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. 2024 Jun 27;18(6):e0012248. doi: 10.1371/journal.pntd.0012248

Is the rise in childhood obesity rates leading to an increase in hospitalizations due to dengue?

Chandima Jeewandara 1,#, Maneshka Vindesh Karunananda 1,#, Suranga Fernando 2,#, Saubhagya Danasekara 1, Gamini Jayakody 2, Segarajasingam Arulkumaran 2, Nayana Yasindu Samaraweera 2, Sarathchandra Kumarawansha 2, Subramaniyam Sivaganesh 2, Priyadarshanie Geethika Amarasinghe 2, Chintha Jayasinghe 2, Dilini Wijesekara 2, Manonath Bandara Marasinghe 2, Udari Mambulage 2, Helanka Wijayatilake 2, Kasun Senevirathne 2, Aththidayage Don Priyantha Bandara 2, Chandana Pushpalal Gallage 2, Nilu Ranmali Colambage 2, Ampe Arachchige Thilak Udayasiri 2, Tharaka Lokumarambage 2, Yasanayakalage Upasena 2, Wickramasinghe Pathiranalage Kasun Paramee Weerasooriya 2; Seroprevalence study group1,, Graham S Ogg 3,‡, Gathsaurie Neelika Malavige 1,3,‡,*
Editor: Amy C Morrison4
PMCID: PMC11210816  PMID: 38935620

Abstract

Background

Obesity and diabetes are known risk factors for severe dengue. Therefore, we sought to investigate the association of obesity with increased risk of hospitalization, as there is limited information.

Methods and findings

Children aged 10 to 18 years (n = 4782), were recruited from 9 districts in Sri Lanka using a stratified multi-stage cluster sampling method. Details of previous admissions to hospital due to dengue and anthropometric measurements were recorded and seropositivity rates for dengue were assessed. The body mass index (BMI) centile in children aged 10 to 18, was derived by plotting the values on the WHO BMI-for-age growth charts, to acquire the percentile ranking.

Results

Although the dengue seropositivity rates were similar in children of the different BMI centiles, 12/66 (18.2%) seropositive children with a BMI centile >97th, had been hospitalized for dengue, compared to 103/1086 (9.48%) of children with a BMI centile of <97th. The logistic regression model suggested that BMI centiles 50th to 85th (OR = 1.06, 95% CI, 1.00 to 1.11, p = 0.048) and BMI centile of >97th (OR 2.33, 95% CI, 1.47 to 3.67, p = 0.0003) was significantly associated with hospitalization when compared to children in other BMI categories.

Conclusions

Obesity appears to be associated with an increased risk of hospitalization in dengue, which should be further investigated in longitudinal prospective studies. With the increase in obesity in many countries, it would be important to create awareness regarding obesity and risk of severe disease and hospitalization in dengue.

Author summary

Although obesity and diabetes are known risk factors for severe dengue, there is limited information on whether they are risk factors for increased hospitalization due to dengue. To investigate this, we studied the association of obesity with hospitalization rates for dengue, in children aged 10 to 18 years (n = 4782), who were recruited from 9 districts in Sri Lanka using a stratified multi-stage cluster sampling method. Details of previous admissions to hospital due to dengue and anthropometric measurements were recorded and seropositivity rates for dengue were assessed. The body mass index centile (BMI) in children aged 10 to 18, was derived by plotting the values on the WHO BMI-for-age growth charts, to acquire the percentile ranking. We found that BMI centiles 50th to 85th and BMI centile of >97th were significantly associated with hospitalization rates when compared to children in other BMI categories, which should be further investigated in longitudinal prospective studies.

Introduction

Dengue is a climate sensitive infection, which was named as 1 of the top 10 threats to global health by the WHO in 2019 [1]. The incidence of dengue is markedly rising in many endemic countries, due in part to intense circulation of multiple dengue virus (DENV) serotypes, increase in global temperatures and erratic rainfall, rapid urbanization and population expansion [2]. Three hundred and ninety million individuals are thought to be infected with the DENV annually, resulting in 100 million symptomatic dengue infections [3]. Although symptomatic dengue is estimated to occur in 1 in 4 of those who are infected with the virus, many studies have reported a wide variability in the ratio of symptomatic: asymptomatic dengue infections. For instance, from 1 in 1.1 to 2.9 in 2004 to 2007 in Thailand [4], 1 in 6.1 in 1980 to 1981 in Thailand [5], 1 in 6 to 13 in Nicaragua [6] and more recently 1 in 1.5 in Indonesia [7]. These differences could be due to different factors such as differences in the virulence of the virus, intense transmission resulting in an increased number of secondary dengue infections associated with a higher risk of severe disease, the interval between infection with different DENV serotypes and host factors [8]. However, there is limited information if host factors such as the presence of comorbidities increase the likelihood of symptomatic infection leading to hospitalizations.

