Body Fat Percentage as an Indicator of Adiposity in Adolescents: An Overview Based on Circadian Rhythm, Ultra-Processed Food Consumption, and Physical Activity
DOI:
https://doi.org/10.35451/jkg.v9i1.3919Keywords:
Body fat percentage; Adolescent; Circadian rhythmAbstract
Obesity among adolescents is an important nutritional problem associated with an increased risk of metabolic disorders and non-communicable diseases. Body fat percentage provides a more specific assessment of adiposity than body mass index, while circadian rhythm, ultra-processed food consumption, and physical activity are lifestyle factors that may be associated with adolescent adiposity. This study aimed to analyze the characteristics of circadian rhythm, ultra-processed food consumption, physical activity, and body fat percentage and to examine the relationships of these factors with body fat percentage among adolescents. An analytical observational study with a cross-sectional design was conducted among 110 adolescents aged 16–18 years at senior high schools in Surabaya in June 2026. Circadian rhythm was assessed using the Morningness-Eveningness Questionnaire, ultra-processed food consumption was assessed using a Semi-Quantitative Food Frequency Questionnaire based on the NOVA classification, physical activity was assessed using the Physical Activity Questionnaire for Adolescents, and body fat percentage was measured using Bioelectrical Impedance Analysis. Bivariate analysis was performed using the Spearman rank correlation test with a significance level of 5%. The results show that circadian rhythm is not significantly associated with body fat percentage (r = −0.221; p = 0.053). Ultra-processed food consumption is positively and significantly associated with body fat percentage (r = 0.461; p = 0.016), whereas physical activity is negatively and significantly associated with body fat percentage (r = −0.411; p = 0.002). Thus, higher ultra-processed food consumption and lower physical activity are associated with a higher body fat percentage, whereas circadian rhythm shows no significant association with body fat percentage.
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[1] R. Agustina et al., “Psychosocial, Eating Behavior, and Lifestyle Factors Influencing Overweight and Obesity in Adolescents,” [1] R. Agustina al., “Psychosocial, Eat. Behav. Lifestyle Factors Influ. Overweight Obes. Adolesc., vol. 42, no. 1, hal. 72–91, 2021, doi: https://doi.org/10.1177/0379572121992750.
[2] N. Gifari, L. Sitoayu, R. Nuzrina, P. Ronitawati, M. Kuswari, dan T. J. Prasetyo, “The association of body image, percent body fat, nutrient intake, physical activity among adolescent,” Nutr. Food Sci., vol. 52, no. 8, hal. 1221–1230, 2022, doi: https://doi.org/10.1108/NFS-10-2021-0305.
[3] E. M. Barreto, A. T. Almeida, A. C. Neta, dan F. E. Ferreira, “Influence of Sleep Time on the Consumption of Ultra-Processed Foods in Adolescents in a Capital of Brazil: A Longitudinal Study,” 2025. doi: 10.3390/nu17010022.
[4] Y. Xie, K. Zhou, Z. Shang, D. Bao, dan J. Zhou, “The Effects of Time-Restricted Eating on Fat Loss in Adults with Overweight and Obese Depend upon the Eating Window and Intervention Strategies: A Systematic Review and Meta-Analysis,” Nutrients, vol. 16, no. 19, hal. 3390, 2024, doi: 10.3390/nu16193390.
[5] F. Mariestu, B. Wiboworini, dan V. Budiastuti, “Relationship between ultra-processed food consumption with body fat percentage and blood pressure in adolescence,” J. Gizi dan Diet. Indones. (Indonesian J. Nutr. Diet., vol. 13, hal. 268, Jul 2025, doi: 10.21927/ijnd.2025.13(4).268-275.
[6] R. De Amicis et al., “Ultra-processed foods and obesity and adiposity parameters among children and adolescents: a systematic review,” Eur. J. Nutr., vol. 61, no. 5, hal. 2297–2311, 2022, doi: 10.1007/s00394-022-02873-4 PMID- 35322333.
[7] I. Buekenhout, M. I. Clara, A. A. Gomes, dan J. Leitão, “Examining sex differences in morningness-eveningness and inter-individual variability across years of age: A cross-sectional study.,” Chronobiol. Int., vol. 42, no. 1, hal. 29–45, Jan 2025, doi: 10.1080/07420528.2024.2444667.
[8] A. Duston et al., “Sex Differences in Circadian Timing and Biological Night in Adolescents.,” J. Biol. Rhythms, vol. 40, no. 1, hal. 7–18, Feb 2025, doi: 10.1177/07487304241309165.
