**6. Conclusions**

Body-size changes in infancy (0–2 y) and childhood (0–6 y) showed similar strength of association with respect to CV properties assessed at 6 y. Conversely, changes between 0–6, 6-18 or 0–18 y were not associated with CV parameters evaluated at 18 y.

The association between CV characteristics at 6 yand body-size changes during growth showed: (a) equal or greater strength than the observed for body-size at birth, and (b) lower strength with respect to that obtained when considering current z-BMI at 6 y. In 6 y children variables capable of explaining CV variations showed a "hierarchical order". Conversely, only z-BMI at 18 y showed significant associations with arterial z-scores at 18 y. Body size at birth showed almost no association with arterial characteristics at 6 or 18 y. The associations between ΔBWH z-score 0–2 y or Δz-BMI 0–6 y and CV properties at 6 y were mostly independent of body-size at birth. When current z-BMI was taken into account some associations between body changes in childhood and CV properties at 6 y were no longer significant. In adolescents, the associations between growth-related body changes and CV properties were dependent on z-BMI at the time of CVstudy.

Current z-BMI was the anthropometric parameter with the greatest capacity to explain the variations in CV properties at 6 y. However, interindividual variations in some hemodynamic and arterial parameters were mainly explained by growth-related anthropometric changes and/or by their interaction with current z-BMI. Similar findings were observed when the associations were analyzed taking into account the exposure to factors associated with CV risk. Current z-BMI at 18 y was the anthropometric variable with the greatest capacity to explain CV variations at 18 y. Body-size changes during childhood and/or adolescence contributed to explain arterial variations through the interaction with current z-BMI or BWH z-score at birth.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2308-3425/6/3/33/s1. Table S1. Clinical, anthropometric hemodynamic, structural and sti ffness parameters forchildren and adolescent reference subgroups; Table S2. Hemodynamic, structural and sti ffness parameters z-score, forchildren and adolescent Cohorts; Table S3. Multiple linear regression analysis between CVparameters z-scores (dependent variables) and anthropometric parameters (independent variables), children cohort (*n* = 632); Table S4. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters (independent variables), children cohort (*n* = 632); Table S5. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters (independent variables), children cohort (*n* = 632); Table S6. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters (independent variables), children cohort (*n* = 632); Table S7. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters (independent variables), adolescent cohort (*n* = 340); Table S8. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters (independent variables), adolescent cohort (*n* = 340); Table S9. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters (independent variables), adolescent cohort (*n* = 340); Table S10. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters (independent variables), adolescent cohort (*n* = 340); Table S11. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometricparameters (independent variables), adolescent cohort (*n* = 340); Table S12. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters (independent variables), adolescent cohort (*n* = 340); Table S13. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters and CVRFs (independent variables), children cohort (*n* = 632) (Enter Method); Table S14. Multiple linear regression analysis between CV parameters z-scores (dependent variables) and anthropometric parameters and CVRFs (independent variables), adolescent cohort (*n* = 340) (Enter Method)

**Author Contributions:** Conceptualization, D.B. and Y.Z.; Formal analysis, J.M.C., D.B. and Y.Z.; Funding acquisition, D.B. and Y.Z.; Investigation, D.B. and Y.Z.; Methodology, J.M.C., V.G.-E., A.Z., M.M., C.S., D.B. and Y.Z.; Project administration, D.B. and Y.Z.; Visualization, J.M.C., D.B. and Y.Z.; Writing–original draft, J.M.C., D.B. and Y.Z.; Writing–review and editing, J.M.C., V.G.-E., A.Z., M.M., C.S., P.C., D.B. and Y.Z.

**Funding:** This research was funded byAgencia Nacional de Investigación e Innovación (ANII), Ministry for Social Development (MIDES), United Nations Children's Fund (UNICEF), gran<sup>t</sup> number/code: FSPI\_X\_2015\_1\_108484, PRSCT-008-020; and extrabudgetary funds provided by CUiiDARTE.

**Acknowledgments:** We thank the children, adolescents and their families for their participation in the study. The authors thank the technical staff from CUiiDARTE and IECON (Lic. Cecilia Toledo and LucíaNuñez). ELBU Study (IECON; http://fcea.edu.uy/estudio-del-bienestar-multidimensional-en-uruguay.html) is directed by Martín Leites, Gonzalo Salas and Andrea Vigorito.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
