Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Nutrition in acute and chronic diseases

Lipid and saturated fatty acids intake and cardiovascular risk factors of obese children and adolescents

Abstract

Objective

To test the hypothesis that lipid intake is associated with triglycerides to HDL-cholesterol ratio (TG/HDL-cholesterol), a predictor of the development of cardiovascular disease, in obese children and adolescents, independently from the level of overweight, insulin resistance, blood pressure, and non-alcoholic fatty liver disease (NAFLD).

Study design

One hundred and eighty non-diabetic obese children/adolescents (age range 6–16 years) were enrolled. Diet (3-day weighed dietary record), physical and biochemical parameters and liver ultrasonography were measured. The impact of lipid intake on TG/HDL-cholesterol ratio >2.2 was measured by regression models, adjusting for covariates (age, gender, height, weight, systolic and diastolic blood pressure, NAFLD positivity, HOMA-IR, and total energy intake).

Results

Independently from covariates, children consuming a diet with a fat content higher than 35% of total energy had a significantly higher chance [OR = 3.333 (95% CI: 1.113–9.979), P = 0.031] to have a TG/HDL-cholesterol >2.2 than children consuming less than 35% of fat. Moreover, if saturated fatty acids (SFA) intake was higher than 13% of total energy, children had a significantly higher chance [OR = 4.804 (95% CI: 1.312–17.593), P = 0.018] to have a TG/HDL-cholesterol >2.2 than children consuming less than 13% of SFA in their diet.

Conclusions

High fat intake, especially SFA intake, is associated with TG/HDL-cholesterol levels of obese children and adolescents, independently from other cardiovascular risk co-factors. Further intervention studies will contribute to clarify the potential role of changes in the composition and amount of fat in the diet of obese children and adolescents, on their cardiovascular risk factors.

Introduction

The dramatic epidemiological impact of obesity has caused a progressive anticipation of the onset of diabetes, hypertension, and cardiovascular disease also in youth and adolescence [1, 2]. All these obesity-associated morbidities promote cardiovascular disease, leading to a reduction of life expectancy [3]. At the same time, preventive and therapeutic interventions for obesity have not shown encouraging results, especially in the long term [4]. On these bases, early recognition and a prompt intervention to reduce cardiovascular and metabolic risk factors in obese children and adolescents are recommended [5, 6].

Diet has been identified as a crucial component of prevention of cardiovascular disease. In fact, excess of fat mass accumulation is the consequence of a chronic excess of energy intake in respect to energy requirement. In addition to the energy content of the diet, macronutrient composition has been suggested to be involved in the regulation of food intake and its associated metabolic pathways [7, 8]. In particular, in both children and adults, high-fat diets have been associated with obesity and other non-communicable chronic diseases [9, 10]. The risk of developing cardiovascular disease could, in fact, be increased by a high-fat diet, not only for the associated increase of a pro-atherogenic post-prandial lipid profile, but also for the effects of inflammation, insulin sensitivity, and blood pressure [11,12,13]. Most of these effects are associated with the quality of fatty acid intake: in general, trans fatty acid intake was associated with the risk of coronary heart disease (CHD), whereas the role of other fatty acids is still controversial, although a protective effect was primarily associated with unsaturated fatty acids intake, both monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA). Moreover, the reduction of SFA intake in children, mostly when they were replaced with PUFA, has been demonstrated to lead to an improvement on LDL-cholesterol and DBP without a negative effect on growth and development [14,15,16].

The cause–effect relationship between diet and cardiovascular disease has to be analyzed with the disease itself as the endpoint. This is possible in adulthood but not in childhood, when the available surrogate endpoints are some cardiovascular risk factors associated with the future onset of the clinical disease. Nevertheless, children have the advantage over adults of short-term exposure to obesity and associated morbidity and this offers the chance to reduce the impact of potential confounders in the analysis. Dyslipidemia, including hyper-LDL cholesterolemia, hypo-HDL cholesterolemia and hyper-triglyceridemia, is a major risk factor of cardiovascular disease [17]. The triglyceride/HDL-cholesterol ratio (TG/HDL-cholesterol) has been proposed as a good predictor of cardiovascular disease. It has been shown to reflect small dense LDL particles, more atherogenic than larger buoyant LDL particles, and has been reported to be an independent risk factor for coronary heart disease [18,19,20]. High levels of TG/HDL-cholesterol were associated with increased cardiovascular risk, metabolic syndrome, and increased arterial stiffness [21, 22]. Moreover, TG/HDL-cholesterol has been shown to be a better predictor of cardiovascular events rate, and LDL particle size than other commonly used parameter as the non-HDL cholesterol [23, 24]. Furthermore, in a cohort of obese Italian children, a level of TG/HDL-cholesterol >2.2 has been shown to be a better predictor of cardiometabolic risk factors and preclinical signs of organ damage than non-HDL cholesterol [25]. Finally, a trial led on male adults has shown that a high level of TG/HDL-cholesterol could predict mortality, based on cardiovascular and coronary diseases [26]. Other factors than dyslipidemia, such as insulin resistance, high blood pressure, and non-alcoholic fatty liver disease (NAFLD), contribute to cardiovascular risk in obese people [27,28,29]. Therefore, already in childhood, several factors contribute to the cardiovascular disease risk and the specific contribution of lipid intake on this risk is, to the best of our knowledge, unknown in obese children.

