Investigation of quality of life indicators by Structural Equation Modeling in the city of Sarpol-e Zahab

Extended Abstract

Introduction

Today, quality of life studies have mainly focused on the urban environment and the quality of urban life and its study is of great necessity and importance (Ebrahimzadeh and Karbakhsh, 2017: 8). Urban areas are always faced with important issues in the areas of social deprivation, unemployment, housing shortages, insecurity, etc., which have severely affected the quality of urban life. Irregular physical growth of cities, changes in the socio-economic structure, traffic and pollution, quality of housing, the existence of parallel organizations in the management of urban centers and the lack or improper distribution of recreational spaces have caused a decline in quality of life in urban centers. Today, with the expansion of cities and increasing inequalities, quality of life studies have become an important tool for planning and managing cities (Alavi et al., 2018: 2). For urban planners, managers, and policymakers, especially cities that shape the quality of life of citizens, the core of the planning process and policy decisions, the study of quality of life by identifying problem areas and discovering the causes of citizens' dissatisfaction, factors Social, economic and environmental factors affecting the quality of life, citizens' priorities in life and monitoring and evaluating the effectiveness of urban policies and strategies, have a significant share in the formulation of urban strategies and policies (Hatami Nejad et al., 2013: 30). Due to the importance of quality of life, this study examines the status of quality of life indicators using structural equation modeling in Sarpole Zahab.



Methodology

The method of the present study is applied in terms of purpose and descriptive-correlational in terms of method. The statistical population is the citizens of Sarpolzahab city. According to the size of the population (N = 45481), 381 of these people were calculated using the Cochran's formula and distributed by simple random sampling. To collect information, the quality of urban life tool developed by Ebrahimzadeh Esmin and Karbakhsh (2017) was used. This questionnaire consists of 29 questions and 5 components that were used to analyze the data using SPSS 25 software (Cronbach's alpha) and LISREL 8.8 (structural equation modeling, confirmatory factor analysis).

Sarpole Zahab city is one of the western cities of Kermanshah province. Sarpole-Zahab city is located 177 km west of Kermanshah and its average altitude is 550 meters above sea level and is located at 45 degrees and 52 minutes east longitude and 34 degrees and 28 minutes north latitude (Azizi and Shams, 2020: 202) and is the center of Sarpole Zahab city. According to the 2016 census, the city of Sarpole Zahab has a population of 45,481 (Statistics Center of Iran, 2016).



Results and discussion

In first-order confirmatory factor analysis models, the scores of each item in a variable actually reflect the status of that item in a more underlying factor that cannot be measured directly because it is hidden. To estimate the model from chi-square ) (, index chi-square to freedom )df/ ( , comparative fit index (CFI), relative fit index (RFI), non-normalized fit index (NNFI), square root error Mean approximation (RMSEA) was used. Regarding CFI, RFI and NFI indices, some researchers believe that the minimum acceptable value is 0.90 And values above 0.95 indicate excellent model fit. Also, for the RMSEA index, a value less than 080 indicates a good fit of the model. According to the findings, the significance of T-statistic related to each of the questions of the Urban Quality of Life Scale is higher with a significance level of error of 1.96 And the relationship between structures is meaningful and confirmed.



Conclusion

The results show that in the environmental dimension, the feeling of calm (lack of noise pollution (visual, visual, etc.) and satisfaction with the level of clean air are the most important factors. In the social dimension, satisfaction with the sense of happiness and vitality in the place of residence and the level of interest in the place of residence have the most factor. In the economic dimension, the tendency to continue living if income increases and satisfaction with living costs (water, electricity, gas, telephone and housing costs) have the most factor. In the physical dimension, satisfaction with the conditions of the residential unit (size, number of rooms, necessary equipment, etc.) and satisfaction with the quality of streets and pedestrian crossings (quality of coverage, width of passages, night lighting, etc.) and the highest factor load. Finally, in terms of urban management, they are satisfied with the services provided by the municipality (timely collection of garbage, sewage and construction waste and the highest factor. Quality of life (QoL) assessment in urban areas is considered a difficult task. Some of the main reasons This difficulty is directly related to the complexity of the set of criteria to be considered in such an assessment, as well as the inherent relevance of the subject matter, which prevents the development of models that can reflect the performance of different urban environments in terms of their quality of life.

Keywords: Quality of life, Sarpol‌e Zahab, LISREL, confirmatory factor analysis



Refrence

1- Ebrahimzadeh Asmin, Hossein and Karbakhsh, Hassan (2017). Assessing the quality of urban life in an area of Zahedan. Geography Quarterly (Regional Planning). Volume, 7, No. 3, pp. 20-7.

2- Hatami Nejad, Hossein; Poorahmad, Ahmad and Mansoorian, Hossein and Rajaei, Abbas (2013), Spatial analysis of quality of life indicators in Tehran, Journal of Humanities Research, Volume 45, Number 4, pp. 56-29.

3- Alavi, Seyed Ali; Aboudi, Mohammad Reza and Daneshvar, Mahnaz (2018), Assessing mental indicators of quality of urban life with a healthy city approach. Case study: Behbahan city, Journal of Spatial Planning, Scientific-Research Quarterly of Golestan University, 8th year, serial number 28, pp. 18-1.

4- Statistics Center of Iran (2016). General Population and Housing Census 2016 Kermanshah Province.