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  • Data collection,  Data value chain,  India

    Tracking India’s Progress on Addressing Malnutrition and Enhancing the Use of Data to Improve Programs

    January 8, 2021

    In collaboration with Partnerships and Opportunities to Strengthen and Harmonize Actions for Nutrition in India (POSHAN), NITI Aayog, and ID Insight, DataDENT developed a joint report addressing considerations for improving the availability and use of data to improve nutrition programs in India. The report shares a comprehensive indicator framework aligned with India’s National Nutrition Mission, POSHAN Abhiyaan, and describes a theory…

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    DataDENT No Comments
  • Data collection,  India

    Understanding the Role of Cognitive Interviewing in Improving Survey Questions

    November 17, 2020

    While answering a survey questionnaire, how do the respondents interpret the questions? What techniques of cognitive interviewing can facilitate appropriate framing of the questions? These are important considerations to have while designing survey questions to ensure that they clearly communicate the question’s intent and elicit responses aligned with the intended interpretation. To look at these concepts more closely, IFPRI—an implementing…

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    Sattvika Ashok and Emily Myers, IFPRI No Comments
  • Data collection,  Data for Nutrition,  Data visualization

    Webinar Round Up: Measuring food security and nutrition during COVID-19

    May 22, 2020

    The COVID-19 pandemic has had a significant impact on food security and nutrition. Organizations and initiatives have shared webinars, blogs, and additional resources to help governments, donors, program implementors, and other stakeholders on how to monitor and assess how COVID-19 threatens food systems and nutritional status of populations. Below is a list of webinars on measuring food security and nutrition…

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    Riley Auer No Comments
  • Advocacy,  Data collection,  Demographic and Health Surveys,  Survey data

    Overview of new nutrition questions in the Demographic and Health Survey (DHS) core questionnaires

    October 11, 2019

    The Demographic and Health Survey (DHS) Program just released the new DHS model questionnaires for round 8 (2018-2023). We previously shared on the blog how DHS and the Multiple Indicator Cluster Survey (MICS) are main sources of nationally-representative maternal, newborn, child health, and nutrition data. The four DHS core questionnaires (household, woman, man, and biomarker) will be used globally, and…

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    Tricia Aung 1 Comment
  • Data collection,  Data value chain,  Fortification

    Updated guidance on measuring fortification coverage

    August 9, 2019

    The Global Alliance for Improved Nutrition (GAIN) has released new guidance on measuring coverage of food fortification. The Fortification Assessment Coverage Toolkit (FACT) provides standardized tools to collect, analyze and synthesize data on quality, coverage, and consumption of fortified foods in different countries and contexts. FACT also provides guidance on survey design and use in evaluation contexts. GAIN Briefing Paper…

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    jennafritz No Comments
  • Data collection,  Data value chain,  Survey data

    Beyond Definition: Attaching meaning to indicators

    June 26, 2019

    An interview with Jef Leroy, IFPRI A worker with the partner organization of Save the Children measures a child in the slums of Govandi, Mumbai, India. © 2016 Mayank Soni (Save the Children), Courtesy of Photoshare Stunting, or children assessed as too short for their age, has become a north star indicator for the nutrition community. Many advocates, policy makers,…

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    jennafritz No Comments
  • Breastfeeding,  Children,  Complementary feeding,  Data collection,  Survey data,  Women

    Innovations in Nutrition Measurement: Lessons Learned from Population-Based Household Surveys in Burkina Faso and Kenya

    April 18, 2019

    A resident enumerator in Burkina Faso prepares for the third round of data collection for PMA2020, a mobile technology-based survey project that supports routine, rapid-turnaround, high quality data on family planning and other health indicators. ©2016 PMA2020/Shani Turke, Courtesy of Photoshare Countries with high burdens of malnutrition have increased investment in nutrition, but monitoring and evaluation efforts have been hindered…

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    Audrey Buckland No Comments
  • Data collection,  Survey data

    Inspiration from the Water, Sanitation and Hygiene (WASH) community: Core Questions on WASH for Household Surveys

    March 22, 2019

    © 2014 Faisal Azim, Courtesy of Photoshare World Water Day 2019’s theme of “Leaving no one behind” focuses on vulnerable populations—including women, children, refugees, and indigenous peoples—that lack access to safe water. This theme is aligned with Sustainable Development Goal (SDG) targets on universal and equitable access to safe and affordable drinking water (6.1) and adequate and equitable sanitation and…

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    jennafritz No Comments
  • Data collection,  Survey data

    Digging in to the DHS and MICS nutrition data

    December 6, 2018

    The Demographic Health Survey (DHS) and Multiple Indicator Cluster Survey (MICS) are primary sources of nationally-representative maternal, newborn, child health, and nutrition data for the global health community. In an online survey conducted by DataDENT earlier this year, nutrition professionals were asked how they access and use data on nutrition. Among the 191 survey respondents, the two most commonly reported…

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    jennafritz 3 Comments
  • Data collection,  Survey data

    Launch of DataDENT Online Survey on Data Use

    July 18, 2018

    Understanding how people use data is critical for developing strong programs and policy in nutrition. Data for Decisions to Expand Nutrition Transformation (DataDENT) is conducting a survey to better understand how people in the multisectoral nutrition community—including health, agriculture, water and sanitation, and social protection—use data in their work. Professionals working in programs, policy, advocacy or data at global, regional,…

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    Jenna Fritz No Comments
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