Background A remarkable drop in tuberculosis (TB) incidence has been achieved in China, although in 2019 it was still considered the second most communicable disease. However, TB’s spatial features and risk factors in urban areas remain poorly understood. This study aims to identify the spatial differentiations and potential influencing factors of TB in highly urbanized regions on a fine scale. Methods This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou, China. TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention. Before using Pearson correlation and a geographical detector (GD) to identify potential influencing factors, we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales. Results Owing to its strong spatial autocorrelation (Moran’s I = 0.33, Z = 4.71), the 2 km × 2 km grid was selected as the spatial scale. At this level, TB incidence was closely associated with most socioeconomic variables (0.31 < r < 0.76, P < 0.01). Of five environmental factors, only the concentration of fine particulate matter displayed significant correlation (r = 0.21, P < 0.05). Similarly, in terms of q values derived from the GD, socioeconomic variables had stronger explanatory abilities (0.08 < q < 0.57) for the spatial differentiation of the 2017 incidence of TB than environmental variables (0.06 < q < 0.27). Moreover, a much larger proportion (0.16 < q < 0.89) of the spatial differentiation was interpreted by pairwise interactions, especially those (0.60 < q < 0.89) related to the 2016 incidence of TB, officially appointed medical institutions, bus stops, and road density. Conclusions The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably influenced by several socioeconomic and environmental factors and their pairwise interactions on a fine scale. We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou. Our study provides helpful clues for local authorities implementing more effective intervention measures to reduce TB incidence in China’s municipal areas, which are featured by both a high degree of urbanization and a high incidence of TB. Graphical Abstract
Background: The prevalence of tuberculosis (TB) in China has heavily affected people’s health for decades, which has been widely investigated for the rural regions and west parts. However, its spatial features in urban areas remain little understood. Thus, this study aims to identify its spatial differentiations and their influencing factors in highly urbanized region on a fine scale.Methods: Together with the TB cases in 2017 obtained from Guangzhou Institute of Tuberculosis Control and Prevention, in total 18 socioeconomic and environmental variables were included in this study. Two spatial analysis tools were respectively applied to select the relative appropriate spatial scale (global Moran’s I), and to identify specific urban factors (the Geographical detector) for this epidemic in the central four districts of Guangzhou.Results: The 2 km × 2 km grid was determined as the most appropriate spatial scale due to its relatively higher spatial autocorrelation (Moran’s I=0.33, Z=4.71). At this spatial level, the TB epidemic in the four central districts was obviously closely associated with most of socioeconomic factors (0.31<r<0.76) at the significance level of 0.01. By contrast, among environmental factors, only the concentration of fine particulate matter (PM2.5) correlated with this epidemic (r=0.21) at the significance level of 0.05. Similarly, according to the q-values derived from geographical detector analysis, socioeconomic factors posed stronger impacts (0.08<q<0.57) on the spatial differentiations of TB prevalence than those of environmental variables (0.06<q<0.27), Furthermore, 153 pairs of variables presented more powerful explanatory abilities for this epidemic’s spatial disparities due to their notable enhancements of q-values (7.3%<sq<311.6%) caused by the pairwise interactions.Conclusion: The spatial heterogeneity of TB prevalence was remarkably influenced by a series of specific urban elements and their pairwise interactions across the central region of Guangzhou. We accordingly suggest that more attentions should be paid to the areas with pairwise interactions of these specific urban elements in this city. This study would provide meaningful clues for local authorities making more targeted interventions on this disease in China’s municipal areas featured by both high urbanization and severe tuberculosis.
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