Some of the results reported by Gallup are:
Mapping well-being scores across the country, a clear pattern emerges with higher well-being states located primarily in the West and lower well-being states clustered in the Midwest and the South.
Hawaii, for instance, does rank high on five of the six sub-indexes, but reports the lowest quality work environments out of all 50 states. On the flipside, certain bottom ranked states in overall well-being shine in select sub-indexes. Oklahoma is eighth to last in overall well-being, but reports the third best score for work environment in the country.
The chart illustrates the 15 U.S. states with the highest well-being, as measured by the survey. In economics, we commonly use real per-capita income to proxy well being with the understanding that, on average, higher per-capita income signals better access to goods and services. However, some contributors to well-being (health care, environmental control, tendency toward happiness, etc.) cannot be directly measured.
The survey is interesting, as it tries to quantify unmeasurable identifiers of well-being, including life evaluation, physical health, emotional health, healthy behavior, work environment, and basic access. The phone survey is conducted by Gallup and Healthways on a daily basis of over 1,000 adults.
I suspect that the survey doesn't interview the same adults over the course of the year (because the methodologies doesn't state this fact), which makes it slightly kooky. But nevertheless, it does paint a different picture of well-being than does the standard economic measure, real per-capita income.
This survey shows only a tenuous relationship between per-capita income and the well-being index by state.
This is a new survey, and has no time series with which to base inference. It will be interesting to see how this survey plays out in the economics literature, as it does counter the standard measure of well-being. I would definitely want to know more about the methodology (the description on the website is quite vague), as survey methodologies are important in judging the reliability of the data.