Sri Lanka has experienced dengue outbreaks for over 3 decades, with the incidence rising over time as seen in many countries [9]. The reported cases in Sri Lanka reflects the number of patients who are clinically diagnosed as having dengue and who are hospitalized [9]. In Sri Lanka, as in many other countries, point-of care diagnostic tests such as the dengue NS1 antigen test, or confirmatory tests such as quantitative real-time PCR is not done in public hospitals, due to the non-availability of such tests [10]. Therefore, those who present to out-patient departments with symptomatic dengue infections, who do not require hospitalization are not included in the reported number of cases. The prevalence of diabetes has markedly increased in Sri Lanka, especially in the Western province, where the prevalence of diabetes as risen from 5.02% in 1990, 16.4% in 2006, 27.6% by 2015 to 29% in 2019 [9, 11]. The prevalence of obesity among children also rose from 6.43% in 2003 to by 9.85% 2013, in Colombo, Sri Lanka [9]. Approximately 50% of dengue infections in Sri Lanka are reported from the Western province, which has seen a marked rise over time [9]. Although there could be multiple factors that led to this rise, such as changes in dengue transmission, evolution of the DENV leading to increased virulence, climate change and an increased proportion of those experiencing a secondary dengue infection [10], many host factors could have played a role. For instance, the presence of comorbidities such as obesity, diabetes and renal disease increases the risk of developing severe dengue [8, 12]. As obesity and diabetes are risk factors for occurrence of severe disease, it is possible that they could also lead to an increase in symptomatic/ apparent infection in those infected with the DENV and lead to increase in hospitalizations.

Although obesity is a known risk factor for severe dengue in hospitalized patients [13, 14], whether obesity is a risk factor for an increase in hospitalizations has not been studied. Given the marked rise in obesity, in order to adopt suitable control strategies for dengue, it would be important to find out if obesity indeed increases the risk of hospitalization. Therefore, we investigated if obesity is associated with an increased risk of hospitalization in a large cohort of Sri Lankan children, in an island-wide dengue sero-surveillance study.

Methods

Ethics statement

Ethics approval was obtained from the Ethics review committee of University of Sri Jayewardenepura and administrative clearance was obtained from the Ministry of Health Sri Lanka. Informed written consent was obtained from the parents or guardians and assent was obtained from all children. Approval number COVID 12/21.

Study participants and sampling technique

We carried out an island-wide dengue serosurvey in 4782 school children between the age of 10 and 18 years, who were attending public or private schools in Sri Lanka, during September 2022 to 31st March 2023 [15]. Briefly, healthy children without any comorbidities were recruited following informed written consent from the parents/guardians and assent was taken from children (Table 1). The study was carried out in 9 districts in Sri Lanka, representative of each of the 9 provinces (Fig 1). A stratified multi-stage cluster sampling method was used to select the schools in each district, with a cluster size of 40 students from each cluster. A probability proportionate to the size (PPS) sampling technique was used to select the sample size from each district, as the population size and urbanicity grade varied in different districts. The schools were classified as based in urban, rural or estate areas (tea plantation areas in central highlands) based on the classification from the latest census for Sri Lanka [16].

Table 1. Summary of the demographics of the study population.

Number of Children
Age
10 494
11 558
12 544
13 584
14 577
15 605
16 588
17 178
18 654
Total 4782
Gender
Male 2240
Female 2542
Total 4782
Seropositivity
Negative 3500
Equivocal 130
Positive 1152
Total 4782
Urbanization
Urban 840
Rural 3772
Estate 170
Total 4782
Hospitalized for Dengue
Yes 115
No 4600
Total 4782
BMI Centile
<3rd 1057
3rd-15th 939
15th-50th 1298
50th-85th 862
85th-97th 411
>97th 215
Total 4782
District
Trincomalee 236
Polonnaruwa 231
Jaffna 297
Matara 436
Badulla 478
Ratnapura 465
Kandy 608
Kurunegala 757
Gampaha 1274
Total 4782
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Fig 1. A map of Sri Lanka showing the locations of recruitment of children from the 9 districts in Sri Lanka.

Fig 1

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Each yellow circle corresponds to a study site. The basemap was obtained from the following sources at ArcGIS: Esri, TomTom, Garmin, FAO, NOAA, USGS, OpenStreetMap contributors, and the GIS User Community. https://basemaps.arcgis.com/arcgis/rest/services/World_Basemap_v2/VectorTileServer.

Anthropometric measurements were obtained at the time the data was collected and blood samples obtained at the schools of the children. The height was measured by a stadiometer to within 0.5cm and weight was measured using a digital scale, which was calibrated regularly throughout the study. In calculating the body mass index centile (BMI) in children aged 10 to 18, the BMI was plotted on the WHO BMI for age growth charts for boys or girls to acquire the percentile ranking, as percentile rankings are the most suitable indicator for growth patterns in children [17].

Determining past dengue disease severity

The parents/guardians of all children who were enrolled in the study were asked to bring all relevant records and diagnosis cards of past hospital admissions, outpatient treatment and clinic attendance. In Sri Lanka, a diagnosis card is issued for each episode of hospitalization, which includes data such as the diagnosis of the illness, relevant clinical, radiological and laboratory findings during hospitalization that supported the clinical diagnosis. Accordingly, details of previous admissions to hospital due to a clinically diagnosed dengue infection were recorded. Those who were found to be seropositive for dengue, but who were not admitted to hospital were considered as not hospitalized due to dengue.

