dc.contributor.author |
Tingen, Candace |
|
dc.contributor.author |
Stanford, Joseph B |
|
dc.contributor.author |
Dunson, David B |
|
dc.coverage.spatial |
United States |
|
dc.date.accessioned |
2017-10-01T21:16:05Z |
|
dc.date.available |
2017-10-01T21:16:05Z |
|
dc.date.issued |
2004-01 |
|
dc.identifier |
https://www.ncbi.nlm.nih.gov/pubmed/14698936 |
|
dc.identifier.issn |
0091-6765 |
|
dc.identifier.uri |
https://hdl.handle.net/10161/15595 |
|
dc.description.abstract |
Although there has been growing concern about the effects of environmental exposures
on human fertility, standard epidemiologic study designs may not collect sufficient
data to identify subtle effects while properly adjusting for confounding. In particular,
results from conventional time to pregnancy studies can be driven by the many sources
of bias inherent in these studies. By prospectively collecting detailed records of
menstrual bleeding, occurrences of intercourse, and a marker of ovulation day in each
menstrual cycle, precise information on exposure effects can be obtained, adjusting
for many of the primary sources of bias. This article provides an overview of the
different types of study designs, focusing on the data required, the practical advantages
and disadvantages of each design, and the statistical methods required to take full
advantage of the available data. We conclude that detailed prospective studies allowing
inferences on day-specific probabilities of conception should be considered as the
gold standard for studying the effects of environmental exposures on fertility.
|
|
dc.language |
eng |
|
dc.publisher |
Environmental Health Perspectives |
|
dc.relation.ispartof |
Environ Health Perspect |
|
dc.subject |
Data Collection |
|
dc.subject |
Environmental Exposure |
|
dc.subject |
Epidemiologic Studies |
|
dc.subject |
Female |
|
dc.subject |
Fertility |
|
dc.subject |
Fertilization |
|
dc.subject |
Humans |
|
dc.subject |
Male |
|
dc.subject |
Menstruation |
|
dc.subject |
Ovulation |
|
dc.subject |
Prospective Studies |
|
dc.subject |
Research Design |
|
dc.title |
Methodologic and statistical approaches to studying human fertility and environmental
exposure.
|
|
dc.type |
Journal article |
|
duke.contributor.id |
Dunson, David B|0277221 |
|
pubs.author-url |
https://www.ncbi.nlm.nih.gov/pubmed/14698936 |
|
pubs.begin-page |
87 |
|
pubs.end-page |
93 |
|
pubs.issue |
1 |
|
pubs.organisational-group |
Duke |
|
pubs.organisational-group |
Duke Institute for Brain Sciences |
|
pubs.organisational-group |
Electrical and Computer Engineering |
|
pubs.organisational-group |
Institutes and Provost's Academic Units |
|
pubs.organisational-group |
Pratt School of Engineering |
|
pubs.organisational-group |
Statistical Science |
|
pubs.organisational-group |
Trinity College of Arts & Sciences |
|
pubs.organisational-group |
University Institutes and Centers |
|
pubs.publication-status |
Published |
|
pubs.volume |
112 |
|