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Offspring: Human Fertility Behavior in Biodemographic Perspective 2 Genetic Influences on Fertility: Strengths and Limitations of Quantitative Inferences Michael L. Rutter There are many different reasons why society should be interested in the number of children being born and the numerous factors that influence this figure. VARIATIONS IN FERTILITY First, it is well established that there are strong psychopathological correlates of fertility. Thus, the number of children born to individuals with schizophrenia has tended to be below the general population’s average (Jablensky, 2000). To some extent, this is likely to be a function of the social impairments that accompany schizophrenia, but it is also likely to be partly a function of the fact that, at least in the past, many individuals with schizophrenia have spent much of their adult lives in long-term hospital care. In addition, a contributory factor will be the effects on sexual behavior of the drugs used to treat schizophrenia. The situation could well change with the much greater use of so-called atypical drugs that are probably more effective in restoring near-normal social functioning and have lower rates of serious side effects. The expectation is that the use of these drugs will enable more individuals with schizophrenia to live in the community, and this could well have effects on the number of children born to them. Somewhat similarly, very few individuals with autism have children and very few are born to parents with autism, at least as traditionally diagnosed (Rutter et al., 1997; Rutter, 2000a). For the most part, this is probably a function of the substantial impairment in the ability to develop committed reciprocal social relationships, particularly love relationships. In
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Offspring: Human Fertility Behavior in Biodemographic Perspective recent years, genetic findings have made it clear that the liability to autism extends much more broadly than the severely handicapping condition that is traditionally diagnosed. Very little is known about the fertility shown by individuals with this broader phenotype. Conversely, antisocial behavior is associated with a larger average family size and a considerable tendency to start having children in the teenage years (Rutter et al., 1998; Moffitt and the E-Risk Team, 2002). Second, there have been major trends in fertility patterns in recent years. The average number of children born to each couple has dropped markedly in most industrialized countries, and in many European countries the number is well below 2—and hence below population replacement rates (Hess, 1995). This has been associated with a parallel marked rise in the average age at which individuals have their first child. It might be expected from these figures that there would have been a very sharp fall in the number of births to teenage parents, but at least in the United States and the United Kingdom, the drop has been quite modest. The implication is that there has probably been a change over time in the pattern of births. Another change has been a major increase in the number of multiple births in most industrialized countries, this being a consequence of an increase in the use of various methods of assisted conception (Derom and Bryan, 2000). Third, in many countries there are marked variations in average completed family size among ethnic groups. For example, in the United Kingdom the average number of children per family is much higher in people of Pakistani or Bangladeshi origin than in “white” families (Modood et al., 1997). There are even more marked differences in the pattern of births. Thus, in the United Kingdom the proportion of children born to one parent of Afro Caribbean origin and one Caucasian parent is very high, whereas the comparable figure is very low for those of Bangladeshi origin (39 versus 1 percent). Similarly, in the United Kingdom there are very marked differences among ethnic groups in the proportion of children reared by a single parent (Modood et al., 1997). Concerns have been expressed over evidence that in many countries there has been a marked fall in men’s sperm counts (Bostofte et al., 1983; Swan et al., 1997). It is not clear whether this has resulted in reduced male fecundity, but there may have been some effects of that kind. Whether there have been parallel changes in female fecundity is not yet known and the fecundity in both sexes needs to be considered in relation to possible effects on number of births (Joffe, 2000). Finally, there is much evidence of major changes over time in a range of behaviors likely to influence fertility (Rutter and Smith, 1995). For example, there has been a substantial fall in the age at which children first have sexual intercourse, and there has been a marked fall in the proportion of children born within a legal marriage and a corresponding rise in those
