The aim of the study was to investigate the attitudes of people concerning second-hand products and to find out about the management of these products. The informants were three sellers from Thailand and five customers from Indonesia, Nepal, Nigeria, Bhutan, and Thailand. The research employed as qualitative method using mainly in-depth interviews and the data was analyzed by content analysis. Two second-hand product categories clothes and other products were mentioned in this study. The results showed that there were two terms of attitudes regarding second-hand clothes including acceptance and rejection. The sellers had a positive attitude towards second-hand products because of good profits, while the customers had concerns about sanitation/hygiene. The second-hand management practices for sellers were a cyclic process where they re-sell the same goods repeatedly, while the people included the customers from this study donated their unwanted goods for selling since the donation is an attractive way to reduce unused belongings. Keywords: second-hand product, attitude, management, acceptance, rejection, sanitation

Background Survey data from low income countries on birth weight usually pose a persistent problem. The studies conducted on birth weight have acknowledged missing data on birth weight, but they are not included in the analysis. Furthermore, other missing data presented on determinants of birth weight are not addressed. Thus, this study tries to identify determinants that are associated with low birth weight (LBW) using multiple imputation to handle missing data on birth weight and its determinants. Methods The child dataset from Nepal Demographic and Health Survey (NDHS), 2011 was utilized in this study. A total of 5,240 children were born between 2006 and 2011, out of which 87% had at least one measured variable missing and 21% had no recorded birth weight. All the analyses were carried out in R version 3.1.3. Transform-then impute method was applied to check for interaction between explanatory variables and imputed missing data. Survey package was applied to each imputed dataset to account for survey design and sampling method. Survey logistic regression was applied to identify the determinants associated with LBW. Results The prevalence of LBW was 15.4% after imputation. Women with the highest autonomy on their own health compared to those with health decisions involving husband or others (adjusted odds ratio (OR) 1.87, 95% confidence interval (95% CI) = 1.31, 2.67), and husband and women together (adjusted OR 1.57, 95% CI = 1.05, 2.35) were less likely to give birth to LBW infants. Mothers using highly polluting cooking fuels (adjusted OR 1.49, 95% CI = 1.03, 2.22) were more likely to give birth to LBW infants than mothers using non-polluting cooking fuels. Conclusion The findings of this study suggested that obtaining the prevalence of LBW from only the sample of measured birth weight and ignoring missing data results in underestimation.

The presented study aims to classify precipitation regions, analyze trends, and fit an appropriate model for daily precipitation in Thailand. Factor analysis and generalized linear model (GLM) with gamma regression are performed on the historical records of daily rainfall amounts from 114 weather stations during 2001 to 2012. The study shows that the factor analysis divides the area of Thailand into seven regions with explanation of 58.9% of the total variance. The conducted gamma models reveal a good fit for the upper part, south-east, and south-west of the examined regions. The deviance residual plots from these models also provide a reasonable fit.

The Southern Oscillation Index (SOI) has been used as a predictor of variables associated with climatic data, such as rainfall and temperature, and is related to the El Nino and La Nina phenomena, also called the El Nino Southern Oscillation (ENSO). The present study aims to describe the characteristics of the SOI between 1876 and 2014 using statistical methods. The graph of the cumulative monthly SOI in the period 1876 - 2014 shows that the data can be divided into 4 periods. The first period, from 1876 to 1919, shows no trend. An increasing trend is apparent in the second period from 1920 until 1975, while a decreasing trend is apparent in the third period, 1976 to 1995. In the last period, between 1996 and 2014, the SOI appears fairly stable. In order to investigate those trends, the linear regression and autoregressive (AR) model have been fitted. For the linear regression model, the outcome, SOI, is regressed against boxcar function, where the functions model the trends of the SOI. An autoregressive process is used to account for serial correlation in the residuals. The conclusion is that the SOI is quite similar to a random noise process.

We consider methods for modeling and comparing incidence rates of adverse events that vary over space, time and demographic characteristics of subjects including gender and age group. We assume that the adverse events and their corresponding population-at-risk denominators are aggregated into a contingency table whose dimensions correspond to the spatial, temporal and demographic factors. We compare regression models for Poisson and negative binomial generalized linear models with zero-corrected log-transformed linear models. These methods are applied to the terrorism events in regions of Southern Thailand that occurred over the period from 2004 to 2010.

We investigated statistical models for describing the incidence rate of injuries to civilian resident victims of violence from terrorism in Pattani, Yala and Narathiwat provinces and four eastern districts of Songkhla province. For six years, there were 4,143 Muslim residents and 3,544 other (mainly Buddhist) residents of the target area have been recorded as victims by the Deep South Coordination Centre (DSCC). The overall incidence rates per 100,000 residents are 48 for Muslims and 121 for non-Muslims. We focused on the Muslim population and fitted negative binomial and log-normal models to incidence rates classified by gender, age group, region and year, with comparing relative risk by these factors, after adjusting for other factors to remove confounding. The models gave different results and showed that while specific regions were at higher risk at different times and these patterns could not be easily predicted, risks in different demographic groups remained relatively constant.

A method for modeling and graphically comparing incidence rates of adverse events that vary over geographical regions is shown and discussed. To achieve our goal, we used a statistical model to compare incidence rates and showed how informative three-dimensional graphs of such incidence rates can be created dynamically using R and interactively controlled using Google Earth with Keyhole Markup Language (KML). These methods are applied to the terrorism events in regions of Southern Thailand that occurred from 2004 to 2009.

Background: The deep south of Thailand is an area which has been affected by violence since 2004, yet the concurrent coverage of antenatal care has remained at over 90%. Our study aimed to describe the prevalence of nutrient inadequacy among pregnant women who attended antenatal care clinics in hospitals in the study area and assess factors associated with nutrient inadequacy.Methods: Pregnant women from four participating hospitals located in lower southern Thailand were surveyed during January-December 2008. Nutrient intake was estimated based on information provided by the women on the amount, type and frequency of various foods eaten. Logistic regression was used to assess individual and community factors associated with inadequate nutrient intake, defined as less than two thirds of the recommended dietary allowance (RDA).Results: The prevalence of carbohydrate, protein, fat, calories, calcium, phosphorus, iron, thiamine, riboflavin, retinol, niacin, vitamin C, folic acid and iodine inadequacy was 86.8%, 59.2%, 78.0%, 83.5%, 55.0%, 29.5%, 45.2%, 85.0%, 19.2%, 3.8%, 43.2%, 0.8%, 0.0% and 0.8%, respectively. Maternal age, education level, gestational age at enrolment and pre-pregnancy body mass index and level of violence in the district were significantly associated with inadequacy of carbohydrate, protein, phosphorus, iron, thiamine and niacin intake.Conclusions: Nutrient intake inadequacy among pregnant women was common in this area. Increasing levels of violence was associated with nutrient inadequacy in addition to individual factors.

In statistical studies, generalized linear models (GLMs) are usually preferred for modeling incidence rates, often with extensions to zero-inflated GLMs when the proportion of zero counts is large. However Warton has shown that for many ecological studies, simple linear models fitted to log-transformed counts do surprisingly well. In this study, we used data comprising a sizable set of pneumonia incidence rates. We compared the negative binomial GLM with a log transformed linear model, and found further support for this simpler alternative method.

The transmission of malaria in Thailand is common, particularly in the North-western region of the country. The objective of this study is to identify the patterns of hospital-diagnosed malaria incidences in districts and quarterly periods in the North-western region of Thailand in 1999-2004. Regression models based on principal components describe these patterns. The models show trends and spatial variations in disease incidence. Graphical displays showing both regional and period effects are presented. The results of this study show that malaria incidence rates decreased substantially in most districts during the study period, but remained very high in border districts with Myanmar.

The primary purpose of this study was to analyze the internal consistency and construct validity of a classification of bullying outcomes, and to investigate the risk factors associated with bullying behaviour at Pattani primary schools, southern Thailand. A cross-sectional study was conducted with a sample of 1,440 students. Factor analysis, descriptive statistics, Pearson’s chi-squared test, and logistic regression were used for data analysis. The results showed that 20.9% of students in Pattani primary schools reported having bullied others. A four factors structure of bullying was clearly shown; serious, general physical, psychological-maligning parent and psychological-maligning student. Witnessing parental physical abuse was clearly the most strongly associated determinants, and much more strongly linked to bullying others than was the group who had never witnessed parental physical abuse (OR 7.60, 95% CI 5.60-10.31). The students who preferred action cartoons were more often bullies than were those who preferred comedy cartoons (OR 2.87, 95% CI 1.91-430).

This study aimed to investigate the prevalence of physical bullying and to identify a suitable statistical model accounting for risk factors affecting physical bullying among lower secondary school students in Pattani province, southern Thailand.A cross-sectional survey was conducted among 244 students aged 12 to 19 years by questionnaire.All participants were interviewed in December 2006 in a neutral location outside the schools.Questions on physical bullying referred to behaviour during both the preceding six months and during the previous month.Pearson's chi-squared test was used to assess the associations between the outcome and various determinants.Logistic regression was used to identify risk factors for physical bullying.The overall prevalence of physical bullying was found to be 18.5% (95% CI: 13.6-23.4).Gender was not significantly associated with bullying others.The outcome was associated to a statistically significant degree with age group, ethnicity, school type and parental violence.Specifically, the results from this study indicated that students who had experience of parental violence were more likely to be bullies at school.

This study proposed a graphical method for displaying informative confidence intervals for any data set involving a categorical determinant, an outcome that could be either continuous or categorical, and an optional covariate. For continuous outcomes the graph is similar to the conventional plot of confidence intervals for individual means, but focuses on specified natural contrasts. The analogous graph for categorical outcomes involves graphing confidence intervals for specified natural odds ratios. In each case the method can be extended to include a covariate, and the extent of confounding can be illustrated on the graph. The confidence intervals are adjusted for multiplicity.

This study is based on the individual hospital case records of malaria routinely reported from 1999 to 2004 in the North-western area of Thailand, which included Mae Hong Son and Tak provinces. The objective of this study was to model the patterns of hospital-diagnosed malaria incidences by month, district and age-group for the two North-western border provinces in Thailand. The model used linear regression, Poisson regression and negative binomial regression to forecast the districts and age groups in which epidemics are likely to occur in the near future in order to prevent the disease by using suitable measures. Among the models fitted, the best were chosen based on the analysis of deviance and the negative binomial generalized linear model was clearly preferable. The model contains additive effects associated with the season of the year, district, age group and the malaria incidence rates in previous months, and can be used to provide useful short-term forecasts. Having a model that provides such forecasts of disease outbreaks, even if based purely on statistical data analysis, can provide a useful basis for allocation of resources for disease prevention.

To study the prevalence and predictors of physical abuse among pregnant women in Pattani Hospital, Pattani, Thailand. A total of 611 women receiving antenatal clinic services through Pattani Hospital between July 1, 2002 and November 21, 2002 were interviewed. Information was collected on the women’s sociodemographic characteristics, experience of abuse, demographic characteristics of their partners, partner’s smoking habit and use of alcohol. The women’s experience of abuse was assessed by a questionnaire modified from the Abuse Assessment Scale (AAS). In all, 99 (16.2%) women reported experiencing past physical abuse (during a prior pregnancy or during the preceding year), 24 (3.9%) reported experiencing physical abuse during their current pregnancy, and 58 (9.5%) reported experiencing physical abuse both in the past and during their current pregnancy. Physical abuse was associated with parity, marital status, length of relationship, women’s education, smoking habit and the use of alcohol by their partner. After adjustment for confounding factors, the strongest risk factor for physical abuse during pregnancy was partner with a drinking problem. Women whose partner had a drinking problem were more likely to experience abuse during their current pregnancy than those whose partners did not have a drinking problem. In this study, one in eight pregnant women experienced physical abuse during current pregnancy. All types of abuse should be routinely ascertained in antenatal clinics.

In this cross-sectional study, 8,481 women aged 15-49 who had at least one pregnancy outcome were considered. This study aimed to examine the characteristics of Filipino women having had a pregnancy loss, and to test the association between domestic violence and pregnancy loss. To control for the confounding effect of the number of pregnancies, the sample was divided into seven groups classified by the number of pregnancies. The risk factors considered were demographic characters (age and partner's age, marital status, and place of residence), socioeconomic status (education and partner's education, having a paid helper at home, having a say in how income was spent), domestic violence (physical abuse and forced sex), sexual behavior of partner, whether the pregnancy was wanted, and disease history (tuberculosis, diabetes, hypertension, malaria, hepatitis, kidney disease, heart disease, anemia, goiter and other medical problems). The major risk factors were found to be physical abuse, region, faithfulness of partners, hypertension, hepatitis, kidney disease, anemia, and the other medical problems, respectively. The risk of pregnancy loss for the women suffering domestic violence was 1.59 (95% CI 1.28-1.97) times higher than for the women who did not. Women aged 15-19 years had a much higher risk of pregnancy loss than the other age groups (OR = 1.49, 95% CI 1.22-1.82). There were similar risk for women aged 20-24 years (OR = 1.08, 95% CI 0.94-1.25) and 35-39 years (OR = 1.05, 95% CI 0.92-1.19). No association emerged with marital status, socioeconomic status, forced sex, the number of partners, unwanted pregnancy, tuberculosis, diabetes, malaria, heart disease, and goiter. Although women's age, partner's age, residence, women's education, partner's education, and paid helper at home were significantly associated with pregnancy loss, they were likely to be confounders rather than risk factors.