Literature DB >> 3940433

Estimating the impact of risk factor modification programs.

W S Browner.   

Abstract

Most studies of the etiology and prevention of disease do not adequately address the quantitative implications of their findings for the population. This report presents a method of combining observational and experimental data to estimate the overall impact of a risk factor modification program. After the terminology is introduced, the model is applied to a categoric risk factor (serum cholesterol) for coronary heart disease, with data from the Pooling Project (1964-1974) and the Lipid Research Clinics studies (1972-1983). With optimistic assumptions about the impact of cholestyramine treatment at various cholesterol levels, about 5% of the cases of coronary heart disease in middle-aged men in the United States could be prevented; more realistic assumptions reduce that estimate by more than half. The model emphasizes the importance of estimating and comparing the overall impact of available risk factor modification programs when planning public health strategies.

Entities:  

Mesh:

Substances:

Year:  1986        PMID: 3940433     DOI: 10.1093/oxfordjournals.aje.a114208

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  7 in total

Review 1.  Choosing quality of care measures based on the expected impact of improved care on health.

Authors:  A L Siu; E A McGlynn; H Morgenstern; M H Beers; D M Carlisle; E B Keeler; J Beloff; K Curtin; J Leaning; B C Perry
Journal:  Health Serv Res       Date:  1992-12       Impact factor: 3.402

2.  Standards, guidelines and clinical policies. Health Services Research Group.

Authors: 
Journal:  CMAJ       Date:  1992-03-15       Impact factor: 8.262

3.  Quantifying the expected vs potential impact of a risk-factor intervention program.

Authors:  M Bulterys; H Morgenstern; D L Weed
Journal:  Am J Public Health       Date:  1997-05       Impact factor: 9.308

4.  From exposures to population interventions: pregnancy and response to HIV therapy.

Authors:  Daniel Westreich
Journal:  Am J Epidemiol       Date:  2014-02-25       Impact factor: 4.897

5.  Sample size and power based on the population attributable fraction.

Authors:  W S Browner; T B Newman
Journal:  Am J Public Health       Date:  1989-09       Impact factor: 9.308

6.  Physician management of hypercholesterolemia. A randomized trial of continuing medical education.

Authors:  W S Browner; R B Baron; S Solkowitz; L J Adler; D S Gullion
Journal:  West J Med       Date:  1994-12

Review 7.  From Patients to Policy: Population Intervention Effects in Epidemiology.

Authors:  Daniel Westreich
Journal:  Epidemiology       Date:  2017-07       Impact factor: 4.822

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.