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Offspring: Human Fertility Behavior in Biodemographic Perspective born to unmarried couples who live together in a committed relationship, with the child’s birth being registered in the names of both parents. Divorce rates have risen markedly in most industrialized countries, and there has been a corresponding increase in complex family arrangements involving multiple social parents with children coresiding with a mixture of children born to different pairs of parents (Dunn et al., 1998). Lastly, the ravages of the AIDS (Acquired Immune Deficiency Syndrome) pandemic in many parts of the world, especially southern Africa, are having a devastating effect on family patterns due to the very high death rate among young adults still in their childbearing years. This brief summary of just a few of the main correlates of variations in fertility serves to emphasize the multiplicity of influences likely to affect people’s behavior in relation to mating and childbearing. In addition, of course, the figures on the number of surviving children per couple will be hugely influenced by the rate of infant mortality, which has fallen greatly in the past 100 years (McKeown, 1976). These multiple influences need to be kept in mind when considering possible genetic influences on fertility. A word about terminology is necessary. “Fecundity” and “fertility” are often used interchangeably (and dictionary definitions encourage this). However, in terms of attempts to understand causal processes, it is helpful to have a means of drawing a distinction between variations in the biological ability to have children and variations in the number of children born to particular groups. Throughout this paper, fecundity will be used to refer to the first (i.e., biological ability to conceive) and fertility to the second (i.e., number of births). RATIONALE OF QUANTITATIVE GENETIC RESEARCH STRATEGIES Geneticists have been aware for a long time that similarities between parents and children on some trait or even a familial loading on traits across a broader kinship do not allow an inference about genetic mediation. That is because parents both pass their genes on to their children and shape and select the rearing environments for them. In addition, families will be open to broader societal, environmentally mediated, influences that can create clustering effects. Sophisticated statistical techniques, such as segregation analyses, that can be applied to family data have often been used to infer modes of genetic transmission. However, they are open to numerous methodological hazards and can easily give rise to misleading conclusions. McGuffin and Huckle (1990), with their tongues firmly in their cheeks, illustrated this nicely with their demonstration that attendance at medical school was due to a single recessive gene that was transmitted along Mendelian lines!
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Offspring: Human Fertility Behavior in Biodemographic Perspective Accordingly, reliance has been placed on natural experiments that, in one way or another, can separate genetic and environmental influences. These tend to be thought of in terms of twin and adoptee research strategies. However, both actually involve several different research designs that differ in their patterns of advantages and disadvantages (Rutter et al., 1990, 1999, 2001). Thus, for example, twin strategies include comparisons of separated and nonseparated twins and also studies of the offspring of twins. Similarly, there are several different varieties of adoptee design. Twin Designs Equal Environments Assumption The traditional twin design is predicated on the fact that monozygotic (MZ) pairs share all their segregating genes, whereas dizygotic (DZ) pairs, on average, share just half. The contrast between within-pair correlations or concordances in MZ pairs and DZ pairs can be used to infer the genetic effects on population variance for any particular trait. However, various additional assumptions have to be made. The most important, by far, of these is the equal environments assumption (EEA). This specifies that the environmental variance in MZ pairs is closely similar to that in DZ pairs insofar as the environments are associated with the trait in question. It should be noted that the assumption does not require that the environmental variances in the two sorts of the pair are the same but only that, insofar as they are different, they do not relate to the trait being studied. Thus, MZ pairs are much more likely to be dressed alike than are DZ pairs, but this is of no consequence for the vast majority of traits. However, there are some features that, although not directly related to mating behavior or procreation, are likely to influence it. For example, this would be likely to apply to both physical attractiveness and age at puberty. Nevertheless, this is unlikely to violate the EEA because the features are very strongly genetically influenced and therefore would be unlikely to lead to within-pair differences in most circumstances for most traits. On the other hand, such features may be very informative because they could indicate the route by which genetic effects are mediated. Thus, it is not implausible that part of the genetic effects on population variance in fertility could derive from genetic effects on either physical attractiveness or age at puberty (although it is most unlikely that that is the only mode of genetic mediation). Most reviews by behavior geneticists (e.g., Kendler et al., 1994) have concluded that there is a lack of evidence for violation of the EEA. However, recent evidence has shown that this conclusion is mistaken (Rutter et al., 1999, 2001). It is necessary to note why the conclusion is mistaken as well as its implications for inferences about genetic effects.
