Understanding the Relationship between Dominant Geo-Environmental Factors and Rural Poverty in Guizhou, China

Geo-environmental factors are believed to be major determinants of rural poverty. However, few studies have quantified the effects of these factors on rural poverty in China. In this paper, we used county-level poverty incidence data and geo-environmental factors to explore spatial patterns of the incidence of poverty using global and local spatial autocorrelation analysis and to investigate the effect of geo-environment factors on rural poverty using a geo-detector model. Our results demonstrated that there was spatial clustering of the incidence of poverty in the study area. The incidence of poverty decreased from south to north and from the east and west to the central area. The incidence of high–high poverty areas was mainly distributed in the southeast of Guizhou Province and the incidence of low–low poverty areas was distributed in the northeast. The results also demonstrated that percentage of effective irrigation on arable land, slope, elevation and vegetation cover were the dominant factors explaining the spatial pattern of poverty. Interaction analysis demonstrated that the slope non-linearly enhanced the percentage of effective irrigation on arable land. Our findings suggested that geo-environment is the fundamental control factor explaining the spatial pattern of rural poverty in China. Through analysis of the impact of the geo-environment on the spatial pattern of poverty, this study provides a reference for effectively implementing targeted alleviation of poverty.

Socioeconomic Status and Determinants of Pediatric Antibiotic Use

Introduction. Evidence suggests that early-life antibiotic use can alter gut microbiome, predisposing children to obesity. The obesity epidemic has a disproportionate effect on individuals from lower socioeconomic status (SES). Thus, this study aims to explore the link between SES and antibiotic use. Design. We performed a retrospective cohort study of all babies born at and receiving 2 or more outpatient visits at a large, suburban health system in Illinois (United States) between 2007 and 2017. We collected data on zip code as a proxy for SES and antibiotic use in the first year of life. We also obtained comorbid diagnosis codes, race/ethnicity, gender, and number of inpatient, outpatient, and emergency department visits. Results. A total of 7224 patients met our study criteria. Children from low-poverty areas received a lifetime average of 4.28 prescriptions, while those from high-poverty neighborhoods received an average of 3.31 prescriptions. This was statistically significant in our unadjusted analysis but not after adjusting for covariates. Children from high-poverty areas were significantly more likely to receive more antibiotics at 48 hours, 1 week, and 1 month of life in our unadjusted analysis, but not after adjusting for covariates. In our unadjusted and adjusted analyses, children from high-poverty areas were significantly more likely to have received antibiotics at 1 week of life. Conclusion. The relationship between SES and antibiotic use warrants further investigation to help elucidate possible causes of the disproportionate impact obesity has in low-income communities.