|Men's average longevity from age 50 "binned" by income quintile. These are not projections. This is data. Green was longevity in 1930. Orange was longevity for men who were age fifty in 1960. Data from the National Institute for Health.|
|Same chart for women, average longevity from age 50 binned by income quintile.|
Lowest Quintile: $11.7K
Second Quintile: $31.1K
Third Quintile: $54.0K
Fourth Quintile: $87.8K
Highest Quintile: $194K
I am now going to commit a statistical sin, I am going to combine 1960 data (life expectancy) and 2014 income data.
Based on the combination of these data, every additional thousand dollars of income (per year) raises life expectancy by 24 days for men and 27 days for women.
It should be noted that this is significant under-estimate. "Households" often include both women and men and my math made the very conservative assumption that the increased longevity was not cumulative. The increased life expectancy might be as much as 65% higher than reported in the previous paragraph.
Converting this to "packs of cigarettes", the loss of one thousand dollars per year of income has the same impact on life expectancy as smoking 165 packs of cigarettes. Note: 11 minutes per cigarette is a figure that is commonly bandied about.
Is this still true?
Lets use diabetes and obesity as a proxy for life expectancy.
|Income by county. I took the liberty of outlining an area that is pale yellow, i.e. lower income.|
|Counties in black are in the top two quintiles for both diabetes and obesity.|
|The population binned by income quintile, the vertical axis is the percentage of that sub-population exhibiting two or more of the following chronic diseases: arthritis, cancer, high blood pressure, diabetes, heart disease, chronic obstructive pulmonary disease (COPD), mood disorder and anxiety disorder. Source|
Assuming that lack of access to health care, "healthy" food and safe places to exercise is at least a partial factor, then factors that hamper personal mobility must be considered unhealthy. Perhaps even as a cause that contributed to a person's early death.
What about the 860,000 people in the bottom quintile who die every year in the US? Surely, a very large number of them died early because of the high costs of vehicles....high costs driven, in part, by regulations that past the point of diminishing returns a long time ago. Hmmm. 5-to-20 deaths a year vs 430,000 deaths a year in just the lowest quintile. Seems like we are focusing on the gnat and not the elephant.
"Joe," you say, "poor folks don't buy new vehicles."
True, but the buy the vehicles that the new car buyers dump to make room in their driveway. It all flows downhill.
Given the relationship between income and life expectancy, I believe that all regulations should be tested against the known opportunity costs. That is, the expected improvements due to a regulation must demonstrate 130% improvement over the proven costs that the regulation will have on life expectancy due to reduced buying power.