We recently carried out a study of 3,000 Americans to determine how many spiked eggnogs they typically consume during the holiday season.
The fun and surprising results are illustrated below.
- Overall Consumption: The average American is expected to drink 6 spiked eggnogs this month, totaling an estimated 1.2 billion eggnogs nationally.
- State-Specific Consumption: Californians are projected to consume the most eggnogs (163 million), but on a per capita basis, Vermonters lead with an average of 19 eggnogs per adult.
- Drinking Time Norms: Our survey found that the acceptable time to start drinking over the holidays is 2:42 p.m., but 18% admit to starting before lunchtime.
- Festive Burnout: The average drinker expects to reach a state of festive burnout by December 10th, just 15 days into the holiday season.
- Drunkest States: North Dakota is ranked as the drunkest state during the festive season, with an average of 8 alcoholic drinks per day per person.
- Worst Hangover Days: The mornings after Independence Day, Christmas Day, Christmas Eve, St. Patrick's Day, and Thanksgiving are notably prone to hangovers, with January 1st being the peak day for hangovers.
Implications of the Study:
- Cultural Significance: Our study underscores just how important holiday cocktails like eggnog are to many people during the festive season, reflecting its role in our festive traditions.
- Health and Well-being: The findings raise awareness about the potential health impacts of excessive holiday drinking, including the risk of holiday burnout and hangovers.
- Social Norms and Behavior: Our study reveals interesting insights into social norms and behaviors related to holiday drinking, such as the socially accepted time to start consuming alcohol.
- Public Safety Concerns: The ‘drunkest states' and peak hangover days can help in planning public safety campaigns and medical preparedness during this holiday season.
Online panel survey of 3,000 adults based on age, gender, and geography. Internal data sources are used to obtain population data sets. We used a two-step process to ensure representativeness through stratified sampling and post-stratification weighting.