September 16 &18, 2003
Demography and other social sciences
0. Preamble :Summary of statistics from the US
The following is a summary of basic stats for the US
__________________________________________________________
Sample demographic statistics for the US : 1950-2000
Source: Statistical Abstract of the US: 2002, US Census Bureau
Rates are o/oo and population are in millions
____________________________________________________________________
Year Pop
CDR CBR r
CmarR
CdivR
TFR
Eo (M-F)
1950 151
9.6
24.1
14.5
11.1
2.6
-
-
1960 179
9.5
23.7
14.2
8.5
2.2
-
-
1970 203
9.5
18.4
8.9
10.6
3.5
2.5
67.1-74.7
1980 226
8.6
15.9
7.3
10.6
5.2
1.9
70.0-77.4
1990 248
8.6
16.7
8.1
9.8
4.7
2.1
71.8-78.8
2000 289
8.7
14.7
6.0
8.5
4.2
2.1
74.1-81.4
2010 -
-
-
-
-
-
-
75.6-81.4
Total rate of increase 1990-2000~12.5
Mean age at childbearing (2000)~ 27.4
(1980)~ 25.2
If the prob of surviving from birth until age 25, S(25), approximately .990 in 2000.
What’s the NRR? (NRR~.495*.990*2.1=1.029)
=NRR is barely above replacement but r~6.0/oo is not zero. Why not?
(Note: an NRR=1.029 and Tg=27.4 imply r~.0010 or about 1/6 of the observed one)
=The doubling time implies by rate of growth 1990-2000 is 55 years; the one implied by
r is 115. Why the discrepancy?
=The momentum of pop growth should be:
{[(CBR*Eo)/(r*A)]*[NRR*(NRR-1)]}
{(.0147*79.5)/(.006*27.4)} *(1.029*.029)=.21
What does this number mean? Can it be interpreted?
Why the discrepancy between the inference made before and the inference we can make
from the momentum factor below
1. Lessons the contrasts between appearances and realities
In all cases examined during last class we identified some regularity--observed or
inferred--and proceeded to interpret it. The two most typical examples were the
following:
i. One abortion prevents one live birth
ii. Improvements in survival make populations older
iii. Age differences between partners are crucial for the spread of HIV/AIDS
First, in each of these cases we formulated a model to represent the observed or
inferred relation: (a) birth interval model for (i) and (b) stable population for (ii) and (iii).
In the case of (iii) I bypassed the sable model and instead we used a mental experiment.
We then proceeded to interpret the statement we were making about those relations.
The objective of today’s class is to show you that in order to build models for
demographic phenomenon we need to rely on the insights from other disciplines We
will tour the following areas: biology, economics, sociology and social psychology.
2. Relations between demography and biology
The points of contacts between demography and biology are many. I will focus on
fertility and mortality separately and provide examples that increase in order of
complexity.
In each case I will discuss two types of connections: “soft” and “hard”. What all
these points of contact show is how desperately demographers need the conceptual
machinery of biology to understand population flows and structures.
2.1. Two clarifications.
We need to define two sets of concepts:
2.1.1. Reproductive fitness
The reproductive fitness of any species can be assessed using the approximate
equality
exp(r*T)=NRR= ∑ 15-49 {Fx *S(x)}
when NRR~1 the species survives; when NRR>1 the species grows and when NRR<1
the species disappears. Thus, reproductive fitness is a joint function of the capacity to
reproduce and survival probabilities. In theory, members of a species could invest both
on increasing Fx and S(x); the latter strategy however requires heavier investments since
it implies expenditures in each and everyone of the offspring. Notice that it may well be
that changes in one (say fertility) may imply changes in the other mortality. That is, the
two dimensions may not be (and indeed they are not) independent.
2.1.2 Connections between biology and demography: soft and hard
I mean by “hard” connections where biology clearly constrains possibilities. For
example, women are NOT fecund beyond age 50. Mortality is HIGHER at age 60 than at
age 20. Gestation lasts between 8 and 9 months, etc…
On the other hand, “soft” connections involve evolutionary accommodation of behavior.
For example, low fertility levels may result in optimization of fitness of surviving
offspring and, if so, it is evolutionary desirable.
