IPUMS MICS – Use It for Good

Measures of Depression and Anxiety in Adults, in IPUMS (U.S.) National Health Interview Survey and IPUMS Global Health

October 16, 2026 by mpcblog

By Miriam L. King, Anna Bolgrien, & Julia Rivera Drew

Mental health conditions, such as depression and generalized anxiety disorder, are an important aspect of population health around the world. Including measures of mental health conditions in population health surveys is important for elucidating overall wellbeing. For example, a 2025 IPUMS Best Student Paper winner used data from the IPUMS-harmonized National Health Interview Survey (NHIS) and Medical Expenditure Panel Survey (MEPS) to document increasingly poor self-rated health among young adults in the U.S., largely due to an increase in the prevalence of poor mental health.¹ While mental health measures have long been included in U.S. health surveys such as the NHIS, the Demographic and Health Surveys (DHS) and the UNICEF Multiple-Indicator Cluster Surveys (MICS) have recently incorporated measures of mental health comparable to those found in the NHIS.

This blog post will identify new opportunities for the comparative study of mental health by highlighting some of the widely available measures of depression and anxiety in the U.S. NHIS and in international population health data sources available from IPUMS. Which mental health measures to use will depend on the research question and the population of interest. Diagnosis-focused measures ask whether a person was (ever) told by a health professional that they have a certain mental health condition. Symptom-focused approaches ask about recent symptoms associated with mental health conditions, often using validated scales. Symptom-focused queries give a more accurate view of the prevalence of mental health problems, particularly in settings where medical and mental health resources are sparse, so few people are diagnosed.

Linking children and adolescents to their mothers using IPUMS MICS

March 20, 2026 by mpcblog

By Anna Bolgrien

IPUMS MICS offers hundreds of harmonized variables related to children’s health and wellbeing that allow for rich and innovative research. From the IPUMS MICS website, users can browse variables and create custom data extracts within a selected unit of analysis. In order to conduct many analyses, however, users will want to combine and link datasets relating to different units of analysis available in MICS.

For example, to investigate how child characteristics are related to characteristics of their mother, users will need to download and link data between the Children (either 0-4 or 5-17) unit of analysis and the Women unit of analysis.

IPUMS MICS provides instructions for linking across units of analysis as a user note. This user note lists the variables available as linking keys for each unit of analysis, and is a general guide for linking across the units, such as linking household characteristics with individual person records.

In this blog post, we provide more detailed information on how to link children and adolescents to their mothers. Similar logic can be applied to link children to fathers or other caregivers in the household. As IPUMS MICS requires Stata to conduct harmonization, we provide example code in Stata syntax.

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

Making Your Customized IPUMS MICS Data File

January 25, 2024January 24, 2024 by mpcblog

By Anna Bolgrien

The newest IPUMS data collection, IPUMS MICS, has many similarities with other IPUMS microdata collections. However, there is one major difference: the IPUMS MICS Data Extract System only uses Stata.

Yes, you read that right. Users of IPUMS MICS must use Stata to open and create their customized data file.

Let’s start with how using IPUMS MICS is the same as using other IPUMS microdata collections.

If you are an IPUMS user, you will find the process of browsing the variables, looking at documentation, and adding samples to your data cart completely familiar. If you are not familiar with IPUMS, you can read more about browsing and selecting variables.

However, when you finish choosing variables and samples in IPUMS MICS and click “Create Extract,” things start to look different.

Normally, you could change the data format, but the only option currently available for IPUMS MICS is a .dat (fixed-width text) file format.

Announcing IPUMS MICS

May 28, 2025October 19, 2023 by mpcblog

By Anna Bolgrien

IPUMS has an exciting new data collection to announce: IPUMS MICS!

IPUMS MICS is the integrated version of UNICEF MICS (Multiple Indicator Cluster Surveys), the largest and most robust source of data on women and children’s well-being across the globe, including countries in Africa, Eastern Europe, Asia, and Latin America. Separate datasets cover women of childbearing age, children aged 0 to 4, children aged 5 to 17, respondent’s birth history, men, household members, and household characteristics.

Currently, IPUMS MICS includes harmonization of data from 202 MICS samples, which represent 88 countries, and cover surveys conducted between 2005-forward. There are over 800 integrated variables currently available on our website. Future releases will expand the sample and variable coverage of IPUMS MICS.