Assessment of dengue seropositivity

Dengue seropositivity was determined as previously described using a commercial assay (PanBio Indirect IgG ELISA), which has been widely used for dengue seroprevalence studies [18–20]. PanBio units were calculated according to the manufacturer instructions and accordingly, PanBio units of > 11 were considered positive, 9–11 was considered equivocal and < 9 was considered negative.

Statistical analysis

GraphPad Prism version 9.5 and Jupyter Notebook (python IDE) was used for statistical analysis and to implement models. As the data were not normally distributed, differences in means were compared using the Mann-Whitney U test (two tailed), and the Kruskal-Walli’s test was used to compare the differences of the antibody levels in the different districts, and in urban, rural and estate sectors. The degree of associations between BMI, urbanicity and the risk of hospitalization with dengue, was expressed as the odds ratio (OR). Chi Square test was used to determine the association of seropositivity and BMI Centiles of children. The associations between BMI, urbanicity socio-demographic factors to hospitalization status for dengue, was analyzed with the Binary Logistic Regression Model (S1 Data) and implemented using the Synthetic minority oversampling technique (SMOTE) to recover the imbalanced data. The data was considered to be imbalanced as the number of hospitalized children were far fewer than the children who were not hospitalized. Therefore, in order to develop the best performing model, SMOTE model was implemented. Co-morbidities were not assessed in the model as all children were previously healthy apart from varying BMIs.

Results

BMI centile and risk of hospitalization due to dengue infection

Overall 1152/4782 (24.1%) were found to be seropositive for dengue and age-stratified seroprevalence rates of each of the districts, and seropositivity rates based on urbanicity has been previously described for this cohort [15]. The number of children enrolled from each district and their demographics are shown in Table 1.

The number of children who had been hospitalized for dengue out of the total number of children who were seropositive for dengue was 182/1152 (15.8%). The BMI centiles of all children aged 10 to 18 (n = 4782), the dengue seropositivity rates of children of different BMIs and hospitalization rates are shown in Table 2. A large proportion (22.1%) of children in Sri Lanka were underweight with their BMIs <3rd centile for age, according to the WHO BMI for age growth charts for boys or girls [17]. However, 4.5% of children had a BMI of >97th centile for age, when plotted on the WHO BMI for age charts (S1 Table). The dengue seropositivity rates were between 18.9% to 24.6% in children of the BMI groups <97% centile, while the seropositivity rates were 30.7% in those who had a BMI centile of >97th, which were not significantly different (p = 0.16). Of the seropositive children with BMI centile >97th, 12/66 (18.2%) were hospitalized, compared to 103/1086 (9.48%), of children with a BMI centile of <97th (Fig 2). Those with a BMI centile of >97th, were twice as likely (odds ratio 2.1, 95% CI, 1.1 to 3.9, p = 0.03) to have been hospitalized for dengue compared to children with a lower BMI. The logistic regression model suggested that BMI centiles 50th to 85th (OR = 1.06, 95% C.I,1.00 to 1.11, p = 0.048) and BMI centile of >97th (odds ratio = 2.33, 95% CI, 1.47 to 3.67, p = 0.0003) was significantly associated with hospitalization when compared to children in other BMI categories.

Table 2. The BMI centile, dengue seropositivity rates and hospitalization rates of children from 9 districts in Sri Lanka aged 10 to 18 years of age.

BMI Centile BMI Centile of Children Aged 10–18 years N = 4782 (%) Dengue Seropositivity Rates N = 1152 (%) Hospitalization Rates for Dengue in Dengue Seropositive Children N (%)
<3rd 1057 (22.10%) 253 (21.96%) 22 (8.70%)
3rd to 15th 939 (19.64%) 218 (18.92%) 25 (11.47%)
15th to 50th 1298 (27.14%) 284 (24.65%) 25 (8.80%)
50th to 85th 862 (18.03%) 239 (20.75%) 22 (9.21%)
85th to 97th 411 (8.59%) 92 (22.4%) 9 (9.78%)
>97th 215 (4.50%) 66 (30.7%) 12 (18.18%)
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Fig 2. The proportion of children who were dengue seropositive from admitted to hospital for each BMI category.

Fig 2

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In addition to the BMI centiles, the risk of hospitalization was significantly higher for females when compared to males (odds ratio = 1.03, 95% CI, 1.00 to 1.06, p = 0.001).

Urbanicity and risk of hospitalization

Dengue is predominantly an urban infection, as Aedes aegypti is the main vector responsible for transmitting dengue along with Aedes albopictus [21]. Therefore, we assessed the risk of hospitalization based on the grade of urbanicity (S2 Table). 32/293 (10.9%) dengue seropositive children living in urban areas and 83/859 (9.66%) living in rural and estate areas had been hospitalized for a dengue infection. The implemented logistic model shows that the significant association for urban areas (OR = 1.05, 95% CI, 1.00–1.09, p = 0.015) with the risk of hospitalization with respect to rural areas, although this risk was low.

