Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh
Background and objectives: Hypertension (HTN) is a leading cause of non-communicable disease in low- and middle-income countries, including Bangladesh. Thus, the objectives of this study were to investigate the associated risk factors for HTN and develop with validate a monogram model for predicting...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-11-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024162779 |
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| author | Merajul Islam Jahangir Alam Sujit Kumar Ariful Islam Muhammad Robin Khan Symun Rabby N.A.M. Faisal Ahmed Dulal Chandra Roy |
| author_facet | Merajul Islam Jahangir Alam Sujit Kumar Ariful Islam Muhammad Robin Khan Symun Rabby N.A.M. Faisal Ahmed Dulal Chandra Roy |
| author_sort | Merajul Islam |
| collection | DOAJ |
| description | Background and objectives: Hypertension (HTN) is a leading cause of non-communicable disease in low- and middle-income countries, including Bangladesh. Thus, the objectives of this study were to investigate the associated risk factors for HTN and develop with validate a monogram model for predicting an individual's risk of HTN in Bangladesh. Materials and methods: This study exploited the latest nationally representative cross-sectional BDHS, 2017–18 data, which consisted of 6569 participants. LASSO and logistic regression (LR) analysis were performed to reduce dimensionality of data, identify the associated risk factors, and develop a nomogram model for predicting HTN risk in the training cohort. The discrimination ability, calibration, and clinical effectiveness of the developed model were evaluated using validation cohort in terms of area under the curve (AUC), calibration plot, decision curve analysis, and clinical impact curve analysis. Results: The combined results of the LASSO and LR analysis demonstrated that age, sex, division, physical activity, family member, smoking, body mass index, and diabetes were the associated risk factors of HTN. The nomogram model achieved good discrimination ability with AUC of 0.729 (95 % CI: 0.685–0.741) for training and AUC of 0.715 (95 % CI: 0.681–0.729)] for validation cohort and showed strong calibration effects, with good agreement between the actual and predicted probabilities (p-value = 0.231). Conclusion: The proposed nomogram provided a good predictive performance and can be effectively utilized in clinical settings to accurately diagnose hypertensive patients who are at risk of developing severe HTN at an early stage in Bangladesh. |
| format | Article |
| id | doaj-art-9bb759c0b28b4d59a4a0940a8bf46f70 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-9bb759c0b28b4d59a4a0940a8bf46f702024-11-30T07:12:13ZengElsevierHeliyon2405-84402024-11-011022e40246Development and validation of a nomogram model for predicting the risk of hypertension in BangladeshMerajul Islam0Jahangir Alam1Sujit Kumar2Ariful Islam3Muhammad Robin Khan4Symun Rabby5N.A.M. Faisal Ahmed6Dulal Chandra Roy7Department of Statistics, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh, 2224, Bangladesh; Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh; Corresponding author. Department of Statistics, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh, 2224, Bangladesh.Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh; Mainanalytics GmbH, Otto-Volger-Str. 3c, 65843, Sulzbach, Taunus, GermanyDepartment of Statistics, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh, 2224, BangladeshDepartment of Statistics, University of Rajshahi, Rajshahi, 6205, BangladeshDepartment of Statistics, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh, 2224, BangladeshDepartment of Statistics, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh, 2224, BangladeshInstitute of Education and Research, University of Rajshahi, Rajshahi, 6205, BangladeshDepartment of Statistics, University of Rajshahi, Rajshahi, 6205, BangladeshBackground and objectives: Hypertension (HTN) is a leading cause of non-communicable disease in low- and middle-income countries, including Bangladesh. Thus, the objectives of this study were to investigate the associated risk factors for HTN and develop with validate a monogram model for predicting an individual's risk of HTN in Bangladesh. Materials and methods: This study exploited the latest nationally representative cross-sectional BDHS, 2017–18 data, which consisted of 6569 participants. LASSO and logistic regression (LR) analysis were performed to reduce dimensionality of data, identify the associated risk factors, and develop a nomogram model for predicting HTN risk in the training cohort. The discrimination ability, calibration, and clinical effectiveness of the developed model were evaluated using validation cohort in terms of area under the curve (AUC), calibration plot, decision curve analysis, and clinical impact curve analysis. Results: The combined results of the LASSO and LR analysis demonstrated that age, sex, division, physical activity, family member, smoking, body mass index, and diabetes were the associated risk factors of HTN. The nomogram model achieved good discrimination ability with AUC of 0.729 (95 % CI: 0.685–0.741) for training and AUC of 0.715 (95 % CI: 0.681–0.729)] for validation cohort and showed strong calibration effects, with good agreement between the actual and predicted probabilities (p-value = 0.231). Conclusion: The proposed nomogram provided a good predictive performance and can be effectively utilized in clinical settings to accurately diagnose hypertensive patients who are at risk of developing severe HTN at an early stage in Bangladesh.http://www.sciencedirect.com/science/article/pii/S2405844024162779HypertensionLASSOLogistic regressionNomogramBangladesh |
| spellingShingle | Merajul Islam Jahangir Alam Sujit Kumar Ariful Islam Muhammad Robin Khan Symun Rabby N.A.M. Faisal Ahmed Dulal Chandra Roy Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh Heliyon Hypertension LASSO Logistic regression Nomogram Bangladesh |
| title | Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh |
| title_full | Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh |
| title_fullStr | Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh |
| title_full_unstemmed | Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh |
| title_short | Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh |
| title_sort | development and validation of a nomogram model for predicting the risk of hypertension in bangladesh |
| topic | Hypertension LASSO Logistic regression Nomogram Bangladesh |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024162779 |
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