Therefore, the aim of this study was to test the hypothesis that lipid intake is associated with TG/HDL-cholesterol in obese children and adolescents, independently from other cardiovascular risk cofactors, i.e., insulin resistance, blood pressure, and NAFLD.

Materials and methods

Subjects

One hundred and eighty obese children and adolescents were enrolled in the study. They were consecutively recruited at the moment of their first access to the Obesity Clinic of the Regional Center for Pediatric Diabetes in Verona (Italy) from January the 1st 2018 and December the 31st 2019. Inclusion criteria were: age between 6–16 years, European ancestry and body mass index (BMI) greater than the age-specific and sex-specific BMI cutoff for obesity (using the World Health Organization BMI cutoffs as reference) [30]. Exclusion criteria were: secondary obesity, known chronic hepatic diseases, congenital or chronic diseases, malformations, and ongoing drug therapies. The consent of the parents and assent of the child below the age of 10 years was obtained. The protocol was approved by the Institutional Ethics Committee of Verona (Italy).

Anthropometric and clinical data

At recruitment, anthropometric and clinical data were collected. Weight was measured to the nearest 0.5 kg on standard physician’s beam scales, with the child wearing only underwear and no shoes. Height was measured to the nearest 0.5 cm on a stadiometer without shoes, with the child’s heels, buttocks, shoulders, and head against the vertical wall with line of sight aligned horizontally. BMI was calculated as body weight (in kilograms) divided by body height (in meters) squared. BMI values were standardized (BMI z-score) using age-specific and sex-specific median, standard deviation and power of the box-cox transformation (least mean square method) based on World Health Organization norms [30]. Waist circumference was measured as the minimal circumference measurable on the horizontal plane between the lowest portion of the rib cage and the iliac crest. Waist-to-height ratio (WHtR) was calculated and used as an index of body fat distribution, as previously described [31]. Puberty was assessed by Tanner stage, categorizing subjects into: prepubertal (Tanner stage: 1), pubertal (Tanner stage: 2–4), and post-pubertal (Tanner stage: 5). Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were recorded three times on the right arm in mmHg using a manual sphygmomanometer and a cuff appropriate for the children’s age; the average of the three blood pressure values was used for analysis [32].

Biochemical measurements

Venous blood samples were collected in the morning after an overnight fast of at least 8 h. Serum liver enzymes [alanine aminotransferase (ALT) and aspartate aminotransferase (AST)] and triglycerides (TG), total cholesterol and high-density lipoprotein cholesterol (HDL-cholesterol), were measured using standard laboratory procedures at the central Laboratory of the university hospital. The laboratory is part of the Italian National Health System, is certified according to International Standards ISO 9000 (www.iso9000.it/) and undergo semiannual quality controls and interlab comparisons [33].

Low-density-lipoprotein cholesterol (LDL-cholesterol) was computed using the Friedewald equation [LDL-cholesterol = total cholesterol – (HDL-cholesterol + TG/5)]. Non-HDL cholesterol was calculated as total cholesterol − HDL-cholesterol. Triglycerides and HDL-cholesterol ratio was calculated. Plasma glucose was measured with glucose oxidase method. Insulin and levels were analyzed by enzyme-immunoassay (Mercodia AB, Sweden). Homeostasis model assessment for insulin resistance (HOMA-IR) was calculated as [insulin (mU/L) · glucose (mg/dL)]/405 and used as a fasting biomarker of insulin resistance [34].

Dietary intake

A 3-day weighed dietary record of food and fluid and the amounts consumed was kept by the children/adolescents and their parents [35]. Food was weighed on an electronic scale by the parents. Parents reported the total food intake of their children at meals, and the children/adolescents were encouraged to report all the foods, including snacks, consumed outside home. Kitchen supervisory staff recorded the food consumed at school. Each family recorded the foods and beverages consumed in a logbook provided during the hospital visit. A complete description of how the food was prepared and recipes for composite dishes were also requested. Written instructions with examples of completed forms were also provided. A dietician checked logbooks for completeness and accuracy with each family on the day after the recording. Pictures of different items were shown along with cups, glasses, spoons, and food shapes of different portion sizes, as an aid in determining the amount of food and drinks consumed outside home. Food and drink energy values were calculated from tables of food comparison set out by the National Institute of Nutrition with the use of a computerized database and analysis program (Metadieta, Meteda, S. Benedetto del Tronto, Italy) [36].

Liver ultrasonography

Hepatic steatosis was diagnosed at recruitment, according to ultrasonographic characteristics, including diffuse hyper-echogenicity of the liver relative to the kidneys, ultrasonography beam attenuation, or poor visualization of the intrahepatic vessel borders and diaphragm [37]. Liver ultrasonography has a good sensitivity and specificity for detecting moderate and severe hepatic steatosis, and traditionally its sensitivity is thought to be poor when >20–30% of hepatocytes are steatotic. In this study, a semi-quantitative ultrasonographic scoring of the degree of hepatic steatosis was not available.

Statistical analysis

Patients baseline characteristics are reported as mean and standard deviation (SD) or median [IQR], according to their Gaussian or non-Gaussian distribution, respectively. Student’s t-test or Mann–Whitney test, as appropriate, were used to compare physical characteristics, biochemical measurements, and dietary variables between patients stratified by gender and TG/HDL-cholesterol ratio. Quartiles of lipid, SFA, MUFA, and carbohydrate intake distribution were also calculated. The cut-off value between the third and the fourth quartile of total lipid (35% of total energy), SFA (13% of total energy), and MUFA (17.5% of total energy) intake were chosen as indicator of high lipid intake, respectively.

The potential role of high lipid intake (fourth quartiles; independent variables) in predicting TG/HDL-cholesterol (TG/HDL-cholesterol >2.2 = 1; dependent variable) was tested by logistic regression analyses (block models); covariates included in the regression models [age, gender, height, BMI z-score, blood pressure, total energy intake, HOMA-IR, NAFLD (yes = 1)] were selected on the basis of the univariate comparisons between TG/HDL-cholesterol categories. Due to collinearity between lipid and carbohydrate intake (r = −0.73, P < 0.001), the latter was not included in the model. Data were analyzed using SPSS version 20.0 software (SPSS, Chicago, IL, USA). A P value of <0.05 was considered to be statistically significant.

Our sample of 180 children had an 80% power to detect, with an alpha-error of 0.05, a positive OR of association of at least 2.44 between a fat intake >35% and TG/HDL > 2.2, adjusting for age, gender, BMI z-score, height, SBP, DBP, HOMA-IR, NAFLD status, and EI. The sensitivity calculation was performed by G-Power 3.1.9.2 software (www.gpowe.hhu.de).

Results

The total sample included 90 males and 90 females. Their median [IQR] age were 11.8 (10.4–13.2) and 12.0 (9.7–13.3) years, respectively (range: 6–16 years). Physical characteristics (age, height, weight, BMI, BMI z-score, WC, WHtR, SBP, DBP, and pubertal stage), prevalence of NAFLD and biochemical variables (fasting blood glucose and fasting insulin, total, HDL-cholesterol, LDL-cholesterol, non-HDL-cholesterol, TG, TG/HDL-cholesterol, ALT, and AST) of the studied sample are shown in Table 1, stratified by gender. Males had significantly (all P < 0.02) higher waist circumference, BMI z-score, systolic blood pressure, ALT, AST, and NAFLD positivity than females. Puberty distribution was statistically different between genders, with females having a more advanced pubertal development then males.

Table 1 Clinical and biochemical characteristics of children and adolescents stratified by gender and TG/HDL-cholesterol ratio.

Energy and nutrient intake were not statistically different between genders, but males had significantly (P < 0.04) higher intake of protein expressed as g/day (Table 2).

Table 2 Energy intake and diet composition of children and adolescents stratified by gender and TG/HDL-cholesterol ratio.

