Total cholesterol and low-density lipoprotein alterations in children and adolescents from Brazil: a prevalence meta-analysis

Silva, Thales Philipe Rodrigues da; Mendes, Larissa Loures; Barreto, Virgínia Maria Jorge; Matozinhos, Fernanda Penido; Duarte, Camila Kümmel

doi:10.20945/2359-3997000000508

Thales Philipe Rodrigues da Silva

Escola de Enfermagem, Programa de Pós-graduação em Enfermagem, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil

http://orcid.org/0000-0002-7115-0925

Larissa Loures Mendes

Departamento de Nutrição, Escola de Enfermagem, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil

http://orcid.org/0000-0002-0031-3862

Virgínia Maria Jorge Barreto

Departamento de Nutrição, Escola de Enfermagem, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil

http://orcid.org/0000-0001-7296-2979

Fernanda Penido Matozinhos

Departamento de Enfermagem Materno-Infantil e Saúde Pública, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil

http://orcid.org/0000-0003-1368-4248

Camila Kümmel Duarte Correspondence to: Camila Kümmel Duarte Departamento de Nutrição, Escola de Enfermagem, Universidade Federal de Minas Gerais Avenida Alfredo Balena, 190, Santa Efigênia 30130-100 – Belo Horizonte, MG, Brasil. camila.kummel@gmail.com

Departamento de Nutrição, Escola de Enfermagem, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil

http://orcid.org/0000-0003-1930-3282

Correspondence to: Camila Kümmel Duarte Departamento de Nutrição, Escola de Enfermagem, Universidade Federal de Minas Gerais Avenida Alfredo Balena, 190, Santa Efigênia 30130-100 – Belo Horizonte, MG, Brasil. camila.kummel@gmail.com

Authorship: VMJB, TPRS and CKD conducted the literature research, extracted the data and evaluated the quality of studies. CKD performed the statistical analysis. VMJB, TPRS, LLM, FPM and CKD drafted/revised the manuscript. TPRS and CKD designed the study and interpreted the results. All authors (VMJB, TPRS, LLM, FPM and CKD) made substantial contributions and approved the final version.

Disclosure: no potential conflict of interest relevant to this article was reported.

