Category Archives: Data

07 Jan 2020

Introducing DHS Program Analysis Briefs

Over the last 30 years, The DHS Program has published more than 500 analytical reports in collaboration with researchers and institutions around the world. These reports extend to a wide variety of topics covering population and health issues with the ultimate purpose to be used in policy formation, program planning, and monitoring and evaluation. However, many potential beneficiaries of DHS Program research findings are intimidated by these long, technical reports.

In order to expand the reach of DHS analyses to program managers, policymakers, and academic researchers, The DHS Program is pleased to announce a new user-friendly format of analysis reports. Analysis Briefs are two- to three-page user-friendly documents summarizing the methods, key findings, and any relevant action steps.

 

Analysis Brief AB2 (shown above) provides the methodology and key results for Further Analysis 110: Maternal Health Indicators in High-Priority Counties of Kenya: Levels and Inequities.

These abbreviated, colorful briefs with graphics highlight major findings in a more accessible way that allow readers to use the findings for program or policy use in their respective country. If readers choose to dive into the full report, the brief still provides an orientation through the technical data in the full report. The graphics are presented in a simplified way to orient the information in a clear, visual display. Readers with limited time and attention are encouraged to review the accompanying briefs for a condensed summary of the full analysis report.

Briefs can be found on the full report publication summary page or by filtering by publication type ‘Analysis Briefs’ in The DHS Program publication search.

 
02 Dec 2019

16 Days of Activism against Gender-based Violence

The 16 Days of Activism against Gender-based Violence campaign is back in action for 2019 under the theme “Orange the World: Generation Equality Stands against Rape!” This year, The DHS Program is highlighting sexual and physical violence indicators, as well as help seeking behavior in Tajikistan, Pakistan, Nigeria, Benin, and Mali.

Click on a graph below to open the indicator in STATcompiler. Use STATcompiler to compare other domestic violence indicators across countries, and share your results on social media using #orangetheword and #generationeqaulity. You can even add additional background characteristics and view the data over time or by region. For more ways to use STATcompiler, watch our STATcompiler tutorials.

 

Still want to do more? Share these 16 days messages from UN Women’s social media toolkit. Additionally, try The DHS Program’s Gender mini tool to compare indicators of gender inequality, women’s empowerment, and gender norms all in one easy tool.

22 Oct 2019

Journey Mapping Methods: Results from a Study on Place of Delivery

Data from the World Health Organization (WHO) estimate that, globally, 289,000 women of reproductive age die of maternal causes each year. Over 80% of these deaths are due to complications during childbirth and the postpartum period. Skilled birth attendance at health facilities equipped to handle complications is crucial for ensuring maternal survival. While Kenya has made progress in improving maternal health services in the last decade, data from the 2014 Kenya Demographic and Health Survey show that less than two-thirds of births are delivered in a health facility.

The DHS Program recently published a study on place of delivery and shared the results with county stakeholders and USAID project implementers at dissemination events in Kisumu, Turkana, Nakuru, and Nairobi counties. One aim of the study was to explore the “why” questions that sometimes are left unanswered with indicator estimates and other quantitative analysis; specifically: Why do women in Kenya deliver at home, even in instances when health facilities appear to be available?

Click photos to enlarge.

Exploring this research question included the use of journey mapping methods. In particular, the data collection tools were designed with the aim of mapping the journey for Kenyan women from the time when they learn they are pregnant to when and where they give birth.

A journey mapping approach recognizes that often a journey does not follow a straight line; instead, a journey—from pregnancy to delivery in this case—includes many economic, familial, and sociocultural factors that must be navigated along the way. In addition, the focus on mapping journeys works to uncover the story related to a woman’s delivery experience.

Data from the study suggest that place of delivery is not as simple as grouping women into the dichotomy of those who choose to deliver in a health facility and those who choose to deliver outside a health facility. Numerous factors influence place of delivery, and women do not necessarily always choose the place of delivery. The study’s conclusions recognize that contextual factors and decision making pertaining to place of delivery are complex. The pregnancy-to-delivery continuum follows an ever-shifting terrain influenced by myriad individual and collective beliefs, perceptions, tensions, and experiences.

