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Objective: To investigate the association between long-term fasting blood glucose (FPG) variability and all-cause mortality in patients with type 2 diabetes. Methods: A total of 7 174 type 2 diabetic patients included in National Basic Public Health Service Program in Changshu of Jiangsu Province were recruited as participants. Long-term glucose variability was assessed using standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) across FPG measurements at the more than three visits. Death information were mainly obtained from the death registry system in Jiangsu. Then Cox proportional hazards regression models were used to estimate the associations of four variability indicators and all-cause mortality's hazard ratios (HRs) and their 95%CIs. Results: Among 55 058.50 person-years of the follow-up, the mean follow-up time was 7.67 years, and 898 deaths occurred during the follow-up period. After adjustment, compared with T1 group, the Cox regression model showed that HRs of T3 group in SD, CV, ARV and VIM were 1.24 (95%CI: 1.03-1.49), 1.20 (95%CI: 1.01-1.43), 1.28 (95%CI: 1.07-1.55) and 1.20 (95%CI:1.01-1.41), respectively. HRs of per 1 SD higher SD, CV, ARV and VIM were 1.13 (95%CI: 1.06-1.21), 1.08 (95%CI: 1.01-1.15), 1.05 (95%CI: 1.00-1.12) and 1.09 (95%CI: 1.02-1.16) for all-cause mortality, respectively. In the stratified analysis, age, gender, hypoglycemic agent and insulin uses had no effect on the above associations (all P for interaction >0.05). Conclusion: Long-term FPG glycemic variability was positively associated with the risk of all-cause mortality in type 2 diabetes patients.
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Objective: To investigate the distribution of blood pressure and analyze the associated factors of blood pressure of the elderly with type 2 diabetes in Jiangsu Province. Methods: The elderly over 60 years old participants with type 2 diabetes in the communities of Huai'an City and Changshu City, Jiangsu Province were selected in this study. They were divided into two groups: taking antihypertensive drugs and not taking antihypertensive drugs. The demographic characteristics, such as age and sex, and relevant factors were collected by questionnaire. The systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by physical examination. The percentile of SBP and DBP in each age group of men and women were described. The kernel density estimation curve was used to show the blood pressure distribution. The trend of blood pressure with age was fitted by locally weighted regression. The logistic regression model was used to analyze relevant factors of blood pressure. Results: A total of 12 949 participants were included in this study, including 7 775 patients in the antihypertensive drug group and 5 174 patients in the group without antihypertensive drugs. The SBP of participants was concentrated at 140-160 mmHg, and their DBP was concentrated at 75-85 mmHg. There were significant differences in the distribution of blood pressure among the subgroups of body mass index (BMI) and rural areas whether taking antihypertensive drugs and not. For participants aged under 80 years old, the SBP showed an increasing trend with age and the DBP showed a decreasing trend with age. Age, BMI ≥24 kg/m2, fasting blood glucose ≥7.0 mmol/L, living in rural areas and no smoking were influencing factors of the elevated SBP; BMI ≥24 kg/m2, male, living in rural areas, no smoking, drinking alcohol and not receiving drug hypoglycemic treatment were influencing factors of the elevated DBP. Conclusion: The SBP of older diabetic adults in Jiangsu Province is at a high level, and the distribution of blood pressure is significantly different between men and women in taking antihypertensive drugs group. The SBP presents a rising trend and the DBP is decreasing at the age of 60-80 years. The blood pressure level of this population are mainly affected by age, BMI, urban and rural areas, smoking.
Subject(s)
Adult , Aged , Humans , Male , Female , Middle Aged , Aged, 80 and over , Blood Pressure/physiology , Diabetes Mellitus, Type 2/epidemiology , Antihypertensive Agents/therapeutic use , Smoking , Body Mass Index , Hypertension/epidemiologyABSTRACT
Objective To explore the effect of smoking on blood glucose level among male patients with type 2 diabetes in Changshu City.Methods Totally 41 57 male patients with type 2 diabetes involved in the national basic public health service were selected and assigned into four groups,including heavy smokers,current mild smokers,former smokers and non -smokers.All of them were investigated about the general social demographic data,living habits and health condition.Height,weight,waist and hipline were measured.BMI and WHR were calculated.FPG and HbA1 c were checked.Covariance analysis was used to correct the confounding factors,and the methods of multiple linear regression and partial correlation were used to evaluate the relationship between smoking and blood glucose level.Results FPG of the heavy smokers was higher than the current mild smokers,former smokers and non -smokers(P <0.05),but after the correction of the confounding factors,the differences were not statistically significant(P >0.05).HbA1 c of the heavy smokers and current mild smokers were higher than the former smokers and non -smokers(P <0.05 ),and after the correction of the confounding factors,the differences were still statistically significant(all P <0.05).Daily smoking amount was one of the influencing factors of HbA1 c(β=0.07,P <0.05).There was no correlation between the age of smoking initiation and FPG,HbA1 c(P >0.05).Daily smoking amount was positively correlated with HbA1 c(r =0.06,P <0.05), but was not correlated with FPG(P >0.05).Conclusion Smoking has a certain degree of influence on blood glucose level among male patients with type 2 diabetes in Changshu City,and we need to reduce the smoking rate among male patients with type 2 diabetes by health education.
