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Impact of Environment on Pain among the Working Poor: Making Use of Random Forest-Based Stratification Tool to Study the Socioecology of Pain Interference.
Leung, Eman; Lee, Albert; Liu, Yilin; Hung, Chi-Tim; Fan, Ning; Ching, Sam C C; Yee, Hilary; He, Yinan; Xu, Richard; Tsang, Hector Wing Hong; Guan, Jingjing.
Afiliación
  • Leung E; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Lee A; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Liu Y; Department of Rehabilitation Science, Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Hung CT; Centre for Health Education and Health Promotion, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Fan N; Hong Kong Health Education and Health Promotion Foundation, Hong Kong SAR, China.
  • Ching SCC; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Yee H; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • He Y; Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Xu R; Health in Action Limited, Hong Kong SAR, China.
  • Tsang HWH; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Guan J; Faculty of Medicine and Health, The University of Sydney, Sydney 2006, Australia.
Article en En | MEDLINE | ID: mdl-38397670
ABSTRACT
Pain interferes with one's work and social life and, at a personal level, daily activities, mood, and sleep quality. However, little research has been conducted on pain interference and its socioecological determinants among the working poor. Noting the clinical/policy decision needs and the technical challenges of isolating the intricately interrelated socioecological factors' unique contributions to pain interference and quantifying the relative contributions of each factor in an interpretable manner to inform clinical and policy decision-making, we deployed a novel random forest algorithm to model and quantify the unique contribution of a diverse ensemble of environmental, sociodemographic, and clinical factors to pain interference. Our analyses revealed that features representing the internal built environment of the working poor, such as the size of the living space, air quality, access to light, architectural design conducive to social connection, and age of the building, were assigned greater statistical importance than other more commonly examined predisposing factors for pain interference, such as age, occupation, the severity and locations of pain, BMI, serum blood sugar, and blood pressure. The findings were discussed in the context of their benefit in informing community pain screening to target residential areas whose built environment contributed most to pain interference and informing the design of intervention programs to minimize pain interference among those who suffered from chronic pain and showed specific characteristics. The findings support the call for good architecture to provide the spirit and value of buildings in city development.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Contaminación del Aire / Dolor Crónico / Trabajadores Pobres Límite: Humans Idioma: En Revista: Int J Environ Res Public Health / Int. j. environ. res. public health (Online) / International journal of environmental research and public health (Online) Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Contaminación del Aire / Dolor Crónico / Trabajadores Pobres Límite: Humans Idioma: En Revista: Int J Environ Res Public Health / Int. j. environ. res. public health (Online) / International journal of environmental research and public health (Online) Año: 2024 Tipo del documento: Article País de afiliación: China