Prevalence of overweight and obesity in Brazilian children and adolescents: a systematic review

Prevalência de sobrepeso e obesidade em crianças e adolescentes brasileiros: uma revisão sistemática

abstract

It is important to know about overweight and obesity situation of Brazilian children and adolescents. The present study aims to update scientific production, through a systematic review, on the prevalence and factors associated with overweight and obesity in Brazilian children and adolescents. Nine databases were verified, and 1,316 references were examined from 2018 to 2019. The electronic search was conducted by three independent researchers. All review steps followed a strategy based on PRISMA. 40 studies were included in this systematic review. Most studies use the World Health Organization classification criteria. The prevalence of overweight in Brazilian children and adolescents varies from 8.8% to 22.2% (boys: 6.2% to 21%; girls: 6.9% to 27.6%). The prevalence of obesity varied from 3.8% to 24% (boys: 2.4% to 28.9%; girls: 1.6% to 19.4%). It was observed that the socioeconomic factors (sex, skin color, economic level, region, mother's educational level, living in a rented house and without access to the internet), hereditary/genetic (family history of dyslipidemia and overweight and rs9939609 genotype) and behavioral (physical activity, screen time, eating habits, perceived body weight, health vulnerability, presence of a result close to home, alcoholic beverages, cigarette consumption) were associated with the outcome. It is concluded that the prevalence of overweight and obesity among Brazilian children and adolescents are worrisome and most of the factors associated with the outcomes are subject to change from the adoption of a healthy lifestyle.

Key words:
Overweight; Obesity; Risk factors; Childhood; Adolescence; Brazil

resumo

É importante conhecer a situação de sobrepeso e obesidade de crianças e adolescentes brasileiros. O presente estudo teve como objetivo atualizar a produção científica, por meio de uma revisão sistemática, sobre a prevalência e os fatores associados ao sobrepeso e à obesidade em crianças e adolescentes brasileiros. Nove bases de dados foram verificadas e 1.316 referências foram examinadas de 2018 a 2019. A busca eletrônica foi realizada por três pesquisadores independentes. Todas as etapas de revisão seguiram uma estratégia baseada no PRISMA. 40 estudos foram incluídos nesta revisão sistemática. A maioria dos estudos usou os critérios de classificação da Organização Mundial da Saúde. A prevalência de excesso de peso em crianças e adolescentes brasileiros variou de 8,8% a 22,2% (meninos: 6,2% a 21%; meninas: 6,9% a 27,6%). A prevalência de obesidade variou de 3,8% a 24% (meninos: 2,4% a 28,9%; meninas: 1,6% a 19,4%). Observou-se que os fatores socioeconômicos (sexo, cor da pele, nível econômico, região, escolaridade da mãe, morar em casa alugada e sem acesso à internet), hereditários/genéticos (histórico familiar de dislipidemia e excesso de peso e genótipo rs9939609) e comportamentais (atividade física, tempo de tela, hábitos alimentares, peso corporal percebido, vulnerabilidade à saúde, presença de resultado próximo a casa, bebida alcoólica, consumo de cigarro) estiveram associados ao desfecho. Conclui-se que as prevalências de sobrepeso e obesidade entre crianças e adolescentes brasileiros são preocupantes e a maioria dos fatores associados aos desfechos está sujeita a mudanças a partir da adoção de um estilo de vida saudável.

Palavras-chave:
Sobrepeso; Obesidade; Fatores de risco; Infância; Adolescência; Brasil

introduction

Overweight and obesity have been presented as one of the biggest problem public health face worldwide, mainly due to the increase in their prevalence observed in recent years in different age groups¹. In children and adolescents (5 to 19 years old), from 1975 to 2016, an increase of more than four times (from 4% to 18%) was observed in the prevalence of obesity¹.

The global epidemic of obesity in childhood and adolescence remains one of the greatest global health challenges¹. The obesity problem is not only related to excess body fat, but the relationship established between the highest levels of fat with metabolic and cardiovascular consequences (arterial hypertension, dyslipidemia, type 2 diabetes, atherosclerosis, metabolic syndrome)². In addition to physical health, obesity also stands out, impacting psychological (low self-esteem, anxiety, depression, mood changes) and social (discrimination, prejudice, exclusion)³.

The knowledge of the prevalence of overweight and obesity in children and adolescents, as well as the identification of the groups most exposed to this outcome are extremely relevant, because the earlier the interventions in these specific groups occur, the impact and the permanence of this condition in adulthood can be avoided or mitigated. Furthermore, it has been observed that the treatment of obesity in adulthood has been burdensome, and the problem becomes even more worrying since obese children are five times more likely to remain with this status in adulthood when compared to non-obese children⁴.

