Attributable risk percent

About: Attributable risk percent is a research topic. Over the lifetime, 100 publications have been published within this topic receiving 18566 citations.

Prediction of Coronary Heart Disease Using Risk Factor Categories

Abstract: Background—The objective of this study was to examine the association of Joint National Committee (JNC-V) blood pressure and National Cholesterol Education Program (NCEP) cholesterol categories with coronary heart disease (CHD) risk, to incorporate them into coronary prediction algorithms, and to compare the discrimination properties of this approach with other noncategorical prediction functions. Methods and Results—This work was designed as a prospective, single-center study in the setting of a community-based cohort. The patients were 2489 men and 2856 women 30 to 74 years old at baseline with 12 years of follow-up. During the 12 years of follow-up, a total of 383 men and 227 women developed CHD, which was significantly associated with categories of blood pressure, total cholesterol, LDL cholesterol, and HDL cholesterol (all P,.001). Sex-specific prediction equations were formulated to predict CHD risk according to age, diabetes, smoking, JNC-V blood pressure categories, and NCEP total cholesterol and LDL cholesterol categories. The accuracy of this categorical approach was found to be comparable to CHD prediction when the continuous variables themselves were used. After adjustment for other factors, ’28% of CHD events in men and 29% in women were attributable to blood pressure levels that exceeded high normal ($130/85). The corresponding multivariable-adjusted attributable risk percent associated with elevated total cholesterol ($200 mg/dL) was 27% in men and 34% in women. Conclusions—Recommended guidelines of blood pressure, total cholesterol, and LDL cholesterol effectively predict CHD risk in a middle-aged white population sample. A simple coronary disease prediction algorithm was developed using categorical variables, which allows physicians to predict multivariate CHD risk in patients without overt CHD. (Circulation. 1998;97:1837-1847.)

Use and misuse of population attributable fractions.

Abstract: How much of the disease burden in a population could be eliminated if the effects of certain causal factors were eliminated from the population? To address this question, epidemiologists calculate the population attributable fraction. As noted in a recent editorial in the Journal, population attributable fraction estimates can help guide policymakers in planning public health interventions.' Despite numerous articles on population attributable fraction estimation, 2-7 errors in computation and interpretation persist. In addition, in certain settings, the value of a population attributable fraction estimate may be questionable. This commentary considers computational and conceptual issues relevant to population attributable fraction estimation that are infrequently discussed elsewhere, with illustrations from the breast cancer literature.

Thyroid Cancer after Exposure to External Radiation: A Pooled Analysis of Seven Studies

Abstract: The thyroid gland of children is especially vulnerable to the carcinogenic action of ionizing radiation. To provide insights into various modifying influences on risk, seven major studies with organ doses to individual subjects were evaluated. Five cohort studies (atomic bomb survivors, children treated for tinea capitis, two studies of children irradiated for enlarged tonsils, and infants irradiated for an enlarged thymus gland) and two case-control studies (patients with cervical cancer and childhood cancer) were studied. The combined studies include almost 120,000 people (approximately 58,000 exposed to a wide range of doses and 61,000 nonexposed subjects), nearly 700 thyroid cancers and 3,000,000 person years of follow-up. For persons exposed to radiation before age 15 years, linearity best described the dose response, even down to 0.10 Gy. At the highest doses (> 10 Gy), associated with cancer therapy, there appeared to be a decrease or leveling of risk. For childhood exposures, the pooled excess relative risk per Gy (ERR/Gy) was 7.7 (95% CI = 2.1, 28.7) and the excess absolute risk per 10(4) PY Gy (EAR/10(4) PY Gy) was 4.4 (95% CI = 1.9, 10.1). The attributable risk percent (AR%) at 1 Gy was 88%. However, these summary estimates were affected strongly by age at exposure even within this limited age range. The ERR was greater (P = 0.07) for females than males, but the findings from the individual studies were not consistent. The EAR was higher among women, reflecting their higher rate of naturally occurring thyroid cancer. The distribution of ERR over time followed neither a simple multiplicative nor an additive pattern in relation to background occurrence. Only two cases were seen within 5 years of exposure. The ERR began to decline about 30 years after exposure but was still elevated at 40 years. Risk also decreased significantly with increasing age at exposure, with little risk apparent after age 20 years. Based on limited data, there was a suggestion that spreading dose over time (from a few days to > 1 year) may lower risk, possibly due to the opportunity for cellular repair mechanisms to operate. The thyroid gland in children has one of the highest risk coefficients of any organ and is the only tissue with convincing evidence for risk about 1.10 Gy.

Estimating the population attributable risk for multiple risk factors using case-control data

Abstract: A straightforward and unified approach is presented for the calculation of the population attributable risk per cent (etiologic fraction) in the general multivariate setting, with emphasis on using data from case-control studies. The summary attributable risk for multiple factors can be estimated, with or without adjustment for other (confounding) risk factors. The relation of this approach to procedures in the literature is discussed. Given values of the relative risks for various combinations of factors, all that is required is the distribution of these factors among the cases only. The required information can often be estimated solely from case-control data, and in some situations relative risk estimates from one population can be applied to calculation of attributable risk for another population. The authors emphasize the benefits to be obtained from logistic regression models, so that risks need not be estimated separately in a large number of strata, some of which may contain inadequate numbers of individuals. This approach allows incorporation of important interactions between factors, but does not require that all possible interactions be included. The approach is illustrated with data on four risk factors from a pair-matched case-control study of participants in a multicenter breast cancer screening project.

The Burden of Mortality Attributable to Diabetes: Realistic estimates for the year 2000

Abstract: OBJECTIVE —To estimate the global number of excess deaths due to diabetes in the year 2000. RESEARCH DESIGN AND METHODS —We used a computerized generic formal disease model (DisMod II), used by the World Health Organization to assess disease burden through modeling the relationships between incidence, prevalence, and disease-specific mortality. Baseline input data included population structure, age- and sex-specific estimates of diabetes prevalence, and available published estimates of relative risk of death for people with diabetes compared with people without diabetes. The results were validated with population-based observations and independent estimates of relative risk of death. RESULTS —The excess global mortality attributable to diabetes in the year 2000 was estimated to be 2.9 million deaths, equivalent to 5.2% of all deaths. Excess mortality attributable to diabetes accounted for 2–3% of deaths in poorest countries and over 8% in the U.S., Canada, and the Middle East. In people 35–64 years old, 6–27% of deaths were attributable to diabetes. CONCLUSIONS —These are the first global estimates of mortality attributable to diabetes. Globally, diabetes is likely to be the fifth leading cause of death.