J. Pediatr. (Rio J.) vol.91 número5

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www.jped.com.br

ORIGINAL

ARTICLE

Predictive

capacity

of

anthropometric

indicators

for

dyslipidemia

screening

in

children

and

adolescents

夽

,

夽

Teresa

Maria

Bianchini

de

Quadros

a,∗

,

Alex

Pinheiro

Gordia

a

,

Rosane

Carla

Rosendo

da

Silva

b

_,

_Luciana

_Rodrigues

_Silva

c,d,e

a_Universidade_Federal_do_Recôncavo_da_Bahia_(UFRB),_Amargosa,_BA,_Brazil b_Universidade_Federal_de_Santa_Catarina_(UFSC),_{Florianópolis,}_SC,_Brazil

c_Department_of_Pediatrics,_Faculdade_de_Medicina_(FAMED),_Universidade_Federal_da_Bahia_(UFBA),_Salvador,_BA,_Brazil d_Servic¸o_de_{Gastroenterologia}_e_Hepatologia_Pediátrica,_Complexo_Hospitalar_{Universitário}_Professor_Edgard_Santos_(C-HUPES),

UniversidadeFederaldaBahia(UFBA),Salvador,BA,Brazil

e_Programa_de_{Pós-Graduac¸ão}_em_Medicina_e_Saúde,_Faculdade_de_Medicina_(FAMED),_Universidade_Federal_da_Bahia_(UFBA),

Salvador,BA,Brazil

Received21May2014;accepted19November2014 Availableonline6June2015

KEYWORDS Dyslipidemia; Bodymassindex; Abdominal circumference; Skinfoldthickness; Child;

Adolescent

Abstract

Objective: Toanalyzethepredictivecapacityofanthropometricindicatorsandtheircut-off

valuesfordyslipidemiascreeninginchildrenandadolescents.

Methods: This wasa cross-sectionalstudy involving1139children and adolescents,ofboth

sexes,aged6---18years.Bodyweight,height,waistcircumference,subscapular,andtriceps

skin-foldthicknessweremeasured.Thebodymassindexandwaist-to-heightratiowerecalculated.

Childrenandadolescentsexhibitingatleastoneofthefollowinglipidalterationsweredefined

ashavingdyslipidemia:elevatedtotalcholesterol,lowhigh-densitylipoprotein,elevated

low-density lipoprotein,andhigh triglycerideconcentration.A receiveroperating characteristic

curvewasconstructedandtheareaunderthecurve,sensitivity,andspecificitywascalculated

fortheparametersanalyzed.

Results: Theprevalenceofdyslipidemiawas62.1%.Thewaist-to-heightratio,waist

circum-ference,subscapular,bodymassindex,andtricepsskinfoldthickness,inthisorder,presented

thelargestnumber ofsignificantaccuracies, rangingfrom0.59to0.78.The associationsof

theanthropometricindicatorswithdyslipidemiawerestrongeramongadolescentsthanamong

children.Significantdifferencesbetweenaccuraciesoftheanthropometricindicatorswereonly

夽 _Please_cite_this_article_as:_Quadros_TM,_Gordia_AP,_Silva_RC,_Silva_LR._Predictive_capacity_of_{anthropometric}_indicators_for_dyslipidemia screeninginchildrenandadolescents.JPediatr(RioJ).2015;91:455---63.

夽

StudyconductedatCentrodeFormac¸ãodeProfessores,UniversidadeFederaldoRecôncavodaBahia(UFRB),Amargosa,BA,Brazil.

∗_{Corresponding}_author.

E-mails:tetemb@gmail.com,tetemb@ufrb.edu.br(T.M.B.deQuadros). http://dx.doi.org/10.1016/j.jped.2014.11.006

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observedbytheendofadolescence;theaccuracyofwaist-to-heightratiowashigherthanthat

ofsubscapular(p=0.048)for females, andtheaccuracy ofwaistcircumference washigher

thanthatofsubscapular(p=0.029)andbodymassindex(p=0.012)formales.Ingeneral,the

cut-offvaluesoftheanthropometricpredictorsofdyslipidemiaincreasedwithage,exceptfor

waist-to-heightratio.Sensitivityandspecificityvariedsubstantiallybetweenanthropometric

indicators,rangingfrom75.6to53.5andfrom75.0to50.0,respectively.

