Search published articles
Volume 11, Issue 2 (11-2013)
Anderson, H.R., 2009. Air pollution and mortality: A history. Atmospheric Environment, 43, pp. 142-152 .
Box, GEP. and Jenkins, G.M., 1976. Time series analysis: forecasting and control, San Francisco, Holden Day Pulications .
Duenas, C., Fernandez, M.C., Canete, S., Carretero,Liger E, 2005. Stocastic model to forecast ground level ozone concentration at urban and rural areas . Chemosphere, 61(10), pp. 1379-1389 .
Ghorbani, M. and Younesian, M., 1389. Research Projects in Air pollution Epidemiology. Iranian Epidemiology Journal . 5, pp. 44-52 [In Persian].
Goyal, P., Chan, A.T. and Jaiswal, N., 2006. Statistical models for the prediction of respirable suspended particulate matter in urban cities. Atmospheric Environment, 40, pp. 2068-2077 .
Hamilton, JD., 1994. Time series analysis, Princeton Publications, USA .
Hosseinpour, A.R., Forouzanfar, M.H., Yunesian, M., Asghari, F., Holakouie Naieni, K. and Farhood, D., 2005. Air pollution and hospitalization due to angina pectoris in Tehran, Iran: A time-series study. Environmental Research, 99, pp. 126-131 [In Persian].
Ingrisch, M., Sourbron, S., Reiser, M.F. and Peller, M., 2009. Model selection in dynamic contrast enhanced MRI: The Akaike Information Criterion. In Dössel, O. and Schlegel, WC. (Eds.) IFMBE Proceedings 25/IV
Khosravi Dehkordi, A. and Modarres, R., 1386. Time Series analysis of the daily air pollution in Isfahan from the Petrolium Industry. Mohit shenasi. 33, pp. 33-42 [In Persian].
Kumar, U. and De Ridder, K., 2010. GARCH modelling in association with FFT-ARIMA to forecast ozone episodes. Atmospheric Environment, 44, pp. 4252-4265.
Lau, J.C., Hung, W.T., Yuen, D.D. and Cheung, C.S., 2009. Long memory characteristics of urban roadside air quality. Transportation Research Part D, 14, pp. 353-359 .
Liang, W., Wei, H. and Kuo, H., 2009. Association between daily mortality from respiratory and cardiovascular diseases and air pollution in Taiwan. Environmental Research, 109, pp. 51-58 .
Liu, P.G., 2009. Simulation of the daily average PM10 concentrations at Ta-Liao with Box–Jenkins time series models and multivariate analysis. Atmospheric Environment, 43, pp. 2104 - 2113 .
López-Villarrubia, E., Ballester, F., Iñiguez, C. and Peral, N., 2010. Air pollution and mortality in the Canary Islands:a time-series analysis. Environmental Health, 9 .
Lumbreras, J., Garcia-Martos, C., Mira, J. and Borge, R., 2009. Computation of uncertainty for atmospheric emission projections from key pollutant sources in Spain. Atmospheric Environment, 43, pp. 1557-1564 .
Masjedi, M.R., Jamaati, H.R., Dokoohki, P., Ahmadzadeh, Z., Alinejad Taheri, S., Bigdeli, M., Agin, K., Ghavam, S.M., Rostiman, A. and Izadi S., 2001. The correlation between air pollution and acute respiratory and cardiac attacks. Pazhoohesh dar pezeshki, 25, pp. 25-33 [In Persian].
Nasrollhi, Z. and Ghaffari Goolak, M., 2010. Air pollution and its effective factors. Faslnameh Pazhoohesh Eghtesadi, 3, pp. 375-395 [In Persian].
Quintela-del-Rio, A. and Francisco-Fernandez, M., 2011. Nonparametric functional data estimation applied to ozone data: Prediction and extreme value analysis. Chemosphere, 82, pp. 800-808 .
Rajarathnam, U., Sehgal M., Nairy S., Patnayak R.C., Chhabra S.K., Kilnani, K.V., R and Committee., HHR, 2011. Time Series study on air pollution and mortality in Dehli. Res Rep Health Eff Inst, Mar, pp. 47-74 .
Samet, J.M., Dominici, F., Zeger, S.L., Schwartz, J. and Dockery, D.W., 2000. The national morbidity, mortality and air pollution study. Part 1: Methods and Methodologic Issues. Research Report 94 Cambridge, MA, Health Effects institute .
Sharma, P., Chandra, A. and Kaushik, S.C., 2009. Forecasts using Box–Jenkins models for the ambient air quality data of Delhi City. Environ Monit Assess, 157, pp. 105–112 .
Wagemakers, E. and Farrell, S., 2004. AIC model selection using Akaike weights. Psychonomic Bulletin and Review, 11, pp. 192-196 .
Zhang, F., Wang, W., Lv, J., Krafft, T. and Xu, J., 2011. Time-series studies on air pollution and daily outpatient visits for allergic rhinitis in Beijing, China. Science of the Total Environment, 409, pp. 2486–2492 .
