Analysis of the severity of occupational injuries in the mining industry using a Bayesian network / 한국역학회지

OBJECTIVES@#Occupational injuries are known to be the main adverse outcome of occupational accidents. The purpose of the current study was to identify control strategies to reduce the severity of occupational injuries in the mining industry using Bayesian network (BN) analysis.@*METHODS@#The BN structure was created using a focus group technique. Data on 425 mining accidents was collected, and the required information was extracted. The expectation-maximization algorithm was used to estimate the conditional probability tables. Belief updating was used to determine which factors had the greatest effect on severity of accidents.@*RESULTS@#Based on sensitivity analyses of the BN, training, type of accident, and activity type of workers were the most important factors influencing the severity of accidents. Of individual factors, workers' experience had the strongest influence on the severity of accidents.@*CONCLUSIONS@#Among the examined factors, safety training was the most important factor influencing the severity of accidents. Organizations may be able to reduce the severity of occupational injuries by holding safety training courses prepared based on the activity type of workers.

Analysis of the severity of occupational injuries in the mining industry using a Bayesian network / 한국역학회지

OBJECTIVES: Occupational injuries are known to be the main adverse outcome of occupational accidents. The purpose of the current study was to identify control strategies to reduce the severity of occupational injuries in the mining industry using Bayesian network (BN) analysis. METHODS: The BN structure was created using a focus group technique. Data on 425 mining accidents was collected, and the required information was extracted. The expectation-maximization algorithm was used to estimate the conditional probability tables. Belief updating was used to determine which factors had the greatest effect on severity of accidents. RESULTS: Based on sensitivity analyses of the BN, training, type of accident, and activity type of workers were the most important factors influencing the severity of accidents. Of individual factors, workers’ experience had the strongest influence on the severity of accidents. CONCLUSIONS: Among the examined factors, safety training was the most important factor influencing the severity of accidents. Organizations may be able to reduce the severity of occupational injuries by holding safety training courses prepared based on the activity type of workers.

Analysis of the severity of occupational injuries in the mining industry using a Bayesian network / 한국역학회지

OBJECTIVES: Occupational injuries are known to be the main adverse outcome of occupational accidents. The purpose of the current study was to identify control strategies to reduce the severity of occupational injuries in the mining industry using Bayesian network (BN) analysis.METHODS: The BN structure was created using a focus group technique. Data on 425 mining accidents was collected, and the required information was extracted. The expectation-maximization algorithm was used to estimate the conditional probability tables. Belief updating was used to determine which factors had the greatest effect on severity of accidents.RESULTS: Based on sensitivity analyses of the BN, training, type of accident, and activity type of workers were the most important factors influencing the severity of accidents. Of individual factors, workers' experience had the strongest influence on the severity of accidents.CONCLUSIONS: Among the examined factors, safety training was the most important factor influencing the severity of accidents. Organizations may be able to reduce the severity of occupational injuries by holding safety training courses prepared based on the activity type of workers.

Application of an artificial neural network model for diagnosing type 2 diabetes mellitus and determining the relative importance of risk factors / 한국역학회지

OBJECTIVES@#To identify the most important demographic risk factors for a diagnosis of type 2 diabetes mellitus (T2DM) using a neural network model.@*METHODS@#This study was conducted on a sample of 234 individuals, in whom T2DM was diagnosed using hemoglobin A1c levels. A multilayer perceptron artificial neural network was used to identify demographic risk factors for T2DM and their importance. The DeLong method was used to compare the models by fitting in sequential steps.@*RESULTS@#Variables found to be significant at a level of p < 0.2 in a univariate logistic regression analysis (age, hypertension, waist circumference, body mass index [BMI], sedentary lifestyle, smoking, vegetable consumption, family history of T2DM, stress, walking, fruit consumption, and sex) were entered into the model. After 7 stages of neural network modeling, only waist circumference (100.0%), age (78.5%), BMI (78.2%), hypertension (69.4%), stress (54.2%), smoking (49.3%), and a family history of T2DM (37.2%) were identified as predictors of the diagnosis of T2DM.@*CONCLUSIONS@#In this study, waist circumference and age were the most important predictors of T2DM. Due to the sensitivity, specificity, and accuracy of the final model, it is suggested that these variables should be used for T2DM risk assessment in screening tests.

