Trial reportObesity (Silver Spring, Md.)2016
A randomized trial Examining The Impact Of Communicating Genetic And Lifestyle Risks For Obesity.
Trial report in Obesity (Silver Spring, Md.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01355224 (Communicating Genetic Information for Obesity), which is not on this 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.
Communicating Genetic Information for Obesity
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Are There Any Effective Behavior Change Strategies for Communicating Genetic Risk in Obesity Prevention and Body Weight Reduction Interventions?Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Pooled it
- Trial
- Polygenic prediction of body mass index and obesity through the life course and across ancestries.Nature medicine · 2025Article
- Ethical, legal, and social implications (ELSI) and challenges in the design of a randomized controlled trial to test the online return of cancer genetic research results to U.S. Black women.Contemporary clinical trials · 2023Article
- Proactive Assessment of Obesity Risk during Infancy (ProAsk): a qualitative study of parents' and professionals' perspectives on an mHealth intervention.BMC public health · 2019Article
- Learning one's genetic risk changes physiology independent of actual genetic risk.Nature human behaviour · 2019Article
- Recent Advances in Human Genetics and Epigenetics of Adiposity: Pathway to Precision Medicine?Gastroenterology · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
objectiveGenetic testing for obesity is available directly to consumers, yet little is understood about its behavioral impact and its added value to nongenetic risk communication efforts based on lifestyle factors.
methodsA randomized trial examined the short-term impact of providing personalized obesity risk information, using a 2 × 2 factorial design. Participants were recruited from the Coriell Personalized Medicine Collaborative (CPMC) and randomized to receive (1) no risk information (control), (2) genetic risk, (3) lifestyle risk, or (4) combined genetic/lifestyle risks. Baseline and 3-month follow-up survey data were collected. Analyses examined the impact of risk feedback on intentions to lose weight and self-reported weight.
resultsA total of 696 participants completed the study. A significant interaction effect was observed for genetic and lifestyle information on intent to lose weight (P = 0.0150). Those who received genetic risk alone had greater intentions at follow-up, compared with controls (P = 0.0034). The impact of receiving elevated risk information on intentions varied by source and combination of risks presented. Non-elevated genetic risk did not lower intentions. No group differences were observed for self-reported weight.
conclusionsGenetic risk information for obesity may add value to lifestyle risk information depending on the context in which it is presented.
Indexed as
Identifiers
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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.