Abstract
The aim of this study was to examine any differences in cardiovascular disease (CVD) risk in Portuguese children split by parental educational level. A cross-sectional school-based study was conducted in 2011 on 359 Portuguese children (202 girls and 157 boys) aged 10 to 17 years (mean age ± SD = 13.9 ± 1.98 years). Height and body mass were assessed to determine body mass index (BMI). Parental education level (PEL) was used as a surrogate for socioeconomic status (SES). Capillary blood sampling was used to determine: Total Cholesterol (TC), Triglycerides (TG), Fasting Glucos (GLUC), High and Low Density Lipoprotein (HDL/LDL). These measurements were combined with measures of systolic blood pressure and cardiorespiratory fitness as z-scores. CVD risk was constructed by summing the z-scores. Analysis of covariance, controlling for BMI, indicated that CVD risk was significantly different across PEL groups (p = 0.01), with CVD risk score being significantly lower in low (p = 0.04) and middle (p = 0.008) PEL groups, compared to high PEL. Moreover, the covariate, BMI was also significant (p = 0.0001, β = 0.023), evidencing a significant positive association between BMI and CVD risk, with higher BMI associated with greater CVD risk. In Portuguese children, significantly greater CVD risk was found for children of high PEL, while higher BMI was associated with greater CVD risk.
Highlights
Increasing incidence of type 2 diabetes, metabolic abnormality and clustering of cardiovascular disease (CVD) risk factors are worldwide public health concerns [1]
The use of analysis of covariance (ANCOVA) in the analysis enables any differences between CVD risk between Parental education level (PEL) groups to be analysed controlling for any impact of weight status, whilst at the same time enabling the association between the dependant variable
Bonferroni post hoc multiple comparisons indicated that CVD risk score was significantly lower in low (p = 0.024) and middle (p = 0.005) PEL compared to high PEL
Summary
Increasing incidence of type 2 diabetes, metabolic abnormality and clustering of cardiovascular disease (CVD) risk factors are worldwide public health concerns [1]. The predominant approach taken in these studies has been to assess a range of variables independently associated with cardiovascular disease or metabolic abnormality, including aerobic fitness, resting blood pressure, waist circumference, body fatness, blood lipids, blood glucose and insulin [6]. A number of studies have attempted to provide a CVD risk score by converting all these physiological measures to z-scores and summing them to provide a single measure with high scores indicating increased CVD risk [3,7] This approach has its merits, the literature in this area is mixed, partially due to the range of different dependant variables employed to construct the summed CVD risk scores. Friedemann et al [6]
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