Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 258

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Is infection risk linked to exercise workload?

NIEMAN, DAVID C.·2000·Medicine & Science in Sports & Exercise

Abstract

Anecdotal, survey, and epidemiological data suggest that endurance athletes are at an increased risk for upper respiratory tract infection (URTI) during periods of heavy training and the 1 - to 2-wk period after race events. The majority of athletes, however, who participate in endurance race events do not experience illness. Of greater public health importance is the consistent finding of a reduction in URTI risk reported by fitness enthusiasts and athletes who engage in regular exercise training while avoiding overreaching/overtraining. Although it naturally follows that infection risk should in some way be linked to acute and chronic exercise-induced alterations in immunity, attempts thus far to measure this association have been unsuccessful. There is growing evidence that for several hours subsequent to heavy exertion, several components of both the innate and adaptive immune system exhibit suppressed function. The immune response to heavy exertion is transient, however, and further research on the mechanisms underlying the immune response to prolonged and intensive endurance exercise is necessary before meaningful clinical applications can be drawn. Some attempts have been made through chemical or nutritional means (e.g., indomethacin, glutamine, vitamin C, and carbohydrate supplementation) to attenuate immune changes after intensive exercise to lower the risk of infection. No consistent relationship between nutritional interventions, exercise immunology, and alteration in URTI risk has yet been established.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1097/00005768-200007001-00005

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 258

Metadata

Authors
NIEMAN, D. C.
Venue
Medicine & Science in Sports & Exercise
Published
2000-07
Volume
32
Issue
Supplement
Pages
S406-S411
ISSN
0195-9131 (ISSN-L)
OpenAlex
W2020700357
Cited by
258
References
5
FWCI
7.24
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.