What is the difference between a percentage and a percent distribution? What about a mean and a median? How do rates and ratios differ? Essential Statistical Concepts for Understanding DHS Program Data is a new open course for anyone who wants to familiarize themselves with the most commonly used statistics found in tables in DHS Program household-based surveys.
Available for free with a simple registration on the DHS Program Learning Hub, this self-paced course will give you the skills you need to correctly and confidently cite DHS Program data.
Identify the statistical measures used for indicators in DHS Program tables
Practice calculating basic statistics
Learn about sampling errors, confidence intervals, statistical significance, and standard deviation and how to apply these concepts when interpreting DHS Program data
Learn on your own schedule and expect to spend 1-2 hours to complete this course. After taking Essential Statistical Concepts for Understanding DHS Program Data, participants will be able to confidently interpret tables and correctly cite DHS data and use DHS data to inform program and policy decision making. To register and access the course, click the button below, create a new Learning Hub account, and get ready to learn!
The DHS Program’s Final Reports include comprehensive survey results. The most important findings are highlighted in the chapter text and figures, though not every finding is discussed or displayed graphically. Therefore, it is important for DHS data users to feel comfortable reading and interpreting the statistical tables included in every Final Report, which can look intimidating at first.
To help DHS data users confidently read and interpret tables, The DHS Program has a new open course available for free with a simple registration on the Learning Hub. Essential Reading and Understanding The DHS Program Tables is a course for anyone interested in understanding demographic and health data found in Final Reports. This interactive course familiarizes users with the basic elements of DHS Program tables.
In the Essential Reading and Understanding The DHS Program Tables course, participants will learn:
The 4 basic steps in reading The DHS Program tables
To identify the denominator of the table, the indicators and background characteristics presented, and the totals in the table
How to compare indicator data by background characteristics and identify patterns in the data
Why parentheses and asterisks are used in The DHS Program tables and their implications for data use
Learn on your own schedule and expect to spend 1-2 hours to complete this course. After taking the Essential Reading and Understanding The DHS Program Tables course, participants will be able to read tables and find patterns and stories in the data with confidence. To register and access the course, click the button below, create a new Learning Hub account, and prepare to read DHS Program tables!
The DHS Fellows Program builds the long-term institutional capacity of universities in DHS Program 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.
The 2022 DHS Fellows Program will be conducted virtually and in English. Because the DHS Fellows Program will be virtual, this year’s call for applications is open to countries that have not been included in the DHS Fellows Program previously. Applications are accepted from university faculty members at universities in Angola, Benin, Burundi, Gambia, Liberia, Mali, Sierra Leone, South Africa, Maldives, Papua New Guinea, Timor-Leste, Guatemala, Haiti, Armenia, and Tajikistan. Teams of three members from the same university who teach and/or conduct research in demography, public health, economics, sociology, or other social sciences are encouraged to apply.
Read about how the 2020 DHS Fellows Program was impacted by the COVID-19 pandemic and adapted to be delivered virtually.
Visit The DHS Program Fellows page to see all DHS Fellows’ working papers and publications in peer-reviewed journals. The deadline to submit applications is November 21, 2021.
The Biomarker Manual aligns with DHS-8 standard materials and policies representing the most up-to-date procedures. Standard measures in DHS surveys include height/length, weight, and hemoglobin. Anthropometric data are collected for children age 0-59 months, women age 15-49, and men age 15-49, 15-54, or 15-59 depending on the survey. These data are used to estimate malnutrition in children, body mass index (BMI) in adults, and BMI-for-age in adolescents. Hemoglobin measurement provides anemia prevalence estimates for children age 6-59 months along with women and men.
Children age 0-59 months
Children age 6-59 months
-Malnutrition in children
Women age 15-49
Men age 15-49, 15-54, or 15-59
-BMI in adults
-BMI-for-age in adolescents (age 15-19)
The Biomarker Manual is a critical resource used by DHS Program biomarker specialists and consultants to train biomarker technicians and supervisors on all aspects of collecting high-quality biomarker data. The Biomarker Manual can serve as a tool for others conducting surveys similar to DHS surveys. The manual includes procedures for:
Completing The DHS Program Biomarker Questionnaire and related documentation
Capillary blood collection
Biohazardous waste management and disposal
The Biomarker Manual also includes examples of materials to aid in data collection – informational pamphlets provided to households, referral forms provided for cases of severe acute malnutrition and severe anemia, forms used during training on anthropometry (e.g., standardization exercises), and forms for monitoring equipment during fieldwork (daily maintenance logs).
The DHS Height Standardization Tool is used during the anthropometry standardization exercise to record trainees’ height or length measurements and to calculate trainees’ accuracy and precision. The results of the calculations are illustrated visually for each trainee and compared to the pass/fail cutoffs for accuracy and precision. The tool is a useful resource for anyone collecting anthropometry data in surveys or research as it helps to identify trainees who may need further training and re-standardization before data collection.
Many DHS surveys collect additional biomarkers in addition to the standard biomarkers mentioned above, e.g., malaria rapid diagnostic testing (RDT), dried blood spot (DBS) preparation for lab-based testing for a variety of infections or conditions, blood pressure measurement, and micronutrient biomarkers. The resources in the new Biomarker Manual can be adapted to accommodate the collection of these other biomarkers.
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.
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.