Discussion

In this study we have assessed if obesity was associated with an increased risk of hospitalization during an acute dengue infection by assessing hospitalization rates and the BMIs at the time of recruitment to our island wide sero-surveillance study. We found that obese children (BMI centile >97th) were twice as likely to be hospitalized than leaner children. However, although we adopted a novel approach, which uses less resources and time than a prospective, longitudinal observational study, to investigate potential associations between obesity and risk of hospitalization, as this is a retrospective-observational study, there are certain limitations. We only assessed anthropometric measurements at the time of recruitment to this cross-sectional, serosurvey, it would not reflect the BMIs of children at the time of them being infected with the DENV, which is a major limitation of the study. Furthermore, only 12/115 (10.4%) children hospitalized due to dengue had a BMI >97th centile, which suggests that many other factors play a role in symptomatic dengue leading to hospitalization. Nevertheless, although there are many studies that show obesity and diabetes are risk factors for severe dengue in hospitalized patients, if obesity itself leads to increased hospitalization has not been studied. Therefore, despite the limitations, we believe it would be important to explore the findings of our study, by longitudinal study cohorts, to find out if obesity itself was a risk factor for hospitalization and if so the immune mechanisms that lead to this.

Although many high income countries have had the BMIs of their populations rising, the BMIs have plateaued in these countries and in Latin America, while there is a marked and steady rise in the BMI of the population in South Asia and Southeast Asia [22]. The relationship between obesity and development severe dengue had been observed for many years and reported in children in studies in the 1990s from Thailand, India and El Salvodor [23–25]. Many subsequent studies showed that obesity was an independent risk factor for developing severe dengue in hospitalized patients [13, 14] including a recent metanalysis [26]. However, this is the first study reporting that obesity may also associate with higher rates of hospitalization, which needs further examination with longitudinal studies. The number of cases of dengue reported from many countries reflect the number of suspected dengue patients admitted to hospitals, due to the limited availability of point-of care diagnostic tests and confirmatory tests [10, 27]. Therefore, factors that lead to an increase in hospitalizations would also lead to an increase in the reported number of dengue cases in these countries. As there is a marked rise in obesity in many Asian countries, this could be an additional factor contributing the increase in hospitalization rates, along with intense transmission, co-circulating of multiple DENV serotypes and environmental factors such as climate change, urbanization, and improper waste management.

Obesity is associated with an increase in risk of severe disease due to many other infections such as influenza and COVID-19. While public education programs have focused on the importance of reducing obesity to prevent occurrence of diabetes, cardiovascular diseases and cancer, there has been limited focus on the impact of obesity on many infectious diseases. If the increase in obesity leads to higher hospitalization rates due to dengue, obesity would be an important contributing factor for the current trend in an increase in hospitalizations, experienced in many dengue endemic countries. Therefore, it would be crucial to further investigate the risk of hospitalization due to obesity and to carry out public health campaigns, educating the public on the prevention of obesity. Furthermore, the mechanisms by which obesity and diabetes increase disease severity of dengue, should be further explored to develop biomarkers and therapeutics specially targeting at risk populations.

Supporting information

S1 Table. Percentages of children in different BMI centile categories for each of the 9 districts sampled and island-wide.

(DOCX)

pntd.0012248.s001.docx (16.6KB, docx)
S2 Table. Dengue seropositivity rates and hospitalisation rates for dengue in dengue seropositive children in urban, rural and estate areas island-wide.

(DOCX)

pntd.0012248.s002.docx (14KB, docx)
S1 Data. Supplementary data on binary regression model.

(DOCX)

pntd.0012248.s003.docx (106.7KB, docx)
S2 Data. Dataset used to generate tables and figures in manuscript.

(XLSX)

pntd.0012248.s004.xlsx (297.9KB, xlsx)

Acknowledgments

Seroprevalence study group includes the following members:

Lahiru Perera, Pradeep Pushpakumara, Laksiri Gomes, Jeewantha Jayamali, Inoka Sepali Aberathna, Thashmi Nimasha, Madushika Dissanayake, Shyrar Ramu, Deneshan Peranantharajah, Hashini Colambage, Rivindu Wickramanayake, Harshani Chathurangika, Farha Bary, Sathsara Yatiwelle, Michael Harvie, Maheli Deheragoda, Tibutius Jayadas, Shashini Ishara, Dinuka Ariyaratne, Shashika Dayarathna, Ruwanthi Wijekulasuriya, Chathura Ranathunga.

Data Availability

Data is available in the manuscript and the supplementary files.

Funding Statement

This study has been supported by the World Health Organization Unity Studies (GNM and CJ), a global sero-epidemiological standardization initiative, with funding to the World Health Organization and the UK Medical Research Council (GSO). The World Health Organization unity trial protocol was adopted in trial design. The funders had no role in data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0012248.r001

Decision Letter 0

Amy C Morrison

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

18 Jan 2024

Dear Professor Malavige,

Thank you very much for submitting your manuscript "Are the rise in childhood obesity rates leading an increase in hospitalizations due to dengue?" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

Editor Comments:

I strongly encourage the authors to address each of the reviewer's observations point by point (you can refer to previous responses when appropriate), as there was considerable consistency among the reviews.

