The woman as final arbiter: a case for the facultative character of the human sex ratio.

The gender role of a person influences that person's life experiences and life chances in myriad ways, profound and subtle. Several libraries have been filled with the consequences and the relative desirability of such influences. We take a step back and address the question, What determines the initial selection of the sex of the newborn? Framed differently, What selective factors--if any--affect the conception of a male versus a female (the primary sex ratio), and what selective factors--if any--affect differential miscarriages by gender to affect, in turn, the sex of the newborn (the secondary sex ratio)?

High school biology textbooks have handled sex determination in a rather straightforward manner: (1) The father can contribute to the ovum a "Y" sperm (androsperm) or an 16X11 sperm (gynosperm); (2) the mother can contribute only an "X" ovum; (3) hence, the father determines the sex of the child--a male if "XY" or a female if "XX." At the genetic or chromosomal level, this presentation has consensual approval. But the more intriguing question becomes whether there are variables that may bias the chances of an androsperm versus an gynosperm fertilizing the ovum. Two answers are available. The first answer is simply that random chance, a coin flip, determines the outcome: Luck, or a random or stochastic model is sufficient to explain the genetic sex of the conceptus. The second answer is that the intrauterine environment systematically biases the chances of a female versus a male conception (primary sex ratio) or a female versus a male miscarriage. That is, the human sex ratio at birth (secondary sex ratio) is facultative, not a mere happenstance. The argument is made below that the human sex ratio is facultative and not a random event.

RANDOM VERSUS FACULTATIVE SEX RATIOS

Two pieces of evidence argue against a random or stochastic model. The first is direct and prima facie. Across the world's cultures, the secondary sex ratio (number of male births per 100 female births) is 105 (United Nations, 1992). Some populations have slightly higher ratios and some have slightly lower ratios, but all exceed the gender identity of 100. That is, the coin-flip analogy is simply wrong: Fifty-two percent of the births are male and 48% are female. There can be legitimate disagreement concerning whether the bias occurs at conception or through gender differential miscarriage. The central tendency of the 105 sex ratio at birth, however, seems to be unchallenged.

The second piece of evidence is inferential and stems from fraternal (dizygotic) twins. Dizygotic twins are formed from two separate sperms, each fertilizing a separate egg. Fraternal twins are no more alike genetically than any other pair of siblings born at two separate times. If conceptions reflect a random or coin-flip model, then the number of unlike-sex twins (male-female, female-male) would equal the number of like-sex twins (male-male, female-female).(1) On the other hand, if a bias occurs, especially at the time of conception, then because dizygotic twins are generally conceived within a short time of each other (Bomsel-Helmreich & Al Mufti, 1995), a bias would be expected to generate an excess of like-sex twins (male-male, female-female) versus unlike-sex twins (male-female, female-male): Whatever the mechanism that biase-s the sex ratio, it would not be so volatile or labile as to change markedly between two closely timed conceptions.

A review of 23 surveys of the secondary sex ratio of dizygotic twins supports the biased or facultative position (see Table 1). The support comes from three separate analyses: First, of the 23 studies, 19 show an excess of like-sex twins versus unlike-sex twins (p [is less than] .05; two-tailed test). Second, the mean ratio of like-sex twins to unlike-sex twins (1.24) exceeded that of the random model wherein the number of unlike-sex twins would equal the number of like-sex twins (1.00) (t (22) = 5.00, p [is less than] .01; two-tailed test). Third, the mean observed frequency of like-sex twins was higher than the expected frequency, generated by a random model, of like-sex twins ([chi square] (1, N = 5,853) = 113.0, p [is less than] .01).(2) The facultative model is predictive of these data, whereas the random model is not.

Table 1. Ratio of Like-Sex to Unlike-Sex Dizygotic Twins in 23 Studies

                                                   Ratio of Like-Sex
                                                   to Unlike-Sex
Source                                      n      Dizygotic Twins

