{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T13:15:19Z","timestamp":1788527719941,"version":"build-2803163510"},"reference-count":46,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T00:00:00Z","timestamp":1788480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Machine learning is increasingly applied to identify hypertension from broad predictor panels, but whether it outperforms a few routine measurements is unclear. We compared machine learning pipelines against three readily obtained variables in a national Chilean survey. Methods: We analysed 5516 participants aged 15 years and older from the Chilean National Health Survey 2016\u20132017 with two valid blood-pressure readings. Hypertension was defined as mean systolic pressure \u2265 140 mmHg or mean diastolic pressure \u2265 90 mmHg or current antihypertensive treatment, the mean taken over the second and third readings. A total of 43 candidate predictors plus 11 laboratory missingness indicators formed 54 model inputs, excluding all blood pressure and hypertension-related variables. Data were partitioned once by census segment. Seventeen algorithms were compared under segment-grouped cross-validation with preprocessing fitted within folds; twelve were tuned identically, nested specifications independently, thresholds locked on development data and intervals derived from segment bootstrap. Results: Prevalence was 38.3% unweighted and 29.2% design-weighted. Across seven metrics, the twelve tuned pipelines were closely comparable, and none ranked first on all. On held-out data, the full XGBoost model reached an area under the receiver operating characteristic curve (AUC) of 0.890 (95% confidence interval [CI] 0.872 to 0.906) and the full penalised logistic model 0.882 (0.864 to 0.901). A model containing age, sex and waist-to-height ratio alone reached 0.882 (0.864 to 0.900) under XGBoost and 0.881 (0.861 to 0.898) under penalised logistic regression, differing from the corresponding full model of the nested comparison, which was tuned independently and reached 0.881 under penalised logistic regression and 0.891 under XGBoost, by \u22120.0004 (\u22120.0087 to +0.0081) under penalised logistic regression and \u22120.0084 (\u22120.0148 to \u22120.0024) under XGBoost, computed on unrounded values. Removing age cost 0.027 AUC. Findings held under design weighting, in the laboratory subsample and among untreated participants. Conclusions: Three routine measurements provided most of the discrimination achieved by fifty-four inputs; the remainder added no detectable increment under a penalised logistic specification and approximately 0.008 AUC under XGBoost. Equivalence was not formally tested, validation was internal, and transportability is undemonstrated.<\/jats:p>","DOI":"10.3390\/diagnostics16172843","type":"journal-article","created":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T12:20:19Z","timestamp":1788524419000},"page":"2843","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Age, Sex, and Waist-to-Height Ratio Approach the Discrimination of Fifty-Four Model Inputs for Prevalent Hypertension: An Explainable Machine Learning Analysis of the Chilean National Health Survey"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9311-6576","authenticated-orcid":false,"given":"Rodrigo","family":"Y\u00e1\u00f1ez-Sep\u00falveda","sequence":"first","affiliation":[{"name":"Faculty of Education and Humanities, Universidad Andr\u00e9s Bello, Vina del Mar 2520000, Chile"},{"name":"Department of Sport Sciences, Faculty of Sport and Health Sciences, Fit Generation Research Institute, AD500 Andorra la Vella, Andorra"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9581-5071","authenticated-orcid":false,"given":"Boryi A.","family":"Becerra-Pati\u00f1o","sequence":"additional","affiliation":[{"name":"Facultad de Educaci\u00f3n F\u00edsica, Universidad Pedag\u00f3gica Nacional, Bogota 480100, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0004-3089","authenticated-orcid":false,"given":"Felipe","family":"Montalva-Valenzuela","sequence":"additional","affiliation":[{"name":"Escuela de Entrenador en Actividad F\u00edsica y Deporte, Facultad de Ciencias Humanas, Universidad Bernardo O\u2019Higgins, Santiago 8370040, Chile"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0582-954X","authenticated-orcid":false,"given":"Rodrigo","family":"Olivares","sequence":"additional","affiliation":[{"name":"Escuela de Ingenier\u00eda Inform\u00e1tica, Universidad de Valpara\u00edso, Valparaiso 2340000, Chile"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"}]},{"given":"Alejandra","family":"Uribe-D\u00edaz","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Universidad Tecnol\u00f3gica Atl\u00e1ntico Mediterr\u00e1neo (UTAMED), 29590 Malaga, Spain"},{"name":"Department of Health Research, Icen Cognis, 38370 Tenerife, Spain"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7001-9004","authenticated-orcid":false,"given":"Eduardo","family":"Guzm\u00e1n-Mu\u00f1oz","sequence":"additional","affiliation":[{"name":"Escuela de Kinesiolog\u00eda, Facultad de Salud, Universidad Santo Tom\u00e1s, Talca 3460000, Chile"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7013-3894","authenticated-orcid":false,"given":"Yeny","family":"Concha-Cisternas","sequence":"additional","affiliation":[{"name":"Escuela de Kinesiolog\u00eda, Facultad de Salud, Universidad Santo Tom\u00e1s, Talca 3460000, Chile"},{"name":"Vicerrector\u00eda de Investigaci\u00f3n e Innovaci\u00f3n, Universidad Arturo Prat, Iquique 1100000, Chile"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0717-8827","authenticated-orcid":false,"given":"Daniel","family":"Rojas-Valverde","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n, Desarrollo e Innovaci\u00f3n en Salud y Deporte (CIDISAD), Escuela Ciencias del Movimiento Humano y Calidad de Vida (CIEMHCAVI), Universidad Nacional de Costa Rica, Heredia 863000, Costa 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Chile"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,4]]},"reference":[{"key":"ref_1","unstructured":"NCD Risk Factor Collaboration (NCD-RisC) (2021). 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