Title: Geospatial inequalities in women’s malnutrition in Pakistan
Version: 1 Date: 25 Apr 2024
Reviewer:  Bhaskar Tiwary
Reviewer's report:
This study holds significant importance in understanding the multifaceted dynamics of
malnutrition among women in Pakistan, shedding light on spatial disparities, socioeconomic
factors, and lifestyle influences contributing to varying forms of malnutrition. By employing
a Bayesian quantile regression approach and considering spatial effects, the research offers
nuanced insights into the prevalence and risk factors associated with severe thinness,
underweight, overweight, and obesity among women of reproductive age. Such comprehensive
understanding is crucial for informing targeted interventions, policy formulation, and public
health strategies aimed at addressing the complex challenge of malnutrition and promoting
women's health and well-being in Pakistan.
However, I have few queries before we accept this paper.
1. Could you elaborate on how the study accounts for the unique nutritional requirements of
pregnant and lactating women compared to non-pregnant and non-lactating women? How does
this approach contribute to more accurate estimations of malnutrition prevalence among women
in Pakistan?
2. You mentioned that the study utilized a Bayesian geo-additive quantile regression to assess
the spatial distribution and explore risk factors associated with various forms of malnutrition
in Pakistan. Could you provide insights into why this methodology was chosen and how it
enhances the understanding of malnutrition patterns compared to previous studies that may not
have considered spatial dependence?
3. Given the complex interplay of sociodemographic factors, dietary habits, and healthcare
accessibility influencing malnutrition among women in Pakistan, what are some key policy
implications that emerge from your research findings? How can policymakers effectively
address these risk factors to improve nutritional outcomes for women across different regions
in the country?
4. Could you provide insight into the rationale behind excluding pregnant women and those
within three months postpartum from the analysis? How might their exclusion impact the
generalizability of the findings, particularly considering their unique nutritional needs and
potential contribution to malnutrition patterns?
5. You mentioned using a Bayesian Quantile regression approach to examine the association
of explanatory variables with the entire conditional distribution of the response variable. Could
you elaborate on why this method was chosen over other regression techniques and how it
addresses the specific objectives of your study in assessing malnutrition patterns among women
in Pakistan?
6. The study utilized Gaussian Markov random fields (GMRF) to model spatial effects. How
does this approach enhance the analysis of spatial dependence in the context of malnutrition
prevalence among women? Additionally, what considerations were made in selecting and
implementing this method within the Bayesian inferential framework?
7. The study findings reveal significant associations between various sociodemographic factors
and the nutritional status of women in Pakistan. Could you discuss potential mechanisms
underlying these associations, particularly regarding factors such as education level, household
wealth, access to media, and sanitation facilities? How might these findings inform targeted
interventions to address malnutrition among women in different socioeconomic contexts?
8. Figure 1 provides spatial distribution maps indicating the estimates of severe thinness,
underweight, overweight, and obesity across different regions of Pakistan. Could you elaborate
on the implications of these spatial patterns for public health policies and programs aimed at
addressing malnutrition among women? How might the identification of geographical hotspots
of malnutrition help prioritize resource allocation and intervention strategies at the regional
level?
9. In your study, you found that women living in urban areas of Pakistan are more likely to
be overweight compared to those in rural areas, which is consistent with previous research.
Could you discuss potential urbanization-related factors contributing to this trend, such as
changes in dietary patterns, availability of processed foods, or sedentary lifestyles? How might
policymakers address these urban-specific challenges to mitigate the rising prevalence of
overweight and obesity among urban women?
10. Your findings suggest a significant association between women's education level and their
risk of experiencing different forms of malnutrition. Considering that education can influence
dietary choices and health behaviors, how might educational interventions be tailored to improve
nutritional awareness and promote healthy eating habits among women, particularly those with
lower education levels? What strategies could be effective in enhancing nutrition literacy and
empowering women to make informed dietary decisions?
11. The study highlights the impact of access to improved toilet facilities on women's likelihood
of being overweight or obese. Could you elaborate on the potential mechanisms underlying this
association? How might improvements in sanitation infrastructure contribute to better nutritional
outcomes for women, and what policy interventions could be implemented to ensure equitable
access to improved sanitation facilities, especially in low-income communities?
12. If you could also cite and refer the importance of spatial technqiues and nutrition from India
from these two studies,
- https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2021.667502/full
- https://link.springer.com/article/10.1007/s10708-021-10464-9