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This document provides a pediatric-focused companion to the American Heart Association (AHA) Strategic Impact Goal Through 2020 and Beyond, focused on cardiovascular (CV) health promotion and disease reduction in adults and children. The principles detailed in the document reflect the AHA’s new dynamic and proactive goal to promote CV health throughout the lifecourse. The primary focus is on adult CV health and disease prevention, but critical to achievement of this goal is maintenance of ideal CV health from birth through childhood to young adulthood and beyond.
Emphasis is placed on the fundamental principles and metrics that define CV health in children for the clinical or research setting and a balanced and critical appraisal of the strengths and weaknesses of the CV health construct in children and adolescents are provided. Specifically, it discusses two important factors: 1) the promotion of ideal CV health in all children, and 2) the improvement of CV health metric scores in children currently classified as having “poor” or “intermediate” CV health. Other topics include the current status of CV health in U.S. children, opportunities for the refinement of health metrics, improvement of health metric scores, and possibilities for promoting ideal CV health. Importantly, concerns about the suitability of using single thresholds to identify elevated CV risk throughout the childhood years and the limits of our current knowledge are noted, while providing suggestions for future directions and research.
The American Heart Association (AHA) Strategic Impact Goal Through 2020 and Beyond statement, published in 2010, provides guidance on cardiovascular (CV) health promotion and disease reduction in adults and children.1 It also offers a novel definition of CV health and identifies metrics to enable CV health monitoring in the pediatric and adult populations over time. The principles detailed in the document reflect the AHA’s new dynamic and proactive goal to promote CV health throughout the lifecourse. The primary focus is on adult CV health and disease prevention, but critical to achievement of this goal is maintenance of ideal CV health from birth through childhood to young adulthood and beyond.
This paper provides a pediatric-focused companion document emphasizing the fundamental principles and metrics that define CV health in children for the clinical or research setting. The authors offer a balanced and critical appraisal of the strengths and weaknesses of the CV health construct in children and adolescents and will discuss two important factors: 1) the promotion of ideal CV health in all children, and 2) the improvement of CV health metric scores in children currently classified as having “poor” or “intermediate” CV health. Other topics include the current status of CV health in U.S. children, opportunities for the refinement of health metrics, improvement of health metric scores, and possibilities for promoting ideal CV health. Concerns about the suitability of using single thresholds to identify elevated CV risk throughout the childhood years and the limits of our current knowledge will be noted, while providing suggestions for future directions and research.
Despite a comprehensive definition of CV health, it is now widely recognized that the development of childhood CV and metabolic disease risk factors, and the consequent loss of CV health, accelerate in childhood primarily in conjunction with weight gain and obesity.2–9 The number of overweight children (defined as a BMI of ≥ 85th percentile using the Centers for Disease Control and Prevention (CDC) growth charts) and the prevalence of obesity (defined as a BMI of ≥ 95th percentile using the CDC growth charts) have risen dramatically over the last four decades for youth from 2 to 19 years of age,10,11 with a recognized epidemic occurring between the mid-1980s and mid-1990s in the U.S.11,12 U.S. data from 2009–2010 indicate that 17% of 2 to 19 year-olds are obese, and an additional 15% are overweight.13,14 Youth with obesity have significantly worse circulating lipid profiles (higher total and low-density lipoprotein (LDL) cholesterol, higher triglycerides, and lower high-density lipoprotein (HDL) cholesterol), higher blood pressure (BP), glucose, and insulin concentrations than their non-obese peers.3,7–9,15 Obesity in youth is also linked to increased left ventricular (LV) mass in childhood16,17 and adulthood,18 as well as increased carotid intima-media thickness measured in adulthood.19–24 Although obesity prevalence has plateaued in the last decade, the rates in minority, low income, and rural populations remain high.25
Moreover, rates of pediatric severe obesity are increasing and the prevalence is approximately 6% in the U.S.26 Youth with severe obesity are at much higher risk of developing CV disease even compared to overweight or obese peers.27
There is also evidence that childhood levels of CV risk factors predict early subclinical atherosclerosis and cardiac pathology28,29, adult morbidity and mortality.30,31 The Bogalusa Heart Study demonstrated that in youth who died at an average age of 19.6 years, there was a direct association between degree of atherosclerosis in the coronary arteries and levels of ante-mortem CV risk factors, including BMI, lipids, and BP.28 The Pathobiologic Determinants of Atherosclerosis in Youth (PDAY) Study, which included autopsies of nearly 3,000 individuals aged 15–34, provided similar results in post-mortem examination to the Bogalusa Heart Study findings.29
The stages of CV disease prevention include primordial (the prevention of risk factor development), primary (the prevention of CV disease and stroke among individuals at risk), and secondary (the prevention of recurrent disease and complications). Most children are born with ideal CV health, which is defined by the AHA as the simultaneous presence of four favorable health behaviors (related to smoking, body mass index, physical activity, and healthy diet status) and three favorable health factors (total cholesterol, blood pressure, and fasting blood glucose levels) (Table 1).1 Unfortunately, over time most children experience a decline in health factors and behaviors resulting in loss of ideal CV health as they reach adulthood. Since it is well known that it is difficult to achieve sustained lifestyle changes in adults, and risk factor control through the use of medication cannot fully restore the low risk state present in ideal CV health, maintaining better levels of CV health through childhood is a desirable goal.1 The advancement and sustainability of the AHA’s goal (“By 2020, to improve the cardiovascular health of all Americans by 20% while reducing deaths from cardiovascular diseases and stroke by 20%”)1 directly hinges upon promoting ideal health behaviors for the maintenance (or improvement of non-ideal) health factors in children and adolescents. The collective goal of pediatric healthcare providers and researchers—and for society as a whole should be to understand how ideal health behaviors and health factors are lost, and how this decline might be prevented.
For the pediatric population, the following AHA health behavior criteria are suggested in AHA’s definition of CV health: abstinence from smoking, a body-mass index (BMI) < 85th percentile, sixty minutes or more of moderate/vigorous physical activity daily, and adherence to a diet emphasizing fruits, vegetables, fish, whole grains, low sodium and few sugar-laden foods and drinks. AHA recommended health factor metrics for ideal CV health in children are as follows: total cholesterol < 170 mg/dL, blood pressure (BP) < 90th percentile, and a fasting plasma glucose level of < 100 mg/dL.1 Although the authors recognize BMI could more objectively be viewed as a health factor, for purposes of agreement with the AHA Strategic Impact Goal Statement, in this document we have maintained its classification as a behavior. The issue of BMI classification merits further consideration in future definitions.
Although “normal” levels for childhood CV health factors have been defined using population-based distributions, definitions for elevated or “high risk” levels have been based on clinical expert consensus32–37 due to the lack of long-term data relating elevated childhood CV risk factor levels to adult CV endpoints. Significant developmental changes during maturation are likely to reduce the strength of the associations between CV risk factors measured in childhood and adult CV risk factors and outcomes; for example, fluctuations in CV risk factor levels during puberty are well known.38–41 The International Childhood Cardiovascular Cohort (i3C) Consortium data indicate that current childhood risk thresholds for lipids have low sensitivity and specificity for identifying elevated lipid classification in adulthood.42–45 The use of cross-sectional population-based cut-points for defining risk in childhood can contribute to significant risk misclassification later in life. Thus, longitudinal data tracking CV health metrics from very early in life through maturation and linking these to adult CV health metrics is essential for establishing improved surveillance tools.
In the AHA Strategic Impact Goal Statement pediatric cut-points defining ideal CV health were provided as a first step toward improving primordial prevention of CVD.1 Some of these cut-points are imperfect and pose challenges to accurately identifying the “at risk” child. These cut points are less than optimal because they are based on percentiles from general populations rather than on relations to outcomes. The values were chosen to coincide with definitions used in current guidelines, and are available in NHANES. Nevertheless, such metrics will aid in the assessment of educational and preventive programs, provide data about improvements in health behaviors (i.e. as healthy diets and physical activity), and for reporting on declines in prevalence of smoking, overweight and obesity, and improvement in values for total cholesterol, blood pressure, and presence of elevated fasting blood glucose.46 Clearly, many aspects of ideal CV health are challenging to define and measure; the sections below offer perspectives on the challenges for addressing specific CV health factors.
In the AHA Strategic Impact Goal Statement, the ideal metric for smoking behavior is defined for youth 12 to 19 years of age as “Never tried; never smoked a whole cigarette”. Determination of smoking habits, particularly in children and adolescents, is challenging. Questionnaires may underestimate the true smoking rate due to perceived loss of confidentiality when parents or others are present,47 however the Centers for Disease Control Data may circumvent some of these limitations.48 Assessment is also affected by factors such as varying definitions of smoking, fear of reprisal, or desire to inflate one’s status in the eyes of others. To successfully estimate smoking behavior in pediatric populations, objective measurement techniques can be used (e.g., cotinine levels) to estimate second-hand smoke exposure, light smoking, and heavy smoking.
Availability to evaluate such assessments in pediatric populations is particularly pertinent since approximately 4.8 million U.S. children younger than 12 years are exposed to second-hand smoke in their homes. Furthermore, a report on neurobehavioral disorders in children exposed to second-hand smoke has shown a two-fold increase in prevalence compared to those not exposed to second-hand smoke in their homes.49 Although cotinine levels are available in many population-based investigations, including in a subset of participants in NHANES, exposure to second-hand smoke was not included as a primary CV health metric in the AHA Strategic Impact Goal Statement due to insufficient evidence linking second-hand smoke exposure to adverse CV health among youth.
The growing numbers of youth that have used electronic cigarettes or “e-cigarettes” is also notably increasing50. This is particularly concerning for the CV health of US children and adolescents because the use of e-cigarettes is associated with increased intention to smoke cigarettes among those who never smoked conventional cigarettes.50,51 E-cigarette use was also not listed as a primary CV health metric in the AHA Strategic Impact Goal Statement due to insufficient data available to evaluate its contribution to adverse CV health.
BMI is the most widely used measure of weight status in public health surveillance and in epidemiological research in children and adolescents. In large, diverse groups BMI is well correlated with adiposity (i.e., body composition). BMI is widely used to screen children and adolescents for overweight and obesity and is an easy-to-calculate metric. The Centers for Disease Control and Prevention (CDC) Growth Charts provide sex-specific BMI-for-age growth curves for children aged 2 to 20 years.52 Using these charts, normal weight status is defined as an age/sex-specific BMI < 85th percentile. Overweight is defined as an age/sex-specific BMI ≥ 85th and < 95th percentile. Obesity is defined as an age/sex-specific BMI ≥ 95th percentile.34 The criterion set for ideal CV health is a BMI < 85th percentile. The recommended method for determining BMI is to objectively measure height and weight, calculate BMI as kg/m2, and either plot BMI on the CDC growth chart52 or use statistical analysis software to calculate the age/sex-specific BMI percentile. BMI is the most widely used measure of weight status in public health surveillance and in epidemiological research in children and adolescents. While BMI is highly correlated with adiposity,52 it is not an ideal measure of fatness (i.e., percent body fat) in children and adolescents.53,54 It is known that variability in lean weight is a source of error in estimates of adiposity that are based on BMI.54,55 A criterion measure of adiposity is provided by dual-energy x-ray absorptiometry (DXA), which provides highly reliable estimates of lean mass, fat mass and percent body fat.56,57 Further, skinfold thicknesses58 and bioelectrical impedance59 have been widely used to estimate percent body fat in research studies.