Study	Year	Sample		Region	City	State		Population origin	Criteria		Quality assessment
									CT	LDL
CHILDREN
Almeida ( ²¹21 Almeida PCD, Silva JP, Pinasco GC, Hegner CC, Mattos DC, Potratz MO, et al. Perfil lipídico em escolares de Vitória – Brasil. J Hum Growth Dev. 2016;26:61-6. )	2016	511	6 to 9 y	Southeast	Vitória	Espírito Santo		Public School	≥170	≥130	7
Barbalho ( ²²22 Barbalho SM, Oshiiwa M, Lia CSF, Finalli EFR, Paiva-Filho ME, et al. Diabetes & Metabolic Syndrome: Clinical Research & Reviews Metabolic syndrome and atherogenic indices in school children: A worrying panorama in Brazil. Diabetes Metab Syndr Clin Res Rev. 2017:10-2. )	2017	150	6 to 10 y	Southeast	Lins	São Paulo		Public School	≥170	≥130	7
Filgueiras ( ²³23 Filgueiras MDS, Suhett LG, Silva MA, Rocha NP, Novaes JF. Lower vitamin D intake is associated with low HDL cholesterol and vitamin D insufficiency/deficiency in Brazilian children. Public Health Nutr. 2018;21:2004-12. )	2018	378	8 to 9 y	Southeast	Viçosa	Minas Gerais		Public and Private Schools	≥170	≥100	8
Nobre ( ²⁴24 Nobre LN, Lamounier JA, Franceschini SCC. Sociodemographic, anthropometric and dietary determinants of dyslipidemia in preschoolers. J Pediatr (Rio J). 2013;89:462-9. )	2013	227	5 y	Southeast	Diamantina	Minas Gerais		–	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	8
Rinaldi ( ²⁵25 Rinaldi AEM, Oliveira EP de, Moreto F, Gabriel GFCP, Corrente JE, Burini RC. Dietary intake and blood lipid profile in overweight and obese schoolchildren. BMC Res Notes. 2012;5:1-7. )	2012	147	7,4 ± 1,4 y ^* * Mean and standard deviation.	Southeast	Botucatu	São Paulo		not informed	≥200	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	7
Silva ( ²⁶26 Silva NP da, Souza FIS de, Pendezza AI, Fonseca FLA, Hix S, Oliveira AC, et al. Homocysteine and cysteine levels in prepubertal children : Association with waist circumference and lipid profile. Nutrition. 2013;29:166-71. )	2013	677	6 to 10 y	Southeast	Santo André	São Paulo		Public School	≥200	≥130	6
Teixeira ( ²⁷27 Teixeira FDC, Pereira FEF, Pereira AF, Ribeiro BG. Overweight or obesity and abdominal obesity and their association with cardiometabolic risk factors in Brazilian schoolchildren: A cross-sectional study. Nutrition. 2020;78:110780. )	2020	501	6 to 10 y	Southeast	Macaé	Rio de Janeiro		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	8
ADOLESCENTS
Arruda-Neta ( ²⁸28 Arruda-Neta ACP, Júnior JCF, Martins PR, Ferreira FELL. Conicity index as a predictor of changes in the lipid profile of adolescents in a city in Northeast Brazil. Cad Saúde Pública. 2017;33:1-12. )	2017	774	10 to 14 y	Northeast	João Pessoa	Paraíba		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	7
Bauman ( ²⁹29 Bauman CD, Bauman JM, Mourão DM, Pinho L, Brito MFSF, Carneiro ALG, et al. Dyslipidemia prevalence in adolescents in public schools. Rev Bras Enferm. 2020;73(3):e20180523. )	2020	635	10 and 16 y	Southeast	Montes Claros	Minas Gerais		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Beck ( ³⁰30 Beck CC, Lopes AS, Giuliano ICB, Borgatto AF. Cardiovacular risk factors in adolescents from a town in the Brazilian South: prevalence and association with sociodemographic variables. Rev Bras Epidemiol. 2011;14:36-49. )	2011	660	14 to 19 y	South	Três de Maio	Santa Catarina		Public and Private Schools	≥170		8
Carvalho ( ³¹31 Carvalho DF, Paiva AA, Melo ASO, Ramos AT, Medeiros JS, Medeiros CCM, et al. Blood lipid levels and nutritional status of adolescents. Rev Bras Epidemiol. 2007;10:491-8. )	2007	180	14 to 17 y	Northeast	Campina Grande	Paraíba		Public and Private Schools	≥170	≥110 ^\|\| \|\| Friedewald formula to estimate LDL.	8
Chaves ( ³²32 Chaves OC, Franceschini SCC, Ribeiro SMR, Sant’Ana LFR, Faria CG, Priore SE. Comparison of the biochemical, anthropometric and body composition variables between adolescents from 10 to 13 years old and their parents. Nutr Hosp. 2012;27:1127-33. )	2012	120	10 to 13 y	Southeast	Viçosa	Minas Gerais		Public School	≥170	≥130	9
