LABORATORIO DE URGENCIAS

Childhood Cardiovascular Risk Factors and Adult Cardiovascular Events

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David R. Jacobs, Jr., Ph.D; Jessica G. Woo, Ph.D; Alan R. Sinaiko, M.D; Stephen R. Daniels, M.D., Ph.D;  Johanna Ikonen, M.S; Markus Juonala, M.D., Ph.D; Noora Kartiosuo, M.S; Terho Lehtimäki, M.D., Ph.D., Lydia A. Bazzano, M.D., Ph.D; et al.

                                                                                              N Engl J Med 2022; 386:1877-1888 / DOI: 10.1056/NEJMoa2109191

Prevention of cardiovascular disease remains a major public health issue, with well-documented associations between cardiovascular risk factors in adulthood and cardiovascular events.¹ Despite the interest in childhood risk factors and subsequent adult cardiovascular disease, as recently reviewed,^2,3 findings from longitudinal studies that begin with the evaluation of childhood risk factors have generally been restricted to associations with subclinical disease in adulthood.
The possibility of extending the findings to include associations with adult cardiovascular events has been hampered by a lack of cohorts with available comprehensive childhood data on anthropometric measures, blood pressure, and laboratory values and with follow-up conducted up to ages at which cardiovascular events become prevalent.
The International Childhood Cardiovascular Cohort (i3C) Consortium^4,5 includes seven cohorts in Australia, Finland, and the United States, in which data on cardiovascular risk factors from early childhood through adolescence have been collected and adult cardiovascular events have been adjudicated. In the current study, we used these data to examine the development of cardiovascular disease over the life course and test our hypothesis that traditional cardiovascular risk factors in childhood are associated with the subsequent development of adult cardiovascular events.

METHODS

STUDY DESIGN AND OVERSIGHT
A total of 42,324 participants 3 to 19 years of age were enrolled in the seven i3C Consortium cohorts from the 1970s through the 1990s; of these participants, 40,648 had identifying information for follow-up and were included in the sampling frame.
This study was approved by the institutional review board at each site of the seven cohorts. Written parental permission and oral assent by the participant were obtained for childhood visits, written informed consent was obtained from the participant for in-person adult visits, and oral consent under waiver of documentation of consent was obtained for the recent follow-up questionnaire
Our study focused on the five risk factors most often evaluated in childhood and adolescence: the body-mass index, systolic blood pressure, total cholesterol level, triglyceride level, and youth smoking. Triglyceride levels were transformed by means of the natural logarithm (ln[triglycerides]). Data on the cardiovascular risk factors were harmonized across the seven cohorts into a single database (114,476 visits, with 1 to 19 visits per participant). Because independent protocols, with variable schedules for clinic visits that were conducted at various participant ages, were used for each cohort, not every study measure was assessed in every cohort, in every participant within a cohort, or in every participant at every age.⁵ Age, sex, parent-reported race (which was updated if the participant was seen in adulthood), height, weight, and systolic blood pressure (measured by mercury sphygmomanometry) were assessed prospectively at the clinic visits; fasting levels of plasma or serum cholesterol and triglycerides were measured by means of standard methods.⁶ The education levels of the parents and participants were obtained at childhood and adult visits.
From 2015 through 2019, the i3C Consortium investigators conducted a coordinated study to locate and survey participants and search national death indexes for the participants who were not located (Figs. S1 and S2).⁵ 
Fatal cardiovascular events in all the cohorts were classified according to the coded causes of death in the International Classification of Diseases (ICD), versions 9 and 10  Finnish participants were followed for nonfatal cardiovascular events through December 31, 2017, with the use of the Finnish national medical registry, and the events were classified according to the same version of the ICD that was used for the classification of deaths. U.S. and Australian adult participants who had been successfully located reported any cardiovascular event that had occurred, and medical records were requested for adjudication of the participant reports.
The medical records were reviewed by a physician committee that was unaware of the study data from the participants, and each reported event was classified as a confirmed cardiovascular event, not a cardiovascular event, or not possible to adjudicate. Nonfatal cardiovascular events included the first instance of adjudicated myocardial infarction, stroke, transient ischemic attack, ischemic heart failure, angina, peripheral artery disease, carotid intervention, abdominal aortic aneurysm, or coronary revascularization.

