Title: Individual and community-level determinants of Knowledge of ovulatory cycle among
women of reproductive age in 29 Sub-Saharan African countries: A multilevel analysis
Version: 1 Date: 11 Jun 2022
Reviewer's report:
Congratulations on your study and development of this manuscript for publication. A study of
this nature potentially can add to the body of knowledge on a very sensitive topic and contribute
to a reduction in unintended pregnancies. So a study to illuminate the subject is welcome
and valuable. Below I offer comments and questions that could make the manuscript more
streamlined and improved.
1. I have made it my duty to remind every author for any manuscript I review that no part of
Africa is under the Sahara desert. The notion of sub-Saharan Africa needs to be phased out
as it is racist. It separates the predominately fairer-complexioned (brown-skin) Africans from
the predominantly black-skinned Africans for no apparent reason. Other than that, it serves no
purpose. Therefore, I strongly suggest removing the word “sub-Saharan” when describing the
countries in Africa one conducts a study. Instead, you can say some African countries, etc.
2. In the background, the authors wrote about the connection between unintended pregnancy and
several outcomes, including a high crime rate. I don’t understand how a mother with unintended
pregnancy connects with a higher crime rate. Please, explain. Similarly, the authors need to
clarify how unintended pregnancy relates to reduced school performance.
3. Why did the authors select these countries? I ask this because studies like this have been
carried out in some of these countries, as the authors have highlighted. For example, highlight
Ethiopia and Ghana in the background as having studies on ovulatory knowledge. So what
informed the choice of these 29 countries?
4. Why did the authors select these explanatory variables? Why did the authors not ask specific
questions about factors that could explain ovulatory knowledge? What is the new contribution
from this study? The authors need to make a better case for why this paper is worth it and what
it adds to scientific knowledge.
5. If Dagnew et al. (2021) have researched this question in Ethiopia (as the authors indicated),
why include Ethiopia in the current study? What’s the rationale for Ethiopia instead of another
country without such a study?
6. What is the justification for including the husband’s educational level?
7. Exposure to the media: Usage of this variable in studies always leaves me with the question: is
it about exposure to the media or the specific issue of focus – in this case, the ovulatory period?
What if the person is exposed to TV but is watching comedy, football, or baseball all the time?
There has to be a strong justification for including this variable. Otherwise, I see this as garbage
in, garbage out.
8. What is a community in this case? Is it the primary sampling unit? Is it a country or
enumeration area? How are the authors defining “community”? I don’t understand it.
9. Based on my concern with the definition of community, I am also unsure about the suitability
of how community variables were created. A much more detailed and precise description of
what community-level variables are distinguished from individual ones needs to be undertaken.
For example, when the authors described community-level literacy, I gained no knowledge of
how that is distinct from individual/household level variables. I offer one suggestion here. The
authors can create community literacy by classifying all communities with a proportion of 60%
or higher of individuals with a primary, secondary, and tertiary education and who can read
a complete sentence as high literacy. Any community with a proportion below 60% (this is
just an example to illustrate the point) is a low literacy community. Currently, the definition of
community and the creation of community-level variables still require more work.
10. Who decides whether distance to a health facility is a big or small problem? Unfortunately,
it appears that the authors have no straightforward research questions to investigate but merely
throw in a bunch of variables to see if they are associated.
11. Fixed effects. Why include fixed effects? If the variables are calculated at the country level,
adding fixed effects will confuse things if there are no country-specific variations.
12. By putting random effects in a model, you relax things and may find associations that are not
really there. Did they run the models to see if the random effects are necessary? My statistical
knowledge is not excellent, but did the authors perform any test to assess that the data satisfied
the need for random effects in their analysis? Why the combination of both fixed and random
effects?