Thursday, February 14, 2008

Cohort-Based Mortality

As has been outlined in the previous section, belief in the explanatory value of the traditional version of the demographic transition theory hinged, in part,on the idea that in the agrarian society which preceded the transition mortality was always and everywhere at a relatively high level, even if did, as a matter of fact, vary not insubstantially from one year to another. It is, however, precisely this assumption that has furnished one of the most important difficulties for the original version of the theory, since historical observers have long been able to confirm the proposition that death rates in pre-industrial Europe fluctuated widely from one decade to another over a time-span of centuries.

The McKeown Hypothesis

Awareness of this reality lead researchers to begin to explore a variety of issues associated with the social and medical determinants of health, and to examine how these might impact on mortality. The standard account of the 'great mortality decline' which accompanied the transition can in many ways be traced back to the work of Thomas McKeown (1976, 1979). McKeown argued that economic growth and better nutrition were the fundamental causes of the remarkable improvements in population health which were seen in Western Europe from the late 18th century onwards. His criticism of earlier views was based on a study of cause-specific mortality in England and Wales from 1838 to 1947, where he found that two-thirds of the mortality decline was due to a reduction in infectious diseases. In later work he also analyzed mortality rates and economic development for a wider group of countries and argued that, contrary to what was at the time the received opinion, medical advances had little direct influence on health before the breakthrough which followed the generalised use of sulphonamides and antibiotics in the 1930s and 40s. According to McKeon, up to this time the only disease that active medical treatment had been able to cure was diphtheria, and this even this was achieved via the use of an antitoxin whose existence itself only dated back to around 1900. Thus only a very small part of the pre-twentieth century mortality decline could , on McKeon's account, be credited to active medical intervention, and even where medical advance was pertinent - as in the case of the diphtheria antitoxin - it could hardly claim to have played a significant part in the mortality conquest, since the disease was in fact already in remission by the time the antitoxin was developed and widely available.

Addressing the earlier part of the mortality decline - from the late 18th to the mid 19th centuries - McKeown made the seemingly valid point that medical influence on one of the key 'killer diseases', smallpox, was not essentially attributable to modern medicine since vaccination (despite being available from the end of the eighteenth century) was not widely used in England until after 1840 when it became freely available at public expense. Gunnar Fridlizius has also drawn similar conclusions regarding the evolution of the decline in Sweden (Fridlizius 1984).

According to McKeown, while an improvement of personal hygiene may have had some effect on mortality in England and Wales after about 1880, when a decline in intestinal infections coincided with substantial improvements in water supply and sewage control, a change which must surely have reduced the incidence of waterborne infections. Since changes in mortality from intestinal infections constituted only a small part of the general mortality decline prior to 1870 the general reduction must have been in large part due to factors other than improved personal hygiene and equally those public health measures which were introduced must have had little impact on the great mortality decline prior to 1870 and only a partial effect thereafter.

In fact long before the time of McKeown researchers had been aware of the existence of apparently 'spontaneous' changes in mortality, and of the changes in population size that these seemed to produce (Helleiner,1957, Chambers, 1972, Fridlizius, 1984, Schofield,1984). In particular Helleiner argued, based on Western European data, that population sizes had fluctuated substantially with a marked increase occuring from the mid-eleventh century until the late thirteenth century and then again from the mid-fifteenth century to the end of the sixteenth century.

The population growth which occured in the eighteenth century was therefore not unique, except insofar as mortality started its decline from a higher level and then continued for longer than it had done previously. McKeown's argument is essentially that since the eighteenth century decline forms an initial (integrated) part of what was later to become the great decline, it is not plausible simply to view it as being a spontaneous decline, one which was due, for example, to a remittance in the virulence of pathogens. McKeown's strong argument seemed to lie in the fact that once started this decline then continued across the entirety of the two following centuries. In explaining the decline McKeown himself focused on the role played by nutrition, and argued that the nutritional improvement determined not only declining impact of infectious diseases from 1848 onwards, but also the initial phase of the decline which began in the late 18th century.

His intransigence over the idea of a common nutritional causal component, and his consequent 'condensation' of what some consider to be two phenomena into one is really the by-product of his laudable desire to find a single common explanation for the entire process of the great mortality decline.

Inflamation, and the Thrifty Phenotype Hypothesis

The Mckeown thesis, however, has not worn well with time (see, for example, Emily Grundy's review: The McKeown debate: time for burial, Grundy, 2005) and ideas which were to seriously challenge what had to all intent and purpose had become the "Mckeown consensus" were not long in appearing. The death knell was perhaps first tolled among what might seem a rather surprising congregation: the practitioners of modern epidemiology. In his seminal work "Mothers, Babies, and Disease in Later Life" (Barker, 1994), the epidemiologist David Barker brought together under one roof what was at the time a growing body of medical evidence which drew attention the apparent importance of fetal nutrition in the subsequent health of the mature adult. The "Barker hypothesis" - which is sometimes referred to as the "womb with a view" hypothesis (Deaton, 2005) - is essentially constituted by the idea that events in the womb have long-lasting effects on health throughout the entire lifespan, and especially effects on health outcomes that only express themselves later in the life course. More technically put, nutritional insults in utero, which prevent the foetus developing to its full potential, or which produce an adaptation ill suited to the external environment which the individual will ultimately encounter, may cause a selective abandonment of function, an abandonment which disfavors or disables precisely those features in the organism whose primary function is to prevent disease in late life beyond the normal reproductive span. While the hypothesis itself is still somewhat controvesial, evidence in support of it has been mounting in recent years.

In this context Gabrielle Dobblhammer and James Vaupel (Dobblhammer and Vaupel 2000, Dobblhammer, 2002), for example, have shown that life expectancy at 50 varies seasonally depending on the month of birth. According to their findings, in the northern hemisphere, 50 year olds in the cohorts studied who were born in the months of October and November (to mothers who perhaps had had better access to cheap and plentiful fresh fruits, vegetables, and eggs through most of their pregnancy) could expect to live about three-quarters of a year longer than those born in the spring.

In the southern hemisphere, the same seasonal pattern was found to occur, although with a six-month shift in the timing of the effect, while those born in the Northern hemisphere who die in the South (European immigrants to Australia, for example) continue to display the Northern pattern.

Other similar evidence comes from the Dutch famine of 1943, follow-up studies on which seem to support the claim that nutritional deficits in pregnancy have long-term consequences for, for example, obesity, with deficits in the first trimester of pregnancy predicting later adiposity, and deficits in the third trimester inhibiting it. There have even been findings which relate subsequent behavioural disorders and schizophrenia to early prenatal nutrition in this context.(Susser and Lin, 1992, Neugebauer, Hoek, Ravelli et al, 1998, 1999, Rosebooma, 2000, Susser, 1999, van der Zee, 1998).

Indeed, explosions of obesity and associated diseases (adult-onset diabetes, heart disease, and so on) have often been found to come come close on the heels of a loosening of nutritional constraints, when those whose parents were undernourished, who were themselves undernourished in utero, move into an environment in which food is plentiful and heavy manual work is no longer the norm. One study found, for example, that in the black township of Khayelitsha near Cape Town in South Africa, more than a half of the adult women had body-mass indexes above 30 (Case and Deaton, 2005).

One clear implication of the Barker hypothesis is that the health of the adult may be a function of birth timing: the when of birth. This has given rise to what has come to be called cohort analysis in epidemiological research, a line of investigation which attempts to explore how disease incidence and life expectancy vary across cohorts in differing (and especially extreme) environmental settings.

The Cohort Thesis and the Great Mortality Decline

As has been said, what later became known as 'the great mortality decline' began in Western and Northern Europe around the middle of the eighteenth century (in some cases possibly a little earlier), levelled off slightly in the mid-nineteenth century, and then continued an inexorable downward course. During this time life expectancy at birth rose from around 35 years to more than 70. In several countries the increase in life expectancy was, indeed, truly spectacular: For the earliest cohorts to have been systematically studied - Sweden 1751, France 1806, England 1841, and Switzerland 1876 - cohort life expectancy at birth was initially very low: 34 years in Sweden, 38 years in France, 42 years in England, and 45 years in Switzerland. By the 1899 cohort, however, life expectancy had jumped to 55 years in Sweden, 56 years in Switzerland, 53 years in England, and 50 years in France.

In these initial (prototypical) European cases mortality began to decline somewhere between 50 and 150 years before the arrival of the industrial revolution in each country and in any event significantly before living standards started their long monotonic upward movement. Also life expectancy normally tended to start to rise some 100 to 150 years before marital fertility started its long-term decline. It should be noted that there are important exceptions to this 'rule'. In England the decline in death rates started around the same time as the initiation of the industrial revolution, during, as it happened, a time of falling real wages, while in France, fertility started declining at about the same time as mortality did, and both of these changes again took place well before living standards started to improve. This having been said, it is noteworthy how the timing of the great mortality decline was strikingly similar across the countries of Western and Northern Europe despite the not insignificant differences in their respective levels of economic and social development. It was also often surprisingly simultaneous in different regions of the same country despite again the large differences in the internal economic development of the countries concerned. (Bengtsson, 2001).

Initially the decline was characterised by a dramatic and sustained decline in infant and child mortality, however later in the nineteenth century improvements in adult mortality also began to occur. Adult and old age mortality had in fact started to decline slowly right from the beginning of the nineteenth century, and possibly even earlier for England. But this decline became much more pronounced in the latter part of the nineteenth century and accelerated after World War I along with mortality at all other ages. The decline then slowed for adults and the elderly around 1950 but from the 1970s onwards it has once more continued apace (Crimmins and Finch, 2006).

In the context of the 'great mortality decline' when we talk about cohort-based health factors what we are normally talking about are factors which affect only certain generational groups, factors which may nonetheless may have longlasting effects on the lifetime health of those groups themselves.

In fact in terms of the great mortality decline 'cohort analysis' is essentially concerned with with two factors, improvements in nutrition and living conditions during the pre-birth foetal period and in early childhood, and the disease environment present during pregnancy and the early life years of a child. Both of these factors may, through their subsequent impact on health, be associated with longer term changes in life expectancy.

As suggested above, in the literature it is possible to identify two types of cohort-related explanations for the great mortality decline:

(1) increased nutritional intake during the foetal stage and/or early years of life, and

(2) decreased 'effort' during the foetal stage or early childhood being required to fight disease either on the part of the mother or of the child, or both.

In each case these factors operate not only through their impact on short term mortality but through their longer run effects on the health of the individual. One possible mechanism for this process may be via the imact of early life events on the rate of growth of the individual and how this affects long run health. (Mangel and Munch, 2005, Gluckman, Hanson and Spencer, 2005, Metcalfe and Monaghan, 2003). Certainly laboratory studies on rodents have found that severe caloric restriction retards growth (resulting in a small bodied adult) but also lengthens lifespan, which might be thought to suggest that fast growth can have negative impacts on subsequent mortality and lifespan (Rollo, 2002; Metcalfe and Monaghan, 2003). Calorie restriction of rats at young ages has also been found to have a tendancy to slow down growth rates and to lead to short adult stature, even when food becomes abundant later in the juvenile period (Shanley and Kirkwood, 2000).

Epidemiologists and demographers of an earlier generation, and who studied the modern mortality decline during the 1920s and 30s, were already aware of this 'early life history' possibility (Derrick 1927, Kermack et al 1934). They noticed that mortality for children declined much earlier than mortality for adults, and that each succeeding generation seemed to carry with it the same relative mortality from childhood though to old age. Distinguishing here between what are called period and what we have termed cohort effects, if period effects (that is environmentally significant imacts on health like more clement weather, or better nutrition, or rising living standards, operating across a given time period) were the dominant factor in the decline, then the heath consequences of these effects should be found to be evenly distributed between both young and old. If, however, this change is found to be asymmetric with one group showing a different pattern from the other, then there are arguably reasonable prima facie grounds for suspecting that cohort factors may be at work, and this in fact was the conclusion these early researchers began to draw.

In more recent times studies have continued to confirm the impact of cohort membership on health and mortality. Sam Preston and Etienne van de Walle , for example, in their study of urban France, and Gunnar Fridlizius, who examined the Swedish case, found such effects to be significant (Preston and van de Walle, 1978, Fridlizius, 1989). But in the realm of modern economic theory, and in it's interaction with economic history, there can be little doubt that if there has been one scholar who has done than any other to advance our understanding of how the cohort hypothesis might play a central role not only in epidemiological research, but also in our understanding of the process of modern economic growth, it has been Robert Fogel (Fogel, 1993, 1996, 2004).

In support of his thesis that cohort factors play a decisive role in the process of long term improvement in life expectancy Fogel used final heights as a proxy measure of net nutrition and health during childhood. Height is seen by Fogel as a cohort related measure of health, while weight and body mass index are seen as life-period measures (Fogel, 1996). On the Fogel account, individuals who, as a consequence of having had well-nourished and healthy mothers, were well nourished during the foetal stage experience lower death-risk during infancy. If they are well nourished and healthy their cells and organs develop better, they attain a greater height and tend to have a longer life.

Since here it is net and not gross nutrition that determines health and height, there is no direct link between gross nutrition during childhood, or GDP, and heights. This is because improvements in health and height may be the result of either better nutrition, or of reduced claims on health due to the impact of disease, or, of course, of both of these. Thus a decline in the prevalence of smallpox, for example, has a positive effect on heights and on the length of the life span, everything else being equal. One problem that immediately presents itself in this line of research is how to evaluate the extent to which the improvement in height and health is due to diet, as opposed to being due to lower claims from disease. Calculating diets for pre-modern populations is a difficult task (Fogel,1996), and it is even more difficult to calculate disease claims. Still, historical records do show similarities between trends in height and GDP (Fogel 1994, 1996), which suggested to Fogel at least that the trend in disease claims may have been been of lesser importance.

Now if Fogel is right here, then one important immediate consequence, and one that is central to his entire argument, is the absence of any single determinate equilibrium between food supply, population heights and population numbers: the relationship is characterised, in fact, by the esistence of multiple equilibria (Fogel 1994). Undernourishment, whether a result of low or badly-composed food intake, or a consequence of an increased disease claim, may rather lead to a stunting of height or weight and a higher incidence of illness, disease and mortality in later life as opposed to any notable increase in direct and immediate mortality. The one-to-one relationship (or period link) between economic output and mortality is thus much weaker than Malthus appears to have believed, at least on Fogel's account.

Now body size has received a good deal of attention in life history analysis (Roff, 1992, Stearns, 1992), and between species, body size is found to correlate with a number of life history traits, including mortality rates. In general large species, including humans, tend to have lower mortality rates and longer lifespans (Harvey and Zammuto, 1985; Gaillard et al., 1989). As a large bodied mammal, we have relatively low mortality and relatively long lives (though our lifespan seems to be proportionately longer than would be predicted by referring to our body size alone: Hill and Kaplan, 1999; Hill et al., 2001). Within species however the relationship between size and mortality is less clear-cut, since large size may offer some advantages, such as protection from predators, but these advantages do not come without cost, since, for example, there are greater nutrient requirements involved in maintaining a large body (Blanckenhorn, 2000). One complicating factor, as we have noted, is the speed of growth experienced during childhood, which is correlated with final adult height but may also have implications for mortality in adulthood.

The relationship between adult size (height) and mortality in humans has been extensively studied. Changes in height have been shown to correlate with mortality trends in both the US and the UK, with life expectancy appearing to rise with average height (Floud et al., 1990; Fogel, 1993), and being taller has been found to correlate with a lower mortality rate (Marmot et al., 1984; Waaler, 1984), but the situation may not be as straightforward as it appears to be. There is evidence that while the incidence of some causes of death, such as cardio-vascular and respiratory disease, are inversely related to height; others, such as reproductive cancers, increase in frequency with height (Barker et al., 1990; Leon et al., 1995; Smith et al., 2000; Song et al., 2003). There is therefore some debate as to whether being taller is as beneficial as it is sometimes thought to be (Samaras et al., 2003).

It is also not clear what the exact relationship is between measures of body condition and mortality. As in the case of height, there has been a good deal of research has into how exactly BMI interacts with mortality. The relationship is normally thought to be non-linear (Wienpahl et al., 1990; Rissanen et al., 1991; Laara and Rantakallio, 1996; Yuan et al., 1998; Engeland et al., 2003; Kuriyama et al., 2004). Individuals with low BMI experience high mortality rates, but those with high BMI do too.

Being short, on the other hand may also be considered to be an indicator of early life conditions, however when it comes to analysis, correlations are one thing, and explanatory mechanisms another. In this context indirect support for a modified variant of the Fogel hypothesis has come more recently from the work of Caleb Finch and Eileen Crimmins (Finch and Cribbins, 2004a, Crimmins and Finch, 2006). Finch and Crimmins advance the general proposition that a 'cohort morbidity phenotype' may serve as a representative of the inflammatory processes (disease claims) that persist from early age into adult life. Specifically Finch and Crimmins propose the hypothesis that decreased inflammation experienced during early life, which is associated with improved infant and child health, led directly to the subsequent decrease in morbidity and mortality resulting from chronic conditions found in old age. They point out that, for example, later life risk of heart attack and stroke is known to be correlated with serum levels of inflammatory proteins such as C-reactive protein (CRP). At the individual level, CRP levels are also correlated with the number of seropositivities to common pathogens, a relationship which tends to indicate a history of prior infections. Furthermore, drugs with anti-inflammatory properties (nonsteroidal anti-inflammatory drugs, statins etc) have been found to reduce the risk of vascular events and even possibly Alzheimer's disease. This kind of evidence may be read as implying the existence of links between levels of inflammation and major chronic conditions which are important in old age, and thus between exposure to infectious disease in early life and health in old age.

Now if we seek to apply these known correlations to the course of the great mortality decline, the early Swedish example assumes,due to its systematic character, considerable importance, and it is hardly surprising that Finch and Crimmins have recourse to the detailed, micro-level, work of Bengtsson and Lindström, as well as other earlier work based on aggregate data conducted in a UK context by William Kermack and the pioneering work (again using aggregated data) of HB Jones for Sweden (Bengtsson and Lindström, 2003, Kermack et al, 1934, Jones, 1956).

So, using the longer data series that is available today for Sweden (infant mortality data was not available to Jones for cohorts which had been born before 1895) Finch and Crimmins have updated Jones’ earlier work, detailing age-specific mortality rates for five birth cohorts in the years between 1751 and 1940. They find that mortality at any given age across the lifespan drops steadily across successive cohorts. Cohorts with lower young-age mortality also have lower mortality at any given age in later life, and this is entirely consistent with an earlier (and very interesting) Jones hypothesis to the effect that “the physiological age of each new generation is remaining more youthful at the same chronological age”.

As Finch and Crimmins emphasise the historical demography of Sweden offers an unparralled possibility of deriving unique mortality profiles across the entire life span, starting with the years immediately prior to the industrial revolution (when mortality was, of course, high) and following each cohort across the entire life course from birth to old age. Taking this data as their starting point they proceed to examine age-specific mortality trajectories for Sweden from 1751 right through to 1940, and find that the data offer support to the hypothesis that old-age mortality declined in a cohort and not a period fashion across all ages. In so doing they develop two points which were essentially already hinted at in the earlier work of Kermack et al. and Jones:

(i) that the historical mortality decline among the old and young begins in the same cohort, and

(ii) that infant mortality has a stronger relationship to later-life mortality than does mortality in subsequent childhood years.

They also conclude that declines in mortality after age 70 tend to lag about 70 years behind those for infants. When they relate childhood mortality to later-age mortality for Swedish birth cohorts born in the 177-year period from 1751 to 1927, they find strong relationships between rates of childhood mortality and mortality for cohort survivors in old age, indeed they found that most of the identified variance in cohort mortality was explicable in terms of mortality before the age of 10. Moreover, they also found that the annualized effect of each childhood year on old-age mortality was three times as great for infant mortality as it was for mortality in subsequent childhood years.

Based on this study of the Swedish data they go on to argue that the inflammatory-infection and Barker fetal-nutrition hypotheses may be seen not as competing but rather as complementary hypotheses, in that they jointly link the two mechanisms of morbidity between early and later life. As they argue, even well-fed babies are vulnerable to rampant infections, and infections alone can cause malnutrition and later dietary deficiencies. Childhood diarrheas, for example, impair cardiac muscle synthesis, and this could underlie the associations which have been found between infant diarrhea and later cardiovascular disease . As they suggest slowed infant growth under the Barker hypothesis could in part be consequent to infections that cause inflammatory responses as well as impairing nutrient absorption.

In a similar vein Bengtsson and Lindstrom, using longitudinal data, and following individual cases rather than relying on grouped aggregate data - a limitation which had characterised the earlier work of Kermack, Fridlizius, and others - have studied historical Swedish cohorts to test both the nutritional and the inflammation hypotheses. They did this by examining the effects of food prices and the disease load at the time of birth on subsequent old age mortality during the years 1766–1894. They conclude that the level of infection among infants was a stronger influence than food availability on later-life mortality and life expectancy. In particular they identify problems leading to the impairment of the respiratory mechanism as the principal source of this influence. (Bengtsson and Lindström, 2000, 2003)

Barbi and Vaupel - in a rejoinder to Finch and Crimmins (Barbi and Vaupel, 2004) - have objected to their findings on the ground that the most recent analyses of mortality patterns over age and time have revealed that period effects are generally more important than cohort ones in explaining mortality decline at the older ages and that, in fact contemporary demographic and epidemiological studies tend to suggest that the cohort effect is at best modest.. In defence of their position they cite, for example, the Danish twin studies which indicate that less than 10% of the variation in how long these twins live is attributable to variation in shared health conditions early in life ( McGue et al, 1993, Herskind et al, 1996). In particular they point out that, in developed countries at least, progress in reducing old-age mortality accelerated around 1950 and accelerated even further around 1970, doing so simultaneously at all older ages.

Finch and Cribbins (2004b) have responded to this by pointing out that since their analysis explicitly excludes modern birth cohorts, members of which have benefited from immunizations and the use of antibiotics, many of the points made by Barbi and Vaupel have limited validity in the context of their argument. They specifically hypothesize that inflammation associated with vascular disease and cancer (the incidence of which is attenuated by modern drugs with anti-inflammatory activities) is the strongest connective link between early and later cohort mortality and that such cohort inflammatory mechanisms are most active when mortality from infections is high. As childhood infection has decreased due to immunization, public health advances, and the use of antibiotics, early inflammatory exposure has had much less impact on cohort old-age mortality for the modern cohorts.

What we seem to have here are two interrelated, but distinct phenomena, the pre-1950 cohort-related effects of decreased childhood inflammation on average life expectancies, and the post 1950 improvement in mortality

rates at the older ages. At this level the arguments of Finch & Crimmins and Barbi & Vaupel are entirely compatible, with the former having a high degree of relevance to the pre-1950 situation, and the latter to the post 1950 one.Now analytically these processes are really quite distinct, as is the economic interpretation which can be given to each of them. Basically, following Finch and Crimmins, we might say that a predominance of cohort influences characterise the first stage, whilst (following Vaupel) period (or environmental and health care) influences characterise the

second one. It also raises the rather interesting point about whether Jones, when he observed that "the physiological age of each new generation is remaining more youthful at the same chronological age" may not have been looking at cohorts which came from the first stage of mortality decline, and not cohorts which form part of the elderly expectancy improvement we are currently seeing. If this is so the implications will be important.

As indicated above the age-specific mortality trajectories from 1751 to 1940 used in the Finch and Cribbins work strongly suggest that old-age mortality declined in a cohort, and not a period, fashion. The mortality trends at age 70 in any given calendar year, or the period mortality trend in old age, do not resemble the trend for the younger age groups. In fact they find that, following an initial rise after 1751, mortality declines first became significant in the Swedish 1791 cohort, and this at both the young and the older ages for that cohort. Period mortality, on the other hand, first declined significantly among the old in the years from 1861 to 1870, years, of course, which correspond to the very cohort in which the onset of the decline was first observed. Again, generally speaking child mortality trends correlate less with old-age mortality trends in the same year (period effect) than with mortality trends seven decades later (Finch and Crimmins, 2004b).

Barbi and Vaupel's critique has not, however, been completely barren, and it has forced Finch and Crimmins to sharpen and clarify their argument considerably. Hence, in a second, and subsequent, work on the same core topic (Crimmins and Finch, 2006) , where they extend their analysis to France, England and Switzerland, they are at pains to point out that they:

"focus exclusively on cohorts born before the 20th century, when levels of infection were high, but before smoking, a major inflammatory stimulus, became popular. Most importantly, these cohorts entered adulthood before general childhood immunizations and before antibiotics. The inflammatory mechanisms that we describe can only work when mortality from infection is high; once childhood infection is low, it can no longer be a factor in explaining old-age


In fact in their second paper Crimmins and Finch produce some really intriguing cohort-relative life-expectancy data. For the earliest cohorts they study (Sweden 1751, France 1806, England 1841, and Switzerland 1876) cohort life expectancy at birth was low: 34 years in Sweden, 38 years in France, 42 years in England, and 45 years in Switzerland. By the time we get to the 1899 cohort, however, life expectancy has jumped to 55 years in Sweden, 56 years in Switzerland, 53 years in England, and 50 years in France. In both cases the comparatively low life expectancies imply that all the cohorts (both the earlier and the later ones) were exposed to the then highly prevalent infections.

Confirmation of these Crimmins and Finch findings comes in more recent work from Tommy Bengsston (in association this time with Göran Broström). Bengtsson and Broström once more develop a methodology to try to test whether or not events which occur during the subsequent life course may mediate the effects of early-life factors on later life mortality, and in particular whether the degree of access to land in adult life plays any kind of role (Bengtsson and Broström, 2006). Bengtsson and Broström find no support for the null hypothesis that the influence of disease load in the first year of life is not permanent throughout life but is moderated by an individual’s socioeconomic condition later in life (and more specifically at age 50 years). They find that those who (according to the land-wealth criteria they use) could be considered economically unsuccessful by the time they reached 50 did not suffer more from the damage caused by the first year of life disease load than those who had done relatively well (economically speaking) and who had attained or retained access to land. They also find that those who were exposed to a heavy disease load in the first year of life, and who survived to be 50, had an estimated remaining median life expectancy of about two years less than those who were born in years with low to moderately high infant mortality: This is indeed an intersting finding as it makes exposure to infection during the birth year a more important determinant of later life health than sex or socio-economic status.

Similar results showing links between early infections and late-life health have also been found in the case of Union Army veterans in the United States using data from the current Health and Retirement sample (Costa, 2000).

As Crimmins and Finch also point out , maternal infections, including influenza, malaria, and tuberculosis, were common in Europe and the United States well into the 20th century (Riley, 2001). Babies of mothers with infections are known to reveal elevated inflammatory markers and retarded uterine growth (Moorman et al, 1999) and Crimmins and Finch even specualte that suboptimal adult female health may transgenerationally transmit the imprints of infections and inflammation as well as malnutrition while increasing the risk of smaller babies with lowered resistance to environmental pathogens. This additional path is not developed in the Barker hypothesis and is consistent with observations that improved infant mortality lags a generation behind the decline in adult mortality (Kermack et al, 1934).

Now at this point the argument becomes truly interesting. Fogel himself has recently proposed that a ‘‘techno-physiological revolution’’ increased energy available for growth and improved resistance to infection through a dual mechanism which both improved food production and at the same time lead to higher incomes which enabling an ongoing revolution in living conditions (Fogel, 2004). The Fogel hypothesis has been thought to present the difficulty that increases in height did not always follow increases in income and nutrition; and certainly not in the way his theory would anticipate. Height has even been found to have decreased during some periods of improving income in early industrial cities (Flood et al, 1990). However modifying (or blending) the Fogel hypothesis with the work of Crimmins and Finch it can be argued that a decrease in infections and ensuing inflammation had the potential to increase height independently of improved food intake, thus making the joint hypothesis far more compatible with the observed evidence.

Also, as Hillard Kaplan would argue, 'Life is an energy harvesting process'. More specifically this process is characterised by a series of trade-offs, of which the most important are those between growth, maintenance and reproduction. Since energy used for one purpose cannot be used for another (the ‘principal of allocation’), much of what has come to be known as life history theory is concerned with the functioning and impact of such energetic trade-offs. As Kaplan says:

"Organisms capture energy (resources) from the environment. Their capture rate (or income) determines their energy budget. At any point in time, they can "spend" income on three different activities. Through growth, organisms can increase their energy capture rates in the future, thus increasing their future fertility. For this reason, organisms typically have a juvenile phase in which fertility is zero until they reach a size at which some allocation to reproduction

increases fitness more than growth. Through maintainance, organisms repair somatic tissue, allocate energy to immune function, engage in further energy production, and so on. Through reproduction, organisms replicate genes. How organisms solve this energetic tradeoff shapes their life histories."

(Kaplan and Gangestad, 2004)

Mixing this further with an old idea of Lionel Robbins that 'economics is the science which studies human behavior as a relationship between given ends and scarce means which have alternative uses.' we can begin to see just how such trade-offs may have important implications.

Bengtsson and Broström, for example, find that:

"Children born in years with very high disease load, face more than 90 percent higher mortality than the others after controlling for all the covariates included in the model"

Well lets think about this for a moment, and lets think about it in the context of the behavioural relationship between scarce means and conflicting demands, in the context of Kaplans trichotomy between growth, reproduction and maintenance and lets go back in order to do so to Vaupel's original objection to Finch and Crimmins. Which was


"while Finch and Crimmins hypothesize that decreased inflammation during early life has led directly to a decrease in morbidity and mortality resulting from chronic conditions in old age.......demographic and epidemiological studies suggest that the effect is modest".

Well, as we have noted, this leads Finch and Crimmins to respond to Vaupel with a much sharper version of their argument. In particular the qualify their argument by stating:

"Our analysis excludes modern birth cohorts, individuals of which have benefited from immunizations and the use of antibiotics....(while)...The comment by Barbi and Vaupel incorrectly implies that death rates among the elderly in developed countries declined only after 1950.....As childhood infection decreases because of immunization, public

health advances, and antibiotics, the early inflammatory exposure has much less impact on cohort old-age mortality."

So what we have here are two interrelated, but distinct phenomena, the pre-1950 cohort-related effects of decreased childhood inflammation on average life expectancies, and the post 1950 improvement in mortality levels in the older ages.

Crimmins and Finch in fact clearly spell this in their 2006 PNAS piece:

"We focus exclusively on cohorts born before the 20th century, when levels of infection were high, but before smoking, a major inflammatory stimulus, became popular. Most importantly, these cohorts entered adulthood before general childhood immunizations and before antibiotics. The inflammatory mechanisms that we describe can only work when mortality from infection is high; once childhood infection is low, it can no longer be a factor in explaining old-age trends."

So inflammation is largely a pre-1950 issue (in the Swedish, but not of course, in the current developing world, context) and this is where things get, frankly interesting, especially if we think about Bengsston's finding that children born in years with a low disease load experience around 10% of the mortality exposure of children born in the high disease load years.

These (low disease load) children, not only survive in greater numbers, they also live longer, healthier (and hence logically more productive) lives. Now lets think of this in terms of Kaplan's tripartite trade off. And in terms of economics. And in terms of his embodied capital model.

Firstly the low disease-load years mean the mums need to invest less energy in reproduction, since more children survive. That immediately frees off more energy for growth and maintenance. But, since the children are healthier there is less expenditure on maintenance, or, what amounts to the same thing, the investment in maintenance is more

cost effective.

Then there is growth, and let's think here in terms of economic growth, since as Xavi Sala i Martin nicely points out:

"The relation between most measures of human capital and economic growth is weak. Some measures of health, however, (such as life expectancy) are robustly correlated with growth" (Sala i Martin, 2002)

Now, if we go back to Kaplan we should easily be able to see why this relation between growth and "growth" (which was also to some extent evident to Fogel) should be so.

Kaplan estimates that no child in any society is ever really self-sufficient till the age of around 20. Now in the low disease-load years, getting the individual child to 20, not only involves less maintenance energy, it also produces an individual with say 35 productive years out in front of them instead of. say, none, or at least considerably less than 35. The productive impact of this has to be enormous. Of course this productive impact can only be realised within a technological and institutional context that makes such realisation possible, but in the presence of this we seem to have here a huge increasing-returns type mechanism which can help explain why demographic processes are much more important to economic development and growth than has been hitherto modelled.

This also has very important implications for those contemporary societies where diahorrea and malaria etc are still huge killers, and might give us some indication of how societies which are still caught in this health trap will be able to grow once they break out. The finding is also important since it indicates that such a demographic 'dividend' is only possible in the cases of societies where child-health related inflammation is still an issue, and thus tells us

relatively little about the economic outloook for those societies where the major increases in life expectancy come from improving the outlook in the older age groups.

Is There An End State?

The sum total of everything which has gone before is that the fall in mortality which preceded the industrial revolution may be much better seen not as the start of something new, but as the end of something old. There was, of course, something new to follow (in the shape of better public hygiene, and later imporved medical intervention), but that something "new" did not come onstream until well into the nineteenth century, when general improvements in conditions of life, in the form of better diet, better housing, improved hygiene, better child care and better sanitary systems in the towns, effectively prevented a posterior mortality increase, an increase which had unfailingly taken place following all earlier periods of enduring mortality reductions.

This leads us to one rather obvious and uncomfortable conclusion: all those economic growth models which have predicated the rise of the modern 'growth era' on a fall in mortality consequent to the technology revolution which accompanied the industrial one may in fact have the causal arrows pointing the wrong way.

In the account of Galor and Weil (2000), for example, growing population, through its assumed effect on the growth rate of skill-biased technological progress, causes the rate of return to human capital accumulation to increase. This ultimately leads to sustained growth in per capita income. Jones (1999), argues that increasing returns to accumulable factors (usable knowledge and labour) cause growth rates of population and technological progress to accelerate over time, and eventually, it is this which permits an escape from the Malthusian stagnation. The reality, as we have seen, is more complex, and both the 'weakly-Malthusian' initial state, and the low-fertility, increasing-life-expectancy end state seem to be full of surprises both interms of their implications for the initial demographic transition theory, and for the economic growth theory explanations which have rested on it.

As I have already emphasised, following the initial mortality decline which marks the onset of the transition all societies are effectively ageing. This ageing is a continuous process, and at the present time it is hard to identify an indestructible natural barrier which stands in its way. In this sense the transition doesn't really seem to have an 'end state', and thus can hardly be called a transition, since the word transition seems to imply a movement from something to something. If, in fact, there is a transition it is one from a society homeostatically balanced around high mortality to one which is pivoted around declining fertility, declining mortality, and ever-increasing life expectancy. As Lutz emphasises we don't yet know if there is any lower bound to fertility, and as Vaupel suggests there is now no good reason to assume that life expectancy has any natural upper limit..

Having said all this, and in fairness to Ronald Lee and others who use the expression, what may be meant by the process of 'population ageing' may well be a society with a comparatively high proportion of dependent elderly, as indicated by a conventionally determined life-course anchor point, such as the retirement age.Following the Lee account the initial mortality decline creates a child dependency ratio which is considerably higher than that in the earlier agricultural society. This 'imbalance' takes many years to correct as fertility rates remain high and societies slowly recover the earlier ratios. But equilibrium is not restored, and, after an initial 'sweet demographic period' (which may, as we have seen really be a 'sweet immuniological period', dependency ratios once more start to rise, only this time the rise is amongst the elderly population. This transition is rooted in the structure of the human life history and its mortality representation, with the disease load being attacked asymmetrically, initially in the earlier years, then in the later ones.In fact, what many authors may mean when they talk of ageing societies are societies where elderly dependency ratios rise (and continue to increase) above a certain notional level, and this dependency increase is, in the longer run of things, simply the historical footprint and shadow of the earlier, initial, mortality decline (in other words what we may have is one single 'great mortality decline', or transition, otherwise known as the rectangularisation of human mortality).

The traditional demographic transition way of looking at the mortality decline does, of course, have a certain validity, but it does beg one very important - indeed possibly from a policy perspective critical - question: just what do we mean by 'old'. This expression, like similar socially relative terms - 'modern' and`post-modern' would be good examples - is a deceptive one, since it gives the impression of being carved eternally in time, when in fact it is, of course, extraordinarily relative to our life course and our life history evolution.. To give a simple illustrative example, a populist Turkish politician famously got himself elected during the early 1990s on the promise of introducing comprehensive male pensions starting at the age of 43, with female entitlement starting at the even more 'tender' age of 39 (a policy decision which, of course, resulted in one of the worst pension's crises in world history). The politician in question presumeably considered that the age of 43 was 'old', and those who voted him into power evidently agreed with him. The point really is that what we consider to be old is a socially defined (and hence relative) concept. It will hold different values at different times. In the Turkey of the 1990s life expectancy was not especially high when compared with that which which may now be anticipated in contemporary developed societies, an indeed similar, if not so spectacular, examples of the Turkish definition are to be found littered around the history of the third world. They correspond to an earlier, and rapidly transforming, shape associated with the population pyramids.

However as modern life expectancy breaches ever higher limits we can expect our definition of 'old' to increasingly adjust itself upwards accordingly, and in general we should probably keep our fingers crossed that Jones was right when he surmised - back in 1956 - that “the physiological age of each new generation is remaining more youthful at the same chronological age”.

Whatever the ultimate verdict on the validity or utility of the transition phases schema, we should not leave the topic without noting one last thing: those societies which enter their transition process later tend to pass through it at an ever increasing rate. In the case of the mortality decline component of the transition we can see that gains in life expectancy occured in the twentieth century in developing countries at rates which were very rapid by historical standards. In India, life expectancy rose from around 24 in 1920 to the contemporary level of 62 (a gain of 0.48 years per calendar year over 80 the 80 years in question), while in China, life expectancy rose from 41 in 1950–1955 to 70 in 1995–1999, (a gain of 0.65 years per year over 45 years.(Lee 2003) (Find some other data here, this is less than useless as an illusrtation, to myself, Edward). Like wise fertility transitions since World War II have typically been more rapid than those which occured in the nineteenth century, with fertility reaching replacement level in 20 to 30 years post onset, and then continuing to fall steadily, and apparently inexorably, in the direction of lowest-low fertility.. Fertility transitions in East Asia were particularly early and notably rapid, while those in South Asia and Latin America were slower in starting but now seem to be accelerating very rapidly (Casterline, 2001, United Nations Population Division, 2003).


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