Effects of human and organizational deficiencies on workers' safety behavior at a mining site in Iran / 한국역학회지

OBJECTIVES@#Throughout the world, mines are dangerous workplaces with high accident rates. According to the Statistical Center of Iran, the number of occupational accidents in Iranian mines has increased in recent years. This study investigated and analyzed the human and organizational deficiencies that influenced Iranian mining accidents.@*METHODS@#In this study, the data associated with 305 mining accidents were analyzed using a systems analysis approach to identify critical deficiencies in organizational influences, unsafe supervision, preconditions for unsafe acts, and workers' unsafe acts. Partial least square structural equation modeling (PLS-SEM) was utilized to model the interactions among these deficiencies.@*RESULTS@#Organizational deficiencies had a direct positive effect on workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.23). The effect of unsafe supervision on workers' violations and workers' errors was also significant, with path coefficients of 0.14 and 0.20, respectively. Likewise, preconditions for unsafe acts had a significant effect on both workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.21). Moreover, organizational deficiencies had an indirect positive effect on workers' unsafe acts, mediated by unsafe supervision and preconditions for unsafe acts. Among the variables examined in the current study, organizational influences had the strongest impact on workers' unsafe acts.@*CONCLUSIONS@#Organizational deficiencies were found to be the main cause of accidents in the mining sector, as they affected all other aspects of system safety. In order to prevent occupational accidents, organizational deficiencies should be modified first.

Effects of human and organizational deficiencies on workers' safety behavior at a mining site in Iran / 한국역학회지

OBJECTIVES: Throughout the world, mines are dangerous workplaces with high accident rates. According to the Statistical Center of Iran, the number of occupational accidents in Iranian mines has increased in recent years. This study investigated and analyzed the human and organizational deficiencies that influenced Iranian mining accidents. METHODS: In this study, the data associated with 305 mining accidents were analyzed using a systems analysis approach to identify critical deficiencies in organizational influences, unsafe supervision, preconditions for unsafe acts, and workers' unsafe acts. Partial least square structural equation modeling (PLS-SEM) was utilized to model the interactions among these deficiencies. RESULTS: Organizational deficiencies had a direct positive effect on workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.23). The effect of unsafe supervision on workers' violations and workers' errors was also significant, with path coefficients of 0.14 and 0.20, respectively. Likewise, preconditions for unsafe acts had a significant effect on both workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.21). Moreover, organizational deficiencies had an indirect positive effect on workers' unsafe acts, mediated by unsafe supervision and preconditions for unsafe acts. Among the variables examined in the current study, organizational influences had the strongest impact on workers' unsafe acts. CONCLUSIONS: Organizational deficiencies were found to be the main cause of accidents in the mining sector, as they affected all other aspects of system safety. In order to prevent occupational accidents, organizational deficiencies should be modified first.

Application of an artificial neural network model for diagnosing type 2 diabetes mellitus and determining the relative importance of risk factors / 한국역학회지

OBJECTIVES: To identify the most important demographic risk factors for a diagnosis of type 2 diabetes mellitus (T2DM) using a neural network model. METHODS: This study was conducted on a sample of 234 individuals, in whom T2DM was diagnosed using hemoglobin A1c levels. A multilayer perceptron artificial neural network was used to identify demographic risk factors for T2DM and their importance. The DeLong method was used to compare the models by fitting in sequential steps. RESULTS: Variables found to be significant at a level of p < 0.2 in a univariate logistic regression analysis (age, hypertension, waist circumference, body mass index [BMI], sedentary lifestyle, smoking, vegetable consumption, family history of T2DM, stress, walking, fruit consumption, and sex) were entered into the model. After 7 stages of neural network modeling, only waist circumference (100.0%), age (78.5%), BMI (78.2%), hypertension (69.4%), stress (54.2%), smoking (49.3%), and a family history of T2DM (37.2%) were identified as predictors of the diagnosis of T2DM. CONCLUSIONS: In this study, waist circumference and age were the most important predictors of T2DM. Due to the sensitivity, specificity, and accuracy of the final model, it is suggested that these variables should be used for T2DM risk assessment in screening tests.

