Title: Magnitude of sugar-sweetened beverage consumption and associated factors among
women aged 15-49 years old in two Sub-Saharan African Countries
Version: 1 Date: 16 Aug 2023
Reviewer's report:
Globally, I read this interesting paper with a lot of interest! This paper evaluates the factors
associated with having drink SSB in women from Kenya and Burkina. It’s one of the first, and
I’m sure it will lead to further research in this area in part of the world where it’s lacking. It’s
also helps better understand the Nutrition transition stage of these 2 countries, which is very
interesting to predict the health future! I have a major concern about the fact that the paper is
based on a 1-day question about SSBs consumption. Thus, I suggest that the authors rephrase
and moderate their findings and acknowledge that as a limitation. Also, I suggest that the authors
reshape the title as they are not estimating the “SSB consumption”.
In addition, a lot of work is needed in the discussion. Finally, from my point of view,
the conclusion is not correct: targeting intervention or policy toward the high-income/
socioeconomic group will not curb the rise in morbidity and mortality but will increase
inequalities. Please find my detailed comments below. Good luck to the authors, I am sure that
this will lead to a great paper.
Abstract:
Background: the authors must add their aim/objective.
Methods:
- You should clearly state the meaning of IPUM-PMA
- We need more information about the study, as at least the year(s) and how the SSBs intakes
have been calculated (at least explained that is a specific question). If you exceed the number
of words, you can delete the L26-28.
Results: should be reshaped. It’s hard to read as you are mixing the socio-demographic
characteristics (e.g., education, employment, wealth score) and other diet characteristics. Also,
as we don’t know the references, we can’t understand the results.
Conclusion: do your results really call for targeting middle-income groups? Even the high, its
mostly a call to target women from high socio-economic classes, no?
Background: The introduction needs to be reshaped.
Opening on the definition is weird. This is mostly methodology, not really a background
underlining the need for your analysis. Also, ref 1 and 2 are not providing def of SSB. Please
find better references.
L61-64: once again, everything is mixed. You should talk separately about the socioeco/demo
characteristics, and then the health ones (obesity, perceived overweight), and then the diet ones.
Are you sure about the fruit consumption though? I not that just link to the fact that your
definition of SSBs includes fruit juice?
Overall, I will better detail that section (l61-64), put better references, and maybe made a part
about the overall characteristics, including in the high-income country, and then do a specific
sentence(s) about the previous findings in Burkina and Kenya, or Africa.
L69: how can surveys on women only can be representative?
Methods: we cannot employ “cross sectional study design” to analyses data… you need to
rephrase. Also is not clear if IPUMS-PMA is the name of the data, or the project. Same with
PMA 2020. It’s also unclear how PMA2020 can have data from 2017-2018. Please make this
clearer in the manuscript.
What was the primary aim/objective of the data collection?
L90-93 and L95-97: same sentence twice. As the same methods applies to both countries, just
say so after detailing the EAs for each country.
The ref 29 and 30 should be mentioned when detailing the EAs.
Can the author explain why they are adjusting for savory and fried snack consumption?
Same question about dietary diversity?
Why included age in continuous? It seems that using children and adults in the same way in
the analysis.
Also, for what I understand, women and child of each household have been both included in the
data collection, right? Thus, how do you take into account that in your model, as you included
women 10 to 40? Does it why you are using mixed-effect logistic regression? Please better
explain that.
For the educational status, how do you take into account women still in the education process?
For employment: thus, when you are unemployed, it can be because you are 10-year-old and
still in school right? Thus, the interpretation of the results association with employment status
should be a bit different, isn’t it?
Why use pregnancy in your models? The number of pregnant women is low and can impact the
regression. Plus, in studies, we are often excluding pregnant women considering their intakes
as non-representatives.
Please provide more information about the wealth index used.
Please better describe MDD.
Can you use the 2 different datasets (Burkina and Kenya) without declaring them prior to the
analysis? I mean, you are using weights and strata. Do you not need to have something related
to the country?
Also, does the results are the same stratified by country? Does the women had the same SSBs
intakes in both countries?
Why not include obesity or BMI in your model?
Results:
We need information on the women excluded because of missing data.
Also, does these missing data are not related to age? (i.e., more missing information about the
employment status for the kids?)
You say that half of the women consumed SSBs. But, in the survey, the question is only about
one day (i.e., yesterday), so I will be more careful with the interpretation and generalisation, and
I will acknowledge that as a limitation.
