CC BY 4.0 DEED Attribution 4.0 InternationalSalway, RuthArmstrong, MirandaMariapun, JeevithaReidpath, DanielBrady, SophiaYasin, Mohamed ShajahanSu, Tin TinJohnson, Laura2024-05-282024-05-282024-05-272023-11-20Salway, R., Armstrong, M., Mariapun, J., Reidpath, D.D., Brady, S., Yasin, M.S., Su, T.T. and Johnson, L. (2024) ‘Predicting higher child BMI z-score and obesity incidence in Malaysia: a longitudinal analysis of a dynamic cohort study’, BMC Public Health, 24(1), p. 1408. Available at: https://doi.org/10.1186/s12889-024-18917-9.https://eresearch.qmu.ac.uk/handle/20.500.12289/13745https://doi.org/10.1186/s12889-024-18917-9From Springer Nature via Jisc Publications RouterHistory: received 2023-11-20, registration 2024-05-21, accepted 2024-05-21, epub 2024-05-27, online 2024-05-27, collection 2024-12-01Acknowledgements: The authors would like to express their appreciation to the SEACO Field Teams and survey participants. The research described in this paper was supported by the South East Asia Community Observatory (SEACO, https://www.monash.edu.my/seaco). The views, however, are those of the authors and there is no real or implied endorsement by SEACO.Publication status: PublishedFunder: UK Medical Research Council and the Malaysian Ministry of Higher Education/UK-MY Joint Partnership on Non-Communicable Diseases; Grant(s): 2019/MR/T018984/1, 2019/MR/T018984/1, 2019/MR/T018984/1, 2019/MR/T018984/1, 2019/MR/T018984/1, 2019/MR/T018984/1Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-0420Background: To target public health obesity prevention, we need to predict who might become obese i.e. predictors of increasing Body Mass Index (BMI) or obesity incidence. Predictors of incidence may be distinct from more well-studied predictors of prevalence, therefore we explored parent, child and sociodemographic predictors of child/adolescent BMI z-score and obesity incidence over 5 years in Malaysia. Methods: The South East Asia Community Observatory in Segamat, Malaysia, provided longitudinal data on children and their parents (n = 1767). Children were aged 6–14 years at baseline (2013-14) and followed up 5 years later. Linear multilevel models estimated associations with child BMI z-score at follow-up, adjusting for baseline BMI z-score and potential confounders. Predictors included parent cardiometabolic health (overweight/obesity, central obesity, hypertension, hyperglycaemia), and socio-demographics (ethnicity, employment, education). Logistic multilevel models explored predictors of obesity incidence. Results: Higher baseline BMI z-score predicted higher follow-up BMI z-score both in childhood to late adolescence (0.60; 95% CI: 0.55, 0.65) and early to late adolescence (0.76; 95% CI: 0.70, 0.82). There was inconsistent evidence of association between child BMI z-score at follow-up with parent cardiometabolic risk factors independent of baseline child BMI z-score. For example, maternal obesity, but not overweight, predicted a higher BMI z-score in childhood to early adolescence (overweight: 0.16; 95% CI: -0.03, 0.36, obesity: 0.41; 95% CI: 0.20, 0.61), and paternal overweight, but not obesity, predicted a higher BMI z-score in early to late adolescence (overweight: 0.22; 95% CI: 0.01, 0.43, obesity: 0.16; 95% CI: -0.10, 0.41). Parental obesity consistently predicted five-year obesity incidence in early to late adolescence, but not childhood to early adolescence. An adolescent without obesity at baseline with parents with obesity, had 3–4 times greater odds of developing obesity during follow-up (incidence OR = 3.38 (95% CI: 1.14–9.98, mother) and OR = 4.37 (95% CI 1.34–14.27, father) respectively). Conclusions: Having a higher BMI z-score at baseline was a stronger predictor of a higher BMI z-score at follow-up than any parental or sociodemographic factor. Targeting prevention efforts based on parent or sociodemographic factors is unwarranted but early childhood remains a key period for universal obesity prevention.1408Licence for this article: http://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.http://creativecommons.org/licenses/by/4.0/Cardiometabolic Risk FactorsChildrenIntergenerational ObesityBMIAdolescentsMalaysiaarticle2024-05-27