In view of the above, updating information about the prevalence and the groups most exposed to overweight and obesity, in pediatric age, is necessary for planning prevention and treatment actions aimed at combating childhood and youth obesity. Therefore, the present study aimed to update scientific production, through a systematic review, on the prevalence and factors associated with overweight and obesity in Brazilian children and adolescents.

methods

This systematic review was prepared in accordance with the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA)⁵ and was published in the OSF (DOI 10.17605/OSF.IO/SJGV9).

The searches were carried out on July 30, 2020, in the databases MEDLINE/Pubmed, Scopus, Web of Science, Virtual Health Library, SciELO, CINAHL/EBSCO, SPORTDiscus/EBSCO, PsycINFO/APA and Embase. All studies published in 2018 and 2019 were selected without language restriction. These databases were chosen because they include journals in the health field.

The terms used to elaborate the search key were consulted in the Medical Subject Headings (MeSH). The Boolean operators “OR” and “AND” were used to combine the terms, in English, (prevalence OR frequency) AND (obesity OR obese OR overweight) AND (children OR adolescent OR youth OR schoolchildren) AND (Brazil OR Brazilian). As an example of the searches, you can see the following key, used in the MEDLINE/Pubmed database: ((((prevalence) OR (frequency)) AND (((obesity) OR (obese)) OR (overweight))) AND ((((children) OR (adolescent)) OR (youth)) OR (schoolchildren))) AND ((Brazil) OR (Brazilian))).

The review included: a) articles published from April 1, 2018 to December 31, 2019, as the present study refers to an update of the findings of Simões et al.⁶; b) studies with a cross-sectional design; c) studies carried out with Brazilian children and adolescents (ages 7 to 19); d) published in Portuguese, English or Spanish; e) who used the body mass index as an anthropometric indicator to determine the status of body weight; f) studies in which the outcome was overweight and/or obesity; g) studies published in its full version. Studies were not included in which: a) overweight and obesity were treated as exposure factors; b) did not present the cutoff point used to classify overweight/obesity.

All stages of this review were conducted by three researchers, independently. Whenever they had any disagreement confronting the results of the reading steps, the opinion of a fourth expert researcher in the area was asked. After selecting the articles included in the review, the information on the author and year of publication were extracted, where the study was carried out, age range and sample size, cutoff point used to classify the status of body weight, prevalence of the outcome and associated factors. In the present study, we chose to present the prevalences and factors associated with overweight, obesity and overweight (defined as overweight + obesity), due to the different classifications used in the studies.

The National Institutes of Health's Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies⁷ was used in order to assess the risk of bias in the studies included in the review. This tool is specific for cohort or cross-sectional studies and has 14 evaluation criteria, which were applied individually for each study. Each criterion can receive the answers “yes”, “no”, “not applicable” or “not reported”. In order to classify the risk of bias, a sum of criteria was obtained that obtained a “yes” answer. Studies that scored 0 to 6 were classified as “high risk of bias”, 7 to 8 “moderate” and 9 to 14 “low”.

results

Searches of selected databases resulted in a total of 1,316 records. After excluding duplicates (n = 579), reading titles (n = 659), abstracts (n = 31) and full texts (n = 23), a total of 40 studies were considered eligible to make up the present systematic review (Figure 1).

Figure 1
Flowchart diagram of studies selection.

The main characteristics of the studies included in this review are shown in Table 1. The total sample, considering all studies, was greater than 266,529 children and adolescents aged 7 to 19 (two studies with nationally representative data did not specify the final sample).

Table 1
Characteristics of studies on the prevalence of overweight and obesity in Brazilian children and adolescents.

