Tools for Combining Data Across IPUMS Global Health Surveys

By Miriam King, Devon Kristiansen, and Anna Bolgrien

IPUMS Global Health includes integrated data from three international health surveys: Demographic and Health Surveys (IPUMS DHS), Multiple Indicator Cluster Surveys (IPUMS MICS), and Performance Monitoring for Action (IPUMS PMA). All three surveys are nationally representative, primarily focus on low- and middle-income countries, and address issues related to the health and well-being of women and young children. These commonalities make combining integrated data across these data collections appealing. As Figure 1 shows, IPUMS DHS and IPUMS MICS cover different countries; combining them extends the geographic coverage of harmonized versions of data covering similar topics. Researchers can also combine data for those countries included in both IPUMS DHS and IPUMS MICS to provide additional observation points for time-series analyses.

Figure 1: Countries covered by IPUMS DHS and IPUMS MICS

World map with the countries included in IPUMS MICS and IPUMS DHS shaded in

Researchers who want to carry out cross-survey analyses face practical challenges. IPUMS imposes consistent variable names and codes within one kind of survey (DHS, MICS, or PMA); harmonized variable names and codes differ between these surveys. On each project’s website, the documentation for each variable highlights comparability issues to keep in mind when combining multiple samples, either within one type of survey or across survey types. IPUMS users must make separate customized data files from each database and merge those files. And subtle differences in question wording, skip patterns, geographic boundaries, and sampling procedures—such as MICS’ taking reports on child health from caretakers other than the biological mother—can introduce inconsistencies and inadvertent errors.

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Constructing comparable intimate partner violence indicators across the DHS, MICS, and PMA health surveys

By Miriam King, Anna Bolgrien, Mehr Munir, and Devon Kristiansen

The three data series comprising IPUMS Global Health—IPUMS DHS, IPUMS PMA, and IPUMS MICS—contain intersecting subjects related to women’s and children’s health, while retaining distinct patterns of temporal and geographic coverage. This content overlap opens the door to combining harmonized data across the three surveys, to extend time series and/or increase the number of countries in comparative analyses. However, there are important yet subtle differences between these survey types, in sample frames, questionnaire wording, and variable responses and universes, which require cautious consideration. As the example below demonstrates, researchers must use extra care to avoid errors when combining data across IPUMS DHS, MICS, and PMA.

A July 2024 article in the Journal of Public Health Policy, “Constructing Comparable Intimate Partner Violence Indicators across DHS, MICS, and PMA Health Surveys,” describes some challenges and solutions to combining data across these IPUMS databases, using measures of intimate partner violence as an example. The piece, authored by Devon Kristiansen and colleagues at IPUMS, notes two necessary steps in combining data across survey types:

  • Identify and combine only variables with similar question wording
  • Adjust the samples to include only comparable subpopulations

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IPUMS at ICFP2022

by Devon Kristiansen

IPUMS was proud to partake in the International Conference on Family Planning in Pattaya City, Thailand. We participated by hosting a pre-conference workshop, sponsoring the conference, staffing an exhibit both, and presenting research as part of the conference program. The conference, held between November 14th and 17th, 2022, had 3,500 in-person attendees, with many virtual participants, as well.

Research staff representing IPUMS PMA, IPUMS DHS, IPUMS MICS, and IPUMS International conducted a 2-hour pre-conference workshop, providing participants with an overview of each of the IPUMS data collections featuring international data as well as a website and data analysis demonstration.

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IPUMS PMA Longitudinal Data

By Devon Kristiansen

When Performance Monitoring for Action (PMA) initiated data collection in 2013, the survey design was a high-frequency, cross-sectional series with a focus on family planning, water, and sanitation indicators. Beginning in 2019, PMA refocused on reproductive and sexual health, and adjusted the survey design to add a contraceptive calendar and a longitudinal panel of women of childbearing age to observe contraceptive and fertility dynamics.

In order help researchers leverage the rich data from the redesigned PMA, IPUMS PMA has updated its online data dissemination system to provide longitudinal data in long form or wide form, delivering data files that link the women’s panel records.

The longitudinal data are designed to allow for analysis of contraceptive uptake, discontinuation, and method switching, as well as changes in fertility intentions and actualization over time. However, the redesigned survey also includes many new questions, including questions about domestic violence, women’s economic empowerment, abortion, health care access during COVID-19, and many other topics.

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Visualizing IPUMS Global Health with Storymaps

By Matt Gunther

IPUMS data are a great research resource; they are also widely used by faculty for teaching students about using data to tell stories. This blog post, adapted from the IPUMS PMA Data Analysis Hub blog series, highlights work from students using IPUMS Global Health data.

This semester, students in the Global Health Survey Analysis course at the University of Minnesota used an amazing tool called StoryMaps to develop interactive narratives exploring different topics related to family planning. StoryMaps have been used in both the undergraduate and graduate curriculum throughout the College of Liberal Arts and beyond – we encourage you to check out the full gallery of student projects here!

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IPUMS Announces 2020 Research Award Recipients

IPUMS research awardsIPUMS is excited to announce the winners of its annual IPUMS Research Awards. These awards honor the best-published research and nominated graduate student papers from 2020 that used IPUMS data to advance or deepen our understanding of social and demographic processes.

IPUMS, developed by and housed at the University of Minnesota, is the world’s largest individual-level population database, providing harmonized data on people in the U.S. and around the world to researchers at no cost.

There are six award categories, and each is tied to the following IPUMS projects:

  • IPUMS USA, providing data from the U.S. decennial censuses, the American Community Survey, and IPUMS CPS from 1850 to the present.
  • IPUMS International, providing harmonized data contributed by more than 100 international statistical office partners; it currently includes information on 500 million people in more than 200 censuses from around the world, from 1960 forward.
  • IPUMS Health Surveys, which makes available the U.S. National Health Interview Survey (NHIS) and the Medical Expenditure Panel Survey (MEPS).
  • IPUMS Spatial, covering IPUMS NHGIS and IPUMS Terra. NHGIS includes GIS boundary files from 1790 to the present; Terra provides data on population and the environment from 1960 to the present.
  • IPUMS Global Health: providing harmonized data from the Demographic and Health Surveys and the Performance Monitoring and Accountability surveys, for low and middle-income countries from the 1980s to the present.
  • IPUMS Time Use, providing time diary data from the U.S. and around the world from 1965 to the present.

Over 2,500 publications based on IPUMS data appeared in journals, magazines, and newspapers worldwide last year. From these publications and from nominated graduate student papers, the award committees selected the 2020 honorees.

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PMA Data Analysis Hub

By Matt Gunther

IPUMS PMA has launched a new blog aimed at introducing harmonized family planning data through step-by-step analysis examples written in R. Whether you’re looking for a place to dive into Performance Monitoring for Action data or a way to learn more about free and open-source data analysis tools, the PMA Data Analysis Hub is a great place to start!

You’ll find a new post every two weeks highlighting different tips for working with PMA data. Usually, we organize these posts in a series around a theme or a particular group of variables. For example, did you know that PMA collects data from both individuals and health service providers in the same geographic area? We’ve just completed our first series of posts showing how to use service provider data as context for the family planning outcomes experienced by individuals.

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