Most of social science still operates as if there were no biological differences among human groups. This so-called “uniformitarian” assumption is pervasive and it works in the sense that a lot of research money falls into the social science hole. On the other hand there are several glaring instances in which it seems to fail badly: a typical response to these is to look embarrassed and quickly change the subject else to social-science-talk away at them, hoping they can be made to disappear.

A recent such instance is the “Hispanic Health Paradox” in which Hispanics in North America enjoy better health and live longer than Anglos. For example, the table on page 11 shows that Hispanic females have 2.7 more years of expectation of life at birth than do Anglo females, 83.1 to 80.4 years. If poverty is the cause of health disparities, how can this be?

An older instance is the “Black-White Crossover” in mortality between US Black and White populations. In North America death rates for Whites are notoriously lower than death rates for Blacks, so that the expectation of life at birth is about five years greater for Whites. This generalization holds at every age up to 70 to 80 at which times the hazard of death curves cross. Eighty year old Blacks live longer, on average, that 80 year old whites. A classic treatment is the monograph by Manton and Stallard (1984). Much effort by demographers has been directed at wishing this away but they just can’t get rid of it. Indeed, today a Google Scholar search of “Black White Crossover” returns a recent paper about breast cancer: Black women have a higher annual risk before about age 50 and a lower annual risk after that age.

A few years ago Renee Pennington and I (Pennington and Harpending 1993) did a lot of ethnographic research among Herero, about whom I often write in this blog. They are prosperous Bantu-speaking ranchers in the northern Kalahari of Namibia and Botswana. Unique in Africa, they have a system in which every year is given a name. Everyone knows not only the name of the year of his or her birth, they know the birth year names of their parent and grandparents and occasionally even further back. Herero are family fanatics, and you would know the birth years of your friends in the same way that in North America you are likely to know the middle names of your friends. In line with other posts at this blog about Herero, “family” has nothing much to do with marriage, and hardly anyone knew years of marriages and divorces. Year names are known back to the early nineteenth century.

Few Herero know how the year names map to calendar years, but there are specialists who curate year name lists. An informant might tell me that his grandfather was born in “onburra ojomevaomengi”, year of heavy rains. I could look it up in my copy of the name list and find it was 1854.

North American data about the crossover come from censuses mostly. How many 85 year olds were there in the state last year and how many deaths of 85 year olds? We were able to take advantage of the year system to estimate mortality statistics from family history interviews. We used life history information from living people and patched in information from partial lifetimes of other family members using a Kaplan-Meier kind of procedure. Details are in the book. At any rate our information was completely different in kind from census data from large North American populations. Both have weaknesses, and it is interesting to compare our estimated hazard of death curves with census results. Here are the estimated curves for US White and Herero males and females: The pattern, for what it is worth, is a great exaggeration of the North American pattern: the crossover occurs way earlier in the lifespan.

We have a brief discussion of the phenomenon in the book but we have never looked any further into the matter. I have been meaning to put a graduate student on the issue for years but I always forget. At any rate we did a quick and dirty sampling of world censuses and produced this scatter plot. The horizontal axis is expectation of life at birth, longer lifespans going east. The vertical axis plots the probability that a 75 year old will live to 80, higher survival from 75 to 80 going north. There is a lot of scatter but there is an interesting regularity. African populations are the furthest north, European populations in the middle, Asian populations at the bottom. At oldest ages African live the longest, Europeans are intermediate, and Asians have the shortest remaining lifespans.

This needs to be looked into. BTW the point with label “Botswana census 1981” is raw data from the census. What national censuses do in much of the world is cook their data until they follow like a standard generic European pattern. There are, after all, no biological differences between populations: we all know this as a sacred truth. The data point from the Botswana census is data before cooking: you will not see it in the final census product.

Next, is the African pattern of aging related to late age at paternity?

References

Manton, Kenneth G., and Eric Stallard. 1984. Recent Trends in Mortality Analysis. New York: Academic Press.

Pennington, R., and H. Harpending. 1993. The structure of an African pastoralist community: demography, history, and ecology of the Ngamiland Herero. Clarendon press.