Scientific Journal of School of Public Health and Institute of Public Health Research /85
Vol. 11, No. 2, Summer 2013
Forecasting ambient air pollutants by time series models in Kerman, Iran
Mansouri, F., MS.c. Student, Dept of Environmental Health Engineering, Faculty of Public Health, Kerman Medical University, Kerman, Iran
Khanjani, N., Ph.D. Assistant Professor, Department of Epidemiology and Department of Environmental Health, Faculty of Public Health, Kerman Medical University, Kerman, Iran - Corresponding author: n_khanjani@kmu.ac.ir
Rananadeh Kalankesh, L., MS.c. Student, Department of Environmental Health Engineering, Faculty of Public Health, Kerman Medical University, Kerman, Iran
Pourmousa, R., MS.c. Lecturer, Department of Statistics, School of Mathematics and Statistics, Shahid Bahonar University, Kerman, Iran
Received: Apr 3, 2012 Accepted: Feb 14, 2013
ABSTRACT
Background and Aim: Air pollution is one of the most important problems of big cities in developing countries and can have several negative health effects on humans. Therefore studying these pollutants can help in developing programs for air pollution control. The aim of this study was to estimate and predict the changes of air pollutants in Kerman, Iran.
Materials and Methods: In this ecological study, data about seven important air pollutants in Kerman including NO, CO, NO2, NOx, PM10, SO2 and O3 from March 2006 until September 2010 was inquired from the Kerman Province Environmental Protection Agency. Then the data was calculated as averages per month and by incorporating time series models, predictions were done for each pollutant.
Results: All of the pollutants were steady in Kerman, except CO which is significantly decreasing and PM10 which is increasing. All of the pollutants had a seasonal pattern. Time series models with a 12, 3, 8, 12, 12, 12 and 6 month seasonal pattern were fit for O3 , SO2 , PM10 , NOx , NO2 , CO and NO consecutively.
Conclusion: The production of ambient CO is decreasing in Kerman and one reason is probably replacing and retiring old automobiles. However PM10 is increasing in Kerman and in most seasons it is above standard and therefore control initiatives should be implemented.
Volume 21, Issue 4 (3-2024)
Background and purpose: The purpose of this research was to write a critical review of the available service packages in the Mental and Social Health and Addiction Office (MSHAO) of the Ministry of Health and Medical Education in the areas of drugs, alcohol and tobacco, which are currently used in the primary health care system. The content analysis method was used to extract the specialists’ critiques.
Materials and Methods: Initially the MSHAO sent 1362 pages of information in the form of 47 files to researchers to be reviewed. The files were classified, eliminating/removing additional, unrelated and duplicated items; finally 840 pages in 29 files were studied and carefully examined. Then, seven experts in the field of addiction were asked to criticize the packages, using the content analysis method to extract the experts' critiques.
Results: The findings showed that comprehensive information about drugs, alcohol and tobacco addiction is provided to the clients. However, based on a critical review of the existing packages four main critiques were extracted, namely, sources/references, epidemiology, incompatibility of Iranian-Islamic culture, and technical-specialist issues. In addition, criticisms were also extracted in the following areas/services: the number of files and the variety of interventions, editing and writing problems, interventions and discussions with inappropriate in-text sources/citations, some old sources/references (published in 2013 and 2014), old interventions, lack of appropriate compatibility with the culture of the Islamic society of Iran, and direct translation of some parts of the original texts and documents of international meetings/gatherings.
Conclusion: Despite the efforts of the Mental and Social Health and Addiction Office to cover the needs of the majority of people referring to the primary care system, it seems that the high number of interventions and additional information can cause confusion of/for the physician, mental health care provider, family health care provider, general health care provider and other relevant individuals. It is, therefore, suggested that some packages be merged with each other, duplicate items be removed and specific sections be added, some packages be fundamentally revised based on the suggested items, and updated packages be developed with due consideration of to the culture of the Iranian society.
Volume 22, Issue 2 (9-2024)
Background and Aim: Available evidence shows the effectiveness of psychotherapy. However, the number of patients who deteriorate or do not improve is still problematic. On the other hand, while some therapists are generally more successful than others, most therapists have experienced both success and failure of therapy in different cases. The purpose of this study was to determine the factors effective in psychotherapy from the perspective of therapists and clients.
Materials and Methods: Based on the purpose of this research, it can be considered as an applied research and qualitative in nature. Data were collected through interviews and analyzed using the content analysis method based on the analogical approach. The samples of therapists and clients were selected purposefully from the statistical population including 1. Therapists (psychiatrists, psychologists and counselors) licensed by the Psychology and Counseling Organization with 5 years or more of therapy experience, and 2. Clients who had participated in at least one psychotherapy course. The sample size was based on theoretical saturation and, therefore, the interview process continued until ensuring sufficiency of the collected data; thus the interviews ended with the 21st person in the therapists group and the 15th person in the clients group.
Results: The factors in effective treatment were found to be in three areas, namely, the therapist (attitude, competence, personality, maturity, ability and appearance), the client (demographic characteristics, reason and method of referral, insight), and environmental factors (economic, socio-political issues, location of the psychological center, supporting problems, and daily living events of clients and therapists).
Conclusion: The findings of this research show the components and importance of the model of effective factors in effective psychotherapy to policy makers, trustees, professors and therapists in the field of mental health. The achievement of these components can increase the efficiency of the therapists in achieving their goals and also help a clients to choose a therapist.
| Page 1 from 1 |
Related Websites
Site Keywords
Health, Institute of Public Health Research, Tehran University of Medical Sciences,Site Statistics
- Registered users: 4435 users
- Online users: 0 users
- Guest users: 198 users
- All visits: 16720734 visits
- Visits in 24 Hours: 13296 visits
- Total articles: 1728 articles
- Published articles: 705 articles
© 2026 , Tehran University of Medical Sciences, CC BY-NC 4.0
Designed & Developed by : Yektaweb