The socioeconomic variables have a strong impact on the decision-making and physical movement of women, worldwide studies suggest the same. In this study, we have tried to know the various determinants of women’s autonomy. We have taken the data from the fourth round National Family Health Survey (NFHS) (2015-16), published by the International Institution on Population Sciences (IIPS). For the statistical analysis, we used basic descriptive statistics and cross-tabulation between the socioeconomic variables and autonomy responses. Later to predict the occurrence of various autonomy aspects, binary logistic regression has been used with various socioeconomic variables. After getting the results, it has come to know that women’s decision-making and freedom of movement-related autonomy are largely influenced by socioeconomic variables. Major findings stated that with increasing age of women, autonomy increases. Women who belong to the rural setup have a low level of autonomy. From a religious perspective, women from the Muslim community have lower autonomy. Apart from these women have higher education, employed and in rich households have a higher likelihood of autonomy. Based on the outcomes, it is clear to us that women’s autonomy is largely influenced by their socioeconomic condition.
Gender inequality remains a pervasive problem, with cultural, traditional and ideological factors as well as religious interpretations, contributing to differences and inequalities between men and women. These differences can lead to gender disparities in the division of labor and the undervaluation of women’s contributions in various aspects of life. This study aims to explore the social situation of rural women in Morocco, with a particular focus on the Taounate Province in the country’s northern region. The paper investigates whether rural women and girls have been adequately considered in governmental actions and development initiatives, and if so, whether these initiatives effectively benefit them. Additionally, the study assesses how these actions may contribute to or hinder the success of development in rural areas. Ultimately, this research sheds light on the challenges and opportunities are faced by rural women in Taounate Province and provide insights into potential solutions to address the gender disparities that continue to exist in these communities.
The present research was aimed to evaluate the educational potentiality of southern states of India using a new innovative Composite Education Index (CEI). An integrated seven step procedure was followed for the calculations of CEI. After preparing a composite hierarchical structure using two parameters, ten criteria and twelve indicators, the Analytical Hierarchy Process (AHP) and weighted sum technique were applied to get the CEI. The lowest category of CEI was marked with 20.573% area, the low category with 27.817% area, the moderate category with 20.771% area and the highest category were marked with 30.839% area of the study region. Further, the CEI was compared with School Education Quality Index (SEQI) and a high R-square value of 97.3% was obtained. Therefore, the CEI can be utilized to measure educational potentialities without hesitation. A large number of indicators are merged in this index, and it is flexible and easy to implement in any region.
Low Back Pain (LBP) is considered one of the most frequently reported causes of visits to healthcare establishments. In India, the prevalence of LBP is alarming with approximately 60% of people suffering from LBP. It has been observed that most people have experienced back discomfort at least once in their lives. Globally, LBP features amongst work-related disorders as a frequently prevailing issue in occupational settings. In the Indian scenario, the prevalence of LBP is generally found to be gender-specific. Females are reported to suffer more from LBP than males in the same working environment. Recent research suggests that school teachers exhibit a higher prevalence of LBP issues. Therefore, the present study focuses on enquiring about the occurrence of LBP and understanding the associated risk factors among female teachers. Simple random sampling is used to identify schools in 5 urban units of the Srinagar district. Binary logistic regression is employed to identify the risk factors, both at the workplace and at home. Married females (58.33 %) complained of LBP more than unmarried ones. At the workplace, prolonged standing (40%) was the most common self-reported risk factor for LBP. In general, prolonged standing, teaching hours, and mental health were found to be the three statistically significant risk factors contributing to LBP at the workplace. Amongst all the activities at home, domestic chores carried out by females (married and unmarried both) were the highest self-reported risk factor (78%), married women at 82.14% and unmarried women at 75.9%. The same was found statistically significant along with the additional factor being professional work done at home. The study establishes the need for a comprehensive strategy and preventive interventions in lowering the prevalence of LBP disability, especially among teachers, given the immense role they play in shaping our society.
The spatiotemporal fluctuation of Surface Soil Moisture (SSM) is important for prediction of weather, modeling of hydrological cycle, water management, agricultural managing and making strategy. Optical remote sensing has demonstrated significant promise for precise surface soil moisture estimate. The study aimed to estimate the moisture content in the upper layer of agricultural fields using Landsat 8 OLI, Sentinel-2A multi-spectral satellite data as well as TVDI [Temperature Vegetation Dryness Index] data. The spatial resolution of the Landsat OLI and Sentinel-2A images was 30m and 10m, respectively. The spectral Thermal Infrared (TIR 10.9µm ), TIR (10.9µm) and along with the Short-Wave-Infrared (SWIR 2.2µm) band of the Landsat 8 and the Shore-Wave-Infrared (SWIR 2.2 µm) band of sentinel 2B satellite imagery was utilized to estimate how moist was topsoil of the agricultural lands. The soil moisture estimates using remote sensing based model were acquired and compared with in-situ soil moisture. In a depth of 10cm below the surface, the field-based soil moisture was measured. Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and TVDI were measured to estimate moisture content. The reflectance values of the TVDI show over the study area generally low, with the values ranging from -0.07 to 1.37. The statistical tests of TVDI values and gravimetric soil moisture values presented a positive correlation with RMSE= 0.17. The results of the study can give insight of better hydrological modeling, management of agriculture and policy making. However, further research is required to validate the methodology over a larger geographical area and to evaluate the preciseness of the assessed SSM at various depths of the soil.