Background and objective: bipolar mood disorder type I, a major psychiatric disorder with one percent prevalence is as the same as schizophrenia. With regard to high disability rate of bipolar mood disorder type I, suicide, relation problems in the family and society and high cost of its therapy, searching for a way for prevention of bipolar mood disorder type I is necessary. The aim of this study was to determine an association between breast feeding during infancy and bipolar mood disorder type I.Methods: This case-control study was performed on 200 patients (100 cases and 100 controls) without family history of major psychiatric disorders. Research instruments were 3 questionnaires including breast feeding, Delphi socioeconomic status and stressful life events questionnaire.Findings: Twelve percent of case group and 8 percent of controls didn’t have breast feeding. Thirty nine percent of cases and 38 percent of controls fed more than one year and 17 percent of cases and 24 percent of controls had exclusive breast feeding. No significant association between breast feeding and bipolar I mood disorder is found.Conclusion: The therapeutic effect of omega 3 fatty acids in the psychiatric disorder is confirmed, the preventive role of it, in this research, was not known. With respect to multifactorial etiology of this disorder, psychosocial and prenatal factors may be causative in the development of BMDI.

In this research, 5 percent of normal Precipitation Index (PNPI), Deciles of Precipitation(DPI),Rainfall Anomaly Index (RAI), Bahlme & Mooley Drought Index (BMDI) and standardized Precipitation Index (SPI) were used in order to investigate drought in Yazd synoptic station and 31 non synoptic stations all around this province. For this purpose, the present statistical errors were reconstructed via correlation between the stations, after raining data collection from the considered stations. Then, calculation of PNPI, DPI, RAI, BMDI and SPI indexes were calculated on monthly and annual scales. Situation of drought was determined based on the obtained values from calculation of each index according to tables related to the considered indexes in different classes of drought during the statistical period. Then indexes were compared to each other, considering drought given situation for each station. The difference and similarity of each index with other 4 indexes were calculated and investigated. Also after determination of drought situation in each station, given percentage of drought different situations via each Index was determined on annual scales, in 33 study stations. After passing the above mentioned stages, it was found that there was the highest percentage value of similarity between the two indexes RAI & DPI, as both indexes indicated similar situation of hard drought in the stations. These two indexes are considered most efficient to investigate aerology drought. But considering that static indexes are faced with problem on monthly scales and in stations located in drought regions, it is recommended to use SPI & BMDI dynamic indexes whose similarity percentages are acceptable.

Drought is a consequence of fluctuations in climate conditions that their effect on human societies is more than another phenomenon. For drought investigation، monthly data of precipitation in 9 synoptic stations of Fars province during twenty years period (1995-2014) was used. After calculation of drought severity using run theory، suitable index among DI، PNPI، SIAP، RAI، SPI and BMDI indices was selected. Then time series of drought severity fitted on different distributions and after selection of best distribution for each station، drought severity with duration 2، 4، 6 and 8 months in return periods of 2، 3، 5، 10، 25 and 50 years calculated and related table was prepared. Also using cluster analysis studied stations divided into different groups. At least، drought severity zoning map in 2 decades plotted in GIS. Results showed that Standard precipitation index (SPI) as the best index could be a proper interpret of drought computing. Generally، in study area drought severity increase in the recent decade.

The aim of this study is to preserve the sustainability of the Doiraj watershed in RCP scenarios. The observation and future period in this study is (1987-2015) and (2044-2016). For this purpose, the combined weight of 5 models of Fifth Report (AR5), rcp8. 5 scenario, used to assess changes in temperature and precipitation in the coming period. MOTP weighting method to reduce uncertainty of GCM models were used Meteorological drought monitoring in monthly, Seasonal and yearly intervals using Markov chain, frequency analysis and drought indexes SIAP, SPI, Z score and BMDI was calculated. The results showed that long-term average monthly rainfall and temperature at a rate of 14 percent and 2. 1 degrees Celsius as compared to the baseline. Markov chain probability of uncertainty precipitation showed, two months without precipitation in winter, spring and autumn, respectively 56, 63 and 52 percent and the chance of precipitation after a month of dry seasons, respectively 44, 35 and 47 percent. Based on the analysis of the indices during the years 2017-2018 than in 2016-2017 wetter and future years in the period 2024-2025 and 2025-2026 wettest years on the basis of this research.

Extended Abstract Introduction: One of the most important natural disasters is drought phenomenon. If it lasts longer than a season or a long period, it will have economic, social and environmental effects. Drought has no absolute definition and has a specific definition in each region. Each drought varies in severity, duration and extent. Moreover, Drought can be considered as the equivalent of a dry and unusual period or climate that lasts long enough to create a serious imbalance in the hydrological state of a region. Drought can also be regarded as an inevitable phenomenon, including disasters that cannot be prevented but can be managed and organized. Drought indices are an important tool for monitoring and evaluating drought and establish an accurate relationship between many climatic parameters. The information obtained from the indices can be useful for planners, designers and managers of water resources, which is also confirmed by comparative studies of indices. Materials and Methods: This study focuses on studies of drought indices and how they function on different time and place scales. In order to conduct this research, the required materials were collected from domestic and foreign sources. In this study, 19 drought indices used in Iran and the world are evaluated, the results of different researchers are investigated, andlogical conclusions are made from different researches. Results and discussion: The results showed that each index can be used in different regions according to its nature and water resources indicators, plant-related indicators and risk indicators of agricultural, economic and social indices. All indicators in turn and in areas compatible with the nature of these indicators can have a good prediction of drought, and these indicators all should not be compared because the results of this comparison will not be appropriate, but they should be selected appropriately according to the study area. Meanwhile, time scale is very important in each of the indicators and should be considered in order to achieve a more reliable result. Another point that was obtained from the results of this study is that most of the indices used in Iran and the world have paid more attention to the severity of drought andless to the duration, extent and frequency of drought, which is one of the weaknesses of existing drought indices in Iran and the world. An index of drought can persist in the world to pay for the severity, duration, frequency and extent of drought simultaneously and accordingly, it can definitely have appropriate predictions. Conclusion: The results showed that the indices of DI, SPI, PDSI, SPEI, BMDI index are the most widely used drought indices. The results also showed that the weakest drought index is the PNPI index and the strongest indeices of drought are SPEI and BMDI indices. In general, in order to use drought indices, the time and place scale related to those indices should be considered in their use. Since each index of drought has been created under certain conditions, it is suggested that they should not be used in Iran or be used with caution. The overall results of this study suggest that it is better to conduct native statistical models of linear and nonlinear regression according to specific climates of Iran in relation to drought indices according to Iranian meteorological and hydrological data and be introduced multivariate Iranian drought index which definitely has more valuable results.