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1.
Zhonghua Yu Fang Yi Xue Za Zhi ; (12): 512-516, 2014.
Article in Chinese | WPRIM | ID: wpr-298893

ABSTRACT

<p><b>OBJECTIVE</b>Based on the characteristics of hierarchical data, a multilevel model was used to analysis possible influencing factors of urinary cadmium levels in one county population, and to discuss the advantages of multilevel model for processing hierarchical data in practical problems.</p><p><b>METHODS</b>In May 2013, 1 460 participants aged 20 and above in 12 administrative villages in one county in central China were recruited by cluster sampling. Urinary cadmium level and its possible influencing factors were investigated, and cadmium level in farmland soil of survey area was also tested. A total of 1 410 participants completed the survey and met the inclusion criterion. 318 farmland samples in survey area were detected. According to the data, individuals were set as the level one unit, and the village was set as level two unit. the data were analyzed by MIXED procedure for hierarchical data of SAS 9.3 software. In the case of not considering the hierarchy of data, the general linear model was fitted by SAS 9.3 software, and the fitting results of the two models were compared.</p><p><b>RESULTS</b>A total of 1 410 participants were included finally, the age was (55.2 ± 11.1) years. 645 (45.74%) were males and 765 (54.26%) were females. The amount of household per capita consumption of rice was (100.9 ± 40.3) kg/y. All 18.65% (262/1 410) of the participants had mining and mineral separation work experience. The urinary cadmium level was (9.39 ± 2.16) µg/g Cr. Most of the soil cadmium levels in villages were greater than tolerance value. The fitting results of general linear model suggested that whether doing mining and mineral separation work does not have significant difference (χ(2) = 1.05, P = 0.305). There was significant difference in the village soil cadmium levels, age, the amount of household per capita consumption of rice, and gender (χ(2) = 401.39, 34.9, 4.16 and 86.15, respectively, P < 0.01, <0.01, 0.041, <0.01, respectively). The fitting result of empty model showed the ICC was 0.435 5, the urinary cadmium had clustering at village level. The results of multilevel model showed that the explanatory variables of the village soil cadmium levels, age, the amount of household per capita consumption of rice and gender had significant difference (Wald χ(2) values 2.55, 6.34, 2.37 and 10.32, respectively, P = 0.029, <0.01, = 0.018 and <0.01), while whether doing mining and mineral separation work had no significant difference (χ(2) = 0.78, P = 0.438). To the fitting optimization index using for the comparison of models, the results of multilevel model were less than that of general linear model. The regression coefficient of level-2 explanatory variable (the village soil cadmium levels) was 0.84, which could explain the 35.26% of the total variance.</p><p><b>CONCLUSION</b>Multilevel model could analyze hierarchical data more reasonably than general linear model. Urinary cadmium levels is highly influenced by the village soil cadmium levels.</p>


Subject(s)
Adult , Aged , Female , Humans , Male , Middle Aged , Agriculture , Cadmium , China , Diet , Environmental Exposure , Environmental Pollution , Mining , Models, Theoretical , Oryza , Risk Factors , Soil
2.
Chinese Journal of Epidemiology ; (12): 269-272, 2002.
Article in Chinese | WPRIM | ID: wpr-244292

ABSTRACT

<p><b>OBJECTIVE</b>To estimate the current knowledge on hypertension and the effect of management on hypertension in patients attending hospital clinics.</p><p><b>METHODS</b>A cross-sectional survey was used in the outpatients over the age of 35 years in 18 general hospitals (provincial, district and community) which represented the different levels of medical care in 8 major cities covering Northern and Southern China including an interview with two blood pressure measurements and one questionnaire in one clinical visit.</p><p><b>RESULTS</b>A total of 9 703 subjects participated in this project, who were similarly distributed by gender and age in the hospitals at different levels. Of all the 9 703 subjects, 4 510 (46.5%) were found to be hypertensive. 6.4%, 12.1%, 25.5%, 41.1% and 14.6% of all the participants were categorized into knowledge on hypertension grade 0, 1, 2, 3, 4 respectively. The classification was based on the number of correct answers to four questions about knowledge of hypertension. The higher the grade of hypertension knowledge the more response to higher rate of awareness, treatment, and control in this hypertensive population was noticed. There was significantly positive correlation between the grade of hypertension knowledge and treatment compliance. The major cause of poor treatment compliance was due to lack of hypertension knowledge.</p><p><b>CONCLUSION</b>There was poor knowledge on hypertension in the investigated participants, which would influence on the management of hypertension. Data suggested that health education on the knowledge of hypertension in the population needs to be improved.</p>


Subject(s)
Adult , Female , Humans , Male , China , Epidemiology , Cross-Sectional Studies , Health Education , Hypertension , Epidemiology , Outpatients , Patient Education as Topic
3.
Article in Chinese | WPRIM | ID: wpr-244310

ABSTRACT

<p><b>OBJECTIVE</b>Discussion on utility and purposed value of obesity and abdomen obesity when body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) used as indexes predicting hypertension, hyper-blood glucose, and both clusters, to provide scientific basis for the decision on the indexes and their cut-off points of obesity and abdomen obesity in Chinese people.</p><p><b>METHODS</b>Using the data of diabetes mellitus (DM) from epidemiological studies carried out in 11 provinces/autonomous regions/municipalities of China from July 1995 to June 1997. Partial relative analysis, logistic multi-factors regression analysis, interaction analysis were used. Relative risk (RR), attributable risk proportion (ARP) and population attributable risk proportion (PARP) of hypertension, hyper-blood glucose, and the both cluster as BMI, WC, WHR with the different cut off points were analysed.</p><p><b>RESULTS</b>1) The correlations between BMI, WC and blood pressure, blood glucose were better than the WHR. 2) After adjusted by age, sex, occupation leisure physical activity, education degree and the family history of DM, the results suggested that BMI, WC, WHR were important predictive factors, with relative importance as BMI > WC > WHR. 3) There were augment interactions on BMI, WC and WHR with hypertension, hyper-blood glucose, with the interaction of BMI and WC in particular. Their pure attributable interaction proportion were from 5.95% to 29.34%. 4) The values of RR were about 2.5 when BMI >/= 23, >/= 24 and >/= 25, suggesting the relationship with exposure factors and diseases were with medium and high maleficent extent. Their ARP were from 0.580 to 0.623 with PARP from 0.259 to 0.425. The values of RR were from 2.06 to 3.08 as WC >/= 85 cm in males, WC >/= 80 cm in females while WC >/= 90 cm in males, WC >/= 80 cm in females, which suggested that the relationship with exposure factors and diseases were in medium and high maleficent extent. Their ARP were from 0.515 to 0.676 while PARP from 0.241 to 0.431.</p><p><b>CONCLUSIONS</b>Since the maleficent extent of exposure factors to diseases, the acceptability for overweight and obesity in population, and the prevention and care for overweight and obesity were just in the introduction stage in China. The utility value of predicted hypertension, hyper-blood glucose in BMI and WC seemed to be better then in WHR. We suggested that BMI used as the obesity index, with the diagnostic cut-off point BMI >/= 24. WC as the abdomen obesity index. The diagnostic cut-off points are suggested to be WC >/= 85 cm in males, and WC >/= 80 cm in females.</p>


Subject(s)
Adult , Aged , Female , Humans , Male , Middle Aged , Blood Glucose , Metabolism , Blood Pressure , Physiology , Body Constitution , Body Mass Index , Diastole , Hyperglycemia , Diagnosis , Hypertension , Diagnosis , Logistic Models , Obesity , Predictive Value of Tests , Systole
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