Author/year	Location	Sample	Age (years old)	Overweight (%)			Obesity (%)			Overweight (%)			Cutoff	Statistical analysis
				Boys	Girls	Total	Boys	Girls	Total	Boys	Girls	Total
Bezerra et al. (2018)8	Recife, PE	2400 (46.4% girls)	12 to 17	-	-	17.0	-	-	9.6	-	-	26.6	WHO	Poisson regression
Borges et al. (2018)9	Family Budget Research (POF- Brasil)	6784 (50.4% girls)	10 to 18	-	-	17.7	-	-	4.6	-	-	22.3	IOTF	Logistic regression
Chaput et al. (2018)10	São Paulo, SP	484 (51% girls)	09 to 11	-	-	-	-	-	21.7	-	-	-	WHO	-
Cnop et al. (2018)11	Rio de Janeiro, RJ	1749 (49.9% girls)	10 to 19	-	-	21.0	-	-	14.8	-	-	35.8	WHO	-
Conde et al. (2018)12	National School Health Survey (PeNSE-Brasil)									21.4	22.9	22.2	IOTF	-
Corrêa et al. (2018)13	Florianópolis, SC	2195 (47.8% girls)	07 to 14							37.6	29.0	33.5	WHO	Logistic regression
Cureau et al. (2018)14	Study of Cardiovascular Risks in Adolescents (ERICA-Brasil)	62063 (54.9% girls)	12 to 17									25.8	WHO	Poisson regression
Dumith et al. (2018)15	Caracol, PI	1075 (52.4% girls)	13 to 19	-	-	-	-	-	-	9.2	11.0	10.1	WHO	-
Fradkin et al. (2018)16	AM, CE, RS and SC	1738 (51% girls)		9.9	12.9	-	9.1	6.0	-	19.0	18.9	-	CDC	Logistic regression
Jardim et al. (2018)17	Goiânia, GO	1169 (53.1% girls)	12 to 17	-	-	-	-	-	-	29.0	18.2	23.3	WHO	-
Leal et al. (2018)18	Florianópolis, SC	1232 (49.3% girls)	07 to 10	-	-	-	-	-	-	-	-	34.4	WHO	Multilevel linear regression
Martini et al. (2020)19	Campinas, SP	822 (49.4% girls)	10 to 19	17.1	15.3	16.2	13.3	6.9	10.2	30.4	22.2	26.4	WHO	Chi-squared
Murphy et al. (2018)20	Brasil (ISAAC)	Nationally representative data	13 to 14	11.7	11.3	-	2.4	1.6	-	14.1	12.9	-	IOTF	-
Pereira et al. (2018)21	São Paulo, SP	822 (53% girls)	12 to 19	-	-	19.5	-	-	9.3	-	-	28.8	WHO	-
Pereira et al. (2018)22	São Paulo, SP	377	12 to 19	-	-	-	-	-	-	-	-	29.4	WHO	-
Previato and Behrens (2018)23	Minas Gerais	132 (51% girls)	15 to 19	7.7	13.4	10.6	9.3	6.0	7.6	17.0	19.4	18.2	WHO	-
Reuter et al. (2018)24	Santa Cruz do Sul, RS	381 (50.4% girls)	07 to 17	-	-	-	-	-	-	-	-	35.7	WHO	Poisson regression
Rossi et al. (2018)25	Florianópolis, SC	2484	07 to 14	-	-	-	-	-	-	21.5	12.7	34.2	WHO	Multivariate linear regression
Silva and Hasselmann (2018)26	Rio de Janeiro, RJ	1594 (56.2 girls)	13 to 19	-	-	-	-	-	-	16.5	18.6	17.7	WHO	Logistic regression
Silva Filho and Ybargollin (2019)27	Paraguaçu Paulista, SP	263 (44.1% girls)	10 to 15	19.7	27.6	-	9.5	15.5	-	29.2	43.1	-	Conde and Monteiro	-
Andrade et al. (2019)28	Salvador, BA	1496 (57.1% girls)	11 to 17	9.2	8.6	8.8	7.0	5.1	5.9	16.2	13.7	14.7	WHO	Chi-squared
Assis et al. (2019)29	Juiz de Fora, MG	661 (51.7% girls)	07 to 14	-	-	-	14.7	13.2	13.9	-	-	-	WHO	Logistic regression
Barbosa et al. (2019)30	Montes Claros, MG	635 (60.9% girls)	10 to 16	-	-	-	-	-	-	27.8	35.0	32.8	WHO	Poisson regression
Barbosa et al. (2019)31	Recife, PE	225 (56.4% girls)	10 to 19	15.3	24.4	20.4	13.3	18.1	16.0	28.6	42.5	36.4	WHO	Logistic regression
Dalmaso et al. (2019)32	Vitória, ES	572 (54.2% girls)	07 to 14	20.6	21.0	20.8	6.5	7.7	7.2	27.1	28.7	28.0	IOTF	-
Fávaro et al. (2019)33	Pesqueira, PE	139	07 to 09	-	-	-	-	-	-	-	-	2.9	WHO	-
Francesquet. (2019)34	Santa Cruz do Sul, RS	1243 (54.7% girls)	07 to 17	-	-	-	-	-	-	-	-	29.1	CDC	Logistic regression
Gonçalves et al. (2019)35	Brazil (ERICA)	73399 (49.8% girls)	12 to 17	-	-	-	9.1	7.6	8.4	-	-	-	WHO	Logistic regression
Guimarães et al. (2019)36	Curitiba, PR	997 (57% girls)	12 to 17	21.0	17.5	19.0	8.2	8.5	8.4	29.2	26.0	27.4	WHO	-
Lamarão et al. (2019)37	Macapá, AM	306 (48.7% girls)	10 to 19	6.2	6.9	-	2.6	3.6	-	8.8	10.5	-	WHO	Logistic regression
Leal et al. (2019)38	Brasil (PeNSE)	10926	13 to 17	-	-	-	-	-	-	23.7	23.8	23.7	WHO	Logistic regression
Li et al. (2019)39	São Paulo, SP	435 (51.5% girls)	09 to 11	-	-	-	-	-	21.8	-	-	-	WHO	Logistic regression
Neves et al. (2019)40	Juiz de Fora, MG	480 (57.5% girls)	14 to 19	-	-	18.6	-	-	9.5	-	-	28.1	WHO	-
Oliveira et al. (2019)41	Study of Cardiovascular Risks in Adolescents (ERICA-Brasil)	73624 (55.4% girls)	12 to 17	-	-	-	-	-	-	25.7	25.3	25.5	WHO	-
Pereira et al. (2019)42	Pelotas, RS	596 (48.2% girls)	07 to 08	-	-	-	28.9	19.4	24.0	-	-	-	WHO	Multiple linear regression
Rossi et al. (2019)43	Criciúma, Florianópolis, Joinville, Blumenau, Jaraguá do Sul, Lages, Chapecó and Joaçaba, SC	3930 (52% girls)	07 to 10	-	-	-	-	-	-	-	-	20.9	IOTF	Logistic regression
Rossi et al. (2019)44	Florianópolis, SC	2484 (56.5% girls)	07 to 14	-	-	21.5	-	-	12.7	-	-	34.2	WHO	Multivariate linear regression
Santos et al. (2019)45	Santa Catarina	6366	15 to 19	19.0	13.3	15.7	4.7	3.1	3.8	23.7	16.4	19.5	WHO	-
Santos et al. (2019)46	Hinterland and Agreste (dry region) of PE	179 (67% girls)	10 to 19	6.8	16.7	13.4	10.2	5.0	6.7	17.0	21.7	20.1	WHO	Poisson regression
Soria et al. (2019)47	Acreúna, GO	72	10 to 15	-	-	22.2	-	-	18.1	-	-	40.3	WHO	-

