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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Progress in Cardiova...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Progress in Cardiovascular Diseases
Article . 2016 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Personalized Weight Management Interventions for Cardiovascular Risk Reduction: A Viable Option for African-American Women

Authors: Nina C, Franklin; Ross, Arena;

Personalized Weight Management Interventions for Cardiovascular Risk Reduction: A Viable Option for African-American Women

Abstract

Obesity is an independent contributor to cardiovascular disease (CVD) and a major driving force behind racial/ethnic and gender disparities in risk. Due to a multitude of interrelating factors (i.e., personal, social, cultural, economic and environmental), African-American (AA) women are disproportionately obese and twice as likely to succumb to CVD, yet they are significantly underrepresented in behavioral weight management interventions. In this selective review we highlight components of the limited interventions shown to enhance weight loss outcomes in this population and make a case for leveraging Web-based technology and artificial intelligence techniques to deliver personalized programs aimed at obesity treatment and CVD risk reduction. Although many of the approaches discussed are generally applicable across populations burdened by disparate rates of obesity and CVD, we specifically focus on AA women due to the disproportionate impact of these non-communicable diseases and the general paucity of interventions targeted to this high-risk group.

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Keywords

Health Knowledge, Attitudes, Practice, Attitude to Computers, Delivery of Health Care, Integrated, Biomedical Technology, Patient Acceptance of Health Care, Risk Assessment, Telemedicine, United States, Black or African American, Primary Prevention, Treatment Outcome, Artificial Intelligence, Cardiovascular Diseases, Risk Factors, Weight Loss, Humans, Female, Obesity, Healthcare Disparities

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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