A major issue for me was a lack of details on the retrospective analysis. It is important to know how far back (years) were "hospitalized" cases included: 10 years, 5 years, 2 years, 1 year. I do not need to say that your IgG ELISA probably indicates exposure in the past, but is not necessarily associated with the hospitalization record. Was there definitive laboratory confirmation of a dengue case at the time of admission and if so how. Could you distinguish between patients who sought care but were managed as outpatients -- that is your IgG positive children without hospitalization should be called non-hospitalized, they could have had a range of symptoms at home including inapparent infections. Again the concerns that BMI and data collected during the cross-sectional survey would be consistent with that observed in the past when the child had dengue. Also think the suggestions for a more sophisticated multivariate statistical approach is warranted. I appreciated the creative approach (retrospective approach) your research group took to examine the role of obesity in dengue severity. If retrospective review of hospital records (not just parents records - unless they are complete), would provide make this a lot more convincing.

I look forward to a revised manuscript.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

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Amy C. Morrison, PhD

Section Editor

PLOS Neglected Tropical Diseases

Andrea Marzi

Section Editor

PLOS Neglected Tropical Diseases

***********************

Editor Comments:

I strongly encourage the authors to address each of the reviewer's observations point by point (you can refer to previous responses when appropriate), as there was considerable consistency among the reviews.

A major issue for me was a lack of details on the retrospective analysis. It is important to know how far back (years) were "hospitalized" cases included: 10 years, 5 years, 2 years, 1 year. I do not need to say that your IgG ELISA probably indicates exposure in the past, but is not necessarily associated with the hospitalization record. Was there definitive laboratory confirmation of a dengue case at the time of admission and if so how. Could you distinguish between patients who sought care but were managed as outpatients -- that is your IgG positive children without hospitalization should be called non-hospitalized, they could have had a range of symptoms at home including inapparent infections. Again the concerns that BMI and data collected during the cross-sectional survey would be consistent with that observed in the past when the child had dengue. Also think the suggestions for a more sophisticated multivariate statistical approach is warranted. I appreciated the creative approach (retrospective approach) your research group took to examine the role of obesity in dengue severity. If retrospective review of hospital records (not just parents records - unless they are complete), would provide make this a lot more convincing.

I look forward to a revised manuscript.

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: -Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

The study aim is well described in the last sentence of the introduction. However, the justification could be strengthened. What additional information will this study provide beyond the existing studies that show an association between obesity and severe disease in hospitalized patients? While I believe it does add value—for instance, this study utilizes a community-based denominator which might be more representative of the general population than hospitalized patients—there are other unique aspects that should be explicitly stated.

-Is the study design appropriate to address the stated objectives?

I found that the methods section lacked the necessary detail to answer this question. For instance, were hospitalizations from any time in the past considered? How can you ensure that the current BMI centile accurately reflects the BMI at the time of admission? Additionally, there is no mention of adjustments for confounders, the most significant of which could be co-morbidities.

-Is the population clearly described and appropriate for the hypothesis being tested?

The population is well described in the first paragraph of the methods and appears to be an appropriate group for this research question. However, dividing the population into 10-18 years and 19-20 years groups is a bit confusing due to the different approaches to scoring obesity. Is this segmentation necessary? If there's no way to apply the same scoring method across the entire age range, perhaps consider only including those aged <=18. The conclusions would remain consistent, and the sample size is still substantial with n=4,782 (1,152 sero-positive). A map of the study sites would be a beneficial addition.

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

With a sample size of n=5,207, it appears adequate for this analysis.

-Were the correct statistical analyses used to support the conclusions?

I'm concerned about the absence of an adjusted analysis. There wasn't any adjustment for age, co-morbidities, or social class—all of which could act as confounders. Additionally, it's worth noting that obesity and these other factors vary over time, implying they might have differed at the time of admission. If an adjusted analysis isn't feasible, then this should be clearly highlighted as a limitation in the discussion section.

-Are there concerns about ethical or regulatory requirements being met?

No.

Reviewer #2: As obesity and diabetes are risk factors for occurrence of dengue severe disease, due to the increasing prevalence of obesity among children in Sri Lanka, the authors hypothesize that this phenomenon also are occurring in the country.

Consistently, the study population include children aged 10 to 18 , the exposure is the body mass index centile (BMI) and the main outcome hospital admissions. However, in the introduction the authors suggest the potential association between obesity with the risk of symptomatic infection, a driver of hospitalizations, suggesting that obesity could be a risk factor to suffer a symptomatic dengue disease

Also, as end-point the title of the paragraph “determining past dengue disease severity” could be cause confusion about the research question of the study. It´s important.

Dengue prognosis study require longitudinal design to obtain outcomes as hypotension (determined by age-specific) tachycardia, signs of circulatory insufficiency, any abnormal neurological sign, etc, etc. In this case a cross-sectional will be an inappropriate study design to address this objective.

This study was well conducted using a stratified multi-stage cluster sampling method to select the schools in each district, that is, a method to guarantee a representative sample of the Sri Lanka population, taken account that urbanicity grade varied in different districts. Hopefully, the large sample size will provide an adequate statistical power to examine the questions of interest. The authors should be including the estimates with 95% confidence interval to demonstrate the study has obtained accuracy results thanks to the sample size selected. All of us know the advantages of a confidence interval (rather than a P value) to evaluate research questions.