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Offspring: Human Fertility Behavior in Biodemographic Perspective Violation of the EEA will come about when two conditions are met. First, there must be a gene-environment correlation. This is necessary because that is the way in which an environmental variance difference between MZ and DZ pairs will arise. In other words, there must be a genetic effect on some environmental feature with the result that the within-pair correlation or concordance for that feature will be greater in MZ pairs than in DZ pairs. Second, the specific environment that has shown evidence of a gene-environment correlation must relate to differences in the trait in MZ pairs. This second condition is necessary because, if it is not, although it may affect influences on other traits, it will not affect the validity of the MZ-DZ comparison in relation to the trait being considered. Evidence for violation of the EEA is available for life events in relation to the liability to depression and the effects of parental negativity, hostility, or criticism on antisocial behavior. That is, parent-child negativity toward each twin is more similar in MZ than DZ pairs, but even in MZ pairs the differences found in negativity are associated with within-pair differences in antisocial behavior. Because MZ twins are genetically identical with respect to the DNA they inherit, the effect of the negativity must reflect some form of environmental mediation. The consequence is that some (but only some) of the MZ-DZ differences will reflect environmental, not just genetic, effects. Although the conclusion up to now has been resisted by most behavior geneticists, it must be inferred that violation of the EEA is likely to be quite common. That is because gene-environment correlations have been shown to apply to a very broad range of behaviors and are, indeed, likely to be operative with any environment that is susceptible to shaping or selecting as a result of individual behavior. Moreover, there is a good deal of evidence that environments affected by gene-environment correlations are also ones that create an environmentally mediated risk (as demonstrated by genetically sensitive designs; see Rutter, 2000b). Two further points must be made with respect to possible violation of the EEA. First, some of the differences go in the opposite direction. Thus, the birth-weight differences in MZ pairs tend to be greater than those in DZ pairs. In part, this arises from the transfusion syndrome in which there is a shared circulation between the twins that results in one being “overstuffed” with blood and the other relatively exsanguinated (see Rutter et al., in press). This can only arise in monochorionic MZ pairs and never DZ pairs. Second, there is probably no violation of EEA with respect to those traits in which, although there is multifactorial determination, there is no known specific environmental effect. That would apply, for example, to both schizophrenia and autism. In other words, violation of the EEA must be considered a trait-specific phenomenon and not something that is applicable in all circumstances to all traits. The question, then, is how much this violation of the EEA is likely to
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Offspring: Human Fertility Behavior in Biodemographic Perspective matter with respect to heritability estimates. That is difficult to quantify. What is clear is that, when there is violation of the EEA, part of the effects attributed to genetics will in fact be due to the environment. The net effect is that the estimated heritability will be somewhat too high. That sounds as if it ought to be a major concern, but in practice it probably does not matter as much as one might think. For example, say, an estimated heritability of 40 percent were, in actuality, one of 30 percent, the difference would have no implications for theory, policy, or practice. That is because the level of heritability carries no necessary implications about the ease or difficulty of a change as a result of altered environments. Of course, it would matter if violation of the EEA completely eliminated a genetic effect as previously shown on traditional analyses. Because that has not been put to the test, it is not possible to be definite, but it is quite clear that that is a most implausible consequence. Where violation of the EEA does matter rather more is in quantification of the effects of specific measured environments. Because they apply to just a portion of the overall environmental effect, they could be influenced to a much greater extent than the overall proportion of the variance attributed to genes or environment. It is necessary, too, to go on to ask whether violation of the EEA is likely to apply to quantitative genetic studies of fertility or, more importantly, to the different traits that together make up the influences on fertility. Because the relevant analyses have not, as yet, been undertaken, it is, once more, not possible to be definite. However, one may infer that some behaviors influencing fertility will be subject to violation of the EEA (that would apply, for example, to antisocial behavior) but it is less likely that it will apply to other features (such as physical attractiveness or age at puberty, neither of which are likely to have much of an effect in MZ pairs). However, with respect to the role of education as an influence on fertility, as discussed in other chapters in this volume, it is quite likely that (although not as yet examined) there may be violation of the EEA. That is because there is good evidence of genetic influences on scholastic achievement (Thompson et al., 1991; Walker et al., 2002) and because environmentally mediated effects of education are probable. Sampling As is the case with any research design, the validity of conclusions deriving from twin studies is heavily dependent on the quality of the sampling. Many twin studies have been based on volunteers of one kind or another and, even with samples based on the general population, the final usable sample is necessarily dependent on those who agree to participate. It has been very common for MZ pairs to be overrepresented in twin samples, and, clearly, this constitutes a potential source of bias. There are no good
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Offspring: Human Fertility Behavior in Biodemographic Perspective data that would enable an accurate estimate of resulting bias, but, in any case, this will be enormously influenced by the factors associated with willingness or unwillingness to participate in research on twins. Nevertheless, there is reason to be cautious in view of the known possibilities of bias (Berk, 1983; Taylor, 2002). A second aspect of sampling that matters is the fact that very few studies of twins have included adequate numbers of either ethnic minorities or seriously socially disadvantaged or other high-risk families. This matters because genetic effects may not be equally strong at all points on the distribution of traits. For example, Rowe et al. (1999) found that genetic effects on educational attainment were most marked at the top of the range and least marked at the bottom. Similar effects could well apply to at least some behaviors associated with variations in fertility. As repeatedly emphasized by behavior geneticists, it is important to appreciate that all estimates of heritability are both population specific and time specific. That is because the statistic is solely concerned with variances in the population studied, and therefore the analyses can only apply to the sample providing the data. If environmental circumstances change, either through the introduction of new environmental influences or because existing ones become more powerful or much weaker, there will be consequent effects on estimates of the strength of genetic influences on population variance. Exactly the same applies, of course, if the changes involve a strengthening or weakening of the pool of susceptibility genes in the population. Heritability is not a measure of the strength of genetic influence at an individual level, it is not a direct function of a particular phenotype, and it is not a reflection of gene frequency or pattern. Accordingly, although heritability is a most useful population statistic, it can (and sometimes does) change rapidly if environmental circumstances or population composition are altered. The rapid change does not mean there has been any change in gene action as it operates within individuals. That is not to say that environmental circumstances cannot influence gene frequencies; both thalassaemia and lactose intolerance provide examples where that seems to have been the case (see Rutter and Silberg, 2002). With respect to genetic influences on population variance in fertility, there has been emphasis on the ways in which heritability has risen or fallen in an apparently meaningful way in relation to changed environmental circumstances (Kohler et al., 1999). The findings are interesting, but there must be a good deal of skepticism about secular trends in view of the highly conflicting evidence from cohort studies that have examined changes over time in relation to traits for which there have been probably relevant changes in environmental circumstances. For example, Heath et al. (1985) found an increase in the heritability of educational attainment in Norway for males but not females over a time period in which educational opportunities
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Offspring: Human Fertility Behavior in Biodemographic Perspective became more widely available. Why should this have applied to one sex and not the other? Conversely, Kendler et al. (2000) found a rise over the 20th century in the heritability of smoking in women but not men. Again, the same question arises. The need in each case is to develop focused hypotheses on why there might be a meaningful sex difference that reflects different patterns of causal processes. The alternative, of course, is that the processes are similar in males and females and that the observed difference reflects only a failure of replication due to chance variation or error. Possible sex differences need to be taken seriously, but they call for rigorous research to test their reality and, if real, their causation (Moffitt et al., 2001; Rutter et al., 2002). By contrast, Heath et al. (1993) found no difference across cohorts in the heritability of smoking initiation. In a Finnish study, Silventoinen et al. (2000), found a marginal increase over time in the heritability of height (from 76 to 81 percent), but such a small change is not likely to have much theoretical or practical significance. It may be concluded that the research strategy of looking at secular trends is potentially useful, but the results so far have been rather inconclusive. That is probably because so much depends on the specificity of measures and the nature of samples, as well as the fact that the confidence limits for heritability are typically rather wide. In recent years there has been increasing reliance on statistical modeling in order to provide for more precise estimates of genetic and environmental effects. The basic principle is primarily one of parsimony. In other words, if there is no worsening of a model when one effect is dropped, it may be assumed that the particular effect is not needed. Accordingly, the estimates are recalculated after dropping that variable. In most cases the consequence is an increase in the estimate of genetic effects (although that need not be the case). It sounds like a perfectly reasonable approach, but the problem is that, when confidence limits are very wide (as they often are), an effect may be dropped even though it might actually be quite strong. Also, such modeling procedures can give rise to findings that obviously cannot be valid (see Rutter et al., 1999, for examples). Accordingly, although modeling approaches definitely have their place, they need to be treated with a certain amount of caution. It may often be prudent to rely primarily on the full model in which all the relevant parameters are included. Gene-Gene Interplay Typically, traditional genetic analyses assume that all genetic effects are additive. However, it is known that in some circumstances there are synergistic interactions of a nonadditive kind. Sometimes, these involve interactions between different alleles of the same gene (usually referred to as dominance), and in other cases they arise through interactions between
