Cohort Profile: Chongqing Pubertal Timing and Environment Study in China with 15 Follow-Ups since 2014
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Participants
2.2. Measurements
2.2.1. Physical Examinations
2.2.2. Urine Sample Measurements
2.2.3. Questionnaires
3. Results
3.1. Pubertal Development
3.2. Risk Factors
3.3. Health Outcomes
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Appendix B
Publication Title | DOI | Key Findings | Language |
---|---|---|---|
Risk Factors of Pubertal Development | |||
Levels and risk factors for urinary metabolites of polycyclic aromatic hydrocarbons in children living in Chongqing, China [25] | 10.1016/j.scitotenv.2017.04.103 | (1) Urinary concentrations of OH-PAHs were elevated in Chongqing compared to children in other countries. (2) Being female, older age, having a school location near an industrial site, consuming smoked foods, and low family income were associated with higher OH-PAH concentrations. | English |
Association of prepubertal obesity with pubertal development in Chinese girls and boys: A longitudinal study [65] | 10.1002/ajhb.23195 | Higher prepubertal BMI was associated with earlier puberty in both Chinese boys and girls. | English |
Maternal Age at Menarche and Pubertal Timing in Boys and Girls: A Cohort Study From Chongqing, China [1] | 10.1016/j.jadohealth.2020.06.036 | Earlier maternal age at menarche was related to earlier pubertal timing in Chongqing. | English |
Measuring urinary concentrations of neonicotinoid insecticides by modified solid-phase extraction-ultrahigh performance liquid chromatography-tandem mass spectrometry: Application to human exposure and risk assessment [26] | 10.1016/j.chemosphere.2021.129714 | (1) A robust method for quantification of urinary neonicotinoids was developed. (2) Girls had significantly higher urinary concentrations of clothianidin than boys. | English |
Polycyclic aromatic hydrocarbons are associated with later puberty in girls: A longitudinal study [72] | 10.1016/j.scitotenv.2022.157497 | (1) Girls with higher concentrations of 1-OHPyr and 2-OHFlu were at risk of delayed pubic hair. (2) Girls with higher concentrations of 2-OHNap were at risk of delayed breast and pubic hair. (3) Girls with higher concentrations of 9-OHPhe were at risk of delayed breast, pubic hair and axillary hair development. | English |
Urinary neonicotinoid concentrations and pubertal development in Chinese adolescents: A cross-sectional study [66] | 10.1016/j.envint.2022.107186 | (1) Higher thiacloprid concentration was associated with delayed genitalia development in boys and early axillary hair development in girls. (2) Neonicotinoid mixture was negatively associated with genitalia stage in the joint effect. | English |
The influence of the trajectory of obesity indicators on the age of pubertal onset and pubertal tempo in girls: A longitudinal study in Chongqing, China [77] | 10.3389/fpubh.2023.1025778 | (1) Overweight and obesity (BMI scale) before pubertal onset can influence pubertal onset age and B2-B5 pubertal tempo. (2) Overweight (BMI scale) and high WC before menarche have an impact on the age of menarche. (3) Overweight (WHtR scale) before menarche is associated with B2-B5 pubertal tempo. | English |
Relevant factors of early puberty timing in urban primary schools in Chongqing [58] | 10.19813/j.cnki.weishengyanjiu.2016.03.013. | Gender, parents’ relationship, and hair product use have an essential impact on early puberty timing. | Chinese |
