About

Suzanne Davies Withers is a spatial demographer whose work and presence are acknowledged on her academic webpage. Her interests include exploring the spatial aspects of demographic phenomena, and she engages with her community through outreach and teaching. The webpage emphasizes her role within the University of Washington, which is situated on the traditional lands of the Coast Salish Peoples, reflecting her awareness of indigenous lands and histories. Her contributions encompass academic research, community engagement, and fostering a supportive and curious learning environment, as indicated by her welcoming message for a new academic year.

Research topics

• Demography
• Medicine
• Mathematics
• Geography
• Statistics
• Environmental health
• Econometrics
• Internal medicine

Selected publications

• An introduction to bayesian spatial smoothing methods for disease mapping: modeling county firearm suicide mortality rates

  American Journal of Epidemiology · 2024 · 8 citations

  • Statistics
  • Medicine
  • Econometrics

  This article introduces bayesian spatial smoothing models for disease mapping-a specific application of small area estimation where the full universe of data is known-to a wider audience of public health professionals using firearm suicide as a motivating example. Besag, York, and Mollié (BYM) Poisson spatial and space-time smoothing models were fitted to firearm suicide counts for the years 2014-2018. County raw death rates in 2018 ranged from 0 to 24.81 deaths per 10 000 people. However, the highest mortality rate was highly unstable, based on only 2 deaths in a population of approximately 800, and 80.5% of contiguous US counties experienced fewer than 10 firearm suicide deaths and were thus suppressed. Spatially smoothed county firearm suicide mortality estimates ranged from 0.06 to 4.05 deaths per 10 000 people and could be reported for all counties. The space-time smoothing model produced similar estimates with narrower credible intervals as it allowed counties to gain precision from adjacent neighbors and their own counts in adjacent years. bayesian spatial smoothing methods are a useful tool for evaluating spatial health disparities in small geographies where small numbers can result in highly variable rate estimates, and new estimation techniques in R software have made fitting these models more accessible to researchers.

  PublisherOA PDFDOI

• University of Washington’s Master of Geographic Information Systems for Sustainability Management

  Sustainability The Journal of Record · 2014-06-01

  articleSenior author
  PublisherDOI

• Quantitative Methods in Human Geography

  Geography · 2013-02-26 · 2 citations

  reference-entry1st authorCorresponding

  The term “quantitative research” refers to the systematic scientific investigation of quantitative properties and phenomena and their relationships, by using statistical methods. It includes the analysis of numerical spatial data, the development of spatial theory, and the constructing and testing of mathematical models of spatial processes. As geographers know, spatial analysis is very important. The aim of spatial analysis is to understand differences across space rather than regularities. Quantitative methods have been an integral part of human geography since the quantitative revolution of the 1950s. Quantitative methods in the early 21st century are vastly more sophisticated than their earlier counterparts. Since the early 1990s, in particular, the interest in georeferenced data and the need to understand it have led to an enormous field of spatial analysis. By the late 1990s, the field of spatial analysis had matured to the point where the methods of spatial analysis served as fundamental research techniques in a variety of disciplines, including geography, ecology, environmental studies, epidemiology, regional science, sociology, and urban planning. The quantitative methods of yesteryear have given way to a complex field of spatial analysis that serves as a unifying methodology for social science in general.

