The prevalence of metabolic syndrome in drivers: A meta-analysis and systematic review.

BACKGROUND: Metabolic syndrome is an increasing disorder, especially in night workers. Drivers are considered to work during 24 hours a day. Because of job characteristics such as stress, low mobility and long working hours, they are at risk of a metabolic syndrome disorder. OBJECTIVES: The purpose of this study is a meta-analysis and systematic review of the prevalence of metabolic syndrome in drivers. METHODS: In this systematic review, articles were extracted from national and international databases: Scientific Information Database (SID), Iran Medex, Mag Iran, Google Scholar, Science Direct, PubMed, ProQuest, and Scopus. Data analysis was performed using meta-analysis and systematic review (random effect model). The calculation of heterogeneity was carried out using the I2 index and Cochran's Q test. All statistical analyses were performed using STATA software version 11. RESULTS: A total of nine articles related to the prevalence of metabolic syndrome in drivers in different regions of the world from 2008 to 2016 were obtained. The total sample size studied was 26156 with an average of 2906 samples per study. The prevalence of metabolic syndrome in drivers was 34% (95% CI: 30-37)CONCLUSIONS:According to the results of this study, the prevalence of metabolic syndrome in drivers is high. Occupational stress, unhealthy diet and physical inactivity cannot be cited as causes of metabolic syndrome prevalence in drivers. Therefore, to maintain and to improve the health of this group, the implementation of preventive, therapeutic and rehabilitation measures for these people as well as training should be considered.

Survey of accidents in suburban Tehran and the prediction of future events based on a time-series model.

BACKGROUND: Car accidents are currently a social issue globally because they result in the deaths of many people. The aim of this study was to examine traffic accidents in suburban Tehran and forecast the number of future accidents using a time-series model. METHODS: The sample population of this cross-sectional study was all traffic accidents that caused death and physical injuries in suburban Tehran in 2010 and 2011, as registered by the Tehran Emergency Section. In the present study, Minitab 15 software was used to provide a description of traffic accidents in suburban Tehran for the specified time period as well as those that occurred during April 2012. RESULTS: The results indicated that the average number of traffic accidents in suburban Tehran per day in 2010 was 7.91 with a standard deviation of 7.70. This figure for 2011 was 6 daily traffic accidents with a standard deviation of 5.30. A one-way analysis of variance indicated that the average of traffic accidents in suburban Tehran was different for different months of the year (P = 0.000). The study results showed that different seasons in 2010 and 2011 had significantly different numbers of traffic accidents (P < 0.05). Through an auto-regressive moving average (ARMA), it was predicted that there would be 166 traffic accidents in April 2012 with a mean of 5.53 and maximum of 6 traffic accidents/day. CONCLUSION: There has been a decreasing trend in the average number of traffic accidents per day.

Review the number of accidents in Tehran over a two-year period and prediction of the number of events based on a time-series model.

BACKGROUND: One of the significant dangers that threaten people's lives is the increased risk of accidents. Annually, more than 1.3 million people die around the world as a result of accidents, and it has been estimated that approximately 300 deaths occur daily due to traffic accidents in the world with more than 50% of that number being people who were not even passengers in the cars. The aim of this study was to examine traffic accidents in Tehran and forecast the number of future accidents using a time-series model. METHODS: The study was a cross-sectional study that was conducted in 2011. The sample population was all traffic accidents that caused death and physical injuries in Tehran in 2010 and 2011, as registered in the Tehran Emergency ward. The present study used Minitab 15 software to provide a description of accidents in Tehran for the specified time period as well as those that occurred during April 2012. RESULTS: The results indicated that the average number of daily traffic accidents in Tehran in 2010 was 187 with a standard deviation of 83.6. In 2011, there was an average of 180 daily traffic accidents with a standard deviation of 39.5. One-way analysis of variance indicated that the average number of accidents in the city was different for different months of the year (P < 0.05). Most of the accidents occurred in March, July, August, and September. Thus, more accidents occurred in the summer than in the other seasons. The number of accidents was predicted based on an auto-regressive, moving average (ARMA) for April 2012. The number of accidents displayed a seasonal trend. The prediction of the number of accidents in the city during April of 2012 indicated that a total of 4,459 accidents would occur with mean of 149 accidents per day during these three months. CONCLUSION: The number of accidents in Tehran displayed a seasonal trend, and the number of accidents was different for different seasons of the year.