{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T16:45:04Z","timestamp":1785775504164,"version":"3.56.0"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":52,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32500156"],"award-info":[{"award-number":["32500156"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shandong Province Traditional Chinese Medicine Science and Technology Project","award":["Z20243204"],"award-info":[{"award-number":["Z20243204"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["World J Pediatr"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Early-life growth trajectories, especially during the first two years, are important for future health. However, in the context of rapidly rising childhood obesity, it is essential to characterize BMI-for-age\n                      <jats:italic>Z<\/jats:italic>\n                      -score (BAZ) trajectories in early childhood, compare optimal modeling approaches, and identify associated risk factors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This prospective birth cohort study enrolled participants in Jinan, Shandong from 2019 to 2022. World Health Organization (WHO)-standardized BAZ scores were calculated for children at eight timepoints (0\u201324\u00a0months). Sex-specific BAZ trajectories were derived using growth mixture modeling (GMM) and k-means for longitudinal data (KML). The possible risk of being overweight (BAZ\u2009&gt;\u20091) at age three years was predicted using logistic regression with five folds cross-validation, comparing model performance via the area under the curve (AUC). Associations between trajectory classification and antenatal and postnatal factors were examined.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 4629 mother-infant dyads were enrolled in this study. The KML-derived four-class trajectory model demonstrated optimal predictive performance for possible risk of being overweight at age three years, achieving an AUC of 0.749 and significantly outperforming the GMM model (AUC\u2009=\u20090.571). Male sex [odds ratio (OR)\u2009=\u20091.314; 95% confidence interval (95%\u00a0CI): 1.098, 1.572], high birth weight (OR\u2009=\u20094.739; 95%\u00a0CI: 3.594, 6.250), multiparity (OR\u2009=\u20091.265; 95%\u00a0CI: 1.003, 1.594), and gestational hypertension (OR\u2009=\u20092.581; 95%\u00a0CI: 1.387, 4.801) were identified as risk factors for high growth trajectory.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The KML model was identified as the more effective approach for delineating BAZ trajectories and predicting the risk of being overweight in our study population. Furthermore, male sex, high birth weight, multiparity, and gestational hypertension were identified as key antenatal and postnatal factors associated with higher growth trajectories.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s12519-026-01057-y","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T12:53:58Z","timestamp":1784811238000},"page":"664-677","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["BMI-for-age Z-score trajectories in early childhood: a comparison of GMM and KML and associated antenatal and postnatal factors"],"prefix":"10.1007","volume":"22","author":[{"given":"Ting","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zi-Yun","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen-Yu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mai","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui-Juan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai-Jun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2233-7061","authenticated-orcid":false,"given":"Yan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"key":"1057_CR1","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph13090838","volume":"13","author":"C Mameli","year":"2016","unstructured":"Mameli C, Mazzantini S, Zuccotti GV. Nutrition in the first 1000 days: the origin of childhood obesity. Int J Environ Res Public Health. 