  PublisherDOI

• Longitudinal Methods; Cohort Analysis, Life Tables

  Elsevier eBooks · 2009-01-01 · 2 citations

  book-chapter1st authorCorresponding
  PublisherDOI

• Data Analysis, Categorical

  Elsevier eBooks · 2009-01-01 · 3 citations

  book-chapter1st authorCorresponding
  PublisherDOI

• Categorical Data Analysis

  Elsevier eBooks · 2009-01-01 · 16 citations

  book-chapter1st authorCorresponding
  PublisherDOI

• Fertility, mobility and labour‐force participation: a study of synchronicity

  Population Space and Place · 2009-05-28 · 55 citations

  articleSenior author

  Abstract Delayed childbearing is common in a workforce that is now dominated by dual‐income households, and survey results report increasing concerns about how to manage family formation and labour‐force participation. In the past, mobility research tended to focus on the mobility event and looked at fertility as a ‘triggering’ event that stimulates mobility and migration. In contrast this research focuses on the fertility event and explores the relationship between fertility events and both mobility and labour‐force outcomes. Using the Panel Study of Income Dynamics, we undertake an analysis of ‘windows’ around fertility events and look for mobility activity, and for a smaller subsample, labour‐force events. Then we also examine ‘windows’ around mobility events to test competing explanations for fertility behaviour and mobility behaviour. The research moves beyond parental status and the links to mobility and labour‐force participation to the actual synchronicity of these behaviours. While it is no surprise that women do drop out of the labour force to have children, many fewer actually leave the labour force than expected and they re‐enter at significantly high rates. The results for mobility are even more mixed, and while there is some evidence of increased mobility with fertility, it is much weaker than suggested by other research. Overall, this research reaffirms an emerging view of mobility and migration behaviour as much more complex than earlier research presented. Copyright © 2009 John Wiley & Sons, Ltd.

  PublisherDOI

• Longitudinal Methods (Cohort Analysis, Life Tables)

  Elsevier eBooks · 2009-01-01 · 2 citations

  book-chapter1st authorCorresponding
  PublisherDOI

• Demographic variation in housing cost adjustments with US family migration

  Population Space and Place · 2008-07-01 · 1 citations

  article1st authorCorresponding

  Abstract This paper examines the demographic variation in housing‐cost adjustment associated with family migration in the United States. The American population continues to migrate away from very large metropolitan areas down the urban hierarchy towards smaller metropolitan and micropolitan areas, an exodus that is frequently attributed to the push effects of diseconomies and congestion, increasing presence of foreign‐born population, and housing affordability problems, particularly in the large gateway cities. Yet, there is no empirical study of the housing‐cost adjustments associated with migration. This study addresses this gap by empirically assessing whether migration is associated with housing affordability adjustments, whether migrating families increase or decrease their housing costs, whether demographic variations occur in these adjustments, and whether there are significant differences in the geographies of housing‐cost adjustments among migrant families. These questions are addressed using the Census 2000 county‐to‐county migration flows merged with Census measures, and the 2000 Public Use Micro‐Sample 5% National file. The results indicate significant changes in housing costs associated with migration, and interstate migration in particular. On average, the direction of migration is to more affordable places. Families migrating from the traditional gateway cities with a relatively high percentage of foreign‐born populations are the most likely to make enormous shifts in affordability. However, these moves do not correspond neatly with regional white‐flight theory. Hispanics are far more likely to decrease housing costs with migration, as are non‐citizens and naturalised citizens. This research makes an important contribution to debates within the family migration literature, including conjectures of regional white flight and gendered theories of migration. Family migration towards greater housing affordability appears strategic and embedded in larger issues of family work–life balance. Copyright © 2008 John Wiley & Sons, Ltd.

  PublisherDOI

• Family migration and mobility sequences in the United States: Spatial mobility in the context of the life course

  DOAJ (DOAJ: Directory of Open Access Journals) · 2007-12-01 · 20 citations

  articleOpen access1st authorCorresponding

  Significant changes in family composition in the past quarter-century raise important questions about life-course outcomes embedded in these family changes, especially in relation to the migratory and mobility patterns of individuals and families. The classic distinction between long-distance/employment and short-distance/housing-related moves may be eroding. Patterns of movement appear much less dichotomous and more diverse as family structures become more diverse. Using the Panel Study of Income Dynamics this study shows that the previous research, which suggested relatively simple links between long-distance and short-distance moves, is an over-simplification. Moreover, there is much more unintended movement at both migratory and mobility scales suggesting the economic models of employment migration may be missing important family dynamics in the migration mobility process.

  Publisher

Frequent coauthors

• William A. V. Clark

  13 shared

• Tricia Ruiz

  Seattle University

  8 shared

• Youqin Huang

  University at Albany, State University of New York

  4 shared

• Alice M. Ellyson

  Seattle University

  2 shared

• Emma Gause

  Boston University

  2 shared

• Austin E Schumacher

  Institute for Health Metrics and Evaluation

  1 shared

• Darren M. Kavanagh

  1 shared

• Jonathan D. Mayer

  1 shared

Awards & honors

• 2024 Awards, Honors and Achievements (June 10, 2024)
• 2022 Awards, Honors and Achievements (June 15, 2022)
• 2021 Awards, Honors and Achievements (June 8, 2021)