Conclusions: The anthropometric indicators studied had little utility as screening tools for

dyslipidemia,especiallyinchildren.

PALAVRAS-CHAVE Dislipidemia; Índicedemassa corporal; Circunferência abdominal; Dobrascutâneas; Crianc¸a;

Adolescente

Capacidadepreditivadeindicadoresantropométricosparaorastreamentoda dislipidemiaemcrianc¸aseadolescentes

Resumo

Objetivo: Analisaracapacidadepreditivadosindicadoresantropométricoseosseusvaloresde

corteparaatriagemdadislipidemiaemcrianc¸aseadolescentes.

Métodos: Estudotransversalde1.139 crianc¸aseadolescentesdeambosossexoscomidade

entre6e 18anos. Peso corporal,estatura,circunferência dacintura (CC)eprega cutânea

subescapular(PCSE)epregacutâneatricipital(PCT)forammedidos.Oíndicedemassacorporal

(IMC)erelac¸ãocintura-estatura(RCE)foramcalculados.Ascrianc¸aseadolescentesquetinham

pelomenos umadasseguintesalterac¸õeslipídicasforamdefinidoscomotendodislipidemia:

elevadosníveisdecolesteroltotal,HDL-Cbaixo,LDL-Celevado,econcentrac¸ãoelevadade

triglicérides.UmacurvaROC(ReceiverOperatingCharacteristics)foiconstruídaeaáreasoba

curva,asensibilidadeeespecificidadeforamcalculadasparaosparâmetrosanalisados.

Resultados: Aprevalênciadedislipidemiafoide62,1%.RCE,CC,PCSE,IMCePCT,nestaordem,

apresentaramomaiornúmerodeprecisõessignificantes,variandode0,59-0,78.Asassociac¸ões

dosindicadoresantropométricoscomdislipidemiaforammaisfortesnosadolescentesdoque

nascrianc¸as.Diferenc¸assignificantesentreprecisõesdosindicadoresantropométricossóforam

observadasnofinaldaadolescência,sendoaprecisãodaRCEmaiordoqueadaPCSE(p=0,048)

parameninaseaprecisãodeCCsendomaiordoqueaPCSE(p=0,029)eIMC(p=0,012)paraos

meninos.Emgeral,osvaloresdecortedospreditoresantropométricosdedislipidemia

aumen-taramcomaidade,excetoparaRCE.Sensibilidadeeespecificidadevariaramsubstancialmente

entreosindicadoresantropométricos,variandode75,6-53,5e75,0-50,0,respectivamente.

Conclusões: Osindicadoresantropométricosestudadosmostrarampoucautilidadecomo

ferra-mentasderastreamentoparadislipidemia,especialmenteemcrianc¸as.

reservados.

Introduction

Atherosclerosis is a chronic inflammatory cardiovascular disease of multifactorial etiology that causes endothelial dysfunction in the intimal layers of medium- and large-sizedarteries.1_The_progression_of_atherogenic_plaques_can resultinsevereclinicalmanifestations,suchasmyocardial infarctionandcerebrovascularaccident,inadditiontoother significantmorbidities.1_The_{atherosclerosis}_develops_slowly andgraduallyduringlifeanditsfirstmanifestationscanbe observedinchildhoodandadolescence.2

Evidence indicates that dyslipidemia is a determinant factor for the occurrence of atherosclerosis in the pedi-atricpopulation.2 _The _{identification} _of _dyslipidemia_at _an earlyageisanimportantstrategyfortheprimaryprevention ofatherosclerosis. However,the diagnosis of dyslipidemia is performed by laboratory tests as part of lipid profile evaluation.These techniques are invasive andcostly,and

access is limited. It is therefore necessary to identify easy-to-use and low-cost methods for the epidemiologi-cal screening of individuals whoareat risk of developing dyslipidemia.

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Asaconsequence,otheranthropometricindicatorssuch asskinfoldthickness,waistcircumference(WC),and waist-to-height ratio (WHtR) have been proposed as promising tools for cardiometabolicriskassessment in young people duetotheircapacitytoestimatebodyadiposityand abdom-inal obesity.9---11 _However, _in _young _people _the _amount _of visceralfatmaynotaccompanytheincreaseintotaland sub-cutaneousadiposityatthesamerate.12_It_therefore_remains unclearwhetherindicatorsofadiposityandabdominal obe-sity arebetter predictorsof dyslipidemiathan BMI during childhoodandadolescence.

