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. 2022 Sep 29;17(9):e0273485. doi: 10.1371/journal.pone.0273485

Double burden of malnutrition in Nepal: A trend analysis of protein-energy malnutrition and High Body Mass Index using the data from Global Burden of Disease 2010–2019

Priza Pradhananga 1,*, Archana Shrestha 1,2,3, Nabin Adhikari 1, Namuna Shrestha 1, Mukesh Adhikari 3,4, Nicole Ide 5, Saurya Dhungel 6, Swornim Bajracharya 3, Anu Aryal 1,3,7
Editor: Pranil Man Singh Pradhan8
PMCID: PMC9521909  PMID: 36174008

Abstract

Background

The co-existence of undernutrition and overnutrition is a global public health threat. We aim to report the burden of both nutritional deficiency (Protein-Energy Malnutrition) and overweight (high Body Mass Index) in Nepal over a decade (2010–2019) and observe the changes through trend charts.

Methods

We did a secondary data analysis using the Institute for Health Metrics and Evaluation (IHME)’s Global Burden of Disease (GBD) database to download age-standardized data on Protein Energy Malnutrition (PEM) and high Body Mass Index (BMI). We presented the trend of death, Disability Adjusted Life Years (DALYs), Years of Life Lost (YLL), and Years Lost due to Disability (YLD) of PEM and high BMI in Nepal from 2010 to 2019 and also compared data for 2019 among South Asian countries.

Results

Between 2010 and 2019, in Nepal, the Disability Adjusted Life Years (DALYs) due to PEM were declining while high BMI was in increasing trend. Sex-specific trends revealed that females had higher DALYs for PEM than males. In contrast, males had higher DALYs for high BMI than females. In 2019, Nepal had the highest death rate for PEM (5.22 per 100,000 populations) than any other South Asian country. The burden of PEM in terms of DALY was higher in under-five children (912 per 100,000 populations) and elderly above 80 years old (808.9 per 100,000 populations), while the population aged 65–69 years had the highest burden of high BMI (5893 per 100,000 populations). In the last decade, the DALYs for risk factors contributing to PEM such as child growth failure (stunting and wasting), unsafe water, sanitation and handwashing, and sub-optimal breastfeeding have declined in Nepal. On the contrary, the DALYs for risk factors contributing to high BMI, such as a diet high in sugar-sweetened beverages, a diet high in trans fatty acid, and low physical activity, have increased. This could be a possible explanation for the increasing trend of high BMI and decreasing trend of PEM.

Conclusion

Rapidly growing prevalence of high BMI and the persistent existence of undernutrition indicate the double burden of malnutrition in Nepal. Public health initiatives should be planned to address this problem.

Introduction

The co-existence of undernutrition and overnutrition is a global public health threat. Adults with obesity are at increased risk of developing non-communicable diseases such as diabetes, hypertension, stroke, cardiovascular diseases, and some forms of cancer [1]. On the other hand, being underweight is linked with consequences such as premature mortality, infirmities, impaired intellectual development, and poor self-rated health and well-being [2]. In 2016, 1.9 billion adults aged 18 years and above were overweight or obese, whereas 462 million adults were underweight globally [3]. Around 33% of the world’s population suffers from at least one form of malnutrition like wasting, stunting, vitamin and mineral deficiencies, overweight, and obesity [4]. Along with the health impacts, malnutrition also has serious consequences on countries’ social and economic development. Mortality and morbidities due to malnutrition could cost almost US$3.5 trillion annually, of which US$2.5 trillion is covered by undernutrition and micronutrient deficiency while US$1.4 trillion by overweight and obesity-related non-communicable diseases, which have a direct loss in human capital and productivity [5].

This double burden of malnutrition has been observed in many developing countries, including countries in South Asia, including Nepal [6–9]. In South Asian countries, the prevalence of underweight among children aged 24 to 59 months was 37%, 38%, 19%, 28%, and 29% in Bangladesh, India, Maldives, Nepal, and Pakistan, respectively. The prevalence of overweight amongst children was higher in Pakistan (7%) and Maldives(9%) and lower in Nepal, India, and Bangladesh (between 2% and 4%) [10, 11]. The Global Nutrition Report estimated that 17.4% of female and 16% of male adults in Nepal were underweight in 2016, while 22.8% of females and 19.1% of male adults were overweight in the same year [12]. The National Demographic and Health Survey (NDHS) 2016 reported the prevalence of underweight as 19.2% and the prevalence of overweight as 18.2% among Nepali adults [13].

Historically, significant focus in Nepal has been given to curbing undernutrition due to its high prevalence, and overnutrition is not given much attention. The NDHS, which is done every five years, started collecting overweight measures only since 2016; also the NDHS 2021 report has not been published yet, so there are not enough data points to observe a trend [14]. In this study, we used the Global Burden of Disease(GBD) database to analyze the trend of undernutrition and overnutrition in Nepal over a decade (2010–2019). We used Protein-Energy malnutrition, a primary form of malnutrition in Nepali children [15], as a measure of undernutrition and high Body Mass Index (BMI) as a measure of overnutrition. We further analyzed the trend by gender and additionally compared the burden with other South Asian countries. The findings from this study will help to observe trends in both forms of malnutrition in Nepal and help policymakers develop comprehensive nutrition strategies in Nepal that address the double burden of malnutrition.

Methods

Data source

We did a secondary data analysis using the Institute for Health Metrics and Evaluation’s (IHME) Global Burden of Diseases (GBD) database available online through the GBD results tool. The GBD contains estimates of the burden of diseases, including incidence, mortality, prevalence, years of life lost due to premature mortality(YLL), years lived with disability (YLD), and disability-adjusted life years (DALY) of various illnesses and injuries for 195 countries. GBD defines high BMI in adults 20 years and older as BMI greater than 20–25 kg/m2 and in children 19 years and younger as being obese or obesity as per International Obesity Task Force standards. They define PEM as a health loss associated with moderate and severe acute wasting [16, 17]. The detailed description of metrics, data collection procedures, and analytical approaches used for GBD are reported elsewhere [18]. The data input source tool of GBD showed a total of 9 high BMI-related research articles and 4 PEM-related articles used to create GBD estimates for Nepal [19].

Analysis

We downloaded the estimates and their 95% confidence interval for age-standardized deaths, Disability-Adjusted Life Years (DALYs), Years of Life Lost (YLL), Years Lost to Disability (YLD), rates per 100,000 population for Protein Energy Malnutrition (PEM), and high Body Mass Index (BMI) for Nepal from 2010–2019 in.csv format. We repeated the same data extraction procedure for other South Asian countries as comparators, including India, Bangladesh, Bhutan, Pakistan, Sri Lanka, Maldives, and Afghanistan. We used Microsoft Excel to create tables and figures. The download data steps with our comparison analysis and charts are included in the S1 File.

In this article, we present the trend of death, DALYs, YLL, and YLD of PEM, and high BMI in Nepal from 2010–2019 and compare data of 2019 among South Asian countries. We also presented changes in DALYs due to various risk factors in Nepal from 2010 to 2019.

Results

Fig 1 illustrates the trend in DALYs for PEM and high BMI in Nepal. Between 2010 to 2019, the DALYs due to PEM is declining, while the DALYs due to high BMI are increasing. The DALYs for PEM has dropped from 390 per 100,000 population in 2010 to 208 per 100,000 population in 2019. Meanwhile, the DALYs for High BMI has increased steadily from 953 in 2010 to 1354 per 100,000 population in 2019. Sex-specific trends revealed that females had higher DALY for PEM than males in the past decade. In contrast, males had higher DALYs for high BMI than females in the past decade.

Fig 1. Trend of DALY for Protein Energy Malnutrition and High Body Mass Index in Nepal (2010–2019).

Fig 1

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Table 1 compares the death rate, DALYs, YLDs, and YLLs\ related to PEM and high BMI in Nepal with other South Asian countries. Although PEM was declining, Nepal had the highest death rate(5.22 per 100,000 population) for PEM than other South Asian countries. DALY for PEM in Nepal was slightly lower than the South Asia average but higher than Bangladesh, Bhutan, Sri Lanka, and the Maldives. With high BMI, Nepal had a higher death rate and DALY than Bangladesh and Maldives but lower than Bhutan, India, Pakistan, Sri Lanka, and Afghanistan. Among the South Asian countries, Pakistan had the highest DALYs (287.44 per 100,000) due to PEM, while Afghanistan had the highest death (177.28 per 100,000) and DALYs (5098.61 per 100,000) due to high BMI.

Table 1. DALY, YLL, YLD, Death for PEM and High BMI among South Asian countries (2019).

Protein Energy Malnutrition (PEM)
rates per 100,000 population (95% CI)		 High Body Mass Index (BMI)
rates per 100,000 population (95% CI)
Location Death DALY YLD YLL Death DALY YLD YLL
South Asia 1.68 (2.21–1.23) 217.60 (275.54–167.94) 106.91 (150.39–68.02) 110.68 (150.02–77.87) 52.0 (77.93–30.92) 1769.15 (2440.57–1043.51) 373.15 (571.24–215.54) 1356.58 (1945.68–812.62)
Nepal 5.22 (6.86–3.89) 208.01 (274.82–154.06) 45.94 (66.65–29.22) 162.06 (228.40–114.11) 42.14 (70.53–20.02) 1354.33 (2144.73–707.98) 310.15 (497.09–157.17) 1044.18 (1689.75–510.56)
Bangladesh 2.03 (2.70–1.42) 139.97 (193.56–98.33) 46.17 (65.07–29.04) 93.79 (144.50–55.63) 33.29 (56.83–15.18) 1149.48 (1836.28–590.90) 233.99 (389.63–117.07) 915.49 (1489.42–452.11)
Bhutan 0.51 (1.23–0.18) 83.61 (141.93–50.51) 46.83 (70.61–28.17) 36.77 (94.71–12.86) 55.74 (87.03–27.83) 1733.59 (2601.51–972.05) 385.60 (597.06–217.41) 1347.98 (2088.36–726.66)
India 1.18 (1.77–0.77) 208.04 (274.31–153.14) 125.37 (176.17–79.73) 82.67 (127.20–52.79) 51.59 (75.68–30.12) 1697.83 (2370.73–1015.12) 383.16 (585.03–223.20) 1314.66 (1909.49–784.11)
Pakistan 3.50 (4.84–2.40) 287.44 (388.80–209.55) 56.24 (79.84–36.34) 231.20 (327.84–154.47) 92.24 (141.10–51.29) 2777.63 (4165.90–1605.49) 447.23 (699.17–245.93) 2330.39 (3548.34–1308.63)
Sri Lanka 0.76 (1.01–0.57) 142.87 (196.35–96.13) 129.49 (183.10–81.61) 13.38 (17.94–10.01) 66.84 (104.80–36.77) 2073.38 (3078.99–1210.16) 659.88 (989.68–369.35) 1413.49 (2195.84–791.38)
Afghanistan 2.38 (3.61–1.57) 202.04 (300.72–137.94) 37.0 (52.28–23.27) 165.04 (262.13–102.69) 177.28(256.14–109.10) 5098.61 (7244.70–3230.86) 670.18 (985.84–413.34) 4428.42 (6447.93–2732.61)
Maldives 1.28 (1.61–0.98 185.89 (261.52–124.41) 161.83 (237.78–101.59) 24.06 (30.78–18.86) 35.54 (58.66–17.96) 1229.06 (1838.10–699.19) 376.09 (591.59–204.21) 852.97 (1307.06–467.49)
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Fig 2 presents the age-wise distribution of DALYs for PEM and high BMI in Nepal in 2019, respectively. The burden of PEM in terms of DALYs was higher in under-five children and elderly above 80 years old while lowest in 10–14 years old (40.6 per 100,000 population). The rate of PEM started to decrease in the population above five years but began to increase consistently after the age of 50. In the case of high BMI, children below 19 years had a low burden, while the population aged 65–69 had the highest burden (5893 per 100,000 population). The rate of high BMI is observed to increase with the increase in age.

Fig 2. Age-Wise distribution of DALY for PEM and High BMI in Nepal (2019).

Fig 2

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In Fig 3, we noticed a pattern of various contributing risk factors over the past decade in Nepal. Over the past decade, the DALYs for child growth failure (stunting and wasting), unsafe water, sanitation and handwashing, and sub-optimal breastfeeding, which are often associated with PEM, have declined. On the contrary, the DALYs for a diet high in sugar-sweetened beverages, a diet high in trans fatty acid, and low physical activity, which are often associated with high BMI, have increased.

Fig 3. Change in DALY due to various risk factors in Nepal between 2010–2019.

Fig 3

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Discussion

Using the GBD data, we examined the trend of malnutrition (both protein-energy malnutrition and high body mass index) for the past ten years in Nepal. The findings of our study provide evidence for the existence of a dual burden of malnutrition. The pattern of undernutrition is declining; however, a significant population is still underweight. Meanwhile, overweight and obesity are becoming dominant forms of malnutrition, indicating a shift in the nutritional trend.

Prior studies in South Asian countries show consistent findings of the double burden of malnutrition with our study. A Bangladeshi study showed that 30% of the adults were underweight, 18.9% overweight, and 4.6% obese [20, 21]. Likewise, in 2012–13, a study in Pakistan indicated 13% undernutrition and 25% overweight in women [22]. A study in India also suggested that the high prevalence of undernutrition coexisted with overweight and obesity [2].

Our results examined that the trend of undernutrition is declining in Nepal. This is in line with studies in India and Nepal that showed that underweight among adults decreased by almost 15% [2] and stunting in under-five children decreased by 18% in urban settings [23]. Between 2006 to 2016, the NDHS reported a declining stunting prevalence among Nepali children from 39% to 29% and wasting from 49% to 36%.