Percent of total lipid intake and TG/HDL-cholesterol were significantly correlated (Rho 0.21, P = 0.007).

Comparison between groups with low and high TG/HDL-cholesterol

Weight, height, BMI, SBP and DBP, NAFLD positivity, TG, total cholesterol, LDL-cholesterol, and non-HDL-cholesterol, fasting plasma insulin and HOMA-IR were significantly (all P < 0.03) higher in children with a TG/HDL-cholesterol >2.2 than in those with TG/HDL-cholesterol ≤2.2. HDL-cholesterol was significantly (P < 0.001) lower in the former than in the latter group (Table 1).

Children with TG/HDL-cholesterol >2.2 had (all P < 0.02) higher protein (g/day), lipid (both as percentage of total energy and g/day), SFA, and MUFA (both as percentage of total energy and g/day) and cholesterol but lower total carbohydrate (percentage of total energy) than those with TG/HDL-cholesterol ≤2.2. All the other variables were not significantly different between the two groups (Table 2).

The main contributors of SFA and MUFA in the children’s diet were dairy products, processed meats, high-fat snacks and fast-food meals.

Regression analyses

Regression analysis showed that, independently from covariates (age, gender, BMI z-score, height, SBP, DBP, NAFLD positivity, HOMA-IR, and total energy intake), children consuming a diet with more than 35% of total energy covered by fat had a significantly higher chance [OR = 3.333 (95% CI 1.113–9.979), P = 0.031] to have a TG/HDL-cholesterol >2.2 than children consuming less than 35% of fat in their diet (Table 3).

Table 3 Logistic regression analysis in the total sample for TG/HDL-cholesterol ratio using age, gender, BMI z-score, height, NAFLD diagnosis, systolic blood pressure, diastolic blood pressure, HOMA-IR, total energy intake, and lipid >35% of total energy as independent variables.

A second model including also MUFA and total cholesterol among independent variables, showed that children consuming a diet with more than 13% of total energy covered by SFA had a significantly higher chance [OR = 4.804 (95% CI: 1.312–17.593), P = 0.018] to have a TG/HDL-cholesterol >2.2 than children consuming less than 13% of saturated fatty acids in their diet (Table 4).

Table 4 Logistic regression analysis in the total sample for TG/HDL-cholesterol ratio using age, gender, BMI z-score, height, NAFLD diagnosis, systolic blood pressure, diastolic blood pressure, HOMA-IR, total energy intake, saturated fatty acid >13% total energy, monounsaturated fatty acid >17.5% of total energy, and cholesterol intake, as independent variables.

Discussion

The main result of this study is that, in obese children/adolescents, a high intake of total lipid or saturated fatty acids are associated with TG/HDL-cholesterol, i.e., a cardiovascular risk factor index, independently from other cardiovascular risk co-factors.

Several studies, conducted in adults, showed that a high fat intake was associated with insulin resistance, glucose intolerance and type 2 diabetes, independently from the level of adiposity [12, 38]. Moreover, a high lipid intake contributes to NAFLD, which further increases insulin resistance [39]. Insulin-resistance is an atherogenic co-factor: reduces capture of glucose by skeletal muscle, increases lipogenesis with increased release of glycerol and free fatty acids into the circulation, which in turn contributes to a greater oxidation of LDL-cholesterol, increases circulating triglycerides and decreases HDL-cholesterol [40]. All these are factors that, associated with the acceleration of the processes, take to the formation of the atherosclerotic plaque and a greater cardiovascular disease risk.

Nevertheless, the results of our study showed that, independently from the level of overweight, insulin resistance and NAFLD, high fat intake contributes to explain TG/HDL-cholesterol inter-individual variability, suggesting that other factors may be involved in the process. One of these factors may be the low-grade inflammation, previously reported in obese children [41]. In fact, available evidence suggests that a high fat intake promotes a proinflammatory state, by increasing gut permeability [42].

Interestingly, the cut-off of total lipid intake used in this study was occasionally coincident with the highest value of the range of fat intake suggested for children older than 4 years, and adolescents in the Italian Recommended dietary intakes [43].

