Metabolic Syndrome in Childhood Cancer Survivors: Does Delta BMI Predict Risk in Lower-middle-income Countries?



Purpose Metabolic syndrome (MetSyn) is an important late effect of childhood cancer. The combination of rising obesity and high prevalence of under-nutrition at diagnosis, make this a unique population to study in LMIC (lower middle-income countries).

Methods Children <18 years of age at cancer diagnosis, in a single-centre in a LMIC, who were disease free and had completed treatment at least 2 years prior to study were included. MetSyn was defined using International Federation for Diabetes criteria for Asian Indians. Logistic regression analyses were carried out to evaluate the influence of various risk factors, including delta BMI (increase in body mass index from diagnosis to evaluation), on MetSyn.

Results A high prevalence of MetSyn (12.2%), central obesity (33%), and dyslipidemia (61.8%) was found in a cohort of 500 Asian Indian childhood cancer survivors (CCS) at a median follow-up age of 17 years. Multivariable analysis revealed older age at diagnosis >10 years, OR 2.9(1.6-5), longer survival duration >10 years, OR 2.2(1.3-3.8), high BMI at diagnosis OR 3.2(1.5-6.9) and large delta BMI >50, OR 3.15(1.7-5.9) to be independent predictors of MetSyn.  Patients who were under-weight or normal at diagnosis with large Delta BMI > 50 had very high odds (OR, 12.5,1.7-92) of developing MetSyn compared to those with lower Delta BMI.

Conclusions and implications for cancer survivors: A high prevalence of MetSyn was observed in CCS with early age at onset. Timely screening and early intervention are proven to be beneficial and delta BMI could be a useful screening tool for LMIC.


With improved survival of childhood cancers, late effects have emerged as a serious area of concern. As a result, survivors of childhood cancer are at an increased risk of chronic health conditions such as cardio-metabolic disorders, pulmonary problems, stroke, diabetes and second neoplasms. This is true even in the lower middle-income countries (LMIC) as evidenced by an ever-increasing number of survivors, particularly in Asian Indians [1-3]. Of concern is the substantially elevated risk of cardiovascular diseases (CVD) observed in numerous investigations worldwide [4-8] and Oeffinger et al observed this risk to be 10 times higher in childhood cancer survivors (CCS) in the US as compared to their siblings [8]. Metabolic syndrome (MetSyn) is an important predictor of CVD and constitutes a cluster of risk factors including obesity, glucose intolerance, insulin resistance, dyslipidemia, and hypertension [9]. Although the epidemiology of MetSyn is multifactorial, it is to a large extent determined by modifiable factors like obesity, dietary habits and sedentary life style. 

Recent data shows that obesity, is rising in every region of the world, and may in fact be increasing more rapidly in the LMIC than in the high-income countries (HIC) [10-12]. Furthermore, the majority of undernourished children live in LMIC [13]. Hence, child under-nutrition and adult obesity coexist in many LMIC (e.g., India), leading to sarcopenic obesity wherein deficits of muscle mass relative to fat persist into adulthood. This dual combination has been implicated as a risk factor for cardio-metabolic disorders unique to LMIC [14-17].  Recent studies indicate that even among those who are not overweight or obese, the increase in BMI (delta) during growth and development should be closely monitored, as it may predict early onset MetSyn [18]. Hence, we planned to study delta BMI in this context as it has not previously been evaluated among CCS. The present study aims to address this knowledge deficit by analyzing the prevalence of MetSyn in CCS in a LMIC setting and determine the risk factors associated with it.


Patient selection

This was a cross-sectional, observational, single-centre study, conducted over a period of 18 months, from July 2018 to December 2019, in a tertiary care cancer centre. The Pediatric Oncology department of our Institute runs an after completion of therapy (ACT) clinic, where all off-therapy patients are registered. The hospital and ACT e-database were mined to identify CCS who were ≤18 years at diagnosis, in complete remission and at least two years from treatment completion. Among 1430 patients registered in the hospital, data for 954 patients was available in the ACT e-database, of these 714 could be contacted telephonically; 500 consented and were evaluated at the ACT clinic. The evaluation comprised a complete history (including details of anti-hypertensive and anti-hyperglycemic medication), physical examination, anthropometry, and laboratory tests. Demographic, socioeconomic, disease and treatment details were extracted from the e-medical records. Exposure to various classes of chemotherapeutic agents (anthracycline, alkylating agent, anti-metabolite), steroids and cumulative equivalence doses of anthracycline were calculated. Radiation fields and doses were obtained and categorized as cranial, head and neck (not brain), chest, abdomen/pelvis, extremity and other). Assessment of urban/ rural residence and socioeconomic class was done based on the Kuppuswamy scale (based on overall family income, occupation and education) [19]. The study received approval from the Institute’s ethics committee and written informed consent was obtained from patients/parents (for minors).

