Category Archives: Data

07 Aug 2018

World Breastfeeding Week 2018

World Breastfeeding Week, held annually from August 1-7, is a week where over 180 countries come together to promote and support breastfeeding. And although World Breastfeeding Week 2018 has come to a close, you can still take part in advocating for breastfeeding and its role in achieving the Sustainable Development Goals with DHS data:

  • Use STATcompiler to discover and share the prevalence of exclusive breastfeeding for children under 6 months.
  • Use STATcompiler to discover what percent of children age 6-9 months are breastfeeding and consuming complementary foods.
  • Share and retweet the new World Breastfeeding Week 2018 infographic using DHS data from 5 recently released Demographic and Health Surveys (DHS).

The DHS Program has collected breastfeeding data for over 30 years and has more than 50 breastfeeding indicators available in 80+ countries on STATcompiler. Continue to share DHS data on breastfeeding and stay connected for updates and resources!

Photo Credit: © 2012 Javier Arcenillas, Courtesy of Photoshare

18 Jul 2018

Release of the 4th India National Family Health Survey

We are pleased to announce the release of the 2015-16 India National Family Health Survey (NFHS-4) Final Report and State Reports. This nationally-representative survey was conducted in over 600,000 households and interviewed both women and men to collect information on population, health, and nutrition indicators. NFHS-4, for the first time, also includes measurements of blood pressure and random blood glucose, and provides district-level estimates for all 640 districts, in addition to national and state-level estimates for most important indicators.

Download the 2015-16 NFHS-4 Final Report

State Reports for all 29 states have been released and are now available for download. The complete list of State Reports is shown below.

2015-16 NFHS-4 State Reports

Andhra Pradesh Jharkhand Punjab
Arunachal Pradesh Karnataka Rajasthan
Assam Kerala Sikkim
Bihar Madhya Pradesh Tamil Nadu
Chhattisgarh Maharashtra Telangana
Goa Manipur Tripura
Gujarat Meghalaya Uttar Pradesh
Haryana Mizoram Uttarakhand
Himachal Pradesh Nagaland West Bengal
Jammu & Kashmir Odisha  

ⓒ 2015 Arvind Jodha, UNFPA, Courtesy of Photoshare

11 Jun 2018

New e-Learning Course: Measuring Malaria through Household Surveys

The National Malaria Control Program (NMCP) in the Democratic Republic of Congo (DRC) recently reoriented their communication strategy around insecticide-treated nets or ITNs, moving from a focus on behavior change around ITN use to a focus on net care and repair to extend the life of existing ITNs. Why the change?

The 2013-14 DRC Demographic and Health Survey (DHS) showed that only 50% of the household population had slept under an ITN the night before the survey, an indicator they wanted to improve. But when they dove deeper into ITN use, interpreting it in the context of ITN access, a different picture emerged. The survey also found that 47% of the population had access to an ITN. Interpreting these two indicators together, the NMCP redefined their strategy with the understanding that people were using the ITNs they had, and since use was higher than access, more than two people were using each net. In this context, the behavior change messages needed to be targeted toward helping people extend the life of their ITNs.

This kind of data use is only successful when decision makers understand the indicators that are informing their policies and programs. Our new course on K4Health’s Global Health eLearning (GHeL) Center, Measuring Malaria through Household Surveys, dives into the major malaria indicators, guiding learners through the process of collecting and calculating these indicators and through considerations for their interpretation.

Click here to take the course

The DHS Program has continuously sought to develop tools and curricula to strengthen the capacity of stakeholders to use survey data. From the survey report and dataset to STATcompiler and the mobile app, from tutorial videos to the user forum, and from one-day Data to Action workshops to advanced data analysis workshops, we are always innovating to meet users’ needs.

Last year, The DHS Program developed a Malaria Indicator Trends workshop curriculum to increase the capacity of data users from National Malaria Control Programs to utilize DHS/MIS data to answer key programmatic questions and to accurately interpret trends in malaria indicators. The workshop targets users who needed more information that could be provided in a one-day dissemination workshop but does not have the skills (or need) to analyze with STATA. It was immediately clear that this workshop, which dives into each of the recommended indicators, their calculation, their limitations, and considerations for their interpretation, was meeting a need for data users. The next step to increase the well-informed use of these important indicators was to expand the reach of this curriculum through an online course on the Global Health eLearning Center platform.

This free course targets professionals (both generalist staff working on malaria as well as those with programmatic expertise in malaria) from donor agencies, ministries of health, and implementing and collaborating agencies. It takes 2-3 hours to complete and can be taken as a part of the Monitoring & Evaluation or Infectious Diseases certificates offered through the GHeL center.

