Infant mortality and its determinants in Uganda 2016: Using a geographically weighted regression approach.

Infant mortality (IM) represents the overall health of a country or region as it relates to access to medicine, health care, and clean water in a population. IM remains understudied in many areas of Uganda, as many studies are from urban the capital (Kampala). The long-term goal of this research is the mitigation of IM and poor pregnancy outcomes in Uganda. Insights gained from geographic distribution of IM will allow adaptation of diagnosis, treatments, and interventions within the studied areas. Through using OLS and geographically weighted regression, this study has explored the significant factors and their heterogeneous and scaling effects in 2016 across Uganda. The empirical findings from this study include a significant association between IM and both being unmarried and preferring to speak Luganda when interviewed. Those unmarried may lack a social network to assist with income, childcare, and household chores representing decreased resources. Additionally, being interviewed in Luganda was associated over a large geographic area, which may represent not being comfortable in English, which is the language of education, commerce, and presumably health care, thus suggesting a disconnect with health care settings. These data suggest that strides can be made in Uganda by providing targeted resources to areas with high rates of unmarried mothers and those areas with high rates of Luganda as their language of choice.

Examining the impact of spatial accessibility to rehabilitation facilities on the degree of disability: A heterogeneity perspective.

The positive effect of healthcare facilities on residents' health has been extensively studied. However, few studies have focused on the role of rehabilitation services as unique healthcare services for persons with disabilities. This study aimed to examine the relationship between the spatial accessibility of rehabilitation facilities and the degree of disability. To this end, an approach of measuring the spatial accessibility of rehabilitation facilities to persons with disabilities was proposed. This approach integrates multiple key elements including the characteristics of facilities (i.e., the capacity, frequency of use and service radius), characteristics of the mobility of persons with disabilities (i.e., the mode of travel, escort support, transportation fee and barrier-free environment requirements) and travel time obtained from a routing application programme interface. The accessibility of rehabilitation facilities was calculated at the neighbourhood level within the Central Urban Area of Tianjin Municipality. The ordinal logistic regression analysis revealed that higher accessibility to rehabilitation facilities generally corresponded to lower severity of disability. However, the impact varied depending on the type of disability. Increased accessibility was associated with greater severity of intellectual disability, whereas it was linked to reduced severity of visual, hearing, limb, mental and speech disabilities. It is suggested to incorporate disability diversity and the accessibility of rehabilitation facilities into spatial planning and governance.

Analysing the global and local spatial associations of medical resources across Wuhan city using POI data.

BACKGROUND: There is a sharp contradiction between the supply and demand of medical resources in the provincial capitals of China. Understanding the spatial patterns of medical resources and identifying their spatial association and heterogeneity is a prerequisite to ensuring that limited resources are allocated fairly and optimally, which, along with improvements to urban residents' quality of life, is a key aim of healthy city planning. However, the existing studies on medical resources pattern mainly focus on their spatial distribution and evolution characteristics, and lack the analyses of the spatial co-location between medical resources from the global and local perspectives. It is worth noting that the research on the spatial relationship between medical resources is an important way to realize the spatial equity and operation efficiency of urban medical resources. METHODS: Localized colocation quotient (LCLQ) analysis has been used successfully to measure directional spatial associations and heterogeneity between categorical point data. Using point of interest (POI) data and the LCLQ method, this paper presents the first analysis of spatial patterns and directional spatial associations between six medical resources across Wuhan city. RESULTS: (1) Pharmacies, clinics and community hospitals show "multicentre + multicircle", "centre + axis + dot" and "banded" distribution characteristics, respectively, but specialized hospitals and general hospitals present "single core" and "double core" modes. (2) Overall, medical resources show agglomeration characteristics. The degrees of spatial agglomeration of the five medical resources, are ranked from high to low as follows: pharmacy, clinic, community hospital, special hospital, general hospital and 3A hospital. (3) Although pharmacies, clinics, and community hospitals of basic medical resources are interdependent, specialized hospitals, general hospitals and 3A hospitals of professional medical resources are also interdependent; furthermore, basic medical resources and professional medical resources are mutually exclusive. CONCLUSIONS: Government and urban planners should pay great attention to the spatial distribution characteristics and association intensity of medical resources when formulating relevant policies. The findings of this study contribute to health equity and health policy discussions around basic medical services and professional medical services.

Spatiotemporal characteristics and influencing factors of urban resilience efficiency in the Yangtze River Economic Belt, China.