BMI was calculated as: BMI= weight (kg)/ height(m2). Nutritional status was defined as per Centre for Disease Control (CDC) and WHO criteria using Asia-Pacific guidelines for South Asians: age 5-19 years, BMI <5th percentile was defined as underweight, BMI = 5th to <85th percentile defined as normally nourished, BMI > 85th to <95th percentile as overweight and >95th percentile as obese, adjusted for age and sex; age >19 years, BMI <18.5 kg/m2 were defined as underweight, normal BMI range was 18.5-22.9 kg/m2, BMI >23 kg/mto <25 kg/m2   was defined as overweight and those with BMI >25 kg/mas obese [20, 21]. Delta BMI was calculated as the percentage change in BMI z-score from diagnosis to follow-up evaluation. Delta BMI = [(BMI z-score at evaluation - BMI z-score at diagnosis) / BMI z-score at diagnosis] x 100. Waist circumference (WC) was measured midway between the lowest rib and the top of the iliac crest at the end of expiration in a standing position using a fiberglass tape with an accuracy of 1 mm. For survivors <18 years of age at evaluation, age- and sex-specific reference percentiles for WC reported in Indian children by Khadilkar et al. were utilized as normative data for defining central obesity [22]. International Diabetes Federation (IDF) criteria for Asian Indians were utilized for adults [23]. Blood pressure (BP) was measured in the right upper arm in sitting position using mercury sphygmomanometer with an appropriate size cuff. Hypertension (HT) was defined as systolic or diastolic values ≥90th percentile for age, sex, and height. Blood biochemistries included fasting blood glucose (FBG) and lipid profile after 12 hours of overnight fasting.

Definition of MetSyn

Using IDF criteria cut-offs for Asian Indians, MetSyn was defined [23] as follows for children 10 to 15 years of age as having central obesity (WC≥90th percentile) plus two or more of the following criteria: (1) Triglycerides (TGs) >150 mg/dL, (2) High-density lipoprotein cholesterol (HDL-c) <40 mg/dL, (3) systolic BP (SBP) >130 mm Hg or diastolic BP (DBP) >85 mm Hg, (4) FBG >100 mg/dL. For those >16 years of age, MetSyn was defined as having central obesity (WC≥90 cm for men and >80 cm for women), plus 2 or more of the following criteria: (1) TGs 150 mg/dL, (2) HDL-c <40 mg/dL in males and <50 mg/dL in females, (3) SBP ≥130 mm Hg or DBP 85 mm Hg, (4) FBG 100 mg/dL. As per IDF guidelines children 6 to < 10years of age were identified as high risk if their WC≥90th percentile and had a family history; in which case further measurements were carried out [24].

Statistical analysis

The participants’ demographic, disease and treatment details were analysed by descriptive statistics and mean (± standard deviation, SD) or median (inter quartile range, IQR) were used as appropriate. Fischer’s exact test and chi-square test were utilized for categorical variables. Quantitative variables were compared using the Student t-test or the Mann-Whitney test. Analysis of variance (ANOVA) was used to compare delta BMI among various nutrition categories (underweight and normal versus overweight and obese). Logistic regression analysis was done to investigate the influence of various pre-treatment and treatment related factors on MetSyn among the survivors. Adjusted OR was calculated to study the impact these factors on individual components of MetSyn.  Factors with p value <0.05 on univariate analysis were included for multivariable analysis. A receiver operating characteristic (ROC) curve was plotted to determine the cut-off value of delta BMI to predict MetSyn. The results were interpreted using odds ratio (OR) and 95% confidence interval (CI), and the significance threshold was set as p-value of <0.05. Statistical analysis was performed using the SPSS software (version 23.0, 2011; IBM, Armonk, NY, USA).


