PONE-D-24-59293Early Childhood Female Genital Mutilation in Sierra Leone: Trends and Inequalities, 2008-2019PLOS ONE

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Reviewers' comments:

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Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: No

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: N/A

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

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Reviewer #1: In the results in Table 1 it is unclear what the denominator is for the age groups across the various years. Are the denominators the same? Also the conclusion on a declining trend from 2008 till 2019 wasn't observed in the table.

Let there be some clarity on what denominators were used for the various categories.

This would also mean that the direction of the discussion might need to change

Reviewer #2: The study title (and to some extent, the study aim) suggests that FGM is the outcome variable and its occurrence was to be observed and stratified by health equity/inequality indices and time periods. However, the narrative in the ABSTRACT suggest otherwise. For example, age-related and residential area differences were reported against inequality (and not FGM); economic inequality was reported as an outcome variable that changed over time, and not in relation to FGM.

That said, the expression "inequalities in FGM" seem inappropriate; this is because FGM is not a healthy state or condition that equality would be desired in the first place. The authors should reconsider using a different expression, as this seems to be a central theme to the entire paper. Same could be said for the term "disparities" again considering that FGM is not a desired state of health.

Line 141 - it is stated that the study investigated "inequalities in early childhood FGM prevalence" should be rephrased, in line with the previous comment.

Under data analysis, the four metrics used to evaluate inequality were explained; however the two subgroups for comparison of FGM prevalence were not made quite explicit.

Line 181&182 - authors should consider rephrasing the statement which seems suggestive that they have not provided sufficient explanation.

By convention, computation of Population Attributable Risk (and by inference Population Attributable Factor) should be done in a cohort study design that has afforded the measurement of true 'risk" (incidence). Thus, even though PAR and PAF have been proposed to compute health inequalities their use in this cross-sectional/ecological study design is contestable, where exposure and outcome were established and observed at the same point in time.

In addition, the authors' use of the term, "trend" should be carefully re-examined given that only three, interrupted data points were available, and there was no application of a statistical test of trend analysis.

Results - subheadings appear rather long; authors should consider rephrasing them.

Figure 1 - as already noted, a statistical test of trend analysis should be conducted to show the statistical validation of the results.

Table 1 appears to show the socio-demographic characteristics of a subgroup of the study population, that is, those that had FGM before age five. However, the "subgroup" in the table title suggests another use of this term. Authors should be consistent and avoid confusing terms - in the narrative the term "dimensions" was also used.

Furthermore and importantly in Table 1, the decrease observed in the prevalence of the outcome variable for each socio-demographic variable are simply reflective of the same observed overall decrease in prevalence over the three time periods. It is suggested that instead the differences in proportions within social groups e.g. wealth quintiles, should be re-analyzed for only the sub-population of those who had FGM before age 5. That way, column percentages total 100% each year.

And again, statistical tests of significance would enhance the interpretation of the validity of the results, especially given that they are based on data from sample-based surveys.

In the narrative for Table 2, authors should take care to be particular where 'difference' as a measure of inequality was the reference as opposed to 'difference' as a variance between two prevalence, for instance.

The first paragraph of the Discussion section appeared like a summary of all findings; a departure from the conventional. Typically, each key finding should be discussed before taking on the next one, supported by findings from existing literature.

In addition, in more than one instance reference was made to suggest that the study population were "children under five years" as opposed to women of reproductive age group who reported having FGM done when they were under five years old.

As earlier mentioned, the use of phrases such as "FGM inequalities" could be confusing as FGM is not a positive health outcome or service.

Reviewer #3: The introduction section requires a more comprehensive contextual background on Sierra Leone for the reader. This also bears significantly on the interpretation of the findings outlined below.

Purpose: The authors acknowledge that FGM in SL is deeply rooted in cultural practices and traditional belief making it a complex social and public health challenge (Lines 89 -91) and that a complex interplay exists between factors that influence attitudes towards FMG but exclude at least two critical variables used for the analysis: ethnicity and religion.

This study describes association between a limited number of independent variables and the dependent/outcome variable (i.e. FMG in < 5 girls in SL) using a tool and data sets that already exist for monitoring trends in health disparities. Describing results from applying the tool could be viewed as recapitulation and not original research.