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Offspring: Human Fertility Behavior in Biodemographic Perspective different genes (termed epistasis). The most obvious pointer to the likelihood of the operation of such synergistic genetic effects is provided by the finding that the correlation within DZ pairs is well below half of that in MZ pairs. This comes about because, although DZ pairs share, on average, half of their segregating genes, they will share only a quarter of two gene combinations and an eighth of three gene combinations, whereas MZ pairs share all their genes and all their gene combinations. Such effects have been found for both autism (Pickles et al., 1995) and schizophrenia (Moldin and Gottesman, 1997) as well as for some personality traits. Caution is needed in inferring dominance or epistasis because the same divergence between MZ and DZ pairs can arise from contrast effects in ratings of behavior (see Simonoff et al., 1998). Critics of behavior genetics are fond of attacking it on the grounds of the unwarranted presumption of additivity. However, behavior geneticists are well aware of this issue, and it is commonplace nowadays to make explicit tests for dominance or epistatic effects. Moreover, it is perfectly straightforward to include these in any overall model. There is a need to consider such effects, but their likely existence for some traits is not a justifiable reason for doubting behavior genetics. Gene-Environment Interplay A somewhat similar issue arises with respect to assortative mating, gene-environment correlations, and gene-environment interactions. Again, old-style traditional genetic analyses have usually made the assumption that none of these are sufficiently operative to warrant being taken into account. It is now clear that for many traits that assumption is unwarranted. Thus, although there is little assortative mating for personality traits, there is substantial assortative mating (in terms of like mating with like) with respect to educational attainment and antisocial behavior (Farrington et al., 1996; Krueger et al., 1998; Plomin et al., 2001), to give two rather different examples. There is also extensive evidence of gene-environment correlations (Plomin, 1994) and growing evidence of gene-environment interaction in relation to emotional and behavioral disturbances (Rutter and Silberg, 2002). Three points need to be made on this topic. First, unless there is evidence to the contrary, it ought to be assumed that there may be assortative mating, gene-environment correlations, or gene-environment interactions. These should be tested for and, where relevant, included in the analyses. Second, as ordinarily presented, gene-environment correlations and interactions will be included in the estimate for genetic effects, despite the fact that they actually reflect the combination of genetic and environmental influences operating together. On the other hand, it is perfectly possible to disaggregate the genetic term into the portion attributable to baseline ge-
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Offspring: Human Fertility Behavior in Biodemographic Perspective netic effects and the portion reflecting gene-environment interaction (see Silberg et al., 2001). Third, although it has proved problematic up to now to model the effects of gene-environment correlations and gene-environment interactions simultaneously, it now seems that use of Markov chain Monte Carlo techniques provides a way forward (Eaves and Erkanli, in press; Eaves et al., 2002). Accordingly, it should now be possible to determine not only the overall genetic effect but also the extent to which this operates through gene-environment correlations and interactions. Other Concerns Regarding Behavior Genetics Over the years, numerous concerns of one sort or another have been expressed in relation to behavior genetics. For the most part, they fall under one of four headings. First, there are the issues that arise out of the biology of twinning. Twins differ from singletons in having a substantially higher rate of obstetric complications at birth and a somewhat higher rate of congenital anomalies (Myrianthopoulos and Melnick, 1977; Rutter et al., 1990). Also, there is the possibility of placentation effects—meaning the effects of the twin pair sharing the same chorion or having two different chorions (Machin and Still, 1995). Evidence on the importance, or otherwise, of such biological differences is fragmentary. They appear to be of negligible importance in relation to language development (Rutter et al., in press), but they might be more important for some kinds of psychopathology (Davis et al., 1995; Prescott et al., 1999). Second, there is the possibility that the postnatal rearing environment of twins may be somewhat different from that of singletons. The mothers of twins tend to be much more stressed and to have a somewhat higher rate of depression. They also tend to communicate in a somewhat different way because of the different “press” of having two young children at the same developmental level (Thorpe et al., in press). These findings have been shown to be relevant in relation to language development, but it is quite uncertain whether or not they have effects on other behaviors. Certainly, it seems unlikely that the effects will ordinarily be sufficient to invalidate the twin strategy. Third, there are problems of sampling, which have been raised most forcefully in relation to the two main studies of separated twins (Kamin and Goldberger, 2002). In my view there is some validity to these concerns, and it would be prudent not to place too much weight on separated-twin studies. One of the potential advantages that has been put forward is that they cannot be open to the problem of violation of the EEA because they have been separated and have not had contact with one another. However, this reflects a serious misunderstanding of EEA. Although, of course, separation eliminates the influence of contact, it definitely does not remove the poten-