2.2. Fertility: hard connections
It is quite clear that fertility is biologically bounded; examination of our simple
formula to generate the number of children a women can have over a life time, shows it
clearly: age at menopause and age at menarche, time to conception, postpartum
infecundity etc…The same is apparent when one examines age fertility patterns.
The fact that fertility is biologically determined does not imply inevitability; quite
the contrary, the variation of fertility among humans now, and since the origins of
mankind, is enormous. Some of it is due to unintentional behavioral patterns which
indirectly affect fertility; some to intentional interference with the process of
reproduction
=Age at menarche and at menopause is a function of: nutritional levels; intensity of work;
altitude; patterns of disease (diabetes I, for example)
=breastfeeding inhibits ovulation and return of menses;
=fecundability (the monthly probability of conception) is somewhat fixed and depends on
sperm counts, ovulation cycles; as well as frequency of intercourse. These in turn are at
least partially determined by environmental conditions (for example, sperm counts are
declining apparently due to food contamination)
=The age pattern of fertility is probably hard wired and has maximized
reproduction and survival: lower fertility levels prevail at ages when care of children is
more demanding.
=Note the implication of the above: transmission of fitness-related genes can only
occur at ages below the upper limit of reproduction (issue of diseases of the aged)
=The curve of fertility declines rapidly as the genetic damage in both male and
female accumulates. The probabilities of normal births decline rapidly at ages above 45
=Why would long breastfeeding inhibit ovulation? Because it enables mothers to
provide maximum resources to a child, even though she may be involved in work
activities. Indeed, births that follow a short birth interval are exposed to higher mortality
risks and those who are followed by a short birth interval are even more exposed to the
risk of death. Thus, long breastfeeding and inhibition of ovulation is probably adaptive
and maximizes survival of the group (inclusive fitness).
=Why should areas with high levels of STD’s have lower fertility (STD does
decrease fecundability). Is STD’s itself a mechanism to keep population growth down? If
STD infected women were not sterile, would additional fertility endanger surviving
children?
2.3.Fertility: soft connections
Soft connections normally involve evolutionary premises (behavioral genetics):
=We are programmed to reproduce; but we are not useless at the end of
reproduction as older people have always been (a) depository of knowledge, memory and
(b) utilized to protect grand children. Keep this in mind when reading about the fact that
survival beyond reproduction is an evolutionary aberration
=Can one think that low fertility is a strategy that maximizes fitness that can get
passed on to subsequent generations? Suppose that a species discovered that with higher
levels of expenditures per offspring improves their fitness (better prepared to survive, be
successful and reproduce). However, the tradeoff is this: one requires a lower number of
offspring per generation. If so, one would expect that fertility goes down and that,
subsequent generations will do the same by virtue of heritability.
As Pinker puts it “kind acts toward our children benefit copies of the
genes that build a brain that inclines a person towards such acts”)
So, are we to conclude that low fertility is here to stay?
2.4. Mortality and morbidity: hard connections
As in the case of fertility there are some fairly well-identified connections
between mortality and morbidity, on the one hand, and biology, on the other.
First, age pattern of mortality (Mx’s) or survival curve has--as the fertility pattern does--a
universal shape. The “bathtub” shape reflects the following: (a) at the outset (ages 0-10)
there is fast adapting to environment; (b) middle range (10-40) slowly, quasi constant
mortality; (c) accumulation of genetic damage and systematic organ failure leads to
rapidly increasing mortality rates.
But, within the confines of what is biologically permissible, a huge array of
mortality patterns do exist. The variation affects LEVEL of mortality as well as AGE
PATTERNS. And these variations are in most cases determined by environment, social
and economic factors. But some are associated with biological conditions
Human mortality versus light bulbs: the model applicable to light bulbs or
machinery does not apply and we have a strangely shaped curve of Mx. Is this the result
of natural selection or simply reflects the failure processes of relatively complex
organisms/systems?
=early in life: large selections effects so that those less frail reach reproduction. But as
advanced in medicine occur, the high mortality around 0 recedes.
=middle life: the light bulb model applies with exceptions: violence among males and
maternal mortality among females increase mortality in middle ages
=late life: assumed to be a period of progressive deterioration. Experimentation with med
flies suggests the mortality curve can be increasing, constant, declining depending on
environmental conditions as well as manipulation of genetic materials.
Think of this: what if stem-cell research leads to ability to replace organs as they fail?
Can life expectancy be increased indefinitely? Or, equivalently, will the function Mx
become a constant or decline?
2.5. Mortality and morbidity: soft connections
Age patterns of mortality and morbidity have evolved through thousand of years.
The most important linkages between these and biology was engineered by infectious
organisms, their ability to evolve with us, our capacity to learn about them and to protect
themselves from them and, more recently, by our ability to tinker with their own
evolution.
Historians such as McNeill and McKeown suggest that an important part of
population history --and as a consequence of the formation of mortality and fertility
patterns-- is the mutual accommodation between humans and agents of disease. One has
to wonder then if what we see today, us, are the descendants of a branch that was able to
accommodate. Those that were not able to do so, are no longer with us. Thus, patterns of
mortality and morbidity must have been chiseled by natural selection.
i. Types of agents
virus………………………..polio, HIV
bacteria…………………….TB, rheumatic fever, typhoid, cholera, plague, tetanus
fungi……………………….histoplamosis
protozoa……………………malaria
Metazoa……………………hookworm
rickettsia……………………typhus
ii. Main types of immunological defenses
.
cell mediated……………T cells (thymus dependent//chromosome No 6)
(T4 cells are invaded by HIV))
blood mediated…………B cells, immunoglobulin producing molecules that bind
and neutralize invading organisms and are they disposed by scavenging cells
(macrophages)
iii. Some basic principles: diseases that are epidemic, endemic, sustainable size and herd
immunity
We need to keep in mind that the co-evolution of human and infectious diseases depends
on several factors:
transmissibility,
infectiousness,
incubation periods,
passive versus active carriers,
demand for vectors,
lethality of organisms
immunological status of the host.
There are important differences in transmissibility. For example, contrast HIV and
malaria. Or TB and cholera. Or plague and influenza.
Infectiousness is also highly variable: TB is highly infectious when the carrier is active
whereas even HIV is not so. Ebola is highly infectious
Ebola and HIV are at the opposite extremes of incubation periods and are offer
contrasting experiences regarding possibility of passive and active carriers
Hosts’ immunological status depends on previous exposure and nutritional status.
Accordingly, there are also different examples of coevoloution:
smallpox has become extinct whereas we have been able to adapt to TB and influenza.
However, note the dramatic effect of Spanish influenza in 1918-19.
scarlet fever became less and less pathogenic through mutations
measles is a disease that comes in waves, expressing itself among children who have not
been exposed to it before. Thus, provided that it is reintroduced from the outside (and this
requires that it be endemic in a population), measles will appear to proceed through
waves that last five years or so.
Improvements in nutritional status among humans appears to have played a major role in
controlling either the lethality or the pathogeneicity of diseases
Equilibrium between hosts and infectious agents may adopt a variety of forms: Some
diseases such as smallpox and measles were epidemic, others can become endemic (such
as HIV or malaria). Epidemic diseases required reservoirs out of which they could be
diffused and therefore areas of endemicity.
iv. Examples involving evolutionary links:
iv.1 Syphilis and blood group O among American Indians
The chromosome coding for blood group O contains a protein that increases resistance to
syphilis and makes it less likely. Almost 98% of American Indian belong to the same
blood group. This is an example of genetic drift, I believe.
iv.2. Malaria and sickle cell anemia
Hemoglobin S is a variant of hemoglobin A. It depends on one gene. Presence of
Hemoglobin A leads to a distortion in red cell membranes and this is called sickle cell
anemia (sickle cell shape of red blood cells). They are less able to operate as Oxygen
carriers. If the gene comes from both parents, it causes sickle cell anemia and death. If it
comes from only one parent then it is protective against malaria (the falciparum parasite)
though it may cause mild anemia.
Sickle cell anemia is widespread among Blacks in West Africa and the US and the
Caribbean
iv.3. Hypertension, slavery and over mortality of the Black population in the US
Surviving the trip from West Africa required ability to resist severe dehydration. This is
made easier by a set of genes that also induce high blood pressure (remember that
treatment of high blood pressure usually includes diuretics which allow individuals to
shed excess H2O)
iv.4 Mutations in agents of disease:
Genetic changes in agents that make them less virulent and lethal have occurred and may
account for mortality trends
=The bacillus causing the plague is thought to have become less virulent (circa
1400)
=Scarlet fever: ibid (circa XIXth century)
=smallpox: became extinct as a result of our intervention
=TB declined initially due to reduction in virulence? But, what about the new,
resistant forms?
Can one predict whether and how Ebola will change? Whether HIV will change?
iv.5. The case of respiratory TB
Important distinction: active and passive TB.
Prevalence of respiratory TB and associated mortality rates began to decline long
before the introduction of sulfa based drugs in the 1940’s or the BCG inoculation. Why
did this occur? There are at least three explanations:
(a) the most virulent variety of the bacterium went extinct and left only the milder
varieties;
(b) we evolved means to cut down the rate of transmission;
(c) we evolved means to reduce the rate of transition from passive to active cases
(nutritional status and better health environments)
iv.6 The most important change
Man tinkering with the genetic architecture of the agents or vectors themselves. I will
provide you a mind-boggling example of this: the attempt to engineer an anopheles
mosquito incapable of passing on the malaria parasite to a human host.
There is a current attempt to introduce into nature a mosquito that if supplied with a
particular gene, it cannot transmit the parasite that causes malaria. The question is: how
to make it dominate among all other, malaria carrier mosquito? The answer: those
carrying the gene who mate with non-carriers do not reproduce at all. Those who mate
with the a mosquito carrying the gene produce offspring!.
But, remember, once you release into the wild such a genetically engineered beast, you
will not be able to recall it….
3. Biology is not enough: the need for social science
But biology is not enough to explain the facts of demography. There is plenty of
variability in fertility, mortality and migration that simply cannot be accounted for
biological features of either the soft or hard type.
=Why, for example, was fertility relatively low in Western Europe during the pre-fertility
decline era (before 1850)? It appears to be attributable to a peculiar marriage pattern, the
result of high proportion of people who would never marry and very late marriage.
And this occurred because marriage and household formation was tied to the need to have
land or some type of property.
=Why did mortality decline so sharply after 1750? Surely there must have been some
evolutionary changes that took place and the resulted in, for example, decreases in TB.
But the bulk of mortality decline appears to be a product of social and economic forces.
Some as complex as those that led to increases in nutritional status and the emergence of
infrastructure that slowed down transmission by reducing exposure. Others were as
innocuous as washing hands and using soap. But in both cases there are factors related to
social organization and individual behaviors.
Moreover, there is strong evidence suggesting that the sharp economic transformation
experienced after 1900 may not have been possible if the disease environment had not
changed before.
=Why is breastfeeding so long in countries of Africa?
Surely, there is a biological mechanism in operation here (longer breastfeeding insures
survival through nutritional status and length of birth intervals) but it cannot be sustained
unless there are proper social props in place: post-partum intercourse is not practiced
precisely because of breastfeeding. If it were practiced, it could induce increases of
fertility beyond the sixth month after pregnancy.
=Why did fertility remain high in developing countries up until 1970 and then, except in
Africa, it came crashing down faster than ever before? Is there a biological reason for
this? Unlikely. It was probably due to changes in choices (preferences) and these are
affected by diffusion of ideas, adoption of new patterns of behaviors, some rational and
some not so rational. This is not biology, it is the matter of social and economic
constraints.
=Why does fertility in the US appear to follow long term swings even while a secular
decline is on course?
The so-called “Easterlin hypothesis” suggests that this has to do with the relation
between preferences sculpted during early childhood and constraints experienced during
the period of full productivity
The so-called “Caldwell-hypothesis” suggests that fertility props are a function of
whether or not there is a net flow of wealth from older to younger or from younger to
older generations.
Just as ideas play a role so do central states: think of those that block family planning
program initiatives or those that embrace the Catholic Church supporting status quo.
Culture is also important: adherence to some principles may make or break a fertility
decline. Why is Pakistan ‘s fertility so different from Bangladesh’s fertility?
These examples argue for a comprehensive view: we need to take into account biological
boundaries for demographic phenomena but also be alert to the role played by social,
economic, political and cultural facts.