Determination of polycyclic aromatic hydrocarbons in girls and association between polycyclic aromatic hydrocarbons exposure and puberty timing [78] | 10.19813/j.cnki.weishengyanjiu.2017.05.011 | (1) We developed a method for simultaneous determination of four metabolites of polycyclic of aromatic hydrocarbons. (2) Early exposure to PAHs might be one of the factors causing early puberty timing in girls. | Chinese |
Relationship between puberty growth and sexual development of boys [79] | 10.16835/j.cnki.1000-9817.2020.06.006 | (1) The height growth of boys reached its peak one year before the first ejaculation and began to decrease after first ejaculation. (2) The first ejaculation age of boys was negatively correlated with the increment of height in the following year. (3) The testicular development of boys was positively correlated with height, weight, and BMI. | Chinese |
Prospective cohort study on the association between family factors and the puberty timing in children [80] | 10.16835/j.cnki.1000-9817.2020.06.004. | Left behind children, self-perceived parental relationship, and family economic conditions were the influencing factors of pubic hair of girls. | Chinese |
Health Outcomes | |||
Co-Development and Bidirectional Associations Between Psychological Stress and Obesity in School-Aged Children: A Longitudinal Study in China [81] | 10.1097/PSY.0000000000001212 | Different aspects of psychological stress were differentially associated with obesity. There may be a clear reciprocal relationship between peer interaction psychological stress and obesity. | English |
Urinary neonicotinoid concentrations and obesity: A cross-sectional study among Chinese adolescents [82] | 10.1016/j.envpol.2024.123516 | (1) Nitenpyram, neonicotinoid mixtures, and clothianidin were positively associated with obesity. (2) Imidacloprid and thiacloprid were inversely associated with general obesity. (3) Acetamiprid and its metabolite were differently associated with obesity measures. (4) Sex differences were seen with nitenpyram and clothianidin and obesity. | English |
Predictive effect of psychological stress in early puberty on subsequent anxiety and depression [83] | 10.16835/j.cnki.1000-9817.2020.06.008 | The psychological stress level and age during early puberty had a positive predictive effect on anxiety and depression after 4 years. | Chinese |
Associations between psychosocial stress in early and middle adolescence with emotional and behavioral problems one year later [84] | 10.16835/j.cnki.1000-9817.2022.05.002 | Psychological stress levels in early and middle puberty have a positive predictive effect on emotional and behavioral problems in the following year. | Chinese |
Depressive symptoms and associated factors among adolescents in different pubertal stages in a district of Chongqing [85] | 10.16835/j.cnki.1000-9817.2022.05.018 | (1) The detection rate of depressive symptoms among adolescents is relatively low. (2) Boys who have had the first spermatorrhea and girls with advanced pubic hair development or who have had menarche are more likely to suffer from depressive symptoms. | Chinese |
Predictive effects of psychological stress in early and middle puberty on adolescent health-risk behaviors [86] | 10.16835/j.cnki.1000-9817.2022.05.004 | (1) Unreasonable physical activity and food preferences are the most common health-risk behaviors among adolescents. (2) Psychological stress during early to middle puberty is predictive of adolescent health-risk behaviors. | Chinese |
