Ali Sheidaei1, Kimiya Gohari2, Amir Kasaeian3, Nazila Rezaei4, Anita Mansouri5, Ardeshir Khosravi6, Mahboubeh Parsaeian7, Younes Mohammadi8, Parinaz Mehdipour4, Shadi Rahimzadeh9, Farshad Sharifi10, Mehdi Varmaghani11, Maryam Chegini12, Shohreh Naderimagham4, Hamid Reza Jamshidi13, Farshad Farzadfar4. 1. Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran, Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2. Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran, Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 3. Hematology-Oncology and Stem Cell Transplantation Research Center, Tehran University of Medical Sciences, Tehran, Iran, Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 4. Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran, Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 5. Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 6. Ministry of Health and Medical Education, Deputy for Public Health, Tehran, Iran. 7. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran, Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 8. Department of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran, Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 9. Department of Epidemiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran, Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 10. Elderly Health Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran Iran. 11. Department of Health Economics and Management Sciences, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran, Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 12. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran, Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 13. Department of Pharmacology, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abstract
BACKGROUND: Causes of death statistics provide crucial health intelligence in national and international communities. An efficient death registration system provides reliable information for health policy system. In many developing countries, death registration systems face a degree of misclassification and incompleteness. There are many impediments to putting an estimate of cause-specific death rates. Addressing those challenges could prevent misleading results. METHODS: Our data was collected by Ministry of Health and Medical Education, Tehran and Isfahan cemeteries from 1995 to 2010. After converting ICD codes of Iran's death registration into GBD codes, 170 underlying causes of deaths were recognized in the available data. A wide range of methods were applied for preparing the data. We used several statistical models to estimate mortality rates in age-sex-province groups for all causes of deaths. The considerable number of combinations for age, sex, cause of death, year, and province variables made further complicated model selection and evaluation of the results. RESULTS: Totally, 58.91% of deaths were related to males. The majority of cases of death were classified as NCDs (77.83%) and injuries (14.80%). We extrapolated 71.76% and 14.71% of causes of death by mixed effect model, spline model with parameter 0.9 and 0.6, respectively. CONCLUSION: A comprehensive and unique registration system is able to solve many DRS issues. It is necessary to assess the quality and validity of cause of death data. Scientific methods like analyzing mortality level and cause-of-death data are used to provide an overview for better decisions.
BACKGROUND: Causes of death statistics provide crucial health intelligence in national and international communities. An efficient death registration system provides reliable information for health policy system. In many developing countries, death registration systems face a degree of misclassification and incompleteness. There are many impediments to putting an estimate of cause-specific death rates. Addressing those challenges could prevent misleading results. METHODS: Our data was collected by Ministry of Health and Medical Education, Tehran and Isfahan cemeteries from 1995 to 2010. After converting ICD codes of Iran's death registration into GBD codes, 170 underlying causes of deaths were recognized in the available data. A wide range of methods were applied for preparing the data. We used several statistical models to estimate mortality rates in age-sex-province groups for all causes of deaths. The considerable number of combinations for age, sex, cause of death, year, and province variables made further complicated model selection and evaluation of the results. RESULTS: Totally, 58.91% of deaths were related to males. The majority of cases of death were classified as NCDs (77.83%) and injuries (14.80%). We extrapolated 71.76% and 14.71% of causes of death by mixed effect model, spline model with parameter 0.9 and 0.6, respectively. CONCLUSION: A comprehensive and unique registration system is able to solve many DRS issues. It is necessary to assess the quality and validity of cause of death data. Scientific methods like analyzing mortality level and cause-of-death data are used to provide an overview for better decisions.
Authors: Mehdi Varmaghani; Malihe Ghobadi; Farshad Sharifi; Payam Roshanfekr; Ali Sheidaei; Masoume Mansouri; Amin Adel; Mohammad Mohammadi; Mohammad Reza Masjedi Journal: Int J Prev Med Date: 2021-02-24