Obesity and responsibility: Is it time to rethink agency?

Obes Rev

Diabetes Complications Research Centre, Conway Institute, University College Dublin, Dublin, Ireland.

Published: August 2021

Despite obesity declared a disease, there still exists considerable weight stigma in both popular culture and health care, which negatively impacts policy making regarding prevention and treatment. While viewed as a choice or a failure of willpower by many, evidence exists to challenge the argument that both weight gain and failure to achieve weight loss maintenance are the individuals' fault due to personal failure or lack of responsibility. In this article, we draw upon literature from obesity treatment, neuroscience, philosophy of mind, and weight stigma to challenge the commonly held beliefs that individuals are free to choose how much they can weigh, and achievement of long-term weight loss maintenance is completely subject to conscious choice. In reality, the regulation of hunger, satiety, energy balance, and body weight takes place in subcortical regions of the brain. Thus, hunger and satiety signals are generated in regions of the brain, which are not associated with conscious experience. This points towards biological determinism of weight and challenges ideas of willpower and resultant moralization regarding body weight regulation. In this article, we will thus argue that in the context of dysregulation of hunger and satiety contributing to the obesity epidemic, a wider discourse related to personal responsibility and the stigma of obesity is needed to enhance understanding, prevention, and treatment of this complex disease. Obesity is a chronic disease requiring personalized treatment. Lifestyle interventions alone may not be enough to achieve medically significant and sustained weight loss for many individuals with obesity. By understanding that obesity is not due to a lack of motivation or willpower, the availability and utilization of additional treatments or combination of treatments such as lifestyle, pharmacotherapy, and surgery are likely to improve the quality of life for many suffering with this disease.

Download full-text PDF

Source
http://dx.doi.org/10.1111/obr.13270DOI Listing

Publication Analysis

Top Keywords

weight loss
12
hunger satiety
12
weight
9
obesity
8
weight stigma
8
prevention treatment
8
loss maintenance
8
body weight
8
regions brain
8
obesity responsibility
4

Similar Publications

For patients considering bariatric surgery, it is essential to have clear answers to common questions to ensure the success of the procedure. Patients should understand that surgery is not a quick fix but a tool that must be complemented by lifestyle changes, including dietary adjustments and regular physical activity. The procedure carries potential risks that should be weighed against the potential benefits.

View Article and Find Full Text PDF

In the current investigation, the efficiency inhibition of two newly synthesized bi-pyrazole derivatives, namely 2,3-bis[(bis((1 H-pyrazol-1-yl) methyl) amino)] pyridine (Tetra-Pz-Ortho) and 1,4-bis[(bis((1 H-pyrazol-1-yl) methyl) amino)] benzene (Tetra-Pz-Para) for corrosion of carbon steel (C&S) in 1 M HCl medium was evaluated. A Comparative study of inhibitor effect of Tetra-Pz-Ortho and Tetra-Pz-Para was conducted first using weight loss method and EIS (Electrochemical Impedance Spectroscopy) and PDP (Potentiodynamic Polarisation) techniques. Tetra-Pz-Ortho and Tetra-Pz-Para had a maximum inhibition efficacy of 97.

View Article and Find Full Text PDF

Loss-of-function mutations induced by CRISPR-Cas9 in the TaGS3 gene homoeologs show non-additive dosage-dependent effects on grain size and weight and have potential utility for increasing grain yield in wheat. The grain size in cereals is one of the component traits contributing to yield. Previous studies showed that loss-of-function (LOF) mutations in GS3, encoding Gγ subunit of the multimeric G protein complex, increase grain size and weight in rice.

View Article and Find Full Text PDF

Remote sensing images often suffer from the degradation effects of atmospheric haze, which can significantly impair the quality and utility of the acquired data. A novel dehazing method leveraging generative adversarial networks is proposed to address this challenge. It integrates a generator network, designed to enhance the clarity and detail of hazy images, with a discriminator network that distinguishes between dehazed and real clear images.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!