2016;13:838. https:\/\/doi.org\/10.3390\/ijerph13090838.","journal-title":"Int J Environ Res Public Health"},{"key":"1057_CR2","doi-asserted-by":"publisher","first-page":"872","DOI":"10.1038\/s41366-025-01714-8","volume":"49","author":"A Heiskala","year":"2025","unstructured":"Heiskala A, Tucker JD, Choudhary P, Nedelec R, Ronkainen J, Sarala O, et al. Timing based clustering of childhood Bmi trajectories reveals differential maturational patterns; study in the Northern Finland Birth Cohorts 1966 and 1986. Int J Obes (Lond). 2025;49:872\u201380. https:\/\/doi.org\/10.1038\/s41366-025-01714-8.","journal-title":"Int J Obes (Lond)"},{"key":"1057_CR3","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1002\/cdt3.58","volume":"9","author":"JYL Tung","year":"2023","unstructured":"Tung JYL, Poon GWK, Du J, Wong KKY. Obesity in children and adolescents: overview of the diagnosis and management. Chronic Dis Transl Med. 2023;9:122\u201333. https:\/\/doi.org\/10.1002\/cdt3.58.","journal-title":"Chronic Dis Transl Med"},{"key":"1057_CR4","unstructured":"World Health Organization, United Nations Children's Fund (UNICEF), World Bank Group. Levels and Trends in Child Malnutrition: UNICEF \/WHO\/World Bank Group Joint Child Malnutrition Estimates: Key Findings of the 2025 Edition. Geneva: World Health Organization; 2025. Available from: https:\/\/iris.who.int\/handle\/10665\/381846. Accessed 6 Jan 2026."},{"key":"1057_CR5","unstructured":"The State Council Information Office of the People's Republic of China (SCIO). Scio Holds News Conference on High-Quality Implementation of 14th Five-Year Plan, Highlighting Health Achievements. Available from: http:\/\/www.scio.gov.cn\/live\/2025\/37226\/index.html. Accessed 6 Jan 2026."},{"key":"1057_CR6","doi-asserted-by":"publisher","first-page":"34","DOI":"10.3109\/07853890.2014.963664","volume":"47","author":"MB von Bonsdorff","year":"2015","unstructured":"von Bonsdorff MB, T\u00f6rm\u00e4kangas T, Rantanen T, Salonen MK, Osmond C, Kajantie E, et al. Early life body mass trajectories and mortality in older age: findings from the Helsinki Birth Cohort Study. Ann Med. 2015;47:34\u20139. https:\/\/doi.org\/10.3109\/07853890.2014.963664.","journal-title":"Ann Med"},{"key":"1057_CR7","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1111\/jora.12239","volume":"26","author":"ME Ames","year":"2016","unstructured":"Ames ME, Wintre MG. Growth mixture modeling of adolescent body mass index development: longitudinal patterns of internalizing symptoms and physical activity. J Res Adolesc. 2016;26:889\u2013901. https:\/\/doi.org\/10.1111\/jora.12239.","journal-title":"J Res Adolesc"},{"key":"1057_CR8","doi-asserted-by":"publisher","first-page":"e2919","DOI":"10.1210\/clinem\/dgab235","volume":"106","author":"YF Wu","year":"2021","unstructured":"Wu YF, Fan HY, Chen YC, Kuo KL, Chien KL. Adolescent tri-ponderal mass index growth trajectories and incident diabetes mellitus in early adulthood. J Clin Endocrinol Metab. 2021;106:e2919\u201327. https:\/\/doi.org\/10.1210\/clinem\/dgab235.","journal-title":"J Clin Endocrinol Metab"},{"key":"1057_CR9","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1111\/resp.12928","volume":"22","author":"M Movin","year":"2017","unstructured":"Movin M, Garden FL, Protudjer JL, Ullemar V, Svensdotter F, Andersson D, et al. Impact of childhood asthma on growth trajectories in early adolescence: findings from the Childhood Asthma Prevention Study (Caps). Respirology. 2017;22:460\u20135. https:\/\/doi.org\/10.1111\/resp.12928.","journal-title":"Respirology"},{"key":"1057_CR10","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1136\/jech-2014-204571","volume":"69","author":"TF Mebrahtu","year":"2015","unstructured":"Mebrahtu TF, Feltbower RG, Petherick ES, Parslow RC. Growth patterns of White British and Pakistani children in the Born in Bradford Cohort: a latent growth modelling approach. J Epidemiol Community Health. 2015;69:368\u201373. https:\/\/doi.org\/10.1136\/jech-2014-204571.","journal-title":"J Epidemiol Community Health"},{"key":"1057_CR11","doi-asserted-by":"publisher","first-page":"e112","DOI":"10.1016\/j.cmpb.2011.05.008","volume":"104","author":"C Genolini","year":"2011","unstructured":"Genolini C, Falissard B. Kml: a package to cluster longitudinal data. Comput Methods Programs Biomed. 2011;104:e112\u201321. https:\/\/doi.org\/10.1016\/j.cmpb.2011.05.008.","journal-title":"Comput Methods Programs Biomed"},{"key":"1057_CR12","doi-asserted-by":"publisher","DOI":"10.1097\/pn9.0000000000000037","volume":"2","author":"W Huang","year":"2023","unstructured":"Huang W, Meir AY, Olapeju B, Wang G, Hong X, Venkataramani M, et al. Defining longitudinal trajectory of body mass index percentile and predicting childhood obesity: methodologies and findings in the boston birth cohort. Precis Nutr. 2023;2:e00037. https:\/\/doi.org\/10.1097\/pn9.0000000000000037.","journal-title":"Precis Nutr"},{"key":"1057_CR13","doi-asserted-by":"publisher","first-page":"1000","DOI":"10.1093\/ije\/dyab021","volume":"50","author":"P Massara","year":"2021","unstructured":"Massara P, Keown-Stoneman CD, Erdman L, Ohuma EO, Bourdon C, Maguire JL, et al. Identifying longitudinal-growth patterns from infancy to childhood: a study comparing multiple clustering techniques. Int J Epidemiol. 2021;50:1000\u201310. https:\/\/doi.org\/10.1093\/ije\/dyab021.","journal-title":"Int J Epidemiol"},{"key":"1057_CR14","doi-asserted-by":"publisher","first-page":"5513","DOI":"10.1002\/sim.9917","volume":"42","author":"Z Lu","year":"2023","unstructured":"Lu Z, Ahmadiankalati M, Tan Z. Joint clustering multiple longitudinal features: a comparison of methods and software packages with practical guidance. Stat Med. 2023;42:5513\u201340. https:\/\/doi.org\/10.1002\/sim.9917.","journal-title":"Stat Med"},{"key":"1057_CR15","doi-asserted-by":"publisher","first-page":"998","DOI":"10.1111\/obr.12842","volume":"20","author":"M Mattsson","year":"2019","unstructured":"Mattsson M, Maher GM, Boland F, Fitzgerald AP, Murray DM, Biesma R. Group-based trajectory modelling for Bmi trajectories in childhood: a systematic review. Obes Rev. 2019;20:998\u20131015. https:\/\/doi.org\/10.1111\/obr.12842.","journal-title":"Obes Rev"},{"key":"1057_CR16","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0319237","volume":"20","author":"N van Biljon","year":"2025","unstructured":"van Biljon N, Lake MT, Goddard L, Botha M, Zar HJ, Little F. Latent classes of anthropometric growth in early childhood using uni- and multivariate approaches in a South African birth cohort. PLoS ONE. 2025;20:e0319237. https:\/\/doi.org\/10.1371\/journal.pone.0319237.","journal-title":"PLoS ONE"},{"key":"1057_CR17","doi-asserted-by":"publisher","DOI":"10.1038\/nutd.2016.6","volume":"6","author":"B Stuart","year":"2016","unstructured":"Stuart B, Panico L. Early-childhood Bmi trajectories: evidence from a prospective, nationally representative British cohort study. Nutr Diabetes. 2016;6:e198. https:\/\/doi.org\/10.1038\/nutd.2016.6.","journal-title":"Nutr Diabetes"},{"key":"1057_CR18","doi-asserted-by":"publisher","first-page":"1703","DOI":"10.1002\/oby.21158","volume":"23","author":"AW Tu","year":"2015","unstructured":"Tu AW, Masse LC, Lear SA, Gotay CC, Richardson CG. Body mass index trajectories from ages 1 to 20: results from two nationally representative Canadian longitudinal cohorts. Obesity. 