*2.1. Study Population*

The study was carried out in the context of the Centro Universitario de Investigación, Innovación y Diagnóstico Arterial (CUiiDARTE) Project [13–16]. The protocol was approved by the Institutional Ethics Committee. Both parents' consent and child's assent were received before data collection. Participants (or their guardians) signed a written consent prior to the evaluation. Subjects from two cohorts, one of children (*n* = 682) and the other of adolescents (*n* = 340) were included (Table 1). The children cohort, defined based on probabilistic, bi-stage and stratified sampling of subjects attending public kindergartens in Montevideo, is part (subsample) of the longitudinal study "Patrón de crecimiento, estadonutricional y calidad de la alimentaciónen la primerainfancia: análisis de suimpactosobre la estructura y función vascular y el riesgo cardiovascular relativoenniñosuruguayos (CUiiDARTE-Agencia Nacional de Investigación e Innovación(ANII), Ministerio de Desarrollo Social (MIDES), United Nations Children's Fund(UNICEF) that started in 2010 (first phase) and had in 2016 a second phase [15,16]. In turn, the adolescent cohort (subsample from Montevideo) belongs to a longitudinal (four stages) study called "Estudio Longitudinal del Bienestaren Uruguay" (ELBU) aimed at investigating multidimensional well-being [17] working with a national representative sample of children (and their families) attending in 2004 the first grade of primary public schools in urban areas, which account for 87% of the Uruguayan population.

Similar approaches were carried out on children and adolescents: clinical and anthropometric evaluation, compilation (questionnaires) of data about lifestyle and family history (e.g., educational level, socioeconomic conditions, nutritional factors) and non-invasive CV evaluation.

## *2.2. Anthropometric Evaluation*

Anthropometric data (BW and BH) corresponding to ages ≤36 months (mos.) were obtained from registers of the obligatory health-controlsfor children within those ages, established by the Ministry of Health (Children cohort). BW and length at birth in the adolescent cohort were obtained by documented self-report, during parents' interviews. In turn, following standard procedures, trained technicians obtained anthropometric data from children and adolescents (at participants' home, school and/or during the CV evaluation). BW and BH were measured with lightweight clothing and without shoes. Standing BH was measured (subject's head in the Frankfurt Plane position) using a portable stadiometer and recorded to the nearest 0.1 cm. BW was measured with an electronic scale (model 841/843, Seca Inc., Hamburg, Germany; model HBF-514C, Omron Inc., Chicago, Illinois, USA) and recorded to the nearest 0.1 kg. Two measurements were made and a third measurement was obtained in case the first two readings di ffered by more than 0.5 cm or 0.5 kg. After aggregating records from our technicians and those from health-controls, we obtained BW and BH data corresponding to: (1) birth, 6, 12, 18, 24, 36 and ~72 mos (~6 y) in the children cohort, and (2) birth, ~6 y, ~8 y, ~12 y and ~18 y in the adolescents' cohort. BMI was calculated as BW-to-squared BH ratio and converted into z-scores (z-BMI). Standardized z-scores for BMI and BWH (up to 2 y), BW-for-age, BH-for-age and BMI-for-age were obtained using World Health Organization software (Anthro-v.3.2.2; Anthro-Plus-v.1.0.4). The changes or di fferences ( Δ) in BWH z-score ( ΔBWH z-score) between birth (0 y) and 24 mos. (0–2y, children cohort) were determined. In turn, the changes in z-BMI (ΔBMI z-score) between 0 and 6 y (0–6y, both cohorts), 0 and 18 y (0–18y, adolescents cohort) and 6 and 18 y (6–18y, adolescents cohort) were calculated. Changes were always determined as the difference between the latest (e.g., 18 y) and the earliest (e.g., 0 y) z-score.

**Table 1.** Clinical, anthropometric and arterial parameters, of children and adolescent cohorts.



**Table 1.** *Cont*.

MV: mean value. STD: standard deviation. Min., Max.: minimum and maximum values. z: z-score. p25th, p75th: percentile 25 and 75. BW, BH: body weight and height. BMI: body mass index. CV: cardiovascular. pSBP, pDBP, pPP, pMBP: peripheral systolic, diastolic, pulse and mean pressure. CO, C.I.: cardiac output and index. cSBP, cPP: central systolic and pulse pressure. SVR: systemic vascular resistances. AIx, AIx@75: aortic augmentation index without and with heart rate adjustment. AP: augmented pressure. PF and PB: forward and backward aortic pressure component. R: Right. L: Left. CCA, CFA: common carotid and femoral artery. DD, SD: diastolic and systolic diameter. EM: elastic modulus. IMT: intima-media thickness. cfPWV: carotid-femoral pulse wave velocity.

