Overweight or obesity and abdominal obesity and their association with cardiometabolic risk factors in Brazilian schoolchildren: A cross-sectional study

Nutrition 78 (2020) 110780

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Original article

Overweight or obesity and abdominal obesity and their association with cardiometabolic risk factors in Brazilian schoolchildren: A crosssectional study
via Erika Felix Pereira M.Sc. a, Avany Fernandes Pereira Ph.D. b, Fabiana da Costa Teixeira Ph.D. a, Fla b,c, Beatriz Gon¸c alves Ribeiro * a

Federal University of Rio de Janeiro, Josue de Castro Nutrition Institute, Postgraduate Program in Nutrition, Rio de Janeiro, Brazil Federal University of Rio de Janeiro, Josu
e de Castro Nutrition Institute, Rio de Janeiro, Brazil c Federal University of Rio de Janeiro, Campus Maca
e, Integrated Laboratory of Research in Sports and Sciences, Brazil b

A R T I C L E

I N F O

Article History: Received 30 March 2019 Received in revised form 28 January 2020 Accepted 7 February 2020 Keywords: Schoolchildren Cardiovascular risk Abdominal obesity Dyslipidemia Systemic arterial hypertension

A B S T R A C T

Objectives: The aim of this study was to access the association between overweight or obesity and abdominal obesity (AO) and cardiometabolic risk factors (CRF) of schoolchildren. Methods: We evaluated body weight (BW), height, body mass index (BMI), waist circumference (WC), fasting glycaemia (FG), blood pressure (BP), triacylglycerides (TGs), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) in 501 students (6
10 y of age) from
, Brazil. Statistical analyses were performed by x2, Fisher exact tests, and odds municipal schools in Macae ratio (OR; 95% confidence interval [CI]). Results: Children with overweight or obesity had higher TG, TC, and BP values than normal weight children (P < 0.05). The same trend was observed in children with AO versus those without AO. Among the schoolchildren, 58.5% had at least one CRF. Overweight or obese children had increased risk for high BP (OR, 3.98; 95% CI, 2.4
6.57), high TGs (OR, 2.81; 95% CI, 1.64
4.8), high TC (OR, 2.47; 95% CI, 1.53
4), high LDL-C (OR, 3.07; 95% CI, 1.09
8.6) and two or more CRFs (OR, 4.6; 95% CI, 2.89
7.3). Children with AO had increased risk for high BP (OR, 3.97; 95% CI, 2.18
7.22), high TGs (OR, 3.4; 95% CI, 1.79
6.49), high TC (OR, 2.57; 95% CI, 1.39
4.75), high LDL-C (OR, 3.7; 95% CI, 1.24
11.07), and two or more CRFs (OR, 3.25; 95% CI, 1.82
5.78). Schoolchildren with CRFs presented higher means of BW, BMI, WC, FG, TGs, TC, LDL-C, SBP, DBP, and lower HDL-C than children without CRFs. Conclusion: The relationship between increased body weight or AO and CRF, described in the present data, reinforces the importance of early prevention of excess weight in children. © 2020 Elsevier Inc. All rights reserved.

Introduction There is a high global prevalence of cardiovascular diseases (CVDs), which is the predominant cause of mortality, especially in ~o de Aperfei¸c oamento de Pessoal This study was financed in part by the Coordena¸c a de Nível Superior - Brasil (CAPES) Finance Code 001. This work was supported by the Foundation of Research Support of the State of Rio de Janeiro (FAPERJ no. E-26/ 110,487/2010), National Counsel of Technological and Scientific Development (CNPQ no. 19011). BGR was responsible for the study concept and design. FdCT and FEFP were responsible for acquisition of data. BGR, AFP, FdCT, and FEFP were responsible for the analysis and interpretation of the data, and drafting of the manuscript. BGR and AF were responsible for the critical revision of the manuscript. BGR was responsible for funding acquisition and study supervision. All authors read and approved the final version of this manuscript. The authors had no conflicts of interest to declare. *Corresponding author: Tel.: +55 22 2141 4056. E-mail address: [email protected] (B.G. Ribeiro). https://doi.org/10.1016/j.nut.2020.110780 0899-9007/© 2020 Elsevier Inc. All rights reserved.

