Abstract
The objective of this analysis was to estimate the prevalence of cardiovascular disease risk factors in ethnically diverse young children. A retrospective medical chart review identified overweight/obese 2‐ to 9‐year‐old children (N=147) from a local pediatric clinic who were matched (for age, sex, and ethnicity) with normal weight patients from the 2005–2010 National Health and Nutrition Examination Survey (N=294). Comparisons of mean systolic blood pressure and diastolic blood pressure, total, and high‐density lipoprotein (HDL) cholesterol were conducted. Results showed that compared with the population‐based normal‐weight sample, the local overweight/obese sample was significantly more likely to have diastolic prehypertension (15% vs 75%, P<.0001), systolic prehypertension (10% vs 43%, P<.0001), and the lowest quintile of HDL cholesterol (19% vs 34%, P=.003). At this young age, excess weight is significantly associated with cardiovascular disease risk factors. These results suggest that overweight/obese children in this age group should be monitored closely to prevent potential chronic disease risk.
One in four US children under 10 years old are either overweight (≥85 to <95th percentile of body mass index [BMI] for age and sex) or obese (≥95th percentile BMI for age and sex),1 with ethnic minority children being disproportionately affected.2, 3 These statistics are of particular concern because obese preschool‐aged children are five times more likely to be overweight during adolescence4 and four times more likely to be obese as adults when compared with their normal‐weight counterparts.5 These results show that contrary to popular belief, children do not “grow out of” their “baby fat.” In fact, evidence indicates that excessive weight gain in the early years of life can alter developing neural, metabolic and behavioral systems in ways that increase the risk for obesity and chronic disease later in life such as type 2 diabetes, cardiovascular disease (CVD), hypertension, stroke, osteoarthritis, asthma, and certain cancers.6, 7, 8 However, the age in childhood at which increased weight begins to have health‐related consequences is largely unknown. In a previous population‐based analysis, our group showed that in preschool‐aged children, greater BMI and waist circumference are associated with biomarkers that are related to CVD risk, but these associations vary by ethnicity.2
BMI is a common and easily obtained measure of adiposity that can stratify the risk for overweight and obesity among children and adults.1 However, the relationship between BMI and other CVD risk factors among very young children and various ethnic groups is not well explored. The objective of this analysis was to estimate the prevalence of CVD risk factors in an ethnically diverse sample of 2‐ to 9‐year‐old children who were overweight or obese and compare it with normal‐weight children of the same age. CVD risk markers are not routinely measured in pediatric clinics among children aged 2 to 9 years; therefore, we matched our clinic sample on age, sex, and ethnicity with a population‐based sample of 2‐ to 9‐year‐olds from various ethnic groups in the United States using National Health and Nutrition Examination Survey (NHANES) data.
Methods
Clinic‐Based Sample
A retrospective medical chart review identified overweight and obese (BMI ≥85th percentile for age and sex) 2‐ to 9‐year‐old children (N=150). Data were abstracted from January to June 2013 from the medical charts of children who attended the pediatric endocrinology clinic at the University of Miami Miller School of Medicine from 2009 to 2013. Children who attend the pediatric endocrinology clinic are referred from general pediatric and adolescent medicine clinics within the university or community pediatric clinics as a result of concerns of possible obesity‐related health issues. This study was approved by the University of Miami's institutional review board.
Data Collection
Information from all clinic visits available during the previous 5 years was entered into a database. Chart information collected included: (1) anthropometric measurements (height and weight with light clothing), (2) systolic blood pressure (SBP) and diastolic blood pressure (DBP), (3) lipid profiles (total and high‐density lipoprotein [HDL] cholesterol), (4) family health history, and (5) medication history. Familial information obtained during the initial clinic visit includes an exhaustive medical history to assess familial obesity, type 2 diabetes mellitus (or gestational diabetes), dyslipidemia, hypertension or early CVD, diet (pregnancy nutrition, infant feeding history, and daily diet habits), medication history, and exercise/activity patterns.
All measures (anthropometric, medical history, clinical, and laboratory) analyzed are considered standard procedure during a routine pediatric endocrinology clinic visit and are not considered experimental. Patients with diabetes, familial dyslipidemia, HIV infection, history of intrauterine growth restriction, or renal or liver disease or who used medications that altered blood pressure (BP), lipid metabolism, or blood glucose such as insulin, androgens, anabolic steroids, or adrenal corticosteroids were excluded from the analysis. Three children were excluded from the sample because of incomplete records.
Anthropometric Measures
Anthropometric outcome measures included height and weight, which were then converted to BMI. Weight was collected on calibrated scales (Seca model 869; Seca North America East Medical Scales & Measuring Devices, Hanover, MD). Children did not wear their shoes, were asked to empty their pockets, and wore only light clothing (eg, shorts, T‐shirt). Height was measured using a stadiometer (Seca 217 Mechanical Telescopic; Seca North America East Medical Scales & Measuring Devices). BMI was calculated as weight (kilograms) divided by height in meters squared and was then converted to an age‐ and sex‐adjusted percentile and z score.10
Blood Pressure
SBP and DBP were measured with sphygmomanometers (model 9005; American Diagnostic Corporation Drive, Hauppauge, NY) and standard recommendations for child cuff size were followed.11 A total of three diastolic and systolic measurements were taken successively with 1 minute in between each measure. For analysis, the first value was dropped and the subsequent two averaged.
Cholesterol
Fasting total and HDL cholesterol were collected at the clinic and sent to Quest Diagnostics or Labcorp for analysis. HDL cholesterol was measured by a direct immunoassay technique.12
Population‐Based Sample
The 2005–2010 NHANES population of 2‐ to 9‐year‐old children was used to find random 2‐to‐1 matches of normal weight (BMI <85th percentile for age and sex) to the local clinical sample of overweight/obese children based on age, sex, and ethnicity. Similar to the local overweight/obese sample, any child taking medication that altered BP, lipid metabolism, or blood glucose such as insulin, androgens, anabolic steroids, or adrenal corticosteroids were excluded from the analysis. NHANES uses a stratified, multistage probability design to capture a representative sample of the civilian, noninstitutionalized US population.13 To produce estimates with greater statistical reliability for demographic subgroups and rare events, combining two or more 2‐year periods of the survey results is strongly recommended. Therefore, for this study, NHANES data files for 2005–2006, 2007–2008, and 2009–2010 were combined to form a single analytic file.
Data Collection
Persons selected to participate in the NHANES survey were invited to be interviewed in their homes by trained study personnel. Household interview data were collected with computer‐assisted personal interviewing procedures and included demographic, socioeconomic, dietary, and health‐related information. After the interview, participants were asked to undergo a physical examination at a Mobile Examination Center (MEC). Laboratory methods used at the centers are described in The NHANES Laboratory/Medical Technologists Procedures Manual.14
Anthropometrics
Briefly, anthropometric measures taken during the standardized examination consisted of barefoot standing height (with a stadiometer) and weight with minimal clothing (on a digital electronic scale).13
Blood Pressure
BP was obtained for children aged 8 and older via mercury sphygmomanometer (and auscultation) following the American Heart Association's latest technique recommendations of BP determination by sphygmomanometers.15 After resting quietly in a sitting position for 5 minutes and determining the maximum inflation level, three and sometimes four BP determinations (systolic and diastolic) were taken in the MEC.13
Cholesterol
Total cholesterol was measured in children aged 6 and older using standardized enzymatic methods. HDL cholesterol measured by a direct immunoassay technique. All serum blood samples were collected, processed, stored at −20°C, and shipped to the Lipid Laboratory, Johns Hopkins University, Baltimore, Maryland (lipids) for the 1999 to 2006 surveys and to the University of Minnesota, Minneapolis, for the 2007 to 2008 and 2009 to 2010 surveys for analysis.15
Definition of Abnormal Values
To define threshold values of normal SBP and DBP adjusted for sex and age, we used standardized 90th percentile values.16 These values are proposed by the Update on the Task Force for High Blood Pressure in Children and Adolescents, a working group on hypertension control in children and adolescents from the National High Blood Pressure Education Program.11, 17 BP was considered abnormal if systolic and/or diastolic values were abnormal. A total of three diastolic and systolic measurements were available for each child analysis. Consistent with the local clinical sample BP data analysis approach, the first value was dropped and the subsequent two were averaged.15
Abnormal total cholesterol was defined as the empirical highest quintile (≥190 mg/dL) and HDL cholesterol as the lowest quintile (≤42 mg/dL). These cut‐offs are consistent with the percentages used for abnormal values in studies of older children and were used because no standardized cutoffs currently exist for this age group.2
Statistical Methods
Frequencies were used to obtain demographic descriptive characteristics of each group in the study sample. Means were obtained to describe each CVD risk factor. t tests were used to compare the means between the local clinic sample and population‐based sample. Binary variables were created using the cutoff points for analysis purposes. Mantel‐Haenszel chi‐square analyses were used to compare proportions of abnormal risk factors between groups. Each risk factor was then analyzed with separate logistic regression analyses. There was no adjustment for potential confounding factors such as dietary patterns or physical activity level because the children in this analysis were so young and their eating and exercise patterns tend to be inconsistent. An α value of 0.05 was set and all tests were two‐tailed. Analyses were performed with SAS version 9.2 (SAS Institute, Cary, NC).
