Abstract
Background
Life's Essential 8 (LE8) metrics for cardiovascular health (CVH) aid primordial prevention in US populations.
Methods and Results
We conducted a child cohort study (PROC [Beijing Child Growth and Health Cohort]) with baseline (2018–2019) and follow‐up (2020–2021) assessments, enrolling disease‐free 6‐ to 10‐year‐old children from 6 elementary schools in Beijing. We collected LE8‐assessed components via questionnaire surveys and 3 cardiovascular structural parameters by 2‐dimensional M‐mode echocardiography: left ventricular mass (LVM), LVM index, and carotid intima‐media thickness. Compared with 1914 participants (mean age, 6.6 years) at baseline, we saw lower mean CVH scores at follow‐up (n=1789; 8.5 years). Among LE8 components, diet presented the lowest perfect‐score prevalence (5.1%). Only 18.6% of participants had physical activity ≥420 min/wk, 55.9% had nicotine exposure, and 25.2% had abnormal sleep duration. Prevalence of overweight/obesity was 26.8% at baseline and 38.2% at follow‐up. We noted optimal blood lipid scores in 30.7%, while 12.9% of children had abnormal fasting glucose. Normal BP was 71.6% at baseline and 60.3% at follow‐up. LVM (g), LVM index (g/m2.7), and carotid intima‐media thickness (mm) were significantly lower in children with high (56.8, 33.2, 0.35) or moderate CVH scores (60.6, 34.6, 0.36), compared with children with low CVH scores (67.9, 37.1, 0.37). Adjusting for age/sex, LVM (β=11.8 [95% CI, 3.5–20.0]; P=0.005), LVM index (β=4.4 [95% CI, 0.5–8.3]; P=0.027), and carotid intima‐media thickness (β=0.016 [95% CI, 0.002–0.030]; P=0.028) were higher in the low‐CVH group.
Conclusions
CVH scores were suboptimal, declining with age. LE8 metrics indicated worse CVH in children with abnormal cardiovascular structural measurements, suggesting the validity of LE8 in assessing child CVH.
Registration
URL: https://www.chictr.org.cn/index.html; Unique identifier: ChiCTR2100044027.
Keywords: cardiovascular health, children, cohort study, Life's Essential 8
Subject Categories: Diet and Nutrition, Epidemiology, Exercise, Lifestyle, Obesity
Nonstandard Abbreviations and Acronyms
- AHA
American Heart Association
- cIMT
carotid intima‐media thickness
- CVH
cardiovascular health
- FBG
fasting blood glucose
- LE8
Life's Essential 8™
- LS7
Life's Simple 7™
- LVM
left ventricular mass
- LVMI
left ventricular mass index
- PROC
Beijing Child Growth and Health Cohort
Clinical Perspective.
What Is New?
The new American Heart Association's Life's Essential 8 metrics are appropriate for assessing cardiovascular health (CVH) in Chinese children.
CVH scores were suboptimal and decreasing with age from an average of 6.6 years to 8.5 years on the basis of our general pediatric population‐based cohort study, which enrolled 1914 Chinese children at baseline and 1789 at follow‐up.
Children with high CVH scores on Life's Essential 8 had significantly lower left ventricular mass, left ventricular mass index, and carotid intima‐media thickness.
What Are the Clinical Implications?
This study provides evidence that children with high CVH scores had optimal heart/vascular health status as assessed by Life's Essential 8 versus children with low CVH scores.
The Life's Essential 8 is a valid tool to assess CVH in Chinese children and can aid in the primordial prevention of childhood cardiometabolic disorders and promotion of CVH.
