Modeling of hypertension risk factors using local linear of additive nonparametric logistic regression

E. Ana, N. Chamidah, P. Andriani, B. Lestari

Research output: Contribution to journalConference articlepeer-review

23 Citations (Scopus)

Abstract

Hypertension has become a serious health problem in Indonesia because of its prevalence, however, the causative factors could not be ascertained for about ninety percent of the patients. Various studies have found several risk factors causing hypertension to be obesity, family history, stress levels, heart rate, and an unhealthy lifestyle. In this case, the variables are considered influential on hypertension through a regression curve without a specific pattern. Also, we need to describe the functional relationships between several predictor variables with binary or dichotomous response variables and need to describe locally effect of predictor variables to the response variable. Therefore, in this study, to model the case of hypertension by age, body mass index, heart rate, stress levels we use the additive nonparametric logistic regression approach based on local linear estimators. The results of the study showed that hypertension was most prevalent among respondents over 65 years of age with BMI between 25-30 kg/m2 (obesity) and normal heart rate (60-100) bpm and most of them were found to be experiencing mild stress conditions. The model obtained a classification accuracy of 95 percent (in-sample) and 89.47 percent (out-sample) with a cut off probability value of 0.4.

Original languageEnglish
Article number012067
JournalJournal of Physics: Conference Series
Volume1397
Issue number1
DOIs
Publication statusPublished - 19 Dec 2019
Event6th International Conference on Research, Implementation, and Education of Mathematics and Science, ICRIEMS 2019 - Yogyakarta, Indonesia
Duration: 12 Jul 201913 Jul 2019

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