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In this study, the tracking of triglycerides (TG), high-density cholesterol (HDL-c), atherogenic coefficient (AC), waist circumference to height ratio (WC\/Height), mean arterial pressure (MAP), and homeostatic model assessment of insulin resistance (HOMA-IR) was examined in the INMA-Asturias cohort between 4 and 8\u00a0years of age. The analysis was conducted in 307 children who participated in the INMA-Asturias cohort (Spain) at 4 and at 8\u00a0years of age. Quantile regression models were used to evaluate tracking between measures at both ages, with each measure at 8\u00a0years as the dependent variable and the rank transformation of the same measure at 4\u00a0years as the independent variable. We found a positive association between HDL-c rank at 4\u00a0years and higher quantiles of the HDL-c distribution at 8\u00a0years, with an increase of 2.93\u00a0mg\/dL (95% CI: 1.98, 3.87) per decile in the 0.9 quantile. A positive association was also found for WC\/Height, with an increase of 0.008 (95% CI: 0.004, 0.012) per decile in the 0.9 quantile. We observed that tracking for AC increased in the higher quantiles of the distribution at 8\u00a0years, with an increase of 0.11 (95% CI: 0.09, 0.14) in the 0.6 quantile compared to an effect of 0.15 (95% CI: 0.09, 0.21) in the 0.9 quantile.<\/jats:p><jats:p>\u00a0 <jats:italic>Conclusions<\/jats:italic>: Adult markers of dyslipidemia and central obesity tracked between ages 4 and 8\u00a0years. For AC, tracking increased in the higher quantiles of the distribution.<jats:table-wrap><jats:table><jats:tbody>\n                    <jats:tr>\n                      <jats:td colspan=\"2\"><jats:bold>What is Known:<\/jats:bold>\u2022 <jats:italic>Atherosclerosis begins in early life, so preventive efforts that start in childhood may delay progression to clinical disease. Determine what cardiovascular risk factors track into time since childhood bring the opportunity to identified those subjects at risk for later cardiovascular disease.<\/jats:italic>\u2022 <jats:italic>The study of risk factors in health populations and, particularly in children, copes with not clear and\/or controversial thresholds definition. This makes it challenging to study tracking in pediatric ages.<\/jats:italic><\/jats:td>\n                    <\/jats:tr>\n                    <jats:tr>\n                      <jats:td colspan=\"2\"><jats:bold>What is New:<\/jats:bold>\u2022 <jats:italic>Quantile regression is a useful tool for assessing the tracking of risk factors for which there are no clinically meaningful thresholds. The increasing trend observed in the tracking of dyslipidemia suggests the possible difficulty that children with abnormal values at 4 years of age might have in normalizing them in future years.<\/jats:italic>\u2022 <jats:italic>The findings of this article may help to determine which cardiovascular-related measures could be screened and followed-up in children.<\/jats:italic><\/jats:td>\n                    <\/jats:tr>\n                  <\/jats:tbody><\/jats:table><\/jats:table-wrap><\/jats:p>","DOI":"10.1007\/s00431-023-05051-8","type":"journal-article","created":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T10:01:52Z","timestamp":1687255312000},"page":"3893-3906","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Tracking between cardiovascular-related measures at 4 and 8\u00a0years of age in the INMA-Asturias cohort"],"prefix":"10.1007","volume":"182","author":[{"given":"Roc\u00edo","family":"Fern\u00e1ndez-Iglesias","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pablo","family":"Martinez-Camblor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana","family":"Fern\u00e1ndez-Somoano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristina","family":"Rodr\u00edguez-Dehli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rafael","family":"Venta-Obaya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret R.","family":"Karagas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adonina","family":"Tard\u00f3n","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isolina","family":"Ria\u00f1o-Gal\u00e1n","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,6,20]]},"reference":[{"key":"5051_CR1","doi-asserted-by":"publisher","first-page":"1223","DOI":"10.1016\/S0140-6736(20)30752-2","volume":"396","author":"C Abbafati","year":"2020","unstructured":"Abbafati C, Abbas KM, Abbasi-Kangevari M, et al (2020) Global burden of 87 risk factors in 204 countries and territories, 1990\u20132019: a systematic analysis for the Global Burden of Disease Study 2019. 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