Details

Autor(en) / Beteiligte

• Chang, Chi-Jen
• Jian, Deng-Yuan
• Lin, Ming-Wei
• Zhao, Jun-Zhi
• Ho, Low-Tone
• Juan, Chi-Chang
• Peterson, Jonathan

Titel

Evidence in obese children: contribution of hyperlipidemia, obesity-inflammation, and insulin sensitivity

Ist Teil von

• PloS one, 2015-05, Vol.10 (5), p.e0125935-e0125935

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2015

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Evidence shows a high incidence of insulin resistance, inflammation and dyslipidemia in adult obesity. The aim of this study was to assess the relevance of inflammatory markers, circulating lipids, and insulin sensitivity in overweight/obese children. We enrolled 45 male children (aged 6 to 13 years, lean control = 16, obese = 19, overweight = 10) in this study. The plasma total cholesterol, HDL cholesterol, triglyceride, glucose and insulin levels, the circulating levels of inflammatory factors, such as TNF-α, IL-6, and MCP-1, and the high-sensitive CRP level were determined using quantitative colorimetric sandwich ELISA kits. Compared with the lean control subjects, the obese subjects had obvious insulin resistance, abnormal lipid profiles, and low-grade inflammation. The overweight subjects only exhibited significant insulin resistance and low-grade inflammation. Both TNF-α and leptin levels were higher in the overweight/obese subjects. A concurrent correlation analysis showed that body mass index (BMI) percentile and fasting insulin were positively correlated with insulin resistance, lipid profiles, and inflammatory markers but negatively correlated with adiponectin. A factor analysis identified three domains that explained 74.08% of the total variance among the obese children (factor 1: lipid, 46.05%; factor 2: obesity-inflammation, 15.38%; factor 3: insulin sensitivity domains, 12.65%). Our findings suggest that lipid, obesity-inflammation, and insulin sensitivity domains predominantly exist among obese children. These factors might be applied to predict the outcomes of cardiovascular diseases in the future.