developing countries [1]. Epidemiologic studies indicate that cardiometabolic risk factors (CRFs) as dyslipidemias, high blood pressure (BP), and hyperglycemia may occur in childhood. The occurrence of CRFs correlates with metabolic, functional, or structural changes at early ages, which also can lead to CVDs in adulthood [2
5]. The severity and extent of these changes may increase with age and may be related to the magnitude of each CRF and to the association among two or more CRFs [6]. Studies in children and adolescents have shown an association between overweight or obesity and abdominal obesity (AO) during childhood and the occurrence of CRFs [7
12]. Body fat, especially abdominal fat, stimulates the secretion of proinflammatory cytokines, which predict cardiometabolic changes, insulin resistance, type 2 diabetes mellitus (T2DM), metabolic syndrome and, consequently, CVDs [13]. Therefore, although CRFs may be present

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F.d.C. Teixeira et al. / Nutrition 78 (2020) 110780

among children and adolescents, regardless of their nutritional status, CRFs are more frequently found in individuals with overweight or obesity or AO [14]. Monitoring excess weight and CRFs during childhood can subsidize and direct actions to promote healthy eating programs and regular physical exercise practices among children. Although there are studies in the literature about CRFs in children and adolescents, there are not many in the age group <10 y, especially in developing countries such as Brazil. Therefore, the present study investigated the association between overweight or obesity and AO and cardiometabolic risk factors among Brazilian schoolchildren. Methods and procedures A cross-sectional study was performed between March 2013 and November 2014 using schoolchildren from 6 to 10 y of age. The study was conducted within
(Rio de Janeiro, Brazil), which has 9 administrathe public school system of Macae tive sectors, 52 schools, and 10 247 students (6
10 y of age). To clarify how the studied population was selected, it is important to mention that for logistical reasons a school from each administrative sector was chosen. Thus, 1553 students were invited to participate in the study. The sample size was calculated based on the study of the national obesity prevalence in the targeted age group (14.2%) [15]. Data obtained from reference population of 1553 schoolchildren is presented with a 95% confidence interval (CI) and a maximum error of 2.5%. Children with some physical impairment, which could interfere with data collection, children who had T1DM, T2DM, or hypothyroidism were excluded from study, as well as those who were taking one or more medications that could interfere in study results. Among 1553 schoolchildren, 1 was excluded, 936 were not authorized for the biochemical examination, and 115 had incomplete data. Thus, 501 children were evaluated (Fig. 1). Body weight (BW; kg) and height (m) were measured in duplicate according to Lohman et al. [16]. An electronic scale (Tanita Platform, Arlington Heights, IL, USA) with a capacity of
150 kg and a 50 g variation was used to collect BW, and Exata Altura anthropometer (Minas Gerais, Brazil) with a variation of 0.1 cm was used to measure height. The students were evaluated wearing lightweight clothing, without shoes, and no adornment on the head. The mean value between the two measurements was used to calculate body mass index for age (BMI-for-age), which was categorized according to the criteria proposed by the World Health Organization (WHO) [17]. The waist circumference (WC; cm) was measured at midpoint between the last rib and the iliac crest upper border as recommended by the WHO [18]. All values were collected in duplicate and the mean between measurements was calculated. Owing to the lack of a universal cutoff point for WC associated to CRF in children, AO was considered to be WC >90th percentile, which is widely suggested in the literature [19]. Children with a WC >90th percentile are more likely to have CRFs than