Application of an artificial neural network model for diagnosing type 2 diabetes mellitus and determining the relative importance of risk factors / 한국역학회지

OBJECTIVES: To identify the most important demographic risk factors for a diagnosis of type 2 diabetes mellitus (T2DM) using a neural network model.METHODS: This study was conducted on a sample of 234 individuals, in whom T2DM was diagnosed using hemoglobin A1c levels. A multilayer perceptron artificial neural network was used to identify demographic risk factors for T2DM and their importance. The DeLong method was used to compare the models by fitting in sequential steps.RESULTS: Variables found to be significant at a level of p < 0.2 in a univariate logistic regression analysis (age, hypertension, waist circumference, body mass index [BMI], sedentary lifestyle, smoking, vegetable consumption, family history of T2DM, stress, walking, fruit consumption, and sex) were entered into the model. After 7 stages of neural network modeling, only waist circumference (100.0%), age (78.5%), BMI (78.2%), hypertension (69.4%), stress (54.2%), smoking (49.3%), and a family history of T2DM (37.2%) were identified as predictors of the diagnosis of T2DM.CONCLUSIONS: In this study, waist circumference and age were the most important predictors of T2DM. Due to the sensitivity, specificity, and accuracy of the final model, it is suggested that these variables should be used for T2DM risk assessment in screening tests.

Effects of human and organizational deficiencies on workers' safety behavior at a mining site in Iran / 한국역학회지

OBJECTIVES: Throughout the world, mines are dangerous workplaces with high accident rates. According to the Statistical Center of Iran, the number of occupational accidents in Iranian mines has increased in recent years. This study investigated and analyzed the human and organizational deficiencies that influenced Iranian mining accidents.METHODS: In this study, the data associated with 305 mining accidents were analyzed using a systems analysis approach to identify critical deficiencies in organizational influences, unsafe supervision, preconditions for unsafe acts, and workers' unsafe acts. Partial least square structural equation modeling (PLS-SEM) was utilized to model the interactions among these deficiencies.RESULTS: Organizational deficiencies had a direct positive effect on workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.23). The effect of unsafe supervision on workers' violations and workers' errors was also significant, with path coefficients of 0.14 and 0.20, respectively. Likewise, preconditions for unsafe acts had a significant effect on both workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.21). Moreover, organizational deficiencies had an indirect positive effect on workers' unsafe acts, mediated by unsafe supervision and preconditions for unsafe acts. Among the variables examined in the current study, organizational influences had the strongest impact on workers' unsafe acts.CONCLUSIONS: Organizational deficiencies were found to be the main cause of accidents in the mining sector, as they affected all other aspects of system safety. In order to prevent occupational accidents, organizational deficiencies should be modified first.

Public Awareness of Early and Late Complications of Type 2 Diabetes - Application of Latent Profile Analysis in Determining Questionnaire Cut-Off Points

OBJECTIVES: A questionnaire was designed to determine public understanding of early and late complications of Type 2 diabetes mellitus (T2DM). METHODS: A cross-sectional study was performed in participants who were selected using a multi-stage sampling method and a standard questionnaire of 67 questions was proposed. An expert panel selected 53 closed-ended questions for content validity to be included in the questionnaire. The reliability of the questionnaire was tested using Cronbach’s alpha coefficient giving a score of 0.84. RESULTS: Of the 825 participants, 443 (57.6%) were male, and 322 (41.87%) were 40 years or more. The proportion of low-, moderate- and high- awareness about T2DM and its complications was 29.26%, 62.68%, and 8.06%, respectively. Friends (56.31%) and internet and social networks (20.55%) were the 2 major sources of awareness, respectively. The medical staff (e.g., physicians) had the lowest share in the level of public awareness (3.64%) compared to other sources. CONCLUSION: These results present data that shows the general population awareness of T2DM is low. Healthcare policymakers need to be effective at raising awarenes of diabetes and it should be through improved education.

effect of Pender's health promotion model in improving the nutritional behavior of overweight and obese women

Background: Changes in lifestyle and eating habits have put women at risk of obesity and overweight more than ever. This aim of this study was to investigate the effect of Pender's Health Promotion Model [HPM] to improve the nutritional behavior of overweight and obese women admitted to Fatemiyeh Hospital clinics in Hamadan, west Iran in 2015

