14 Jun

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

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

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.

01 Jun

New Data Available from DHS-7 Questionnaire: Literacy, Ownership of Goods, Internet Use, Finances, and Tobacco Use

This is Part 3 in the DHS-7 questionnaire blog series that explores the new data that are available in DHS reports resulting from changes made to the DHS questionnaires in 2014. This week’s post focuses on changes made to gather additional information about DHS respondents.

Part 3:  Respondents’ Characteristics

Understanding DHS survey respondents is critical to interpreting DHS data. In addition to fertility and health data, the DHS captures information on education and literacy; exposure to mass media; ownership of goods, homes, and land; employment; and use of tobacco. Some of these topics are tabulated in Chapter 3 on Respondent Characteristics, while others are discussed in the chapter on Women’s Empowerment. Changes to these topics are outlined below.

More precise collection of literacy data. In previous DHS surveys, women and men who had attended at least some secondary education were assumed to be literate and only those with primary education and below were asked to read a card in their local language to test for literacy. In DHS-7, only those who have gone to “higher than secondary school” are assumed to be literate; all others, including those who have attended or completed secondary school, are asked to read the literacy card (pictured right).

Why?  This change was made to improve the precision of literacy measures. Not all people who have attended some secondary school are literate. In some cases, this confirmation of literacy may also point to a misclassification of educational levels of respondents.

Implications: In some countries, this change may affect the interpretation of trends, as a more inclusive group of respondents is actually being tested for literacy in DHS-7 surveys. Recently released surveys do not suggest a major impact, however. In the 2015-16 Malawi DHS, for example, 72% of women were found to be literate (when women with primary, secondary, or secondary completed were asked to read the card). This includes about 40 female respondents (out of over 24,000) with some secondary education who previously would have been assumed to be literate but were identified in the 2015-16 survey as illiterate because they could not read the card. This more precise measure adjusts the national literacy rate in Malawi by only 0.15%; both methodologies result in a 72% literacy rate at the national level.

Additional questions on mobile phone ownership. Previous DHS surveys collected data on mobile phone ownership at the household level. In DHS-7, women and men are asked about mobile phone ownership individually. These data are presented in the Women’s Empowerment chapter.

Why? Having one mobile phone per household is not very informative when programs are designing mobile interventions to reach pregnant women or facilitate receiving HIV results.

New finance-related questions. In DHS-7, women and men are now asked whether or not they have used their mobile phone for financial transactions, and whether or not they have an account in a bank or other financial institute. These data are tabulated in the Women’s Empowerment chapter.

New question on internet usage. Respondents to woman’s and man’s questionnaires are now asked if they have ever used the internet. Those who answer yes are asked if they’ve used the internet in the past 12 months. For those who have used the internet in the year before the survey, they are also asked, “during the last month, how often did you use the internet?”New question on ownership of title or deed for house or land. Previously, women and men were asked if they owned a house or land alone or jointly. Now they are asked two follow-up questions if they say yes to the ownership questions:  whether or not they have a title deed, and whether or not their name is on the title deed. These data are tabulated in the Women’s Empowerment chapter. Because these questions may be considered sensitive not all countries will elect to include them in their surveys.

New and more detailed questions on tobacco use. In DHS-7, women and men are asked more detailed questions about tobacco use to capture how often the respondent smokes or uses other tobacco products. Men are also asked whether they have previously been a daily smoker, how many of different types of tobacco products are used per day and per week, and whether or not the man uses smokeless tobacco.

To learn more, read the full blog series or download the DHS-7 model questionnaire.

15 May

Everything You Need to Know about DHS Data and More

So, you’re new to DHS and you’ve registered as a DHS data user, downloaded the free available datasets, but now what? We have the perfect resources to get you started.

The following videos provide an overview of DHS data answering key questions such as, what is a data file or dataset? What is the difference between De Jure and De Facto? What types of data files are available for download?

Starting with the Introduction to DHS Datasets, this video provides a guide to units of analysis, basic terminology, and DHS data files.

As mentioned in the video above, separate data files are created for different units of analysis. DHS Dataset Types in 60 Seconds runs through the most common data files and what they contain.

De Jure and De Facto are terms that you will see often within DHS reports and datasets. The following video breaks down what the terms mean, and how they apply to analyzing DHS data.

And finally, where is the information about interviewed households and individuals located in different data files? The Introduction to DHS Data Structure examines DHS datasets in a hierarchical structure.

We will have more videos released this summer, but for those who are still eager to learn more about DHS data, check out DHS Dataset Names Explained below.

 

05 May

New data available from DHS-7 Questionnaire: WASH Indicators

DHS Survey manager Joanna Lowell washes her hands in Zimbabwe during fieldwork in 2010.

This is Part 2 in the New Data Available from DHS-7 Questionnaire blog series that explores the new data that are available in DHS reports resulting from changes made to the DHS-7 questionnaire in 2014. This post focuses on changes made to improve the quality and quantity of data collected about water and sanitation.

Part 2:  Water and Sanitation

There has been increasing demand from the water, sanitation, and hygiene (WASH) community to gather more detailed information to measure the Sustainable Development Goal of access to water and sanitation for all. The major DHS-7 questionnaire enhancements in this area are outlined below.

Bottled water is now defined as an improved or unimproved source of drinking water depending on the source of water for cooking and handwashing. In the previous DHS-6 questionnaire, if a household indicated that the main source of drinking water for household members was bottled water, this was categorized as an improved source of drinking water. In the DHS-7 questionnaire (as in DHS-5), a household that uses bottled water for drinking is asked a follow-up question about the source of water used for cooking and handwashing (see questionnaire). For example, a household that uses bottled water for drinking but surface water (an unimproved source) for cooking and handwashing is considered to have an unimproved source. A household that uses bottled water for drinking and piped water (an improved source) for cooking and handwashing is considered to have an improved source. Both categories are listed in Table 2.1 (see figure).

Why? This change was made to align DHS data with recommendations from the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation (JMP) which monitors progress towards Sustainable Development Goal 6: Ensure access to water and sanitation for all. It is important to note that while surveys like the DHS can assess the main source of household water, the source of water is only a proxy measure for quality. Sometimes water from an improved source is not safe to drink.

Implications: For most countries, this change will simply add insight into how households use water sources for different purposes. In countries where there is heavy reliance on bottled drinking water, reclassification of some of the bottled water users as having an unimproved water source may affect interpretation of trends in the larger “improved source” and “unimproved source” categories between surveys that include information about the source of water for cooking and handwashing and those that do not.

New category of improved source of drinking water added. Respondents to the household questionnaire can now indicate that their drinking water source is water piped to a neighbor.

Why? This response category was added because it is a common source of drinking water in some countries.

New question and table on availability of water. For households using piped water or water from a borehole or tubewell, a new question has been added asking if water was available without an interruption of at least one day in the past 2 weeks (see Table 2. 2).

Why? Scheduled or unscheduled interruptions in the water supply may force households to use unimproved sources.  All persons should have sustainable access to adequate quantities of affordable and safe water. The new question helps determine whether or not households have a sustainable supply of water.

Implications: Water availability from some improved sources, such as piped water or tubewells, is not always consistent. Intermittent and unreliable water services result in inconvenience to water users and increased risk of compromised water safety.

Sanitation and toilet facilities language clarified. The collection of data about toilet facilities has changed only marginally, however the language used to describe the different types of unimproved sanitation has been clarified. In DHS-7 reports, sanitation is divided into the categories seen in Table 2.3 from the 2015-16 Malawi DHS. Improved sanitation includes flush/pour systems, VIP latrines, and composting toilets, among others. Unimproved sanitation now includes three subcategories: a shared facility (this may still be a flush system, but by definition a shared facility is not improved); an unimproved facility, such as a pit latrine without a slab, an open pit latrine or a bucket; and open defecation, that is, the household has no facility and uses the field or bush.

Why? Improved sanitation facilities are meant to separate human excreta from human contact. If an otherwise improved sanitation facility is shared with other households, the likelihood of exposure to fecal materials is increased.

