ArticleJournal of general internal medicine2014
A cross-sectional study examining Australian general practitioners' identification of overweight and obese patients.
Article in Journal of general internal medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Enablers and barriers to implementing obesity assessments in clinical practice: a rapid mixed-methods systematic review.BMJ open · 2022Pooled it
- A randomised trial assessing the acceptability and effectiveness of providing generic versus tailored feedback about health risks for a high need primary care sample.BMC family practice · 2015Trial
- Registration and management of children with overweight by general practitioners in The Netherlands.The European journal of general practice · 2024Article
- Article
- Determinants and extent of weight recording in UK primary care: an analysis of 5 million adults' electronic health records from 2000 to 2017.BMC medicine · 2019Article
- Health advice and education given to overweight patients by primary care doctors and nurses: A scoping literature review.Preventive medicine reports · 2019Article
- Recording of weight in electronic health records: an observational study in general practice.BMC family practice · 2018Observational
- Increasing advance personal planning: the need for action at the community level.BMC public health · 2018Article
- Visual body size norms and the under-detection of overweight and obesity.Obesity science & practice · 2018Article
- Overweight but unseen: a review of the underestimation of weight status and a visual normalization theory.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2017Review
- Why Australia needs to define obesity as a chronic condition.BMC public health · 2017Article
- Visual perceptions of male obesity: a cross-cultural study examining male and female lay perceptions of obesity in Caucasian males.BMC public health · 2015Article
- Missed opportunities: general practitioner identification of their patients' smoking status.BMC family practice · 2015Article
- Capsule commentary on Yoong et al., a cross-sectional study examining Australian general practitioners' identification of overweight and obese patients.Journal of general internal medicine · 2014Article
Corrections and comments
- Commented on by
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOverweight and obese patients attempt weight loss when advised to do so by their physicians; however, only a small proportion of these patients report receiving such advice. One reason may be that physicians do not identify their overweight and obese patients.
objectivesWe aimed to determine the extent that Australian general practitioners (GP) recognise overweight or obesity in their patients, and to explore patient and GP characteristics associated with non-detection of overweight and obesity.
methodsConsenting adult patients (n = 1,111) reported weight, height, demographics and health conditions using a touchscreen computer. GPs (n = 51) completed hard-copy questionnaires indicating whether their patients were overweight or obese. We calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for GP detection, using patient self-reported weight and height as the criterion measure for overweight and obesity. For a subsample of patients (n = 107), we did a sensitivity analysis with patient-measured weight and height. We conducted an adjusted, multivariable logistic regression to explore characteristics associated with non-detection, using random effects to adjust for correlation within GPs.
resultsSensitivity for GP assessment was 63 % [95 % CI 57-69 %], specificity 89 % [95 % CI 85-92 %], PPV 87 % [95 % CI 83-90 %] and NPV 69 % [95 % CI 65-72 %]. Sensitivity increased by 3 % and specificity was unchanged in the sensitivity analysis. Men (OR: 1.7 [95 % CI 1.1-2.7]), patients without high blood pressure (OR: 1.8 [95 % CI 1.2-2.8]) and without type 2 diabetes (OR: 2.4 [95 % CI 1.2-8.0]) had higher odds of non-detection. Individuals with obesity (OR: 0.1 [95 % CI 0.07-0.2]) or diploma-level education (OR: 0.3 [95%CI 0.1-0.6]) had lower odds of not being identified. No GP characteristics were associated with non-detection of overweight or obesity.
conclusionsGPs missed identifying a substantial proportion of overweight and obese patients. Strategies to support GPs in identifying their overweight or obese patients need to be implemented.
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.