STATISTICAL ANALYSIS
Because of the potential for bias due to loss to follow-up, fatal cardiovascular events were analyzed separately from the composite outcome of fatal or nonfatal cardiovascular events. There were 319 fatal cardiovascular events among the 38,589 participants (95% of the sampling frame) who could be classified as alive and located, deceased with known cause, or searched for and not found in the death indexes and thus presumed to be alive. The analysis of fatal or nonfatal cardiovascular events included 779 adjudicated nonfatal events and 784 imputed nonfatal events (the mean number across imputations) for persons who were not located or who reported a cardiovascular event that was not possible to be adjudicated. Among 13,401 participants with adult measurements before any cardiovascular event, there were 115 fatal cardiovascular events and a mean of 524 fatal or nonfatal events (406 observed) across imputations.
Because of age-related developmental changes, childhood risk factors at each visit were normalized to z scores within the i3C Consortium, which were calculated with the mean values (with standard deviations) of the study variables, stratified according to age and sex. The resulting i3C-derived z scores for each participant were then averaged across their childhood and adolescent measurements (obtained at the ages of 3 to 19 years) to obtain a single mean z score of childhood risk per person. The classification of youth smoking was based on reports by the participants during childhood,⁷ augmented by adult recall of the smoking initiation date, and was analyzed as a dichotomous variable (yes vs. no). An a priori combined-risk z score was calculated as the unweighted mean of the z scores of the four childhood risk factors plus youth smoking, which was included in the calculation as either 2 (a high-risk value in terms of z score units) for smoking or 0 (average risk) for nonsmoking. The use of this combined-risk z score addresses our hypothesis that all five risk factors predict future events, without the estimation of risk-factor weights. Individual risk factors and the combined-risk z score were analyzed as continuous measures. In addition, we examined childhood risk factors using thresholds for standard clinical categories,^8-10 dividing the clinically normal category into low-normal and high-normal groups. Adult combined-risk z scores were calculated with the same algebraic procedures and risk factors as those used for the childhood combined-risk z scores.
All primary analyses were performed after multiple imputation of missing values by means of chained equations with fully conditional specification (10 replications) in PC-SAS software (version 9.4, SAS Institute); data were assumed to be missing at random.¹¹ Imputation was conducted in three phases with the use of subsampling methods.¹² 
In phase 1, multiple imputation was applied for missing data on childhood risk factors and events among 38,589 participants; in phase 2, for nonfatal events that could not be adjudicated among 1360 participants who reported a nonfatal event; and in phase 3, for missing ages at which the imputed event occurred among 779 adjudicated events and a mean of 784 imputed events. All proportional-hazards regression analyses were conducted with the use of adult age as the time axis and noncardiovascular mortality as a competing risk¹³ and were adjusted for sex, race, cohort indicator, mean childhood age at and mean calendar year of childhood measurement, and parental education level. The widths of the 95% confidence intervals were not adjusted for multiple comparisons.
Adequacy of the linearity assumption was visualized with the use of restricted cubic splines and by examining categories of z score units in widths of 0.5 with extreme higher and lower categories open-ended. The proportionality assumption was assessed with the addition of the interaction term between the risk factor and age transformed by the natural logarithm (risk factor*ln[age]). When hazards varied according to participant age during follow-up, we present hazard ratios for events in participants younger than the median age of 47.7 years or 47.7 years of age or older. Interactions with sex, race, and age group of childhood measurement (3 to 11 years vs. 12 to 19 years) were estimated. We examined the predictive power of the childhood combined-risk z score, accounting for adult risk factors using three analytic models, one in which the adult combined-risk z score was considered alone, one in which the childhood combined-risk z score was paired with the adult combined-risk z score, and one in which the childhood combined-risk z score was paired with the change in combined-risk z score between childhood and adulthood.

RESULTS

PARTICIPANTS
A total of 38,589 participants were included in the overall sample; 19,168 (49.7%) were male, 5792 (15.0%) were Black, and the mean (±SD) age at which the participant was seen during childhood was 11.8±3.1 years. The mean age of the participants at the time of their cardiovascular event was 47.0±8.0 years. Participants with cardiovascular events were older, more likely to be male, and had a lower parental and personal education level than those without cardiovascular events. Correlations among childhood risk factors ranged from −0.002 to 0.35, and within-person correlations among childhood, adolescence, and adulthood ranged from 0.40 to 0.84. The mean combined-risk z score was 0.16±0.49

ADULT CARDIOVASCULAR EVENTS
Hazard ratios for a fatal cardiovascular event in adulthood with respect to the risk-factor z scores ranged from 1.30 (95% confidence interval [CI], 1.14 to 1.47) per unit increase in the z score for the total cholesterol level to 1.61 (95% CI, 1.21 to 2.13) for youth smoking (yes vs. no). The hazard ratio for a fatal cardiovascular event in adulthood with respect to the combined-risk z score was 2.71 (95% CI, 2.23 to 3.29) per unit increase, and the hazard ratio for a fatal or nonfatal cardiovascular event in adulthood was 2.75 (95% CI, 2.48 to 3.06) per unit increase.
The hazard ratio with respect to the combined-risk z score showed some attenuation for fatal or nonfatal events at older adult ages. None of the interaction terms of childhood age group (3 to 11 years vs. 12 to 19 years), race, or sex were notable. The childhood risk score was also positively associated with total mortality.
The study measures in adulthood were evaluated in the participants at a mean age of 31.0±5.6 years. In the analyses involving participants who had data on the study measures in both childhood and adulthood, the adult combined-risk z score was associated with adult cardiovascular events, both alone and when paired with the childhood combined-risk z score. The childhood combined-risk z score, when paired with the adult combined-risk z score, was attenuated and remained independently associated only with fatal or nonfatal cardiovascular events. In the analysis including the childhood combined-risk z score and the change in the combined-risk z score from childhood to adulthood, both predictors were associated with fatal cardiovascular events and fatal or nonfatal cardiovascular events, with the hazard ratio lower for the prediction of events at older adults ages than at younger adult ages. Between 30% and 50% of the participants in each quartile of childhood combined-risk z score remained in the same quartile of combined-risk z score in adulthood.

RIS-FACTOR CATEGORIES AND THRESHOLDS
With the use of “no” (for youth smoking), low-normal (for body-mass index and systolic blood pressure) and low-acceptable (for triglyceride level and total cholesterol level) as references in the standard clinical categories currently used for the risk factors, the gradient of the hazard ratio for cardiovascular events, whether fatal only or fatal or nonfatal, was apparent across the clinical categories for each risk factor.
There was a higher risk observed not only among the participants in the highest category of the risk-factor level but also — in the analysis of fatal or nonfatal events — among those in the high-normal or high-acceptable categories for the body-mass index, systolic blood pressure, and triglyceride level. The gradient of risk across the categories of the combined-risk z score was steeper than the gradient of risk across the categories of any of the individual risk factors; among the participants with a combined-risk z score of 0 or greater (23,103 of 38,589 [59.9%]), the risk of adult cardiovascular events was 2 to 9 times as high as the risk among those in the lowest z score category (a z score of less than −0.5), with the risk increasing with age in the life-table analysis. Several sensitivity analyses were conducted to evaluate the effect of loss to follow-up, the reasonableness of the imputation results, and the differences among the cohorts, which did not materially change the findings.

DISCUSSION

The current study, with its large sample and use of prospective data on five traditional cardiovascular risk factors (body-mass index, total cholesterol level, triglyceride level, systolic blood pressure, and youth smoking) from childhood to adulthood, showed comprehensive associations between the levels of these childhood risk factors, individually and in combination, and the development of incident adult cardiovascular events beginning as early as 40 years of age. Cardiovascular events in children are rare,¹⁴ but autopsies have shown pervasive histologic atherosclerotic lesions of the aorta and coronary arteries in young persons that were associated with dyslipidemia, elevated blood pressure and smoking ¹⁵ 
Data from the Coronary Artery Risk Development in Young Adults (CARDIA) study have shown a relation between the Framingham risk score and cardiovascular events among young adults followed for 20 years,¹⁷ but studies linking childhood risk factors to adult events have been lacking.
Traditional cardiovascular risk factors have been evaluated in childhood because of their presumed association with the occurrence of adult cardiovascular events.² Each risk factor was related to adult cardiovascular events in our study, and the combination of the risk factors into a mean risk score, similar in concept to the Framingham score, resulted in a stronger association than any single risk factor; among 38,589 participants, the 59.9% who had a combined-risk z score of 0 or greater, corresponding to the risk-factor level of an average child, were at increased risk for cardiovascular events, as compared with those who were in the lowest z score category (a z score of less than −0.5). Risk factors during childhood (3 to 11 years of age) and adolescence (12 to 19 years of age) were similarly related to adult cardiovascular events, as were risk factors according to sex and racial groups. Hazard ratios for fatal or nonfatal events with respect to the childhood combined-risk z score decreased as adult age increased.
We evaluated cardiovascular events in relation to the standard clinical categories currently used for childhood risk factors and found that children in the highest category of risk (e.g., overweight or obese body-mass index and prehypertensive or hypertensive blood-pressure levels) had a markedly higher risk of adult cardiovascular events, as expected. However, most children who were at excess risk for the development of adult cardiovascular events were in the middle to lower categories of the combined-risk z score. Previous longitudinal studies involving the i3C Consortium also showed an association of the midrange of childhood risk-factor levels with the development of adult hypertension⁶ and adult diabetes.¹⁸
Because of the rarity of cardiovascular disease in childhood, there continue to be questions about the merits of evaluating cardiovascular risk factors in childhood as opposed to adulthood, when subclinical and clinical disease are prevalent.¹⁹ In the model including both childhood and adult combined-risk z scores, the adult combined-risk z score was a strong predictor of adult events, and the childhood combined-risk z score was seemingly attenuated. Such attenuation suggests that childhood risk factors predicted adult events principally because they tracked to adult values. However, a complementary analysis²⁰ showed that both the childhood combined-risk z score and the change in combined-risk z score between childhood and adulthood were important in predicting the risk of adult events. From the perspective of prevention, both childhood risk-factor levels and the path to risk in adulthood appear to be informative. Thus, we posit that assessment of cardiovascular risk should begin in childhood, and a reduction in risk-factor levels between childhood and adulthood may have the potential to lower the incidence of premature cardiovascular disease.
Our study raises important questions about broader childhood strategies for reducing the risk of premature cardiovascular disease. Rather than a sole focus on a medical approach of identifying children with elevated risk-factor levels, the current results would suggest that an equally relevant focus on public health strategies for maintaining ideal cardiovascular health in all children is warranted.²¹ Previous studies showed that persons with lifelong genetic exposure to low levels of low-density lipoprotein cholesterol and systolic blood pressure tend to have a lower risk of cardiovascular disease,²² and recently published results from the Special Turku Coronary Risk Factor Intervention Project (STRIP) study showed beneficial effects on risk factors over a period of 26 years after dietary counseling that began in infancy and continued throughout childhood.²³ Furthermore, comprehensive public health efforts in Finland over the past 40 years have led to positive lifestyle changes, a decline in major risk-factor levels, and dramatic reductions in cardiovascular-related mortality.^24,25 In acknowledgment of the difficulty of individual behavioral change, we think our findings suggest a need for stronger public health programs for children.
Strengths of our study include the large sample, the broad age range of childhood participants, adjudication of medical records, and a mean follow-up of children and adolescents of 35 years. The evidence that pooling the data from the separate cohorts was an appropriate strategy was that the risk of adult cardiovascular events before the age of 40 years was similarly low in all seven cohorts and that the adjusted hazard ratios with respect to each risk factor were similar across the four oldest cohorts.

Our study also has certain limitations. First, because 46.5% of the sample could not be located to ascertain nonfatal cardiovascular events, loss to follow-up presented a potential response bias. We addressed this issue through two analytic approaches. We determined vital status and cause of death in 95% of the original participants. By limiting the initial analysis to fatal cardiovascular events in that nearly complete sample, we found the expected relationships with the childhood risk factors. Next, we used multiple imputation to assess the association of childhood risk factors with adult fatal or nonfatal cardiovascular events in all participants. With respect to this end point, we relied heavily on the imputation model in the assessment of the findings. The primary function of the multiple imputation was to reinstate the data on all study variables in the analysis of the full sample distribution, as compared with analysis restricted to participants who were located or found to be dead. These two approaches yielded similar results; thus, bias resulting from loss to follow-up was unlikely to have affected our findings. Second, the generalizability of the current study was restricted by the limited number of participants from non-White groups, a factor that reflects the decades-old recruitment of the cohorts (Table S30). Black participants represented 15% of the analysis sample and 21% of the participants from the United States, which is a higher percentage than that in the U.S. population. However, the current study was not specifically powered to detect racial differences, did not include many Hispanic participants, and focused on the experience of high-income countries. Third, we would posit that our unweighted and straightforward combined-risk z score facilitates comparison of childhood and adult risk but may not improve risk prediction across the life course.
This prospective cohort study showed that the cardiovascular risk factors of body-mass index, systolic blood pressure, total cholesterol level, triglyceride level, and youth smoking, particularly in combination beginning in early childhood, were associated with adult cardiovascular events and death from cardiovascular causes before the age of 60 years.

NOTE: Details, bibliographical references, tables and graphs in the original work and the appendices. They can be consulted in the magazine mentioned at the beginning of this summary.