#### *2.3. Clinical Evaluation*

None of the included subjects were taking medications, had congenital, chronic or infectious diseases at the moment of the CV study A brief clinical interview, together with the anthropometric evaluation enabled to assess CRFs exposure. Hypertension, dyslipidemia and diabetes were considered present if they had been previously diagnosed, in agreemen<sup>t</sup> with reference guidelines [18]. Subjects <16 y who had brachial systolic and/or diastolic pBP (pSBP and pDBP) >95th percentile for sex, age and BH during the study were considered with high BP levels (HBP); regardless previous diagnosis of hypertension. For subjects aged ≥16 y, HBP levels were defined using cuto ff values similar to those for adults (pSBP ≥ 140 mmHg, pDBP ≥ 90 mmHg) [18]. Smokingwas defined as at least one cigarette/week for as long as a month. A family history of CV disease (CVD) was defined by presence of first-degree relatives with premature (<55 y in males; <65 y in females) CVD.

#### *2.4. Cardiovascular Evaluation*

CV studies were performed in children and adolescents (6 and 18 y, respectively) at the educational centers and/or in CUiiDARTE non-invasive vascular laboratories. The same protocol was applied in both cohorts (Figure 1) and was performed by experienced technicians using the same equipment. In order to reach steady hemodynamic conditions, before starting CV evaluation the subjects hada 10 min rest in a supine position in a quiet, temperature-controlled room.

#### *2.5. Peripheral and Central Pressure and Aortic Wave-Derived Parameters*

Heart rate (HR), pSBP and pDBP were obtained at 5 min intervals (Hem-4030, OmronInc., Illinois, USA). Peripheral pulse pressure (pPP = pSBP − pDBP) and mean BP (MBP = pDBP + pPP/3) were calculated. To assess cBP and aortic wave-derived parameters, radial artery BP waveforms were recorded using applanation tonometry (SphygmoCor-CvMS, AtCor-Medical, Sidney Australia) (Figure 1). Pressure signals were calibrated topDBP and MBP. A generalized transfer-function (GTF) enabled us to obtain the correspondingcBP waves and central systolic, diastolic and pulse pressure levels (cSBP, cDBP, cPP) [15,19] (Figure 1). Only adequate waveforms (visual inspection) and high-quality recordings (operator index ≥85) were considered. By means of pulse wave analysis (PWA) the first (P1) and second (P2) peaks in cBP wave were identified and their height (amplitude) and time were

determined. Then, the di fference between P2 and P1 was computed as central augmented pressure (AP) and used to quantify central aortic augmentation index (Aix = AP/cPP). Since AIx depends on HR, AIx adjusted to a 75 beats/minHR (AIx@75) was calculated. Forward and backward (Pf and Pb) components of the aortic pulse wave were also quantified (Figure 1). AIx is a measure of the contribution of reflections to cBP wave amplitude. It depends on the timing and magnitude of the reflected (backward) wave and is influenced by the compliance and structure of vessels distal to the site of measurement, as well as by the distance to the reflection sites. Greater Pb and/or AIx values indicate increased reflections and/or earlier return of reflected waves due to increased arterial sti ffness and/or closer reflection sites. Systemic vascular resistance, cardiac output and index were quantified from brachial pulse contour analysis (Mobil-O-Graph, I.E.M.-GmbH, Stolberg, Germany) [15,19]. Only high quality records (index ≤2) and satisfactory waves (visual inspection) were considered. Subjects' values are the average of at least six consecutive records obtained in a single visit.

#### *2.6. Arterial Beat-to-Beat Diameter and Intima-Media Thickness (IMT)*

Left and right common carotid and femoral arteries (CCA, CFA) were analyzed using ultrasound (6–13 MHz, M-Turbo, SonoSite Inc., Bothell, WA, USA) and image sequences (30 s, B-Mode, longitudinal views) were stored for o ff-line analysis. Beat-to-beat diameter waves were obtained using border detection software. Systolic (SD) and end-diastolic (DD) diameters and IMT (far wall, end-diastolic) values were obtained averaging at least 20 beats (Figure 1). CCA diameter and IMT were measured one centimeter proximal to the bulb; CFA diameter and IMT were measured in the straight segmen<sup>t</sup> of the penultimate centimeter proximal to the arterial bifurcation (Figure 1) [13].

**Figure 1.** 1-A: Radial pulse wave obtained by applanation tonometry (SphygmoCor device); pSBP, pDBP, pPP: peripheral systolic, diastolic and pulse pressure. GTF: general transfer function. 1-B: Aortic wave derived using a GTF; augmented pressure (AP) and augmentation index (AIx) quantified from time-domain pulse wave analysis (PWA). cSBP, cDBP, cPP: central systolic, diastolic and pulsepressure. P1, P2: first and second pressure wave peaks. 1-C: Forward (Pf) and backward (Pb) components' amplitude obtained from wave separation analysis (WSA). 2-A, 2-B: Methodological approach used to assess common carotid (CCA) and femoral (CFA) artery diameter and intima-media thickness (IMT). Z: acoustic impedance. 2-C: Software for IMT and diameter measurement (Hemodyn-4M). 3-A, 3-B: Methodological approach used to assess carotid-femoral pulse wave velocity (cfPWV). Δx: CCA-to-CFA distance. Δt1, Δt2: time delay between R (ECG) and CCA and CFA foot wave. Δt3: time delay between arterial waves. 3-C: Software for cfPWV measurement (SphygmoCor device).

#### *2.7. Local and Regional Arterial Sti*ff*ness*

CCA and CFA pressure-strain elastic modulus (EM; local stiffness) were calculated as EM = PP/(SD − DD)/DD; cPP and pPP were considered to quantify CCA EM and CFA EM, respectively. Aortic regional stiffness was assessed by means of carotid-femoral pulse wave velocity (cfPWV) (SphygmoCor-CvMS) (Figure 1). The SphygmoCor allowed us to obtain cfPWV from sequential CCA and CFA wave recordings. cfPWV was calculated as the quotient between pulse wave travel distanceand pulse transit time. Real cfPWV was obtained multiplying measured cfPWV by 0.8. cfPWV values were obtained as the mean of three measurements.

#### *2.8. Data Analysis and Statistics*

A step-wise analysis was performed. First, CV variables were standardized and expressed as z-scores. To this end, subjects not exposed to CRFs (i.e., hypertension, HBP, dyslipidemia, smoking, diabetes, obesity or family history of CVD) were selected from each cohort (reference subgroups: 400 children, 153 adolescents) (Supplementary (S) Table S1). Working with the reference subgroups, mean value (MV) and standard deviation (STD) were determined for each variable (considering age and sex). Then, individual data were converted into z-scores (dimensionless numbers obtained

by subtracting the reference MV from an observation, dividing the result by the reference STD) (Table S2) [13].

Second, Pearson product-moment correlations were obtained to quantify the strength of association between CVz-scores and anthropometric variables: (1) at birth: BWH z-score (both cohorts); (2) at the time of the CVstudy: current z-BMI (6 y for children, 18 y for adolescents); (3) growth-related changes: (a) early: ΔBWHz-score 0–2y, (b) intermediate: ΔBMI z-score 0–6y, (c) late: ΔBMI z-score 6–18y and (d) global: ΔBMI z-score 0–18y (Tables 2 and 3).

Third, statistical comparisons of the correlations' strengths were done using two-tailed William's test, making statistical corrections for dependent (same cohort) and overlapping (correlations have a variable in common) variables (e.g., when comparing the correlations "ΔBMI z-score 0–6y and z-pSBP" and "current z-BMI and z-pSBP" in the children cohort) [20] (Tables 2 and 3). Comparisons between cohorts were made considering William's test for non-overlapping (no variables in common) and independent (different cohort) variables (e.g., when comparing the R obtained for ΔBMI z-score 0–6y and z-pSBP in children and adolescents) (Table 4).

Fourth, the association between CV z-scores and anthropometric changes during growth was analyzed after statistical adjustment (partial correlations) for: (a) BWH z-score at birth; (b) BWH z-score at birth and current z-BMI and (c) BWH z-score at birth and ΔBMI z-score 6-18y (Tables 5–8). Multiple linear regression models (MLR; input: enter and forward), enabled to analyze the association between standardized CV data (dependent variables) and (1) single, specific anthropometric changes (ΔBWH z-score 0–2y, Δz-BMI 0–6y, Δz-BMI 0–18y and Δz-BMI 6–18y); (2) BWH z-score at birth; (3) current z-BMI, and (4) the interactions between growth-related changes and birth size or current z-BMI (e.g., (Δz-BMI 0–6y\*BWH at birth) and (Δz-BMI 0–6y\*current z-BMI)). In other words, since an association between postnatal growth and CV properties might be modified by birth or current body size, interaction between these conditions and growth-related body size changes on CV characteristics was tested adding two product terms (as continuous variables) to the model [21] (Tables S3–S12).

Fifth, using MLR models (input: enter and forward) we analyzed the association between standardized CV variables at 6 and 18 y and anthropometric variables and CRFs (independent variables) (Tables 8 and 9, Tables S13 and 14). A variance inflation factor (VIF) <5 was selected to evaluate (discard) significant collinearity.

Analyses were done using MedCalc Statistical Software (v.18.5. MedCalc Inc., Ostend, Belgium); Cocor Statistical Package (http://comparingcorrelations.org/) and IBM-SPSS Software (v.20, IBM-SPSS Inc., Chicago, IL, USA). A *p* < 0.05 was considered statistically significant.
