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Cited by 508

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Migraine prevalence by age and sex in the United States: A life-span study

Open access
Victor, TW, Hu, X, Campbell, JC, Buse, DC, Lipton, RB·2010·Cephalalgia

Abstract

The present study assessed age- and sex-specific patterns of migraine prevalence in a US population of 40,892 men, women, and children who participated in the 2003 National Health Interview Survey. Gaussian mixture models characterised the relationship between migraine, age, and sex. Migraine prevalence was 8.6% (males), 17.5% (females), and 13.2% (overall) and showed a bimodal distribution in both sexes (peaking in the late teens and 20s and around 50 years of age). Rate of change in migraine prevalence for both sexes increased the fastest from age 3 years to the mid-20s. Beyond the age of 10 years, females had a higher prevalence of migraine than males. The prevalence ratio for females versus males was highest during the female reproductive/child-bearing years, consistent with a relationship between menstruation and migraine. After age 42 years, the prevalence ratio was approximately 2-fold higher in women.

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Metadata

Authors
Victor, T., Hu, X., Campbell, J., Buse, D., & Lipton, R.
Venue
Cephalalgia
Published
2010-03-12
Volume
30
Issue
9
Pages
1065-1072
ISSN
  • 0333-1024 (ISSN-L)
  • 1468-2982
OpenAlex
W2067656815
Cited by
508
References
38
FWCI
11.96
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Migraine prevalence by age and sex in the United States: A life-span study. https://app.cochat.ai/papers/10.1177/0333102409355601
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Victor, T., Hu, X., Campbell, J., Buse, D., & Lipton, R. (2010). Migraine prevalence by age and sex in the United States: A life-span study. Cephalalgia. https://doi.org/10.1177/0333102409355601

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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.