Anthropometric features as predictors of atherogenic dyslipidemia and cardiovascular risk in a large population of school-aged children

Abstract

BackgroundAutopsy studies reveal that atherosclerosis lesions can be found as early as two years of age. To slow the development of this early pathology, obesity and dyslipidemia prevention should start from childhood making it urgent to explore new ways to evaluate dyslipidemia risk in children that can be applied widely, such as the non-invasive anthropometric evaluation.ObjectiveAssess the metabolic profile of a pediatric population at a specific age to describe the association between anthropometric and biochemical cardiovascular disease risk factors; and evaluate selected anthropometric variables as potential predictors for dyslipidemic cardiovascular risk.Design and methodsAnthropometric features, bioimpedance parameters and fasting clinical profile were assessed in Lisbon and the Tagus Valley region pre-pubertal nine-year-old children (n = 1.496) from 2009–2013 in a descriptive, cross-sectional study. Anthropometric variables predictive power was evaluated through regression analysis.ResultsAt least one abnormal lipid parameter was found in 65% of “normal weight”, 73% of “overweight” and 81% of “obese” children according to the International Obesity Task Force (IOTF) standards. Dyslipidemia was present in 67.8% of children. Waist-hip ratio (WHR) explained 0.4% of total cholesterol (TC) variance. Waist circumference (WC) explained 2.8% of apolipoprotein (APO) A1 variance. Waist-circumference-to-height-ratio (WHtR) explained 2.7%, 2.8% and 1.9% of low-density lipoprotein cholesterol (LDL-c), APO B, and N_HDL-c variance, respectively. Children with abnormally high WHR levels had an increase in risk of 4.49, 3.40 and 5.30 times, respectively, for developing cardiovascular disease risk factors measured as high-risk levels of TC, LDL-c and non-HDL-c (N_HDL-c) (p<0.05). Only 29.9% of “normal weight” children had no anthropometric, bioimpedance or biochemical parameters associated with CV risk.ConclusionA large proportion of school age children have at least one lipid profile abnormality. BMI, zBMI, calf circumference (CC), hip circumference (HC), WC, and WHR are directly associated with dyslipidemia, whereas HC and calf circumference (CC) adjusted to WC, and mid-upper arm circumference (MUAC), are all inversely associated with dyslipidemia. Selected anthropometric variables are likely to help predict increased odds of having CV risk factors.

A Study of Correlation of Anthropometric Data with Atherogenic Indices of Students of Rivers State University, Port Harcourt, Nigeria

“…Between 1993 and 2003, CVD prevalence was reported to be at an average of 17.6% in the Country and 20.1% in 2017 in South-East Nigeria [3]. More so, the assessment of lipoproteins and other risk factors for CVD in younger population such as student population has become necessary since metabolic changes such as atherosclerosis has been reported to begin in childhood and adolescent without sign of CVD risks [4,5,6]. Therefore, early detection of CVD risks could present a lot of time to slow down metabolic changes that results in obesity and dyslipidaemia.…”

“…Therefore, early detection of CVD risks could present a lot of time to slow down metabolic changes that results in obesity and dyslipidaemia. Several clinical measures are used in evaluating CVD risks and one of such measures involve the use of atherogenic and anthropometric indices which are non-invasive techniques [4,5].…”

“…Individuals with BMI of < 18.5kg/m 2 are classified as underweight, those with BMI of 18.5-25.5kg/m 2 are classified as ideal weight, while those with BMI of 25.5 -30.0kg/m 2 are classified as overweight and finally, those with BMI of >30.0kg/m 2 are classified as obese. However, BMI cannot discriminate between adipose and non-adipose tissue in individuals and also cannot distinguish the different types of adipose tissue [4,26]. WHR assess the regional adiposity especially at the legs [4].…”

“…However, BMI cannot discriminate between adipose and non-adipose tissue in individuals and also cannot distinguish the different types of adipose tissue [4,26]. WHR assess the regional adiposity especially at the legs [4]. Elevated WHR value = 0.88 for women and 0.95 for men [4].…”

“…WHR assess the regional adiposity especially at the legs [4]. Elevated WHR value = 0.88 for women and 0.95 for men [4]. WHtR has been reported to predict coronary artery risk factors alongside WC, WHR and BMI [4].…”