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Objective To explore the roles of peroxisome proliferator-activated receptors (PPARs) on the levels of serum C-reactive protein (CRP) and the interactions of PPARs haplotypes with abnormal body weight.Methods Subjects (n=644) were randomly selected from the cohort ‘Prevention of Multiple metabolic disorders and Metabolic syndrome in Jiangsu province (PMMJS)'Variance test,t test and lineal regression were used to analyze the associations between PPARs polymorphisms and the levels of CRP.The association between PPARs haplotypes and serum CRP levels as well as the interaction of PPARs haplotypes with abnormal body weight were analyzed,under the SNPStats software.Results After adjusting for sex,age,blood pressure,cigarette smoking,alcohol drinking and so on,data showed that both rs1800206 and rs9794 were associated with the changes along with the levels of CRP (P＜0.05).After adjusting for the same factors,haplotypes of AVG and CVG in PPARα,CG in PPARδ appeared to be associated with the increase (P＜0.05) while haplotypes of CC in PPARδ,CPCAC in PPARγ were associated with the decrease of CRP levels (P＜0.05).Results from the Interaction analysis also noted that the interactions did exist between abnormal body weight and both AVG,CVG in PPARαt,and CG in PPARδ.Conclusion PPARs polymorphisms and haplotypes were associated with CRP.Interaction between PPAR α/δand abnormal body weight might contribute to the levels of CRP.
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<p><b>OBJECTIVE</b>To investigate the association of ten SNP at peroxisome proliferator-activated receptors (PPARα, δ, γ) with hypertriglyceridemia and the gene-gene interaction.</p><p><b>METHODS</b>Participants were recruited from the Prevention of MetS and Multi-metabolic Disorders in Jiangsu province of China Study (PMMJS). A total of 820 subjects were selected from the 4083 participants who had received follow-up examination, by using simple random sampling. Participants in baseline and follow-up study surveys were both collected blood samples 11 ml in the morning after at least 8 hours of fasting. Blood samples which collected at the baseline were subjected to PPARα, PPARδ and PPARγ genotype analyses. Blood samples which collected at the follow-up were used to measure serum triglyceride levels. The logistic regression model was used to analyze the association between different SNP and hypertriglyceridemia, and the generalized multifactor dimensionality reduction (GMDR) was applied to explore the gene-gene interaction.</p><p><b>RESULTS</b>The samples included 474 in the non-hypertriglyceridemia group and 346 in the hypertriglyceridemia group. The genotype frequencies of rs1800206 in the hypertriglyceridemia group were 211 (61.0%) for LL, 132 (38.2%) for LV and 3 (0.9%) for VV, and in the non-hypertriglyceridemia group were 411 (86.7%) for LL, 59 (12.4%) for LV and 4(0.8%) for VV (χ(2) = 74.18, P < 0.01). V allele frequencies of rs1800206 in the hypertriglyceridemia group was 138(19.9%), and in the non-hypertriglyceridemia group was 67 (7.1%) (χ(2) = 60.62, P < 0.01). The genotype frequencies of rs2016520 in the hypertriglyceridemia group were 177 (51.2%) for TT, 154 (44.5%) for TC and 15 (4.3%) for CC, and in the non-hypertriglyceridemia group were 211 (44.5%) for TT, 212 (44.7%) for TC and 51 (10.8%) for CC(χ(2) = 15.93, P < 0.01). C allele frequencies of rs2016520 in the hypertriglyceridemia group was 184(26.6%), and in the non-hypertriglyceridemia group was 314 (33.1%) (χ(2) = 8.07, P < 0.01). The genotype frequencies of rs3856806 in the hypertriglyceridemia group were 149 (43.1%) for CC, 156 (45.1%) for CT and 41 (11.8%) for TT, and in the non-hypertriglyceridemia group were 269 (56.8%) for CC, 170 (35.9%) for CT and 35 (7.4%) for TT (χ(2) = 15.93, P < 0.01). T allele frequencies of rs3856806 in the hypertriglyceridemia group was 238(34.4%), and was 240 (25.3%) in the non-hypertriglyceridemia group (χ(2) = 15.96, P < 0.01). The genotype frequencies of rs1805192 in the hypertriglyceridemia group were 145 (41.9%) for PP, 158(45.7%) for PA and 43(12.4%) for AA, and in the non-hypertriglyceridemia group were 314 (66.2%) for PP, 137(28.9%) for PA and 23(4.9%) for AA (χ(2) = 50.92, P < 0.01). A allele frequencies of rs1805192 in the hypertriglyceridemia group was 244(35.2%), and was 183 (19.3%) in the non-hypertriglyceridemia group(χ(2) = 52.89, P < 0.01). After adjusting age, gender, smoking, alcohol consumption, high-fat diet, low -fiber diet and occupational physical activity factors, rs1800206, rs2016520, rs3856806 and rs1805192 were significantly associated with hypertriglyceride, while the OR (95%CI) was 3.88 (2.69 - 5.60), 0.71 (0.52 - 0.96), 1.40 (1.03 - 1.90) and 2.56 (1.88 - 3.49), respectively (P < 0.05). GMDR model analysis showed that the second-order model (rs1800206 and rs1805192) was the best model when quality traits of triglyceride was chosen as outcome (P < 0.01); while third-order model (rs1800206, rs1805192 and rs2016520) was the best model when quantitative traits of triglyceride was chosen as outcome (P < 0.01).</p><p><b>CONCLUSION</b>The rs1800206, rs2016520, rs3856806 and rs1805192 were significantly associated with hypertriglyceridemia. There was a gene-gene interaction between multiple SNP.</p>
Subject(s)
Adult , Female , Humans , Male , Middle Aged , China , Gene Frequency , Genotype , Hypertriglyceridemia , Blood , Genetics , Logistic Models , Peroxisome Proliferator-Activated Receptors , Genetics , Polymorphism, Single NucleotideABSTRACT
Objective To investigate the association between ten single nucleotide polymorphism (SNP) in the peroxisome proliferator-aetivated receptor (PPAR) α/δ/γ and essential hypertension (EH).Methods Participants were recruited within the framework of a cohort populations survey from the PMMJS (Prevention of Multiple Metabolic Disorders and MS in Jiangsu Province) which was conducted in the urban community of Jiangsu province from 1999 to 2007.Eight handred and twenty subjects (551 non-hypertensive subjects,269 hypertensive subjects) were randomly selected but were not related to each other.Ten SN P ( rs 135539,rs1800206,rs4253778 of PPAR αt; rs2016520,rs9794 of PPARδ ; rs10865710,rs1805192,rs4684847,rs709158 and rs3856806 of PPARγ ) were selected from the HapMap database.x2 test was used to determine whether the whole population was in H-W genetic equilibrium.SHEsis software was used to examine the relations of SNP and linkage equilibrium.Logistic regression model was used to examine the association between ten SNP in the PPAR and EH.Results Difference on the distribution of four SNP genotypes including rs1800206,rs9794,rsl0865710 and rs4684847 between high blood pressure and non-high blood pressure group,high systolic blood pressure(SBP) and normal SBP group,high diastolic blood pressure(DBP) and normal DBP group was significant (P＜0.05).After adjusting factors as age,sex,body mass index,fasting plasma glucose,high density lipoprotein cholesterol-C,high-fat diet and compared with wildtype gene carriers,the OR(95％ CI) of objects with rs1800206 V allele appeared in high blood pressure,high SBP and high DBP were 0.60 (0A1-0.89),0.57 (0.37-0.88) and 0.61 (0.39-0.96),respectively.The OR(95％CI) of objects with G allele of rs9794 were 0.63 (0.46-0.87),0.51 (0.36-0.73) and 0.68(0.47-1.01).The OR (95％CI) of objects with G allele of rs10865710 were 1.62 (1.19-2.20),1.59(1.14-2.22) and 1.53 ( 1.07-2.18),respectively.While the OR (95％ CI) of objects with rs4684847 T allele were 1.42 ( 1.04-1.94),1.38 (1.03-1.92) and 1.37 ( 1.00-1.88),respectively.Conclusion The four SNPs including rs1800206 of PPARα,rs9794 of PPARδ and rs4684847,rs10865710 of PPARγ influenced high blood pressure,high SBP and high DBP to different degrees.
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Objective To investigate the association of ten single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptors (α,δ,γ) with low high-density lipoproteincholesterol (HDL-C) hyperlipidemia and the additional role of a gene-gene interactions among the 10 SNPs.Methods Participants were recruited under the framework of the PMMJS (Prevention of Multiple Metabolic Disorders and MS in Jiangsu Province) cohort populations survey,in the urban community of Jiangsu province,China.820 subjects (579 normal HDL-C,241 low HDL-C) were randomly selected,with one of them related to each other.Ten SNPs (rs135539,rs4253778,rs1800206,rs2016520,rs9794,rs10865710,rs1805192,rs709158,rs3856806,rs4684847) were selected from the HapMap database,which covered PPARα,PPARδ and PPARγ.Logistic regression model was used to examine the association between ten SNPs in the PPARs and low HDL-C.Odds ratios (OR) and 95％ confident interval (95％CI) were calculated.Interactions were explored by using the method of Generalized Multifactor Dimensionality Reduction (GMDR).Results After adjusting the factors as age,sex,smoking status,occupational physical activity,high-fat diet as well as low-fiber diet,both rs 135539 and rs1800206 were significantly associated with the incidence of low HDL-C,with the OR (95％ CI) values as 1.46 (1.07-1.99) and 0.62 (0.42-0.90).No statistically significant difference was found between other SNPs and the occurrence of low HDL-C.Data from GMDR analysis showed significant gene-gene interaction among rs135539,rs4253778 of PPAR α and rs10865710,rs3856806,rs709158 and rs4684847 of PPARγ (P＝0.0107).Conclusion PPARα rs135539 was associated with the occurrence of low HDL-C,and had interacted with rs4253778,rs10865710,rs3856806,rs709158 and rs4684847.