Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah

被引:3
作者
Murad, Abdulkader [1 ]
Faruque, Fazlay [2 ]
Naji, Ammar [1 ]
Tiwari, Alok [1 ]
Helmi, Mansour [1 ]
Dahlan, Ammar [3 ]
机构
[1] King Abdulaziz Univ, Fac Architecture & Planning, Dept Urban & Reg Planning, Jeddah, Saudi Arabia
[2] Univ Mississipi, Dept Prevent Med, Jackson, MS USA
[3] King Abdulaziz Univ, Fac Architecture & Planning, Dept Architecture, Jeddah, Saudi Arabia
关键词
Geographically weighted regression model; multi-scale geographically weighted regression model; Type-2 diabetes prevalence; Jeddah; Saudi Arabia; WEIGHTED REGRESSION-ANALYSIS; PHYSICAL INACTIVITY; LIFE-STYLE; COMPLICATIONS; GEORGIA; BURDEN; HEALTH; BIRTH;
D O I
10.4081/gh.2022.1072
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Type-2 diabetes is a growing lifestyle disease mainly due to increasing physical inactivity but also associated with various other variables. In Saudi Arabia, around 58.5% of the population is deemed to be physically inactive. Against this background, this study attempts explore the spatial heterogeneity of Type-2 diabetes prevalence in Jeddah and to estimate various socio-economic and built environment variables contributing to the prevalence of this disease based on modelling by ordinary least squares (OLS), weighted regression (GWR) and multi-scale geographically weighted (MGWR). Our OLS results suggest that income, population density, commercial land use and Saudi population characteristics are statistically significant for Type-2 diabetes prevalence. However, by the GWR model, income, commercial land use and Saudi population characteristics were significantly positive while population density was significantly negative in this model for 70.6%, 9.1%, 26.6% and 58.7%, respectively, out of 109 districts investigated; by the MGWR model, the corresponding results were 100%, 22%, 100% and 100% of the districts. With the given data, the corrected Akaike information criterion (AICc), the adjusted R2, the log-likelihood and the residual sum of squares (RSS) indices demonstrated that the MGWR model outperformed the GWR and OLS models explaining 29% more variance than the OLS model, and 10.2% more than the GWR model. These results support the development of evidence-based policies for the spatial allocation of health associated resources for the control of Type-2 diabetes in Jeddah and other cities in the Arabian Gulf.
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页数:9
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