A second result of this study is the association between the fat composition of the diet and TG/HDL-cholesterol, independently from potential confounding factors. In particular, a high SFA intake was associated with high TG/HDL-cholesterol values. Even though the debate on the role of SFA in the development of cardiovascular disease is still controversial, what emerges from a wide number of studies is that having a diet with high consumption of SFA can lead to a change in the lipid profile and an increase of cardiovascular risk [44,45,46]. The importance of replacing them with unsaturated fatty acids, both MUFA and PUFA, has likewise been shown. Consumption of these unsaturated fatty acids, together with a reduction of SFA seems to take towards improvement of lipid profile, and consequently towards reduction of the risk of beginning or mortality for cardiovascular disease [47, 48]. In addition, it has been noted that reducing the consumption of SFA in children improves the lipid profile with reduction of the total cholesterol and LDL-cholesterol as well as diastolic arterial blood pressure, without having though negative effects on growth and development [49]. Replacing SFA with MUFA and PUFA has besides shown improvement in cardiovascular risk also as a consequence of the reduction of the number of microparticles in circulation, and thus to a probable improvement of endothelial repair and to increase of endothelial progenitor cells, all elements that take to the reduction of cardiovascular risk [50]. However, in this study the association between TG/HDL-cholesterol with SFA was not affected by high MUFA intake, suggesting that a reduction of SFA might be more effective than increasing MUFA in reducing the cardiovascular risk factors. Therefore, on the basis of the evidence reported above, keeping the quantity of SFA in a diet within the recommended dietary intake suggested rates, i.e., less than 10% of total energy, seems to be reasonable in order to limit cardiovascular risk in obese children and adolescents [51].

Potential limitations of this study are: (i) ethnicity: only children with European ancestry have been recruited, therefore, it is not possible to generalize these results to children of other ethnic groups; (ii) study design: the cross-sectional design of the study allows to point out just associations between variables and not cause–effect relationships, that could be assessed by future longitudinal studies; (iii) physical activity: physical activity affects energy balance and nutrient metabolism as well as cardiovascular risk factors. Unfortunately, no data on the level of physical activity were available in this population; (iv) assessment of liver content: unfortunately, in this study, a semiquantitative ultrasonographic scoring of the degree of hepatic steatosis was not available and a convenient sampling was used.

This study has also some strengths: (i) the sample set, including obese children and adolescents who have much lower obesity associated comorbidities than obese adults. This allows to explore relationships between variables avoiding potential confounders due to comorbidity; (ii) the measurement of nutritional, anthropometric, biochemical data, and NAFLD positivity in a relatively high number of children and adolescents, by the same operators in the same clinical center; (iii) the inclusion of the main cardiovascular risk cofactors in the analysis of the association between TG/HDL-cholesterol and lipid intake.

In conclusion, the results of this study suggest that a high fat diet and especially a high SFA diet is associated with a high TG/HDL-cholesterol, i.e., a predictor of cardiovascular disease, independently from other cardiovascular risk cofactors. Further intervention studies, using diet with low SFA and adequate fat intake, conducted in obese children and adolescents will contribute to clarify the potential role of changes in the composition and amount of fat in the diet, on their cardiovascular risk factors.

References

  1. 1.

    Flegal KM, Kit BK, Orpana H, Graubard BI. Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA. 2013;2:71–82.

    Google Scholar 

  2. 2.

    Reilly JJ, Kelly J. Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review. Int J Obes. 2011;35:891–8.

    CAS  Google Scholar 

  3. 3.

    Twig G, Yaniv G, Levine H, Leiba A, Goldberger N, Derazne E, et al. Body-mass index in 2.3 million adolescents and cardiovascular death in adulthood. N Engl J Med. 2016;23:2430–40.

    Google Scholar 

  4. 4.

    Reinehr T, Widhalm K, l’Allemand D, Wiegand S, Wabitsch M, Holl RW, et al. Two-year follow-up in 21,784 overweight children and adolescents with lifestyle intervention. Obesity 2009;17:1196–9.

    PubMed  Google Scholar 

  5. 5.

    National Institutes of Health National Heart, Lung, and Blood Institute. Expert panel on integrated pediatric guideline for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics 2011;128:S1–S446.

    Google Scholar 

  6. 6.

    Valerio G, Maffeis C, Saggese G, Ambruzzi MA, Balsamo A, Bellone S, et al. Diagnosis, treatment and prevention of pediatric obesity: consensus position statement of the Italian Society for Pediatric Endocrinology and Diabetology and the Italian Society of Pediatrics. Ital J Pediatr. 2018;31:88.

    Google Scholar 

  7. 7.

    Howell S, Kones R. “Calories in, calories out” and macronutrient intake: the hope, hype, and science of calories. Am J Physiol Endocrinol Metab. 2017;313:E608–12.

