This week the NTIA (National Telecommunications and Information Administration), Economics and Statistics Administration and U.S. Department of Commerce came out with a new study: Exploring the Digital Nation: Home Broadband Internet Adoption in the United States. In the research, they used Census Bureau’s Current Population Survey Internet Use Supplement, a survey of approximately 54,000 households conducted over one week in October 2009.

I’ll try to provide a very abridged abstract on the report by pulling out various nuggets:

How many households are online?

Despite this overall growth in Internet use, it is important to realize that a significant portion of American households (36%) did not have a broadband Internet service at home. Almost one-fourth of American households (23%) did not have any Internet user in 2009.

Who’s online?

Persons with high incomes, those who are younger, Asians and Whites, the more highly-educated, married couples, and the employed tend to have higher rates of broadband use at home.

Who’s not?

Conversely, persons with low incomes, seniors, minorities, the less-educated, non-family households, and the nonemployed tend to lag behind other groups in home broadband use.

Why aren’t people online?

• Cost
• No interest
• No computer
• No access

I found these numbers and details to be very similar to what Jack Geller (64% of homes had broadband) and Connect Minnesota (72% of Minnesotans – people not households – use broadband at home) has found – at least in terms of Minnesota’s broadband adoption.

But this report went beyond the basics. The tables below show the level of detail.

They tried to look at which characteristics were most pertinent in broadband adoption. There are some obvious difficulties, especially if, like me, you’re focusing on geography – because you’re not comparing apples. The demographic makeup of rural areas tends to be heavier on older folks, lower income so which characteristic is weighted most heavily? Hopefully the table below (from the report) will help show how they assigned weight (if you want the methodology, check out the report and the regression analysis framework – I’ve poste the results):

As you can see the urban-rural gap is assigned 7 percentage points – so all other things being equal, a house in a rural area is 7 percent less likely to have broadband than their urban counterparts.