Please add CI to your figure 1.
L181: you state higher consumption of SSBs in women with the highest HH income: compare
to who?
L190-196: please refer to Table 2. Same for multivariable paragraph.
You will need to rephrase your multi-variable results. Indeed “higher odds of SSBs
consumption” is not clear. Maybe something like more likely to consume SSBs.
209-212: very wrong interpretation of the results. An OR of 0.78 does mean a 78% decrease!!!
Discussion:
Lack of 2-3 sentences reminding the overall results before discussing it.
Also, the discussion should be improved. For example, the study finding that almost 50% of
Kenyan and Burkina-Fasso’s women having SSBs don’t agree with an increased trend in SSBs
consumption. For what we know, it may be the case for 10 years now (even if I get the point).
Also, you are not showing any magnitude of SSBs consumption.
Then, can you not rather compare that to other African studies? Or at least more comparable
studies that an Australian in adults drinking prepackages drinks containing free sugar (hardly
comparable to your definition of SSBs) or Michigan overweight or obese PREGNANT women.
Can you better describe the India study? The SSBs definition, the population? Also put a ref.
L232-239: I am totally disagreeing. The fact that you are observing a higher SSB frequency
in women from high SES is due to the change in social gradient in health in food, observed
worldwide. You should read about the nutrition transition (especially Popkin papers), and
the epidemiological transition. This phenomenon has been observed worldwide, especially for
nutrition: high intake of “bad” foods in high SES and then a switch towards the lower SES (due
to price, habits etc) while the high SES increases their intake of “healthy” food.
Thus, you can not compare to Michigan. If you don’t find literature about SSBs directly, please
refer to the one about fast-foods, diet quality, UPF, sugar intakes etc.
L251-255: this is better. You should build on that and go deeper.
You need to acknowledge all your limitations: the way of measuring SSB consumption, the
potential recall bias or the social desirability bias, etc.
Does the study is representative? Or do you have more urban or rural participants?
Finally, your needs to discuss the policy / public health impacts of your findings as you are
mentioning that in your conclusion.
Conclusion: results for women from 2 sub-Saharan countries can not be generalised to Africa.
Also, I'm still not convinced that your analysis proved results about SSBs consumption.
A conclusion should conclude, not remind all results. “Tailored XX targeting women from high
socioeconomic classes will help to curb xxx”
Finally, as previously said, I’m really not sure that targeting the high socioeconomic classes will
help… indeed, as observed worldwide, soon, the low socioeconomic classes will see their SSBs
consumption increase. By targeting the high SEP, you will just decrease the demand for SSB,
then the price will decrease which will help increase the SSB intake in the low SEP. But I will
be happy if the authors can better defend their position.
Other suggestions:
Overall, the authors should be more careful and delete the double space, and the unneeded space
before the dots.
- L20: delete space before the dot.
- L21: replace sugar sweetened beverages by SSBs as you have defined it previously. Do the
same for the entire abstract, you will gain words.
- L22-24: lack of flowing here. You should restructure, or at least say “However, there is a
paucity, XXX, thus, we aimed at XX”
- Abstract Results
o Defined AOR
o Be consistent: either 95%CI or 95% CI but be consistent across the abstract and the entire
manuscript.
o Space should be after the coma, not before “ ,”
- L45 space between the word and the reference or not, but be consistent thorough the manuscript.
- L88 and l89: you are defining twice EA. Delete the second one, and add an s to the first.
- Numbers: you are using the coma for the thousand (2,411), either not (as in the results). Please
be consistent.
- L106: SSBs
- L171: make it clearer that 15-33 is the itr. “the median age (iqr)” is not clear enough.
- L173: 6.20% and delete bracket
- T1: specify the meaning of CI
- T1: delete “(4 categories)”
- T1: first 2 sum of the percent not egal to 100.
- T1: 6.20 not 6.2
- T1: putting “HH Characteristics” more left (aligned with weath, not his lowest)
- T1: delete the last row, total=100.
- L182: harmonised the number of digits
- F1 and T2 titleS: need to add the survey names and dates, + number of participants.
- T2: add footnote with abbreviations + be more specific about COR being the bi and AOR
being the multi.
- Results: when you state the AOR in the sentence, do not put it back in the brackets
- L200-201: you said 3 time 1.22
- L220: when, where? And it’s only from a 1 day question