Five hundred CCS were enrolled in the present study; 78% (389) were male, 85% (424) belonged to the middle class and 74% (370) were from urban areas. At the time of evaluation, the median age of the survivors was 17 years, 49% (245) were adults >18 years of age, median survival duration was 7 years and 32.6% (163) had survived for >10 years. Based on BMI at diagnosis, the patients were categorized as underweight (130, 26%), normal (295, 59%), overweight (36, 7.2%) and obese (39, 7.8%). The two most common primary diagnoses were acute lymphoblastic leukemia (ALL) (226, 45.2%) and Hodgkin lymphoma (82, 16.4%). Treatment exposures included chemotherapy in all, steroids in 53% (265), radiotherapy (RT) in 32.4% (162), definitive surgery in 23.4% (117) and bone marrow transplant (BMT) in 2.8% (14) of patients (Table 1). 

Table 1 

Characteristics of childhood cancer survivors with and without metabolic syndrome (MetSyn)


No MetSyn 




P value





335 (76.3)

            104 (23.7)                                                                                  


54 (88.5)

7 (11.5)


Median age at diagnosis (years) 

8 (IQR:4-12)

11 (IQR:6-15)


Age at diagnosis


<10 years

278 (63.3)

23 (37.7)


10-18 years

161 (36.7)

38 (62.3)

Median age at evaluation (years) 

17 (IQR:12-21)

22 (IQR:6-15)


<18 years

240 (54.7)

15 (24.6)


> 18 years

199 (45.3)

46 (75.4)

Median duration from treatment completion (years) 




Survival time from diagnosis


< 10 years

306 (69.7)

31 (50.8)


> 10 years

133 (30.3)

30 (49.2)

BMI at diagnosis 


Underweight, normal

385 (87.7)

40 (65.6)


Obese, overweight

54 (12.4)

21 (34.4)

Delta BMI


48 (10.9)

17 (27.9)



391 (89.1)

44 (72.1)

Primary diagnosis 

Hematological malignancy

 319 (72.7)

48 (78.7)


Solid tumor & brain tumor

 120 (27.3)

13 (21.3)

Hematological malignancy




Acute lymphoblastic leukemia

198 (45.5)

28 (43.1)


Acute myeloid leukemia

17 (3.9)

3 (4.6)


Non-hodgkin lymphoma

35 (8)

4 (6.2)


Hodgkin lymphoma

69 (15.9)

13 (20)


Solid tumor




Osteosarcoma/ Ewing sarcoma

51 (11.7)

6 (9.2)



23 (5.3)

0 (0)


Wilms tumor

15 (3.4)

3 (4.6)



7 (1.6)

0 (0)


Germ cell tumor

17 (3.9)

3 (4.6)



3 (0.7)

0 (0)


Brain tumor

4 (0.9)

1 (1.5)


Treatment Exposure





405 (92.25)



58 (95.1)






271 (61.7)

37 (60.65)









233 (10.9)

32 (27.9)




206 (89.1)

29 (72.1)









68 (15.6)

14 (21.5)



Head & neck not brain

24 (5.5)

4 (6.2)



Abdomen & pelvis

21 (4.8)

1 (1.5)




10 (2.3)

3 (4.6)




4 (0.9)

3 (4.6)




9 (2.1)

1 (1.5)




107 (24.4)

10 (16.4)



Bone marrow transplant

12 (2.7)

2 (3.3)



IQR, interquartile range; BMI, body mass index. Delta BMI is percent change in BMI z-score from diagnosis to evaluation.

Prevalence of MetSyn and its components

The prevalence of MetSyn in the CCS was 12.2% (61) at a median age of 22 years, their characteristics are detailed in categorical Table 1. The prevalence was lower in children/ adolescents (<18 years, 6%) and higher in adults >18 years (19%). Figure 1 clearly demonstrates the age-wise increment in both males and females. Among the children 6-10 years of age, 28.5% (13/49) were obese by BMI and 22.4% (11/49) had central obesity (WC> 90th centile). Those with family history for cardiovascular risk factors were further assessed and 3 (all were male) of these survivors were observed to have HT (> 90th centile for age and height), elevated TG (>150 mg/dL) and low HDL-c (< 40 mg/dL), hence for the purpose of this analysis they were considered to have MetSyn.

Derangements in individual components [central obesity, impaired fasting glycemia (IFG), hypertriglyceridemia (high TG), low HDL-c, HT] of MetSyn were observed in 68.6% (343) of CCS, one component was abnormal in 40.2% (201) and two components in 16.2% (81). Low values for HDL-c and high WC (central obesity) were the most frequently observed derangements (Table 2). Their frequency and mean values were significantly higher among survivors with MetSyn and in those with high delta BMI (Table 2). It is noteworthy that, 40/61 survivors who developed MetSyn were non-obese/overweight at diagnosis. 

Table 2 

Prevalence of components of metabolic syndrome (MetSyn) and their mean values among childhood cancer survivors by presence of MetSyn and delta body mass index (BMI) 

Components of MetSyn

No MetSyn N=439(%)

MetSyn N=61(%)

P- value

Delta BMI <50

N=435 (%)

Delta BMI ≥50

N=65 (%)

P- value

Prevalence of individual components

Central obesity (WC)

104 (23.7)

61 (100)


87 (20.0)

40 (61.5)



19 (4.3)

29 (47.5)


36 (8.3)

12 (18.5)


Low HDL-c

242 (55.1)

55 (90.2)


250 (57.5)

47 (72.3)



8 (1.8)

13 (21.3)


13 (3.0)

8 (12.3)



23 (5.2)

39 (63.9)


      50 (11.5)

12 (18.5)


Mean values















































No of components








157 (35.8)

0 (0)


154 (35.4)

4 (6.2)




0 (0)


180 (41.4)

21 (32.3)



81 (18.5)

0 (0)


58 (13.3)

26 (40)



0 (0)

61 (100)


43 (9.9)

14 (21.5)


SD, standard deviation; WC, Waist circumference; IFG, Impaired fasting glycemia; TG, Triglycerides; HDL-c, High-density lipoprotein cholesterol; FBG, fasting blood glucose; SBP, Systolic Blood Pressure; DBP; Diastolic Blood Pressure.

Delta BMI and Nutritional status

Calculation of means and SD of percent BMI z-score increment from diagnosis to evaluation (delta BMI) revealed that the highest delta BMI occurred among those who were underweight (74+2) and normally nourished (123+53) at diagnosis, followed by those who were obese (15.8+1.4) and overweight (7.9+1.5), p, 0.04 (Supplemental Table 1). The ROC curve analysis (Supplemental Figure 1) revealed that underweight and normal patients who had >50 percent increase in delta BMI, had 12.5 (1.69-92) times higher odds of MetSyn compared to those with a smaller delta BMI (<50); and the odds were 43 (5.8-315) times for those with delta BMI of 108 percent (Table 3). 

Table 3 

Metabolic syndrome by nutritional status at diagnosis and Delta BMI

 BMI at Diagnosis

Prevalence of MetSyn

p value

OR (95% CI) of MetSyn when Delta BMI >50

Delta BMI <50

Delta BMI >50

Under-weight, Normal (N=428)

7.4% (28/377)

23.5%   (12/51)


12.5 (1.7-92.2)

Overweight, Obese (N=72)

27% (16/58)

35% (5/14)


2.0 (0.6-8.1)

BMI, body mass index; OR, odds ratio; CI; confidence interval. Delta BMI is percent change in BMI z-score from diagnosis to evaluation.

Risk Factors for MetSyn and its individual components

Of the various risk factors studied, multivariable analysis revealed older age at diagnosis (OR 2.78,1.43-5.4), longer survival duration (OR 2.74, 1.43-5.26), high BMI (obese) at diagnosis (OR 3.2, 1.64-6.2) and high delta BMI (OR 2.26, 1.13-4.55) to be independent predictors of MetSyn (Table 4, supplemental Table 2). 

Table 4 

Univariate and multivariable logistic regression analysis: risk factors for metabolic syndrome 







95% CI



95% CI


Gender Female





Gender Male







Age at diagnosis <10 years





Age at diagnosis 10-18 years







Age at eval <18 years





Age at eval >18 years




Survival time from diagnosis < 10 years





Survival time from diagnosis > 10 years


1.3- 3.8





BMI at diagnosis, underweight, normal





BMI at diagnosis, Obese, overweight







Delta BMI <50







Delta BMI ≥50







Primary Diagnosis





Hematological malignancy





Solid tumor & brain





Treatment exposure*






























OR, Odds ratio; CI, confidence interval; P, p-value; eval, evaluation; BMI, body mass index; RT, radiotherapy; BMT, bone marrow transplant.* All patients received chemotherapy.

 Results of chemotherapy exposure showed that use of steroids, anthracyline (>120mg/m2), alkylators or antimetabolites did not influence the occurrence of MetSyn. Patients receiving RT at various sites (cranial, abdominal or pelvic), had similar prevalence of MetSyn. Childhood cancer survivors with ALL treated with cranial RT (CRT) had a low OR (1.9, 0.85-4.24) for developing MetSyn, except in very young children (< 5 years), OR (5.48, 1.5-20), p, 0.01), when compared to those not exposed to CRT of the same age.

On multivariable analysis, adjusted OR revealed that HT (OR 3.9,1.6-9.6) and obesity (OR 2,1-3.8) were more likely in adult survivors (compared to children); hypertriglyceridemia was more in males than females (OR, 3.8;1.1-12.6) and IFG was more likely in survivors of solid tumor (OR 3.7, 1.4-9.6) .Central obesity (OR 2.4, 1.3-4.7) and low HDL-c  (OR 1.7, 1-2.8) were more common in the longer surviving patients(Supplemental Table 2).


The present study demonstrates a high prevalence of MetSyn and its components in long term Asian Indian survivors of various childhood cancers. The prevalence of MetSyn was age dependent (Figure 1), being lower among children and adolescents (6%) and higher among the adult (19%) survivors. The data from published National studies on healthy individuals revealed that the prevalence of MetSyn in children/adolescents (1-3%) and adults of similar age (11-13%) was significantly lower than in the present analysis [25-30]. It is well established that MetSyn increases with increasing age, however the higher prevalence in survivors compared to the healthy population is noteworthy and concerning [29-33].

Furthermore, the prevalence of MetSyn and its components in CCS are known to vary with ethnicity, and duration of follow-up, in addition to age. Compared to published literature from Asia, and Europe (France, Netherlands) the current analysis reveals a higher prevalence of MetSyn and at an earlier age [34, 35]. However, it is lower than that reported from US by the St Jude Lifetime Cohort Study (34%) although they had a much longer follow-up and older age at evaluation [6]. The present study demonstrates a 12.2% prevalence of MetSyn in a cohort of 500 CCS in a tertiary care centre in a LMIC at a median follow-up age of 17 years at evaluation. This is higher than that previously reported from Asia (including India), wherein MetSyn was observed in 1.3-8% of pediatric and 10-12% of adult CCS [36-38]. This may be partly explained due to the fact that these studies had a shorter follow-up and younger age at evaluation. High prevalence of MetSyn at an early age among CCS in our study and its potential adverse implications on health and quality of life reinforces the need for increasing awareness for its early identification. This assumes greater significance as it is often an ignored and underestimated late effect and early institution of preventive strategies and lifestyle modification may significantly delay or reverse the associated long-term morbidities.

Components of MetSyn

Two MetSyn components, low HDL-c (61.8%) and central obesity (33%) were observed in a large number of CCS and were much higher than values reported from HIC [6, 35]. This observation may be explained by ethnic differences in patterns of dyslipidemia and obesity in Asian Indians and also the trend of increasing obesity in LMIC in recent times. Investigators have shown that compared to other ethnic groups, children with ancestral origin in South Asia manifest central adiposity, insulin resistance and metabolic perturbations earlier in life and these derangements are of higher magnitude than white Caucasian children [30]. Both these components are associated with high odds of developing MetSyn and known to predispose to atherosclerotic heart disease [6, 31, 35]. Therefore, regular assessment of these individual components may aid in early identification of CCS at risk of developing MetSyn. This may also facilitate streamlining ACT activity and allocation of adequate manpower and resources to institute frequent monitoring, and counselling for aggressive risk-reduction strategies.  

The risk factors 

Delta BMI

It is well established that obesity is the central factor in the pathogenesis of insulin resistance and MetSyn [35]. However, it is noteworthy that most of our CCS who developed MetSyn were non-obese/overweight at diagnosis and a high delta BMI at follow-up strongly predicted MetSyn (OR 12.5[1.7-92]). Our results indicate that an 'increasing trend in BMI' reported as delta BMI may be of greater value, than a 'spot BMI' to look at risk of obesity and MetSyn [18, 32, 33]. Hence we believe that the trajectory of delta BMI should be monitored during follow-up visits to the ACT clinic and any recent large change in BMI should prompt evaluation for MetSyn. Therefore the observed mean increment in BMI z-score as a risk factor for development of MetSyn in CCS needs to be validated in a larger prospective study. Furthermore, it highlights the fact that monitoring should not be limited to only those who are obese/ overweight. 

Among the other potential risk factors, our study revealed older age at diagnosis, longer survival and high BMI at diagnosis to be the only independent predictors of MetSyn and similar results have been reported by other investigators [6, 35, 39]. While age at diagnosis and survival duration both reflect ageing and its ineliminable consequences, high BMI (obesity) is a modifiable fore-runner of MetSyn. 

Although we observed a higher prevalence of MetSyn and hypertriglyceridemia in males, on univariate analysis, sex was not found to be an independent prognostic factor. While the French L.E.A. study has reported a higher incidence in males [35], the St Jude Life Time Cohort Study found a higher prevalence in females, although statistically non-significant [6]. Another study in Asian Indians by Mohapatra et al has also observed male predominance [36]. Gender bias and preferential male treatment (overprotectiveness and overfeeding) in this part of the world may have been a contributory factor. 

We observed the prevalence of MetSyn to be similarly high across the spectrum of various childhood cancers (10-16%), including ALL survivors (12%) (Table 1). Hence, type of primary cancer as also the nature of treatment exposure did not significantly influence risk of MetSyn. Others have reported survivors of sarcomas, germ cell tumors, those treated with abdominal RT and BMT to be at higher risk of MetSyn. Furthermore, published studies have implicated CRT in patients with brain tumor and ALL as risk factors for the development of MetSyn [6, 34, 40-42]. Despite having a large cohort of ALL survivors we were unable to elicit cranial RT as a risk factor. The primary mediator of MetSyn associated with CRT is believed to be growth hormone deficiency leading to obesity and dyslipidemia and has been reported with RT doses of 18-24 Gy for ALL and 25 Gy for brain tumor. The CRT doses administered to majority of our ALL patients was lower (12.6 Gy) and may explain our observation that, except for exposure to CRT in very young children (<5 years) with ALL, we did not observe it to be a risk factor. Furthermore, our cohort included small numbers of survivors of brain tumor and BMT that precluded meaningful analysis. 

The main limitation of our study is that it was a cross-sectional cohort study and lacked serial, annual BMI assessments during follow-up. Furthermore we did not have age- and sex-matched control group for comparison. Nonetheless it has a number of strengths, it is one of the largest studies from a single LMIC centre wherein MetSyn was classified based on IDF criteria. It provides valuable insight into the risk factors of MetSyn in CCS and highlights  the novel predictive role of delta BMI in LMIC.


The present study demonstrates Asian Indian CCS to be at high risk for MetSyn and its components at an early age. Obesity and dyslipidemia were the two major contributing factors for its development and are both modifiable with lifestyle changes. Monitoring delta BMI during follow-up can be a useful tool for early identification of non-obese/overweight CCS, at risk of MetSyn that needs validation in larger longitudinal cohort. Due to the manifold increased risk of morbidity and mortality as a consequence of MetSyn, there is an overwhelming medical and ethical imperative for its early detection and timely intervention. Further research into the genetic landscape of MetSyn may help to better predict risk and individualize cancer treatment thereby leading to lower toxicities in the future.



expanded form


Metabolic syndrome


Childhood cancer survivors


Lower middle-income countries


Body mass index


Waist circumference


International Diabetes Federation 




Systolic blood pressure


Diastolic blood pressure


Fasting blood glucose


High-density lipoprotein cholesterol


Impaired fasting glycemia




standard deviation


Inter quartile range


Analysis of variance


Odds ratio


Receiver operating characteristic


Confidence interval


Acute lymphoblastic leukemia




Cranial radiotherapy


Bone marrow transplant


After completion of therapy



• Funding: 

Not applicable 

• Conflicts of interest/Competing interests: 


• Ethics approval (include appropriate approvals or waivers): 

The study was approved by the ethical committee of the institute

• Consent to participate: 

Informed consent was obtained from all individual participants/guardians included in the study.

• Consent for publication: 

The participant has consented to the submission of the data in the manuscript to the journal.

• Availability of data and material (data transparency): 


• Code availability (software application or custom code): 

not applicable

• Disclosure: 

Presented at annual national conference PHOCON 2018 held at Bangalore, November 2018 (abstract published): Agarwal A, Kapoor G, Jain S. Risk factors for metabolic syndrome in long-term survivors of childhood cancer: a single centre study. Pediatric Hematology Oncology Journal. 2018; 3(3):S1. DOI: 10.1016/j.phoj.2018.11.002.

• Authors' contributions:

AA: Data collection, analysis of data, writing the first draft manuscript

GK: Designing and conceptualizing the study, analysis and interpretation of data, drafting the manuscript, proofreading manuscript

SJ: Drafting and proof-reading the manuscript

PM: Drafting and proofreading the manuscript 

AS: Data analysis and statistics for the study


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