Estimating population cause-specific mortality fractions in the Islamic Republic of Iran: validation of Murray's method.

BACKGROUND: Vital civil information is recorded in only 25% of middle-income countries. AIMS: To estimate the number and causes of deaths expected in the population, using hospital mortality data and comparing them with data from the Ministry of Health and Medical Education, Tehran, Islamic Republic of Iran. METHODS: Hospital mortality data for 2011-2015 were extracted and were corrected qualitatively through reference to medical records. Using Murray's proposed method, an estimate of the expected deaths was obtained according to cause of death. RESULTS: During 2011-2015, 12 704 deaths were recorded in the hospital and Murray's method estimated 28 768 deaths for the entire population. The most frequent cause of death was ischemic heart disease. The results were compared with data from the Ministry of Health and Medical Education, which had a relative error of 6.9% and -13.5% respectively. The mortality rates registered by the Civil Registration Office were higher than those estimated in the present study. The mortality rates registered by the Ministry of Health and Medical Education were lower than those in the present study. CONCLUSIONS: Considering the importance of registering deaths, alternative methods, with efficiency and low cost, are needed to estimate the number and causes of death in a population.

The Relationship Between Obesity, Overweight, and the Human Development Index in World Health Organization Eastern Mediterranean Region Countries.

OBJECTIVES: Obesity is regarded as one of the most prominent health threats worldwide and a serious risk factor for non-communicable diseases, such as diabetes mellitus type 2, high blood pressure, cardiovascular diseases, and some types of cancer. Given the role that societal development-as reflected by the Human Development Index (HDI)-may play in the prevalence of obesity and overweight, this study aimed to investigate the degree to which the prevalence of obesity and overweight is affected by HDI and its components. METHODS: In this ecological study, the required data on HDI and its components were gathered from the latest report of the United Nations Development Program, and data on obesity and overweight were acquired from the latest reports published on the World Health Organization website. Statistical analyses were conducted using SPSS version 24.0. RESULTS: The prevalence of obesity was determined to be significantly higher among females than males, and the gross national index per capita was found to be significantly higher for males than females (p<0.05). Significant positive correlations were found between HDI and its components and sex, as well as indices of obesity and overweight. CONCLUSIONS: A significant positive correlation exists between HDI and obesity. As policy-makers attempt to improve the general welfare of the people, they should be aware of potential unwanted effects of development on the risk of obesity and overweight among the population.