    PubMed  Google Scholar 

  8. 8.

    Tremblay A, Bellisle F. Nutrients, satiety, and control of energy intake. Appl Physiol Nutr Metab. 2015;40:971–9.

    PubMed  Google Scholar 

  9. 9.

    Dubois L, Diasparra M, Bogl LH, Fontaine-Bisson B, Bédard B, Tremblay RE, et al. Dietary intake at 9 years and subsequent body mass index in adolescent boys and girls: a study of monozygotic twin pairs. Twin Res Hum Genet. 2016;19:47–59.

    PubMed  Google Scholar 

  10. 10.

    Setayeshgar S, Ekwaru JP, Maximova K, Majumdar SR, Storey KE, McGavock J, et al. Dietry intake and prospective changes in cardiometabolic risk factors in children and youth. Appl Physiol Nutr Metab 2017;42:39–45.

    CAS  PubMed  Google Scholar 

  11. 11.

    Morandi A, Fornari E, Opri F, Corradi M, Tommasi M, Bonadonna R, et al. High-fat meal, systemic inflammation and glucose homeostasis in obese children and adolescents. Int J Obes. 2017;41:986–9.

    CAS  Google Scholar 

  12. 12.

    Feskens EJ, Virtanen SM, Räsänen L, Tuomilehto J, Stengård J, Pekkanen J, et al. Dietary factors determining diabetes and impaired glucose tolerance. A 20-year follow-up of the Finnish and Dutch cohorts of the Seven Countries Study. Diabetes Care. 1995;18:1104–12.

    CAS  PubMed  Google Scholar 

  13. 13.

    Niinikoski H, Jula A, Viikari J, Rönnemaa T, Heino P, Lagström H, et al. Blood pressure is lower in children and adolescents with a low-saturated-fat diet since infancy: the special turku coronary risk factor intervention project. Hypertension 2009;53:918–24.

    CAS  PubMed  Google Scholar 

  14. 14.

    Sacks FM, Lichtenstein AH, Wu JHY, Appel LJ, Creager MA, Kris-Etherton PM, et al. Dietary fats and cardiovascular disease: a presidential advisory from the American Heart Association. Circulation. 2017;136:e1–e23.

    PubMed  Google Scholar 

  15. 15.

    Bendsen NT, Christensen R, Bartels EM, Astrup A. Consumption of industrial and ruminant trans fatty acids and risk of coronary heart disease: a systematic review and meta-analysis of cohort studies. Eur J Clin Nutr. 2011;65:773–83.

    CAS  PubMed  Google Scholar 

  16. 16.

    Wu JHY, Micha R, Mozaffarian D. Dietary fats and cardiometabolic disease: mechanisms and effects on risk factors and outcomes. Nat Rev Cardiol. 2019;16:581–601.

    Google Scholar 

  17. 17.

    Juonala M, Wu F, Sinaiko A, Woo JG, Urbina EM, Jacobs D, et al. Non-HDL cholesterol levels in childhood and carotid intima-media thickness in adulthood. Pediatrics 2020;145:e2019–2114.

    Google Scholar 

  18. 18.

    Dobiásová M, Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: correlation with lipoprotein particle size and esterification rate in apoB-lipoprotein-depleted plasma (FERHDL). Clin Biochem. 2001;34:583–8.

    PubMed  Google Scholar 

  19. 19.

    Austin MA, Breslow JL, Hennekens CH, Buring JE, Willett WC, Krauss RM. Low-density lipoprotein subclass patterns and risk of myocardial infarction. JAMA 1988;260:1917–21.

    CAS  PubMed  Google Scholar 

  20. 20.

    Gardner CD, Fortmann SP, Krauss RM. Association of small low-density lipoprotein particles with the incidence of coronary artery disease in men 31. and women. JAMA 1996;276:875–81.

    CAS  PubMed  Google Scholar 

  21. 21.

    Quijada Z, Paoli M, Zerpa Y, Camacho N, Cichetti R, Villaroel V, et al. The triglyceride/HDL-cholesterol ratio as a marker of cardiovascular risk in obese children; association with traditional and emergent risk factors. Pediatr Diabetes. 2008;9:464–71.

    CAS  PubMed  Google Scholar 

  22. 22.

    Urbina EM, Khoury PR, McCoy CE, Dolan LM, Daniels SR, Kimball TR. Triglyceride to HDL-C ratio and increased arterial stiffness in children, adolescents, and young adults. Pediatrics 2013;131:e1082–90.

