable, large sample representing the adult populations at the national and state levels. It then applied a reweighting decomposition method to decompose the black-white mean BMI and obesity prevalence disparities at the national and state levels into the portion attributable to the differences in distribution of observable obesity risk factors and the remaining portion unexplainable with risk factors. Results: We found that the observable differences in distribution of known obesity risk factors explain 18.5% of the mean BMI difference and 20.6% of obesity prevalence disparities between non-Hispanic blacks and non-Hispanic whites. There were substantial variations in how much the differences in distribution of known obesity risk factors can explain black-white gaps in mean BMI (-67.7% to 833.6%) and obesity prevalence (-278.5% to 340.3%) at the state level. Conclusion: The results from this study demonstrate that known obesity risk factors explain a small proportion of the racial, ethnic and between-state disparities in obesity prevalence in the United States. Future etiologic studies are required to further understand the causal factors underlying obesity and racial, ethnic and geographic disparities.

Adult obesity prevalence at the county level in the United States, 2000-2010: Downscaling public health survey data using a spatial microsimulation approach.

Obesity is a growing public health concern in the United States. There is a need to monitor obesity prevalence at the local level to intervene in place-specific ways. However, national public health surveys suppress the local geographic information of respondents due to small sample sizes and the protection of confidentiality. This study therefore, uses a spatial microsimulation approach to estimate obesity prevalence rates at the county level across the United States to visualize temporal, spatial and spatio-temporal changes from 2000 to 2010 for use in the monitoring of obesity prevalence. This method iteratively replicates the demographic characteristics of public health survey respondents with census data for those areas. Following, Local Moran's I was used to identify clusters of high and low obesity prevalence. The findings showed that obesity prevalence rose dramatically over the last decade with substantial variation across counties and states. Counties in Southern states, especially along the Mississippi River and Appalachian Mountains and counties containing or in proximity to Native American reservation sites showed elevated obesity prevalence rates across the decade. Counties in Midwestern states had higher obesity prevalence rates compared to counties in Western and Northeastern states. This study demonstrated the use of spatial microsimulation modeling as an alternative method to obtain reliable obesity prevalence rates at the local-level using existing health survey and census data.

Impacts of Federally Funded State Obesity Programs on Adult Obesity Prevalence in the United States, 1998-2010.

OBJECTIVES: From 2000 to 2010, the Division of Nutrition, Physical Activity, and Obesity (DNPAO) at the Centers for Disease Control and Prevention (CDC) funded 37 state health departments to address the obesity epidemic in their states through various interventions. The objective of this study was to investigate the overall impacts of CDC-DNPAO statewide intervention programs on adult obesity prevalence in the United States. METHODS: We used a set of an individual-level, interrupted time-series regression and a quasi-experimental analysis to evaluate the overall effect of CDC-DNPAO intervention programs before (1998-1999) and after (2010) their implementation by using data from CDC's Behavioral Risk Factor Surveillance System. RESULTS: States that implemented the CDC-DNPAO program had a 2.4% to 3.8% reduction in the odds of obesity during 2000-2010 compared with states without the program. The effect of the CDC-DNPAO program varied by length of program implementation. A quasi-experimental analysis found that states with longer program implementation did not necessarily have lower odds of obesity than states with shorter program implementation. CONCLUSIONS: Statewide obesity interventions can contribute to reduced odds of obesity in the United States. Future research should evaluate the CDC-DNPAO programs in relation to their goals, objectives, and other environmental obesity risk factors to inform future interventions.

The Relationship of Neighborhood Socioeconomic Differences and Racial Residential Segregation to Childhood Blood Lead Levels in Metropolitan Detroit.

This study uses a new approach to assess the impact of different neighborhood characteristics on blood lead levels (BLLs) of black versus white children in metropolitan Detroit. Data were obtained from the Michigan Department of Community Health and the US Bureau of the Census American Community Survey. The Modified Darden-Kamel Composite Socioeconomic Index, bivariate regression, and the index of dissimilarity were used to compute neighborhood BLL unevenness by neighborhood characteristics. Neighborhoods with lower socioeconomic characteristics and high racial residential segregation predicted higher average childhood BLLs. This reveals a social spatial structure that will aid researchers/policymakers in better understanding disparities in childhood BLLs.