2015;23:1703\u201311. https:\/\/doi.org\/10.1002\/oby.21158.","journal-title":"Obesity"},{"key":"1057_CR19","doi-asserted-by":"publisher","first-page":"934","DOI":"10.1136\/jech-2014-203808","volume":"68","author":"AH Ziyab","year":"2014","unstructured":"Ziyab AH, Karmaus W, Kurukulaaratchy RJ, Zhang H, Arshad SH. Developmental trajectories of body mass index from infancy to 18 years of age: prenatal determinants and health consequences. J Epidemiol Community Health. 2014;68:934\u201341. https:\/\/doi.org\/10.1136\/jech-2014-203808.","journal-title":"J Epidemiol Community Health"},{"key":"1057_CR20","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1111\/j.2047-6310.2012.00112.x","volume":"8","author":"CA Magee","year":"2013","unstructured":"Magee CA, Caputi P, Iverson DC. Identification of distinct body mass index trajectories in Australian children. Pediatr Obes. 2013;8:189\u201398. https:\/\/doi.org\/10.1111\/j.2047-6310.2012.00112.x.","journal-title":"Pediatr Obes"},{"key":"1057_CR21","doi-asserted-by":"publisher","first-page":"906","DOI":"10.1001\/archpediatrics.2011.153","volume":"165","author":"LE Pryor","year":"2011","unstructured":"Pryor LE, Tremblay RE, Boivin M, Touchette E, Dubois L, Genolini C. Developmental trajectories of body mass index in early childhood and their risk factors: an 8-year longitudinal study. Arch Pediatr Adolesc Med. 2011;165:906\u201312. https:\/\/doi.org\/10.1001\/archpediatrics.2011.153.","journal-title":"Arch Pediatr Adolesc Med"},{"key":"1057_CR22","doi-asserted-by":"publisher","first-page":"2067","DOI":"10.1038\/oby.2009.123","volume":"17","author":"AK Ventura","year":"2009","unstructured":"Ventura AK, Loken E, Birch LL. Developmental trajectories of girls\u2019 Bmi across childhood and adolescence. Obesity. 2009;17:2067\u201374. https:\/\/doi.org\/10.1038\/oby.2009.123.","journal-title":"Obesity"},{"key":"1057_CR23","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-09046-y","volume":"7","author":"IM Aris","year":"2017","unstructured":"Aris IM, Chen LW, Tint MT, Pang WW, Soh SE, Saw SM, et al. Body Mass Index trajectories in the first two years and subsequent childhood cardio-metabolic outcomes: a prospective multi-ethnic Asian cohort study. Sci Rep. 2017;7:8424. https:\/\/doi.org\/10.1038\/s41598-017-09046-y.","journal-title":"Sci Rep"},{"key":"1057_CR24","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1016\/j.amepre.2015.11.012","volume":"50","author":"JA Woo Baidal","year":"2016","unstructured":"Woo Baidal JA, Locks LM, Cheng ER, Blake-Lamb TL, Perkins ME, Taveras EM. Risk factors for childhood obesity in the first 1,000 days: a systematic review. Am J Prev Med. 2016;50:761\u201379. https:\/\/doi.org\/10.1016\/j.amepre.2015.11.012.","journal-title":"Am J Prev Med"},{"key":"1057_CR25","doi-asserted-by":"publisher","DOI":"10.1111\/ijpo.12633","volume":"15","author":"X Li","year":"2020","unstructured":"Li X, Keown-Stoneman CDG, Lebovic G, Omand JA, Adeli K, Hamilton JK, et al. The association between Body Mass Index trajectories and cardiometabolic risk in young children. Pediatr Obes. 2020;15:e12633. https:\/\/doi.org\/10.1111\/ijpo.12633.","journal-title":"Pediatr Obes"},{"key":"1057_CR26","doi-asserted-by":"publisher","DOI":"10.1111\/ijpo.13180","volume":"20","author":"D Goulet","year":"2025","unstructured":"Goulet D, Boivin M, Gravel CA, Little J, Potter BK, Dubois L. Mediation of genetic susceptibility to obesity through eating behaviours in children. Pediatr Obes. 2025;20:e13180. https:\/\/doi.org\/10.1111\/ijpo.13180.","journal-title":"Pediatr Obes"},{"key":"1057_CR27","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1111\/j.1651-2227.2006.tb02378.x","volume":"450","author":"WHOMGRS","year":"2006","unstructured":"WHOMGRS. Who child growth standards based on length\/height, weight and age. Acta Paediatr Suppl. 