Health & Fitness
Binge Drinking A Problem In These Michigan Counties: Report
The Michigan county with the highest percentage of binge drinkers is also one of the healthiest, according to annual survey.

About 20 percent of Michigan adults are binge drinkers, according to a study from the U.S. Centers for Disease Control and Prevention that relied on state health department data. The counties with the highest percentage of people who meet the CDC definition of excessive drinking are Isabella and Livingston, both with 23 percent.
Alcona and Ontonagon counties had the lowest percentage of binge drinkers — 16 percent — according to results from the Behavioral Risk Factor Surveillance System, an annual phone survey conducted by the Michigan Department of Health and Human Services.
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The CDC definition of binge drinking is: “a woman consuming more than four alcoholic drinks during a single occasion or a man consuming more than five alcoholic drinks during a single occasion.”
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A “heavy drinker,” by comparison, is men who have more than two drinks a day or 14 drinks a week or women who have more than one drink a day and more than seven a week.
Livingston County residents may have more excessive drinkers, but they’re the third-healthiest in the state, just below Ottawa and Clinton counties. The least healthy Michiganders live in Wayne, Genesee and Lake counties. Read more here.
Excessive-drinking rates in selected Iowa counties include:
- Genesee: 18 percent
- Kent: 22 percent
- Livingston: 23 percent
- Macomb:19 percent
- Oakland: 20 percent
- Washtenaw: 21 percent
- Wayne: 20 percent
See a complete county-by-county listing.
The CDC estimates formerly relied on seven years of responses from landline telephone surveys, but those results were limited, missing populations that use cellphones only. In 2016, the CDC began producing estimates that used a single year of survey data and modeled that data using characteristics of the people who live in that county such as age, sex, race/ethnicity, poverty and other factors that add context to the data.
Photo by Sally T via Flickr Commons
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