Next Article in Journal
UK Dietary Policy for the Prevention of Cardiovascular Disease
Previous Article in Journal
Socio-Demographic Determinants of Diet Quality in Australian Adults Using the Validated Healthy Eating Index for Australian Adults (HEIFA-2013)
Article Menu
Issue 1 (March) cover image

Export Article

Open AccessArticle
Healthcare 2017, 5(1), 8; doi:10.3390/healthcare5010008

Preventive Healthcare: A Neural Network Analysis of Behavioral Habits and Chronic Diseases

1
Koppelman School of Business, Brooklyn College of the City University of New York, Brooklyn, NY 11210, USA
2
Gabelli School of Business, Fordham University, New York, NY 10058, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Sampath Parthasarathy
Received: 30 November 2016 / Revised: 18 January 2017 / Accepted: 19 January 2017 / Published: 6 February 2017
View Full-Text   |   Download PDF [908 KB, uploaded 6 February 2017]   |  

Abstract

The research aims to explore the association between behavioral habits and chronic diseases, and to identify a portfolio of risk factors for preventive healthcare. The data is taken from the Behavioral Risk Factor Surveillance System (BRFSS) database of the Centers for Disease Control and Prevention, for the year 2012. Using SPSS Modeler, we deploy neural networks to identify strong positive and negative associations between certain chronic diseases and behavioral habits. The data for 475,687 records from BRFS database included behavioral habit variables of consumption of soda and fruits/vegetables, alcohol, smoking, weekly working hours, and exercise; chronic disease variables of heart attack, stroke, asthma, and diabetes; and demographic variables of marital status, income, and age. Our findings indicate that with chronic conditions, behavioral habits of physical activity and fruit and vegetable consumption are negatively associated; soda, alcohol, and smoking are positively associated; and income and age are positively associated. We contribute to individual and national preventive healthcare by offering a portfolio of significant behavioral risk factors that enable individuals to make lifestyle changes and governments to frame campaigns and policies countering chronic conditions and promoting public health. View Full-Text
Keywords: behavioral habit; chronic disease; preventive; health care; SPSS modeler; neural network; bayesian network; association behavioral habit; chronic disease; preventive; health care; SPSS modeler; neural network; bayesian network; association
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Raghupathi, V.; Raghupathi, W. Preventive Healthcare: A Neural Network Analysis of Behavioral Habits and Chronic Diseases. Healthcare 2017, 5, 8.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Healthcare EISSN 2227-9032 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top