The identification of anthropometric indicators that allowfor simpledyslipidemiascreening indifferentpublic health caresectors(schools, healthclinics,and hospitals) andinprimarycaremaycontributebothtoprevent cardio-vasculardiseasesandtoreducepublichealthexpenditure. This tool may be particularly useful in low- and middle-incomecountries suchasBrazil, where accesstomedical specialties and laboratory tests is limited and uneven.13 In those countries, children and adolescents often reach adulthood without ever having undergone a lipid profile assessment.Therefore,theaimofthepresentstudywasto evaluatethepredictivecapacityofanthropometric indica-torsandtoestablishthebestcut-offvaluesfordyslipidemia screening in children and adolescents from Northeastern Brazil.

Methods

Thepresentstudyispartofaschool-basedepidemiological studyconductedinacityofNortheasternBrazil.The esti-matedpopulationin2012was34,845inhabitants,14 _with_a humandevelopmentindexof0.662.15_The_study_population consisted of school-agechildren and adolescents,of both sexes,ranginginagefrom6to18years.Thestudentswere enrolledinthe1stto9thgradesofelementaryschooland inthe1stto3rdyear ofhighschoolof publicandprivate schoolsinthecity.

The representativesample sizeof thelargerstudywas calculatedusinganestimatedprevalenceof50%(for differ-entoutcomes),95%confidenceinterval,andaprecisionof 3%,inaccordancewithLuizandMagnanini.16_The_estimated samplesizewas971childrenandadolescents;a20% mar-gin(n=194)wasaddedtoaccountforpossibleincomplete dataofthesubjectsorrefusaltoparticipateinthedata col-lection.Therateoflossesduetorefusalorabsenceonthe day of datacollection was2.2%, correspondingtoa sam-pleof 1139children andadolescents.The sample studied (n=1139)hadapowerof90%(ˇ=10%)anda95%confidence level(˛=5%)todetectareasunderthereceiveroperating characteristics(ROC)curveof0.58orhigherassignificant.

Data were collected between August of 2011 and May of 2012. The socio-demographic variables were obtained by self-report and included age, sex, monthly household income,numberofpeoplelivinginthehousehold,maternal education level, study place, school type, and socioeco-nomic class (estimated using the Brazilian Criterion of EconomicClassification).17

Body weight wasmeasured with a Plennadigital scale (Plenna®_,_Brazil)_(capacity_of₁₅₀_kg)_to_the_nearest₁₀₀_g.

Height wasmeasured withaSeca(Seca®_,_Brazil)_portable

stadiometer (0---220cm) fixed to the wall, to the near-est 0.1cm. Both variables were measured using standard techniques18_and_were_used_to_calculate_BMI._To_characterize thesampleintermsofthepercentageofchildrenand ado-lescentwithexcessweight(overweightandobese),BMIwas classifiedusingthecut-offvaluesproposedbyColeetal.19 WCwasmeasuredwithanon-elasticmeasurementtapeto thenearest0.1cm,inaccordancewiththeprocedures rec-ommendedbytheWorldHealthOrganization.20 _Height_and WCwereusedtocalculateWHtR.Adipositywasevaluated bythemeasurementofsubscapular(SSF)andtriceps skin-foldthickness(TSF). These skinfolds weremeasured with aCescorf(Cescorf®_,_Brazil),_scientific_caliper_to_the

near-est0.1mm,inaccordancewithstandardtechniques.21 _The measurementswereobtained intriplicate per siteonthe rightsideofthesubject.Themeanofthethree measure-mentswasusedforanalysis.

Anthropometricassessmentwasperformedinthe morn-ingbytwoexaminers of thesamesexasthestudents, to avoid any embarrassment. The two examiners presented intra-andinterobservererrorsoflessthan5%and7.5%for skinfoldthickness,respectively,andoflessthan1%and1.5% fortheothermeasures,whichareacceptableaccordingto theliterature.22