Cardiovascular disease is a major contributor to the global death rate and is the leading cause of death in China, accounting for 40% of total deaths. 1 Cardiovascular disease processes often begin in childhood and progress through adolescence into adulthood. 2 The prevalence of cardiovascular disease was 421.2 per 100 000 population among people aged <20 years in China. 3 A national survey among Chinese children and adolescents reported that <2% of participants had all 7 ideal cardiovascular health (CVH) metrics assessing by the similar components of Life's Simple 7 (LS7). 4 In 2010, the American Heart Association (AHA) proposed key components (the LS7) to characterize CVH. The 7 CVH components in the LS7 were diet, physical activity, nicotine exposure, body mass index (BMI), fasting blood glucose (FBG), total cholesterol (TC), and blood pressure (BP). 5 CVH condition assessment has served as a tool for public health surveillance, guiding primordial prevention strategies. 6
LS7 proved limited in its ability to provide a comprehensive assessment of healthy lifestyles in modern stressful social environments. 6 The LS7 was hard to generalize across diverse individuals and was a suboptimal screen for children. 6 Therefore, in 2022, the AHA updated LS7 to Life's Essential 8 (LE8) by adding sleep health, revising diet, nicotine exposure, blood lipids (non–high‐density lipoprotein [HDL] cholesterol), and blood glucose (FBG or hemoglobin A1c) measures and keeping physical activity, BMI, and BP unchanged. The component metrics of LE8 can be categorized into 2 groups, 4 for health indicators and 4 for health behaviors, each applying a new scoring algorithm ranging from 0 to 100 points. LE8 score combining the 8 components also ranges from 0 to 100 points, generating a composite CVH score. 6
To verify the validity of the new LE8 metrics for CVH assessment in Chinese children, we engaged participants in a cohort study with a hypothesis that the LE8 could accurately identify the childhood CVH status of Chinese children using left ventricular mass (LVM), left ventricular mass index (LVMI), and carotid intima‐media thickness (cIMT) and thereby promote healthy behaviors in children and inform effective CVH promotion.
Methods
Study Population and Data Source
The data that support the findings of this study are not publicly available but are available from the corresponding author upon reasonable request. This study extracts data from the PROC (Beijing Child Growth and Health Cohort) study, a population‐based prospective cohort study of 1914 children aged 6 to 8 years in nonboarding primary schools in Beijing from 2018. Details of the recruitment have been published previously 7 (official website: https://www.procstudy.com). The study protocol was reviewed and approved by the institutional review board of Capital Medical University, China (No. 2018SY82). Written informed consent was distributed by the school teachers and evaluated and signed by their parents and all participants with assistance from their parents. The sequential baseline survey of the PROC study was conducted from October 2018 to June 2019 and collected comprehensive sociodemographic information, anthropometric data, blood and urine assays, cardiovascular function and structure data including cIMT and LVM via M‐model and 2‐dimensional echocardiography, and lifestyle information. We measured BP and anthropometrics again at the follow‐up in September 2020 and conducted a questionnaire survey in June 2021 adding nicotine exposure.
We enrolled all PROC study participants and extracted 11 main indicators. These were the aforementioned LE8 CVH indicators and 3 cardiovascular subclinical outcome indicators: LVM, LVMI, and cIMT. Complete LE8 indicators, the 3 cardiovascular outcomes, and other covariates were imputed and available for 1914 children at baseline and 1789 at follow‐up (Figure S1).
Health Behaviors (Diet, Physical Activity, Nicotine Exposure, Sleep Health)
LE8 includes 4 health behavioral exposures: diet, physical activity, nicotine exposure, and sleep health. A parent reported these via self‐administered questionnaire, since the children's young age would inhibit reading and understanding the questions.
1.Diet was measured using a 16‐item Mediterranean Dietary Quality Index in children and adolescents with a total score of 12 points (12 items as +1 positive scores and 4 items as −1 negative scores). 8
2.Physical activity was measured using a self‐administered questionnaire, including 16 indoor and outdoor activities lasting at least 15 minutes, modified on the basis of the Children's Leisure Activities Study Survey Chinese Version. 9 Parents recorded a child's daily activities for a week, reporting physical activities lasting >15 minutes. Activities were categorized to moderate or high intensity including walking, jogging, cycling, treadmill, skipping rope, swimming, fitness classes, and dancing. We then calculated the total duration of medium‐ and high‐intensity activities for the week.
3.Nicotine exposure measured secondhand smoke exposure based on child–parent discussion in 2021 as an effort to optimize accuracy, using modified Global School‐Based Student Health Survey core‐expanded questions 2021 Version 2. 10
4.Sleep health was measured using the Children's Sleep Habits Questionnaire. 11 Average daily sleep duration equaled [(weekday sleep duration×5)+(rest day sleep duration×2)]/7.
Health Factors (BMI, Non‐HDL Cholesterol, FBG, BP)
LE8 includes 4 health factor metrics (BMI, non‐HDL cholesterol, FBG, and BP). BMI and BP were measured at baseline and follow‐up.
1.We calculated BMI as weight in kilograms divided by height in meters squared (kg/m2). 7 We calculated sex‐ and age‐specific BMI percentiles as per the US Centers for Disease Control and Prevention 2000 growth charts.
2.We assayed blood lipids and FBG using an AU5800 automatic biochemical analyzer (Beckman Coulter Co., Ltd, Shizuoka, Japan). We calculated non‐HDL cholesterol as total cholesterol subtracting HDL cholesterol.
