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Alta prevalencia de dislipidemias y riesgo aterogénico en una población infanto-juvenil

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Abstract

Background: Dyslipidemias in childhood increase the risk of cardiovascular events in adult life. Aim: To evaluate the prevalence of dyslipidemia and risk of atherogenicity based in the atherogenic index of plasma (AIP) in a sample of school children and adolescents. Material and methods: Cross-sectional study of 208 children aged 10.4 ± 1.0 years (107 women). Demographic data were obtained, and a clinical evaluation was conducted, including pubertal development according to Tanner and anthropometric parameters. A fasting blood sample was obtained to measure total cholesterol (CT), HDL cholesterol (cHDL) and triglycerides (TG), glucose and insulin. LDL cholesterol (cLDL), Non-HDL cholesterol and the indices CT/cHDL, cLDL/cHDL and AIP (log[TG/cHDL]) were calculated. Risk categories according to AIP for the pediatric population were also determined (low: AIP < 0.11, intermediate: AIP 0.11-0.21, high: AIP > 0.21). Results: Thirty eight percent of participants had dyslipidemia, without differences by gender and pubertal development. The frequency of dyslipidemia was significantly higher in children with obesity (54%, p < 0.01) and a waist circumference over percentile 90 (61%; p < 0.01). The later conditions had also higher CT/cHDL, cLDL/cHDL and AIP. According to AIP, 54% of children had a high atherogenicity risk along with alterations in anthropometric parameters and insulin resistance. All anthropometric and insulin resistance parameters were significantly correlated with the AIP. Conclusions: There is a high prevalence of dyslipidemia in the studied population, which is associated with an increased cardiometabolic risk. The indices of atherogenicity and particularly AIP are correlated with nutritional status, abdominal obesity and parameters of insulin resistance.
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

