The DHS Program has added a new open course to the roster of courses on the Learning Hub available for free with a simple registration. DHS Dataset Users is a course for anyone interested in using DHS data in research and analysis related to demography, public health, economics, sociology, or other social sciences. This course will help learners understand and begin to use DHS data for analysis.
In the DHS Dataset Users course, participants will learn:
To recognize different types of datasets that are a part of DHS surveys
How DHS survey samples are selected and designed to be nationally representative
How to open DHS datasets, find variables of interest, and perform descriptive analyses
To create Stata do files to make DHS data analysis quicker, easier, and more replicable
To complete all activities in this course and earn a certificate, participants must have any version of the statistical software package Stata. Learn on your own schedule and expect to spend 3-6 hours to complete the DHS Dataset Users course.
Practice new skills using standardized DHS model datasets and earn a certificate upon completion of the course that can be printed or shared on social media. To register and access the DHS Dataset Users course, click the button below, create a new Learning Hub account, and prepare to use DHS data!
Did you know that almost half of sexually active unmarried women in Nigeria age 15-49 have an unmet need for family planning, compared with only 19% of married women? Or that unmet need among sexually active unmarried women is lowest in Peru, at only 6%? These are the types of patterns and trends that jump off the screen in The DHS Program’s new family planning Tableau dashboard.
The DHS Program’s first Tableau dashboard visualizes 5 key family planning indicators in 58 countries. Users can explore global patterns and trends or deep dive into data from a single country.
The first view presents 5 family planning indicators for 3 groups of women (married women, sexually active unmarried women, and all women). Users can see at a glance how these indicators compare across these 3 groups of women, by background characteristics, and over time.
The “SDG visuals” option visualizes the more complex “demand satisfied by modern methods” indicator.
The “deep dive” presents the individual country data by 5 background characteristics (residence, education, age, wealth quintile, and subnational region).
In the global map view, users can see the range of any selected indicator across 58 recent DHS Program countries.
If you are brand new to Tableau, have no fear. Just click on the “?” icon and basic instructions will overlay your view.
July 11th is World Population Day. The Household Questionnaire collects information on all members of and visitors to households selected to participate in Demographic and Health Surveys. Basic information including age, sex, marital status, education, and relationship to the head of the household is collected for everyone who stayed in the selected households the night before the interview. Some of this information is visualized in a population pyramid, a great visualization of a country’s distribution of age groups by sex. The population pyramid is typically found in chapter 2 of Demographic and Health Survey Final Reports. Demographers can identify population trends based on a population pyramid’s shape and make predictions about that country’s population in the future.
Test your knowledge of demography, fertility, and population pyramids by taking The DHS Program’s #PopPyramid Quiz featuring population pyramids from recently published Demographic and Health Surveys (DHS). Hint: Use STATcompiler.com to find the answers.
Every year, hundreds of papers are published using DHS Program data. Datasets for individual DHS surveys are available for download from The DHS Program website by completing a simple registration form. Researchers and students can also access the IPUMS DHS data collection to facilitate comparative analysis of DHS Program data. Harmonized across time and space, IPUMS DHS features consistently named and coded variables for 32 African countries and 9 Asian countries, with more datasets constantly being added.
The IPUMS DHS team recently announced the winners of this year’s IPUMS Global Health paper awards, which highlight some of the most exciting research to take advantage of the IPUMS DHS integrated datasets. These papers were selected from a highly competitive field that included nearly 50 studies released in 2020.
Fan and Loria resolve a puzzle in prior research on intimate partner violence (IPV): Why is the relationship between IPV and contraceptive use negative in some countries and positive in others? Using 30 IPUMS DHS samples from 17 countries, the authors demonstrate that the relationship between IPV and family planning is modified by macro contextual factors, including legal prohibitions and national levels of female empowerment. This study stands out not just for answering an important social science question but also in its creative use of the broad range of information collected in DHS Program surveys, including variables on contraceptive use and type, family size preferences, husband-wife disagreement on fertility goals, various indicators of women’s status (e.g., education, employment, decision-making), and domestic violence. In addition, the authors draw on IPUMS DHS variables to determine the direction of causality: from the experience of IPV to increased contraceptive use, rather than from contraceptive use to increased incidence of IPV.
This study leverages geographic heterogeneity to determine the effect of reduced malaria burden on low-birth-weight rates across communities in 19 sub-Saharan African countries. Low birth weight is a serious health risk associated with cognitive and physical difficulties among children. This careful and cleverly designed study analyzes IPUMS DHS data from countries with at least two surveys and GPS data on survey cluster locations. After using optimal matching to pair DHS Program survey clusters separated in time, the authors use a difference-in-difference approach to compare the incidence of low birth weight in areas that did and did not experience malaria decline. Results reveal a substantial decline in low birth weight resulting from declines in malaria prevalence, especially for first-born children.
Congratulations to these scholars on this impressive accomplishment!
IPUMS DHS is a system that makes it easy to find and review thousands of DHS survey variables and to download a single fully harmonized data file with only the variables and samples that interest you. IPUMS DHS currently includes variables from DHS survey samples from 32 African and 9 Asian countries; more samples are constantly being added.
Special thanks to our guest blog contributors, Elizabeth Boyle and Miriam King!
Elizabeth Heger Boyle is Professor of Sociology & Law at the University of Minnesota. She studies the role of international laws and policies on women and children’s health around the world. She has written extensively on the impetus for and impact of laws related to female genital cutting, including the book Female Genital Cutting: Cultural Conflict in the Global Community. Her current research focuses on abortion policies globally and their effects; this includes a 2015 article in the American Journal of Sociology. Professor Boyle is currently co-Principal Investigator (with Dr. Miriam King) on IPUMS DHS, a National Institute of Child Health and Human Development grant that integrates Demographic and Health Surveys over time and across countries to make them more user-friendly for researchers. Professor Boyle has a Ph.D. in Sociology from Stanford University and a J.D. from the University of Iowa.
Miriam L. King is a Senior Research Scientist at the Institute for Social Research and Data Innovation at the University of Minnesota. She has managed data integration projects on the U.S. Current Population Survey, the U.S. National Health Interview Survey, and, most recently, the Demographic and Health Surveys. Her research has focused on the history of the U.S. census, data integration methods, U.S. historical fertility differences, living arrangements, and disparities in access to insurance for same-sex couples. Dr. King has a Ph.D. jointly in Demography and History from the University of Pennsylvania.
Over the next four days, demographers and public health professionals will present research, view and comment on posters, and network with peers. For those attending the PAA Annual Meeting, DHS Program staff will be presenting their findings using DHS data. Find the schedule below:
The DHS Program recently released three YouTube tutorial videos to help DHS data users access The DHS Program’s Code Share Library on GitHub. The Code Share Library was started in 2018 to provide code for producing DHS indicators listed in the Guide to DHS Statistics using statistical software like Stata or SPSS. This year, The DHS Program has begun preparing R code as well. You do not need to create a GitHub account to copy or download any code to produce DHS indicators; it is publicly available for use.
The first video, Overview of The DHS Program’s Code Share Library on GitHub, explains the main components of the Code Share Library, including Stata and SPSS repositories, the indicator list, ReadMe file, and chapter folder contents. In each repository on GitHub, there is an important ReadMe file with instructions for users to read before using the code provided.
One way to start using the Code Share Library is to download the entire repository on your computer. If any update is made to the code in the future, you will need to download the updated code from the Code Share Library. Another way to run the code is to copy and paste the code for your indicator of interest from GitHub to your own personal do file, without having to download the entire repository.
The third video, Running The DHS Program’s Shared Code on Stata, demonstrates how to run the code in Stata to construct indicator variables and produce tables for the indicators. The tables provide a simple tabulation that follows the standard DHS tabulation plan used for survey final reports.
The DHS Fellows Program builds the long-term institutional capacity of universities in DHS countries to train students and faculty to analyze DHS data. Since 2011, the DHS Fellows Program has trained more than 150 researchers from over 40 universities in 25 countries in Africa, Asia, and the Middle East. Typically, Fellows attend two separate in-person workshops, prepare publication-quality research papers in teams using DHS datasets, and implement capacity strengthening activities at their home universities.
For the 2020 DHS Fellows Program, a cohort of university faculty from Bangladesh, Burkina Faso, Cameroon, Guinea, Jordan, and Pakistan convened for the first workshop in Nairobi, Kenya, in February 2020. The second workshop, scheduled to begin in April 2020, was canceled due to the COVID-19 pandemic. The DHS Program worked quickly to convert the second workshop into online activities. A remote teaching space was created on The DHS Program Learning Hub with presentations and assignments for the Fellows to complete. Virtual meetings were held with each Fellows team to discuss drafts of their working papers.
The 2020 DHS Fellows produced working papers that addressed a variety of research topics including:
As of this blog’s publication, the teams from Jordan and Cameroon have published their working papers in peer-reviewed journals. Visit The DHS Program Fellows page to see all DHS Fellows’ working papers and publications in peer-reviewed journals.
We interviewed teams of 2020 Fellows from the Asian University for Women in Bangladesh and the Gamal Abdel Nasser University of Conakry in Guinea about the virtual DHS capacity strengthening activities conducted for faculty and students.
For their working paper, Nazmul Alam, Mohammad Manir Hossain Mollah, and Sharin Shajahan Naomi wrote about the prevalence and determinants of adolescent fertility. They conducted two virtual capacity strengthening sessions via Zoom, one for 21 faculty members, researchers, and development practitioners, and another session for 25 students. In the sessions, the Fellows introduced participants to The DHS Program, reviewed basic characteristics of DHS data, and highlighted how one can effectively generate new ideas from available DHS data without needing to conduct field research, which has become difficult during the COVID-19 pandemic. “Although we were a bit hesitant about the outcome of online sessions, they appeared to be beneficial…faculty members from social sciences, public health, and natural sciences joined…after the workshop, we got very positive feedback.”
Bienvenu Salim Camara, Sidikiba Sidibé, and Nafissatou Dioubate wrote about non-use of contraceptives among married women. Days before their planned capacity strengthening presentations, Guinea declared a health emergency due to COVID-19. Universities were closed and gatherings of more than 20 people were prohibited, so the Fellows recorded video presentations introducing The DHS Program survey questionnaires and datasets and uploaded them to Google drive. Students watched the videos at their own pace and emailed the Fellows with questions. Now some students are using DHS data in their research. “One of my students is currently working on his Master’s thesis in maternal health using DHS data, and I am supporting him in the data analysis,” explains Camara. Dioubate notes, “I am proud that I was able to pass on the knowledge gained from the DHS Fellows Program to others and show the opportunities that DHS data can offer.”
Explore indicators related to women’s empowerment, reproductive health, and more using STATcompiler. Download Stata and SPSS code for these and other topics from The DHS Program’s code library on GitHub, and check out the wealth of gender-related resources and publications available at dhsprogram.com.
Learn more about Sustainable Development Goal #5, gender equality indicators from recent DHS surveys in the infographic below.
Anthropometry measurement (height and weight) is a core component of DHS surveys that is used to generate indicators on nutritional status. The Biomarker Questionnaire now includes questions on clothing and hairstyle interference on measurements for both women and children for improved interpretation.