For lipid profile evaluation, venous blood samples (10mL) were collected at the schools in the morning, after a 12-h fast and a normal diet, and were trans-portedunderrefrigerationforanalysis.Serumtriglycerides, total cholesterol and high-density lipoprotein (HDL-C) were measured with a Biosystems® _(Biosystems®_, _Brazil)

automatic biochemistry analyzer (model A15) using an enzymatic method. Low-density lipoprotein (LDL-C) was calculatedusing theequation of Friedewald etal.23 Chil-dren and adolescents exhibiting at least one of the followinglipidalterationsweredefinedashaving dyslipid-emia:elevatedtotalcholesterol(≥170mg/dL),lowHDL-C (<45mg/dL),elevatedLDL-C(≥130mg/dL),andhigh triglyc-erideconcentration(≥130mg/dL).asestablished bytheI guidelinesofpreventionofatherosclerosisinchildhoodand adolescence.3

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Table1 Socio-demographicvariablesandprevalenceofexcessweightanddyslipidemiaamongthechildrenandadolescents

studied.NortheasternBrazil,2011---2012.

Variable n %(95%CI)

Sex

Male 506 44.4(41.4---46.7)

Female 633 55.6(53.0---58.1)

Agerange

Children(6---9years) 363 31.9(29.2---34.2)

Adolescents(10---18years) 776 68.1(65.2---70.3)

Studyplace

Urbanarea 864 75.9(73.4---77.9)

Ruralarea 275 24.1(21.5---26.2)

Schooltype

Public 1044 91.7(90.0---93.0)

Private 95 8.3(6.8---9.7)

Maternalschooling

<4years 264 24.5(21.9---26.7)

4---8years 389 36.2(33.4---38.7)

>8years 423 39.3(36.5---41.7)

Monthlyhouseholdincomea

<1minimumwage 614 57.2(54.3---59.7)

≥1minimumwage 459 42.8(39.7---45.1)

Socioeconomicclass

AandB(high) 141 12.4(10.6---14.0)

C(middle) 550 48.4(45.3---50.8)

DandE(low) 446 39.2(36.2---41.6)

Excessweight(overweightandobese) 181 15.9(13.9---18.1)

Dyslipidemia

Elevatedtotalcholesterol 259 23.1(20.8---25.0)

LowHDL-C 465 41.5(38.6---44.0)

ElevatedLDL-C 50 4.5(3.2---5.5)

Elevatedtriglycerides 139 12.4(10.6---14.0)

Resultsarereportedasabsoluteandrelativefrequencyand95%confidenceinterval(95%CI). HDL-C,high-densitylipoprotein;LDL-C,low-densitylipoprotein.

a_Brazilian_minimum_wage_during_the_study_period:₂₀₁₁₌_US$_325.00;₂₀₁₂₌_US$_371.00.

differenceinaccuracybetweentheanthropometric indica-torsassociatedwithdyslipidemiawascalculatedaccording toHanleyandMcNeil.Thecut-offvaluesfor anthropomet-ric indicators with significant areas under the ROC curve wereidentified based onthe balance between sensitivity andspecificity.

ThestudyprotocolwasapprovedbytheEthics Commit-teeoftheuniversity.Onlystudentswhovoluntarilyaccepted toparticipateandwhoseparentsorlegalguardianssigned theinformedconsentformwereincludedinthestudy.

Results

Table1shows thesocio-demographicvariablesand preva-lence of overweight and dyslipidemia. There was a predominanceoffemales,adolescents,studentsfromurban public schools, and students with a monthly household incomeoflessthanoneBrazilianminimumwage.Over60% ofthe samplereported maternaleducationof less than8

years and approximately 40% belonged to socioeconomic classesDandE(low).Theprevalenceofexcessweight (over-weightandobesity)anddyslipidemiawas15.9%and62.1%, respectively.Individualanalysisshowedalowerprevalence of elevated LDL-C (4.5%) and a higher prevalence of low HDL-C(41.5%).

Withrespecttotheanthropometriccharacteristicsofthe sample,BMI,WC,WHtR,SSF,andTSFwerehigherinfemales than in males (p<0.05). The mean values of the anthro-pometricindicatorstendedtoincreasewithage(p<0.05), exceptforWHtRinmalesandfemalesandforTSFinmales. Therewasnodifference(p>0.05)inanyof the anthropo-metric indicators studied between ages 6 and 7 years, 8 and9years,10and12years,13and15years,and16and 18 yearsineither males or females.As shown inTable 2, triglyceride levels were higher in females than in males. Totalcholesterol,HDL-C,andLDL-Ctendedtodecreaseand triglyceridestendedtoincreasewithage(Table2).