Effects of screen time and internet addiction on social anxiety among adolescents in a district of Chongqing [87] | 10.12173/j.issn.1004-5511.202304013 | Daily screen time might increase adolescents’ social anxiety, and more attention should be paid to teenage girls. | Chinese |
Effects of passive smoking exposure on adolescent emotional behaviors in household environment [88] | 10.16168/j.cnki.issn.1002-9982.2023.07.008 | (1) About 50% of adolescents had been exposed to second-hand smoke in their family environment. (2) Second-hand smoke exposure in the family environment is an important influencing factor of internalizing behaviors and overall emotional behavior. | Chinese |
Tool Development | |||
Development of the Stressful Life Events for Primary School Students [28] | NA | The Scale of Stressful Life Events for Primary School Students has good validity and reliability, and it could be used as an assessment tool for psychological stress level in primary school students. | Chinese |
Tool Name | Description | KMO in This Study | Cronbach α in This Study | Reference No. |
---|---|---|---|---|
Scale of Stressful Life Events for Primary School Students | The scale includes 45 items, with the score of stressful life events ranging from 1 to 5 points. | 0.85 | 0.88 | [17] |
Adolescent Psychosexual Health Questionnaire | The questionnaire includes 46 items with three sub-scales of sexual knowledge, sexual values, and sexual adaptation. | 0.92 | 0.89 | [18] |
Adolescent Students’ Life Satisfaction Scale | This scale includes 6 dimensions of friendship, family, study, freedom, school, and environment, with a total of 36 items. | 0.95 | 0.95 | [27] |
Social Support Scale | The scale includes 17 items based on a social support theory (subjective support, objective support, and support utilization). | 0.94 | 0.96 | [31] |
Multidimensional Sub-health Questionnaire of Adolescents | The questionnaire includes 71 items with physical sub-health with a total of 32 items and psychological sub-health areas with a total of 39 items. | 0.78–0.97 * | 0.93–0.98 * | [34] |
Adolescents Self-Harm Scale | The scale includes 18 items and 1 open-ended question with each item divided into 4 self-harm grades and 5 physical injury grades. | 0.93 | 0.99 | [35] |
Mental Health Inventory of Middle-School Students | The scale has a total of 60 items, composed of 10 sub-scales, evaluating 10 common psychological problems of middle school students. | 0.97 | 0.98 | [36] |
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Data | Baseline | Follow-Up 1 | Follow-Up 2 | Follow-Up 3 | Follow-Up 4 | Follow-Up 5 | Follow-Up 6 | Follow-Up 7 | Follow-Up 8 | Follow-Up 9 | Follow-Up 10 | Follow-Up 11 | Follow-Up 12 | Follow-Up 13 | Follow-Up 14 | Follow-Up 15 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Response rates (%) # | 100.0 | 99.4 | 98.4 | 98.0 | 83.1 | 90.3 | 84.0 | 83.4 | 73.5 | 70.1 | 57.9 | 58.8 | 50.3 | 46.7 | 38.8 | 30.7 |
Basic information | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
Physical examination | ||||||||||||||||
Anthropometric measurement | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
Tanner stage | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
Self-rated Tanner stage | √ | |||||||||||||||
Pubertal event to date | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
Urine sample | ||||||||||||||||
PAHs * | √ | √ | ||||||||||||||
