Sleep duration and cancer risk in women View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-07

AUTHORS

Susan Hurley, Debbie Goldberg, Leslie Bernstein, Peggy Reynolds

ABSTRACT

PURPOSE: The objective was to conduct an analysis of sleep duration and risk of selected site-specific and groups of cancer among a large prospective cohort of California women. METHODS: The study population was comprised of 101,609 adult females participating in the California Teachers Study. All sites of invasive cancer prospectively diagnosed from baseline (1995-1996) through 2011 were identified through linkage to the California Cancer Registry (n = 12,322). Site-specific analyses focused on the following cancers: breast (n = 5,053), colorectal (n = 983), lung (n = 820), melanoma (n = 749), and endometrial (n = 957). Additionally, we evaluated a group of estrogen-mediated cancers consisting of breast, endometrial, and ovarian cancer (n = 6,458). Sleep duration was based on self-report of average time sleeping in the year prior to baseline. Cox proportional hazard models were used to calculate adjusted hazard ratios and 95 % confidence intervals (HRs, 95 % CI). RESULTS: Point estimates for all sites and site-specific cancers generally were near or below one for short sleepers (<6 h/night) and above one for long sleepers (10+ h/night); confidence intervals, however, were wide and included unity. Compared to average sleepers (7-9 h/night), long sleepers had an increased risk of the group of estrogen-mediated cancers (HR 1.22, 95 % CI 0.97-1.54, p (trend) = 0.04). CONCLUSIONS: These analyses suggest that longer sleep may be associated with increased risks of estrogen-mediated cancers. Further studies with more refined measures of sleep duration and quality are warranted. More... »

PAGES

1037-1045

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10552-015-0579-3

DOI

http://dx.doi.org/10.1007/s10552-015-0579-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1011849327

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25924583


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10552-015-0579-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10552-015-0579-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10552-015-0579-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10552-015-0579-3'


 

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