ABSTRACT
Objective To study the effect of smoking on resting energy expenditure ( REE ) and the relationships among REE, smoking , inflammation and oxidative stress in patients with diabetic kidney disease. Methods A case control study of 31 smokers and 40 non-smokers with early stage of diabetic kidney disease( stage Ⅲ ) were performed to evaluate the chronic effect of smoking on REE. REE/fat free mass( FFM ), biomarkers of oxidative stress malondialdehyde ( MDA ), superoxide dismutase ( SOD ) and inflammation high-sensitivity C-reactive protein (hs-CRP), adiponectin, TNFα were also measured in these subjects. Data were analyzed by Pearson correlation analysis. Results Compared with non-smokers, REE/FFM in smokers group was significantly increased by 15.96% ( P =0.001 ). Pearson analysis showed that smoking was significantly correlated with REE/FFM ( t = 0.395, P = 0.001 ). There were significantly different between smokers and non-smokers in MDA, SOD and hs-CRP ( P＜0.05 ). But no difference between two groups in adiponectin and TNFα ( P ＞ 0.05 ). No significant relationships between REE/FFM and MDA, SOD, hs-CRP, adiponectin, TNFα was found ( P ＞ 0.05 ). Conclusion Chronic smoking can lead to increased REE, arouse oxidative stress and inflammatory in patients with early stage of diabetic kidney disease. However, there is no relationship between increased REE due to smoking and oxidative stress and inflammatory.
ABSTRACT
Objective To investigate the features of resting energy expenditure (REE) in patients with well controlled type 2 diabetes mellitus (T2DM). Methods Totally 45 T2DM patients with stable blood glucose were enrolled. The general conditions, biochemical indicators, measurements of REE ( MREE), and basal energy expenditure (BEE) calculated with Harris-Benedict formula (HBEE) and Owen formula (OBEE) were recorded and compared. Results MREE had no significant difference with HBEE or OBEE in T2DM patients with stable blood glucose (P ＞ 0. 05). Correlation analysis showed that REE was significantly correlated with gender, age, body weight, body height, body surface area, and fat-free mass ( all P ＜ 0.05 ), but was not correlated with body mass index, fat mass, fasting plasma glucose, postprandial plasma glucose, haemoglobin Alc, total cholesterol, triglyceride, total protein, albumin, and haemoglobin (P ＞ 0. 05 ). Multiple regression analysis showed that fat free mass and age had the closest correlation with REE. Conclusions REE does not increase in T2DM patients with well controlled blood glucose. Factors that influence their REE are similar with healthy individuals. Determi nation of REE can provide useful information for the nutrition treatment of T2DM.