    PubMed  PubMed Central  Google Scholar 

  23. 23.

    Nomikos T, Panagiotakos D, Georgousopoulou E, Metaxa V, Chrysohoou C, Skoumas I, et al. Hierarchical modelling of blood lipids’ profile and 10-year (2002–12) all cause mortality and incidence of cardiovascular disease: the ATTICA study. Lipids Health Dis. 2015;14:108.

    PubMed  Google Scholar 

  24. 24.

    Watabe Y, Arisaka O, Miyake N, Ichikawa G, Koyama S, Shimura N. Estimation of LDL particle size using lipid indices: a population-based study of 1578 schoolchildren. Metab Syndr Relat Disord. 2015;13:465–9.

    CAS  PubMed  Google Scholar 

  25. 25.

    Di Bonito P, Valerio G, Grugni G, Licenziati MR, Maffeis C, Manco M, et al. CARdiometabolic risk factors in overweight and obese children in ITALY (CARITALY) Study Group. Comparison of non-HDL-cholesterol versus triglycerides-to-HDL-cholesterol ratio in relation to cardiometabolic risk factors and preclinical organ damage in overweight/obese children: the CARITALY study. Nutr Metab Cardiovasc Dis. 2015;25:489–94.

    PubMed  Google Scholar 

  26. 26.

    Vaga GL, Barlow CE, Grundy SM, Leonard D, DeFina LF. Triglyceride-to-high-density-lipoprotein-cholesterol ratio is an index of heart disease mortality and incidence of type 2 diabetes mellitus in men. J Invest Med. 2014;62:345–9.

    Google Scholar 

  27. 27.

    Oni E, Budoff MJ, Zeb I, Li D, Veledar E, Polak JF, et al. Nonalcoholic fatty liver disease is associated with arterial distensibility and carotid intima-media thickness: (from the Multiethnic study of atherosclerosis). Am J Cardiol. 2019;124:534–8.

    PubMed  Google Scholar 

  28. 28.

    Yusuf S, Joseph P, Rangarajan S, Islam S, Mente A, Hystad P, et al. Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet 2020;395:795–808.

    Google Scholar 

  29. 29.

    Jelenik T, Flögel U, Álvarez-Hernández E, Scheiber D, Zweck E, Ding Z, et al. Insulin resistance and vulnerability to Cardiac ischemia. Diabetes. 2018;67:2695-–702.

  30. 30.

    De Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85:660–7.

    PubMed  Google Scholar 

  31. 31.

    Maffeis C, Banzato C, Talamini G. Obesity Study Group of the Italian Society of Pediatric Endocrinology and Diabetology. Waist-to-height ratio, a useful index to identify high metabolic risk in overweight children. J Pediatr. 2008;152:207–13.

    PubMed  Google Scholar 

  32. 32.

    Di Bonito P, Licenziati MR, Di Sessa A, Manco M, Morandi A, Maffeis C, et al. A new simple formula built on the American Academy of Pediatrics criteria for the screening of hypertension in overweight/obese children. Eur J Pediatr. 2019;178:1291–5.

    PubMed  Google Scholar 

  33. 33.

    Di Bonito P, Miraglia Del Giudice E, Chiesa C, Linceziati MR, Manco M, Franco F, et al. Preclinical signs of liver and cardiac damage in youth with metabolically healthy obese phenotype. Nutr Metab Cardiovasc Dis. 2018;28:1230–6.

    PubMed  Google Scholar 

  34. 34.

    Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Burrows TL, Martin RJ, Collins CE. A systematic review of the validity of dietary assessment methods in children when compared with the method of doubly labeled water. J Am Diet Assoc. 2010;110:1501–10.

    PubMed  Google Scholar 

  36. 36.

    National Institute for the Research in Food and Nutrition. Food Composition Tables (Edra Publishing, Florida, 2007).

  37. 37.

    Hernaez R, Lazo M, Bonekamp S, Kamel I, Brancati FL, Guallar E, et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology. 2011;53:1082–90.

    Google Scholar 

  38. 38.

    Pastorino S, Richards M, Pierce M, Ambrosini GL. A high-fat, high-glycaemic index, low-fibre dietary pattern is prospectively associated with type 2 diabetes in a British birth cohort. Br J Nutr. 2016;115:1632–42.

    CAS  PubMed  Google Scholar 

  39. 39.

    Cheng Y, Zhang K, Chen Y, Li Y, Li Y, Fu K, et al. Associations between dietary nutrient intakes and hepatic lipid contents in NAFLD patients quantified by H-MRS and dual-echo MRI. Nutrients. 2016;8:52.

    Google Scholar 

  40. 40.

    Di Pino A, DeFronzo RA. Insulin resistance and atherosclerosis: implications for insulin-sensitizing agents. Endocr Rev. 2019;40:1447–67.

    PubMed  Google Scholar 

  41. 41.

    Maffeis C, Silvagni D, Bonadonna R, Grezzani A, Banzato C, Tatò L. Fat cell size, insulin sensitivity, and inflammation in obese children. J Pediatr. 2007;151:647–52.

    CAS  PubMed  Google Scholar 

  42. 42.

    Moreira AP, Texeira TF, Ferreira AB, Peluzio Mdo C, Alfenas, Rde C. Influence of a high-fat diet on gut microbiota, intestinal permeability and metabolic endotoxaemia. Br J Nutr. 2012;108:801–9.

    CAS  PubMed  Google Scholar 

  43. 43.

    Società Italiana di Nutrizione Umana (SINU) (Italian Society of Human Nutrition). Nutrients and Energy Reference Intake Levels, IV Revision; (Società Italiana di Nutrizione Umana Milan, 2014).

  44. 44.

    Sacks FM, Lichtenstein AH, Wu JHY, Creager MA, Kris-Etherton PM, Miller M, et al. Dietry fats and cardiovascular disease. Circulation 2017;136:e1–e23.

    PubMed  Google Scholar 

  45. 45.

    Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: A Report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines. J Am Coll Cardiol. 2019;74:e177–e232.

    PubMed  Google Scholar 

  46. 46.

    Te Morenga L, Montez JM. Health effects of saturated and trans-fatty acid intake in children and adolescents: systematic review and meta-analysis. PLoS ONE. 2017;12:e0186672.

    Google Scholar 

  47. 47.

    Ricci C, Baumgartner J, Zec M, Kruger HS, Smuts CM. Type of dietary fat intakes in relation to all-cause and cause specific mortality in US adults: an iso-energetic substitution analysis from the American National Health and Nutrition examination survey linked to the US mortality registry. Br J Nutr. 2018;119:456–63.

    CAS  PubMed  Google Scholar 

  48. 48.

    Mozaffarian D, Micha R, Wallace S. Effects on coronary heart disease of increasing polyunsaturated fat in place of saturated fat: a systematic review and meta-analysis of randomized controlled trials. PLoS Med. 2010;7:e1000252.

    PubMed  Google Scholar 

  49. 49.

    Lapinleimu H, Viikari J, Jokinen E, Salo P, Routi T, Leino A, et al. Prospective randomised trial in 1062 infants of diet low in saturated fat and cholesterol. Lancet 1995;345:471–6.

    CAS  PubMed  Google Scholar 

  50. 50.

    Weech M, Altowaijri H, Mayneris-Perxachs J, Vafeiadou K, Madden J, Todd S, et al. Replacement of dietary saturated fat with unsaturated fats increases numbers of circulating endothelial progenitor cells and decreases numbers of microparticles: findings from randomized, controlled Dietary Intervention and VAScular function (DIVAS) study. Am J Clin Nutr. 2018;107:876–82.

    PubMed  Google Scholar 

  51. 51.

    National Heart, Lung, and Blood Institute. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics. 2011;128:S213–56.

Download references

Acknowledgements

We are sincerely indebted to the children and adolescents who participated in the study and to their families. We thank the dedicated staff of the Pediatric Diabetes and Metabolic Disorders Unit of the University Hospital in Verona for their support during the clinical study.

Funding

This research was funded by grants (FURMAF2019) from the University of Verona to CM.

Author information

Affiliations

Authors

Contributions

CM designed the study, analyzed data, and wrote the manuscript. MC and FO researched data and co-wrote the manuscript. FT, MT, IB, EF, and AM researched data. CM is the guarantor of this work and, as such, had full access to all the data in the study and take responsibility for the integrity and the accuracy of the data analysis.

Corresponding author

Correspondence to Claudio Maffeis.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Maffeis, C., Cendon, M., Tomasselli, F. et al. Lipid and saturated fatty acids intake and cardiovascular risk factors of obese children and adolescents. Eur J Clin Nutr 75, 1109–1117 (2021). https://doi.org/10.1038/s41430-020-00822-0

Download citation

Search

Quick links