From 2010 to 2019, we noticed a sharp rise in the rates of overweight and obesity in Nepal and other South Asian countries. India also showed an increasing pattern of obesity [24, 25]. From 1980 to 2013, the rate of obesity in South Asia increased by 5% [26]. Prevalence of obesity among women of reproductive age also increased by 6.2% in Bangladesh, 8.5% in Nepal, and 4.2% in India from 1996 to 2006 [27].

The findings of our study are also important as they highlight that women are at a higher risk of being undernourished than men. Gender disparity is observed in previous studies, showing that globally, women are more likely to be undernourished [28–30]. In the context of developing countries like Nepal, women’s reproductive health, poverty, lack of education, low social status, low access to health and social services, household work patterns, gender disparities, and socio-economics disparities are the possible reasons for women’s vulnerability towards suffering from malnourishment [31]. Though our study showed higher BMI in males than females, a few studies comparing obesity across countries show contrasting findings that the prevalence of obesity is typically higher in females [32–34].

We have found that the older population above 80 years was at more risk of being underweight. Possible explanations for this include aging is associated with loss of appetite, decrease in taste and smell, less physical activity, psychological disorders, deteriorating dental health causing difficulty in eating a variety of food, and chewing problems that can interfere with nutritional status resulting in malnourishment [35]. Our study also showed that under-five children were at higher risk of undernutrition. The lesser the age of children, the higher the risk of undernutrition [36–38]. Children under 12 months were twice as likely to be stunted than children aged 24 to 36 months [37]. Low household income, mother’s educational status, antenatal checkup, the health-seeking practice of mothers, diarrhea and respiratory infections within one month of birth, and mother’s nutritional status have been cited as the major associated factors for under-five malnutrition [38, 39].

Our study is the first to identify the trends in the dual burden of malnutrition among Nepalese over an extended period. We acknowledge that a large-scale primary data collection effort would have been the best approach to capture this trend in Nepal. In the absence of such, we have attempted this analysis through the Global Burden of Disease database. Our study is able to show the trend but is limited to offering explanations for such trends. Additional studies on various risk factors contributing to malnutrition in Nepal will be needed to identify areas of intervention.

Policy implications

Our analysis has a few policy implications. First, observing the high burden of undernutrition, along with a rapidly increasing trend of DALYs associated with high BMI, the government and non-governmental key stakeholders should think of revising the existing policies to curb the double burden of nutrition in Nepal. Second, the increasing prevalence of overweight/ high BMI shows that either the current policies are ineffective or there is a lack of concrete policies and programs to support healthy lifestyle adoption for Nepali people. Since the risk for other chronic diseases and the subsequent costs associated with being overweight or obese are high, a low-income country like Nepal should timely intervene in this burgeoning problem. Third, with disparities associated with overweight and underweight being much starker by gender and age groups, there is a high need for targeted interventions. Fourth and more importantly, the concerned stakeholders should generate robust evidence on direct and indirect factors associated with overweight and underweight at federal, provincial, and local levels to effectively formulate policies to curb malnutrition at different levels.

Conclusion

Our study provides evidence for the co-existence of undernutrition and overnutrition in Nepal. Nepal is going through a nutritional transition where undernutrition is declining but still prevalent, while obesity/overweight is increasing steadily. Undernutrition is higher in females, while high BMI is higher in males. The prevalence of overweight/obesity is low in under-five children, but undernutrition remains highest in that age group. The dual burden of malnutrition is alarming and should be taken into consideration. Public health interventions should be planned to emphasize a healthy diet and lifestyle. Our findings also substantiate the need for nutritional strategies that address the situation of dual burden of malnutrition in Nepal.

Supporting information

S1 File

(XLSX)

Click here for additional data file. (29.7KB, xlsx)

Data Availability

Our study included use of aggregated third party data publicly available from the IHME GBD database. The Global Burden of Disease data are freely available to download from the GBD results tool (https://ghdx.healthdata.org/gbd-results-tool). A user account is not needed. Researchers can select the required year, sex, age group, location, metrics, measures, causes, and risk factors of their interest. Once the selections have been made, the data can be downloaded in CSV file format by providing a valid email address. When the file is ready for download, the website sends an email with the link to download the data. The downloaded data can easily be opened in Excel for analysis or other statistical software.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Pranil Man Singh Pradhan

24 Feb 2022

PONE-D-21-41047Double Burden of Malnutrition in Nepal: Analysis of Data from Global Burden of Disease for Trend in Protein-Energy Malnutrition and High Body Mass IndexPLOS ONE