Alta prevalencia de dislipidemias
y riesgo aterogénico en población
infanto-juvenil de La Araucanía.
Uso del índice de aterogenecidad del
plasma (IAP) para evaluación de riesgo
cardiometabólico
JORGE SAPUNAR1,2,3, NICOLÁS AGUILAR-FARÍAS2,4,a,
JUAN NAVARROb, GUSTAVO ARANEDA1,5,c,
DAMIAN CHANDÍA-POBLETE4,d, VÍCTOR MANRÍQUEZ1,e,
ROBERTO BRITO1,f, ÁLVARO CERDA1,2,6,g
High prevalence of dyslipidemia and
high atherogenic index of plasma
in children and adolescents
Background: Dyslipidemias in childhood increase the risk of cardiovascular
events in adult life. Aim: To evaluate the prevalence of dyslipidemia and risk
of atherogenicity based in the atherogenic index of plasma (AIP) in a sample of
school children and adolescents. Material and Methods: Cross-sectional study
of 208 children aged 10.4 ± 1.0 years (107 women). Demographic data were
obtained, and a clinical evaluation was conducted, including pubertal develo-
pment according to Tanner and anthropometric parameters. A fasting blood
sample was obtained to measure total cholesterol (CT), HDL cholesterol (cHDL)
and triglycerides (TG), glucose and insulin. LDL cholesterol (cLDL), Non-HDL
cholesterol and the indices CT/cHDL, cLDL/cHDL and AIP (log[TG/cHDL])
were calculated. Risk categories according to AIP for the pediatric population
were also determined (low: AIP < 0.11, intermediate: AIP 0.11-0.21, high:
AIP > 0.21). Results: Thirty eight percent of participants had dyslipidemia,
without differences by gender and pubertal development. The frequency of dys-
lipidemia was significantly higher in children with obesity (54%, p < 0.01) and
a waist circumference over percentile 90 (61%; p < 0.01). The later conditions
had also higher CT/cHDL, cLDL/cHDL and AIP. According to AIP, 54% of
children had a high atherogenicity risk along with alterations in anthropometric
parameters and insulin resistance. All anthropometric and insulin resistance
parameters were significantly correlated with the AIP. Conclusions: There is
a high prevalence of dyslipidemia in the studied population, which is associa-
ted with an increased cardiometabolic risk. The indices of atherogenicity and
particularly AIP are correlated with nutritional status, abdominal obesity and
parameters of insulin resistance.
(Rev Med Chile…)
Key words: Cardiovascular Diseases; Child; Dyslipidemias; Risk Factors.
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En Chile las enfermedades cardiovasculares
(ECV) constituyen la primera causa de
mortalidad, dando cuenta del 27% de las
defunciones anuales1. En la Encuesta Nacional
de Salud (ENS) 2016-2017, el 3,3% de la muestra
reconoció haber tenido un infarto agudo al mio-
cardio y el 2,6% un evento cerebro vascular, lo que
representa un incremento significativo respecto a
lo reportado en ENS 20102. El factor de riesgo de
ECV más estudiado es la dislipidemia y su meca-
nismo patogénico es la ateroesclerosis, proceso que
comienza en la niñez y progresa en forma gradual
y silenciosa hasta expresarse en la vida adulta3.
Se ha reportado correlación positiva entre
factores de riesgo cardiovascular presentes en la
infancia y lesiones vasculares preclínicas como
mayor espesor de la íntima en arterias carótida y
femoral en la vida adulta4,5. Dos grandes estudios
de cohortes prospectivos encontraron que la
concentración sérica de colesterol en la infancia
permite predecir el valor de este parámetro en la
vida adulta6,7. Por lo tanto, el análisis del perfil
lipídico en población infanto-juvenil permitiría
identificar e intervenir tempranamente sujetos en
riesgo de desarrollar ECV en la vida adulta.
La prevalencia de dislipidemias en población
infanto-juvenil es sorprendentemente alta. Un
estudio de corte transversal con datos obtenidos
del National Health and Nutrition Examination
Survey (NHANES) entre los años 1999 y 2006,
reportó que el 20,6% de los adolescentes de 12 a 19
años presentaban a lo menos un parámetro lipídi-
co alterado8. Hallazgos similares se han reportado
en Europa9,10, Asia11,12 y África13. En Latinoamérica
la prevalencia de dislipidemia infanto-juvenil
alcanza valores tan alarmantes como 48,8%14 y
62,1%15. En Chile, Barja y colaboradores16 encon-
traron que el 32% de una muestra de escolares de
la ciudad de Santiago presentaba alguna forma
clínica de dislipidemia.
Entre los factores asociados con mayor
prevalencia de dislipidemia en población infan-
to-juvenil, destacan la obesidad, el síndrome
metabólico y determinantes de éstos como la
inactividad física16-17. El status socio-económico y
la ruralidad también están asociados con la pre-
sencia de dislipidemia y otros factores de riesgo
cardiovascular18-20. En la ENS 2010 La Araucanía,
en relación a otras regiones de Chile, presentó una
alta prevalencia de trastornos nutricionales por
exceso, diabetes mellitus, dislipidemia e hiperten-
sión arterial21. Por otra parte, esta región tiene los
peores indicadores socio-económicos del país, una
alta proporción de población rural y aborigen en
algunas de sus comunas22,23. La comuna de Cara-
hue, ubicada en la costa de la provincia de Cautín
en la Región de la Araucanía, es representativa de
este perfil demográfico.
Por lo tanto, el propósito del presente estudio
fue establecer la prevalencia de dislipidemia y de
riesgo de aterogenicidad en escolares de la comuna
de Carahue.
Material y Métodos
Muestra de población
Estudio de corte transversal que incluyó escola-
res de 4º a 6º año de enseñanza básica de la comuna
de Carahue, Región de la Araucanía, entre noviem-
bre 2015 y diciembre 2016. Los participantes del
estudio fueron seleccionados mediante muestreo
probabilístico aleatorio multinivel según tipo de
establecimiento, ubicación geográfica y tamaño
de la matrícula.
El protocolo de investigación fue aprobado por
el Comité Ético Científico de la Universidad de
La Frontera (Folio N° 026/15). Los directores de
cada establecimiento firmaron una autorización
para evaluar su escuela. Luego, los apoderados o
cuidadores de los escolares de cursos selecciona-
dos firmaron un consentimiento informado, para
proceder con el asentimiento de los escolares para
realizar los procedimientos.
Evaluación clínica, medidas antropométricas y
estado nutricional
Se recolectaron datos bio-demográficos y se
realizó evaluación clínica completa por médico
pediatra, incluyendo desarrollo puberal y pará-
metros antropométricos.
Los participantes fueron clasificados de acuer-
do a su desarrollo puberal en estadio de 1 a 5 según
Tanner. Para el cálculo del Índice de Masa Corpo-
ral (IMC) el peso y talla fueron medidos mediante
balanza y estadiómetro. La circunferencia de cin-
tura y de cadera fueron medidas con cinta métrica
no extensible a nivel de ombligo y trocánteres
respectivamente y con éstas se calculó el índice
cintura/cadera (ICC). Las presiones arteriales
sistólica y diastólica (PAS y PAD) fueron medidas
con esfigmomanómetro pediátrico, registrándose
el promedio de 2 mediciones consecutivas. El es-
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tado nutricional se estableció mediante el criterio
percentilar del Center for Disease Control (CDC) a
través del cálculo del z-score del IMC normalizado
por edad y sexo según recomendación de la Norma
para la Evaluación Nutricional de Niños, Niñas y
Adolescentes de 5 a 19 años de edad del Ministerio
de Salud 201624. Brevemente, individuos con IMC
z-score entre -1 y +1 (p5 a p85) fueron conside-
rados eutróficos, aquellos con IMC z-score entre
+1 y +2 (p85 a p95) fueron considerados con
sobrepeso y aquellos con valores mayores que +2
(> p95) fueron considerados obesos. Cuando se
detectó una diferencia mayor a 1 año entre la edad
cronológica y la edad biológica según su desarrollo
puberal, se consideró esta última para el cálculo del
IMC z-score. Se definió obesidad abdominal como
el tener una circunferencia de cintura mayor que
el percentil 90 de acuerdo a edad y sexo según la
Norma para la Evaluación Nutricional de Niños,
Niñas y Adolescentes de 5 a 19 años de edad del
Ministerio de Salud 201624. Los individuos con
valores de PAS y PAD superiores al percentil 90
para su edad y sexo, según recomendación del
National High Blood Pressure Education Program
(NHBPEP), fueron considerados hipertensos25.
Finalmente se consignó la presencia de acantosis
nigricans, el perímetro del brazo y cuello. La grasa
corporal fue obtenida mediante impedanciometria
(Tanita TBF300, Tanita Incorporation of America,
Arlington Heights, IL, EUA).
Parámetros bioquímicos, definición de
dislipidemia e índices de aterogenicidad
Se obtuvieron muestras de sangre en ayuno de
10 a 12 horas para determinar concentraciones
séricas de glucosa, colesterol (CT) y triglicéridos
(TG) a través de métodos enzimático-colori-
métricos. La concentración de colesterol VLDL
(cVLDL) fue calculada como la quinta parte
de la concentración de triglicéridos (TG/5), la
concentración de colesterol LDL (cLDL) fue cal-
culada mediante la Formula de Friedewald26 y la
concentración de colesterol no-HDL (c-noHDL)
fue calculada como la diferencia entre el colesterol
total y colesterol HDL (cHDL). La insulinemia fue
determinada por quimioluminiscencia. El análisis
de los parámetros bioquímicos y hormonales fue-
ron realizadas en equipos Roche-Cobas 311 y 411
(Roche Diagnostics, Basilea, Suiza).
La condición de dislipidemia se estableció por
la presencia de al menos un parámetro del perfil
lipídico alterado. Fueron utilizados los valores
de corte propuestos por el National Cholesterol
Education Program (NCEP) y American Academic
of Pediatrics para población pediátrica27:
• CT 200 mg/dL.
• cLDL 130 mg/dL.
• cHDL<40mg/dL.
• c-noHDL 145 mg/dL.
• TG 100 mg/dL entre 0-9 años y 130 mg/dL
en mayores de 10 años.
También fueron calculados las razones CT/
cHDL, cLDL /cHDL y el índice de aterogenicidad
del plasma (IAP), definido como log[TG/cHDL].
Las categorías de riesgo según IAP para población
pediátrica fueron definidas como riesgo bajo
(IAP< 0,11),riesgo intermedio(IAP 0,11-0,21)
y riesgo alto (IAP > 0,21), de acuerdo a Vlavrik y
colaboradores28.
Para describir resistencia a la insulina (RI) se
calcularon los índices HOMA-IR y QUICKI. La
definición de RI se estableció de acuerdo a los
criterios propuestos por Barja y colaboradores
para población pediátrica chilena29.
Análisis estadístico
Se realizó un análisis descriptivo de los datos.
La prueba de Kolmogorov-Smirnov fue usada
para evaluar normalidad de variables continuas.
Comparaciones entre grupos se realizaron usando
pruebas de chi-cuadrado para variables categóricas
y de t o ANOVA seguido de Tukey para variables
continuas con distribución normal. Variables
con distribución no paramétrica fueron com-
paradas mediante prueba de Mann-Withney o
Kruskal-Wallis seguido de método de Dunn. Un
análisis de regresión logística utilizando modelo
paso a paso de selección de variables fue usado
para evaluar la contribución de variables clínicas
y antropométricas para el riesgo de dislipidemias.
Para evaluar la asociación entre variables conti-
nuas se realizó un análisis de correlación lineal y
cálculo del coeficiente de correlación de Pearson.
Se consideró una significancia de 5% para los
análisis estadísticos.
Resultados
Fueron evaluados 208 escolares (101 varones
y 107 mujeres) con edad promedio de 10,4 ± 1,0
años. En la Tabla 1 se resumen las variables clínicas

