Related Experiment Video
Updated: Nov 12, 2025
15:00
Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
Published on: February 3, 2023
2.8K
Weight Bias During the COVID-19 Pandemic
Rebecca L Pearl1,2, Erica M Schulte3
1Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA. rebecca.pearl@phhp.ufl.edu.
Current Obesity Reports
|March 19, 2021
Summary
The "quarantine-15" effect during COVID-19 is not well-supported by evidence. Weight bias and stigma during the pandemic require further research for public health consideration.
Area of Science:
- Public Health
- Psychology
- Sociology
Background:
- The COVID-19 pandemic introduced public health challenges and societal shifts.
- Concerns arose regarding potential weight gain and the impact of public messaging on body image and weight stigma.
Purpose of the Study:
- To review sources of weight bias and stigma during the COVID-19 pandemic.
- To examine the effects of weight bias on well-being amidst the pandemic.
- To identify gaps for future research on weight stigma and public health.
Main Methods:
- Literature review of studies on weight change during stay-at-home orders.
- Analysis of media and public health campaign content related to obesity.
- Examination of psychological impacts on individuals with a history of weight bias.
Main Results:
- Evidence for a widespread "quarantine-15" effect is weak, based on mixed findings and self-reported data.
- No studies have evaluated the health impacts of obesity-focused COVID-19 messaging.
- Individuals with prior weight bias experiences may face increased vulnerability to psychological distress and binge eating.
Conclusions:
- Weight bias and stigma during the COVID-19 pandemic warrant greater investigation.
- Public health efforts should consider the effects of weight stigma on health and well-being.
- Future research is needed to address the multifaceted impacts of weight bias in public health crises.
More Related Videos
09:03Nasal Brushing Sampling and Processing Using Digital High Speed Ciliary Videomicroscopy – Adaptation for the COVID-19 Pandemic
Published on: November 7, 2020
5.2K
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
14.9K
Related Concept Videos
01:29Bias in Epidemiological Studies
948
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
948
01:22Bias
6.6K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
6.6K
00:57Weighted Mean
6.0K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
6.0K
01:09Types of Skewness
15.2K
If the frequency distribution of a data set is more inclined towards smaller or larger values, the distribution is said to be skewed. If data values are skewed to the right, then the distribution is called positively skewed. Conversely, if the plot is skewed to the left, the distribution is called negatively skewed.
For instance, in the middle of a pandemic, the geographical distribution of vaccine coverage may be positively skewed towards populations in the global north countries. However,...
For instance, in the middle of a pandemic, the geographical distribution of vaccine coverage may be positively skewed towards populations in the global north countries. However,...
15.2K
01:27Confounding in Epidemiological Studies
356
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
356
01:52Regression Toward the Mean
6.6K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.6K