Lujiao Li1, Jinhua Yin1, Hong Cheng1, Ying Wang1, Shan Gao1, Mingyao Li1, Struan F A Grant1, Changhong Li1, Jie Mi1, Ming Li1. 1. Department of Endocrinology (L.L., J.Y., Y.W., Ming.L.), Key Laboratory of Endocrinology, National Health and Family Planning Commission, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, People's Republic of China; Department of Epidemiology (H.C., J.M.), Capital Institute of Paediatrics, Beijing 10020, People's Republic of China; Department of Endocrinology (S.G.), Chaoyang Hospital, Capital Medical University, Beijing 100043, China; and Department of Biostatistics and Epidemiology (Mingy.L.), Division of Endocrinology (S.F.A.G., Ming.L.), The Children's Hospital of Philadelphia, Perelman School of Medicine, Division of Human Genetics, (S.F.A.G.), The Children's Hospital of Philadelphia Research Institute, Department of Pediatrics (S.F.A.G.), Perelman School of Medicine, University of Pennsylvania; Philadelphia, Pennsylvania 19104.
Abstract
CONTEXT: Available data related to the metabolically healthy obesity (MHO) phenotype are mainly derived from studies in adults because studies during childhood are very limited to date. OBJECTIVE: The objective of the study was to determine the prevalence of MHO in Chinese children and to investigate environmental and genetic factors impacting on MHO status. DESIGN: This was a cross-sectional study. PARTICIPANTS: A total of 1213 children with a body mass index at the 95th percentile or greater aged 6–18 years were included in this study. Participants were classified as MHO or of metabolically unhealthy obesity based on insulin resistance (IR) or cardiometabolic risk (CR) factors (blood pressure, lipids, and glucose). Twenty-two genetic variants previously reported from genome-wide association studies of obesity and diabetes plus the environmental factors of lifestyle, socioeconomic status, and birth weight was assessed. RESULTS: The prevalence of MHO-IR and MHO-CR were 27.1% and 37.2%, respectively. Waist circumference was an independent predictor of MHO, regardless of definitions, whereas walking to school and KCNQ1-rs2237897 were independent predictors of MHO-CR. Acanthosis nigricans, birth weight, the frequency of soft drink consumption, the mother's education status, and KCNQ1-rs2237892 were independent predictors of MHO-IR. Multiplicative interaction effects were found between KCNQ1-rs2237897 and walking to school on MHO-CR (odds ratio 1.31 [95% confidence interval 1.05–1.63]) and between rs2237892 and consumption of soft drinks on MHO-IR (odds ratio 0.80 [95% confidence interval 0.68–0.94]). CONCLUSIONS: Approximately one-third of Chinese obese children can be classified as MHO. Both genetic predisposition and environment factors and their interaction contribute to the prediction of MHO status. This study provides novel insights into the heterogeneity of obesity and has the potential to impact the optimization of the intervention options and regimens in the management of pediatric obesity.
CONTEXT: Available data related to the metabolically healthy obesity (MHO) phenotype are mainly derived from studies in adults because studies during childhood are very limited to date. OBJECTIVE: The objective of the study was to determine the prevalence of MHO in Chinese children and to investigate environmental and genetic factors impacting on MHO status. DESIGN: This was a cross-sectional study. PARTICIPANTS: A total of 1213 children with a body mass index at the 95th percentile or greater aged 6–18 years were included in this study. Participants were classified as MHO or of metabolically unhealthy obesity based on insulin resistance (IR) or cardiometabolic risk (CR) factors (blood pressure, lipids, and glucose). Twenty-two genetic variants previously reported from genome-wide association studies of obesity and diabetes plus the environmental factors of lifestyle, socioeconomic status, and birth weight was assessed. RESULTS: The prevalence of MHO-IR and MHO-CR were 27.1% and 37.2%, respectively. Waist circumference was an independent predictor of MHO, regardless of definitions, whereas walking to school and KCNQ1-rs2237897 were independent predictors of MHO-CR. Acanthosis nigricans, birth weight, the frequency of soft drink consumption, the mother's education status, and KCNQ1-rs2237892 were independent predictors of MHO-IR. Multiplicative interaction effects were found between KCNQ1-rs2237897 and walking to school on MHO-CR (odds ratio 1.31 [95% confidence interval 1.05–1.63]) and between rs2237892 and consumption of soft drinks on MHO-IR (odds ratio 0.80 [95% confidence interval 0.68–0.94]). CONCLUSIONS: Approximately one-third of Chinese obesechildren can be classified as MHO. Both genetic predisposition and environment factors and their interaction contribute to the prediction of MHO status. This study provides novel insights into the heterogeneity of obesity and has the potential to impact the optimization of the intervention options and regimens in the management of pediatric obesity.
Authors: Lujiao Li; Junling Fu; Xin Ting Yu; Ge Li; Lu Xu; Jinghua Yin; Hong Cheng; Dongqing Hou; Xiaoyuan Zhao; Shan Gao; Wenhui Li; Changhong Li; Struan F A Grant; Mingyao Li; Yi Xiao; Jie Mi; Ming Li Journal: Sleep Date: 2017-05-01 Impact factor: 5.849
Authors: Jieyu Liu; Tao Ma; Manman Chen; Ying Ma; Yanhui Li; Di Gao; Qi Ma; Xinxin Wang; Li Chen; Yi Zhang; Yanhui Dong; Yi Song; Jun Ma Journal: Front Endocrinol (Lausanne) Date: 2022-08-25 Impact factor: 6.055
Authors: Ge Li; Ling Zhong; Lanwen Han; Yonghui Wang; Bo Li; Dongmei Wang; Yanglu Zhao; Yu Li; Qian Zhang; Lu Qi; John R Speakman; Steven M Willi; Ming Li; Shan Gao Journal: Int J Obes (Lond) Date: 2021-10-29 Impact factor: 5.551
Authors: Johanna Gunnarsdottir; Sven Cnattingius; Maria Lundgren; Katarina Selling; Ulf Högberg; Anna-Karin Wikström Journal: PLoS One Date: 2018-02-13 Impact factor: 3.240
Authors: Junling Fu; Ge Li; Lujiao Li; Jinhua Yin; Hong Cheng; Lanwen Han; Qian Zhang; Naishi Li; Xinhua Xiao; Struan F A Grant; Mingyao Li; Shan Gao; Jie Mi; Ming Li Journal: Oncotarget Date: 2017-08-24
Authors: Ge Li; Issy C Esangbedo; Lu Xu; Junling Fu; Lujiao Li; Dan Feng; Lanwen Han; Xinhua Xiao; Mingyao Li; Jie Mi; Ming Li; Shan Gao; Steven M Willi Journal: Cardiovasc Diabetol Date: 2018-05-14 Impact factor: 8.949