7 research outputs found

    Contributions to predicted nutritional change by nutrition indicator.

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    <p>Source: Authors’ estimates. Note: HAZ = height-for-age <i>z</i> score.</p

    Shifts in height-for-age <i>z</i> scores (HAZs), by child’s age, from 2001 to 2011.

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    <p>Source: These are local polynomial smoothing predictions with 95% CIs estimated from the Demographic Health Surveys [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0145738#pone.0145738.ref018" target="_blank">18</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0145738#pone.0145738.ref020" target="_blank">20</a>]. Note: CI = confidence interval.</p

    Unadjusted mean values of outcome variables for Non-BCC neighbor households.

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    <p>Unadjusted mean values of outcome variables for Non-BCC neighbor households.</p

    Behavior change communication activities improve infant and young child nutrition knowledge and practice of neighboring non-participants in a cluster-randomized trial in rural Bangladesh

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    <div><p>Objective</p><p>To examine the impact on infant and young child nutrition knowledge and practice of mothers who were neighbors of mothers participating in a nutrition Behavior Change Communication (BCC) intervention in rural Bangladesh.</p><p>Methods</p><p>We analyzed data from 300 mothers whose neighbor participated in a nutrition BCC intervention and 600 mothers whose neighbor participated in an intervention that did not include BCC. We constructed measures capturing mothers’ knowledge of infant and young child nutrition (IYCN) and measures of food consumption by children 6-24m. The effect on these outcomes of exposure to a neighbor receiving a nutrition BCC intervention was estimated using ordinary least squares and probit regressions. The study was registered with ClinicalTrials.gov (Study ID: NCT02237144).</p><p>Results</p><p>Having a neighboring mother participate in a nutrition BCC intervention increased non-participant mothers’ IYCN knowledge by 0.17 SD (translating to 0.3 more correct answers). They were 14.1 percentage points more likely to feed their 6-24m children legumes and nuts; 11.6 percentage points more likely to feed these children vitamin A rich fruits and vegetables; and 10.0 percentage points more likely to feed these children eggs. Children of non-participant mothers who had a neighboring mother participate in a nutrition BCC intervention were 13.8 percentage points more likely to meet World Health Organization (WHO) guidelines for minimum diet diversity, 11.9 percentage points more likely to meet WHO guidelines for minimum acceptable diet, and 10.3 percentage points more likely to meet WHO guidelines for minimum meal frequency for children who continue to be breastfed after age 6m. Children aged 0-6m of non-participant mothers who are neighbors of mothers receiving BCC were 7.1 percentage points less likely to have ever consumed water-based liquids.</p><p>Conclusions</p><p>Studies of nutrition BCC that do not account for information spillovers to non-participants may underestimate its benefits in terms of IYCN knowledge and practice.</p></div

    Impact of exposure to neighbor’s BCC on infant and young child feeding practices, marginal effects calculated from probit regression with clustered standard errors.

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    <p>Impact of exposure to neighbor’s BCC on infant and young child feeding practices, marginal effects calculated from probit regression with clustered standard errors.</p

    Trends in Mathematics Learning in Ethiopia: 2012-2019

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    This insight note reports trends in mathematics learning for Grade 4 pupils in Ethiopia and is based on a longitudinal survey of 33 schools between 2012-13 and 2018-19

    Which Aspects of Educational Reforms in Ethiopia Have Promoted Equitable Achievements in Mathematics?

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    This paper assesses the factors underpinning trends in mathematics learning for Grade 4 pupils in Ethiopia based on data collected in 2012-13 (the Young Lives surveys, YL) and 2018-19 (the RISE surveys) during the GEQIP-II Education Reform. It combines comparable data on attainments on tests of students’ mathematics knowledge with information on their family background, their teachers, and the schools they attend
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