Predicting obesity rate and obesity-related healthcare costs using data analytics. Issue 2 (June 2017)
- Record Type:
- Journal Article
- Title:
- Predicting obesity rate and obesity-related healthcare costs using data analytics. Issue 2 (June 2017)
- Main Title:
- Predicting obesity rate and obesity-related healthcare costs using data analytics
- Authors:
- Revels, Stephanie
Kumar, Sathish A.P.
Ben-Assuli, Ofir - Abstract:
- Abstract: Objective: Obesity is a worldwide problem that has been linked to serious medical issues. Obesity-related conditions drain healthcare expenditures globally, and in particular in the U.S. This article suggests methods to forecast future costs associated with obesity-related healthcare in the next two decades. Methods: An Auto Regressive Integrated Moving Average (ARIMA) time series analysis was implemented to model the data published by the Center for Disease Control and Prevention. Results: The findings suggest that the proportion of individuals in the population defined as overweight will decline slowly in the next 20 years. However, the proportion of the population considered obese will increase substantially and could represent as much as 45% of the entire population by 2035. The proportion of morbidly obese will also increase considerably. These trends are likely to impact the actual costs of healthcare considerably. Conclusions: Policy makers in the healthcare sector should be aware of this trend and prepare to deal with increasing numbers of medical problems related to obesity. Concrete recommendations for policy makers are put forward in the discussion as well as avenues for future research. Highlights: Obesity is a worldwide problem which causes a lot of serious medical problems. Obesity affects the healthcare expenditures worldwide and especially for the U.S. Obesity will be increased, about 45% out of the whole population by 2035. The proportion of morbidAbstract: Objective: Obesity is a worldwide problem that has been linked to serious medical issues. Obesity-related conditions drain healthcare expenditures globally, and in particular in the U.S. This article suggests methods to forecast future costs associated with obesity-related healthcare in the next two decades. Methods: An Auto Regressive Integrated Moving Average (ARIMA) time series analysis was implemented to model the data published by the Center for Disease Control and Prevention. Results: The findings suggest that the proportion of individuals in the population defined as overweight will decline slowly in the next 20 years. However, the proportion of the population considered obese will increase substantially and could represent as much as 45% of the entire population by 2035. The proportion of morbidly obese will also increase considerably. These trends are likely to impact the actual costs of healthcare considerably. Conclusions: Policy makers in the healthcare sector should be aware of this trend and prepare to deal with increasing numbers of medical problems related to obesity. Concrete recommendations for policy makers are put forward in the discussion as well as avenues for future research. Highlights: Obesity is a worldwide problem which causes a lot of serious medical problems. Obesity affects the healthcare expenditures worldwide and especially for the U.S. Obesity will be increased, about 45% out of the whole population by 2035. The proportion of morbid obese and the actual costs on healthcare will be increased. Implementation of our recommendations can help in the fight against obesity. … (more)
- Is Part Of:
- Health policy and technology. Volume 6:Issue 2(2017)
- Journal:
- Health policy and technology
- Issue:
- Volume 6:Issue 2(2017)
- Issue Display:
- Volume 6, Issue 2 (2017)
- Year:
- 2017
- Volume:
- 6
- Issue:
- 2
- Issue Sort Value:
- 2017-0006-0002-0000
- Page Start:
- 198
- Page End:
- 207
- Publication Date:
- 2017-06
- Subjects:
- Obesity -- Healthcare costs -- Data analytics -- Medical problems -- ARIMA model
Medical policy -- Periodicals
Medical technology -- Periodicals
Medical policy
Medical technology
Health Policy -- Periodicals
Biomedical Technology -- Periodicals
Technology Assessment, Biomedical -- Periodicals
Periodicals
362.105 - Journal URLs:
- http://www.sciencedirect.com/science/journal/22118837 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.hlpt.2017.02.002 ↗
- Languages:
- English
- ISSNs:
- 2211-8837
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1093.xml