Results
Sample
The local clinic sample (n=147) was composed of Hispanic (64.4%) girls (74%) with an average age of 7 years. Since the NHANES comparison group (n=294) was matched for age, sex, and ethnicity, demographics were the same (64.9% Hispanic, 73.5% female, average age 7.2 years).
Mean Cardiovascular Risk Factors
Mean values of each cardiovascular risk factor are presented in Table 1 in both groups by sex. Overall, the children in the local sample were significantly more likely to have elevated mean BMI (25.7 kg/m2 vs 17.5 kg/m2, P<.0001), SBP (110.4 mm Hg vs 99.7 mm Hg, P<.0001), and DBP (67.3 mm Hg vs 52.1 mm Hg, P<.0001) values compared with those in the NHANES sample. The children in the local sample also presented with significantly lower mean HDL cholesterol (47.3 mg/dL vs 53.5 mg/dL, P<.0001) compared with those in the NHANES sample. Mean total cholesterol values were not significantly different between children in the overall local and NHANES samples (P=.66).
Table 1.
Comparison of Cardiometabolic Disease Risk Factors Between a Local Clinical‐Based Sample of Overweight/Obese 2‐ to 9‐Year‐Olds and an Age‐, Sex‐, and Ethnicity‐Matched Normal‐Weight Sample From NHANES 2005–2010 Data, by Sex
| Cardiovascular Disease Risk Factor | Local Clinical Overweight/Obese Sample | Population‐Based Normal‐Weight 2005–2010 NHANES Sample | ||||
|---|---|---|---|---|---|---|
| Overall | Male | Female | Overall | Male | Female | |
| Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | |
| Systolic blood pressure, mm Hg | 110.4 (10.6)a | 114.2 (11.6)a | 109.0 (9.8)a | 100.0 (8.6) | 98.4 (8.8) | 100.9 (8.4) |
| Diastolic blood pressure, mm Hg | 67.3 (7.3)a | 70.1 (7.2)a | 66.2 (7.1)a | 52.0 (12.0) | 51.2 (13.0) | 52.5 (11.5) |
| Total cholesterol, mg/dL | 159. (35.2) | 161.5 (36.2) | 159.3 (35.1) | 161.4 (27.6) | 155.7 (28.5) | 163.6 (27.1) |
| HDL cholesterol, mg/dL | 47.3 (10.6)a | 49.2 (9.7)b | 46.7 (10.9)a | 53.5 (11.9) | 55.9 (12.9) | 52.6 (11.3) |
Abbreviations: HDL, high‐density lipoprotein; NHANES, National Health and Nutrition Examination Survey; SD, standard deviation. a P<.0001 compared with the overall population‐based sample. b P=.01 compared with the overall population‐based sample.
Stratified by sex, local girls and boys had elevated mean BMI, SBP, and DBP (P<.0001 for each) when compared with girls and boys in the NHANES sample. Similar to the overall group comparison, mean total cholesterol values were not significantly different between the samples by sex (boys: P=.41; girls: P=.28). Girls in the local sample had lower mean HDL cholesterol values compared with those in the NHANES sample (46.7 mg/dL vs 52.6 mg/dL, P<.0001). Similarly, boys in the local sample had lower HDL cholesterol (49.2 mg/dL) than boys in the NHANES sample (55.9 mg/dL) (P=.01).
Comparisons by ethnicity between the local and NHANES samples are illustrated in Table 2. Children of all ethnicities in the local clinic (Hispanic, non‐Hispanic white, non‐Hispanic black, and other) had significantly higher BMI values than the population‐based sample (P<.0001, for all). Hispanic and non‐Hispanic white children in the local sample had significantly higher SBP values when compared with their counterparts among the NHANES sample (Hispanic: P<.0001; non‐Hispanic white: P=.006). Children of all ethnicities (except “other”) in the local clinical sample had significantly higher DBP levels (P<.0001, for all) and significantly lower HDL cholesterol levels (Hispanic: P=.002; non‐Hispanic white: P=.01; non‐Hispanic black: P=.002) than their population‐based sample counterparts. There were no significant differences in total cholesterol levels across the ethnic group comparisons.
Table 2.
Comparison of Cardiometabolic Disease Risk Factors Between a Local Clinical‐Based Sample of Overweight/Obese 2‐ to 9‐Year‐Olds and an Age‐, Sex‐, and Ethnicity‐Matched Normal‐Weight Sample From NHANES 2005–2010 Data by Ethnicity
| Cardiovascular Disease Risk Factor | Local Clinical Overweight/Obese Sample | Population‐Based 2005–2010 NHANES Normal‐Weight Sample | ||||||
|---|---|---|---|---|---|---|---|---|
| Non‐Hispanic White | Non‐Hispanic Black | Hispanic | Other | Non‐Hispanic White | Non‐Hispanic Black | Hispanic | Other | |
| Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | |
| Systolic blood pressure, mm Hg | 108.8 (10.4)a | 108.6 (8.2)a | 111.0 (10.8)a | 111.6 (11.5) | 98.9 (9.1) | 101.9 (9.2) | 99.6 (8.55) | 106.0 (1.4) |
| Diastolic blood pressure, mm Hg | 67.6 (5.5)a | 67.3 (6.1)a | 67.7 (7.6)a | 62.4 (10.3) | 44.3 (16.4) | 58.5 (9.2) | 52.4 (10.7) | 48.0 (5.7) |
| Total cholesterol, mg/dL | 147.7 (36.8) | 162.6 (29.6) | 161.5 (36.1) | 167.5 (29.0) | 164.2 (37.7) | 159.8 (26.2) | 160.4 (26.0) | 174.7 (20.6) |
| HDL cholesterol, mg/dL | 45.8 (10.0)a | 48.1 (12.8)a | 47.1 (10.1)a | 52.8 (11.1) | 52.3 (8.0) | 59.0 (12.1) | 52.3 (12.2) | 53.5 (10.6) |
Abbreviations: HDL, high‐density lipoprotein; SD, standard deviation. a P<.05. t test comparisons of means by ethnicity of a local sample compared with a population‐based sample (eg, body mass index of non‐Hispanic white patients in the local sample vs body mass index of non‐Hispanic white patients in the National Health and Nutrition Examination Survey [NHANES] sample).
Prevalence of Cardiovascular Risk
The majority of children (87%) in the local clinical sample presented with age‐ and sex‐standardized BMI greater than the 85th percentile. When compared with the population‐based sample, the local children had a significantly higher prevalence of diastolic prehypertension (75.4% vs 8.6%, P<.0001) and systolic prehypertension (42.8% vs 10.3%, P<.0001) and HDL cholesterol in the lowest quintile (34.2% vs 19.4%, P=.003). The prevalence of elevated total cholesterol levels was not significantly different between the samples (local: 18.3%; NHANES: 13.7%; P=.26). (Table 3).
Table 3.
