Blog
About

39
views
0
recommends
+1 Recommend
0
shares
    • Review: found
    Is Open Access

    Review of 'Associations between the household environment and stunted child growth in rural India: a cross-sectional analysis'

    Bookmark
    4
    Associations between the household environment and stunted child growth in rural India: a cross-sectional analysisCrossref
    Average rating:
        Rated 4 of 5.
    Level of importance:
        Rated 4 of 5.
    Level of validity:
        Rated 3 of 5.
    Level of completeness:
        Rated 4 of 5.
    Level of comprehensibility:
        Rated 4 of 5.
    Competing interests:
    The Reviewer is a Theme Editor for the journal

    Reviewed article

    • Record: found
    • Abstract: found
    • Article: found
    Is Open Access

    Associations between the household environment and stunted child growth in rural India: a cross-sectional analysis

    Stunting is a major unresolved and growing health issue for India. There is a need for a broader interdisciplinary cross sectoral approach in which disciplines such as environment and health have to work together to co-develop integrated socio-culturally tailored interventions. However, there remains scant evidence for the development and application of such integrated, multifactorial child health interventions across Indias most rural communities. In this paper we explore and demonstrate the linkages between environmental factors and stunting thereby highlighting the scope for interdisciplinary research. We examine the associations between household environmental characteristics and stunting in children under five years across rural Rajasthan, India. We used DHS-3 India (2005-06) data from 1194 children living across 109,041 interviewed households. Multiple logistic regression analyses independently examined the association between (i) primary source of drinking water, (ii) primary type of sanitation facilities, (iii) primary cooking fuel type, and (iv) agricultural land ownership and stunting adjusting for child age. Results suggest, after adjusting for child age, household access to (i) improved drinking water source was associated with a 23% reduced odds (OR=077, 95% CI 05 to 100), (ii) improved sanitation facility was associated with 41% reduced odds (OR=051, 95% CI 03 to 082), and (iii) agricultural land ownership was associated with a 30% reduced odds of childhood stunting (OR 070, 95% CI 051 to 094). The cooking fuel source was not associated with stunting. Our findings indicate that a shift is needed from nutrition-specific to contextually appropriate interdisciplinary solutions, which incorporate environmental improvements. This will not only improve living conditions in deprived communities but also help to tackle the challenge of childhood malnutrition across Indias most vulnerable communities.
      Bookmark

      Review information

      10.14293/S2199-1006.1.SOR-SOCSCI.A0MZVI.v1.RBVPGN

      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

      Keywords:

      Review text

      This statistical analysis of DHS data should be using survey statistics (survey logistic regression), not asymptotic-theory “normal” logistic regression. Specifically, the authors should do a subpopulation analysis of the Rajasthan State data to correct the weights for exclusion of some of the survey sample. This is not a self-weighted random sample, it is a multistate cluster sample (from which a single state is being included in this analysis). Failure to use appropriate survey weights / survey estimation techniques (even before getting into subpopulation estimation issues) can sometimes lead to completely different conclusions from the “same” dataset. See for example: https://pubmed.ncbi.nlm.nih.gov/19713856/

      The authors used SPSS to do their analysis; an overview of how to do survey estimation (the right way for these logistic regressions to be done) in SPSS is available here: https://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=3253&context=jmasm


      Also in Methods 2.1, they have a “c” bullet point listed but the text is empty.
       

      on behalf of Dr Matthew Gribble

      Theme Editor, UCL Open Environment

      Comments

      Comment on this review