The study claims that no research exists on the trends and inequalities in early childhood FMG, particularly regarding socioeconomic and geographic disparities and aims to fill this crucial gap. Several papers looking at trends already exist and some of these are referenced in the reference section of the manuscript, for example Bjalkander et al. (2013). This study undertaken a decade previously in Sierra Leone utilises an inclusive list of socio-economic and geographical variables and also concludes a declining prevalence of FGM in younger age groups.

The study design should be described as a time-trend ecological study design.

Under the methods section, the paper explains that the SLDHS data used in this study was captured from household surveys of mothers/caregivers of girls < 5 years [Line 146 -149]. However results from Line 194 onwards refer to the responses from women across different age-groups. For example:

In 2008, women aged 20-29 had the highest prevalence at 24.5%, while those aged 40 - 49 had the highest prevalence at 17.2% in 2013. This is confusing for the reader. Are these adult women reporting on whether FMG was conducted on their < 5 y.o female children or whether they are self-reporting that they were subjected to FMG when they were < 5. This need to be more clearly explained.

The analysis needs to consider critical confounders and/or effect modifiers such as ethnicity, religion and the heterogeneity within and between the populations of both Provinces. These factors have a major bearing on the interpretation of the results and should be discussed alongside them. For example, concluding that illiteracy and lack of resources are the most likely determinants to explain the inequalities in FMG practices in children between western and northwestern Province without considering the effect of cultural and religious differences in demographics between these geographical areas leads to over-simplification of how results are interpretated.

The authors need to review the paper against all steps in the STROBE protocol. The study states that it aligns with STROBE protocol but does not consider reporter bias in relation to the validity of DHS data. A referenced publication in this study describes findings from an earlier study conducted in Ghana (Jackson et al., 2003) which demonstrated that up to 50% of survey responders denied being subjected to FMG. It found that those denying the practice were more likely to be more educated, located in areas where legislation and information campaigns were introduced against the practice (i.e. urban areas), were significantly younger and less likely to practice traditional religion compared to those who provided a positive response. The inverse relationship between denial and these variables was not discussed as a potential bias when interpreting the results.

Line [197-199], the authors infer that “women who have undergone FGM before age 5 declined from 23.2% in 2008 to 12.3% in 2019, mainly attributable to the government of SL’s efforts to reduce the practice”.

This statement is making a wide inference between cause and effect without any scientific basis and hence reflects researcher bias that should be addressed as part of adhering to STOBE protocol.

The results also assume that the populations under study remained static between 2008, 2013 and 2019 i.e. that no rural to urban displacement or migration occurred that could account for disrupting/diluting differences in trends and reported as a “no inequality” result.

Excluding contextual consideration of major events in SL such as the Ebola outbreak (2014 -2016) and climatic related events in the north and northwestern Provinces as influencing factors is another major limitation reflected in the interpretation of results.

The study sets out to fill a knowledge gap by analysing trends and inequalities in FMG in girls <5 in SL “to understand patterns and disparities essential for developing targeted interventions and informing policy decisions…”

This is not acheived mainly because quantitative analysis is not a suitable methodology to understand patterns and disparities. Only exploratory qualitative research can delve deep into understanding the nuanced complexities (i.e. the why?) behind trends and disparities necessary for informing policy and interventions. This is a major critique of so-called evidence-based interventions applied in developing countries that emerge from over simplification of results from the application one size fits all tools and models.

The same research question could be used to critically evaluate whether the tool can actually effectively measure inequities in health outcomes, particularly between population sub-groups and ethnic minorities. This might yield a more objective and beneficial outcome to the study. While some limitations of the tool are outlined, a more scientific critique of its use and limitations in terms of whether it is or not appropriate to inform policy decisions should be considered as well as alternative research approaches than can inform these understandings more effectively.

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Reviewer #1: No

Reviewer #2: Yes:  SEYE BABATUNDE

Reviewer #3: No

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<p>Early Childhood Female Genital Mutilation in Sierra Leone, 2008-2019

PONE-D-24-59293R1

Dear Dr. Osborne,

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Kind regards,

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Academic Editor

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