Rural areas

Purpose - With increasing governmental revenue and budgets, their responsibility for community development and growth has increased. The first step to policy-making in order to attain the desired welfare levels is identify and measure the related indicators such as poverty in the best possible way. In Iran, most of conducted poverty surveys due to the lack of panel data cannot decompose households to transient and chronic poverty group. In this situation, the Synthetic panel data is a useful and new approach to estimates of poverty mobility in countries with only cross-sectional statistics. Therefore, based on this method we calculated the poverty dynamic of rural areas in Iran. Design/methodology/approach - The present study, initially calculates the absolute poverty line of rural areas in Iran in 2012, 2015 and 2016, and then calculates the status of mobility of poverty during those years based on Synthetic panel data approach. Finding- The results of the estimation of probability functions for studying poverty dynamics indicated that in rural areas of Iran there was a kind of state dependence in poverty. According to the results, there is a dependency state in the rural poverty situation, where more than 86% of the households who were poor in 2016 were also poor (non-poor) during the first period (2012 or 2015) and only with the probability of less than 14% of the poor (non-poor) households during the past years was in the non-poor (poor) state.

Purpose - Quality and living conditions of humans are heavily reliant on their housing. A suitable shelter will prevent illness and damage to a large extent and plays a crucial role in promoting people's mental and physical condition. This study seeks to analyze and evaluate the effects of improving the quality of housing on promoting the physical and mental health of villagers. Design/methodology/approach - This is an applied research that adopts a descriptive-analytical method. The main data collection instrument is a questionnaire. The studied area is Shandiz district in Binalud town, Khorasan Razavi Province. The statistical population of this research consists of 11 villages, which according to 2017 Census accommodated 5921 households. The sample size was estimated at n=190 using the Cochran formula with an error of 0.07%. Data gathering tool comprised interview, field questionnaire and observation. The questionnaire items were designed based on a Likert scale. For the analysis of data, descriptive and inferential statistics (Pearson correlation test, single sample t-test and regression) were used in the SPSS software. The villages were ranked by WASPAS analysis (the weighing in WASPAS analysis is based on entropy). Findings - The results of Pearson correlation test showed that the quantitative (0.549), physical (0.513), the socio-cultural (0.505), and the environmental (0.522) dimension were significantly correlated with mental- psychological health. With regard to the physical health, there was only a direct and weak relationship with the physical dimensions (0.149). As for the health variable, the quantitative (0.651), physical (0.623), socio-cultural (0.605) and environmental (0.596) dimensions had a strong direct relationship, meaning that as dimensions of the quality of housing improves, the health of villagers is affected and their physical and mental health is promoted. The results of pathway analysis showed that among independent variables (quantitative, physical, socio-cultural and environmental variables) the quantitative dimension had the highest effect on dependent variable (physical and mental health) with a value of 0.564. Practical implications - According to the results, improving the quality of housing will promote the mental and psychologic health of villagers. Originality/value - Selecting a suitable rural housing model can definitely yield positive outcomes for promotion of health standards both in physical and mental dimensions.