Evidence map›Paper›PMID 41777813›Full record

ArticleObesity pillars2026

The burden of bias: Patient experiences and providers' perspectives on weight bias.

Stephanie L Albert, Lorraine Kwok, Rachel Massar, Michelle McMacken, Héctor E Alcalá, Robin Ortiz

Abstract read
In one paragraph

Article in Obesity pillars, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Stephanie L AlbertDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.
Lorraine KwokDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.
Rachel MassarDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA.
Michelle McMackenDepartment of Medicine, NYU Grossman School of Medicine, 550 1st Avenue, New York, NY, 10016, USA.
Héctor E AlcaláDepartment of Community and Behavioral Health, University of Maryland, School of Public Health, 4200 Valley Dr Room 1234, College Park, MD, 20742, USA.
Robin OrtizDepartments of Population Health and Pediatrics, Institute for Excellence of Health Equity, 180 Madison Avenue, New York, NY, 10016, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Weight bias is pervasive, occurs in a variety of contexts, and is associated with a range of suboptimal outcomes, including delays or avoidance in seeking health care, misdiagnosis, and denial of services. The aim of this study was to quantitatively describe the relationship between experiences of weight bias and eating behaviors of patients in a lifestyle medicine program and qualitatively describe healthcare providers' insights about weight bias. Methods: This study utilized an explanatory sequential design that drew on one-time survey data collected from 109 patients of a Plant-Based Lifestyle Medicine (PBLM) Program in New York City in 2019. Ordinary Least Squares and logistic regression models examined the association between weight bias and healthful plant-based eating and emotional eating after adjusting for sociodemographic characteristics. Qualitative data come from asynchronous interviews with five healthcare providers from the PBLM program completed in 2024 which were analyzed using rapid coding. Results: Survey participants were on average 53 years old, 67.0% female, 68.6% Black, Indigenous, and other people of color (BIPOC), and 56.2% reported experiencing weight bias. Weight bias was associated with 4.07 fewer points on the healthful plant-based eating measure (95%CI: 6.86, -1.27), and participants had 5.06 times the odds (95%CI: 1.76, 14.59) of emotional eating compared to those not reporting weight bias. Interview themes were: (1) Weight bias negatively influences patient lives, (2) Weight bias is negatively associated with patients' mental health, (3) Promising weight-inclusive approaches, and (4) Recommendations for providers to address weight bias. Conclusion: Experiences of weight bias were associated with suboptimal eating behaviors and poor mental health. Providers observed their patients experience harm in connection with weight bias, suggested weight-inclusive approaches, and identified recommendations that would mitigate weight bias in healthcare environments including routinely screening for weight bias, training providers on weight inclusive care, incorporating mental health services into care teams, and creating size inclusive spaces. This study demonstrates that weight bias is linked to deleterious outcomes and the importance of weight-inclusive care delivery and environments.

Indexed as

Eating behaviorsLifestyle medicineWeight biasWeight-inclusive careWeight stigma

Identifiers

PMID41777813
PMCPMC12950446

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.