Revisiting a basic question: does growing up in either female or male environment affect sex differences in academic strengths and occupational choices?

The study asks whether growing up in a more female- or male-typed environment—operationalized as having same- or opposite-sex siblings—affects two domains that typically show sex differences: (1) relative academic strengths at age 16 in verbal/language versus technical/numerical school subjects, and (2) the cognitive (verbal vs numerical) demands of one’s chosen occupation at age 35. Prior work shows females tend to outperform males in verbal tasks and males show advantages in spatial and some numerical tasks, which is reflected in school grades and occupational distributions. Social learning and related theories suggest sibling sex could shape gender-typed behaviors and possibly abilities and choices. The authors test whether sibling sex composition influences intraindividual academic strength profiles and later occupational cognitive demands, and whether any association is moderated by academic strengths at age 16.

Extensive literature documents sex differences in cognitive abilities and academic performance: females show advantages in verbal domains (e.g., fluency, production, reading, episodic memory), whereas males often perform better in spatial and certain numerical tasks. These differences map onto academic grades (larger female advantage in language; smaller in mathematics/technical subjects) and into occupational choices, contributing to gender segregation across fields. Early studies on sibling sex composition and gender-typical behavior in childhood suggested more gender-typical behavior with same-sex siblings, but subsequent findings are mixed. Evidence directly linking sibling sex composition to cognitive strengths and educational/occupational choices is limited. Gabay-Egozi et al. (2020) reported higher preference for STEM with a greater proportion of brothers; among second-born boys, having an older brother increased STEM major likelihood by ~12%. Conversely, Brenøe (2018) found girls with a brother tend to choose more female-dominated occupations compared to girls with a sister. The present study addresses gaps by examining both academic strengths and later occupational cognitive demands using population registers.

Design and samples: Two register-based cohort studies using Swedish nationwide registers for birth cohorts 1973–1982 (~800,000 individuals). Study 1 analyzed mid-born children in 3-sibling families with symmetric same-sex or opposite-sex compositions: girls GGG (older sister, younger sister) vs BGB (older brother, younger brother); boys BBB (older brother, younger brother) vs GBG (older sister, younger sister). Study 2 analyzed last-born children in 2-sibling families: girls GG (older sister) vs BG (older brother); boys BB (older brother) vs GB (older sister). Data sources: Multi-generation register, National School Register (grades), Swedish Register of Education, STATIV longitudinal database (occupations), and SSYK96 occupational codes (Swedish adaptation of ISCO-88). Inclusion/exclusion and final Ns: - Study 1: Identified 111,744 3-sibling families; excluded non-target compositions (BBG, BGG, GBB, GGB), wide spacing, missing grades (9th grade between 1988–1997), missing key variables. Final N=17,233 (females 8,349: GGG 4,317; BGB 4,032; males 8,884: BBB 5,205; GBG 3,679). Sibling age spacing required: older sibling 1–5 years older; younger sibling 1–5 years younger. - Study 2: Identified 222,107 2-sibling families; excluded wide spacing (<1 or >5 years), missing 9th-grade data (1988–1997), missing key variables. Final N=117,915 (females 58,105: GG 26,528; BG 31,577; males 59,810: BB 28,794; GB 31,016). Measures: - Academic strengths at age 16: From 9th-grade normalized grades (scale 1–5; national mean 3.0, SD=1) in Swedish, English (verbal), Mathematics, and Technics (numerical/technical). Sum verbal (Swedish+English; 2–10) and numerical (Technics+Math; 2–10); compute numerical minus verbal. Negative scores indicate relative strength in numerical/technical; positive indicate relative strength in verbal/language. Extreme values beyond ±4 were winsorized to ±4 due to rarity. - Cognitive demands of chosen occupation at ~35: Occupation at age 35 (2008–2017; nearest available year if missing) coded via SSYK-3 (three-digit; 113 occupations). Numerical vs verbal task demands per occupation based on Dekhtyar et al. (2018) coder ratings (1–7), using the difference (numerical minus verbal). Original SSYK-4 ratings were averaged to SSYK-3 categories. Scores ranged from about -3.94 (more numerical) to +4.50 (more verbal); e.g., Mathematicians/Statisticians most numerical; Pastors most verbal. Covariates: 9th-grade GPA, mother’s age at birth, mother’s education, sibship type (identical vs non-identical parents), ethnicity (Swedish vs other), and sibling age differences (relevant pairs per study). Analytic approach: Multiple linear regressions assessed associations of sex (overall) and sibship composition (within sex) with (1) academic strengths and (2) occupational cognitive demands at 35, adjusting for covariates. Effect sizes reported as Cohen’s f². Moderator analyses used 2×3 factorial ANOVAs to test sibship composition × academic strengths categories (verbal aligned >0; equal 0; numerical aligned <0) on occupational demands, adjusted for covariates. Sensitivity analyses restricted to siblings with identical parents and tested interactions with spacing (age difference). Analyses conducted in R.