Neonicotinoid | √ | |||||||||||||||
Heavy metals | √ | |||||||||||||||
Scale | ||||||||||||||||
Pubertal Development scale | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
Stressful life events | √ | √ | √ | √ | √ | √ | √ | |||||||||
Psychosexual health | √ | |||||||||||||||
YSR * | √ | √ | ||||||||||||||
CBCL * | √ | |||||||||||||||
Health risk behavior | √ | √ | ||||||||||||||
CDI * | √ | √ | √ | |||||||||||||
SCARED * | √ | √ | √ | |||||||||||||
Parent and peer attachment | √ | |||||||||||||||
Internet addiction | √ | √ | ||||||||||||||
Index of well-being | √ | |||||||||||||||
Life satisfaction | √ | |||||||||||||||
CLS * | √ | √ | ||||||||||||||
Self-esteem | √ | √ | ||||||||||||||
Aggression Questionnaire | √ | √ | ||||||||||||||
Social support | √ | |||||||||||||||
Social anxiety | √ | √ | ||||||||||||||
FAD * | √ | |||||||||||||||
PTM * | √ | √ | ||||||||||||||
MSQA * | √ | |||||||||||||||
Self-harm | √ | |||||||||||||||
MMHI-60 * | √ | |||||||||||||||
Potential influence factors | ||||||||||||||||
Family factors | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
Food exposures | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
Screen time | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | |
Exercise | √ | √ | √ | √ | ||||||||||||
Sleep | √ | √ | √ | |||||||||||||
Mother’s menarche time | √ | |||||||||||||||
Gestational Conditions | √ | |||||||||||||||
Self-report myopia | √ | √ |
Boys | Girls | |||||||
---|---|---|---|---|---|---|---|---|
Second Grade (n = 213) | Third Grade (n = 178) | Fourth Grade (n = 147) | Fifth Grade (n = 157) | Second Grade (n = 158) | Third Grade (n = 215) | Fourth Grade (n = 180) | Fifth Grade (n = 181) | |
Age (years, mean (SD)) | 7.4 (0.5) | 8.4 (0.5) | 9.4 (0.5) | 10.4 (0.5) | 7.7 (0.3) | 8.7 (0.4) | 9.7 (0.4) | 10.7 (0.5) |
Height (cm, mean (SD)) | 127.0 (5.7) | 132.5 (6.6) | 138.3 (6.6) | 142.4 (6.0) | 125.3 (5.3) | 131.3 (5.9) | 136.7 (6.8) | 143.9 (6.9) |
Weight (kg, mean (SD)) | 27.6 (5.1) | 31.7 (7.5) | 34.9 (7.8) | 38.7 (9.0) | 26.0 (4.8) | 29.4 (5.4) | 32.8 (7.0) | 37.9 (7.7) |
Waist circumference (cm, mean (SD)) | 56.4 (6.6) | 59.8 (8.9) | 61.5 (9.2) | 65.0 (10.0) | 51.9 (6.4) | 53.9 (7.0) | 56.4 (7.3) | 59.5 (7.6) |
Hip circumference (cm, mean (SD)) | 63.5 (5.9) | 67.3 (7.4) | 70.1 (7.2) | 73.2 (7.5) | 63.8 (5.5) | 66.7 (5.4) | 69.6 (6.7) | 73.8 (6.4) |
BMI | ||||||||
Normal | 140 (65.7%) | 101 (56.7%) | 98 (66.7%) | 97 (61.8%) | 119 (75.3%) | 160 (74.4%) | 138 (76.7%) | 143 (79.0%) |
Overweight | 34 (16.0%) | 29 (16.3%) | 23 (15.6%) | 33 (21.0%) | 22 (13.9%) | 33 (15.3%) | 20 (11.1%) | 22 (12.2%) |
Obesity | 39 (18.3%) | 48 (27.0%) | 26 (17.7%) | 27 (17.2%) | 17 (10.8%) | 22 (10.2%) | 22 (12.2%) | 16 (8.8%) |
Menarche | 1 (0.6%) | 0 (0.0%) | 1 (0.6%) | 16 (8.8%) | ||||
First spermatorrhea | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 10 (6.4%) | ||||
Tanner Stage | ||||||||
PH2 * | 0 (0.0%) | 1 (0.6%) | 3 (2.0%) | 9 (5.7%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 22 (12.2%) |
G2* | 2 (0.9%) | 17 (9.6%) | 61 (41.5%) | 113 (72.0%) | ||||
B2 | 0 (0.0%) | 20 (9.3%) | 55 (30.6%) | 129 (71.3%) | ||||
AH2 * | 0 (0.0%) | 1 (0.6%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 10 (5.5%) |
TV * ≥ 4 mL | 0 (0.0%) | 2 (1.1%) | 24 (16.3%) | 60 (38.2%) | ||||
Beard2 | 1 (0.4%) | 11 (6.2%) | 24 (16.3%) | 37 (23.6%) |
Characteristic | Girls (n = 734) | Boys (n = 695) | p-Value |
---|---|---|---|
Age (SD) | 9.2 (1.2) | 8.7 (1.2) | <0.001 |
