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The Västerbotten Intervention Programme: background, design and implications
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BACKGROUND AND OBJECTIVE: In Sweden, mortality from cardiovascular diseases (CVD) increased steadily during the 20th century and in the mid-1980s it was highest in the county of Västerbotten. Therefore, a community intervention programme was launched - the Västerbotten Intervention Programme (VIP) - with the aim of reducing morbidity and mortality from CVD and diabetes. DESIGN: The VIP was first developed in the small municipality of Norsjö in 1985. Subsequently, it was successively implemented across the county and is now integrated into ordinary primary care routines. A population-based strategy directed towards the public is combined with a strategy to reach all middle-aged persons individually at ages 40, 50 and 60 years, by inviting them to participate in systematic risk factor screening and individual counselling about healthy lifestyle habits. Blood samples for research purposes are stored at the Umeå University Medical Biobank. RESULTS: Overall, 113,203 health examinations have been conducted in the VIP and 6,500-7,000 examinations take place each year. Almost 27,000 subjects have participated twice. Participation rates have ranged between 48 and 67%. A dropout rate analysis in 1998 indicated only a small social selection bias. Cross-sectional, nested case-control studies and prospective studies have been based on the VIP data. Linkages between the VIP and local, regional and national databases provide opportunities for interdisciplinary research, as well as national and international collaborations on a wide range of disease outcomes. A large number of publications are based on data that are collected in the VIP, many of which also use results from analysed stored blood samples. More than 20 PhD theses have been based primarily on the VIP data. CONCLUSIONS: The concept of the VIP, established as a collaboration between politicians and health care providers on the one hand and primary care, functioning as the operating machinery, and the public on the other, forms the basis for effective implementation and endurance over time. After more than 20 years of the VIP, there is a large comprehensive population-based database, a stable organisation to conduct health surveys and collect data, and a solid structure to enable widespread multidisciplinary and scientific collaborations.
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Metadata
- Authors
- Norberg, M., Wall, S., Boman, K., & Weinehall, L.
- Affiliations
- Umeå University (SE)
- Skellefteå Hospital (SE)
- Corresponding author
- Norberg, Margareta
- Venue
- Global Health Action
- Publisher
- Informa UK Limited
- Published
- 2010-03-22
- Volume
- 3
- Issue
- 1
- ISSN
- 1654-9716 (ISSN-L)
- 1654-9880
- PMC
- PMC2844807
- OpenAlex
- W2138185074
- Cited by
- 373
- References
- 70
- Citations by year
- 2026: 24 · 2025: 22 · 2024: 37 · 2023: 26 · 2022: 26 · 2021: 36 · 2020: 27 · 2019: 26 · 2018: 29 · 2017: 23 · 2016: 16 · 2015: 10 · 2014: 12 · 2013: 16 · 2012: 17
- FWCI
- 18.13
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Global Health Action (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DiVA at Umeå University (Umeå University) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Epidemiology › Healthcare Systems and Public Health
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- Västerbotten Intervention Programme, cardiovascular disease prevention, diabetes prevention, community-based intervention, risk factor screening, primary care integration, biobanks, multidisciplinary research collaboration
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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.
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