Research ArticleENVIRONMENTAL STUDIES

Impacts of forests on children’s diet in rural areas across 27 developing countries

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Science Advances  15 Aug 2018:
Vol. 4, no. 8, eaat2853
DOI: 10.1126/sciadv.aat2853
  • Fig. 1 Causal pathways between forests and dietary diversity.
  • Fig. 2 Distribution of communities included in the analyses.

    The data set includes 43,011 households in 27 developing countries.

  • Fig. 3 Estimated impacts of forests on dietary diversity.

    Partial-ID-27, partial identification for 27 countries; Partial-ID-14, partial identification for 14 African countries; Matching-14, matching design for 14 African countries; Placebo-14, placebo test for the matching design for 14 African countries. Values in parentheses, impact expressed in percent of the average dietary diversity of nonforest households. NaN, not a number (undefined). Blue bars, 95% confidence intervals.

  • Fig. 4 Heterogeneity of impacts of forests on dietary diversity.

    (A) Variation of impact with community GDP. (B) Moderating effect of distance to the nearest urban town. (C) Moderating effect of distance to the nearest road. (D) Moderating effect of the education of the head of household. Y axis represents the difference in dietary diversity (IDDS) between forest and similar nonforest households. Blue bands, 95% confidence intervals.

  • Fig. 5 Estimated ranges of impacts of forests on the prevalence of households where children ate vitamin A– or iron-rich food in 27 developing countries.

    Blue bars, 95% confidence intervals.

  • Table 1 Means and SDs (in parentheses) of characteristics of forest and nonforest households across 27 countries.
    VariableForest householdNonforest household
    IDDS3.12 (2.29)2.50 (2.05)
    Communities in lands suitable for agriculture (%)38.22 (48.60)45.15 (49.76)
    Slope (°)2.66 (3.32)1.04 (1.48)
    Elevation (m)586.59 (562.83)627.27 (564.34)
    Distance to a road (km)10.94 (26.09)2.84 (3.18)
    Distance to a city (km)40.85 (36.34)32.66 (25.37)
    Communities in areas with low livestock density (%)74.88 (43.37)19.52 (39.63)
    Communities in areas with medium livestock density (%)18.29 (38.66)56.77 (49.54)
    Communities in areas with high livestock density (%)6.83 (25.23)23.71 (42.53)
    Community GDP (US$ billion Purchasing Power Parity)0.87 (1.26)1.37 (1.34)
    Population size (individuals)6,139.85 (10,561.69)14,445.98 (35,939.32)
    Education of head of household (years)5.18 (4.02)3.70 (4.23)
    Age of head of household (years)38.73 (12.76)39.34 (12.82)
    Household size (individuals)6.32 (2.62)6.95 (3.69)
    Children younger than 5 years (individuals)2.02 (0.89)2.22 (1.14)

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/8/eaat2853/DC1

    Section S1. Why not controlling for the DHS wealth variable?

    Table S1. Description and sources of the confounding variables.

    Table S2. Covariate balance between forest and nonforest households in 14 sub-Saharan countries.

    Reference (57)

  • Supplementary Materials

    This PDF file includes:

    • Section S1. Why not controlling for the DHS wealth variable?
    • Table S1. Description and sources of the confounding variables.
    • Table S2. Covariate balance between forest and nonforest households in 14 sub-Saharan countries.
    • Reference (57)

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