ArticleHeliyon2024
A nomogram and online calculator for predicting depression risk in obese Americans.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Article
- Development and validation of a nomogram for predicting depression risk in patients with chronic kidney disease based on NHANES 2005-2018.Journal of health, population, and nutrition · 2025Article
- Construction and Validation of a Major Depression Risk Predictive Model for Patients with Coronary Heart Disease: Insights from NHANES 2005-2018.Reviews in cardiovascular medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Obese patients with depression face higher risks of adverse events. However, depression is often misdiagnosed and undertreated in this group. This study aimed to identify predictors of depression and create a nomogram and calculator to assess depression risk in obese Americans. Methods: This cross-sectional study included 2674 patients from the National Health and Nutrition Examination Survey database (NHANES). These participants were randomly classified into the training and validation groups in a 7:3 ratio. Predictors were selected by LASSO and multivariate logistic regression analysis to create the nomogram. C-statistics, calibration plots, and decision curve analysis (DCA) were used to test the nomogram's discriminative ability, calibration quality, and clinical value. Internal validation with bootstrap resampling and external validation with the validation group were also conducted. Results: The training and validation group consists of 1871 and 803 participants. Depression was presented in 11.4 % (203/2674) of these participants. Seven predictors were found, including gender, hypertension, weekday sleep duration, poverty to income ratio, history of seeing mental health doctor, diabetes, and feeling sleepy during the day. The nomogram showed good discrimination, with the area under the receiver operating characteristic curve (AUC) of 0.817 (95 % CI: 0.786-0.848) (0.806 through internal validation and 0.772 through external validation) and good calibration (P = 0.536). The DCA further confirmed the nomogram's clinical usefulness. Conclusion: The nomogram and calculator effectively predict depression risk in obese Americans and can be used as auxiliary tools for early screening in primary care.
Indexed as
Identifiers
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.