Methods: In this quasi-experimental study, 108 eligible women were selected and randomly assigned to two groups: one experimental and one control. Data were gathered using three questionnaires: demographics, Pender's HPM constructs, and nutritional behavior. The questionnaires were filled out by both groups as pre-test and two months later. A Pender's HPM-based intervention was conducted for the experimental group. The data were analyzed by paired and independent t-tests, ANCOVA, and Spearmans' correlation coefficient in SPSS/16. The level of significance was considered to be <0.05

Results: The mean score of nutritional behavior was 41.75+/-3.28 and 42.36+/-3.69 before the intervention and 79.09+/-5.27 and 49.72+/-9.49 after it in the experimental and control groups, respectively. The difference was significant only between before and after the intervention in the experimental group [P<0.001]. Furthermore, the mean scores of the following variables were significantly different between before and after the intervention in the experimental group: nutritional behavior, perceived benefits, perceived self-efficacy, commitment to action, interpersonal and situational influences, behavior-related affect, and perceived barriers [P<0.001]

Conclusion: The results showed that Pender's HPM-based training improved nutritional behavior and some constructs of the model. Therefore, this educative model can be used by healthcare providers to improve the nutritional and other health promoting behaviors

Surprising Incentive: An Instrument for Promoting Safety Performance of Construction Employees

BACKGROUND: In comparison with other industries, the construction industry still has a higher rate of fatal injuries, and thus, there is a need to apply new and innovative approaches for preventing accidents and promoting safe conditions at construction sites. METHODS: In this study, the effectiveness of a new incentive system-the surprising incentive system-was assessed. One year after the implementation of this new incentive system, behavioral changes of employees with respect to seven types of activities were observed. RESULTS: The results of this study showed that there is a significant relationship between the new incentive system and the safety performance of frontline employees. The new incentive system had a greater positive impact in the first 6 months since its implementation. In the long term, however, safety performance experienced a gradual reduction. Based on previous studies, all activities selected in this study are important indicators of the safety conditions at workplaces. However, there is a need for a comprehensive and simple-to-apply tool for assessing frontline employees' safety performance. Shortening the intervals between incentives is more effective in promoting safety performance. CONCLUSION: The results of this study proved that the surprising incentive would improve the employees' safety performance just in the short term because the surprising value of the incentives dwindle over time. For this reason and to maintain the surprising value of the incentive system, the amount and types of incentives need to be evaluated and modified annually or biannually.

Comparison of small area techniques for estimating prevalence of mental disorder symptoms among Iranian's southern adolescents

Mental disorders may lead to several complications in adolescents' people whose compensation is very difficult and sometime impossible. They are prone to emotional problems. Therefore, knowing prevalence of diseases and valid statistical technique is necessary to plan for prevention and control of diseases. In this cross-sectional study; direct, synthetic, and post-stratified estimation as small area methods were used to compute mental disorder symptoms [MDS] prevalence with county-level reference among adolescents in south of Iran. We conducted Mental Health Study data [MHS] conducted in Bushehr Province, southern Iran in 2005 for individual-level classification of MDS [n=2584]. Students were in grade 9, 10 and 11, and enrolled with complete satisfaction. The synthetic method was superior to the direct and post-stratified technique with respect to discrepancy statistics such as MSE and width 95% confidence interval [MSEs[synthetic]=0.001, MSEs[post-stratified]=0.010, MSEs[direct]=0.100]. In addition, the width range of 95% confidence intervals for all county estimates was 9.7% to 65.3% based on in direct methods. Besides, the width range of 95% confidence intervals for all county estimates under post-stratified and synthetic method was 16.7% to 62.2% and 11.8%-25.1%, respectively. Hence, we could categorize prevalence of mental disorder symptoms in Bushehr's counties into five categories based-on synthetic methods. Maximum and minimum prevalence belongs to Geneveh [0.403] and Dashty [0.398] counties, respectively. The MHS cannot be used as a valid source of county-level mental health prevalence data and the small-area method such synthetic method should be used to estimate prevalence of mental disorder symptoms in county-level. Furthermore, the synthetic method improved MDS prevalence more than direct and post-stratified methods

Prevalence and factors associated with methamphetamine use among adult substance abusers

