Dataset Information

An illustration of and programs estimating attributable fractions in large scale surveys considering multiple risk factors.

ABSTRACT: BACKGROUND: Attributable fractions (AF) assess the proportion of cases in a population attributable to certain risk factors but are infrequently reported and mostly calculated without considering potential confounders. While logistic regression for adjusted individual estimates of odds ratios (OR) is widely used, similar approaches for AFs are rarely applied. METHODS: Different methods for calculating adjusted AFs to risk factors of cardiovascular disease (CVD) were applied using data from the National Health and Nutrition Examination Survey (NHANES). We compared AFs from the unadjusted approach using Levin's formula, from Levin's formula using adjusted OR estimates, from logistic regression according to Bruzzi's approach, from logistic regression with sequential removal of risk factors ('sequential AF') and from logistic regression with all possible removal sequences and subsequent averaging ('average AF'). RESULTS: AFs following the unadjusted and adjusted (using adjusted ORs) Levin's approach yielded clearly higher estimates with a total sum of more than 100% compared to adjusted approaches with sums < 100%. Since AFs from logistic regression were related to the removal sequence of risk factors, all possible sequences were considered and estimates were averaged. These average AFs yielded plausible estimates of the population impact of considered risk factors on CVD with a total sum of 90%. The average AFs for total and HDL cholesterol levels were 17%, for hypertension 16%, for smoking 11%, and for diabetes 5%. CONCLUSION: Average AFs provide plausible estimates of population attributable risks and should therefore be reported at least to supplement unadjusted estimates. We provide functions/macros for commonly used statistical programs to encourage other researchers to calculate and report average AFs.

SUBMITTER: Ruckinger S

PROVIDER: S-EPMC2636839 | biostudies-other | 2009

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

An illustration of and programs estimating attributable fractions in large scale surveys considering multiple risk factors.

Rückinger Simon S von Kries Rüdiger R Toschke André Michael AM

BMC medical research methodology 20090123

<h4>Background</h4>Attributable fractions (AF) assess the proportion of cases in a population attributable to certain risk factors but are infrequently reported and mostly calculated without considering potential confounders. While logistic regression for adjusted individual estimates of odds ratios (OR) is widely used, similar approaches for AFs are rarely applied.<h4>Methods</h4>Different methods for calculating adjusted AFs to risk factors of cardiovascular disease (CVD) were applied using da ...[more]

PMID: 19166593

Similar Datasets

Project description:BackgroundIn recent years, national and global mortality data have been characterized in terms of well-established risk factors. In this regard, alcohol consumption has been called the third leading "actual cause of death" (modifiable behavioral risk factor) in the United States, after tobacco use and the combination of poor diet and physical inactivity. Globally and in various regions of the world, alcohol use has been established as a leading contributor to the overall burden of disease and as a major determinant of health disparities, but, to our knowledge, no one has characterized alcohol-related harm in such broad terms at the local level. We asked how alcohol-related premature mortality in San Francisco, measured in years of life lost (YLLs), compares with other well-known causes of premature mortality, such as ischemic heart disease or HIV/AIDS.MethodsWe applied sex- and cause-specific population-attributable fractions (PAFs) of years of life lost (YLLs) from the Global Burden of Disease Study to 17 comparable outcomes among San Francisco males and females during 2004-2007. We did this in three ways: Method 1 assumed that all San Franciscans drink like populations in developed economies. These estimates were limited to alcohol-related harm. Method 2 modified these estimates by including several beneficial effects. Method 3 assumed that Latino and Asian San Franciscans drink alcohol like populations in the global regions related to their ethnicity.ResultsBy any of these three methods, alcohol-related premature mortality accounts for roughly a tenth of all YLLs among males. Alcohol-related YLLs among males are comparable to YLLs for leading causes such as ischemic heart disease and HIV/AIDS, in some instances exceeding them. Latino and black males bear a disproportionate burden of harm. Among females, for whom estimates differed more by method and were smaller than those for males, alcohol-related YLLs are comparable to leading causes which rank somewhere between fifth and fourteenth.ConclusionsAlcohol consumption is a major contributor to premature mortality in San Francisco, especially among males. Interventions to avert alcohol-related harm in San Francisco should be taken at the population level and deserve the same attention that is given to other major risk factors, such as smoking or obesity.

Project description:ImportanceThe extent to which uveal melanoma is cured by ocular therapy is not known.ObjectiveTo estimate cured fractions (CF) of uveal melanoma using combination of institutional and Surveillance, Epidemiology, and End Results (SEER) data.Design, setting, and participantsIntegrative analysis of 42 years of SEER data (1975-2016) with 25 years (1993-2018) of complementary institutional data. The analysis included SEER US patients and molecularly prognosticated patients in the United States and Europe. Three SEER databases (SEER-9, SEER-13, and SEER-18) were merged. A total of 10 678 SEER cases of uveal melanoma diagnosed from 1975 to 2016 using International Classification of Disease for Oncology morphology codes 8720-8790 (for melanoma) and site codes C69.2-4 (for choroid, ciliary body, and iris) were downloaded April 16, 2019. The institutional data included 5 institutional cohorts of 788 molecularly prognosticated patients (diagnosed prior to July 2019) with 3115 person-years at risk of death and 262 observed deaths.Main outcomes and measuresExcess absolute risks of death (EAR) and cured fraction (CF) indicates lifetime area under the EAR curve. These are applied to populations and subpopulations.ResultsThe SEER EAR, with sexes and races pooled, can be modeled as a sum of 2 waves. The first wave peaks at approximately 3 years and is negligible by 15 years, at which time the second wave peaks. Institutional data suggest that the first wave is owing to BAP1 mutant cases (204 of 355 [57.5%]; 95% CI, 52%-63%) and that the second wave is owing to BAP1 wild-type SF3B1 mutant cases (60 of 355 [17%]; 95% CI, 13%-21%). There is also a third group with a low flat EAR time course (91 of 355 [25.5%]; 95% CI, 21%-30%). The overall statistical CF of 60% is reached by approximately 25 years.Conclusions and relevanceThese findings suggest that the benefits of ocular therapy for curing uveal melanoma may be questionable because statistical cures reflect deaths of poor prognosis cases and survival of good prognosis cases. Changes in uveal melanoma patient management may be needed to improve survival.

Dataset Information

An illustration of and programs estimating attributable fractions in large scale surveys considering multiple risk factors.

Publications

An illustration of and programs estimating attributable fractions in large scale surveys considering multiple risk factors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets