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Male Life Expectancy, the Story of Region & Income
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My post below alluded to the fact that there seems to be a non-trivial between region difference in male life expectancy, even controlling for race, in the United States. From what I can tell Americans seem to have a somewhat schizophrenic attitude toward the reality of regionalism. On the one hand we are a relatively mobile people, and the original social-political aspect of states has been superseded by states as simply arbitrary sub-national units. And yet regional identities are still alive, most notably in the case of Southerners (with Texas as perhaps a special particular case even in the South, along with other areas such as Cajun Country). The differences are obvious in the case of accent and dialect, but one might think of these as simply indicators of a host of implicit underlying variables which are often imperceptible until one takes oneself “out of region.” In Albion’s Seed David Hackett Fisher explored the possible cultural roots of American regionalism as a work of history, while in The Nine Nations of North America Joel Garreau treated the subject in the manner of contemporary human geography.

These works paint with a broad brush, and explore the variation on a relatively coarse scale. Most Americans are aware of local religionalisms to a far greater level of detail, something which they are often not explicitly cognizant of. As a personal example I spent my adolescence in an area of the Intermontane West where both Mormons and “cowboys” were well represented. Though both groups were politically conservative, culturally there were stark differences which everyone was implicitly aware of. It was only later on that I learned that this region had experienced an influx of people from the Upper South in the 19th century, and later “Okies”, which was evident in the speech patterns of some individuals. On the other hand many of the Mormons had roots in Utah and eastern Idaho, and were cultural descendants of New England Yankees or later Northwest European converts who emigrated to Utah (the Mormon fixation on genealogy meant that if you had Mormon friends you would usually find out where their family was from through casual conversation since they knew). Last fall Steve Sailer pointed out that the counties where Barack Obama underperformed John Kerry, against the national trend, were those settled by and dominated by the Scots-Irish in the 18th century. Greg Cochran has told me that he was aware as a child the differences between Midwesterners whose origins were in the Upper South, and those who were Yankees.

Why does this matter? Because American public policy is often predicated on ceteris paribus assumptions once race and income are accounted for. Public policy prescriptions generated on the federal level will make the nod to race and class as interaction effects, but rarely allude to the possibility that white Americans even controlling for class may behave differently because of distinct cultural traditions. American regionalism is often conceived of as how you speak and what you eat, but I believe that these are simply the most obvious aspects of whole folkways, which are often assumptions and behaviors we take for granted.

But I come here not to talk, but to explore. The paper Eight Americas: Investigating Mortality Disparities across Races, Counties, and Race-Counties in the United States has the data for the white male longevity for each county in the United States. The Census has data on median household income, as well as the proportion of non-Hispanic whites in each county, or at least a subset. Unfortunately the tables I found had many counties missing for income and the proportion non-Hispanic white, so when I merged them with the one from the supplemental data from the paper above I was left with far fewer counties. I invite readers to point to better data sets in the comments than what I found poking through the Census website. There are certainly many likely variables which might explain longevity differences between regions, from climate to military service to participation in risky behaviors (the Mormon ban on alcohol probably means fewer men die of stupid acts at younger ages). But income is the primary predictor people think of, so it is what I focused on. Below are a set of charts and maps where I try and tease out regional variation. The x-axis is always median household income, while the y-axis is male life expectancy. Keep in mind that I filtered and constrained the data set in various ways when viewing the results, as my choices naturally have an effect. My point in presenting these results is to leverage reader knowledge about local variation. I am not interested in offering general explanations of why variation exists within the United States, rather, I am interested in outliers, and sharp local gradients. As the data was limited to counties which are at least 80% or more non-Hispanic white, there is a strong skew toward some regions, rural areas and less populous counties. This is not optimal, but I think it does the trick for this cursory examination.

All counties where non-Hispanic whites are 80% or more, male life expectancy vs. median household

All counties where non-Hispanic whites are 80% or more, male life expectancy vs. median household, labeled only with states

What I’m really interested in is the middle of the distribution, not the really rich or really poor counties. So I limited to incomes between $35,000 and $65,000 dollars. So the same as above, but now constrained as noted.

