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Monday, July 8, 2013

Secondary Analyses of Alcohol and Chronic Disease (R01)


This funding opportunity encourages use of existing datasets to examine associations between alcohol and chronic disease.
Alcohol consumption has a significant effect on chronic disease from the probable benefits of moderate drinking to the detrimental effects of heavy drinking.  Research is needed to better understand the impact of alcohol on chronic disease and the myriad factors that may interact with alcohol to modify chronic disease risk.
Alcohol-related chronic diseases and conditions of interest include, but are not limited to: Alzheimer's disease, cardiovascular disease, cancer, chronic liver disease, chronic pancreatitis, type 2 diabetes, fetal alcohol syndrome, HIV/AIDS, hypertension, age-related macular degeneration, metabolic syndrome, obesity, osteoporosis, and psychiatric disorders such as depression and schizophrenia. Healthy aging and survival free of chronic disease are included. 
Exposures of interest include, but are not limited to:
  • Drinking patterns such as quantity/frequency, binge, or drinking with meals;
  • Changes in drinking over time
  • Alcohol dependence/abuse
  • Gene-environment interactions
  • Lifestyle factors such as smoking, nutrition/eating behavior, physical activity
  • Concurrent use of prescription drugs particularly among moderate drinkers or the elderly;
  • Concurrent use of illicit drugs;
Populations of interest include, but are not limited to those defined by:
  • Stage-of-life
  • Race/ethnicity
  • Pregnancy
  • Menopausal status
  • Cancer survivorship
This funding opportunity does not exclude any secondary analyses that use epidemiologic or clinical data to study associations between alcohol and chronic disease (including biomarkers/intermediate outcomes). Of particular interest is the examination of understudied areas, populations, exposures, or outcomes. A significant barrier to conducting secondary data analyses on alcohol and chronic disease is that many epidemiologic or clinical studies have too few subjects to examine critical subgroups, rare exposures, or rare outcomes. Secondary analyses of existing datasets may overcome that barrier in a cost-efficient manner through use of combined or pooled datasets, or targeted sub-studies within ongoing cohorts.  To facilitate secondary analyses of understudied areas up to 25% of the direct costs of the grant may be spent on acquiring new information that would significantly strengthen the analysis. Such information may, for example, be derived from re-contacting subjects, or laboratory testing of stored specimens. Obtaining such new information must serve the purpose of the secondary data analysis and should not be considered for any other reason.  

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