Title: The varying estimation of infertility in Ethiopia: The need for a comprehensive definition
Version: 0 Date: 01 Feb 2024
Reviewer's report:
Thank you for the opportunity to review this manuscript. Infertility is an important public
health issue, potentially causing psychological distress and other adverse outcomes for many
individuals and couples. It remains understudied in sub-Saharan Africa, and the varying
definitions and approaches to measure fertility contribute to the broad range of estimates for the
region. For this reviewer, results from this paper make an important contribution highlighting
the variation in estimates from two different infertility measurement approaches applied to the
same dataset in the same country, eliminating the many differences across existing studies that
contribute to the variation of estimates.
For this reviewer, the key outcomes from the analysis are that the demographic approach
estimates a 7.6% infertility prevalence over a five-year period, while the current duration (CD)
approach estimates higher infertility prevalence of 24%, 13%, and 9% at 12, 24, and 36 months.
The demographic approach estimate is closer to the 36-month CD estimate, but this is not
surprising given the longer reference period for the former.
It would be helpful if the authors are explicit about the objectives of the study. The way the
manuscript is currently written, it seems like an analysis of calculating infertility using two
different approaches on the same data. But the background does not set this up very well and
describe what gap it fills. Why these two approaches for example? Are they the only ones that
can be applied to national surveys such as the DHS? In the background, the approaches are
introduced here: “Approaches that include all individuals at risk of pregnancy through national
surveys – such as the demographic and current duration approaches…” (line 60) but it would help
if the authors can expand a bit more to justify why these two approaches were used specifically.
Additionally, the authors attempt to explain the utility of this comparison on line 66 “researchers
can assess which results are robust across definitions and which may vary. This may help to
understand variation across studies better and improve the overall characterization of infertility
” But this justification is not clear to me. I am not sure what “which results are robust across
definitions” mean. The authors already explain that the variation across studies is due to different
measures, units of analysis, etc. (line 51). It’s not clear what the added value of this study is,
based on the current introduction section.
The authors could strengthen their analysis by conducting a side-by-side comparison of the
different definitions and assumptions for the approaches and how they may contribute to
the varying estimates (for example: does the definition of sexual exposure in one approach
contribute to the lower/higher estimate? the sample for demographic approach is much large than
the sample for CD , could this affect the estimate? period of exposure is 5 years for demographic
approach vs the <3 years for CD, does the shorter duration of the period of investigation for CD
introduce potential misclassification). The authors attempt to do this, but they could organize
their comparisons to more explicitly point out these differences. For example they have a table
for the demographic approach. They could expand this table and include columns for the CD
approach to better point out the differences in the measures along each component included in
the calculations.
Lastly, the discussion could be improved by doing more direct comparisons of the two
approaches instead of comparing the approaches to other studies. Here is an opportunity to
compare different approaches that use the same data for the same country. Based on the
introduction, it does not seem like this has been done before, is that correct? Comparing
the findings to different studies in different settings introduces several limitations, such as
differences in measures, context, data source, cultural norms around infertility, etc. And the
authors already highlight differences in these factors as contributors to the wide range of
estimates for infertility globally and even within regions such as in SSA. I think the opportunity
here lies in the use of the same data and the same country so more direct comparisons of the
assumptions of the approaches can be teased out and there are no cultural/contextual differences
to consider.
Specific comments/questions:
Introduction:
- The introduction could be better organized. The second paragraph of the introduction starts
with infertility in Africa, and then in the middle discusses the challenge of determining global
infertility level. Is the sentence starting at line 45 supposed to be a new paragraph?
- Line 50 – “explanned” should by “explained”
- Line 51 – no period after “measured”
- The introduction could expand a bit more on why Ethiopia was chosen for the analysis or at least
describe existing studies that have attempted to estimate infertility in the country – what were
the approaches used? The estimates? Did they use DHS as well or other sources? Limitations of
these approaches? There’s an article published last year by Legese et al. and another published
in 2022 by Akalewold et al.
- Line 71 – only married? Or also in union?
Methods:
- The table starting line 99 could be clearer: variable, definition and what it’s measuring (for
ex: “Married or in union can be a proxy for regular sexual intercourse” are writte), and how
it’s measured in this study using the DHS (what are the specific items from the DHS used to
define it).
- “Thus, we first selected women with five or more years of union…” – This is unclear. If union
time is only calculated starting from the first union, then the selection includes women whose
first union was five or more years ago? If so, probably best to specify that “we first selected
women whose first union was five or more years prior to interview” and discuss the limitations
of these definition in the discussion section.
- “Thus, ever contraceptive use history was used to capture current use as well.” – This is unclear.
Are women who reported that they ever used contraception but did not report a contraceptive
episode in the 5-year calendar considered “current” users as well? The subsequent sentence
“Those using outside the calendar were also considered non-users” is also unclear. I am unclear
why ever use of contraception is considered if the analysis is only looking at a five-year exposure
period?  Was sterilization considered?
- Analysis: the authors should explain why these factors were considered for the logistic
regressions. Could cite studies that have shown that these are important to consider when
examining infertility or studies that have shown associations between the factor and infertility.
Discussion:
- A strength of these approaches is that they can leverage national survey such as the DHS which
are collected every five years and therefore enable monitoring of infertility trends
Lastly, there are too many tables. The authors could move some to an appendix.