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Lin Q, Jiang Y, Sun X, Zhang Y, Shan W, Zhao J, Wang X, Zhu Q, Sun W, Lu H, Jiang F. Weight spectrum and executive function in adolescents: the moderating role of negative emotions. Child Adolesc Psychiatry Ment Health 2022; 16:34. [PMID: 35534893 PMCID: PMC9087912 DOI: 10.1186/s13034-022-00468-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 04/06/2022] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND While recent works suggested that overweight/obesity may impair executive function (EF), the overweight/obesity-EF relationship has not been well studied in adolescents. Furthermore, no research has investigated adolescent EF impairments across the weight spectrum (e.g., underweight or thinness, normal, overweight/obesity), especially those with underweight condition, with the moderating effect of negative emotions in the weight-EF association being limitedly investigated. We aimed to determine whether overall and abdominal weight spectrum associated with EF impairments and to identity whether negative emotions moderate the weight-EF link in adolescents. METHODS We applied a subsample of the SCHEDULE-A project. Adolescents (11-18 years) were recruited using a multi-stage cluster random sampling approach. We measured the overall and abdominal weight spectrum by body mass index z-score and waist-to-height ratio, respectively. We used the Behavior Rating Inventory of Executive Function (BRIEF) to evaluate adolescent EF in nature setting, and utilized the Depression Anxiety and Stress Scales (DASS-21) to assess three types of negative emotional status (i.e., depression, anxiety, and stress). RESULTS Of the 1935 adolescents, 963 (49.8%) were male. We observed that abdominal, not overall, overweight was associated with the Global Executive Composite (GEC) impairment (OR = 1.59, 95% CI 1.07-2.35), particularly for inhibit, emotion control, shift, working memory, and monitor domains. Furthermore, depression moderated the abdominal overweight-GEC association (P = 0.032 for interaction term), especially for emotional control, working memory, and initiate dimensions. Moreover, we also found abdominal thinness was associated with the Metacognition Index problem (OR = 1.33, 95% CI 1.04-1.72), particularly for plan and monitor areas. CONCLUSIONS Both abdominal overweight and thinness were associated with adolescent EF, and depression would be a modifiable target to improve EF in adolescents with abdominal overweight. Future longitudinal studies are needed to investigate the causal relationship between abdominal weight spectrum and EF, as well as the underlying mechanisms among adolescents suffering from depression.
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Affiliation(s)
- Qingmin Lin
- grid.16821.3c0000 0004 0368 8293School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Yanrui Jiang
- grid.16821.3c0000 0004 0368 8293Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Rd., Shanghai, 200127 China ,grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092 China
| | - Xiaoning Sun
- grid.16821.3c0000 0004 0368 8293Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Rd., Shanghai, 200127 China ,grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092 China ,grid.511008.dShanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, 201602 China
| | - Yunting Zhang
- grid.16821.3c0000 0004 0368 8293Child Health Advocacy Institute, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127 China
| | - Wenjie Shan
- grid.16821.3c0000 0004 0368 8293Child Health Advocacy Institute, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127 China ,grid.16821.3c0000 0004 0368 8293Department of VIP Clinic, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127 China
| | - Jin Zhao
- grid.16821.3c0000 0004 0368 8293Child Health Advocacy Institute, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127 China
| | - Xuelai Wang
- grid.16821.3c0000 0004 0368 8293Child Health Advocacy Institute, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127 China
| | - Qi Zhu
- grid.16821.3c0000 0004 0368 8293Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Rd., Shanghai, 200127 China ,grid.16821.3c0000 0004 0368 8293Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092 China
| | - Wanqi Sun
- grid.16821.3c0000 0004 0368 8293Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200030 China
| | - Hui Lu
- grid.16821.3c0000 0004 0368 8293School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Fan Jiang
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Rd., Shanghai, 200127, China. .,Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China. .,Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, 201602, China.
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Sjöholm P, Pahkala K, Davison B, Juonala M, Singh G. Socioeconomic status, remoteness and tracking of nutritional status from childhood to adulthood in an Australian Aboriginal Birth Cohort: the ABC study. BMJ Open 2020; 10:e033631. [PMID: 31992605 PMCID: PMC7045147 DOI: 10.1136/bmjopen-2019-033631] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
OBJECTIVES To determine prevalences of underweight and overweight as well as low and high waist-to-height ratio (WHtR) in three prospective follow-ups and to explore tracking of these measures of nutritional status from childhood to adolescence and adulthood. The influence of socioeconomic status, remoteness, maternal body mass index (BMI) and birth weight on weight status was assessed. DESIGN Longitudinal birth cohort study of Indigenous Australians. SETTING Data derived from three follow-ups of the Aboriginal Birth Cohort study with mean ages of 11.4, 18.2 and 25.4 years for the participants. PARTICIPANTS Of the 686 Indigenous babies recruited to the study between 1987 and 1990, 315 had anthropometric measurements for all three follow-ups and were included in this study. PRIMARY AND SECONDARY OUTCOME MEASURES BMI categories (underweight, normal weight, overweight and obesity),WHtR categories (low and high), sex, areal socioeconomic disadvantage as defined by the Indigenous Relative Socioeconomic Outcomes index, urban/remote residence, maternal BMI and birth weight. Logistic regression was used to calculate ORs for belonging to a certain BMI category in adolescence and adulthood according to BMI category in childhood and adolescence. RESULTS Underweight was common (38% in childhood and 24% in adulthood) and the prevalence of overweight/obesity increased with age (12% in childhood and 35% in adulthood). Both extremes of weight status as well as low and high WHtR tracked from childhood to adulthood. Underweight was more common and overweight was less common in remote and more disadvantaged areas. Birth weight and maternal BMI were associated with later weight status. There were significant sex differences for prevalences and tracking of WHtR but not for BMI. CONCLUSIONS Socioeconomic factors, remoteness and gender must be addressed when assessing nutrition-related issues in the Indigenous communities due to the variation in nutritional status and its behaviour over time within the Indigenous population.
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Affiliation(s)
- Pauline Sjöholm
- Department of Medicine, University of Turku, Turku, Finland
- Department of Anesthesiology, Vaasa Central Hospital, Vaasa, Finland
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Paavo Nurmi Centre, Sports & Exercise Medicine Unit, Department of Physical Activity and Health, University of Turku, Turku, Finland
| | - Belinda Davison
- Menzies School of Health Research, Casuarina, Northern Territory, Australia
| | - Markus Juonala
- Department of Medicine, University of Turku, Turku, Finland
- Murdoch Childrens Research Institute, Parkville, Victoria, Australia
| | - Gurmeet Singh
- Menzies School of Health Research, Casuarina, Northern Territory, Australia
- Northern Territory Medical Program, Flinders University, Darwin, Northern Territory, Australia
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