Key Conclusions: Understanding the Nuances of a Women’s Journey along the Pregnancy-to-Delivery Continuum

  • Decision making occurs over time
  • Limited options for services to address fears and insecurities
  • Gendered views regarding male partner involvement in health care
  • Geographic and transportation challenges
  • Free maternity care is not always free
  • Expectation of support and respectful maternal care not always met
  • Prominence of and preferences for traditional birth attendant (TBA)
  • Challenges negotiating decisions and power dynamics in a marriage or partnership
  • Hesitancy of health facilities to accommodate for traditional practice
  • Potential reliance on financial support from male partners

The conclusions from this study represent a platform to galvanize momentum and facilitate a commitment to take positive steps forward. Past and present strategies and programs put into operation by USAID/Kenya, the Government of Kenya, and their partners have made substantial progress in improving the uptake of optimal maternal and child health practices. Research studies such as this one—and the use of journey mapping methods—can make a valuable contribution to knowledge about both the context in which women experience pregnancy and delivery and the specific challenges they face along the pregnancy-to-delivery continuum.

Download the full study, “Place of Delivery: Perceptions, Tensions, and Experiences. Results from a Study in Baringo, Kisumu, Migori, Samburu, and Turkana Counties, Kenya” on The DHS Program website.


Photo gallery captions (left to right):

  1. Participants at the Kisumu County dissemination and data use workshop, August 1, 2019. © ICF
  2. Participants at the Turkana County dissemination and data use workshop, August 5, 2019. © ICF
  3. Participants at the Nakuru County dissemination and data use workshop, July 29, 2019. © ICF
  4. Participants at the Nairobi dissemination and data use workshop, July 17, 2019. The group included Nairobi-based stakeholders as well as key stakeholders who traveled to Nairobi from Baringo, Kisumu, Migori, Nakuru, Samburu, and Turkana counties. © ICF
10 Oct 2019

DHS-8 Questionnaires

The DHS Program is pleased to share our updated questionnaires for DHS-8. We held an open comment period in early 2019 and received over 1,000 pages of material from stakeholders worldwide. After careful consideration of each submission, we made numerous changes to better meet existing and emerging data needs in global health. We are especially excited to announce the shift from a birth history to a full pregnancy history and the addition of minimum dietary diversity for women.

We added 183 new questions across all health areas, revised existing questions to better measure current indicators, and deleted questions that were no longer programmatically relevant. We have also expanded into new areas, including alcohol consumption and breast and cervical cancer screening. Additional changes to DHS optional modules and a list of new modules will be announced later this year.

In addition to the updated questionnaires, a brief summary document was developed highlighting the revision process and new content included in the core questionnaires. Revisions were made to the majority of topics including, family planning, nutrition, gender, HIV, vaccination, and more.

Learn more about the DHS-8 questionnaire revisions by the numbers in the infographic below.

Visit The DHS Program to learn more about the standard model questionnaires for all types of surveys.

Analysis Brief AB2 (shown above) provides the methodology and key results for Further Analysis 110: Maternal Health Indicators in High-Priority Counties of Kenya: Levels and Inequities.

24 Sep 2019

Global Goals Week 2019

Global Goals Week is back with a full week of action, awareness, and accountability for the Sustainable Development Goals (SDGs), also known as the Global Goals. The Demographic and Health Surveys (DHS) Program collects demographic and health indicators to calculate approximately 30 of the indicators supporting the SDGs.

These indicators and more can be found in STATcompiler, a tool that allows users to create custom tables, charts, and maps. Use the SDG tag to select from a list of SDG indicators and view them by background characteristics, overtime, and across countries.

This week we are highlighting three Global Goals using DHS data from five recent DHS surveys. Click an SDG indicator in the infographic below and compare the indicators of demand for family planning satisfied by modern methods, secondary education, and age at first marriage in Albania, Benin, Jordan, Mali, and Pakistan. Customize the tables by background characteristics or trends over time to create your own data visualization. Share your results with the #GlobalGoals community.

Share this infographic on Facebook and Twitter, and don’t forget to tag #GlobalGoals to engage with others in this global conversation!

19 Aug 2019

DHS Data Users: Samuel Oppong, Ghana National Malaria Control Programme M&E Specialist

If you are interested in being featured in the ‘DHS Data Users’ blog series, let us know here by submitting your example of DHS Program data use. 


How are you involved in DHS Program surveys and analysis workshops?

My first time working on a DHS Program survey was for the 2016 Ghana Malaria Indicator Survey (GMIS). I helped with fieldwork monitoring and report writing. After the 2016 GMIS, I participated in the 2017 Regional DHS/MIS Malaria Analysis Workshop. At this workshop, I worked with my team members from the Ghana National Malaria Control Program (NMCP) to write an abstract, “Factors Influencing Malaria Prevalence in Children Under 5,” using the 2016 GMIS data.

Samuel Oppong (left) with participants from Ghana at
the 2017 DHS/MIS Malaria Analysis Workshop. © ICF

I then transitioned from being a workshop participant to a workshop co-facilitator, facilitating the 2017 Regional Malaria Indicator Trends Workshop in Uganda. This workshop brought together NMCP monitoring and evaluation (M&E) program managers from Liberia, Malawi, Nigeria, Sierra Leone, and Uganda to examine trends in malaria indicators.

More recently, I co-facilitated the 2018 Ghana Malaria Trends Workshop. This workshop brought together district malaria health officers to analyze trends in household survey indicators in Ghana. This was a great workshop because I was able to work with the data I am most familiar with! The output from this workshop is published on The DHS Program website.

Samuel Oppong (left) and Annē Linn co-facilitated the 2018
Ghana Malaria Indicator Trends Workshop. © ICF

How has NMCP used DHS data for programmatic decision making?

After the release of the 2016 GMIS, NMCP noticed a low uptake of artemisinin-based combination therapy (ACTs) in the Northern region, but the use of SP/Fansidar was high, which is not a recommended treatment for malaria in children. This triggered us to do additional research to figure out what was going on in this region and investigate which outlets were distributing SP. We realized that people were not receiving SP from public health facilities but from private clinical shops and other drug peddlers. The 2016 GMIS results provided a snapshot of the malaria case management situation in the Northern region and provided us justification to explore further. To solve this problem, NMCP implemented a sensitization activity to ensure people in the region know the recommended treatment and sources to get the correct treatment.

Another example of evidence-based decision making was the implementation of a malaria sensitization campaign using data the 2016 GMIS. Malaria prevalence by microscopy in the Eastern region increased between the 2014 GDHS and 2016 GMIS. This was a worrying trend because in Ghana we normally only see high malaria prevalence in the Northern and Upper West regions. NMCP looked more critically at the 2016 GMIS results and saw that while insecticide-treated net (ITN) ownership was high, the proportion of people who recognized the cause and symptoms of malaria was very low. As a result, NMCP implemented a community level sensitization activity in four districts of the Eastern region.

How do you use MIS survey data during your daily job?

I recently collaborated on a research paper using DHS data. The paper, published in The Malaria Journal, used survey data from the 2014 GDHS and the 2016 GMIS to examine ITN use behavior by exploring how several household and environmental variables related to use among Ghanaians with access to an ITN. This further analysis paper has been extremely helpful for programmatic decision making here at NMCP.

What data are you looking forward to in the upcoming 2019 GMIS?

I am interested in further examining the information about the type of nets in households. NMCP finished a mass long-lasting insecticidal net (LLIN) distribution campaign in 2018 and implemented a school-based piperonyl butoxide (PBO) net distribution campaign in 2019. The 2019 GMIS results will provide information on the reach and use of these nets across Ghana as well as where people obtained their nets.

Analysis Brief AB2 (shown above) provides the methodology and key results for Further Analysis 110: Maternal Health Indicators in High-Priority Counties of Kenya: Levels and Inequities.


Written by: Samuel Oppong

Samuel Oppong is a Monitoring and Evaluation Specialist with the Ghana National Malaria Control Programme. He coordinators M&E activities in vector control interventions, routine data quality audits, and SMC. He is involved in capacity building of national, regional, district and health facility staff on capturing, reporting, and analyzing malaria-related data from routine health information systems as well as other malaria data sources. He also leads capacity building programs of national, regional, and district staff on conducting data quality audits as well as onsite training, supportive supervision (OTSS) on malaria data management.

06 Aug 2019

DHS Program Analysis Highlights: Summer 2019

Many students and faculty are out of school at this time of year, but The DHS Program’s analysis team is busy at work. In addition to finalizing their annual analytical papers, the team continues to support country-specific further analysis, train Fellows, write code to share with other researchers, and support data quality improvements.

Here are some of the highlights of 2019 so far:

  • The DHS Program hosted a showcase of the major findings from a dozen further analysis papers based on the 2015-16 Myanmar Demographic and Health Survey in Yangon in early July. More than 50 population and health professionals in Myanmar participated in DHS data analysis trainings, resulting in the publication of 9 papers now available on The DHS Program website. Several more will be published in the coming months.
  • Another class of DHS Fellows has graduated! This year, 6 teams from universities in Afghanistan, Indonesia, Myanmar, Ethiopia, Ghana, and Senegal have prepared working papers in areas covering child vaccination, nutrition, malaria, contraceptive discontinuation, men’s family planning, and HIV testing.
2019 DHS Fellows Program facilitators and participants. © ICF
  • A recent analysis workshop in Ghana linked research to action by integrating policy brief writing with statistical analysis of data from the 2017 Ghana Maternal Health Survey. Proposed policy recommendations address inequalities and advocate for programs that protect and promote the health of women. Policy briefs will be published soon on The DHS Program website.
Participants from the policy brief writing workshop in Ghana. © ICF

Coming Soon in 2019!

  • By geographically linking SPA and DHS data, two upcoming working papers explore the relationship between the antenatal care service environment and maternal health behaviors including iron-folic acid consumption and early breastfeeding. Working Papers 160 and 161 will be published in mid-August.
  • What are the determinants of child marriage in Asia? In Bangladesh and Nepal, marriage by age 15 is more common in clusters where women’s acceptance of wife-beating is more prevalent. Find out more in Analytical Studies 69.
  • Do regional disparities in fertility preferences and family planning satisfied by modern methods persist when controlling for poverty? Analytical Report 7 will explore this question for 12 DHS Program countries and 3 groups of absolute poverty measurements.
  • The DHS Program explores strategies to identify potential data quality issues after data collection in Methodological Report 26.
  • For the first time, summary briefs will be available for almost all analytical studies and comparative reports published this year. Briefs will feature figures and maps and easily digestible bullets of key findings for a variety of audiences.

Analysis Brief AB2 (shown above) provides the methodology and key results for Further Analysis 110: Maternal Health Indicators in High-Priority Counties of Kenya: Levels and Inequities.

10 Jul 2019

Luminare: Programming Code for DHS Indicators

DHS Staff Programming

This blog post is part of Luminare, our blog series exploring innovative solutions to data collection, quality assurance, biomarker measurement, data use, and further analysis.


Have you ever wondered how to write a Stata program for vaccination coverage or struggled to construct mortality rates using DHS data? Well, DHS Program staff are busy writing SPSS and Stata code for all indicators listed in the Guide to DHS Statistics, and you can use this code to jump-start your exploration of the data. And as they are completed, the code will be posted on GitHub for open access to the public. 

The DHS Program GitHub site contains two repositories: DHS-Indicators-Stata and DHS-Indicators-SPSS. Users can download the code from these repositories or clone the repository to their own Github site. Users can also suggest changes to the code that will be reviewed by DHS Program staff before acceptance. 

Don’t see what you need? The programming for all indicators listed in the Guide to DHS Statistics will be available by September 2020. The Guide corresponds to the topics/chapters that are typically found in a DHS survey final report in addition to the modules for malaria and HIV prevalence. As of July 2019, about half of the indicators have been coded and shared in Stata including indicators covering child health, family planning, and reproductive health. SPSS code will follow later in 2019 and 2020, along with the remainder of the indicators. Review the Readme text file for more details.

Questions? Email codeshare@DHSprogram.com 

Analysis Brief AB2 (shown above) provides the methodology and key results for Further Analysis 110: Maternal Health Indicators in High-Priority Counties of Kenya: Levels and Inequities.

25 Jun 2019

DHS Data Users: More than 2,000 Users Accessing DHS Data through IPUMS-DHS

Students presenting posters using IPUMS-DHS data at the first-ever Student Poster Extravaganza

© 2019 Students presenting posters using IPUMS-DHS data at the first-ever Student Poster Extravaganza at the Institute for Social Research and Data Innovation.

If you are interested in being featured in the ‘DHS Data Users’ blog series, let us know here by submitting your example of DHS Program data use. 


Over the past four years, the IPUMS-DHS program has grown substantially, in both the magnitude of available data and in use. As of June 2019, more than 2,000 users have accessed the IPUMS-DHS database, and multiple papers have been published using DHS data through IPUMS-DHS.

One of the advantages of accessing DHS data through IPUMS-DHS is that variables are harmonized across surveys, facilitating comparative research. Recent research using IPUMS-DHS data highlight innovative methods and fascinating results:

This year, IPUMS announced its first-ever IPUMS-DHS Award, an honor given to outstanding use of IPUMS-DHS data. The winning paper, Neonatal mortality in East Africa and West Africa: a geographic analysis of district-level demographic and health survey data (Grady et al., Geospatial Health 2017 volume 12:501) identifies high-risk districts and counties for neonatal mortality. This analysis aims to help prioritize intervention sites for countries as they strive to reach the Sustainable Development Goals.

IPUMS-DHS is also being used to train the next generation of analysts and data users. The Quantitative Global Health Analysis course taught at the University of Minnesota this spring relied on IPUMS-DHS as a primary data source for its students. Final products were research posters using the data. Research questions explored by students analyzing IPUMS-DHS data included:

  • How Violence against Women Affects Fertility and Family Planning in Uganda
  • Changes in and Predictors of Antenatal Care for Women in Mali
  • Effects of Family Size and Food Insecurity on Child Mortality in Ethiopia
  • Understanding Variation in Vaccination Status in Ethiopia
  • Vitamin A Vaccination and Deficiency in Uganda
  • Perceptions of HIV/AIDS in India in the Context of Education

IPUMS-DHS Data Update: As of June 2019, the IPUMS-DHS database includes 156 samples from 38 countries and nearly 15,000 consistently coded variables, including all standard DHS variables from DHS Phases 1 through 7 and many country-specific variables. Learn more on our website and read our previous blogs on the IPUMS-DHS collaboration here.

30 May 2019

Luminare: Customize Fertility and Childhood Mortality Rates with DHS.rates

This blog post is part of Luminare, our new blog series exploring innovative solutions to data collection, quality assurance, biomarker measurement, data use, and further analysis. This is the second post in the series that focuses on innovations using DHS.rates data. 


Ever struggled to calculate fertility or child mortality indicators from survey data? Want to customize the reference period?
DHS.rates can do it for you!

What is DHS.rates?

The DHS.rates is a user-friendly R package to calculate fertility and childhood mortality rates based on DHS datasets. First released in March 2018, the current version of DHS.rates calculates the Total Fertility Rate, General Fertility Rate, Age-Specific Fertility Rates, Neonatal Mortality Rate, Post-Neonatal Mortality Rate, Infant Mortality Rate, Child Mortality Rate, Under-5 Mortality Rate and mortality probabilities. For each indicator, the package calculates standard error, design effect, relative standard error, and confidence intervals. Data users can customize rates:

  • Using reference periods other than DHS standard reference periods
  • Based on calendar years so the end of the reference period is not the date of the survey
  • Using different sub-populations or domains other than those produced by The DHS Program
  • Based on other surveys other than DHS if the required variables are available

This innovation was recently featured in PLOS One: Calculating fertility and childhood mortality rates from survey data using the DHS.rates R package

Download the DHS.rates package today!

Not an R user? Try the web-application, DHS.rates Shiny

This web-application provides all the DHS.rates functions without needing to download or use R. The DHS.rates Shiny web application includes two main tabs, fert and chmort. After uploading the relevant survey dataset, the application calculates fertility or childhood mortality rates according to the DHS methodology.

Just as with the R package, Shiny web application users can customize the reference period as well as the end date of the reference period. By adding a variable to “Class of the rate”, users can do the calculations for different subpopulations other than the ones produced by The DHS Program. Users also can change any of the fields on the screen allowing them to use the application with other surveys other than the DHS.

The information provided on this Web site is not official U.S. Government information and does not represent the views or positions of the U.S. Agency for International Development or the U.S. Government.

The DHS Program, ICF
530 Gaither Road, Suite 500, Rockville, MD 20850
Tel: +1 (301) 407-6500 • Fax: +1 (301) 407-6501
dhsprogram.com