Prepubertal Growth Trajectory and Pubertal Onset
Survey
LSAC
Author(s)
Rui Deng
dengrui@alumni.pku.edu.cn
Institute of Nutrition and Food Hygiene, Beijing Center for Disease Prevention and Control, Beijing, China
https://orcid.org/0000-0002-8875-7379
Bin Dong
bindong@bjmu.edu.cn
Institute of Child and Adolescent Health, School of Public Health, Peking University Health Science Centre, Beijing, China; Beijing Key Laboratory of Innovations and Transformations in Intelligent and Precise Diagnosis and Treatment Technologies for Reproductive Health, Beijing, China
https://orcid.org/0000-0002-8123-4401
Susan Sawyer
susan.sawyer@rch.org.au
Centre for Adolescent Health, Murdoch Children’s Research Institute and Royal Children’s Hospital, Parkville, Victoria, Australia ; Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
https://orcid.org/0000-0002-9095-358X
Date Issued
2026-06-09
Pages
e2617435
Abstract
IMPORTANCE Adiposity has been reported to be a major contributor to earlier pubertal timing, but
most pediatric studies have relied on body mass index (BMI) from single or short-term
measurements. Studies tracking growth repeatedly from birth to puberty are needed.
OBJECTIVE To explore the association of growth trajectory and cumulative exposure to different
levels of adiposity (CEA) with pubertal onset across the first decade of life and identify sensitive
periods for possible weight intervention.
DESIGN, SETTING, AND PARTICIPANTS This population-based cohort study included data from 2
birth cohorts: the Longitudinal Study of Australian Children (LSAC), conducted from March 2004 to
September 2021, with more than a 10-year follow-up, and the Tianjin Birth Cohort Study (TBCS) in
China, conducted from May 2021 to April 2024, with follow-up from December 2010 to April 2024.
Data analysis was conducted from April 2023 to November 2025. Participant inclusion required at
least 4 anthropometric measures in the LSAC and 9 in the TBCS and completed measures of pubertal
onset in both cohorts.
EXPOSURES Prepubertal BMI trajectories, CEA, and rates of BMI increase at each age.
MAIN OUTCOMES AND MEASURES Pubertal status and timing were obtained by a parent-reported
Pubertal Development Scale. A latent class growth mixed model was used to identify prepubertal
BMI trajectories. An interval regression model and the Cox proportional hazards regression model
were used to examine the association of the exposures with the age and risk of pubertal onset.
RESULTS A total of 3354 Australian children (1723 boys [51.37%]) and 1105 Chinese children (563
girls [50.95%]) were included. At the last round, the mean (SD) ages were similar across sexes within
each cohort, while children in LSAC (14.83 [0.61] years) were overall older than those in TBCS (10.63
[0.60] years). Girls in BMI trajectory groups characterized as high-level or increasing were younger at
pubertal onset (from β = −0.36 [95% CI, −0.66 to −0.07] years to β = −1.51 [95% CI, −2.68 to −0.35]
years) and were associated with increased risk of pubertal initiation (from hazard ratio [HR], 1.35
[95% CI, 1.04 to 1.74] to HR, 2.80 [95% CI, 1.69 to 4.63]). A higher CEA and average CEA (both >2)
were associated with an earlier age at pubertal onset (from β = −0.04 [95% CI, −0.05 to −0.03] years
to β = −0.85 [95% CI, −1.48 to −0.23] years), with a greater effect size after averaging. Consistent
results were found in boys of the LSAC but not those of the TBCS. Sensitive ages of 3 to 4 years were
identified, at which BMI increase was associated with pubertal timing, with greater effect sizes of
pubertal timing (from β = −1.35 [95% CI, −2.00 to −0.71] years to β = −3.41 [95% CI, −4.13 to −2.68]
years) and greater risk of pubertal onset (from HR, 1.85 [95% CI, 1.29 to 2.67] to HR, 5.59 [95% CI,
3.73 to 8.37]) than at other ages. Notably, the effect sizes of CEA within this period were greater than
that outside it.
CONCLUSIONS AND RELEVANCE In this cohort study, high-level or increasing prepubertal growth
trajectories and greater CEA were associated with earlier and higher risk of pubertal onset. These
findings highlight the importance of considering CEA in relation to early pubertal onset and suggest
that ages 3 to 4 years may be an important intervention period for earlier pubertal onset monitoring.
most pediatric studies have relied on body mass index (BMI) from single or short-term
measurements. Studies tracking growth repeatedly from birth to puberty are needed.
OBJECTIVE To explore the association of growth trajectory and cumulative exposure to different
levels of adiposity (CEA) with pubertal onset across the first decade of life and identify sensitive
periods for possible weight intervention.
DESIGN, SETTING, AND PARTICIPANTS This population-based cohort study included data from 2
birth cohorts: the Longitudinal Study of Australian Children (LSAC), conducted from March 2004 to
September 2021, with more than a 10-year follow-up, and the Tianjin Birth Cohort Study (TBCS) in
China, conducted from May 2021 to April 2024, with follow-up from December 2010 to April 2024.
Data analysis was conducted from April 2023 to November 2025. Participant inclusion required at
least 4 anthropometric measures in the LSAC and 9 in the TBCS and completed measures of pubertal
onset in both cohorts.
EXPOSURES Prepubertal BMI trajectories, CEA, and rates of BMI increase at each age.
MAIN OUTCOMES AND MEASURES Pubertal status and timing were obtained by a parent-reported
Pubertal Development Scale. A latent class growth mixed model was used to identify prepubertal
BMI trajectories. An interval regression model and the Cox proportional hazards regression model
were used to examine the association of the exposures with the age and risk of pubertal onset.
RESULTS A total of 3354 Australian children (1723 boys [51.37%]) and 1105 Chinese children (563
girls [50.95%]) were included. At the last round, the mean (SD) ages were similar across sexes within
each cohort, while children in LSAC (14.83 [0.61] years) were overall older than those in TBCS (10.63
[0.60] years). Girls in BMI trajectory groups characterized as high-level or increasing were younger at
pubertal onset (from β = −0.36 [95% CI, −0.66 to −0.07] years to β = −1.51 [95% CI, −2.68 to −0.35]
years) and were associated with increased risk of pubertal initiation (from hazard ratio [HR], 1.35
[95% CI, 1.04 to 1.74] to HR, 2.80 [95% CI, 1.69 to 4.63]). A higher CEA and average CEA (both >2)
were associated with an earlier age at pubertal onset (from β = −0.04 [95% CI, −0.05 to −0.03] years
to β = −0.85 [95% CI, −1.48 to −0.23] years), with a greater effect size after averaging. Consistent
results were found in boys of the LSAC but not those of the TBCS. Sensitive ages of 3 to 4 years were
identified, at which BMI increase was associated with pubertal timing, with greater effect sizes of
pubertal timing (from β = −1.35 [95% CI, −2.00 to −0.71] years to β = −3.41 [95% CI, −4.13 to −2.68]
years) and greater risk of pubertal onset (from HR, 1.85 [95% CI, 1.29 to 2.67] to HR, 5.59 [95% CI,
3.73 to 8.37]) than at other ages. Notably, the effect sizes of CEA within this period were greater than
that outside it.
CONCLUSIONS AND RELEVANCE In this cohort study, high-level or increasing prepubertal growth
trajectories and greater CEA were associated with earlier and higher risk of pubertal onset. These
findings highlight the importance of considering CEA in relation to early pubertal onset and suggest
that ages 3 to 4 years may be an important intervention period for earlier pubertal onset monitoring.
URI (Link)
External resource (Link)
ISBN
2574-3805
Type
Journal Articles
