| pubmed-article:19037217 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:19037217 | lifeskim:mentions | umls-concept:C0086418 | lld:lifeskim |
| pubmed-article:19037217 | lifeskim:mentions | umls-concept:C0028754 | lld:lifeskim |
| pubmed-article:19037217 | lifeskim:mentions | umls-concept:C0035171 | lld:lifeskim |
| pubmed-article:19037217 | lifeskim:mentions | umls-concept:C1704675 | lld:lifeskim |
| pubmed-article:19037217 | lifeskim:mentions | umls-concept:C0002783 | lld:lifeskim |
| pubmed-article:19037217 | lifeskim:mentions | umls-concept:C0449255 | lld:lifeskim |
| pubmed-article:19037217 | pubmed:dateCreated | 2008-11-27 | lld:pubmed |
| pubmed-article:19037217 | pubmed:abstractText | The epidemiology of obesity suggests that, for the majority of individuals, the disorder arises from an interaction between genetic predisposition and lifestyle behaviors such as dietary intake and physical activity. Unravelling the molecular basis of such interactions is complex but is becoming a realistic proposition as evidence emerges from whole genome association studies of genetic variants that are definitively associated with obesity. A range of possible study designs is available for investigating gene-lifestyle interaction, and the strengths and weaknesses of each approach are discussed in this article. Given the likely small main effect of common genetic variants and the difficulties in demonstrating associations of lifestyle factors with future risk of obesity, we would favor an analytical approach based on the clear specification of prior probabilities to reduce the likelihood of false discovery. Mixed approaches combining data from large-scale observational studies with smaller intervention trials may be ideal. In designing new studies to investigate these issues, a key choice is how precisely to quantify the important, but difficult to measure lifestyle behaviors. It is clear from power calculations that an approach based on enhancing precision of measurement of diet and physical activity is critical. | lld:pubmed |
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| pubmed-article:19037217 | pubmed:language | eng | lld:pubmed |
| pubmed-article:19037217 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:19037217 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:19037217 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:19037217 | pubmed:month | Dec | lld:pubmed |
| pubmed-article:19037217 | pubmed:issn | 1930-7381 | lld:pubmed |
| pubmed-article:19037217 | pubmed:author | pubmed-author:WarehamNichol... | lld:pubmed |
| pubmed-article:19037217 | pubmed:author | pubmed-author:LoosRuth J... | lld:pubmed |
| pubmed-article:19037217 | pubmed:author | pubmed-author:YoungElizabet... | lld:pubmed |
| pubmed-article:19037217 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:19037217 | pubmed:volume | 16 Suppl 3 | lld:pubmed |
| pubmed-article:19037217 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:19037217 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:19037217 | pubmed:pagination | S66-71 | lld:pubmed |
| pubmed-article:19037217 | pubmed:dateRevised | 2011-9-26 | lld:pubmed |
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| pubmed-article:19037217 | pubmed:meshHeading | pubmed-meshheading:19037217... | lld:pubmed |
| pubmed-article:19037217 | pubmed:year | 2008 | lld:pubmed |
| pubmed-article:19037217 | pubmed:articleTitle | Epidemiological study designs to investigate gene-behavior interactions in the context of human obesity. | lld:pubmed |
| pubmed-article:19037217 | pubmed:affiliation | Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK. nick.wareham@mrc-epic.cam.ac.uk | lld:pubmed |
| pubmed-article:19037217 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:19037217 | pubmed:publicationType | Review | lld:pubmed |
| pubmed-article:19037217 | pubmed:publicationType | Research Support, N.I.H., Extramural | lld:pubmed |
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