Journal of School of Public Health and

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Background and Aim: Mortality from cardiovascular and other chronic diseases has increased in Iran. Our aim was to estimate the effects of smoking and high systolic blood pressure (SBP), fasting plasma glucose (FPG), total cholesterol (TC), and body mass index (BMI) on mortality and life expectancy, nationally and sub-nationally using representative data and comparable methods.

Materials and Methods: We used data from the Non-Communicable Disease Surveillance Survey to estimate means and standard deviations for the metabolic risk factors, nationally and by region. Lung cancer mortality was used to measure cumulative exposure to smoking. We used data from the death registration system to estimate age-, sex-, and disease-specific numbers of deaths in 2005, adjusted for incompleteness using demographic methods. We used systematic reviews and meta-analyses of epidemiologic studies to obtain the effect of risk factors on disease specific mortality. We estimated deaths and life expectancy loss attributable to risk factors using the comparative risk assessment framework.

Results: In 2005, high SBP was responsible for 41,000 (95% uncertainty interval: 38,000, 44,000) deaths in men and 39,000 (36,000, 42,000) deaths in women in Iran. High FPG, BMI, and TC were responsible for about one-third to one-half of deaths attributable to SBP in men and/or women. Smoking was responsible for 9,000 deaths among men and 2,000 among women. If SBP were reduced to optimal levels, life expectancy at birth would increase by 3.2 years (2.6, 3.9) and 4.1 years (3.2, 4.9) in men and women, respectively the life expectancy gains ranged from 1.1 to 1.8 years for TC, BMI, and FPG. SBP was also responsible for the largest number of deaths in every region, with age-standardized attributable mortality ranging from 257 to 333 deaths per 100,000 adults in different regions.

Conclusion: Management of blood pressure through diet, lifestyle, and pharmacological interventions should be a priority in Iran. Interventions for other metabolic risk factors and smoking can also improve population health.

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Background and Aims: Heavy metals in atmospheric dust can enter the human body through ingestion, respiration and skin contact and cause various diseases. The aim of this study was to determine the concentration of lead, a heavy metal, in atmospheric dust and assess its health risk during the period between winter of 1397 and the fall of 1398 in regions 9, 10, 11 and 12 of Tehran Municipality, Tehran, Iran.
Materials and Methods: Atmospheric dusts were collected monthly during one year in the following locations in Tehran: west and east of region 9; east of regions 10, 11 and 12 (the locations in the west of these regions had common borders with the eastern part of the adjacent region). A factorial experiment was performed in a completely randomized design with three replications; the experimental factors included sampling locations and sampling times (seasons). The concentration of lead in the samples was then determined after extraction with hydrochloric acid and concentrated nitric acid (ration 3:1).
Results: The lowest (177.1 mg/kg) and highest (98.476 mg/kg) concentration of lead were found to be in location 9W (Tehransar) in winter and in location 11E (Vahdet-E-eslami Avenue) in autumn, respectively. Further analysis of the data showed that ingestion of the atmospheric dust was the main risk of exposure to lead and that more than 90% of the risk index for non-cancerous diseases caused by lead was related to ingestion hazard quotient (HQ, risk equation).
Conclusion: Based on the findings it can be concluded that in winter the hazard quotient (HQ) and hazard index (HI, non-cancer Risk Index) for lead were lower than the maximum permitted levels for adults and children and, so, did not pose any health risk for these age groups. However, in spring, summer and autumn the risk index for lead was higher than the maximum permitted level for children and, thus, the risk of children developing non-cancerous diseases was high in all the sampling locations.