When the indicators from household surveys are better understood, better programmatic decisions will be made.

Click here to take the course

© 2016 Sarah Hoibak/VectorWorks, Courtesy of Photoshare

05 Jun 2018

Confused about Maternal & Pregnancy-Related Mortality? Our New Video Series Explains All

Did you know The DHS Program has made changes to the collection, calculation, and terminology used for maternal and pregnancy-related mortality data? Our new three-part video series based on our blog post addressing changes to the DHS-7 questionnaire breaks down everything you need to know.

The first video in the series, the Maternal Mortality Ratio (MMR) Indicator Snapshot, is our newest Indicator Snapshot. Based on the recently revised MMR definition, this video covers important things to know, why maternal mortality matters, calculation, where to find it in DHS reports, and how to use MMR in a sentence.

The second video details the differences between The DHS Program’s definitions of maternal and pregnancy-related mortality, as well as how our definitions compare to WHO’s definitions.

The DHS Program estimates of pregnancy-related mortality ratios (PRMR) have limitations which can make interpretation difficult. The final video in the series discusses how to interpret trends in PRMR, as well as other DHS survey indicators which may be more useful to program managers and policymakers.

You can find these videos and other resources on the Maternal Mortality page of our website. Did you find these video helpful? Need more guidance? Let us know in the comment section below!

Photo credit: © UNICEF Burundi/Colfs

28 Feb 2018

DHS Data in the News

Journalists worldwide use DHS, MIS, and SPA surveys as source data for essential stories – stories about domestic violence, HIV prevention, and child survival. Coverage of these topics brings awareness to these critical issues and often prompts policy change.

In any given month, DHS Program data are cited in hundreds of print, television, radio, and digital media across the world. While we can’t possibly review and share every example of accurate DHS data coverage in the news, we do highlight some of the best examples in The DHS Program’s News Room. The results from India’s 2015-16 National Family Health Survey have been featured in India’s biggest newspapers, and topics range from anemia prevalence to child marriage. A recent article from the Midrand Report in South Africa cites condom use data from the 2016 South Africa Demographic and Health Survey as an argument for voluntary male circumcision, and a Ghana News Agency article highlights adolescents’ needs for reproductive health services.

Using data from a reputable source like a DHS survey adds credibility and context to journalistic reporting. But covering topics such as mortality, fertility, and disease prevalence is not simple, and journalists often struggle to interpret DHS survey results and write about demographic and health data in language that is accessible for their audiences. Following a survey’s national release, The DHS Program’s dissemination team facilitates a workshop to educate journalists on reading and understanding DHS tables, accessing comparable data, and using data in reporting. Learn more about these media trainings in this reflections piece on a Journalist Workshop in Togo.

The DHS Program also has user-friendly tools, such as STATcompiler and the mobile app that allow journalists to verify the accuracy of DHS data used in their reporting. In addition to featuring news that accurately cites DHS data, we have a Journalists’ Guide to the Demographic and Health Surveys, available in both English and French. This guide provides tips on how journalists can properly use DHS data in their stories.

Connect with us on Facebook, Twitter, LinkedIn, or email press@dhsprogram.com to share your accurate news story with DHS data for a chance to be featured in The DHS Program’s News Room.

Photo credits: 1) Officials from the Ethiopia Ministry of Health and Central Statistics Agency answer questions at the 2016 Ethiopia DHS National Seminar press conference; 2) Dr. Thet Thet Mu of the Myanmar Ministry of Health and Sports responds to questions from the press at the launch of the 2015-16 Myanmar DHS. © 2017 ICF

22 Feb 2018

A New Way to Interact with your Favorite Indicators

We are pleased to showcase a new mini-tool on our website that allows you to quickly interact with indicators for topics such as family planning, gender, malaria, and nutrition. We have preselected 10-15 key indicators per topic that you can view by country or globally.

Simply navigate to your favorite topic to see a trend visualization from the most recently released survey. Then, select either a country or indicator within the drop-down menus to instantly see results. To start over, click “Reset” to return to the featured trend graphic.

Indicators are pulled from The DHS Program Application Programming Interface (API). As you click on a country or indicator within the data table, hyperlinks direct you to STATcompiler. There, you can compare even more indicators over time and geographically.

With the 1,000s of demographic and health indicators available, grouping key indicators by topic allows you to quickly interact with DHS data. Visit The DHS Program Topics page for a list of the featured topic pages containing the mini-tool.