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Table2 Lipidprofileofthechildrenandadolescentsstudiedaccordingtosexandage.NortheasternBrazil,2011---2012.

n Totalcholesterol(mg/dL)a _HDL-C_(mg/dL)a _LDL-C_(mg/dL)a _{Triglycerides}_(mg/dL)b

Sex

Male 506 146.6(29.3) 47.1(11.4) 82.4(24.0) 77(60,104)

Female 633 151.1(30.2) 47.1(10.7) 85.4(25.4) 82(65,111)

pc _0.501 _0.296 _0.336 _0.006

Agegroup(years)

6---7 155 155.9(30.1) 50.2(10.8) 88.9(26.4) 80(62,106) 8---9 208 148.9(28.5) 47.8(10.7) 83.7(23.7) 75(60,107) 10---12 314 149.5(31.7) 48.1(11.2) 84.0(25.5) 77(63,105) 13---15 285 157.1(29.7) 45.6(10.5) 82.8(24.9) 85(64,114) 16---18 177 145.9(27.7) 44.4(11.0) 82.5(23.1) 84(65,108)

pd _0.002 _0.001 _0.022 _0.009

Total 1139 149.1(29.9) 47.1(11.0) 84.1(24.8) 80(63,108)

HDL-C,high-densitylipoprotein;LDL-C,low-densitylipoprotein.

a _Mean_(standard_deviation). b _Median_(25th_and_75th_{percentiles).}

c _Significance_level_for_total_cholesterol,_HDL-C,_and_LDL-C_(Student’s_t_-test)_and_{triglycerides}_{(Mann---Whitney}_test). d _Significance_level_for_total_cholesterol,_HDL-C,_and_LDL-C_(linear_trend)_and_{triglycerides}_{(Jonckheere---Terpstra}_test).

Table3 AreasundertheROCcurveand95%confidenceintervalsoftheanthropometricindicatorsfordyslipidemiascreening

inthechildrenandadolescentsstudiedaccordingtoagegroupandsex.NortheasternBrazil,2011---2012.

Agegroup(years) Anthropometricindicator Males Females

AUC(95%CI) AUC(95%CI)

6---7

BMI(kg/m2₎ _0.61_{(0.49---0.72)} _0.61_{(0.49---0.72)}

WC(cm) 0.64(0.52---0.75)a _0.64_{(0.52---0.75)}a

WHtR 0.66(0.55---0.77)a _0.65_{(0.53---0.76)}a

SSF(mm) 0.55(0.43---0.66) 0.63(0.51---0.74)a

TSF(mm) 0.56(0.44---0.67) 0.55(0.43---0.66)

8---9

BMI(kg/m2₎ _0.52_{(0.42---0.63)} _0.57_{(0.47---0.66)} WC(cm) 0.52(0.41---0.62) 0.57(0.47---0.66) WHtR 0.57(0.46---0.67) 0.58(0.48---0.67) SSF(mm) 0.49(0.38---0.59) 0.56(0.46---0.65) TSF(mm) 0.50(0.39---0.61) 0.54(0.44---0.64)

10---12

BMI(kg/m2₎ _0.58_{(0.49---0.66)} _0.57_{(0.48---0.65)} WC(cm) 0.57(0.49---0.65) 0.59(0.51---0.67)a

WHtR 0.61(0.52---0.68)a _0.59_{(0.51---0.67)}a

SSF(mm) 0.62(0.53---0.69)a _0.56_{(0.48---0.64)}

TSF(mm) 0.60(0.53---0.69)a _0.57_{(0.49---0.65)}

13---15

BMI(kg/m2₎ _0.65_{(0.55---0.74)}a _0.54_{(0.46---0.62)}

WC(cm) 0.64(0.54---0.73)a _0.53_{(0.46---0.61)}

WHtR 0.65(0.55---0.73)a _0.59_{(0.51---0.66)}a

SSF(mm) 0.63(0.54---0.72)a _0.54_{(0.46---0.62)}

TSF(mm) 0.60(0.51---0.70)a _0.54_{(0.46---0.61)}

16---18

BMI(kg/m2₎ _0.63_{(0.50---0.74)}a,b _0.70_{(0.60---0.78)}a

WC(cm) 0.78(0.65---0.87)a,b _0.68_{(0.59---0.78)}a

WHtR 0.68(0.55---0.79)a _0.70_{(0.60---0.78)}a,c

SSF(mm) 0.64(0.51---0.75)a,b _0.62_{(0.53---0.71)}a,c

TSF(mm) 0.62(0.49---0.74) 0.58(0.48---0.67)

AUC,areaundertheROCcurve;95%CI,95%confidenceinterval;BMI,bodymassindex;WC,waistcircumference;WHtR,waist-to-height ratio;SSF,subscapularskinfoldthickness;TSF,tricepsskinfoldthickness;ROC,receiveroperatingcharacteristics.

a _Area_under_the_ROC_curve_indicating_the_{discriminatory}_power_for_dyslipidemia_(lower_limit_of_the_confidence_interval_≥0.50). b _Significant_difference_in_the_AUC_between_WC_and_BMI_and_SSF₍_p_<_0.05).

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Table4 Cut-offvalues,sensitivity,andspecificityoftheanthropometricindicatorsfordyslipidemiascreeninginthechildren

andadolescentsstudiedaccordingtoagegroupandsex.NortheasternBrazil,2011---2012.

Agegroup(years) Anthropometric

indicator

Males Females

Cut-off Sensitivity(%) Specificity(%) Cut-off Sensitivity(%) Specificity(%)

6---7

BMI(kg/m2₎ _--- _--- _--- _--- _---

---WC(cm) 54.2 62.8 58.8 54.3 62.2 55.2

WHtR 0.45 53.5 67.6 0.45 60.0 58.6

SSF(mm) --- --- --- 5.7 60.0 69.0

TSF(mm) --- --- --- --- ---

---8---9

BMI(kg/m2₎ _--- _--- _--- _--- _---

---WC(cm) --- --- --- --- ---

---WHtR --- --- --- --- ---

---SSF(mm) --- --- --- --- ---

---TSF(mm) --- --- --- --- ---

---10---12

BMI(kg/m2₎ _--- _--- _--- _--- _---

---WC(cm) --- --- --- 64.6 57.4 56.7

WHtR 0.43 65.6 51.7 0.44 57.4 53.3

SSF(mm) 5.8 55.9 53.3 --- ---

---TSF(mm) 8.4 58.1 53.3 --- ---

---13---15

BMI(kg/m2₎ _18.1 _67.6 _63.4 _--- _---

---WC(cm) 68.4 60.6 58.5 --- ---

---WHtR 0.42 64.8 56.1 0.45 58.1 59.3

SSF(mm) 6.2 62.0 61.0 --- ---

---TSF(mm) 7.9 56.3 53.7 --- ---

---16---18

BMI(kg/m2₎ _19.7 _64.4 _50.0 _19.7 _73.7 _61.1

WC(cm) 70.5 75.6 65.0 71.8 65.8 55.6

WHtR 0.42 60.0 75.0 0.45 67.1 50.0

SSF(mm) 7.5 64.4 55.0 11.4 67.1 58.3

TSF(mm) --- --- --- --- ---

---BMI,bodymassindex;WC,waistcircumference;WHtR,waist-to-heightratio;SSF,subscapularskinfoldthickness;TSF,tricepsskinfold thickness.

Forcellscontaining‘‘---’’therewasnoanthropometricindicatorwithasignificantareaundertheROCcurvetopredictdyslipidemia.

Forgirls,WHtR,WC,SSF,andBMI,inthisorder,presented the largest number of significant accuracies. For males, WHtRshowedsignificantaccuracyforfouragegroups, fol-lowedbyWCandSSF(threegroups)andBMIandTSF(two groups).Significant differencesbetweenaccuracies ofthe anthropometricindicators wereonlyobserved for theage group of 16---18 years. For females, only the accuracy of WHtRwashigherthanthatofSSF(p=0.048).Formales,only theaccuracyofWCwashigherthanthatofSSF(p=0.029) andBMI(p=0.012).Intheagegroupof8---9years,noneof the anthropometric indicators was a significant predictor ofdyslipidemia,regardlessofsex. Conversely, thehighest accuracieswereobservedintheagegroupof16---18years.