Implications: In this case, the labeling of these categories is all that has changed. The DHS STATcompiler has been updated with new labels to reflect these categories. Interpretation of data for trend analysis is not affected.

New question added on location of toilet facilities. The DHS-7 questionnaire now also asks where the toilet facility is located. Table 2.3 categorizes these locations as “in own dwelling,” “in own yard/plot,” and “elsewhere.”

Why? If the sanitation facility used by the household is not in the dwelling or yard/plot, it is more difficult to access when needed, and it may pose a safety issue, especially for women and children.

Implications of this addition are not yet known; analysis of future survey data may provide insight.

DHS Survey manager Joanna Lowell washes her hands in Zimbabwe during fieldwork in 2010.

DHS Survey manager Joanna Lowell washes her hands in Zimbabwe during fieldwork in 2010.

Mobile sites for handwashing now captured. In previous surveys, interviewers asked household respondents to show them where members of the household usually wash their hands. The DHS-7 questionnaire allows for interviewers to indicate whether this handwashing site was fixed (such as a sink) or mobile (such as a pitcher or basin) (see Table 2.7 from the 2015-16 Malawi DHS).

Why? Many households without piped water do not have a fixed place for handwashing. In some countries (particularly in Africa), many households rely on mobile items for handwashing. When hands need to be washed, the individual may move a jug, basin, and soap from inside the home to the outdoor courtyard in order to wash hands. The ability to determine whether handwashing relies on a fixed or mobile place helps to interpret the handwashing data and to understand the physical and social norm-related barriers to handwashing with soap.

Implications: Early review of data from DHS-7 countries suggest that adding the mobile site for handwashing increases the percentage of households that will report that they have a handwashing site. Trends in this area should be interpreted with caution, as an increase in reported handwashing sites may be a function of the questionnaire change rather than a true change in handwashing practices.

24 Apr

The DHS Program at the 2017 PAA Annual Meeting

The DHS Program research team at the 2016 PAA Annual Meeting

We are pleased to announce that The DHS Program and staff will be attending this year’s Population Association of America (PAA) Annual Meeting in Chicago from April 27-29.

PAA is a nonprofit, scientific, professional organization established to promote the improvement, advancement, and progress of the human race through research of problems related to human population.

The DHS Program has been participating in the PAA Annual Meeting over the last few years and we are excited to share our recent surveys and other publications.

If you plan to attend PAA, visit booth #200 for your copy of free survey publications and tours of our new web and mobile tools. Several DHS staff will also be presenting posters, sessions, and will be available to answer any questions you may have about DHS data and results.

View the full DHS staff participation schedule here.

We are looking forward to seeing you there!

11 Apr

New Data Available from DHS-7 Questionnaire: Maternal and Pregnancy-Related Mortality

Baby Kabuche, 30 yrs old, 4 months pregnant, outside her house. Baby has 2 children: Eric, 12, living with granparents in Musoma and Judith, 6, living with her and her husband. She works in a factory manufacturing alluminium pots and iron rods. But as she becqme pregnant she took some unpaid leave as the factory uses acid and other toxic materials and she cares for the safety and health of her baby. Baby got malaria only once as she sleeps under mosquito net all the time. This new one makes her happy as it is treated with mosquito repellent and it is more effective.

© 2016 Riccardo Gangale/VectorWorks, Courtesy of Photoshare

In 2014, The DHS Program began the process of updating the standard DHS questionnaires. With input from stakeholders, feedback from in-country implementing agencies, and a host of lessons learned from the previous 5-year program, we added, modified, and, in some cases, deleted questions. For many indicators, the actual questionnaire did not require an adjustment, but the calculation of indicators or the tabulation of the data needed an update to reflect new international indicators and best practices.

While questionnaire revision started in 2014, it can take a long time to see this exercise bear fruit. The 2015-16 Malawi DHS, for example, went into the field with the DHS-7 updated questionnaires in October 2015. The final report and dataset for the 2015-16 Malawi DHS were released in March 2017, allowing us to explore the new data for the first time.