Mother’s menarche time (SD) | 13.4 (2.5) | 13.5 (2.6) | 0.297 |
Birth weight (kg, mean (SD)) | 3.2 (0.5) | 3.3 (0.5) | <0.001 |
Weekday screen time/day (min, mean (SD)) | 57.9 (52.0) | 63.2 (55.8) | 0.063 |
Weekend screen time/day (min, mean (SD)) | 149.9 (112.6) | 156.8 (114.3) | 0.253 |
Parental marital status | 0.735 | ||
Divorced | 69 (9.4%) | 69 (9.9%) | |
Married | 664 (90.6%) | 625 (90.1%) | |
Parental relationship | 0.008 | ||
Very good | 486 (66.2%) | 413 (59.4%) | |
Good | 153 (20.8%) | 143 (20.6%) | |
Fair | 64 (8.7%) | 94 (13.5%) | |
Bad | 20 (2.7%) | 32 (4.6%) | |
Very bad | 11 (1.5%) | 13 (1.9%) | |
Father’s education | 0.646 | ||
Primary school and below | 63 (8.6%) | 63 (9.1%) | |
Middle school | 274 (37.3%) | 248 (35.8%) | |
High school | 236 (32.2%) | 242 (34.9%) | |
College and above | 161 (21.9%) | 140 (20.2%) | |
Mother’s education | 0.136 | ||
Primary school and below | 112 (15.3%) | 80 (11.6%) | |
Middle school | 248 (33.8%) | 254 (36.8%) | |
High school | 231 (31.5%) | 234 (33.9%) | |
College and above | 142 (19.4%) | 123 (17.8%) | |
Father’s smoking | 0.991 | ||
Yes | 420 (58.3%) | 400 (58.2%) | |
No | 301 (41.7%) | 287 (41.8%) | |
Mother’s smoking | 0.927 | ||
Yes | 10 (1.4%) | 9 (1.3%) | |
No | 719 (98.6%) | 675 (98.7%) | |
Foods with high estrogen | 0.235 | ||
Never | 29 (4.0%) | 32 (4.6%) | |
Less than once per month | 8 (1.1%) | 19 (2.7%) | |
1 to 3 times per month | 292 (39.8%) | 276 (39.8%) | |
Once per week | 195 (26.6%) | 170 (24.5%) | |
2 to 3 times per week | 141 (19.2%) | 144 (20.8%) | |
4 to 6 times per week | 41 (5.6%) | 31 (4.5%) | |
Every day | 28 (3.8%) | 21 (3.0%) | |
Smoked food | 0.242 | ||
Never | 190 (25.9%) | 170 (24.5%) | |
Occasionally | 47 (6.4%) | 69 (10.0%) | |
1 to 3 times per month | 376 (51.2%) | 352 (50.8%) | |
Once per week | 66 (9.0%) | 62 (8.9%) | |
2 to 3 times per week | 32 (4.4%) | 25 (3.6%) | |
4 to 6 times per week | 20 (2.7%) | 14 (2.0%) | |
Every day | 3 (0.4%) | 1 (0.1%) | |
Fried food | 0.011 | ||
Never | 89 (12.1%) | 59 (8.5%) | |
Occasionally | 20 (2.7%) | 42 (6.2%) | |
1 to 3 times per month | 398 (54.3%) | 382 (55.1%) | |
Once per week | 129 (17.6%) | 116 (16.7%) | |
2 to 3 times per week | 69 (9.4%) | 60 (8.7%) | |
4 to 6 times per week | 25 (3.4%) | 26 (3.8%) | |
Every day | 3 (0.4%) | 7 (1.0%) |
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Wu, D.; Luo, J.; Zhang, Q.; Liu, S.; Xi, X.; Wu, W.; Zhou, Y.; Tian, Y.; Wang, Y.; He, Z.; et al. Cohort Profile: Chongqing Pubertal Timing and Environment Study in China with 15 Follow-Ups since 2014. Future 2024, 2, 107-125. https://doi.org/10.3390/future2030009
Wu D, Luo J, Zhang Q, Liu S, Xi X, Wu W, Zhou Y, Tian Y, Wang Y, He Z, et al. Cohort Profile: Chongqing Pubertal Timing and Environment Study in China with 15 Follow-Ups since 2014. Future. 2024; 2(3):107-125. https://doi.org/10.3390/future2030009
Chicago/Turabian StyleWu, Di, Jie Luo, Qin Zhang, Shudan Liu, Xuan Xi, Wenyi Wu, Yuanke Zhou, Yu Tian, Yujie Wang, Zongwei He, and et al. 2024. "Cohort Profile: Chongqing Pubertal Timing and Environment Study in China with 15 Follow-Ups since 2014" Future 2, no. 3: 107-125. https://doi.org/10.3390/future2030009
APA StyleWu, D., Luo, J., Zhang, Q., Liu, S., Xi, X., Wu, W., Zhou, Y., Tian, Y., Wang, Y., He, Z., Zhang, J., Wang, H., & Liu, Q. (2024). Cohort Profile: Chongqing Pubertal Timing and Environment Study in China with 15 Follow-Ups since 2014. Future, 2(3), 107-125. https://doi.org/10.3390/future2030009