Rated 3.5 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 3 of 5.
|Engineering, Civil engineering, Social & Behavioral Sciences, General behavioral science, Environmental engineering
|water, sanitation, environment, stunting, agriculture, fuel, Sanitation, health, and the environment, People and their environment, malnutrition, rural, growth, India
Thank you for submitting your paper ‘Associations between the household environment and stunted child growth in rural India: a cross-sectional analysis’ for consideration to UCL Open: Environment. Prof Dan Osborn, Editor-in-Chief, has reviewed the paper and here provides a combined editorial pre-review of the submitted paper to help and encourage the authors to revise this version 1 for open peer review.
This paper is potentially very interesting as it looks across the economic social and environmental conditions in children who have and have not suffered stunting in an Indian state. It thus examines three main pillars of sustainable development.
The data is complex if in part somewhat old (15 years) and more needs to be done to describe the study’s findings about the two populations of stunted and unstunted children and to set the background of these two groups of children in a wider context much of which currently appears too late in the paper to inform the reader in a timely way. The context setting should explain more fully how this study sits in relation to other studies on stunting in India (e.g. with respect to urban vs rural communities) so that it can be more clearly established in the reader’s mind what this study contributes. There has been a lot of work on stunting and spelling this out will help the reader appreciate the importance of the work and may help guide the discussion of the results which at present is rather too short on explaining the wider significance of the work and how it relates to the policy positions of the state concerned on such issues as open defecation.
It may be more productive to conduct other forms of statistical analysis than the ones chosen. Some calculation of relative risk rather than the odds-ratio approach may allow for a more rounded interpretation of the results. The issues involved here seem to be much more in the public health rather than the medical domain. The study is fundamentally examining the wider determinants of health where the Bradford Hill criteria can be helpful in organising data and analysis. Much depends on the authors’ view of their data and whether they are viewing the study as being exploratory of a real world situation or one where the unstunted children are a de facto control group such that the study becomes one where the intervention is the unimproved economic, social and environmental circumstances of the child. The first approach may be preferable, in which case perhaps the whole data set could be analysed by some approach based on the principle components of the dataset or on some simple multiple regression that might in effect allow the relative importance of the large number of variables (some of which are parametric and some non-parametric) to be more clearly set out for a reader. Such approaches may have the advantage of allowing a re-examination of the data once main principle components have been established and consideration given to underlying mechanistic or process-based cause and effect pathways. The authors may think this approach too discursive but it may avoid corralling a wide ranging study into a narrow interpretation set determined by the odds-ration format.
There would be room in a methods or approach section to describe more fully the reasoning behind the statistical approach selected. This might help the field in general. More discourse on analytical approaches is needed to avoid misunderstandings arising in operational or policy arena.
This might include something about whether the study’s objective is to examine how various variables might be related or whether there is enough evidence to describe relative causal significance.
Detailed comments on text (comments on Tables follows)
L27-29: Use of the word “unparalled” is difficult to understand in the sentence and thus the sentence if unclear.
L35-37: This text is unclear.
L60-62: The reference to UNICEF should perhaps move up the text to L56 at least. Perhaps this is part of the contextual material that sets the scene?
L70-71: A statement of robustness would be more appropriate in a medical journal in its current form it means that some of this material could be worked into to other sections of the paper and have greater impact.
L72: Are there any other factors linked to stunting that might be important that could not be studied in this work due to lack of access to relevant data? If so these could be stated in order to inform readers of the limitations of the study – perhaps describing the limitations, scope and focus of this kind of study is more important than a description or statement of robustness?
L85-92: Clarification of the wording here would again help the importance of the work come across more clearly.
L101-105: The rationale for choosing the factors included may need to be set out just a little more. For are they a standard set or are they what were available in this location?
L109: Is a comment needed about the age of the data – especially if there is a mismatch between age of data and any comparison made to more recent policy positions.
L135: Check the words about sub-categories here.
Line 151: Is a reference needed here?
Line 153: There seems to something of a jump here in the wording on risks to older children compared to younger ones. The domestic situation must be hugely complex in the social circumstances being dealt with. This piece of text is one of several that suggests the authors main interests are considering risks and how these might be reduced rather than examining interventions per se (see general comments).
Line 157: Determining age by cultural memory is an interesting approach doubtless used previously. As age classes were then determined the approach seems acceptable although some of the children may have been close to class boundaries. Can the authors comment on how many children were near class boundaries or the impact of using an approach using the absolute ages discovered. Maybe this data is not available but nonetheless should be clarified.
L162-164: More needed here perhaps on the reasons why this view of other factors is the one to go with in this study (may link back to L101-105). A little more explanation is needed as to how this importance of age vs other factors was determined.
L169: unclear sentence
L174: The overall dataset is complex with many variables or even sub-variables so the wish to simplify it must be almost irresistible but the impact of dichotomising needs to be explained more clearly. It would be a shame if data richness was lost or the interpretive power of the analysis lessened.
L195-196: It is not absolutely clear why it is that age appears as the only confounding variable. Age is certainly a strong influence on the outcome of stunting but the text needs some addition to explain why it is given a confounding status when other variables are treated more as explanatory or even perhaps “causal” or at least correlative ones.
L198: It seems as if there are relatively small numbers in some of the improved categories. Are these so small that it affects the approach to statistical analysis? The problem is not uncommon. Many environmental studies suffer from this kind of issue.
Comments on Tables
Both Tables need a clear explanatory legend given their complexity. The Journal format is such that this is possible.
Should any detailed data on length and height be provided so that readers can see whether there was a clear separation between the stunted and non-stunted groups?
In the last line of Table 1 there is an arithmetical error, hopefully not found in the statistical analysis.
In describing the data in Table 2 has a sufficient amount been said about the impacts of age on the outcomes for very young and older children – this could have a major impact on policies and interventions. This might be especially important for cases where water-borne health factors are involved and the pathways by which the health factors could be managed.
The data as expressed in the Tables raises some issues about how this kind of data can best be explored/analysed. For example when considering land ownership it appears from a quick look at the data as shown in the table that there are more stunted children in situations where land is not owned and rather less when land is owned. Does this kind of clear message emerge in the text clearly enough (provided it is supported by an appropriate analysis)? I think the numbers involved are No land ownership: 116/224 stunted vs 108/224 non-stunted whereas where land is owned the ratios are the opposite way round: 416/970 vs 554/970 and of course this is only one of the factors – what would happen if these results were broken down by age class? Would the effect be stronger still in some age classes?