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This is a Quantitative Study study.

September 16, 2025JTAM (Jurnal Teori dan Aplikasi Matematika)Open Access

Modeling Prevalence of Hypertension in Indonesia with Multivariate Adaptive Regression Splines Method

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The best model achieved an R-Square of 0.278, indicating significant but incomplete explanation of hypertension variance.
Key predictors of hypertension included consumption of fatty foods (100% importance), physical inactivity, and sweets consumption.
The MARS method effectively modeled complex interactions and nonlinear relationships between predictors affecting hypertension prevalence.
Findings emphasize the need for interventions focused on nutrition education and physical activity to combat hypertension.

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Implication

This analysis identifies significant predictors of hypertension among Indonesians, suggesting health policy adjustments to address non-communicable diseases.

Cite This Study

Suliyanto et al. (2025) studied this question.

synapsesocial.com/papers/68d453a431b076d99fa59976 https://doi.org/10.31764/jtam.v9i2.28392

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Implication

This analysis identifies significant predictors of hypertension among Indonesians, suggesting health policy adjustments to address non-communicable diseases.

Modeling Prevalence of Hypertension in Indonesia with Multivariate Adaptive Regression Splines Method

Key Points

Discussion

Implication

Cite This Study

Modeling Prevalence of Hypertension in Indonesia with Multivariate Adaptive Regression Splines Method

Key Points

Discussion

Implication

Cite This Study

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Also Consider