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Luo S, Hsu E, Lawrence KE, Adise S, Pickering TA, Herting MM, Buchanan T, Page KA, Thompson PM. Associations among prenatal exposure to gestational diabetes mellitus, brain structure, and child adiposity markers. Obesity (Silver Spring) 2023; 31:2699-2708. [PMID: 37840377 PMCID: PMC11025497 DOI: 10.1002/oby.23901] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/22/2023] [Accepted: 04/04/2023] [Indexed: 10/17/2023]
Abstract
OBJECTIVE The aim of this study was to investigate the mediating role of child brain structure in the relationship between prenatal gestational diabetes mellitus (GDM) exposure and child adiposity. METHODS This was a cross-sectional study of 9- to 10-year-old participants and siblings across the US. Data were obtained from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study®. Brain structure was evaluated by magnetic resonance imaging. GDM exposure was self-reported, and discordance for GDM exposure within biological siblings was identified. Mixed effects and mediation models were used to examine associations among prenatal GDM exposure, brain structure, and adiposity markers with sociodemographic covariates. RESULTS The sample included 8521 children (7% GDM-exposed), among whom there were 28 sibling pairs discordant for GDM exposure. Across the entire study sample, prenatal exposure to GDM was associated with lower global and regional cortical gray matter volume (GMV) in the bilateral rostral middle frontal gyrus and superior temporal gyrus. GDM-exposed siblings also demonstrated lower global cortical GMV than unexposed siblings. Global cortical GMV partially mediated the associations between prenatal GDM exposure and child adiposity markers. CONCLUSIONS The results identify brain markers of prenatal GDM exposure and suggest that low cortical GMV may explain increased obesity risk for offspring prenatally exposed to GDM.
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Affiliation(s)
- Shan Luo
- Division of Endocrinology and Diabetes, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Department of Psychology, University of Southern California, Los Angeles, California, USA
- Center for Endocrinology, Diabetes and Metabolism, Children’s Hospital Los Angeles, Los Angeles, California, USA
| | - Eustace Hsu
- Division of Endocrinology and Diabetes, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Katherine E. Lawrence
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Shana Adise
- Center for Endocrinology, Diabetes and Metabolism, Children’s Hospital Los Angeles, Los Angeles, California, USA
- Division of Research on Children, Youth, and Families, Children’s Hospital Los Angeles, Los Angeles, California, USA
| | - Trevor A. Pickering
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Megan M. Herting
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Department of Pediatrics, Keck School of Medicine of University of Southern California, Los Angeles, California, USA
- Neuroscience Graduate Program, University of Southern California, Los Angeles, California, USA
| | - Thomas Buchanan
- Division of Endocrinology and Diabetes, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Kathleen A. Page
- Division of Endocrinology and Diabetes, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Diabetes and Obesity Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Neuroscience Graduate Program, University of Southern California, Los Angeles, California, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Neuroscience Graduate Program, University of Southern California, Los Angeles, California, USA
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Xu J, Zhang L, Wu Q, Zhou Y, Jin Z, Li Z, Zhu Y. Body roundness index is a superior indicator to associate with the cardio-metabolic risk: evidence from a cross-sectional study with 17,000 Eastern-China adults. BMC Cardiovasc Disord 2021; 21:97. [PMID: 33593274 PMCID: PMC7885560 DOI: 10.1186/s12872-021-01905-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 02/03/2021] [Indexed: 12/11/2022] Open
Abstract
Background To investigate the ability of body shape index (ABSI), body roundness index (BRI), waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body adiposity index (BAI) for predicting non-adipose cardio-metabolic risk. Methods A total of 17,360 Chinese subjects aged 18–95 years old who escaped cardiovascular disease (CVD) or diabetes were recruited in the cross-sectional study. Anthropometric and biochemical parameters were assessed. Receiver operating characteristic curve (ROC) and multinomial logistic regression were conducted to examine the association of anthropometric indicators with cardio-metabolic risk factors. Results The mean age of subjects were 53.7(13.1) years, 41.6 % were males. The areas under the curve (AUC) demonstrated that WC, BMI, WHR, WHtR and BRI were able to predict high cardio-metabolic risk (AUC > 0.70). Meanwhile, multinomial logistic regression showed BRI was significantly associated with high cardio-metabolic risk (OR 3.27, 95% CI 3.01–3.55). The optimal cut-off values of BRI for high cardio-metabolic risk were (< 60 y: 3.49 vs. ≥60 y: 3.46) in males and (< 60 y: 3.47 vs. ≥60 y: 3.60) in females. Conclusions WC, BMI WHR, and WHtR were potential obesity indicators in discriminating high cardio-metabolic risk, while BAI or ABSI was not. Moreover, BRI revealed superior predictive capacity and significant association with accumulated cardio-metabolic risk factors. Supplementary Information The online version contains supplementary material available at 10.1186/s12872-021-01905-x.
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Affiliation(s)
- Jinjian Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Liqun Zhang
- Putuo District People's Hospital, Zhoushan, 316100, Zhejiang, China
| | - Qiong Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Yaohan Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Ziqi Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Zhijian Li
- The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Yimin Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University, Hangzhou, 310058, Zhejiang, China. .,Department of Respiratory, Sir Run Run Shaw Hospital Affiliated to School of Medicine, Zhejiang University, Hangzhou, 310020, Zhejiang, China.
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A simple cut-off for waist-to-height ratio (0·5) can act as an indicator for cardiometabolic risk: recent data from adults in the Health Survey for England. Br J Nutr 2019; 123:681-690. [DOI: 10.1017/s0007114519003301] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
AbstractThe National Institute for Health and Care Excellence (NICE) has acknowledged the value of waist-to-height ratio (WHtR) as an indicator for ‘early health risk’. We used recent UK data to explore whether classification based on WHtR identifies more adults at cardiometabolic risk than the ‘matrix’ based on BMI and waist circumference, currently used for screening. Data from the Health Survey for England (4112 adults aged 18+ years) were used to identify cardiometabolic risk, indicated by raised glycated Hb, dyslipidaemia and hypertension. HbA1c, total/HDL-cholesterol and systolic blood pressure (BP) were more strongly associated with WHtR than the ‘matrix’. In logistic regression models for HbA1c ≥ 48 mmol/mol, total/HDL-cholesterol > 4 and hypertension (BP > 140/90 mmHg or on medication), WHtR had a higher predictive value than the ‘matrix’. AUC was significantly greater for WHtR than the ‘matrix’ for raised HbA1c and hypertension. Of adults with raised HbA1c, 15 % would be judged as ‘no increased risk’ using the ‘matrix’ in contrast to 3 % using WHtR < 0·5. For hypertension, comparative values were 23 and 9 %, and for total/HDL-cholesterol > 4, 26 and 13 %. Nearly one-third of the ‘no increased risk’ group in the ‘matrix’ had WHtR ≥ 0·5 and hence could be underdiagnosed for cardiometabolic risk. WHtR has the potential to be a better indicator of cardiometabolic risks associated with central obesity than the current NICE ‘matrix’. The cut-off WHtR 0·5 in early screening translates to a simple message, ‘your waist should be less than half your height’, that allows individuals to be aware of their health risks.
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