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Offspring: Human Fertility Behavior in Biodemographic Perspective tial effect of gene-environment correlations that could affect environments that matter. Fourth, concerns have been expressed over the fact that measures of many traits do not show a normal distribution (Capron and Vetta, 2001). This is not a valid criticism because there is no necessary assumption that the “true” distribution is normal and because there are various statistical techniques that can be used to normalize distributions and hence to make them more suitable for the usual genetic analyses. There is no reason to suppose that this creates a significant problem. Adoptee Studies At first sight, adoptee designs might seem preferable to twin designs because they provide a cleaner separation of biological heritage and rearing environment. For that reason they have indeed proved very valuable with respect to some phenotypes, most particularly schizophrenia (Kety et al., 1994). However, there are more limitations to adoptee designs than usually appreciated by behavior geneticists. To begin with, social agencies select prospective adoptive parents on the grounds that they will provide a good rearing environment. Of course, they succeed in that goal to only a limited extent, but there is no doubt that extremely adverse environments are greatly underrepresented in samples of adoptive parents (Rutter et al., 2001; Stoolmiller, 1999). Also, adoptive parents tend to be older and better educated than biological parents in the general population. In addition, women who give up their children for adoption are far from a random sample of the general population. With respect to the study of fertility, there is also the obvious problem that, by definition, biological parents cannot include any individuals who have not had children. Finally, in most industrialized countries the number of nonhandicapped children adopted in infancy has dropped greatly. Intercountry adoptions have risen pari per su but these involve a much more complicated situation, often including serious early deprivation and adoption after infancy (Selman, 2000). For all these reasons, it is not likely that adoptee studies will have a major place in the study of fertility, and because, so far as I am aware, there have been no adoptee studies that are relevant, these designs will not be considered further here. Evolutionary Considerations If only because the theory of evolution is based on natural selection for reproductive fitness, it is necessary to consider how evolutionary theory might inform the quantitative genetic study of fertility. Indeed, as other chapters in this volume illustrate, it does include most useful pointers as to
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Offspring: Human Fertility Behavior in Biodemographic Perspective Rather, it influences the biological substrate of these traits, but variations in the level of the trait are influenced by environmental, as well as genetic, factors. That raises the crucial parallel issue of the need to determine what environmental influences do to the organism. Are they having effects on the same biological substrate that is influenced by genetic factors or, instead, are they operating in a rather different way? There has been scarcely any research on this issue, and it is much needed. Potentially, the identification of susceptibility genes will be particularly useful in the study of nature-nurture interplay. The study of gene-environment correlations and interactions has necessarily been a rather uncertain enterprise when it had to rely on “black box” analyses with anonymous genes. This situation will be transformed once it is known which genes these are and what they do. However, if multiple genes are involved (and that will usually be the case), the gains will not be great until most of those genes are identified. Simply finding one gene with very small effects is not likely to be very helpful. Throughout the whole of this enterprise, it will have to be borne in mind that determination of biological effects will not provide an answer in itself because there will always be further need to determine whether they account for the particular features that have been studied. For example, research has shown that, to a considerable extent, the sex hormone testosterone plays a major role in sex drive in both men and women. However, it has also been shown that testosterone levels are hugely influenced by social experiences. Thus, levels tend to rise in the winner of competitive chess or tennis games and fall in the loser (Booth et al., 1989; Mazur et al., 1992). Also, although it is clear that the surge of testosterone levels at puberty is largely responsible for the rise in libido at that time, it is nowhere near as clear whether individual variations in testosterone level in adult life account for individual differences in sexual activity, let alone with the more indirect connections with fertility. Again, the relevance of testosterone levels for group differences in fertility is even more open to question. Although almost anything is possible in biology, it does not seem plausible that this is responsible for the major ethnic variations in average completed family size or the fall in the same over time in most industrialized countries. ETHICAL ISSUES Some critics have raised concerns that the behavior genetics study of social behaviors and evolutionary theory will lead to a highly misleading impression of biological determinism that will bring about a neglect of research into social influences and, even worse, to a failure to act to alleviate or counter adverse social influences (Rose, 1995, 1998; Rose and Rose, 2000). Although a few scientists have made unwarranted claims that could
