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Background Risk (background + risk)

Distribution by Scientific Domains

Medical Sciences	42%

Selected Abstracts

Portfolio Choice in the Presence of Background Risk

THE ECONOMIC JOURNAL, Issue 460 2000
John Heaton
In this paper, we focus on how the presence of background risks , from sources such as labour and entrepreneurial income , influences portfolio allocations. This interaction is explored in a theoretical model that is calibrated using cross-sectional data from a variety of sources. The model is shown to be consistent with some but not all aspects of cross-sectional observations of portfolio holdings. The paper also provides a survey of the extensive theoretical and empirical literature on portfolio choice. [source]

Drinking Patterns and Myocardial Infarction: A Linear Dose,Response Model

ALCOHOLISM, Issue 2 2009
Marcia Russell
Background:, The relation of alcohol intake to cardiovascular health is complex, involving both protective and harmful effects, depending on the amount and pattern of consumption. Interpretation of data available on the nature of these relations is limited by lack of well-specified, mathematical models relating drinking patterns to alcohol-related consequences. Here we present such a model and apply it to data on myocardial infarction (MI). Methods:, The dose,response model derived assumes: (1) each instance of alcohol use has an effect that either increases or decreases the likelihood of an alcohol-related consequence, and (2) greater quantities of alcohol consumed on any drinking day add linearly to these increases or decreases in risk. Risk was reduced algebraically to a function of drinking frequency and dosage (volume minus frequency, a measure of the extent to which drinkers have more than 1 drink on days when they drink). In addition to estimating the joint impact of frequency and dosage, the model provides a method for calculating the point at which risk related to alcohol consumption is equal to background risk from other causes. A bootstrapped logistic regression based on the dose,response model was conducted using data from a case-control study to obtain the predicted probability of MI associated with current drinking patterns, controlling for covariates. Results:, MI risk decreased with increasing frequency of drinking, but increased as drinking dosage increased. Rates of increasing MI risk associated with drinking dosage were twice as high among women as they were among men. Relative to controls, lower MI risk was associated with consuming < 4.55 drinks per drinking day for men (95% CI: 2.77 to 7.18) and < 3.08 drinks per drinking day for women (95% CI: 1.35 to 5.16), increasing after these cross-over points were exceeded. Conclusions:, Use of a well-specified mathematical dose,response model provided precise estimates for the first time of how drinking frequency and dosage each contribute linearly to the overall impact of a given drinking pattern on MI risk in men and women. [source]

Confounder summary scores when comparing the effects of multiple drug exposures,

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 1 2010
Suzanne M. Cadarette PhD
Abstract Purpose Little information is available comparing methods to adjust for confounding when considering multiple drug exposures. We compared three analytic strategies to control for confounding based on measured variables: conventional multivariable, exposure propensity score (EPS), and disease risk score (DRS). Methods Each method was applied to a dataset (2000,2006) recently used to examine the comparative effectiveness of four drugs. The relative effectiveness of risedronate, nasal calcitonin, and raloxifene in preventing non-vertebral fracture, were each compared to alendronate. EPSs were derived both by using multinomial logistic regression (single model EPS) and by three separate logistic regression models (separate model EPS). DRSs were derived and event rates compared using Cox proportional hazard models. DRSs derived among the entire cohort (full cohort DRS) was compared to DRSs derived only among the referent alendronate (unexposed cohort DRS). Results Less than 8% deviation from the base estimate (conventional multivariable) was observed applying single model EPS, separate model EPS or full cohort DRS. Applying the unexposed cohort DRS when background risk for fracture differed between comparison drug exposure cohorts resulted in ,7 to,+,13% deviation from our base estimate. Conclusions With sufficient numbers of exposed and outcomes, either conventional multivariable, EPS or full cohort DRS may be used to adjust for confounding to compare the effects of multiple drug exposures. However, our data also suggest that unexposed cohort DRS may be problematic when background risks differ between referent and exposed groups. Further empirical and simulation studies will help to clarify the generalizability of our findings. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Risk Assessment for Quantitative Responses Using a Mixture Model

BIOMETRICS, Issue 2 2000
Mehdi Razzaghi
Summary. A problem that frequently occurs in biological experiments with laboratory animals is that some subjects are less susceptible to the treatment than others. A mixture model has traditionally been proposed to describe the distribution of responses in treatment groups for such experiments. Using a mixture dose-response model, we derive an upper confidence limit on additional risk, defined as the excess risk over the background risk due to an added dose. Our focus will be on experiments with continuous responses for which risk is the probability of an adverse effect defined as an event that is extremely rare in controls. The asymptotic distribution of the likelihood ratio statistic is used to obtain the upper confidence limit on additional risk. The method can also be used to derive a benchmark dose corresponding to a specified level of increased risk. The EM algorithm is utilized to find the maximum likelihood estimates of model parameters and an extension of the algorithm is proposed to derive the estimates when the model is subject to a specified level of added risk. An example is used to demonstrate the results, and it is shown that by using the mixture model a more accurate measure of added risk is obtained. [source]

Public health projects for preventing the recurrence of neural tube defects in the United States,,

BIRTH DEFECTS RESEARCH, Issue 11 2009
Julianne S. Collins
Abstract BACKGROUND: The recurrence risk for neural tube defects (NTDs) in subsequent pregnancies is approximately 3%, or 40 times the background risk. Prevention projects target these high-risk women to increase their folic acid consumption during the periconceptional period, a behavior which decreases their recurrence risk by at least 85%. This study surveyed birth defect surveillance programs to assess their NTD recurrence prevention activities and to identify components of intervention projects that might be implemented in states with limited resources. METHODS: In 2005, the National Birth Defects Prevention Network developed and distributed an online survey to primary state birth defects surveillance contacts for the purpose of gathering information on NTD recurrence prevention activities in the United States. RESULTS: Responses came from 37 contacts in 34 states and Puerto Rico. There were 13 active NTD recurrence prevention projects, four past projects, and three planned projects. Fifteen past and present projects recommended that women with a prior NTD-affected birth take 4.0 mg of folic acid daily, and four projects provided folic acid to the women. Reasons given for not having an NTD recurrence prevention project included staffing limitations (53%), lack of funds (47%), lack of priority (18%), and confidentiality/privacy concerns (6%). CONCLUSIONS: Only 15 states and Puerto Rico had or were planning NTD recurrence prevention projects. An NTD recurrence prevention project using minimal resources should consist of timely case ascertainment, educational materials, and mechanisms for disseminating these materials. Birth Defects Research (Part A), 2009. © 2009 Wiley-Liss, Inc. [source]