3.We measured BP using a calibrated automatic electronic sphygmomanometer (OMRON HBP‐1300, Dalian, China), clinically validating it before use with a standardized protocol with children resting quietly for at least 5 minutes and then sitting with their right arms naturally extended in front of them and placed flat on the table with the palm facing up. We adjusted the height of the chair so that the upper arm was at the same level as the heart and feet were flat on the floor. The sleeves labeled “SS,” “S,” and “M” were chosen to fit their arm circumference, and lower ends of each sleeve were positioned 1 to 2 cm from the elbow joint, with the width of the cuff covering about two‐thirds of the upper arm. Three measurements were conducted at 2‐minute intervals, and the average of the last 2 measures was calculated. We calculated BP percentiles according to the 2017 American Academy of Pediatrics Clinical Practice Guidelines for screening and management of high BP in children and adolescents (scoring criteria in Table S1). 12
According to the AHA guideline, LE8 scores of 80 to 100 were considered as high (ie, favorable) CVH, 50 to 79 as moderate CVH, and 0 to 49 points as low (or worse) CVH. 6
Outcome Variables
LVM, LVMI, and cIMT were our main outcome indicators to validate LE8 predictive effectiveness. We used echocardiography with an Aplio 500 Platinum Series ultrasound (Canon Medical Systems Inc., Tochigi, Japan). We measured cIMT using a probe frequency of 4 to 11 MHz, sweeping longitudinally along the long axis of the common carotid artery, measuring the anterior and posterior wall thicknesses at 1.0 to 1.5 cm anterior to the bifurcation of the carotid artery bilaterally 3 times to take the mean value in millimeters and then calculate the mean value of the 4 measurements. We measured LVM using probe frequency 2.5 to 4 MHz, according to the protocol recommended by the American Society of Echocardiography. 13 The left ventricular end‐diastolic diameter, left ventricular end‐systolic diameter, left ventricular end‐diastolic wall thickness, and end‐diastolic ventricular septal thickness were measured by a trained doctor in 3 cardiac cycles, and the average values were analyzed. Using the Devereux recommended formula, we calculated the LVM, LVM=0.80×[1.04×(end‐diastolic ventricular septal thickness + left ventricular end‐diastolic wall thickness + left ventricular end‐diastolic diameter)3− left ventricular end‐diastolic diameter3]+0.6 (g). 14 We calculated LVMI, adjusting for differences in height according to the method of de Simone (LVMI=LVM/height2.7). 15 The cIMT assesses vascular health, and LVM or LVMI assesses CVH; higher values are less healthy.
Statistical Analysis
Proportion and SE showed the distribution of scores of 8 LE8 indicators at baseline and follow‐up. We used a trend chi‐square test to determine if there was any increasing trend in the proportion of children who were overweight/obese or had elevated BP. The mean and SD assessed CVH with the 3 cardiovascular outcomes. Multiple imputations were performed for variables with missing values and 20 complete data sets were generated for analysis using PROC MIANALYZE. We performed multiple imputations according to the percentage of missing data, with 6 (0.3%) missing values in height, 7 (0.4%) missing values in weight, 43 (2.2%) missing values in sleep duration, 149 (7.8%) missing values in BP, 190 (9.9%) missing values in nicotine exposure, 198 (10.3%) missing values in LVM and cIMT, 221 (11.5%) missing values in blood glucose, 259 (13.5%) missing values in non‐HDL cholesterol, 361 (18.9%) missing values in dietary scores, and 442 (23.1%) missing values in physical activity time. We compared intergroup CVH using 1‐way ANOVA. To investigate the associations of cardiovascular structure size with CVH subgroups, a generalized linear model was used to determine point estimates with 95% CIs to compare low/moderate CVH with high CVH (reference). The results in Tables 1, 2, 3 through 1, 2, 3 and Figure 1 were based on the first imputed data set. We generated Table 4 with valid statistical inferences of the parameters on the basis of 20 data sets. Sensitivity analysis was performed to test the difference of multiple imputed data sets and the original data sets. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). A 2‐tailed P value <0.05 was considered statistically significant. A butterfly plot for categorical LE8 scores by sex was visualized using Microsoft Office 365 Excel (Microsoft Corp., Redmond, WA).
Table 1.
Baseline and Follow‐Up Characteristics of Chinese Children Aged 6 to 10 years in PROC
| Characteristics | Baseline (n=1914) | Follow‐up (n=1789) |
|---|---|---|
| Boys, N (%) | 956 (50.0) | 890 (49.7) |
| Age, y, mean (SD) | 6.6 (0.3) | 8.5 (0.3) |
| Height, cm, mean (SD) | 122.5 (5.4) | 135.1 (6.1) |
| Weight, kg, mean (SD) | 24.8 (5.9) | 33.3 (9.2) |
| Body mass index, kg/m2, mean (SD) | 16.4 (2.9) | 18.0 (3.8) |
| Systolic blood pressure, mm Hg, mean (SD) | 101 (11) | 108 (9) |
| Diastolic blood pressure, mm Hg, mean (SD) | 55 (10) | 61 (7) |
| Diet (KIDMED scores), median (quartile 1–quartile 3) | 7 (5–8) | ‐ |
| Physical activity time, min/wk, median (quartile 1–quartile 3) | 180 (30–350) | ‐ |
| Nicotine exposure, N (%) | 1070 (55.9) | ‐ |
| Sleep duration, h/d, median (quartile 1–quartile 3) | 9.3 (9.0–9.9) | ‐ |
| Total cholesterol, mg/dL, median (quartile 1–quartile 3) | 176 (157–193) | ‐ |
| HDL cholesterol, mg/dL, median (quartile 1–quartile 3) | 62 (55–70) | ‐ |
| Non‐HDL cholesterol, mg/dL, median (quartile 1–quartile 3) | 112 (96–128) | ‐ |
| Fasting blood glucose, mg/dL, median (quartile 1–quartile 3) | 92 (87–96) | ‐ |
| LVM, g, mean (SD) | 59.3 (13.8) | ‐ |
| LVM index, LVM/ht2.7, mean (SD) | 34.1 (6.6) | ‐ |
| Carotid intima‐media thickness, mm, mean (SD) | 0.36 (0.03) | ‐ |
“‐” indicates no repeated measurements; HDL, high‐density lipoprotein; KIDMED, the 16‐item Mediterranean Dietary Quality Index in children and adolescents; LVM, left ventricular mass; and PROC, the Beijing Child Growth and Health Cohort.
Table 2.
The Application of Life's Essential 8 Components Including Health Behaviors and Health Factors for Chinese Children Aged 6 to 10 Years in PROC
| CVH metric | Baseline | Follow‐up | ||
|---|---|---|---|---|
| No. | Proportions (SE) | No. | Proportions (SE) | |
| CVH group | ||||
| High CVH | 683 | 35.7 (1.1) | 573 | 32.0 (1.1) |
| Moderate CVH | 1216 | 63.5 (1.1) | 1194 | 66.7 (1.1) |
| Low CVH | 15 | 0.8 (0.2) | 22 | 1.2 (0.2) |
| Health behaviors | ||||
| Diet score | ||||
| 0 | 70 | 3.7 (0.4) | 64 | 3.6 (0.4) |
| 25 | 533 | 27.8 (1.0) | 496 | 27.7 (1.0) |
| 50 | 887 | 46.3 (1.1) | 835 | 46.7 (1.1) |
| 80 | 327 | 17.1 (0.9) | 302 | 16.9 (0.9) |
| 100 | 97 | 5.1 (0.5) | 92 | 5.1 (0.5) |
| Physical activity score | ||||
| 0 | 385 | 20.1 (0.9) | 361 | 20.2 (0.9) |
| 20 | 316 | 16.5 (0.8) | 295 | 16.5 (0.8) |
| 40 | 396 | 20.7 (0.9) | 369 | 20.6 (0.9) |
| 60 | 202 | 10.6 (0.7) | 183 | 10.2 (0.7) |
| 80 | 152 | 7.9 (0.6) | 145 | 8.1 (0.6) |
| 90 | 107 | 5.6 (0.5) | 102 | 5.7 (0.5) |
| 100 | 356 | 18.6 (0.9) | 334 | 18.7 (0.9) |
| Tobacco/nicotine exposure score | ||||
| 80 | 1070 | 55.9 (1.1) | 997 | 55.7 (1.1) |
| 100 | 844 | 44.1 (1.1) | 792 | 44.3 (1.1) |
| Sleep health score | ||||
| 0 | 1 | 0.1 (0.1) | 1 | 0.1 (0.1) |
| 20 | 9 | 0.5 (0.2) | 9 | 0.5 (0.2) |
| 40 | 138 | 7.2 (0.6) | 127 | 7.1 (0.6) |
| 70 | 325 | 17.0 (0.9) | 308 | 17.2 (0.9) |
| 90 | 9 | 0.5 (0.2) | 9 | 0.5 (0.2) |
| 100 | 1432 | 74.8 (1.0) | 1335 | 74.6 (1.0) |
| Health factors | ||||
| Body mass index score | ||||
| 0 | 12 | 0.6 (0.2) | 16 | 0.9 (0.2) |
| 15 | 68 | 3.6 (0.4) | 91 | 5.1 (0.5) |
| 30 | 234 | 12.2 (0.7) | 298 | 16.7 (0.9) |
| 75 | 198 | 10.3 (0.7) | 278 | 15.5 (0.8) |
| 100 | 1402 | 73.2 (1.0) | 1106 | 61.8 (1.1) |
| Blood lipids (non‐HDL cholesterol) score | ||||
| 0 | 25 | 1.3 (0.3) | 24 | 1.3 (0.3) |
| 20 | 200 | 10.4 (0.7) | 181 | 10.1 (0.7) |
| 40 | 497 | 26.0 (1.0) | 464 | 25.9 (1.0) |
| 60 | 605 | 31.6 (1.1) | 564 | 31.5 (1.1) |
| 100 | 587 | 30.7 (1.1) | 556 | 31.1 (1.1) |
| Blood glucose score | ||||
| 60 | 246 | 12.9 (0.8) | 231 | 12.9 (0.8) |
| 100 | 1668 | 87.1 (0.8) | 1558 | 87.1 (0.8) |
| Blood pressure score | ||||
| 0 | 8 | 0.4 (0.1) | ‐ | ‐ |
| 25 | 51 | 2.7 (0.4) | 53 | 3.0 (0.4) |
| 50 | 309 | 16.1 (0.8) | 388 | 21.7 (0.9) |
| 75 | 175 | 9.1 (0.7) | 269 | 15.0 (0.8) |
| 100 | 1371 | 71.6 (1.0) | 1079 | 60.3 (1.1) |
“‐” indicates null or no value; CVH, cardiovascular health; HDL, high‐density lipoprotein; and PROC, the Beijing Child Growth and Health Cohort.
Table 3.
Difference in Cardiovascular Structures by the Life's Essential 8 CVH group for Chinese Children Aged 6 to 10 years in PROC
| Wave | CVH group | Baseline cardiovascular measurement, mean (SD) | ||
|---|---|---|---|---|
| LVM* | LVMI* | cIMT* | ||
| Baseline (n=1914) | High CVH | 56.8 (12.1) | 33.2 (6.4) | 0.35 (0.02) |
| Moderate CVH | 60.6 (14.4) | 34.6 (6.7) | 0.36 (0.03) | |
| Low CVH | 67.9 (14.1) | 37.1 (6.9) | 0.37 (0.03) | |
| P value | <0.001 | <0.001 | <0.001 | |
| Follow‐up (n=1789) | High CVH | 56.1 (12.0) | 32.9 (6.3) | 0.35 (0.02) |
| Moderate CVH | 60.7 (14.2) | 34.6 (6.6) | 0.36 (0.03) | |
| Low CVH | 70.6 (13.9) | 38.9 (7.1) | 0.37 (0.02) | |
| P value | <0.001 | <0.001 | <0.001 | |
cIMT indicates carotid intima‐media thickness; CVH, cardiovascular health; LVM, left ventricular mass; LVMI, left ventricular mass index; and PROC, the Beijing Child Growth and Health Cohort.
Cardiovascular measurement only at baseline.
Figure . Cardiovascular health (CVH) total scores and all 8 Life's Essential 8 (LE8) component metric scores by sex at baseline for Chinese children aged 6 to 10 years in PROC (the Beijing Child Growth and Health Cohort).
Table 4.
Associations of the Life's Essential 8 and Cardiovascular Structures in Chinese Children Aged 6 to 10 years in PROC
| Model | Baseline CVH group (n=1914) | Baseline cardiovascular measurement | |||||
|---|---|---|---|---|---|---|---|
| LVM* | LVMI* | cIMT* | |||||
| β (95% CI) | P | β (95% CI) | P | β (95% CI) | P | ||
| Crude model | High CVH | Ref. | Ref. | Ref. | |||
| Moderate CVH | 4.0 (2.6, 5.3) | <0.001 | 1.4 (0.8, 2.1) | <0.001 | 0.005 (0.002, 0.007) | <0.001 | |
| Low CVH | 13.6 (4.9, 22.4) | 0.003 | 5.0 (0.8, 9.1) | 0.020 | 0.017 (0.002, 0.031) | 0.023 | |
| Adjusted model | High CVH | Ref. | Ref. | Ref. | |||
| Moderate CVH | 3.7 (2.4, 5.0) | <0.001 | 1.3 (0.7, 1.9) | <0.001 | 0.005 (0.002, 0.007) | <0.001 | |
| Low CVH | 11.8 (3.5, 20.0) | 0.005 | 4.4 (0.5, 8.3) | 0.027 | 0.016 (0.002, 0.030) | 0.028 | |
Crude model: no adjustment; adjusted model: adjusting for age and sex. β values stand for differences in absolute values compared with the high CVH group. cIMT indicates carotid intima‐media thickness; CVH, cardiovascular health; LVM, left ventricular mass; LVMI, left ventricular mass index; and PROC, the Beijing Child Growth and Health Cohort.
Cardiovascular measurement only at baseline.
Results
We included 1914 children with a mean age of 6.6 years, about half girls and half boys (956) at baseline, and 1789 participants in the 2020 follow‐up of BMI and BP. LE8 characteristics of the participants are shown in Table 1. Mean childhood cardiovascular indicators at baseline were 59.3 g for LVM, 34.1 g/m2.7 for LVMI and 0.36 mm for cIMT, respectively. Height, weight, BMI, and systolic and diastolic BP increased with age.
Table 2 demonstrated the distribution of scores for each LE8 measure and the CVH groups for participants at baseline and follow‐up. Most children exhibited moderate CVH (63.5%). The proportions of moderate CVH and lower CVH were increased in both sexes due to lower BMI and BP optimal scores at follow‐up. Among the 4 health behavior metrics, children performed the best in sleep health with the highest percentage of maximal scores (score=100, 74.8% of overall). The proportion of children receiving perfect (ie, good) scores for nicotine exposure was 44.1%, physical activity 18.6%, and diet 5.1%. Virtually no moderate/vigorous physical activity per week was noted among 20.1% of children. More than half (55.9%) of children were exposed to regular smokers at home. Details of dietary component goal measures are shown in Table S2. Of the 4 health factor metrics in baseline, blood lipids had the lowest (ie, not good) in the percentage of maximal scores (30.7%). More than one‐quarter (26.8%) of children were overweight or obese. For FBG, 12.9% of children scored 60 rather than 100, and 28.4% had elevated BP or were prehypertensive. The BMI and BP at follow‐up showed that the proportion of children who were overweight/obese (Z=6.4, trend P<0.001) and who had elevated BP (Z=5.5, trend P<0.001) continued to increase.
Figure 1 shows the total CVH and all 8 component metric scores at baseline and follow‐up by sex. At baseline, girls had higher total CVH scores and scores of 4 components, excluding blood lipids, physical activity, diet, and sleep health, than boys. At follow‐up, girls had higher total CVH, BMI, BP, blood glucose, and nicotine exposure scores than boys. Physical activity, diet, and blood lipids were the 3 lowest‐scoring indicators in the LE8 for both boys and girls.
Table 3 presents the baseline size of cardiovascular structures in the baseline or follow‐up LE8 CVH group. The LVM, LVMI, and cIMT were significantly lower in children with high (56.8 g, 33.2 g/m2.7, 0.35 mm) or moderate CVH score (60.6 g, 34.6 g/m2.7, 0.36 mm), compared with low CVH score (67.9 g, 37.1 g/m2.7, 0.37 mm) at baseline (P<0.001). The results on the follow‐up LE8 CVH group were consistent, and the LVM, LVMI, and cIMT at baseline were significantly lower in children with high or moderate CVH scores, compared with low CVH scores (P<0.001).
Table 4 presents the association between CVH subgroups and cardiovascular subclinical outcome indicators at baseline. In the crude model, the values of LVM (β=13.6 [95% CI, 4.9–22.4]), LVMI (β=5.0 [95% CI, 0.8–9.1]), and cIMT (β=0.017 [95% CI, 0.002–0.031]) were higher in the low‐CVH group, and LVM (β=4.0 [95% CI, 2.6–5.3]), LVMI (β=1.4 [95% CI, 0.8–2.1]), and cIMT (β=0.005 [95% CI, 0.002–0.007]) were higher in moderate‐CVH group, taking the high‐CVH group as the reference (P<0.05). After adjusting for age and sex, the value of LVM (β=11.8 [95% CI, 3.5–20.0]), LVMI (β=4.4 [95% CI, 0.5–8.3]), and cIMT (β=0.016 [95% CI, 0.002–0.030]) in the low‐CVH group, and LVM (β=3.7 [95% CI, 2.4–5.0]), LVMI (β=1.3 [95% CI, 0.7–1.9]), and cIMT (β=0.005 [95% CI, 0.002–0.007]) in the moderate‐CVH group were higher than the high‐CVH group.
Discussion
This study validates the AHA's new Life's Essential 8 metrics and scoring algorithm for its clinical relevance and potential for primordial intervention in healthy children using cardiovascular structure and function indicators as outcomes in the Chinese context. To assess the cardiovascular health status of urban children aged 6 to 10 years in a China cohort (PROC) study, our study examines the LE8 index against cardiovascular structure and function measurements using echocardiography. Hence, we verified the clinical relevance of LE8 as a robust measure of children's CVH. We found that most Chinese children belong to the moderate‐CVH group, with physical activity and blood lipid scores being the lowest health behavior and health factor, respectively. CVH group predicted the size of LVM, LVMI, and cIMT cardiovascular structures. High CVH as assessed by LE8 was a protective factor for abnormal pediatric cardiovascular structures and functions.
Exposure to cardiovascular risk factors may directly affect the cardiovascular structure of children and may further cause permanent adverse effects in adulthood. 16 , 17 , 18 The Bogalusa Heart Study found that left ventricular hypertrophy in adulthood, an increase in LVM, is a vigorous predictor of cardiovascular disease and is regarded as a subclinical surrogate cardiovascular end point. 19 Increased cIMT is a well‐established marker for future blood vessel stiffness and is also used frequently in young population cohorts to predict future risk. 20 , 21 , 22 Our study found that after adjusting for age and sex, high CVH is associated with optimal LVM, LVMI, and cIMT structures. The AHA CVH definition emphasizes the prevention of adverse health behaviors and factors (ie, primordial prevention) early in life rather than addressing or modifying risk factors later in adulthood (ie, primary prevention). 6
A heart‐healthy lifestyle, beginning at an early age and sustained throughout life, would lower the risks of cardiovascular disease in adulthood. 23 In our study, favorable physical activity was the least prevalent among LE8 health metrics. Physical inactivity in children, along with diet, has been shown to contribute to obesity and cardiovascular‐related risks. However, only 18.6% of children achieved a recommended level of physical activity (≥420 minutes of exercise per week) in this study, with boys being slightly more physically active than girls. In a 2017 national survey study, 38.5% of elementary school students in China were reported to have the recommended 60 minutes of moderate or vigorous daily activity. 24 Survey differences may be due to the different measurement instruments used and to different age ranges of study populations. Our participants of the cohort had a high obesity prevalence, as reported previously. 25
Lower diet scores in our study were similar to children in the United States. 26 In recent decades, China has undergone rapid urbanization and subsequently a major nutrition transition. 27 Our study found that Chinese children's diets lack sufficient intake of vegetables, fruits, fish, and seafood and inadequate intake of dairy products. 8 Due to China's special dietary patterns, most families use rapeseed oil or peanut oil or a mixture of edible oils. Even though increased fish and seafood intake can reduce cardiometabolic risk factors, 28 the intake of pork (73.9%) far exceeds the intake of fish and seafood in Chinese households. 29 Another factor consistent with China National Nutrition and Health Surveillance data is the relatively low but increasing dairy consumption in both frequency and quantity among Chinese children and adolescents aged 6 to 17, which might be related to improved milk accessibility (such as China's School Milk Program). 30 Furthermore, the low intake of dairy products is associated with another fact, namely, the huge prevalence of lactose intolerance in China (estimated at 85% of Chinese adults 31 ), which may start in childhood. The results from a cross‐sectional study conducted in 4 cites of China, including Beijing, showed that the incidences of lactase deficiency of children of 3 to 5, 7 to 8, and 11 to 13 years old were 38.5%, 87.6%, and 87.8%, respectively. The incidences of lactose intolerance were 12.3%, 33.2%, and 30.5%, respectively. 32
Nicotine and carcinogen exposures in children are noteworthy; 55.9% of Chinese children were exposed to secondhand smoke, highlighting an opportunity for primordial prevention via smoke exposure reduction education through application of LE8 score assessments. Our previous study shows that smoke exposure can adversely affect cardiovascular structure and function even at the young age of 6 to 8 years, 10 and increase cancer risks. Although the sleep health of most children in our study was ideal, one‐quarter had insufficient or excessive sleep. According to the China National Nutrition and Health Surveillance Report (2010–2013), the average daily sleep duration was 8.9 hours for children aged 6 to 12 years and 7.9 hours for children aged 13 to 17 years, and the duration had decreased by 0.2 and 0.6 hours, respectively, compared with 2002. 33 The Healthy China Initiative (2019–2030) recommends that primary school students should get at least 10 hours of sleep per day. 34
Lifestyle changes have led to declines in many health factors. In our study, lipid (non‐HDL cholesterol) score (30.7%) was the least optimized health factor. The new LE8 uses non‐HDL cholesterol instead of total cholesterol as an index for judging blood lipids because non‐HDL cholesterol can be measured in the nonfasting state. 6 Non‐HDL cholesterol has been demonstrated to be an important cardiovascular disease predictor, 35 and many countries use non‐HDL cholesterol as a second target after low‐density lipoprotein cholesterol. 36 , 37 Childhood obesity contributes a disproportionate burden toward the development of multiple cardiometabolic risk factors in children and adults. 38 , 39 Although the prevalence of overweight and obesity (26.8% for overall) were lower compared with US youths, 40 it is worrisome that the childhood obesity rate has risen dramatically over the past 2 decades in China, and will likely continue to increase. 41 China has seen an increase in the prevalence of prehypertension from 5.7% to 12.7% and hypertension from 4.5% to 18.2% in children aged 7 to 12 years from 1991 to 2015, 42 similar to our findings. However, lack of targeted interventions was included in national programs to combat the BP rise to hypertensive levels in children. Furthermore, >12.9% of children had abnormal fasting glucose in our study, further underscoring the need for early intervention in children. Our study is of critical importance to endorse the use of LE8 in promoting cardiovascular health in terms of fostering healthy lifestyle and facilitating primordial prevention among children.
Strengths of our study include its timeliness, validating the new LE8 CVH metrics in Chinese children. BMI, blood glucose, lipids, and BP in our study were based on actual measurements rather than self‐report. Moreover, we provide direct measurement of cardiovascular structure and function of the children. A follow‐up survey of BMI and BP was used to validate findings longitudinally. Our study also has limitations. First, our study is a single‐center urban cohort, reducing generalizability. Previous studies have shown that children from rural areas have a lower prevalence of overweight/obesity and elevated BP compared with urban children. 43 Second, there were some missing values of the extracted LE8 and other indicators due to the missing visits of the sequential baseline surveys, requiring imputation modeling to reduce bias. Third, the health behaviors (diet, physical activity, nicotine exposure, sleep health) were reported mainly by their parents or the assistance with their parents. Such communication between parent and child may affect the accuracy of the data, potentially underestimating consumption of certain foods or nicotine exposures, as we have shown previously. 10 Given the ages of the children (6–8 years), our participants were not able to understand and complete all of the survey questions on their own, so parental assistance was necessary.
Conclusions
CVH scores were suboptimal and decreasing with age from an average of 6.6 years to 8.5 years. Since children with high CVH had optimal heart/vascular LE8 health status versus children with low CVH, our study suggests that the AHA LE8 is a valid and effective tool to assess CVH of Chinese children to inform primordial interventions to reduce cardiovascular disease later in life.
Sources of Funding
This research was funded by the Capital's Funds for Health Improvement and Research (Grant No. 2022‐1G‐4262), the National Natural Science Foundation of China (Grant No. 82073574), and the Beijing Natural Science Foundation (Grant No. 7202009) (all for Dr Hu). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclosures
None.
Supporting information
Tables S1–S2
Figure S1
Acknowledgments
The authors thank the parents and children in the PROC study for their contributions. Author contributions: Dr Hu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: W. Shu, M. Li, and Dr Hu. Acquisition, analysis, or interpretation of data: W. Shu, M. Li, H. Xiao, N. Amaerjiang, N. M. Khattab, J. Zunong, M. Guan, Dr Vermund, and Dr Hu. Drafting of the manuscript: W. Shu, M. Li, and Dr Hu. Critical revision of the manuscript for important intellectual content: all authors. Statistical analysis: W. Shu and M. Li. Obtained funding: Dr Hu. Supervision: Dr Hu.
This manuscript was sent to Tiffany M. Powell‐Wiley, MD, MPH, Associate Editor, for review by expert referees, editorial decision, and final disposition.
Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.122.029077
For Sources of Funding and Disclosures, see page 9.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Tables S1–S2
Figure S1