Guo Yingqi, Chang Shu-Sen, Sha Feng, Yip Paul S F
Department of Social Work and Social Administration, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Institute of Health Behaviors and Community Sciences and Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan.
PLoS One. 2018 Feb 23;13(2):e0190566. doi: 10.1371/journal.pone.0190566. eCollection 2018.
Previous investigations of geographic concentration of urban poverty indicate the contribution of a variety of factors, such as economic restructuring and class-based segregation, racial segregation, demographic structure, and public policy. However, the models used by most past research do not consider the possibility that poverty concentration may take different forms in different locations across a city, and most studies have been conducted in Western settings. We investigated the spatial patterning of neighborhood poverty and its correlates in Hong Kong, which is amongst cities with the highest GDP in the region, using the city-wide ordinary least square (OLS) regression model and the local-specific geographically weighted regression (GWR) model. We found substantial geographic variations in small-area poverty rates and identified several poverty clusters in the territory. Factors found to contribute to urban poverty in Western cities, such as socioeconomic factors, ethnicity, and public housing, were also mostly associated with local poverty rates in Hong Kong. Our results also suggest some heterogeneity in the associations of poverty with specific correlates (e.g. access to hospitals) that would be masked in the city-wide OLS model. Policy aimed to alleviate poverty should consider both city-wide and local-specific factors.
先前对城市贫困地理集中情况的调查表明,经济结构调整、基于阶层的隔离、种族隔离、人口结构和公共政策等多种因素都有影响。然而,过去大多数研究使用的模型没有考虑到贫困集中在城市不同地点可能呈现不同形式的可能性,并且大多数研究是在西方背景下进行的。我们利用全市普通最小二乘法(OLS)回归模型和特定地点的地理加权回归(GWR)模型,研究了香港邻里贫困的空间格局及其相关因素。香港是该地区GDP最高的城市之一。我们发现小区域贫困率存在显著的地理差异,并在该地区识别出了几个贫困集群。在西方城市中发现的导致城市贫困的因素,如社会经济因素、种族和公共住房,在香港也大多与当地贫困率相关。我们的结果还表明,贫困与特定相关因素(如就医便利性)之间的关联存在一些异质性,而这些异质性在全市OLS模型中会被掩盖。旨在缓解贫困的政策应同时考虑全市性和特定地点的因素。