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Cited by 623

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Intelligence Predicts Health and Longevity, but Why?

Gottfredson, Linda S., Deary, Ian J.·2004·Current Directions in Psychological Science

Abstract

Large epidemiological studies of almost an entire population in Scotland have found that intelligence (as measured by an IQ-type test) in childhood predicts substantial differences in adult morbidity and mortality, including deaths from cancers and cardiovascular diseases. These relations remain significant after controlling for socioeconomic variables. One possible, partial explanation of these results is that intelligence enhances individuals' care of their own health because it represents learning, reasoning, and problem-solving skills useful in preventing chronic disease and accidental injury and in adhering to complex treatment regimens.

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Research works printed but not linked: 2

  1. Gottfredson L.S, 1998, Scientific American Presents, 9, 24
  2. Gottfredson L.S., Journal of Personality and Social Psychology

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Metadata

Authors
Gottfredson, L. S., & Deary, I. J.
Venue
Current Directions in Psychological Science
Published
2004-02
Volume
13
Issue
1
Pages
1-4
ISSN
  • 0963-7214 (ISSN-L)
  • 1467-8721
OpenAlex
W2140125999
Cited by
623
References
21
FWCI
24.15
Type
journal article
Language
en
Open access
closed
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)

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CoChat. (2026). Citation check: Intelligence Predicts Health and Longevity, but Why? https://app.cochat.ai/papers/10.1111/j.0963-7214.2004.01301001.x
The paper
Gottfredson, L. S., & Deary, I. J. (2004). Intelligence Predicts Health and Longevity, but Why? Current Directions in Psychological Science. https://doi.org/10.1111/j.0963-7214.2004.01301001.x

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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.