Enes ( ³³33 Enes CC, Silva JR. Association between excess weight and serum lipid alterations in adolescents. Ciênc Saúde Coletiva. 2018;23:4055-64. )	2018	525	10 to 19 y	Southeast	Piracicaba	São Paulo		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	5
Faria ( ³⁴34 Faria ER, Gontijo CA, Franceschini SCC, Peluzio MCG, Priore SE. Body composition and risk for metabolic alterations in female adolescents. Rev Paul Pediatr. 2014;32:207-15. )	2014	100	14 to 17 y	Southeast	Viçosa	Minas Gerais		Public School	≥170	≥130	8
Faria-Neto ( ¹⁴14 Faria-Neto JR, Bento VFR, Baena CP, Olandoski M, Gonçalves LGO, Abreu GA, et al. ERICA: prevalência de dislipidemia em adolescentes brasileiros. Rev Saude Publica. 2016;50:1s-10s. )	2016	38,069	13 to 17 y	Brazil ^† † ERICA – nationwide, school based and carried out in all regions of the country				Public and Private Schools	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Gadelha ^‡ ‡ Data from 2012 and 2013 ( ³⁵35 Gadelha PCFP, de Arruda IKG, Coelho PBP, Queiroz PMA, Maio R, da Silva Diniz A. Consumption of ultraprocessed foods, nutritional status, and dyslipidemia in schoolchildren: a cohort study. Eur J Clin Nutr. 2019;73(8):1194-9. )	2019	236	15.1 ± 1.4 ^* * Mean and standard deviation.	Northeast	Recife	Pernambuco		Cohort study of the public school	≥170	≥130	7
Gonçalves ( ³⁶36 Gonçalves VSS, Chaves OC, Ribeiro SMR, Sant’Ana LFR, Franceschini SCC, Priore SE. Household availability of lipids for consumption and its relationship with serum lipids in adolescents. Rev Paul Pediatr. 2012;30:229-36. )	2012	95	10 to 13 y	Southeast	Viçosa	Minas Gerais		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	10
Guimarães ( ³⁷37 Guimarães RF, Silva MP, Mazzardo O, Martins RV, Watanabe PI, Campos W. Metabolic risk factors clustering among adolescents: a comparison between sex, age and socioeconomic status. Ciênc Saúde Coletiva. 2019;24:545-52. )	2019	997	12 to 18 y	South	Curitiba	Paraná		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	8
Lunardi ( ³⁸38 Lunardi CC, Petroski ÉL. Índice de Massa Corporal, Circunferência da Cintura e Dobra Cutânea Triciptal na Predição de Alterações Lipídicas em Crianças com 11 Anos de Idade. Arq Bras Cir Dig. 2008;52:1009-14. )	2008	374	11.25 ± 0,28y ^* * Mean and standard deviation.	South	Santa Maria	Rio Grande do Sul		Public and Private Schools	≥200	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Lunardi ( ³⁹39 Lunardi CC, Moreira CM, Santos DL dos. Blood Lipids Abnormalities and Overweight Prevalence in Students of Santa Maria, RS, Brazil. Rev Bras Med Esporte. 2010;16:250-3. )	2010	358	16 y	South	Santa Maria	Rio Grande do Sul		Public and Private Schools	≥200		9
Mastroeni ( ⁴⁰40 Mastroeni SSB, Mastroeni MF, Gonçalves MC, Debortoli G, Silva NN, Bernal RTI, et al. Cardiometabolic Risk Markers of Normal Weight and Excess Body Weight in Brazilian Adolescents. Appl Physiol Nutr Metab. 2016;41:659-65. )	2016	222	15 to 17 y	South	Joinville	Santa Catarina		not informed	≥170	≥130	8
Melo ( ⁴¹41 Melo EMFS, Azevedo GD, Silva JD, Lemos TMAM, Maranhão TMO, Freitas AKMSO, et al. Clustering of risk factors for cardiometabolic diseases in low-income, female adolescents. Arch Endocrinol Metab. 2016;60:205-10. )	2016	196	11 to 19 y	Northeast	Natal	Rio Grande do Norte		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Pereira ( ⁴²42 Pereira PB, Arruda IKG, Cavalcanti AMTS, Diniz AS. Lipid Profile of Schoolchildren from Recife, PE. Arq Bras Cardiol. 2010;95:606-13. )	2010	470	10 to 14 y	Northeast	Recife	Pernambuco		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Pinto ( ⁴³43 Pinto KAC, Priore SE, Carvalho KMB. Parâmetros metabólicos e fatores de risco associados à obesidade abdominal em adolescentes do sexo feminino de escolas públicas do Distrito Federal (Brasil). Arch Latinoam Nutr. 2011;61:55-65. )	2011	117	14 to 17 y	Midwest	Brasília	Distrito-Federal		Public School	≥150	≥110 ^\|\| \|\| Friedewald formula to estimate LDL.	8