Healthy dietary behaviors directly influence multiple CV risk factors such as obesity, dyslipidemia, hypertension, and hyperglycemia. Two of the primary features of healthy eating include diet quality and energy balance; the latter is defined as caloric consumption matched with energy expenditure. Unfortunately, compared to the other six ideal health behaviors/factors categories, children in the United States score most poorly in regard to a healthy diet. Approximately 91% of U.S. children are classified as having a “poor” diet score, 9% are classified as “intermediate,” and <0.5% as “ideal.”1 Moreover, a higher percentage of children than adults are ranked in the “poor” category for diet quality.1 This worrisome finding is consistent across all pediatric age groups, races, and sex.60
Dietary recommendations in the AHA Strategic Impact Goal Statement are clear but need to be scaled to account for the varying energy requirements across childhood.1 Avoidance of obesity in children is key. Balancing energy intake to match growth and activity needs can mean the difference between successful versus compromised management of lifetime risk. Diet assessment remains challenging in the absence of standardized, simple to use, age-appropriate, validated tools. Available diet measures have poor reliability,61,62 and many youth consume a major portion of their diet outside the home, unobserved by parents/guardians, making assessment of diet in children difficult for providers and researchers.63,64 In addition, commercially-available food frequency questionnaires may not be appropriate across race/ethnicity and are challenging in situations of low literacy.65–67
The majority of US children do not meet the recommendations for a healthy diet. Sodium, sugar, solid fats and refined carbohydrates are over-consumed while fruits, vegetables, whole grains, dairy and dietary fiber are under-consumed by the majority of children. The 2015 US Dietary Guidelines Advisory Committee (DGAC)68 emphasized the role of the macro-environment, including economic and price structures, food production and distribution systems, transportation and agricultural practices and policies, as major influences driving personal choices in the various settings where food is prepared and served. On the basis of thorough review of the literature, the DGAC prioritized four key settings that were considered especially relevant in obesity prevention: neighborhood and community food access; child care (early care and education); schools; and worksites. Two of these four areas concern environments relevant to children. The AHA is actively engaged in addressing heart healthy diet and lifestyle in early childcare through the “Healthy Way to Grow” program involving underserved communities. Also the Voices for Healthy Kids Policy Research program, in conjunction with the Robert Wood Johnson Foundation, is addressing policy levers in community, schools and early childcare that target key factors considered strategic in improving adherence to the recommended diet and lifestyle behaviors. Included are healthy food financing initiatives, healthy restaurant meals, school foods, school marketing and water access throughout schools and other environments where children are active. For maximum adoption the recommended heart healthy diet for children requires personal choice on the part of parents and ideally is reinforced throughout the community and school settings.
Physical activity has been defined as any bodily movement produced by skeletal muscles that requires energy expenditure.69 The 2008 Physical Activity Guidelines for Americans recommend that children ages 6 to 17 years engage in 60 or more minutes of moderate- to-vigorous-intensity aerobic physical activity per day.70 Further, it is recommended that this period of activity include muscle-strengthening and bone-loading activities at least 3 days a week.70 Physical activity is a complex behavior that is performed for many different purposes, in many different settings, and in a wide range of forms. Accordingly, there is no single measure of physical activity that can validly assess all elements of a child’s physical activity pattern.
For determination of compliance with the aforementioned federal physical activity guideline, the preferred method of assessment is accelerometry. An accelerometer is an electro-mechanical motion sensor that provides an objective measure of a child’s participation in physical activity across the entire range of physical activity intensities. The device is small and relatively unobtrusive, and therefore it can be used to measure physical activity for multiple days thereby providing a reliable reflection of a child’s usual physical activity level. Accelerometry has been incorporated into the protocol for NHANES, and so this procedure now serves as the basis for producing prevalence estimates for compliance with physical activity guidelines in U.S. children and adolescents.71 Accelerometry has been used to measure physical activity in children across the developmental continuum, and this method has been used extensively with children as young as three years of age to evaluate physical activity behavior of children attending childcare centers and preschools.72,73 A positive attribute of accelerometry is that raw data can be stored indefinitely and reanalyzed as new data reduction strategies are developed.
Accelerometry, while providing an objective and reliable assessment of physical activity in children and adolescents, has some significant limitations. Accelerometry underdetects non-weight-bearing activity (e.g., bicycle riding) and cannot be used to assess water-based activities (e.g., swimming). There are also challenges with compliance in wearing accelerometers, particularly among children and adolescents. Importantly, accelerometry does not provide any contextual information about the type, location and social setting in which physical activity is performed.