In this blog series, New Data Available from DHS-7 Questionnaire, we will be detailing, topic by topic, some of the key changes to the questionnaire, with a focus on why the changes were made, how the changes affect the tabulations, and some guidance on how the resulting data should be interpreted.

Part 1:  Maternal and Pregnancy-Related Mortality

DHS surveys now collect data to provide the maternal mortality ratio in line with the definition provided by WHO. For almost 30 years, The DHS Program has collected data on maternal mortality in a subset of countries. In previous DHS cycles, maternal mortality was defined as any death to a woman while pregnant, during childbirth, or within two months of delivery. The WHO definition of maternal mortality is more precise:  any death to a woman during pregnancy, childbirth, or within 42 days of delivery but not from accidental or incidental causes (see full WHO definition here). The new DHS-7 questionnaire allows us to calculate the maternal mortality ratio (MMR) in closer alignment with this more precise WHO definition.

As always, women interviewed in the DHS are asked to list their siblings. The interviewer then collects information about the siblings’ survival status. In the case of female siblings who have died at age 12 or older, the interviewer inquires whether or not the sister died during pregnancy, childbirth, or within the 2 months following delivery. If the sister died within 2 months after childbirth, the interviewer asks how many days after childbirth the sister died. This clarification on the number of days is a new addition to the DHS-7 questionnaire. The interviewer then asks additional questions to determine if the death was accidental or due to violence. In DHS-7 these deaths are excluded from the calculation of the MMR per the WHO definition.

Why?  These changes were made to improve the precision of the MMR, as well as to align the DHS estimation of the MMR with the standard definition provided by the WHO.

Implications:  While the newly added questions allow for a more precise and up-to-date measure of maternal mortality, the change does present challenges for interpretation. DHS has reported on maternal mortality for 30 years, but estimates obtained using the new definition of maternal mortality cannot be directly compared to the old definition of maternal mortality which included deaths up to 2 months after delivery and did not exclude deaths due to accidents and violence.

And yet, one of the main objectives for conducting DHS surveys is to provide trend data. Fortunately, the old definition of maternal mortality can still be applied to calculate the mortality ratio estimate comparable to estimates from previously collected mortality data. This less precise measure of mortality is referred to as the pregnancy-related mortality ratio (PRMR).

DHS reports that include the maternal mortality module will now contain both the maternal mortality ratio and the pregnancy-related mortality ratio. The maternal mortality ratio will be used as the primary point estimate, but the pregnancy-related mortality ratio will be shown in an additional table and in figures to illustrate the trend. Keep in mind that the new measure of maternal mortality, by definition, will result in a lower maternal mortality ratio than the old measure because the accidental and violence-related deaths to women during the maternal period and deaths occurring between 42 days and 2 months after childbirth are being excluded from maternal deaths while using the new definition but included while using the old definition.

Summary of Maternal Mortality and Pregnancy-related Mortality:

Maternal Mortality Ratio The number of maternal deaths to any woman during pregnancy, childbirth, or within 42 days of delivery excluding accidents and acts of violence per 100,000 live births More precise Not comparable to surveys before DHS-7
Pregnancy-related Mortality Ratio The number of pregnancy-related deaths (deaths to a woman during pregnancy or delivery or within 2 months of the termination of a pregnancy, from any cause, including accidents or violence per 100,000 live births Less precise Comparable to previous surveys; shown to allow for trend  interpretation

The DHS-7 questionnaire includes additional prompts to fully capture more siblings and siblings’ deaths. In previous DHS questionnaires, women were asked to list their siblings in order and then were asked follow-up questions about their survival status. In the DHS-7 adult mortality module, respondents are asked to list their siblings without worrying about their order but are then asked a list of probing questions to ensure that all siblings have actually been recorded. This change is likely to produce a more complete list of siblings for which information on adult and maternal mortality is collected. Once a complete list is produced they are then ordered and the questions on their survival status and age or age at death and years since death, as well as the maternal mortality related questions, are then asked as applicable. 

Why?  Several studies have suggested that respondents’ lists of siblings are not always complete. This often happens when the sibling is a half-brother or sister, when the sibling did not live with the respondent as a child, or when the sibling has died. A pre-test in Ghana indicated that the addition of these probing questions resulted in capturing additional siblings for about 10% of women.

Implications:  Omissions in the sibling history can affect the adult and maternal mortality ratios in different ways. The inclusion of more siblings tends to increase the adult mortality rate. This is because often the siblings who were previously omitted were not spontaneously mentioned because they have already died. However, studies suggest that these deaths are not disproportionately maternal deaths, so a more complete sibling listing might result in a lower maternal mortality ratio.

Key Take-Aways

The changes described above may sound confusing for non-demographers.  The major points to remember for DHS data users include:

  • The new Maternal Mortality Ratio is not comparable with previous measures of maternal mortality in DHS surveys
  • For trends, look at Pregnancy-related Mortality Ratio
  • Despite the different names, both measures include deaths during pregnancy. The MMR is a more precise measure as it excludes some of the deaths during pregnancy that were not related to pregnancy (i.e. accidents and acts of violence).
  • Maternal mortality is still a relatively rare event, and therefore both MMR and PRMR have wide confidence intervals. Both measures are always presented with their confidence interval so that the user can draw their own conclusions about the relative certainty of the point estimate.
06 Apr

Inside The DHS Program: Q&A with Trevor Croft

Name:  Trevor Croft

Position title: Technical Director/Capacity Strengthening Technical Coordinator (way too much and doesn’t really capture what I do).

Languages spoken: French (not great, but workable), Spanish (pretty weak, but I have worked in Spanish speaking countries), a smattering of Russian (when I worked in Kazakhstan, Kyrgyzstan, Uzbekistan and Armenia), and a few words of Bahasa Indonesia, plus enough to order a beer in most other places.

Albania and Health Survey 2008-09 [FR230](English)Favorite DHS cover: 2008-09 Albania DHS – it is based on a photograph I took of a piece of cloth with a very stylized version of the Albanian double-headed eagle that is seen on their national flag.

What has been the biggest change in The DHS Program during your time here? There are many, many changes but two of the biggest have been firstly the change in questionnaire content from a relatively small family planning focused survey in the 1980s to the much bigger and more extensive health content that we see today; and secondly the changes that computing and the internet have brought, going from computers with only floppy drives for data entry of paper questionnaires to the use of tablet computers, data capture in the field, and the rapid transfer of data, but with the ever increasing complexity of the data collection and processing systems.

What work are you most proud of?  Several things come to mind – in the early days the creation of standard tools and conventions for the processing of surveys that are still in effect (and effective) today, the widespread distribution of datasets through the internet, the development of CSPro with colleagues at the US Bureau of the Census, and the development of  STATcompiler back in 1999 and its further development in more recent years.

What’s your favorite trip to date?  There have been several memorable trips including fascinating trips to Zimbabwe, Nepal, and Indonesia. A visit to Zimbabwe for the 1988 DHS particularly comes to mind and combined a successful work trip with my first visit to Victoria Falls – probably my favorite place to visit anywhere in the world.

Is there a country that you would like to visit that you haven’t been to?  I’ve worked in over 65 countries, but there are still many that I would like to visit.  I’ve still yet to work in Tanzania or Uganda.  There are also several Asian countries such as Vietnam and the Philippines. I also want to visit Australia and New Zealand one day – purely for vacation.

Is there anything else you’re looking forward to? There continue to be changes at The DHS Program in how we conduct surveys, how data needs and interests change over time, and I’m interested to see how things will change in the next decade. The Millennium Development Goals (MDGs) have brought a bigger emphasis in the use of high-quality data, and I’m expecting that to be more so with the Sustainable Development Goals (SDGs).  I’ve seen great improvements globally over the course of my career, and I’m looking forward to seeing greater improvements in the coming years.

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21 Mar

7 Tips to Matching DHS Final Report Tables

Can't match DHS Final Report tables?
Feeling frustrated because you can’t match DHS Final Report tables in your statistical software?