What other topics do you want to see? Let us know what you think in the comments section below! Don’t forget to subscribe to The DHS Program newsletter for more updates on our digital tools, surveys, and more.

Photo Credit: © 2001 Marcel Reyners, Courtesy of Photoshare

31 Jan 2018

IPUMS-DHS Unlocks Research Possibilities with New Contextual Data

Have you ever wondered if high-levels of precipitation affect birthweights and infant and child survival? Is increased use of insecticide-treated bed nets associated with lower incidence of malaria? Do children in households near battle zones or other violent contexts have higher levels of child malnutrition? Do some staple crop regimes promote better health outcomes than others?

Now with IPUMS-DHS, you can easily study these questions and others on how environmental and social contexts affect human health and behavior.

Using GPS coordinates, we’ve linked contextual variables drawn from many data sources directly to individual DHS survey respondent records. All context variables describe the features of a small geographic area (5-10 kilometers) surrounding each DHS survey cluster location.

New variables include:

Environmental
Variables
Agricultural
Variables
Social
Variables
  • Soil type
  • Ecoregion
  • Level of vegetation
  • Precipitation
  • Proportion of land area used for agriculture or pastureland
  • Total harvested area and yield for 17 major crops
  • Dominant livelihood
  • Population density
  • Counts of violent episodes
  • Incidence of malaria

Keep checking back! Over the next year, IPUMS-DHS will still be adding more contextual variables, including summary statistics calculated from large census-based samples.

Plan a new research project linking individual characteristics and outcomes with the surrounding context, and let us know about it. We’re always eager to hear how people are using IPUMS-DHS!

________________________________

IPUMS-DHS is a system that makes it easy to find and review the thousands of DHS survey variables and to download a single fully-harmonized data file with precisely the variables and samples that interest you. The system currently includes variables from all DHS survey samples taken in India and 22 African countries; more samples are constantly being added.

For DHS survey samples with GPS cluster data that are not yet in IPUMS-DHS, the contextual variables are available in linkable CSV files.

To learn more about the IPUMS-DHS contextual variables, check out our Technical Note, Using IPUMS-DHS Contextual Variables, which provides much more detail.

24 Aug 2017

How Things Have Changed! Looking Back at Data Distribution Practices from 20 Years Ago

A lot can change in 20 years. For The DHS Program, it’s the difference between over 250 datasets for 70 separate surveys to more than 10,000 datasets from over 300 surveys. The contents of the model survey questionnaires changed radically, as did the media used for data distribution. And two decades ago, the internet had only recently emerged as a potential means of communication around the world!

It might be hard to imagine life without internet access today – for us, we rely on the internet for many of our activities. In 1995, The DHS Program established a website which had the basics: an informational brochure, survey statuses, fact sheets, press releases, and newsletters.

Though the website has been updated several times since then, it still has these basic features. The crucial difference lies in how we only provided an archive of publications and data and information on how to place an order for them. Yes, users had to pay for the cost of media – which, at the time, included diskettes (AKA a floppy disk), Bernoulli cartridges, and CD-ROMS – and shipping. At one point, we were deciding on whether to charge for the data itself, to ensure the fullest use of the data.

That decision was part of a proposal from 20 years ago, which proposed the following data dissemination over the internet:

  1. DHS data
  2. India NFHS data
  3. Report text
  4. Online newsletter (tentatively named ‘DHS Discoveries’)
  5. User forum

These look familiar, don’t they? Today, both reports and datasets are free and available over the internet for download (though we still require users to apply for access to datasets), we email our newsletter to subscribers (which includes news, new publications and datasets, and articles that have cited DHS data), and the User Forum has been live since February 2013.

The DHS Program has utilized the internet beyond what was proposed 20 years ago; to name only a few ways, the creations of STATcompiler, development of eLearning courses for data visualization and social media for global health, and utilization of social media to engage with our users. And if you want to know what is coming next, be sure to Follow or Like us on social media, subscribe to our newsletter or even this very blog you are just a few clicks away!

This blog post is based on the rediscovery of the paper prepared for the Population Association of America (PAA) meeting back in 1996. Go back in time and read the original paper here!

11 Jul 2017

World Population Day 2017

How well do you know your population pyramids? Celebrate World Population Day with The DHS Program’s Guess the Population Pyramid Quiz!

See how you stack up against others and share your results below in the comment section, on Facebook, or Twitter! We are also having a live version of Guess the #PopPyramid on Twitter July 11 at 10AM EST.

Take the full-screen version of the quiz here.

Good luck!

14 Jun 2017

An Age of Change: A More Precise Way to Measure Children’s Age in DHS Surveys

DHS-7 surveys are using a more precise method to calculate children’s age. The change, though far-reaching, has very little impact on interpretation and use of DHS data for program managers and policymakers. It does, however, have major implications for researchers doing secondary analysis of DHS data. If you are working with DHS datasets, a full description of the changes to the age-related variables is documented on The DHS Program website, and a brief summary is presented below.

Background:

For most of DHS history, interviewers have collected age data by asking the month and year of birth of the respondent, her age in years, month and year of marriage or age at marriage, and month and year of birth of each of her children as well as the age of living children. For children under 5 who are weighed and measured to assess nutritional status, day of birth was collected in the household questionnaire but was not connected with the birth history. Beginning with the DHS-7 questionnaires (most surveys with fieldwork in 2015/2016 and beyond), we asked the day of birth for all children listed in the birth history.

Why was day of birth added for children in DHS-7?

Adding day of birth permits calculating the age of children more accurately. Calculating age in months using just month and year of birth and month and year of interview meant that age in months could be off by one month in approximately half of all cases. For example, a child born February 2017 was considered a 3-month-old in May 2017. However, if the birth took place on February 25, 2017, and the interview was May 3, 2017, then the child is actually only two completed months old. Thus, if the day of birth is greater than the day of interview (roughly half of all cases), then the age would be over-estimated by one month.

Why make the change now?

Historically DHS surveys have not collected the day of birth of all children as the quality of reporting of dates of births and ages was simply not reliable enough, especially for older children or those who have died. The quality of date and age reporting for children has improved over time and now appears to be sufficiently reliable for use throughout the survey data.

How is the age calculation different in DHS-7?

Previously, child’s age was calculated by subtracting the month and year of birth from the month and year of interview to give age in months. In DHS-7, we introduced the calculation of age taking into account the day of birth and the day of interview. To do this, we introduced a new concept – the century day code (CDC).  DHS datasets now contain several new variables related to the century day codes.

For more details on the definition of the CDC and a list of the new variables, a complete description of changes made to existing age variables (e.g. age of child in years, age of child in months, and birth intervals), and programming notes for STATA and SPSS users, visit The DHS Program website.

How do these changes affect analysis?

In surveys that introduced the day of birth of the child, changes have been made in the analysis of the data in two main ways:

  1. The restrictions on the denominator for tables now all use the age variables based on the calculation to the day, rather than to the month as was previously done.
  2. All background age group variables used in analysis are now based on the revised ages. Previously, on average, because the calculation method only considered month and year and not day of birth, the age group of 0 months would have roughly half the number of cases of age group 1 month or other older single month age groups. With the new method, age group 0 months will have a roughly similar number of cases as other single month age groups.

These changes affect virtually all tables related to children, particularly to children under 5.

It is important to note that fertility rate and childhood mortality rate tables are not impacted as these tables exclude the month of interview from calculations and effectively use complete months in the calculations.

More precise calculation results in a shift in age

The diagrams below show the age of the child calculated using the old and new methods, given a particular month of interview and month of birth, giving examples here for interviews in January to June 2017, and births in December 2015 to June 2017. For any birth taking place on a day in the month on or before the day of interview there is no change in the calculation, but for any birth taking place on a day in the month after the day of interview the age of the child is now calculated as 1 month less than previously. For example, a child born in late April 2017 and included in an interview in early June 2017 (equivalent to a point in the bottom right corner of box “2” in the first row below, marked with a red star) was calculated as 2 months using the old method, but looking at the equivalent position in the second example, this child is calculated as age 1 month in the new calculation method.

Old age calculation method example:

New age calculation method example:

This shift in age in months affects roughly half of all children, but only has an effect on age in years for roughly 1/24 of children – those previously classified as 12 months old, but now classified as 11 months old, and similarly around ages 24 months, 36 months, etc.

While these changes will unlikely have a major impact on the interpretation of trends, they do mark a significant shift towards a more precise, accurate measure of children’s age.  Dataset users striving to replicate DHS tabulations need to adjust their logic to match DHS results using some of the new or modified variables to capture the more accurate measure of child age.

Download the full PDF here.

Questions?  After reviewing the full guidance document, please visit the DHS User Forum and post additional questions there for discussion.

© 2012 Xinshu She/Boston Children’s Hospital Global Pediatrics Fellow, Courtesy of Photoshare

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.

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