ArticleBioMed research international2021
Predicting Obesity Using Facial Pictures during COVID-19 Pandemic.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Validity of non-traditional measures of obesity compared to total body fat across the life course: A systematic review and meta-analysis.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025Pooled it
- Use of Deep Neural Networks to Predict Obesity With Short Audio Recordings: Development and Usability Study.JMIR AI · 2024Article
- Coordinate-wise monotonic transformations enable privacy-preserving age estimation with 3D face point cloud.Science China. Life sciences · 2024Article
- Association between the three-dimensional facial shape and its color in a boundary group of young to middle-aged Asian women.Heliyon · 2024Article
- Article
- Influence of the nutritional status on facial morphology in young Japanese women.Scientific reports · 2022Article
- Patient Perspectives of Inpatient Telemedicine During the COVID-19 Pandemic: Qualitative Assessment.JMIR formative research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSedentary lifestyle and work from home schedules due to the ongoing COVID-19 pandemic in 2020 have caused a significant rise in obesity across adults. With limited visits to the doctors during this period to avoid possible infections, there is currently no way to measure or track obesity.
methodsWe reviewed the literature on relationships between obesity and facial features, in white, black, hispanic-latino, and Korean populations and validated them against a cohort of Indian participants (
resultsLower facial geometry was highly correlated with BMI (
conclusionsThe ability to predict obesity using facial images through mobile application or telemedicine can help with early diagnosis and timely medical intervention for people with obesity during the pandemic.
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What OpenQuestion holds
Registered trials
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.