Dear Dr. Pradhananga,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

Kind regards,

Pranil Man Singh Pradhan, M.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: No

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: PONE-D-21-41047: Double Burden of Malnutrition in Nepal: Analysis of Data from Global Burden of Disease for Trend in Protein-Energy Malnutrition and High Body Mass Index

This study is aimed to assess the coexistence of undernutrition and overnutrition among the Nepalese population over a period of 2010 to 2019 using data from the Institute for Health Metrics and Evaluation (IHME)’s Global Burden of Disease (GBD) database. Overall, this study found that undernutrition is exists but decreasing in trend, whilst overnutrition is rising gradually. The author(s) are addressing the most important public health issues in Nepal. I would recommend the following points which need to be improved before the manuscript is accepted for publication.

MAJOR COMMENTS

• The authors have not stated the sampled populations, inclusion criteria, and sampling strategy to select the desired number of samples from the GBD database. Therefore, sampling strategy and exclusion criteria are fundamentals of sampling strategy and need to be stated in the manuscript transparently and using complete and clear descriptions.

• Why author(s) did include all ages instead of using a certain target age group? That might have reflected the heterogeneity and large variation of data. In addition, physiologically there is more likely to be obese with an increase in age, whilst the undernutrition problem is more prevalent in under 5 children. Therefore, the findings of this study could be affected by this phenomenon.

• Overall, the method section needs to revise extensively. The methods section needs to be reported in a way that another research with access to the same database would be able to reproduce the (sub) sample used in this study. For instances, data extracting procedure, own sampling strategy for secondary data, description of study variables, and statistical analyses used for this study, etc.

• Since this study is not based on the multi-country analysis, why did the author(s) include the other south Asian country's data in the result? This is not in line with the study objectives.

• The entire paper could benefit from additional proofreading and grammatical correction to improve clarity and directness.

MINOR COMMENTS

Abstract

• Overall abstract section needs to be reformat like a background, methods, results, and conclusions.

• Replace the word “report” with “identify or examine”

• Description of results in the abstract is mostly subjective. It is recommended to include objective measures of the results in this section.

• I would recommended to write clear and concise conclusions with brief recommendation.

Background

• The authors start from the macro idea, contextualize, and even identify the problem. The section is finished with the justification and the main objective of the work, there are some concerns that have to be addressed.

• The authors should provide the tangible rationale of the study. Why does this study need to conduct? What is already known? What do new findings implicit? In the background, all these things need to be well addressed.

• In the sentence “This double burden of malnutrition has been observed in many developing countries including countries in South Asia, including Nepal [6–9]” of these citations, number 8 study is not conducted in South Asia. Please revise it.

Results

• In figure 2, along with the age-wise distribution of PEM and BMI, it would be better to present gender-wise too.

• Only subjective results are presented for table 3, it is recommended to write numbers too.

 

Discussion

• The overall discussion needs to be specific. It could be more concise by only mentioning of most important discussion.

References

Reformat all references with PLOS ONE referencing style and revise the references # 3, 9, 12, 14, 16,17,18, 20, 25, 32, 42 etc….

Reviewer #2: This is interesting paper that aims for trend analysis of PEM and BMI of Nepal using the data from global burden of disease. Although the research article made an early attempt on trend analysis, the content in the paper seems to be all over the place. The research paper appeared to explain a lot of stuff but data provided were limited. I think only way the research article could be made workable is by being more specified and detailed.

1. The basic guidelines of research paper submission need to be followed. There is no any line numbering. It would have been easier to give suggestion indicating the line number. Please check the submission guidelines

2. Title of the study and the content present in the paper do not match.

3. Methodology section is like nonexistent in the paper. There is no information about sample size, sampling strategy, inclusion and exclusion criteria of the study. There is no information on any predictor or outcome variable while discussion section is filled with various predictors of high BMI and PEM. How was the statistical analysis done? The questions like: How were the data extracted and what software was used for analysis, remain unanswered. Methodology need to be explained well enough to make the paper more transparent and meet the criteria of replicablility.

4. BMI and PEM are quantitative variable. They require objective measurement and still they are prone to various errors. BMI and PEM are age sensitive. It would be interesting if the researcher had explained specifically on how information on PEM and BMI were assessed in GBD studies. Also, please provide clear operational definition of PEM and BMI.

5. The discussion section in research paper is basically based on findings of the research study and then one can explain how they fit with existing research and theory. The discussion in this research study is completely out of context. The aim of the study is trend analysis while discussion section was all about factors associated with BMI and PEM. In the discussion section, defend the findings of your own study than explaining results of other studies. Target population in the study is too wide/ vague.

6. The referencing style does not follow the guidelines given by PLOS ONE. For instance, reference number 18 is about a research article while in the reference section only URL is copy pasted. Please recheck your reference section.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Dev Ram Sunuwar

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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PLoS One. 2022 Sep 29;17(9):e0273485. doi: 10.1371/journal.pone.0273485.r002

Author response to Decision Letter 0

24 Apr 2022

Reviewer #1

MAJOR COMMENTS

1. The authors have not stated the sampled populations, inclusion criteria, and sampling strategy to select the desired number of samples from the GBD database. Therefore, sampling strategy and exclusion criteria are fundamentals of sampling strategy and need to be stated in the manuscript transparently and using complete and clear descriptions.

● Response: Thank you for this comment. This is a secondary data analysis using Global Burden of Disease database. To add clarity to the readers we have now divided the methods section into two subsections- ‘data source’, and ‘analysis’, and have included additional details.

2. Why did the author(s) include all ages instead of using a certain target age group? That might have reflected the heterogeneity and large variation of data. In addition, physiologically there is more likely to be obese with an increase in age, whilst the undernutrition problem is more prevalent in under 5 children. Therefore, the findings of this study could be affected by this phenomenon.

● Response: We used age standardized rates for overall trend analysis. We understand age-wise variation is important in case of malnutrition and high BMI, and have presented age wise distribution of DALY for both in the figure 2.

3. Overall, the method section needs to revise extensively. The methods section needs to be reported in a way that another research with access to the same database would be able to reproduce the (sub) sample used in this study. For instances, data extracting procedure, own sampling strategy for secondary data, description of study variables, and statistical analyses used for this study, etc.

● Response: Based on your comment #1, and this comment, we have revised the structure of our methods section. We have provided the link to the website where the data was downloaded from, specified the indicators, year, country, and measures (rate per 100,000) which ensures reproducibility of our analysis.

4. Since this study is not based on the multi-country analysis, why did the author(s) include the other south Asian country's data in the result? This is not in line with the study objectives.

● Response: We included results from other South Asian countries to compare where Nepal stands. We mentioned this in line 83 in the introduction section, and in line 104 in the methods section.

5. The entire paper could benefit from additional proofreading and grammatical correction to improve clarity and directness.

● Response: Thank you for your comment. We have extensively copy edited the manuscript this time around.

MINOR COMMENTS

Abstract

6. Overall abstract section needs to be reformatted like a background, methods, results, and conclusions.

● Response: Thank you for this helpful note. We have now added those subsections in the abstract.

7. Replace the word “report” with “identify or examine”

● Response: We have edited it in the new version.

8. Description of results in the abstract is mostly subjective. It is recommended to include objective measures of the results in this section.

● Response: We have added numbers in the results section in the current revised manuscript.

9. I would recommended to write clear and concise conclusions with brief recommendation.

● Response: Thank you. We have edited our conclusion section.

Background

The authors start from the macro idea, contextualize, and even identify the problem. The section is finished with the justification and the main objective of the work, there are some concerns that have to be addressed.

10. The authors should provide the tangible rationale of the study. Why does this study need to conduct? What is already known? What do new findings implicit? In the background, all these things need to be well addressed.

● Response: We revisited the introduction section and made minor changes. Overall we felt it does answer questions raised by the reviewer.

11. In the sentence “This double burden of malnutrition has been observed in many developing countries including countries in South Asia, including Nepal [6–9]” of these citations, number 8 study is not conducted in South Asia. Please revise it.

● Response: We have revised the above mentioned reference.

Results

12. In figure 2, along with the age-wise distribution of PEM and BMI, it would be better to present gender-wise too.

● Response: We have presented gender wise differences in the trend in PEM and high BMI in figure 1 already.

13. Only subjective results are presented for table 3, it is recommended to write numbers too.

● Response: We do not have a Table 3, but we assumed you meant figure 3. Based on your feedback we added values for each bar in the graph.

Discussion

14. The overall discussion needs to be specific. It could be more concise by only mentioning of most important discussion.

● Response: We have extensively edited the discussion section in response to reviewers’ comments.

References

15. Reformat all references with PLOS ONE referencing style and revise the references # 3, 9, 12, 14, 16,17,18, 20, 25, 32, 42 etc….

● Response: Thankyou for addressing it. We have extensively revised the references section.

—-------------------------------------------------------------------------------------------------------------------

Reviewer #2:

1. The basic guidelines of research paper submission need to be followed. There is no any line numbering. It would have been easier to give suggestion indicating the line number. Please check the submission guidelines

● Response: We appreciate the note, and have added line numbers in the revised version of the manuscript.