Urban resilience efficiency is an important indicator to explore the relationship between resource consumption and urban resilience, shedding new light on the study of urban sustainable development. Based on the panel data of 2008, 2012, and 2017, this paper makes a spatiotemporal assessment on the urban resilience efficiency of 126 cities in the Yangtze River Economic Belt (YREB) in China by applying an entropy weight-TOPSIS method and a slack-based measure (SBM) model. Combined with the analysis of a geographically weighted regression model (GWR), the influencing factors on resilience efficiency are also investigated. The results show that both the resource consumption index (RC, inputs) and the urban resilience index (UR, outputs) presented a steady upward trend, and their spatial distribution characteristics were similar, showing a gradual decrease from the eastern coastal cities to the central and western inland cities. Derived from inputs and outputs, the mean values of resilience efficiency index (RE) in three periods were 0.3149, 0.2906, and 0.1625, respectively, revealing that there had been a noticeable decline. Spatially, its spatial distribution has evolved from a relatively balanced pattern to an unbalanced one, showing a gradual decrease from west to east. The results of the GWR model analysis indicate that the total electricity consumption and area of construction land had a considerable correlation with the overall urban resilience of the YREB. Furthermore, total quantity of water supply and science and technology (S&T) expenditure continued to be the main driving factors on urban resilience of the upstream cities. The midstream regions mainly depended on the scale of construction land, and the influencing factors are relatively single. The influencing factors in the downstream areas have changed from dominance of resources and capital factors to the single dominance of resource factors, and total electricity consumption had a strong explanatory power. Based on these findings, we had put forward the overall and local regional policy implications.

Health-related quality of life of hospitalized COVID-19 survivors: An initial exploration in Nanning city, China.

Understanding the health-related quality of life (HrQoL) of hospitalized COVID-19 survivors is an emerging global challenge arising from the current pandemic. A qualitative study of the experiences of sixteen hospitalized COVID-19 survivors from Nanning City, China, was conducted using semi-structured telephone interviews in May 2020. These first-hand accounts were critically and empirically analysed to identify emerging health and social issues, and provide potential solutions to improve survivors' quality of life. This in-depth, qualitative study of HrQoL for hospitalized COVID-19 survivors provides the first empirical evidence and conceptual framework with eight dimensions (physical symptoms, anxiety, trauma, economic loss, place-based identity, self-stigma, health self-interventions, and changing lifestyle) for understanding the physiological, psychological, socio-economic and health behavioral aspects of their daily lives. We argue that local and global governments should provide integrated healthcare, social and digital infrastructure to support this vulnerable group. More comparative and multi-disciplinary studies in this area are needed to generate academic standards of assessing health-related quality of life and produce good practice guidelines for promoting urban resilience in response to public health disasters.

Spatial inequity in access to healthcare facilities at a county level in a developing country: a case study of Deqing County, Zhejiang, China.

BACKGROUND: The inequities in healthcare services between regions, urban and rural, age groups and diverse income groups have been growing rapidly in China. Equal access to basic medical and healthcare services has been recognized as "a basic right of the people" by Chinese government. Spatial accessibility to healthcare facilities has received huge attention in Chinese case studies but been less studied particularly at a county level due to limited availability of high-resolution spatial data. This study is focused on measuring spatial accessibility to healthcare facilities in Deqing County. The spatial inequity between the urban (town) and rural is assessed and three scenarios are designed and built to examine which scenario is instrumental for better reducing the spatial inequity. METHODS: This study utilizes highway network data, Digital Elevation Model (DEM), location of hospitals and clinics, 2010 census data at the finest level - village committee, residential building footprint and building height. Areal weighting method is used to disaggregate population data from village committee level to residential building cell level. Least cost path analysis is applied to calculate the travel time from each building cell to its closest healthcare facility. Then an integral accessibility will be calculated through weighting the travel time to the closest facility between three levels. The spatial inequity in healthcare accessibility between the town and rural areas is examined based on the coverages of areas and populations. The same method is used to compare three scenarios aimed at reducing such spatial inequity - relocation of hospitals, updates of weighting values, and the combination of both. RESULTS: 50.03% of residents can reach a county hospital within 15 min by driving, 95.77% and 100% within 30 and 60 min respectively. 55.14% of residents can reach a town hospital within 5 min, 98.04% and 100% within 15 and 30 min respectively. 57.86% of residential building areas can reach a village clinic within 5 min, 92.65% and 99.22% within 10 and 15 min. After weighting the travel time between the three-level facilities, 30.87% of residents can reach a facility within 5 min, 80.46%% and 99.88% within 15 and 30 min respectively. CONCLUSIONS: The healthcare accessibility pattern of Deqing County has exhibited spatial inequity between the town and rural areas, with the best accessibility in the capital of the county and poorest in the West of the county. There is a high negative correlation between population ageing and healthcare accessibility. Allocation of more advanced medical and healthcare equipment and highly skillful doctors and nurses to village clinics will be an efficient means of reducing the spatial inequity and further consolidating the national medical security system. GIS (Geographical Information Systems) methods have proven successful method of providing quantitative evidence for policy analysis although the data sets and methods could be further improved.