Queiroz ( ⁴⁴44 Queiroz DJM, Silva AS, Dinis AS, Carvalho AT, Araújo EPS, Neves JPR, et al. Vitamin D insufficiency/deficiency and its association with cardiometabolic risk factors in Brazilian adolescents. Nutr Hosp. 2019;36:142-8. )	2019	220	15 to 19 y	Northeast	João Pessoa	Paraíba		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Romero ( ⁴⁵45 Romero A, Rezende LFM, Romero SCS, Villar BS. Relationship between obesity and biochemical markers in Brazilian adolescents. Rev Bras Cineantropom Desempenho Hum. 2014;16:268-76. )	2014	199	10 to 14 y	Southeast	Piracicaba	São Paulo		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Scheer ( ⁴⁶46 Scheer C, Helal L, Ferrari F, Belém LJ, Fabiano LCC, Pinheiro LT, et al. The Olympic Experimental Gymnasium Program and its Association with the Prevalence of Cardiovascular Risk Factors in Adolescents: A Cross-Sectional Study. Arq Bras Cardiol. 2019;112(6):775-81. )	2019	394 ^§ § Data from regular schools.	13.3 ± 1,5y ^* * Mean and standard deviation.	Southeast	Rio de Janeiro	Rio de Janeiro		Public School	≥170		7
Sousa ( ⁴⁷47 Sousa MACA, Guimarães ICB, Daltro C, Guimarães AC. Association between Birth Weight and Cardiovascular Risk Factors in Adolescents. Arq Bras Cardiol. 2013;101:9-17. )	2013	250	11 to 18 y	Northeast	Salvador	Bahia		Public and Private Schools	>170	>110	8
Vasconcelos( ⁴⁸48 Vasconcelos IQA, Stabelini-Neto A, Mascarenhas LPG, Bozza R, Ulbrich AZ, Campos W, et al. Cardiovascular Risk Factors in Adolescents with Different Levels of Energy Expenditure. Arq Bras Cardiol. 2008;91:227-33. )	2008	140	12 to 16 y	South	São Mateus do Sul	Paraná		Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
CHILDREN AND ADOLESCENTS
Alcântara-Neto ( ⁴⁹49 Alcântara-Neto OD, Silva RCR, Assis AMO, Pinto EJ. Factors associated with dyslipidemia in children and adolescents enrolled in public schools of Salvador, Bahia. Rev Bras Epidemiol. 2012;15:335-45. )	2012	937	7 to 14 y	Northeast	Salvador		Bahia	Public School	≥170		9
Bergmann ( ⁵⁰50 Bergmann MLA, Bergmann GG, Halpern R, Rech RR, Constanzi CB, Alli LR. Associated Factors to Total Cholesterol: School Based Study in Southern Brazil. Arq Bras Cardiol. 2011;97:1-9. )	2011	1,294	7 to 12 y	South	Caxias do Sul		Rio Grande do Sul	Public and Private Schools	≥170		9
Burgos ( ⁵¹51 Burgos MS, Tornquist D, Tornquist L, Reuter CP, Garcia EL, Renner JDP, et al. Cardiometabolic risk factors associated with active commuting to school. Rev Paul Pediatr. 2019;37:181-7. )	2019	1,743	7 to 17 y	South	Santa Cruz do Sul		Rio Grande do Sul	Public and Private Schools	≥200	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Burgos ( ⁵²52 Burgos MS, Reuter CP, Possuelo LG, Valim ARM, Renner JDP, Tornquist L, et al. Obesity parameters as predictors of early development of cardiometabolic risk factors. Ciênc Saúde Coletiva. 2015;20:2381-8. )	2015	1,254	7 to 17 y	South	Santa Cruz do Sul		Rio Grande do Sul	not informed	≥200	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	8
Guimarães ( ⁵³53 Guimarães ICB, Guimarães AC. Prevalence of Cardiovascular Risk Factors in Selected Samples of Schoolchildren – Socioeconomic Influence. Prev Cardiol. 2005;8:23-8. )	2005	366	6 to 12 y	Northeast			Bahia	Public and Private Schools	≥170		6
Giuliano ( ⁵⁴54 Giuliano ICB, Coutinho MSSA, Freitas SFT, Pires MMS, Zunino JN, Ribeiro RQC. Serum Lipids in School Kids and Adolescents from Florianópolis, SC, Brazil – Healthy Floripa 2040 Study. Arq Bras Cardiol. 2005;85:85–91. )	2005	1,053	7 to 18 y	South	Florianópolis		Santa Catarina	Public and Private Schools	≥170		8
Gomes ( ⁵⁵55 Gomes ÉIL, Zago VHS, Faria EC. Evaluation of Lipid Profiles of Children and Youth from Basic Health Units in Campinas, SP, Brazil: A Cross-Sectional Laboratory Study. Arq Bras Cardiol. 2020;114(1):47-56. )	2020	61,870	2 to 19y	Southeast	Campinas		São Paulo	Basic health unit	≥170	≥110	8
Moura ( ⁵⁶56 Moura EC, Castro CM, Mellin AS, Figueiredo DB. Lipidic profile among schoolchildren, Brazil. Rev Saude Publica. 2000;34:499-505. )	2000	1,600	7 to 14 y	Southeast	Campinas		São Paulo	Public School	≥170		10
Cunha ( ⁵⁷57 Cunha HP. Avaliação dos fatores de riscos cardiometabólicos e do efeito da atividade física e orientação nutricional em crianças e adolescentes. Florianópolis: Universidade Federal de Santa Catarina; 2014. )	2014	399	6 to 15 y	South	Botuverá		Santa Catarina	Public School	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Pereira( ⁵⁸58 Pereira A, Guedes AD, Verreschi ITN, Santos RD, Martinez TLR. Obesity and Its Association with Other Cardiovascular Risk Factors in School Children in Itapetininga, Brazil. Arq Bras Cardiol. 2004;93:253-60. )	2009	494	2 to 19 y	Southeast	Itapetininga		São Paulo	Public School	≥170	≥110 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Quadros ( ⁵⁹59 Quadros TMB de, Gordia AP, Silva LR, Silva DAS, Mota J. Epidemiological survey in schoolchildren: determinants and prevalence of cardiovascular risk factors. Cad Saúde Pública. 2016;32:1-17. )	2016	1,139	6 to 18 y	Northeast	Armagosa		Bahia	Public and Private Schools	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Quadros ( ⁶⁰60 Quadros TMB de, Gordia AP, Silva RCR da, Silva LR. Predictive capacity of anthropometric indicators for dyslipidemia screening in children and adolescents. J Pediatr (Rio J). 2015;91:455-63. )	2015	1,139	6 to 18 y	Northeast	Armagosa		Bahia	Public and Private Schools	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Reuter ( ⁶¹61 Reuter CP, Burgos L, Camargo MD, Possuelo LG, Reckziegel MB, Reuter ÉM, et al. Prevalence of obesity and cardiovascular risk among children and adolescents in the municipality of Santa Cruz do Sul, Rio Grande do Sul. Sao Paulo Med J. 2013;131:323-30. )	2013	564	8 to 17 y	South	Santa Cruz do Sul		Rio Grande do Sul	Public and Private Schools	≥170	≥130	10
Reuter ( ⁶²62 Reuter CP, Silva PT da, Renner JDP, Mello ED de, Valim AR de M, Pasa L, et al. Dyslipidemia is Associated with Unfit and Overweight-Obese Children and Adolescents. Arq Bras Cardiol. 2016;106:188-93. )	2016	1,243	7 to 17 y	South	Santa Cruz do Sul		Rio Grande do Sul	Public School	≥200	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	6
Ribas ( ⁶³63 Ribas SA, Silva LCS. Anthropometric indices predictors of dyslipidemia in children and adolescents from north of Brazil. Nutr Hosp. 2012;27:1228-35. )	2012	874	6 to 19 y	North	Belém		Pará	Public and Private Schools	≥170	≥130 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Ribas ( ⁶⁴64 Ribas SA, Silva LCS da. Cardiovascular risk and associated factors in schoolchildren in Belém, Pará State, Brazil. Cad Saúde Pública. 2014;30:577-86. )	2014	571	6 to 19 y	North	Belém		Pará	Public and Private Schools	≥170	≥110 ^\|\| \|\| Friedewald formula to estimate LDL.	9
Ribas ( ⁶⁵65 Ribas SA, Silva LCS da. Dyslipidemia in Schoolchildren from Private Schools in Belém. Arq Bras Cardiol. 2009;92:446-51. )	2009	437	6 to 19 y	North	Belém		Pará	Private School	≥170	≥110 ^\|\| \|\| Friedewald formula to estimate LDL.	8
Ribeiro ( ⁶⁶66 Ribeiro RC, Coutinho M, Bramorski MA, Giuliano IC, Pavan J. Association of the Waist-to-Height Ratio with Cardiovascular Risk Factors in Children and Adolescents: The Three Cities Heart Study. Int J Prev Med. 2010;1:39-49. )	2010	3,106	6 to 18 y	South and Southeast	Belo Horizonte Florianópolis Blumenau		Minas Gerais e Santa Catarina	Public and Private Schools	≥200	≥130	9