The used an objective measure of dengue IgG serostatus to assess whether participants had ever been infected with DENV precludes recall bias. However, the study was conducted during the COVID pandemic period. When you evaluate clinical record, how to differentiate hospitalized Covid-19 from hospitalized dengue cases? any clinical definition? RT-PCR, NS1, IgM test, other methods were conducting for dengue diagnosis?

Are Outpatients considered inapparent dengue?

Could you provide information about people who receive medical care and were not hospitalized?

Reviewer #3: Degree of associations between BMI, urbanicity and the risk of hospitalization, was expressed as the odds ratio (OR), there are other statistical methods that could be used to give it greater statistical power. Or use odd ratio adjusted

--------------------

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: -Does the analysis presented match the analysis plan?

Not entirely. I don't see the following analyses described in the "statistical analysis" section in the results:

"As the data were not normally distributed, differences in means were compared using the Mann-Whitney U test (two-tailed), and the Kruskal-Wallis test was used to compare the differences of the antibody levels in the different districts, and in urban, rural, and estate sectors." OR

"Spearman rank order correlation coefficient was used to evaluate the correlation between age and DENV-specific antibody levels (Panbio155 Units)."

Also, the statistical analysis plan doesn't present methods for the "Urbanicity and risk of hospitalization" section in the results.

-Are the results clearly and completely presented?

The text results are sufficient, but some additional tables and figures would help clarify the findings.

Table 1: A summary of the demographics of the population (traditional Table 1), presenting: Age, district, gender, seropositivity, urbanization, etc.

Table 2: The current table 1 could be a new table 2.

Figure 1: A figure showing how the case hospitalization rate varies with BMI centile categorically. With BMI centile category on the X-axis and case hospitalization rate on the Y-axis.

-Are the figures (Tables, Images) of sufficient quality for clarity?

Yes

Reviewer #2: The information provided by the authors is limited . The characteristics of the baseline of the study population should be informed with more detail. Covariates as sex, age (maybe 10-14, 15-18 , more than 18 years), the informant’s education level, any enrolled household member having had a dengue illness diagnosed by a physician either at a hospital , anothers available . I suggest compared, in bivariate analysis, the prevalence of seropositivity by categories of sociodemographic characteristics.

These characteristics are important to appreciate the similarity between groups by covariate’s if not balanced or if the imbalance is not statistically adjusted, these characteristics can cause confounding and can bias study results. This requires adjusted analysis takes into account this baseline between groups that may influence the outcome.

I cannot identify an specific analysis plan in the manuscript. May be the prevalence ratios could be estimated from generalized estimating equations (GEE) with the Poisson distribution, using the robust sandwich estimate of the variance to account for intra-family correlations

There are not description about the limitations of analysis. The characteristics of the baseline of the population study should be informed in detail to appreciate the differences between groups by covariate.

Reviewer #3: The number of hospitalized people is not very large, they should be very cautious when interpreting the results.

The authors analyze the urbanization variable and the risk of hospitalization. Although they did not find an association when analyzing this variable, it is not well described what health services care is like in urban and rural areas.

--------------------

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: -Are the conclusions supported by the data presented?

Yes I think so ingeneral, but there a signifant lack of context and depth in the discussion.

1. Relationship with Previous Studies:

There a some reflection on current literature. However, what do prior studies highlight about other risk factors for hospitalization? How might these factors be realted with obesity?

2. In-depth Analysis of Results:

It's noteworthy that, while obesity was associated with hospitalization, the vast majority of individuals aged <=18 who were hospitalized fell below the 97th BMI centile (103 out of 115). This observation deserves further elaboration. What implications does this finding have for your overarching conclusions? Further, it's intriguing that only the >97th BMI centile group showcased a heightened admission rate. Why wasn't there a gradational increase observed across the various BMI groups?

-Are the limitations of analysis clearly described?

No, there is no in depth discussion of the limitations of this paper.

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

Not significantly

-Is public health relevance addressed?

Somewhat, but more detail could be provided. How big a factor is obesity likely to be compared to other risk factors for admis

PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0012248.r003

Decision Letter 1

Amy C Morrison

1 May 2024

Dear Professor Malavige,

Thank you very much for submitting your manuscript "Is the rise in childhood obesity rates leading to an increase in hospitalizations due to dengue?" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

Editor comments:

All reviewers were very appreciative to all of your efforts toward improving your manuscript and although, I'm never supposed to say so directly, this is very close to going to production, but Reviewer #1 still has a few additional queries and suggestions, that I think if addressed with again improve the manuscript. Most of the suggestions are rapid changes and including the logistic regression output as supplemental information is a reasonable request and becoming the new normal in the era of "open" science (I'm still getting used to this).

Again, I will be on alert when the next version comes back and will make the decision myself (no return to reviewers), which was appropriate during the last revision. Congratulations this is almost over the finish line.

Amy

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Amy C. Morrison, PhD

Section Editor

PLOS Neglected Tropical Diseases

Andrea Marzi

Section Editor

PLOS Neglected Tropical Diseases

***********************

Editor comments:

All reviewers were very appreciative to all of your efforts toward improving your manuscript and although, I'm never supposed to say so directly, this is very close to going to production, but Reviewer #1 still has a few additional queries and suggestions, that I think if addressed with again improve the manuscript. Most of the suggestions are rapid changes and including the logistic regression output as supplemental information is a reasonable request and becoming the new normal in the era of "open" science (I'm still getting used to this).

Again, I will be on alert when the next version comes back and will make the decision myself (no return to reviewers), which was appropriate during the last revision. Congratulations this is almost over the finish line.

Amy

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: -Are the objectives of the study clearly articulated with a clear testable hypothesis stated? YES

- Is the study design appropriate to address the stated objectives? YES (with limitations)

-Is the population clearly described and appropriate for the hypothesis being tested? YES

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested? YES

-Were correct statistical analysis used to support conclusions? YES

-Are there concerns about ethical or regulatory requirements being met? NO

The methods are significantly clearer.

1. Line197: Worth making it clear to the reader what "imbalanced data" is being referred to here.

2. The authors no present a logistic regression as requested. The reason I had originally requested this was so that co-morbidities could be included in that model. The eligibility excludes children with co-morbidities. I think this is fine, but I would make it clear in the the description of the model within the methods, that co-morbidities were not assessed in the odel as the children were all previous healthy (aprat from varying BMIs).

Reviewer #2: Yes, the hypothesis has been clearly articulated and is verifiable. Although, the best design to answer this research question is a prospective cohort, the authors have declared the limitations of a cross-sectional study to evaluate this research question. The sample was obtained using probabilistic methods, hence the reason why, it is a representative group of the population under study. Additionally, this sampling ensures an adequate sample size for the evaluation of the hypothesis. Finally, the revised manuscript includes a proper statistical analysis to support the discussion.

Reviewer #3: (No Response)

--------------------

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: -Does the analysis presented match the analysis plan? YES

-Are the results clearly and completely presented? NO (see below)

-Are the figures (Tables, Images) of sufficient quality for clarity? YES

Results are also much improved.

2. The authors should present logistic regression summary tables, ideally in the main mansucript but could be in supplement.

3. I am unclear whether the results of "Urbanicity and risk of hospitalization" are derived from the same logistic regression analysis or a separate one. Could this be made clearer? The model summary tables will help resolve this. The methods mention 4. Spearman rank correlation coefficient, but where are these presented in the results? I mentioned this previously, but perhaps I wasn't clear.

5. Line 198: this is not a predicitive model. I would put a fullstop after model and lose the rest of the sentence.

Reviewer #2: Yes

Reviewer #3: (No Response)

--------------------

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: -Are the conclusions supported by the data presented? YES

-Are the limitations of analysis clearly described? NO (see below)

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study? YES

-Is public health relevance addressed? YES

The conclusions are significantly broader and detailed which has strengthened the paper.

1. Line 258: The authors mention a single weakness, 'However, as we only assessed anthropometric measurements at the time of recruitment'. There are several other weakness, for example this is a retrospecrive and observational study. I would like to see a slightly deeper look at these. Having said this, one of the great strengths of this study, to me, are the innovative (albeit limited) methods. This apporoach does not incur the same time and resource costs as a prospective study and therefore I think this positive point is also woth mentioning.

2. Finally, I think it is worth noting that only 12/115 hospitalised people were actually in the >97th BMI contile group. I think this statement could be fairly easily integrated into the discussion. I personally think it helps contextualise the findings and reminds us of the importance of non-obesity related factors associated with hospitalisation. The exclusion of individuals with co-morbidities limits the ability of this study to compare the realtive importance of obesity and other co-morbid factors.

Reviewer #2: Yes, this is a relevant public health study.

It could be inferred that , in children and adolescent ( between 10-18 years old ) , interventions in the lifestyle, diet, physical activity and reduction of sugar intake would be useful to mitigate the risk of hospitalization by dengue. This kind of hypothesis will require different randomized trials.

Reviewer #3: (No Response)

--------------------

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: Minor issues:

Abstract:

- Line 48: Clearly state the aim in the abstract.

- Line 54: BMI should come directly after index. I don't think you mean BMI = "Body Mass Index Centile".

- Line 58: Missing 'Result' subheading.

- Line 60: Missing 'regression' after logistic.

- Line 63: I think it should be “significantly associated with hospitalisation” not “hospitalisation rates”. This was a patient level analysis.

Author summary

This is text recycled from manuscript and should be more aimed at the general public.

Introduction

- Line 97: 390 starts the sentence, perhaps this should be written out

- Line 99: (and others): Is use of colons better replaced by the word 'in'. e.g 1 in 4 rather than 1:4.

- Line 131: 'with dengue' is unnecessary.

- Line 132: is a bit muddled

- Line 145: Inconsistent use of digits and text for numbers. Here 'nine' is used. In other places numbers are used e.g. line 147. Good to check the whole manuscript.

- Line 150: What is an 'estate' area.

Methods

- Line 141-2: should be 'between the ages of 10 *and* 18' not '10 *to* 18'.

- Line 162: ethics statement should be moved to the beginning or end of the methods.

- Line 187: should be 'and *to* implement models' not 'and implement models'

Results

- Line 210: 'and age-stratified seroprevalence rates of each of the districts, and seropositivity rates based on urbanicity has been previously described for this cohort [15]'. Not sure why this is in the results.

- Line 215: starts with a number.

- Line 222-3: Table 2 doesn't test the significance of this difference, there are no p-values or confidence intervals presented.

- Line 227: should be 'logistic regression' not just 'logisitic'

- Line 229: 'was significantly associated with hospitalization rates when compared to children in other BMI categories' It should state was significantly associated with hospitalization not 'hospitalization rates' as this is a patient level analysis. Although, we need the model summary tables to be clear about this.

Discussion

- Line 255: First sentence needs to be a little clearer. '...when infected with DENV...' I don't think is grammatically correct.

- Line 258: should be '...twice as likely...' not '...twice as more likely...'

- Line 270: '...steady rise in BMIs....' perhaps '...steady rise in the BMI of the population in....' or something like like.

Reviewer #2: The authors have carefully studied the comments and recommendations from the reviewers and they have included new data analysis. Aditionally, they offered answers to our questions including new information in the manuscript.

Reviewer #3: (No Response)

--------------------

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: Well done to the authors for making significant improvements to this manuscript.

I think there are still some minor but essential issues that should be addressed before acceptance. However, I don't think they should be too challeneging to manage. I hope you find the comments helpful.

As there is no section specfically dedicated to the introduction, I'd like to make some important comments about the introduction:

Line106: “However, if host factors such as the presence of comorbidities increase the likelihood of symptomatic infection leading to hospitalizations has not been studied.” I don’t think this is true. This paper does do this: https://www.sciencedirect.com/science/article/pii/S1201971221006172#sec0006

While this study does not discuss obesity it does look at host factors associated with hospitalisation, which is the claim made by the authors. I don’t think it is essential that this has never been studied for this paper to be valuable and I would strongly recommend removing concrete statements like this. I would rephrase it to say e.g. “there is limited information on…”

-Line131: “Although obesity is a known risk factor for severe dengue in hospitalized patients with dengue[13, 14], whether obesity associates with an increase in hospitalizations has not been studied. The fact that it has never studied is not a sufficient justification for doing the study. I think you just need an additional sentence here (or at the end of paragraph 1) which states the extra value of this study over studies in hospitalised patients, there are several. This is what I was trying to say in my first review, apologies if it wasn’t clear.

Reviewer #2: As I previously wrote , the hypothesis of this study has been clearly articulated and is verifiable.

Also, the authors have declared the limitations of a cross-sectional study to evaluate this research question, the sample was obtained using probabilistic methods and the revised manuscript includes a proper statistical analysis to support the discussion.

If multiple prospective cohort studies in children and adolescents obtain similar results , it would be possible that interventions (in the lifestyle, diets and others ) would be useful to reduce the risk of hospitalization by dengue; randomized trials will be necessary in order to demonstrate this hyphotesis.

Reviewer #3: (No Response)

--------------------

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Crystyan Siles

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PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0012248.r005

Decision Letter 2

Amy C Morrison

24 May 2024

Dear Professor Malavige,

We are pleased to inform you that your manuscript 'Is the rise in childhood obesity rates leading to an increase in hospitalizations due to dengue?' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Amy C. Morrison, PhD

Section Editor

PLOS Neglected Tropical Diseases

Andrea Marzi

Section Editor

PLOS Neglected Tropical Diseases

***********************************************************

Congratulations and we appreciate your careful consideration of reviewer feedback.

PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0012248.r006

Acceptance letter

Amy C Morrison

31 May 2024

Dear Professor Malavige,

We are delighted to inform you that your manuscript, "Is the rise in childhood obesity rates leading to an increase in hospitalizations due to dengue?," has been formally accepted for publication in PLOS Neglected Tropical Diseases.

We have now passed your article onto the PLOS Production Department who will complete the rest of the publication process. All authors will receive a confirmation email upon publication.

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Soon after your final files are uploaded, the early version of your manuscript will be published online unless you opted out of this process. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers.

Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Shaden Kamhawi

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

Paul Brindley

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

Associated Data

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

    Supplementary Materials

    S1 Table. Percentages of children in different BMI centile categories for each of the 9 districts sampled and island-wide.

    (DOCX)

    pntd.0012248.s001.docx (16.6KB, docx)
    S2 Table. Dengue seropositivity rates and hospitalisation rates for dengue in dengue seropositive children in urban, rural and estate areas island-wide.

    (DOCX)

    pntd.0012248.s002.docx (14KB, docx)
    S1 Data. Supplementary data on binary regression model.

    (DOCX)

    pntd.0012248.s003.docx (106.7KB, docx)
    S2 Data. Dataset used to generate tables and figures in manuscript.

    (XLSX)

    pntd.0012248.s004.xlsx (297.9KB, xlsx)
    Attachment

    Submitted filename: Reponses to Reviewer Comments 18.03.2024.docx

    pntd.0012248.s005.docx (30.9KB, docx)
    Attachment

    Submitted filename: Answer to review comments 21.05.2024.docx

    pntd.0012248.s006.docx (24.1KB, docx)

    Data Availability Statement

    Data is available in the manuscript and the supplementary files.

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