Focus on the outliers. What is going on in Baker County, Florida? Raw data is below, but I want to map these results above. Again these are the counties from the chart above (income between $35 and $65 K) shaded in proportion to the value of of the residual. In other words, a “dark” blue county is far deviated from the trendline by being above it, while a “dark” red county is deviated by being below it. Being above the trendline means that the county has a high life expectancy for its income, while below means it has one below what one would expect for income.

As I said above, there are constraints with these data. Some counties are missing from the source tables which I used, and only those counties present in all of the source datasets remain. Additionally, the map excludes very wealthy areas (parts of New England) and very poor ones (much of Appalachia), as well as those areas where less than 80% of the population is non-Hispanic white. The income data here surely exaggerations differences in real consumption; it isn’t taking into account cost of living. But, I think the general insight from the earlier map remains: being close to Canada is good for a county’s average life expectancy.

Here are the counties 2 or more years above the trendline:
FL – Charlotte 2.008085
ND – Ward 2.015647
SD – Lawrence 2.050383
MT – Gallatin 2.058849
ND – Cass 2.079347
WI – Marathon 2.112865
WA – Kittitas 2.146117
WI – Dunn 2.153582
MN – Steele 2.156426
IA – Bremer 2.200
543
TX – Bandera 2.202348
MN – Stearns 2.262364
WA – Whatcom 2.280879
MN – Winona 2.289539
MN – Crow Wing 2.296179
ID – Kootenai 2.319326
WI – Wood 2.365409
NE – Madison 2.386554
MN – Martin 2.407487
MI – Emmet 2.418643
NY – Tompkins 2.437007
NY – Seneca 2.546057
PA – Union 2.568985
CO – Larimer 2.582040
NE – Buffalo 2.583082
IA – Henry 2.662992
MN – Freeborn 2.683949
MN – Mower 2.770022
KS – Douglas 2.811094
CO – La Plata 2.815263
WI – Eau Claire 2.821042
WI – Clark 2.920767
MN – Brown 2.980544
MN – Kandiyohi 3.064475
WA – Island 3.071250
IA – Mahaska 3.080397
UT – Iron 3.114267
WA – Jefferson 3.229158
PA – Centre 3.274080
IA – Winneshiek 3.305467
MI – Leelanau 3.378293
ID – Latah 3.605875
IA – Johnson 3.618503
OR – Polk 3.661479
MO – Nodaway 3.750706
IA – Story 3.761283
KS – Riley 3.812826
UT – Washington 3.857329
MN – Douglas 3.871383
SD – Brookings 3.893517
ID – Madison 4.116757
UT – Cache 4.261088
IA – Sioux 4.312095
OR – Benton 4.544464

And 2 or more years below:
FL – Baker -7.775926
AL – Walker -4.976348
AR – Greene -4.273662
MD – Cecil -3.862680
TX – Hardin -3.856310
TN – Carroll -3.577800
GA – Bartow -3.459386
IN – Starke -3.429478
WV – Berkeley -3.344611
GA – Jackson -3.282126
MS – George -3.254395
TN – Wilson -3.244293
AL – Chilton -3.208314
TX – Orange -3.199165
AL – Marshall -3.176659
OK – Garvin -3.107875
TN – Henry -3.006837
NC – Currituck -2.953442
WV – Jefferson -2.951280
GA – Walker -2.876994
VA – Warren -2.823080
AL – St. Clair -2.801636
TX – Fannin -2.779233
AR – Lonoke -2.673197
MS – Hancock -2.639797
FL – Nassau -2.636036
KY – Scott -2.605132
TN – Robertson -2.579745
GA – Murray -2.565466
TN – Lawrence -2.544601
TN – Maury -2.534866
MO – Jefferson -2.503979
TN – Dickson -2.490682
GA – Walton -2.475931
GA – Gordon -2.433042
MI – Osceola -2.378020
FL – Clay -2.370529
GA – Paulding -2.369467
TX – Wise -2.366306
IA – Marshall -2.331662
MS – Pearl River -2.283195
OK – Grady -2.256928
340 MO – St. Francois -2.224602
WY – Sweetwater -2.212283
IL – Lee -2.204632
AZ – Mohave -2.203554
TX – Van Zandt -2.147798
MI – Calhoun -2.143441
TN – Obion -2.138999
KY – Kenton -2.124380
WV – Kanawha -2.121422
OH – Madison -2.115574
IN – Dearborn -2.089985
GA – Oconee -2.077321
KY – Nelson -2.059997
TN – Rhea -2.056843
TN – Cheatham -2.053162
WV – Raleigh -2.006031

