Apparently Slate.com is now doing a “map of the week”. This week, it was a map of states by marriage rate. Can’t get it to format well….click on the map and drag to see other states.
It shows Nevada as the overwhelming winner, with Hawaii second. This reminded me about my annoyance at most marriage data.
Marriage data is often quoted, but fairly poorly understood. The top two states in the map above should tip you off as to the major problem with marriage data derived from the CDC in particular….it’s based on the state that issued the marriage license, not the state where the couple resides. Since all (heterosexual) marriages affirmed by one state are currently recognized by every other state, state of residence information is not reported to the CDC. This means that states with destination wedding type locations (Las Vegas anyone?) skew high, and all others are presumably a bit lower than they should be. Anecdotally, it’s also conceivable that states with large meccas for young people (New York City, Boston, DC) may be artificially low because many young people return to their childhood home states to marry. This
The other problem with marriage data is the resulting divorce data is even more skewed. Quite a few states don’t report divorce statistics at all (California, Georgia, Hawaii, Indiana, Louisiana, Minnesota) and the statistics from the remaining states are often misinterpreted. One of the most commonly quoted statistics is that “50% of marriages end in divorce”. This isn’t true.
In any given year, there are about twice as many marriages as there are divorces….but thanks to changing population, changing marriage rates, people with multiple divorces, and the pool of the already married, this does not mean that half of all marriages end in divorce. In fact, if you change the stat to “percent of people who have been married and divorced”, you wind up at only about 33%. More explanation here.
Ultimately, when considering any marriage data, it is important to remember that there are no national databases for this stuff. All data has to come from somewhere, and if the source is spotty, the conclusions drawn from the data will likely be wrong. This all applies to quite a few types of data….but marriage data is used with such confidence that it’s tough to remember how terrible the sources are. A few people have let me know that I’ve ruined infographics for them forever, and I’m hoping to do the same with all marriage data.