The use of methamphetamine and other drugs among young adults has been a theme of growing interest and concern on the part of researchers and health associations. This paper reports recent use of methamphetamine and its relation with some demographic variables among substance users in west of Iran. This cross-sectional study was carried out on 559 substance users of Hamadan, western Iran recruited through a snowball sampling method in 2012. The participants received a self-administered questionnaire contained questions regarding substance use, reasons of drug abuse and pattern of MA use. Data were analyzed using SPSS software using Chi-square, Fisher's exact tests and logistic regression methods. A number of 248 [44.4%] people reported a history of having ever used methamphetamine and the mean drug abuse initiation age was 17.8 [SD= 3.9]. According to the history, reducing effect of previous drug and resurfacing of new drug were common reasons associated with the changes in previous drug to use of methamphetamine. In multivariate analysis, 'being single' and higher school were obtained as independent predictors of methamphetamine use [P<0.001]. Methamphetamine use is common among adult substance abusers in Iran. Demographic, behavioral and psychosocial correlates of methamphetamine use identified in this research may be helpful for the development of preventive interventions

[ study of reliability and validity of the teacher evaluation form and factors affecting student's evaluation of teachers]

Background and Objective: Evaluation is an essential process for educational institutions, and one of the most common methods of evaluation of teachers is evaluation by students. Students are the real customers in the educational process; therefore, their judgments should be important variables in determining teaching status of teachers. According to customer-centric principles, the consumer's satisfaction must be met. This study assessed the validation of the current teacher evaluation form in theoretical courses

Methods: This was a cross-sectional study investigating the validity and reliability of the teacher evaluation form that is completed by students, and identifying some factors affecting student evaluations. To determine content validity of the teacher evaluation form, 20 expert teachers were selected proportional to the number of teachers of each school of the Hamadan University of Medical Sciences. To assess the reliability coefficient of the form, 189 students were selected from different schools by proportional random sampling

Results: According to the results, questions such as rate of adherence to the determined topics, providing practical application of teaching materials, and the efficacy of determined assignments did not have the necessary validity score. However, the results indicated that validity of the questionnaire was acceptable. In the present study, the Spearmen-Brown correlation coefficient indicated that the teacher evaluation form did not have an acceptable reliability [r = 0.456, P < 0.001]

Conclusion: The current teacher evaluation form has an acceptable content validity, but it does not seem reliable

Noise annoyance due to construction worksites

Noise pollution can contribute to adverse health effects in humans. Noise annoyance and related problems, caused by noise emission during the progress of building construction, have become increasingly important. These problems can influence the exposed workers, as well as vicinity residents. The goal of the present study was to assess the noise annoyance due to noise from construction worksites among residents of Hamadan City [west of Iran]. In this cross-sectional study, 20 construction worksites and 140 near vicinity residents were selected. The main sources of construction worksite noise were diesel power generators, cutting and welding processes, heavy machinery [such as trucks] and transport of materials. Ambient noise levels were measured using a calibrated sound level meter, at each home of the residents included in the study. A noise annoyance questionnaire was employed for annoyance assessment. The majority of subjects had very high annoyance [87.1%]. The mean and SD of ambient levels were 74.57 +/- 7.12 dB [A] which exceeded the acceptable recommended level for residential areas. The most common problems among the participants were disturbance in sleep, difficulty in reading and distraction. Results showed significant relationship between noise annoyance and some factors including residing which floors had highest annoyance [F=13.22, P<0.001] and ambient noise [F=11.313, P<0.001]. High levels of noise annoyance among near vicinity residents who are affected by construction activities. This means that construction activities and other noise related sources should be regarded as the major source of ambient noise leading to noise annoyance

relationship between salivary beta-2 microglobulin and uremia intensity in men with chronic renal failure

This study defines the relationship between salivary beta-2 microglobulin [beta 2-M] and intensity of uremia in male patients diagnosed with chronic renal failure [CRF]. In total of 42 males were enrolled in a case-control study. There were 21 cases of CRF and 21 control cases. We collected 10cc of saliva plus 5 cc of blood from all patients to determine beta 2-M, blood urea nitrogen [BUN] and creatinine [Cr] levels. There was a correlation between the level of serum BUN and salivary urea in controls and patients, which was statistically significant for controls [p=0.028].The correlation between serum and salivary Cr was 0.195 in controls [p=0.398] and 0.598 in patients [p=0.006], which was statistically significant in patients. The correlation between serum and saliva was 0.133 [p=0.566] in controls and 0.078 [p=0.737] in patients, which was not statistically significant. The correlation between serum BUN and beta 2-M was 0.168 [p=0.469] in the control group and 0.629 [p=0.002] in patients, which was statistically significant in patients. The correlation between serum Cr and beta 2-M was 0.110 [p=0.635] in the control group and 0.678 [p=0.001] in patients, which was statistically significant in patients. The correlation between serum BUN and salivary beta 2-M was 0.093 [p=0.0690] in controls and 0.152 [p=0.152] in patients, which was not statistically significant. The correlation between serum Cr and salivary beta 2-M was 0.072 [p=0.070] in the control group and 0.286 [p=0.209] in patients, which was not statistically significant in either group. The results of the study indicated that salivary beta 2-M cannot be used as a non-invasive indicator to detect the severity of renal failure

