New Data Release from IPUMS International – From Mexico to MOSAIC

By Lara Cleveland and Jane Lee

IPUMS International has released new data! Eighteen new census samples have been added to the collection, including data from Côte d’Ivoire, which is new to IPUMS International. Newly released census samples include Cambodia (2019), Côte d’Ivoire (1988, 1998), Denmark (1845, 1880, 1885), Laos (1995, 2015), Mexico (2020), Peru (2017), Puerto Rico (2015, 2020), Switzerland (2011), United Kingdom (1961, 1971), United States (2015, 2020) and Vietnam (2019). As always, we gratefully acknowledge the national statistical offices of all the countries partnering with IPUMS International to make data available for research.

New geography variables are also now available with harmonized migration variables at the second-administrative level; the codes for the newly released migration variables match existing IPUMS International geography codes and labels. As an example, the geographic units in the migration variable for Mexico at the municipo level (place of residence 5 years ago, MIG2_5_MX) are reconciled to the boundaries for place of current residence (GEO2_MX).

This is a map showing the 2020 census 5-year migration rates for GEO1 in Mexico, and GEO2 in Nuevo Leon state
2020 census 5-year migration rates for GEO1 in Mexico, and GEO2 in Nuevo Leon state. Map by Quinn Heimann

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New IPUMS DHS Climate Change and Health Research Hub

By Miriam King, Senior Research Scientist

Men wading through flood watersIn October 2023, the World Health Organization stated, “3.6 billion people already live in areas highly susceptible to climate change. Between 2030 and 2050, climate change is expected to cause approximately 250,000 additional deaths per year, from undernutrition, malaria, diarrhea and heat stress alone.”

The Demographic and Health Surveys (DHS) are an ideal source for research on the health effects of climate change. Since the 1980s, the DHS has collected a broad range of nationally representative health data from over 90 countries. With supplemental funding from NICHD, harmonized DHS data from IPUMS (dhs.ipums.org) is now doing more to support research on the effects of climate change on health. We are adding new contextual variables; we are integrating data from Malaria Indicator Surveys (MIS); and we are offering guidance through the new Climate Change and Health Research Hub.

Sound research on climate change and health requires combining social science and health data with natural science data. While social scientists and public health researchers have considerable experience analyzing health survey data, few have been trained in simultaneously employing data on environmental factors. This knowledge gap is addressed by the Climate Change and Health Research Hub, under the leadership of Dr. Kathryn Grace and Senior Data Analyst Finn Roberts.

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2020 Public Use Microdata Area (PUMA) Updates in the 2022 American Community Survey

By Natalie Mac Arthur, Senior Research Associate, SHADAC

Thank you to our collaborators at the State Health Access Data Assistance Center (SHADAC) for contributing this blog post; view the original blog on the SHADAC website.

A Public Use Microdata Area (PUMA) is a type of geographic unit created for statistical purposes. PUMAs represent geographic areas with a population size of 100,000–200,000 within a state (PUMAs cannot cross state lines). PUMAs are the smallest level of geography available in American Community Survey (ACS) microdata. They are designed to protect respondent confidentiality while simultaneously allowing analysts to produce estimates for small geographic areas.

Every ten years, the decennial census results are used to redefine ACS PUMA boundaries to account for shifts in population and continue to maintain respondent confidentiality. This process is intended to yield geographic definitions that are meaningful to many stakeholders.

Most recently, new PUMAs were created based on the 2020 Census; these 2020 PUMAs were implemented in the ACS starting in the 2022 data year. Although Public Use Microdata Area components remain consistent to the extent possible, they are updated based on census results and revised criteria. Therefore, they are not directly comparable with PUMAs from any previous ACS data years. For example, the 2020 PUMAs used in the 2022 data year are distinct from the 2010 PUMAs, which were used in the 2012–2021 ACS data years.

The 2020 PUMAs were created based on definitions that include two substantive changes relative to the 2010 PUMAs:

1) An increase in the minimum population threshold for the minimum size of partial counties from 2,400 to 10,000. Increasing the population minimum for a PUMA-county part aims to further protect the confidentiality of respondents. However, exceptions are allowed on a case-by-case basis in order to maintain the stability of PUMA definitions (that were based on the previous minimum of 2,400) and due to unique geography.

2) Allowing noncontiguous geographic areas. Allowing PUMAs to include noncontiguous geographic areas aims to avoid unnecessarily splitting up demographic groups in order to provide more meaningful data. This change is not intended to create highly fragmented PUMAs.

Other than the two changes listed above, PUMA criteria remained consistent, such as treating 100,000 as a strict minimum population size for PUMAs. The maximum population size for PUMAs can exceed a population of 200,000 in certain instances due to expected population declines or geographic constraints.

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