Title: Trends and Determinants of Adolescent Pregnancy: Results from Kenya Demographic
Health Surveys 2003–2014
Version: 2 Date: 09 Sep 2021
Reviewer:  Gebretsadik Shibre
Reviewer's report:
Background
-I think this section has been organized well.
Method
-Authors need to document the reason for restricting analysis to the 20-24 age cohort. How
have you selected the exposure variables; why do you not include other exposure variables than
included in the analysis. You need to also cite that similar literature were done using these
variables. How each of the variables were measured; particularly important is detailing the
procedure of wealth index construction in the DHS. I suggest you briefly discuss the sampling
procedure of the surveys. It is good if you put in the response rate, for both women and household
level.
Analysis
-I found the analysis procedure rather insufficient and do not reflect the data generating
process.  The KDHS data were collected through multi-stage clustered stratified process, so
the stratification, weighting and clustering, all the three design elements, must be taken into
cognizant during the analysis. In the abstract you mentioned that you used multi-level model,
but you used the conventional one level regression. Pls clarify the inconsistencies.
The authors examined the over time change of the pregnancy rate using p-value. This is not
the right research practice; you should not use p-value to see whether there is change. Null
hypothesis significance testing, NHST, has adequately been criticized and is on the verge of
being banned from research world as it has damaged science. I therefore recommend you to
rely heavily on estimation and confidence intervals. If the confidence intervals, for instance,
between 2008 and 2013 overlap, then you can possibly conclude that pregnancy rate has not
changed between the two time points. But, you falsely reported that there was a decreasing trend
by looking at a p-value. It is the right time to say no to NHST.  Pls read this: Full article: Moving
to a World Beyond “p < 0.05” (tandfonline.com). pls revise the interpretation of the findings
across all the five tables.
You did both separate analysis as well as pooled analysis. Why did you use both? I can argue,
with reasons, that the pooled analysis is better than the separate analysis and you can assess
the trend by looking at the coefficients of the 2008 and 2014 time points in reference to the
baseline. That tells you an adjusted trend, whether pregnancy rate has changed between 2003 and
2008, and 2003 and 2014. This can best be interpreted together with the descriptive pregnancy
coverage findings. So, I did not the importance of the separate regression analysis, and you are
required to justify this.
Relatedly, the most important thing in the pooled analysis is that, you are required to ensure
that the three design elements I described above, clustering, stratification and weighting, are all
UNIQUE in all the three data points. When more than one data time points are pooled from
a single country, it is likely that two survey points, for example 2003 and 2008, can have the
same name for different cluster. These two different clusters but with same name are treated by
the software as if they are the same. So, make sure that they are UNIQUE, you need to create
survey /year specific cluster, strata and weight.  For instance, you can create survey specific
cluster in STATA as egen new_strata=group (year old_strata). Here, the variable “year” has to
be created first in each survey. I recommend you to read the DHS user forum to see how this
can be done, if you did not have a methodologist around you to consult.
In the pooled analysis, how did you use weight. Since weights in DHS are survey-specific and
are normalized, you need to first deformalize the weight in the pooled data. Then, whether have
you weighted all the three DHS data equally or differently is nowhere discussed in your method.
This is an extremely useful step. Read the DHS data analysis guides and or consult someone on
this if you have problem in figuring this out.
Discussion
In the statement “………establish the socioeconomic determinants of pregnancy among
adolescents aged 15–19 years old”, you vowed to “establish” determinants of the pregnancy rate.
However, It is virtually impossible to do this from a single study.  Any study should be conducted
with contributing to future meta-analysis in mind. This is the recent “best” research practices.
Throughput your findings above and discussion too, be refrain from using the word “statistically
significant” as it has nothing to do with importance of the findings, as I said above already. Pls
read the material I shared with you. This the best opportunity for you to apply this best and
current research paradigm.
A statement about VIF has to be removed from this section and pasted onto the method section
above.
“……On the other hand, the trend in wealth quintile was not consistent with findings from
the regression analysis; the percentage of those in the fourth and highest wealth quintiles,
respectively, decreased from 39.6% in 2009 to 33.4% in 2014 and from 27.7% in 2009 to 23.2%
in 2014.” The reason for the inconsistencies is that, the result from the pooled analysis was
adjusted for the confounding variables, including the structural effect of time via year dummy.
Finally, the limitations of the manuscript have not been used to inform the findings of the study.
You just put the findings and limitations one after the other. But, the effect of the limitations
needs to be taken into account while interpreting your bottom-line findings; as it stands currently,
they are presented separately without the result being discussed in light of the extent of the effect
of the limitations.
Else, I found the discussion very intelligent.