2. Title of the study and the content present in the paper do not match.

● Response: Based on your feedback we have edited the title in this revised version.

3. Methodology section is like nonexistent in the paper. There is no information about sample size, sampling strategy, inclusion and exclusion criteria of the study. There is no information on any predictor or outcome variable while discussion section is filled with various predictors of high BMI and PEM. How was the statistical analysis done? The questions like: How were the data extracted and what software was used for analysis, remain unanswered. Methodology need to be explained well enough to make the paper more transparent and meet the criteria of replicablility.

● Response: Thank you for this comment. This is a secondary data analysis using Global Burden of Disease database. To add clarity to the readers we have now divided the methods section into two subsections- ‘data source’, and ‘analysis’, and have included additional details. In this revised version we have now provided the link of website where the data was downloaded from. We have specified the indicators, year, country, and measures (rate per 100,000) which ensures reproducibility of our analysis.

4. BMI and PEM are quantitative variable. They require objective measurement and still they are prone to various errors. BMI and PEM are age sensitive. It would be interesting if the researcher had explained specifically on how information on PEM and BMI were assessed in GBD studies. Also, please provide clear operational definition of PEM and BMI.

● Response: We agree that BMI and PEM are age sensitive, and thank you for pointing that out. We have now edited the methods section and have specified methods for age groups (>=20 years, and <=19years) for BMI.

About operational definition, unfortunately because it is a secondary data analysis using GBD data, we could only use the definition provided by the GBD.

In lines 80-82 we have clarified that we used PEM and high BMI as proxy indicators for undernutrtion and overnutrition. “We used Protein-Energy malnutrition, a primary form of malnutrition in Nepali children[15] as a measure of undernutrition, and high body mass index (BMI) as a measure of overnutrition.”

5. The discussion section in research paper is basically based on findings of the research study and then one can explain how they fit with existing research and theory. The discussion in this research study is completely out of context. The aim of the study is trend analysis while discussion section was all about factors associated with BMI and PEM. In the discussion section, defend the findings of your own study than explaining results of other studies. Target population in the study is too wide/ vague.

● Response: We have extensively edited the discussion section in response to reviewers’ comments.

6. The referencing style does not follow the guidelines given by PLOS ONE. For instance, reference number 18 is about a research article while in the reference section only URL is copy pasted. Please recheck your reference section.

● Response: Thank you for raising this. We have edited the references section in the current revised manuscript. We hope that we satisfyingly addressed them.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (13.6KB, docx)

Decision Letter 1

Pranil Man Singh Pradhan

27 Jun 2022

PONE-D-21-41047R1Double Burden of Malnutrition in Nepal: A trend analysis of Protein-Energy Malnutrition and High Body Mass Index using the data from Global Burden of Disease 2010-2019PLOS ONE

Dear Dr. Pradhananga,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Aug 11 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Pranil Man Singh Pradhan, M.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Double Burden of Malnutrition in Nepal: A trend analysis of Protein-Energy Malnutrition and High Body Mass Index using the data from Global Burden of Disease 2010-2019

Manuscript ID: PONE-D-21-41047R1

There are major issues with this manuscript as at present stage which has to be addressed.

1. Methodology: Transparency and thoroughness are essential in reporting, since it is strongly advised to not leave readers in the shadows about the procedure. All we know that author(s) have used secondary data from GBD database. However, things is GBD database contains large data with various information. The concern is how did you sample the required data, and how did you perform all these analyses? Therefore, sampling strategy, robust statistical analysis, software used for data analysis needs to be reported in a way that another research with access to the same database would be able to reproduce the (sub) sample used in this study. In this case here, that does not seem feasible. Therefore, it is strongly recommended that the authors clearly and transparently describe their methodology with complete sentences either within the main text or in the supplementary materials.

Reviewer #2: It’s disappointing that guidelines that need to be followed in journal submission are not followed even when pointed out priory. There is no line numbering in the PDF version that I received. It would be really convenient to provide suggestions. In the discussion section in page no. 7 last line you have mentioned and I quote here, ”This double burden of malnutrition is observed in almost every part of the world.” By providing references of 3 south Asian countries I don’t think you can extrapolate the findings to prevail in entire world. You need to backup such sentences with more references from various corners of world.

The major issue I find in the study is the methodology section. It needs to be more extensive. It is mentioned that it is secondary data analysis research but in page no. 3 in analysis section you have indicated that you just downloaded the estimate and their CI and further no any statistical analysis was done. Without any statistical analysis of your own and methodologies that is not transparent and that can’t be followed by future researchers to replicate similar studies in different regions or settings, I find very little significance of this study .