(all these are the counties between $35 and $65 K in median household income. The trendline was generated from this constrained sample as well)

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Longevity, Regions 
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  1. Fascinating, but, one question – is this life expectancy at birth (and if so how is it estimated), or actual recorded age at death? Because the obvious outlier on your map is southern Florida, which is far from Canada but long-lived. But is that just because old people retire there? 
     
    Looked at another way, do people born in the South really die earlier (vs what you expect from income) or is it that people who live long enough move out of the South and die somewhere else?

  2. Oh dear, your web page’s width control has misbehaved again, but only after “read full post”.

  3. bio, no, it hasn’t. i just decided not to resize my charts. there’s not much text after the jump, so i figured it won’t matter.

  4. neuro, it looks like they averaged death rates over 5 years. you can dig deeper if you want into the methods. in any case, if you look at the previous post the whole southern fringe of the USA has higher than average male white life expectancy, but it doesn’t show up on my map because *i excluded white hispanics*. so for example if i look at just “white” counties, the biggest outlier for male life expectancy in relation to income is a south texas one, presumably hispanics who live way longer than their low incomes should warrant. 
     
    the point about migration is important. i’ll look more into. but, note the western south florida coast is populated by retired midwesterners, while the eastern coast is mostly northeasterners (broward county is the second most jewish county after brooklyn). i guess it would be interesting if someone could point out mobility data, as that would give us a handle on how much distortion internal migration induces. but it seems to me that the biggest effect would be disproportionately wealthy northerners moving to arizona and florida to retire.

  5. an idea: it may be that the natural operating temperature for people of northern euro descent is colder weather. The military has stats on this. Perhaps we could put temperature of the county as another axis and do a multiple regression (taking into account both income and temp). 
     
    You might also add in humidity and altitude. Maybe Douglas CO is the climactic opposite of Baker FL.

  6. Broward county is the second most Jewish county in the U.S. after Brooklyn!? 
     
    I should have figured as much after the last time I caught a Saturday Matinee and the audience was entirely filled with Jews. It was an odd sight, a singular young Chinese man amidst a sea of Jewish retirees. Probably didn’t hurt that I was watching a foreign language film involving Jews and the Holocaust.  
     
    P.S. the Seinfeld Stereotypes. They are all true.

  7. an idea: it may be that the natural operating temperature for people of northern euro descent is colder weather. The military has stats on this. Perhaps we could put temperature of the county as another axis and do a multiple regression (taking into account both income and temp). 
     
    could be. the only thing though is that a physical anthropologist told me that military found that cold weather people were much more well adapted to hot conditions than vice versa (or that they could adjust much more easily).

  8. being close to Canada is good for a county’s average life expectancy” 
     
    If this life expectancy phenomena is due to German vs British descent, as I think you are suggesting here… 
     
    http://www.gnxp.com/blog/2009/07/dont-blame-canada.php 
     
    … then I’d expect to see a “hard” change in life expectancies if the map was continued into Canada, since Canada tends to be dominated by people of British descent in many parts of Canada… 
     
    http://en.wikipedia.org/wiki/File:Censusdivisions-ethnic.png

  9. Charles, I don’t really see how the argument follows. Razib was originally positing that Germans outlive Scots-Irish, but Canada has people of mainly British origins except in some South-Central areas of Saskatchawan, Alberta and Manitoba. I think that most who identify as “Canadian” are part of that same 18th century Scot-Irish influx into North America that Razib mentions. 
     