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Offspring: Human Fertility Behavior in Biodemographic Perspective justify that impression, the main messages from genetics and evolutionary theory actually point in the opposite direction. Genetic influences are probabilistic, not determinative, in the case of multifactorial behaviors, and often they act through indirect routes that involve an intrinsic interplay between genes and the environment (Rutter and Silberg, 2002). That consideration makes it crucially important to support research that brings the two together and not separate them. Evolutionary theory has led to a valuable corpus of knowledge on biological forces that are likely to operate in relation to fertility, and it would be foolish to neglect the insights that it provides. On the other hand, as other chapters in this volume note, it is much more directly helpful for some sorts of questions than it is for others and for some it provides little help. Much the same applies to hormonal effects and to other aspects of biology; they constitute an essential part of the overall understanding, but there are still some puzzles as to how they operate, and they do not give answers to all questions. The first ethical concern, then, is that research could become dominated by a narrow mechanistic deterministic program. Of course, that is a possible danger, but the clear and unambiguous messages from genetic research lead in an entirely different direction. The issue needs to be expressed in an opposite fashion. The topic of human social behavior, including the study of fertility, is of such immense public importance that it would be seriously unethical not to investigate its origins and meaning. Genetic research must constitute a crucial part of that research endeavor because it can be so usefully informative on genetic, environmental and developmental mechanisms and especially their interaction (Plomin and Rutter, 1998; Rutter, 2002a, 2002b). Nevertheless, it is of paramount importance that the research be conducted ethically, as widely recognized in a range of official reports (Medical Research Council, 2000, 2001; Nuffield Council on Bioethics, 1993, 2002b; Royal College of Psychiatrists’ Working Party, 2001) as well as papers by individuals (Durfy, 2001; Rutter, 1999). With very few exceptions, the issues related to genetics research into social behaviors are not different from those that apply to any sort of research, and there is no need here to re-review the details. However, a few key points require emphasis. Most especially the concerns arise from the immense power of modern molecular genetics research and the certainty that, in conjunction with other strategies, it will lead over the next decade or so to a much improved understanding of biological processes. That means that the findings will really matter for society (and bring benefits to it) and, in turn, that it will be open to misuse. The evils of the past, of course, highlight that danger (Devlin et al., 1997), but even if that had not been the case, it is clear that the dangers of misuse are ever present. The challenge is to act in ways that
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Offspring: Human Fertility Behavior in Biodemographic Perspective reduce the danger as much as possible and to set in motion procedures to deal with the misuse when it occurs. Before turning to specific concerns in relation to genetics, some points need to be made with respect to the wide range of community and general population studies that are an essential part of the overall research enterprise as applied to fertility (as discussed in other chapters). Social scientists sometimes wish to argue that when their research involves only observations, interviews, and questionnaires (rather than intrusive medical procedures), there is no need for detailed ethical scrutiny. Obviously, that is a mistaken view not only because of concerns over personal intrusion but also because, if mishandled, even anonymized data can stigmatize groups of individuals. There are also special concerns that apply to research in developing countries, particularly with illiterate individuals (Nuffield Council on Bioethics, 2002a). All human research needs to be subject to independent ethical review. Nevertheless, it needs to be appreciated that those reviewing medical research may well not have the knowledge and experience to assess ethical issues as they apply to social, behavioral, historical, and other non-medical research. Accordingly, other bodies will need to be established, if they are not already available. In addition to scrutiny of the research approach itself, attention needs to be paid to the funding source, to the benefits to researchers, and to the appropriateness or otherwise of benefits (or inducements) for participants. Possible conflicts of interest need to be made overt, not only at the point of initial ethical review and at the annual monitoring of research progress but also at the point of publication, as has been increasingly recognized and handled. With respect to genetic research, several main features warrant attention. First, with any kind of tissue bank in which there is a pooling of tissues for future use by other researchers (whether the banking concerns DNA, umbilical cord blood, placental or other tissues), some modification of the usual approach to informed consent will be needed. That is because neither the precise use of the pooled material nor the researchers using it can be specified in advance (although a range of acceptable research aims can, and should, be specified). The practice that has developed is to require (and specify in the relevant information sheet) that any future use will have to be subject to further independent ethical scrutiny. Second, genetic information on one family member will inevitably have implications for other family members (who may well not have agreed to participate in the study). The most appropriate guidelines for this issue are still being considered and developed. Thus, there is the dilemma of when and how to provide feedback to research participants. The usual expectation in the past when dealing with