1105

Tabla 1. Datos demográficos, clínicos y antropométricos de participantes del estudio
en el grupo total y según sexo
Variable Grupo total (208) Masculino (101) Femenino (107) Valor p
    
    
    
    
    
score    

    
   
   
    
    
    
    
    
c



y antropométricas de la muestra de acuerdo al
sexo. El 80% de los varones y el 61% de las mujeres
presentaron trastornos nutricionales por exceso.
En el caso de obesidad, los niños presentaron
prevalencias mayores que las niñas (40% vs 27%
respectivamente; p = 0,029). También fueron
observados valores más altos de IMC z-score y
perímetro cervical, así como menor porcentaje
de grasa corporal en los varones en comparación
alasniñas(p<0,05).
En la Tabla 2 se presentan los parámetros
bioquímicos de la población estudiada de acuerdo
Tabla 2. Parámetros bioquímicos y hormonales de participantes del estudio
en el grupo total y de acuerdo al sexo
Variable Grupo total (208) Masculino (101) Femenino (107) Valor p
    
    
    
    
    
    
    
    
    
    
c

    
 Homeostatic model assessment-insulin
resistance, Quicki: Quantitative Insulin Sensitivity Check Index

1106

Tabla 3. Prevalencia de dislipidemia en la
población de estudio de acuerdo a sexo,
desarrollo puberal, estado nutricional y
obesidad abdominal
Dislipidemia

  
  
c

  
  
c

 
  
  
c

  
  
c
    

        

c
 

al sexo. No se observaron diferencias según sexo,
excepto para el índice Quicki que mostró valores
disminuidos en el sexo femenino (p = 0,006).
El 38% de los escolares presentó dislipidemia,
sin diferencias por género y estado del desarrollo
puberal. La prevalencia de dislipidemia fue sig-
nificativamente mayor en sujetos con obesidad
(54% vs 34% en sobrepeso y 25% en normope-
so; p = 0,002) y con obesidad abdominal (61%;
p = 0,001) (Tabla 3).
En la Tabla 4 se presenta la prevalencia de al-
teraciones en parámetros del perfil lipídico según
estado nutricional y presencia de obesidad abdo-
minal. Las alteraciones del perfil lipídico asociadas
con el estado nutricional y la presencia de obesidad
abdominal fueron la elevación de triglicéridos y la
disminución de cHDL, mientras que el c-noHDL
elevado fue también más prevalente en sujetos
con obesidad abdominal. La hiperlipidemia
mixta y dislipidemia aterogénica fueron también
más prevalentes en sujetos obesos y con obesidad
abdominal. Un análisis de regresión múltiple
paso a paso mostró que la obesidad abdominal
contribuye para dislipidemia y todas sus formas
más frecuentes (Tabla 5), siendo que perímetro
cervical también se asocia a dislipidemia y la edad
con triglicéridos elevado y cHDL bajo.
El valor de los índices CT/cHDL, cLDL/cHDL
Tabla 4. Prevalencia de dislipidemia de acuerdo al parámetro del perfil lipídico alterado según estado
nutricional y obesidad abdominal
Parámetro alterado Grupo
total
Estado nutricional Obesidad Abdominal
Eutrófico Sobrepeso Obeso Valor p CC <p90 CC >p90 Valor p
        
        
        
        
        
        
        

     
c
National
Cholesterol Education ProgramAmerican Academic of Pediatrics

 




1107

Tabla 5. Análisis de regresión logística para las formas más frecuentes de dislipidemia
Parámetro Forma de Dislipidemia
Dislipidemia Triglicéridos
elevado
Colesterol HDL bajo Dislipidemia
aterogénica
OR
(IC 95%)
Valor p OR
(IC 95%)
Valor p OR
(IC 95%)
Valor p OR
(IC 95%)
Valor p
 
  
  
  
 
 
      
 
  
  


Odds Ratio
Tabla 6. Valores de diferentes índices de aterogenicidad según sexo, desarrollo puberal,
estado nutricional y obesidad abdominal en la población de estudio
Índice de aterogenicidad
CT/HDL-c LDL/HDL-c IAP (log[TG/HDL-c)
   

    
    
  

    
    
  

    
    
  bbb
  

   
   
  






e IAP no varió en relación al género ni al desa-
rrollo puberal, pero sí por el estado nutricional y
lapresenciadeobesidadabdominal(p<0,001)
(Tabla 6).
El 54,3% de los sujetos presentaron riesgo
elevado de aterogenicidad de acuerdo al IAP.
En la Tabla 7 son presentados los parámetros
antropométricos y de resistencia a la insulina de
acuerdo a categoría de riesgo según valor de IAP.
Todos los parámetros antropométricos, así como
insulinemia e índices de resistencia a la insulina es-
tuvieron aumentados en el grupo de mayor riesgo
(p<0,001).Delamismaforma,individuoscon
mayor riesgo aterogénico según el IAP mostraron

1108

Tabla 7. Medidas antropométricas e índices de resistencia a la insulina de acuerdo a categoría
de riesgo según el índice de aterogenicidad del plasma (AIP)
Categoría de riesgo según IAP
Parámetro Bajo Intermedio Alto Valor p
 55  

   b
   
   b
   b
 b
 b

    
 bb
 bb
 bb




Homeostatic model assessment-insulin resistanceQuantitative Insulin Sensitivity Check Index.
Figura 1. 


c

mayor prevalencia de obesidad, obesidad abdomi-
nal,RIyacantosisnigricans(p<0,001)(Figura1).
Como se puede observar en la Figura 2, todos
los parámetros antropométricos se correlaciona-
ran positivamente con el IAP. El mismo compor-
tamiento fue observado para insulinemia y el HO-
MA-IR, mientras que el índice Quicki correlacionó
negativamente con el riesgo de aterogenicidad.