 

Our new four-part video series shows the Top 7 Tips & Tricks for Matching DHS Final Report Tables.

In this four-part video series, we will be covering the top 7 tips and tricks to matching The DHS Program Final Reports using a statistical software program.

The videos will guide you through the following questions:

  1. Are you using the correct data file?
  2. Are you using the correct denominator of cases?
  3. Are you using the correct variable(s)?
  4. Are you properly recoding?
  5. Are you applying the correct weights?
  6. Are you selecting the correct software specific code?
  7. Are you properly coding the tabulation commands in your statistical program?

Watch the four videos in the series below on Matching DHS Final Report tables to get all the details on the top 7 tips and tricks.


Additional help can be found on our website and the User Forum.
01 Mar

Spotlight on Implementing Agencies: Madagascar

De gauche à droite: José Miguel Guzmán, Louise Ranaivo, Victor Rabeza Rafaralahy, Irène Hanitra Ranaivoarison, and Marius Randriamanambintsoa

De gauche à droite: José Miguel Guzmán, Louise Ranaivo, Victor Rabeza Rafaralahy, Irène Hanitra Ranaivoarison, and Marius Randriamanambintsoa

In January 2017, The DHS Program welcomed visitors from Madagascar. This post is one in a series of interviews with visitors to DHS headquarters.

Don’t read French? You can use the translate feature at the top of the page!

Nom, titre et organisation : Louise Ranaivo (Assistante Technique, MOH, NMCP) Victor Rabeza Rafaralahy (Coordonnateur MIS-INSTAT), Irène Hanitra Ranaivoarison (Programme National de Lutte Contre le Paludisme), Marius Randriamanambintsoa (Chef de Service,  Enquêtes et Recensements Démographiques, Institut National de la Statistique)

Pays d’origine : Madagascar


Q: Racontez un peu la première fois que vous avez travaillé sur des données de « The DHS Program »:

R: Marius Randriamanambintsoa: En 2010, on a utilisé les données de l’EDS pour le memoire sur l’Education de la mère et mortalité des enfants (IFOR)

Q: Qu’est-ce que vous avez trouvé comme surprise agréable lors de votre séjour  à « The DHS Program »?

R: Louise Ranaivo : Accueil, organisation, sécurité, spécialité de chacun.

R: Victor Rabeza Rafaralahy : Plus de femmes travaillent au bureau.

Q: Qu’est-ce que vous manque le plus de chez vous quand vous êtes ici ?

R: Louise Ranaivo : Famille.

R: Marius Randriamanambintsoa : La chaleur; on dirait que tout le monde est  « cloitré » dans un coin et à envoyer de mails pour dire  « bonjour ».

Q: Quelle est la plus grande différence entre le bureau de « The DHS Program » et votre bureau dans votre pays ?

R: Irène Hanitra Ranaivoarison : La disponibilité de tout le monde en cas de problème.

R: Louise Ranaivo : Responsabilité, disponibilité, efficacité de chaque personne.

R: Marius Randriamanambintsoa : Le bureau est très vaste et calme.

Q: Quelle est votre  page de couverture préférée ?

R: Marius Randriamanambintsoa : Couleur verte
     Madagascar Enquête Démographique et de Santé 2003-04 [FR158]

R: Irène Hanitra Ranaivoarison : Paysage
     Madagascar Enquête Démographique et de Santé 2008-09 (French)

Q: Quel est votre chapitre ou indicateur préféré, et pourquoi ? 

R: Victor Rabeza Rafaralahy : La mortalité des enfants. Mortalité infantile est toujours un des grands problèmes dans les pays en développement.

R: Marius Randriamanambintsoa : Connaissance et information en matière du paludisme. Je suis expérimenté pour ce chapitre et que ça a une influence sur les moustiquaires à imprégnation durable (MID).

R: Louise Ranaivo: Prévention : « Mieux vaut prévenir que guérir ».

Q: Quel est le thème de population ou de santé qui vous intéresse le plus, et pourquoi ?

