ABSTRACT
Background and objective : There were many articles determined factors associated with microalbuminuria in type 2 diabetes. Some articles reported the same result, some articles reported difference. It was confusing which is to apply for prevention and health promotion in public health and clinical practice. The aim of this study was to determine factors associated with microalbuminuria in type 2 diabetes by meta-analysis.Methods : We performed our search using Ovid MEDLINE, Scopus, BMJ Clinical Evidence, ProQuest, Thai index medicus and Thai Medical index. The study design\ was an analytical cross sectional study and detection of microalbuminuria by quantitative technique, published during 1992 -2009. Criteria of quality assessment for publication composed of microalbuminuria classification and urine collection method. Heterogeneity assessment for the studies\’ results was the use of Cochran\’s 2.Results : Of 2,428 identified articles on electronic database, 17 articles were included for the analysis because of selection criteria and quality assessment criteria. The data was extracted and converted to be a standard measurement unit. Pooled effect estimates were obtained by using fixed effect and random effect meta-analysis. This study found that age, duration of diabetes, smoking, high blood pressure, high blood plasma glucose and dyslipidemia were the risk factors associated with microalbuminuria. But there is only HDL that expresses the protective factor of microalbuminuria (OR = 0.850, 95% CI = 0.748-0.966), p-value = 0.013).\ \ \ \ \ Conclusion : The health promotion program to prevent microalbuminuria in type 2 diabetes should be considered the behavioral optimization programming such as stop smoking programs, blood pressure control, blood glucose control and nutrition education.Keywords : microalbuminuria , diabetes, meta analysis
ABSTRACT
Abstract How to Detect and Handle Confounding Factors Sirima Mongkolsomlit BSc, MSc Epidemiology* Jayanton Patumanond MD, DTM\&H, MSc Clin Trop Med, DSc Clinical Epidemiology** Petch Rawdaree MD, MSc Epidemiology, DLSHTM*** * Faculty of Public Health, Thammasart University. ** Faculty of Medicine, Chiangmai University. *** Department of Medicine, BMA Medical College and Vajira Hospital. When a researcher investigates the association between an exposure of factors and an occurrence of outcome, there are other influencing factors to the test result so called "confounding factors". Confounding factors may cause indistinct or inaccurate results of the study. Since statistical analysis cannot clear out the effect of confounders which have not been collected or being unidentified, it is crucial for the researcher to identify and control the impact of these confounding factors. In order to collect all essential data including any potential confounding factors, a thorough literature review prior to conducting a research is the first and important step. If confounders are identified, there are many approaches to deal with confounders: by randomization, restriction, or matching in the research design or methodology process; or by stratification or multivariable analysis in the statistical analysis process. Keywords: confounding factors, randomization, restriction, matching, stratification Vajira Med J 2010 ; 54 : 223-235