Journal of School of Public Health and

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Background and Aim: Breast cancer is the leading cause of cancer death among women, both in Iran and worldwide. The wide variation in breast cancer incidence in different geographical areas calls for studies to clarify the role of potential risk factors. In this study we looked at some factors that could be involved in the pathogenesis of breast cancer.
Material and Methods: This matched case-control study was carried out in the summer of 2004, and it drew on data recorded in Babol (Caspian) Cancer Registry. We investigated 250 biopsy-proven cases of breast cancer, together with 500 controls chosen from the neighbors of cases. We matched the subjects with regard to age (with 3 years intervals). Crude and adjusted odds ratios and relevant 95% confidence intervals were calculated through conditional logistic regression, using STATA 8.0.
Results: This study involved 250 incident cases of breast cancer and 500 age-matched controls. The mean age of the cases was 48.7 (±11.37) years with 48, 22 and 80 years as median, min. and max. values, respectively. Mean age in the controls was 48.0 (±11.46) years with 47.5, 19 and 77 years as median, min. and max. values, respectively. In the multivariate analysis, the following variables were found to be risk factors: university education (OR=5.89, 95%CI: 1.73-20.09), menopause (OR=3.98, 95%CI: 2.29-6.91), induced abortion (OR=1.56, 95%CI: 1.02-2.22), BMI (OR=1.02, 95%CI: 1.01-1.03) and longer duration of breast feeding was determined as protective factor against breast cancer (OR=0.995, 95%CI: 0.990-0.999).
Conclusion: Modifiable risk factors should be considered in the community-based preventive interventions. The following areas could serve as topics for community education in Mazandaran: the role of high BMI and induced abortion in increasing the chance of breast cancer and also the protective role of breast feeding on this issue.

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Background and Aim: Limitations of the traditional methods for assessing G*E interaction- including case-control studies- led to development of several non-traditional approaches. This study aims to assess the interaction between the genetic background (history of breast cancer in first degree relatives) and environmental influences (reproductive/menstrual factors) in patients with breast cancer we also compare the statistical efficiency and power of case-control and case-only designs in this setting.
Materials and Methods: In a matched case-control study in Mazandaran province (Iran), 250 incident biopsy-proven cases of breast cancer and 250 age-matched neighbor controls were interviewed. History of breast cancer in mother and/or sister(s) was taken as a surrogate measure of genetic predisposition, while age at first birth, parity, breast feeding, age at menarche and irregular menstruation were considered as relevant environmental factors. For the matched case-control design, we used a conditional logistic regression model to examine main effects and the G*E interaction. In the case-only design, logistic regression analysis was applied to obtain an estimate of G*E interaction, after checking for the independence assumption. We also calculated the power for detecting the interaction by matched case-control and case-only analyses.
Results: Age at first delivery did not meet the assumption of independence (p=0.02), and so was not included in the case-only analysis. No statistically significant interaction effect was seen in the case-control analysis, while case-only analysis showed significant negative interaction between disease in first-degree relatives on the one hand and parity and breast feeding on the other. We also detected a significant positive interaction between genetic predisposition and age at menarche. All the estimated 95% confidence intervals for OR in G*E interactions were narrower in the case-only analysis. For all factors, the power for detecting G*E interaction was greater in the case-only analysis compared to the case-control analysis, with ratios ranging from 1.08 to 2.23.
Conclusion: The case-only design is more efficient and powerful than the case-control design for detecting gene-environment interaction under the assumption of independence. Baseline disease risk, interactions and independent effects should be considered in using the control data for checking the assumption of independence. Considering the existence of another explanatory variable, eg. a mutant gene which may have passed unnoticed, would be the safest approach in a case-only study.

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Background and Aim: Previous studies show that disability and mortality due to cardiovascular diseases are closely related to socioeconomic status in a community. The objective of this study was to determine the relationships between socioeconomic factors and coronary artery disease (CAD) among people under 45 years old at Shahid Rajaei Hospital, Tehran, Iran.

Materials and Methods: This case-control study was conducted in Shahid Rajaei Hospital, Tehran, Iran in summer 2008. The participants were 100 CAD cases (<45 years old, mean age = 41.2 years 85% men) and 100 controls from among accompanying persons matched for age and gender. In order to assess the risk of factors related to such variables as educational level, occupation, income, social exclusion, social support, stress, exercise, nutritional status, smoking, etc, odds ratio (95% CI) was used. Multinomial logistic regression was used to assess the synchronic effect of the risk factors, and the t-test was used to find differences between means.

Results: The odds ratio (95% CI) for smoking vs nonsmoking was 3.9 (1.9-7.9) for CAD. Individuals with a low educational level showed an odds ratio of 2.7 (1.9-7-9), compared to those with a high educational level. Eating fruits and vegetables at least seven servings a week has an odds ratio of 2.7 (1.01-7.4) vs eating fewer servings. Occupation, job grade and physical activity had statistically significant relationships with CAD. Mean BMI was different between cases and controls. The disease had no significant association with stress, social support, social exclusion or income.

Conclusion: Smoking, a low educational level and eating small amounts of fruits and vegetables were the most important socioeconomic factors contributing to coronary artery disease. Policymaking and planning aiming at improving the socioeconomic situation of the people, particularly those under 45 years old, seem essential.

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Background and objectives: Relapse after treatment is a common problem among drug addicts in addiction control and prevention programs. About 80% of the addicts relapse into drug abuse within 6 months after treatment. The purpose of this study was to determine factors associated with drug abuse relapse in patients consulting two selected addiction treatment centers in Tehran. 

Material and Methods: In this case-control study, 160 relapsed patients were compared with 160 abstentious patients. A researcher-developed questionnaire was used to collect data. Chi-square test, odds ratio (OR) and logistic regression were performed for data analysis.

Results: The findings showed that factors increasing rate of relapse were smoking after relapse (OR=7.14, CI=3.855-13.244), substance-related cues (OR=6.76, CI= 3.915-11.678), interaction with addict peers (OR=6.38, CI=3.921-10398), malaise (OR=3.93, CI=2.446-6.305), and family conflict (OR=2.04, CI=1.227-3.385). Opium- and dross-addicts were found to be less likely to have a relapse than crack- or pot- users (OR= 0.208, CI-0.128- 0.336). 

Conclusion: The findings of this study reveal that relapse into drug abuse is significantly associated with personal, social, psychological and medical variables. It is recommended to 

integrate family counseling and therapeutic approaches, constant monitoring, and health care in treatment plans in order to reduce the adverse effects of factors such as family conflicts, peer pressure and drug-related cues in patients' likelihood of relapse.   

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  Background and Aim: There is some evidence that nutrition probably plays a role in the etiology of multiple sclerosis (MS). The present case-control study was conducted in the City of Tehran, Iran with the purpose of finding any possible relations between food groups and MS.

  Materials and Methods: In this case-control hospital-based study conducted in 2011 in the City of Tehran, data were collected on several variables including socio-economic status, life style, and food intakes of 70 MS patients and 140 controls matched for age and gender, through interviews and questionnaires. All the statistical tests were done using the SPSS software version 16. Logistic regression was used to calculate the odds ratio (OR).

  Results: After adjusting for confounding variables, it was seen that subjects in the upper tertile of intakes of the fruit group, tomatoes, other vegetables, and liquid oils, were significantly less likely to be suffering from MS disease, the odds ratio being 68% (OR: 0.32 95% CI: 0.13-0.79), 82% (OR: 0.18 95% CI: 0.05-0.65), 61% (OR: 0.39 95% CI: 0.93-0.16), and 94% (OR: 0.06 95% CI: 0.08-0.58), respectively. On the other hand, subjects shown to be significantly less at risk of the disease were those in the upper tertile of the intakes of non-liquid oil [ 1.58 times (OR: 2.58 95% CI: 1.05-6.33) ] and soft drinks [1.87 times (OR: 2.87 95% CI: 1.17-7.02)] (p for trend < 0.05).

  Conclusion: The findings of this study support the probable role of nutrition in preventing multiple sclerosis.

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Background and Aim: Cardiovascular diseases (CVD) are the leading cause of death globally, causing annually 17.3 million deaths, more than 75% of these deaths occurring in the low- and middle-income countries. Although extensive studies have been conducted to determine the risk factors for these diseases, limited studies have been performed to investigate these factors using a multilevel analysis method. The aim of this study was to determine the CVD risk factors in the staff of Mashhad University of Medical Sciences using a multilevel analysis approach, as well as compare the application of the conventional and multilevel logistic regressions in doing this according to the hierarchical structure of the data.
Materials and Methods: This was a case-control study including a total of 1091 randomly selected individuals from among the people in a prospective cohort study, namely, the “PERSIAN Cohort Study in Mashhad University of Medical Sciences” in 2018.  The case group included 152 patients with a definite diagnosis of CVD and the control group 939 staff members not suffering at the time from CVD. Data analysis was done using the STATA software. Data analysis (based on frequencies and percentages) was done using one-way and two-level logistic regression analysis at α = 0.05.
Results: Multivariate analysis showed that hypertension, smoking, fasting blood sugar and cholesterol were among the cardiovascular risk factors with a significant relationship with the disease. Based on the two-tier logistic regression model, the odds ratio for CVD in the hypertensive patients was 3.93 times that in individuals with a normal blood pressure with a confidence interval of 2.64-6.28. The risk in smokers was 1.85 (1.11-3.09) times that in nonsmokers. The CVD odds ratio in individuals with a high fasting blood glucose level (undiagnosed/uncontrolled diabetes) was 2.7 (1.18-6.18) times that in those with a normal blood pressure. There were no statistically differences between the case and control groups as regards the other variables ─ body mass index, diabetes (controlled or uncontrolled), or blood triglyceride level.
Conclusion: The findings show that statistical model selection can influence the results of data analysis in a dataset. It should be noted that the results of this study indicate a high prevalence of some cardiovascular risk factors among the staff. Another crucial point in this study is that the level of physical activity of the staff was found to be low, which would result in increased risk of overweight and obesity.