1109

Figura 2. 
ABscoreCDE
FGHJI
Homeostatic model assessment-insulin
resistanceQuantitative Insulin Sensitivity Check Index.

1110
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Discusión
En nuestra muestra de escolares de la comu-
na de Carahue encontramos una prevalencia de
33,1% de obesidad, en tanto que en el estudio
de Barja sólo el 15,3% de la muestra de escolares
de la comuna de Puente Alto, Región Metropo-
litana, estaban en esta categoría nutricional16. De
acuerdo a la encuesta CASEN 2013 el 41,91%
de los habitantes de la comuna de Carahue se
encontraba en situación de pobreza por ingresos,
en cambio en Puente Alto sólo el 14,6%, lo que
sugiere marcadas diferencias socioeconómicas
en las características de población estudiada.
Por otro lado, en el censo 2002 el 29,02% de la
población de Carahue reconoció pertenecer a
la etnia Mapuche, cifra que sólo llegó al 2,99%
en Puente Alto30,31. Dichas diferencias en el nivel
socioeconómico y en el origen étnico, así como el
aumento sostenido de la obesidad infanto-juvenil
en los últimos años, sugieren que las diferencias
en relación a las características de la muestra
estudiada podrían explicar la alta prevalencia de
obesidad observada en nuestra población en re-
lación al estudio previo. Un hallazgo de nuestro
estudio fue la mayor proporción de individuos
con indicadores nutricionales desfavorables en
el sexo masculino, aspecto que lamentablemente
no fue analizado en el estudio de Barja ni en otros
realizados en Latinoamérica14-16.
El 38% de los escolares tuvo algún tipo de
alteración del perfil lipídico, proporción que fue
significativamente mayor en sujetos con obesidad
respecto de los grupos sobrepeso y normopeso,
pero sin diferencias por género y estado del desa-
rrollo puberal. En el estudio de Barja la frecuencia
de dislipidemia clínica fue 32%, siendo también
mayor en sujetos obesos16. En ambos estudios la
disminución del cHDL y la elevación de TG fueron
las alteraciones del perfil lipídico más frecuentes,
particularmente en sujetos con obesidad.
El mayor riesgo cardiovascular lo confiere la
presencia simultánea de cHDL bajo, cLDL y TG
elevados, asociación denominada dislipidemia
aterogénica32. En un esfuerzo por lograr un mar-
cador de dislipidemia aterogénica se ha propuesto
el IAP, el cual se ha mostrado más promisorio que
la medición de otros parámetros lipídicos en la
estimación del riesgo de ECV33, probablemente
debido al hecho de que existe una fuerte correla-
ción con el tamaño de partículas de lipoproteínas,
como el aumento de LDL pequeñas y más densas
asociado a un aumento de IAP. En nuestro estu-
dio el 54,3% de los escolares tuvo riesgo elevado
de aterogenicidad de acuerdo al IAP, cifra que
contrasta con 9,5% comunicado por Vrablik
y colaboradores para escolares de la República
Checa28. En ambos estudios se demostró una
fuerte asociación entre el valor de IAP y el estado
nutricional, la diferencia es que la frecuencia de
obesidad en escolares de Carahue fue 33,1% y en
la República Checa sólo 6%. Igualmente, llama la
atención la correlación observada entre el IAP y
medidas antropométricas, particularmente con la
circunferencia de cintura y perímetro cervical, lo
cual evidencia la importancia de una evaluación
clínica exhaustiva que considere estos parámetros
como potenciales indicadores de la presencia de
dislipidemia. Sin embargo, se necesita explorar
más profundamente este aspecto en otras po-
blaciones en el país e idealmente con un diseño
prospectivo. Finalmente pudimos establecer una
asociación entre indicadores de resistencia a la in-
sulina y riesgo de aterogenicidad. En su conjunto,
los resultados obtenidos en torno al análisis de
IAP en nuestra población sugieren que el uso de
este índice puede ser útil para la caracterización
del riesgo cardiometabólico en población infan-
to-juvenil, como propuesto recientemente en
población turca donde se concluyó que el IAP es
superior al uso de otros índices de aterogenicidad
y parámetros del perfil lipídico34.
En conclusión, escolares chilenos provenientes
de una comuna con altos índices de pobreza y
ruralidad mostraron un riesgo de aterogenicidad
elevado basado en el uso del IAP, fuertemente
vinculado a una alta prevalencia de obesidad. Estos
hallazgos probablemente se explican por la asocia-
ción entre resistencia a la insulina y dislipidemia
aterogénica. Además, se observó que medidas
antropométricas simples, como la circunferencia
de cintura, cuello y brazo tienen un potencial para
ser evaluados como identificadores de riesgo de
aterogenicidad elevado.
Agradecimientos: Agradecemos a todos los
participantes y funcionarios de escuelas y Depar-
tamento de Educación Municipal de la comuna
de Carahue que voluntariamente contribuyeron
con esta investigación. El presente trabajo fue
financiado por el Fondo de Investigación UNE-
TE (#UNT15-004) del Convenio de Desempeño