    Instead, I go along with what Blah says, except that I think temperature mediates life expectancy through IQ. People with higher IQ have been shown to get in much fewer accidents and take less risks in general than those of lower IQ, which can make a big difference over a lifetime. If pathogen load or bodily stress caused by higher temperature leads to lower IQ in the South, this could explain Southerners lower than predicted life expectancies.  
     
    I would also like to see what the results would be like controlled for either temperature or IQ. I suspect the correlation between region and life expectancy would go almost to nil.

  10. to be clear, i think the primary issue might be scots-irish vs. non-scots irish. the lowlands of the south and new england were settled by other british streams. i do not know what stream was dominant in canada, though i assume that the tories who fled from the northeast after the revolution were not scots-irish. i brought up the germans because in texas there is a notable socio-cultural difference between germans and the anglo-celtic stock among the whites. some of the same came be found among germans vs. anglos in illinois. but the type of anglos matters too; yankees from new england tended to set up communitarian towns with a thick arena of public obligations. scots-irish not so much. observers claimed that in the midwest you could tell the provenance of settlers by how they kept their houses. yankees were neat & trim, and non-yankees tended to be more laissez-faire. 
     
    i also naturally think there are interaction effects.

  11. Just looking at the outliers in the upper left corner of the first graph (Whitman County, WA)– that’s a moderately high, dry, cool weather desert college town with a well-regarded liberal arts college. 
     
    The outlier in the upper right corner is Summit County, Utah, which is a lot like the rich parts of the Colorado Rockies. 
     
    I would be fascinated by the effects of altitude, as mediated directly or through coolness or dryness, if I didn’t figure it wasn’t self-selecting: sickly people head for lower altitudes where they can catch their breaths.

  12. I don’t know the composition of British immigration to Canada — I’ll see if I have time to look it up. I do know that Canada had the largest Orange Order in the world up to the Thirties, and Toronto had the world’s biggest Orangeman’s parade (today, the largest parade in Toronto is Caribana, North America’s biggest Carribean festival). 
     
    Quick googling suggests another possibility for differences above and below the great lakes: 
     
    Catharine Anne Wilson has written an excellent book on the group and chain migration of some 105 Ulster Scot families from the Ards Peninsula of County Down to Amherst Island, near Kingston during the 19th century. Her study concludes that these emigrants, who had remained in Ireland for roughly a century more than the classic Scotch-Irish migrants to the American frontier, were quite different from their distant cousins, taking a more cautious, rational and family-based approach to the migration process 
     
    Citation, for those who can find it 
     
    Catherine Anne Wilson, A New Lease on Life: Landlords, Tenants and Immigrants in Ireland and Canada, Kingston: McGill-Queen?s Univ. Press, 1994. For a shorter version of her work, see Catherine Anne Wilson, ?The Scotch-Irish and Immigrant Culture on Amherst Island, Ontario?, in Ulster and North America: Transatlantic Perspectives on the Scotch-Irish, edited by H. Tyler Blethen and Curtis W. Wood, Jr, Tuscaloosa: The University of Alabama Press, 1997.

  13. Just looking at the map, it almost requires a cost of living adjustment to carry useful data, but I haven’t been able to find a by county graph to even look at side by side… Still New England can’t possibly benefit by adding in CoL, can it? It’s set to get even MORE blue…

  14. Additionally, if you look at the Maine/Vermont border up top, there’s something fishy. (Additionally, Utah and Northern California). 
     