Elevated Cardiometabolic Disease Risk Factors Between a Local Clinical‐Based Overweight/Obese Sample of 2‐ to 9‐Year‐Olds and an Age‐, Sex‐, and Ethnicity‐Matched Normal‐Weight Sample From NHANES 2005–2010a
| Risk Factor | Local Clinical Sample, % | Population‐Based 2005–2010 NHANES Sample, % | P Value |
|---|---|---|---|
| Systolic blood pressure, mm Hgb | 42.1 | 8.1 | <.0001 |
| Systolic hypertension, mm Hg | 22.4 | 0.0 | <.0001 |
| Diastolic blood pressure, mm Hgc | 21.4 | 1.0 | <.0001 |
| Diastolic hypertension, mm Hgc | 10.7 | 0.90 | .002 |
| Total cholesterol, mg/dLd | 18.0 | 13.7 | .29 |
| HDL cholesterol, mg/dL | 34.2 | 19.4 | .003 |
Abbreviation: NHANES, National Health and Nutrition Examination Survey. aCenters for Disease Control and Prevention standardized cutoff values for body mass index ≥85th percentile defining overweight. bSystolic blood pressure and diastolic blood pressure standardized cutoff values for blood pressure ≥90th percentile defining abnormal/prehypertensive. cDefined by standardized cutoff values ≥95th percentile for age and sex. dTotal cholesterol ≥highest quintile. eHigh‐density lipoprotein (HDL) ≤lowest quintile. Bold values indicate significance.
Predictors of Cardiovascular Risk
Logistic regression analysis confirmed that overweight/obese children in the local clinic were significantly more likely to have abnormal cardiovascular risk factors compared with their population‐based normal‐weight counterparts. Specifically, local clinic children had an 8‐fold increased odds of presenting with elevated SBP (odds ratio [OR], 8.3; 95% confidence interval [CI], 3.9–17.6), 30‐fold increased odds of having higher DBP (OR, 30.0; 95% CI, 4.0–223), and twice the odds of presenting with lower (abnormal) HDL cholesterol (OR, 2.2; 95% CI, 1.3–3.6) than their NHANES counterparts. There was no significant difference in total cholesterol levels between the children in the local and population‐based samples (OR, 1.4; 95% CI, 0.76–2.5).
Discussion
The results reported here indicate that the cardiovascular health risks of being overweight and/or obese begin early in life. Specifically, we found that even at this young age, regardless of sex or ethnicity, excess weight is significantly associated with CVD risk factors, especially prehypertension. These findings suggest that pediatricians and other healthcare professionals who take care of patients in this age range may want to consider initiating discussions with parents as well as the child concerning healthy lifestyle behaviors as early as possible. This increased intervention in high‐risk children in particular may provide an early opportunity to decrease the progression to overt CVD outcomes later in life.
Other studies have noted that several CVD risk factors strongly and consistently persist through childhood into adulthood, underscoring the importance of early childhood detection and prevention methods and strategies. For example, the Princeton Lipid Research Clinics Follow‐up Study showed that over 30 years, the risk for CVD was 9 times as high and that for type 2 diabetes mellitus was 4 times as high in children with the metabolic syndrome than in children without the syndrome, after adjusting for age, sex, ethnicity, and family history.18 This same study reported that the first appearance of differences between adults with and without the metabolic syndrome occurred at ages 8 and 13 for BMI and at ages 6 and 13 for waist circumference in boys and girls, respectively.19 In addition, identifying young children with lipid elevations is critical to tracking their CVD risk profile through childhood and has been shown to track strongly into adulthood.20
This study is one of the first in the literature to report the association between CVD risk factors and components of the metabolic syndrome (elevated BP and lipids), and overweight in children younger than 8 years. The only line of defense against the progression of cardiometabolic disease risk at this age is prevention, highlighting the importance of early detection and prevention tools, such as healthy dietary choices and increased physical activity.
Clinically, BMI screening may detect children in this age group who are at higher risk for subsequent CVD.20, 21 We have reported elsewhere that age‐, sex‐, and ethnicity‐ or race‐specific threshold values for BMI and waist circumference may have great clinical utility in identifying older children at risk for CVD.22 Both measures are potentially valuable in detecting the risk of chronic disease at the very earliest stages of life, are minimally invasive, and can be acquired with relative ease in virtually any setting. Children as young as 8 years old can have the metabolic syndrome,23 making it critical to identify those at risk as early as possible24 so that modifiable risk factors such as nutrition25 and physical activity26 can be discussed with the family during well‐child visits.27 Our analysis supports starting these discussions as early in the child's life as possible, as well as expanding counseling to families about CVD and risk prevention, particularly among those families with overweight children.