Bulmer (1959, 1960)                        566      1.11
Corney, Robson, & Strong (1968)            172      0.95
Heuser (1967)                            2,752      1.26(*)
Heuser (1967)                           23,129      1.41(**)
Husby et al. (19910                        172      0.98
James (1992)                             2,629      1.13([dagger])
MacGillivray, Campbell, &
  Thompson (1988)                          568      1.47(**)
Nylander (1969)                            169      1.09
Nylander (1970a)                           701      1.20([dagger])
Nylander (1970b)                           250      1.19
Nylander & Corney (1969)                   664      1.14
Nylander & Corney (1976)                   145      1.20
Potter (1963)                              150      1.11
Register General (1963)                 35,480      1.30(*)
Register General (1967)                  6,985      1.33
Renkonen (1967)                          6,239      1.21
Say, Gungor, & Durmus (1967)               106      1.41
Shipley et al. (1967)                    6,882      1.31(**)
Shipley et al. (1967)                   44,815      1.37
Simmons et al. (1960)                       70      1.80([dagger])
Strong & Corney (1967)                     382      0.89
Vlietinck et al. (1987)                  1,368      0.92
Walsh & Kooptzoff (1955)                    60      1.73
Weighted Mean                                       1.32(*)
Mean (Each Sample Weighted Equally)                 1.24(**)

(*) p < .05 (one-tailed).

(**) p < .01 (two-tailed).

([dagger]) p < .05 (two-tailed).

SOURCES OF BIAS

If it can be agreed that a random, unbiased model of sex determination is not adequate to explain the data but that a facultative model is more appropriate, then the question becomes what factors act to bias the woman toward a female (and away from a male) conceptus or toward a male (and away from a female) conceptus. Two seminal models set a foundation for this question. First, Fisher (1930) developed a model applicable to a population's sex ratio. In brief, Fisher's thesis is that, across a population and across generations, parental investment will be sculpted such that parents will spend equal energy toward rearing sons and daughters to independence. If one gender were less costly to rear per individual, then more numbers of that gender would be born. Conversely, if one gender were more costly to rear per individual, then fewer numbers of that gender would be born. If the two genders were of equal cost to rear, then the sex ratio would be at unity (see Hamilton, 1967 for refinements).

Second, Trivers and Willard (1973) narrowed the focus to an individual parent within a population. The mother would be expected to bias the sex of her offspring in order to optimize, if not maximize, the opportunities of those offspring. These offspring, in turn, would create viable offspring of their own, generating grandchildren for the mother.

In gist, using humans as the example, a male potentially can have a much larger number of offspring than can a female. A woman's fertility is circumscribed by lactation, gestation, and menopause. Because mating generally occurs by the female's choice, however, an unattractive male could have no progeny for himself and thus could not procreate grandchildren for his mother. Females, on the other hand, have virtually no difficulty in attracting a potential mate. Thus, having a son is more of a gamble for the mother: A son may have many grandchildren, but it is plausible that he may have none. Giving birth to a daughter is less a gamble: A daughter would be more likely to have a few children, but would procreate fewer children than her brother would be capable of siring. Thus, Trivers and Willard's model suggests that over many generations, mechanisms have emerged that selected for women who, in the position of rearing healthy, attractive children, are biased more toward having a son; the same mechanisms have operated such that there was selection for women who, within a problematic environment for rearing their children, are more biased toward a daughter. Framed differently, as a potential mother assesses, at whatever level of consciousness, her proximate environment, a more promising prospective should bias her toward having sons; a poorer prospective would bias her toward having daughters.

For nonhumans, data supporting Trivers and Willard's model have been published across a wide variety of species--for example the opossum (Austad & Sunquist, 1986), dairy cattle (Bra-Anan & Robertson, 1975), prosimians (Clark, 1978), red deer (Clutton-Brock, Albon, & Guinness, 1986), the wood lemming (Fredga, Gropp, Winking, & Frank, 1977), Bonnet macaques (Silk, Clark-Wheatley, Rodman, & Samuels, 1981), hamsters (Labov, Huck, Vaswani, & Lisk, 1986; Pratt, Huck, & Lisk, 1989), Barbary macaques (Paul & Thommen, 1984), rhesus macaques (Simpson & Simpson, 1982), Spider monkeys (Symington, 1987), spiders (Vollrath, 1986), and wasps (Werren, 1980). (See Blaffer-Hrdy, 1987 for a review of the literature.) Whether the mother is herself the environment that is the effective variable (healthy, well nourished, and unstressed vs. sickly, malnourished, and highly stressed) or her reading of her environment's potential is the prepotent variable is not particularly relevant to this discussion. What is immediately relevant is that a model suggesting that the human sex ratio is biased is both available and supported.