Among theanthropometricindicators identifiedas pre-dictorsofdyslipidemia,thecut-offvaluesforWCandWHtR weresimilarformalesandfemalesaged6---7years.Forthe age groups corresponding to adolescence (10---12, 13---15, and16---18years),thecut-offvaluesforWHtRwerehigher forfemales.Fortheagegroupof16---18years,similarBMI andWCcut-offvalueswereobtainedforbothsexes,whereas SSFcut-offvalueswerehigherforfemales.Ingeneral,the cut-off values of the anthropometric predictors of dysli-pidemia increasedwith age, except for WHtR. Sensitivity

andspecificity variedsubstantiallybetween anthropomet-ricindicators, rangingfrom75.6to53.5andfrom75.0to 50.0,respectively(Table4).

Discussion

Evidence suggeststhat cardiovascular risk factorspresent inchildhoodandadolescencetend topersist andincrease inadult life.2_Considering_that _the_prevalence_of dyslipid-emia was62.1%in thepresent study,theidentification of anthropometricindicatorsfordyslipidemiascreeninginthe pediatric population is a feasible and important strategy forprimarypreventionofchronicdiseasesthatpersistinto adulthoodatthepopulationlevel.Tothebestoftheauthor’s knowledge, this is the first school-based epidemiological study thatevaluated severalanthropometricindicators as screeningtoolsfordyslipidemiainchildrenandadolescents ofbothsexesfromamunicipalityinNortheasternBrazil.

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childhoodandadolescence3_for _the_diagnosis _of dyslipide-mia.Itshouldbenotedthat,asobservedinotherstudies,4,5 low HDL-C was the most prevalent outcome. This finding mayhavebeenfavoredbythehighercut-offforthis lipopro-teinproposedbytheBrazilian guidelines3 _when_compared withinternationalguidelines.7 _Although_controversy_exists in theliteratureregarding whichguidelines touse,4---6 _the authorschosethenationalguidelinesastheyareareference inBrazilforestablishingindividualandpopulationstrategies forthecontrolofriskfactorsforatherosclerosisinchildhood andadolescence.3

Regarding thecomparisonof anthropometricindicators accordingtosexandagegroup,thepresentfindingsshowed significantdifferencesbetweensexesfor all anthropomet-ricindicators, whereas theindicators were similaramong age groups, regardless of sex. Therefore, the association between anthropometric indicators and dyslipidemia con-sidered sex and age group. It should be emphasized that inadequatesexandagestratificationmayleadtoerroneous interpretationoftheresultsduetothebodychangesthat occurduringgrowthandphysicaldevelopment.24_However, severalstudies investigating thepower of anthropometric indicatorstopredictcardiovascularriskfactorsinchildren andadolescentshaveoverlookedtheseaspects.9,10

The present findings demonstrated little difference in the capacity of the anthropometric indicators to identify childrenandadolescentswithdyslipidemia.Analysisofthe ROC curve showed that only WHtR and WC were associ-atedwithdyslipidemiainchildrenof bothsexes aged6---7 years, with a slightly higher accuracy for WHtR (without statisticalsignificance).Incontrast,noneoftheindicators evaluatedwasabletoidentifydyslipidemiainchildrenaged 8---9 years. The lack of an association in this age group mightberelatedtothetransitionfromchildhoodto adoles-cence,whenserumlipidlevelspeakasaresultofhormonal changes,andthispeakdoesnotnecessarilyimplyalterations intheamountofbodyfat.25 _In_adolescents,_WHtR _was_the onlyindicatorassociatedwithdyslipidemiainbothsexesfor thethreeagegroups(10---12,13---15,and16---18years).The associationsoftheanthropometricindicatorswith dyslipide-miawerestrongeramongadolescentsthanamongchildren, especiallyintheage groupof16---18years.These findings corroboratethe dataofliterature,indicating that anthro-pometryismoreusefultodiscriminatedyslipidemiainlate adolescence.26

TSF showed theworst performance inpredicting dysli-pidemia,especiallyinfemales.Otherstudiesalsoreported aweakassociationbetweenthisskinfoldmeasureand car-diovascularriskfactorsinthepediatricpopulation.11,27_TSF is a measure of peripheral body fat, which may explain, at leastin part,thelow discriminatory capacityfor dysli-pidemia.Fatlocatedintheabdominalregion,especiallyin non-fattytissues(ectopicfat),hasbeenshowntobea deter-minantfactoroflipidprofileabnormalities.8_It_is_therefore expectedthatindicatorsof centralfatdistributionhave a higherpredictivecapacityofthisoutcome.

