STRUCTURAL GLOBAL SENSITIVITY METHOD BASED ON PARTIAL DERIVATIVE WHOLE DOMAIN INTEGRAL

In view of the problems that the traditional variance-based Sobol’method had a low solving efficiency,lacked of enough robustness,and it cannot further effectively decompose and reasonably distribute the influences of the high-order cross subterms,a practical and effective structural global sensitivity method was proposed in this paper based on partial derivative whole domain integral and optimal polynomial surrogate model. Firstly,optimal surrogate model was constructed through polynomial structure-selection,which had good fitting and predictive ability,and it was convenient for direct integral operations. Then,local sensitivity method based on partial derivative was extended to a global sensitivity method by integrating partial derivatives of model variables in variable sapces. In addition,the paper redefined a more conveniently calculated sensitivity indice that can achieve effective decomposition for the high-order sensitivity indices,and the sensitivity results directly corresponded to model variables without the high-order indices,which had more practical engineering significance. Numerical example 1 shows the deficiency of Sobol’total sensitivity indices in application. Numerical example 2 illustrates the validity of the proposed method for complex high-dimensional model. Engineering example demonstrates the applicability and effectiveness of the present method for complex engineering structure problems

Built environment, physical activity, and obesity of adults in Pingshan District, Shenzhen City in Southern China

Background The relation between neighbourhood built environment and obesity has been described as both nuanced and complex. Aim The objective of this study was to examine the relationship between the built environment, physical activity, and obesity in a rapidly urbanised area of China. Subjects and methods This is a cross-sectional study. Descriptive statistics were used to describe the socio-demographic variables, physical activity levels and BMI status. Multivariable logistic regression models were used to examine the association between neighbourhood environment, the likelihood of engaging in different types of physical activity, and BMI. Results A total of 842 respondents completed the questionnaires and were included (84.1% response rate). Among them, 56.4% reported meeting high physical activity levels, while 40.7% were overweight or obese. Multivariable regression analysis showed that better road conditions (β = 0.122, t = 2.999, p = 0.003) and access to physical activity facilities (β = 0.121, t = 3.193, p = 0.001) were significantly associated with higher levels of physical activity. Physical activity levels were inversely associated with the likelihood of being overweight (OR = 0.565, 95%CI: 0.3 4 9–0.917) or obese (OR = 0.614, 95%CI: 0.3 9 0–0.966). Conclusion The built environment has an important impact on physical activity. However, the direct impact of leisure physical activity on BMI is not significant. This research provides a summary of recent evidence in Pingshan District on built environments that are most favourable for physical activity and obesity