Bingyang Liu1, Yue Li2, Jiamei Guo1, Yuting Fan1, Ling Li1, Ping Li1. 1. Department of Endocrinology, Shengjing Hospital of China Medical University, Shenyang 110022, China. 2. Department of Endocrinology, Tianjin Third Central Hospital, Tianjin, China.
Abstract
AIMS: To investigate the influence of body mass index (BMI) and its change from adolescence to adulthood (ΔBMI) on the risk of metabolic syndrome (MetS) in early adulthood. METHODS: We selected 931 students from 12 to 16 years of age in Liaoyang City, China. Ninety-three participants from 18 to 22 years of age with complete baseline data were available for follow-up after 5 years. Statistical analysis determined the relationship of MetS at follow-up with baseline BMI (BMIb), ΔBMI, and follow-up BMI (BMIf). RESULTS: ΔBMI was positively correlated with the change of waist circumference (ΔWC), systolic blood pressure (ΔSBP), triglycerides (ΔTG), uric acid, and glycosylated hemoglobin (ΔHbA1c) in follow-up (p < 0.05). For every 1 kg/m2 increase in BMIb, ΔBMI, and BMIf, the risk of MetS at follow-up increased 1.201-fold, 1.406-fold, and 1.579-fold, respectively. Both BMIb and ΔBMI were predictive of MetS at follow-up, with prediction thresholds of 23.47 kg/m2 and 1.95 kg/m2. The participants were divided by the predicted BMIb and ΔBMI threshold values into four study groups. Interestingly, the group with lower BMI but a higher increase in BMI presented the same metabolic derangements and Mets% of the group with higher BMI but lower Δ BMI. CONCLUSION: Both BMI of adolescence and ΔBMI were predictive of MetS and cardiovascular risk factors in adulthood. Control of both variables in adolescents would be more effective in decreasing the risk of MetS in young adults than control of BMI alone.
AIMS: To investigate the influence of body mass index (BMI) and its change from adolescence to adulthood (ΔBMI) on the risk of metabolic syndrome (MetS) in early adulthood. METHODS: We selected 931 students from 12 to 16 years of age in Liaoyang City, China. Ninety-three participants from 18 to 22 years of age with complete baseline data were available for follow-up after 5 years. Statistical analysis determined the relationship of MetS at follow-up with baseline BMI (BMIb), ΔBMI, and follow-up BMI (BMIf). RESULTS: ΔBMI was positively correlated with the change of waist circumference (ΔWC), systolic blood pressure (ΔSBP), triglycerides (ΔTG), uric acid, and glycosylated hemoglobin (ΔHbA1c) in follow-up (p < 0.05). For every 1 kg/m2 increase in BMIb, ΔBMI, and BMIf, the risk of MetS at follow-up increased 1.201-fold, 1.406-fold, and 1.579-fold, respectively. Both BMIb and ΔBMI were predictive of MetS at follow-up, with prediction thresholds of 23.47 kg/m2 and 1.95 kg/m2. The participants were divided by the predicted BMIb and ΔBMI threshold values into four study groups. Interestingly, the group with lower BMI but a higher increase in BMI presented the same metabolic derangements and Mets% of the group with higher BMI but lower Δ BMI. CONCLUSION: Both BMI of adolescence and ΔBMI were predictive of MetS and cardiovascular risk factors in adulthood. Control of both variables in adolescents would be more effective in decreasing the risk of MetS in young adults than control of BMI alone.
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