Next Article in Journal
Screening of Heavy Metal-Immobilizing Bacteria and Its Effect on Reducing Cd2+ and Pb2+ Concentrations in Water Spinach (Ipomoea aquatic Forsk.)
Next Article in Special Issue
“They Just Need to Come Down a Little Bit to Your Level”: A Qualitative Study of Parents’ Views and Experiences of Early Life Interventions to Promote Healthy Growth and Associated Behaviours
Previous Article in Journal
Mediating Effects of Specific Types of Coping Styles on the Relationship between Childhood Maltreatment and Depressive Symptoms among Chinese Undergraduates: The Role of Sex
Open AccessArticle

Sensitivity of Nutrition Indicators to Measure the Impact of a Multi-Sectoral Intervention: Cross-Sectional, Household, and Individual Level Analysis

1
Feinstein International Center, Tufts University, Boston, MA 02111, USA
2
Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(9), 3121; https://doi.org/10.3390/ijerph17093121
Received: 23 February 2020 / Revised: 21 April 2020 / Accepted: 26 April 2020 / Published: 30 April 2020
(This article belongs to the Special Issue Early Influences on Child Health and Wellbeing)
Interventions tackling multiple drivers of child malnutrition have potential, yet the evidence is limited and draws on different analysis and nutrition outcomes, reducing comparability. To better understand the advantages and disadvantages of three different analytical approaches on seven common nutrition indicators, we use panel data (2012, 2014, 2015) on 1420 households from a randomized control study of a multi-sectoral intervention in Chad. We compare program impact using three types of analysis: a cross-sectional analysis of non-matched children; a panel analysis on longitudinal outcomes following the worst-off child in the household; and a panel analysis on longitudinal outcomes of matched children. We find that the sensitivity of the nutrition outcomes to program impact increases with each subsequent analytical approach, despite the reduction in sample size, as the analysis is able to control for more non-measured child and household characteristics. In the matched child panel analysis, the odds of a child being severely wasted were 76% lower (CI: 0.59–0.86, p = 0.001), the odds of being underweight were 33% lower (CI: 0.15–0.48, p = 0.012), and weight-for-height z-score was 0.19 standard deviations higher (CI: 0.09–0.28, p = 0.022) in the treatment versus control group. The study provides evidence for multi-sectoral interventions to tackle acute malnutrition and recommends the best practice analytical approach. View Full-Text
Keywords: nutrition; early childhood; multi-sectoral programming; mixed-effects model; Chad; analytical approach nutrition; early childhood; multi-sectoral programming; mixed-effects model; Chad; analytical approach
Show Figures

Figure 1

MDPI and ACS Style

Marshak, A.; Young, H.; Radday, A.; Naumova, E.N. Sensitivity of Nutrition Indicators to Measure the Impact of a Multi-Sectoral Intervention: Cross-Sectional, Household, and Individual Level Analysis. Int. J. Environ. Res. Public Health 2020, 17, 3121.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop