Title: Determinants of contraceptive continuation among women in sub-Saharan Africa
Version: 1 Date: 30 Nov 2022
Reviewer:  Shireen Assaf
Reviewer's report:
Dear authors,
While this is an important topic that included analysis on several countries in SSA, I had some
concerns about the methodology as described in more detail below. The interpretation of the
results also needs a closer look.
Minor comments:
Abstract:
- describe your outcome in the method section.
- I would not include all the aOR and CI for the results. It’s very distracting to read this way.
Introduction:
- For the sentence “Conversely, 33 million unplanned pregnancies are estimated to occur
globally among women using any of the modern or traditional methods of contraception [10]”,
I believe the wrong reference was used since reference #10 is about Southern Ethiopia and not
a study on global estimates.
- On page 4, the Population Council, 2021 reference should be numerical as the other references.
Variables:
- In the Statistical analysis, there is no need to indicate the variable name for the weight variable
that is divided by 1 million. It would be sufficient to say that the analysis took into consideration
the sampling weight and survey design.
- The program is no longer called MeasureDHS but the DHS Program.
Results:
- Need to identify a results section after the ethical consideration section. Also, the ethical
consideration was repeated again at the end of the article. This same section was found in the
methods. I suggest deleted from the method section.
- The authors do not discuss the results of Model I. There may not be a need for Model I since
in Table 2 we see the associations between the variables and the outcome.
- Need to define LARCs in the variables section.
- Why was Angola chosen as the reference country?
Major comments:
Methods
- A 10-year range between the countries is relatively large. Contraceptive prevalence can change
greatly in 10 years. In addition, the contraceptive prevalence in these countries vary greatly. For
example, in Burkina Faso 2010 survey 15% of women used a modern method compared to 48%
in Rwanda. These countries can also vary greatly in their cultural norms and family planning
services and availability. Therefore, I am not convinced about pooling these countries for the
analysis. Alternatively, a sperate model can be fit for each country with a summary of the aORs
for the main indicators of interest. Another alternative is to create sub-regions of East Africa,
West Africa, and Southern Africa with more closely spaced surveys.
- The title of the paper indicates that this is a multilevel analysis, but this was not described in
the methods. What are the levels and how was the weights at each level computed? This appears
to be a pooled analysis. If that is the case, how did the authors calculate the pooled weight? Was
equal weight given to each country or was the weight proportion to the country sample size?
Variables
- Was the outcome variable obtained from the calendar data (https://www.dhsprogram.com/
data/Calendar-Tutorial/index.cfm) ? The authors should explain the calendar data
and how this information is collected from women. For DHS data, there is a
specific way to measure contraceptive discontinuation/continuation as described in
the Guide to DHS Statistics (https://www.dhsprogram.com/Data/Guide-to-DHS-Statistics/
index.htm#t=Contraceptive_Discontinuation.htm).  In addition, the unit of analysis should be
the women or the episodes as described in the calendar data and not the “Yes” responses.
- The wealth quintile is not a comparative wealth measure. The results of the wealth quintile
from a pooled analysis are not reliable. The wealth quintile is a data driven method constructed
for each survey. This is also probably why we see the unexpected results for the wealth index
in the adjusted model and the change from a higher odds among the higher wealth quintiles
in Model I to a lower odds in Model II. This variable should be removed from the model. A
comparative poverty measure can be used instead if desired.
Results
- The discussion of the logistic results does not indicate with the reference category is. For
instance, the richer and richest should say that this is compared to the lowest wealth quintile.
In addition, the categories for the wealth quintile should be: lowest, second, middle, fourth, and
highest. DHS no longer uses the terms poorest, poor, richer, or richest for the wealth quintile.
However, as discussed previously, it is not recommended for the wealth index to be used in the
model for a pooled analysis.