To complement accelerometry, self-report and/or surrogate report instruments have been developed to provide information about activity types and contexts. An example is the Youth Risk Behavior Surveillance system, which includes several items on physical activity behavior. This instrument is administered at regular intervals to nationally representative samples of American high school students. The YRBS provides student-reported information on frequency of participation in moderate and vigorous intensity physical activity, muscle strengthening activities, physical education classes, and organized sports.74 In addition, the School Health Policies and Practices Study (SHPPS), a CDC managed surveillance system, provides information on the availability of school-based physical activity programs including physical education, school sports, recess, and other physical activity opportunities at the elementary, middle, and high school levels.75
The 2011 National Heart, Blood, and Lung Institute (NHBLI) Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents noted that the 1992 Guidelines targeted the identification of children with elevated LDL-C, while the current Guidelines address the increasingly predominant combined dyslipidemic pattern detected in children and adolescents including moderate-to-severe elevation in triglyceride level, normal-to-mild elevation in LDL-C, and lower HDL-C levels.33 Key findings of this report are summarized in Table 2.
The current AHA Strategic Impact Goal Statement establishes a level of 170 mg/dL as ideal for children 6–19 years of age, but this wide age range presents some challenge. For example, during puberty, there is typically a reduction in total blood cholesterol of 10–15%, regardless of diet and the mechanisms are poorly understood.76 There are also race and sex differences in lipids that become more pronounced after puberty. Higher levels of LDL-C and lower levels of HDL-C are noted after puberty, especially in white boys. Counterintuitively lower levels of triglyceride are documented in black girls after puberty despite a higher prevalence of obesity.77 These effects of puberty may contribute to the differences noted by race in the post pubertal clustering of risk factors that typically occurs.78 While total blood cholesterol level remains the strongest predictor of CV outcomes in NHANES, the increasingly more prevalent detection of combined dyslipidemia that accompanies the development of an obesity pattern (high triglycerides/low HDL-C) may represent an important risk factor that should be addressed.
The AHA Strategic Impact Goal Statement defines ideal BP as a level <90th percentile for children 8 to 19 years of age. As with BMI, the practitioner should evaluate BP levels using the sex/height-specific percentile charts,32 with the caveat that the charts do not account for known differences in BP levels by race.33,79,80 A major challenge of this definition is its reliance on the statistical distribution of BP levels from pooled epidemiologic data rather than linking cut-points to hard CV events.
Although 24-hour ambulatory BP monitoring is considered the most accurate method in the evaluation of hypertension and to define BP-related CV risk,81 and can reduce the uncertainty in classification due to day-to-day variability of BP levels, the cost and burden on patients to use this method make it less appealing as a technique in defining ideal CV health on a population basis. Furthermore, there is a lack of normative data across races and ethnicities.82 Therefore, replicative measures of casual (office) BP starting at age 3 may be a reasonable approach to track a child’s BP over time.
A fasting blood glucose level of < 100 mg/dL was set as the AHA Strategic Impact Goal Statement as ideal for pediatric patients. This is a challenging goal, as fasting blood glucose is rarely measured in routine pediatric care. Also, it is known that hyperinsulinism is the first abnormality seen in obese pediatric patients developing metabolic derangement, with impaired fasting glucose occurring at a much later stage in the progression toward type 2 diabetes mellitus;83 the current definition of ideal CV health does not capture this aspect of CV risk.
The American Diabetes Association developed clear guidelines, applicable to both children and adults, that define impaired glucose tolerance as a fasting blood glucose between 100 and 125 mg/dL and diabetes as a fasting blood glucose ≥ 126 mg/dL).84 While defining the upper limits of normal for diagnostic purposes is supported by high-quality evidence, establishing ideal levels for glucose and insulin is challenging due to a) differences in insulin levels based on measurement method,85–87 b) observed racial/ethnic differences in metabolic parameters in healthy children,79,88,89 and c) the physiologic rise in insulin levels during puberty that makes a single cut-point unreliable.40,90 Fortunately puberty-related changes in glucose have not been documented suggesting that the use of a single cut-point for glucose may be reasonable.91
Developing strategies toward achieving the AHA Strategic Impact Goal1 in youth populations depends largely on estimating the current prevalence of CV health behaviors and factors and identifying the target behaviors and factors as well as the populations in need of improvement. The AHA Strategic Impact Goal statement presented the “baseline” prevalence of each component and category of CV health based on both youth and adult data from the 2007–2008 National Health and Nutritional Examination Surveys (NHANES). NHANES data are collected bi-annually and have proven to be reliable and valid assessments of the health and nutritional status of adults and children in the U.S. NHANES prevalence estimates will be the primary data source for monitoring progress towards achievement of the AHA Strategic Impact Goal. However, it is important to note that despite the strengths of NHANES, these data are limited in several ways when estimating the prevalence of CV health, particularly in children and adolescents. Although NHANES participants are strategically sampled to estimate the health status of the US population, only 4,000–5,000 children and adolescents <19 years of age are recruited for each exam. These sample sizes are further reduced when stratifying by age groups: ≈30% 0–5 years old, ≈30% 6–11 years old, ≈30% is 12–19 years old. Furthermore, a subsample of only 10–15% of participants are selected for laboratory-based assessments, such as fasting blood glucose and blood lipids. The numbers of NHANES participants representing the CV health status of different race/ethnicity groups is also very limited: non-Hispanic whites make up the largest proportion of participants (≈ 40%), followed by non-Hispanic blacks (≈ 25%), and Hispanic-Mexican Americans (≈ 25%). The remaining participants are comprised of Hispanics-Other (≈20%) and a combined group of American Indians, or Alaskan Natives, Asian, Native Hawaiians or Other Pacific Islanders (≈10%) limiting differentiation between these racial/ethnic groups. Overall, these limitations in sample sizes become very restrictive when attempting to examine the status of CV health according to age, sex, and/or race/ethnicity. This issue becomes particularly evident when estimating “poor” and “intermediate” CV health due to the lower prevalence of these categories compared to adults.
To remain consistent with the baseline data used in the AHA Strategic Impact Statement for the 2020 goal baseline, in this paper the current status of CV health in children and adolescents was estimated using NHANES 2007–2008 data, however, additional population-based sources will be presented to gain additional estimates of CV health prevalence in areas where NHANES data may be limited. NHANES prevalence estimates for the status of CV health in U.S. children and adolescents according to age, sex, and race/ethnicity are presented in Figure 1.92
The NHANES 2007–2008 survey includes questions about tobacco use for participants 12 years of age and older. Among participants 12–19 years, approximately one-third were categorized as having “poor” current smoking status (i.e. had tried a cigarette in the prior 30 days), with a slightly higher prevalence in boys (34%) than in girls (31%). When examined across major racial/ethnic groups, non-Hispanic black adolescents had the lowest prevalence of “poor” CV health status for smoking (26%), and Mexican-Americans exhibited the highest prevalence of “poor” current smoking status (36%).
Obesity continues to be a challenging problem among children and adolescents. According to the NHANES 2007–2008 estimates, prevalence of “poor” BMI (≥ 95th percentile) is higher across older age groups, ranging from 9–11% in 2–5 year olds to 19–27% of 12–19 year olds. At younger ages, girls have a lower prevalence of “poor” BMI status compared to boys, but at ages 6–19 years, boys consistently exhibit a higher prevalence of “poor” BMI than females. Younger children (2–5 years) also exhibit the highest prevalence of “ideal” BMI (78–80%), while adolescents (12–19 years) exhibit the lowest prevalence of “ideal” BMI (girls, 52%; boys, 60%). Mexican-American and non-Hispanic black children 2–5 years exhibit notably greater prevalence of “poor” BMI than non-Hispanic white children. Mexican-Americans children 6–11 years exhibit the highest prevalence of “poor” BMI (24%) compared to non-Hispanic white and non-Hispanic black youth. However at 12–19 years, non-Hispanic black youth exhibit similar levels of “poor” BMI status compared to Mexican-American youth (≥30%). Non-Hispanic black adolescents 12–19 years exhibit the lowest prevalence of “ideal” BMI (42%) compared to Mexican American (52%) and non-Hispanic white adolescents (56%).
The prevalence of compliance with the current physical activity guideline (60 or more minutes of moderate- to vigorous-intensity aerobic physical activity)70 was assessed via accelerometry in the 2003–2004 cycle of NHANES. Among children ages 6–11 years, 48.9% of boys and 34.7% of girls met the physical activity guideline.71 The prevalence of compliance was much lower among 12- to 15-year-olds, as only 11.9% of boys and 3.4% of girls met the guideline, and among 16- to 19-year-olds, only 10.0% of boys and 5.4% of girls met the guideline. In an examination of the prevalence of meeting the physical activity guideline in selected race/ethnicity groups, among 6- to 11-year olds, compliance with the guideline was highest among non-Hispanic black children (50.4%) compared to non-Hispanic white (39.9%) and Mexican American children (41.3%).93 Among 12- to 15-year-olds and 16- to 19-year-olds, compliance with the guideline was much lower than that of 6- to 11-year-old children for each of the racial/ethnic groups and was not markedly different across racial/ethnic groups. The NHANES protocol also included child self-report of physical activity, which produced higher prevalence estimates of compliance with the physical activity guidelines compared to accelerometry. For example, self-reported data from 2007–2008 NHANES for adolescents 12–19 years of age showed approximately two-thirds of boys but only fifty percent of girls report “ideal” levels of physical activity, while 13% of boys and 21% of girls report “poor” levels of physical activity (i.e., report no physical activity over the past 30 days).
The 2010 U.S. Dietary Guidelines Advisory Committee reviewed the most recent NHANES data in determining mean dietary intake across all age groups. For children ages 2–18 years, the highest sources of energy intake (kcal/day) are contributed by simple carbohydrates (grain-based desserts, sugar-sweetened beverages). The impact of a diet based on these energy-dense, nutrient-poor foods is further heightened by inadequate intakes of vegetables, whole grains, and fiber.94 The components of the healthy diet score and adherence to dietary recommendations in children are illustrated in Figure 2. Prevalence estimates for children and adolescents who meet the “ideal” levels of the healthy diet score are the lowest of all CV health metrics. Based on 2007–2008 NHANES data, less than 1% of 2–19 year-olds report dietary intakes consistent with meeting 4 or 5 components of the healthy diet score. At 5–11 years, the majority of children (boys, 86%; females, 83%) met either zero or one healthy diet score components (i.e., exhibited a “poor” healthy diet score); these estimates were consistent with estimates in the 12–19 year age range. At 5–19 years, Mexican Americans were the least likely to have a “poor” diet score (79–85%) while Non-Hispanic white males were most likely (88–89%).
