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Sex/Gender Differences in Cardiovascular Disease Prevention: What a Difference a Decade Makes
Open accessAbstract
O ver the past decade, scientists, healthcare providers, the public, and policy makers have made substantial efforts to improve understanding of the sex/gender* differences in cardiovascular disease (CVD) † and to recognize the importance of heart disease in women.Federal and American Heart Association (AHA) initiatives to raise awareness and to reduce gender disparities in research and clinical care are listed in Table 1.There was a near doubling of the rate of awareness of heart disease as the leading cause of death in women between 1997, when the AHA launched its first campaign for women, and 2009; during that same period, the death rate resulting from CVD decreased by nearly half.[2][3][4] The extent to which efforts to close research gaps and to heighten awareness of heart disease in women are causally linked to lower CVD mortality or have resulted in improved clinical outcomes for women is not established.The purposes of this article are to evaluate contemporary sex/gender differences in the burden of CVD, to assess the impact of recent clinical trials on recommendations for the prevention of CVD in women, and to examine factors that may facilitate or impede quality CVD preventive care in women.Recommendations for the design and analyses of future CVD clinical trials in women are also provided.*Gender is referred to throughout this document as a person's self-representation as male or female or how that person is responded to in social situations on the basis of the individual's gender representation.Gender is shaped by environment and experience.Sex is the classification of female or male according to reproductive organs and functions assigned by chromosomal complement. 1 †Throughout this document, CVD is inclusive of coronary heart disease, stroke, and other atherosclerotic conditions except when national statistics are provided in which CVD encompasses International Classification of Diseases, 10th revision, codes 100 to 199.
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“Compared with our understanding of sex differences in coronary heart disease and stroke,168 substantial gaps exist in our knowledge of sex differences in AF (Table 1).”
From Atrial fibrillation in women: epidemiology, pathophysiology, presentation, and prognosis (2016) · cites this paper as [168]
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Metadata
- Authors
- Mosca, L., Barrett-Connor, E., & Kass Wenger, N.
- Affiliations
- Emory University (US)
- From the Columbia University Medical Center, New York, NY (L.M.); University of California San Diego School of Medicine, La Jolla (E.B.-C.); and Emory University School of Medicine, Atlanta, GA (N.K.W.).
- Venue
- Circulation
- Published
- 2011-11-08
- Volume
- 124
- Issue
- 19
- Pages
- 2145-2154
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- PMC
- PMC3362050
- OpenAlex
- W2155311570
- Cited by
- 1,045
- References
- 91
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- FWCI
- 22.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Circulation (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Heart, Lung, and Blood Institute (K24HL076346, K24 2HL076346-06)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Sex and Gender in Healthcare
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Menopause: Health Impacts and Treatments
- Keywords
- sex differences, gender differences, cardiovascular disease prevention, heart disease in women, cardiovascular mortality, gender disparities in research
- MeSH terms
- Adult, Aged, Cardiology, Coronary Disease, Female, Health Policy, Humans, Male, Middle Aged, Mortality, Risk Factors, Sex Characteristics, Prevalence, Women's Health, Risk Reduction Behavior
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 ›
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