Journal of Biostatistics and Epidemiology
Volume:3 Issue: 1, Winter 2017

Pemphigus vulgaris (PV) with painful blisters and erosions on skin and mucosa can significantly impair patient’s social life. There are few studies that have focused on the socioeconomic status (SES) of these patients. The aim of this study was to evaluate the SES of newly diagnosed PV patients who were referred to our clinic.
Methods & Materials: A total of 153 patients with PV participated in this case–control study. Among them, 58 patients had the disease for Level indicator of the family socioeconomic was 13.10 ± 6.08 (range 6-28) and 19.32 ± 6.24 (range 9-33) in the case and control groups, respectively. The difference between these two groups was statistically significant (P 0.00100). There was an association between socioeconomic level and forbearing of some of their diagnostic or treatment process (P = 0.00900). Comparison between patients from urban and rural area showed that patients from rural area had significantly lower level of socioeconomic (P = 0.00698). Comparing new onset PV patients with those with disease > 1 year did not show any significant difference (P = 0.41000) .
SES of PV patients was significantly lower than controls, and this difference was not related to disease duration. This situation was more significant in rural patients. Hence, by recognizing these groups, we could help them more effectively.

In clinical dental studies, each participant has usually several visits, and since the review and ongoing monitoring of the subjects are often expensive or even impossible, so people are examined periodically during regularly pre-scheduled visits. Therefore, discrete or grouped clustered failure time data are collected. We aimed to show the use of Monte Carlo Markov Chain (MCMC) and the non-informative prior in a Bayesian framework in multilevel modeling of clustered grouped survival data.
Methods & Materials: A two-level model with additive variance components model for the random effects was considered. Both the grouped proportional hazards model and logistic regression with logit link function model were used. Using grouped proportional hazards method, we could approximate intracluster correlation of the log failure times. The statistical package OpenBUGS was adopted to estimate the parameter of interest based on the MCMC method. A cohort study was used in which 1011 persons visited at clinic dentistry of Tehran University of Medical Sciences, Iran, between the years 2002 and 2013 for dental implant and 2368 implants were placed for them in total. Clinical status of dental implants was evaluated in three periods after placement, thus clustered grouped failure times of the dental implants were recorded.
The grouped proportional hazards model showed that clustering effect among the log failure times of the different implants from the same person was fairly strong (correlation = 0.99). Complication and biomaterial variables had no effect on the implant failure, and there was no difference in the failure times related to the molar, premolar, canine, primary, and incisor since 95% credible interval (CI) included 0. The CI related to the gender and place of teeth not including 0, so these variables were significant in the model. The estimates of the baseline parameters (γ1, γ2, and γ3) were increasing indicating increasing hazard rates from interval 1-3. Results of logistic regression were similar to grouped proportional hazards model with wider confidence intervals.
The use of MCMC approach and non-informing prior in Bayesian framework to mimic maximum likelihood estimations in a frequentist approach in multilevel modeling of clustered grouped survival data can be easily applied with the use of the software OpenBUGS

Changes in the trend of births among women have been studied worldwide with indications of peaks and troughs over a specified period. Periodic variations in the number of births among women are unknown at the Korle-Bu Teaching Hospital (KBTH). This study sought to model and predicts monthly number of births at the Department of Obstetrics and Gynaecology (O&G), KBTH.
Methods & Materials: Box-Jenkins time series model approach was applied to an 11-year data from the Department of (O&G), KBTH on the number of births from January, 2004 to December, 2014. Box-Jenkins approach was put forward as autoregressive integrated moving average (ARIMA) model. Several possible models were formulated, and the best model, which has the smallest Akaike information criterion corrected (AICc) was selected. The best model was then used for future predictions on the expected monthly number of births for the year 2015. Analysis was performed in R statistical software (version 3.0.3).
Seasonal ARIMA (2,1,1) × (1,0,1)12 was selected as the best model because it had the smallest AICc. Furthermore, the forecasted values showed that the expected number of births were lowest in January (750 births) and highest in May (970 births) for the year 2015.
Seasonal ARIMA (2,1,1) × (1,0,1)12 was identified as the model that best describes monthly expected births and its use to forecast the expected number of births at the KBTH in Ghana will facilitate formulation of health policies and planning for safe maternal delivery and prudent use of hospital obstetric services and facilities.

Health locus of control (HLC) is a construct that refers to how person’s beliefs influence on his/her health. The aim of this study was to assess the reliability and construct validity of multidimensional HLC (MHLC) scale in a representative Iranian samples.
Methods & Materials: This cross-sectional study was done among 881 subjects over 15 years old in Bandar Abbas, in the south of Iran through cluster sampling. Translated Persian version of MHLC questionnaire was administered to participants. Data were analyzed using confirmatory factor analysis (CFA) to compare three different models. Multiple groups CFA were conducted to examine the measurement equivalence across gender (390 men and 391 women) in EQS software. Reliability assessment was done by Cronbach’s α coefficient in SPSS v.16 software.
Based on CFA, 18-item with three correlated factor had good fit (goodness-of-fit index = 0.92 and comparative fit index = 0.9). The results established full configural, metric, and scalar invariance across gender. Cronbach’s α for subscales was ranged from 0.65 to 0.74.
Eighteen items Persian version of MHLC scale in three oblique subscales was introduced as a valid and reliable tool for assessing HLC among the general population in Iran. Furthermore, it is derived that the MHLC was full invariant across gender.

Dear Sir,1
There is growing interest in applying e-health approaches to prevent and control of the diseases and their risk factors (1). Using electronic information and communication technologies for health provide immediate and tailored feedback, cost-effective outcome and have the potential for widespread reach for high risk and hard reach populations (2). The internet, on the one hand, provides a powerful tool in unique opportunity to identify, management and prevention of the diseases, and on the other hand it as an interactive tool increases knowledge about the diseases, risk factors, and offer approaches to deal with health problem (3). Internet-based health technologies are becoming increasingly available for the rapid identification of the risk factors and also for the more accurate monitoring of non-communicable disease activity. Web-based surveillance tools and e-screening intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely detection (1, 4). E-screening provides real-time scoring of screen for professionals and patients. E-screening was used for non-communicable risk factors and lifestyle (5-7). E-screening has the potential to
* Corresponding Author: Leila Jahangiry, Postal Address: Department of Health Education and Health Promotion, School of Public Health, Tabriz University of Medical Sciences, Tabriz, Iran. Email: Jahangiry@razi.tums.ac.ir
increase the efficiency of mental health care by reallocating limited human resources where they are most needed in-depth follow-up assessment, referral, and treatment (8). The web-based healthy lifestyle education, focused on healthy nutrition and exercise, can lead to improvements in general health (9). There is substantial evidence showing that use of web-based interventions improves behavioral change outcomes. These outcomes included increased exercise time, increased knowledge of nutritional status, increased knowledge of asthma treatment, increased participation in health care, slower health decline, improved body shape perception, and 18-month weight loss maintenance (10). According to Rose (11) general population and at-risk population is accessed to screening and intervention tools. According to Rose (11) general population and at-risk population screening is used to detect certain individuals who were well but they must know that they are in high-risk conditions. It seems that the web can act as a relatively simple approach for diagnosing the risk factors of high prevalence diseases such as cardiovascular diseases. Metabolic syndrome that defines as clustering of risk factors might be provided in the prevention through web due to easily measurable risk factors. In addition, it seems that selfmeasurement of waist circumference is easy to perform and it is known in related to cardiovascular diseases (12). Thus, from a public health point of view, early identification of high risk and difficult to reach individuals
Journalthrough the internet is an important issue, especially in primary care.