2006;450:76\u201385. https:\/\/doi.org\/10.1111\/j.1651-2227.2006.tb02378.x.","journal-title":"Acta Paediatr Suppl"},{"key":"1057_CR28","doi-asserted-by":"publisher","first-page":"458","DOI":"10.3109\/17477161003615583","volume":"5","author":"M de Onis","year":"2010","unstructured":"de Onis M, Lobstein T. Defining obesity risk status in the general childhood population: which cut-offs should we use? Int J Pediatr Obes. 2010;5:458\u201360. https:\/\/doi.org\/10.3109\/17477161003615583.","journal-title":"Int J Pediatr Obes"},{"key":"1057_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.envres.2023.117509","volume":"240","author":"MA Bravo","year":"2024","unstructured":"Bravo MA, Zephyr D, Fiffer MR, Miranda ML. Weekly prenatal Pm(2.5) and No(2) exposures in preterm, early term, and full term infants: decrements in birth weight and critical windows of susceptibility. Environ Res. 2024;240:117509. https:\/\/doi.org\/10.1016\/j.envres.2023.117509.","journal-title":"Environ Res"},{"key":"1057_CR30","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.bpobgyn.2020.06.006","volume":"70","author":"E Attali","year":"2021","unstructured":"Attali E, Yogev Y. The impact of advanced maternal age on pregnancy outcome. Best Pract Res Clin Obstet Gynaecol. 2021;70:2\u20139. https:\/\/doi.org\/10.1016\/j.bpobgyn.2020.06.006.","journal-title":"Best Pract Res Clin Obstet Gynaecol"},{"key":"1057_CR31","doi-asserted-by":"publisher","first-page":"1205","DOI":"10.2147\/CLEP.S265287","volume":"12","author":"HL Nguena Nguefack","year":"2020","unstructured":"Nguena Nguefack HL, Page MG, Katz J, Choiniere M, Vanasse A, Dorais M, et al. Trajectory modelling techniques useful to epidemiological research: a comparative narrative review of approaches. Clin Epidemiol. 2020;12:1205\u201322. https:\/\/doi.org\/10.2147\/CLEP.S265287.","journal-title":"Clin Epidemiol"},{"key":"1057_CR32","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1093\/jpepsy\/jst085","volume":"39","author":"KS Berlin","year":"2014","unstructured":"Berlin KS, Parra GR, Williams NA. An introduction to latent variable mixture modeling (Part 2): longitudinal latent class growth analysis and growth mixture models. J Pediatr Psychol. 2014;39:188\u2013203. https:\/\/doi.org\/10.1093\/jpepsy\/jst085.","journal-title":"J Pediatr Psychol"},{"key":"1057_CR33","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1002\/oby.22095","volume":"26","author":"P Montazeri","year":"2018","unstructured":"Montazeri P, Vrijheid M, Martinez D, Basterrechea M, Fernandez-Somoano A, Guxens M, et al. Maternal metabolic health parameters during pregnancy in relation to early childhood BMI trajectories. Obesity. 2018;26:588\u201396. https:\/\/doi.org\/10.1002\/oby.22095.","journal-title":"Obesity"},{"key":"1057_CR34","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1093\/ije\/dyac177","volume":"52","author":"N Michael","year":"2023","unstructured":"Michael N, Gupta V, Fogel A, Huang J, Chen L, Sadananthan SA, et al. Longitudinal characterization of determinants associated with obesogenic growth patterns in early childhood. Int J Epidemiol. 