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Cited by 228

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Can Noncommunicable Diseases Be Prevented? Lessons from Studies of Populations and Individuals

Open access
Ezzati, Majid, Riboli, Elio·2012·Science

Abstract

Noncommunicable diseases (NCDs)—mainly cancers, cardiovascular diseases, diabetes, and chronic respiratory diseases—are responsible for about two-thirds of deaths worldwide, mostly in low- and middle-income countries. There is an urgent need for policies and strategies that prevent NCDs by reducing their major risk factors. Effective approaches for large-scale NCD prevention include comprehensive tobacco and alcohol control through taxes and regulation of sales and advertising; reducing dietary salt, unhealthy fats, and sugars through regulation and well-designed public education; increasing the consumption of fresh fruits and vegetables, healthy fats, and whole grains by lowering prices and improving availability; and implementing a universal, effective, and equitable primary-care system that reduces NCD risk factors, including cardiometabolic risk factors and infections that are precursors to NCDs, through clinical interventions.

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Registry

Crossref · 10.1126/science.1227001

Cites

27 of 27 references verified0 citation errors · 0 not checkable

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Citations

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Metadata

Authors
Ezzati, M., & Riboli, E.
Venue
Science
Published
2012-09-21
Volume
337
Issue
6101
Pages
1482-1487
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W1976784452
Cited by
228
References
27
FWCI
59.07
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Can Noncommunicable Diseases Be Prevented? Lessons from Studies of Populations and Individuals. https://app.cochat.ai/papers/10.1126/science.1227001
The paper
Ezzati, M., & Riboli, E. (2012). Can Noncommunicable Diseases Be Prevented? Lessons from Studies of Populations and Individuals. Science. https://doi.org/10.1126/science.1227001

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.