Background: According to the International Labor Organization (ILO), 2.78 million workers are injured and killed each year as a result of occupational diseases, while 374 million are injured. Furthermore, work-related injuries cost the global economy 4% of its GDP. Construction workers are more likely than other workers to die and twice as likely to be injured. Construction accidents are frequently caused by a lack of knowledge and training, negligence, and inadequate safety equipment. Workers account for 70% of the factors influencing accidents, 49% of workplace problems, 56% of equipment shortages, 27% of material conditions, and 84% of risk management. Between 2009 and 2017, 3321 industrial accidents and acute poisoning cases were reported in Mongolia. 509 people died as a result of industrial accidents, 761 people became disabled as a result of injuries, and 2051 people temporarily lost their ability to work. As a result, determining the distribution, causes, and factors of accidents is reasonable. Purpose: To detect the prevalence and influencing factors of accidents in the construction industry in the last 5 years. Material and Method: Secondary data was collected using a quantitative research method based on a single-moment model of observational research from the "General Directorate of Professional Supervision" quantitative data on industrial accidents and acute poisoning by sampling 10 groups and 59 indicators of accident cases in the construction industry. Result: The prevalence of accidents in the construction industry was calculated for 1000 workers in Ulaanbaatar's 21 provinces and 9 districts using the ARC GS program. For the calculation of influencing factors and injury causes at www.graphpad.com, P values less than 0.05 was considered significant.
Between 2017 and 2021, 134 accidents and injuries were reported in Mongolia's construction industry. All accidents were male in 123 cases (92%), and female in 11 cases (8%).
Accidents and injuries in the construction industry are distributed. In Mongolia, Ulaanbaatar had 66 cases, Umnugovi had 10, Orkhon had 10, and Khovd province had 12, all of which had more accidents than other provinces. Calculating the distribution per 1000 workers, Sukhbaatar has 20, Dornogovi has 15, Umnugovi has 12, and Khovd has 10.9.
The most important factors influencing construction accidents are the workplace environment and human factors. In terms of accident causes, falling, tripping, or slipping caused 55 or 41% of all accidents, falling objects caused 24 or 18%, being trapped by objects caused 19 or 14%, and 20 or 15% were remaining causes of injuries. In the last 5 years, 47 or 35.07% of all accidents were caused by workplace environment, 45 or 33.5% by human factors, 23 or 17.1% by management system, and 19 or 14.1% by technical and technological factors. Conclusions
1. In the last five years, the prevalence of accidents among construction workers is 16.3 per 1000. The prevalence is 42.9% (66) highest in Ulaanbaatar City, 20.1% (27) in Khan-Uul district, and 8.9% (12) in Khovd province. The prevalence per 1000 workers is 20 in Sukhbaatar, 15.7 in Dornogovi, 12 in Umnugovi, and 10.9 in Khovd, with a high prevalence of 1.07 in Ulaanbaatar.
2. Human factors, such as falling from a height due to noncompliance with safety rules, limited space in the workplace and environment, and falling into pits, wells, ditches, and excavated pits, are the leading causes of injuries and accidents. Closed fractures and head injuries are the most common.

Introduction : In the last years other country scientists told about not only determine infant weights, need to interest correlation between maternal weight, height and infant weight. In our country few research articles posted about anthropometry of obstetrics and gynecology. Our study aim is determine maternal weight, infant weight, placenta weight and assess factors affecting roles on maternal story of “Amgalan” Maternity Hospital in 2014-2015. Goal: The current study aimed at assessing maternal weight, infant weight, placenta weight and evaluating the effect of factors leading to it. Materials and Methods: The data was already collected from “Amgalan” Maternity Hospital using maternal history and record and it was collected measuring general physical characteristics such as body weight and height, infant weight, placenta weight and body circumferences. We used retrospective method and collected statistical data was analyzed using SPSS 21.0 software. Results: Of total 964 study participants aged 18-45. The average age of participants was 29.6 ± 5.8 years old and 49.7% (n=479) was working during pregnancy, 45.7% (n=441) hadn’t works, 4.6% (n=44) was student. The average weight of mothers was 75.4±11.5, weight of infants was 3439.5±456, weight of placenta was 685±129. The following factors affected maternal and infant weights: lower education, working, early and late pregnancy complication. Maternal weight had a low direct correlation with infant weight (r=0.267, p<0.01) and placenta weight (r=0.208, p<0.01). In our study maternal height had a low direct correlation with infant weight(r=0.173, p<0.01) and infant weight had a moderate direct correlation with placenta weight (r=0.376, p<0.01). Conclusions
1. The average maternal weight was 75.4±11.5, infant weight was 3539.5±456, placenta weight was 685±129.
2. The following factors affected maternal and infant weights: lower education, working status, early and late pregnancy complications.
3. Maternal weight had a little direct correlation with infant weight (r=0.267, p<0.01) and placenta weight (r=0.208, p<0.01).

Background: Accreditation of healthcare institutions serves as a fundamental mechanism for ensuring patient safety and validating the quality of medical services provided to the population. At Intermed Hospital, a quality measurement system for healthcare services has been established since 2015, encompassing 126 quality indicators at both institutional and departmental levels. This system facilitates continuous quality improvement efforts. In this context, quality indicators specific to the endoscopy department play a pivotal role in objectively assessing the quality of endoscopic services. Aim: To assess the quality indicators in gastrointestinal endoscopy unit. Materials and Methods: A retrospective single-center study was conducted by collecting data from the Intermed hospital’s electronic information systems which included HIS and PACS and Quality and Safety Department’s Database and the results were processed using the SPSS software. Ethical approval was granted by the Intermed hospital’s Scientific research committee. The quality of endoscopic services in the Intermed hospital was assessed based on: a) the average values of four quality indicators measured monthly; b) sample survey data from five categories of quality indicators. Results : Between 2016 and 2024, the quality indicators of the endoscopy unit measured as the level of early warning score evaluations for patients was 95.97%±3.33, the level of cases where peripheral blood oxygen saturation decreased during sedation was 1.54%±3.78, the level of cases where patients experienced paradoxiical response during sedation was 5.82%±1.75, surveillance culturing level for validation of endoscopy reprocessing was 11.6%. The endoscopic documentation quality by peer review showed 95.7-100%, the colonoscopy quality indicators were followings as adenoma detection rate: 24.5% Cecal intubation rate: 99.1%, 95.2%, Colonoscope withdrawal average time: 13.28±10.62 minutes, Bowel preparation quality (Boston Scale): 89.3% 95.7%), patient discharge from the recovery room, Average discharge time post-procedure: With propofol alone: 30.92 minutes; With propofol and fentanyl combined: 31.52 minutes, The intermediate risk was 0.28% by the TROOPS evaluation during procedural sedation. Conclusion The quality benchmark levels for these endoscopic units, as determined by a single-center study, can be effectively implemented by benchmark endoscopy centers to enhance their quality and safety operations.