- National and State Estimates for Various Causes of Deaths in US due to Alcohol Use
- Alcohol Attributable Fractions in US due to Alcohol Use
- Alcohol Use
- Alcohol Attributable Deaths
- Years of Potential Life Lost
- Alcohol Related Disease Impact
- Causes of Death
- Alcohol Related Health Impacts
- Alcohol Attributable Fractions
ARDI Alcohol Attributable Fractions for Alcohol Use
This dataset provides national and state estimates of alcohol related health impacts, including deaths and years of potential life lost (YPLL). These estimates are calculated for 54 acute and chronic causes using alcohol attributable fractions, and are reported by age and sex for 2006-2010. This dataset provides estimates of the proportion of deaths from various causes that are attributable to alcohol.
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The US Centers for Disease Control and Prevention (CDC) convened a scientific workgroup comprised of experts on alcohol and health to guide the development of the ARDI application. One of the group’s tasks was to select alcohol related causes of death based on ones that were previously examined in meta-analyses. Some causes (e.g., tuberculosis, pneumonia, and hepatitis C) were not included in this version of ARDI because suitable pooled relative risk estimates or alcohol attributable fractions (AAF) were not available for them at the time the work group convened.
Excessive alcohol consumption, the fourth leading preventable cause of death in the United States, resulted in approximately 88,000 deaths and 2.5 million years of potential life lost (YPLL) annually during 2006–2010 and cost an estimated $223.5 billion in 2006. To estimate state-specific average annual rates of alcohol attributable deaths (AAD) and YPLL caused by excessive alcohol use, different states analyzed 2006–2010 data (the most recent data available) using the CDC Alcohol Related Disease Impact (ARDI) application.
Alcohol attributable fractions (AAF) are used to express the extent to which alcohol consumption contributes to a health outcome. In ARDI, AAF measure the total proportion of deaths from various causes that are directly or indirectly attributable to alcohol consumption. For some causes of death, especially acute causes (e.g., injuries), ARDI uses direct estimates of AAF. These direct estimates are based on scientific studies that have directly measured the relationship between excessive alcohol use and a given health outcome. These estimates typically come from follow-up studies that included information obtained from medical record reviews, interviews with next-of-kin, or some combinations of these, that have directly assessed a decedent’s pattern of alcohol consumption, or from studies that have assessed the proportion of persons dying from a particular alcohol attributable condition that had a blood alcohol concentration (BAC) above a specified level (e.g., 100 mg/dL, or 0.10 g/dL).
The chronic conditions that are assessed using direct estimates of AAF include acute pancreatitis, chronic pancreatitis, epilepsy, esophageal varices, gastroesophageal hemorrhage, liver cirrhosis unspecified, portal hypertension, and spontaneous abortion. In contrast, the AAF for most of the acute causes of death (e.g., injuries), except for deaths due to motor-vehicle traffic crashes, are based on a meta-analysis by Smith et al. (1999). In this study, the researchers systematically reviewed studies that directly measured the BAC of persons who had died of fatal non-traffic injuries. In this study, injuries were defined as having been alcohol-attributable if the decedent had a blood alcohol concentration (BAC) ≥ 100 mg/dL (0.10 g/dL) at the time of death. The fatal non-traffic injuries that are assessed using direct estimates of AAF from this study include air-space transport, aspiration, child maltreatment, drowning, falls, fires, firearms, hypothermia, motor-vehicle non-traffic crashes, occupational and machine injuries, other road vehicle crashes, poisonings, suicide, and water transport. The AAF for homicide came from a meta-analysis by English et al. (1995) that systematically reviewed studies that measured the alcohol levels of those who caused the crime (i.e., perpetrators) and not just the alcohol level of victims.
For some causes of death, particularly chronic causes, ARDI calculates indirect estimates of AAF. These calculations use pooled risk estimates obtained from large, systematic reviews of the scientific literature, known as meta-analyses, on the relationship between alcohol and various causes as well as data on the prevalence of alcohol consumption at specific levels (e.g., more than one drink per day on average). Most of the pooled risk estimates used in ARDI were drawn from a study done by English et al. (1995) with a few causes of death drawn from other meta- analyses.
Indirect estimates of AAF are calculated in ARDI using the following formula:[(Prevalence)(Relative Risk – 1)]/[1+(Prevalence)(Relative Risk – 1)]
Alcohol at a specified level of average daily consumption within a given year, and relative risk is the likelihood of death from a particular cause at a specified level of average daily alcohol consumption. In accordance with the methods used by English et al. (1995), when evaluating the relationship between medium and high alcohol use and deaths from various causes, the risk estimates for these consumption levels were divided by the risk estimate for low alcohol consumption, thus making those in the low average daily consumption group the reference population rather than abstainers. When calculating indirect AAF, ARDI uses the prevalence or the proportion of U.S. adults aged 20 years and older (stratified by sex) who reported average daily alcohol consumption at various levels.
The findings for this dataset are subject to the following seven limitations:
– ARDI exclusively uses the underlying cause of death and does not consider contributing causes that might be alcohol related.
– ARDI does not include AAD estimates for several causes (e.g., tuberculosis) for which excessive alcohol use is believed to be an important risk factor.
– The alcohol data used to calculate AAF estimates were based on self-reports and might underestimate the actual prevalence of excessive alcohol use.
– State estimates calculated in this study might be different than those available in the ARDI application.
– National AAF data were used, even though studies suggest that there are important state differences in AAF for some causes of alcohol-attributable deaths.
– AAD and YPLL rates could not be calculated for some age and race/ethnicity categories because of the small number of AAD in some of these groups.
The Community Preventive Services Task Force has recommended several population-level, evidence-based strategies to reduce excessive drinking and related harms, including:
– Increasing the price of alcohol
– Limiting alcohol outlet density
– Holding alcohol retailers liable for harms related to the sale of alcoholic beverages to minors and intoxicated patrons.
Routine monitoring of alcohol attributable health outcomes, including deaths and YPLL, in states could support the planning and implementation of evidence-based prevention strategies to reduce excessive drinking and related harms.
About this Dataset
John Snow Labs; Centers for Disease Control and Prevention;
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Alcohol Use, Alcohol Attributable Deaths, Years of Potential Life Lost, Alcohol Related Disease Impact, Causes of Death, Alcohol Related Health Impacts, Alcohol Attributable Fractions
National and State Estimates for Various Causes of Deaths in US due to Alcohol Use, Alcohol Attributable Fractions in US due to Alcohol Use
|State_Abbreviation||Two-character postal abbreviation for state name.||string||required : 1|
|State||It represents the full name of different US States.||string||required : 1|
|Consumption_Pattern_of_Alcohol||Refers to the consumption pattern according to which alcohol is used by the individuals.||string||required : 1enum : Array (  => Excessive Use  => Any Use )|
|Condition_Type||It identifies the cause type of disease condition.||string||required : 1enum : Array (  => Acute  => All causes  => Chronic )|
|Disease_Condition||It refers to the disease contition over health.||string||required : 1|
|Gender||It identifies the gender of the patients.||string||required : 1enum : Array (  => Male  => Female )|
|Age_Group||It refers to the range for age of the patient.||string||required : 1|
|Direct_Alcohol_Attributable_Fraction||It refers to the Direct estimate for Alocohol Attributable Fraction to measure the relationship between excessive alcohol use and a given health outcome.||number||level : Ratio|
|Indirect_Alcohol_Attributable_Fraction_Low||It refers to the Indirect estimate for Alocohol Attributable Fraction to measure the relationship between excessive alcohol use and a given health outcome.||number||level : Ratio|
|Indirect_Alcohol_Attributable_Fraction_Medium||It refers to the Indirect medium level estimate for Alocohol Attributable Fraction using the prevalence or the proportion of U.S. adults aged 20 years and older (stratified by sex) who reported average daily alcohol consumption at various levels.||number||level : Ratio|
|Indirect_Alcohol_Attributable_Fraction_High||It refers to the Indirect higher estimate for Alocohol Attributable Fraction using the prevalence or the proportion of U.S. adults aged 20 years and older (stratified by sex) who reported average daily alcohol consumption at various levels.||number||level : Ratio|
|Location_ID||Refers to the location identity.||integer||level : Nominal|
|Class_ID||Refers to the class identity||string||required : 1|
|Condition_ID||Refers to the condition identity.||string||required : 1|
|Stratification_ID1||Refers to the stratification identity.||string||required : 1|
|Stratification_ID2||Identifies the sampling sub identity of the population.||string||required : 1|
|IA||Iowa||Any Use||Acute||Suicide||Male||All Ages||0.23||19||ACUTE||SUICID||GENM||AGEGRP0|
|OH||Ohio||Any Use||Acute||Suicide||Male||All Ages||0.23||39||ACUTE||SUICID||GENM||AGEGRP0|
|UT||Utah||Any Use||Acute||Suicide||Male||All Ages||0.23||51||ACUTE||SUICID||GENM||AGEGRP0|
|AK||Alaska||Any Use||Acute||Suicide||Male||All Ages||0.23||2||ACUTE||SUICID||GENM||AGEGRP0|
|ID||Idaho||Any Use||Acute||Suicide||Male||All Ages||0.23||16||ACUTE||SUICID||GENM||AGEGRP0|
|IA||Iowa||Any Use||Acute||Drowning||Male||All Ages||0.34||19||ACUTE||DROWNI||GENM||AGEGRP0|
|IA||Iowa||Any Use||Acute||Homicide||Male||All Ages||0.47||19||ACUTE||HOMICI||GENM||AGEGRP0|
|ME||Maine||Any Use||Acute||Suicide||Male||All Ages||0.23||23||ACUTE||SUICID||GENM||AGEGRP0|
|OH||Ohio||Any Use||Acute||Drowning||Male||All Ages||0.34||39||ACUTE||DROWNI||GENM||AGEGRP0|
|OH||Ohio||Any Use||Acute||Homicide||Male||All Ages||0.47||39||ACUTE||HOMICI||GENM||AGEGRP0|