In NHANES 2007–2008 children ages 6–11 years, over one-third have total cholesterol levels that are not ideal. Specifically, 27% of girls and 28% of boys 6–11 years exhibit “intermediate” status for total cholesterol, with 10–11% exhibiting “poor” status. Prevalence is similar for adolescents 12–19 years of age, with 65% of girls and 73% of boys categorized as “ideal” and 26–35% of adolescents categorized as “intermediate” or “poor” for levels of total cholesterol. Across racial/ethnic groups, prevalence of “ideal” total cholesterol was similar (63–65%); Mexican-American children exhibited the highest prevalence of “ideal” and non-Hispanic whites the lowest prevalence of “ideal” total cholesterol. At 12–19 years, non-Hispanic adolescents exhibited the lowest prevalence of “poor” total cholesterol (7%) compared to Mexican-Americans (9%) and non-Hispanic blacks (10%)
The prevalence of “ideal: blood pressure for children and adolescents is the highest of all CV health metrics. Approximately 93% of boys and 90% of girls 8–11 years and 91% of boys and 88% of girls 12–19 years exhibit “ideal” blood pressure. Differences in prevalence of “intermediate” and “poor” status for blood pressure are most notable when examined across racial/ethnic groups. Among children 8–11 years, the prevalence of “poor” blood pressure is consistently around 4% across non-Hispanic white, non-Hispanic black and Mexican-American youth. At ages 12–19 years, 6% of non-Hispanic white adolescents are categorized as having “poor” blood pressure status, compared to 3% of Mexican-Americans and <1% for non-Hispanic blacks. Despite low prevalence of “poor” blood pressure status among non-Hispanic black adolescents (12–19 years), non-Hispanic black adolescents exhibit the highest prevalence of “intermediate” blood pressure status (15%), compared to Mexican Americans (12%) and non-Hispanic whites (1%)
At 12–19 years, prevalence of “ideal” fasting blood glucose is notably higher in girls (80%) than boys (63%) and between 20–38% of children exhibit “intermediate” or “poor” fasting plasma glucose. Mexican-Americans exhibit the lowest prevalence of “ideal” fasting blood glucose (58%) compared to non-Hispanic whites (73%) and non-Hispanic blacks (79%) at the same age. Since a very small number of NHANES 2007–2008 participants ages 12–19 years were noted to have “poor” status for fasting blood glucose levels (n=5), the accuracy of the prevalence estimates from this sample is limited and it is likely that many were not fasting. Another data source with specific prevalence estimates for type 2 diabetes (which is consistent with the AHA definition of poor fasting plasma glucose) is The SEARCH for Diabetes in Youth study. SEARCH is an observational, multicenter study focusing on physician-diagnosed diabetes in individuals < 20 years old. It provides estimates of the population prevalence of diabetes by type, age, sex, and ethnicity in a nationally-representative sample of U.S. children with wide ethnic and socioeconomic representation from four geographically defined populations and two national health plans. In 2009, SEARCH estimates95 of the prevalence of type 2 diabetes among adolescents aged 10 through 19 years was 0.046%, with lower rates in males (0.038%) than females (0.058%). The highest prevalence of type 2 diabetes in children 10–19 years of age was observed in American Indians (0.120%), followed by black (0.106%), Hispanic (0.079%), and Asian/Pacific-Islander youth (0.034%), and the lowest prevalence in non-Hispanic white youth (0.017%). Children aged 10–14 years exhibited lower prevalence (0.023%) compared to those 15–19 years of age (0.068%). These estimates more precisely represent the prevalence of type 2 diabetes in youth; estimates from the population-based surveillance study should be used in conjunction with estimates from the NHANES data to monitor changes in the prevalence of type 2 diabetes (e.g. “poor” status in levels of fasting blood glucose) in children < 20 years of age.
Engaging in ideal health behaviors early in life can have a beneficial impact on all of the health factors. The maintenance of ideal health from birth throughout the life-course is the prime goal. However, many children born healthy will, unfortunately, develop unhealthy behavioral patterns early in life. The life-course approach is an important tenet of the concept of ideal CV health. That is, a premium should be placed on assisting children to maintain the standards of ideal CV health early in life (primordial prevention) instead of taking a “wait and see” approach by addressing and/or treating health and risk factors later in adulthood when they have become entrenched. While the level of intensity required to improve CV health classification (from “poor” to “intermediate” and from “intermediate” to “ideal”) may differ, the core principles and approaches are the same.
The eating pattern recommended to achieve nutrient adequacy while reducing sources of solid fats, added sugars, and non-nutrient dense foods is the Dietary Approaches to Stop Hypertension (DASH) diet. The DASH diet is a plant-focused diet rich in fruits, vegetables, nuts, which includes low-fat and non-fat dairy products, lean meats, fish, poultry, mostly whole grains, and heart healthy fats; it is ideal for growing children. This eating pattern was incorporated into the CHILD-1 Diet recommended by the 2011 Expert Panel on Integrated Guidelines.96,97 Rather than targeting nutrient-specific goals, this approach recommends servings of foods that meet nutrient needs.
Strengths of the CHILD-1 Diet are: inclusion of evidence-based recommendations beginning at birth through age 18 years that are consistent with U.S. Dietary Guidelines and the DASH-type diet recommended for adults, as well as an emphasis on the benefits of breastfeeding and delayed introduction of solid foods. The CHILD-1 Diet provides nutritious, preventive, energy-balanced guidelines appropriate for children, adults and families.
Research is needed to address the influence of environmental, behavioral and cultural factors that can enhance or detract from the adoption of the recommended guidelines and to develop methods for pediatric providers to best assess and address these factors within a busy clinical setting. Limited research has been initiated to test and evaluate possible approaches.98
To help children develop healthy eating habits, they should be introduced early and often to a wide variety of fruits, vegetables, fish, and whole grains. This requires help from parents and caregivers who need to recognize the advantages of role modeling. Our immediate goal should be to educate parents and children about the advantages of a diet that includes 2 to 3 age-appropriate servings of healthy diet components at each meal with a goal of achieving the following by age 18: ≥ 4.5 cups of fruits and vegetables per day; ≥ two 3.5 ounce servings of fish per week; ≥ three 1 ounce servings of fiber-rich whole grains per day; < 1500 mg of sodium per day; and ≤ 450 kcal of sugar sweetened beverages per week,1 as illustrated in the age-specific CHILD 1 Diet.96 Parents are important change agents in achieving these goals, and in contributing to halting and reversing adolescent obesity. There is consistent and growing evidence that the DASH-style eating pattern offers many advantages in providing nutrient quality and risk reduction potential in growing children despite continuing questions regarding the role of specific nutrients or foods, that may have the most effective impact long term.99
Health care providers can use Motivational Interviewing Principles by asking parents what foods their children most enjoy. The health care providers can then help parents choose reasonable goals and approaches that the parents would be willing to initiate to improve their child’s diet. A practical first step for many children is to include at least one more serving of a favorite fruit or vegetable or a fiber rich whole grain food on a daily basis. Gradual reduction of high sodium foods and sugar-sweetened beverages is encouraged, without focusing on immediate elimination of unhealthy foods. Creative approaches to food preparation (e.g., finger sized cut-up fruits served on colorful plates, different shapes, making faces or animals, fruit salsa served with whole-grain crackers, vegetable-laced pastas, pizza, lasagna, etc.) and encouraging participation of child with parent in food preparation, vegetable gardening and harvesting can enhance adherence to good dietary practices and habits. Similarly, preparing and serving mixed dishes that contain mild-flavored fish (e.g., fish on a stick, or in a soft taco with salsa), increases the attraction while enhancing nutrient quality, energy balance (unless fried) and expanding nutritious meal options.
The documented association between sugar-sweetened beverages and childhood obesity has now been established.100,101 The AHA Strategic Impact Goal Statement healthy diet advocates consumption of ≤ 450 kcal of sugar-sweetened beverages per week),1 or no more than 70 kcals daily. (This is about half a 12 oz. soda can/day). The American Academy of Pediatrics and the CHILD 1 Diet, recommend avoidance of all sugar- sweetened beverages. Although zero consumption is ideal, this may require gradual reduction, depending on the age of the child. In the youngest children, beverages should primarily include water and low-fat milk (except in the case of infants who are recommended to consume only breast milk in the first six months of life or formula if breast milk is not an option. If consumed at all, sugar sweetened beverages should be reserved only for special occasions and consumed in small amounts.
A large majority of children in the U.S. do not meet recommendations for physical activity, and their time spent in sedentary activities is higher than recommended.102,103 The Physical Activity Guidelines for Americans Midcourse Report: Strategies to Increase Physical Activity among Youth summarized the evidence regarding the effectiveness of interventions to increase physical activity and youth.104 Interventions were categorized by settings: school, preschool and childcare center, community, family and home, and primary care. An expert panel conducted a literature review using a review-of-reviews approach.
A major conclusion of the report was that the strongest evidence of effectiveness is for school-based intervention strategies.104 Within the school setting, solid evidence exists to recommend multi-component school interventions. Multi-component school interventions typically include strategies such as enhanced physical education classes, classroom activity breaks, activity sessions before and/or after school and active transportation to and from school. In addition, interventions that focused specifically and singly on enhanced physical education classes were also found to be effective in increasing physical activity levels of youth. Several other school-based strategies were considered, but supportive evidence was either less robust or lacking. Some evidence supports strategies based on promotion of active transport to school and classroom exercise breaks. Evidence was insufficient for afterschool programs and physical environmental changes at the school site. The review of physical environmental interventions included consideration of modifications to children’s play spaces. Interventions in preschools and childcare settings have produced some positive results, and the same is true for community-based enhancements of the built environment. At the present time there is insufficient evidence to support home/family-based interventions and strategies implemented through healthcare settings. The report included a strong endorsement for more research on physical activity interventions to increase physical activity in youth, particularly in settings outside the school environment.
Smoking is a clear and still present danger to the CV health of America’s children. Although tobacco use has declined,48,105,106 many youth are exposed to secondhand smoke and/or are primary tobacco or e-cigarette smokers.48,51,107 It is a risk factor that is eminently modifiable with a variety of techniques, including behavioral interventions, pharmacological interventions, and policy tools. A major goal for health professionals is to encourage smoking cessation in primary users, reduce secondhand exposure, and prevent smoking initiation. This could help those considered in the poor range of CV health metrics for smoking to move towards the ideal CV health metric for smoking.
A wealth of behavioral modification tools have been developed, and have shown varying degrees of effectiveness.108,109 Behavioral change is dependent on the motivation of the smoker; therefore interventions generally use a cognitive behavioral approach. Interventions include counseling, motivational enhancement and, more recently, text message-based, or Internet-based messaging, as well as pharmacological approaches such as the use of bupropion or nicotine replacement therapies.110–114 In a recent meta-analysis, state-of-change interventions and motivational enhancement interventions were associated with a roughly 50–60% improvement in smoking cessation rates.109 The few studies available for review of pharmacological interventions were not found to be effective in smoking cessation for youth.
Secondhand smoking exposure renders multiple individuals vulnerable, including passersby, coworkers, spouses, and children (both alive and in utero). Education efforts to prevent smoking and intervention efforts to achieve non-exposure in children and adolescents have included messaging to pregnant women about the health risks to their unborn child. It is important to note that 40% of children are smoke-exposed worldwide.115 A recent study on the effectiveness of parent-directed interventions to protect children from secondhand smoke reveals that parent-reported outcomes improved by only 12% for individual smokers and 7% for intervention families, with some evidence for publication bias.116 However, modest effects over a broad base can add up to substantial change.
Broad-based effects can be achieved through assiduously implemented individual therapies or group- or population-based interventions. Population interventions are generally disincentives, including prohibition on smoking in public places or private locations likely to offer high exposure, taxes on cigarette purchases, and health insurance penalties. Policy-based incentive approaches are less common but include cessation-treatment subsidies and inducements.117,118 The zenith of broad-based interventions is the prevention campaign. School-based prevention is modestly effective, reducing smoking initiation by ~12%.119 Mass media messaging campaigns are popular, low-intensity avenues of intervention, but formal investigations into their effectiveness are warranted. The myriad health effects associated with smoking may call for the implementation of the World Health Organization’s Framework Convention on Tobacco Control mPOWER initiative in communities across America.120
The 2012 Preventing Tobacco Use among Youth and Young Adults Report of the Surgeon General (http://www.surgeongeneral.gov/library/reports/preventing-youth-tobacco-use/factsheet.html) summarizes the continued need to address this important issue, as for every death of an adult caused by smoking there are two new replacement smokers under the age of 26. Evidence regarding the urgency of addressing youth in this CV health promotion initiative is compelling; 9 out of 10 smokers start by the age of 18, with rare smokers starting after age 26.
Historically, avoidance of excessive risk has been the basis for improvement of CV health. The lack of CV disease outcomes in childhood makes it difficult to rely on dichotomized levels of CV risk metrics, and underscores the importance of addressing these metrics as a continuum of poor-intermediate-ideal levels. Future research will need to address whether current recommended cutoffs of ideal health metrics are appropriate.
In addition to the clear need for prevention strategies for outcomes with long lag times, continuing efforts are needed with respect to improved surveillance and public policy. There is a paucity of valid, large scale, longitudinal assessments on CV health factors and behaviors. The benefits of surveillance are two fold: data can assess the effects of interventions; and it can assist in predicting future health risks and health related budgets. Roll-out of tools and surveys to assess ideal CV health is urgently needed, and should focus on continuous measurements as opposed to only measuring abnormal CV risk factors. Also there is limited information in the literature on short-term improvements in CV health metrics in children as a result of lifestyle changes.
While the application of primary and secondary prevention strategies have clearly played a role in the observed reduction, more attention to the retention of CV health metrics from childhood through the course of life is a rational strategy to pursue.121 Data are needed to translate that rational strategy to proven interventions. Core data needed to promote ideal CV health in children include: differentiating between physiologic maturation versus pathologic aberration, disentangling intertwined CV risk behaviors and factors, quantifying effects across the long latency between childhood risk factor and adult outcome events.
The AHA Strategic Impact Goal targets improving the CV health of “all Americans,” including individuals of all ages and races/ethnicities. However, the major data source for health surveillance of Americans (i.e. NHANES) is limited with regard to the age ranges of children surveyed. Although BMI is assessed in NHANES participants as young as 2 years of age, no assessments are available that allow categorization of CV health status in children under the age of 12 years for smoking or fasting blood glucose.92 NHANES data are also limited in that surveillance of dietary intake is available for children younger than 5 years, but no surveillance of total cholesterol is available for children younger than 6 years, and no surveillance of blood pressure is available for children younger than 8 years. Due to the small numbers of individuals sampled across various racial/ethnic groups, NHANES data are also limited in providing prevalence estimates for the status of CV health in Asian/Pacific Islanders, American Indians and Alaskan Natives, and other Hispanic individuals besides Mexican-Americans. More detailed surveillance of the majority of CV health components in all early childhood populations is needed, particularly across a wider range of race/ethnicities to assess the effectiveness of current and future population-based strategies aimed at improving the CV health among children of all ages.
One potential opportunity to improve upon current surveillance methods is to take advantage of “big data” and analytics to track trends in various health factors and health behaviors. In regard to health factors, use of data from the electronic health record could be used to compliment data generated from ongoing studies like NHANES to further refine surveillance. In addition, patient-generated data, including data obtained from wearable technologies such as accelerometers, could be prospectively collected and examined in the context of epidemiological studies of CV health. A recent scientific statement on mobile health illustrated a dearth of research validating wearable technology, while a large proportion of the adult population is already using them.122 Harnessing the power of “big data” and patient-generated data will address some of the limitations of existing cohort studies and form the basis for refining many of the ideal health factors and behaviors. “Big data” can also be harnessed to assist with problems inherent in existing datasets, such as the lack of childhood cohort data with sufficient events for analyses. The personal and public health perspective on ideal health should include assessment beginning at birth, as well as consideration for genomic basis for cardiovascular health.
In this document we identified important strengths and limitations with the current approach to ideal CV health in children and adolescents. While the overall concept is a very important one, the choice of health metrics and development of the poor intermediate and ideal categories is limited by currently available national survey data. A new process by which CV health factors are identified independent of available data, with that process then driving decisions for NHANES and other population-based studies would be an improvement. Optimally, availability of longitudinal data on these factors would allow evaluation of the process of loss of ideal CV health and connect that loss with later adverse CV health outcomes.
Overall it is clear that much of the benefit of ideal CV health factors is lost in childhood and adolescence. This is in large part due to the adoption of unhealthful diet and physical activity behaviors. Assessment of best practices to maintain ideal CV health behaviors and factors is beyond the scope of this statement. Subsequent analyses should address the evidence base for counseling and other behavior change methods for young individuals and their families to maintain ideal CV health in practice.
The authors want to thank Annabel Kornblum MPH, and Mindi Khan, MPH, RD, for conducting literature search, compiling and organizing the sections, ensuring cohesiveness of the sections and assisting with tables and figures.