SOAN October 2017 Colloquium: How “dependent” are we? An exploratory spatiotemporal analysis of the youth and elderly populations in the U.S.
Speaker: Dr. David Wong
Wednesday, October 18, 2017 10:30 AM to 11:30 AM EDT
#B313
Aging is a recognized demographic characteristic of the U.S. population. Where the retired population is concentrated seems to be well known, but the size of the elderly population relative to the sizes of other age cohorts of the population is often not considered in the analysis of elderly population concentration. Dependency ratios have been used to assess the burdens that youth and elderly populations may have imposed onto the population. This talk presents some preliminary results of an exploratory analysis of dependency ratios from both the spatial and temporal perspectives. Using 1990 and 2010 census data at the state and county levels, results show how the spatial patterns of dependency ratios changed over the two decades. Overall dependency has declined, but the central sections of the U.S. have the highest overall dependency. Areas with large burdens contributed by the youth population are identical to those areas with large burdens contributed by the elderlies, but the overlapping parts of these high burden areas have the largest overall burdens. Burdens from the youths have declined over time while burdens from the elderly have increased, and the burdens also shifted geographically over the two decades. At the local scale (county-level analysis), whether an area was urban or non-urban seems to be related to the levels of burdens from both population groups, but the relationships have switched directions over time.
Bio:
David Wong, is Professor in Geography & GeoInformation Science Department at George Mason University. He has broad research interests, ranging from geovisualization and 3D GIS, to spatial epidemiology. His primary research interests are on spatial scale issues, spatial analysis and statistics, and population analysis, particularly in measuring segregation. Recently, his research in spatial data quality focuses on effectively incorporating error information in mapping and modeling.