Analogous supportive data from humans have been less easily extracted, but there are indications that Trivers and Willard's model is applicable to humans. For example, research has shown that a more resource-rich prospective environment translates to a son bias, whereas a lack of such prospective environment translates to a daughter bias (Mackey, 1993; Mackey & Coney, 1987; Mealey & Mackey, 1990; Teitelbaum, 1970; Teitelbaum & Mantel, 197 1; cf, Gangestad & Simpson, 1990; Grant, 1994; see Chahnazarian, 1988 for a review of the literature). See Grant (1994), Gualtieri, Hicks, & Mayo (1984), Guerrero (1975), Harlap (1979), and James (1986, 1987, 1992) for candidates for proximate mechanisms (e.g., hormone levels and psychological types) that bias the human sex ratio, generally at the level of conception (the primary sex ratio).

The limited generalizability from nonhumans to humans may reflect two unique features of the human ecological niche. First, human infants, compared to the young of other species, are quite dependent upon adult care for extended periods. Humans are highly altricial, with singleton births being the norm. Second, unlike nonhuman adult males, the human social father (usually the biological father, but occasionally the avunculus) is systematically expected to provide for the physical needs of his children. Again, across cultures, this expectation is predictably and systematically fulfilled (Hewlett, 1992; Mackey, 1985, 1995; Mackey & Day, 1995; Human Relations Area Files, 1949).

Thus, there are two important variables that affect the mother-to-be: (1) the preexisting family structure--namely, the number and age and gender of her already-born children--and (2) her relative evaluation of the father of her children in his willingness and capacity to provide an enriched environment within which their children will be reared to independence. These two variables are argued to become elements of the woman's calculus in her evaluation of her own relative life chances and, by extension, of those of the conceptus. We now turn to a test of the two variables.

If the ongoing father, as part of the microenvironment of the mother, is evaluated as providing a relative and incremental advantage to the conceptus, then ceteris paribus, the woman would be expected to be biased toward having a son. Accordingly, we surveyed the reproductive history of the wives of three samples of men, who were probably able to provide such an incremental advantage (i.e., overachieving men): (1) Men listed in Who's Who, (2) U.S. presidents, and (3) Mormons during an era of legal polygyny.

MEN IN WHO'S WHO

Method

Men who are included in Who's Who (henceforth WW) are, nearly by definition overachievers, even within their own occupational niches.(3) Twenty-five married or previously married men were randomly selected in WW from each letter of the alphabet, with the exception of the letter "X." A total of 632 men were surveyed. The gender, number and birth order of their children were coded (per wife if he had more than one set of children). The ages of the wives of men in WW were not available. Because of the unknown impact that Roe v. Wade and sonograms may have upon birthing histories, we surveyed individuals listed in the 1975 Who's Who (Who's Who, 1975).

To serve as controls, two additional groups of women were surveyed: women who were included in WW (n = 2,114)(4) and mothers (n = 170) who were enrolled in a local community college. The latter group of women, student-mothers, were self-selected in that they responded to notices posted on bulletin boards or to an advertisement in the school newspaper, or heard of the study by word-of-mouth from fellow students. For both of these samples of women, the woman's marriage status was not coded. For both of these samples of women, there was no reason to presume that the biological fathers, as a group, would be any more or less successful in providing a superior nurturing environment for their children than would other men in comparable occupational niches. The mean age of the women in WW was just over 50 years; thus, their reproductive histories were nearly complete. The mean age of the student-mothers was just under 24 years, thereby indicating that their reproductive histories might not have been completed.

Results

Number of children. The wives of men in WW had distinctly different reproductive histories compared to women in WW (see Table 2). The wives were less likely than the women in WW to be childless (14.6% versus 54.2%, z-score = 17.5, p [is less than] .01). Compared with women in WW, the wives also had a higher mean number of children per woman (t (2,744) = 28.5, p [is less than] .01); and, if they did have one child, the wives were more likely to have additional children than were the mothers listed in WW (t (1,506) = 13.4, p [is less than] .01; see Table 2).

Table 2. Percentage Distribution of Children in the Two Samples of WW, by Sample of Women and by Number of Children Born

Number of                 Wives of                Women
Children Born             Men in WW      n        in WW

0                          14.6%          92       54.2%
1                           9.3           59       13.8%
2 & Later                  76.1%         481       32.0%
Totals                    100.0%         632      100.0%
Mean Number of
Children per Woman          2.35                    0.98
Mean Number of
Children per Mother         2.75                    2.14

Number of
Children Born               n          z              t

0                         1,146      17.5
1                           292       3.0(*)
2 & Later                 6,761       9.7(*)
Totals                    2,114
Mean Number of
Children per Woman                                   28.5(*)
Mean Number of
Children per Mother                                  13.4(*)

(*) p < .01.

Because only mothers were surveyed in the sample of student-mothers, and because their reproductive histories were undoubtedly incomplete, their sample was not analogous and, thereby, not comparable to either sample of women from WW.

Birth order and gender The wives of men in WW were clearly biased toward having a first-born son (see Table 3). For these women, the sex ratio of 131.6 was higher than the population norm of 105 ([chi square] (1, N = 528) = 6.670; p [is less than] .05; two-tailed test) and higher than the sex ratio of their second-born and later children ([chi square] (1, N = 1437) = 10.478; p [is less than] .01).

Table 3. Sex Ratios by Sample of Women and by Birth Order

                                        Birth Order
                                                     Second-Born
                           First-Born                & Later
Wives of Men
in WW                      131.6(*)                   92.2
  Sons                     300                        436
  Daughters                228                        473
Women in WW                101.7                       96.6
  Sons                     483                        534
  Daughters                475                        553
Student-Mothers             53.8(*)                   111.9
  Sons                      28                         47
  Daughters                 52                         42
[chi square] (df = 2)       15.10([double dagger])      0.87

                           [chi square]
                           (df = 1)
Wives of Men
in WW                      10.46([double dagger])
  Sons
  Daughters
Women in WW                 0.34
  Sons
  Daughters
Student-Mothers             5.42([dagger])
  Sons
  Daughters
[chi square] (df = 2)

(*) Differs from population norm of 105, p < .05 (two-tailed).

([dagger]) p < .05 (two-tailed).

([double dagger]) p < .01 (two-tailed).

Compared with the women in WW, the wives of men in WW had a higher percentage of first-born sons ([chi square] (1, N = 1,486) = 5.60, p [is less than] .05; two-tailed test). Chi-square tests revealed that the sex ratios of the second-born and later children were the same for the wives of men in WW and the women in WW.

Compared with the student-mothers, the wives of men in WW had a higher percentage of first born sons ([chi square] (1, N = 608) = 13.30, p [is less than] .01). Again, chi-square tests revealed that the sex ratios of the second-born and later children were the same for both the wives of men in WW and the student-mothers.

Compared with the women in WW, the student-mothers had a higher percentage of first-born daughters ([chi square] (1, N = 1,038) = 7.02, p [is less than] .05; two-tailed test), with second born and later children having similar sex ratios for the two groups. It is the first-born children that separate the three samples.

U.S. PRESIDENTS

Method

Presidents' children were surveyed by birth order, age, and gender. These men were overachievers, at least from middle age onward, if not at the beginning of their early adulthood (Kane, 1981; Who's Who, 1995). For all children, the sex ratio was 146.7 ([chi square] (1, N = 148) = 4.04, p [is less than] .05), which indicated a bias toward having sons. For first-born children, the sex ratio did not differ from the population norm of 105. For the second-born and later children, however, the sex ratio was 179.5, exceeding the population norm of 105 ([chi square] (1, N = 109) = 7.40, p [is less than] .05)(5) (see Table 4).

Table 4. Sex Ratio of Presidents' Children by Birth Order

                                Birth Order

                                Second-Born
                First-Born      & Later          All Children

Sex Ratio       85.7             179.0(*)        146.7(*)
Sons             18               70              88
Daughters        21               39              60

(*) Exceeds population norm of 105 (p < .05).

Results

Of interest is the one-child family. There were 5 one-child families in the sample of presidents. All five were singleton daughters. In the women in the WW sample, the sex ratio of singleton births was 75.9 with 126 sons and 166 daughters ([chi square] (1, N = 292) = 7.57, p [is less than] .01), which indicated a clear bias toward having daughters. The sex ratio of the student-mother sample was 66.7 (12 of 18 singletons were daughters). The sex ratio of singleton births for the wives of men in WW was 126.9 (33 of 59 singletons were sons).

MORMON MEN

Mormon men in the nineteenth century were allowed to have plural wives; polygyny was legal. Large families were encouraged, and accurate and complete demographic records were maintained (see Mealey, 1984, 1985 for discussion). We reviewed data on number of wives and sex ratios from these records. Three additional points are germane. First, women had full control of whom they would accept or reject as a husband (Young, 1954). Second, the wealth of an individual man was positively correlated to the number of wives that he had (Mealey, 1985; Quinn, 1976). Third, there was a moderately large proportion of young Mormon men who were marriageable and poor (i.e., they owned no property; Mealey & Mackey, 1990).

We compiled the number of co-wives that a new bride would join in a household and the sex ratio of her children.(6) If the bride was the only wife or joined a single co-wife, then the bride's eventual sex ratio (105.6) was at the population norm (105). However, if the bride joined a family with two or more wives already present, then the sex ratio of her completed reproductive history (129.9) was higher than both the population norm of 105 ([chi square] (1, N = 1,260) = 14.20, p [is less than] .01) and the sex ratio of the women who had joined a family with only one or with no additional wives ([chi square] (1, N = 8,211) = 11.61, p [is less than] .01) (see Table 5).

Table 5. Sex Ratios of Mormon Women's Children, by Number of Husband's Prior Co-Wives

Number of                           Number of       Number of
Prior Co-Wives      Sex Ratio       Sons            Daughters

None or One         105.6           4,217           3,994
Two or More         129.9(*)          712             548

Note. [chi square] (1, N = 9,471) = 11.609, p < .01 (two-tailed test).

(*) Exceeds population norm of 105 (p < .05).

INTERVALS BETWEEN BIRTHS

Method

The time gaps, in months, between adjacent births were available from the sample of presidents' children, a sub-sample of the Mormon data,(7) the sample of student-mothers, and a sample from National Survey of Family and Households (Bumpass & Sweet, 1986). The latter three samples evinced no evidence to suggest overachieving on the part of the husband/father; thus, we combined these three samples and compared them to the sample of presidents' children. The four dyads were analyzed separately: male-male, male-female, female-male, female-female.

Results

For the combined sample, there was no difference in timing of adjacent births among the three dyads of male-male, male-female, and female-male. The length of time between births for the female-female dyad, however, was significantly shorter than each of the dyads containing at least one male (male-female, female-male, male-male). This difference is primarily located in the longer birth intervals. That is, female-female adjacent births were underrepresented in the longer periods between births.

The same pattern was found in the sample of presidents' children. Dyads involving at least one male (male-male, female-male, male-female) tended have longer intervals between adjacent births than did female-female dyads. Similarly, the increased length tended to result from an underrepresentation of the female-female dyad in extended intervals (see Table 6). Thus, given the more problematic character of the son's future attractiveness to women, his formative years seem to be given a marginal decrease in sibling competition.

Table 6. Birth Intervals by Sex of Adjacent Sibling and by Sample of Women

                                Sample of Women:
                        Combined                U. S. Presidents'
Dyad Gender             Sample                  Wives
Composition, Prior      Interval                Interval
Child/Later Child       (Months)        n       (Months)        n

Male/Male               32.8(*)         221     34.5(*)         42
Male/Female             33.1(*)         229     39.1(*)         21
Female/Male             32.8(*)         226     35.7(*)         24
Subtotal                32.9(*)         676     35.8(**)        87
Female/Female           29.8            221     26.3            17

(*) Exceeds length of birth interval for female/female dyad (p < .05).

(**) Exceeds length of birth interval for female/female dyad (p < .01).

DISCUSSION

Before we discuss the results, we must insert a caveat. Although statistical significance has been found in birthing patterns, the strength of the relationships is not robust. The relationships seem more real than merely apparent; yet the linkages are not powerful. Clearly, other more potent variables have yet to be profiled. The dynamic of sex determination may be the summation of a large number of variables, each of which by itself is not overwhelming. Despite this caveat, some interesting patterns have occurred.

A brief review of the salient data may be useful. Women married to men in WW were biased toward having a first-born son. Women in WW had fewer children and, although they had no overall bias, if they had a singleton child, they were biased toward having a daughter. Women who were exercising the dual roles of student and mother were biased toward having a first-born daughter.

The wives of presidents had an overall bias toward having sons. The bias was restricted to second-born and later-born children. More affluent Mormon men had more wives and a higher proportion of sons. Conceptions of sons tended to occur more often when there was a greater interval between adjacent conceptions; a daughter-daughter tandem occurred in significantly shorter birth intervals.

These data support the notion that if a woman has, within her own referent social group, marginally increased levels of resources from her husband, she translates those incremental resources to a son. A random, coin-flip model seems inadequate to explain the data: Patterns occurred that cannot be explained by chance. There are three main sources of potential bias: (1) the father, (2) the mother through gender-biased miscarriage, and (3) the mother before conception. We review the feasibility of each.

The Father

Although there are undoubtedly exceptions, male ejaculates tend to have millions of sperm of each sex type (androsperm, gynosperm). If the numbers are not exactly equal, they certainly seem functionally equivalent (Afzelius, 1975). Once the man has ejaculated, his role in sex determination of the conceptus seems very close to zero. "Sperm wars" seem to be limited to competition between different men's ejaculates rather than to a single man attempting to bias the sex of the conceptus (Smith, 1984). Given the problematic linkage between a biological father and a social father, there seems to be no advantage accrued to the man for him to contest the woman on selecting the sex of the conceptus.

The Mother and Sex-Biased Miscarriages

Although a logical category, the systematic selection of the offspring's sex via sex-biased miscarriages seems unlikely for two reasons. First, the fetus/placenta is not a passive entity. The fetus/placenta would be selected to contest a miscarriage if the gender of the fetus/placenta, rather than the mother's viability, were in question (Mackey, 1984). Second, miscarriages are costly: Time and nutrients are wasted, and the health of the mother is threatened.

The Mother and Conception

The more likely candidate for sex selection would be at the level of biased conceptions. That is, different intrauterine conditions would systematically fluctuate to bias toward androsperm or toward gynosperm. This systematic fluctuation would be a function of the woman's reactions to her current and prospective microenvironment. Compared to a miscarriage, the costs to the woman of varying her intrauterine environment are meager. The advantages of ignoring any biases that may stem from an absent, biological, and hence, absent social, father seem intuitively clear.

That bias occurs in the sex determination of the conceptus seems clear. What is not clear, however, is (1) the environmental triggers to which the mother is responding and (2) how her "read" of those parameters translates to the physiology of conception. The chestnut of "more research is needed" seems appropriate, indeed.

(1) The assumption of independence in the conception of each of the dizygotic twins is the basis of Weinberg's Rule (Weinberg, 1902). To the extent that the secondary sex ratio parallels the primary sex ratio, the data that support a facultative sex ratio are at variance with Weinberg's Rule.

(2) Survivability by gender combination of the twin pair is an interesting variable. For one (large) sample from the U.S. National Natality files, White like-sex pairs--particularly male-male pairs--had a higher risk of infant mortality than did male-female pairs. Among Blacks, male-male pairs had higher rates of infant mortality than did either female-female pairs or female-male pairs. The female-female and the female-male pairs were at equivalent risk (Powers, Kiely, & Fowler, 1995). Any increase in mortality of like-sex twins from conception to birth, would increase the proportion of unlike-sex twins recorded in birthing records. Given the over-representation of like-sex pairs in the survey of dizygotic twin studies, such a dynamic would create numbers supportive of the facultative position and weaken the Weinberg position. However, to the extent that the mortality of one or both of the twins is due to the effects that one twill has upon the other (rather than due to the mother's physiological reaction), the empirical support for the facultative model is weakened.

(3) It is useful to emphasize that the referent group for the female is her own social network and her evaluation of her relative position within that restricted network. Absolute levels of resources are not predictive. For example, births of women in the Social Register (Social Register Association, 1977), an index of access to enhanced resources, had a lower sex ratio than that of Black teenage women, a group not usually associated with enhanced resources. The comparative position within one's own social microenvironment is suggested to be the operant variable.

(4) Occupation was also coded. The women in our samples were employed in occupations in which at least 15% of the labor force within that occupation was female (Casserly, 1975; U.S. Department of Labor, 1992). Women in nontraditional occupations (those in which less than 15% of those employed were female) had a different profile from those women in more traditional occupations. Space precludes the additional sample.

(5) Some of the presidents' wives had prior children. For example, Dolley Madison had two sons from a former marriage. However, only Martha Jefferson's prior son would affect the analysis presented here, and then only in terms of birth order. The patterns for the entire sample were not changed. Also, the birthdays for the Bush children could not be found. Hence, they are included in birth-order data, but not birth-interval data.

(6) The data on the Mormons were made available through the generosity of Linda Mealey.

(7) The subsample of the Mormons was made available through the generosity of Linda Mealey.

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Manuscript accepted on 5/22/97.

This project was supported, in part, by the Harry Frank Guggenheim Foundation. Their support is gratefully acknowledged. The project also benefited greatly from comments and suggestions by Forest Morrisett.

Address correspondence and reprint requests to Nancy S. Coney, MSW, Department of Sociology, Anthropology, and Social Work, Western Illinois University, Macomb, IL 61455; e-mail: [e-mail].