Population and Environment Study

Website: http://perl.psc.isr.umich.edu/populationandenvironmentstudy1.html

Institution: University of Michigan Population and Ecology Research Laboratory

Description: This study was originally funded through a Request for Applications (RFA) from the National Institute of Child Health and Human Development (NICHD R01 HD-33551) for a five year period, 1995 through 2000. The study builds directly on the CVFS and uses the same study area, population, and sampling frame. The Population and Environment Study was designed to answer the following specific questions regarding the relationships between population change and environmental change: (1) To what extent do changes in marriage timing, household fission, childbearing, and migration influence changes in land use, water quality, and flora diversity? (2) To what extent do variations in land use, water quality, and flora diversity produce changes in marriage timing, household fission, child rearing, and migration? And (3) To what extent are the observed relationships between population processes and the environment produced by exogenous changes in the social and institutional context? This study includes a complete census of households within 171 neighborhoods, a household-level survey of agricultural practices and consumption patterns, land use maps of selected neighborhoods, flora data collection from surrounding forests and common lands, lab analysis and interviewer assessments of water samples collected from each neighborhood, a seasonal update of agricultural practices, and a monthly update of demographic events, including contraceptive use. A five year continuation (2001 through 2006) of the project was also subsequently granted by NICHD. The continuation grant includes funding for analysis of the data collected under the original grant, and focuses on a slightly refined set of research questions: (1) To what extent do marriage timing, household fission, childbearing, and migration influence land use and flora diversity? (2) To what extent do land use and flora diversity influence marriage, household fission, childbearing, and migration? (3) To what extent do agricultural practices and consumption patterns link population processes to environmental outcomes? And (4) To what extent are the observed relationships between population processes and the environment produced by exogenous changes in the social, economic, and institutional context? The continuation grant also includes funding for new data collection, including updates of land use and flora diversity measures, an extension of the monthly registry of demographic events, an update of the neighborhood contextual histories, a repeat of the household-level measures of agricultural practices and consumption patterns, and ethnographic information on environmentally-related behaviors and attitudes.

Texas Higher Education Opportunity Project

Website: http://theop.princeton.edu/index.html

Institution: Princeton University The Office of Population Research at Princeton University

Description: The Texas Higher Education Opportunity Project i(THEOP) is a multi-year study that began in fall, 2000, which investigates college planning and enrollment behavior under a policy that guarantees admission to any Texas public college or university to high school seniors who graduate in the top decile of their class. The investigators have collected administrative data from 10 colleges and universities in Texas that differ in the selectivity of their admissions. The centerpiece of the study is a two-cohort longitudinal survey of sophomores and seniors who were enrolled in Texas public schools as of spring, 2002.

TeachSpatial

Website: http://teachspatial.org

Affiliation: Center for Spatial Studies, University of California, Santa Barbara

Principal Investigators: Donald G. Janelle and Karl Grossner

Project Description:
http://teachspatial.org is a web portal to promote the discussion of spatial literacy among researchers and educators. It provides access to digital teaching and learning resources that support the integration of spatial thinking into course curricula. With funding from NSF (small-grant NSDL Pathways project) the Resources section of the website is a managed Collection within the National Science Digital Library. It is organized according to a concept-based framework that transcends disciplinary boundaries. Linkage to NSDL leverages advanced aspects of  a data repository and content model that allows users to discover and navigate among related spatial concepts and provides guided access to National Science Digital Library resources. The TeachSpatial collection was accessioned to NSDL in February 2012.

Urbanization, Health and Environmental Quality in Coastal Ghana

Website Link: http://www.brown.edu/academics/population-studies/research/projects/urbanization-ghana-and-kenya

Institution: Population Studies and Training Center, Brown University University of Cape Coast, Ghana

Description: This project draws upon existing links between Brown University, the University of Rhode Island, and the University of Cape Coast in Cape Coast, Ghana, to examine the social and demographic processes that are closely linked to health and environmental health risks, and how these in turn influence local thinking about environmental issues. The project includes such studies as the relationship between population concentration and water pollution in coastal lagoons; the determinants of environmental attitudes; knowledge of disease etiology, and the relationship between urbanization and fertility. The setting for this research is coastal Ghana, chosen for the ecological sensitivity of its coastal zone.

Related Publications: White, M.J., E. Tagoe, C. Stiff, K. Adazu, and D.J. Smith. 2005. “Urbanization and the Fertility Transition in Ghana,” Population Research and Policy Review. 24:59-83. White, M., S. Muhidin, C. Stiff, E. Tagoe and R. Knight. 2005. “Migration and Fertility in Coastal Ghana: An Event History Analysis,” in S. Agyei-Mensah, J. Casterline and D. Agyeman, eds., Reproductive Change in Ghana: Recent Patterns and Future Prospects. Department of Geography and Resource Development, University of Ghana, Legon: 101-115. Chattopadhyay, A. and M.J. White. “Migration and Fertility in Ghana: Beyond Rural-Urban Differentials.” Hunter, L.M. 2005. “Household Strategies in the Face of Resource Scarcity: Are They Associated with Development Priorities?” Forthcoming in Population Research and Development Review. Reed, H.E., Andrzejewski, C.S., and M.J. White. 2005. “An Event History Analysis of Internal Migration in Ghana: Determinants of Interregional Mobility among Residents of Coastal Central Region.” Under review. White, M.J. and L.M. Hunter. 2005. “Public Perception of Environmental Issues in a Developing Setting.” Andrzejewski, C.S. 2005.

The VII World Conference of the Spatial Econometrics Association, Washington DC, 10-12 July

Event Date(s): 07/10/2013–07/12/2013


Join economists, econometricians, and regional scientists to review accomplishments and challenges in spatial data analysis. The 2013 SEA World Conference will explore empirical, theoretical and methodological themes, including: Economic Growth, Knowledge Diffusion, Labor Market and Migration, Explanatory Spatial Data Analysis, Bayesian Methods, Health, Criminology, Environmental Economics and Energy, Spatial Data Mining, Spatial and Social Networks, and Spatial Concentration.

The Conference will take place 10-12 July, 2013 in the Key Bridge Marriott Hotel, Washington, DC.
For more information, http://www.spatialeconometricsassociation.org/2013/.

The Public Health Disparities Geocoding Project Monograph

Website Link: http://www.hsph.harvard.edu/thegeocodingproject/

Institution: Harvard School of Public Health

Description: The problem: A lack of socioeconomic data in most US public health surveillance systems. Absent these data, we cannot: (a) monitor socioeconomic inequalities in US health; (b) ascertain their contribution to racial/ethnic and gender inequalities in health; and (c) galvanize public concern, debate, and action concerning how we, as a nation, can achieve the vital goal of eliminating social disparities in health. We accordingly launched the Public Health Disparities Geocoding Project to ascertain which area-based socioeconomic measures [ABSMs], at which geographic level (census block group [BG], census tract [CT], or ZIP Code [ZC]), would be suitable for monitoring US socioeconomic inequalities in the health. Drawing on 1990 census data and public health surveillance systems of 2 New England states, Massachusetts and Rhode Island, we analyzed data for: (a) 7 types of outcomes: mortality (all cause and cause-specific), cancer incidence (all-sites and site-specific), low birth weight, childhood lead poisoning, sexually transmitted infections, tuberculosis, and non-fatal weapons-related injuries, and (b) 18 different ABSMs. We conducted these analyses for both the total population and diverse racial/ethnic-gender groups, at all 3 geographic levels. Our key methodologic finding was that the ABSM most apt for monitoring socioeconomic inequalities in health was the census tract (CT) poverty level, since it: (a) consistently detected expected socioeconomic gradients in health across a wide range of health outcomes, among both the total population and diverse racial/ethnic-gender groups, (b) yielded maximal geocoding and linkage to area-based socioeconomic data (compared to BG and ZC data), and (c) was readily interpretable to and could feasibly be used by state health department staff. Using this measure, we were able to provide evidence of powerful socioeconomic gradients for virtually all the outcomes studied, using a common metric, and further demonstrated that: (a) adjusting solely for this measure substantially reduced excess risk observed in the black and Hispanic compared to the white population, and (b) for half the outcomes, over 50% of cases overall would have been averted if everyone’s risk equaled that of persons in the least impoverished CT, the only group that consistently achieved Healthy People 2000 goals a decade ahead of time. US public health surveillance data should be geocoded and routinely analyzed using the CT-level measure “percent of persons below poverty,” thereby enhancing efforts to track—and improve accountability for addressing—social disparities in health.

Demographic Dynamics, Health, and Immigrant Issues Along the U.S.-Mexico Border

Website Link: http://geography.sdsu.edu/Research/Projects/IPC/research/border.html

Institution: San Diego State University International Population Center

Description: The website link gives access to a series of funded projects (noted below) and listings of related publications.

John R. Weeks, Principal Investigator, “Determining the Costs of Illegal Immigrant Criminal Activity and Use of Emergency Medical Services in San Diego and Imperial Counties,” Grant from the U.S. Department of Justice, through the United States/Mexico Border Counties Coalition, 2000-2001.  .

John R. Weeks, Co-Investigator (Douglas Stow, PI); Spatial Decision Support for Border Security, Grant from the National Aeronautics and Space Administration (NASA), 2003-2007.

John R. Weeks, Co-Principal Investigator (with Rubén G. Rumbaut), “Perinatal Risks and Outcomes Among Low-Income Immigrants,” grant from the U.S. Public Health Service, Bureau of Maternal and Child Health and Resource Development, 1990-91.

John R. Weeks, Principal Investigator,  “Border Issues in Population/Family Planning,” Grants from the William and Flora Hewlett Foundation, the Bergstrom Foundation, the S. H. Cowell Foundation, and the Rockefeller Foundation to the San Diego State University Foundation, 1986-1987.

 

Intra-Urban Health In Accra, Ghana Assessed with Remote Sensing and GIS

Website Link: http://geography.sdsu.edu/Research/Projects/IPC/ipc2_research.html

Institution: San Diego State University International Population Center

Description: This project explores the use of remotely sensed imagery and GIS to enhance our understanding of intra-urban inequalities in health, using data for the metropolitan area of Accra, Ghana as a study site. The specific aims are as follows: (1) to derive local (neighborhood) measures of health by combining spatially referenced census data, survey data, and vital statistics into a geographic information system (GIS) for metropolitan Accra; (2) to derive local (neighborhood) measures of the built and natural environment through the classification and analysis of data from remotely sensed imagery; (3) to test the hypothesis that health levels in urban places are importantly influenced by the local neighborhood environmental context, including the natural and built environment, the socio-economic composition of the neighborhood’s residents, and the location of a neighborhood within the broader urban environment (including its proximity to health clinics and hospitals); (4) to assess the relative contribution of neighborhood environmental context, population composition, and the neighborhood locational attributes to health outcomes in metropolitan Accra; (5) to model the interaction among the variables that predict health levels to determine what changes might be introduced into a neighborhood to bring its overall level of health up to a minimally acceptable standard; and (6) to evaluate how well the remotely-sensed data can, on their own as a proxy, model the intra-urban inequalities in health in ways that might lead these data to be used as health monitoring tools. The research involves three major steps: (1) creation of data layers and specification of georeferenced variables to be measured, including data from the 2000 Census, the 1998 and 2003 Demographic and Health Surveys, the 2003 Women’s Health in Accra Survey, the 2003 WHO World Health Survey in Ghana, data from the vital statistics for 1999-2001, and a high resolution multispectral satellite image which will be classified according to the Ridd V-I-S model of urban ecology, subsequent to which a set of landscape metrics will be calculated to measure the built and natural environments; (2) statistical analysis to answer the questions posed by our Specific Aims, which will include spatial statistics, regression, and multi-level approaches; and (3) interpretation and dissemination of the results.