Association of hypertension with risk factors using logistic regression

Abstract

Hypertension is one of the important public health challenges worldwide because of its high frequency and concomitant risks of cardiovascular and kidney disease. A hypertension model is built to test the interaction and significance between the factors. In this present paper, we present the results that gained from multiple logistic regression method and used to model the relationship between the ordinal outcome variable. The significant variables is chosen based on the p-value associated to the significant level of model that lies on α = 0.05. Logit determination and the correlation between the variables are also discussed for further analysis. there are three factors that most significant of the six factors tested were identified as having influence significantly the performance of human blood pressure (hypertension). These factors are age (p-value <0.000), body mass index (p-value <0.001) and systolic (p-value <0.001). The use of mathematical software PASW version 18 is applied in this research as an alternatives calculation procedures derived from the methodology.

Quantitative Identification of Maize Lodging-Causing Feature Factors Using Unmanned Aerial Vehicle Images and a Nomogram Computation

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Risk prediction model of self-reported hypertension for telemedicine based on the sociodemographic, occupational and health-related characteristics of seafarers: a cross-sectional epidemiological study

“…In the general population, a risk model in the context of CVD risk factors (hypertension, diabetes and other modifiable risk factors) is well documented as a means of assessing individual risk based on different variables. [12][13][14][15] So far, no studies on a risk prediction model have been conducted in seafarers in order to assess their individual risk for selfreported hypertension (HTN). It is possible that a risk model will have a positive effect on mitigating risk factors and reducing the burden of CVD among seafarers, who reside hundreds of kilometres from healthcare facilities.…”

“…A risk model can also help healthcare professionals in decision-making. In the general population, a risk model in the context of CVD risk factors (hypertension, diabetes and other modifiable risk factors) is well documented as a means of assessing individual risk based on different variables 12–15. So far, no studies on a risk prediction model have been conducted in seafarers in order to assess their individual risk for self-reported hypertension (HTN).…”

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“…If the area is 1.0, we have an ideal test because it achieves both 100% sensitivity and 100% specificity. If the area is 0.5, then we have a test that effectively has 50% sensitivity and 50% specificity [26,27]. In practice, a diagnostic test will have an area somewhere between these two extremes.…”