Background Globorisk is a novel risk prediction model for predicting cardiovascular disease (CVD). Globorisk is a country-specific risk prediction model that determines CVD risk for all countries. This model has two versions; laboratory-based and office-based. This study aimed to determine the agreement between laboratory-based and office-based models in a large sample of the general population. Methods Baseline data from the Fasa cohort study was used for the current study. In total, 6810 participants ≥ 40 years without any history of cardiovascular disease or stroke were included in the study. To determine the laboratory-based risk model, factors include age, sex, current smoking status, history of diabetes, systolic blood pressure (SBP), and total cholesterol. To estimate the office-based risk model, factors were age, sex, current smoking status, SBP, and body mass index (BMI). Kappa statistics was used to distinguish the agreement between grouped scores in these two models. Additionally, correlation coefficients and scatter plots were used to determine the linear correlation between the two models. Results In this study 46.53% of the participants were men. The mean age (SD) of participants was 51.08 (7.88) years. Agreements between the two models were moderate and substantial in all women and all men, respectively. The agreement between the two CVD risk groups was 90.15% (kappa = 0.717) in all men, 92.94% (kappa = 0.571) among men aged < 60 years and 77.60% (kappa = 0.645) in men aged ≥ 60 years. The agreement between the two CVD risk groups was 86.68% (kappa = 0.572) among all women, 93.96% (kappa = 0.274) among women aged < 60 years and 62.46% (kappa = 0.422) among women aged ≥ 60 years. A very strong positive correlation (r = 0.94) was found between the two risk scores in all men, and it was similar among men aged < 60 years (r = 0.84) and men aged > 60 years (r = 0.94). Among all women, there was a very strong positive correlation (r = 0.87), and the strong positive correlation remained among < 60 years old (r = 0.76) and women > 60 years old (r = 0.76). Conclusion The Globorisk office-based model which is easier to use as it does not require blood testing can determine the risk groups in this population. The Globorisk office-based model may be used for CVD risk screening in low-middle income countries where resources are limited.

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Background Road traffic crashes (RTCs) and its associated injuries are one of the most important public health problems in the world. In Iran, RTCs rank second in terms of mortality. To address this issue, there is a need for research-based interventions. Prioritizing researches using a variety of approaches and frameworks to determine the most effective interventions is a key nodal point in the RTCs' research policy planning cycle. Thus, this study aims to generate and prioritize research questions in the field of RTCs in Iran. Methods By adapting the Child Health and Nutrition Research Initiative (CHNRI) method, this study engaged 25 prominent Iranian academic leaders having role in setting Iran’s long-term road safety goals, a group of research funders, and policymakers. The experts' proposed research questions were independently scored on a set of criteria: feasibility, impact on health, impact on the economy, capacity building, and equity. Following the prioritization of Research Questions (RQs), they were all classified using the 5 Pillar frameworks. Results In total, 145 Research Questions were systematically scored by experts against five criteria. Iran's top 20 road traffic safety priorities were established. The RQs related to “road safety management” and “road and infrastructure” achieved a high frequency. Conclusions The top 20 research questions in the area of RTCs in Iran were determined by experts. The majority of these RQs were related to “road safety management”. The results of this study may contribute to the optimal use of resources in achieving long-term goals in the prevention and control of road traffic crashes and its related injuries. Considering these RQs as research investment options will improve the current status of Road Traffic Injuries (RTIs) at a national level and further advance toward compliance with international goals. If these research priorities are addressed, and their findings are implemented, we can anticipate a significant reduction in the number of crashes, injuries, and deaths.

Background This study aims to examines child occupants’ unsafe behaviors and design, implement and evaluate the multi-level intervention program using Socio-ecological model (SEM) to promote child occupants’ safe behaviors. Methods This interventional study was conducted in two educational districts of Tabriz, northwest of Iran. SEM was used in two intervention and control groups (n = 160 children per group). The intervention group received educational programs through virtual education application. Messages, images and short videos of unsafe behaviors were sent to students, teachers and parents by this application. Social support was provided through peers, parents and teachers to promote safe behaviors. Interventions were implemented at intrapersonal, interpersonal and social levels. The frequency of unsafe behaviors was examined in both groups before and after intervention. Results Behaviors of sitting in the front seat, sitting on the lap of the front passenger, standing in the back seat and sticking hands or other parts of the body out of the window decreased among children by 64.8%, 32.4%, 38% and 84% in the intervention group, respectively (vs. 27%, 23%, 7% and 30.6% in the control group, respectively). However, no statistically significant difference was observed between the two groups in the frequency of using safety seats. Conclusion Using multi-level interventions by SEM could reduce child occupants’ unsafe behaviors.

BackgroundThe present study aims to investigate one of the major causes of traffic accidents: drivers' unsafe behaviors while driving.MethodsIn this cross-sectional study, the behaviors of 946 drivers at traffic lights were observed in the morning, at noon, and in the evening using direct in-field observation. The unsafe behaviors of the drivers included not fastening the seat belt, using a cellphone or handsfree device, smoking, being distracted by a child, talking with passengers, not observing the stop line, eating and drinking, and getting out of the car, letting out a passenger, or arguing with a passenger at the traffic light.ResultsOf the drivers at the traffic light, 60% did not obey the stop line, and 72% did not fasten their seat belt. Also, 13.6% used their cellphones, and 22% talked with passengers. The frequency of the other unsafe behaviors was &lt;3%. For wearing seat belts, drivers aged 41–50 years wore seat belts almost five times more than drivers under 25 years of age (4.94 [2.36–10.320]; p &lt; 0.001), and drivers aged 50 years and older were almost three times likelier to wear seat belts than drivers under 25 years of age (2.8 [1.31–6.08]; p &lt; 0.001). The results showed that the drivers were significantly likelier to wear seat belts on Saturdays (after the weekend) (0.56 [0.40–0.78]; p = 0.001). Regarding using mobile phones while driving, women were twice as likely to use mobile phones as men (2.20 [1.30–3.72]; p &lt; 0.001). Drivers aged 26–40 years used mobile phones significantly less than drivers under 25 years of age (0.24 [0.14–0.43]; p &lt; 0.001) and drivers aged 41–50 years were significantly less likely to use mobile phones than drivers under 25 years of age (0.19 [1.31–6.08]; p &lt; 0.001).ConclusionThe results showed that the occurrence of wearing a seat belt in Shahin Dej was low. We observed a significant association between wearing a seat belt, age, whether it was Saturday (a day after weekend for Iranians). Additionally, similar associations were observed between using mobile phones and gender, age, and day of the week.