2023;52:426\u201339. https:\/\/doi.org\/10.1093\/ije\/dyac177.","journal-title":"Int J Epidemiol"},{"key":"1057_CR35","doi-asserted-by":"publisher","first-page":"1348","DOI":"10.3760\/cma.j.cn112338-20240513-00270","volume":"45","author":"SS Wang","year":"2024","unstructured":"Wang SS, Yue ZH, Han N, Lyu JL, Ji YL, Wang H, et al. Association of Maternal Pre-Pregnancy Bmi, Gestational Weight Gain, and Gestational Diabetes Mellitus with Bmi Trajectory in Early Childhood: A Prospective Cohort Study. Zhonghua Liu Xing Bing Xue Za Zhi. 2024;45:1348\u201355. https:\/\/doi.org\/10.3760\/cma.j.cn112338-20240513-00270.","journal-title":"Zhonghua Liu Xing Bing Xue Za Zhi"},{"key":"1057_CR36","doi-asserted-by":"publisher","DOI":"10.1111\/ijpo.12769","volume":"16","author":"T Begum","year":"2021","unstructured":"Begum T, Fatima Y, Perales F, Anuradha S, Mamun A. Associations of caesarean section with body mass and waist circumference trajectories from age 2 to 13\u2009years: a nationally representative birth cohort study in Australia. Pediatr Obes. 2021;16:e12769. https:\/\/doi.org\/10.1111\/ijpo.12769.","journal-title":"Pediatr Obes"},{"key":"1057_CR37","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0330715","volume":"20","author":"X Meng","year":"2025","unstructured":"Meng X, Wang J, Zhang N, Li X, Wu Q. Application of group-based trajectory models to evaluate the association of fetal growth trajectories and childhood overweight and obesity: a longitudinal study with 2-year follow-up. PLoS ONE. 2025;20:e0330715. https:\/\/doi.org\/10.1371\/journal.pone.0330715.","journal-title":"PLoS ONE"},{"key":"1057_CR38","doi-asserted-by":"publisher","DOI":"10.3389\/fped.2020.612235","volume":"8","author":"L Lucaccioni","year":"2020","unstructured":"Lucaccioni L, Trevisani V, Boncompagni A, Marrozzini L, Berardi A, Iughetti L. Minipuberty: looking back to understand moving forward. Front Pediatr. 2020;8:612235. https:\/\/doi.org\/10.3389\/fped.2020.612235.","journal-title":"Front Pediatr"},{"key":"1057_CR39","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1111\/ppe.12099","volume":"28","author":"SN Hinkle","year":"2014","unstructured":"Hinkle SN, Albert PS, Mendola P, Sjaarda LA, Yeung E, Boghossian NS, et al. The association between parity and birthweight in a longitudinal consecutive pregnancy cohort. Paediatr Perinat Epidemiol. 2014;28:106\u201315. https:\/\/doi.org\/10.1111\/ppe.12099.","journal-title":"Paediatr Perinat Epidemiol"},{"key":"1057_CR40","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2022.906781","volume":"13","author":"S Yan","year":"2022","unstructured":"Yan S, Lyu J, Liu Z, Zhou S, Ji Y, Wang H. Association of gestational hypertension and preeclampsia with offspring adiposity: a systematic review and meta-analysis. Front Endocrinol (Lausanne). 2022;13:906781. https:\/\/doi.org\/10.3389\/fendo.2022.906781.","journal-title":"Front Endocrinol (Lausanne)"}],"container-title":["World Journal of Pediatrics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12519-026-01057-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12519-026-01057-y","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12519-026-01057-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T15:52:55Z","timestamp":1785772375000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12519-026-01057-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":40,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["1057"],"URL":"https:\/\/doi.org\/10.1007\/s12519-026-01057-y","relation":{},"ISSN":["1708-8569","1867-0687"],"issn-type":[{"value":"1708-8569","type":"print"},{"value":"1867-0687","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"6 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 February 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 May 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 July 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"No financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ethical approval was granted by Shandong Provincial Maternal and Child Health Care Hospital Affiliated to Qingdao University (No. 2025\u2013040).","order":2,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Declarations"}}]}}