children with a WC
90th percentile [19,20]. The WC percentile was determined according to the sex and age of all students who had WC measurement [11]. A blood sample collected after a 12-h fasting period was obtained for biochemical analyses. To assure fasting, a reminder was sent to children’s parents the day before the blood draw, and a signed confirmation was required before biochemical analysis. Blood samples (»10 mL from each child) were collected and centrifuged for 5 min. The samples were kept in thermal boxes and transported to the laboratory within 2 h for analysis. Fasting glycemia (FG; mmol/L), total cholesterol (TC; mmol/L), high-density lipoprotein cholesterol (HDL-C; mmol/L), and triacylglycerols (TGs; mmol/L) were analyzed by enzymatic colorimetric method (Labtest kit). Low-density lipoprotein cholesterol (LDL-C; mmol/L) was estimated by the Friedewald formula [21]. To establish the classifications, cutpoints suggested by the Brazilian Society of Cardiology [22] and of Diabetes [23] were used. The TC (4.4 mmol/L), HDL-C (1.16 mmol/L), LDL-C (3.36 mmol/L), TG (1.47 mmol/L), and FG (5.55 mmol/L) values were used to identify each biochemical CRF. Dyslipidemia was considered as one or more alterations in the lipid profile (high TG, high TC, reduced HDL-C, and increased LDL-C) [10]. The procedures and BP analysis were based on the Brazilian Society of Cardiology guidelines [24]. OMRON HEM-705 CP (G-Tech International- Republic of Korea) digital equipment was used and the sleeves were suitable for each arm size. The measurements were performed in duplicate and with a 2-min interval between them. The mean value between the two measurements was considered to identify child’s BP. The BP values >95th percentile according to age, sex, and height were considered as high BP [24]. Regarding the stratification of CRFs, at least the presence of one CRF was considered: hyperglycemia, high TGs, reduced HDL-C, hypercholesterolemia, increased LDLC, and high BP. The study was approved by the Ethics and Research Committee of Veiga de Almeida University and authorized by the Municipal Department of Education of
, RJ. The parents or guardians signed a free and informed consent form. Macae Considering a normal distribution of the BP, biochemical, and anthropometric variables, the continuous variable means, SD, categorical variables frequencies, and their respective 95% CI were calculated. Quantitative variables were compared using analysis of varance. To evaluate the prevalence of CRFs and their association with overweight or obesity or AO incidence, x2 and Fisher exact tests and OR by logistic regression method were both used. The dependent variables were the CRF (BP, FG, TG, TC, HDL-C, and LDL-C) and the number of CFRs (one CRF, two or more CRFs). The independent variables were excessive BW (overweight or obesity) and AO. Normal weight and non-AO were considered as the reference (OR, 1). The statistical significance was considered if P < 0.05. The SPSS version 21 was used (SPSS, Chicago, IL, USA).

Results The study included 219 boys (43.7%) and 282 girls (56.3%). Thirteen (2.6%), 312 (62.3%), 86 (17.2%), and 90 (18%) schoolchildren

1553 children (6 to 10 years old) enrolled at 9 schools

↓

Excluded: 1 schoolchildren due to dwarfism

1552 schoolchildren

936 Without authorization for biochemical analysis

↓ 616 schoolchildren

↓

115 Were not included in the study: absence of any data (blood pressure, biochemical analysis and/or anthropometry)

501 (219 boys and 282 girls) Included for analysis
, Brazil, 2013
2014. Fig. 1. Flowchart of the study sample of children 6
10 y of age, Macae

F.d.C. Teixeira et al. / Nutrition 78 (2020) 110780

3

Table 1
, Brazil, 2013/2014 Anthropometric, biochemical, and blood pressure data according to nutritional status in schoolchildren aged 6
10 y, Macae Variables

All (N = 501)

Normal weight (n = 312)

Overweight (n = 86)

Obesity (n = 90)

Overweight + obesity (n = 176)

non-AO (n = 443)

AO (n = 58)

Age (y) Weight (kg) BMI (kg/m2) WC (cm) FG (mmol/L) TG (mg/dL) HDL-C (mmol/L) TC (mmol/L) LDL-C (mmol/L) SBP (mm Hg) DBP (mm Hg)

7.8 (1) 30.5 (8.4) 17.6 (3.3) 61.3 (9.1) 4.75 (0.78) 0.96 (0.47) 1.31 (0.24) 3.82 (0.66) 2.07 (0.6) 107.2 (9.3) 67.2 (7.6)

7.8 (1) 26.5 (4.3) 15.8 (1.2) 56.5 (4) 4.71 (0.77) 0.89 (0.38) 1.3 (0.23) 3.74 (0.56) 2.02 (0.55) 105.0 (8.6) 65.5 (7.3)

7.9 (1.1) 33.7 (6.5)* 19.2 (1.3)* 64.4 (6.1)* 4.83 (0.79) 1.01 (0.5) 1.29 (0.26) 3.93 (0.75) 2.16 (0.64) 110.1 (7.5)* 69.1 (6.6)*

7.9 (1) 42.5 (8.1)*,y 23.2 (2.5)*,y 76 (7.2)*,y 4.81 (0.84) 1.17 (0.60)* 1.33 (0.27) 4.0 (0.80)* 2.14 (0.73) 112.9 (10)* 71.6 (7.5)*

7.9 (1) 38.2 (8.6)z 21.2 (2.8)z 70.4 (8.8)z 4.82 (0.82) 1.09 (0.56)z 1.31 (0.26) 3.97 (0.79)* 2.15 (0.69) 111.5 (9)z 70, 4 (7.2)z

7.8 (1) 28.6 (6.3) 16.8 (2.3) 58.9 (6.4) 4.75 (0.8) 0.92 (0.42) 1.3 (0.24) 3.79 (0.61) 2.05 (0.57) 106.4 (9) 66.7 (7.5)

7.9 (1) 45.1 (8.08)z 24.0 (2.5)z 79.5 (5.9)z 4.72 (0.67) 1.26 (0.63)z 1.31 (0.25) 4.10 (0.90)* 2.21 (0.78) 113.1 (9.4)z 71.4 (7.3)z

AO, abdominal obesity; BMI, body mass index; DBP, diastolic blood pressure; FG, fasting glycemia; HDL-C, high-density cholesterol; LDL-C, low-density cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triacylglycerol; WC, waist circumference. Data represented as mean (SD). Analysis of variance P <0.05. Underweight children were not included in the analysis (n = 13). Comparison between means: overweight or obesity and normal weight: *P <0.001 vs normal weight. y P <0.001 vs overweight. Comparison between means: overweight + obesity and normal weight: *P <0.05 vs normal weight. z P <0.001 vs normal weight. Comparison between means: non-AO and with AO: *P <0.05 vs non-OA zP <0.001 vs non-AO.

were classified as underweight, normal weight, overweight, and obesity, respectively. The prevalence of AO was 11.6% (n = 58). None of the normal weight schoolchildren was classified as AO. However, 118 (67%) of the schoolchildren classified as having excess BW (overweight or obese) were non-AO, and 58 (33%) of them were classified as AO. Anthropometric, biochemical, and BP data are presented in Table 1. Overweight or obese and AO children showed higher mean TG, TC, systolic BP (SBP), and diastolic BP (DBP) values when compared with normal weight and non-AO children (P < 0.05; Table 1). There was no difference by sex in any of the parameters evaluated (P > 0.05). Of the 293 (58.5%) children who had one or more CRFs, 190 (37.9%) had one CRF and 103 (20.6%) had two or more. Schoolchildren with one CRF had mean values that were significantly higher in anthropometric variables, FG, TG, TC, LDL-C, SBP, DBP and lower HDL-C when compared with non-CRF children. The mean values were also higher in schoolchildren with two or more CRFs when compared with one CRF occurrence (Table 2). The prevalence of dyslipidemia was 46.7%(n= 234), predominantly by reduced HDL-C (25.9%). Overweight or obesity and AO schoolchildren had increased risk for high BP, TGs, TC, LDL-C, as well as two or more CRFs compared with normal weight and nonAO children (Table 3). Excessive weight and AO were associated with borderline LDLC. Among the normal weight and non-AO children, 158 (50.6%) and 243 (54.8%) had at least one CRF (Table 3).

Discussion The present study reported a positive association between overweight, obesity, AO and CRFs of schoolchildren (6
10 y of age). Similar to the present study, Rover et al. [25], in your investigation observed higher means in the lipid profiles of children with excess weight in Brazil. Higher SBP and DBP means also were observed in overweight or obese children compared with normal weight children, as reported in studies conducted in different countries [8,12,26]. The data reinforce the influence of excess weight and/or AO on lipid profile and BP.

Table 2 Anthropometric, biochemical, and blood pressure data according to cardiovascular
, Brazil, 2013
2014 risk factors in schoolchildren 6
10 y of age, Macae Variables

No CRFs (n = 208)

1 CRF (n = 190)

2 CRF (n = 103)

Age (y) Weight (kg) BMI (kg/m2) WC (cm) FG (mmol/L) TG (mmol/L) HDL-C (mmol/L) TC (mmol/L) LDL-C (mmol/L) SBP (mm Hg) DBP (mm Hg)

7.7 (1.1) 28.4 (6.5) 16.8 (2.4) 58.8 (6.8) 4.56 (0.6) 0.81 (0.28) 1.37 (0.19) 3.62 (0.39) 1.88 (0.4) 103.8 (7.1) 64.8 (5.9)

7.9 (0.9) 30.7 (8.5)* 17.6 (3.5)* 61.7 (9.8)* 4.81 (0.82)* 0.96 (0,41)y 1.26 (0.26)y 3.78 (0.6)* 2.07 (0.58)* 107.5 (9.1)y 67.3 (7.8)y

7.9 (1) 34.3 (10.1)y,z 19.4 (3.8)y,z 65.5 (10.3)y,z 5.02 (0.94)y,x 1.28 (0.66)y,z 1.26 (0.28)y 4.30 (0.9)y,z 2.45 (0.79)y,z 113.5 (10.2)y,z 72.0 (7.9)y,z

BMI, body mass index; CRF, cardiovascular risk factor; DBP, diastolic blood pressure; FG, fasting glycemia; HDL-C, high-density cholesterol; LDL-C, low-density cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triacylglycerol; WC, waist circumference Data represented as mean (SD). Analysis of variance for number of CRFs P <0.05. *P < 0.05 vs non-CRF. y P <0.001 vs non-CRF. z P <0.001 vs 1 CRF. x P <0.05 vs 1 CRF.

Although an excess of adiposity may impair glucose metabolism, FG was not influenced by nutritional status, corroborating findings of other studies [14,27]. In a study conducted by Costa et al. [28], obese children whose FG levels were normal had altered insulinemia and homeostatic model assessment index when compared with eutrophic children. Undesirable values of cardiometabolic variables suggest an increased susceptibility to premature development of cardiovascular diseases in childhood, and consequently, an increased risk for morbidity and mortality in adulthood. Naidoo et al. [29] found that children with the highest BPs had increased risk for high SBP and DBP in adulthood. Furthermore, studies have shown a high CRF occurrence in childhood and adolescence [10,14], similar to evidence found in more than half of the sample in the present study. There is an increase in the global prevalence of hypertension (HTN) among younger individuals [30]. A high BP prevalence was

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Table 3
, Brazil, 2013
2014 Prevalence of cardiovascular risk factors and their association to overweight or obesity and abdominal obesity among schoolchildren 6
10 y of age, Macae Variables

CRF BP Desirable Borderline High FG Desirable High TG Desirable Borderline High TC Desirable Borderline High HDL-C Desirable Reduced LDL-C Desirable Borderline High Number of CRFs 1 CRF 2 CRFs

All (N = 501) n (%)

Normal-weight (n = 312) n (%)

338 (67.5) 82 (16.4) 81 (16.2)

232 (74.4) 51 (16.3) 29 (9.3)

453 (90.4) 48 (9.6)

Overweight + obesity (n = 176) n (%)

OR (95% CI)

non-AO (n = 443) n (%)

AO (n = 58) n (%)

OR (95% CI)

94 (53.4)* 31 (17.6) 51 (29.0)*

0.39 (0.26
0.58) 1.09 (0.67
1.78) 3.98 (2.4
6.57)

310 (70) 74 (16.7) 59 (13.3)

28 (48.3)* 8 (13.8) 22 (37.9)*

0.4 (0.23
0.69) 0.79 (0.36
1.75) 3.97 (2.18
7.22)

290 (92.9) 22 (7.1)

150 (85.2)y 26 (14.8)y

0.43 (0.24
0.79) 2.28 (1.25
4.16)

399 (90.1) 44 (9.9)

54 (93.1) 4 (6.9)

1.48 (0.51
4.3) 0.67 (0.23
1.93)

356 (71.1) 80 (16) 65 (13)

237 (76.0) 48 (15.4) 27 (8.7)

108 (61.4)* 31 (17.6) 37 (21.0)*

0.50 (0.33
0.74) 1.17 (0.17
1.92) 2.81 (1.64
4.80)

325 (73.4) 70 (15.8) 48 (10.8)

31(53.4)y 10 (17.2) 17 (29.3)*

0.41 (0.23
0.72) 1.11 (0.53
2.29) 3.4 (1.79
6.49)

322 (64.3) 95 (19.0) 84 (16.8)

216 (69.2) 58 (18.6) 38 (12.2)

97 (55.1)y 34 (19.3) 45 (25.6)*

0.54 (0.37
0.80) 1.04 (0.65
1.69) 2.47 (1.53
4)

294 (66.4) 83 (18.7) 66 (14.9)

28 (48.3)y 12 (20.7) 18 (31)y

0.47 (0.27
0.82) 1.13 (0.57
2.23) 2.57 (1.39
4.75)

371 (74.1) 130 (25.9)

237 (76) 75 (24)

126 (71.6) 50 (28.4)

0.79 (0.52
1.21) 1.25 (0.82
1.90)

329 (74.3) 114 (25.7)

42 (72.4) 16 (27.6)

0.91 (0.49
1.68) 1.09 (0.59
2.03)

410 (81.8) 75 (15) 16 (3.2)

268 (85.9) 38 (12.2) 6 (1.9)

132 (75)y 34 (19.3)y 10 (5.7)y

0.49 (0.30
0.78) 1.72 (1.04
2.86) 3.07 (1.09
8.6)

371 (83.7) 61 (13.8) 11 (2.50)

39 (67.2)y 14 (24.1)y 5 (8.6)y

0,39 (0.21
0.72) 1.93 (1.03
3.85) 3.70 (1.24
11.07)

190 (37.9) 103 (20.6)

122 (39.1) 36 (11.5)

62 (35.2) 66 (37.5)*

0.84 (0.57
1.24) 4.6 (2.89
7.30)

164 (37) 79 (17.8)

26 (44.8) 24 (41.4)*

1.38 (0.79
2.40) 3.25 (1.82
5.78)

AO, abdominal obesity; BP, blood pressure; CI, confidence interval; CRF, cardiovascular risk factor; FG, fasting glycemia; HDL-C, high-density cholesterol; LDL-C, low-density cholesterol; OR, odds ratio; TC, total cholesterol; TG, triacylglycerol. x2 and Fisher exact tests (nutrition status and AO) P < 0.05. Underweight children were not included in the analysis (n = 13). *P <0.001. y P <0.05.

found in >16% of the studied sample. However, the assessment of BP was made in only one moment, which may not lead to the diagnosis of HTN [24]. Nonetheless, altered BP in childhood tends to persist during adolescence and may result in HTN during adulthood, in addition to metabolic and structural changes as ventricular hypertrophy and loss of arterial elasticity [31]. Therefore, early recognition of high BP during childhood is important to prevent HTN and metabolic changes in the future. Reduced HDL-C was the most common CRF in the present study, as previously reported by Hosvsepian et al. [32] and Rosini et al. [33] in children and adolescents. National studies in children whose lipid profile stratification and cutoff points were similar to those used in the present investigation also indicated a high prevalence of lipid disorders, especially in high or borderline TC and TGs [34,35]. Nonetheless, independent of cutoff points used, studies in childhood indicate high prevalence of reduced HDL-C, hypercholesterolemia, and hypertriacylglycerolmia [9,11,14]. In a recent review, Kosmeri et al. [2] showed that dyslipidemia was adversely associated with endothelial function in children, which suggests an increased risk for metabolic dysfunctions in the evaluated children in the present study. Except for reduced HDL-C, schoolchildren who were overweight or obese or AO had higher prevalence of dyslipidemia and high BP than normal weight and non-AO children. Dl'AllemandJander [36], in a review based on studies conducted in >260 000 German and Swiss children, also showed a high prevalence of dyslipidemia and high BP among those with overweight and AO. Additionally, overweight or obese and AO schoolchildren had increased risk of high BP, TG, TC, LDL-c and two CRFs when compared to with normal weight and non-AO children. The relationship between overweight, obesity, AO and CRFs has been reported

in the literature and can be partially explained by the chronic inflammatory process caused by fat excess, specifically in the abdominal cavity [5,7,8,13,37]. Overweight or obesity and AO were linked to high and borderline LDL-C. Based on the analysis of four cohort studies, with almost 3000 adolescents, Koskinen et al. [3] showed increased risk for thickness in the arterial intima layer in both high and borderline LDL-C. Therefore, maintenance of adequate values may reduce risks for undesirable structural and metabolic changes. However, after sample stratification by CRF number, the positive association between excess weight or AO occurred only in the presence of two or more CRFs. The data suggests an increased atherosclerosis risk in obese schoolchildren and in those with at least two CRFs. McCrindle et al. [7] reported that concomitant lipid profile disorders, characterized by high TGs, low HDL-C, and increased numbers of LDL-C particles, may promote atherogenesis and are related to overweight, obesity, and AO at early ages. With the exception of HDL-C, schoolchildren with isolated and concomitant CRFs had higher mean values in all studied variables when compared with non-CRF students, and they were even higher in when there were two or more CRFs. Therefore, the present study suggested that schoolchildren with at least one CRF are most likely susceptible to new cardiometabolic alterations and consequently, CRF, when compared with children with no CRFs. Overweight and obesity has increased in the pediatric population. Based on data from Global Burden of Disease, Lobstein and JacksonLeach [38] estimated that without effective interventions, by 2025 »268 million children and adolescents will be considered overweight or obese. Therefore, considering the relationship between the nutritional status in childhood and the occurrence of CRFs, morbidity, and mortality [39,40], programs to combat excessive body fat in children

F.d.C. Teixeira et al. / Nutrition 78 (2020) 110780

are highly necessary. However, the high prevalence of CRFs in normal-weight and non-AO children observed in this study, as well as populations studied in literature [26], suggests that, besides adiposity, other factors such as genetics, sedentary lifestyles, and food quality may contribute to CRFs [5,14,41]. Although previous investigations have shown CRFs in the pediatric population, the present study identified CRF in children 6 to 10 y of age. Additionally, the present study showed biochemical, anthropometric, and BP profiles of schoolchildren according to nutritional status and CRF occurrence. To our knowledge, this type of study is scarce in investigations conducted in Brazil. However, the present findings should be interpreted considering the limitations of the study. Despite the CRF cutoff points recommended for children in the present study, these cannot represent a consensus. It is noteworthy to mention that ethnicity, as well as behavior, may influence metabolic variables, which may compromise interpretation and comparison between the present results and current literature [10,41]. Moreover, similar to adults, AO is associated with increased risk for cardiometabolic disorders in children and WC can be a good predictor of AO in the pediatric age group [13,19]. However, although WC >90th percentile, used in the present study, has been widely suggested to identify AO, it is not a universal recommendation [19,20]. Although the data from this specific group of children do not necessarily represent other groups, the association between excessive BW or AO, cardiometabolic alterations, and concomitant CRF does reinforce the importance of early prevention of excessive BW.

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

Authors’ contributions [15]

Study concept and design: Beatriz Gon¸c alves Ribeiro. Acquisition of data: Fabiana da Costa Teixeira, Fl
avia Erika Felix Pereira. Analysis and interpretation of data: Beatriz Gon¸c alves Ribeiro; Avany Fer
via Erika Felix Pereira. nandes Pereira; Fabiana da Costa Teixeira; Fla
via Erika Drafting of the manuscript: Fabiana da Costa Teixeira; Fla Felix Pereira. Critical revision of the manuscript: Beatriz Gon¸c alves Ribeiro; Avany Fernandes Pereira; Funding acquisition: Beatriz Gon¸c alves Ribeiro. Study supervision: Beatriz Gon¸c alves Ribeiro. All authors read and approved the final version of this manuscript. Declarations of interest None.

[16] [17] [18]

[19]

[20]

[21] [22]

Acknowledgments [23]

The authors acknowledge Ronir Raggio (Postgraduate Program in Public Health at the Federal University of Rio de Janeiro) for his assistance with statistical analysis, Jackson Menezes and Anderson Morales for their biochemical analysis and the CAPES (BRASIL) for a grant support. The authors also acknowledge the Municipal Department of Education and the Municipal Health Department for permission to access the schools and technical support, respectively.

[24] [25]

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