Journal of School of Public Health and

Misclassification of disease status and risk factors is one of the main sources of error in studies. Wrong assignment of individuals into exposed and non-exposed groups may seriously distort the results in case-control studies. This study investigates the effect of misclassification error on odds ratio estimates and attempts to introduce a correction method. Data on 3332 men aged 30-69 years from Tehran Lipid and Glucose Study (TLGS) were considered for investigating the relationship between angina pectoris and smoking. The “Rose” questionnaire was used to evaluate angina status. Two different definitions of smoking were included: I) active smokers versus non-smokers, II) active and ex-smokers versus never smoked. The relation between variables was assessed both with and without considering misclassification in smoking. Definition I (commonly used in many epidemiologic studies), resulted in a non-significant OR=1.09 (95% CI: 0.84, 1.41). Using the correction method based on the principle of non-differential misclassification, the OR increased to 1.13 (95% CI: 0.89, 1.43), which was still non-significant. However, a correction procedure that included the probability of differential misclassification produced a significant OR=1.46 (95% CI: 1.15, 1.85), p<0.05. It is evident that misclassification in risk factors can lead to inaccurate results. This study showed that the relation between variables may have not been discovered if the probability of misclassification was ignored. Moreover, in case of probable differential misclassification, applying correction methods for non-differential misclassification would be inefficient.

Background and Aim: Type 2 diabetes mellitus is a heterogeneous disorder resulting from a combination of genetic and environmental factors which contribute to pathogenesis by influencing beta cell function and tissue insulin sensitivity. Protein tyrosine phosphatase 1B (PTP1B)" efficiently dephosphorylates the insulin receptor and attenuates insulin signaling. Recently, a 1484insG variant of the PTP1B gene was linked to increased risk of the metabolic syndrome in an Italian population, but this was not confirmed in subsequent studies. The purpose of this research was to investigate the association of 1484insG polymorphism of the PTP1B with obesity, insulin resistance, type 2 diabetes and other cardiovascular-related traits in an Iranian population.

Materials and Methods: The genotypes of 1484insG variant were determined by the PCR-RFLP method in 242 unrelated subjects, including 171 individuals with normal glucose tolerance and normal fasting glucose levels, and 71 type 2 diabetics. Insulin resistance was assessed using the homeostasis assessment model.

Results: The allelic frequency of the 1484insG polymorphism among type 2 diabetic patients and non-diabetic individuals was 6.3% and 3.8%, respectively (p=0.205). None of the subjects were homozygous for the 1484insG allele. Concerning quantitative traits in non-diabetic subjects, carriers of 1484insG allele had significantly higher body mass index (p=0.01), diastolic blood pressure (p=0.012), and HOMA-IR (p= 0.041) levels compared to those carrying the wild-type genotype. In type 2 diabetics, carriers of 1484insG allele had only significantly higher HOMA-B (P= 0/04) level compared to the individuals with the wild-type genotype.

Conclusion: Our results from a sample of Iranian type 2 diabetes cases and controls provide evidence that the 1484insG genotype of the PTP1B gene may be associated with obesity and insulin resistance.