[9] R. H. O. Araujo et al., “Global prevalence and gender inequalities in at least 60 min of self-reported moderate-to-vigorous physical activity 1 or more days per week: An analysis with 707,616 adolescents,” J. Sport Heal. Sci., vol. 13, no. 5, hal. 607–617, 2024, doi: 10.1016/j.jshs.2023.10.011.
[10] T. Zahl-Thanem, L. Wichstrøm, dan S. Steinsbekk, “Relations between physical activity, sedentary time, and body fat from childhood to adolescence: Do they differ by sex?,” Int. J. Obes., vol. 46, no. 9, hal. 1615–1623, 2022, doi: 10.1038/s41366-022-01156-6.
[11] M. A. Duarte Junior, A. E. Mesas, dan S. Chen, “Adolescents’ chronotype and its association with obesity-related outcomes: The EHDLA study,” Pediatr. Obes., vol. 20, no. 4, hal. e13184, 2025, doi: 10.1111/ijpo.13184.
[12] N. Jankovic, S. Schmitting, B. Stutz, B. Krüger, A. Buyken, dan U. Alexy, “Alignment between timing of ‘highest caloric intake’ and chronotype in relation to body composition during adolescence: the DONALD Study,” Eur. J. Nutr., vol. 63, no. 1, hal. 253–265, 2024, doi: 10.1007/s00394-023-03259-w.
[13] J. Overberg, L. Kalveram, T. Keller, H. Krude, P. Kühnen, dan S. Wiegand, “Interactions between nocturnal melatonin secretion, metabolism, and sleeping behavior in adolescents with obesity,” Int. J. Obes., vol. 46, no. 5, hal. 1051–1058, 2022, doi: 10.1038/s41366-022-01077-4.
[14] D. Neri, E. Martínez-Steele, N. Khandpur, dan R. Levy, “Associations between ultra-processed foods consumption and indicators of adiposity in US adolescents: Cross-sectional analysis of the 2011–2016 National Health and Nutrition Examination Survey,” J. Acad. Nutr. Diet., vol. 122, no. 8, hal. 1474–1487, 2022, doi: 10.1016/j.jand.2022.01.005.
[15] V. Magalhães, M. Severo, S. Vilela, D. Torres, dan C. Lopes, “Patterns of ultra-processed foods consumption throughout childhood and trajectories of growth and adiposity,” Clin. Nutr., vol. 43, no. 10, hal. 2364–2371, 2024, doi: 10.1016/j.clnu.2024.08.032.
[16] E. Petridi, E. Magriplis, K. Karatzi, E. Charidemou, E. Philippou, dan A. Zampelas, “Ultra Processed Food Consumption in Children and Adolescents: Main Food Group Contributors and Associations With Weight Status.,” Nutr. Bull., vol. 50, no. 2, hal. 278–289, Jun 2025, doi: 10.1111/nbu.70001.
[17] B. Robles, A. Mota-Bertran, M. Saez, dan M. Solans, “Association between ultraprocessed food consumption and excess adiposity in children and adolescents: A systematic review,” Obes. Rev., vol. 25, no. 10, hal. e13796, 2024, doi: 10.1111/obr.13796.
[18] T. Wu et al., “Physical activity, screen time and body composition in 16-year-old adolescents: The Generation R Study.,” Pediatr. Obes., vol. 18, no. 11, hal. e13076, Nov 2023, doi: 10.1111/ijpo.13076.
[19] R. Soares, I. Brasil, W. Monteiro, dan P. Farinatti, “Effects of physical activity on body mass and composition of school-age children and adolescents with overweight or obesity: Systematic review focusing on intervention characteristics.,” J. Bodyw. Mov. Ther., vol. 33, hal. 154–163, Jan 2023, doi: 10.1016/j.jbmt.2022.09.004.
[20] B. Ribeiro et al., “The Benefits of Resistance Training in Obese Adolescents: A Systematic Review and Meta-analysis,” Sport. Med. - Open, vol. 8, no. 1, hal. 109, 2022, doi: 10.1186/s40798-022-00501-3.
[21] P. Haghjoo, G. Siri, E. Soleimani, M. A. Farhangi, dan S. Alesaeidi, “Screen time increases overweight and obesity risk among adolescents: a systematic review and dose-response meta-analysis,” BMC Prim. Care, vol. 23, no. 1, hal. 161, 2022, doi: 10.1186/s12875-022-01761-4.
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