Study Limitations and Strengths
In a cross‐sectional study, causality cannot be inferred. Insulin and glucose measures are not routinely collected in this age group and thus were not available for analysis, yet they are important components of the metabolic syndrome and risk factors for adult‐onset CVD and diabetes. The local clinic‐based sample consisted of many patients who were referrals from community general pediatricians for follow‐up assessment of risk factors associated with being overweight/obese, which may have introduced a selection bias. In addition, the local clinic used an automated oscillometric monitor to measure BPs whereas NHANES uses a mercury sphygmomanometer, which may have affected the results. Specifically, the use of the oscillometric method could have biased the study results toward finding higher BP values in the local clinic group. Finally, dietary and physical activity level data were not included because the children in this analysis were so young and their eating and exercise patterns tend to be inconsistent as a result. While these limitations may not produce a comprehensive analysis of the consequential health effects of the current obesity epidemic in this age group, they nevertheless provide important and useful information that has not been previously reported.
Conclusions
These results show that even at this young age, excess weight is significantly associated with CVD risk factors. Our analysis shows that easily obtained anthropometric measures in very young children, such as BMI, are associated with biomarkers of CVD risk. Children in this age group are important to monitor for the onset of future chronic disease risk as a result of the current obesity epidemic. When BMI is elevated at this young age, pediatricians might consider also monitoring BP and lipids as potential clinical tools to detect preschool‐aged children who may be at higher risk for CVD. These findings also suggest that healthcare professionals should initiate lifestyle behavior discussion focused on healthy dietary choices and physical activity as early in a child's life as possible and among those families with overweight/obese children in particular.
Acknowledgments and disclosures
This research was supported by the following: National Institutes of Health grant # K01 DA 026993 and the 2011 Micah Batchelor Award for Excellence in Child Health Research. The authors have no financial or other conflicts of interest to report.
J Clin Hypertens (Greenwich). 2014;16:889–894. DOI: 10.1111/jch.12427. © 2014 Wiley Periodicals, Inc.
References
- 1. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999–2010. JAMA. 2012;307:483–490. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Messiah SE, Arheart K, Lipshultz SE, Miller TL. Body mass index, waist circumference, and cardiovascular disease risk factors among preschool‐age children in the United States. Obesity. 2012;20:1942–1949. [DOI] [PubMed] [Google Scholar]
- 3. Nader PR, O'Brien M, Houts R, et al. National Institute of Child Health and Human Development Early Child Care Research Network. Identifying risk for obesity in early childhood. Pediatrics. 2006;118:e594–e601. [DOI] [PubMed] [Google Scholar]
- 4. U.S. Center for Disease Control, National Center for Chronic Disease Prevention and Health Promotion, Division of Nutrition, Physical Activity and Obesity . Obesity among low‐income preschool children. http://www.cdc.gov/obesity/downloads/PedNSSFactSheet.pdf. Accessed May 19, 2013.
- 5. Birch LL, Anzman SL. Learning to eat in an obesogenic environment: a developmental systems perspective on childhood obesity. Child Dev Persp. 2010;4:138–143. [Google Scholar]
- 6. Gluckman PD, Hanson MA, Cooper C, Thornburg KL. Effect of in utero and early‐life conditions on adult health and disease. N Engl J Med. 2008;359:61–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Institute of Medicine . School Food Recommendations. Published 2007. http://www.iom.edu/Reports/2009/School-Meals-Building-Blocks-for-Healthy-Children.aspx. Accessed June 11, 2012.
- 8. Sun SS, Liang R, Huang TTK, et al. Childhood obesity predicts adult metabolic syndrome: the Fels Longitudinal Study. J Pediatr. 2008;152:191–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Centers for Disease Control and Prevention . Body mass index: BMI for children and teens. 2006. http://www.cdc.gov/nccdphp/dnpa/bmi/bmi-for-age.htm. Accessed September 20, 2014. [Google Scholar]
- 10. Kuczmarski RJ, Ogden CL, Grummer‐Strawn LM, et al. CDC growth charts: United States. Adv Data. 2000;314:1–27. [PubMed] [Google Scholar]
- 11. National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents . (2004). The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics., 114, 555–576. [PubMed] [Google Scholar]
- 12. Bachorik PS, Walker RE, Virgil DG. High‐density‐lipoprotein cholesterol in heparin‐MnCl2 supernates determined with the Dow enzymatic method after precipitation of Mn2+ with HCO3−. Clin Chem. 1984;30:839–842. [PubMed] [Google Scholar]
- 13. Centers for Disease Control and Prevention. National Center for Health Statistics . National Health and Nutrition Examination Survey Data. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2010. http://www.cdc.gov/nchs/about/major/nhanes/nhanes2009-2010/questexam03_04.htm. Accessed May 11, 2014. [Google Scholar]
- 14. The Centers for Disease Control and Prevention . National Health and Nutrition Examination Survey: Laboratory Procedures Manual; 2004. www.cdc.gov/nchs/data/nhanes/lab1-6.pdf. Accessed January 11, 2014.
- 15. Pickering TG, Hall JE, Appel LJ, et al. Recommendations for blood pressure measurement in humans: an AHA scientific statement from the Council on High Blood Pressure Research Professional and Public Education Subcommittee. J Clin Hypertens (Greenwich). 2005;7:102–109. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. The Centers for Disease Control and Prevention . NHANES 1999–2000 Public Release Dataset—September 2003: Laboratory 10AM—Glucose, Insulin, and C‐peptide; 2004. www.cdc.gov/nchs/data/nhanes/frequency/l10amdoc.pdf. Accessed January 11, 2011.
- 17. The 4th report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents (NIH, NHLBI, 2005) NIH Publication No. 05‐5267.
- 18. Huang TT, Nansel TR, Belsheim AR, Morrison JA. Sensitivity, specificity, and predictive values of pediatric metabolic syndrome components in relation to adult metabolic syndrome: the Princeton LRC follow‐up study. J Pediatr. 2008;152:185–190. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Morrison JA, Friedman LA, Gray‐McGuire C. Metabolic syndrome in childhood predicts adult cardiovascular disease 25 years later: the Princeton Lipid Research Clinics Follow‐up Study. Pediatrics. 2007;120:340–345. [DOI] [PubMed] [Google Scholar]
- 20. Webber LS, Srinivasan SR, Wattigney WA, Berenson GS. Tracking of serum and lipids and lipoproteins from childhood to adulthood: the Bogalusa Heart Study. Am J Epidemiol. 1991;133:884–899. [DOI] [PubMed] [Google Scholar]
- 21. Hickman TB, Briefel RR, Carroll MD, et al. Distributions and trends of serum lipid levels among United States children and adolescents ages 4–19 years: data from the Third National Health and Nutrition Examination Survey. Prev Med. 1998;27:879–890. [DOI] [PubMed] [Google Scholar]
- 22. Messiah SE, Arheart K, Lipshultz SE, Miller TL. Body mass index, waist circumference, and cardiovascular risk factors in adolescents. J Pediatr. 2008;153:845–850. [DOI] [PubMed] [Google Scholar]
- 23. Messiah SE, Arheart K, Luke B, et al. Relationship between body mass index and metabolic syndrome risk factors among US 8‐ to 14‐year olds, 1999–2002. J Pediatr. 2008;153:215–221. [DOI] [PubMed] [Google Scholar]
- 24. Lipshultz SE, Messiah SE, Wilkinson J, Miller TL. Clinical research directions in pediatric cardiology. Curr Opin Pediatr. 2009;21:585–593. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Lee Y, Mitchell DC, Smiciklas‐Wright H, Birch LL. Diet quality, nutrient intake, weight status, and feeding environments of girls meeting or exceeding recommendations for total dietary fat of the American Academy of Pediatrics. Pediatrics. 2001;107:E95. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Berkey CS, Rockett HR, Gillman MW, Colditz GA. One‐year changes in activity and in inactivity among 10‐ to 15‐year‐old boys and girls: relationship to change in body mass index. Pediatrics. 2003;111:836–843. [DOI] [PubMed] [Google Scholar]
- 27. Strauss RS, Knight J. Influence of the home environment on the development of obesity in children. Pediatrics. 1999;103:E85. [DOI] [PubMed] [Google Scholar]