Alireza Khajavi1, Farhad Pishgar2, Mahboubeh Parsaeian3, Sahar Saeedi Moghaddam4, Alireza Jeddian5, Hamid Reza Bahrami-Taghanaki6, Hamid Reza Jamshidi7, Shohreh Naderimagham8. 1. 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. 2. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran. 3. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. 4. 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; Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 5. Digestive Diseases Research Institute (DDRI), Tehran University of Medical Sciences, Tehran, Iran. 6. Complementary and Chinese Medicine, Persian and Complementary Medicine Faculty, Mashhad University of Medical Sciences, Mashhad, Iran. 7. Department of Pharmacology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 8. 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. Electronic address: sh-naderimagham@sina.tums.ac.ir.
Abstract
PURPOSE: We conducted this study to investigate birth seasonality in rural parts of Iran. METHODS: In this study, patterns of 5,536,262 live births in rural parts of Iran between 1992 and 2007 were studied. Information about birth numbers, environmental factors, and sociocultural status of participants was obtained from previous works. Visually inspecting the seasonal variation of birth, studying its trend using autocorrelation analysis, examining the trend of birth seasonality using the seasonality coefficient, a newly introduced index, studying correlations between birth seasonality and possible associated factors, and analyzing associations between these variables and birth seasonality using multiple regression model were performed in this study. RESULTS: In this study, we showed birth seasonality in rural parts of Iran, with the highest births in the first two seasons, winter and spring, mostly before the year of 2002. Latitude and mean temperature of districts, wealth status of families, education of women, and mothers' ages were associated with birth seasonality. However, latitude, temperature, and mothers' ages lost their associations after adjusting for sociocultural factors in the regression model. CONCLUSIONS: Birth numbers in rural areas of Iran follow a rhythmic seasonal pattern; however, the ordering of seasons changes in the last years of the study period. Copyright Â
PURPOSE: We conducted this study to investigate birth seasonality in rural parts of Iran. METHODS: In this study, patterns of 5,536,262 live births in rural parts of Iran between 1992 and 2007 were studied. Information about birth numbers, environmental factors, and sociocultural status of participants was obtained from previous works. Visually inspecting the seasonal variation of birth, studying its trend using autocorrelation analysis, examining the trend of birth seasonality using the seasonality coefficient, a newly introduced index, studying correlations between birth seasonality and possible associated factors, and analyzing associations between these variables and birth seasonality using multiple regression model were performed in this study. RESULTS: In this study, we showed birth seasonality in rural parts of Iran, with the highest births in the first two seasons, winter and spring, mostly before the year of 2002. Latitude and mean temperature of districts, wealth status of families, education of women, and mothers' ages were associated with birth seasonality. However, latitude, temperature, and mothers' ages lost their associations after adjusting for sociocultural factors in the regression model. CONCLUSIONS: Birth numbers in rural areas of Iran follow a rhythmic seasonal pattern; however, the ordering of seasons changes in the last years of the study period. Copyright Â