R: Victor Rabeza Rafaralahy : Nutrition et vaccination (deux problèmes clés pour la réduction de la mortalité).

R: Louise Ranaivo: Paludisme, car c’est encore un fléau. Beaucoup de facteurs entrent en scène : homme – vecteurs – parasites – environnement.

Q: Comment espérez-vous que les données de l’EIP sur votre pays seront utilisées ?

R: Louise Ranaivo: Prévention : Comparaison avec celle des données antérieures et comparaison avec autres pays.

R: Victor Rabeza Rafaralahy : Les responsables concernés par chaque donnée doivent utiliser ces résultats et en tenir compte pour améliorer leur domaine respectif.

R: Marius Randriamanambintsoa : C’est intéressant aux décideurs, les données de l’EIP. Ils ont confiance de ces données.

Q: Qu’avez–vous appris en travaillant avec « The DHS Program »?

R: Louise Ranaivo: Prévention : Qualité du travail, discussions.

R: Victor Rabeza Rafaralahy : Beaucoup de choses : productivité, rapidité contact, plus connaissance, et organisation du travail.

R: Marius Randriamanambintsoa : J’ai appris pas mal de choses comme : la méthode de travail pour faire une enquête, analyse descriptive des données, dissémination des résultats, analyse approfondie des données en utilisant les logiciels : SPSS, SPAD et STATA.


Madagascar MIS 2016 Cover Final.indd

The 2016 Madagascar MIS was released on February 28th.

Download the final report here.

 

 

 

 

21 Feb

Spotlight on New Staff: Annē Linn

Name: Annē Linn

Position title: Communications Associate

Languages spoken: French, Spanish, Malinke, and I’ve been working on my Portuguese since starting at The DHS Program.

When not working, favorite place to visit:  Montana…there’s no place like home.

Favorite type of cuisine: Ooh, tough one…I like everything. I’m a wannabe vegetarian, so I’ll have to say fun, creative vegetarian cuisine.

Last good book you read: This was the hardest question on here, since I’ve read a lot of great books in the past few months. I recently read “American Gods” by Neil Gaiman for a book club and really enjoyed it.

Where would we find you on a Saturday?  Exploring DC and the surrounding area. There’s so much to do here!

First time you worked with DHS survey data: In graduate school, we used the 1997 Indonesia DHS in my course on Advanced Analysis for Nutrition Data.

What is on your desk (or bulletin board/wall) right now?  A mask from Tanzania, a metal butterfly from Mexico, and a wedding picture of my husband and me on our tandem bike.


Namibia Demographic and Health Survey 2000 [FR141]What is your favorite survey final report cover?
   I took a field trip to the publications library to provide a more informed answer for this one. The winner was the 2000 Namibia DHS cover, which brought back amazing memories of climbing dunes in the Namib desert when I studied abroad there in 2005.

Favorite chapter or indicator, and why?  Children with fever for whom advice or treatment was sought the same or the next day. I care a lot about timely care seeking for malaria.

What’s your favorite way to access The DHS Program’s data?  I love STATcompiler. Somehow I had never come into contact with it before I started here. When I first started using it and saw how easy it was to quickly access and visualize data, I was so excited, but also bummed that I hadn’t found it earlier!

What population or health issue are you most passionate about?  Why?  As I said before, I am very passionate about access to and utilization of treatment for malaria. As a Peace Corps volunteer in Senegal, I worked on a community-based model of proactive case detection for malaria that was designed to increase timely case management.

What are you most looking forward to about your new position?  Working with stakeholders in-country to ensure that survey data is utilized in program and policy planning.

What has been your biggest surprise so far?  I guess it’s not a surprise, but I have been fascinated to be behind the scenes and see how a DHS survey comes together after having utilized the data for so long before starting here. It’s such a huge undertaking with so much hard work by so many people, both on the ground and here in Maryland.

What do you look forward to bringing to The DHS Program (job-related or not!)? I have heard a lot about people being excited that I speak French, which is great, because I’m a huge language nerd and love speaking French.

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