    I would check those counties to make sure those counties actually had hospitals before taking that data seriously… If a large number of sick or wounded people cross county lines to go to the hospital, you’re going to see a lot of counties with high lifespans simply because people need to leave when they are near death to find a hospital. (I wasn’t born in the same county my parents were living in at the time…) 
     
    There’s a lot of patches of dark blue in and around Minnesota that exhibit the same qualities (significantly longer lifespans in relation to immediate neighbors in relatively low density areas)

  15. @Ikram, you said… 
    I don’t know the composition of British immigration to Canada — I’ll see if I have time to look it up. I do know that Canada had the largest Orange Order in the world up to the Thirties, and Toronto had the world’s biggest Orangeman’s parade (today, the largest parade in Toronto is Caribana, North America’s biggest Carribean festival).I think it would interesting to explore the European descent (that I expect to probably be mostly British descent) from the time of Rupert’s Land and the Hudson Bay Company. 
     
    http://en.wikipedia.org/wiki/Rupert%27s_Land 
     
    I’d imagine that this is one of the oldest lines of British descent in North America. Or in Canada at least. 
     
    (I have some descent from this from my Father’s Mother side. Looking at what I know of that part of my family tree, it’s Scottish. But I don’t know if that’s representative of those people, in general, from the Rupert’s Land and HBC era.)

  16. I do know that Canada had the largest Orange Order in the world up to the Thirties 
     
    The “Orange” thing isn’t part of the symbology of rednecks in the US. Perhaps there was a different pattern of migration after the Revolution and people who wanted to keep that tradition went to Canada rather than the US. 
     
    I haven’t looked up the history, but a guess is that early Canada is likely to resemble early Virginia. The commercial sponsors of the colonies recruited working class English who had mediocre economic prospects, so males and areas around ports were selected for. In VA, a governor strongly favored the aristoi, so 20-30 gentry families came, determining the public culture but making only a small contribution to the gene pool.  
     
    There was probably a genetic selection process. Risk taking, but not impulsive gambling type risk. Openness to novelty. Naive optimism. Features of the American character (if that is the word) that many have found sometimes praiseworthy, and often regrettable.

  17. The HBC lands on the prairies were fur-trade areas — the only real long lasting settlement was the red river settlement. The descendents of that community are Mètis of Manitoba. You may also find descendents among the Cree (for example, the old residents of York Factory). 
     
    British settlement in Canada mostly dates from after the seven years war (except Halifax, founded 1759).

  18. Canada had an influx of Loyalists who didn’t support the Revolution. The four groups Fisher wrote up in Albion’s Seed had reasons to oppose the King, so those who left would have been from the working- or middle-class group. This would have been the source of immigration from England, so it’s difficult to say how much difference they made.  
     
    My ancestor in the male line could have been one. He showed up in the South Side of VA by 1764 aged 18. My Y markers are almost the same (one mismatch) as someone with the same surname whose ancestors were in MD by the early 18th Cent and are know to have come from Shropshire, well south of the Borderlands. My guy at first opposed the Revolution, only later changing his mind. He had property by that time, and may have professed support for the Revolution to avoid forfeiture.

  19. Very interesting. 
     
    I looked at the counties and my eye drifted to my county, dark blue. Then the county where I used to live, dark blue. Then the county my family lived in, dark blue. Then the counties of my spouse’s family, all dark blue. Makes me wonder if and why the long lived folks just hang out together. People in both our families live very long, even into the late 90’s for both men and women. Just anecdote, but makes me wonder. I remember my mother saying that when the Czechs moved to Texas the Germans grabbed the better land to keep the Czechs from getting it. I noticed the Czech counties were not as long lived as the German counties. Better land? genes? both? A long time ago I read that harder water was associated with longevity and some thought that contributed to the somewhat shorter life span in the South.

  20. Anonymous • Disclaimer says:

    One clear problem I see with your analysis is that there is a clearly non-linear relation between income and life expectancy. It appears to level-off above 45000, and drop sharply below 45000; looks like an exponential relation of some sort. You might try an inverse response plot to get an estimate of what the exponent might be. With an improved model you might draw somewhat different conclusions

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