IPUMS DHS – Use It for Good

IPUMS DHS Goes Global

May 4, 2026 by mpcblog

By Miriam L. King and Sula Sarkar

IPUMS DHS now includes integrated variables for 84 counties (up from 51) and nearly 350 samples (up from 233), including new data from Latin America, Eastern Europe, Oceania, the Caribbean, and Central and East Asia. Providing DHS data in a form that facilitates micro-analyses across countries is one of IPUMS’ greatest strengths, so researchers will be excited to learn that they can now do even more! Our latest data release expands the scope of IPUMS DHS beyond its initial coverage of Africa, the Middle East, and South Asia and adds the latest samples for 12 countries previously in the database. Figure 1 shows the full geographic scope of IPUMS DHS, as well as highlighting newly added countries and previously included countries with new samples.

Figure 1: Countries included in IPUMS DHS

Demographic and Health Survey (DHS) Data Again Available to New Users

September 3, 2025 by mpcblog

By Miriam King

After funding for USAID and the Demographic and Health Surveys (DHS) was eliminated in February 2025, new researchers could no longer apply online for access to DHS data, and existing DHS users could not gain access to additional countries’ data. This restriction affected would-be users of both the original DHS public use files and the integrated version of DHS data through IPUMS DHS. Fortunately, The DHS Program just announced, “We are now open for new registrations.”

The DHS Program logo According to The DHS Program website, a three-year grant from the Gates Foundation is supporting the dhsprogram.com website and data archive, where researchers apply for access and can download the original public use files. Once a researcher is approved for DHS data access, they can log in to the IPUMS DHS website, create a customized dataset with the samples and harmonized variables they need, and download that file for analysis on their computer. Anyone can use the IPUMS DHS website to learn about the data, including documentation about the consistently coded variables and the availability of variables by sample, to plan a research project; they need to log in only if they would like to create and download a customized data file.

The grant funding will also support other useful elements of The DHS Program website: StatCompiler (for summary statistics by sample), the DHS Program API, and the Spatial Data Repository (for maps and shapefiles).

Working with Subnational Geographies in IPUMS Global Health

June 17, 2025 by mpcblog

By Divya Pandey and Anna Bolgrien

In a research project combining data from IPUMS MICS and IPUMS DHS, IPUMS Global Health staff examined trends in the relationship between open defecation and high infant mortality rates (IMR) in the Eastern Indo-Gangetic Plains. The project focused on selected bordering regions in Nepal, Bangladesh, and India. By analyzing these environmentally and agro-climatically comparable regions, the study aimed to isolate the impact of national and local policies on open defecation and infant mortality rates.

Figure 1: Regions included in the study

A map of the border and surrounding regions of Nepal, Bangladesh, and India that highlights the sub-national regions included in the study.

The study pooled data from IPUMS MICS and IPUMS DHS to look at trends over almost two decades. IPUMS DHS includes data for all three countries, and IPUMS MICS provides additional years of data for Nepal and Bangladesh. Since the study focused on selected bordering geographies, the authors worked with data from lower administrative levels—divisions in Bangladesh, states in India, and regions in Nepal. Leveraging the geography resources provided by IPUMS, the team used both spatially harmonized and sample-specific geography variables (learn more about IPUMS DHS geography variables and IPUMS MICS geography variables). Spatially harmonized geography variables identify geographic regions using a consistent spatial footprint to allow for the comparison of the same physical space over time. Sample-specific geography variables are not harmonized across time; as their name suggests, they use the geographic boundaries that are sample-specific or contemporaneous to the survey-year in a country.

Tools for Combining Data Across IPUMS Global Health Surveys

May 14, 2025March 3, 2025 by mpcblog

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.

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

June 4, 2025September 16, 2024 by mpcblog

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

Harmonized Malaria Indicator Survey (MIS) Data Now in IPUMS DHS

September 5, 2024September 3, 2024 by mpcblog

By Miriam King, Senior Research Scientist

Malaria is a pressing global health problem, with nearly 250 million malaria cases in 2022, according to the World Health Organization. Approximately 95 percent of malaria deaths were in Africa, with three-quarters of those deaths to children under 5. Climate change is increasing the transmission of mosquito-borne diseases, such as malaria. When IPUMS DHS recently received supplemental funding to support research on Climate Change Effects on Health, adding data on malaria was a top priority. Specifically, IPUMS DHS chose to integrate data from the DHS Malaria Indicator Surveys (MIS).

MIS have been fielded in nearly 30 African countries during the twenty-first century. Developed under an international partnership coordinating efforts to fight malaria, MIS surveys include some standard DHS variables on topics such as demographics, fertility, and household characteristics. MIS questionnaires also include hundreds of questions related to malaria. People’s knowledge about malaria causes, symptoms, and prevention; use of bednets; diagnosis and treatment of malaria, especially for pregnant women and children; exposure to public health messaging; and diagnostic blood testing for malaria in children under 5 are among the topics covered.

Map of Africa with the countries with MIS data in IPUMS DHS filled in with purple — Figure 1: Countries with MIS Data in IPUMS DHS

IPUMS DHS users now have access to harmonized data from 38 MIS samples, with geographic coverage shown in Figure 1. We prioritized harmonizing responses to MIS questions that matched variables already in the IPUMS DHS database, for approximately 700 widely available variables.

New IPUMS DHS Climate Change and Health Research Hub

June 15, 2025April 23, 2024 by mpcblog

By Miriam King, Senior Research Scientist

Men wading through flood waters In 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 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.