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2022 Sep 29;17(9):e0273485. doi: 10.1371/journal.pone.0273485.r004

Author response to Decision Letter 1

28 Jul 2022

Reviewer #1

There are major issues with this manuscript as at present stage which has to be addressed.

1. Methodology: Transparency and thoroughness are essential in reporting, since it is strongly advised to not leave readers in the shadows about the procedure. All we know that author(s) have used secondary data from GBD database. However, things is GBD database contains large data with various information. The concern is how did you sample the required data, and how did you perform all these analyses? Therefore, sampling strategy, robust statistical analysis, software used for data analysis needs to be reported in a way that another research with access to the same database would be able to reproduce the (sub) sample used in this study. In this case here, that does not seem feasible. Therefore, it is strongly recommended that the authors clearly and transparently describe their methodology with complete sentences either within the main text or in the supplementary materials.

Response: We have attached a supplement with step-by-step guidance for any future researchers interested to replicate this study. Hope that satisfies the reviewer’s concern on transparency.

Reviewer #2

It’s disappointing that guidelines that need to be followed in journal submission are not followed even when pointed out priory. There is no line numbering in the PDF version that I received. It would be really convenient to provide suggestions. In the discussion section in page no. 7 last line you have mentioned and I quote here, ”This double burden of malnutrition is observed in almost every part of the world.” By providing references of 3 south Asian countries I don’t think you can extrapolate the findings to prevail in entire world. You need to backup such sentences with more references from various corners of world.

The major issue I find in the study is the methodology section. It needs to be more extensive. It is mentioned that it is secondary data analysis research but in page no. 3 in analysis section you have indicated that you just downloaded the estimate and their CI and further no any statistical analysis was done. Without any statistical analysis of your own and methodologies that is not transparent and that can’t be followed by future researchers to replicate similar studies in different regions or settings, I find very little significance of this study.

Response: Sorry that the pdf version you received didn’t show line numbers. We were diligent not to miss it this time. Hope the current revised version you received appeared with line numbers.

• We agree that the sentence extrapolating to the “world” is an over-reach with references from South Asia only. So we have removed it, and the paragraph now talks about South Asia only.

• We however respectfully disagree with reviewer #2’s sentiment that by using GBD estimates our study has “very little significance”. Yes, GBD data are already analyzed estimates from a third party (IHME). But, numbers alone don’t tell the story, thus GBD database is widely used by researchers worldwide to answer relevant research questions on their topic, country, and region of interest, and numerous publications have come out of those endeavors. As chronic disease researchers in Nepal, we see double malnutrition and its trend to be a highly relevant and important topic to look at with a very reliable data source and discuss the relevance to our country. We have additional faith in the GBD database for use in Nepal because of the collaboration with Nepal Health Research Council (http://nhrc.gov.np/projects/estimating-burden-of-disease-for-nepal-using-globally-used-methods/). We strongly believe that by writing this paper with relevant background, presenting data in useful tables and visuals, and discussing the relevance of findings for Nepal, we have provided a significant scientific contribution in the field.

• To address the reviewer’s comment about methodology transparency, we have added a tab in the supplement file named “steps”, and mentioned step by step procedure to download for “future researchers to replicate similar studies in different regions or settings”. We also added a sentence about that supplement in the main text also. We hope this satisfies the reviewer’s concern

Attachment

Submitted filename: Response.docx

Click here for additional data file. (6.8KB, docx)

Decision Letter 2

Pranil Man Singh Pradhan

10 Aug 2022

Double Burden of Malnutrition in Nepal: A trend analysis of Protein-Energy Malnutrition and High Body Mass Index using the data from Global Burden of Disease 2010-2019

PONE-D-21-41047R2

Dear Dr. Pradhananga,

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Pranil Man Singh Pradhan, M.D.

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PLOS ONE

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Acceptance letter

Pranil Man Singh Pradhan

21 Sep 2022

PONE-D-21-41047R2

Double Burden of Malnutrition in Nepal: A trend analysis of Protein-Energy Malnutrition and High Body Mass Index using the data from Global Burden of Disease 2010-2019

Dear Dr. Pradhananga:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Pranil Man Singh Pradhan

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

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    Data Availability Statement

    Our study included use of aggregated third party data publicly available from the IHME GBD database. The Global Burden of Disease data are freely available to download from the GBD results tool (https://ghdx.healthdata.org/gbd-results-tool). A user account is not needed. Researchers can select the required year, sex, age group, location, metrics, measures, causes, and risk factors of their interest. Once the selections have been made, the data can be downloaded in CSV file format by providing a valid email address. When the file is ready for download, the website sends an email with the link to download the data. The downloaded data can easily be opened in Excel for analysis or other statistical software.

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