1111

Regional, FRO 1301, Universidad de La Frontera,
Proyecto SOCHED Nº 2017-17 de la Sociedad
Chilena de Endocrinología Diabetes y FONDE-
CYT #11150445.
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... Atherogenic dyslipidemia is the most common dyslipidemia seen in children and adolescents and can be suspected based on the presence of risk factors, such as obesity or metabolic syndrome (MetS) [8,9]. Indeed, in children, adolescents, and young adults, AIP is associated with cardiometabolic risk factors, such as obesity, fatty liver, insulin resistance, and MetS [10][11][12][13][14]. However, except for Dag et al.'s [13] study focusing on obese subjects, the mentioned investigations studied general populations. ...
... years, the prevalence of central obesity is about 1.5-fold lower than that of hypertriacylglycerolemia and 4-fold lower than low HDL-C levels in males, and 2.3-fold and 8.4-fold, respectively, in females. This data [10][11][12]14,16] suggests that alterations in AIP may even precede obesity and abdominal adiposity, indicating that a proportion of young Slovaks presenting with increased AIP are lean. Data on the prevalence of increased AIP (>0.11) in lean subjects are missing. ...
... In our subjects, the prevalence of AIP > 0.11 reached 3.6% in females and 8.5% in males. This prevalence is much lower than that reported for 5-to-19-year-old Chileans (54%) [10] or 18-to-22-year-old Mexicans (30%) [12]. Different prevalence was mirrored by differences in mean AIP values in these cohorts: negative in both sexes in our probands, varying around zero in Mexicans [12], and highly positive in the Chilean study [10]. ...
Article
Full-text available
Cardiometabolic risk factors at a young age pose a significant risk for developing atherosclerotic cardiovascular disease in adulthood. Atherogenic dyslipidemia is highly associated with obesity and metabolic syndrome already in young age. It remains unclear whether cardiometabolic risk factors associate with the atherogenic index of plasma (AIP = log (TAG/HDL-C) in lean subjects with low atherogenic risk. As both the AIP and markers of cardiometabolic risk are continuous variables, we expected their association to be linear before the manifestation of obesity and atherogenic dyslipidemia. We analyzed the prevalence of increased atherogenic risk (AIP ≥ 0.11) in 2012 lean 14-to-20-year-old subjects (55% females) and the trends of cardiometabolic risk factors across the quartiles (Q) of AIP in a subgroup of 1947 (56% females) subjects with low atherogenic risk (AIP < 0.11). The prevalence of AIP ≥ 0.11 reached 3.6% in females and 8.5% in males. HDL-C, non-HDL-C, triglycerides, and the continuous metabolic syndrome score showed a stepwise worsening across the AIP quartiles in both sexes. Measures of obesity and insulin resistance were worse in Q4 vs. Q1 groups, and leukocyte counts were higher in Q4 and Q3 vs. Q1. Females in Q4 presented with a higher C-reactive protein and lower adiponectin, estradiol, and testosterone levels. The multivariate regression model selected non-HDL-C, QUICKI, and erythrocyte counts as significant predictors of AIP in males; and non-HDL-C and C-reactive protein in females. A question arises whether the lean individuals on the upper edge of low atherogenic risk are prone to earlier manifestation of metabolic syndrome and shift to the higher AIP risk group.
... To define the presence of insulin resistance (IR), the HOMA-IR was used using the criteria for the Chilean pediatric population proposed by Barja et al. [13], considering the Tanner stage and the sex of the individuals. The presence of dyslipidemia according to criteria for the pediatric population was defined as previously described in the work of our group [14]. It was possible to obtain 205 blood samples from the participants. ...
Article
Full-text available
Background: Previous infection with Adenovirus-36 (HAdv-D36) has been associated with adipogenesis and glycemic regulation in cell culture and animal models. In humans, HAdv-D36 antibodies correlate with increased obesity risk yet paradoxically enhance glycemic control across various demographics. This study assesses the association of HAdv-D36 seropositivity with obesity, lipid, and glycemic profiles among school-aged children. Methods: We evaluated 208 children aged 9–13, categorized by BMI z-scores into normal weight (−1 to +1), overweight (+1 to +2), and obese (>+3). Assessments included anthropometry, Tanner stage for pubertal development, and biochemical tests (relating to lipids, glucose, and insulin), alongside HAdv-D36 seropositivity checked via ELISA. Insulin resistance was gauged using Chilean pediatric criteria. Results: The cohort displayed a high prevalence of overweight/obesity. HAdv-D36 seropositivity was 5.4%, showing no correlation with nutritional status. Additionally, no link between HAdv-D36 seropositivity and lipid levels was observed. Notably, insulin levels and HOMA-RI were significantly lower in HAdv-D36 positive children (p < 0.001). No cases of insulin resistance were reported in the HAdv-D36 (+) group in our population. Conclusions: HAdv-D36 seropositivity appears to decrease insulin secretion and resistance, aligning with earlier findings. However, no association with obesity development was found in the child population of southern Chile.
... In Venezuela, reports from a study indicate a metabolic syndrome (MetS) prevalence of 2.2% in subjects aged 9-18 years and an increased risk of having MetS if abdominal obesity is present (Reyes et al., 2014). Prevalence of dyslipidemias in children was 38%, with a higher prevalence among obese children (54%, p < 0.01), and 54% of the studied population had a high atherogenicity risk (measured with the atherogenic index of plasma), in addition to insulin resistance, and excess weight (Sapunar et al., 2018). ...
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Preventable diseases in Latin America related to the triple burden of malnutrition in children -undernutrition, hidden hunger, and overweight- are the leading risk factors for premature death, physical and mental disabilities. Moreover, its impacts on health in the following years of life will be negative if they are not treated promptly. There is a need to create health standards and national reference values in Mexico to integrate monitoring, screening, and actions that promote child well-being and development. One of the most used risk-evaluating indicators, the body mass index, does not consider body composition, neglecting relevant information such as possible excess adipose tissue, underestimating the risk of early metabolic alterations, making it more difficult to achieve international health goals. New non-invasive and accessible anthropometric indicators such as the waist-to-height ratio could narrow the gap to improve population health due to its association with cardiovascular risk factors. For this reason, it is crucial to establish its usefulness for nutritional screening and assessment and even to rethink public policies to monitor children’s health status.KeywordsSchoolchildrenAnthropometric assessmentBody mass indexWaist-to-height ratioNutritional status
... In Venezuela, reports from a study indicate a metabolic syndrome (MetS) prevalence of 2.2% in subjects aged 9-18 years and an increased risk of having MetS if abdominal obesity is present . Prevalence of dyslipidemias in children was 38%, with a higher prevalence among obese children (54%, p < 0.01), and 54% of the studied population had a high atherogenicity risk (measured with the atherogenic index of plasma), in addition to insulin resistance, and excess weight (Sapunar et al., 2018). ...
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Performance of elite athletes depends on a complex combination of determinants ranging from physical, physiological, and morphological characteristics to biomechanics and kinematics inherent to each sport. Among adolescent athletes, growth, maturation, and development significantly influence such attributes. Frequently, young athletes of the same chronological age (CA) exhibit significantly different biological maturation (BM). Influence of BM on physical fitness and performance has been described in previous studies. The individual variations of BM lead to a phenomenon called Relative Age Effect (RAE) that is particularly associated with performance and success both in the competitions as well as in the identification of young talents. In most countries, federated sport at young ages is organized by age groups according to the CA of athletes. Therefore, monitoring athletes’ morphological, physical, and maturity characteristics are important not only to establish a well-timed talent identification system but also to implement adequate training programs, based on those characteristics. Recently, experts have focused their efforts on the attempt to deal with particular differences in BM amongst youth sports, labelling this strategy as “bio-banding” and aiming to band young athletes within a specific CA range based on maturity status.
... As shown in several studies, the prevalence varies significantly in relation to the specific country, type of dyslipidemia and children's body weight. Particularly, the category of children with obesity usually presents an even higher prevalence of hyperlipidemia, up to 42% [3][4][5][6]. Thus, the prevalence of dyslipidemia increases with increasing BMI, but also with increasing age, with 15% of children aged 6-11 years and 25% of adolescents aged [12][13][14][15][16][17][18][19] years presenting at least one adverse lipid level, while no significant differences were found in the frequency of dyslipidemia in boys and girls [7,8]. ...
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Atherosclerotic cardiovascular disease (ASCVD) represents the major cause of morbidity and mortality worldwide. The onset of the atherosclerosis process occurs during childhood and adolescence, subsequently leading to the onset of cardiovascular disease as young adults. Several cardiovascular risk factors can be identified in children and adolescents; however, hyperlipidemia, in conjunction with the global obesity epidemic, has emerged as the most prevalent, playing a key role in the development of ASCVD. Therefore, screening for hyperlipidemia is strongly recommended to detect high-risk children presenting with these disorders, as these patients deserve more intensive investigation and intervention. Treatment should be initiated as early as possible in order to reduce the risk of future ASCVD. In this review, we will discuss lipid metabolism and hyperlipidemia, focusing on correlations with cardiovascular risk and screening and therapeutic management to reduce or almost completely avoid the development of ASCVD.
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La obesidad es un problema de salud pública debido a su asociación al desarrollo de diversas enfermedades crónicas, entre los cuales destacan la aparición de dislipidemias, patologías endocrino-metabólicas y cardiovasculares. El objetivo de la investigación fue determinar la prevalencia de dislipidemias y los factores de riesgo en jóvenes obesos. Se realizó un estudio de tipo documental descriptivo lo cual va desde el año 2015-2023. Mediante la búsqueda de información de bases de datos científicas como Scielo, Google Académico, Redalyc y Dialnet. Se utilizó una totalidad de 91 artículos luego de la aplicación de criterios de inclusión o exclusión. Los estudios seleccionados son provenientes de diferentes países los cuales manifiestan datos sobre la prevalencia mundial de dislipidemias y factores de riesgo en jóvenes obesos. Se emplearon términos MeSH para facilitar la búsqueda de información como obesidad, estilo de vida, sobrepeso, dislipidemia, obesidad en jóvenes. Como resultado se pudo lograr evidenciar que la prevalencia de dislipidemia en los pacientes jóvenes a nivel mundial posee cifras elevadas en relación a los diversos países estudiados, además se puede determinar la existencia de diversos factores de riesgo que contribuyen de manera frecuente al aumento de casos en esta población, entre los cuales destacan malos hábitos alimenticios, sedentarismo, alcohol, tabaco, así como la presencia de patologías que predisponen a la aparición de dislipidemias. La relación entre dislipidemias y obesidad contribuye de forma inminente al desarrollo de otras patologías de tipo crónico como la aparición de diabetes mellitus y problemas a nivel cardiovascular relevantes.
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Introduction: Increased triglycerides (TGs) are a major risk factor for cardiovascular disease. Furthermore, hypertriglyceridemia is commonly associated with a reduction of high-density lipoprotein cholesterol (HDL-C) and an increase in atherogenic small-dense low-density lipoprotein (LDL-C) levels. Studies provide support that polyunsaturated omega-3 fatty acids (ω3-LCPUFAs) are cardioprotective and have antithrombotic and anti-inflammatory effects. The potential effects of ω3-LCPUFAs on cardiometabolic factors and anti-inflammatory actions in children with acute lymphoblastic leukemia (ALL) are limited. This is a secondary analysis of a previous clinical trial registered at clinical trials.gov (# NCT01051154) that was conducted to analyze the effect of ω3-LCPUFAs in pediatric patients with ALL who were receiving treatment.Objective: To examine the effect of supplementation with ω3-LCPUFAs on cardiometabolic factors in children with ALL undergoing treatment. Methods: Thirty-four children (placebo group: 20 patients; ω3-LCPUFAs group: 14 patients) aged 6.7 ± 2.7 years who were newly diagnosed with ALL were evaluated. Children were randomized to receive either ω3-LCPUFAs or placebo capsules (sunflower oil). ω3-LCPUFAs were administered in the form of 500-mg soft capsules. The ω3-LCPUFA capsules contained 225 mg of DHA, 45 mg of EPA, and 20 mg of another ω3-LCPUFAs. The omega-3 dose was administered at a rate of 0.100 g/kg of body weight/day for three months. Main outcomes: Fasting cholesterol, HDL-C, very-low-density lipoprotein (VLDL-C), TGs, atherogenic index of plasma (AIP), android/gynoid ratio (A/GR), IL-6, TNF-α, and percentage of fat mass (DXA) were measured in all patients. Fatty acid analyses in red blood cells were performed with gas chromatography. Results: We found significantly lower levels of TGs (p=0.043), VLDL-C (p=0.039), IL-6 (p=0.025), and AIP (p=0.042) in the ω3-LCPUFAs group than in the placebo group at three months. In contrast, the total cholesterol concentration was higher at 3 months in the ω3-LCPUFAs group than in the placebo group (155 mg/dl vs. 129 mg/dl, p=0.009). The number of children with hypertriglyceridemia (85% vs. 50%; p=0.054) tended to be lower between the time of diagnosis and after 3 months of supplementation with ω3-LCPUFAs. Conclusion: These findings support the use of ω3-LCPUFAs to reduce some adverse cardiometabolic and inflammatory risk factors in children with ALL. Clinical trial registration: ClinicalTrials.gov, identifier NCT01051154.
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Objective: This study endeavored to assess the lipid profile and atherogenic lipid indexes in children with transfusion-dependent thalassemia (TDT) and to compare them with matched healthy children. Method: The study group consisted of a total of 72 TDT patients aged 3 to14 years, while the control group had 83 age- and sex-matched healthy children. The fasting lipid profile and lipid indexes were estimated and the atherogenic index of plasma (AIP), Castelli's risk indexes I and II, atherogenic coefficient were calculated and compared between the two groups. Result: Compared to the control group, the mean LDL, HDL and cholesterol levels were significantly lower among the case group (p-value < 0.001). The mean VLDL and triglycerides were significantly higher in the case group (p-value < 0.001). Lipid indexes, including the atherogenic index of plasma (AIP), Castelli's risk indexes I and II and atherogenic coefficients were significantly higher in TDT children. Conclusion: Dyslipidemia and increased risk of atherosclerosis were found in TDT children, as they had elevated atherogenic lipid indexes. Our study underlines the importance of the routine use of these indexes in TDT children. Future studies should focus on lipid indexes in this high-lipid group of children so that preventive strategies can be planned accordingly.
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Introductoin: The prevalence of childhood cardiovascular disease (CVD) risk factors often increases in more rural geographic regions in the USA. However, research on the topic often has conflicting results. Researchers note differences in definitions of rurality and other factors that would lead to differences in inference, including appropriate use of statistical clustering analysis, representative data, and inclusion of individual-level covariates. The present study's objective was to examine CVD risk factors during childhood by geographic distribution in the US Appalachian region as a first step towards understanding the health disparities in this area. Methods: Rurality and CVD risk factors (including blood pressure, body-mass index (BMI), and cholesterol) were examined in a large, representative sample of fifth-grade students ( N= 73 014) from an Appalachian state in the USA. A six-category Rural-Urban Continuum Codes classification system was used to define rurality regions. Mixed modeling analysis was used to appropriately cluster individuals within 725 unique zip codes in each of these six regions, and allowed for including several individual-level socioeconomic factors as covariates. Results: Rural areas had better outcomes for certain CVD risk factors (lowest low-density lipoprotein cholesterol (LDL-C), and blood pressure (BP) and highest high-density lipoprotein cholesterol (HDL-C)) whereas mid-sized metro and town areas presented with the worst CVD risk factors (highest BMI% above ideal, mean diastolic BP, LDL-C, total cholesterol, triglyceride levels and lowest HDL-C) outcomes in children and adolescence in this Appalachian state. Conclusions: Counter to the study hypothesis, mid-sized metro areas presented with the worst CVD risk factors outcomes in children and adolescence in the Appalachian state. This data contradicts previous literature suggesting a straightforward link between rurality and cardiovascular risk factors. Future research should include a longitudinal design and explore some of the mechanisms between cardiovascular risk factors and rurality.
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Purpose Hispanic/Latinos have a high burden of cardiovascular disease (CVD) risk factors which may begin at young ages. We tested the association of CVD risk factors between Hispanic/Latino parents and their children. Methods We conducted a cross-sectional study in the Hispanic Community Health Study/Study of Latinos Youth study. Girls (n = 674) and boys (n = 667) aged 8 to 16 years (mean age 12.1 years) and their parents (n = 942) had their CVD risk factors measured. Results CVD risk factors in parents were significantly positively associated with those same risk factors among youth. After adjustment for demographic characteristics, diet and physical activity, obese parents were significantly more likely to have youth who were overweight (odds ratios [ORs], 2.39; 95% confidence interval [CI], 1.20–4.76) or obese (OR, 6.16; 95% CI, 3.23–11.77) versus normal weight. Dyslipidemia among parents was associated with 1.98 higher odds of dyslipidemia among youth (95% CI, 1.37–2.87). Neither hypertension nor diabetes was associated with higher odds of high blood pressure or hyperglycemia (prediabetes or diabetes) in youth. Findings were consistent by sex and in younger (age <12 years) versus older (≥12 years) youth. Conclusions Hispanic/Latino youth share patterns of obesity and CVD risk factors with their parents, which portends high risk for adult CVD.
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Background Physical activity and sedentary behavior are common factors influencing cardiovascular health. However, how school and leisure-time activity/sedentary behavior are associated with physical fitness and blood lipid levels in primary school children in consideration of gender disparity remains unclear. Methods Data was obtained from a health and nutrition survey on primary school children from nine areas in China. The association between physical activities/sedentary behaviors (school and leisure-time physical activity levels, screen time, and other sedentary behaviors) and anthropometric measurements/prevalence of dyslipidemia were examined by multilevel analysis (the individual level, class level, grade level, and investigation area level) adjusted for age, energy intake and family income. ResultsA total of 770 participants (average age = 9.4 ± 1.7 years) were included. Prevalence of dyslipidemia was 10.9%. Prevalence of dyslipidemia was associated with screen time in boys [OR = 3.04, 95% CI (1.24–7.45)] and inversely associated with leisure-time physical activity in boys [OR = 2.22, 95% CI (1.08–4.56)] and school-time activity in girls [OR = 5.34, 95% CI (1.18–24.16)]. Conclusions Physical activity—but not sedentary behavior—was significantly associated with dyslipidemia in both genders. Increasing leisure-time physical activity for boys and school-time physical activity for girls may be critical.
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Obesity and metabolic syndrome (MS) are one of the biggest public health issues in child and adolescent population. To the best of the authors' knowledge, this hospital based study is the first report on the prevalence of MS in obese children and adolescents in Dalmatia, the Mediterranean part of Croatia. The objectives of this study were to determine the prevalence of individual cardiovascular risk factors and MS. Between January 2009 and June 2014, 201 obese subjects aged 6 to 18 were analyzed retrospectively from our Pediatric Endocrine Unit database. The subjects were then classified in two groups of obesity; subjects with BMI z score 2.0-3.0 were classified as moderately obese and subjects with BMI z score > 3.0 were classified as severely obese. The overall prevalence of MS using the modified IDF criteria was 30.3%. The most common component of MS in both groups was arterial hypertension, while impaired fasting glucose was the least common component of MS. Our finding of high prevalence of MS underlines the importance of early childhood obesity treatment.
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Background: The increase in overweight and obese children and adolescents may be linked to increased rates of dyslipidaemia. The aim was to assess the serum lipid profile, the prevalence of dyslipidaemia and associated risk factors among the North Mexican adolescent population. Methods: Two hundred and ninety-three subjects (47.8% girls) aged 11-16 took part in the Nuevo León State Survey of Nutrition and Health 2011-2012. According to the 2011 Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents, dyslipidaemia was defined as a presence of ≥1 of the following levels (mg/dL): TChol≥200, LDL-chol≥130, non-HDL-c≥145, HDL-c<40, TG ≥130. Results: The overall frequency of dyslipidaemia was 48.8% with no differences between sexes. Adolescents with high BMI were more likely to have at least one abnormal lipid level (overweight: OR: 2.07; 95% CI: 1.14-3.77, P < 0.05; obesity: OR: 2.21, 95% CI: 1.11-4.41, P < 0.05) than those with normal-weight. Abdominally obese subjects were also more likely to have at least ONE abnormal lipid level (OR: 2.30; 95% CI: 1.35-3.91, P < 0.01) than their leaner counterparts. Conclusions: Half of Mexican adolescents living in the State of Nuevo León have at least one abnormal lipid concentration. Low HDL-chol level was the most common dyslipidaemia. BMI and abdominal obesity were associated with the prevalence of at least one abnormal lipid level.
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Background: Serum lipid concentrations are thought to be risk factors for the development of cardiovascular disease. The present study aims to investigate the prevalence of dyslipidemia and provide sex-and age-related reference values for triglycerides, total cholesterol, LDL and HDL cholesterol as well as apolipoproteins A1 and B by using modern analytical approaches. Materials and methods: Venous blood and anthropometric data were collected from 2571 subjects of the LIFE Child study, aged between 0.5 and 16years. Age- and gender-related reference intervals (3rd and 97th percentiles) were established by using Cole's LMS method. Results: Serum concentrations of TC, LDL-C, TG and ApoB were higher in girls than in boys. In girls TC reached peak levels two years earlier than in boys. Triglyceride levels initially declined until the school age. Until early adolescence there was a steady increase. The LDL-C concentrations in girls and boys followed similar patterns to that of TC. Up to the age of 8years, a continuous increase in HDL levels for both sexes was found. Due to the strong correlation between HDL-C and ApoA1 (r=0.87) or rather between LDL-C and ApoB (r=0.93), the respective percentiles showed very similar patterns. Dyslipidemia prevalence were as follows: increased TC 7.8%, increased LDL 6.1%, increased TG 0-9years 22.1%, increased TG 10-16years 11.7%, and decreased HDL 8.0%. Conclusion: Age- and sex-related trends for all parameters are similar to those of the German KIGGS study. With the exception of HDL cholesterol, the prevalence of dyslipidemias in the German LIFE Child cohort are similar to the US-American prevalence.
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Aim: Increased incidence of CVD has been observed in recent years in the Kashmir valley (North India). Since the risk factor development of the cardiovascular diseases (CVD) takes place during childhood, we undertook an epidemiological survey to assess the prevalence of dyslipidemia in the school children of Kashmir valley. Materials and methods: 1131 children of 5-19 years of age were selected and evaluated for BMI, cholesterol, TGs, LDL and HDL levels from different areas of Srinagar city (urban) region of the Kashmir valley from June 2011-June 2014. Results: The frequency of dyslipidemia in Kashmiri children varied along the subjects. Hypertriglyceridemia was seen in 82.6% of the males and 47.6% of females in the age group of 5-9 years, 38.5% of males and 51.1% of females in the age group of 10-14 years and 24.7% of males and 35.9% of the females in the age group of 15-19 years. Low levels of HDL than normal were seen in 34.7% of males and 19% of females in the age group of 5-9 years. Similarly low HDL levels were seen in 17.9% of males and 15.5% of females in the age group of 10-14 years. The incidence of low HDL was also seen in 4.9% of males and 10.8% of females in the age group of 15-19 years. Conclusions: In the present study dyslipidemia was more common in centrally obese children and the most common component was high triglycerides and low HDL's. Female school children were at higher risk of developing CVD than males.
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Background Most of the studies investigating the correlation between the atherogenic index of plasma (AIP) and cardiometabolic risk factors have been conducted with adults, while only a limited number of related studies that involved children and adolescents has been conducted. The purpose of this study is to assess the correlation between the AIP and other cardiometabolic risk factors in adolescents. Methods This study was conducted with 310 girls and 90 boys who were between the ages of 6 and 18 years. After a 10-h fasting period, the biochemical values of the participants were measured in the morning. The anthropometric measurements of the participants were also taken. The AIP was calculated as Log10 (triglycerides/high density lipoprotein-cholesterol; TG/HDL-C). Results In adolescents between the ages of 12 and 18, the mean AIP of the group with TG ≥130 mg/dL was significantly higher than that of the groups with TG of 90–129 mg/dL and <90 mg/dL. There was a strong correlation between TG and AIP for both boys and girls among the children and adolescents, while there was a strong correlation between the TG/HDL-C ratio and TG only in the boys who were within the 6–11-year-old age group. Conclusions An increase in AIP is associated with cardiovascular risk factors in children and adolescents other than those seen in adults. Based on the TG/HDL-C ratio, the AIP may be superior as a complementary index in the assessment of cardiometabolic risks in children and adolescents.
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Methods The incidence of obesity is increasing worldwide, especially in countries with accelerated economic growth. We determined the prevalence of and associations between overweight/ obesity and cardiovascular risk factors in pre-pubertal (seven- to 11-year-old) schoolchildren (both genders, n = 198) in Luanda, Angola. Biochemical (fasting blood) and clinical examinations were obtained in a single visit. Data are reported as prevalence (95% confidence intervals) and association (r, Pearson). Results Prevalence of overweight/obesity was 17.7% (12.4–23.0%), high blood pressure (BP < 90% percentile) was 14.6% (9.7–19.5%), elevated glucose level was 16.7% (11.5–21.9%) and total cholesterol level < 170 mg/dl (4.4 mmol/l) was 69.2% (62.8–75.6%). Significant associations between body mass index (BMI) and systolic and diastolic BP (r = 0.46 and 0.40, respectively; p < 0.05) were found. No association between BMI and elevated glucose or cholesterol levels was found. Conclusion The prevalence of cardiovascular risk factors was high in pre-pubertal schoolchildren in Angola and fat accumulation was directly associated with blood pressure increase but not with other cardiovascular risk factors.