Hafiz Khan1, Drew Rasmussen1, Lisaann Gittner1, Aamrin Rafiq2, Summre Blakely3, Obadeh Shabaneh1, P Hemachandra Reddy4. 1. Julia Jones Matthews Department of Public Health, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA. 2. Department of Biology, Texas Tech University, Lubbock, TX 79409, USA. 3. School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA. 4. Department of Cell Biology and Biochemistry, Neuroscience/Pharmacology and Neurology, Texas Tech University Health Sciences Center, Lubbock, TX 79409, USA.
Abstract
Background: Heart disease is the leading cause of death in the United States. Incidence rates of myocardial infarction (MI) in rural West Texas signify a lack of effective, risk-specific prevention programs. The purpose of this study was to identify gender-specific risk factors for MI in rural West Texans. Subjects and methods: Hospital patient data for those with and without a history of MI were obtained from the Project FRONTIER database for rural West Texas counties. We used statistical software, such as SPSS, R, and WinBUGS to detect and understand the nature of MI risk factors. Statistical methods including t-tests, Chi-squared, logistic regression, and a Bayesian approach were utilized to analyze data. Results: MI significant risk factors obtained for females were systolic blood pressure (p = 0.002), diastolic blood pressure (p = 0.004), pulse (p = 0.015), and smoking (p = 0.002). For males, these were glucose (p = 0.022), age (p = 0.050), body fat (p = 0.034), and smoking (p = 0.017). The mean risk parameter followed a normal distribution, while the precision parameter depicted skew for both sexes. Conclusions: Gender-specific differences in MI risk factors exist, and incorporating such variables can guide relevant policymaking to reduce MI incidence in rural West Texans.
Background: Heart disease is the leading cause of death in the United States. Incidence rates of myocardial infarction (MI) in rural West Texas signify a lack of effective, risk-specific prevention programs. The purpose of this study was to identify gender-specific risk factors for MI in rural West Texans. Subjects and methods: Hospital patient data for those with and without a history of MI were obtained from the Project FRONTIER database for rural West Texas counties. We used statistical software, such as SPSS, R, and WinBUGS to detect and understand the nature of MI risk factors. Statistical methods including t-tests, Chi-squared, logistic regression, and a Bayesian approach were utilized to analyze data. Results: MI significant risk factors obtained for females were systolic blood pressure (p = 0.002), diastolic blood pressure (p = 0.004), pulse (p = 0.015), and smoking (p = 0.002). For males, these were glucose (p = 0.022), age (p = 0.050), body fat (p = 0.034), and smoking (p = 0.017). The mean risk parameter followed a normal distribution, while the precision parameter depicted skew for both sexes. Conclusions: Gender-specific differences in MI risk factors exist, and incorporating such variables can guide relevant policymaking to reduce MI incidence in rural West Texans.
Authors: Véronique L Roger; Alan S Go; Donald M Lloyd-Jones; Robert J Adams; Jarett D Berry; Todd M Brown; Mercedes R Carnethon; Shifan Dai; Giovanni de Simone; Earl S Ford; Caroline S Fox; Heather J Fullerton; Cathleen Gillespie; Kurt J Greenlund; Susan M Hailpern; John A Heit; P Michael Ho; Virginia J Howard; Brett M Kissela; Steven J Kittner; Daniel T Lackland; Judith H Lichtman; Lynda D Lisabeth; Diane M Makuc; Gregory M Marcus; Ariane Marelli; David B Matchar; Mary M McDermott; James B Meigs; Claudia S Moy; Dariush Mozaffarian; Michael E Mussolino; Graham Nichol; Nina P Paynter; Wayne D Rosamond; Paul D Sorlie; Randall S Stafford; Tanya N Turan; Melanie B Turner; Nathan D Wong; Judith Wylie-Rosett Journal: Circulation Date: 2010-12-15 Impact factor: 29.690
Authors: Javier López Pais; Bárbara Izquierdo Coronel; David Galán Gil; María Jesús Espinosa Pascual; Carlos Gustavo Martinez Peredo; Paula Awamleh García; Juan Górriz Magaña; Rebeca Mata Caballero; Alfonso Fraile Sanz; Javier Muñiz; Joaquín J Alonso Martín Journal: Cardiol J Date: 2017-12-14 Impact factor: 2.737