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"Birth order."
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The birth order book : why you are the way you are
Explains family dynamics and the effects of birth order on personality and offers advice on parenting and other important relationships.
Book
Male homosexuality and maternal immune responsivity to the Y-linked protein NLGN4Y
We conducted a direct test of an immunological explanation of the finding that gay men have a greater number of older brothers than do heterosexual men. This explanation posits that some mothers develop antibodies against a Y-linked protein important in male brain development, and that this effect becomes increasingly likely with each male gestation, altering brain structures underlying sexual orientation in their later-born sons. Immune assays targeting two Y-linked proteins important in brain development—protocadherin 11 Y-linked (PCDH11Y) and neuroligin 4 Y-linked (NLGN4Y; isoforms 1 and 2)—were developed. Plasma from mothers of sons, about half of whom had a gay son, along with additional controls (women with no sons, men) was analyzed for male protein-specific antibodies. Results indicated women had significantly higher anti-NLGN4Y levels than men. In addition, after statistically controlling for number of pregnancies, mothers of gay sons, particularly those with older brothers, had significantly higher anti-NLGN4Y levels than did the control samples of women, including mothers of heterosexual sons. The results suggest an association between a maternal immune response to NLGN4Y and subsequent sexual orientation in male offspring.
Journal Article
You were the first
Reminds firstborn children that they will always special--even if another child or children follow--because they have been the first to do many things, including teaching their mother and father to be parents.
Book
Asexuality: Its Relationship to Sibling Sex Composition and Birth Order
While recent research has advanced our understanding of asexuality, very little effort has been devoted to examining biomarkers and possible prenatal correlates of asexuality. In response, we recruited a large international sample (
N
= 1634 women and men) to explore associations between sibling composition and asexual sexual orientation (
n
= 366) and to replicate previously reported sibship effects in individuals with a same-sex attracted orientation (
n
= 276) and bisexual sexual orientation (
n
= 267) compared to heterosexual individuals (
n
= 725). Our analyses used two of the most recent statistical approaches that attempt to disentangle older sibling effects from family size effects (Ablaza et al., 2022; Khovanova, 2020). We found that higher overall number of siblings (female fecundity effect) predicted higher probability of asexuality in men and having fewer older sisters and being an only-child predicted higher probability of asexuality in women. Regarding the same-sex attracted orientations, higher number of older sisters increased likelihood of being a gay man (sororal birth order effect). Having fewer older sisters was associated with bisexual sexual orientation in women and higher overall number of siblings predicted increased likelihood of bisexuality in men. We did not find a fraternal birth order effect for gay, lesbian, bisexual or asexual groups using the Ablaza et al. (2022) method but the effect was significant for gay men using the Khovanova (2020) analytic approach. These findings point to potential sibship-related contribution to development of asexuality in women and men but future studies will need to replicate these results and articulate potential underlying mechanisms.
Journal Article
WHY DO MOTHERS BREASTFEED GIRLS LESS THAN BOYS? EVIDENCE AND IMPLICATIONS FOR CHILD HEALTH IN INDIA
Breastfeeding is negatively correlated with future fertility because nursing temporarily reduces fecundity and because mothers usually wean on becoming pregnant again. We model breastfeeding under son-biased fertility preferences and show that breastfeeding duration increases with birth order, especially near target family size; is lowest for daughters and children without older brothers because their parents try again for a son; and exhibits the largest gender gap near target family size, when gender is most predictive of subsequent fertility. Data from India confirm each prediction. Moreover, child survival exhibits similar patterns, especially in settings where the alternatives to breastmilk are unsanitary.
Journal Article
Evidence for distinct biodevelopmental influences on male sexual orientation
Several biological mechanisms have been proposed to influence male sexual orientation, but the extent to which these mechanisms cooccur is unclear. Putative markers of biological processes are often used to evaluate the biological basis of male sexual orientation, including fraternal birth order, handedness, and familiality of same-sex sexual orientation; these biomarkers are proxies for immunological, endocrine, and genetic mechanisms. Here, we used latent profile analysis (LPA) to assess whether these biomarkers cluster within the same individuals or are present in different subgroups of nonheterosexual men. LPA defined four profiles of men based on these biomarkers: 1) A subgroup who did not have these biomarkers, 2) fraternal birth order, 3) handedness, and 4) familiality. While the majority of both heterosexual and nonheterosexual men were grouped in the profile that did not have any biomarker, the three profiles associated with a biomarker were composed primarily of nonheterosexual men. We then evaluated whether these subgroups differed on measures of gender nonconformity and personality that reliably show male sexual orientation differences. The subgroup without biomarkers was the most gender-conforming whereas the fraternal birth order subgroup was the most female-typical and agreeable, compared with the other profiles. Together, these findings suggest there are multiple distinct biodevelopmental pathways influencing same-sex sexual orientation in men.
Journal Article
Testing fraternal birth order effects and antagonistic effects for homosexual men: power comparison of various methods
Research on the biological determinants of male homosexual preference has long realized that the older brother effect (FBOE, i.e., a higher fraternal birth rank of homosexuals) and the antagonist effect (AE, i.e., more fertile women have a higher chance of having a homosexual son) can both generate family data where homosexual men have more siblings and more older siblings than heterosexual men. Various statistical approaches were proposed in the recent literature to evaluate whether the action of FBOE or AE could be discriminated from empirical data, by controlling for the other effect. Here, we used simulated data to formally compare all the approaches that we could find in the relevant literature for their ability to reject the null hypothesis in the presence of a specified alternative hypothesis (tests based on regression, Bayesian modeling, or contingency tables). When testing for the FBOE, the relative performance of the different tests was different depending on the specific function generating the older brother effect. Even if no tests were found to always perform better than the others, some tests performed systematically poorly, and some tests displayed a systematic high rate of type-I error. For testing the AE, the relative performance of the tests was generally not changed across all parameter values assayed, providing a clear ranking of the various proposed approaches. Pros and cons for each candidate test are discussed, taking into consideration power and the rate of type-I error but also practicability, the possibility to control for confounding variables, and to consider alternative hypotheses.
Journal Article
Impact of high-risk fertility behaviours on underfive mortality in Asia and Africa: evidence from Demographic and Health Surveys
Background
Maternal age < 18 or > 34 years, short inter-pregnancy birth interval, and higher birth order are considered to be high-risk fertility behaviours (HRFB). Underfive mortality being disproportionately concentrated in Asia and Africa, this study analyses the association between HRFB and underfive mortality in selected Asian and African countries.
Methods
This study used Integrated Public Microdata Series-Demographic and Health Surveys (IPUMS-DHS) data from 32 countries in sub-Saharan Africa, Middle East, North Africa and South Asia from 1986 to 2017 (
N
= 1,467,728). Previous evidence hints at four markers of HRFB: women’s age at birth of index child < 18 or > 34 years, preceding birth interval < 24 months and child’s birth order > 3. Using logistic regression, we analysed change in the odds of underfive mortality as a result of i) exposure to HRFB individually, ii) exposure to any single HRFB risk factor, iii) exposure to multiple HRFB risk factors, and iv) exposure to specific combinations of HRFB risk factors.
Results
Mother’s age at birth of index child < 18 years and preceding birth interval (PBI) < 24 months were significant risk factors of underfive mortality, while a child’s birth order > 3 was a protective factor. Presence of any single HRFB was associated with 7% higher risk of underfive mortality (OR 1.07; 95% CI 1.04–1.09). Presence of multiple HRFBs was associated with 39% higher risk of underfive mortality (OR 1.39; 95% CI 1.36–1.43). Some specific combinations of HRFB such as maternal age < 18 years and preceding birth interval < 24 month significantly increased the odds of underfive mortality (OR 2.07; 95% CI 1.88–2.28).
Conclusion
Maternal age < 18 years and short preceding birth interval significantly increase the risk of underfive mortality. This highlights the need for an effective legislation to curb child marriages and increased public investment in reproductive healthcare with a focus on higher contraceptive use for optimal birth spacing.
Journal Article
No effect of birth order on adult risk taking
Does birth order shape people’s propensity to take risks? Evidence is mixed. We used a three-pronged approach to investigate birth-order effects on risk taking. First, we examined the propensity to take risks as measured by a self-report questionnaire administered in the German Socio-Economic Panel, one of the largest and most comprehensive household surveys. Second, we drew on data from the Basel–Berlin Risk Study, one of the most exhaustive attempts to measure risk preference. This study administered 39 risk-taking measures, including a set of incentivized behavioral tasks. Finally, we considered the possibility that birth-order differences in risk taking are not reflected in survey responses and laboratory studies. We thus examined another source of behavioral data: the risky life decision to become an explorer or a revolutionary. Findings from these three qualitatively different sources of data and analytic methods point unanimously in the same direction: We found no birth-order effects on risk taking.
Journal Article