We acknowledge that engagement with the content on social media does not equate to attributing the links content to be accurate by the user. Additionally, our study has the underlying assumption that all social media platforms allow users to engage similarly without accounting for the unique experience and engagement dimensions each platform offers. Further investigation into this topic may allow for better stratification of how users engage with male infertility content.Since the late 1990’s, there have been dramatic increases in alcohol-related problems in the United States. Between 1999 and 2016 annual deaths from liver cirrhosis increased by 65% and doubled for liver cancer . Relatedly, from 2006 to 2016 the death rate from alcoholic liver disease increased by over 40% from 4.1 per 100,000 to 5.9 per 100,000 . An increase of nearly 62% in alcohol-related emergency department visits was also found between 2006 and 2014 from 3,080,214 to 4,976,136 visits per year, with the increase occurring predominantly among people aged 45 and older . Further, an analysis of data from two waves of the National Epidemiologic Survey of Alcohol and Related Conditions showed a nearly 50% increase in the prevalence of past year alcohol use disorder from 2002 to 2013 among adults aged 18 and above . Surprisingly, these increases in alcohol-related morbidity and mortality did not occur alongside notable increases in per capita alcohol consumption estimates. These estimates, based on beverage sales data collected by the Alcohol Epidemiologic Data System , increased by approximately 6% over the 2002- 2013 time period . This represents an increase of approximately 28 drinks per person per year .

This increase seems insufficient to explain the observed increases in alcohol-related morbidity and mortality,flood and drain tray as we would expect a notable increase given that the heaviest drinkers consume the vast majority of alcohol . Indeed, the increase in the rate of alcohol-related ED visits between 2006 and 2014 was considered unrelated to the concomitant 1.7% increase in PCC . A possible explanation for the discrepancy between alcohol-related problems and PCC may lie in how PCC estimates are calculated. Per capita alcohol consumption is typically constructed as an aggregate measure using national and state population estimates from the U.S. Census Bureau and alcohol sales data . The state-level alcohol sales figures are from either state-provided taxable withdrawals from bonded warehouses or industry sources for states that fail to provide data. Alcohol sales-based consumption estimates are considered more complete and objective than survey data on alcohol use, which is subject to substantial under-reporting . This consideration is also due to the widespread availability of alcohol tax information and the low level of unrecorded alcohol use in the U.S. . However, the precision of typical PCC estimates is challenged by the fact that they use invariant estimates of the mean percentage of alcohol by volume , i.e. they do not use annual estimates of the alcohol content of the beer, wine, and spirits sold in each state to convert beverage volume into ethanol. The conversion factors used in the typical PCC estimate approach are based on estimates of %ABV for each beverage type and have not been updated since the 1970s. These values are 4.5%, 12.9%, and 41% for beer, wine, and spirits, respectively. Further complicating the issue is that each beverage type is comprised of several sub-types each with different %ABVs. Thus, actual PCC is also influenced by changes over time and place in beverage sub-type preferences.

Failing to acknowledge these changes in %ABVs and beverage preferences risks underestimating important changes in actual PCC that could potentially explain observed changes in alcohol-related morbidities and mortality. Additionally, PCC estimates are key to the estimation of the alcohol-attributable morbidity and mortality used to assess the global burden of disease due to alcohol . Indeed, PCC estimates are the marker against which the estimation of an exposure distribution of alcohol are based . Our previous work has demonstrated meaningful changes in the alcohol content of beer, wine, and spirits during the last half of the 20th century. The mean %ABV of beer and spirits sold in the U.S. have each declined between 1950 and 2002 . The %ABV of wine declined between 1950 and the mid- 1980s to 10.5%, where after it began and continued to increase to 11.5%. Beyond 2002 there is reason to believe there have been further changes in the %ABVs of beverage types with the emergence of high %ABV craft beer and a likely continued increase in the %ABV of wine . The aim of this paper is to extend our previous work estimating the mean alcohol concentration of the beer, wine, and spirits sold in the U.S. and PCC to the period 2003 to 2016. We present the variation in %ABV over this time period for each beverage type and examine this variation in light of changes in beverage sub-type preferences and mean %ABV. We compare PCC estimates based on ourABV-variant methods to estimates from ABV-invariant methods nationally and for each state. Data on the %ABV of specific wine brand and varietal were obtained from Washington State Liquor Control Board Price Lists for the years 2003 – 2012. As WSLB did not produce these price lists after the privatization of alcohol sales in 2012, we used the Liquor Control Board of Ontario’s website to identify %ABV. In the case that a specific brand varietal for a specific year could not be identified in either of these sources, we used the winery-reported value as reported on their websites.

As previously described , we did this for each brand varietal accounting for the top 80% of wine sales in Pennsylvania for each wine sub-type. There were many thousands of brand varietals sold comprising the largest category “table wine”, and an increasing number of brands each year. Further,hydroponic tables canada this methodology of identifying %ABV for each varietal has been critiqued as too labor intensive . To address the labor-intensity of this process, in this update of %ABV estimates and PCC we matched sales and %ABV for the top 50% of table wine sales in Pennsylvania, and calculated a mean %ABV for 30% of the total sales of table wines. We calculated a mean %ABV for the most commonly sold varietals, which were chardonnay, cabernet sauvignon, merlot, and zinfandel, by obtaining the %ABV for all the wines listed in these varietal categories, excluding those already included in the top 50%. We applied this mean %ABV to 30% of the total sales volume thus increasing our mean %ABV estimate to include 80% of the total. This was feasible for each year from 2003 to 2011 because the Washington Price lists were available and included %ABV values for each brand varietal in each top-selling varietal category. For the years from 2012 to 2016 we carried forward the 2011 %ABV value representing the mean of the most commonly sold varietals and applied it to each year’s 30% value of total sales volume. Data sources for spirits. We used the Liquor Handbooks to obtain data on the leading brands, the volume sold of each, and state and national annual market shares of each spirits sub-type . Spirits sub-type categories were straight whiskey, blended whiskey, Canadian whiskey, Scotch whiskey, Irish whiskey, gin, vodka, rum, tequila, brandy & cognac, cordials & liqueurs, and prepared cocktails. We obtained %ABV values for each brand within each spirits sub-type from the WSLB Price Lists for the years 2003 – 2012 and from the NABCA database for the years 2013-2016. If the %ABV could not be identified from these sources we used values from the distillery’s website. Other data sources. We used sales figure data for 2003-2016 from the Alcohol Epidemiologic Data System for the volume of each beverage type sold for each state and nationally for each year . These figures are based on tax receipts and industry sources. We obtained estimates of the United States population aged 15 and older for each state and nationally from 2003 to 2016 from the U.S. Census Bureau . The AEDS figures presented here based on the ABV-invariant method are not the same as those in the AEDS Surveillance reports because here they are referenced to the population aged 15 and older, while AEDS reports used figures for the population aged 14 and older. Estimating sales-weighted mean % ABV. To estimate the sales-weighted mean %ABV for each beverage sub-type for each year we 1) multiplied the %ABV for each leading brand by the volume sold , 2) took the sum of these product values and 3) divided this sum by the sum of the volume sold.

To estimate the mean %ABV for each beverage type we multiplied the annual market share of each beverage sub-type by the sales-weighted mean %ABV of that sub-type and summed across all beverage sub-types for each state for each year, and nationally for each year. Estimating per capita alcohol consumption. Nationally and for each state we calculated PCC estimates for each beverage type by multiplying the mean %ABV by the volume of each beverage type sold and dividing by the population aged 15 and above.To be consistent with international standards, we present PCC estimates in liters. We describe our %ABV estimates for beer, wine, and spirits, their trends between 2003 and 2016, and make comparisons to the static %ABV values used in the AEDS PCC calculations. To explain the trends in %ABV estimates for each beer, wine, and spirits, we describe the mean %ABV and market shares for beverage sub-types. We describe our beverage-specific and total PCC estimates and trends, and make trend comparisons to estimates from the AEDS ABV-invariant methods. We present national estimates as described above followed by a brief overview of state estimates. National %ABV estimates for beer, wine, and spirits. Our estimates of the mean %ABV of beer, wine, and spirits sold in the United States between 2003 and 2016 are presented in Figure 1. Overall, the means for all beverage types increased over the 2003-2016 period from 4.65% to 4.74 %ABV, 11.6% to 12.3 %ABV, and 36.9% to 38.3 %ABV for beer, wine, and spirits, respectively. For beer, the overall trend in mean %ABV was a decline between 2003 and 2005, a small increase in 2006 followed by a steady decline until 2010, after which there was a notable increase until 2015 and a slight decline to 2016. Our estimates were consistently higher than the time-invariant 4.5 %ABV value used for every year in AEDS, with the largest difference of 0.25 percentage points in 2015. For wine, the overall trend in average %ABV was a stable value between 2003 and 2007, then a sharp increase until 2010 after which it declined slightly and remained relatively stable until 2016. Our estimates were lower than the time invariant 12.9 %ABV value for every year in AEDS but the difference decreased over time as our estimates increased. For spirits, the overall trend in mean %ABV showed a steady increase between 2003 and 2014, with a slight dip in 2015 and an increase in 2016. Our estimates were consistently lower than the static AEDS estimates, although differences decreased over the time period as our estimates increased. National mean %ABVs and market shares for beverage sub-types. The changes we observed in our national estimates of mean %ABV of each beverage type were influenced by changes in the sales-weighted mean %ABVs of beverage sub-types and changes in beverage sub-type market shares over time, that is,changes in beverage sub-type preferences. The %ABVs and market shares are presented for selected years for each beverage type in Table 1. The initial decrease in the mean %ABV of beer between 2003 and 2005 was driven by declines in market shares and not %ABV as beer sub-types’ mean %ABV changed by no more than 0.03 over this time period. Premium beer and popular beer had the second and fourth largest market shares in 2003, respectively, and each lost about 12% of their market shares by 2005. On the other hand, the increase in the national mean %ABV of beer between 2005 and 2006 was the result of an increase in the mean %ABV of malt beverages, which increased from 6.14% to 6.68 %ABV.