Diagnostic criteria for the definition of the lipid alterations	Quoted studies	Number of subjects	Summary prevalence estimate	95% confidence interval	Forest plot	p-value
Total cholesterol						0.094
>170 mg/dL, BSC	35	117,159	27.47%	24.36-30.82	Figure S1A
>200 mg/dL, NHLB	7	7,546	17.22%	9.52-29.15	Figure S1A
Low-density lipoprotein						0.040
>110 mg/dL, BSC	7	64,139	19.29%	15.21-24.16	Figure S1B
>130 mg/dL, NHLB	29	53,619	11.63%	7.45-17.71	Figure S1B

Database	Search strategy
PubMed	(((((“Brazil”[Mesh] OR “Brazil”))) AND ((“Child”[Mesh] OR “Child” OR “Children” OR “Adolescent”[Mesh] OR “Adolescent” OR “Adolescents” OR “Adolescence” OR “Teens” OR “Teen” OR “Teenagers” OR “Teenager” OR “Youth” OR “Youths” OR “Adolescents, Female” OR “Adolescent, Female” OR “Female Adolescent” OR “Female Adolescents” OR “Adolescents, Male” OR “Adolescent, Male” OR “Male Adolescent” OR “Male Adolescents”))) AND ((“Dyslipidemias/epidemiology”[Mesh] OR “Dyslipidemias/epidemiology” OR “Dyslipidemias/statistics and numerical data”[Mesh] OR “Dyslipidemias/statistics and numerical data” OR “Dyslipidemia” OR “Dyslipoproteinemias” OR “Dyslipoproteinemia” OR “lipid profile” OR “Cholesterol, VLDL”[Mesh] OR “Cholesterol, VLDL” OR “VLDL Cholesterol” OR “Pre-beta-Lipoprotein Cholesterol” OR “Cholesterol, Pre-beta-Lipoprotein” OR “Pre beta Lipoprotein Cholesterol” OR “Very Low Density Lipoprotein Cholesterol” OR “Prebetalipoprotein Cholesterol” OR “Cholesterol, Prebetalipoprotein” OR “Cholesterol, LDL”[Mesh] OR “Cholesterol, LDL” OR “Low Density Lipoprotein Cholesterol” OR “beta-Lipoprotein Cholesterol” OR “Cholesterol, beta-Lipoprotein” OR “beta Lipoprotein Cholesterol” OR “LDL Cholesterol” OR “Cholesteryl Linoleate, LDL” OR “LDL Cholesteryl Linoleate” OR “Cholesterol, HDL”[Mesh] OR “Cholesterol, HDL” OR “alpha-Lipoprotein Cholesterol” OR “Cholesterol, alpha-Lipoprotein” OR “alpha Lipoprotein Cholesterol” OR “HDL Cholesterol” OR “High Density Lipoprotein Cholesterol” OR “Cholesterol, HDL2” OR “HDL2 Cholesterol” OR “HDL(2) Cholesterol” OR “Cholesterol, HDL3” OR “HDL3 Cholesterol” OR “HDL(3) Cholesterol”))) AND ((“Prevalence”[Mesh] OR “Prevalence” OR “Prevalences”))
SciELO	(“Brazil”) AND (“Child” OR “Children” OR “Adolescent” OR “Adolescents” OR “Adolescence” OR “Teens” OR “Teen” OR “Teenagers” OR “Teenager” OR “Youth” OR “Youths”) AND (“Dyslipidemias” OR “Dyslipidemia” OR “Dyslipoproteinemias” OR “Dyslipoproteinemia” OR “lipid profile” OR “Cholesterol”) AND (“Prevalence” OR “Prevalences”)
Lilacs	tw:((tw:(dislipidemias OR dyslipidemias OR dislipidemias OR colesterol OR cholesterol OR colesterol)) AND (tw:(brasil OR brazil OR brasil)) AND (tw:(criança OR child OR niño OR adolescente OR adolescent OR adolescente)) AND (tw:(prevalência OR prevalence OR prevalencia))) AND (instance:”regional”)
Embase	(‘prevalence’/syn) AND(‘brazil’/syn OR ‘brazil’) AND (‘child’/syn OR ‘adolescent’/syn) AND (‘dyslipidemia’/syn)

[1] Correspondence to: Camila Kümmel Duarte Departamento de Nutrição, Escola de Enfermagem, Universidade Federal de Minas Gerais Avenida Alfredo Balena, 190, Santa Efigênia 30130-100 – Belo Horizonte, MG, Brasil. camila.kummel@gmail.com

Brasil

Brasil

Total cholesterol and low-density lipoprotein alterations in children and adolescents from Brazil: a prevalence meta-analysis

ABSTRACT

Objective:

Materials and methods:

Results:

Conclusion: