{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T19:30:02Z","timestamp":1786649402028,"version":"build-2736575974"},"reference-count":30,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"2","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>BACKGROUND:<\/jats:title>\n                    <jats:p>Hypertension remains a major global health burden, often undetected until complications occur. In Indonesia, evidence integrating multiyear surveillance data with machine learning (ML) to predict population-level risk remains limited. The objective of the study was to examine temporal trends in hypertension risk and develop predictive models at the population level.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>MATERIALS AND METHODS:<\/jats:title>\n                    <jats:p>\n                      This observational study utilized community health surveillance data on 196,951 adults (2019\u20132021). Blood pressure was classified using World Health Organization\/Joint National Committee 7 criteria, with prehypertension and hypertension combined as abnormal (\n                      <jats:italic toggle=\"yes\">y<\/jats:italic>\n                      = 1). Predictors included sociodemographic characteristics, anthropometric measurements, various health behaviors, and comorbidities. Missing values were imputed using K-Nearest Neighbors. Logistic Regression, Random Forest, Gradient Boosting, eXtreme Gradient Boosting (XGBoost), and Support Vector Machine models were developed using an 80:20 split, 10-fold cross-validation, and hyperparameter tuning. Model interpretability was assessed using SHapley Additive exPlanations (SHAP).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS:<\/jats:title>\n                    <jats:p>Abnormal blood pressure prevalence increased from 74.4% (2019) to 79.7% (2020) and 80.2% (2021). XGBoost demonstrated superior performance, achieving 78.3% accuracy and an area under the curve of 0.736, outperforming other models. SHAP analysis identified age, waist circumference, body mass index, and male sex as the strongest predictors of the risk of hypertension.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION:<\/jats:title>\n                    <jats:p>Hypertension risk in Indonesia rose from 2019 to 2021. Interpretable ML models, particularly XGBoost, show potential for population-level risk stratification and early detection in community and primary healthcare settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/jfcm.jfcm_26_26","type":"journal-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T08:00:39Z","timestamp":1777276839000},"page":"137-144","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Trend and predictive modeling of hypertension risk using multiyear community health surveillance data: Evidence from 2019 to 2021"],"prefix":"10.4103","volume":"33","author":[{"given":"Johannes B.","family":"Ginting","sequence":"first","affiliation":[{"name":"Department Master of Public Health, Faculty of Medicine, Dentistry and Health Sciences, Prima University, North Sumatra, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tri","family":"Suci","sequence":"additional","affiliation":[{"name":"Department Master of Public Health, Faculty of Medicine, Dentistry and Health Sciences, Prima University, North Sumatra, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chrismis N.","family":"Ginting","sequence":"additional","affiliation":[{"name":"Department Master of Public Health, Faculty of Medicine, Dentistry and Health Sciences, Prima University, North Sumatra, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristiawan","family":"Indriyanto","sequence":"additional","affiliation":[{"name":"Department Master of Indonesia Language Education, Faculty of Teacher Teaching and Education, Prima University, North Sumatra, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,4,25]]},"reference":[{"key":"R1-20260429","doi-asserted-by":"crossref","first-page":"1205475","DOI":"10.3389\/fcvm.2023.1205475","article-title":"Hypertensive heart disease:Risk factors, complications and mechanisms","volume":"10","author":"Masenga","year":"2023","journal-title":"Front Cardiovasc Med"},{"key":"R2-20260429","first-page":"1","article-title":"Pathophysiology of cardiovascular diseases\u202f:New insights into molecular mechanisms of atherosclerosis, arterial hypertension, and coronary artery disease","volume":"33","author":"Frak","year":"2022","journal-title":"Biomed Rev"},{"key":"R3-20260429","article-title":"Global Report on Hypertension 2025","year":"2025"},{"key":"R4-20260429","first-page":"1512","article-title":"Determinants of hypertension incidence among middle-aged in Indonesia \u2013A study of Indonesian family life survey 5 data","volume":"14","author":"Nugroho","year":"2020","journal-title":"J Public Health Res"},{"key":"R5-20260429","doi-asserted-by":"crossref","first-page":"18","DOI":"10.51866\/oa.409","article-title":"Association between lifestyle factors and hypertension control in Indonesian primary healthcare settings:A cross-sectional study","volume":"19","author":"Rachmawati","year":"2024","journal-title":"Malays Fam Physician"},{"key":"R6-20260429","first-page":"827","article-title":"Factors associated with hypertension among adults:A cross-sectional analysis of the Indonesian family life survey","volume":"23","author":"Alfaqeeh","year":"2023","journal-title":"BMC Public Health"},{"key":"R7-20260429","first-page":"e41907","article-title":"Analysis of a community health screening program and the factors affecting access to care","volume":"15","author":"Fritz","year":"2023","journal-title":"Cureus"},{"key":"R8-20260429","first-page":"1098765","article-title":"E ects of the COVID- pandemic on cardiovascular disease financing in Indonesia JKN claims data analysis","volume":"11","author":"Nugraheni","year":"2023","journal-title":"Front Public Health"},{"key":"R9-20260429","doi-asserted-by":"crossref","first-page":"8023","DOI":"10.3390\/ijerph19138023","article-title":"The impact of the COVID-19 pandemic on healthy lifestyle behaviors and perceived mental and physical health of people living with non-communicable diseases:An international cross-sectional survey","volume":"19","author":"Azzouzi","year":"2022","journal-title":"Int J Environ Res Public Health"},{"key":"R10-20260429","doi-asserted-by":"crossref","first-page":"e0299932","DOI":"10.1371\/journal.pone.0299932","article-title":"Predicting hypertension control using machine learning","volume":"19","author":"Mroz","year":"2024","journal-title":"PLoS One"},{"key":"R11-20260429","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s10916-025-02253-5","article-title":"Prediction of personalised hypertension using machine learning in Indonesian population","volume":"49","author":"Septian","year":"2025","journal-title":"J Med Syst"},{"key":"R12-20260429","first-page":"1","article-title":"Prediction of hypertension risks with feature selection and xgboost","volume":"21","author":"Wang","year":"2021","journal-title":"J Mech Med Biol"},{"key":"R13-20260429","first-page":"1","article-title":"A unified approach to interpreting model predictions","author":"Lundberg","year":"2017","journal-title":"Proceedings of the 31st Conference on Neural Information Processing Systems (NeurIPS)"},{"key":"R14-20260429","doi-asserted-by":"crossref","first-page":"1434418","DOI":"10.3389\/fcvm.2024.1434418","article-title":"Machine learning analysis of emerging risk factors for early-onset hypertension in the Tlalpan 2020 cohort","volume":"11","author":"Mart\u00ednez-Garc\u00eda","year":"2024","journal-title":"Front Cardiovasc Med"},{"key":"R15-20260429","doi-asserted-by":"crossref","first-page":"80","DOI":"10.20473\/jphrecode.v5i2.27923","article-title":"The risk factors of hypertension in Indonesia (data study of Indonesian family life survey 5)","volume":"5","author":"Khasanah","year":"2022","journal-title":"JPHRECODE"},{"key":"R16-20260429","doi-asserted-by":"crossref","first-page":"6259","DOI":"10.3390\/ijerph18126259","article-title":"Gender differences in prevalence and risk factors for hypertension among adult populations:A cross-sectional study in Indonesia","volume":"18","author":"Defianna","year":"2021","journal-title":"Int J Environ Res Public Health"},{"key":"R17-20260429","doi-asserted-by":"crossref","first-page":"4057","DOI":"10.1038\/s41598-022-07896-9","article-title":"Prevalence, awareness, treatment, and control of hypertension based on ACC\/AHA versus JNC7 guidelines in the PERSIAN cohort study","volume":"12","author":"Sepanlou","year":"2022","journal-title":"Sci Rep"},{"key":"R18-20260429","doi-asserted-by":"crossref","first-page":"1140","DOI":"10.1161\/HYPERTENSIONAHA.122.20448","article-title":"Arterial hypertension in women:State of the art and knowledge gaps","volume":"80","author":"Chapman","year":"2023","journal-title":"Hypertension"},{"key":"R19-20260429","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1186\/s12872-023-03126-w","article-title":"Association of normal-weight central obesity with hypertension:A cross-sectional study from the China health and nutrition survey","volume":"23","author":"Ren","year":"2023","journal-title":"BMC Cardiovasc Disord"},{"key":"R20-20260429","doi-asserted-by":"crossref","first-page":"e051315","DOI":"10.1136\/bmjopen-2021-051315","article-title":"Missed opportunities in hypertension risk factors screening in Indonesia:A mixed-methods evaluation of integrated health post (POSBINDU) implementation","volume":"12","author":"Widyaningsih","year":"2022","journal-title":"BMJ Open"},{"key":"R21-20260429","doi-asserted-by":"crossref","first-page":"e270324228382","DOI":"10.2174\/011573403X290574240322041356","article-title":"Revisiting waist circumference:A hypertension risk factor that requires a more in-depth understanding","volume":"20","author":"Su","year":"2024","journal-title":"Curr Cardiol Rev"},{"key":"R22-20260429","doi-asserted-by":"crossref","first-page":"e057383","DOI":"10.1136\/bmjopen-2021-057383","article-title":"Socioeconomic risk factors of hypertension and blood pressure among persons aged 15-49 in Nepal:A cross-sectional study","volume":"12","author":"Joshi","year":"2022","journal-title":"BMJ Open"},{"key":"R23-20260429","doi-asserted-by":"crossref","first-page":"873456","DOI":"10.3389\/fpubh.2022.1042236","article-title":"Comparison of obesity-related indices for predicting hypertension based on ROC analysis in Chinese adults","volume":"10","author":"Lee","year":"2022","journal-title":"Front Public Health"},{"key":"R24-20260429","doi-asserted-by":"crossref","first-page":"e40477","DOI":"10.1097\/MD.0000000000040477","article-title":"Psychological factors, lifestyle habits, and their association with gastroesophageal reflux disease among Egyptian university students:A cross-sectional study","volume":"103","author":"Ahmed","year":"2024","journal-title":"Medicine (Baltimore)."},{"key":"R25-20260429","doi-asserted-by":"crossref","first-page":"3000605231164548","DOI":"10.1177\/03000605231164548","article-title":"Insulin resistance and cardiovascular disease","volume":"51","author":"Kosmas","year":"2023","journal-title":"J Int Med Res"},{"key":"R26-20260429","doi-asserted-by":"crossref","first-page":"1253506","DOI":"10.3389\/fpubh.2023.1253506","article-title":"Metabolic diseases and healthy aging:Identifying environmental and behavioral risk factors and promoting public health","volume":"11","author":"Zhang","year":"2023","journal-title":"Front Public Health"},{"key":"R27-20260429","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/s11906-022-01183-8","article-title":"Sex differences in the prevalence, outcomes and management of hypertension","volume":"24","author":"Connelly","year":"2022","journal-title":"Curr Hypertens Rep"},{"key":"R28-20260429","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1186\/s12877-021-02154-5","article-title":"Association of body mass index and waist circumference with high blood pressure in older adults","volume":"21","author":"Zhang","year":"2021","journal-title":"BMC Geriatr"},{"key":"R29-20260429","doi-asserted-by":"crossref","first-page":"2066","DOI":"10.1093\/eurheartj\/ehac395","article-title":"Hypertension management in patients with cardiovascular comorbidities","volume":"44","author":"Lauder","year":"2023","journal-title":"Eur Heart J"},{"key":"R30-20260429","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s12967-021-03217-2","article-title":"Diabetes, hypertension, and cardiovascular disease development","volume":"20","author":"Yen","year":"2022","journal-title":"J Transl Med"}],"container-title":["Journal of Family and Community Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ovid.com\/10.4103\/jfcm.jfcm_26_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T18:53:40Z","timestamp":1786647220000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ovid.com\/10.4103\/jfcm.jfcm_26_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":30,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026]]}},"URL":"https:\/\/doi.org\/10.4103\/jfcm.jfcm_26_26","relation":{},"ISSN":["2230-8229","2229-340X"],"issn-type":[{"value":"2230-8229","type":"print"},{"value":"2229-340X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"2026-01-14","name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-07","name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}}]}}