- Robust sex differences: - Academic strengths at 16: Girls more verbally aligned; boys more numerically aligned. • Study 1: β = -0.584, 95% CI [-0.614, -0.555], p < 0.001, f² ≈ 0.325. • Study 2: β = -0.574, 95% CI [-0.585, -0.563], p < 0.001, f² ≈ 0.320. - Occupational demands at 35: Women in more verbally demanding, men in more numerically demanding occupations. • Study 1: β = -0.831, 95% CI [-0.859, -0.803], p < 0.001, f² ≈ 0.194–0.426 (table shows -1.673 unstandardized; standardized β -0.831; f² 0.426). • Study 2: β = -0.810, 95% CI [-0.821, -0.799], p < 0.001, f² ≈ 0.411. - Sibship composition and academic strengths (primary question): No significant associations in either sex in either study. • Study 1 girls (GGG vs BGB): β = 0.008, 95% CI [-0.035, 0.051], p = 0.715. • Study 1 boys (BBB vs GBG): β = -0.012, 95% CI [-0.054, 0.030], p = 0.578. • Study 2 girls (GG vs BG): β = 0.009, 95% CI [-0.007, 0.025], p = 0.262. • Study 2 boys (BB vs GB): β = -0.004, 95% CI [-0.020, 0.012], p = 0.658. - Sibship composition and occupational demands: • Study 1: Girls, no effect (β = 0.013, p = 0.553). Boys showed a trend: β = -0.040, 95% CI [-0.082, 0.003], p = 0.065 (boys with sisters tended toward more numerically demanding occupations than boys with brothers). • Study 2: Girls, no effect (β = -0.008, p = 0.304). Boys showed a small but significant effect: β = -0.019, 95% CI [-0.035, -0.003], p = 0.022, f² = 0.007. Direction indicates last-born boys with an older sister chose more numerically demanding occupations than those with an older brother. - Moderator (academic strengths × sibship composition on occupational demands): • Main effect of academic strengths consistent: verbally aligned girls chose more verbally demanding jobs; numerically aligned boys chose more numerically demanding jobs (both studies). • Study 1: No significant interaction for either sex. • Study 2 boys: Significant interaction, F(2, 59,798) = 3.527, p = 0.029, f = 0.011. Follow-ups: among verbally aligned boys, having an older brother was associated with less numerically demanding occupations than having an older sister (F(1, 15,274) = 7.826, p = 0.005). No differences for equal or numerically aligned boys. - Sensitivity analyses restricting to siblings with identical parents and testing spacing effects yielded results consistent with main analyses, suggesting robustness to these factors. Overall: Growing up with same- vs opposite-sex siblings does not affect whether one is verbally or numerically aligned academically at 16. For occupational choices, effects are absent for women and minimal for men, with boys having opposite-sex older siblings tending toward slightly more numerically demanding occupations.

Findings directly address the hypothesis that sibling sex composition shapes sex-typed academic strengths and later occupational cognitive demands. Despite clear sex differences in both domains, sibling composition had no discernible effect on intraindividual academic strength profiles at age 16. This suggests academic strengths are relatively resilient to the gender-typed family environment defined by sibling sex composition, potentially reflecting stability and heritability of cognitive performance. For occupational choices, results were asymmetric by sex: women’s choices were unaffected, whereas men with opposite-sex siblings (particularly last-born boys with older sisters) tended to enter more numerically demanding occupations. Moderator analyses indicated that men’s own academic strengths predicted occupational demands, and the small interaction in Study 2 suggests that among verbally aligned boys, having an older brother was associated with relatively more verbally oriented occupational choices than having an older sister. These effects were very small, indicating that factors beyond sibling composition largely drive occupational sorting. Potential mechanisms discussed include gender-differentiating dynamics in families with opposite-sex siblings and differentiation processes, though reasons for the sex-specific pattern remain unclear. Robustness checks indicated results were not driven by sibling spacing or non-identical parentage.

Using comprehensive Swedish population registers, the study shows that sibling sex composition does not influence whether individuals are more verbally or numerically aligned academically at age 16. Sex-typical academic patterns remain regardless of growing up with same- or opposite-sex siblings. For occupational choices at age 35, women’s outcomes were unaffected by sibling composition, while men with opposite-sex siblings (especially last-born boys with older sisters) showed a slight tendency toward more numerically demanding occupations. Effects on occupation were small, suggesting that sibship composition explains little of occupational sorting by cognitive demands. Future research could examine mechanisms behind the small male-specific occupational effect, test other family structures and birth orders, use more granular occupational coding and direct cognitive testing, explore cross-cultural generalizability, and apply causal designs (e.g., quasi-experiments) to better isolate sibling-composition effects.

- Academic strengths measured via school grades rather than direct cognitive tests; grades may be influenced by non-cognitive factors and teacher bias. Mitigated somewhat by standardized national tests underlying grades and evidence linking grades to cognitive performance. - Occupational demand coding aggregated from SSYK-4 to SSYK-3 may reduce precision; some occupations (e.g., translators) could not be isolated at finer granularity. - Potential differences in occupational skill levels between sexes not fully addressed; authors argue within-sex analyses limit impact on results. - Registry privacy restricts sharing of individual-level data (data availability), though not directly a methodological limitation. Sensitivity analyses suggest results are robust to sibling parentage identity and spacing, but unmeasured confounding cannot be completely ruled out.