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Offspring: Human Fertility Behavior in Biodemographic Perspective medical research with patients was that participants had the right to expect to be told about test findings that might be relevant to their clinical condition. The situation with respect to large-scale general population studies (whether or not focused on genetics) is quite different in three main respects. First, the clinical implications of many findings (such as allelic variations) will not be known until the research is complete (and maybe not even then). The feedback of findings of unknown meaning is generally considered mischievous and unethical because, if the expert does not know what the findings mean, the feedback cannot be relevant or helpful to the participant. Second, most test measures obtained in large surveys will have been collected by researchers with limited training. The findings should be meaningful at a group difference level but not appropriate for individual diagnosis (and hence not for feedback). Third, some insurance companies are requiring clients to report if they have had a “genetic test,” with the anticipation that premiums will be loaded if they have had such a test. They can truthfully answer “no” to that question if there is no feedback and if the research was not focused on the identification of some specific susceptibility gene. This issue, however, raises two other broader issues. On the one hand, it is already clear that there is no straightforward actuarial calculation that can be based on susceptibility genes that contribute to only part (often a small part) of the risk, that may well be dependent on conjunction with some environmental hazard for their contribution to liability, that may vary in their effects with gender or ethnicity, and that may require interaction with other (not yet identified) background genes. As one or more of these conditions will usually apply, actuarial calculations are bound to be hazardous and potentially profoundly misleading. On the other hand, the topic raises the fundamental issue of whether society should penalize, sometimes heavily, particular individuals because they have an increased genetic risk. Most societies do not do so in relation to education, which is equally free for the unusually talented, the average, and the handicapped. Why should it be different in relation to genetics? The final fundamental issue is that of research governance (Royal College of Psychiatrists’ Working Party, 2001). Ethical review bodies provide an essential screening or advisory role, but, fundamentally, the ultimate responsibility that research be undertaken ethically, and reported ethically, must be placed on the individual scientist and, through that individual, to the person’s employing authority. That is necessary because no set of rules, however exhaustive, can possibly anticipate all new ethical issues. The onus is, and has to be, on each and every researcher.
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Offspring: Human Fertility Behavior in Biodemographic Perspective CONCLUSIONS It may be concluded that genetic research, both quantitative and molecular, has an important role to play in gaining a better understanding of all that is involved in the processes that lead to variations in fertility. Nevertheless, the extent to which genetic research provides understanding is crucially dependent on the extent to which it leads to good biological studies of a quite different kind. What is more limiting about genetics is that it is primarily concerned with individual differences, rather than population differences in level. It can contribute to the latter but does so more indirectly. Sometimes behavior genetics has been attacked on the grounds of being excessively reductionist in leading to a biological determinism (Rose, 1998). The alternative is often portrayed as a need for a holistic approach. Personally, I do not agree with that way of putting things. In principle, it must surely always be desirable to seek to reduce explanations to some simple underlying principle (see Bock and Goode, 1998). On the other hand, with respect to all forms of social behavior, there will often be a need to undertake research at a systems, as well as an individual, level. That is to say, as May (1998) put it, it may often be necessary to build from physiology to individual behavior to population dynamics to community structure. There are two-way interactions between individuals and their environments, and there is a vital need to examine these with a sensitivity to the fact that many changes take place over lengthy periods of time that cannot easily be reduced to manipulations in a laboratory experiment. That requires an integration across a range of different sciences, and research priorities must reflect that need. REFERENCES Bailey, J.M. 2000 How can psychological adaptations be heritable? Pp. 171-180 in The Nature of Intelligence. G.R. Bock, J.A. Goode, and K. Webb, eds. (Novartis Foundation Symposium 233.) Chichester: Wiley. Berk, R.A. 1983 An introduction to sample selection bias in sociological data. American Sociological Review 48:386-398. Bock, G.R., and J.A. Goode, eds. 1998 The Limits of Reductionism in Biology. (Novartis Foundation Symposium 213.) Chichester: Wiley. Bock, G.R., J.A. Goode, and K. Webb, eds. 2000 The Nature of Intelligence. Chichester: Wiley. Booth, A., G. Shelley, A. Mazur, G. Tharp, and R. Kittok 1989 Testosterone, and winning and losing in human competition. Hormones and Behavior 23:556-571.
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Representative terms from entire chapter: