10.5061/DRYAD.4B8GTHTBG
Liu, Anthony
0000-0002-1374-2455
University of Sydney
Schafer, Samuel
0000-0002-3101-9367
Linköping University
Nanan, Ralph
University of Sydney
Sundling, Felicia
Linköping University
Raubenheimer, David
University of Sydney
Firstborn sex defines early childhood growth of subsequent siblings
Dryad
dataset
2020
FOS: Medical and health sciences
2020-12-16T00:00:00Z
2020-12-16T00:00:00Z
en
3146137 bytes
5
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Animal studies have shown that maternal resource allocation can be
sex-biased in order to maximize reproductive success, yet this basic
concept has not been investigated in humans. In this study we explored the
relationships between maternal factors, offspring sex and prenatal and
postnatal weight gain. Sex-specific regression models not only indicated
that maternal ethnicity impacted male (n = 2456) and female (n = 1871)
childrens’ postnatal weight gain differently but also that parity and mode
of feeding influenced weight velocity of female (β ± S.E. = -0.31 ± 0.11
kg, P < 0.001; β ± S.E. = -0.37 ± 0.11 kg, P < 0.001) but
not male offspring. Collectively, our findings imply that maternal
resource allocation to consecutive offspring increases after a male
firstborn. The absence of this finding in formula fed children suggests
that this observation could be mediated by breast milk. Our results
warrant further mechanistic and epidemiological studies to elucidate the
role of breastfeeding on the programming of infant growth as well as of
metabolic and cardiovascular diseases, with potential implications for
tailoring infant formulas according to sex and birth order.
Between January 2007 and February 2018, data were obtained from electronic
medical records from 33874 admissions to the Pediatric ward of a
metropolitan teaching hospital in Western Sydney, Australia. Entries of
children that had been transferred from the obstetric ward to another
ward, within a week after birth were excluded (n = 5111), as were entries
of children older than five years of age at admission (n = 5611). Several
children (n = 5762) had been admitted multiple times. To ensure that every
child only entered the analysis once, the latest medical entry with
anthropometric measures was chosen and the remaining entries for that
child were excluded, leaving medical records for 16355 children.
ObstetrixTM (59), a state-wide mandatory database collecting obstetric
data, included information on the mother, pregnancy related information
and infant related information such as anthropometric measurements for
67268 infants delivered at the hospital between 2000 and 2017. ObstetrixTM
was matched with the pediatric database using the children’s individual
medical record number. The included variables were screened for two-way
variable interaction utilizing generalized linear models. If several
interactions included the same variable the possibility of three-way
interactions was investigated. Entering variables and variable
interactions into a stepwise backward eliminated multiple regression model
ensured that only the best sets of predictive variables were included in
the final model. Variables with a P-value ≥ 0.1 were removed through
backward elimination. The regression models were then followed up with
groupwise comparisons, utilizing β-values for all statistically
significant [SS1] variables in the regression model (except the
investigated grouping variabels) to adjust postnatal weight. Grouping
children by firstborn sex (if applicable), infant sex and feeding method
an ANOVA was conducted. ANOVA was followed up with post-hoc Bonferroni
tests to investigate the specific effects of feeding method, firstborn sex
and infant sex on postnatal growth.
Yes. Data is complete. Pls refer to data code sheet.