Binomial Logistic Regression Analysis of Hypertension Based on 4 Risk Factors and 2 Protective Factors Based on Simultaneous Test of Omnimbus Likelihood Ratio
DOI:
https://doi.org/10.24903/kujkm.v9i1.2039Keywords:
Hipertensi, Binomial, BiopsikososialAbstract
Background: Hypertension is one of the most common and dangerous non-communicable diseases in the world. The prevalence of hypertension in Indonesia reaches 34.1% and is the main cause of premature death and disability.
Research Metodes: This study aims to determine the biopsychosocial relationship to the incidence of hypertension.
Results: Hypertension is influenced by anxiety (OR= 7.45; 95% CI= 2.35 to 23.66; p<0.001), stress (OR= 2.95; 95% CI= 1.14 to 7.63; p=0.026) , sleep quality (OR= 8.15; 95% CI= 3.04 to 21.83; p<0.001), family history (OR= 2.83; 95% CI= 1.11 to 7.19; p=0.029) , physical activity (OR= 0.118; 95% CI= 0.038 to 0.367; p<0.001), vegetable and fruit consumption (OR= 0.20; 95% CI= 0.06 to 0.59; p=0.003).
Conclusion: anxiety, stress, sleep quality, family history, physical activity, consumption of vegetables and fruit affect the incidence of hypertension.
Keywords: Hypertension, Binomial, Biopsychosocial.
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References
Adam, A. G. A., Nelwan, J. E., & Wariki, W. M. V. (2018). KEJADIAN HIPERTENSI DAN RIWAYAT KELUARGA MENDERITA HIPERTENSI DI PUSKESMAS PACEDA KOTA BITUNG. KESMAS: Jurnal Kesehatan Masyarakat Universitas Sam Ratulangi, 7(5), Article 5. https://ejournal.unsrat.ac.id/v3/index.php/kesmas/article/view/22131.
Di Raimondo, D., Buscemi, S., Musiari, G., Rizzo, G., Pirera, E., Corleo, D., Pinto, A., & Tuttolomondo, A. (2021). Ketogenic Diet, Physical Activity, and Hypertension-A Narrative Review. Nutrients, 13(8), 2567. https://doi.org/10.3390/nu13082567.
Fox, J., & Weisberg, S. (2020). car: Companion to Applied Regression. [R package]. Retrieved from https://cran.r-project.org/package=car.
Hamidah, S. (2015). Sayuran dan buah serta manfaatnya bagi kesehatan. Artikel Ilmiah. Fakultas Teknik Universitas Negeri Yogyakarta.
Hemmert, G. A. J., Schons, L. M., Wieseke, J., & Schimmelpfennig, H. (2018). Log-likelihood-based Pseudo-R2 in Logistic Regression: Deriving Sample-sensitive Benchmarks. Sociological Methods & Research, 47(3), 507–531. https://doi.org/10.1177/0049124116638107
Huber, E., & Stephens, J. D. (1993). Political parties and public pensions: a quantitative analysis. Acta Sociologica, 36(4), 309-325.
Hypertension. (n.d.). Retrieved February 6, 2023, from https://www.who.int/health-topics/hypertension
Istyanto, F., Mudigdo, A., & Rahardjo, S. S. (2018). Path analysis on the biopsychosocial factors associated with hypertension. Population.
Kemenkes RI. (2018). Hasil Utama Riskesdas 2018. Kemenkes RI.
Lo, K., Woo, B., Wong, M., & Tam, W. (2018). Subjective sleep quality, blood pressure, and hypertension: A meta-analysis. Journal of Clinical Hypertension (Greenwich, Conn.), 20(3), 592–605. https://doi.org/10.1111/jch.13220.
Maryoto, A. (2020). Manfaat Serat bagi Tubuh. Alprin.
Menard, S. (1995). Sage University paper series on quantitative applications in the social sciences. Applied logistic regression analysis, 07-106.
Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to linear regression analysis. John Wiley & Sons.
Myers, R. H., & Myers, R. H. (1990). Classical and modern regression with applications (Vol. 2). Duxbury press Belmont, CA.
Nagata, J. M., Vittinghoff, E., Pettee Gabriel, K., Garber, A. K., Moran, A. E., Sidney, S., Rana, J. S., Reis, J. P., & Bibbins-Domingo, K. (2021). Physical Activity and Hypertension From Young Adulthood to Middle Age. American Journal of Preventive Medicine, 60(6),757–765. https://doi.org/10.1016/j.amepre.2020.12.018.
Polishchuk, O. Y., Tashchuk, V. K., Barchuk, N. I., Amelina, T. M., Hrechko, S. I., & Trefanenko, I. V. (2021). ANXIETY AND DEPRESSIVE DISORDERS IN PATIENTS WITH ARTERIAL HYPERTENSION. Wiadomosci Lekarskie (Warsaw, Poland: 1960), 74(3 cz 1), 455–459.
Pramana, K. D., Okatiranti, O., & Ningrum, T. P. (2016). HUBUNGAN TINGKAT KECEMASAN DENGAN KEJADIAN HIPERTENSI DI PANTI SOSIAL TRESNA WERDHA SENJARAWI BANDUNG. Jurnal Keperawatan BSI, 4(2), Article 2. https://doi.org/10.31311/.v4i2.863.
Putra, S. (2022). Pengaruh Gaya Hidup Dengan Kejadian Hipertensi di Indonesia (A: Systematic Review). Jurnal Pendidikan Tambusai, 6(2), 15794–15798.
R Core Team (2021). R: A Language and environment for statistical computing. (Version 4.0) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from MRAN snapshot 2021-04-01).
Rose, W., & Mann, I. J. S. (2011). The Variability of Pseudo R 2 s in Logistic Regression Models. IUP Journal of Computational Mathematics, 4(1).
Sing, T., Sander, O., Beerenwinkel, N., & Lengauer, T. (2015). ROCR: Visualizing the Performance of Scoring Classifiers. [R package]. Retrieved from https://cran.r-project.org/package=ROCR.
Smith, T. J., & McKenna, C. M. (2013). A comparison of logistic regression pseudo R2 indices. Multiple Linear Regression Viewpoints, 39(2), 17–26.
Syukkur, A., Vinsur, E. Y. Y., & Nurwiyono, A. (2022). Pemberdayaan Kader Lansia dalam Upaya Penatalaksanaan Hipertensi. Selaparang: Jurnal Pengabdian Masyarakat Berkelanjutan, 6(2).
Tabachnick, B. G., & Fidell, L. S. (2001). Using Multivariate Statistics, Allyn and Bacon, Boston, MA. Using Multivariate Statistics, 4th ed. Allyn and Bacon, Boston, MA.
The jamovi project (2021). jamovi. (Version 2.2) [Computer Software]. Retrieved from https://www.jamovi.org.
Walker, D. A., & Smith, T. J. (2016). JMASM36: Nine pseudo R^ 2 indices for binary logistic regression models (SPSS). Journal of Modern Applied Statistical Methods, 15(1), 43.
Walker, D. A., & Smith, T. J. (2016). JMASM36: Nine pseudo R^ 2 indices for binary logistic regression models (SPSS). Journal of Modern Applied Statistical Methods, 15(1), 43.
WHO. (2018). Global Health Estimates 2016: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2016.Geneva: World Health Organization.
Williams, R. (2015). Multicollinearity. University of Notre Dame, 1-14.
Zahara, F. (2019). HUBUNGAN ANTARA KECEMASAN DENGAN TEKANAN DARAH PADA PENDERITA HIPERTENSI DI RSU PKU MUHAMMADIYAH YOGYAKARTA. JURNAL PSIKOLOGI KOGNISI, 2(1), Article 1. https://doi.org/10.22303/kognisi.2.1.2017.42-53.
Zhao, S., Fu, S., Ren, J., & Luo, L. (2018). Poor sleep is responsible for the impaired nocturnal blood pressure dipping in elderly hypertensive: A cross-sectional study of elderly. Clinical and Experimental Hypertension (New York, N.Y.: 1993), 40(6), 582–588. https://doi.org/10.1080/10641963.2017.1411495
Di Raimondo, D., Buscemi, S., Musiari, G., Rizzo, G., Pirera, E., Corleo, D., Pinto, A., & Tuttolomondo, A. (2021). Ketogenic Diet, Physical Activity, and Hypertension-A Narrative Review. Nutrients, 13(8), 2567. https://doi.org/10.3390/nu13082567.
Fox, J., & Weisberg, S. (2020). car: Companion to Applied Regression. [R package]. Retrieved from https://cran.r-project.org/package=car.
Hamidah, S. (2015). Sayuran dan buah serta manfaatnya bagi kesehatan. Artikel Ilmiah. Fakultas Teknik Universitas Negeri Yogyakarta.
Hemmert, G. A. J., Schons, L. M., Wieseke, J., & Schimmelpfennig, H. (2018). Log-likelihood-based Pseudo-R2 in Logistic Regression: Deriving Sample-sensitive Benchmarks. Sociological Methods & Research, 47(3), 507–531. https://doi.org/10.1177/0049124116638107
Huber, E., & Stephens, J. D. (1993). Political parties and public pensions: a quantitative analysis. Acta Sociologica, 36(4), 309-325.
Hypertension. (n.d.). Retrieved February 6, 2023, from https://www.who.int/health-topics/hypertension
Istyanto, F., Mudigdo, A., & Rahardjo, S. S. (2018). Path analysis on the biopsychosocial factors associated with hypertension. Population.
Kemenkes RI. (2018). Hasil Utama Riskesdas 2018. Kemenkes RI.
Lo, K., Woo, B., Wong, M., & Tam, W. (2018). Subjective sleep quality, blood pressure, and hypertension: A meta-analysis. Journal of Clinical Hypertension (Greenwich, Conn.), 20(3), 592–605. https://doi.org/10.1111/jch.13220.
Maryoto, A. (2020). Manfaat Serat bagi Tubuh. Alprin.
Menard, S. (1995). Sage University paper series on quantitative applications in the social sciences. Applied logistic regression analysis, 07-106.
Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to linear regression analysis. John Wiley & Sons.
Myers, R. H., & Myers, R. H. (1990). Classical and modern regression with applications (Vol. 2). Duxbury press Belmont, CA.
Nagata, J. M., Vittinghoff, E., Pettee Gabriel, K., Garber, A. K., Moran, A. E., Sidney, S., Rana, J. S., Reis, J. P., & Bibbins-Domingo, K. (2021). Physical Activity and Hypertension From Young Adulthood to Middle Age. American Journal of Preventive Medicine, 60(6),757–765. https://doi.org/10.1016/j.amepre.2020.12.018.
Polishchuk, O. Y., Tashchuk, V. K., Barchuk, N. I., Amelina, T. M., Hrechko, S. I., & Trefanenko, I. V. (2021). ANXIETY AND DEPRESSIVE DISORDERS IN PATIENTS WITH ARTERIAL HYPERTENSION. Wiadomosci Lekarskie (Warsaw, Poland: 1960), 74(3 cz 1), 455–459.
Pramana, K. D., Okatiranti, O., & Ningrum, T. P. (2016). HUBUNGAN TINGKAT KECEMASAN DENGAN KEJADIAN HIPERTENSI DI PANTI SOSIAL TRESNA WERDHA SENJARAWI BANDUNG. Jurnal Keperawatan BSI, 4(2), Article 2. https://doi.org/10.31311/.v4i2.863.
Putra, S. (2022). Pengaruh Gaya Hidup Dengan Kejadian Hipertensi di Indonesia (A: Systematic Review). Jurnal Pendidikan Tambusai, 6(2), 15794–15798.
R Core Team (2021). R: A Language and environment for statistical computing. (Version 4.0) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from MRAN snapshot 2021-04-01).
Rose, W., & Mann, I. J. S. (2011). The Variability of Pseudo R 2 s in Logistic Regression Models. IUP Journal of Computational Mathematics, 4(1).
Sing, T., Sander, O., Beerenwinkel, N., & Lengauer, T. (2015). ROCR: Visualizing the Performance of Scoring Classifiers. [R package]. Retrieved from https://cran.r-project.org/package=ROCR.
Smith, T. J., & McKenna, C. M. (2013). A comparison of logistic regression pseudo R2 indices. Multiple Linear Regression Viewpoints, 39(2), 17–26.
Syukkur, A., Vinsur, E. Y. Y., & Nurwiyono, A. (2022). Pemberdayaan Kader Lansia dalam Upaya Penatalaksanaan Hipertensi. Selaparang: Jurnal Pengabdian Masyarakat Berkelanjutan, 6(2).
Tabachnick, B. G., & Fidell, L. S. (2001). Using Multivariate Statistics, Allyn and Bacon, Boston, MA. Using Multivariate Statistics, 4th ed. Allyn and Bacon, Boston, MA.
The jamovi project (2021). jamovi. (Version 2.2) [Computer Software]. Retrieved from https://www.jamovi.org.
Walker, D. A., & Smith, T. J. (2016). JMASM36: Nine pseudo R^ 2 indices for binary logistic regression models (SPSS). Journal of Modern Applied Statistical Methods, 15(1), 43.
Walker, D. A., & Smith, T. J. (2016). JMASM36: Nine pseudo R^ 2 indices for binary logistic regression models (SPSS). Journal of Modern Applied Statistical Methods, 15(1), 43.
WHO. (2018). Global Health Estimates 2016: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2016.Geneva: World Health Organization.
Williams, R. (2015). Multicollinearity. University of Notre Dame, 1-14.
Zahara, F. (2019). HUBUNGAN ANTARA KECEMASAN DENGAN TEKANAN DARAH PADA PENDERITA HIPERTENSI DI RSU PKU MUHAMMADIYAH YOGYAKARTA. JURNAL PSIKOLOGI KOGNISI, 2(1), Article 1. https://doi.org/10.22303/kognisi.2.1.2017.42-53.
Zhao, S., Fu, S., Ren, J., & Luo, L. (2018). Poor sleep is responsible for the impaired nocturnal blood pressure dipping in elderly hypertensive: A cross-sectional study of elderly. Clinical and Experimental Hypertension (New York, N.Y.: 1993), 40(6), 582–588. https://doi.org/10.1080/10641963.2017.1411495
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Published
2023-06-29
How to Cite
febry istyanto. (2023). Binomial Logistic Regression Analysis of Hypertension Based on 4 Risk Factors and 2 Protective Factors Based on Simultaneous Test of Omnimbus Likelihood Ratio. KESMAS UWIGAMA: Jurnal Kesehatan Masyarakat, 9(1), 89–94. https://doi.org/10.24903/kujkm.v9i1.2039
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