• WHO: World Health Organization; IOTF: International Obesity Task Force.

According to the regions, most of the studies were carried out in the Southeast (32.5%), followed by the South (25%), studies with nationwide data (17.5%), Northeast (15%), Center- West (5%), a study in the North region (2.5%) and one with data from 10 cities in four states (2.5%). Most studies (80%) used the criteria of the World Health Organization (WHO) to determine overweight/obesity, 12.5% ​​used the cutoff points of the International Obesity Task Force (IOTF), 5% used the criteria of Centers of Disease Control and Prevention (CDC), and a study used the national cutoffs of Conde and Monteiro.

The supplementary file 1 (https://osf.io/4k5r8/) shows the risk of bias in the studies included in the systematic review. It was observed that 32.5% (n = 13) of the studies received the classification “good”, 45% (n = 18) received the classification “reasonable” and 22.5% (n = 9) were classified as “bad”.

The average prevalence of overweight was 13.7% in boys, 15.7% in girls and 17.5% in the total sample. The average prevalence of obesity was 9.9% in boys, 8.5% in girls and 11.7% in the total sample. The range of overweight prevalences ranged from 2.9% to 40.3%, with the general average of overweight prevalences equaling 26.1%. The average overweight in boys and girls did not differ (22.5%) (Table 1).

Factors associated with overweight and obesity in Brazilian children and adolescents

Among the total of 40 studies included in the narrative synthesis, 23 investigated the factors associated with overweight and obesity in Brazilian children and adolescents (Table 2). For a better presentation of the results, we chose to group on socioeconomic, hereditary/genetic and behavioral factors.

Table 2
Factors associated with overweight and obesity in Brazilian children and adolescents.

Author/year	Associated factors
Borges et al. (2018)9	The greater adherence to the Snacks food pattern and the fast-food pattern increases the chances of EW.
Conde et al. (2018)12	Adolescents who declared themselves to be black or indigenous, from the south, from the urban area and from the lower fifths of income are more likely to be overweight.
Corrêa et al. (2018)13	Being male, using public markets/greengrocers and the presence of restaurants in the vicinity of the residence increase the chances of OW/OB.
Cureau et al. (2018)14	A higher lifestyle risk score (physical inactivity, high screen time, low fiber consumption, alcohol and tobacco consumption) increases the chances of OW/OB.
Fradkin et al. (2018)16	Boys were less likely to have OW and more likely to have OB.
	In relation to the region, in general, living in the south was associated with OB while in girls, living in the north was associated with OW.
	The high economic level was associated with overweight and obesity.
	In relation to population density, living in the urban region was associated with OW in general and in girls.
	Regarding race, black girls were more likely to have OB.
Leal et al. (2018)18	Boys living in households with three or more people per room and those with a monthly family income between 2 and 5 minimum wages had a lower BMI z score. Having a higher frequency of daily intake of sweets was inversely associated with BMI. Having an obese mother and high birth weight were associated with a higher BMI.
	In girls, having a monthly family income below 2.5 minimum wages and an income between 5 and 10 minimum wages was negatively associated with BMI. Having an overweight and obese mother, having high birth weight and a higher frequency of eating sweets were positively associated with BMI.
Martini et al. (2018)19	Boys had a higher prevalence of OB and adolescents aged 10 to 14 had a higher prevalence of OW and OB.
Rossi et al. (2018)25	Low-income schoolchildren who live in intermediate distances and close to parks/playgrounds had lower BMI compared to schoolchildren who live far from these places.
	Low-income schoolchildren who live at intermediate distances from the beaches have a lower BMI compared to those who live farther away. Schoolchildren who live at intermediate distances and close to soccer fields have higher BMI values.
Reuter et al. (2018)24	OW/OB was less prevalent in adolescents aged 11 to 17.
	Having an obese maternal father and grandmother, being overweight at birth and having the genotype (rs9939609) increases the chances of OW/OB.
Silva and Hasselmann (2018)26	Girls who receive physical aggression are less likely to have EW.
Andrade et al. (2019)28	Post-pubertal adolescents had a higher prevalence of OW and OB.
Barbosa et al. (2019)30	Having a family history of dyslipidemia and alcohol intake increases the chances of EW.
Assis et al. (2019)29	The older you are, the less likely you are to have OB.
	Children and adolescents residing in urban areas were less likely to be obese.
	Adolescents with higher income tertiles and higher health vulnerability index were more likely to be obese.
Barbosa et al. (2019)31	Total sample: adolescents who rated themselves as “fat” had a higher prevalence of EW.
	Boys: not having access to the internet, having less than four family members, spending more than two hours a day in front of the screen on the weekend were factors that increased the likelihood of EW.
	Girls: having self-perceived weight in “normal” and “fat” increased the chances of having EW.
Francesquet et al. (2019)34	Having a father with hypertension, having a father and mother with OB increase the chances of having OW /OB.
Gonçalves et al. (2019)35	Adolescents who studied in schools that offered food were less likely to have OB compared to those who studied in schools that did not offer food.
Lamarão et al. (2019)37	Drinking alcohol, living at home with more than six people and making fashionable diets were positively associated with EW, while practicing physical activities was negatively associated with EW.
Leal et al. (2019)38	Living in the South and Southeast, being 13 to 15 years old, having a mother with complete or incomplete higher education, consuming vegetables more than four days a week and consuming sweets four days or less a week increase the chances of having EW.
	Living with more than 3 people reduces the chance of EW.
Li et al. (2019)39	Those with low MVPA levels during the week and during the weekend are more likely to have OB.
	Children with high levels of MVPA during the week and low at the weekend and those with low levels of MVPA during the week and at the weekend are more likely to OB.
Rossi et al. (2019)43	In public school students, having an obese father or an obese father and mother increases the chances of OW/OB.
	In private school students, having an obese father and consuming canteen snacks increases the chances of OW/OB.
Rossi et al. (2019)44	In low-income schoolchildren who live far from parks and playgrounds, they presented higher BMI values.
	Schoolchildren with high family income who live farther from soccer fields had lower BMI values.
Pereira et al. (2019)42	The greater the degree of difficulty in maintaining the biological rhythm, the greater the BMI.
Santos et al. (2019)46	Having a rented or rented house, light nutritional security, drinking alcohol, perceiving your weight with OW/OB and being in the 10 to 14 age group increase the chances of having EW.

• Note. EW: excess weight; BMI: body mass index; OW: overweight; OB: obesity

Socioeconomic factors

The groups most exposed to overweight and obesity were male^13,16,19, black or indigenous^12,16, of low and high economic status¹⁶ and residing in the South^12,16,38, Southeast³⁸ and North¹⁶.

In addition, having a mother with complete or incomplete higher education³⁸, having a rented or rented house⁴⁶ and without internet access³¹, being black or indigenous^12,16 increase the chances of children and adolescents being overweight /obesity. Additionally, post-pubertal adolescents²⁸ are also more likely to have the outcome.

Regarding age, divergent results were observed. Reuter et al.²⁴ found that adolescents aged 11 to 17 were more likely to be overweight/obese. On the other hand, Martini et al.¹⁹ and Santos et al.⁴⁶ found that adolescents aged 10 to 14 were more exposed to overweight and obesity. Leal et al.³⁸, observed that the groups most exposed to excess weight were adolescents aged 13 to 15. Regarding income, it was observed that adolescents in the lowest fifths are more likely to be overweight¹². On the other hand, Assis et al.²⁹ found that the chances of overweight/obesity increased in the higher income groups.

Another divergent variable refers to the number of people living with the child/adolescent. Lamarão et al.³⁷ found that living at home with more than six people increases the chances of being overweight/obese. Diverging from these findings, Barbosa et al.³¹ identified that living with less than four family members increases the chances of being overweight, while Leal et al.³⁸ revealed that living with more than 3 people reduces the chance of EW.

As for the area of ​​residence, while Fradkin et al.¹⁶ and Assis et al.²⁹ identified that children and adolescents who live in urban areas were less likely to be obese, Borges et al.⁹ found that living in the urban area increases the chances of being overweight.

Hereditary/genetic factors

Having a family history of dyslipidemia³⁰, having a father with hypertension and having a father, mother and maternal grandmother with obesity increase the chances of children and adolescents being overweight/obese^18,24,25,34. In addition, it was observed that adolescents with the rs9939609 genotype are more likely to be overweight/obese³⁴.

Behavioral Factors

Regarding behavioral factors, the studies included in this systematic review, in general, point out that physical inactivity/low levels of physical activity^14,39, high screen time^14,31, low fiber consumption¹⁴, eating fad diets³⁷, inadequate diet^9,14,38, having perceived weight with overweight/obesity^31,46, presenting higher health vulnerability²⁹, having restaurants in the vicinity of the residence¹³, consuming vegetables four days or more a week³⁸, consuming alcohol and cigarettes^14,37,46 increase the chances of overweight and obesity. Silva and Hasselmann²⁶, observed that girls who suffer physical aggression are less likely to be overweight.

discussion

The prevalence of overweight in Brazilian children and adolescents ranged from 8.8% to 22.2%. In boys, this variation was from 6.2% to 21% and in girls from 6.9% to 27.6%. In regard to obesity, the prevalence varied from 3.8% to 24% in the total sample, from 2.4% to 28.9% in boys and from 1.6% to 19.4% in girls. Such evidence should be interpreted with caution because, although most studies have used the WHO criteria⁴⁸ for the classification of nutritional status, some studies have used the cutoff points of the IOTF^49,50 and Conde and Monteiro⁵¹. Nevertheless, the prevalence of overweight and obesity in childhood and adolescence has been considered a cause of concern due to its relationship with cardiovascular, psychological, and social diseases^2,3. In addition, overweight and obesity at these stages of life increase the likelihood that these conditions will persist into adulthood⁴.

According to the results found in the present study, it was possible to identify that the groups most exposed to overweight/obesity are boys^13,16,19, black and indigenous^12,16 and of low¹² and high economic status^16,29. In addition, those residing in the South^12,16,38, Southeast ³⁸ and North¹⁶ regions are the ones most likely to have the outcome. Still, children of mothers with complete or incomplete higher education³⁸, post-pubertal²⁸, who have a rented or rented house⁴⁶, and those who do not have access to the internet³¹.

It was observed that boys are more susceptible to overweight and obesity than girls. One of the possible assumptions regarding this result may be due to the fact that girls are more concerned with their body appearance and dieting to keep their bodies slim⁵², which consequently generates greater concern for the body and decreases the chances of overweight and obesity in adolescents. However, it should be noted that among adolescents on a diet the likelihood of being overweight and obese increases³⁷. Thus, there still seems to be a divergence in the associations between overweight/obesity and diet.

In addition, it was observed that black and indigenous children and adolescents were the groups most exposed to overweight and obesity. It is believed that this predisposition may happen due to the stresses triggered as a result of ethnic discrimination⁵³. Stress induces hormonal changes that can stimulate appetite and reduce satiety, contributing to an increase in body weight⁵⁴. Despite this evidence, it should be noted that socioeconomic conditions and lifestyle habits may be the most relevant factors for differences in the prevalence of overweight and obesity than, in fact, skin color.

Regarding the economic level, it seems that, regardless of the economic level, overweight and obesity are present, although we still see evidence pointing out that children and adolescents with a high economic level are more likely to end up. This pattern can be attributed to access to consumer goods and services, which, in part, may be related to the consumption of more caloric foods, and also to greater contact with technological means, which favor less engagement in regular health practice of physical activities⁵⁵.

In this context, the higher prevalence of overweight and obesity observed in the most developed regions of the country (South and Southeast), can be explained by the higher purchasing power in relation to the other Brazilian regions⁵⁶. These results may be linked to the higher average monthly household income, as observed by PNAD⁵⁶, in which in the Southeast region the monthly household income is R$ 1,720, while in the North and Northeast regions, monthly incomes are, respectively, R$ 872 and R$ 884. In other words, a higher income can influence the acquisition of foods, which are not always healthy, which can contribute to the increase in body weight.

Another group which is more exposed to overweight and obesity are children and adolescents whose mothers have a higher level of education. A higher level of education may represent better socioeconomic conditions⁵⁷, which corroborates the associations between higher economic levels and obesity⁵⁸.

Also in this context, having a rented or rented house and not having access to the internet, seen as factors associated with being overweight, can be indicators of worse socioeconomic conditions. Adolescents who do not have access to the internet and who do not live in their own home may not have the same economic conditions as their peers, making it impossible to have access to better nutritional quality food and leisure activities, such as practicing formal sports^59,60.

It was found in this review that the post-pubertal stage was associated with overweight/obesity. This association is explained by the sexual maturation process, a period in which the peak of growth occurs, characterized by an increase in height and body weight, an accelerated increase in muscle mass in boys and in adipose tissue in girls⁶¹. Thus, it is assumed that the weight gain acquired during the entire maturation process has been maintained by these adolescents.

Having a family history of dyslipidemia³⁰, having a hypertensive father and having an obese father, mother and maternal grandmother increase the chances of overweight/obesity in childhood and adolescence^18,24,25,34. In addition, it was observed that adolescents with the rs9939609 (FTO) genotype are more susceptible to overweight/obesity³⁴. The home environment, especially family habits, significantly influences the formation of eating behaviors and physical activity in children and adolescents^62,63. Confirming this, Todendi et al.⁶⁴ found that parents' weight contributes to their children's obesity.

Among the genetic polymorphisms of obesity, the FTO (rs9939609) was previously associated with obesity⁶⁴. The FTO variant accelerates weight gain in childhood^65-67, once it plays an important role in energy metabolism and in the regulation of human body homeostasis⁶⁸.

In general, the studies included pointed out that physical inactivity/low levels of physical activity^14,39, high screen time^14,31, low fiber consumption¹⁴, eating fad diets³⁷, food inadequate^9,14,38, having restaurants in the vicinity of the residence¹³, consuming vegetables four or more days a week³⁸, having perceived weight with overweight/obesity^31,46, presenting health vulnerability more discharge²⁹ and consuming alcohol and cigarettes^14,37,46 increase the chances of being overweight.

The relationship between low levels of physical activity and excess weight has been strongly emphasized in the literature, as there is a tendency among individuals with insufficient levels of physical activity to be more predisposed to overweight/obesity. One of the possible justifications for such an association may be linked to excessive time in sedentary behavior⁶⁹ and, consequently, a greater intake of unhealthy foods⁷⁰.

The relationship between overweight/obesity and screen time can be explained by the increase in food consumption^71-73. Nowadays children and adolescents have at their disposal a multitude of options for digital games on cheap or free platforms on a variety of devices, which lead these individuals to spend a long time in front of the screen⁷⁴. Despite such evidence, a systematic review conducted by Kracht et al.⁷⁴ revealed that the association between obesity and the use of video games is inconclusive, mainly due to the scarcity of longitudinal studies that evaluated the direct contribution of gambling to weight gain in children.

With regard to the association between inadequate diet and overweight/obesity, it is highlighted that one of the main factors that can explain this relationship is related to the easy access, the practicality and the low cost of ultra-processed foods when compared to better nutritional quality foods^75,76. A nationwide study revealed that there is an inverse relationship between the price of ultra-processed foods and obesity, highlighting that a 1% increase in the price of processed ultrasound would result in a reduction of 0.33% and 0.59% in the prevalence of overweight and obesity, respectively⁷⁷. To improve this situation, it is up to government authorities to rethink the effectiveness of the numerous existing public policies, in addition to raising the awareness of those responsible for schoolchildren about the importance of a diet with nutritional quality, as children and adolescents normally do not have autonomy for food choices.

The evidence regarding the relationship between alcohol consumption and obesity is still conflicting. If there is no control over several other factors (which may be the main limitations of the studies), such as sex, frequency and quantity of alcohol intake, the type of drink ingested, physical activity, sleep, among others, the associations may be biased⁷⁸. However, alcohol appears to be a risk factor in certain cases, especially if consumption is in excess⁷⁸.

In relation to smoking, associations with obesity are also controversial. Evidence suggests that smoking is related to increased abdominal fat⁷⁹, once smoking can increase insulin resistance, changing the distribution of body fat to the central region⁸⁰. Nonetheless, the association observed in this study legitimates the findings by Chiolero et al.⁸¹, who identified that as the number of cigarettes smoked per day increases, the chances of obesity are greater.

The association between perception of overweight/obesity and excess weight was confirmed by a systematic review that identified strong longitudinal evidence that perceiving being overweight was associated with greater weight gain or increased likelihood of developing overweight/obesity in the course of of time⁸². It is likely that these adolescents who perceive themselves to be overweight do not have effective attitudes to control their body weight and consequently continue with their weight above what is considered healthy.

The study by Corrêa et al.¹³, included in the review, identified that having restaurants around the residence was associated with overweight/obesity, however, the use of these restaurants did not show any association. It is possible that, despite living close to restaurants, individuals choose to consume food from other establishments that have not been investigated, such as shopping centers, schools, friends' houses, or even the use of delivery applications¹³. In addition, in order to understand these associations, the local characteristics of the investigated municipality must be taken into account, such as the number and diversity of restaurants and tourist activity.

Regarding the association between a higher index of vulnerability to health and overweight, the evidence suggests that living in neighborhoods with greater social deprivation increases the chances of having inappropriate health behaviors²⁹. In this scenario, it is assumed that in economically disadvantaged neighborhoods there are fewer opportunities for physical activity, as well as less access to stores and restaurants that offer healthier food.

Among the limitations of the present study, the following stand out: most studies were conducted in the three most developed regions of the country, which limits the generalization of results to all Brazilian regions. In addition, the use of different cutoff points to classify the outcomes characterizes the heterogeneity of the included studies, making it difficult to combine results. Furthermore, the inclusion of inappropriate participants in the studies was not controlled in the present review, which can skew the findings in any direction in the estimates. Other limitations include the heterogeneity of the studies in terms of sample selection, standardization of measurements between evaluators and calibration of the equipment used to obtain the measurements and the confounding variables used in the analyzes. Finally, the potential publication bias cannot be ruled out, which would make the inclusion of smaller studies unfeasible, with null results that tend not to be published.

conclusion

According to the evidence observed in the present systematic review, it is concluded that the prevalence of overweight and obesity in Brazilian children and adolescents are worrisome and that most risk factors associated with outcomes are subject to modifications from the adoption of a style healthier lifestyle.

supplementary material

Supplementary material accompanies this paper.

Supplementary file 1. Bias risk assessment. Free access in: https://osf.io/4k5r8/

This material is available as part of the online article from http://www.scielo.br/rbcdh

• How to cite this articlePelegrini A, Bim MA, Souza FU, Kilim KSS, Pinto AA. Prevalence of overweight and obesity in Brazilian children and adolescents: a systematic review. Rev Bras Cineantropom Desempenho Hum 2021, 23:e80352. DOI: http://doi.org/10.1590/1980-0037.2021v23e80352
• Funding This work was supported by the Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina (FAPESC) [grant number 2019TR784].

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Publication Dates

• Publication in this collection
  21 June 2021
• Date of issue
  2021

History

• Received
  16 Dec 2020
• Accepted
  27 Apr 2021