[ effectiveness of behavioral pain scale in the pain assessment of patients with low level of consciousness]

Pain diagnosis is a frustrating effort especially due to the barriers in communication with patients in low level of consciousness; therefore this study ,aimed at the evaluation of utilizing BPS by nurses for patients who are unable to express their pain because of their low level of consciousness, has been designed. This research is a semi-empirical study on sixty eight nurses chosen with a census method from the staff of ICU in selected hospitals of Hamadan University of Medical Sciences. The subjects' abilities in diagnosis and determining the intensity of pain have been measured in three phases of resting, changing position and secretion suction in ICU patients before and after utilizing behavioral pain scale [BPS]. In Resting phase%25.5 in BPS pre-training,%56 in BPS post training, in changing position phase%58 in BPS pre-training,%76 in post training, and in secretion suction phase%60 in BPS pre-training and%80 in BPS post training of the nurses were able to determine the pain intensity. After being trained, also the number of the nurses who reported the intensity of pain in the mentioned phases was increased compared to BPS pre-training. [P<0/05]. The results of this study in utilizing BPS indicate that this scale has been effective in diagnosing and monitoring pain in patients with low levels of consciousness Therefore teaching and utilizing this kind of scale can be effective to raise the quality of medical treatment and pain management in ICU

Association between physical activity and mental health among high-school adolescents in Boushehr province: a population based study

Mental health is one of the evaluating factors of community indicators, and physical activity is considered an important tool for the importance of public health. Previous studies have demonstrated associations between physical activity and mental health, but these studies did not include those populations in which training children have some traditional and religious aspects. Multiple logistic regression analyses were used to compare the prevalence of mental health among those who had inactive, minimally and HEPA activity in a representative sample of adolescents aged 15-19 in South of Iran using data from the Mental Health Survey [n = 2584]. The GHQ-28 and IPAQ-short forms were used to evaluate the mental health and physical activity, respectively. A total of 2584 adolescents [1401 male and 1178 female] participated in the study. The observed odds of psychological symptoms in boys compared to girls is 1.2 times [p=0.018]. We observed that HEPA-activity decreases odds of somatic distress and social dysfunction compared with inactivity [p=0.031 and 0.001, respectively]; minimally activity decreases odds of anxiety compared with inactivity [p=0.038]; but physical activity rate was not affected on odds of adolescents' depression [p>0.05]. Physical activity decreases mental health subscales except for depression among adolescents in Boushehr, southern city of Iran

Birth distance influential factors: a multilevel recurrent events approach

The study was developed in order to find a subset of potential factors, which affect birth distance pattern, regarding consideration on correlation of events of birth in a family and correlation within clusters/centers which other studies omit these correlations. Referring to documents that were registered for family in the health care centers on socio-economical zone, we consider the families with at least one successful birth. Data were drawn from four health care centers, which selected via 27-health center in Hamedan City, western Iran, each from a socio-economic zone. It was expected, same socio-economic status family have same specific birth distance and a family follows a specific pattern. The multilevel recurrent approach was conducted to analyze the sample. The sample was 480 families and 1115 birth events occurred in these families. The final step model shows that significant factors on the birth distance time were mothers job [P=0.018]. The random effect of second level [clusters/centers] was significant [P=0.038]. In other words, the socio-economic of family affects on the birth distance patterns. Other potential variables were not significantly affected birth distances and were deleted from the final model. There are many potential factors, which may affect to birth distance, but multilevel recurrent event model has a better fit to data because of frailty and center effects. Application of other model such as Cox and frailty models may result in misleading reports