WHtR and WC were, in this order, the anthropomet-ric indicators associated with dyslipidemia in the largest number of age groups per sex. Additionally, only WHtR and WC presented significantly higher accuracy than the other indicators(WHtR>SSFfor femalesand WC>BMIand SSF for males, both aged 16---18 years). These indicators

have alsobeen proposed in other studies as good predic-torsofdyslipidemiaandclusteredcardiovascularriskfactors in the pediatric population.9,10,28 _However, _WC _does _not takeinto accountvariationsresultingfromthe processof growth/physicaldevelopment,whenbodyproportionsand shapes change during different periods and at different speeds.These changesvaryamongthedifferentpediatric agegroups.24 _Conversely, _WHtR _has_some_advantages _that shouldbementioned:(1)itrequirestwosimple,low-cost, and noninvasive anthropometric measurements, providing apromisingindicator ofdyslipidemiain youngpeople;(2) it is a precise indicator of central body fat accumulation anddistributionbytakingintoaccountthechangeinheight thatoccursduringgrowthandphysicaldevelopment,and(3) itdoes notrequirespecific populationreferences andhas nomeasurementunit.However,thepresentresultsshowed pooraccuracyofthisindicatorfor mostoftheage groups studied.Therefore, despitethe easy inclusionof WHtR in routineprimaryhealthcareevaluationsinschoolsand fam-ilyhealthcareunits,itsusefulnessfordyslipidemiascreening needsfurtherinvestigation.

The cut-off valuesproposed in thepresent study were lowerthanthosereportedinstudiesinvolvingsamplesfrom high-incomecountries, regardless of anthropometric indi-cator,sex, or age group.24,29,30 _In _fact, _the _use _of _cut-off values established in developed countries to screen for dyslipidemiainchildrenandadolescentsofdeveloping popu-lationsdoesnotappeartobeadequate,sincethisapproach may result in a large number of false-negative results, underestimatingdiseaseprevalence.Inaddition,less sensi-tivecriteriamaydelaytheimplementationofdyslipidemia preventionandtreatmentprogramsin childhoodand ado-lescence.

The present study had some limitations, such as its cross-sectional design, which did not permit to establish cause---effectrelationships asthedata regardingexposure and outcome were collected simultaneously. Therefore, furtherstudiesmonitoringchangesinanthropometric indi-catorsandthelipidprofileof youngpeopleover timeare needed to gain more insight into this topic. A broad age range was investigated, a fact that may interfere with theresults.Alowerfrequencyofdyslipidemiaisexpected amongchildren. Furthermore,alterationsinthelipid pro-file may be more affected by hormonal changes at the onsetof pubertythan by the accumulationof body fat.25 Among adolescents, the amount and distribution of body fatarestronglyinfluencedbysexwithadvancingbiological maturation.12 _These_factors_may_confound_the_relationship betweenanthropometricindicatorsandlipidprofileinyoung people and explain, at least in part, the low accuracies observed in the present study, especially for children. In this respect, the analyses were performed according to age group and sex, in an attempt to minimize interfer-encesofsampleheterogeneitywiththefindings.However, therelationshipbetweensubcutaneousandectopicfatmay notbelinearinyoungpeople,especiallychildren,12_a_fact thatcouldlimitthe useofanthropometric indicatorsasa screeningtoolfordyslipidemia.

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with dyslipidemia in the age groups studied. The cut-off valuesobservedherewerelowerthanthosefoundin stud-iesconductedindeveloped countries,afindingsuggesting the importance of criteria for the classification of spe-cificanthropometric indicators for populations of middle-andlow-incomecountries.AlthoughWHtRshowedpromising resultsinthepresentstudyandhasadditionaladvantages overWC,itsusefulnessasascreeningtoolfordyslipidemia requiresfurtherinvestigation.

Funding

ThisstudywasfundedbyascholarshipfromtheFundac¸ão deAmparoàPesquisadoEstadodaBahia(FAPESB).

Conflicts

of

interest

Theauthorsdeclarenoconflictsofinterest.

Acknowledgement

TotheMunicipalEducationandHealthDepartmentsof Amar-gosa,Bahia,Brazil,forpermittingthisstudy.

ToDr.DavidS.FreedmanoftheCentersforDisease Con-trolandPrevention, Atlanta, GA,USA, for hissuggestions regardingthemanuscript.

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